600 Technik, Technologie
Refine
Year of publication
Document Type
- Article (86)
- Postprint (55)
- Doctoral Thesis (4)
- Conference Proceeding (2)
- Other (1)
Language
- English (148) (remove)
Is part of the Bibliography
- yes (148)
Keywords
- human behaviour (5)
- Environmental sciences (4)
- animal personality (4)
- deep reinforcement learning (4)
- exploratory-behavior (4)
- expression (4)
- production control (4)
- activation (3)
- disease (3)
- human-robot interaction (3)
Institute
- Mathematisch-Naturwissenschaftliche Fakultät (26)
- Institut für Biochemie und Biologie (25)
- Institut für Physik und Astronomie (21)
- Institut für Geowissenschaften (12)
- Institut für Chemie (9)
- Strukturbereich Kognitionswissenschaften (8)
- Fachgruppe Betriebswirtschaftslehre (7)
- Hasso-Plattner-Institut für Digital Engineering GmbH (7)
- Wirtschaftswissenschaften (7)
- Institut für Informatik und Computational Science (5)
Sea surface temperature (SST) patterns can – as surface climate forcing – affect weather and climate at large distances. One example is El Niño-Southern Oscillation (ENSO) that causes climate anomalies around the globe via teleconnections. Although several studies identified and characterized these teleconnections, our understanding of climate processes remains incomplete, since interactions and feedbacks are typically exhibited at unique or multiple temporal and spatial scales. This study characterizes the interactions between the cells of a global SST data set at different temporal and spatial scales using climate networks. These networks are constructed using wavelet multi-scale correlation that investigate the correlation between the SST time series at a range of scales allowing instantaneously deeper insights into the correlation patterns compared to traditional methods like empirical orthogonal functions or classical correlation analysis. This allows us to identify and visualise regions of – at a certain timescale – similarly evolving SSTs and distinguish them from those with long-range teleconnections to other ocean regions. Our findings re-confirm accepted knowledge about known highly linked SST patterns like ENSO and the Pacific Decadal Oscillation, but also suggest new insights into the characteristics and origins of long-range teleconnections like the connection between ENSO and Indian Ocean Dipole.
The development of new and better optimization and approximation methods for Job Shop Scheduling Problems (JSP) uses simulations to compare their performance. The test data required for this has an uncertain influence on the simulation results, because the feasable search space can be changed drastically by small variations of the initial problem model. Methods could benefit from this to varying degrees. This speaks in favor of defining standardized and reusable test data for JSP problem classes, which in turn requires a systematic describability of the test data in order to be able to compile problem adequate data sets. This article looks at the test data used for comparing methods by literature review. It also shows how and why the differences in test data have to be taken into account. From this, corresponding challenges are derived which the management of test data must face in the context of JSP research.
Keywords
The development of new and better optimization and approximation methods for Job Shop Scheduling Problems (JSP) uses simulations to compare their performance. The test data required for this has an uncertain influence on the simulation results, because the feasable search space can be changed drastically by small variations of the initial problem model. Methods could benefit from this to varying degrees. This speaks in favor of defining standardized and reusable test data for JSP problem classes, which in turn requires a systematic describability of the test data in order to be able to compile problem adequate data sets. This article looks at the test data used for comparing methods by literature review. It also shows how and why the differences in test data have to be taken into account. From this, corresponding challenges are derived which the management of test data must face in the context of JSP research.
Within the framework of precision agriculture, the determination of various soil properties is moving into focus, especially the demand for sensors suitable for in-situ measurements. Energy-dispersive X-ray fluorescence (EDXRF) can be a powerful tool for this purpose. In this study a huge diverse soil set (n = 598) from 12 different study sites in Germany was analysed with EDXRF. First, a principal component analysis (PCA) was performed to identify possible similarities among the sample set. Clustering was observed within the four texture classes clay, loam, silt and sand, as clay samples contain high and sandy soils low iron mass fractions. Furthermore, the potential of uni- and multivariate data evaluation with partial least squares regression (PLSR) was assessed for accurate determination of nutrients in German agricultural samples using two calibration sample sets. Potassium and iron were chosen for testing the performance of both models. Prediction of these nutrients in 598 German soil samples with EDXRF was more accurate using PLSR which is confirmed by a better overall averaged deviation and PLSR should therefore be preferred.
Within the framework of precision agriculture, the determination of various soil properties is moving into focus, especially the demand for sensors suitable for in-situ measurements. Energy-dispersive X-ray fluorescence (EDXRF) can be a powerful tool for this purpose. In this study a huge diverse soil set (n = 598) from 12 different study sites in Germany was analysed with EDXRF. First, a principal component analysis (PCA) was performed to identify possible similarities among the sample set. Clustering was observed within the four texture classes clay, loam, silt and sand, as clay samples contain high and sandy soils low iron mass fractions. Furthermore, the potential of uni- and multivariate data evaluation with partial least squares regression (PLSR) was assessed for accurate determination of nutrients in German agricultural samples using two calibration sample sets. Potassium and iron were chosen for testing the performance of both models. Prediction of these nutrients in 598 German soil samples with EDXRF was more accurate using PLSR which is confirmed by a better overall averaged deviation and PLSR should therefore be preferred.
Signaling pathways in biological systems rely on specific interactions between multiple biomolecules. Fluorescence fluctuation spectroscopy provides a powerful toolbox to quantify such interactions directly in living cells. Cross-correlation analysis of spectrally separated fluctuations provides information about intermolecular interactions but is usually limited to two fluorophore species. Here, we present scanning fluorescence spectral correlation spectroscopy (SFSCS), a versatile approach that can be implemented on commercial confocal microscopes, allowing the investigation of interactions between multiple protein species at the plasma membrane. We demonstrate that SFSCS enables cross-talk-free cross-correlation, diffusion, and oligomerization analysis of up to four protein species labeled with strongly overlapping fluorophores. As an example, we investigate the interactions of influenza A virus (IAV) matrix protein 2 with two cellular host factors simultaneously. We furthermore apply raster spectral image correlation spectroscopy for the simultaneous analysis of up to four species and determine the stoichiometry of ternary IAV polymerase complexes in the cell nucleus.
Monitoring the response of volcanic CO2 emissions to changes in the Los Humeros hydrothermal system
(2021)
Carbon dioxide is the most abundant, non-condensable gas in volcanic systems, released into the atmosphere through either diffuse or advective fluid flow. The emission of substantial amounts of CO2 at Earth's surface is not only controlled by volcanic plumes during periods of eruptive activity or fumaroles, but also by soil degassing along permeable structures in the subsurface. Monitoring of these processes is of utmost importance for volcanic hazard analyses, and is also relevant for managing geothermal resources. Fluid-bearing faults are key elements of economic value for geothermal power generation. Here, we describe for the first time how sensitively and quickly natural gas emissions react to changes within a deep hydrothermal system due to geothermal fluid reinjection. For this purpose, we deployed an automated, multi-chamber CO2 flux monitoring system within the damage zone of a deep-rooted major normal fault in the Los Humeros Volcanic Complex (LHVC) in Mexico and recorded data over a period of five months. After removing the atmospheric effects on variations in CO2 flux, we calculated correlation coefficients between residual CO2 emissions and reinjection rates, identifying an inverse correlation of rho = - 0.51 to - 0.66. Our results indicate that gas emissions respond to changes in reinjection rates within 24 h, proving an active hydraulic communication between the hydrothermal system and Earth's surface. This finding is a promising indication not only for geothermal reservoir monitoring but also for advanced long-term volcanic risk analysis. Response times allow for estimation of fluid migration velocities, which is a key constraint for conceptual and numerical modelling of fluid flow in fracture-dominated systems.
The interplay between cognitive and oculomotor processes during reading can be explored when the spatial layout of text deviates from the typical display. In this study, we investigate various eye-movement measures during reading of text with experimentally manipulated layout (word-wise and letter-wise mirrored-reversed text as well as inverted and scrambled text). While typical findings (e.g., longer mean fixation times, shorter mean saccades lengths) in reading manipulated texts compared to normal texts were reported in earlier work, little is known about changes of oculomotor targeting observed in within-word landing positions under the above text layouts. Here we carry out precise analyses of landing positions and find substantial changes in the so-called launch-site effect in addition to the expected overall slow-down of reading performance. Specifically, during reading of our manipulated text conditions with reversed letter order (against overall reading direction), we find a reduced launch-site effect, while in all other manipulated text conditions, we observe an increased launch-site effect. Our results clearly indicate that the oculomotor system is highly adaptive when confronted with unusual reading conditions.
The interplay between cognitive and oculomotor processes during reading can be explored when the spatial layout of text deviates from the typical display. In this study, we investigate various eye-movement measures during reading of text with experimentally manipulated layout (word-wise and letter-wise mirrored-reversed text as well as inverted and scrambled text). While typical findings (e.g., longer mean fixation times, shorter mean saccades lengths) in reading manipulated texts compared to normal texts were reported in earlier work, little is known about changes of oculomotor targeting observed in within-word landing positions under the above text layouts. Here we carry out precise analyses of landing positions and find substantial changes in the so-called launch-site effect in addition to the expected overall slow-down of reading performance. Specifically, during reading of our manipulated text conditions with reversed letter order (against overall reading direction), we find a reduced launch-site effect, while in all other manipulated text conditions, we observe an increased launch-site effect. Our results clearly indicate that the oculomotor system is highly adaptive when confronted with unusual reading conditions.
The soft error rate (SER) due to heavy-ion irradiation of a clock tree is investigated in this paper. A method for clock tree SER prediction is developed, which employs a dedicated soft error analysis tool to characterize the single-event transient (SET) sensitivities of clock inverters and other commercial tools to calculate the SER through fault-injection simulations. A test circuit including a flip-flop chain and clock tree in a 65 nm CMOS technology is developed through the automatic ASIC design flow. This circuit is analyzed with the developed method to calculate its clock tree SER. In addition, this circuit is implemented in a 65 nm test chip and irradiated by heavy ions to measure its SER resulting from the SETs in the clock tree. The experimental and calculation results of this case study present good correlation, which verifies the effectiveness of the developed method.
After initial detection of target archival DNA of a 116-year-old syntype specimen of the smooth lantern shark, Etmopterus pusillus, in a single-stranded DNA library, we shotgun-sequenced additional 9 million reads from this same DNA library. Sequencing reads were used for extracting mitochondrial sequence information for analyses of mitochondrial DNA characteristics and reconstruction of the mitochondrial genome. The archival DNA is highly fragmented. A total of 4599 mitochondrial reads were available for the genome reconstruction using an iterative mapping approach. The resulting genome sequence has 12 times coverage and a length of 16 741 bp. All 37 vertebrate mitochondrial loci plus the control region were identified and annotated. The mitochondrial NADH2 gene was subsequently used to place the syntype haplotype in a network comprising multiple E. pusillus samples from various distant localities as well as sequences from a morphological similar species, the shortfin smooth lantern shark Etmopterus joungi. Results confirm the almost global distribution of E. pusillus and suggest E. joungi to be a junior synonym of E. pusillus. As mitochondrial DNA often represents the only available reference information in non-model organisms, this study illustrates the importance of mitochondrial DNA from an aged, wet collection type specimen for taxonomy.
The mechanical muscular oscillations are rarely the objective of investigations regarding the identification of a biomarker for Parkinson's disease (PD). Therefore, the aim of this study was to investigate whether or not this specific motor output differs between PD patients and controls. The novelty is that patients without tremor are investigated performing a unilateral isometric motor task. The force of armflexors and the forearm acceleration (ACC) were recorded as well as the mechanomyography of the biceps brachii (MMGbi), brachioradialis (MMGbra) and pectoralis major (MMGpect) muscles using a piezoelectric-sensor-based system during a unilateral motor task at 70% of the MVIC. The frequency, a power-frequency-ratio, the amplitude variation, the slope of amplitudes and their interlimb asymmetries were analysed. The results indicate that the oscillatory behavior of muscular output in PD without tremor deviates from controls in some parameters: Significant differences appeared for the power-frequency-ratio (p=0.001, r=0.43) and for the amplitude variation (p=0.003, r=0.34) of MMGpect. The interlimb asymmetries differed significantly concerning the power-frequency-ratio of MMGbi (p=0.013, r=0.42) and MMGbra (p=0.048, r=0.39) as well as regarding the mean frequency (p=0.004, r=0.48) and amplitude variation of MMGpect (p=0.033, r=0.37). The mean (M) and variation coefficient (CV) of slope of ACC differed significantly (M: p=0.022, r=0.33; CV: p=0.004, r=0.43). All other parameters showed no significant differences between PD and controls. It remains open, if this altered mechanical muscular output is reproducible and specific for PD.
Effective communication among sympatric species is often instrumental for behavioural isolation, where the failure to successfully discriminate between potential mates could lead to less fit hybrid offspring. Discrimination between con- and heterospecifics tends to occur more often in the sex that invests more in offspring production, i.e. females, but males may also mediate reproductive isolation. In this study, we show that among two Campylomormyrus Africanweakly electric fish species, males preferentially associate with conspecific females during choice tests using live fish as stimuli, i.e. when all sensory modalities potentially used for communication were present. We then conducted playback experiments to determine whether the species-specific electric organ discharge (EOD) used for electrocommunication serves as the cue for this conspecific association preference. Interestingly, only C. compressirostris males associated significantly more with the conspecific EOD waveform when playback stimuli were provided, while no such association preference was observed in C. tamandua males. Given our results, the EOD appears to serve, in part, as a male-mediated pre-zygotic isolation mechanism among sympatric species. However, the failure of C. tamandua males to discriminate between con- and heterospecific playback discharges suggests that multiple modalities may be necessary for species recognition in some African weakly electric fish species.
Effective communication among sympatric species is often instrumental for behavioural isolation, where the failure to successfully discriminate between potential mates could lead to less fit hybrid offspring. Discrimination between con- and heterospecifics tends to occur more often in the sex that invests more in offspring production, i.e. females, but males may also mediate reproductive isolation. In this study, we show that among two Campylomormyrus Africanweakly electric fish species, males preferentially associate with conspecific females during choice tests using live fish as stimuli, i.e. when all sensory modalities potentially used for communication were present. We then conducted playback experiments to determine whether the species-specific electric organ discharge (EOD) used for electrocommunication serves as the cue for this conspecific association preference. Interestingly, only C. compressirostris males associated significantly more with the conspecific EOD waveform when playback stimuli were provided, while no such association preference was observed in C. tamandua males. Given our results, the EOD appears to serve, in part, as a male-mediated pre-zygotic isolation mechanism among sympatric species. However, the failure of C. tamandua males to discriminate between con- and heterospecific playback discharges suggests that multiple modalities may be necessary for species recognition in some African weakly electric fish species.
Developing a new product generation requires the transfer of knowledge among various knowledge carriers. Several factors influence knowledge transfer, e.g., the complexity of engineering tasks or the competence of employees, which can decrease the efficiency and effectiveness of knowledge transfers in product engineering. Hence, improving those knowledge transfers obtains great potential, especially against the backdrop of experienced employees leaving the company due to retirement, so far, research results show, that the knowledge transfer velocity can be raised by following the Knowledge Transfer Velocity Model and implementing so-called interventions in a product engineering context. In most cases, the implemented interventions have a positive effect on knowledge transfer speed improvement. In addition to that, initial theoretical findings describe factors influencing the quality of knowledge transfers and outline a setting to empirically investigate how the quality can be improved by introducing a general description of knowledge transfer reference situations and principles to measure the quality of knowledge artifacts. To assess the quality of knowledge transfers in a product engineering context, the Knowledge Transfer Quality Model (KTQM) is created, which serves as a basis to develop and implement quality-dependent interventions for different knowledge transfer situations. As a result, this paper introduces the specifications of eight situation-adequate interventions to improve the quality of knowledge transfers in product engineering following an intervention template. Those interventions are intended to be implemented in an industrial setting to measure the quality of knowledge transfers and validate their effect.
The use of acidic ionic liquids and solids as electrolytes in fuel cells is an emerging field due to their efficient proton conductivity and good thermal stability. Despite multiple reports describing conducting properties of acidic ILs, little is known on the charge-transport mechanism in the vicinity of liquid-glass transition and the structural factors governing the proton hopping. To address these issues, we studied two acidic imidazolium-based ILs with the same cation, however, different anions-bulk tosylate vs small methanesulfonate. High-pressure dielectric studies of anhydrous and water-saturated materials performed in the close vicinity of T-g have revealed significant differences in the charge-transport mechanism in these two systems being undetectable at ambient conditions. Thereby, we demonstrated the effect of molecular architecture on proton hopping, being crucial in the potential electrochemical applications of acidic ILs.
Ecological and physiological factors lead to different contamination patterns in individual marine mammals. The objective of the present study was to assess whether variations in contamination profiles are indicative of social structures of young male sperm whales as they might reflect a variation in feeding preferences and/or in utilized feeding grounds. We used a total of 61 variables associated with organic compounds and trace element concentrations measured in muscle, liver, kidney and blubber gained from 24 sperm whales that stranded in the North Sea in January and February 2016. Combining contaminant and genetic data, there is evidence for at least two cohorts with different origin among these stranded sperm whales; one from the Canary Island region and one from the northern part of the Atlantic. While genetic data unravel relatedness and kinship, contamination data integrate over areas, where animals occured during their lifetime. Especially in long-lived animals with a large migratory potential, as sperm whales, contamination data may carry highly relevant information about aggregation through time and space.
Ecological and physiological factors lead to different contamination patterns in individual marine mammals. The objective of the present study was to assess whether variations in contamination profiles are indicative of social structures of young male sperm whales as they might reflect a variation in feeding preferences and/or in utilized feeding grounds. We used a total of 61 variables associated with organic compounds and trace element concentrations measured in muscle, liver, kidney and blubber gained from 24 sperm whales that stranded in the North Sea in January and February 2016. Combining contaminant and genetic data, there is evidence for at least two cohorts with different origin among these stranded sperm whales; one from the Canary Island region and one from the northern part of the Atlantic. While genetic data unravel relatedness and kinship, contamination data integrate over areas, where animals occured during their lifetime. Especially in long-lived animals with a large migratory potential, as sperm whales, contamination data may carry highly relevant information about aggregation through time and space.
Gene expression data is analyzed to identify biomarkers, e.g. relevant genes, which serve for diagnostic, predictive, or prognostic use. Traditional approaches for biomarker detection select distinctive features from the data based exclusively on the signals therein, facing multiple shortcomings in regards to overfitting, biomarker robustness, and actual biological relevance. Prior knowledge approaches are expected to address these issues by incorporating prior biological knowledge, e.g. on gene-disease associations, into the actual analysis. However, prior knowledge approaches are currently not widely applied in practice because they are often use-case specific and seldom applicable in a different scope. This leads to a lack of comparability of prior knowledge approaches, which in turn makes it currently impossible to assess their effectiveness in a broader context.
Our work addresses the aforementioned issues with three contributions. Our first contribution provides formal definitions for both prior knowledge and the flexible integration thereof into the feature selection process. Central to these concepts is the automatic retrieval of prior knowledge from online knowledge bases, which allows for streamlining the retrieval process and agreeing on a uniform definition for prior knowledge. We subsequently describe novel and generalized prior knowledge approaches that are flexible regarding the used prior knowledge and applicable to varying use case domains. Our second contribution is the benchmarking platform Comprior. Comprior applies the aforementioned concepts in practice and allows for flexibly setting up comprehensive benchmarking studies for examining the performance of existing and novel prior knowledge approaches. It streamlines the retrieval of prior knowledge and allows for combining it with prior knowledge approaches. Comprior demonstrates the practical applicability of our concepts and further fosters the overall development and comparability of prior knowledge approaches. Our third contribution is a comprehensive case study on the effectiveness of prior knowledge approaches. For that, we used Comprior and tested a broad range of both traditional and prior knowledge approaches in combination with multiple knowledge bases on data sets from multiple disease domains. Ultimately, our case study constitutes a thorough assessment of a) the suitability of selected knowledge bases for integration, b) the impact of prior knowledge being applied at different integration levels, and c) the improvements in terms of classification performance, biological relevance, and overall robustness.
In summary, our contributions demonstrate that generalized concepts for prior knowledge and a streamlined retrieval process improve the applicability of prior knowledge approaches. Results from our case study show that the integration of prior knowledge positively affects biomarker results, particularly regarding their robustness. Our findings provide the first in-depth insights on the effectiveness of prior knowledge approaches and build a valuable foundation for future research.
Ribosome biogenesis is tightly associated to plant metabolism due to the usage of ribosomes in the synthesis of proteins necessary to drive metabolic pathways. Given the central role of ribosome biogenesis in cell physiology, it is important to characterize the impact of different components involved in this process on plant metabolism. Double mutants of the Arabidopsis thaliana cytosolic 60S maturation factors REIL1 and REIL2 do not resume growth after shift to moderate 10 degrees C chilling conditions. To gain mechanistic insights into the metabolic effects of this ribosome biogenesis defect on metabolism, we developed TC-iReMet2, a constraint-based modelling approach that integrates relative metabolomics and transcriptomics time-course data to predict differential fluxes on a genome-scale level. We employed TC-iReMet2 with metabolomics and transcriptomics data from the Arabidopsis Columbia 0 wild type and the reil1-1 reil2-1 double mutant before and after cold shift. We identified reactions and pathways that are highly altered in a mutant relative to the wild type. These pathways include the Calvin-Benson cycle, photorespiration, gluconeogenesis, and glycolysis. Our findings also indicated differential NAD(P)/NAD(P)H ratios after cold shift. TC-iReMet2 allows for mechanistic hypothesis generation and interpretation of system biology experiments related to metabolic fluxes on a genome-scale level.
Balancing foraging gain and predation risk is a fundamental trade-off in the life of animals. Individual strategies to acquire, process, store and use information to solve cognitive tasks are likely to affect speed and flexibility of learning, and ecologically relevant decisions regarding foraging and predation risk. Theory suggests a functional link between individual variation in cognitive style and behaviour (animal personality) via speed-accuracy and risk-reward trade-offs. We tested whether cognitive style and personality affect risk-reward trade-off decisions posed by foraging and predation risk. We exposed 21 bank voles (Myodes glareolus) that were bold, fast learning and inflexible and 18 voles that were shy, slow learning and flexible to outdoor enclosures with different risk levels at two food patches. We quantified individual food patch exploitation, foraging and vigilance behaviour. Although both types responded to risk, fast animals increasingly exploited both food patches, gaining access to more food and spending less time searching and exercising vigilance. Slow animals progressively avoided high-risk areas, concentrating foraging effort in the low-risk one, and devoting >50% of visit to vigilance. These patterns indicate that individual differences in cognitive style/personality are reflected in foraging and anti-predator decisions that underlie the individual risk-reward bias.
Balancing foraging gain and predation risk is a fundamental trade-off in the life of animals. Individual strategies to acquire, process, store and use information to solve cognitive tasks are likely to affect speed and flexibility of learning, and ecologically relevant decisions regarding foraging and predation risk. Theory suggests a functional link between individual variation in cognitive style and behaviour (animal personality) via speed-accuracy and risk-reward trade-offs. We tested whether cognitive style and personality affect risk-reward trade-off decisions posed by foraging and predation risk. We exposed 21 bank voles (Myodes glareolus) that were bold, fast learning and inflexible and 18 voles that were shy, slow learning and flexible to outdoor enclosures with different risk levels at two food patches. We quantified individual food patch exploitation, foraging and vigilance behaviour. Although both types responded to risk, fast animals increasingly exploited both food patches, gaining access to more food and spending less time searching and exercising vigilance. Slow animals progressively avoided high-risk areas, concentrating foraging effort in the low-risk one, and devoting >50% of visit to vigilance. These patterns indicate that individual differences in cognitive style/personality are reflected in foraging and anti-predator decisions that underlie the individual risk-reward bias.
The reduction in cost and increasing benefits of 3D printing technologies suggest the potential for printing dental prosthetics. However, although 3D printing technologies seem to be promising, their implementation in practice is complicated. To identify and rank the greatest implementation challenges of 3D printing in dental practices, the present study surveys dentists, dental technicians, and 3D printing companies using a ranking-type Delphi study. Our findings imply that a lack of knowledge is the most crucial obstacle to the implementation of 3D printing technologies. The high training effort of staff and the favoring of conventional methods, such as milling, are ranked as the second and third most relevant factors. Investment costs ranked in seventh place, whereas the lack of manufacturing facilities and the obstacle of print duration ranked below average. An inclusive implementation of additive manufacturing could be achieved primarily through the education of dentists and other staff in dental practices. In this manner, production may be managed internally, and the implementation speed may be increased.
The reduction in cost and increasing benefits of 3D printing technologies suggest the potential for printing dental prosthetics. However, although 3D printing technologies seem to be promising, their implementation in practice is complicated. To identify and rank the greatest implementation challenges of 3D printing in dental practices, the present study surveys dentists, dental technicians, and 3D printing companies using a ranking-type Delphi study. Our findings imply that a lack of knowledge is the most crucial obstacle to the implementation of 3D printing technologies. The high training effort of staff and the favoring of conventional methods, such as milling, are ranked as the second and third most relevant factors. Investment costs ranked in seventh place, whereas the lack of manufacturing facilities and the obstacle of print duration ranked below average. An inclusive implementation of additive manufacturing could be achieved primarily through the education of dentists and other staff in dental practices. In this manner, production may be managed internally, and the implementation speed may be increased.
Trade-offs are inherent to biochemical networks governing diverse cellular functions, from gene expression to metabolism. Yet, trade-offs between fluxes of biochemical reactions in a metabolic network have not been formally studied. Here, we introduce the concept of absolute flux trade-offs and devise a constraint-based approach, termed FluTO, to identify and enumerate flux trade-offs in a given genome-scale metabolic network. By employing the metabolic networks of Escherichia coli and Saccharomyces cerevisiae, we demonstrate that the flux trade-offs are specific to carbon sources provided but that reactions involved in the cofactor and prosthetic group biosynthesis are present in trade-offs across all carbon sources supporting growth. We also show that absolute flux trade-offs depend on the biomass reaction used to model the growth of Arabidopsis thaliana under different carbon and nitrogen conditions. The identified flux trade-offs reflect the tight coupling between nitrogen, carbon, and sulphur metabolisms in leaves of C-3 plants. Altogether, FluTO provides the means to explore the space of alternative metabolic routes reflecting the constraints imposed by inherent flux trade-offs in large-scale metabolic networks.
In this paper, the phenomenon of light-driven diffusioosmotic (DO) long-range attractive and repulsive interactions between micro-sized objects trapped near a solid wall is investigated. The range of the DO flow extends several times the size of microparticles and can be adjusted to point towards or away from the particle by varying irradiation parameters such as intensity or wavelength of light. The "fuel" of the light-driven DO flow is a photosensitive surfactant which can be photo-isomerized between trans and cis-states. The trans-isomer tends to accumulate at the interface, while the cis-isomer prefers to stay in solution. In combination with a dissimilar photo-isomerization rate at the interface and in bulk, this yields a concentration gradient of the isomers around single particles resulting in local light-driven diffusioosmotic (l-LDDO) flow. Here, the extended analysis of the l-LDDO flow as a function of irradiation parameters by introducing time-dependent development of the concentration excess of isomers near the particle surface is presented. It is also demonstrated that the l-LDDO can be generated at any solid/liquid interface being more pronounced in the case of strongly absorbing material. This phenomenon has plenty of potential applications since it makes any type of surface act as a micropump.
How insoluble inclusions and intersecting layers affect the leaching process within potash seams
(2021)
Potash seams are a valuable resource containing several economically interesting, but also highly soluble minerals. In the presence of water, uncontrolled leaching can occur, endangering subsurface mining operations. In the present study, the influence of insoluble inclusions and intersecting layers on leaching zone evolution was examined by means of a reactive transport model. For that purpose, a scenario analysis was carried out, considering different rock distributions within a carnallite-bearing potash seam. The results show that reaction-dominated systems are not affected by heterogeneities at all, whereas transport-dominated systems exhibit a faster advance in homogeneous rock compositions. In return, the ratio of permeated rock in vertical direction is higher in heterogeneous systems. Literature data indicate that most natural potash systems are transport-dominated. Accordingly, insoluble inclusions and intersecting layers can usually be seen as beneficial with regard to reducing hazard potential as long as the mechanical stability of leaching zones is maintained. Thereby, the distribution of insoluble areas is of minor impact unless an inclined, intersecting layer occurs that accelerates leaching zone growth in one direction. Moreover, it is found that the saturation dependency of dissolution rates increases the growth rate in the long term, and therefore must be considered in risk assessments.
Among various types of perovskite-based tandem solar cells (TSCs), all-perovskite TSCs are of particular attractiveness for building- and vehicle-integrated photovoltaics, or space energy areas as they can be fabricated on flexible and lightweight substrates with a very high power-to-weight ratio. However, the efficiency of flexible all-perovskite tandems is lagging far behind their rigid counterparts primarily due to the challenges in developing efficient wide-bandgap (WBG) perovskite solar cells on the flexible substrates as well as their low open-circuit voltage (V-OC). Here, it is reported that the use of self-assembled monolayers as hole-selective contact effectively suppresses the interfacial recombination and allows the subsequent uniform growth of a 1.77 eV WBG perovskite with superior optoelectronic quality. In addition, a postdeposition treatment with 2-thiopheneethylammonium chloride is employed to further suppress the bulk and interfacial recombination, boosting the V-OC of the WBG top cell to 1.29 V. Based on this, the first proof-of-concept four-terminal all-perovskite flexible TSC with a power conversion efficiency of 22.6% is presented. When integrating into two-terminal flexible tandems, 23.8% flexible all-perovskite TSCs with a superior V-OC of 2.1 V is achieved, which is on par with the V-OC reported on the 28% all-perovskite tandems grown on the rigid substrate.
Generated-X LMS (GXLMS)
(2021)
The quality of the reference signal is essential for the adaptation process of an LMS or one of its derivatives. The reference signal affects the stability, the convergence rate and the maximum achievable attenuation. Since the error signal and the control signal are available as numerical values in the algorithm for the LMS, the reference signal can be calculated from both signals. The error signal is the interference between the control signal and the reference signal. This interference of the control signal and the reference signal can be noted mathematically as a simple addition. It is therefore possible to deduce the reference signal from a known error signal and control signal. This approach is the basis of the generated-x LMS (GxLMS) developed by us. It calculates the reference signal itself without having to rely on an externally supplied reference signal. The advantages of the GxLMS are primarily in fields where the reference signal is difficult or impossible to detect. For example, the detection of the reference signal can be problematic due to design reasons or measurement technology. For example, flow noise could have a negative effect on an acoustic detection of the reference signal. However, the calculation of the reference signal in the GxLMS represents a further feedback signal path, which affects the stability of the algorithm as a whole. Based on the theoretical principles mathematically sufficient convergence conditions can be formulated taking into account the delays existing in the signal paths. The experimental testing took place on an acoustic duct with monofrequency disturb signals. Since the use of an efficient design of experiments (DoE) could be excluded, the measurement was designed as parameter variation (one factor at time) and therefore very time-consuming. The theoretical background of the GxLMS as well as the results from the experiments are presented.
The Warm-Hot Intergalactic Medium (WHIM) arises from shock-heated gas collapsing in large-scale filaments and probably harbours a substantial fraction of the baryons in the local Universe. Absorption-line measurements in the ultraviolet (UV) and in the X-ray band currently represent the best method to study the WHIM at low redshifts. We here describe the physical properties of the WHIM and the concepts behind WHIM absorption line measurements of Hi and high ions such as Ovi, Ovii, and Oviii in the far-ultraviolet and X-ray band. We review results of recent WHIM absorption line studies carried out with UV and X-ray satellites such as FUSE, HST, Chandra, and XMM-Newton and discuss their implications for our knowledge of the WHIM.
When inferring on the magnitude of future heat-related mortality due to climate change, human adaptation to heat should be accounted for. We model long-term changes in minimum mortality temperatures (MMT), a well-established metric denoting the lowest risk of heat-related mortality, as a function of climate change and socio-economic progress across 3820 cities. Depending on the combination of climate trajectories and socio-economic pathways evaluated, by 2100 the risk to human health is expected to decline in 60% to 80% of the cities against contemporary conditions. This is caused by an average global increase in MMTs driven by long-term human acclimatisation to future climatic conditions and economic development of countries. While our adaptation model suggests that negative effects on health from global warming can broadly be kept in check, the trade-offs are highly contingent to the scenario path and location-specific. For high-forcing climate scenarios (e.g. RCP8.5) the maintenance of uninterrupted high economic growth by 2100 is a hard requirement to increase MMTs and level-off the negative health effects from additional scenario-driven heat exposure. Choosing a 2 degrees C-compatible climate trajectory alleviates the dependence on fast growth, leaving room for a sustainable economy, and leads to higher reductions of mortality risk.
In natural heterogeneous environments, the fitness of animals is strongly influenced by the availability and composition of food. Food quantity and biochemical quality constraints may affect individual traits of consumers differently, mediating fitness response variation within and among species. Using a multifactorial experimental approach, we assessed population growth rate, fecundity, and survival of six strains of the two closely related freshwater rotifer species Brachionus calyciflorus sensu stricto and Brachionus fernandoi. Therefore, rotifers fed low and high concentrations of three algal species differing in their biochemical food quality. Additionally, we explored the potential of a single limiting biochemical nutrient to mediate variations in population growth response. Therefore, rotifers fed a sterol-free alga, which we supplemented with cholesterol-containing liposomes. Co-limitation by food quantity and biochemical food quality resulted in differences in population growth rates among strains, but not between species, although effects on fecundity and survival differed between species. The effect of cholesterol supplementation on population growth was strain-specific but not species-specific. We show that fitness response variations within and among species can be mediated by biochemical food quality. Dietary constraints thus may act as evolutionary drivers on physiological traits of consumers, which may have strong implications for various ecological interactions.
In natural heterogeneous environments, the fitness of animals is strongly influenced by the availability and composition of food. Food quantity and biochemical quality constraints may affect individual traits of consumers differently, mediating fitness response variation within and among species. Using a multifactorial experimental approach, we assessed population growth rate, fecundity, and survival of six strains of the two closely related freshwater rotifer species Brachionus calyciflorus sensu stricto and Brachionus fernandoi. Therefore, rotifers fed low and high concentrations of three algal species differing in their biochemical food quality. Additionally, we explored the potential of a single limiting biochemical nutrient to mediate variations in population growth response. Therefore, rotifers fed a sterol-free alga, which we supplemented with cholesterol-containing liposomes. Co-limitation by food quantity and biochemical food quality resulted in differences in population growth rates among strains, but not between species, although effects on fecundity and survival differed between species. The effect of cholesterol supplementation on population growth was strain-specific but not species-specific. We show that fitness response variations within and among species can be mediated by biochemical food quality. Dietary constraints thus may act as evolutionary drivers on physiological traits of consumers, which may have strong implications for various ecological interactions.
Fibrous shape-memory polymer (SMP) scaffolds were investigated considering the fiber as basic microstructural feature. By reduction of the fiber diameter in randomly oriented electrospun polyetherurethane (PEU) meshes from the micro-to the nano-scale, we observed changes in the molecular orientation within the fibers and its impact on the structural and shape-memory performance. It was assumed that a spatial restriction by reduction of the fiber diameter increases molecular orientation along the orientation of the fiber. The stress-strain relation of random PEU scaffolds is initially determined by the 3D arrangement of the fibers and thus is independent of the molecular orientation. Increasing the molecular orientation with decreasing single fiber diameter in scaffolds composed of randomly arranged fibers did not alter the initial stiffness and peak stress but strongly influenced the elongation at break and the stress increase above the Yield point. Reduction of the single fiber diameter also distinctly improved the shape-memory performance of the scaffolds. Fibers with nanoscale diameters (< 100 nm) possessed an almost complete shape recovery, high recovery stresses and fast relaxation kinetics, while the shape fixity was found to decrease with decreasing fiber diameter. Hence, the fiber diameter is a relevant design parameter for SMP.
Fast Holocene slip and localized strain along the Liquiñe-Ofqui strike-slip fault system, Chile
(2021)
In active tectonic settings dominated by strike-slip kinematics, slip partitioning across subparallel faults is a common feature; therefore, assessing the degree of partitioning and strain localization is paramount for seismic hazard assessments. Here, we estimate a slip rate of 18.8 +/- 2.0 mm/year over the past 9.0 +/- 0.1 ka for a single strand of the Liquirie-Ofqui Fault System, which straddles the Main Cordillera in Southern Chile. This Holocene rate accounts for similar to 82% of the trench-parallel component of oblique plate convergence and is similar to million-year estimates integrated over the entire fault system. Our results imply that strain localizes on a single fault at millennial time scale but over longer time scales strain localization is not sustained. The fast millennial slip rate in the absence of historical Mw> 6.5 earthquakes along the Liquine-Ofqui Fault System implies either a component of aseismic slip or Mw similar to 7 earthquakes involving multi-trace ruptures and > 150-year repeat times. Our results have implications for the understanding of strike-slip fault system dynamics within volcanic arcs and seismic hazard assessments.
Organic solar cells (OSC) nowadays match their inorganic competitors in terms of current production but lag behind with regards to their open-circuit voltage loss and fill-factor, with state-of-the-art OSCs rarely displaying fill-factor of 80% and above. The fill-factor of transport-limited solar cells, including organic photovoltaic devices, is affected by material and device-specific parameters, whose combination is represented in terms of the established figures of merit, such as theta and alpha. Herein, it is demonstrated that these figures of merit are closely related to the long-range carrier drift and diffusion lengths. Further, a simple approach is presented to devise these characteristic lengths using steady-state photoconductance measurements. This yields a straightforward way of determining theta and alpha in complete cells and under operating conditions. This approach is applied to a variety of photovoltaic devices-including the high efficiency nonfullerene acceptor blends-and show that the diffusion length of the free carriers provides a good correlation with the fill-factor. It is, finally, concluded that most state-of-the-art organic solar cells exhibit a sufficiently large drift length to guarantee efficient charge extraction at short circuit, but that they still suffer from too small diffusion lengths of photogenerated carriers limiting their fill factor.
Enzymes can support the synthesis or degradation of biomacromolecules in natural processes. Here, we demonstrate that enzymes can induce a macroscopic-directed movement of microstructured hydrogels following a mechanism that we call a "Jack-in-the-box" effect. The material's design is based on the formation of internal stresses induced by a deformation load on an architectured microscale, which are kinetically frozen by the generation of polyester locking domains, similar to a Jack-in-thebox toy (i.e., a compressed spring stabilized by a closed box lid). To induce the controlled macroscopic movement, the locking domains are equipped with enzyme-specific cleavable bonds (i.e., a box with a lock and key system). As a result of enzymatic reaction, a transformed shape is achieved by the release of internal stresses. There is an increase in entropy in combination with a swelling-supported stretching of polymer chains within the microarchitectured hydrogel (i.e., the encased clown pops-up with a pre-stressed movement when the box is unlocked). This utilization of an enzyme as a physiological stimulus may offer new approaches to create interactive and enzyme-specific materials for different applications such as an optical indicator of the enzyme's presence or actuators and sensors in biotechnology and in fermentation processes.
Enhanced charge selectivity via anodic-C60 layer reduces nonradiative losses in organic solar cells
(2021)
Interfacial layers in conjunction with suitable charge-transport layers can significantly improve the performance of optoelectronic devices by facilitating efficient charge carrier injection and extraction.
This work uses a neat C-60 interlayer on the anode to experimentally reveal that surface recombination is a significant contributor to nonradiative recombination losses in organic solar cells.
These losses are shown to proportionally increase with the extent of contact between donor molecules in the photoactive layer and a molybdenum oxide (MoO3) hole extraction layer, proven by calculating voltage losses in low- and high-donor-content bulk heterojunction device architectures.
Using a novel in-device determination of the built-in voltage, the suppression of surface recombination, due to the insertion of a thin anodic-C-60 interlayer on MoO3, is attributed to an enhanced built-in potential.
The increased built-in voltage reduces the presence of minority charge carriers at the electrodes-a new perspective on the principle of selective charge extraction layers.
The benefit to device efficiency is limited by a critical interlayer thickness, which depends on the donor material in bilayer devices.
Given the high popularity of MoO3 as an efficient hole extraction and injection layer and the increasingly popular discussion on interfacial phenomena in organic optoelectronic devices, these findings are relevant to and address different branches of organic electronics, providing insights for future device design.
Inorganic perovskite solar cells show excellent thermal stability, but the reported power conversion efficiencies are still lower than for organic-inorganic perovskites. This is mainly caused by lower open-circuit voltages (V(OC)s). Herein, the reasons for the low V-OC in inorganic CsPbI2Br perovskite solar cells are investigated. Intensity-dependent photoluminescence measurements for different layer stacks reveal that n-i-p and p-i-n CsPbI2Br solar cells exhibit a strong mismatch between quasi-Fermi level splitting (QFLS) and V-OC. Specifically, the CsPbI2Br p-i-n perovskite solar cell has a QFLS-e center dot V-OC mismatch of 179 meV, compared with 11 meV for a reference cell with an organic-inorganic perovskite of similar bandgap. On the other hand, this study shows that the CsPbI2Br films with a bandgap of 1.9 eV have a very low defect density, resulting in an efficiency potential of 20.3% with a MeO-2PACz hole-transporting layer and 20.8% on compact TiO2. Using ultraviolet photoelectron spectroscopy measurements, energy level misalignment is identified as a possible reason for the QFLS-e center dot V-OC mismatch and strategies for overcoming this V-OC limitation are discussed. This work highlights the need to control the interfacial energetics in inorganic perovskite solar cells, but also gives promise for high efficiencies once this issue is resolved.
Instructions given prior to extinction training facilitate the extinction of conditioned skin conductance (SCRs) and fear-potentiated startle responses (FPSs) and serve as laboratory models for cognitive interventions implemented in exposure-based treatments of pathological anxiety. Here, we investigated how instructions given prior to extinction training, with or without the additional removal of the electrode used to deliver the unconditioned stimulus (US), affect the return of fear assessed 24 hours later. We replicated previous instruction effects on extinction and added that the additional removal of the US electrode slightly enhanced facilitating effects on the extinction of conditioned FPSs. In contrast, extinction instructions hardly affected the return of conditioned fear responses. These findings suggest that instruction effects observed during extinction training do not extent to tests of return of fear 24 hours later which serve as laboratory models of relapse and improvement stability of exposure-based treatments.
Instructions given prior to extinction training facilitate the extinction of conditioned skin conductance (SCRs) and fear-potentiated startle responses (FPSs) and serve as laboratory models for cognitive interventions implemented in exposure-based treatments of pathological anxiety. Here, we investigated how instructions given prior to extinction training, with or without the additional removal of the electrode used to deliver the unconditioned stimulus (US), affect the return of fear assessed 24 hours later. We replicated previous instruction effects on extinction and added that the additional removal of the US electrode slightly enhanced facilitating effects on the extinction of conditioned FPSs. In contrast, extinction instructions hardly affected the return of conditioned fear responses. These findings suggest that instruction effects observed during extinction training do not extent to tests of return of fear 24 hours later which serve as laboratory models of relapse and improvement stability of exposure-based treatments.
Cells and organelles are not homogeneous but include microcompartments that alter the spatiotemporal characteristics of cellular processes. The effects of microcompartmentation on metabolic pathways are however difficult to study experimentally. The pyrenoid is a microcompartment that is essential for a carbon concentrating mechanism (CCM) that improves the photosynthetic performance of eukaryotic algae. Using Chlamydomonas reinhardtii, we obtained experimental data on photosynthesis, metabolites, and proteins in CCM-induced and CCM-suppressed cells. We then employed a computational strategy to estimate how fluxes through the Calvin-Benson cycle are compartmented between the pyrenoid and the stroma. Our model predicts that ribulose-1,5-bisphosphate (RuBP), the substrate of Rubisco, and 3-phosphoglycerate (3PGA), its product, diffuse in and out of the pyrenoid, respectively, with higher fluxes in CCM-induced cells. It also indicates that there is no major diffusional barrier to metabolic flux between the pyrenoid and stroma. Our computational approach represents a stepping stone to understanding microcompartmentalized CCM in other organisms.
Peripersonal space is the space surrounding our body, where multisensory integration of stimuli and action execution take place. The size of peripersonal space is flexible and subject to change by various personal and situational factors. The dynamic representation of our peripersonal space modulates our spatial behaviors towards other individuals. During the COVID-19 pandemic, this spatial behavior was modified by two further factors: social distancing and wearing a face mask. Evidence from offline and online studies on the impact of a face mask on pro-social behavior is mixed. In an attempt to clarify the role of face masks as pro-social or anti-social signals, 235 observers participated in the present online study. They watched pictures of two models standing at three different distances from each other (50, 90 and 150 cm), who were either wearing a face mask or not and were either interacting by initiating a hand shake or just standing still. The observers’ task was to classify the model by gender. Our results show that observers react fastest, and therefore show least avoidance, for the shortest distances (50 and 90 cm) but only when models wear a face mask and do not interact. Thus, our results document both pro- and anti-social consequences of face masks as a result of the complex interplay between social distancing and interactive behavior. Practical implications of these findings are discussed.
Droughts in São Paulo
(2023)
Literature has suggested that droughts and societies are mutually shaped and, therefore, both require a better understanding of their coevolution on risk reduction and water adaptation. Although the Sao Paulo Metropolitan Region drew attention because of the 2013-2015 drought, this was not the first event. This paper revisits this event and the 1985-1986 drought to compare the evolution of drought risk management aspects. Documents and hydrological records are analyzed to evaluate the hazard intensity, preparedness, exposure, vulnerability, responses, and mitigation aspects of both events. Although the hazard intensity and exposure of the latter event were larger than the former one, the policy implementation delay and the dependency of service areas in a single reservoir exposed the region to higher vulnerability. In addition to the structural and non-structural tools implemented just after the events, this work raises the possibility of rainwater reuse for reducing the stress in reservoirs.
The olfactomotor system is especially investigated by examining the sniffing in reaction to olfactory stimuli. The motor output of respiratory-independent muscles was seldomly considered regarding possible influences of smells. The Adaptive Force (AF) characterizes the capability of the neuromuscular system to adapt to external forces in a holding manner and was suggested to be more vulnerable to possible interfering stimuli due to the underlying complex control processes. The aim of this pilot study was to measure the effects of olfactory inputs on the AF of the hip and elbow flexors, respectively. The AF of 10 subjects was examined manually by experienced testers while smelling at sniffing sticks with neutral, pleasant or disgusting odours. The reaction force and the limb position were recorded by a handheld device. The results show, inter alia, a significantly lower maximal isometric AF and a significantly higher AF at the onset of oscillations by perceiving disgusting odours compared to pleasant or neutral odours (p < 0.001). The adaptive holding capacity seems to reflect the functionality of the neuromuscular control, which can be impaired by disgusting olfactory inputs. An undisturbed functioning neuromuscular system appears to be characterized by a proper length tension control and by an earlier onset of mutual oscillations during an external force increase. This highlights the strong connection of olfaction and motor control also regarding respiratory-independent muscles.
The layered dichalcogenide MoS2 is relevant for electrochemical Li adsorption/intercalation, in the course of which the material undergoes a concomitant structural phase transition from semiconducting 2H-MoS2 to metallic 1T-LixMoS2. With the core hole clock approach at the S L1 X-ray absorption edge we quantify the ultrafast directional charge transfer of excited S3p electrons in-plane () and out-of-plane (perpendicular to) for 2H-MoS2 as tau 2H,=0.38 +/- 0.08 fs and tau 2H,perpendicular to =0.33 +/- 0.06 fs and for 1T-LixMoS2 as tau 1T,=0.32 +/- 0.12 fs and tau 1T,perpendicular to =0.09 +/- 0.07 fs. The isotropic charge delocalization of S3p electrons in the semiconducting 2H phase within the S-Mo-S sheets is assigned to the specific symmetry of the Mo-S bonding arrangement. Formation of 1T-LixMoS2 by lithiation accelerates the in-plane charge transfer by a factor of similar to 1.2 due to electron injection to the Mo-S covalent bonds and concomitant structural repositioning of S atoms within the S-Mo-S sheets. For excitation into out-of-plane orbitals, an accelerated charge transfer by a factor of similar to 3.7 upon lithiation occurs due to S-Li coupling.
Development Aid
(2017)
Development aid has been an important catalyst for economic development and international politics since the end of WWII. A critical analysis of the main political, social and economic advances in development aid, traces the development agenda from the advent of the Bretton Woods agreement, the Truman Doctrine and the Marshall Plan, to the Washington Consensus and its neoliberal manifesto. The failure of the Washington Consensus and the rise of the post-Washington Consensus is analysed providing a backdrop for the critique of economic globalisation as a development aid cornerstone. Trump’s rejection of the neoliberal globalisation agenda and departure from post-WWII ideologies is discussed.
In this work, which is part of a larger research program, a framework called "virtual data fusion" was developed to provide an automated and consistent crack detection method that allows for the cross-comparison of results from large quantities of X-ray computed tomography (CT) data. A partial implementation of this method in a custom program was developed for use in research focused on crack quantification in alkali-silica reaction (ASR)-sensitive concrete aggregates. During the CT image processing, a series of image analyses tailored for detecting specific, individual crack-like characteristics were completed. The results of these analyses were then "fused" in order to identify crack-like objects within the images with much higher accuracy than that yielded by any individual image analysis procedure. The results of this strategy demonstrated the success of the program in effectively identifying crack-like structures and quantifying characteristics, such as surface area and volume. The results demonstrated that the source of aggregate has a very significant impact on the amount of internal cracking, even when the mineralogical characteristics remain very similar. River gravels, for instance, were found to contain significantly higher levels of internal cracking than quarried stone aggregates of the same mineralogical type.
Dendritic hPG-amid-C18-mPEG core-multishell nanocarriers (CMS) represent a novel class of unimolecular micelles that hold great potential as drug transporters, e. g., to facilitate topical therapy in skin diseases. Atopic dermatitis is among the most common inflammatory skin disorders with complex barrier alterations which may affect the efficacy of topical treatment.
Here, we tested the penetration behavior and identified target structures of unloaded CMS after topical administration in healthy mice and in mice with oxazolone-induced atopic dermatitis. We further examined whole body distribution and possible systemic side effects after simulating high dosage dermal penetration by subcutaneous injection.
Following topical administration, CMS accumulated in the stratum corneum without penetration into deeper viable epidermal layers. The same was observed in atopic dermatitis mice, indicating that barrier alterations in atopic dermatitis had no influence on the penetration of CMS. Following subcutaneous injection, CMS were deposited in the regional lymph nodes as well as in liver, spleen, lung, and kidney. However, in vitro toxicity tests, clinical data, and morphometry-assisted histopathological analyses yielded no evidence of any toxic or otherwise adverse local or systemic effects of CMS, nor did they affect the severity or course of atopic dermatitis.
Taken together, CMS accumulate in the stratum corneum in both healthy and inflammatory skin and appear to be highly biocompatible in the mouse even under conditions of atopic dermatitis and thus could potentially serve to create a depot for anti-inflammatory drugs in the skin.
Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions while still guaranteeing high throughputs and robustness against external disruptions. Deep reinforcement learning (RL) algorithms, which already reached impressive success with Google DeepMind's AlphaGo, are increasingly transferred to production systems to meet related requirements. Unlike supervised and unsupervised machine learning techniques, deep RL algorithms learn based on recently collected sensorand process-data in direct interaction with the environment and are able to perform decisions in real-time. As such, deep RL algorithms seem promising given their potential to provide decision support in complex environments, as production systems, and simultaneously adapt to changing circumstances. While different use-cases for deep RL emerged, a structured overview and integration of findings on their application are missing. To address this gap, this contribution provides a systematic literature review of existing deep RL applications in the field of production planning and control as well as production logistics. From a performance perspective, it became evident that deep RL can beat heuristics significantly in their overall performance and provides superior solutions to various industrial use-cases. Nevertheless, safety and reliability concerns must be overcome before the widespread use of deep RL is possible which presumes more intensive testing of deep RL in real world applications besides the already ongoing intensive simulations.
Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions while still guaranteeing high throughputs and robustness against external disruptions. Deep rein- forcement learning (RL) algorithms, which already reached impressive success with Google DeepMind's AlphaGo, are increasingly transferred to production systems to meet related requirements. Unlike supervised and unsupervised machine learning techniques, deep RL algorithms learn based on recently collected sensor- and process-data in direct interaction with the environment and are able to perform decisions in real-time. As such, deep RL algorithms seem promising given their potential to provide decision support in complex environments, as production systems, and simultaneously adapt to changing circumstances. While different use-cases for deep RL emerged, a structured overview and integration of findings on their application are missing. To address this gap, this contribution provides a systematic literature review of existing deep RL applications in the field of production planning and control as well as production logistics. From a performance perspective, it became evident that deep RL can beat heuristics significantly in their overall performance and provides superior solutions to various industrial use-cases. Nevertheless, safety and reliability concerns must be overcome before the widespread use of deep RL is possible which presumes more intensive testing of deep RL in real world applications besides the already ongoing intensive simulations.
The in‐depth understanding of charge carrier photogeneration and recombination mechanisms in organic solar cells is still an ongoing effort. In donor:acceptor (bulk) heterojunction organic solar cells, charge photogeneration and recombination are inter‐related via the kinetics of charge transfer states—being singlet or triplet states. Although high‐charge‐photogeneration quantum yields are achieved in many donor:acceptor systems, only very few systems show significantly reduced bimolecular recombination relative to the rate of free carrier encounters, in low‐mobility systems. This is a serious limitation for the industrialization of organic solar cells, in particular when aiming at thick active layers. Herein, a meta‐analysis of the device performance of numerous bulk heterojunction organic solar cells is presented for which field‐dependent photogeneration, charge carrier mobility, and fill factor are determined. Herein, a “spin‐related factor” that is dependent on the ratio of back electron transfer of the triplet charge transfer (CT) states to the decay rate of the singlet CT states is introduced. It is shown that this factor links the recombination reduction factor to charge‐generation efficiency. As a consequence, it is only in the systems with very efficient charge generation and very fast CT dissociation that free carrier recombination is strongly suppressed, regardless of the spin‐related factor.
Many knowledge representation tasks involve trees or similar structures as abstract datatypes. However, devising compact and efficient declarative representations of such structural properties is non-obvious and can be challenging indeed. In this article, we take a number of acyclicity properties into consideration and investigate various logic-based approaches to encode them. We use answer set programming as the primary representation language but also consider mappings to related formalisms, such as propositional logic, difference logic and linear programming. We study the compactness of encodings and the resulting computational performance on benchmarks involving acyclic or tree structures.
Taxonomy plays a central role in biological sciences. It provides a communication system for scientists as it aims to enable correct identification of the studied organisms. As a consequence, species descriptions should seek to include as much available information as possible at species level to follow an integrative concept of 'taxonomics'. Here, we describe the cryptic species Epimeria frankei sp. nov. from the North Sea, and also redescribe its sister species, Epimeria cornigera. The morphological information obtained is substantiated by DNA barcodes and complete nuclear 18S rRNA gene sequences. In addition, we provide, for the first time, full mitochondrial genome data as part of a metazoan species description for a holotype, as well as the neotype. This study represents the first successful implementation of the recently proposed concept of taxonomics, using data from high-throughput technologies for integrative taxonomic studies, allowing the highest level of confidence for both biodiversity and ecological research.
Cooperation is — despite not being predicted by game theory — a widely documented aspect of human behaviour in Prisoner’s Dilemma (PD) situations. This article presents a comparison between subjects restricted to playing pure strategies and subjects allowed to play mixed strategies in a one-shot symmetric PD laboratory experiment. Subjects interact with 10 other subjects and take their decisions all at once. Because subjects in the mixed-strategy treatment group are allowed to condition their level of cooperation more precisely on their beliefs about their counterparts’ level of cooperation, we predicted the cooperation rate in the mixed-strategy treatment group to be higher than in the pure-strategy control group. The results of our experiment reject our prediction: even after controlling for beliefs about the other subjects’ level of cooperation, we find that cooperation in the mixed-strategy group is lower than in the pure-strategy group. We also find, however, that subjects in the mixedstrategy group condition their cooperative behaviour more closely on their beliefs than in the pure-strategy group. In the mixed-strategy group, most subjects choose intermediate levels of cooperation.
Cooperation is — despite not being predicted by game theory — a widely documented aspect of human behaviour in Prisoner’s Dilemma (PD) situations. This article presents a comparison between subjects restricted to playing pure strategies and subjects allowed to play mixed strategies in a one-shot symmetric PD laboratory experiment. Subjects interact with 10 other subjects and take their decisions all at once. Because subjects in the mixed-strategy treatment group are allowed to condition their level of cooperation more precisely on their beliefs about their counterparts’ level of cooperation, we predicted the cooperation rate in the mixed-strategy treatment group to be higher than in the pure-strategy control group. The results of our experiment reject our prediction: even after controlling for beliefs about the other subjects’ level of cooperation, we find that cooperation in the mixed-strategy group is lower than in the pure-strategy group. We also find, however, that subjects in the mixedstrategy group condition their cooperative behaviour more closely on their beliefs than in the pure-strategy group. In the mixed-strategy group, most subjects choose intermediate levels of cooperation.
With the spread of smart phones capable of taking high-resolution photos and the development of high-speed mobile data infrastructure, digital visual media is becoming one of the most important forms of modern communication. With this development, however, also comes a devaluation of images as a media form with the focus becoming the frequency at which visual content is generated instead of the quality of the content. In this work, an interactive system using image-abstraction techniques and an eye tracking sensor is presented, which allows users to experience diverting and dynamic artworks that react to their eye movement. The underlying modular architecture enables a variety of different interaction techniques that share common design principles, making the interface as intuitive as possible. The resulting experience allows users to experience a game-like interaction in which they aim for a reward, the artwork, while being held under constraints, e.g., not blinking. The co nscious eye movements that are required by some interaction techniques hint an interesting, possible future extension for this work into the field of relaxation exercises and concentration training.
With the spread of smart phones capable of taking high-resolution photos and the development of high-speed mobile data infrastructure, digital visual media is becoming one of the most important forms of modern communication. With this development, however, also comes a devaluation of images as a media form with the focus becoming the frequency at which visual content is generated instead of the quality of the content. In this work, an interactive system using image-abstraction techniques and an eye tracking sensor is presented, which allows users to experience diverting and dynamic artworks that react to their eye movement. The underlying modular architecture enables a variety of different interaction techniques that share common design principles, making the interface as intuitive as possible. The resulting experience allows users to experience a game-like interaction in which they aim for a reward, the artwork, while being held under constraints, e.g., not blinking. The co nscious eye movements that are required by some interaction techniques hint an interesting, possible future extension for this work into the field of relaxation exercises and concentration training.
Emotions are a central element of human experience. They occur with high frequency in everyday life and play an important role in decision making. However, currently there is no consensus among researchers on what constitutes an emotion and on how emotions should be investigated. This dissertation identifies three problems of current emotion research: the problem of ground truth, the problem of incomplete constructs and the problem of optimal representation. I argue for a focus on the detailed measurement of emotion manifestations with computer-aided methods to solve these problems. This approach is demonstrated in three research projects, which describe the development of methods specific to these problems as well as their application to concrete research questions.
The problem of ground truth describes the practice to presuppose a certain structure of emotions as the a priori ground truth. This determines the range of emotion descriptions and sets a standard for the correct assignment of these descriptions. The first project illustrates how this problem can be circumvented with a multidimensional emotion perception paradigm which stands in contrast to the emotion recognition paradigm typically employed in emotion research. This paradigm allows to calculate an objective difficulty measure and to collect subjective difficulty ratings for the perception of emotional stimuli. Moreover, it enables the use of an arbitrary number of emotion stimuli categories as compared to the commonly used six basic emotion categories. Accordingly, we collected data from 441 participants using dynamic facial expression stimuli from 40 emotion categories. Our findings suggest an increase in emotion perception difficulty with increasing actor age and provide evidence to suggest that young adults, the elderly and men underestimate their emotion perception difficulty. While these effects were predicted from the literature, we also found unexpected and novel results. In particular, the increased difficulty on the objective difficulty measure for female actors and observers stood in contrast to reported findings. Exploratory analyses revealed low relevance of person-specific variables for the prediction of emotion perception difficulty, but highlighted the importance of a general pleasure dimension for the ease of emotion perception.
The second project targets the problem of incomplete constructs which relates to vaguely defined psychological constructs on emotion with insufficient ties to tangible manifestations. The project exemplifies how a modern data collection method such as face tracking data can be used to sharpen these constructs on the example of arousal, a long-standing but fuzzy construct in emotion research. It describes how measures of distance, speed and magnitude of acceleration can be computed from face tracking data and investigates their intercorrelations. We find moderate to strong correlations among all measures of static information on one hand and all measures of dynamic information on the other. The project then investigates how self-rated arousal is tied to these measures in 401 neurotypical individuals and 19 individuals with autism. Distance to the neutral face was predictive of arousal ratings in both groups. Lower mean arousal ratings were found for the autistic group, but no difference in correlation of the measures and arousal ratings could be found between groups. Results were replicated in a high autistic traits group consisting of 41 participants. The findings suggest a qualitatively similar perception of arousal for individuals with and without autism. No correlations between valence ratings and any of the measures could be found which emphasizes the specificity of our tested measures for the construct of arousal.
The problem of optimal representation refers to the search for the best representation of emotions and the assumption that there is a one-fits-all solution. In the third project we introduce partial least squares analysis as a general method to find an optimal representation to relate two high-dimensional data sets to each other. The project demonstrates its applicability to emotion research on the question of emotion perception differences between men and women. The method was used with emotion rating data from 441 participants and face tracking data computed on 306 videos. We found quantitative as well as qualitative differences in the perception of emotional facial expressions between these groups. We showed that women’s emotional perception systematically captured more of the variance in facial expressions. Additionally, we could show that significant differences exist in the way that women and men perceive some facial expressions which could be visualized as concrete facial expression sequences. These expressions suggest differing perceptions of masked and ambiguous facial expressions between the sexes. In order to facilitate use of the developed method by the research community, a package for the statistical environment R was written. Furthermore, to call attention to the method and its usefulness for emotion research, a website was designed that allows users to explore a model of emotion ratings and facial expression data in an interactive fashion.
Cell-free protein synthesis as a novel tool for directed glycoengineering of active erythropoietin
(2018)
As one of the most complex post-translational modification, glycosylation is widely involved in cell adhesion, cell proliferation and immune response. Nevertheless glycoproteins with an identical polypeptide backbone mostly differ in their glycosylation patterns. Due to this heterogeneity, the mapping of different glycosylation patterns to their associated function is nearly impossible. In the last years, glycoengineering tools including cell line engineering, chemoenzymatic remodeling and site-specific glycosylation have attracted increasing interest. The therapeutic hormone erythropoietin (EPO) has been investigated in particular by various groups to establish a production process resulting in a defined glycosylation pattern. However commercially available recombinant human EPO shows batch-to-batch variations in its glycoforms. Therefore we present an alternative method for the synthesis of active glycosylated EPO with an engineered O-glycosylation site by combining eukaryotic cell-free protein synthesis and site-directed incorporation of non-canonical amino acids with subsequent chemoselective modifications.
Cell-free protein synthesis as a novel tool for directed glycoengineering of active erythropoietin
(2018)
As one of the most complex post-translational modification, glycosylation is widely involved in cell adhesion, cell proliferation and immune response. Nevertheless glycoproteins with an identical polypeptide backbone mostly differ in their glycosylation patterns. Due to this heterogeneity, the mapping of different glycosylation patterns to their associated function is nearly impossible. In the last years, glycoengineering tools including cell line engineering, chemoenzymatic remodeling and site-specific glycosylation have attracted increasing interest. The therapeutic hormone erythropoietin (EPO) has been investigated in particular by various groups to establish a production process resulting in a defined glycosylation pattern. However commercially available recombinant human EPO shows batch-to-batch variations in its glycoforms. Therefore we present an alternative method for the synthesis of active glycosylated EPO with an engineered O-glycosylation site by combining eukaryotic cell-free protein synthesis and site-directed incorporation of non-canonical amino acids with subsequent chemoselective modifications.
From an active labor market policy perspective, start-up subsidies for unemployed individuals are very effective in improving long-term labor market outcomes for participants. From a business perspective, however, the assessment of these public programs is less clear since they might attract individuals with low entrepreneurial abilities and produce businesses with low survival rates and little contribution to job creation, economic growth, and innovation. In this paper, we use a rich data set to compare participants of a German start-up subsidy program for unemployed individuals to a group of regular founders who started from non-unemployment and did not receive the subsidy. The data allows us to analyze their business performance up until 40 months after business formation. We find that formerly subsidized founders lag behind not only in survival and job creation, but especially also in innovation activities. The gaps in these business outcomes are relatively constant or even widening over time. Hence, we do not see any indication of catching up in the longer run. While the gap in survival can be entirely explained by initial differences in observable start-up characteristics, the gap in business development remains and seems to be the result of restricted access to capital as well as differential business strategies and dynamics. Considering these conflicting results for the assessment of the subsidy program from an ALMP and business perspective, policy makers need to carefully weigh the costs and benefits of such a strategy to find the right policy mix.
Carbon adsorbents from spent coffee for removal of methylene blue and methyl orange from water
(2021)
Activated carbons (ACs) were prepared from dried spent coffee (SCD), a biological waste product, to produce adsorbents for methylene blue (MB) and methyl orange (MO) from aqueous solution. Pre-pyrolysis activation of SCD was achieved via treatment of the SCD with aqueous sodium hydroxide solutions at 90 °C. Pyrolysis of the pretreated SCD at 500 °C for 1 h produced powders with typical characteristics of AC suitable and effective for dye adsorption. As an alternative to the rather harsh base treatment, calcium carbonate powder, a very common and abundant resource, was also studied as an activator. Mixtures of SCD and CaCO3 (1:1 w/w) yielded effective ACs for MO and MB removal upon pyrolysis needing only small amounts of AC to clear the solutions. A selectivity of the adsorption process toward anionic (MO) or cationic (MB) dyes was not observed.
Quorum-sensing bacteria in a growing colony of cells send out signalling molecules (so-called “autoinducers”) and themselves sense the autoinducer concentration in their vicinity. Once—due to increased local cell density inside a “cluster” of the growing colony—the concentration of autoinducers exceeds a threshold value, cells in this clusters get “induced” into a communal, multi-cell biofilm-forming mode in a cluster-wide burst event. We analyse quantitatively the influence of spatial disorder, the local heterogeneity of the spatial distribution of cells in the colony, and additional physical parameters such as the autoinducer signal range on the induction dynamics of the cell colony. Spatial inhomogeneity with higher local cell concentrations in clusters leads to earlier but more localised induction events, while homogeneous distributions lead to comparatively delayed but more concerted induction of the cell colony, and, thus, a behaviour close to the mean-field dynamics. We quantify the induction dynamics with quantifiers such as the time series of induction events and burst sizes, the grouping into induction families, and the mean autoinducer concentration levels. Consequences for different scenarios of biofilm growth are discussed, providing possible cues for biofilm control in both health care and biotechnology.
Quorum-sensing bacteria in a growing colony of cells send out signalling molecules (so-called “autoinducers”) and themselves sense the autoinducer concentration in their vicinity. Once—due to increased local cell density inside a “cluster” of the growing colony—the concentration of autoinducers exceeds a threshold value, cells in this clusters get “induced” into a communal, multi-cell biofilm-forming mode in a cluster-wide burst event. We analyse quantitatively the influence of spatial disorder, the local heterogeneity of the spatial distribution of cells in the colony, and additional physical parameters such as the autoinducer signal range on the induction dynamics of the cell colony. Spatial inhomogeneity with higher local cell concentrations in clusters leads to earlier but more localised induction events, while homogeneous distributions lead to comparatively delayed but more concerted induction of the cell colony, and, thus, a behaviour close to the mean-field dynamics. We quantify the induction dynamics with quantifiers such as the time series of induction events and burst sizes, the grouping into induction families, and the mean autoinducer concentration levels. Consequences for different scenarios of biofilm growth are discussed, providing possible cues for biofilm control in both health care and biotechnology.
Procrastination is a self-regulatory problem of voluntarily and destructively delaying intended and necessary or personally important tasks. Previous studies showed that procrastination is associated with executive dysfunctions that seem to be particularly strong in punishing contexts. In the present event-related potential (ERP) study a monetary version of the parametric Go/No-Go task was performed by high and low academic procrastinators to verify the influence of motivational context (reward vs. punishment expectation) and task difficulty (easy vs. hard) on procrastination-related executive dysfunctions. The results revealed increased post-error slowing along with reduced P300 and error-related negativity (ERN) amplitudes in high (vs. low) procrastination participants-effects that indicate impaired attention and error-related processing in this group. This pattern of results did not differ as a function of task difficulty and motivation condition. However, when the task got more difficult executive attention deficits became even more apparent at the behavioral level in high procrastinators, as indexed by increased reaction time variability. The findings substantiate prior preliminary evidence that procrastinators show difficulties in certain aspects of executive functioning (in attention and error processing) during execution of task-relevant behavior, which may be more apparent in highly demanding situations.
Materials based on biodegradable polyesters, such as poly(butylene terephthalate) (PBT) or poly(butylene terephthalate-co-poly(alkylene glycol) terephthalate) (PBTAT), have potential application as pro-regenerative scaffolds for bone tissue engineering. Herein, the preparation of films composed of PBT or PBTAT and an engineered spider silk protein, (eADF4(C16)), that displays multiple carboxylic acid moieties capable of binding calcium ions and facilitating their biomineralization with calcium carbonate or calcium phosphate is reported. Human mesenchymal stem cells cultured on films mineralized with calcium phosphate show enhanced levels of alkaline phosphatase activity suggesting that such composites have potential use for bone tissue engineering.
Energy system models are advancing rapidly. However, it is not clear whether models are becoming better, in the sense that they address the questions that decision-makers need to be answered to make well-informed decisions. Therefore, we investigate the gap between model improvements relevant from the perspective of modellers compared to what users of model results think models should address. Thus, we ask: What are the differences between energy model improvements as perceived by modellers, and the actual needs of users of model results? To answer this question, we conducted a literature review, 32 interviews, and an online survey. Our results show that user needs and ongoing improvements of energy system models align to a large degree so that future models are indeed likely to be better than current models. We also find mismatches between the needs of modellers and users, especially in the modelling of social, behavioural and political aspects, the trade-off between model complexity and understandability, and the ways that model results should be communicated. Our findings suggest that a better understanding of user needs and closer cooperation between modellers and users is imperative to truly improve models and unlock their full potential to support the transition towards climate neutrality in Europe.
In daily life, we automatically form impressions of other individuals on basis of subtle facial features that convey trustworthiness. Because these face-based judgements influence current and future social interactions, we investigated how perceived trustworthiness of faces affects long-term memory using event-related potentials (ERPs). In the current study, participants incidentally viewed 60 neutral faces differing in trustworthiness, and one week later, performed a surprise recognition memory task, in which the same old faces were presented intermixed with novel ones. We found that after one week untrustworthy faces were better recognized than trustworthy faces and that untrustworthy faces prompted early (350–550 ms) enhanced frontal ERP old/new differences (larger positivity for correctly remembered old faces, compared to novel ones) during recognition. Our findings point toward an enhanced long-lasting, likely familiarity-based, memory for untrustworthy faces. Even when trust judgments about a person do not necessarily need to be accurate, a fast access to memories predicting potential harm may be important to guide social behaviour in daily life.
In daily life, we automatically form impressions of other individuals on basis of subtle facial features that convey trustworthiness. Because these face-based judgements influence current and future social interactions, we investigated how perceived trustworthiness of faces affects long-term memory using event-related potentials (ERPs). In the current study, participants incidentally viewed 60 neutral faces differing in trustworthiness, and one week later, performed a surprise recognition memory task, in which the same old faces were presented intermixed with novel ones. We found that after one week untrustworthy faces were better recognized than trustworthy faces and that untrustworthy faces prompted early (350–550 ms) enhanced frontal ERP old/new differences (larger positivity for correctly remembered old faces, compared to novel ones) during recognition. Our findings point toward an enhanced long-lasting, likely familiarity-based, memory for untrustworthy faces. Even when trust judgments about a person do not necessarily need to be accurate, a fast access to memories predicting potential harm may be important to guide social behaviour in daily life.
In a subset of patients, non-alcoholic fatty liver disease (NAFLD) is complicated by cell death and inflammation resulting in non-alcoholic steatohepatitis (NASH), which may progress to fibrosis and subsequent organ failure. Apart from cytokines, prostaglandins, in particular prostaglandin E-2 (PGE(2)), play a pivotal role during inflammatory processes. Expression of the key enzymes of PGE(2) synthesis, cyclooxygenase 2 and microsomal PGE synthase 1 (mPGES-1), was increased in human NASH livers in comparison to controls and correlated with the NASH activity score. Both enzymes were also induced in NASH-diet-fed wild-type mice, resulting in an increase in hepatic PGE(2) concentration that was completely abrogated in mPGES-1-deficient mice. PGE(2) is known to inhibit TNF-alpha synthesis in macrophages. A strong infiltration of monocyte-derived macrophages was observed in NASH-diet-fed mice, which was accompanied with an increase in hepatic TNF-alpha expression. Due to the impaired PGE(2) production, TNF-alpha expression increased much more in livers of mPGES-1-deficient mice or in the peritoneal macrophages of these mice. The increased levels of TNF-alpha resulted in an enhanced IL-1 beta production, primarily in hepatocytes, and augmented hepatocyte apoptosis. In conclusion, attenuation of PGE(2) production by mPGES-1 ablation enhanced the TNF-alpha-triggered inflammatory response and hepatocyte apoptosis in diet-induced NASH.
In a subset of patients, non-alcoholic fatty liver disease (NAFLD) is complicated by cell death and inflammation resulting in non-alcoholic steatohepatitis (NASH), which may progress to fibrosis and subsequent organ failure. Apart from cytokines, prostaglandins, in particular prostaglandin E-2 (PGE(2)), play a pivotal role during inflammatory processes. Expression of the key enzymes of PGE(2) synthesis, cyclooxygenase 2 and microsomal PGE synthase 1 (mPGES-1), was increased in human NASH livers in comparison to controls and correlated with the NASH activity score. Both enzymes were also induced in NASH-diet-fed wild-type mice, resulting in an increase in hepatic PGE(2) concentration that was completely abrogated in mPGES-1-deficient mice. PGE(2) is known to inhibit TNF-alpha synthesis in macrophages. A strong infiltration of monocyte-derived macrophages was observed in NASH-diet-fed mice, which was accompanied with an increase in hepatic TNF-alpha expression. Due to the impaired PGE(2) production, TNF-alpha expression increased much more in livers of mPGES-1-deficient mice or in the peritoneal macrophages of these mice. The increased levels of TNF-alpha resulted in an enhanced IL-1 beta production, primarily in hepatocytes, and augmented hepatocyte apoptosis. In conclusion, attenuation of PGE(2) production by mPGES-1 ablation enhanced the TNF-alpha-triggered inflammatory response and hepatocyte apoptosis in diet-induced NASH.
Copolyesterurethanes (PDLCLs) based on oligo(epsilon-caprolactone) (OCL) and oligo(omega-pentadecalactone) (OPDL) segments are biodegradable thermoplastic temperature-memory polymers. The temperature-memory capability in these polymers with crystallizable control units is implemented by a thermomechanical programming process causing alterations in the crystallite arrangement and chain organization. These morphological changes can potentially affect degradation. Initial observations on the macroscopic level inspire the hypothesis that switching of the controlling units causes an accelerated degradation of the material, resulting in programmable degradation by sequential coupling of functions. Hence, detailed degradation studies on Langmuir films of a PDLCL with 40 wt% OPDL content are carried out under enzymatic catalysis. The temperature-memory creation procedure is mimicked by compression at different temperatures. The evolution of the chain organization and mechanical properties during the degradation process is investigated by means of polarization-modulated infrared reflection absorption spectroscopy, interfacial rheology and to some extend by X-ray reflectivity. The experiments on PDLCL Langmuir films imply that degradability is not enhanced by thermal switching, as the former depends on the temperature during cold programming. Nevertheless, the thin film experiments show that the leaching of OCL segments does not induce further crystallization of the OPDL segments, which is beneficial for a controlled and predictable degradation.
alt'ai is an agent-based simulation inspired by aesthetics, culture and environmental conditions of the Altai mountain region on the borders between Russia, Kazakhstan, China and Mongolia. It is set into a scenario of a remote automated landscape populated by sentient machines, where biological species, machines and environments autonomously interact to produce unforeseeable visual outputs. It poses a question of designing future machine-to-machine authentication protocols that are based on the use of images encoding agent behavior. Also, the simulation provides rich visual perspective on this challenge. The project pleads for a heavily aestheticized approach to design practice and highlights the importance of productively inefficient and information redundant systems.
In the last decades, there was a notable progress in solving the well-known Boolean satisfiability (Sat) problem, which can be witnessed by powerful Sat solvers. One of the reasons why these solvers are so fast are structural properties of instances that are utilized by the solver’s interna. This thesis deals with the well-studied structural property treewidth, which measures the closeness of an instance to being a tree. In fact, there are many problems parameterized by treewidth that are solvable in polynomial time in the instance size when parameterized by treewidth.
In this work, we study advanced treewidth-based methods and tools for problems in knowledge representation and reasoning (KR). Thereby, we provide means to establish precise runtime results (upper bounds) for canonical problems relevant to KR. Then, we present a new type of problem reduction, which we call decomposition-guided (DG) that
allows us to precisely monitor the treewidth when reducing from one problem to another problem. This new reduction type will be the basis for a long-open lower bound result for quantified Boolean formulas and allows us to design a new methodology for establishing runtime lower bounds for problems parameterized by treewidth.
Finally, despite these lower bounds, we provide an efficient implementation of algorithms that adhere to treewidth. Our approach finds suitable abstractions of instances, which are subsequently refined in a recursive fashion, and it uses Sat solvers for solving subproblems. It turns out that our resulting solver is quite competitive for two canonical counting problems related to Sat.
Fragmentation of peptides leaves characteristic patterns in mass spectrometry data, which can be used to identify protein sequences, but this method is challenging for mutated or modified sequences for which limited information exist. Altenburg et al. use an ad hoc learning approach to learn relevant patterns directly from unannotated fragmentation spectra.
Mass spectrometry-based proteomics provides a holistic snapshot of the entire protein set of living cells on a molecular level. Currently, only a few deep learning approaches exist that involve peptide fragmentation spectra, which represent partial sequence information of proteins.
Commonly, these approaches lack the ability to characterize less studied or even unknown patterns in spectra because of their use of explicit domain knowledge.
Here, to elevate unrestricted learning from spectra, we introduce 'ad hoc learning of fragmentation' (AHLF), a deep learning model that is end-to-end trained on 19.2 million spectra from several phosphoproteomic datasets. AHLF is interpretable, and we show that peak-level feature importance values and pairwise interactions between peaks are in line with corresponding peptide fragments.
We demonstrate our approach by detecting post-translational modifications, specifically protein phosphorylation based on only the fragmentation spectrum without a database search. AHLF increases the area under the receiver operating characteristic curve (AUC) by an average of 9.4% on recent phosphoproteomic data compared with the current state of the art on this task.
Furthermore, use of AHLF in rescoring search results increases the number of phosphopeptide identifications by a margin of up to 15.1% at a constant false discovery rate. To show the broad applicability of AHLF, we use transfer learning to also detect cross-linked peptides, as used in protein structure analysis, with an AUC of up to 94%.
A treemap is a visualization that has been specifically designed to facilitate the exploration of tree-structured data and, more general, hierarchically structured data. The family of visualization techniques that use a visual metaphor for parent-child relationships based “on the property of containment” (Johnson, 1993) is commonly referred to as treemaps. However, as the number of variations of treemaps grows, it becomes increasingly important to distinguish clearly between techniques and their specific characteristics. This paper proposes to discern between Space-filling Treemap TS, Containment Treemap TC, Implicit Edge Representation Tree TIE, and Mapped Tree TMT for classification of hierarchy visualization techniques and highlights their respective properties. This taxonomy is created as a hyponymy, i.e., its classes have an is-a relationship to one another: TS TC TIE TMT. With this proposal, we intend to stimulate a discussion on a more unambiguous classification of treemaps and, furthermore, broaden what is understood by the concept of treemap itself.
A treemap is a visualization that has been specifically designed to facilitate the exploration of tree-structured data and, more general, hierarchically structured data. The family of visualization techniques that use a visual metaphor for parent-child relationships based “on the property of containment” (Johnson, 1993) is commonly referred to as treemaps. However, as the number of variations of treemaps grows, it becomes increasingly important to distinguish clearly between techniques and their specific characteristics. This paper proposes to discern between Space-filling Treemap TS, Containment Treemap TC, Implicit Edge Representation Tree TIE, and Mapped Tree TMT for classification of hierarchy visualization techniques and highlights their respective properties. This taxonomy is created as a hyponymy, i.e., its classes have an is-a relationship to one another: TS TC TIE TMT. With this proposal, we intend to stimulate a discussion on a more unambiguous classification of treemaps and, furthermore, broaden what is understood by the concept of treemap itself.
A tale of shifting relations
(2021)
Understanding the dynamics between the East Asian summer (EASM) and winter monsoon (EAWM) is needed to predict their variability under future global warming scenarios. Here, we investigate the relationship between EASM and EAWM as well as the mechanisms driving their variability during the last 10,000 years by stacking marine and terrestrial (non-speleothem) proxy records from the East Asian realm. This provides a regional and proxy independent signal for both monsoonal systems. The respective signal was subsequently analysed using a linear regression model. We find that the phase relationship between EASM and EAWM is not time-constant and significantly depends on orbital configuration changes. In addition, changes in the Atlantic Meridional Overturning circulation, Arctic sea-ice coverage, El Niño-Southern Oscillation and Sun Spot numbers contributed to millennial scale changes in the EASM and EAWM during the Holocene. We also argue that the bulk signal of monsoonal activity captured by the stacked non-speleothem proxy records supports the previously argued bias of speleothem climatic archives to moisture source changes and/or seasonality.
A tale of shifting relations
(2021)
Understanding the dynamics between the East Asian summer (EASM) and winter monsoon (EAWM) is needed to predict their variability under future global warming scenarios. Here, we investigate the relationship between EASM and EAWM as well as the mechanisms driving their variability during the last 10,000 years by stacking marine and terrestrial (non-speleothem) proxy records from the East Asian realm. This provides a regional and proxy independent signal for both monsoonal systems. The respective signal was subsequently analysed using a linear regression model. We find that the phase relationship between EASM and EAWM is not time-constant and significantly depends on orbital configuration changes. In addition, changes in the Atlantic Meridional Overturning circulation, Arctic sea-ice coverage, El Niño-Southern Oscillation and Sun Spot numbers contributed to millennial scale changes in the EASM and EAWM during the Holocene. We also argue that the bulk signal of monsoonal activity captured by the stacked non-speleothem proxy records supports the previously argued bias of speleothem climatic archives to moisture source changes and/or seasonality.
Large-scale biochemical models are of increasing sizes due to the consideration of interacting organisms and tissues. Model reduction approaches that preserve the flux phenotypes can simplify the analysis and predictions of steady-state metabolic phenotypes. However, existing approaches either restrict functionality of reduced models or do not lead to significant decreases in the number of modelled metabolites. Here, we introduce an approach for model reduction based on the structural property of balancing of complexes that preserves the steady-state fluxes supported by the network and can be efficiently determined at genome scale. Using two large-scale mass-action kinetic models of Escherichia coli, we show that our approach results in a substantial reduction of 99% of metabolites. Applications to genome-scale metabolic models across kingdoms of life result in up to 55% and 85% reduction in the number of metabolites when arbitrary and mass-action kinetics is assumed, respectively. We also show that predictions of the specific growth rate from the reduced models match those based on the original models. Since steady-state flux phenotypes from the original model are preserved in the reduced, the approach paves the way for analysing other metabolic phenotypes in large-scale biochemical networks.
The use of monoclonal antibodies is ubiquitous in science and biomedicine but the generation and validation process of antibodies is nevertheless complicated and time-consuming. To address these issues we developed a novel selective technology based on an artificial cell surface construct by which secreted antibodies were connected to the corresponding hybridoma cell when they possess the desired antigen-specificity. Further the system enables the selection of desired isotypes and the screening for potential cross-reactivities in the same context. For the design of the construct we combined the transmembrane domain of the EGF-receptor with a hemagglutinin epitope and a biotin acceptor peptide and performed a transposon-mediated transfection of myeloma cell lines. The stably transfected myeloma cell line was used for the generation of hybridoma cells and an antigen- and isotype-specific screening method was established. The system has been validated for globular protein antigens as well as for haptens and enables a fast and early stage selection and validation of monoclonal antibodies in one step.
The use of monoclonal antibodies is ubiquitous in science and biomedicine but the generation and validation process of antibodies is nevertheless complicated and time-consuming. To address these issues we developed a novel selective technology based on an artificial cell surface construct by which secreted antibodies were connected to the corresponding hybridoma cell when they possess the desired antigen-specificity. Further the system enables the selection of desired isotypes and the screening for potential cross-reactivities in the same context. For the design of the construct we combined the transmembrane domain of the EGF-receptor with a hemagglutinin epitope and a biotin acceptor peptide and performed a transposon-mediated transfection of myeloma cell lines. The stably transfected myeloma cell line was used for the generation of hybridoma cells and an antigen- and isotype-specific screening method was established. The system has been validated for globular protein antigens as well as for haptens and enables a fast and early stage selection and validation of monoclonal antibodies in one step.
We use the prolonged Greek crisis as a case study to understand how a lasting economic shock affects the innovation strategies of firms in economies with moderate innovation activities. Adopting the 3-stage CDM model, we explore the link between R&D, innovation, and productivity for different size groups of Greek manufacturing firms during the prolonged crisis. At the first stage, we find that the continuation of the crisis is harmful for the R&D engagement of smaller firms while it increased the willingness for R&D activities among the larger ones. At the second stage, among smaller firms the knowledge production remains unaffected by R&D investments, while among larger firms the R&D decision is positively correlated with the probability of producing innovation, albeit the relationship is weakened as the crisis continues. At the third stage, innovation output benefits only larger firms in terms of labor productivity, while the innovation-productivity nexus is insignificant for smaller firms during the lasting crisis.
In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios.
In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios.
The "Lomonosov" space project is lead by Lomonosov Moscow State University in collaboration with the following key partners: Joint Institute for Nuclear Research, Russia, University of California, Los Angeles (USA), University of Pueblo (Mexico), Sungkyunkwan University (Republic of Korea) and with Russian space industry organi-zations to study some of extreme phenomena in space related to astrophysics, astroparticle physics, space physics, and space biology. The primary goals of this experiment are to study:
-Ultra-high energy cosmic rays (UHECR) in the energy range of the Greizen-ZatsepinKuzmin (GZK) cutoff;
-Ultraviolet (UV) transient luminous events in the upper atmosphere;
-Multi-wavelength study of gamma-ray bursts in visible, UV, gamma, and X-rays;
-Energetic trapped and precipitated radiation (electrons and protons) at low-Earth orbit (LEO) in connection with global geomagnetic disturbances;
-Multicomponent radiation doses along the orbit of spacecraft under different geomagnetic conditions and testing of space segments of optical observations of space-debris and other space objects;
-Instrumental vestibular-sensor conflict of zero-gravity phenomena during space flight.
This paper is directed towards the general description of both scientific goals of the project and scientific equipment on board the satellite. The following papers of this issue are devoted to detailed descriptions of scientific instruments.