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The low temperature (95 K) NMR study of 1-Ph-1-t-Bu-silacyclohexane (1) showed the conformational equilibrium to be extremely one-sided toward thePh(ax),t-Bueq conformer. The barrier to interconversion has been measured (4.2-4.6 kcal/mol) and the conformational equilibrium [Delta nu = 1990.64 ppm (Si-29), 618.9 ppm (C-13), 1-Ph-ax:1-Pheq = (95.6-96.6%):(3.4-4.4%), K = 25 +/- 3, Delta G degrees = -RT ln K = 0.58-0.63 kcal/mol] analyzed. The assignment and quantification of the NMR signals is supported by MP2 and DFT calculations.
To predict how widely distributed species will perform under future climate change, it is crucial to understand and reveal their underlying phylogenetics. However, detailed information about plant adaptation and its genetic basis and history remains scarce and especially widely distributed species receive little attention despite their putatively high adaptability.
To examine the adaptation potential of a widely distributed species, we sampled the model plant Silene vulgaris across Europe. In a greenhouse experiment, we exposed the offspring of these populations to a climate change scenario for central Europe and revealed the population structure through whole-genome sequencing. Plants were grown under two temperatures (18°C and 21°C) and three precipitation regimes (65, 75, and 90 mm) to measure their response in biomass and fecundity-related traits. To reveal the population genetic structure, ddRAD sequencing was employed for a whole-genome approach. We found three major genetic clusters in S. vulgaris from Europe: one cluster comprising Southern European populations, one cluster of Western European populations, and another cluster containing central European populations. Population genetic diversity decreased with increasing latitude, and a Mantel test revealed significant correlations between FST and geographic distances as well as between genetic and environmental distances. Our trait analysis showed that the genetic clusters significantly differed in biomass-related traits and in the days to flowering. However, half of the traits showed parallel response patterns to the experimental climate change scenario. Due to the differentiated but parallel response patterns, we assume that phenotypic plasticity plays an important role for the adaptation of the widely distributed species S. vulgaris and its intraspecific genetic lineages.
Recent trends in ubiquitous computing have led to a proliferation of studies that focus on human activity recognition (HAR) utilizing inertial sensor data that consist of acceleration, orientation and angular velocity. However, the performances of such approaches are limited by the amount of annotated training data, especially in fields where annotating data is highly time-consuming and requires specialized professionals, such as in healthcare. In image classification, this limitation has been mitigated by powerful oversampling techniques such as data augmentation. Using this technique, this work evaluates to what extent transforming inertial sensor data into movement trajectories and into 2D heatmap images can be advantageous for HAR when data are scarce. A convolutional long short-term memory (ConvLSTM) network that incorporates spatiotemporal correlations was used to classify the heatmap images. Evaluation was carried out on Deep Inertial Poser (DIP), a known dataset composed of inertial sensor data. The results obtained suggest that for datasets with large numbers of subjects, using state-of-the-art methods remains the best alternative. However, a performance advantage was achieved for small datasets, which is usually the case in healthcare. Moreover, movement trajectories provide a visual representation of human activities, which can help researchers to better interpret and analyze motion patterns.
The scapula plays a significant role in efficient shoulder movement. Thus, alterations from typical scapular motion during upper limb movements are thought to be associated with shoulder pathologies. However, a clear understanding of the relationship is not yet obtained.. Scapular alterations may only represent physiological variability as their occurrence can appear equally as frequent in individuals with and without shoulder disorders. Evaluation of scapular motion during increased load might be a beneficial approach to detect clinically relevant alterations. However, functional motion adaptations in response to maximum effort upper extremity loading has not been established yet. Therefore, the overall purpose of this research project was to give further insight in physiological adaptations of scapular kinematics and their underlying scapular muscle activity in response to high demanding shoulder movements in healthy asymptomatic individuals. Prior to the investigation of the effect of various load situation, the reproducibility of scapular kinematics and scapular muscle activity were evaluated under maximum effort arm movements. Healthy asymptomatic adults performed unloaded and maximal loaded concentric and eccentric isokinetic shoulder flexion and extension movements in the scapular plane while scapular kinematics and scapular muscle activity were simultaneously assessed. A 3D motion capture system (infra-red cameras & reflective markers) was utilized to track scapular and humerus motion in relation to the thorax. 3D scapular position angles were given for arm raising and lowering between humerus positions of 20° and 120° flexion. To further characterize the scapular pattern, the scapular motion extent and scapulohumeral rhythm (ratio of scapular and humerus motion extent) were determined. Muscle activity of the upper and lower trapezius and the serratus anterior were assessed with surface electromyography. Amplitudes were calculated for the whole ROM and four equidistant movement phases. Reliability was characterized by overall moderate to good reproducibility across the load conditions. Irrespective of applied load, scapular kinematics followed a motion pattern of continuous upward rotation, posterior tilt and external rotation during arm elevation and a continuous downward rotation, anterior tilt and internal rotation during arm lowering. However, kinematics were altered between maximal loaded and unloaded conditions showing increased upward rotation, reduced posterior tilt and external rotation. Further, the scapulohumeral rhythm was decreased and scapular motion extent increased under maximal loaded movements. Muscle activity during maximum effort were of greater magnitude and differed in their pattern in comparison to the continuous increase and decrease of activity during unloaded shoulder flexion and extension. Relationships between scapular kinematics and their underlying scapular muscle activity could only be identified for a few isolated combinations, whereas the majority showed no associations. Scapular kinematics and scapular muscle activity pattern alter according to the applied load. Alterations between the load conditions comply in magnitude and partially in direction with differences seen between symptomatic and asymptomatic individuals. Even though long-term effects of identified adaptations in response to maximum load are so far unclear, deviations from typical scapular motion or muscle activation should not per se be seen as indicators of shoulder impairment. However, evaluation of alterations in scapular motion and activation in response to maximum effort may have the potential to identify individuals that are unable to cope with increased upper limb demands. Findings further challenge the understanding of scapular motion and stabilization by the trapezius and serratus anterior muscles, as clear relationships between the underlying scapular muscle activity and scapular kinematics were neither observed during unloaded nor maximal loaded shoulder movements.
TRIPOD
(2021)
Inertial measurement units (IMUs) enable easy to operate and low-cost data recording for gait analysis. When combined with treadmill walking, a large number of steps can be collected in a controlled environment without the need of a dedicated gait analysis laboratory. In order to evaluate existing and novel IMU-based gait analysis algorithms for treadmill walking, a reference dataset that includes IMU data as well as reliable ground truth measurements for multiple participants and walking speeds is needed. This article provides a reference dataset consisting of 15 healthy young adults who walked on a treadmill at three different speeds. Data were acquired using seven IMUs placed on the lower body, two different reference systems (Zebris FDMT-HQ and OptoGait), and two RGB cameras. Additionally, in order to validate an existing IMU-based gait analysis algorithm using the dataset, an adaptable modular data analysis pipeline was built. Our results show agreement between the pressure-sensitive Zebris and the photoelectric OptoGait system (r = 0.99), demonstrating the quality of our reference data. As a use case, the performance of an algorithm originally designed for overground walking was tested on treadmill data using the data pipeline. The accuracy of stride length and stride time estimations was comparable to that reported in other studies with overground data, indicating that the algorithm is equally applicable to treadmill data. The Python source code of the data pipeline is publicly available, and the dataset will be provided by the authors upon request, enabling future evaluations of IMU gait analysis algorithms without the need of recording new data.
Inertial measurement units (IMUs) enable easy to operate and low-cost data recording for gait analysis. When combined with treadmill walking, a large number of steps can be collected in a controlled environment without the need of a dedicated gait analysis laboratory. In order to evaluate existing and novel IMU-based gait analysis algorithms for treadmill walking, a reference dataset that includes IMU data as well as reliable ground truth measurements for multiple participants and walking speeds is needed. This article provides a reference dataset consisting of 15 healthy young adults who walked on a treadmill at three different speeds. Data were acquired using seven IMUs placed on the lower body, two different reference systems (Zebris FDMT-HQ and OptoGait), and two RGB cameras. Additionally, in order to validate an existing IMU-based gait analysis algorithm using the dataset, an adaptable modular data analysis pipeline was built. Our results show agreement between the pressure-sensitive Zebris and the photoelectric OptoGait system (r = 0.99), demonstrating the quality of our reference data. As a use case, the performance of an algorithm originally designed for overground walking was tested on treadmill data using the data pipeline. The accuracy of stride length and stride time estimations was comparable to that reported in other studies with overground data, indicating that the algorithm is equally applicable to treadmill data. The Python source code of the data pipeline is publicly available, and the dataset will be provided by the authors upon request, enabling future evaluations of IMU gait analysis algorithms without the need of recording new data.
Elucidating the molecular basis of enhanced growth in the Arabidopsis thaliana accession Bur-0
(2021)
The life cycle of flowering plants is a dynamic process that involves successful passing through several developmental phases and tremendous progress has been made to reveal cellular and molecular regulatory mechanisms underlying these phases, morphogenesis, and growth. Although several key regulators of plant growth or developmental phase transitions have been identified in Arabidopsis, little is known about factors that become active during embryogenesis, seed development and also during further postembryonic growth. Much less is known about accession-specific factors that determine plant architecture and organ size. Bur-0 has been reported as a natural Arabidopsis thaliana accession with exceptionally big seeds and a large rosette; its phenotype makes it an interesting candidate to study growth and developmental aspects in plants, however, the molecular basis underlying this big phenotype remains to be elucidated. Thus, the general aim of this PhD project was to investigate and unravel the molecular mechanisms underlying the big phenotype in Bur-0.
Several natural Arabidopsis accessions and late flowering mutant lines were analysed in this study, including Bur-0. Phenotypes were characterized by determining rosette size, seed size, flowering time, SAM size and growth in different photoperiods, during embryonic and postembryonic development. Our results demonstrate that Bur-0 stands out as an interesting accession with simultaneously larger rosettes, larger SAM, later flowering phenotype and larger seeds, but also larger embryos. Interestingly, inter-accession crosses (F1) resulted in bigger seeds than the parental self-crossed accessions, particularly when Bur-0 was used as the female parental genotype, suggesting parental effects on seed size that might be maternally controlled. Furthermore, developmental stage-based comparisons revealed that the large embryo size of Bur-0 is achieved during late embryogenesis and the large rosette size is achieved during late postembryonic growth. Interestingly, developmental phase progression analyses revealed that from germination onwards, the length of developmental phases during postembryonic growth is delayed in Bur-0, suggesting that in general, the mechanisms that regulate developmental phase progression are shared across developmental phases.
On the other hand, a detailed physiological characterization in different tissues at different developmental stages revealed accession-specific physiological and metabolic traits that underlie accession-specific phenotypes and in particular, more carbon resources during embryonic and postembryonic development were found in Bur-0, suggesting an important role of carbohydrates in determination of the bigger Bur-0 phenotype. Additionally, differences in the cellular organization, nuclei DNA content, as well as ploidy level were analyzed in different tissues/cell types and we found that the large organ size in Bur-0 can be mainly attributed to its larger cells and also to higher cell proliferation in the SAM, but not to a different ploidy level.
Furthermore, RNA-seq analysis of embryos at torpedo and mature stage, as well as SAMs at vegetative and floral transition stage from Bur-0 and Col-0 was conducted to identify accession-specific genetic determinants of plant phenotypes, shared across tissues and developmental stages during embryonic and postembryonic growth. Potential candidate genes were identified and further validation of transcriptome data by expression analyses of candidate genes as well as known key regulators of organ size and growth during embryonic and postembryonic development confirmed that the high confidence transcriptome datasets generated in this study are reliable for elucidation of molecular mechanisms regulating plant growth and accession-specific phenotypes in Arabidopsis.
Taken together, this PhD project contributes to the plant development research field providing a detailed analysis of mechanisms underlying plant growth and development at different levels of biological organization, focusing on Arabidopsis accessions with remarkable phenotypical differences. For this, the natural accession Bur-0 was an ideal outlier candidate and different mechanisms at organ and tissue level, cell level, metabolism, transcript and gene expression level were identified, providing a better understanding of different factors involved in plant growth regulation and mechanisms underlying different growth patterns in nature.
Patterning along the apical-basal (A-B) axis is a crucial step during the early stages of plant embryogenesis and leads to the establishment of two poles of which each will develop their own stem cell niches. The activity of these meristems is responsible for post-embryonic growth, with the shoot apical meristem (SAM) generating the above-ground organs and the root apical meristem (RAM) producing the subterranean structures of the plant. While several transcriptional regulators governing A-B patterning have been identified, precisely how their regulatory function is orchestrated remains elusive. This study focuses on transcriptional co-regulators LEUNIG (LUG) and closely related LEUNIG_HOMOLOG (LUH) and their role in the formation of A-B patterning during embryogenesis as well as their post-embryonic maintenance. A link between the LUG regulatory complex and SAM formation and maintenance comes from the observation that lug mutants heterozygous for the luh allele (lug luh+/-) often have enlarged SAMs resulting from misregulated cell divisions. A more severe phenotype is observed in lug luh double mutants which are embryonically lethal. In this study, a detailed characterisation of lug luh embryo phenotype reveals that these mutants display aberrant cell divisions along the A-B axis, which correlates with defects in auxin distribution, complete loss of apical identity, and altered expression of transcription factors determining basal fate. Like other co-regulators, LUG and LUH lack intrinsic DNA-binding domains and instead must interact with DNA-binding cofactors to ensure recruitment to regulatory elements of target genes. This either involves direct contact between the co-regulators and transcription factors (TFs) or the formation of higher-order complexes with adaptor proteins such as SEUSS (SEU) or related SEUSS-LIKEs (SLKs), which facilitate binding to specific TFs. Results presented in this study provide insight into the molecular framework for the LUG regulatory complex activity during embryogenesis. Both yeast and in planta assays showed that LUG/LUH and SEU/SLKs physically associate with a variety of WUSCHEL-RELATED HOMEOBOX (WOX) TFs including members of the WOX2-module. Furthermore, genetic interactions between members of the WOX2-module and the LUG regulatory complex, support their mutual action during embryogenesis. Based on the reduced activity of HOMEODOMAIN LEUCINE-ZIPPER CLASS III (HD-ZIPIII) promoters in lug luh embryos, a model is proposed in which the LUG regulatory complex functions together with WOX2-module to promote apical identity and subsequent SAM initiation through regulation of the HD-ZIPIIIs. The activity of the LUG complex in promoting basal embryo identity through positive regulation of microRNA165/166 suggests that this complex also has functions that are independent of the WOX2-module. Preliminary work reported in this study further uncovered the role of the LUG regulatory complex in post-embryonic development. While the fasciated inflorescence meristems of lug luh+/- plants displayed defects in auxin transport and altered activity of stem cell markers, embryonically rescued lug luh mutants formed flat and differentiated SAMs. In addition, rescued lug luh mutants exhibited severely disorganised RAM and defects in quiescent center (QC) specification, supporting the involvement of the LUG complex in post-embryonic RAM maintenance.
Detection of the QRS complex is a long-standing topic in the context of electrocardiography and many algorithms build upon the knowledge of the QRS positions. Although the first solutions to this problem were proposed in the 1970s and 1980s, there is still potential for improvements. Advancements in neural network technology made in recent years also lead to the emergence of enhanced QRS detectors based on artificial neural networks. In this work, we propose a method for assessing the certainty that is in each of the detected QRS complexes, i.e. how confident the QRS detector is that there is, in fact, a QRS complex in the position where it was detected. We further show how this metric can be utilised to distinguish correctly detected QRS complexes from false detections.
As sessile organisms, plants have evolved sophisticated ways to constantly gauge and adapt to changing environmental conditions including extremes that may be harmful to their growth and development and are thus perceived as stress. In nature, stressful events are often chronic or recurring and thus an initial stress may prime a plant to respond more efficiently to a subsequent stress event. An epigenetic basis of such stress memory was long postulated and in recent years it has been shown that this is indeed the case. High temperature stress has proven an excellent system to unpick the molecular basis of somatic stress memory, which includes histone modifications and nucleosome occupancy. This review discusses recent findings and pinpoints open questions in the field.
Any physical system can be described on the level of interacting particles, thus it is of fundamental importance to improve the scientific understanding of interacting many-body systems. This thesis experimentally addresses specific quasi-particle interactions, namely interactions be- tween electrons and between electrons and phonons. It describes the consequential effects of those processes on the electronic structure and the core-hole relaxation pathways in 3d metals. Despite the great amount of experimental and theoretical studies of these interactions and their impact on the behavior of solid-state matter, there are still open questions concerning the cor- responding physical, chemical and mechanical properties of solid-state matter. Especially, the study of 3d metals and their compounds is a great experimental challenge, since those exhibit a variety of spectral features originating from many-body effects such as multiplet splitting, shake up/off satellites, vibrationally excited states or more complex effects like superconductivity and ultrafast demagnetization. In X-ray spectroscopy, these effects often produce overlapping fea- tures, complicating the analysis and limiting the understanding. In this thesis, to overcome the limitations set by conventional X-ray spectroscopy, two different experimental approaches were successfully refined, namely Auger electron photoelectron coincidence spectroscopy (APECS) and temperature-dependent X-ray emission spectroscopy (tXES), which enabled the separation of different core-hole relaxation pathways and the isolation of the impact of specific many-body interactions in the experimental spectra. APECS was utilized at the new Coincidence electron spectroscopy for chemical analysis (Co- ESCA) station at BESSY II to study the core-hole decay and electron-correlation effects in single- crystal Ni, Cu and Co. The observation of photoelectrons in coincidence with Auger electrons allows for the separation of the initial and final state effects in the Auger electron spectra. The results show that a Cu LV V Auger spectrum can be represented by broadened atomic multiplets confirming the localized nature of the intermediate core-hole states. In contrast, the Co LV V Auger spectrum is band-like and can be represented by the self-convolution of the valence band. Ni behaves mixed, localized and itinerant. Thus, the Ni Auger spectrum can only be represented by a mixture of atomic multiplet peaks and the self-convoluted valence band. In the case of Ni, the LV V Auger electrons in coincidence with the 6 eV satellite photoelectrons were also stud- ied. Utilizing the core-hole clock method, the lifetime of the localized double-hole intermediate 2 p53d9 states of 1.8 fs could be determined. However, a fraction of these states delocalizes before the Auger decay contributing to the main peak. A similar delocalization was observed for the double-hole states produced by the L2L3M4,5 Coster-Kronig process. Additionally, the influence of surface oxidation on the Ni(111) 3p levels was studied with APECS. The Ni 3p PES spectrum is broad and featureless, due to overlapping many-body effects and gives little chance for exact analysis using conventional photoelectron spectroscopy. Utilizing APECS or precisely the final state selectivity of the method, the spectral width of the 3p levels could be narrowed and their positions and the spin-orbit splitting were determined. Moreover, due to the surface sensitivity of the method, the chemically shifted 3p photoelectron peaks originating from the oxidized surface and the bulk Ni were disentangled. For the study of the atomic electron-phonon spin-flip scattering in 3d metals as a spin-relaxation channel, the tXES method at the SolidFlexRIXS station was developed. The atomic spin-flip scat- tering was studied in single-crystal Ni, Cu, Co and in FeNi alloys, which show considerable dif- ferences in their behavior. The scattering rate in Ni increases with temperature, whereas the rate in Cu and Co remains constant within the measured temperature range up to 1000 K. In FeNi alloys, our results reveal that the spin-flip scattering is restricted by sublattice exchange energies J. The electron-phonon scattering driven spin-flips only appear in the case where the thermal energy ex- ceeds the exchange energy kT > J. This thresholding is an important microscopic process for the description of the sublattice dynamics in alloys, but as shown also relevant for elemental magnetic systems. Overall, the results strongly indicate that the spin-flip probability is correlated with the exchange energy, which might become an important parameter in the ultrafast demagnetization debate. Taken together, the applied experimental approaches allowed to study complex many-body effects in 3d metals. The results show that utilizing APECS enabled the distinction and clear assignment of otherwise overlapping features in AES or PES spectra of Ni, Cu, Co and NiO. This is of fundamental importance for the basic understanding of photoionization and core-hole decay processes but also for the chemical analysis in applied science. The measurement of the atomic electron-phonon spin-flip scattering rate utilizing tXES shows that the electron-phonon spin-flip scattering is a relevant atomic process for the macroscopic demagnetization process. Additionally, a temperature-dependent thresholding mechanism was discovered, which introduces an important dynamic factor into the electron-phonon spin-flip model.
People perceive sentences more favourably after hearing or reading them many times. A prominent approach in linguistic theory argues that these types of exposure effects (satiation effects) show direct evidence of a generative approach to linguistic knowledge: only some sentences improve under repeated exposure, and which sentences do improve can be predicted by a model of linguistic competence that yields natural syntactic classes. However, replications of the original findings have been inconsistent, and it remains unclear whether satiation effects can be reliably induced in an experimental setting at all. Here we report four findings regarding satiation effects in wh-questions across German and English. First, the effects pertain to zone of well-formedness rather than syntactic class: all intermediate ratings, including calibrated fillers, increase at the beginning of the experimental session regardless of syntactic construction. Second, though there is satiation, ratings asymptote below maximum acceptability. Third, these effects are consistent across judgments of superiority effects in English and German. Fourth, wh-questions appear to show similar profiles in English and German, despite these languages being traditionally considered to differ strongly in whether they show effects on movement: violations of the superiority condition can be modulated to a similar degree in both languages by manipulating subject-object initiality and animacy congruency of the wh-phrase. We improve on classic satiation methods by distinguishing between two crucial tests, namely whether exposure selectively targets certain grammatical constructions or whether there is a general repeated exposure effect. We conclude that exposure effects can be reliably induced in rating experiments but exposure does not appear to selectively target certain grammatical constructions. Instead, they appear to be a phenomenon of intermediate gradient judgments.
Non-fullerene acceptors (NFAs) are far more emissive than their fullerene-based counterparts. Here, we study the spectral properties of photocurrent generation and recombination of the blend of the donor polymer PM6 with the NFA Y6. We find that the radiative recombination of free charges is almost entirely due to the re-occupation and decay of Y6 singlet excitons, but that this pathway contributes less than 1% to the total recombination. As such, the open-circuit voltage of the PM6:Y6 blend is determined by the energetics and kinetics of the charge-transfer (CT) state. Moreover, we find that no information on the energetics of the CT state manifold can be gained from the low-energy tail of the photovoltaic external quantum efficiency spectrum, which is dominated by the excitation spectrum of the Y6 exciton. We, finally, estimate the charge-separated state to lie only 120 meV below the Y6 singlet exciton energy, meaning that this blend indeed represents a high-efficiency system with a low energetic offset.
Ground-penetrating radar (GPR) is a standard geophysical technique used to image near-surface structures in sedimentary environments. In such environments, GPR data acquisition and processing are increasingly following 3D strategies. However, the processed GPR data volumes are typically still interpreted using selected 2D slices and manual concepts such as GPR facies analyses. In seismic volume interpretation, the application of (semi-)automated and reproducible approaches such as 3D attribute analyses as well as the production of attribute-based facies models are common practices today. In contrast, the field of 3D GPR attribute analyses and corresponding facies models is largely untapped. We have developed and applied a workflow to produce 3D attribute-based GPR facies models comprising the dominant sedimentary reflection patterns in a GPR volume, which images complex sandy structures on the dune island of Spiekeroog (Northern Germany). After presenting our field site and details regarding our data acquisition and processing, we calculate and filter 3D texture attributes to generate a database comprising the dominant texture features of our GPR data. Then, we perform a dimensionality reduction of this database to obtain meta texture attributes, which we analyze and integrate using composite imaging and (also considering additional geometric information) fuzzy c-means cluster analysis resulting in a classified GPR facies model. Considering our facies model and a corresponding GPR facies chart, we interpret our GPR data set in terms of near-surface sedimentary units, the corresponding depositional environments, and the recent formation history at our field site. Thus, we demonstrate the potential of our workflow, which represents a novel and clear strategy to perform a more objective and consistent interpretation of 3D GPR data collected across different sedimentary environments.
PC2P
(2021)
Motivation:
Prediction of protein complexes from protein-protein interaction (PPI) networks is an important problem in systems biology, as they control different cellular functions. The existing solutions employ algorithms for network community detection that identify dense subgraphs in PPI networks. However, gold standards in yeast and human indicate that protein complexes can also induce sparse subgraphs, introducing further challenges in protein complex prediction.
Results:
To address this issue, we formalize protein complexes as biclique spanned subgraphs, which include both sparse and dense subgraphs. We then cast the problem of protein complex prediction as a network partitioning into biclique spanned subgraphs with removal of minimum number of edges, called coherent partition. Since finding a coherent partition is a computationally intractable problem, we devise a parameter-free greedy approximation algorithm, termed Protein Complexes from Coherent Partition (PC2P), based on key properties of biclique spanned subgraphs. Through comparison with nine contenders, we demonstrate that PC2P: (i) successfully identifies modular structure in networks, as a prerequisite for protein complex prediction, (ii) outperforms the existing solutions with respect to a composite score of five performance measures on 75% and 100% of the analyzed PPI networks and gold standards in yeast and human, respectively, and (iii,iv) does not compromise GO semantic similarity and enrichment score of the predicted protein complexes. Therefore, our study demonstrates that clustering of networks in terms of biclique spanned subgraphs is a promising framework for detection of complexes in PPI networks.
Previous studies (Hyona, Yan, & Vainio, 2018; Yan et al., 2014) have demonstrated that in morphologically rich languages a word's morphological status is processed parafoveally to be used in modulating saccadic programming in reading. In the present parafoveal preview study conducted in Finnish, we examined the exact nature of this effect by comparing reading of morphologically complex words (a stem + two suffixes) to that of monomorphemic words. In the preview-change condition, the final 3-4 letters were replaced with other letters making the target word a pseudoword; for suffixed words, the word stem remained intact but the suffix information was unavailable; for monomorphemic words, only part of the stem was parafoveally available. Three alternative predictions were put forth. According to the first alternative, the morphological effect in initial fixation location is due to parafoveally perceiving the suffix as a highly frequent letter cluster and then adjusting the saccade program to land closer to the word beginning for suffixed than monomorphemic words. The second alternative, the processing difficulty hypothesis, assumes a morphological complexity effect: suffixed words are more complex than monomorphemic words. Therefore, the attentional window is narrower and the saccade is shorter. The third alternative posits that the effect reflects parafoveal access to the word's stem. The results for the initial fixation location and fixation durations were consistent with the parafoveal stem-access view.
Stunting
(2021)
One of the main challenges of education in modern societies is to effectively address the variability of students in academic learning settings. Students vary in terms of their individual learning preconditions, such as achievement and preknowledge, but also motivation and emotion. Teachers, in turn, have limited resources to provide each learner with individually tailored instruction. This research overview reviews research on artificially intelligent teaching assistants and their role in providing adaptive learning opportunities in relation to learners’ heterogeneous individual learning preconditions in the field of motivation and emotion.
Epistemic logic programs constitute an extension of the stable model semantics to deal with new constructs called subjective literals. Informally speaking, a subjective literal allows checking whether some objective literal is true in all or some stable models. As it can be imagined, the associated semantics has proved to be non-trivial, since the truth of subjective literals may interfere with the set of stable models it is supposed to query. As a consequence, no clear agreement has been reached and different semantic proposals have been made in the literature. Unfortunately, comparison among these proposals has been limited to a study of their effect on individual examples, rather than identifying general properties to be checked. In this paper, we propose an extension of the well-known splitting property for logic programs to the epistemic case. We formally define when an arbitrary semantics satisfies the epistemic splitting property and examine some of the consequences that can be derived from that, including its relation to conformant planning and to epistemic constraints. Interestingly, we prove (through counterexamples) that most of the existing approaches fail to fulfill the epistemic splitting property, except the original semantics proposed by Gelfond 1991 and a recent proposal by the authors, called Founded Autoepistemic Equilibrium Logic.
Tula orthohantavirus (TULV) is a rodent-borne hantavirus with broad geographical distribution in Europe. Its major reservoir is the common vole (Microtus arvalis), but TULV has also been detected in closely related vole species. Given the large distributional range and high amplitude population dynamics of common voles, this host-pathogen complex presents an ideal system to study the complex mechanisms of pathogen transmission in a wild rodent reservoir. We investigated the dynamics of TULV prevalence and the subsequent potential effects on the molecular evolution of TULV in common voles of the Central evolutionary lineage. Rodents were trapped for three years in four regions of Germany and samples were analyzed for the presence of TULV-reactive antibodies and TULV RNA with subsequent sequence determination. The results show that individual (sex) and population-level factors (abundance) of hosts were significant predictors of local TULV dynamics. At the large geographic scale, different phylogenetic TULV clades and an overall isolation-by-distance pattern in virus sequences were detected, while at the small scale (<4 km) this depended on the study area. In combination with an overall delayed density dependence, our results highlight that frequent, localized bottleneck events for the common vole and TULV do occur and can be offset by local recolonization dynamics.
Comb-like geometric constraints leading to emergence of the time-fractional Schrödinger equation
(2021)
This paper presents an overview over several examples, where the comb-like geometric constraints lead to emergence of the time-fractional Schrodinger equation. Motion of a quantum object on a comb structure is modeled by a suitable modification of the kinetic energy operator, obtained by insertion of the Dirac delta function in the Laplacian. First, we consider motion of a free particle on two- and three-dimensional comb structures, and then we extend the study to the interacting cases. A general form of a nonlocal term, which describes the interactions of the particle with the medium, is included in the Hamiltonian, and later on, the cases of constant and Dirac delta potentials are analyzed. At the end, we discuss the case of non-integer dimensions, considering separately the case of fractal dimension between one and two, and the case of fractal dimension between two and three. All these examples show that even though we are starting with the standard time-dependent Schrodinger equation on a comb, the time-fractional equation for the Green's functions appears, due to these specific geometric constraints.
On the basis of certain semantic intuitions, Barros (2012) argues that ellipsis does not require structural isomorphism between elided structure and its antecedent. We tackle this claim. Semantic intuitions cannot be a pointer to the analysis of silent structure. We provide empirical evidence that raises the question of to what extent semantic intuitions about plausible articulable syntax must inform one's analysis of silent structure. We conclude that the answer to this question must be crosslinguistically informed. We conjecture that ellipsis introduces ellipsis-specific interpretive mechanisms, so that intuitions about "how the unelided structure would be interpreted" are not empirically relevant.
Large earthquakes are usually modeled with simple planar fault surfaces or a combination of several planar fault segments. However, in general, earthquakes occur on faults that are non-planar and exhibit significant geometrical variations in both the along-strike and down-dip directions at all spatial scales. Mapping of surface fault ruptures and high-resolution geodetic observations are increasingly revealing complex fault geometries near the surface and accurate locations of aftershocks often indicate geometrical complexities at depth. With better geodetic data and observations of fault ruptures, more details of complex fault geometries can be estimated resulting in more realistic fault models of large earthquakes. To address this topic, we here parametrize non-planar fault geometries with a set of polynomial parameters that allow for both along-strike and down-dip variations in the fault geometry. Our methodology uses Bayesian inference to estimate the non-planar fault parameters from geodetic data, yielding an ensemble of plausible models that characterize the uncertainties of the non-planar fault geometry and the fault slip. The method is demonstrated using synthetic tests considering slip spatially distributed on a single continuous finite non-planar fault surface with varying dip and strike angles both in the down-dip and along-strike directions. The results show that fault-slip estimations can be biased when a simple planar fault geometry is assumed in presence of significant non-planar geometrical variations. Our method can help to model earthquake fault sources in a more realistic way and may be extended to include multiple non-planar fault segments or other geometrical fault complexities.
Background
Depression is one of the key factors contributing to difficulties in one’s ability to work, and serves as one of the major reasons why employees apply for psychotherapy and receive insurance subsidization of treatments. Hence, an increasing and growing number of studies rely on workability assessment scales as their primary outcome measure. The Work and Social Assessment Scale (WSAS) has been documented as one of the most psychometrically reliable and valid tools especially developed to assess workability and social functioning in patients with mental health problems. Yet, the application of the WSAS in Germany has been limited due to the paucity of a valid questionnaire in the German language. The objective of the present study was to translate the WSAS, as a brief and easy administrable tool into German and test its psychometric properties in a sample of adults with depression.
Methods
Two hundred seventy-seven patients (M = 48.3 years, SD = 11.1) with mild to moderately severe depression were recruited. A multistep translation from English into the German language was performed and the factorial validity, criterion validity, convergent validity, discriminant validity, internal consistency, and floor and ceiling effects were examined.
Results
The confirmatory factor analysis results confirmed the one-factor structure of the WSAS. Significant correlations with the WHODAS 2–0 questionnaire, a measure of functionality, demonstrated good convergent validity. Significant correlations with depression and quality of life demonstrated good criterion validity. The WSAS also demonstrated strong internal consistency (α = .89), and the absence of floor and ceiling effects indicated good sensitivity of the instrument.
Conclusions
The results of the present study demonstrated that the German version of the WSAS has good psychometric properties comparable to other international versions of this scale. The findings recommend a global assessment of psychosocial functioning with the sum score of the WSAS.
Exercise is known for its beneficial effects on preventing cardiometabolic diseases (CMDs) in the general population. People living with the human immunodeficiency virus (PLWH) are prone to sedentarism, thus raising their already elevated risk of developing CMDs in comparison to individuals without HIV. The aim of this cross-sectional study was to determine if exercise is associated with reduced risk of self-reported CMDs in a German HIV-positive sample (n = 446). Participants completed a self-report survey to assess exercise levels, date of HIV diagnosis, CD4 cell count, antiretroviral therapy, and CMDs. Participants were classified into exercising or sedentary conditions. Generalized linear models with Poisson regression were conducted to assess the prevalence ratio (PR) of PLWH reporting a CMD. Exercising PLWH were less likely to report a heart arrhythmia for every increase in exercise duration (PR: 0.20: 95% CI: 0.10–0.62, p < 0.01) and diabetes mellitus for every increase in exercise session per week (PR: 0.40: 95% CI: 0.10–1, p < 0.01). Exercise frequency and duration are associated with a decreased risk of reporting arrhythmia and diabetes mellitus in PLWH. Further studies are needed to elucidate the mechanisms underlying exercise as a protective factor for CMDs in PLWH.
Since the beginning of the recent global refugee crisis, researchers have been tackling many of its associated aspects, investigating how we can help to alleviate this crisis, in particular, using ICTs capabilities. In our research, we investigated the use of ICT solutions by refugees to foster the social inclusion process in the host community. To tackle this topic, we conducted thirteen interviews with Syrian refugees in Germany. Our findings reveal different ICT usages by refugees and how these contribute to feeling empowered. Moreover, we show the sources of empowerment for refugees that are gained by ICT use. Finally, we identified the two types of social inclusion benefits that were derived from empowerment sources. Our results provide practical implications to different stakeholders and decision-makers on how ICT usage can empower refugees, which can foster the social inclusion of refugees, and what should be considered to support them in their integration effort.
We present a reconstruction of the dynamics of the radiation belts from solar cycles 17 to 24 which allows us to study how radiation belt activity has varied between the different solar cycles. The radiation belt simulations are produced using the Versatile Electron Radiation Belt (VERB)-3D code. The VERB-3D code simulations incorporate radial, energy, and pitch angle diffusion to reproduce the radiation belts. Our simulations use the historical measurements of Kp (available since solar cycle 17, i.e., 1933) to model the evolution radiation belt dynamics between L* = 1-6.6. A nonlinear auto regressive network with exogenous inputs (NARX) neural network was trained off GOES 15 measurements (January 2011-March 2014) and used to supply the upper boundary condition (L* = 6.6) over the course of solar cycles 17-24 (i.e., 1933-2017). Comparison of the model with long term observations of the Van Allen Probes and CRRES demonstrates that our model, driven by the NARX boundary, can reconstruct the general evolution of the radiation belt fluxes. Solar cycle 24 (January 2008-2017) has been the least active of the considered solar cycles which resulted in unusually low electron fluxes. Our results show that solar cycle 24 should not be used as a representative solar cycle for developing long term environment models. The developed reconstruction of fluxes can be used to develop or improve empirical models of the radiation belts.
Background
The metabolic syndrome (MetS) is a risk cluster for a number of secondary diseases. The implementation of prevention programs requires early detection of individuals at risk. However, access to health care providers is limited in structurally weak regions. Brandenburg, a rural federal state in Germany, has an especially high MetS prevalence and disease burden. This study aims to validate and test the feasibility of a setup for mobile diagnostics of MetS and its secondary diseases, to evaluate the MetS prevalence and its association with moderating factors in Brandenburg and to identify new ways of early prevention, while establishing a “Mobile Brandenburg Cohort” to reveal new causes and risk factors for MetS.
Methods
In a pilot study, setups for mobile diagnostics of MetS and secondary diseases will be developed and validated. A van will be equipped as an examination room using point-of-care blood analyzers and by mobilizing standard methods. In study part A, these mobile diagnostic units will be placed at different locations in Brandenburg to locally recruit 5000 participants aged 40-70 years. They will be examined for MetS and advice on nutrition and physical activity will be provided. Questionnaires will be used to evaluate sociodemographics, stress perception, and physical activity. In study part B, participants with MetS, but without known secondary diseases, will receive a detailed mobile medical examination, including MetS diagnostics, medical history, clinical examinations, and instrumental diagnostics for internal, cardiovascular, musculoskeletal, and cognitive disorders. Participants will receive advice on nutrition and an exercise program will be demonstrated on site. People unable to participate in these mobile examinations will be interviewed by telephone. If necessary, participants will be referred to general practitioners for further diagnosis.
Discussion
The mobile diagnostics approach enables early detection of individuals at risk, and their targeted referral to local health care providers. Evaluation of the MetS prevalence, its relation to risk-increasing factors, and the “Mobile Brandenburg Cohort” create a unique database for further longitudinal studies on the implementation of home-based prevention programs to reduce mortality, especially in rural regions.
Trial registration
German Clinical Trials Register, DRKS00022764; registered 07 October 2020—retrospectively registered.
The Earth's electron radiation belts exhibit a two-zone structure, with the outer belt being highly dynamic due to the constant competition between a number of physical processes, including acceleration, loss, and transport. The flux of electrons in the outer belt can vary over several orders of magnitude, reaching levels that may disrupt satellite operations. Therefore, understanding the mechanisms that drive these variations is of high interest to the scientific community.
In particular, the important role played by loss mechanisms in controlling relativistic electron dynamics has become increasingly clear in recent years. It is now widely accepted that radiation belt electrons can be lost either by precipitation into the atmosphere or by transport across the magnetopause, called magnetopause shadowing. Precipitation of electrons occurs due to pitch-angle scattering by resonant interaction with various types of waves, including whistler mode chorus, plasmaspheric hiss, and electromagnetic ion cyclotron waves. In addition, the compression of the magnetopause due to increases in solar wind dynamic pressure can substantially deplete electrons at high L shells where they find themselves in open drift paths, whereas electrons at low L shells can be lost through outward radial diffusion. Nevertheless, the role played by each physical process during electron flux dropouts still remains a fundamental puzzle.
Differentiation between these processes and quantification of their relative contributions to the evolution of radiation belt electrons requires high-resolution profiles of phase space density (PSD). However, such profiles of PSD are difficult to obtain due to restrictions of spacecraft observations to a single measurement in space and time, which is also compounded by the inaccuracy of instruments. Data assimilation techniques aim to blend incomplete and inaccurate spaceborne data with physics-based models in an optimal way. In the Earth's radiation belts, it is used to reconstruct the entire radial profile of electron PSD, and it has become an increasingly important tool in validating our current understanding of radiation belt dynamics, identifying new physical processes, and predicting the near-Earth hazardous radiation environment.
In this study, sparse measurements from Van Allen Probes A and B and Geostationary Operational Environmental Satellites (GOES) 13 and 15 are assimilated into the three-dimensional Versatile Electron Radiation Belt (VERB-3D) diffusion model, by means of a split-operator Kalman filter over a four-year period from 01 October 2012 to 01 October 2016. In comparison to previous works, the 3D model accounts for more physical processes, namely mixed pitch angle-energy diffusion, scattering by EMIC waves, and magnetopause shadowing. It is shown how data assimilation, by means of the innovation vector (the residual between observations and model forecast), can be used to account for missing physics in the model. This method is used to identify the radial distances from the Earth and the geomagnetic conditions where the model is inconsistent with the measured PSD for different values of the adiabatic invariants mu and K. As a result, the Kalman filter adjusts the predictions in order to match the observations, and this is interpreted as evidence of where and when additional source or loss processes are active.
Furthermore, two distinct loss mechanisms responsible for the rapid dropouts of radiation belt electrons are investigated: EMIC wave-induced scattering and magnetopause shadowing. The innovation vector is inspected for values of the invariant mu ranging from 300 to 3000 MeV/G, and a statistical analysis is performed to quantitatively assess the effect of both processes as a function of various geomagnetic indices, solar wind parameters, and radial distance from the Earth. The results of this work are in agreement with previous studies that demonstrated the energy dependence of these two mechanisms. EMIC wave scattering dominates loss at lower L shells and it may amount to between 10%/hr to 30%/hr of the maximum value of PSD over all L shells for fixed first and second adiabatic invariants. On the other hand, magnetopause shadowing is found to deplete electrons across all energies, mostly at higher L shells, resulting in loss from 50%/hr to 70%/hr of the maximum PSD. Nevertheless, during times of enhanced geomagnetic activity, both processes can operate beyond such location and encompass the entire outer radiation belt.
The results of this study are two-fold. Firstly, it demonstrates that the 3D data assimilative code provides a comprehensive picture of the radiation belts and is an important step toward performing reanalysis using observations from current and future missions. Secondly, it achieves a better understanding and provides critical clues of the dominant loss mechanisms responsible for the rapid dropouts of electrons at different locations over the outer radiation belt.
We use ultrafast x-ray diffraction to investigate the effect of expansive phononic and contractive magnetic stress driving the picosecond strain response of a metallic perovskite SrRuO3 thin film upon femtosecond laser excitation. We exemplify how the anisotropic bulk equilibrium thermal expansion can be used to predict the response of the thin film to ultrafast deposition of energy. It is key to consider that the laterally homogeneous laser excitation changes the strain response compared to the near-equilibrium thermal expansion because the balanced in-plane stresses suppress the Poisson stress on the picosecond timescale. We find a very large negative Grüneisen constant describing the large contractive stress imposed by a small amount of energy in the spin system. The temperature and fluence dependence of the strain response for a double-pulse excitation scheme demonstrates the saturation of the magnetic stress in the high-fluence regime.
Magnetic strain contributions in laser-excited metals studied by time-resolved X-ray diffraction
(2021)
In this work I explore the impact of magnetic order on the laser-induced ultrafast strain response of metals. Few experiments with femto- or picosecond time-resolution have so far investigated magnetic stresses. This is contrasted by the industrial usage of magnetic invar materials or magnetostrictive transducers for ultrasound generation, which already utilize magnetostrictive stresses in the low frequency regime.
In the reported experiments I investigate how the energy deposition by the absorption of femtosecond laser pulses in thin metal films leads to an ultrafast stress generation. I utilize that this stress drives an expansion that emits nanoscopic strain pulses, so called hypersound, into adjacent layers. Both the expansion and the strain pulses change the average inter-atomic distance in the sample, which can be tracked with sub-picosecond time resolution using an X-ray diffraction setup at a laser-driven Plasma X-ray source. Ultrafast X-ray diffraction can also be applied to buried layers within heterostructures that cannot be accessed by optical methods, which exhibit a limited penetration into metals. The reconstruction of the initial energy transfer processes from the shape of the strain pulse in buried detection layers represents a contribution of this work to the field of picosecond ultrasonics.
A central point for the analysis of the experiments is the direct link between the deposited energy density in the nano-structures and the resulting stress on the crystal lattice. The underlying thermodynamical concept of a Grüneisen parameter provides the theoretical framework for my work. I demonstrate how the Grüneisen principle can be used for the interpretation of the strain response on ultrafast timescales in various materials and that it can be extended to describe magnetic stresses. The class of heavy rare-earth elements exhibits especially large magnetostriction effects, which can even lead to an unconventional contraction of the laser-excited transducer material. Such a dominant contribution of the magnetic stress to the motion of atoms has not been demonstrated previously. The observed rise time of the magnetic stress contribution in Dysprosium is identical to the decrease in the helical spin-order, that has been found previously using time-resolved resonant X-ray diffraction. This indicates that the strength of the magnetic stress can be used as a proxy of the underlying magnetic order. Such magnetostriction measurements are applicable even in case of antiparallel or non-collinear alignment of the magnetic moments and a vanishing magnetization.
The strain response of metal films is usually determined by the pressure of electrons and lattice vibrations. I have developed a versatile two-pulse excitation routine that can be used to extract the magnetic contribution to the strain response even if systematic measurements above and below the magnetic ordering temperature are not feasible. A first laser pulse leads to a partial ultrafast demagnetization so that the amplitude and shape of the strain response triggered by the second pulse depends on the remaining magnetic order. With this method I could identify a strongly anisotropic magnetic stress contribution in the magnetic data storage material iron-platinum and identify the recovery of the magnetic order by the variation of the pulse-to-pulse delay. The stark contrast of the expansion of iron-platinum nanograins and thin films shows that the different constraints for the in-plane expansion have a strong influence on the out-of-plane expansion, due to the Poisson effect. I show how such transverse strain contributions need to be accounted for when interpreting the ultrafast out-of-plane strain response using thermal expansion coefficients obtained in near equilibrium conditions.
This work contributes an investigation of magnetostriction on ultrafast timescales to the literature of magnetic effects in materials. It develops a method to extract spatial and temporal varying stress contributions based on a model for the amplitude and shape of the emitted strain pulses. Energy transfer processes result in a change of the stress profile with respect to the initial absorption of the laser pulses. One interesting example occurs in nanoscopic gold-nickel heterostructures, where excited electrons rapidly transport energy into a distant nickel layer, that takes up much more energy and expands faster and stronger than the laser-excited gold capping layer. Magnetic excitations in rare earth materials represent a large energy reservoir that delays the energy transfer into adjacent layers. Such magneto-caloric effects are known in thermodynamics but not extensively covered on ultrafast timescales. The combination of ultrafast X-ray diffraction and time-resolved techniques with direct access to the magnetization has a large potential to uncover and quantify such energy transfer processes.
By regulating the concentration of carbon in our atmosphere, the global carbon cycle drives changes in our planet’s climate and habitability. Earth surface processes play a central, yet insufficiently constrained role in regulating fluxes of carbon between terrestrial reservoirs and the atmosphere. River systems drive global biogeochemical cycles by redistributing significant masses of carbon across the landscape. During fluvial transit, the balance between carbon oxidation and preservation determines whether this mass redistribution is a net atmospheric CO2 source or sink. Existing models for fluvial carbon transport fail to integrate the effects of sediment routing processes, resulting in large uncertainties in fluvial carbon fluxes to the oceans.
In this Ph.D. dissertation, I address this knowledge gap through three studies that focus on the timescale and routing pathways of fluvial mass transfer and show their effect on the composition and fluxes of organic carbon exported by rivers. The hypotheses posed in these three studies were tested in an analog lowland alluvial river system – the Rio Bermejo in Argentina. The Rio Bermejo annually exports more than 100 Mt of sediment and organic matter from the central Andes, and transports this material nearly 1300 km downstream across the lowland basin without influence from tributaries, allowing me to isolate the effects of geomorphic processes on fluvial organic carbon cycling. These studies focus primarily on the geochemical composition of suspended sediment collected from river depth profiles along the length of the Rio Bermejo.
In Chapter 3, I aimed to determine the mean fluvial sediment transit time for the Rio Bermejo and evaluate the geomorphic processes that regulate the rate of downstream sediment transfer. I developed a framework to use meteoric cosmogenic 10Be (10Bem) as a chronometer to track the duration of sediment transit from the mountain front downstream along the ~1300 km channel of the Rio Bermejo. I measured 10Bem concentrations in suspended sediment sampled from depth profiles, and found a 230% increase along the fluvial transit pathway. I applied a simple model for the time-dependent accumulation of 10Bem on the floodplain to estimate a mean sediment transit time of 8.5±2.2 kyr. Furthermore, I show that sediment transit velocity is influenced by lateral migration rate and channel morphodynamics. This approach to measuring sediment transit time is much more precise than other methods previously used and shows promise for future applications.
In Chapter 4, I aimed to quantify the effects of hydrodynamic sorting on the composition and quantity of particulate organic carbon (POC) export transported by lowland rivers. I first used scanning electron miscroscopy (SEM) coupled with nanoscale secondary ion mass spectrometry (NanoSIMS) analyses to show that the Bermejo transports two principal types of POC: 1) mineral-bound organic carbon associated with <4 µm, platy grains, and 2) coarse discrete organic particles. Using n-alkane stable isotope data and particle shape analysis, I showed that these two carbon pools are vertically sorted in the water column, due to differences in particle settling velocity. This vertical sorting may drive modern POC to be transported efficiently from source-to-sink, driving efficient CO2 drawdown. Simultaneously, vertical sorting may drive degraded, mineral-bound POC to be deposited overbank and stored on the floodplain for centuries to millennia, resulting in enhanced POC remineralization. In the Rio Bermejo, selective deposition of coarse material causes the proportion of mineral-bound POC to increase with distance downstream, but the majority of exported POC is composed of discrete organic particles, suggesting that the river is a net carbon sink. In summary, this study shows that selective deposition and hydraulic sorting control the composition and fate of fluvial POC during fluvial transit.
In Chapter 5, I characterized and quantified POC transformation and oxidation during fluvial transit. I analyzed the radiocarbon content and stable carbon isotopic composition of Rio Bermejo suspended sediment and found that POC ages during fluvial transit, but is also degraded and oxidized during transient floodplain storage. Using these data, I developed a conceptual model for fluvial POC cycling that allows the estimation of POC oxidation relative to POC export, and ultimately reveals whether a river is a net source or sink of CO2 to the atmosphere. Through this study, I found that the Rio Bermejo annually exports more POC than is oxidized during transit, largely due to high rates of lateral migration that cause erosion of floodplain vegetation and soil into the river. These results imply that human engineering of rivers could alter the fluvial carbon balance, by reducing lateral POC inputs and increasing the mean sediment transit time.
Together, these three studies quantitatively link geomorphic processes to rates of POC transport and degradation across sub-annual to millennial time scales and nanoscale to 103 km spatial scales, laying the groundwork for a global-scale fluvial organic carbon cycling model.
Background
Depression is one of the key factors contributing to difficulties in one’s ability to work, and serves as one of the major reasons why employees apply for psychotherapy and receive insurance subsidization of treatments. Hence, an increasing and growing number of studies rely on workability assessment scales as their primary outcome measure. The Work and Social Assessment Scale (WSAS) has been documented as one of the most psychometrically reliable and valid tools especially developed to assess workability and social functioning in patients with mental health problems. Yet, the application of the WSAS in Germany has been limited due to the paucity of a valid questionnaire in the German language. The objective of the present study was to translate the WSAS, as a brief and easy administrable tool into German and test its psychometric properties in a sample of adults with depression.
Methods
Two hundred seventy-seven patients (M = 48.3 years, SD = 11.1) with mild to moderately severe depression were recruited. A multistep translation from English into the German language was performed and the factorial validity, criterion validity, convergent validity, discriminant validity, internal consistency, and floor and ceiling effects were examined.
Results
The confirmatory factor analysis results confirmed the one-factor structure of the WSAS. Significant correlations with the WHODAS 2–0 questionnaire, a measure of functionality, demonstrated good convergent validity. Significant correlations with depression and quality of life demonstrated good criterion validity. The WSAS also demonstrated strong internal consistency (α = .89), and the absence of floor and ceiling effects indicated good sensitivity of the instrument.
Conclusions
The results of the present study demonstrated that the German version of the WSAS has good psychometric properties comparable to other international versions of this scale. The findings recommend a global assessment of psychosocial functioning with the sum score of the WSAS.
Recreational exercising and self-reported cardiometabolic diseases in German people living with HIV
(2021)
Exercise is known for its beneficial effects on preventing cardiometabolic diseases (CMDs) in the general population. People living with the human immunodeficiency virus (PLWH) are prone to sedentarism, thus raising their already elevated risk of developing CMDs in comparison to individuals without HIV. The aim of this cross-sectional study was to determine if exercise is associated with reduced risk of self-reported CMDs in a German HIV-positive sample (n = 446). Participants completed a self-report survey to assess exercise levels, date of HIV diagnosis, CD4 cell count, antiretroviral therapy, and CMDs. Participants were classified into exercising or sedentary conditions. Generalized linear models with Poisson regression were conducted to assess the prevalence ratio (PR) of PLWH reporting a CMD. Exercising PLWH were less likely to report a heart arrhythmia for every increase in exercise duration (PR: 0.20: 95% CI: 0.10–0.62, p < 0.01) and diabetes mellitus for every increase in exercise session per week (PR: 0.40: 95% CI: 0.10–1, p < 0.01). Exercise frequency and duration are associated with a decreased risk of reporting arrhythmia and diabetes mellitus in PLWH. Further studies are needed to elucidate the mechanisms underlying exercise as a protective factor for CMDs in PLWH.
Background
The metabolic syndrome (MetS) is a risk cluster for a number of secondary diseases. The implementation of prevention programs requires early detection of individuals at risk. However, access to health care providers is limited in structurally weak regions. Brandenburg, a rural federal state in Germany, has an especially high MetS prevalence and disease burden. This study aims to validate and test the feasibility of a setup for mobile diagnostics of MetS and its secondary diseases, to evaluate the MetS prevalence and its association with moderating factors in Brandenburg and to identify new ways of early prevention, while establishing a “Mobile Brandenburg Cohort” to reveal new causes and risk factors for MetS.
Methods
In a pilot study, setups for mobile diagnostics of MetS and secondary diseases will be developed and validated. A van will be equipped as an examination room using point-of-care blood analyzers and by mobilizing standard methods. In study part A, these mobile diagnostic units will be placed at different locations in Brandenburg to locally recruit 5000 participants aged 40-70 years. They will be examined for MetS and advice on nutrition and physical activity will be provided. Questionnaires will be used to evaluate sociodemographics, stress perception, and physical activity. In study part B, participants with MetS, but without known secondary diseases, will receive a detailed mobile medical examination, including MetS diagnostics, medical history, clinical examinations, and instrumental diagnostics for internal, cardiovascular, musculoskeletal, and cognitive disorders. Participants will receive advice on nutrition and an exercise program will be demonstrated on site. People unable to participate in these mobile examinations will be interviewed by telephone. If necessary, participants will be referred to general practitioners for further diagnosis.
Discussion
The mobile diagnostics approach enables early detection of individuals at risk, and their targeted referral to local health care providers. Evaluation of the MetS prevalence, its relation to risk-increasing factors, and the “Mobile Brandenburg Cohort” create a unique database for further longitudinal studies on the implementation of home-based prevention programs to reduce mortality, especially in rural regions.
Trial registration
German Clinical Trials Register, DRKS00022764; registered 07 October 2020—retrospectively registered.
Introduction
(2021)
Ranking local climate policy
(2021)
Climate mitigation and climate adaptation are crucial tasks for urban areas and can involve synergies as well as trade-offs. However, few studies have examined how mitigation and adaptation efforts relate to each other in a large number of differently sized cities, and therefore we know little about whether forerunners in mitigation are also leading in adaptation or if cities tend to focus on just one policy field. This article develops an internationally applicable approach to rank cities on climate policy that incorporates multiple indicators related to (1) local commitments on mitigation and adaptation, (2) urban mitigation and adaptation plans and (3) climate adaptation and mitigation ambitions. We apply this method to rank 104 differently sized German cities and identify six clusters: climate policy leaders, climate adaptation leaders, climate mitigation leaders, climate policy followers, climate policy latecomers and climate policy laggards. The article seeks explanations for particular cities' positions and shows that coping with climate change in a balanced way on a high level depends on structural factors, in particular city size, the pathways of local climate policies since the 1990s and funding programmes for both climate mitigation and adaptation.
In this study, we analyzed a large seismological dataset from temporary and permanent networks in the southern and eastern Alps to establish high-precision hypocenters and 1-D V-P and V-P/V-S models. The waveform data of a subset of local earthquakes with magnitudes in the range of 1-4.2 M-L were recorded by the dense, temporary SWATH-D network and selected stations of the AlpArray network between September 2017 and the end of 2018. The first arrival times of P and S waves of earthquakes are determined by a semi-automatic procedure. We applied a Markov chain Monte Carlo inversion method to simultaneously calculate robust hypocenters, a 1-D velocity model, and station corrections without prior assumptions, such as initial velocity models or earthquake locations. A further advantage of this method is the derivation of the model parameter uncertainties and noise levels of the data. The precision estimates of the localization procedure is checked by inverting a synthetic travel time dataset from a complex 3-D velocity model and by using the real stations and earthquakes geometry. The location accuracy is further investigated by a quarry blast test. The average uncertainties of the locations of the earthquakes are below 500m in their epicenter and similar to 1.7 km in depth. The earthquake distribution reveals seismicity in the upper crust (0-20 km), which is characterized by pronounced clusters along the Alpine frontal thrust, e.g., the Friuli-Venetia (FV) region, the Giudicarie-Lessini (GL) and Schio-Vicenza domains, the Austroalpine nappes, and the Inntal area. Some seismicity also occurs along the Periadriatic Fault. The general pattern of seismicity reflects head-on convergence of the Adriatic indenter with the Alpine orogenic crust. The seismicity in the FV and GL regions is deeper than the modeled frontal thrusts, which we interpret as indication for southward propagation of the southern Alpine deformation front (blind thrusts).
Proceedings of the HPI Research School on Service-oriented Systems Engineering 2020 Fall Retreat
(2021)
Design and Implementation of service-oriented architectures imposes a huge number of research questions from the fields of software engineering, system analysis and modeling, adaptability, and application integration. Component orientation and web services are two approaches for design and realization of complex web-based system. Both approaches allow for dynamic application adaptation as well as integration of enterprise application.
Service-Oriented Systems Engineering represents a symbiosis of best practices in object-orientation, component-based development, distributed computing, and business process management. It provides integration of business and IT concerns.
The annual Ph.D. Retreat of the Research School provides each member the opportunity to present his/her current state of their research and to give an outline of a prospective Ph.D. thesis. Due to the interdisciplinary structure of the research school, this technical report covers a wide range of topics. These include but are not limited to: Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; and Services Specification, Composition, and Enactment.
Phe2vec
(2021)
Robust phenotyping of patients from electronic health records (EHRs) at scale is a challenge in clinical informatics. Here, we introduce Phe2vec, an automated framework for disease phenotyping from EHRs based on unsupervised learning and assess its effectiveness against standard rule-based algorithms from Phenotype KnowledgeBase (PheKB). Phe2vec is based on pre-computing embeddings of medical concepts and patients' clinical history. Disease phenotypes are then derived from a seed concept and its neighbors in the embedding space. Patients are linked to a disease if their embedded representation is close to the disease phenotype. Comparing Phe2vec and PheKB cohorts head-to-head using chart review, Phe2vec performed on par or better in nine out of ten diseases. Differently from other approaches, it can scale to any condition and was validated against widely adopted expert-based standards. Phe2vec aims to optimize clinical informatics research by augmenting current frameworks to characterize patients by condition and derive reliable disease cohorts.
Background:
Early reports indicate that AKI is common among patients with coronavirus disease 2019 (COVID-19) and associatedwith worse outcomes. However, AKI among hospitalized patients with COVID19 in the United States is not well described.
Methods:
This retrospective, observational study involved a review of data from electronic health records of patients aged >= 18 years with laboratory-confirmed COVID-19 admitted to the Mount Sinai Health System from February 27 to May 30, 2020. We describe the frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aORs) with mortality.
Results:
Of 3993 hospitalized patients with COVID-19, AKI occurred in 1835 (46%) patients; 347 (19%) of the patientswith AKI required dialysis. The proportionswith stages 1, 2, or 3 AKIwere 39%, 19%, and 42%, respectively. A total of 976 (24%) patients were admitted to intensive care, and 745 (76%) experienced AKI. Of the 435 patients with AKI and urine studies, 84% had proteinuria, 81% had hematuria, and 60% had leukocyturia. Independent predictors of severe AKI were CKD, men, and higher serum potassium at admission. In-hospital mortality was 50% among patients with AKI versus 8% among those without AKI (aOR, 9.2; 95% confidence interval, 7.5 to 11.3). Of survivors with AKI who were discharged, 35% had not recovered to baseline kidney function by the time of discharge. An additional 28 of 77 (36%) patients who had not recovered kidney function at discharge did so on posthospital follow-up.
Conclusions:
AKI is common among patients hospitalized with COVID-19 and is associated with high mortality. Of all patients with AKI, only 30% survived with recovery of kidney function by the time of discharge.
Background and objectives
AKI treated with dialysis initiation is a common complication of coronavirus disease 2019 (COVID-19) among hospitalized patients. However, dialysis supplies and personnel are often limited.
Design, setting, participants, & measurements
Using data from adult patients hospitalized with COVID-19 from five hospitals from theMount Sinai Health System who were admitted between March 10 and December 26, 2020, we developed and validated several models (logistic regression, Least Absolute Shrinkage and Selection Operator (LASSO), random forest, and eXtreme GradientBoosting [XGBoost; with and without imputation]) for predicting treatment with dialysis or death at various time horizons (1, 3, 5, and 7 days) after hospital admission. Patients admitted to theMount Sinai Hospital were used for internal validation, whereas the other hospitals formed part of the external validation cohort. Features included demographics, comorbidities, and laboratory and vital signs within 12 hours of hospital admission.
Results
A total of 6093 patients (2442 in training and 3651 in external validation) were included in the final cohort. Of the different modeling approaches used, XGBoost without imputation had the highest area under the receiver operating characteristic (AUROC) curve on internal validation (range of 0.93-0.98) and area under the precisionrecall curve (AUPRC; range of 0.78-0.82) for all time points. XGBoost without imputation also had the highest test parameters on external validation (AUROC range of 0.85-0.87, and AUPRC range of 0.27-0.54) across all time windows. XGBoost without imputation outperformed all models with higher precision and recall (mean difference in AUROC of 0.04; mean difference in AUPRC of 0.15). Features of creatinine, BUN, and red cell distribution width were major drivers of the model's prediction.
Conclusions
An XGBoost model without imputation for prediction of a composite outcome of either death or dialysis in patients positive for COVID-19 had the best performance, as compared with standard and other machine learning models.
FIBER
(2021)
Objectives:
The development of clinical predictive models hinges upon the availability of comprehensive clinical data. Tapping into such resources requires considerable effort from clinicians, data scientists, and engineers. Specifically, these efforts are focused on data extraction and preprocessing steps required prior to modeling, including complex database queries. A handful of software libraries exist that can reduce this complexity by building upon data standards. However, a gap remains concerning electronic health records (EHRs) stored in star schema clinical data warehouses, an approach often adopted in practice. In this article, we introduce the FlexIBle EHR Retrieval (FIBER) tool: a Python library built on top of a star schema (i2b2) clinical data warehouse that enables flexible generation of modeling-ready cohorts as data frames.
Materials and Methods:
FIBER was developed on top of a large-scale star schema EHR database which contains data from 8 million patients and over 120 million encounters. To illustrate FIBER's capabilities, we present its application by building a heart surgery patient cohort with subsequent prediction of acute kidney injury (AKI) with various machine learning models.
Results:
Using FIBER, we were able to build the heart surgery cohort (n = 12 061), identify the patients that developed AKI (n = 1005), and automatically extract relevant features (n = 774). Finally, we trained machine learning models that achieved area under the curve values of up to 0.77 for this exemplary use case.
Conclusion:
FIBER is an open-source Python library developed for extracting information from star schema clinical data warehouses and reduces time-to-modeling, helping to streamline the clinical modeling process.