The 50 most recently published documents
Hybrid nanophotonic elements, fabricated by organic and inorganic materials, are going to be key components of modern devices.
Coupled systems of photoemitters with a plasmonic waveguide serve the demand for nanoscopic frequency converters.
However, processes like the degradation of the photoemitters via photobleaching occur and need to be monitored and controlled, to realize future successful devices.
We introduce a hybrid perylene-diimide / silver nanowire as plasmon frequency converter. A versatile method is presented to monitor and analyze the bleaching process. It is based on a time series of photoluminescence images, during the operation of a single converter.
An analytical model is applied on the data and unveils that the photobleaching rate is constant and independent of the operation of the plasmon converter.
A circular, single-contig Methanobacterium sp. metagenome-assembled genome (MAG) was recovered from high-CO2 enrichments inoculated with drill core material from the tectonic Eger Rift terrestrial subsurface.
Annotation of the recovered MAG highlighted putative methanogenesis genes, providing valuable information on archaeal activity in the deep biosphere.
Refractive index provides fundamental insights into the electronic structure of materials. At high pressure, however, the determination of refractive index and its wavelength dispersion is challenging, which limits our understanding of how physical properties of even simple materials, such as MgO, evolve with pressure.
Here, we report on the measurement of room-temperature refractive index of MgO up to similar to 140 GPa.
The refractive index of MgO at 600 nm decreases by similar to 2.4% from similar to 1.737 at 1 atm to similar to 1.696 (+/- 0.017) at similar to 140 GPa.
Despite the index at 600 nm is essentially pressure independent, the absolute wavelength dispersion of the refractive index at 550-870 nm decreases by similar to 28% from similar to 0.015 at 1 atm to similar to 0.011 (+/- 8.04 x 10(-4)) at similar to 103 GPa.
Single-effective-oscillator analysis of our refractive index data suggests that the bandgap of MgO increases by similar to 1.1 eV from 7.4 eV at 1 atm to similar to 8.5 (+/- 0.6) eV at similar to 103 GPa.
We have investigated the self-assembly of the graphene nanoribbon molecular precursor 10,10'-dibromo-9,9'-bianthryl (DBBA) on Au(111) with frequency modulation scanning force microscopy (FM-SFM) at room temperature combined with ab initio calculations.
For low molecular coverages, the molecules aggregate along the substrate herringbone reconstruction main directions while remaining mobile.
At intermediate coverage, two phases coexist, zigzag stripes of monomer chains and decorated herringbones. For high coverage, the molecules assemble in a dimer-striped phase.
The adsorption behaviour of DBBA molecules and their interactions are discussed and compared with the results from ab initio calculations.
The Gram-negative bacterium Paenalcaligenes niemegkensis NGK35(T) was isolated from plastic debris in an abandoned landfill.
It has the ability to grow on polyethylene and hexadecane as the sole carbon sources. Here, we report the corresponding draft genome, which contains 3.66 Mbp and is characterized by a G+C content of 52.1%.
International migration patterns, at the global level, can to a large extent be explained through economic factors in origin and destination countries.
On the other hand, it has been shown that global climate change is likely to affect economic development over the coming decades.
Here, we demonstrate how these future climate impacts on national income levels could alter the global migration landscape.
Using an empirically calibrated global migration model, we investigate two separate mechanisms. The first is through destination-country income, which has been shown consistently to have a positive effect on immigration.
As countries' income levels relative to each other are projected to change in the future both due to different rates of economic growth and due to different levels of climate change impacts, the relative distribution of immigration across destination countries also changes as a result, all else being equal.
Second, emigration rates have been found to have a complex, inverted U-shaped dependence on origin-country income.
Given the available migration flow data, it is unclear whether this dependence-found in spatio-temporal panel data-also pertains to changes in a given migration flow over time. If it does, then climate change will additionally affect migration patterns through origin countries' emigration rates, as the relative and absolute positions of countries on the migration "hump" change.
We illustrate these different possibilities, and the corresponding effects of 3 degrees C global warming (above pre-industrial) on global migration patterns, using climate model projections and two different methods for estimating climate change effects on macroeconomic development.
Teacher collaboration is an important feature of job satisfaction and self-efficacy for teachers.
Moreover, the collaboration of teachers is important for adopting professional changes as professional development (PD) activities that include opportunities for collaboration have been shown to support teachers in improving classroom practice.
This may even lead to higher student performance.
Situated in the context of the Advanced Placement (AP) reform in the United States, we investigated the perceived importance of opportunities to collaborate with colleagues as a rationale to participate in PD (N = 3,725 teachers).
The opportunity to collaborate with colleagues was a primary rationale why teachers selected PD activities.
While this rationale is only slightly related to school and teacher characteristics, it was related to PD characteristics.
Specifically, opportunities to collaborate with colleagues were important to teachers in selecting informal face-to-face (FtF) PD activities.
We conclude that collaborative structures benefit all forms of teacher professional development.
We present the extension of the Kalmag model, proposed as a candidate for IGRF-13, to the twentieth century.
The dataset serving its derivation has been complemented by new measurements coming from satellites, ground-based observatories and land, marine and airborne surveys.
As its predecessor, this version is derived from a combination of a Kalman filter and a smoothing algorithm, providing mean models and associated uncertainties. These quantities permit a precise estimation of locations where mean solutions can be considered as reliable or not.
The temporal resolution of the core field and the secular variation was set to 0.1 year over the 122 years the model is spanning.
Nevertheless, it can be shown through ensembles a posteriori sampled, that this resolution can be effectively achieved only by a limited amount of spatial scales and during certain time periods.
Unsurprisingly, highest accuracy in both space and time of the core field and the secular variation is achieved during the CHAMP and Swarm era. In this version of Kalmag, a particular effort was made for resolving the small-scale lithospheric field.
Under specific statistical assumptions, the latter was modeled up to spherical harmonic degree and order 1000, and signal from both satellite and survey measurements contributed to its development.
External and induced fields were jointly estimated with the rest of the model. We show that their large scales could be accurately extracted from direct measurements whenever the latter exhibit a sufficiently high temporal coverage.
Temporally resolving these fields down to 3 hours during the CHAMP and Swarm missions, gave us access to the link between induced and magnetospheric fields. In particular, the period dependence of the driving signal on the induced one could be directly observed.
The model is available through various physical and statistical quantities on a dedicated website at https://ionocovar.agnld.uni-potsdam.de/Kalmag/.
The diffusion process of water in swelling (expansive) soil often deviates from normal Fick diffusion and belongs to anomalous diffusion.
The process of water adsorption by swelling soil often changes with time, in which the microstructure evolves with time and the absorption rate changes along a fractal dimension gradient function.
Thus, based on the material coordinate theory, this paper proposes a variable order derivative fractal model to describe the cumulative adsorption of water in the expansive soil, and the variable order is time dependent linearly.
The cumulative adsorption is a power law function of the anomalous sorptivity, and patterns of the variable order.
The variable-order fractal derivative model is tested to describe the cumulative adsorption in chernozemic surface soil, Wunnamurra clay and sandy loam.
The results show that the fractal derivative model with linearly time dependent variable-order has much better accuracy than the fractal derivative model with a constant derivative order and the integer order model in the application cases.
The derivative order can be used to distinguish the evolution of the anomalous adsorption process. The variable-order fractal derivative model can serve as an alternative approach to describe water anomalous adsorption in swelling soil.
Hintergrund
Lungenkrebsbetroffene sind besonders stark durch psychischen Stress belastet. Gleichzeitig sind die Inanspruchnahmeraten von psychoonkologischer Unterstützung relativ gering. Es ist wenig über die Gründe der (Nicht‑)Inanspruchnahme bekannt.
Fragestellung
Welche emotionalen Herausforderungen erleben Menschen mit Lungenkrebs? Was sind ihre Gründe für die (Nicht‑)Inanspruchnahme psychoonkologischer Unterstützung?
Material und Methode
Es wurden qualitative Interviews mit 20 Lungenkrebsbetroffenen ausgewertet, die im Rahmen der CoreNAVI-Studie durchgeführt wurden.
Ergebnisse
Die Befragten erleben psychischen Stress in Form von Unsicherheiten und Zukunftsängsten. Auch den Druck, schnell von einer Behandlung in die nächste gehen zu müssen und keine Zeit für sich zu haben, nehmen die Betroffenen als belastend wahr. Das offene Sprechen, ohne das persönliche Umfeld belasten zu müssen, sowie konkrete Ratschläge erleben die Nutzer*innen der Psychoonkologie als große Hilfestellung. Die Nichtinanspruchnahme wird durch fehlenden Bedarf und mangelnde Kapazitäten begründet. Zudem werden Vorbehalte gegenüber psychologischer Unterstützung deutlich.
Schlussfolgerung
Betroffene mit Lungenkrebs erleben psychische und emotionale Belastungen auch durch die Vielzahl und Dichte an Therapien. Daraus resultierende fehlende Kapazitäten könnten eine Erklärung für die geringe Inanspruchnahme von psychoonkologischer Unterstützung sein. Eine stärkere Gewichtung der Psychoonkologie gegenüber aufwendigen medizinischen, oft nur geringfügig lebensverlängernden Therapien sowie der Abbau von Vorbehalten gegenüber psychologischer Hilfe sollten in der Versorgungspraxis verstärkt in den Fokus rücken.
Since the adoption of the Paris Agreement, the focus of the United Nations climate regime has shifted from forging consensus among national governments toward animating implementation activity across multiple levels.
Based on a case study of the Global Climate Action Portal-an online database designed to document nonstate actor climate commitments and implementation efforts-we trace, conceptualize, and assess how the roles of data, data infrastructures, and actor constellations have changed as a result of this shift.
We argue that in the pre-COP21 negotiation phase, the United Nations Climate Secretariat strategically used the database to orchestrate and leverage nonstate actor commitments to exert pressure on intergovernmental negotiations.
By contrast, in the post-COP21 implementation phase, the Secretariat, in collaboration with climate data specialists, is seeking to develop the portal to track and animate implementation activity.
Given these developments, we discuss the potential and limitations of data-driven climate governance and set out avenues for future research.
Time and angle-resolved time-of-flight electron spectroscopy for functional materials science
(2022)
Electron spectroscopy with the unprecedented transmission of angle-resolved time-of-flight detection, in combination with pulsed X-ray sources, brings new impetus to functional materials science.
We showcase recent developments towards chemical sensitivity from electron spectroscopy for chemical analysis and structural information from photoelectron diffraction using the phase transition properties of 1T-TaS2.
Our development platform is the SurfaceDynamics instrument located at the Femtoslicing facility at BESSY II, where femtosecond and picosecond X-ray pulses can be generated and extracted.
The scientific potential is put into perspective to the current rapidly developing pulsed X-ray source capabilities from Lasers and Free-Electron Lasers.
Das neue Hinweisgeberschutzgesetz verlangt neben der Einrichtung unternehmens- bzw. behördeneigener interner Meldestellen auch den Aufbau externer Meldestellen. Diese wurden zur Vermeidung zusätzlicher Bürokratie bei bestehenden Bundesbehörden angesiedelt. System und Wirkungsweise der externen Meldestellen sollen nachfolgend erörtert werden. Zugleich bieten die Ausführungen Anlass, gesetzgeberische Verbesserungen zu erwägen.
Faults and fractures can be permeable pathways for focused fluid flow in structurally controlled ore-forming hydrothermal systems.
However, quantifying their role in fluid flow on the scale of several kilometers with numerical models typically requires high-resolution meshes.
This study introduces a modified numerical representation of m-scale fault zones using lower-dimensional elements (here, one-dimensional [1D] elements in a 2D domain) to resolve structurally controlled fluid flow with coarser mesh resolutions and apply the method to magmatic-hydrothermal ore-forming systems.
We modeled horizontal and vertical structure-controlled magmatic-hydrothermal deposits to understand the role of permeability and structure connectivity on ore deposition.
The simulation results of vertically extended porphyry copper systems show that ore deposition can occur along permeable vertical structures where ascending, overpressured magmatic fluids are cooled by downflowing ambient fluids. Structure permeability and fault location control the distribution of ore grades.
In highly permeable structures, the mineralization can span up to 3 km vertically, resulting in heat-pipe mechanisms that promote the ascent of a magmatic vapor phase to an overlying structurally controlled epithermal system.
Simulations for the formation of subhorizontal vein-type deposits suggest that the major control on fluid flow and metal deposition along horizontal structures is the absence of vertical structures above the injection location but their presence at greater distances.
Using a dynamic permeability model mimicking crack-seal mechanisms within the structures leads to a pulsating behavior of fracture-controlled hydrothermal systems and prevents the inflow of ambient fluids under overpressured conditions.
Current evidence suggests that migratory animals extract map information from the geomagnetic field for true navigation. The sensory basis underlying this feat is elusive, but presumably involves magnetic particles.
A common experimental manipulation procedure consists of pre-treating animals with a magnetic pulse, with the aim of re-magnetising particles to alter the internal representation of the external field prior to a navigation task.
Although pulsing provoked deflected bearings in caged songbirds, analogous studies with free-flying songbirds yielded inconsistent results.
Here, we pulsed European robins (Erithacus rubecula) at an offshore stopover site during spring migration and monitored their free-flight behaviour with a regional-scale network of radio-receiving stations.
We found no pulse effect on departure probability, nocturnal departure timing departure direction or consistency of flight direction.
This suggests either no use of the geomagnetic map by our birds, or that magnetic pulses do not affect the sensory system underlying geomagnetic map detection.
Biodegradable core-multishell nanocarrier: topical tacrolimus delivery for treatment of dermatitis
(2022)
Two challenges in topical drug delivery to the skin include solubilizing hydrophobic drugs in water-based formulations and increasing drug penetration into the skin. Polymeric core-multishell nanocarrier (CMS), particularly the novel biodegradable CMS (bCMS = hPG-PCL1.1K-mPEG(2k)-CMS) have shown both advantages on excised skin ex vivo.
Here, we investigated topical delivery of tacrolimus (TAC; > 500 g/mol) by bCMS in a hydrogel on an oxazolone-induced model of dermatitis in vivo. As expected, bCMS successfully delivered TAC into the skin.
However, in vivo they did not increase, but decrease TAC penetration through the stratum corneum compared to ointment.
Differences in the resulting mean concentrations were mostly non-significant in the skin (epidermis: 35.7 +/- 20.9 ng/cm(2) for bCMS vs. 92.6 +/- 62.7 ng/cm(2) for ointment; dermis: 76.8 +/- 26.8 ng/cm(2) vs 118.2 +/- 50.4 ng/cm(2)), but highly significant in blood (plasma: 1.1 +/- 0.4 ng/ml vs 11.3 +/- 9.3 ng/ml; erythrocytes: 0.5 +/- 0.2 ng/ml vs 3.4 +/- 2.4 ng/ml) and liver (0.01 +/- 0.01 ng/mg vs 0.03 +/- 0.01 ng/mg). bCMS were detected in the stratum corneum but not in viable skin or beyond.
The therapeutic efficacy of TAC delivered by bCMS was equivalent to that of standard TAC ointment.
Our results suggest that bCMS may be a promising carrier for the topical delivery of TAC. The quantitative difference to previous results should be interpreted in light of structural differences between murine and human skin, but highlights the need as well as potential methods to develop more a complex ex vivo analysis on human skin to ensure quantitative predictive value.
Floods affect more people than any other natural hazard; thus flood warning and disaster management are of utmost importance.
However, the operational hydrological forecasts do not provide information about affected areas and impact but only discharge and water levels at gauges.
We show that a simple hydrodynamic model operating with readily available data is able to provide highly localized information on the expected flood extent and impacts, with simulation times enabling operational flood warning.
We demonstrate that such an impact forecast would have indicated the deadly potential of the 2021 flood in western Germany with sufficient lead time.
This study aimed to validate the Norwegian version of the Basic Psychological Need Satisfaction and Frustration Scale (BPNSFS) and to examine its relations with indicators of well-being and ill-being. Additionally, despite the vast number of studies employing the BPNSFS, norms related to the BPNSFS are currently lacking.
Therefore, we also aimed to provide normative data for this scale. Data were collected among a representative sample of 326 participants (M age = 42.90 years, SD = 14.76; range 18-70) in Norway, of which 49.7% was female.
Results yielded evidence for a six-factor structure (i.e., combining satisfaction/frustration with the type of need) and showed the subscales to be highly reliable. Subsequent structural equation modeling showed that both need satisfaction and need frustration related strongly to vitality, life satisfaction, and internalizing symptoms, but in opposite ways. Norm scores were provided, thereby differentiating between women and men and different age groups.
These findings support the use of the Norwegian BPNSFS and provide researchers and professionals with normative data on the most widely used tool to assess individuals' satisfaction and frustration of the basic psychological needs for autonomy, competence, and relatedness.
Carbohydrates play a vital role in all living organisms; serving as a cornerstone in primary metabolism through the release of energy from their hydrolysis and subsequent re-utilization (Apriyanto et al., 2022). Starch is the principal carbohydrate reserve in plants, providing essential energy for plant growth. Furthermore, starch serves as a significant carbohydrate source in the human diet. Beyond its nutritional value, starch has extensive industrial application associated with many aspects of human society, such as feed, pharmacy, textiles, and the production of biodegradable plastics. Understanding the mechanisms underlying starch metabolism in plants carries multifaceted benefits. Not only does it contribute to increasing crop yield and refining grain quality, but also can improve the efficiency of industrial applications.
Starch in plants is categorized into two classes based on their location and function: transitory starch and storage starch. Transitory starch is produced in chloroplasts of autotrophic tissues/organs, such as leaves. It is synthesized during the day and degraded during the night. Storage starch is synthesized in heterotrophic tissues/organs, such as endosperm, roots and tubers, which is utilized for plant reproduction and industrial application in human life. Most studies aiming to comprehend starch metabolism of Arabidopsis thaliana primarily focus on transitory starch.
Starch is stored as granular form in chloroplast and amyloplast. The parameters of starch granules, including size, morphology, and quantity per chloroplast serve as indicators of starch metabolism status. However, the understanding of their regulatory mechanism is still incomplete. In this research, I initially employed a simple and adapted method based on laser confocal scanning microscopy (LCSM) to observe size, morphology and quantity of starch granules within chloroplasts in Arabidopsis thaliana in vivo. This method facilitated a rapid and versatile analysis of starch granule parameters across numerous samples. Utilizing this approach, I compared starch granule number per chloroplast between mesophyll cells and guard cells in both wild type plants (Col-0) and several starch related mutants. The results revealed that the granule number is distinct between mesophyll cells and guard cells, even within the same genetic background, suggesting that guard cells operate a unique regulatory mechanism of starch granule number.
Subsequently, I redirected my attention toward examining starch morphology. Through microscopy analyses, I observed a gradual alteration in starch granule morphology in certain mutants during leaf aging. Specifically, in mutants such as sex1-8 and dpe2phs1ss4, there was a progressive alteration in starch granule morphology over time. Conversely, in Col-0 and ss4 mutant, these morphological alterations were not evident. This discovery suggests a new perspective to understand the development of starch morphology.
Further investigation revealed that mutants lacking either Disproportionating enzyme 2 (DPE2) or MALTOSE-EXCESS 1 (MEX1) exhibited gradual alterations in starch morphology with leaf aging. Notably, the most severe effects on starch morphology occurred in double mutants lacking either DPE2 or MEX1 in conjunction with a lack of starch synthase 4 (SS4). In these mutations, a transformation of the starch granule morphology from the typical discoid morphology to oval and eventually to a spherical shape.
To investigate the changes in the internal structure of starch during this alteration, I analyzed the chain length distribution (CLD) of the amylopectin of young, intermediate and old leaves of the mutants. Throughout starch granule development, I found an increased presence of short glucan chains within the granules, particularly evident in dpe2ss4 and mex1ss4 mutants, as well as their parental single mutants. Notably, the single mutant ss4 also showed an affected granule morphology, albeit not influenced by leaf aging..
The CLD pattern of the amylopectin reflects an integrative regulation involving several participants in starch synthesis, including starch synthases (SSs), starch branching/debranching enzymes (SBEs/DBEs). Therefore, I further detected the expression of related genes on transcription level and the enzymatic activity of their respective proteins. Results indicated altered gene expression of several regulators in these mutants, particularly demonstrating dramatic alterations in dpe2 and dpe2ss4 with leaf aging. These changes corresponded with the observed alterations in starch granule morphology.
Taken together, I have identified and characterized a progressive alteration in starch granule morphology primarily resulting from the deficiencies in DPE2 and MEX1. Furthermore, I have associated the CLD pattern with the granule morphogenesis, as well as the gene expression and enzymatic activity of proteins involved in starch synthesis. Unlike SS4, which is implicated in starch initiation, MEX1 and DPE2 are involved into starch degradation. MEX1 is located in chloroplast envelope and DPE2 is situated in the cytosol. Considering the locations and known functions of DPE2/MEX1 and SS4, I infer that there might be two pathways influencing starch morphology: an initiation-affected pathway via SS4 and a degradation-affected pathway via DPE2/MEX1.
Massive stars (Mini > 8 Msol) are the key feedback agents within galaxies, as they shape their surroundings via their powerful winds, ionizing radiation, and explosive supernovae. Most massive stars are born in binary systems, where interactions with their companions significantly alter their evolution and the feedback they deposit in their host galaxy. Understanding binary evolution, particularly in the low-metallicity environments as proxies for the Early Universe, is crucial for interpreting the rest-frame ultraviolet spectra observed in high-redshift galaxies by telescopes like Hubble and James Webb.
This thesis aims to tackle this challenge by investigating in detail massive binaries within the low-metallicity environment of the Small Magellanic Cloud galaxy. From ultraviolet and multi-epoch optical spectroscopic data, we uncovered post-interaction binaries. To comprehensively characterize these binary systems, their stellar winds, and orbital parameters, we use a multifaceted approach. The Potsdam Wolf-Rayet stellar atmosphere code is employed to obtain the stellar and wind parameters of the stars. Additionally, we perform consistent light and radial velocity fitting with the Physics of Eclipsing Binaries software, allowing for the independent determination of orbital parameters and component masses. Finally, we utilize these results to challenge the standard picture of stellar evolution and improve our understanding of low-metallicity stellar populations by calculating our binary evolution models with the Modules for Experiments in Stellar Astrophysics code.
We discovered the first four O-type post-interaction binaries in the SMC (Chapters 2, 5, and 6). Their primary stars have temperatures similar to other OB stars and reside far from the helium zero-age main sequence, challenging the traditional view of binary evolution. Our stellar evolution models suggest this may be due to enhanced mixing after core-hydrogen burning. Furthermore, we discovered the so-far most massive binary system undergoing mass transfer (Chapter 3), offering a unique opportunity to test mass-transfer efficiency in extreme conditions. Our binary evolution calculations revealed unexpected evolutionary pathways for accreting stars in binaries, potentially providing the missing link to understanding the observed Wolf-Rayet population within the SMC (Chapter 4). The results presented in this thesis unveiled the properties of massive binaries at low-metallicity which challenge the way the spectra of high-redshift galaxies are currently being analyzed as well as our understanding of massive-star feedback within galaxies.
Seismicity models are probabilistic forecasts of earthquake rates to support seismic hazard assessment.
Physics-based models allow extrapolating previously unsampled parameter ranges and enable conclusions on underlying tectonic or human-induced processes.
The Coulomb Failure (CF) and the rate-and-state (RS) models are two widely used physics-based seismicity models both assuming pre-existing populations of faults responding to Coulomb stress changes.
The CF model depends on the absolute Coulomb stress and assumes instantaneous triggering if stress exceeds a threshold, while the RS model only depends on stress changes.
Both models can predict background earthquake rates and time-dependent stress effects, but the RS model with its three independent parameters can additionally explain delayed aftershock triggering.
This study introduces a modified CF model where the instantaneous triggering is replaced by a mean time-to-failure depending on the absolute stress value.
For the specific choice of an exponential dependence on stress and a stationary initial seismicity rate, we show that the model leads to identical results as the RS model and reproduces the Omori-Utsu relation for aftershock decays as well stress-shadowing effects.
Thus, both CF and RS models can be seen as special cases of the new model. However, the new stress response model can also account for subcritical initial stress conditions and alternative functions of the mean time-to-failure depending on the problem and fracture mode.
In this work we present windlidar data for the research village Ny-Alesund located on Svalbard in the European Arctic (78.923 degrees N, 11.928 degrees F) from 2013 to 2021.
The data have a resolution of 50 m and 10 min with an overlapping height of about 150 m.
The maximum range depends on the meteorologic situation. Up to 1000 m altitude the data availability is better than 71%.
We found that the highest wind speeds occur in November and December, the lowest ones in June and July, up to 500 m altitude the wind is channelled strongly in ESE to NW direction parallel to the fjord axis and the synoptic conditions above 1000 m altitude already dominate.
While the fraction of windy days (v > 10 m/s) varies significantly from month to month, there is no overall trend of the wind visible in our data set.
We define gusts and jets by the requirement of wind maxima v > 2 m/s above and below a wind maximum. In total, more than 24,000 of these events were identified (corresponding to 6% of the time), of which 223 lasted for at least 100 min ("Long Jets"). All of these events are fairly equally distributed over the months relatively to the available data.
Further, gusts and jets follow different distributions (in terms of altitude or depths) and occur more frequently for synoptic flow from roughly a southerly direction. Jets do not show a clear correlation between occurrence and synoptic flow. Gusts and jets are not related to cloud cover.
We conclude that the atmosphere from 400 m to 1000 m above Ny-Alesund is dominated by a turbulent wind shear zone, which connects the micrometeorology in the atmospheric boundary layer (ABL) with the synoptic flow.
Astrophysical shocks, driven by explosive events such as supernovae, efficiently accelerate charged particles to relativistic energies. The majority of these shocks occur in collisionless plasmas where the energy transfer is dominated by particle-wave interactions.Strong nonrelativistic shocks found in supernova remnants are plausible sites of galactic cosmic ray production, and the observed emission indicates the presence of nonthermal electrons. To participate in the primary mechanism of energy gain - Diffusive Shock Acceleration - electrons must have a highly suprathermal energy, implying a need for very efficient pre-acceleration. This poorly understood aspect of the shock acceleration theory is known as the electron injection problem. Studying electron-scale phenomena requires the use of fully kinetic particle-in-cell (PIC) simulations, which describe collisionless plasma from first principles.
Most published studies consider a homogenous upstream medium, but turbulence is ubiquitous in astrophysical environments and is typically driven at magnetohydrodynamic scales, cascading down to kinetic scales. For the first time, I investigate how preexisting turbulence affects electron acceleration at nonrelativistic shocks using the fully kinetic approach. To accomplish this, I developed a novel simulation framework that allows the study of shocks propagating in turbulent media. It involves simulating slabs of turbulent plasma separately, which are further continuously inserted into a shock simulation. This demands matching of the plasma slabs at the interface. A new procedure of matching electromagnetic fields and currents prevents numerical transients, and the plasma evolves self-consistently. The versatility of this framework has the potential to render simulations more consistent with turbulent systems in various astrophysical environments.
In this Thesis, I present the results of 2D3V PIC simulations of high-Mach-number nonrelativistic shocks with preexisting compressive turbulence in an electron-ion plasma. The chosen amplitudes of the density fluctuations ($\lesssim15\%$) concord with \textit{in situ} measurements in the heliosphere and the local interstellar medium. I explored how these fluctuations impact the dynamics of upstream electrons, the driving of the plasma instabilities, electron heating and acceleration. My results indicate that while the presence of the turbulence enhances variations in the upstream magnetic field, their levels remain too low to influence the behavior of electrons at perpendicular shocks significantly. However, the situation is different at oblique shocks. The external magnetic field inclined at an angle between $50^\circ \lesssim \theta_\text{Bn} \lesssim 75^\circ$ relative to the shock normal allows the escape of fast electrons toward the upstream region. An extended electron foreshock region is formed, where these particles drive various instabilities. Results of an oblique shock with $\theta_\text{Bn}=60^\circ$ propagating in preexisting compressive turbulence show that the foreshock becomes significantly shorter, and the shock-reflected electrons have higher temperatures. Furthermore, the energy spectrum of downstream electrons shows a well-pronounced nonthermal tail that follows a power law with an index up to -2.3.
The methods and results presented in this Thesis could serve as a starting point for more realistic modeling of interactions between shocks and turbulence in plasmas from first principles.
Robust research continues to broaden and deepen the field's understanding of immigrants' ethnic-racial identity and mental health.
We highlight opportunities to pioneer the literature by questioning "who" is meant by immigrant (clearly defining generational status, going beyond covariate and difference -based approaches, focusing on immigrants from under-studied ethnic-racial backgrounds), "what" is meant by iden-tity (ethnic/heritage/native, conjoined with multiple identities such as national, regional, politicized), "where" experiences are taking place (globalization, differences in how immigrants are defined and viewed across contexts), and the "why" or importance of continuing this work (identity as resilience against mental health risks).
Targeting under-researched in-tersections among the "who-what-where-why" can build knowledge and insight for researchers and practitioners who work with immigrant families, and perhaps for immigrants themselves.
Condensation and crystallization are omnipresent phenomena in nature. The formation of droplets or crystals on a solid surface are familiar processes which, beyond their scientific interest, are required in many technological applications. In recent years, experimental techniques have been developed which allow patterning a substrate with surface domains of molecular thickness, surface area in the mesoscopic scale, and different wettabilities (i.e., different degrees of preference for a substance that is in contact with the substrate). The existence of new patterned surfaces has led to increased theoretical efforts to understand wetting phenomena in such systems.
In this thesis, we deal with some problems related to the equilibrium of phases (e.g., liquid-vapor coexistence) and the kinetics of phase separation in the presence of chemically patterned surfaces. Two different cases are considered: (i) patterned surfaces in contact with liquid and vapor, and (ii) patterned surfaces in contact with a crystalline phase. One of the problems that we have studied is the following: It is widely believed that if air containing water vapor is cooled to its dew point, droplets of water are immediately formed. Although common experience seems to support this view, it is not correct. It is only when air is cooled well below its dew point that the phase transition occurs immediately. A vapor cooled slightly below its dew point is in a metastable state, meaning that the liquid phase is more stable than the vapor, but the formation of droplets requires some time to occur, which can be very long.
It was first pointed out by J. W. Gibbs that the metastability of a vapor depends on the energy necessary to form a nucleus (a droplet of a critical size). Droplets smaller than the critical size will tend to disappear, while droplets larger than the critical size will tend to grow. This is consistent with an energy barrier that has its maximum at the critical size, as is the case for droplets formed directly in the vapor or in contact with a chemically uniform planar wall. Classical nucleation theory describes the time evolution of the condensation in terms of the random process of droplet growth through this energy barrier. This process is activated by thermal fluctuations, which eventually will form a droplet of the critical size.
We consider nucleation of droplets from a vapor on a substrate patterned with easily wettable (lyophilic) circular domains. Under certain conditions of pressure and temperature, the condensation of a droplet on a lyophilic circular domain proceeds through a barrier with two maxima (a double barrier). We have extended classical nucleation theory to account for the kinetics of nucleation through a double barrier, and applied this extension to nucleation on lyophilic circular domains.
Climate change heavily threatens forest ecosystems worldwide and there is urgent need to understand what controls tree survival and forests stability.
There is evidence that biodiversity can enhance ecosystem stability (Loreau and de Mazancourt in Ecol Lett 16:106-115, 2013; McCann in Nature 405:228-233, 2000), however it remains largely unclear whether this also holds for climate change and what aspects of biodiversity might be most important.
Here we apply machine learning to outputs of a flexible-trait Dynamic Global Vegetation Model to unravel the effects of enhanced functional tree trait diversity and its sub-components on climate-change resistance of temperate forests (http://www.pik-potsdam.de/similar to billing/video/Forest_Resistance_LPJmLFIT.mp4).
We find that functional tree trait diversity enhances forest resistance. We explain this with 1. stronger complementarity effects (similar to 25% importance) especially improving the survival of trees in the understorey of up to +16.8% (+/- 1.6%) and 2. environmental and competitive filtering of trees better adapted to future climate (40-87% importance).
We conclude that forests containing functionally diverse trees better resist and adapt to future conditions.
In this context, we especially highlight the role of functionally diverse understorey trees as they provide the fundament for better survival of young trees and filtering of resistant tree individuals in the future.
The most profound consequences of the presence of Ca-Mg carbonates (CaCO3-MgCO3) in the Earth's upper mantle may be to lower the melting temperatures of the mantle and control the melt composition.
Low-degree partial melting of a carbonate-bearing mantle produces CO2-rich, silica-poor melts compositionally imposed by the melting relations of carbonates.
Thus, understanding the melting relations in the CaCO3-MgCO3 system facilitates the interpretation of natural carbonate-bearing silicate systems.
We report the melting relations of the CaCO3-MgCO3 system and the partition coefficient of trace elements between carbonates and carbonate melt from experiments at high pressure (6 and 9 GPa) and temperature (1300-1800 degrees C) using a rocking multi-anvil press. In the absence of water, Ca-Mg carbonates are stable along geothermal gradients typical of subducting slabs.
Ca-Mg carbonates ( similar to Mg0.1-0.9Ca0.9-0.1CO3) partially melt beneath mid-ocean ridges and in plume settings. Ca-Mg carbonates melt incongruently, forming periclase crystals and carbonate melt between 4 and 9 GPa.
Furthermore, we show that the rare earth element (REE) signature of Group-I kimberlites, namely strong REE fractionation and depletion of heavy REE relative to the primitive mantle, is resembled by carbonate melt in equilibrium with Ca-bearing magnesite and periclase at 6 and 9 GPa.
This suggests that the dolomite-magnesite join of the CaCO3-MgCO3 system might be useful to approximate the REE signature of carbonate-rich melts parental to kimberlites.
A metagenome-assembled genome (MAG), named Methanosarcina sp. strain ERenArc_MAG2, was obtained from a 3-month-old H-2/CO2 atmosphere enrichment culture, originally inoculated with 60-m deep drill core sediment collected from the tectonic Eger Rift terrestrial subsurface.
Annotation of the recovered draft genome revealed putative archaeal methanogenesis genes in the deep biosphere.
A metagenome-assembled genome (MAG), named Methanosarcina sp. strain ERenArc_MAG2, was obtained from a 3-month-old H-2/CO2 atmosphere enrichment culture, originally inoculated with 60-m deep drill core sediment collected from the tectonic Eger Rift terrestrial subsurface.
Annotation of the recovered draft genome revealed putative archaeal methanogenesis genes in the deep biosphere.
Non-alcoholic fatty liver disease (NAFLD) is characterized by excessive lipid accumulation in the liver.
Various mechanisms such as an increased uptake in fatty acids or de novo synthesis contribute to the development of steatosis and progression to more severe stages. Furthermore, it has been shown that impaired lipophagy, the degradation of lipids by autophagic processes, contributes to NAFLD.
Through an unbiased lipidome analysis of mouse livers in a genetic model of impaired lipophagy, we aimed to determine the resulting alterations in the lipidome. Observed changes overlap with those of the human disease.
Overall, the entire lipid content and in particular the triacylglycerol concentration increased under conditions of impaired lipophagy.
In addition, we detected a reduction in long-chain polyunsaturated fatty acids (PUFAs) and an increased ratio of n-6 PUFAs to n-3 PUFAs, which was due to the depletion of n-3 PUFAs.
Although the abundance of major phospholipid classes was reduced, the ratio of phosphatidylcholines to phosphatidylethanolamines was not affected. In conclusion, this study demonstrates that impaired lipophagy contributes to the pathology of NAFLD and is associated with an altered lipid profile.
However, the lipid pattern does not appear to be specific for lipophagic alterations, as it resembles mainly that described in relation to fatty liver disease.
Microalgae are one of the most promising food source of the future.
Nowadays, extracts of high-value active substances of biomass are business aims for the development of food additives in personalized nutrition, in cosmetics and pharmaceuticals.
A new-patented vertical farming cultivation technology was used for production of Porphyridium purpureum. In this work, microwave assisted extraction was used to extract B-phycoerythrin from Porphyridium purpureum biomass.
Response surface methodology was implemented for optimization.
Numerical optimization established the best point of the experimental domain (biomass/solvent of 16.8 mg/mL, time of 172 s, and temperature of 30 degrees C) with a desirability value of 0.82.
Corresponding experimental responses values of 7.2 mg, 8.5 % and 13,961 PA/mu g biomass were obtained for extracted proteins, extraction yield and extracted B-phycoerythrin, respectively.
Final freeze-dried product indicated protein content of 55 % using Kjeldahl while targeted mass spectrometry analysis revealed that B-phycoerythrin represented 93 % of the total protein.
This vision article outlines the main building blocks of what we term AI Compliance, an effort to bridge two complementary research areas: computer science and the law.
Such research has the goal to model, measure, and affect the quality of AI artifacts, such as data, models, and applications, to then facilitate adherence to legal standards.
DrDimont: explainable drug response prediction from differential analysis of multi-omics networks
(2022)
Motivation:
While it has been well established that drugs affect and help patients differently, personalized drug response predictions remain challenging.
Solutions based on single omics measurements have been proposed, and networks provide means to incorporate molecular interactions into reasoning.
However, how to integrate the wealth of information contained in multiple omics layers still poses a complex problem.
Results:
We present DrDimont, Drug response prediction from Differential analysis of multi-omics networks.
It allows for comparative conclusions between two conditions and translates them into differential drug response predictions.
DrDimont focuses on molecular interactions.
It establishes condition-specific networks from correlation within an omics layer that are then reduced and combined into heterogeneous, multi-omics molecular networks. A novel semi-local, path-based integration step ensures integrative conclusions. Differential predictions are derived from comparing the condition-specific integrated networks.
DrDimont's predictions are explainable, i.e. molecular differences that are the source of high differential drug scores can be retrieved. We predict differential drug response in breast cancer using transcriptomics, proteomics, phosphosite and metabolomics measurements and contrast estrogen receptor positive and receptor negative patients. DrDimont performs better than drug prediction based on differential protein expression or PageRank when evaluating it on ground truth data from cancer cell lines. We find proteomic and phosphosite layers to carry most information for distinguishing drug response.
Genome-scale metabolic models are mathematical representations of all known reactions occurring in a cell. Combined with constraints based on physiological measurements, these models have been used to accurately predict metabolic fluxes and effects of perturbations (e.g. knock-outs) and to inform metabolic engineering strategies. Recently, protein-constrained models have been shown to increase predictive potential (especially in overflow metabolism), while alleviating the need for measurement of nutrient uptake rates. The resulting modelling frameworks quantify the upkeep cost of a certain metabolic flux as the minimum amount of enzyme required for catalysis. These improvements are based on the use of in vitro turnover numbers or in vivo apparent catalytic rates of enzymes for model parameterization. In this thesis several tools for the estimation and refinement of these parameters based on in vivo proteomics data of Escherichia coli, Saccharomyces cerevisiae, and Chlamydomonas reinhardtii have been developed and applied. The difference between in vitro and in vivo catalytic rate measures for the three microorganisms was systematically analyzed. The results for the facultatively heterotrophic microalga C. reinhardtii considerably expanded the apparent catalytic rate estimates for photosynthetic organisms. Our general finding pointed at a global reduction of enzyme efficiency in heterotrophy compared to other growth scenarios. Independent of the modelled organism, in vivo estimates were shown to improve accuracy of predictions of protein abundances compared to in vitro values for turnover numbers. To further improve the protein abundance predictions, machine learning models were trained that integrate features derived from protein-constrained modelling and codon usage. Combining the two types of features outperformed single feature models and yielded good prediction results without relying on experimental transcriptomic data. The presented work reports valuable advances in the prediction of enzyme allocation in unseen scenarios using protein constrained metabolic models. It marks the first successful application of this modelling framework in the biotechnological important taxon of green microalgae, substantially increasing our knowledge of the enzyme catalytic landscape of phototrophic microorganisms.
Seasonal variations in landslide activity remain understudied compared to recent advances in landslide early warning at hourly to daily timescales.
Here, we learn the seasonal pattern of monthly landslide activity in the Pacific Northwest from five heterogeneous landslide inventories with differing spatial and temporal coverage and reporting protocols combined in a Bayesian multi-level model.
We find that landslide activity is distinctly seasonal, with credible increases in landslide intensity, inter-annual variability, and probability marking the onset of the landslide season in November.
Peaks in landslide probability in January and intensity in February lag the annual peak in mean monthly precipitation and landslide activity is more variable in winter than in summer, when landslides are rare.
For a given monthly rainfall, landslide intensity at the season peak in February is up to 10 times higher than at the onset in November, underlining the importance of antecedent seasonal hillslope conditions.
The development of interface technologies is driven by the goal of making interaction more positive through natural action-control mappings.
In Virtual Reality (VR), the entire body is potentially involved for interaction, using such mappings with a maximum of degrees of freedom. The downside is the increase in interaction complexity, which can dramatically influence interface design.
A cognitive perspective on detailed aspects of interaction patterns is lacking in common interface design guidelines, although it can be helpful to make this complexity controllable and, thus, make interaction behavior predictable.
In the present study, the distinction between grounding, embodiment, and situatedness (the GES framework) is applied to organize aspects of interactions and to compare them with each other.
In two experiments, zooming into or out of emotional pictures through changes of arm span was examined in VR. There are qualitatively different aspects during such an interaction: i) perceptual aspects caused by zooming are fundamental for human behavior (Grounding: closer objects appear bigger) and ii) aspects of gestures correspond to the physical characteristics of the agents (Embodiment: little distance of hands signals little or, in contrast, "creating more detail").
The GES-framework sets aspects of Grounding against aspects of Embodiment, thus allowing to predict human behavior regarding these qualitatively different aspects.
For the zooming procedure, the study shows that Grounding can overrule Embodiment in interaction design.
Thus, we propose GES as a cognitive framework that can help to inform interaction guidelines for user interface design in VR.
Sulfur mustard (SM) and its derivatives are potent genotoxic agents, which have been shown to trigger the activation of poly (ADP-ribose) polymerases (PARPs) and the depletion of their substrate, nicotinamide adenine dinucleotide (NAD+). NAD+ is an essential molecule involved in numerous cellular pathways, including genome integrity and DNA repair, and thus, NAD+ supplementation might be beneficial for mitigating mustard-induced (geno)toxicity. In this study, the role of NAD+ depletion and elevation in the genotoxic stress response to SM derivatives, i.e., the monofunctional agent 2-chloroethyl-ethyl sulfide (CEES) and the crosslinking agent mechlorethamine (HN2), was investigated with the use of NAD+ booster nicotinamide riboside (NR) and NAD+ synthesis inhibitor FK866. The effects were analyzed in immortalized human keratinocytes (HaCaT) or monocyte-like cell line THP-1. In HaCaT cells, NR supplementation, increased NAD+ levels, and elevated PAR response, however, did not affect ATP levels or DNA damage repair, nor did it attenuate long- and short-term cytotoxicities. On the other hand, the depletion of cellular NAD+ via FK866 sensitized HaCaT cells to genotoxic stress, particularly CEES exposure, whereas NR supplementation, by increasing cellular NAD+ levels, rescued the sensitizing FK866 effect. Intriguingly, in THP-1 cells, the NR-induced elevation of cellular NAD+ levels did attenuate toxicity of the mustard compounds, especially upon CEES exposure. Together, our results reveal that NAD+ is an important molecule in the pathomechanism of SM derivatives, exhibiting compound-specificity. Moreover, the cell line-dependent protective effects of NR are indicative of system-specificity of the application of this NAD+ booster.
kappa-casein (kappa-CN) is one of the key components in bovine milk, playing a unique role in the structuration of casein micelles.
It contains in its chemical structure up to sixteen amino acid residues (mainly serine and threonine) susceptible to modifications, including glycosylation and phosphorylation, which may further be formed during milk processing.
In this study, changes in post-translational modification (PTM) of kappa-CN during bovine milk fermentation were investigated. One-to-five-day fermented milk samples were produced.
A traditional bottom-up proteomics approach was used to establish a multiple-reaction monitoring (MRM) method for relative quantification of kappa-CN PTM. Endoproteinase Glu-C was found to efficiently digest the kappa-CN molecule.
The developed LC-MS method was validated by performing assessments of linearity, precision, repeatability, reproducibility, limit of detection (LOD), and limit of quantification (LOQ).
Among the yielded peptides, four of them containing serine and threonine residues were identified and the unmodified as well as the modified variants of each of them were relatively quantified. These peptides were (1) IPTINTIASGEPTSTTE ([140, 158]), (2) STVATLE ([162, 168]), (3) DSPE ([169, 172]), and (4) INTVQVTSTAV ([180, 190]). Distribution analysis between unmodified and modified peptides revealed that over 50% of kappa-CN was found in one of its modified forms in milk.
The fermentation process further significantly altered the composition between unmodified/modified kappa-CN, with glycoslaytion being predominant compared to phosphorylation (p < 0.01).
Further method development towards alpha and beta-CN fractions and their PTM behavior would be an asset to better understand the changes undergone by milk proteins and the micellar structure during fermentation.
This international curricular review provides a structured overview of the particle physics content in 27 state, national, and international high-school physics curricula. The review was based on a coding manual that included 60 concepts that were identified as relevant for high-school particle physics education.
Two types of curricula were reviewed, namely curricula with a dedicated particle physics chapter and curricula without a dedicated particle physics chapter.
The results of the curricular review show that particle physics concepts are explicitly or implicitly present in all reviewed curricula.
However, the number of particle physics concepts that are featured in a curriculum varies greatly across the reviewed curricula. We identified core particle physics concepts that can be found in most curricula. Here, elementary particles, fundamental interactions, and charges were identified as explicit particle physics concepts that are featured in more than half of the reviewed curricula either as content or context. Indeed, theoretical particle physics concepts are more prominent in high-school physics curricula than experimental particle physics concepts.
Overall, this international curricular review provides the basis for future curricular development with respect to particle physics and suggests an increased inclusion of experimental particle physics concepts in high-school physics curricula.
Traditionally, business models and software designs used to model the usage of artificial intelligence (AI) at a very specific point in the process or rather fix implemented application. Since applications can be based on AI, such as networked artificial neural networks (ANN) on top of which applications are installed, these on-top applications can be instructed directly from their underlying ANN compartments [1]. However, with the integration of several AI-based systems, their coordination is a highly relevant target factor for the operation and improvement of networked processes, such as they can be found in cross-organizational production contexts spanning multiple distributed locations. This work aims to extend prior research on managing artificial knowledge transfers among interlinked AIs as coordination instrument by examining effects of different activation types (respective activation rates and cycles) on by ANN-instructed production machines. In a design-science-oriented way, this paper conceptualizes rhythmic state descriptions for dynamic systems and associated 14 experiment designs. Two experiments have been realized, analyzed and evaluated thereafter in regard with their activities and processes induced. Findings show that the simulator [2] used and experiments designed and realized, here, (I) enable research on ANN activation types, (II) illustrate ANN-based production networks disrupted by activation types and clarify the need for harmonizing them. Further, (III) management interventions are derived for harmonizing interlinked ANNs. This study establishes the importance of site-specific coordination mechanisms and novel forms of management interventions as drivers of efficient artificial knowledge transfer.
We consider the initial value problem for the Navier-Stokes equations over R-3 x [0, T] with time T > 0 in the spatially periodic setting.
We prove that it induces open injective mappings A(s): B-1(s) -> B-2(s-1) where B-1(s), B-2(s-1) are elements from scales of specially constructed function spaces of Bochner-Sobolev typeparametrized with the smoothness index s is an element of N.
Finally, we prove that a map Asis surjective if and only if the inverse image A(s)(- 1) (K) of any pre compact set K from the range of the map Asis bounded in the Bochner space L-s([0, T], L-r(T-3))with the Ladyzhenskaya-Prodi-Serrin numbers s, r.
With the further development of more and more production machines into cyber-physical systems, and their greater integration with artificial intelligence (AI) techniques, the coordination of intelligent systems is a highly relevant target factor for the operation and improvement of networked processes, such as they can be found in cross-organizational production contexts spanning multiple distributed locations. This work aims to extend prior research on managing their artificial knowledge transfers as coordination instrument by examining effects of different activation types (respective activation rates and cycles) on by Artificial Neural Network (ANN)-instructed production machines. For this, it provides a new integration type of ANN-based cyber-physical production system as a tool to research artificial knowledge transfers: In a design-science-oriented way, a prototype of a simulation system is constructed as Open Source information system which will be used in on-building research to (I) enable research on ANN activation types in production networks, (II) illustrate ANN-based production networks disrupted by activation types and clarify the need for harmonizing them, and (III) demonstrate conceptual management interventions. This simulator shall establish the importance of site-specific coordination mechanisms and novel forms of management interventions as drivers of efficient artificial knowledge transfer.
Online-Nutzer begegnen regelmäßig unterschwelligen manipulativen Designstrategien von Anbietern digitaler Produkte, welche sie zu rechtsgeschäftlich relevanten Entscheidungen bewegen sollen, die sie womöglich nicht - oder zumindest nicht so - beabsichtigt haben. Man spricht in diesem Zusammenhang von (vielgestaltig denkbaren) „Dark Patterns“ (dt. „dunkle Muster“). Der Beitrag geht der Frage nach, inwiefern diese insbesondere lauterkeitsrechtlich zulässig sind.
Information regarding the spatial distribution of soil water content is key in many disciplines and applications including soil and atmospheric sciences, hydrology, and agricultural engineering.
Thus, within the past decades various experimental methods and strategies have been developed to map spatial variations in soil moisture distribution and to monitor temporal changes.
Our study examines the combination of electrical resistivity mapping and point observations of soil moisture to infer the spatial and the temporal variability of soil moisture.
Over a period of around two years, we performed field measurements on six days to collect repeated electrical resistivity mapping data for a nine-hectare test site south-east of Berlin, Germany.
Permanently installed TDR probes, temporary TDR measurements within permanently installed tubes, and gravimetric measurements using soil samples provided soil moisture data at various selected points.
In addition, soil analysis and classification results are available for 132 regularly distributed positions up to depths of 1.2 m.
We compare and link three-dimensional resistivity models obtained via data inversion to soil composition and soil moisture as provided by our point data.
Both the soil samples and the resistivity models indicate a two-layer medium characterized by a sandy top layer with varying thickness and a loamy bottom soil.
For all six field campaigns, we observe similar resistivity patterns reflecting the temporally stable influence of soil texture.
While the overall patterns are stable, the range of resistivity values changes with soil moisture. Finally, to estimate spatial models of soil moisture, we link our soil moisture and resistivity data using empirical petrophysical models relying on a second order polynomial function.
We observe a mean prediction error for soil moisture of +/-0.034 m3 & BULL; m? 3 using all observation points while we notice that point-specific models further reduce the error.
Thus, we conclude that our experimental and data analysis strategies represent a reliable approach to establish site-specific models and to estimate three-dimensional moisture distribution including temporal variations.
The work is devoted to the use of electrokinetic phenomena in liquid crystals to create a new class of microfluidics devices - optofluidics, designed to control electromagnetic radiation, including the THz frequency range.
To achieve the goal, an optical method is used to study changes in the orientational structure in LC layers caused by a shear flow generated by electroosmotic pumps. Simula-tion of LC behaviour in an experimental cell containing electroosmotic pumps and flat layers of a nematic liquid crystal is fulfilled.
The experimental depend-ences of the intensity of polarized radiation passing through flat LC layers on the control voltage applied to the electroosmotic pump and the results of calcu-lations of the hydrodynamic and mechano-optical characteristics of the experi-mental LC cell are presented.
The propagation of THz irradiation across the multilayer structure of the optofluidic cell is considered taking into account the minimum number of re-reflections of waves from different layers and the ab-sorption of THz irradiation in a propylene and a liquid crystal.