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V-Edge
(2022)
As we move from 5G to 6G, edge computing is one of the concepts that needs revisiting. Its core idea is still intriguing: Instead of sending all data and tasks from an end user's device to the cloud, possibly covering thousands of kilometers and introducing delays lower-bounded by propagation speed, edge servers deployed in close proximity to the user (e.g., at some base station) serve as proxy for the cloud. This is particularly interesting for upcoming machine-learning-based intelligent services, which require substantial computational and networking performance for continuous model training. However, this promising idea is hampered by the limited number of such edge servers. In this article, we discuss a way forward, namely the V-Edge concept. V-Edge helps bridge the gap between cloud, edge, and fog by virtualizing all available resources including the end users' devices and making these resources widely available. Thus, V-Edge acts as an enabler for novel microservices as well as cooperative computing solutions in next-generation networks. We introduce the general V-Edge architecture, and we characterize some of the key research challenges to overcome in order to enable wide-spread and intelligent edge services.
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.
Virtual reality promises high potential as an immersive, hands-on learning tool for training 21st-century skills. However, previous research revealed that the mere use of digital tools in higher education does not automatically translate into learning outcomes. Instead, information systems studies emphasized the importance of effective use behavior to achieve technology usage goals. Applying the affordance network approach, we investigated what constitutes effective usage behavior regarding a virtual reality collaboration system in digital education. Therefore, we conducted 18 interviews with students and observations of six course sessions. The results uncover how affordance actualization contributed to the achievement of learning goals. A comparison with findings of previous studies on other information systems (i.e., electronic medical record systems, big data analytics, fitness wearables) allowed us to highlight system-specific differences in effective use behavior. We also demonstrated a clear distinction between concepts surrounding effective use theory facilitating the application of the affordance network approach in information systems research.
Mastery is a psychological resource that is defined as the extent to which individuals perceive having control over important circumstances of their lives. Although mastery has been associated with various physical and psychological health outcomes, studies assessing its relationship with weight status and dietary behavior are lacking. The aim of this cross-sectional study was to assess the relationship between mastery and weight status, food intake, snacking, and eating disorder (ED) symptoms in the NutriNet-Sante cohort study. Mastery was measured with the Pearlin Mastery Scale (PMS) in 32,588 adults (77.45% female), the mean age was 50.04 (14.53) years. Height and weight were self-reported. Overall diet quality and food group consumption were evaluated with >= 3 self-reported 24-h dietary records (range: 3-27). Snacking was assessed with an ad-hoc question. ED symptoms were assessed with the Sick-Control-One-Fat-Food Questionnaire (SCOFF). Linear and logistic regression analyses were conducted to assess the relationship between mastery and weight status, food intake, snacking, and ED symptoms, controlling for sociodemographic and lifestyle characteristics. Females with a higher level of mastery were less likely to be underweight (OR: 0.88; 95%CI: 0.84, 0.93), overweight [OR: 0.94 (0.91, 0.97)], or obese [class I: OR: 0.86 (0.82, 0.90); class II: OR: 0.76 (0.71, 0.82); class III: OR: 0.77 (0.69, 0.86)]. Males with a higher level of mastery were less likely to be obese [class III: OR: 0.75 (0.57, 0.99)]. Mastery was associated with better diet quality overall, a higher consumption of fruit and vegetables, seafood, wholegrain foods, legumes, non-salted oleaginous fruits, and alcoholic beverages and with a lower consumption of meat and poultry, dairy products, sugary and fatty products, milk-based desserts, and sweetened beverages. Mastery was also associated with lower snacking frequency [OR: 0.89 (0.86, 0.91)] and less ED symptoms [OR: 0.73 (0.71, 0.75)]. As mastery was associated with favorable dietary behavior and weight status, targeting mastery might be a promising approach in promoting healthy behaviors.
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.
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.
Earthquake source parameters such as seismic stress drop and corner frequency are observed to vary widely, leading to persistent discussion on potential scaling of stress drop and event size. Physical mechanisms that govern stress drop variations arc difficult to evaluate in nature and are more readily studied in controlled laboratory experiments. We perform two stick-slip experiments on fractured (rough) and cut (smooth) Westerly granite samples to explore fault roughness effects on acoustic emission (AE) source parameters. We separate large stick-slip events that generally saturate the seismic recording system from populations of smaller AE events which are sensitive to fault stresses prior to slip. AE event populations show many similarities to natural seismicity and may be interpreted as laboratory equivalent of natural microseismic events. We then compare the temporal evolution of mechanical data such as measured stress release during slip to temporal changes in stress drops derived from Alis using the spectral ratio technique. We report on two primary observations: (1) In contrast to most case studies for natural earthquakes, we observe a strong increase in seismic stress drop with AE size. (2) The scaling of stress drop with magnitude is governed by fault roughness, whereby the rough fault shows a more rapid increase of the stress drop magnitude relation with progressing large stick-slip events than the smooth fault. The overall range of AE sizes on the rough surface is influenced by both the average grain size and the width of the fault core. The magnitudes of the smallest AE events on smooth faults may also be governed by grain size. However, AEs significantly grow beyond peak roughness and the width of the fault core. Our laboratory tests highlight that source parameters vary substantially in the presence of fault zone heterogeneity (i.e. roughness and narrow grain size distribution), which may affect seismic energy partitioning and static stress drops of small and large AE events.
The study of diamond frogs (genus Rhombophryne, endemic to Madagascar) has been historically hampered by the paucity of available specimens, because of their low detectability in the field. Over the last 10 years, 13 new taxa have been described, and 20 named species are currently recognized. Nevertheless, undescribed diversity within the genus is probably large, calling for a revision of the taxonomic identification of published records and an update of the known distribution of each lineage. Here we generate DNA sequences of the mitochondrial 16S rRNA gene of all specimens available to us, revise the genetic data from public databases, and report all deeply divergent mitochondrial lineages of Rhombophryne identifiable from these data. We also generate a multi-locus dataset (including five mitochondrial and eight nuclear markers; 9844 bp) to infer a species-level phylogenetic hypothesis for the diversification of this genus and revise the distribution of each lineage. We recognize a total of 10 candidate species, two of which are identified here for the first time. The genus Rhombophryne is here proposed to be divided into six main species groups, and phylogenetic relationships among some of them are not fully resolved. These frogs are primarily distributed in northern Madagascar, and most species are known from only few localities. A previous record of this genus from the Tsingy de Bemaraha (western Madagascar) is interpreted as probably due to a mislabelling and should not be considered further unless confirmed by new data. By generating this phylogenetic hypothesis and providing an updated distribution of each lineage, our findings will facilitate future species descriptions, pave the way for evolutionary studies, and provide valuable information for the urgent conservation of diamond frogs.
Providing students with efficient instruction tailored to their individual characteristics in the cognitive and affective domains is an important goal in research on computer-based learning. This is especially important when seeking to enhance students' learning experience, such as by counteracting boredom, a detrimental emotion for learning. However, studies comparing instructional strategies triggered by either cognitive or emotional characteristics are surprisingly scarce. In addition, little research has examined the impact of these types of instructional strategies on performance and boredom trajectories within a lesson. In the present study, we compared the effectiveness of an intelligent tutoring system that adapted variable levels of hint details to a combination of students' dynamic, self-reported emotions and task performance (i.e., the experimental condition) to a traditional hint delivery approach consisting of a progressive, incremental supply of details following students' failures (i.e., the control condition). Linear mixed models of time-related changes in task performance and the intensity of boredom over two 1-h sessions showed that students (N = 104) in the two conditions exhibited equivalent progression in task performance and similar trajectories in boredom intensity. However, a consideration of students' achievement levels in the analyses (i.e., their final performance on the task) revealed that higher achievers in the experimental condition showed a reduction in boredom during the first session, suggesting possible benefits of using emotional information to increase the contingency of the hint delivery strategy and improve students’ learning experience.
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.
We would like to inform the readers and editors of the journal that we have discovered some errors in the references of our paper. These errors were brought to our attention by a reader who noticed some inconsistencies between the citations in the text and the bibliography. Upon further investigation, we realized that our literature management software had mistakenly linked some of the references to wrong or non-existent sources. We apologize for this oversight and assure you that it did not affect the validity or quality of our arguments and results, which were based on the correct sources. Below you find a list of the incorrect references along with their corresponding correct ones. We hope that this correction statement will clarify any confusion or misunderstanding that may have arisen from this mistake. The authors would like to apologise for any inconvenience caused.
Purpose
This study investigates the communication behavior of public health organizations on Twitter during the COVID-19 vaccination campaign in Brazil. It contributes to the understanding of the organizational framing of health communication by showcasing several instances of framing devices that borrow from (Brazilian) internet culture. The investigation of this case extends the knowledge by providing a rich description of the organizational framing of health communication to combat misinformation in a politically charged environment.
Design/methodology/approach
The authors collected a Twitter dataset of 77,527 tweets and analyzed a purposeful subsample of 536 tweets that contained information provided by Brazilian public health organizations about COVID-19 vaccination campaigns. The data analysis was carried out quantitatively and qualitatively by combining social media analytics techniques and frame analysis.
Findings
The analysis showed that Brazilian health organizations used several framing devices that have been identified by previous literature such as hashtags, links, emojis or images. However, the analysis also unearthed hitherto unknown visual framing devices for misinformation prevention and debunking that borrow from internet culture such as “infographics,” “pop culture references” and “internet-native symbolism.”
Research limitations/implications
First, the identification of framing devices relating to internet culture add to our understanding of the so far little addressed framing of misinformation combat messages. The case of Brazilian health organizations provides a novel perspective to knowledge by offering a notion of internet-native symbols (e.g. humor, memes) and popular culture references for misinformation combat, including misinformation prevention. Second, this study introduces a frontier of political contextualization to misinformation research that does not relate to the partisanship of the spreaders but that relates to the political dilemmas of public organizations with a commitment to provide accurate information to citizens.
Practical implications
The findings inform decision-makers and public health organizations about framing devices that are tailored to internet-native audiences and can guide strategies to carry out information campaigns in misinformation-laden social media environments.
Social implications
The findings of this case study expose the often-overlooked cultural peculiarities of framing information campaigns on social media. The report of this study from a country in the Global South helps to contrast several assumptions and strategies that are prevalent in (health) discourses in Western societies and scholarship.
Originality/value
This study uncovers unconventional and barely addressed framing devices of health organizations operating in Brazil, which provides a novel perspective to the body of research on misinformation. It contributes to existing knowledge about frame analysis and broadens the understanding of frame devices borrowing from internet culture. It is a call for a frontier in misinformation research that deals with internet culture as part of organizational strategies for successful misinformation combat.
Purpose
Kettle holes are small inland water bodies known to be dominated by terrigenous material; however, the processes and structures that drive the enrichment and depletion of specific geochemical elements in the water column and kettle hole sediment remain unclear. We hypothesized that the mobile elements (Ca, Fe, K, P) behave different from each other in their transport, intermediate soil retention, and final accumulation in the kettle hole sediment.
Methods
Topsoils from transects spanning topographic positions from erosional to depositional areas, sediment cores, shallow groundwater, and kettle hole water of two glacial kettle holes in NE Germany (Rittgarten (RG) and Kraatz (KR)) were collected. The Fe, Ca, K, and total P (TP) concentrations were quantified and additionally the major anions in shallow groundwater and kettle hole water. The element-specific mobilization, relocation, and, finally, accumulation in the sediment were investigated by enrichment factors. Furthermore, a piper diagram was used to estimate groundwater flow directions and pond-internal processes.
Results
At KR only, the upper 10 cm of the kettle hole sediment reflected the relative element composition of the eroded terrestrial soils. The sediment from both kettle holes was enriched in Ca, Fe, K, and P compared to topsoils, indicating several possible processes including the input of clay and silt sized particles enriched in these elements, fertilizer input, and pond-internal processes including biogenic calcite and hydroxyapatite precipitation, Fe-P binding (KR), FeSx formation (RG), and elemental fixation and deposition via floating macrophytes (RG). High Ca concentrations in the kettle hole water indicated a high input of Ca from shallow groundwater inflow, while Ca precipitation in the kettle hole water led to lower Ca concentration in groundwater outflow.
Conclusions
The considerable element losses in the surrounding soils and the inputs into the kettle holes should be addressed by comprehensive soil and water protection measures, i.e., avoiding tillage, fertilizing conservatively, and creating buffer zones.
Examining the dissemination of evidence on social media, we analyzed the discourse around eight visible scientists in the context of COVID-19. Using manual (N = 1,406) and automated coding (N = 42,640) on an account-based tracked Twitter/X dataset capturing scientists’ activities and eliciting reactions over six 2-week periods, we found that visible scientists’ tweets included more scientific evidence. However, public reactions contained more anecdotal evidence. Findings indicate that evidence can be a message characteristic leading to greater tweet dissemination. Implications for scientists, including explicitly incorporating scientific evidence in their communication and examining evidence in science communication research, are discussed.
Simple Summary Gliomas are heterogenous types of cancer, therefore the therapy should be personalized and targeted toward specific pathways. We developed a methodology that corrected strong batch effects from The Cancer Genome Atlas datasets and estimated glioma grade-specific co-enrichment mechanisms using machine learning. Our findings created hypotheses for annotations, e.g., pathways, that should be considered as therapeutic targets. Gliomas develop and grow in the brain and central nervous system. Examining glioma grading processes is valuable for improving therapeutic challenges. One of the most extensive repositories storing transcriptomics data for gliomas is The Cancer Genome Atlas (TCGA). However, such big cohorts should be processed with caution and evaluated thoroughly as they can contain batch and other effects. Furthermore, biological mechanisms of cancer contain interactions among biomarkers. Thus, we applied an interpretable machine learning approach to discover such relationships. This type of transparent learning provides not only good predictability, but also reveals co-predictive mechanisms among features. In this study, we corrected the strong and confounded batch effect in the TCGA glioma data. We further used the corrected datasets to perform comprehensive machine learning analysis applied on single-sample gene set enrichment scores using collections from the Molecular Signature Database. Furthermore, using rule-based classifiers, we displayed networks of co-enrichment related to glioma grades. Moreover, we validated our results using the external glioma cohorts. We believe that utilizing corrected glioma cohorts from TCGA may improve the application and validation of any future studies. Finally, the co-enrichment and survival analysis provided detailed explanations for glioma progression and consequently, it should support the targeted treatment.
We present the discovery of a new double-detonation progenitor system consisting of a hot subdwarf B (sdB) binary with a white dwarf companion with a P (orb) = 76.34179(2) minutes orbital period. Spectroscopic observations are consistent with an sdB star during helium core burning residing on the extreme horizontal branch. Chimera light curves are dominated by ellipsoidal deformation of the sdB star and a weak eclipse of the companion white dwarf. Combining spectroscopic and light curve fits, we find a low-mass sdB star, M (sdB) = 0.383 +/- 0.028 M (circle dot) with a massive white dwarf companion, M (WD) = 0.725 +/- 0.026 M (circle dot). From the eclipses we find a blackbody temperature for the white dwarf of 26,800 K resulting in a cooling age of approximate to 25 Myr whereas our MESA model predicts an sdB age of approximate to 170 Myr. We conclude that the sdB formed first through stable mass transfer followed by a common envelope which led to the formation of the white dwarf companion approximate to 25 Myr ago. Using the MESA stellar evolutionary code we find that the sdB star will start mass transfer in approximate to 6 Myr and in approximate to 60 Myr the white dwarf will reach a total mass of 0.92 M (circle dot) with a thick helium layer of 0.17 M (circle dot). This will lead to a detonation that will likely destroy the white dwarf in a peculiar thermonuclear supernova. PTF1 J2238+7430 is only the second confirmed candidate for a double-detonation thermonuclear supernova. Using both systems we estimate that at least approximate to 1% of white dwarf thermonuclear supernovae originate from sdB+WD binaries with thick helium layers, consistent with the small number of observed peculiar thermonuclear explosions.
The West Burma Terrane (WBT) is a small terrane bounded to the east by the Asian Sibumasu Block and to the west by the Indo-Burman Ranges (IBR), the latter being an exhumed accretionary prism that formed during subduction of Indian oceanic lithosphere beneath Asia. Understanding the geological history of the WBT is important for reconstruction of the closure history of the Tethys Ocean and India-Asia collision. Currently there are major discrepancies in the proposed timings of collision between the WBT with both India and Asia; whether the WBT collided with India or Asia first is debated, and proposed timings of collisions stretch from the Mesozoic to the Cenozoic. We undertook a multi-technique provenance study involving petrography, detrital zircon U-Pb and Hf analyses, rutile U-Pb analyses and Sr-Nd bulk rock analyses on sediments of the Central Myanmar Basins of the WBT. We determined that the first arrival of Asian material into the basin occurred after the earliest late Eocene and by the early Oligocene, thus placing a minimum constraint on the timing of WBT-Asia collision. Our low temperature thermochronological study of the IBR records two periods of exhumation, in the early-middle Eocene, and at the Oligo-Miocene boundary. The Eocene event may be associated with the collision of the WBT with India. The later event at the Oligo-Miocene boundary may be associated with changes in wedge dynamics resulting from increased sediment supply to the system; however a number of other possible causes provide equally plausible explanations for both events.
The aim of this study was to investigate the effects of listening to preferred music during a warm up or exercise, on performance during a 6-min all-out exercise test (6-MT) in young adult males. Twenty-five healthy males volunteered to participate in this study. Following a within subject design, participants performed three test conditions (MDT: music during the test; MDW: music during the warm-up; WM: without music) in random order. Outcomes included mean running speed over the 6-min test (MRS6), total distance covered (TDC), heart rate responses (HRpeak, HRmean), blood lactate (3-min after the test), and the rating of perceived exertion (RPE); additionally, feeling scale scores were recorded. Listening to preferred music during running resulted in significant TDC (Delta up arrow 10%, p=0.006, ES=0.80) and MRS6 (Delta up arrow 14%, p=0.012, ES=1.02) improvement during the 6-MT, improvement was also noted for the warm-up with music condition (TDC:Delta up arrow 8%, p=0.028, ES=0.63; MRS6:Delta up arrow 8%, p=0.032, ES=0.61). A similar reverse "J-shaped" pacing profile was detected during the three conditions. Blood lactate was lower in the MDT condition by 8% (p=0.01, ES=1.10), but not the MDW condition, compared to MW. In addition, no statistically significant differences were found between the test sessions for the HR, RPE, and feeling scale scores. In conclusion, listening to music during exercise testing would be more beneficial for optimal TDC and MRS6 performances compared to MDW and WM.
This study focuses on three key aspects: (a) crude throat swab samples in a viral transport medium (VTM) as templates for RT-LAMP reactions; (b) a biotinylated DNA probe with enhanced specificity for LFA readouts; and (c) a digital semi-quantification of LFA readouts. Throat swab samples from SARS-CoV-2 positive and negative patients were used in their crude (no cleaning or pre-treatment) forms for the RT-LAMP reaction. The samples were heat-inactivated but not treated for any kind of nucleic acid extraction or purification. The RT-LAMP (20 min processing time) product was read out by an LFA approach using two labels: FITC and biotin. FITC was enzymatically incorporated into the RT-LAMP amplicon with the LF-LAMP primer, and biotin was introduced using biotinylated DNA probes, specifically for the amplicon region after RT-LAMP amplification. This assay setup with biotinylated DNA probe-based LFA readouts of the RT-LAMP amplicon was 98.11% sensitive and 96.15% specific. The LFA result was further analysed by a smartphone-based IVD device, wherein the T-line intensity was recorded. The LFA T-line intensity was then correlated with the qRT-PCR Ct value of the positive swab samples. A digital semi-quantification of RT-LAMP-LFA was reported with a correlation coefficient of R2 = 0.702. The overall RT-LAMP-LFA assay time was recorded to be 35 min with a LoD of three RNA copies/µL (Ct-33). With these three advancements, the nucleic acid testing-point of care technique (NAT-POCT) is exemplified as a versatile biosensor platform with great potential and applicability for the detection of pathogens without the need for sample storage, transportation, or pre-processing.
Urbanization promotes specific bacteria in freshwater microbiomes including potential pathogens
(2022)
Freshwater ecosystems are characterized by complex and highly dynamic microbial communities that are strongly structured by their local environment and biota. Accelerating urbanization and growing city populations detrimentally alter freshwater environments. To determine differences in freshwater microbial communities associated with urban-ization, full-length 16S rRNA gene PacBio sequencing was performed in a case study from surface waters and sedi-ments from a wastewater treatment plant, urban and rural lakes in the Berlin-Brandenburg region, Northeast Germany. Water samples exhibited highly habitat specific bacterial communities with multiple genera showing clear urban signatures. We identified potentially harmful bacterial groups associated with environmental parameters specific to urban habitats such as Alistipes, Escherichia/Shigella, Rickettsia and Streptococcus. We demonstrate that urban-ization alters natural microbial communities in lakes and, via simultaneous warming and eutrophication and creates favourable conditions that promote specific bacterial genera including potential pathogens. Our findings are evidence to suggest an increased potential for long-term health risk in urbanized waterbodies, at a time of rapidly expanding global urbanization. The results highlight the urgency for undertaking mitigation measures such as targeted lake restoration projects and sustainable water management efforts.
The physiological dependence of animals on dietary intake of vitamins, amino acids, and fatty acids is ubiquitous. Sharp differences in the availability of these vital dietary biomolecules among different resources mean that consumers must adopt a range of strategies to meet their physiological needs. We review the emerging work on omega-3 long-chain polyunsaturated fatty acids, focusing predominantly on predator-prey interactions, to illustrate that trade-off between capacities to consume resources rich in vital biomolecules and internal synthesis capacity drives differences in phenotype and fitness of consumers. This can then feedback to impact ecosystem functioning. We outline how focus on vital dietary biomolecules in eco-eco-devo dynamics can improve our understanding of anthropogenic changes across multiple levels of biological organization.
The study addresses the question, if observed changes in terms of Arctic-midlatitude linkages during winter are driven by Arctic Sea ice decline alone or if the increase of global sea surface temperatures plays an additional role. We compare atmosphere-only model experiments with ECHAM6 to ERA-Interim Reanalysis data. The model sensitivity experiment is implemented as a set of four combinations of sea ice and sea surface temperature boundary conditions. Atmospheric circulation regimes are determined and evaluated in terms of their cyclone and blocking characteristics and changes in frequency during winter. As a prerequisite, ECHAM6 reproduces general features of circulation regimes very well. Tropospheric changes induced by the change of boundary conditions are revealed and further impacts on the large-scale circulation up into the stratosphere are investigated. In early winter, the observed increase of atmospheric blocking in the region between Scandinavia and the Urals are primarily related to the changes in sea surface temperatures. During late winter, we f nd a weakened polar stratospheric vortex in the reanalysis that further impacts the troposphere. In the model sensitivity study a climatologically weakened polar vortex occurs only if sea ice is reduced and sea surface temperatures are increased together. This response is delayed compared to the reanalysis. The tropospheric response during late winter is inconclusive in the model, which is potentially related to the weak and delayed response in the stratosphere. The model experiments do not reproduce the connection between early and late winter as interpreted from the reanalysis. Potentially explaining this mismatch, we identify a discrepancy of ECHAM6 to reproduce the weakening of the stratospheric polar vortex through blocking induced upward propagation of planetary waves.
This paper deals with the long-term behavior of positive operator semigroups on spaces of bounded functions and of signed measures, which have applications to parabolic equations with unbounded coefficients and to stochas-tic analysis. The main results are a Tauberian type theorem characterizing the convergence to equilibrium of strongly Feller semigroups and a generalization of a classical convergence theorem of Doob. None of these results requires any kind of time regularity of the semigroup.
In real-world scene perception, human observers generate sequences of fixations to move image patches into the high-acuity center of the visual field. Models of visual attention developed over the last 25 years aim to predict two-dimensional probabilities of gaze positions for a given image via saliency maps. Recently, progress has been made on models for the generation of scan paths under the constraints of saliency as well as attentional and oculomotor restrictions. Experimental research demonstrated that task constraints can have a strong impact on viewing behavior. Here, we propose a scan-path model for both fixation positions and fixation durations, which include influences of task instructions and interindividual differences. Based on an eye-movement experiment with four different task conditions, we estimated model parameters for each individual observer and task condition using a fully Bayesian dynamical modeling framework using a joint spatial-temporal likelihood approach with sequential estimation. Resulting parameter values demonstrate that model properties such as the attentional span are adjusted to task requirements. Posterior predictive checks indicate that our dynamical model can reproduce task differences in scan-path statistics across individual observers.
INTRODUCTION:
We investigated the impact of changes in lifestyle habits on colorectal cancer (CRC) risk in a multicountry European cohort.
METHODS:
We used baseline and follow-up questionnaire data from the European Prospective Investigation into Cancer cohort to assess changes in lifestyle habits and their associations with CRC development. We calculated a healthy lifestyle index (HLI) score based on smoking status, alcohol consumption, body mass index, and physical activity collected at the 2 time points. HLI ranged from 0 (most unfavorable) to 16 (most favorable). We estimated the association between HLI changes and CRC risk using Cox regression models and reported hazard ratios (HR) with 95% confidence intervals (CI).
RESULTS:
Among 295,865 participants, 2,799 CRC cases were observed over a median of 7.8 years. The median time between questionnaires was 5.7 years. Each unit increase in HLI from the baseline to the follow-up assessment was associated with a statistically significant 3% lower CRC risk. Among participants in the top tertile at baseline (HLI > 11), those in the bottom tertile at follow-up (HLI <= 9) had a higher CRC risk (HR 1.34; 95% CI 1.02-1.75) than those remaining in the top tertile. Among individuals in the bottom tertile at baseline, those in the top tertile at follow-up had a lower risk (HR 0.77; 95% CI 0.59-1.00) than those remaining in the bottom tertile.
DISCUSSION:
Improving adherence to a healthy lifestyle was inversely associated with CRC risk, while worsening adherence was positively associated with CRC risk. These results justify and support recommendations for healthy lifestyle changes and healthy lifestyle maintenance for CRC prevention.
We consider a system of noninteracting particles on a line with initial positions distributed uniformly with density ? on the negative half-line. We consider two different models: (i) Each particle performs independent Brownian motion with stochastic resetting to its initial position with rate r and (ii) each particle performs run -and-tumble motion, and with rate r its position gets reset to its initial value and simultaneously its velocity gets randomized. We study the effects of resetting on the distribution P(Q, t) of the integrated particle current Q up to time t through the origin (from left to right). We study both the annealed and the quenched current distributions and in both cases, we find that resetting induces a stationary limiting distribution of the current at long times. However, we show that the approach to the stationary state of the current distribution in the annealed and the quenched cases are drastically different for both models. In the annealed case, the whole distribution P-an(Q, t) approaches its stationary limit uniformly for all Q. In contrast, the quenched distribution P-qu(Q, t) attains its stationary form for Q < Q(crit)(t), while it remains time dependent for Q > Q(crit)(t). We show that Q(crit)(t) increases linearly with t for large t. On the scale where Q <; Q(crit)(t), we show that P-qu(Q, t) has an unusual large deviation form with a rate function that has a third-order phase transition at the critical point. We have computed the associated rate functions analytically for both models. Using an importance sampling method that allows to probe probabilities as tiny as 10-14000, we were able to compute numerically this nonanalytic rate function for the resetting Brownian dynamics and found excellent agreement with our analytical prediction.
The capillary-venous pathology cerebral cavernous malformation (CCM) is caused by loss of CCM1/Krev interaction trapped protein 1 (KRIT1), CCM2/MGC4607, or CCM3/PDCD10 in some endothelial cells. Mutations of CCM genes within the brain vasculature can lead to recurrent cerebral hemorrhages. Pharmacological treatment options are urgently needed when lesions are located in deeply-seated and in-operable regions of the central nervous system. Previous pharmacological suppression screens in disease models of CCM led to the discovery that treatment with retinoic acid improved CCM phenotypes. This finding raised a need to investigate the involvement of retinoic acid in CCM and test whether it has a curative effect in preclinical mouse models. Here, we show that components of the retinoic acid synthesis and degradation pathway are transcriptionally misregulated across disease models of CCM. We complemented this analysis by pharmacologically modifying retinoic acid levels in zebrafish and human endothelial cell models of CCM, and in acute and chronic mouse models of CCM. Our pharmacological intervention studies in CCM2-depleted human umbilical vein endothelial cells (HUVECs) and krit1 mutant zebrafish showed positive effects when retinoic acid levels were increased. However, therapeutic approaches to prevent the development of vascular lesions in adult chronic murine models of CCM were drug regiment-sensitive, possibly due to adverse developmental effects of this hormone. A treatment with high doses of retinoic acid even worsened CCM lesions in an adult chronic murine model of CCM. This study provides evidence that retinoic acid signaling is impaired in the CCM pathophysiology and suggests that modification of retinoic acid levels can alleviate CCM phenotypes.
Fetal alcohol-spectrum disorder (FASD) is underdiagnosed and often misdiagnosed as attention-deficit/hyperactivity disorder (ADHD). Here, we develop a screening tool for FASD in youth with ADHD symptoms. To develop the prediction model, medical record data from a German University outpatient unit are assessed including 275 patients aged 0-19 years old with FASD with or without ADHD and 170 patients with ADHD without FASD aged 0-19 years old. We train 6 machine learning models based on 13 selected variables and evaluate their performance. Random forest models yield the best prediction models with a cross-validated AUC of 0.92 (95% confidence interval [0.84, 0.99]). Follow-up analyses indicate that a random forest model with 6 variables - body length and head circumference at birth, IQ, socially intrusive behaviour, poor memory and sleep disturbance - yields equivalent predictive accuracy. We implement the prediction model in a web-based app called FASDetect - a user-friendly, clinically scalable FASD risk calculator that is freely available at https://fasdetect.dhc-lab.hpi.de.
Purpose
Due to the increasing application of genome analysis and interpretation in medical disciplines, professionals require adequate education. Here, we present the implementation of personal genotyping as an educational tool in two genomics courses targeting Digital Health students at the Hasso Plattner Institute (HPI) and medical students at the Technical University of Munich (TUM).
Methods
We compared and evaluated the courses and the students ' perceptions on the course setup using questionnaires.
Results
During the course, students changed their attitudes towards genotyping (HPI: 79% [15 of 19], TUM: 47% [25 of 53]). Predominantly, students became more critical of personal genotyping (HPI: 73% [11 of 15], TUM: 72% [18 of 25]) and most students stated that genetic analyses should not be allowed without genetic counseling (HPI: 79% [15 of 19], TUM: 70% [37 of 53]). Students found the personal genotyping component useful (HPI: 89% [17 of 19], TUM: 92% [49 of 53]) and recommended its inclusion in future courses (HPI: 95% [18 of 19], TUM: 98% [52 of 53]).
Conclusion
Students perceived the personal genotyping component as valuable in the described genomics courses. The implementation described here can serve as an example for future courses in Europe.
At the junction of greenhouse and icehouse climate states, the Eocene-Oligocene Transition (EOT) is a key moment in Cenozoic climate history. While it is associated with severe extinctions and biodiversity turnovers on land, the role of terrestrial climate evolution remains poorly resolved, especially the associated changes in seasonality. Some paleobotanical and geochemical continental records in parts of the Northern Hemisphere suggest the EOT is associated with a marked cooling in winter, leading to the development of more pronounced seasons (i.e., an increase in the mean annual range of temperature, MATR). However, the MATR increase has been barely studied by climate models and large uncertainties remain on its origin, geographical extent and impact. In order to better understand and describe temperature seasonality changes between the middle Eocene and the early Oligocene, we use the Earth system model IPSL-CM5A2 and a set of simulations reconstructing the EOT through three major climate forcings: pCO(2) decrease (1120, 840 and 560 ppm), the Antarctic ice-sheet (AIS) formation and the associated sea-level decrease. Our simulations suggest that pCO(2) lowering alone is not sufficient to explain the seasonality evolution described by the data through the EOT but rather that the combined effects of pCO(2) , AIS formation and increased continentality provide the best data-model agreement.pCO(2) decrease induces a zonal pattern with alternating increasing and decreasing seasonality bands particularly strong in the northern high latitudes (up to 8 degrees C MATR increase) due to sea-ice and surface albedo feedback. Conversely, the onset of the AIS is responsible for a more constant surface albedo yearly, which leads to a strong decrease in seasonality in the southern midlatitudes to high latitudes (> 40 degrees S). Finally, continental areas that emerged due to the sea-level lowering cause the largest increase in seasonality and explain most of the global heterogeneity in MATR changes (1MATR) patterns. The Delta MATR patterns we reconstruct are generally consistent with the variability of the EOT biotic crisis intensity across the Northern Hemisphere and provide insights on their underlying mechanisms.
We present a detailed spectroscopic and timing analysis of X-ray observations of the bright pulsar PSR B0656+14. The observations were obtained simultaneously with eROSITA and XMM-Newton during the calibration and performance verification phase of the Spektrum-Roentgen-Gamma mission (SRG). The analysis of the 100 ks deep observation of eROSITA is supported by archival observations of the source, including XMM-Newton, NuSTAR, and NICER. Using XMM-Newton and NICER, we first established an X-ray ephemeris for the time interval 2015 to 2020, which connects all X-ray observations in this period without cycle count alias and phase shifts. The mean eROSITA spectrum clearly reveals an absorption feature originating from the star at 570 eV with a Gaussian sigma of about 70 eV that was tentatively identified in a previous long XMM-Newton observation. A second previously discussed absorption feature occurs at 260-265 eV and is described here as an absorption edge. It could be of atmospheric or of instrumental origin. These absorption features are superposed on various emission components that are phenomenologically described here as the sum of hot (120 eV) and cold (65 eV) blackbody components, both of photospheric origin, and a power law with photon index Gamma = 2 from the magnetosphere. We created energy-dependent light curves and phase-resolved spectra with a high signal-to-noise ratio. The phase-resolved spectroscopy reveals that the Gaussian absorption line at 570 eV is clearly present throughout similar to 60% of the spin cycle, but it is otherwise undetected. Likewise, its parameters were found to be dependent on phase. The visibility of the line strength coincides in phase with the maximum flux of the hot blackbody. If the line originates from the stellar surface, it nevertheless likely originates from a different location than the hot polar cap. We also present three families of model atmospheres: a magnetized atmosphere, a condensed surface, and a mixed model. They were applied to the mean observed spectrum, whose continuum fit the observed data well. The atmosphere model, however, predicts distances that are too short. For the mixed model, the Gaussian absorption may be interpreted as proton cyclotron absorption in a field as high as 10(14) G, which is significantly higher than the field derived from the moderate observed spin-down.
Deriving mechanism-based pharmacodynamic models by reducing quantitative systems pharmacology models
(2023)
Quantitative systems pharmacology (QSP) models integrate comprehensive qualitative and quantitative knowledge about pharmacologically relevant processes. We previously proposed a first approach to leverage the knowledge in QSP models to derive simpler, mechanism-based pharmacodynamic (PD) models. Their complexity, however, is typically still too large to be used in the population analysis of clinical data. Here, we extend the approach beyond state reduction to also include the simplification of reaction rates, elimination of reactions, and analytic solutions. We additionally ensure that the reduced model maintains a prespecified approximation quality not only for a reference individual but also for a diverse virtual population. We illustrate the extended approach for the warfarin effect on blood coagulation. Using the model-reduction approach, we derive a novel small-scale warfarin/international normalized ratio model and demonstrate its suitability for biomarker identification. Due to the systematic nature of the approach in comparison with empirical model building, the proposed model-reduction algorithm provides an improved rationale to build PD models also from QSP models in other applications.
Quantifying the resilience of vegetated ecosystems is key to constraining both present-day and future global impacts of anthropogenic climate change. Here we apply both empirical and theoretical resilience metrics to remotely-sensed vegetation data in order to examine the role of water availability and variability in controlling vegetation resilience at the global scale. We find a concise global relationship where vegetation resilience is greater in regions with higher water availability. We also reveal that resilience is lower in regions with more pronounced inter-annual precipitation variability, but find less concise relationships between vegetation resilience and intra-annual precipitation variability. Our results thus imply that the resilience of vegetation responds differently to water deficits at varying time scales. In view of projected increases in precipitation variability, our findings highlight the risk of ecosystem degradation under ongoing climate change.
Vegetation dynamics depend on both the amount of precipitation and its variability over time. Here, the authors show that vegetation resilience is greater where water availability is higher and where precipitation is more stable from year to year.
Zunz in Prag
(2021)
The paper addresses an under-researched chapter in the history of the Jewish Reform movement which is at the same time a commonly overlooked period in the biography of Leopold Zunz (1794–1886), one of the founding members of Wissenschaft des Judentums. By placing his eight-month appointment as a preacher to the Reform synagogue in Prague in its socio-political and biographical contexts, the article sheds new light at Zunz’s commitment for the religious renewal of Judaism. A schematic comparison between the development of the Reform movement in the German lands and the Habsburg Monarchy, at the beginning of the nineteenth century highlights the role of state involvement into internal Jewish affairs. Finally, the analysis of Zunz’s Synagogenordnung from 1836, according to the original manuscript from the National Library of Israel, allows a re-evaluation of the (Reform) synagogue as an institution for social disciplining of its members.
Der Judenstaat Ararat
(2022)
Finger-based representation of numbers is a high-level cognitive strategy to assist numerical and arithmetic processing in children and adults. It is unclear whether this paradigm builds on simple perceptual features or comprises several attributes through embodiment. Here we describe the development and initial testing of an experimental setup to study embodiment during a finger-based numerical task using Virtual Reality (VR) and a low-cost tactile stimulator that is easy to build. Using VR allows us to create new ways to study finger-based numerical representation using a virtual hand that can be manipulated in ways our hand cannot, such as decoupling tactile and visual stimuli. The goal is to present a new methodology that can allow researchers to study embodiment through this new approach, maybe shedding new light on the cognitive strategy behind the finger-based representation of numbers. In this case, a critical methodological requirement is delivering precisely targeted sensory stimuli to specific effectors while simultaneously recording their behavior and engaging the participant in a simulated experience. We tested the device's capability by stimulating users in different experimental configurations. Results indicate that our device delivers reliable tactile stimulation to all fingers of a participant's hand without losing motion tracking quality during an ongoing task. This is reflected by an accuracy of over 95% in participants detecting stimulation of a single finger or multiple fingers in sequential stimulation as indicated by experiments with sixteen participants. We discuss possible application scenarios, explain how to apply our methodology to study the embodiment of finger-based numerical representations and other high-level cognitive functions, and discuss potential further developments of the device based on the data obtained in our testing.
Perovskite semiconductors are an attractive option to overcome the limitations of established silicon based photovoltaic (PV) technologies due to their exceptional opto-electronic properties and their successful integration into multijunction cells. However, the performance of single- and multijunction cells is largely limited by significant nonradiative recombination at the perovskite/organic electron transport layer junctions. In this work, the cause of interfacial recombination at the perovskite/C-60 interface is revealed via a combination of photoluminescence, photoelectron spectroscopy, and first-principle numerical simulations. It is found that the most significant contribution to the total C-60-induced recombination loss occurs within the first monolayer of C-60, rather than in the bulk of C-60 or at the perovskite surface. The experiments show that the C-60 molecules act as deep trap states when in direct contact with the perovskite. It is further demonstrated that by reducing the surface coverage of C-60, the radiative efficiency of the bare perovskite layer can be retained. The findings of this work pave the way toward overcoming one of the most critical remaining performance losses in perovskite solar cells.
Cosmic-ray neutron sensing (CRNS) allows for the estimation of root-zone soil water content (SWC) at the scale of several hectares. In this paper, we present the data recorded by a dense CRNS network operated from 2019 to 2022 at an agricultural research site in Marquardt, Germany - the first multi-year CRNS cluster. Consisting, at its core, of eight permanently installed CRNS sensors, the cluster was supplemented by a wealth of complementary measurements: data from seven additional temporary CRNS sensors, partly co-located with the permanent ones; 27 SWC profiles (mostly permanent); two groundwater observation wells; meteorological records; and Global Navigation Satellite System reflectometry (GNSS-R). Complementary to these continuous measurements, numerous campaign-based activities provided data by mobile CRNS roving, hyperspectral im-agery via UASs, intensive manual sampling of soil properties (SWC, bulk density, organic matter, texture, soil hydraulic properties), and observations of biomass and snow (cover, depth, and density). The unique temporal coverage of 3 years entails a broad spectrum of hydro-meteorological conditions, including exceptional drought periods and extreme rainfall but also episodes of snow coverage, as well as a dedicated irrigation experiment. Apart from serving to advance CRNS-related retrieval methods, this data set is expected to be useful for vari-ous disciplines, for example, soil and groundwater hydrology, agriculture, or remote sensing. Hence, we show exemplary features of the data set in order to highlight the potential for such subsequent studies. The data are available at doi.org/10.23728/b2share.551095325d74431881185fba1eb09c95 (Heistermann et al., 2022b).
Cell-level systems biology model to study inflammatory bowel diseases and their treatment options
(2023)
To help understand the complex and therapeutically challenging inflammatory bowel diseases (IBDs), we developed a systems biology model of the intestinal immune system that is able to describe main aspects of IBD and different treatment modalities thereof. The model, including key cell types and processes of the mucosal immune response, compiles a large amount of isolated experimental findings from literature into a larger context and allows for simulations of different inflammation scenarios based on the underlying data and assumptions. In the context of a large and diverse virtual IBD population, we characterized the patients based on their phenotype (in contrast to healthy individuals, they developed persistent inflammation after a trigger event) rather than on a priori assumptions on parameter differences to a healthy individual. This allowed to reproduce the enormous diversity of predispositions known to lead to IBD. Analyzing different treatment effects, the model provides insight into characteristics of individual drug therapy. We illustrate for anti-TNF-alpha therapy, how the model can be used (i) to decide for alternative treatments with best prospects in the case of nonresponse, and (ii) to identify promising combination therapies with other available treatment options.
The color red has been implicated in a variety of social processes, including those involving mating. While previous research suggests that women sometimes wear red strategically to increase their attractiveness, the replicability of this literature has been questioned. The current research is a reasonably powered conceptual replication designed to strengthen this literature by testing whether women are more inclined to display the color red 1) during fertile (as compared with less fertile) days of the menstrual cycle, and 2) when expecting to interact with an attractive man (as compared with a less attractive man and with a control condition). Analyses controlled for a number of theoretically relevant covariates (relationship status, age, the current weather). Only the latter hypothesis received mixed support (mainly among women on hormonal birth control), whereas results concerning the former hypothesis did not reach significance. Women (N = 281) displayed more red when expecting to interact with an attractive man; findings did not support the prediction that women would increase their display of red on fertile days of the cycle. Findings thus suggested only mixed replicability for the link between the color red and psychological processes involving romantic attraction. They also illustrate the importance of further investigating the boundary conditions of color effects on everyday social processes.
Background: Patients with subjective cognitive decline (SCD) report memory deterioration and are at an increased risk of converting to Alzheimer's disease (AD) although psychophysical testing does not reveal any cognitive deficit.
Objective: Here, gustatory function is investigated as a potential predictor for an increased risk of progressive cognitive decline indicating higher AD risk in SCD.
Methods: Measures of smell and taste perception as well as neuropsychological data were assessed in patients with subjective cognitive decline (SCD): Subgroups with an increased likelihood of the progression to preclinical AD (SCD+) and those with a lower likelihood (SCD-) were compared to healthy controls (HC), patients with mild cognitive impairment and AD patients. The Sniffin' Sticks test contained 12 items with different qualities and taste was measured with 32 taste stripes (sweet, salty, bitter, sour) of different concentration.
Results: Only taste was able to distinguish between HC/SCD- and SCD+ patients.
Conclusion: This study provides a first hint of taste as a more sensitive marker than smell for detecting preclinical AD in SCD. Longitudinal observation of cognition and pathology are necessary to further evaluate taste perception as a predictor of pathological objective decline in cognition.
Shams et al. report that glioma patients' motor status is predicted accurately by diffusion MRI metrics along the corticospinal tract based on support vector machine method, reaching an overall accuracy of 77%. They show that these metrics are more effective than demographic and clinical variables.
Along tract statistics enables white matter characterization using various diffusion MRI metrics. These diffusion models reveal detailed insights into white matter microstructural changes with development, pathology and function. Here, we aim at assessing the clinical utility of diffusion MRI metrics along the corticospinal tract, investigating whether motor glioma patients can be classified with respect to their motor status. We retrospectively included 116 brain tumour patients suffering from either left or right supratentorial, unilateral World Health Organization Grades II, III and IV gliomas with a mean age of 53.51 +/- 16.32 years. Around 37% of patients presented with preoperative motor function deficits according to the Medical Research Council scale. At group level comparison, the highest non-overlapping diffusion MRI differences were detected in the superior portion of the tracts' profiles. Fractional anisotropy and fibre density decrease, apparent diffusion coefficient axial diffusivity and radial diffusivity increase. To predict motor deficits, we developed a method based on a support vector machine using histogram-based features of diffusion MRI tract profiles (e.g. mean, standard deviation, kurtosis and skewness), following a recursive feature elimination method. Our model achieved high performance (74% sensitivity, 75% specificity, 74% overall accuracy and 77% area under the curve). We found that apparent diffusion coefficient, fractional anisotropy and radial diffusivity contributed more than other features to the model. Incorporating the patient demographics and clinical features such as age, tumour World Health Organization grade, tumour location, gender and resting motor threshold did not affect the model's performance, revealing that these features were not as effective as microstructural measures. These results shed light on the potential patterns of tumour-related microstructural white matter changes in the prediction of functional deficits.
Rivers regulate the global carbon cycle by transferring particulate organic carbon (POC) from terrestrial landscapes to marine sedimentary basins, but the processes controlling the amount and composition of fluvially exported POC are poorly understood. We propose that hydrodynamic sorting processes modify POC fluxes during fluvial transit. We test this hypothesis by studying POC transported along a similar to 1,200 km reach of the Rio Bermejo, Argentina. Nanoscale secondary ion mass spectrometry revealed that POC was either fine, mineral-associated organic matter, or coarse discrete organic particles. Mineral-associated POC is more resistant to oxidation and has a lower particle settling velocity than discrete POC. Consequently, hydraulic sorting and downstream fining amplify the proportion of fine, mineral-associated POC from similar to 55% to similar to 78% over 1,220 km of downstream transit. This suggests that mineral-associated POC has a greater probability of export and preservation in marine basins than plant detritus, which may be oxidized to CO2 during transit.
Background:
Prejudices against minorities can be understood as habitually negative evaluations that are kept in spite of evidence to the contrary. Therefore, individuals with strong prejudices might be dominated by habitual or "automatic" reactions at the expense of more controlled reactions. Computational theories suggest individual differences in the balance between habitual/model-free and deliberative/model-based decision-making.
Methods:
127 subjects performed the two Step task and completed the blatant and subtle prejudice scale.
Results:
By using analyses of choices and reaction times in combination with computational modeling, subjects with stronger blatant prejudices showed a shift away from model-based control. There was no association between these decision-making processes and subtle prejudices.
Conclusion:
These results support the idea that blatant prejudices toward minorities are related to a relative dominance of habitual decision-making. This finding has important implications for developing interventions that target to change prejudices across societies.
Thanks to dedicated long-term missions like Voyager and GOES over the past 50 years, much insight has been gained on the activity of our Sun, the solar wind, its interaction with the interstellar medium, and, thus, about the formation, the evolution, and the structure of the heliosphere. Additionally, with the help of multi-wavelength observations by the Hubble Space Telescope, Kepler, and TESS, we not only were able to detect a variety of extrasolar planets and exomoons but also to study the characteristics of their host stars, and thus became aware that other stars drive bow shocks and astrospheres. Although features like, e.g., stellar winds, could not be measured directly, over the past years several techniques have been developed allowing us to indirectly derive properties like stellar mass-loss rates and stellar wind speeds, information that can be used as direct input to existing astrospheric modeling codes. In this review, the astrospheric modeling efforts of various stars will be presented. Starting with the heliosphere as a benchmark of astrospheric studies, investigating the paleo-heliospheric changes and the Balmer H alpha projections to 1 pc, we investigate the surroundings of cool and hot stars, but also of more exotic objects like neutron stars. While pulsar wind nebulae (PWNs) might be a source of high-energy galactic cosmic rays (GCRs), the astrospheric environments of cool and hot stars form a natural shield against GCRs. Their modulation within these astrospheres, and the possible impact of turbulence, are also addressed. This review shows that all of the presented modeling efforts are in excellent agreement with currently available observations.
Background Host factors such as angiotensin-converting enzyme 2 (ACE2) and the transmembrane protease, serine-subtype-2 (TMPRSS2) are important factors for SARS-CoV-2 infection. Clinical and pre-clinical studies demonstrated that RAAS-blocking agents can be safely used during a SARS-CoV-2 infection but it is unknown if DPP-4 inhibitors or SGLT2-blockers may promote COVID-19 by increasing the host viral entry enzymes ACE2 and TMPRSS2. Methods We investigated telmisartan, linagliptin and empagliflozin induced effects on renal and cardiac expression of ACE2, TMPRSS2 and key enzymes involved in RAAS (REN, AGTR2, AGT) under high-salt conditions in a non-diabetic experimental 5/6 nephrectomy (5/6 Nx) model. In the present study, the gene expression of Ace2, Tmprss2, Ren, Agtr2 and Agt was assessed with qRT-PCR and the protein expression of ACE2 and TMPRSS2 with immunohistochemistry in the following experimental groups: Sham + normal diet (ND) + placebo (PBO); 5/6Nx + ND + PBO; 5/6Nx + high salt-diet (HSD) + PBO; 5/6Nx + HSD + telmisartan; 5/6Nx + HSD + linagliptin; 5/6Nx + HSD + empagliflozin. Results In the kidney, the expression of Ace2 was not altered on mRNA level under disease and treatment conditions. The renal TMPRSS2 levels (mRNA and protein) were not affected, whereas the cardiac level was significantly increased in 5/6Nx rats. Intriguingly, the elevated TMPRSS2 protein expression in the heart was significantly normalized after treatment with telmisartan, linagliptin and empagliflozin. Conclusions Our study indicated that there is no upregulation regarding host factors potentially promoting SARS-CoV-2 virus entry into host cells when the SGLT2-blocker empagliflozin, telmisartan and the DPP4-inhibitor blocker linagliptin are used. The results obtained in a preclinical, experimental non-diabetic kidney failure model need confirmation in ongoing interventional clinical trials.
Changes in snowpack associated with climatic warming has drastic impacts on surface energy balance in the cryosphere. Yet, traditional monitoring techniques, such as punctual measurements in the field, do not cover the full snowpack spatial and temporal variability, which hampers efforts to upscale measurements to the global scale. This variability is one of the primary constraints in model development. In terms of spatial resolution, active microwaves (synthetic aperture radar - SAR) can address the issue and outperform methods based on passive microwaves. Thus, high-spatial-resolution monitoring of snow depth (SD) would allow for better parameterization of local processes that drive the spatial variability of snow. The overall objective of this study is to evaluate the potential of the TerraSAR-X (TSX) SAR sensor and the wave co-polar phase difference (CPD) method for characterizing snow cover at high spatial resolution. Consequently, we first (1) investigate SD and depth hoar fraction (DHF) variability between different vegetation classes in the Ice Creek catchment (Qikiqtaruk/Herschel Island, Yukon, Canada) using in situ measurements collected over the course of a field campaign in 2019; (2) evaluate linkages between snow characteristics and CPD distribution over the 2019 dataset; and (3) determine CPD seasonality considering meteorological data over the 2015-2019 period. SD could be extracted using the CPD when certain conditions are met. A high incidence angle (>30 circle) with a high topographic wetness index (TWI) (>7.0) showed correlation between SD and CPD (R2 up to 0.72). Further, future work should address a threshold of sensitivity to TWI and incidence angle to map snow depth in such environments and assess the potential of using interpolation tools to fill in gaps in SD information on drier vegetation types.