julilili42/papers huggingface dataset:
Decoding bedrock channel morphology using high-resolution topographic data
2022-03-28

&amp;lt;p&amp;gt;The 3D morphology of a river channel is a key control on the resistance experienced by the flow, affecting the channel hydraulics, sediment transport and in-stream habitats. In bedrock channels, the morphology is a combination of multiple components including exposed bedrock, overlying sediment cover, and boulders. Furthermore, the morphology of exposed bedrock is expected to depend on the lithology, rock structure and the dominant erosion processes. In order to improve predictions of flow resistance in bedrock channels, we first need to understand how these different components contribute to the overall bed morphology. Here, we present high-resolution (cm-scale) topographic data collected using terrestrial laser scanning from multiple bedrock channel sections on different lithologies. We compare how roughness varies between these channels, and at different spatial scales. We identify the dominant wavelengths at which roughness occurs, and consider how they correspond to the different channel components. We also consider the extent to which lithology and sediment grain size appears to affect channel morphology and roughness.&amp;lt;/p&amp;gt;
The eROSITA Final Equatorial Depth Survey (eFEDS)
2022-03-29

Context. The eROSITA X-ray telescope on board the Spectrum-Poentgen-Gamma (SPG) observatory combines a large field of view and a large collecting area in the energy range between ~0.2 and ~8.0 keV. This gives the telescope the capability to perform uniform scanning observations of large sky areas. Aims. SRG/eROSITA performed scanning observations of the ~140 square degree eROSITA Final Equatorial Depth Survey field (the eFEDS field) as part of its performance verification phase ahead of the planned four year of all-sky scanning operations. The observing time of eFEDS was chosen to slightly exceed the depth expected in an equatorial field after the completion of the all - sky survey. While verifying the capability of eROSITA to perform large-area uniform surveys and saving as a test and training dataset to establish calibration and data analysis procedures, the eFEDS survey also constitutes the largest contiguous soft X-ray survey at this depth to date, supporting a range of early eROSITA survey science investigations. Here we (i) present a catalogue of detected X-ray sources in the eFEDS field providing information about source positions and extent, as well as fluxes in multiple energy bands, and (ii) document the suite of tools and procedures developed for eROSITA data processing and analysis, which were validated and optimised by the eFEDS work. Methods. The data were fed through a standard data processing pipeline, which appltes X-ray event calibration and provides a set of standard calibrated data products. A mutiti-stage source detection procedure, building in part on experience from XMM-Newton, was optimised and calibrated by performing realistic simulations of the eROSITA eFEDS observations. Source fluxes were computed in multiple standard energy bands by forced point source fitting and aperture photometry. We cross-matched the eROSITA eFEDS source catalogue with previous XMM-ATLAS observations, which confirmed the excellentt agreement of the eROSITA and XMM-ATLAS source fluxes. Astrometric corrections were performed by cross-matching the eROSITA source positions with an optical reference catalogue of quasars. Results. We present a primary catalogue of 27 910 X-ray sources (542 of which are significantly spatially extended) detected in the 0.2–2.3 keV energy range with detection likelihoods ≥6, corresponding to a (point source) flux limit of 6.5 × 10 –15 erg cm –2 s –1 in the 0.5–2.0 keV energy band (80% completeness). A supplementary catalogue contains 4774 low-significance source candidates with detection likelihoods between 5 and 6. In addition, a hard-band sample of 246 sources detected in the energy range 22.3–5.0 keV above a detection likelihood of 10 is provided. In an appendix, we finally describe the dedicated data analysis software package, the eROSITA calibration database, and the standard calibrated data products.
A critical analysis of research methods and experimental models to study working length determination and the performance of apex locators – A narrative review with recommendations for the future
2022-03-29

Abstract Outcome studies have repeatedly shown that the apical endpoint of root canal preparation and filling is a determinate factor for the outcome of root canal treatment. Accurate determination of root canal length enhances the efficacy of chemo‐mechanical disinfection and prevents over‐/under‐instrumentation and over‐/under‐filling in relation to the canal terminus. Long and short root canal fillings are consistently reported to be associated with higher rates of post‐treatment endodontic disease. Although standards for undertaking and reporting diagnostic accuracy studies are available, publications dealing with the determination of root canal length are highly heterogeneous and describe procedures inconsistently. The aim of this review is to critically assess the methodology of publications in the past three decades. The process of planning, performing and analysing working length studies are presented stepwise with suggestions to optimize research methods.
The persistence of students’ academic effort: The unique and combined effects of conscientiousness and individual interest
2022-03-29

The present study was designed to test the CONscientiousness × Interest Compensation (CONIC) model in a longitudinal setting (four time points; N = 3,880 students). For this purpose, we first examined the power of conscientiousness (measured with student and parent reports) and interest in predicting perceived academic effort in three school subjects (Math, German, and English). In a second step, we investigated whether conscientiousness and interest interacted in a compensatory pattern as predicted by the CONIC model. Results showed that conscientiousness and interest significantly and positively predicted future perceived academic effort. In addition, conscientiousness and interest interacted in a compensatory manner, such that interest was less important for perceived academic effort in students who were high in conscientiousness (and vice versa).
Do your eye movements reveal your performance on an IQ test? A study linking eye movements and socio-demographic information to fluid intelligence
2022-03-29

Understanding the main factors contributing to individual differences in fluid intelligence is one of the main challenges of psychology. A vast body of research has evolved from the theoretical framework put forward by Cattell, who developed the Culture-Fair IQ Test (CFT 20-R) to assess fluid intelligence. In this work, we extend and complement the current state of research by analysing the differential and combined relationship between eye-movement patterns and socio-demographic information and the ability of a participant to correctly solve a CFT item. Our work shows that a participant’s eye movements while solving a CFT item contain discriminative information and can be used to predict whether the participant will succeed in solving the test item. Moreover, the information related to eye movements complements the information provided by socio-demographic data when it comes to success prediction. In combination, both types of information yield a significantly higher predictive performance than each information type individually. To better understand the contributions of features related to eye movements and socio-demographic information to predict a participant’s success in solving a CFT item, we employ state-of-the-art explainability techniques and show that, along with socio-demographic variables, eye-movement data. Especially the number of saccades and the mean pupil diameter, significantly increase the discriminating power. The eye-movement features are likely indicative of processing efficiency and invested mental effort. Beyond the specific contribution to research on how eye movements can serve as a means to uncover mechanisms underlying cognitive processes, the findings presented in this work pave the way for further in-depth investigations of factors predicting individual differences in fluid intelligence.
A Second Gamma-Glutamylpolyamine Synthetase, GlnA2, Is Involved in Polyamine Catabolism in Streptomyces coelicolor
2022-03-29

Streptomyces coelicolor is a soil bacterium living in a habitat with very changeable nutrient availability. This organism possesses a complex nitrogen metabolism and is able to utilize the polyamines putrescine, cadaverine, spermidine, and spermine and the monoamine ethanolamine. We demonstrated that GlnA2 (SCO2241) facilitates S. coelicolor to survive under high toxic polyamine concentrations. GlnA2 is a gamma-glutamylpolyamine synthetase, an enzyme catalyzing the first step in polyamine catabolism. The role of GlnA2 was confirmed in phenotypical studies with a glnA2 deletion mutant as well as in transcriptional and biochemical analyses. Among all GS-like enzymes in S. coelicolor, GlnA2 possesses the highest specificity towards short-chain polyamines (putrescine and cadaverine), while its functional homolog GlnA3 (SCO6962) prefers long-chain polyamines (spermidine and spermine) and GlnA4 (SCO1613) accepts only monoamines. The genome-wide RNAseq analysis in the presence of the polyamines putrescine, cadaverine, spermidine, or spermine revealed indication of the occurrence of different routes for polyamine catabolism in S. coelicolor involving GlnA2 and GlnA3. Furthermore, GlnA2 and GlnA3 are differently regulated. From our results, we can propose a complemented model of polyamine catabolism in S. coelicolor, which involves the gamma-glutamylation pathway as well as other alternative utilization pathways.
MRI lung lobe segmentation in pediatric cystic fibrosis patients using a recurrent neural network trained with publicly accessible CT datasets
2022-03-29

Purpose To introduce a widely applicable workflow for pulmonary lobe segmentation of MR images using a recurrent neural network (RNN) trained with chest CT datasets. The feasibility is demonstrated for 2D coronal ultrafast balanced SSFP (ufSSFP) MRI. Methods Lung lobes of 250 publicly accessible CT datasets of adults were segmented with an open‐source CT‐specific algorithm. To match 2D ufSSFP MRI data of pediatric patients, both CT data and segmentations were translated into pseudo‐MR images that were masked to suppress anatomy outside the lung. Network‐1 was trained with pseudo‐MR images and lobe segmentations and then applied to 1000 masked ufSSFP images to predict lobe segmentations. These outputs were directly used as targets to train Network‐2 and Network‐3 with non‐masked ufSSFP data as inputs, as well as an additional whole‐lung mask as input for Network‐2. Network predictions were compared to reference manual lobe segmentations of ufSSFP data in 20 pediatric cystic fibrosis patients. Manual lobe segmentations were performed by splitting available whole‐lung segmentations into lobes. Results Network‐1 was able to segment the lobes of ufSSFP images, and Network‐2 and Network‐3 further increased segmentation accuracy and robustness. The average all‐lobe Dice similarity coefficients were 95.0 ± 2.8 (mean ± pooled SD [%]) and 96.4 ± 2.5, 93.0 ± 2.0; and the average median Hausdorff distances were 6.1 ± 0.9 (mean ± SD [mm]), 5.3 ± 1.1, 7.1 ± 1.3 for Network‐1, Network‐2, and Network‐3, respectively. Conclusion Recurrent neural network lung lobe segmentation of 2D ufSSFP imaging is feasible, in good agreement with manual segmentations. The proposed workflow might provide access to automated lobe segmentations for various lung MRI examinations and quantitative analyses.
Malaria-associated adhesion molecule activation facilitates the destruction of uninfected red blood cells
2022-03-29

Abstract Severe malarial anemia (SMA) is the main cause of malaria-associated infant mortality in malaria endemic countries. One major factor that contributes to SMA is the accumulation of uninfected red blood cells (uRBCs) in the spleen. We report the activation of adhesion molecules Lutheran/basal cell adhesion molecule (Lu/BCAM) and CD44 on uRBCs from Plasmodium falciparum in vitro cultures and patients with malaria that mediates adherence to the splenic extracellular matrix (ECM) components laminin-α5 and hyaluronic acid (HA), respectively. This tight ECM-adhesion molecule interaction was associated with elevated intracellular Ca2+ levels, increased shedding of microvesicles, and Lu/BCAM clustering on altered uRBCs. Moreover, we observed that a soluble parasite-derived factor promoted the adhesive phenotype of uRBCs, as the incubation of RBCs with filtered malaria-conditioned medium reproduced the same adhesive effect in malaria culture–derived uRBCs. Eventually, Lu/BCAM and CD44 activation facilitate the adherence to ECM components of the red pulp, resulting in the enhanced splenic retention of uRBCs. Our results suggest a novel adhesion molecule–dependent mechanism that augments malaria-induced anemia.
Underdispersion: A Statistical Anomaly in Reported Covid Data
2022-03-29

Abstract Throughout the Covid-19 pandemic, we have become used to seeing daily numbers of cases and deaths go up and down. But in some countries, the reported numbers show very little movement over days and weeks – they are “underdispersed”, says Dmitry Kobak, and this may be a sign that all is not right with the data
Sex differences in the association of math achievement with visual‐spatial and verbal working memory: Does the type of math test matter?
2022-03-29

Abstract Previous research on sex differences in mathematical achievement shows mixed findings, which have been argued to depend on types of math tests used and the type of solution strategies (i.e., verbal versus visual‐spatial) these tests evoke. The current study evaluated sex differences in (a) performance (development) on two types of math tests in primary schools and (b) the predictive value of verbal and visual‐spatial working memory on math achievement. Children ( N = 3175) from grades 2 through five participated. Visual‐spatial and verbal working memory were assessed using online computerized tasks. Math performance was assessed five times during two school years using a speeded arithmetic test (math fluency) and a word problem test (math problem solving). Results from Multilevel Multigroup Latent Growth Modeling, showed that sex differences in level and growth of math performance were mixed and very small. Sex differences in the predictive value of verbal and visual‐spatial working memory for math performance suggested that boys seemed to rely more on verbal strategies than girls. Explanations focus on cognitive and emotional factors and how these may interact to possibly amplify sex differences as children grow older.
Legitimacy of Group-Specific Support for College Access – Results of an Experimental Vignette Study
2022-03-29

In an experimental vignette study, the respondents were asked to decide whether college applicants should be credited with a bonus or malus on the admission grade, for example due to their migration background, social origin, or effort. The results show that dimensions of social educational inequality tend to be considered in the direction of compensation. Hence, there is evidence of a certain legitimacy of measures in the sense of positive discrimination in university access.
Sorption and Mobility of Charged Organic Compounds: How to Confront and Overcome Limitations in Their Assessment
2022-03-30

Permanently charged and ionizable organic compounds (IOC) are a large and diverse group of compounds belonging to many contaminant classes, including pharmaceuticals, pesticides, industrial chemicals, and natural toxins. Sorption and mobility of IOCs are distinctively different from those of neutral compounds. Due to electrostatic interactions with natural sorbents, existing concepts for describing neutral organic contaminant sorption, and by extension mobility, are inadequate for IOC. Predictive models developed for neutral compounds are based on octanol-water partitioning of compounds (<i>K</i><sub>ow</sub>) and organic-carbon content of soil/sediment, which is used to normalize sorption measurements (<i>K</i><sub>OC</sub>). We revisit those concepts and their translation to IOC (<i>D</i><sub>ow</sub> and <i>D</i><sub>OC</sub>) and discuss compound and soil properties determining sorption of IOC under water saturated conditions. Highlighting possible complementary and/or alternative approaches to better assess IOC mobility, we discuss implications on their regulation and risk assessment. The development of better models for IOC mobility needs consistent and reliable sorption measurements at well-defined chemical conditions in natural porewater, better IOC-, as well as sorbent characterization. Such models should be complemented by monitoring data from the natural environment. The state of knowledge presented here may guide urgently needed future investigations in this field for researchers, engineers, and regulators.
Climate warming changes synchrony of plants and pollinators
2022-03-30

Climate warming changes the phenology of many species. When interacting organisms respond differently, climate change may disrupt their interactions and affect the stability of ecosystems. Here, we used global biodiversity facility occurrence records to examine phenology trends in plants and their associated insect pollinators in Germany since the 1980s. We found strong phenological advances in plants but differences in the extent of shifts among pollinator groups. The temporal trends in plant and insect phenologies were generally associated with interannual temperature variation and thus probably driven by climate change. When examining the synchrony of species-level plant–pollinator interactions, their temporal trends differed among pollinator groups. Overall, plant–pollinator interactions become more synchronized, mainly because the phenology of plants, which historically lagged behind that of the pollinators, responded more strongly to climate change. However, if the observed trends continue, many interactions may become more asynchronous again in the future. Our study suggests that climate change affects the phenologies of both plants and insects and that it also influences the synchrony of plant–pollinator interactions.
Deep neural models for color classification and color constancy
2022-03-30

Color constancy is our ability to perceive constant colors across varying illuminations. Here, we trained deep neural networks to be color constant and evaluated their performance with varying cues. Inputs to the networks consisted of two-dimensional images of simulated cone excitations derived from three-dimensional (3D) rendered scenes of 2,115 different 3D shapes, with spectral reflectances of 1,600 different Munsell chips, illuminated under 278 different natural illuminations. The models were trained to classify the reflectance of the objects. Testing was done with four new illuminations with equally spaced CIEL*a*b* chromaticities, two along the daylight locus and two orthogonal to it. High levels of color constancy were achieved with different deep neural networks, and constancy was higher along the daylight locus. When gradually removing cues from the scene, constancy decreased. Both ResNets and classical ConvNets of varying degrees of complexity performed well. However, DeepCC, our simplest sequential convolutional network, represented colors along the three color dimensions of human color vision, while ResNets showed a more complex representation.
Biomimetics Linked to Classical Product Development: An Interdisciplinary Endeavor to Develop a Technical Standard
2022-03-30

Biomimetics is a well-known approach for technical innovation. However, most of its influence remains in the academic field. One option for increasing its application in the practice of technical design is to enhance the use of the biomimetic process with a step-by-step standard, building a bridge to common engineering procedures. This article presents the endeavor of an interdisciplinary expert panel from the fields of biology, engineering science, and industry to develop a standard that links biomimetics to the classical processes of product development and engineering design. This new standard, VDI 6220 Part 2, proposes a process description that is compatible and connectable to classical approaches in engineering design. The standard encompasses both the solution-based and the problem-driven process of biomimetics. It is intended to be used in any product development process for more biomimetic applications in the future.
MAPKinase inhibition after failure of immune checkpoint blockade in patients with advanced melanoma – An evaluation of the multicenter prospective skin cancer registry ADOREG
2022-03-30

BRAF plus MEK inhibition shows meaningful activity and outcome in patients with advanced melanoma resistant to anti-PD-1-based immunotherapy. Rates of long-term benefit and survival in our study were similar to those reported for treatment-naïve patients receiving first-line MAPKi.
Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative
2022-03-30

Abstract Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p=5.41×10 −7 ). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights. Author Summary COVID-19 clinical outcomes vary immensely, but a patient’s genetic make-up is an important determinant of how they will fare against the virus. While many genetic variants commonly found in the populations were previously found to be contributing to more severe disease by the COVID-19 Host Genetics Initiative, it isn’t clear if more rare variants found in less individuals could also play a role. This is important because genetic variants with the largest impact on COVID-19 severity are expected to be rarely found in the population, and these rare variants require different technologies to be studies (usually whole-exome or whole-genome sequencing). Here, we combined sequencing results from 21 cohorts across 12 countries to perform a rare variant association study. In an analysis comprising 5,085 participants with severe COVID-19 and 571,737 controls, we found that the gene for toll-like receptor 7 ( TLR7 ) on chromosome X was an important determinant of severe COVID-19. Importantly, despite being found on a sex chromosome, this observation was consistent across both sexes.