julilili42/papers huggingface dataset:
Diurnal rhythm causes metabolic crises in the cyanobacterial mutants of c-di-AMP signalling cascade
2023-11-14

Abstract In nature, the photoautotrophic lifestyle of cyanobacteria has to cope with the successive diurnal changes in light supply. Light supply throughout the day enables photosynthesis and glycogen biosynthesis, while night phases require the switch to a heterotrophic-like lifestyle relying on glycogen catabolism. We previously highlighted a unique function of the carbon control protein, SbtB, and its effector molecule c-di-AMP, for the nighttime survival of cyanobacteria through the regulation of glycogen anabolism. However, the extent to which c-di-AMP and SbtB impact the cellular metabolism for day-night survivability remained elusive. To gain better understanding of cellular processes regulated by SbtB or c-di-AMP, we compared the metabolomic and proteomic landscapes of Δ sbtB and the c-di-AMP-free (Δ dacA ) mutants of the model strain Synechocystis sp. PCC 6803. While our results indicate that the cellular role of SbtB is restricted to carbon/glycogen metabolism, the diurnal lethality of Δ dacA seems to be a sum of dysregulation of multiple metabolic processes. These processes include photosynthesis and redox regulation, which lead to elevated levels of intracellular ROS and glutathione. Further, we show an impact of c-di-AMP on central carbon as well as on nitrogen metabolism. Effects on nitrogen metabolism are linked to reduced levels of the global nitrogen transcription regulator NtcA and highlighted by an imbalance of the glutamine to glutamate ratio as well as reduced metabolite levels of the arginine pathway. We further identified the HCO 3 - uptake systems, BicA and BCT1 as novel SbtB targets, in agreement with its broader role in regulating carbon homeostasis.
pyESDv1.0.1: an open-source Python framework for empirical-statistical downscaling of climate information
2023-11-14

Abstract. The nature and severity of climate change impacts vary significantly from region to region. Consequently, high-resolution climate information is needed for meaningful impact assessments and the design of mitigation strategies. This demand has led to an increase in the application of empirical-statistical downscaling (ESD) models to general circulation model (GCM) simulations of future climate. In contrast to dynamical downscaling, the perfect prognosis ESD (PP-ESD) approach has several benefits, including low computation costs, the prevention of the propagation of GCM-specific errors, and high compatibility with different GCMs. Despite their advantages, the use of ESD models and the resulting data products is hampered by (1) the lack of accessible and user-friendly downscaling software packages that implement the entire downscaling cycle, (2) difficulties reproducing existing data products and assessing their credibility, and (3) difficulties reconciling different ESD-based predictions for the same region. We address these issues with a new open-source Python PP-ESD modeling framework called pyESD. pyESD implements the entire downscaling cycle, i.e., routines for data preparation, predictor selection and construction, model selection and training, evaluation, utility tools for relevant statistical tests, visualization, and more. The package includes a collection of well-established machine learning algorithms and allows the user to choose a variety of estimators, cross-validation schemes, objective function measures, and hyperparameter optimization in relatively few lines of code. The package is well-documented, highly modular, and flexible. It allows quick and reproducible downscaling of any climate information, such as precipitation, temperature, wind speed, or even short-term glacier length and mass changes. We demonstrate the use and effectiveness of the new PP-ESD framework by generating weather-station-based downscaling products for precipitation and temperature in complex mountainous terrain in southwestern Germany. The application example covers all important steps of the downscaling cycle and different levels of experimental complexity. All scripts and datasets used in the case study are publicly available to (1) ensure the reproducibility and replicability of the modeled results and (2) simplify learning to use the software package.
LayerNet: High-Resolution Semantic 3D Reconstruction of Clothed People
2023-11-14

In this article, we introduce SMPLicit, a novel generative model to jointly represent body pose, shape and clothing geometry; and LayerNet, a deep network that given a single image of a person simultaneously performs detailed 3D reconstruction of body and clothes. In contrast to existing learning-based approaches that require training specific models for each type of garment, SMPLicit can represent in a unified manner different garment topologies (e.g. from sleeveless tops to hoodies and open jackets), while controlling other properties like garment size or tightness/looseness. LayerNet follows a coarse-to-fine multi-stage strategy by first predicting smooth cloth geometries from SMPLicit, which are then refined by an image-guided displacement network that gracefully fits the body recovering high-frequency details and wrinkles. LayerNet achieves competitive accuracy in the task of 3D reconstruction against current 'garment-agnostic' state of the art for images of people in up-right positions and controlled environments, and consistently surpasses these methods on challenging body poses and uncontrolled settings. Furthermore, the semantically rich outcome of our approach is suitable for performing Virtual Try-on tasks directly on 3D, a task which, so far, has only been addressed in the 2D domain.
Engaging Modern Muslims with Their Prophet
2023-11-14

Abstract In contemporary Egypt, the secularization of discourses and practices raises a fundamental challenge to sīra writing concerning its vocation to make the founding narrative and the religious ideals of Islam comprehensible and meaningful to contemporary Muslims. Arguing that the Muslim community’s image of the Prophet does indeed both affect and reflect its religious and spiritual condition, the known Egyptian intellectual and former rector of al-Azhar, ʿAbd al-Ḥalīm Maḥmūd (1910-1978) holds the appearance of de-theologized forms of sīra writing as a symptom of a profound crisis of Islamic intellectuality. Against this background, his prophetological considerations seek to show that this challenge can only be overcome by a sīra writing that engages the audience in a personal and spiritual relationship with the Prophet.
Fairness Hacking: The Malicious Practice of Shrouding Unfairness in Algorithms
2023-11-14

Fairness in machine learning (ML) is an ever-growing field of research due to the manifold potential for harm from algorithmic discrimination. To prevent such harm, a large body of literature develops new approaches to quantify fairness. Here, we investigate how one can divert the quantification of fairness by describing a practice we call "fairness hacking" for the purpose of shrouding unfairness in algorithms. This impacts end-users who rely on learning algorithms, as well as the broader community interested in fair AI practices. We introduce two different categories of fairness hacking in reference to the established concept of p-hacking. The first category, intra-metric fairness hacking, describes the misuse of a particular metric by adding or removing sensitive attributes from the analysis. In this context, countermeasures that have been developed to prevent or reduce p-hacking can be applied to similarly prevent or reduce fairness hacking. The second category of fairness hacking is inter-metric fairness hacking. Inter-metric fairness hacking is the search for a specific fair metric with given attributes. We argue that countermeasures to prevent or reduce inter-metric fairness hacking are still in their infancy. Finally, we demonstrate both types of fairness hacking using real datasets. Our paper intends to serve as a guidance for discussions within the fair ML community to prevent or reduce the misuse of fairness metrics, and thus reduce overall harm from ML applications.
Replenishment of Drosophila Male Pheromone After Mating
2023-11-14

Abstract Insects exocrine gland products can be involved in sexual communication, defense, territory labelling, aggregation and alarm. In the vinegar fly Drosophila melanogaster the ejaculatory bulb synthesizes and releases 11- cis -Vaccenyl acetate ( c Va). This pheromone, transferred to the female during copulation, affects aggregation, courtship and male-male aggressive behaviors. To determine the time-course of c Va replenishment, males of a control laboratory strain and from the desat1 pheromone-defective mutant strain were allowed to mate successively with several females. We measured mating frequency, duration and latency, the amount of c Va transferred to mated females and the residual c Va in tested males. Mating duration remained constant with multiple matings, but we found that the amount of c Va transferred to females declined with multiple matings, indicating that, over short, biologically-relevant periods, replenishment of the pheromone does not keep up with mating frequency, resulting in the transfer of varying quantities of c Va. Adult responses to c Va are affected by early developmental exposure to this pheromone; our revelation of quantitative variation in the amount of c Va transferred to females in the event of multiple matings by a male suggests variable responses to c Va shown by adults produced by such matings. This implies that the natural role of this compound may be richer than suggested by strictly-controlled laboratory experiments.
Experience with German Research Consortia in the Field of Chemical Biology of Native Nucleic Acid Modifications
2023-11-14

The chemical biology of native nucleic acid modifications has seen an intense upswing, first concerning DNA modifications in the field of epigenetics and then concerning RNA modifications in a field that was correspondingly rebaptized epitranscriptomics by analogy. The German Research Foundation (DFG) has funded several consortia with a scientific focus in these fields, strengthening the traditionally well-developed nucleic acid chemistry community and inciting it to team up with colleagues from the life sciences and data science to tackle interdisciplinary challenges. This Perspective focuses on the genesis, scientific outcome, and downstream impact of the DFG priority program SPP1784 and offers insight into how it fecundated further consortia in the field. Pertinent research was funded from mid-2015 to 2022, including an extension related to the coronavirus pandemic. Despite being a detriment to research activity in general, the pandemic has resulted in tremendously boosted interest in the field of RNA and RNA modifications as a consequence of their widespread and successful use in vaccination campaigns against SARS-CoV-2. Funded principal investigators published over 250 pertinent papers with a very substantial impact on the field. The program also helped to redirect numerous laboratories toward this dynamic field. Finally, SPP1784 spawned initiatives for several funded consortia that continue to drive the fields of nucleic acid modification.
Time perception in suspenseful films
2023-11-14

&lt;p&gt;Dataset of an experimental study in which participants (N = 50) watched short video clips from horror films. Participants were asked to estimate perceived suspense levels and to do a time estimation task.&nbsp;&lt;/p&gt;
The Clinical Relevance of the NATALEE Study: Application of the NATALEE Criteria to a Real-World Cohort from Two Large German Breast Cancer Centers
2023-11-15

The NATALEE study showed a significant benefit in invasive disease-free survival (iDFS) for patients with HR+/HER2− early breast cancer (eBC) at intermediate and high risk of recurrence who were treated with the CDK4/6 inhibitor Ribociclib in combination with endocrine therapy (ET). This retrospective study aims to apply the NATALEE inclusion criteria to a representative real-world cohort to estimate the proportion of HR+/HER2− breast cancer patients eligible for adjuvant Ribociclib therapy. Patients who underwent full surgical treatment for eBC between January 2018 and December 2020 at two large German university breast cancer centers (University of Ulm, University of Tuebingen) were included. Descriptive statistics were used to characterize the patient population eligible for Ribociclib treatment based on the NATALEE study’s inclusion criteria. Out of 2384 enrolled patients, 1738 had HR+/HER2− eBC, of whom 43% (747/1738) met the NATALEE inclusion criteria. Of note, these patients were older, received less chemotherapy and presented with less advanced tumor stages compared to the NATALEE study cohort. Additionally, compared to the NATALEE study cohort, fewer patients had lymph node involvement (72.4% vs. 88.7%). Our analysis suggests that approximately 43% of all HR+/HER2− breast cancer patients will qualify for Ribociclib treatment. Given the numerous treatment options for patients with HR+/HER2− eBC, as well as the differences between the NATALEE cohort and patients in the real-world clinical setting, future analyses will be needed to determine which patients would benefit most from adjuvant CDK4/6 inhibitor treatment.
Near-infrared spectroscopy and electroencephalography neurofeedback for binge-eating disorder: an exploratory randomized trial
2023-11-15

Abstract Background Binge-eating disorder (BED) co-occurs with neurobehavioral alterations in the processing of disorder-relevant content such as visual food stimuli. Whether neurofeedback (NF) directly targeting them is suited for treatment remains unclear. This study sought to determine feasibility and estimate effects of individualized, functional near-infrared spectroscopy-based real-time NF (rtfNIRS-NF) and high-beta electroencephalography-based NF (EEG-NF), assuming superiority over waitlist (WL). Methods Single-center, assessor-blinded feasibility study with randomization to rtfNIRS-NF, EEG-NF, or WL and assessments at baseline ( t 0), postassessment ( t 1), and 6-month follow-up ( t 2). NF comprised 12 60-min food-specific rtfNIRS-NF or EEG-NF sessions over 8 weeks. Primary outcome was the binge-eating frequency at t 1 assessed interview-based. Secondary outcomes included feasibility, eating disorder symptoms, mental and physical health, weight management-related behavior, executive functions, and brain activity at t 1 and t 2. Results In 72 patients (intent-to-treat), the results showed feasibility of NF regarding recruitment, attrition, adherence, compliance, acceptance, and assessment completion. Binge eating improved at t 1 by −8.0 episodes, without superiority of NF v. WL (−0.8 episodes, 95% CI −2.4 to 4.0), but with improved estimates in NF at t 2 relative to t 1. NF was better than WL for food craving, anxiety symptoms, and body mass index, but overall effects were mostly small. Brain activity changes were near zero. Conclusions The results show feasibility of food-specific rtfNIRS-NF and EEG-NF in BED, and no posttreatment differences v. WL, but possible continued improvement of binge eating. Confirmatory and mechanistic evidence is warranted in a double-blind randomized design with long-term follow-up, considering dose–response relationships and modes of delivery.
Size Determination of Organic Cages by Diffusion NMR Spectroscopy
2023-11-15

Abstract Reliable structure elucidation of covalent organic cage compounds remains challenging as routine analysis might leave ambiguities. Diffusion‐ordered NMR spectroscopy (DOSY) allows insight into the molecular size and mass of the species present in solution, but a systematic evaluation of the diffusion behavior for cage assemblies is rarely considered. Here we report the synthesis of four series of covalent organic cages based on tribenzotriquinacenes and diboronic acids with varying geometry and exohedral substituents. We provide a guideline for the consistent measurement of diffusion coefficients from 1 H‐DOSY NMR spectroscopy, which was utilized to study the diffusion behavior for the whole set of cages and selected examples from the literature. For structurally similar cages, a linear correlation between the solvodynamic volume and the molecular mass allows precise size determination. For more complex systems, multiple parameters, such as window size or rigid exohedral functionalization. further modulate cage diffusion in solution.
Effects of seasonal variations in vegetation and precipitation on catchment erosion rates along a climate and ecological gradient: insights from numerical modeling
2023-11-15

Abstract. Precipitation in wet seasons influences catchment erosion and contributes to annual erosion rates. However, wet seasons are also associated with increased vegetation cover, which helps resist erosion. This study investigates the effect of present-day seasonal variations in rainfall and vegetation cover on erosion rates for four catchments along the extreme climate and ecological gradient (from arid to temperate) of the Chilean Coastal Cordillera (∼ 26–∼ 38∘ S). We do this using the Landlab–SPACE landscape evolution model to account for vegetation-dependent hillslope–fluvial processes and hillslope hydrology. Model inputs include present-day (90 m) topography and a time series (from 2000–2019) of MODIS-derived Normalized Difference Vegetation Index (NDVI) for vegetation seasonality, weather station observations of precipitation, and evapotranspiration obtained from Global Land Data Assimilation System (GLDAS) Noah. The sensitivity of catchment-scale erosion rates to seasonal average variations in precipitation and/or vegetation cover was quantified using numerical model simulations. Simulations were conducted for 1000 years (20 years of vegetation and precipitation observations repeated 50 times). After detrending the results for long-term transient changes, the last 20 years were analyzed. Results indicate that when vegetation cover is variable but precipitation is held constant, the amplitude of change in erosion rates relative to mean erosion rates ranges between 5 % (arid) and 36 % (Mediterranean setting). In contrast, in simulations with variable precipitation change and constant vegetation cover, the amplitude of change in erosion rates is higher and ranges between 13 % (arid) and 91 % (Mediterranean setting). Finally, simulations with coupled precipitation and vegetation cover variations demonstrate variations in catchment erosion of 13 % (arid) to 97 % (Mediterranean setting). Taken together, we find that precipitation variations more strongly influence seasonal variations in erosion rates. However, the effects of seasonal variations in vegetation cover on erosion are also significant (between 5 % and 36 %) and are most pronounced in semi-arid to Mediterranean settings and least prevalent in arid and humid–temperature settings.
Workload-dependent hemispheric asymmetries during the emotion-cognition interaction: a close-to-naturalistic fNIRS study
2023-11-15

Introduction We investigated brain activation patterns of interacting emotional distractions and cognitive processes in a close-to-naturalistic functional near-infrared spectroscopy (fNIRS) study. Methods Eighteen participants engaged in a monitoring-control task, mimicking common air traffic controller requirements. The scenario entailed experiencing both low and high workload, while concurrently being exposed to emotional speech distractions of positive, negative, and neutral valence. Results Our investigation identified hemispheric asymmetries in prefrontal cortex (PFC) activity during the presentation of negative and positive emotional speech distractions at different workload levels. Thereby, in particular, activation in the left inferior frontal gyrus (IFG) and orbitofrontal cortex (OFC) seems to play a crucial role. Brain activation patterns revealed a cross-over interaction indicating workload-dependent left hemispheric inhibition processes during negative distractions and high workload. For positive emotional distractions under low workload, we observed left-hemispheric PFC recruitment potentially associated with speech-related processes. Furthermore, we found a workload-independent negativity bias for neutral distractions, showing brain activation patterns similar to those of negative distractions. Discussion In conclusion, lateralized hemispheric processing, regulating emotional speech distractions and integrating emotional and cognitive processes, is influenced by workload levels and stimulus characteristics. These findings advance our understanding of the factors modulating hemispheric asymmetries during the processing and inhibition of emotional distractions, as well as the interplay between emotion and cognition. Moreover, they emphasize the significance of exploring emotion-cognition interactions in more naturalistic settings to gain a deeper understanding of their implications in real-world application scenarios (e.g., working and learning environments).
Review and recommendations on deformable image registration uncertainties for radiotherapy applications
2023-11-16

Abstract Deformable image registration (DIR) is a versatile tool used in many applications in radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment planning systems providing accessible and easy-to-use solutions. However, the geometric uncertainty of DIR can be large and difficult to quantify, resulting in barriers to clinical practice. Currently, there is no agreement in the RT community on how to quantify these uncertainties and determine thresholds that distinguish a good DIR result from a poor one. This review summarises the current literature on sources of DIR uncertainties and their impact on RT applications. Recommendations are provided on how to handle these uncertainties for patient-specific use, commissioning, and research. Recommendations are also provided for developers and vendors to help users to understand DIR uncertainties and make the application of DIR in RT safer and more reliable.
Development and validation of a test to assess teachers' knowledge of how to operate technology
2023-11-16

To effectively adopt technology during teaching, teachers require knowledge of how to operate technology. Especially first-time technology users need knowledge of how to handle digital devices and software programs as a foundation to use technology in the classroom successfully. This knowledge has so far been assessed mainly using self-reports. However, self-assessments are insufficient for assessing knowledge as their validity is limited. Moreover, the few tests that exist to measure technological knowledge (TK) show weaknesses (e.g., lack of ecological validity, outdated items). We present a test assessing teachers' TK that is independent of specific operating systems, covers technology that is relevant in everyday teaching, and is grounded in acknowledged psychometric modeling principles. We iteratively developed a test (named T-TK) comprising 26 items, utilizing cognitive testing, expert feedback, and two studies (Npilot study = 268 pre-service and in-service teachers, Nmain study = 233 in-service teachers) to filter items that did not match in content and were not Rasch conform. T-TK showed a satisfactory Andrich's reliability (RelAndrich = 0.73). Using the sample Nmain study, correlations between T-TK and technological knowledge (self-report, r = 0.52), pedagogical knowledge (test scores, r = 0.18), and technological pedagogical knowledge (self-report, r = 0.33; test scores, r = 0.46) indicated convergent and discriminant validity. Thus, the T-TK proves to be a reliable and valid instrument to capture teachers' TK. The T-TK can be used both by practitioners not requiring any statistical knowledge (e.g., for individual diagnostics) and in research (e.g., to analyze teachers' TK).