Miracle-dz/UniFAR-FTUs huggingface dataset:
Recessive CHRM5 variant as a potential cause of neurogenic bladder

Neurogenic bladder is caused by disruption of neuronal pathways regulating bladder relaxation and contraction. In severe cases, neurogenic bladder can lead to vesicoureteral reflux, hydroureter, and chronic kidney disease. These complications overlap with manifestations of congenital anomalies of the kidney and urinary tract (CAKUT). To identify novel monogenic causes of neurogenic bladder, we applied exome sequencing (ES) to our cohort of families with CAKUT. By ES, we have identified a homozygous missense variant (p.Gln184Arg) in CHRM5 (cholinergic receptor, muscarinic, 5) in a patient with neurogenic bladder and secondary complications of CAKUT. CHRM5 codes for a seven transmembrane‐spanning G‐protein‐coupled muscarinic acetylcholine receptor. CHRM5 is shown to be expressed in murine and human bladder walls and is reported to cause bladder overactivity in Chrm5 knockout mice. We investigated CHRM5 as a potential novel candidate gene for neurogenic bladder with secondary complications of CAKUT. CHRM5 is similar to the cholinergic bladder neuron receptor CHRNA3, which Mann et al. published as the first monogenic cause of neurogenic bladder. However, functional in vitro studies did not reveal evidence to strengthen the status as a candidate gene. Discovering additional families with CHRM5 variants could help to further assess the genes' candidate status.
The Effect of Inoculum Size on Antimicrobial Susceptibility Testing of Mycobacterium tuberculosis

During DST application, it can be challenging to evenly homogenize TB cell clumps with lipid-rich cell walls. These experiments must be carried out under Biosafety Level-3 (BSL-3) laboratory conditions with personal protective equipment and taking safety precautions because the procedures applied at this stage cause the formation of bacillus-laden aerosols and carry a serious risk of transmission. ABSTRACT Phenotypic drug susceptibility testing (DST) requires a standardized amount of inoculum to produce reproducible susceptibility results. The most critical step in the application of DST in Mycobacterium tuberculosis isolates is the preparation of the bacterial inoculum. In this study, the effect of bacterial inoculum prepared in various McFarland turbidities on primary antituberculosis drug susceptibility of M. tuberculosis strains was investigated. Five standard ATCC strains (ATCC 27294 [H37Rv], ATCC 35822 [izoniazid-resistant], ATCC 35838 [rifampicin-resistant], ATCC 35820 [streptomycin-resistant], ATCC 35837 [ethambutol-resistant]) were tested. Inoculums of McFarland standard of 0.5, 1, 2, 3, and 1:100 dilutions of 1 McFarland standard of each strain were used. The effect of inoculum size on DST results was determined by the proportion method in Lowenstein-Jensen (LJ) medium and nitrate reductase assay (NRA) in the LJ medium. In both test methods, the increase in inoculum size did not affect the DST results of the strains. On the contrary, DST results were obtained more rapidly as a result of the use of dense inoculum. DST results obtained in all McFarland turbidities were found to be 100% compatible with the recommended amount of inoculum, 1:100 dilution of 1 McFarland standard (inoculum size of gold standard method). In conclusion, the use of a high amount of inoculum did not change the drug susceptibility profile of tuberculosis bacilli. Minimizing manipulations during the inoculum preparation phase of susceptibility testing, this outcome will decrease the need for equipment and make the test application easier, particularly in developing countries. IMPORTANCE During DST application, it can be challenging to evenly homogenize TB cell clumps with lipid-rich cell walls. These experiments must be carried out under Biosafety Level-3 (BSL-3) laboratory conditions with personal protective equipment and taking safety precautions because the procedures applied at this stage cause the formation of bacillus-laden aerosols and carry a serious risk of transmission. Considering this situation, this stage is important given that it is not possible to establish a BSL-3 laboratory in poor and developing countries. Reducing the manipulations to be applied during the preparation of bacterial turbidity will minimize the risk of aerosol formation. Perhaps there will be no need to do these steps for susceptibility tests in these countries or even in developed countries.
Local Electromagnetic Force Calculation on the Rotor of Squirrel-cage Induction Motors With Broken Bar Faults

Electromagnetic stress is one of the reasons for broken bar faults occurring in squirrel-cage induction motors.Based on the results of two-dimensional transient magnetic fields,the magnetic force around the rotor core and in the bars are calculated by the Maxwell stress method and the principle of the Lorentz force,when the motor operates before and after the failure.The accuracy of the algorithm for solving the force in this paper is confirmed through collating the torque calculated by the above-mentioned method with that obtained by the local Jacobian derivative method and comparing all the results with the experimental values.According to the results of various types of the electromagnetic force when the motor operates within different degrees of broken bar faults,the asymmetry characteristics of the distribution of the force and the stress concentration in the rotor are achieved.The possibility of further bar breaking in the motor with the broken bar fault is analyzed from the perspective of magnetic stress.The force results can be used as a load for calculating structural deformation of the rotor,and the ideas for local electromagnetic force analysis in this paper can also provide a reference for solving similar problems of the motor with other fault types.
S1 Guideline onychomycosis

Onychomycosis is a fungal infection of the fingernails and toenails. In Europe, tinea unguium is mainly caused by dermatophytes. The diagnostic workup comprises microscopic examination, culture and/or molecular testing (nail scrapings). Local treatment with antifungal nail polish is recommended for mild or moderate nail infections. In case of moderate to severe onychomycosis, oral treatment is recommended (in the absence of contraindications). Treatment should consist of topical and systemic agents. The aim of this update of the German S1 guideline is to simplify the selection and implementation of appropriate diagnostics and treatment. The guideline was based on current international guidelines and the results of a literature review conducted by the experts of the guideline committee. This multidisciplinary committee consisted of representatives from the German Society of Dermatology (DDG), the German‐Speaking Mycological Society (DMykG), the Association of German Dermatologists (BVDD), the German Society for Hygiene and Microbiology (DGHM), the German Society of Pediatric and Adolescent Medicine (DGKJ), the Working Group for Pediatric Dermatology (APD) and the German Society for Pediatric Infectious Diseases (DGPI). The Division of Evidence‐based Medicine (dEBM) provided methodological assistance. The guideline was approved by the participating medical societies following a comprehensive internal and external review.
Analysis of Flow Timescales on a Periodically Pitching/Surging Airfoil

Time-resolved velocity fields around a pitching and surging NACA 0018 airfoil were analyzed to investigate the influence of three independent timescales associated with the unsteady flowfield. The first of these timescales, the period of the pitch/surge motion, is directly linked to the development of dynamic stall. A simplified model of the flow using only a time constant mode and the first two harmonics of the pitch surge frequency has been shown to accurately model the flow. Full stall and leading-edge flow separation, however, were found to take place before the maximum angle of attack, indicating that a different timescale was associated with leading-edge vortex formation. This second, leading-edge vortex, timescale was found to depend on the airfoil convection time and compare well with the universal vortex formation time. Finally, instantaneous non-phase-averaged measurements were investigated to identify behavior not directly coupled to the airfoil motion. From this analysis, a third timescale associated with quasi-periodic Strouhal vortex shedding was found before flow separation. The interplay between these three timescales is discussed in detail, particularly as they relate to the periodic velocity and angle-of-attack change apparent to the blades of a vertical axis wind turbine.
Sufficient conditions for optimal control and the generalized problem of Bolza

We develop i n t h i s t h e s i s four s u f f i c i e n c y c r i t e r i a f o r the generalized problem of Bolza. These r e s u l t s represent a u n i f i c a t i o n , i n the sense that they can be applied to both the calculus of v a r i a t i o n s and to optimal c o n t r o l problems, as well as to problems with nonsmooth data. The f i r s t c r i t e r i o n , "point convexity", extends the convexity approach of Rockafellar. However, we derive a "Hamiltonian-Jacobi" approach which can be applied when the point convexity assumption f a i l s to be s a t i s f i e d . The method employed f o r t h i s c r i t e r i o n brings to l i g h t a new point of view concerning the Jacobi condition i n the c l a s s i c a l calculus of v a r i a t i o n s . The l a t t e r can be considered as a condition which guarantees the existence of a canonical transformation transforming the o r i g i n a l Hamiltonian to a l o c a l l y concave-convex Hamiltonian. The t h i r d s u f f i c i e n c y c r i t e r i o n i s an extension of the Hamilton-Jacobi approach from optimal c o n t r o l to the generalized problem of Bolza. This r e s u l t gives r i s e to another s u f f i c i e n c y c r i t e r i o n i n terms of a c e r t a i n i n e q u a l i t y . Our theorems on s u f f i c i e n t conditions are c l o s e l y r e l a t e d . We prove that under c e r t a i n assumptions the l a s t three approaches can be u n i f i e d . By t h i s we mean that t h e i r hypotheses are equivalent. However, the point convexity, and hence the convexity, c r i t e r i o n turns out to have the most r e s t r i c t i v e hypotheses of the four. The generality of the theorems proven stems t o a great extent from the f a c t that not only non-differentiable but even i n f i n i t e -
Insomnia—A risk factor for mental disorders

Longitudinal studies observed that individuals suffering from insomnia disorder have a higher vulnerability to develop symptoms of psychopathology compared with good sleepers. Particularly, insomnia disorder has been associated with an increased risk for depression. Previous studies indicate relatively stable effects; however, replication is needed as the last meta‐analysis on the topic has been published 4 years ago. We conducted a replication of a previous systematic review and meta‐analysis evaluating the longitudinal association between insomnia disorder and psychopathology, including original works published between 2018 and 2022. Literature search was conducted from April 2018 to August 2022 using key words identifying longitudinal studies that evaluate individuals with insomnia disorder compared with good sleepers at baseline, and the onset of all possible mental disorders at long‐term follow‐up. Only one work was added to the previous sample of studies published in 2019 looking at the longitudinal association between insomnia disorder and depression. Meta‐analytic results confirmed the previous observation, with an even higher observed effect for the link between insomnia and depression. This again recognizes insomnia disorder as a possible transdiagnostic process in psychopathology, with consequent important clinical implications. Nevertheless, more longitudinal studies are needed evaluating the link between insomnia disorder and mental disorders.
Reproducibility (reliability and agreement) of ventilatory threshold and peak responses during cardiopulmonary exercise test in people with stroke

ABSTRACT Background A cardiopulmonary exercise test (CPET) is used to determine the ventilatory thresholds and to directly assess cardiorespiratory capacity. However, its reproducibility should be tested in people with stroke as sequelae imposed by the stroke may induce important variations among and within each subject, affecting the reproducibility of the physiological responses to CPET. Purpose This cross-sectional repeated measures study design aims to determine the reproducibility of anaerobic threshold (AT), respiratory compensation point (RCP), and maximal cardiorespiratory capacity assessed during a CPET in people with stroke. Methods Twenty-eight subjects with hemiparesis after stroke aging 60 ± 13 years were submitted to two treadmill CPETs with identical protocols. Data Analysis The reproducibility of heart rate (HR) and oxygen consumption (VO2) obtained at AT, RCP, and peak effort was evaluated by systematic error (paired t-test); reliability (ICC and 95% confidence interval); and agreement (typical error and coefficient of variation). Results There were no systematic errors for HR and VO2assessed at AT, RCP, and peak effort (p > 0,05). Reliability was high for these variables during CPET (ICCs > 0.93). Agreement was good for all variables. Typical errors for HR and VO2 assessed at AT, RCP, and peak effort were, respectively, 7, 7, and 8 bpm, and 1.51, 1.44, and 1.57 ml.kg−1.min−1. Coefficients of variation assessed at AT, RCP, and peak effort were, respectively, 5.7, 5.1, and 6.0% for HR and 8.7, 7.3, and 7.5% for VO2. Conclusions HR and VO2 measured at AT, RCP, and peak effort during a treadmill CPET present good reproducibility in people with stroke, showing high reliability and good agreement.
A Benchmark on Extremely Weakly Supervised Text Classification: Reconcile Seed Matching and Prompting Approaches

Etremely Weakly Supervised Text Classification (XWS-TC) refers to text classification based on minimal high-level human guidance, such as a few label-indicative seed words or classification instructions. There are two mainstream approaches for XWS-TC, however, never being rigorously compared: (1) training classifiers based on pseudo-labels generated by (softly) matching seed words (SEED) and (2) prompting (and calibrating) language models using classification instruction (and raw texts) to decode label words (PROMPT). This paper presents the first XWS-TC benchmark to compare the two approaches on fair grounds, where the datasets, supervisions, and hyperparameter choices are standardized across methods. Our benchmarking results suggest that (1) Both SEED and PROMPT approaches are competitive and there is no clear winner; (2) SEED is empirically more tolerant than PROMPT to human guidance (e.g., seed words, classification instructions, and label words) changes; (3) SEED is empirically more selective than PROMPT to the pre-trained language models; (4) Recent SEED and PROMPT methods have close connections and a clustering post-processing step based on raw in-domain texts is a strong performance booster to both. We hope this benchmark serves as a guideline in selecting XWS-TC methods in different scenarios and stimulate interest in developing guidance- and model-robust XWS-TC methods. We release the repo at https://github.com/ZihanWangKi/x-TC.
Constructing Code-mixed Universal Dependency Forest for Unbiased Cross-lingual Relation Extraction

Latest efforts on cross-lingual relation extraction (XRE) aggressively leverage the language-consistent structural features from the universal dependency (UD) resource, while they may largely suffer from biased transfer (e.g., either target-biased or source-biased) due to the inevitable linguistic disparity between languages. In this work, we investigate an unbiased UD-based XRE transfer by constructing a type of code-mixed UD forest. We first translate the sentence of the source language to the parallel target-side language, for both of which we parse the UD tree respectively. Then, we merge the source-/target-side UD structures as a unified code-mixed UD forest. With such forest features, the gaps of UD-based XRE between the training and predicting phases can be effectively closed. We conduct experiments on the ACE XRE benchmark datasets, where the results demonstrate that the proposed code-mixed UD forests help unbiased UD-based XRE transfer, with which we achieve significant XRE performance gains.
Gradient Descent Monotonically Decreases the Sharpness of Gradient Flow Solutions in Scalar Networks and Beyond

Recent research shows that when Gradient Descent (GD) is applied to neural networks, the loss almost never decreases monotonically. Instead, the loss oscillates as gradient descent converges to its ''Edge of Stability'' (EoS). Here, we find a quantity that does decrease monotonically throughout GD training: the sharpness attained by the gradient flow solution (GFS)-the solution that would be obtained if, from now until convergence, we train with an infinitesimal step size. Theoretically, we analyze scalar neural networks with the squared loss, perhaps the simplest setting where the EoS phenomena still occur. In this model, we prove that the GFS sharpness decreases monotonically. Using this result, we characterize settings where GD provably converges to the EoS in scalar networks. Empirically, we show that GD monotonically decreases the GFS sharpness in a squared regression model as well as practical neural network architectures.
Data-efficient Active Learning for Structured Prediction with Partial Annotation and Self-Training

In this work we propose a pragmatic method that reduces the annotation cost for structured label spaces using active learning. Our approach leverages partial annotation, which reduces labeling costs for structured outputs by selecting only the most informative sub-structures for annotation. We also utilize self-training to incorporate the current model's automatic predictions as pseudo-labels for un-annotated sub-structures. A key challenge in effectively combining partial annotation with self-training to reduce annotation cost is determining which sub-structures to select to label. To address this challenge, we adopt an error estimator to adaptively decide the partial selection ratio according to the current model's capability. In evaluations spanning four structured prediction tasks, we show that our combination of partial annotation and self-training using an adaptive selection ratio reduces annotation cost over strong full annotation baselines under a fair comparison scheme that takes reading time into consideration.
The Hunt for Recoiled Black Holes in the Milky Way's Halo

Since black holes inhabit galactic centers, when galaxies merge, so must their central black holes. If the two coalescing black holes emit anisotropic gravitational waves, one of the black holes can be ejected from the galactic center, bringing a core of stars with it. Based on the merger history of the Milky Way, it is estimated there are ∼300 recoiled black holes in the halo. We present a preliminary spectroscopic search, using the search criteria and list of candidates in O’Leary & Loeb (2012). Although we did not find candidate recoiled black holes, we further optimized the search criteria, using Sloan Digital Sky Survey (SDSS) and Wide-field Infrared Survey Explorer (WISE) magnitudes and colors. More specifically, the SDSS colors (g − r), and (r − i) allow us to constrain the search criteria. Our results contribute to making the search for recoiled black holes more efficient, reducing the amount of false positives that are observed. In the event that a recoiled black hole is found, it would be the first discovery of an elusive intermediate-mass black hole and, as a result, would contribute to our understanding of black hole evolution.
Polar Ducks and Where to Find Them: Enhancing Entity Linking with Duck Typing and Polar Box Embeddings

Entity linking methods based on dense retrieval are an efficient and widely used solution in large-scale applications, but they fall short of the performance of generative models, as they are sensitive to the structure of the embedding space. In order to address this issue, this paper introduces DUCK, an approach to infusing structural information in the space of entity representations, using prior knowledge of entity types. Inspired by duck typing in programming languages, we propose to define the type of an entity based on the relations that it has with other entities in a knowledge graph. Then, porting the concept of box embeddings to spherical polar coordinates, we propose to represent relations as boxes on the hypersphere. We optimize the model to cluster entities of similar type by placing them inside the boxes corresponding to their relations. Our experiments show that our method sets new state-of-the-art results on standard entity-disambiguation benchmarks, it improves the performance of the model by up to 7.9 F1 points, outperforms other type-aware approaches, and matches the results of generative models with 18 times more parameters.
A Comprehensive Survey of Sentence Representations: From the BERT Epoch to the CHATGPT Era and Beyond

Sentence representations are a critical component in NLP applications such as retrieval, question answering, and text classification. They capture the meaning of a sentence, enabling machines to understand and reason over human language. In recent years, significant progress has been made in developing methods for learning sentence representations, including unsupervised, supervised, and transfer learning approaches. However there is no literature review on sentence representations till now. In this paper, we provide an overview of the different methods for sentence representation learning, focusing mostly on deep learning models. We provide a systematic organization of the literature, highlighting the key contributions and challenges in this area. Overall, our review highlights the importance of this area in natural language processing, the progress made in sentence representation learning, and the challenges that remain. We conclude with directions for future research, suggesting potential avenues for improving the quality and efficiency of sentence representations.
MultiTurnCleanup: A Benchmark for Multi-Turn Spoken Conversational Transcript Cleanup

Current disfluency detection models focus on individual utterances each from a single speaker. However, numerous discontinuity phenomena in spoken conversational transcripts occur across multiple turns, hampering human readability and the performance of downstream NLP tasks. This study addresses these phenomena by proposing an innovative Multi-Turn Cleanup task for spoken conversational transcripts and collecting a new dataset, MultiTurnCleanup1. We design a data labeling schema to collect the high-quality dataset and provide extensive data analysis. Furthermore, we leverage two modeling approaches for experimental evaluation as benchmarks for future research.