Miracle-dz/UniFAR-FTUs huggingface dataset:
Symptoms of depression and anxiety among elite high school student-athletes in Sweden during the COVID-19 pandemic: A repeated cross-sectional study

ABSTRACT The COVID-19 pandemic precipitated numerous changes in daily life, including the cancellation and restriction of sports globally. Because sports participation contributes positively to the development of student-athletes, restricting these activities may have led to long-term mental health changes in this population. Using a repeated cross-sectional study design, we measured rates of depression using the Patient Health Questionnaire-2 and anxiety using the Generalized Anxiety Disorder-2 scale in student-athletes attending elite sport high schools in Sweden during the second wave of the pandemic (February 2021; n = 7021) and after all restrictions were lifted (February 2022; n = 6228). Depression among student-athletes decreased from 19.8% in 2021 to 17.8% in 2022 (p = .008, V = .026), while anxiety screening did not change significantly (17.4% to 18.4%, p > .05). Comparisons between classes across years revealed older students exhibited decreases in depressive symptoms, while younger cohorts experienced increases in symptoms of anxiety from 2021 to 2022. Logistic regressions revealed that being female, reporting poorer mental health due to COVID-19, and excessive worry over one’s career in sports were significant predictors of both depression and anxiety screenings in 2022. Compared to times when sports participation was limited, the lifting of restrictions was associated with overall reduced levels of depression, but not anxiety.
Interpolating Nonadiabatic Molecular Dynamics Hamiltonian with Bidirectional Long Short-Term Memory Networks

Essential for understanding far-from-equilibrium processes, nonadiabatic (NA) molecular dynamics (MD) requires expensive calculations of the excitation energies and NA couplings. Machine learning (ML) can simplify computation; however, the NA Hamiltonian requires complex ML models due to its intricate relationship to atomic geometry. Working directly in the time domain, we employ bidirectional long short-term memory networks (Bi-LSTM) to interpolate the Hamiltonian. Applying this multiscale approach to three metal-halide perovskite systems, we achieve two orders of magnitude computational savings compared to direct ab initio calculation. Reasonable charge trapping and recombination times are obtained with NA Hamiltonian sampling every half a picosecond. The Bi-LSTM-NAMD method outperforms earlier models and captures both slow and fast time scales. In combination with ML force fields, the methodology extends NAMD simulation times from picoseconds to nanoseconds, comparable to charge carrier lifetimes in many materials. Nanosecond sampling is particularly important in systems containing defects, boundaries, interfaces, etc. that can undergo slow rearrangements.
Clinical pharmacology of emicizumab for the treatment of hemophilia A

ABSTRACT Introduction Emicizumab is a humanized bispecific antibody approved for the routine prophylaxis of bleeding episodes in patients with hemophilia A (PwHA) regardless of the presence of factor VIII (FVIII) inhibitors. It mimics the cofactor function of missing activated FVIII by bridging activated factor IX and factor X, thereby restoring hemostasis. Areas covered This review covers the clinical pharmacology of emicizumab and the translation of its pharmacokinetics (PK) and pharmacodynamics (PD) to clinical efficacy and safety. The PK of emicizumab is linear, with an approximately 1-month half-life. Once-weekly to every-4-week subcutaneous (SC) administrations maintain effective trough concentrations throughout the dosing intervals, associated with a coagulation potential analogous to that in patients with mild hemophilia A. In combination with activated prothrombin complex concentrate, and to a lesser extent with recombinant activated factor VII, emicizumab exerts a synergistic effect, whereas combination with FVIII may result in a non-additive coagulation potential at normal FVIII activity. Expert opinion The translation of emicizumab PK/PD into clinical effects was demonstrated in several phase III studies, which showed remarkable bleed control and a favorable safety profile in PwHA. These emicizumab attributes, together with the convenience of use (infrequent SC injections), offer a novel paradigm for the management of PwHA.
Domain-Generalized EEG Classification With Category-Oriented Feature Decorrelation and Cross-View Consistency Learning

Generalizing the electroencephalogram (EEG) decoding methods to unseen subjects is an important research direction for realizing practical application of brain-computer interfaces (BCIs). Since distribution shifts across subjects, the performance of most current deep neural networks for decoding EEG signals degrades when dealing with unseen subjects. Domain generalization (DG) aims to tackle this issue by learning invariant representations across subjects. To this end, we propose a novel domain-generalized EEG classification framework, named FDCL, to generalize EEG decoding through category-relevant and -irrelevant Feature Decorrelation and Cross-view invariant feature Learning. Specifically, we first devise data augmented regularization through mixing the segments of same-category features from multiple subjects, which increases the diversity of EEG data by spanning the space of subjects. Furthermore, we introduce feature decorrelation regularization to learn the weights of the augmented EEG trials to remove the dependencies between their features, so that the true mapping relationship between relevant features and corresponding labels can be better established. To further distill subject-invariant EEG feature representations, cross-view consistency learning regularization is introduced to encourage consistent predictions of category-relevant features induced from different augmented EEG views. We seamlessly integrate three complementary regularizations into a unified DG framework to jointly improve the generalizability and robustness of the model on unseen subjects. Experimental results on motor imagery (MI) based EEG datasets validate that the proposed FDCL outperforms the available state-of-the-art methods.
Bridging gaps in health? A qualitative study about bridge-building and social inequity in Danish healthcare

ABSTRACT Attendance to health appointments may pose challenges to patients, especially when living in socially disadvantaged situations, with a fragile network. Inequality in health is increasingly highlighted in Denmark. To enhance social equity in health, a non-governmental organization introduced bridge-building, where healthcare students volunteer to accompany persons in socially vulnerable situations to health appointments. The purpose of the study was to explore what bridge-building entails and which gaps bridge-building attempts to span, in a welfare state, based on equal rights to healthcare.The study is based on an ethnographic fieldwork among the stakeholders in bridge-building, using interviews and participant observation in the form of “walking fieldwork”. Informants emphasized safe-making and wayfinding as important components in bridge-building, with bridge-builders acting as as-if-relatives. Bridge-building navigates in borderlands, the in-between spaces with fluid and contested borders, encompassing public, civic society, and family spheres. All informants emphasized that bridge-building covers a need in contemporary Danish healthcare. Bridge-building entails a double temporality, a here-and-now intervention where persons in vulnerable situations get social support to make it to health appointments, and a future investment in future health professionals’ understanding of vulnerability in lives and barriers to health access; insights that may be valuable in their future job positions.
A note on the statistical interpretation of Båth's law

Abstract A theoretical version of Bath9s law is derived on the assumption that aftershock magnitudes are independently and exponentially distributed. The results are not fully in agreement with the commonly accepted picture of Bath9s law, but it is shown by reference to Utsu9s table of Japanese aftershock sequences that the discrepancies may be due to bias introduced by the method of selecting the data for study.
A Mediator subunit imparts robustness to a polyphenism decision

Significance The ability to produce multiple phenotypes from a single genotype, or developmental plasticity, allows organisms to match phenotypes to their surroundings within their lifetime. For this response to be adaptive, perception of the environment must be predictably processed into those phenotypes. This response’s reliability is exemplified in the case of dimorphism, where phenotypes are stereotypical alternatives that result from a decision made during development. Reliability likely requires mechanisms for robustness, especially where decision-making factors (“switch genes”) influence those that build the phenotype itself (“effector genes”). Our finding that a well-known mediator of gene transcription, together with two other factors, ensures the outcomes of a dimorphism gives a molecular context to predictions about how plastic developmental decisions are realized.
External boundary value problems in the quasi static theory of viscoelasticity for Kelvin‐Voigt materials with double porosity

In the present paper the linear quasi static theory of viscoelasticity for Kelvin‐Voigt materials with double porosity is considered. The basic external boundary value problems (BVPs) of steady vibrations in this theory are formulated. The uniqueness and existence theorems for regular (classical) solutions of the BVPs are proved by using of the potential method (boundary integral equations method) and the theory of singular integral equations. (© 2016 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Impact of a patient reminder letter from their general practitioners on influenza vaccination: A quasi-experimental study in Paris, France

Abstract Background Seasonal influenza vaccination coverage levels remain too low in many countries. Objectives This study aimed to evaluate the impact of a reminder letter from their general practitioner (GP) on patients’ influenza vaccination. Methods Eligible patients for this controlled non-randomised study were the vulnerable categories targeted by the 2019–2020 national health insurance fund (NHIF) vaccination campaign, on the lists of 14 GPs from three practices in Paris (France) and unvaccinated on January 2, 2020 (mid-campaign). The choice of practices and assigning five GPs to the intervention arm were made for convenience. At mid-campaign, GPs in the intervention arm sent a standardised letter reminding each eligible patient to be vaccinated. In the control arm, GPs worked as usual. The intervention effect, calculated from the NHIF databases, was estimated by the difference between the groups in their vaccination coverage at the end of the campaign, with a linear mixed model adjusted for age, sex, chronic disease (at the patient level) and medical practice (at the GP level). Results The vaccination coverage at the end of the campaign was 14.7% in the intervention group (n = 317) and 1.7% in the control group (n = 493): a difference of 13.1% points (95% confidence interval [9.0–17.2], number needed to send 7.7). At the campaign’s end, vaccination coverage among patients from the lists of GPs in the intervention arm was 62.7%, and 46.2% among patients from the control-arm GP lists. Conclusion Reminder letters could help increase influenza vaccination coverage.
Telehealth Use During the COVID-19 Pandemic Among Veterans and Nonveterans: Web-Based Survey Study

Background In the first year of the COVID-19 pandemic, studies reported delays in health care usage due to safety concerns. Delays in care may result in increased morbidity and mortality from otherwise treatable conditions. Telehealth provides a safe alternative for patients to receive care when other circumstances make in-person care unavailable or unsafe, but information on patient experiences is limited. Understanding which people are more or less likely to use telehealth and their experiences can help tailor outreach efforts to maximize the impact of telehealth. Objective This study aims to examine the characteristics of telehealth users and nonusers and their reported experiences among veteran and nonveteran respondents. Methods A nationwide web-based survey of current behaviors and health care experiences was conducted in December 2020-March 2021. The survey consisted of 3 waves, and the first wave is assessed here. Respondents included US adults participating in Qualtrics web-based panels. Primary outcomes were self-reported telehealth use and number of telehealth visits. The analysis used a 2-part regression model examining the association between telehealth use and the number of visits with respondent characteristics. Results There were 2085 participants in the first wave, and 898 (43.1%) reported using telehealth since the pandemic began. Most veterans who used telehealth reported much or somewhat preferring an in-person visit (336/474, 70.9%), while slightly less than half of nonveterans (189/424, 44.6%) reported this preference. While there was no significant difference between veteran and nonveteran likelihood of using telehealth (odds ratio [OR] 1.33, 95% CI 0.97-1.82), veterans were likely to have more visits when they did use it (incidence rate ratio [IRR] 1.49, 95% CI 1.07-2.07). Individuals were less likely to use telehealth and reported fewer visits if they were 55 years and older (OR 0.39, 95% CI 0.25-0.62 for ages 55-64 years; IRR 0.43, 95% CI 0.28-0.66) or lived in a small city (OR 0.63, 95% CI 0.43-0.92; IRR 0.71, 95% CI 0.51-0.99). Receiving health care partly or primarily at the Veterans Health Administration (VA) was associated with telehealth use (primarily VA: OR 3.25, 95% CI 2.20-4.81; equal mix: OR 2.18, 95% CI 1.40-3.39) and more telehealth visits (primarily VA: IRR 1.5, 95% CI 1.10-2.04; equal mix: IRR 1.57, 95% CI 1.11-2.24). Conclusions Telehealth will likely continue to be an important source of health care for patients, especially following situations like the COVID-19 pandemic. Some groups who may benefit from telehealth are still underserved. Telehealth services and outreach should be improved to provide accessible care for all.
Pursuit Problems: Generalizations and Numerical Simulations

A pursuit problem consists of studying the path followed by an aggressor (the pursuer) to catch a prey. This problem dates back to Zeno's solution of the classic Achilles and the Tortoise problem, Leonardo Da Vinci and Pierre Bouguer (1732). The term “pursuit curve” was introduced by George Boole in his Treatise on differential equations of 1859. The usual mathematical model in a pursuit problem is that of a differential equation that describes the relative velocity between the pursuer and prey and in which the speed of the pursuer is proportional to that of the prey. Besides the direct applications to biology, this problem is also important in ballistics and aviation. In the classical pursuit problem, the prey follows a given known path and the problem is to determine the path followed by the pursuer. Normally the approach in textbooks and papers is to find exact solutions of the model equations which can only be obtained for fairly simple prey path curves. For more complex situations, numerical methods are the only practical alternative to approximate the solution. A more realistic situation in a pursuit problem is that in which the prey follows a possibly random path. Another interesting situation is the one in which the pursuer chases more than one prey and has to make “decisions” on the fly onto which prey to follow. In this paper we propose models for both of these situations and perform numerical simulations to study the possible resulting trajectories followed by the pursuer.
Gamma Rays Signature of Dark Matter in the CTA Era: status and prospects

High-energy phenomena in the cosmos, and in particular processes leading to the emission of gamma- rays in the energy range 10 MeV - 100 TeV, play a very special role in the understanding of our Universe. This energy range is indeed associated with non-thermal phenomena and challenging particle acceleration processes. The Universe can be thought as a context where fundamental physics, relativistic processes, strong gravity regimes, and plasma instabilities can be explored in a way that is not possible to reproduce in our laboratories. High-energy astrophysics and atmospheric plasma physics are indeed not esoteric subjects, but are strongly linked with our daily life. Understanding cosmic high-energy processes has a large impact on our theories and laboratories applications. The technology involved in detecting gamma-rays is challenging and drives our ability to develop improved instruments for a large variety of applications. In the last decades a vast amount of evidence for the existence of dark matter has been accumulated. At the same time, many efforts have been undertaken to try to identify what dark matter is. Indirect searches look at places in the Universe where dark matter is believed to be abundant and seek for possible annihilation or decay signatures. At high energies, the Cherenkov Telescope Array (CTA) represents the next generation of imaging Cherenkov telescopes and, with one site in the Southern hemisphere and one in the Northern hemisphere, will be able to observe all the sky with unprecedented sensitivity and angular resolution above a few tens of GeV. The CTA Consortium will undertake an ambitious program of indirect dark matter searches for which we report here the brightest prospects. At lower energies, the energy range between 1 and 100 MeV is an experimentally very difficult range and remained uncovered since the time of COMPTEL. New instruments can address all astrophysical issues left open by the current generation of instruments. In particular, a good angular resolution in the energy range 10 MeV - 1 GeV is crucial to resolve patchy and complex features of diffuse sources in the Galaxy and in the Galactic Centre as well as increasing the point source sensitivity. This instrument addresses scientific topics of great interest to the community, with particular emphasis on multifrequency correlation studies involving radio, optical, IR, X-ray, soft gamma-ray and TeV emission. The possibility to study not only the pair production regime but also the Compton regime with this kind of detectors is currently under investigation and it is another possible very interesting breaktrough.
Universal scaling in fractional dimension

The concept of universality has shaped our understanding of many-body physics, but is mostly limited to homogenous systems. Here, we present a first study of universality on a non-homogeneous graph, the long-range diluted graph (LRDG). Its scaling theory is controlled by a single parameter, the spectral dimension $d_s$, which plays the role of the relevant parameter on complex geometries. The graph under consideration allows us to tune the value of the spectral dimension continuously and find the universal exponents as continuous functions of the dimension. By means of extensive numerical simulations, we probe the scaling exponents of a simple instance of O(N) symmetric models on the LRDG showing quantitative agreement with the theoretical prediction of universal scaling in fractional dimensions.
Insights into the dynamics of spray–swirl interactions

The near-field breakup and interaction of a hollow-cone liquid sheet with coannular swirling air flow have been examined using high-speed diagnostics. Time-resolved PIV (particle image velocimetry; $3500~\text{frames}~\text{s}^{-1}$ ) is employed to capture the spatio-temporal behaviour of the swirling air flow field. The combined liquid–gas phase interaction is visualized with the help of high-speed ( $20\,000~\text{frames}~\text{s}^{-1}$ ) shadowgraphy. In this study, the transition from weak to strong spray–swirl interaction is explained based on the momentum ratio. Proper orthogonal decomposition (POD) is implemented on instantaneous PIV and shadowgraphy images to extract the energetic spatial eigenmodes and characteristic modal frequencies. The POD results suggest the dominance of the KH (Kelvin–Helmholtz) instability mechanism (pure axial shear, axial plus azimuthal shear) in swirl–spray interaction. In addition, linear stability analysis also shows the destabilization of the liquid–air interface caused by KH waves ( $\unicode[STIX]{x1D706}_{p}$ ), which arises from the formation of a vorticity layer of thickness $\unicode[STIX]{x1D6FF}_{g}$ near the liquid–air interface. The frequency values obtained from the primary KH wavelength ( $\unicode[STIX]{x1D706}_{p}$ ) exhibit good agreement with the POD modal frequencies. Scaling laws are proposed to elucidate the relationships between the global length scales (breakup length, spray spread) and the primary wavelength. The breakup length scale and liquid sheet oscillations are meticulously analysed in the time domain to reveal the breakup dynamics of the liquid sheet. Furthermore, the large-scale coherent structures of the swirl flow exhibit different sheet breakup phenomena in the spatial domain. For instance, flapping breakup is induced by the central toroidal recalculation zone in the swirling flow field. Finally, the ligament formation mechanism and its diameter, i.e. the size of first-generation droplets, are measured with phase Doppler interferometry. The measured sizes scale reasonably with KH waves.
Fast Multipole accelerated boundary element method for elastic wave propagation in multi-region domains

Solving the 3-D elastodynamic equations using traditional boundary element methods (BEMs) is greatly hindered by the fully-populated nature of the BEM matrix. In a previous study limited to homogeneous media, we have established that the Fast Multipole (FM) method reduces the complexity of a 3-D elastodynamic BEM to N log N per GMRES iteration. Here, the methodology is extented to piecewise-homogeneous domains using a FM-accelerated multi-region BE-BE coupling. Numerical examples, and a simple preconditioning approach, are presented.
Mapping electron dynamics in highly transient EUV photon-induced plasmas: a novel diagnostic approach using multi-mode microwave cavity resonance spectroscopy

A new diagnostic approach using multi-mode microwave cavity resonance spectroscopy (MCRS) is introduced. This can be used to determine electron dynamics non-invasively in an absolute sense, as a function of time and spatially resolved. Using this approach, we have for the first time fully mapped electron dynamics specifically during the creation and decay of a highly transient pulsed plasma induced by irradiating a background gas with extreme ultraviolet (EUV) photons. In cylindrical geometry, electron densities as low as 1012 m−3 could be detected with a spatial resolution of (sub)100 µm and a temporal resolution of (sub)100 ns. Our experiments clearly show production of electrons even after the in-band EUV irradiation fades out. This phenomenon can be explained by both photoionization by out-of-band EUV radiation emitted by the EUV source later in time and delayed electron impact ionization by electrons initially created by in-band EUV photoionization. From the analysis, the absolute width of the electron cloud in the probing volume could also be retrieved temporally resolved. This data clearly indicates cooling of electrons. From an application perspective, it is demonstrated that the method can be used as a non-invasive and in-line monitor for ionizing radiation in terms of beam power, profile and pointing stability.