Miracle-dz/UniFAR-FTUs huggingface dataset:
What supports and what thwarts Olympic athlete well-being?: Coach and organizational perspectives

Abstract The purpose of our study was to examine the perspectives of Olympic coaches and national performance directors regarding factors they felt influence athlete well-being (both positively and negatively), and to explore their perceived roles in contributing to the well-being of their athletes. Coaches (n = 12) and national performance directors (n = 12) participated in semi-structured interviews, that were subjected to reflexive thematic analysis. We adopted a critical interpretivist research paradigm for this study. The findings included three higher-order themes, each of which encompassed two lower-order themes. These higher-order themes included the relentless pursuit of results (i.e., lack of opportunities outside of sport, the focus on results as harmful), the influence of the coach (i.e., the coach as a relationship builder, the coach as a gatekeeper of well-being), and financial uncertainty (i.e., financial uncertainty of the program, financial uncertainty for the athlete). When taken together, the findings highlight that coaches and performance directors were often aware of threats to athlete well-being but were also uncertain how to support athlete well-being or of their role in potentially thwarting the well-being of their Olympic athletes. These findings are discussed within the broader context of the pervading culture of elite sport, and consideration for future research and knowledge mobilization. Lay summary: In this study, we queried Olympic coaches and performance directors regarding factors they felt influence elite athlete well-being, and what they felt their role is in contributing to the well-being of the athletes with whom they work. The findings within our study provide new insight into elite athlete well-being, including potential negative consequences related to the relentless pursuit of results, the impact of the coach, and the effects of financial uncertainty for Olympic athletes. Implications for Practice: The findings highlight that various threats to Olympic athlete well-being persist as a consequence of the underpinning incentive system and priorities within elite sport. The findings demonstrate that coaches and performance directors are, at times, unaware of their role in negatively influencing the well-being of the Olympic athletes with whom they work. The findings underscore that coaches and performance directors acknowledge results are prioritized over all else, but are also often unaware of how to best support the well-being of athletes with whom they work.
Density Compression Ratio across Relativistic‐Strong‐Shock Waves

The relativistic Rankine‐Hugoniot shock wave conditions of Taub are extended to include radiation pressure and energy density. Specialization to the situation of a nonrelativistic ambient gas gives strong shocks, and solutions are obtained separately for the cases of a pure material gas and a pure radiation gas behind the shock. The material gas is considered to have a constant adiabatic exponent γ ≤ 2, or to be itself relativistic, and the value γ=43 gives the radiation gas results. The rest density compression increases above its nonrelativistic strong shock limit (γ + 1)/(γ − 1), by a term proportional to β2 in the lowest order, where β is the ratio of shock velocity to light velocity. As β → 1 (extreme relativistic strong shock) the rest density compression goes as 1/(1 − β2)½, but there is no setting‐in of degeneracy in the shocked gas. In shock coordinates, the flow velocity ratio across the shock (front to back) decreases monotonically from its nonrelativistic limit and approaches the value 1/(γ − .
Exploring Stroke Risk Factors and Outcomes in Sexual and Gender Minority People

Background and Objectives Cerebrovascular disease in sexual and gender minority (SGM) people remains poorly understood. Our primary objective was to describe the epidemiology and outcomes in a sample of SGM people with stroke. As a secondary objective, we compared this group with non-SGM people with stroke to assess for significant differences in risk factors or outcomes. Methods This was a retrospective chart review study of SGM people admitted to an urban stroke center with primary diagnosis of stroke (ischemic or hemorrhagic). We evaluated stroke epidemiology and outcomes, summarizing with descriptive statistics. We then matched 1 SGM person to 3 non-SGM people by year of birth and year of diagnosis to compare demographics, risk factors, inpatient stroke metrics, and outcomes. Results A total of 26 SGM people were included in the analysis: 20 (77%) had ischemic strokes, 5 (19%) intracerebral hemorrhages, and 1 (4%) subarachnoid hemorrhage. Compared with non-SGM people (n = 78), stroke subtypes showed a similar distribution (64 (82%) ischemic strokes, 12 (15%) intracerebral hemorrhages, 1 (1%) subarachnoid hemorrhage, and 1 nontraumatic subdural hematoma, p > 0.05) but suspected ischemic stroke mechanisms had a different distribution (χ2 = 17.56, p = 0.01). Traditional stroke risk factors were similar between the 2 groups. The SGM group seemed to have higher rates of nontraditional stroke factors, including HIV (31% vs 0%, p < 0.01), syphilis (19% vs 0%, p < 0.01), and hepatitis C (15% vs 5%, p < 0.01) but were more likely to be tested for these risk factors (χ2 = 15.80, p < 0.01; χ2 = 11.65, p < 0.01; χ2 = 7.83, p < 0.01, respectively). SGM people were more likely to have recurrent strokes (χ2 = 4.39, p < 0.04) despite similar follow-up rates. Discussion SGM people may have different risk factors, different mechanisms of stroke, and higher risk of recurrent stroke compared with non-SGM people. Standardized collection of sexual orientation and gender identity would enable larger studies to further understand disparities, leading to secondary prevention strategies.
Layered Meta-Learning Algorithm for Predicting Adverse Events in Type 1 Diabetes

Type 1 diabetes mellitus (T1D) is a chronic disease that, if not treated properly, can lead to serious complications. We propose a layered meta-learning approach based on multi-expert systems to predict adverse events in T1D. The base learner is composed of three deep neural networks and exploits only continuous glucose monitoring data as an input feature. Each network specializes in predicting whether the patient is about to experience hypoglycemia, hyperglycemia, or euglycemia. The output of the experts is passed to a meta-learner to provide the final model classification. In addition, we formally introduce a novel parameter, $\alpha $ , to evaluate the advance by which a prediction is performed. We evaluate the proposed approach on both a public and a private dataset and implement it on an edge device to test its feasibility in real life. On average, on the Ohio T1DM dataset, our system was able to predict hypoglycemia events with a time gain of 22.8 minutes, hyperglycemia ones with an advance of 24.0 minutes. Our model not only outperforms presented models in the literature in terms of events predicted with sufficient advance, but also with regard to the number of false positives, achieving on average 0.45 and 0.46 hypo- and hyperglycemic false alarms per day, respectively. Furthermore, the meta-learning approach effectively improves performance in a new cohort of patients by training only the meta-learner with a limited amount of data. We believe our approach would be an essential ally for the patients to control the glycemic fluctuations and adjust their insulin therapy and dietary intakes, enabling them to speed up decision-making and improve personal self-management, resulting in a reduced risk of acute and chronic complications. As our last contribution, we assessed the validity of the approach by exploiting only blood glucose variations as well as in combination with the information of the insulin boluses, the skin temperature, and the galvanic skin response. In general, we have observed that providing other information but CGM leads to slightly lower performances with respect to considering CGM alone.
A Comparative Study of Star-forming and Quiescent Dwarf Galaxies

We present the results from a comparative study of the atomic hydrogen (H I) and optical properties of a sample of 16 dwarf galaxies, chosen to investigate the effects of star formation on the properties of low-mass systems. The violent star formation bursts believed to occur in these low-mass systems suggest a possible connection between the actively star-forming blue compact dwarfs (BCDs), and the quiescent low surface brightness dwarfs (LSBDs). It has been suggested that LSBDs, upon undergoing a burst of star formation, will evolve into BCDs and then back into LSBDs when the star formation slows or stops as the H I column density falls below the critical threshold necessary to support it. We have examined the location and kinematics of H I in eight BCDs and eight LSBDs of similar H I masses and a range of color indices to investigate this "evolutionary" sequence. The starburst episodes in these low-mass galaxies should lead to (1) a dispersal/depletion of the H I seen in the eight LSB dwarfs and (2) more centrally concentrated and agitated H I in the eight BCDs. The results of this project indicate that the quiescent LSBD galaxies have more diffuse H I distributions and often show a ringlike structure, while the active galaxies have more highly centrally concentrated H I reservoirs. The bluer, more recently active systems of both types also have higher internal H I velocity dispersions, indicating that energy has been pumped into the interstellar medium of these galaxies. These observations are consistent with an evolutionary scheme wherein the H I reservoirs in these galaxies take on different characteristics depending upon their star formation histories.
Asymptotic methods applied to semiconductor laser models

Semiconductor lasers subject to a weak external perturbation (optical injection, optical feedback) are unstable devices that generate pulsating intensities. Most of our understanding of these instabilities comes from intensive numerical simulations of simple model equations. These computations are long and delicate because the solution of the laser equations exhibits several time scales. Asymptotic methods may either simplify the laser original equations or lead to useful approximations of the solution of these equations. We illustrate these techniques by reviewing the Hopf bifurcation problem of the well known Lang and Kobayashi equations modeling a laser subject to optical feedback. Basic approximations are reviewed, a low pump problem is examined in detail, and analytical approximations of the (multiple) Hopf bifurcation line in the case of a short cavity are derived for the first time.
The threat of political extraction and corporate cash holdings: The case of the GCC countries

Abstract This study examines the motives of corporations in the Gulf Cooperation Council (GCC) countries to hold cash with a focus on institutional characteristics related to the threat of political extraction. Using firm-level financial data and macro-level and institutional data and applying the GMM estimation method, the study finds that corruption (a proxy of the threat of political extraction) is positively related to cash holdings which suggests that the risk of political extraction induces GCC firms to accumulate cash to make political payoffs and preserve their financial flexibility. In terms of firm-level characteristics, GCC firms follow a pecking order as they deplete more cash the larger their capital expenditures. In addition, GCC firms save cash for transaction and precautionary purposes as indicated by the negative relation between cash and cash substitutes. This is the first study to examine the threat of political extraction on cash holdings using the context of the GCC, a cash-rich region with unique institutional settings. The findings on the GCC countries contribute to the ongoing debate regarding the political extraction-cash holdings relationship by examining a context under which corruption is likely to exert a positive impact on the level of cash holdings.
Mindlin plate buckling with prebuckling in-plane deformation

Ziegler pioneered the study of thick-plate buckling with allowance for the effect of prebuckling in-plane deformation and concluded that this effect is of the same order of magnitude as that due to shear deformation. This research work further explores this important effect on the elastic buckling loads of rectangular plates with various boundary conditions, thicknesses, aspect ratios, and Poisson's ratios. In contrast to Ziegler's static-kinematic approach, the incremental total potential energy approach is adopted. Based on the derived energy functional, the recent pb-2 Rayleigh-Ritz method is applied for solution. The present energy approach is more convenient for handling plates with any combination of support conditions, as compared to Ziegler's approach of having to solve a somewhat difficult boundary-value problem. The salient aspects of plate buckling with prebuckling deformation effect are discussed.
Likelihood-Based Boosting in Binary and Ordinal Random Effects Models

This article presents a likelihood-based boosting approach for fitting binary and ordinal mixed models. In contrast to common procedures, this approach can be used in high-dimensional settings where a large number of potentially influential explanatory variables are available. Constructed as a componentwise boosting method, it is able to perform variable selection with the complexity of the resulting estimator being determined by information criteria. The method is investigated in simulation studies both for cumulative and sequential models and is illustrated by using real datasets. The supplementary materials for the article are available online.
Underrepresented Minority Students in College: The Role of Classmates

The role of racial diversity at colleges has been debated for over more than a half a century with limited quasi-experimental evidence from classrooms. To fill this void, I estimate the extent that classmate racial compositions affect Hispanic and African American students at a large and oversubscribed California community college where they are minorities. I find that when minority students are exposed to a greater share of same-race classmates, they are more likely to complete the class with a pass and are more likely to enroll in a same-subject course the subsequent term. The findings are robust to first-time students with the lowest registration priority versus all students and different combinations of fixed effects (e.g., student, class, and instructor race).
Pressure Reconstruction from the Measured Pressure Gradient Using Gaussian Process Regression

Many numerical algorithms have been established to reconstruct pressure ﬁelds from measured kinematic data with noise by Particle Image Velocimetry (PIV), such as the Pressure Poisson solver and the Omni-Directional Integration (ODI) method. This study adopts Gaussian Process Regression (GPR), a probabilistic framework with an intrinsic de-noising mechanism to tackle drawbacks of traditional Pressure Poisson solver and compares the performance with ODI. To evaluate the accuracy of the algorithm, GPR and ODI are tested in detail in a canon-ical setup of forced homogeneous isotropic turbulence from the Johns Hopkins Turbulence Database. According to the result, GPR has the same level of accuracy as ODI with optimized hyper-parameters for the isotropic turbulence ﬂow. However, GPR has the tendency to ﬂatten impulsive signals. Therefore, without further modiﬁcations, it is not suitable to detect ﬂow structures with impulsive true signals. The error propagation of the proposed framework is also analyzed and discussed in both physical and spectral spaces.
The Effects of Model Parsimony and Sampling Error on the Fit of Structural Equation Models

The fit between a structural equation model and a data set is operationalized as the value of goodness-of-fit indices. The discrepancy between the estimated value and the value indicating perfect fit has three sources: misspecification, error arising from theoretical parsimony in the description of the model (parsimony error), and sampling error. Misspecification, which represents a disparity between “realworld” relationships and relationships in the model, is the most important source of error for researchers. It cannot be accurately assessed, however, unless parsimony error and sampling error are taken into account. Parsimony error occurs in measurement models when secondary relationships are excluded. Secondary relationships are defined here as secondary factor loadings and error term correlations that have small values, no theoretical bases, and no substantive meaning. A simulation was conducted to examine the effects of parsimony error on perfect measurement models and to establish appropriate criteria for model fit when parsimony error is present.
Analysis of effective resistance and eddy-current losses in multiturn winding of high-frequency magnetic components

This paper develops a numerical model for calculation of eddy-current losses in a multiturn winding of a high-frequency transformer. The model assumes periodic arrangement of conductors, and uses the repeat elementary cell concept. The paper proposes analytical expressions and graphic dependences to determine effective frequency-dependent resistance of the winding. It computes the leakage field in the transformer window, taking into consideration the effective magnetic permeability of the multiturn winding as a heterogeneous medium. Finally, it analyzes the values of the resistance at various frequencies for two types of winding (solid conductor winding and Litz wire winding) by numerical and experimental methods.
Convergence analysis of nonlinear dynamical systems by nested Lyapunov functions

A method for estimating the domain of attraction of an asymptotically stable equilibrium point of a nonlinear dynamical system and for deriving an upper bound on the time of convergence in the estimated domain is presented. It is based on a set of Lyapunov functions. Defined on nested regions in the state space. The estimated domain, obtained as the union of a subset of these regions, is based on a local Lyapunov-like condition for the convergence of the solution in each region to its inner boundary. A bound on the time of convergence within the estimated domain is given by the sum of the local bounds. This concept is implemented using a class of regions whose boundaries are described by Fourier series.
Physics of liquid jets

Jets, i.e. collimated streams of matter, occur from the microscale up to the large-scale structure of the universe. Our focus will be mostly on surface tension effects, which result from the cohesive properties of liquids. Paradoxically, cohesive forces promote the breakup of jets, widely encountered in nature, technology and basic science, for example in nuclear fission, DNA sampling, medical diagnostics, sprays, agricultural irrigation and jet engine technology. Liquid jets thus serve as a paradigm for free-surface motion, hydrodynamic instability and singularity formation leading to drop breakup. In addition to their practical usefulness, jets are an ideal probe for liquid properties, such as surface tension, viscosity or non-Newtonian rheology. They also arise from the last but one topology change of liquid masses bursting into sprays. Jet dynamics are sensitive to the turbulent or thermal excitation of the fluid, as well as to the surrounding gas or fluid medium. The aim of this review is to provide a unified description of the fundamental and the technological aspects of these subjects.
The Benefits of Molnupiravir Treatment in Healthcare Facilities Patients with COVID-19

Background Molnupiravir (MOL) is an oral antiviral medication that has recently been treated for COVID-19. Objectively We perform a prospective and observational study to elucidate the efficacy and safety of MOL in healthcare patients with COVID-19. Materials and Methods A observational, non-randomized study of patients diagnosed with COVID-19 in 46 healthcare facilities and treated with MOL started within 5 days after the onset of signs or symptoms. We recorded data for all patients, including demographic data, clinical features, and symptoms. Treatment response was classified into cure, stable, hospitalization and death. Multivariate analysis was performed with stepwise logistic regression for hospitalization and death risk factors. Results In total, 856 patients were diagnosed as having COVID-19 and treated with MOL during the study period. Of those, 496 patients (57.9%) were cured, 256 patients (29.9%) in stable condition, 104 patients (12.2%) hospitalized, and 22 patients (2.6%) died, respectively. There was significant effectiveness (87.8%) in COVID-19 patients using MOL. Multivariate analysis was performed to confirm the risk factors for hospitalization and death and included elder age (>80 years old) (odds ratio (OR) 2.2, 95% confidence interval (CI): 1.1–6.9), old cerebrovascular accident (CVA) (OR=4.1, 95% CI: 1.3–9.9), the presence of diabetes mellitus (DM) (OR=2.6, 95% CI: 1.2–9.1) and chronic respiratory diseases (OR=2.4, 95% (CI): 1.3–8.1). Limitations This is an observational study, neither randomized study nor control group study. Conclusion Initial treatment with MOL has the treatment benefits and is well tolerated for patients with COVID-19 in healthcare facilities. Older age, old CVA, DM, and chronic respiratory diseases were independent risk factors for hospitalization and mortality. The results demonstrate there are important clinical benefits of MOL beyond the reduction in hospitalization or death for these patients with more comorbidities in Taiwan.
On the theory of Ostwald ripening: formation of the universal distribution

A theoretical description of the final stage of Ostwald ripening given by Lifshitz and Slyozov (LS) predicts that after long times the distribution of particles over sizes tends to a universal form. A qualitative behavior of their theory has been confirmed, but experimental particle size distributions are more broad and squat than the LS asymptotic solution. The origin of discrepancies between the theory and experimental data is caused by the relaxation of solutions from the early to late stages of Ostwald ripening. In other words, the initial conditions at the ripening stage lead to the formation of a transition region near the blocking point of the LS theory and completely determine the distribution function. A new theoretical approach of the present analysis based on the Slezov theory (Slezov 1978 Formation of the universal distribution function in the dimension space for new-phase particles in the diffusive decomposition of the supersaturated solid solution J. Phys. Chem. Solids 39 367–74; Slezov 2009 Kinetics of First-Order Phase Transitions (Weinheim: Wiley, VCH)) focuses on a relaxation dynamics of analytical solutions from the early stage of Ostwald ripening to its concluding state, which is described by the LS asymptotic regime. An algebraic equation for the boundaries of a transition layer independent of all material parameters is derived. A time-dependent function ε ( τ ) ? > responsible for the evolution of solutions at the ripening stage is found. The distribution function obtained is more broad and flat than the LS asymptotic solution. The particle radius, supersaturation and number density as functions of time are determined. The analytical solutions obtained are in good agreement with experimental data.