Search Results (467)

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a worldwide challenge. There are an estimated 17–24 million patients worldwide, with an estimated 60 percent or more who have not been diagnosed. Without a known cure, no specific curative medication, disability lasting years to being life-long, and disagreement among healthcare providers as to how to most appropriately treat these patients, ME/CFS patients are in need of assistance. Appropriate healthcare provider education would increase the percentage of patients diagnosed and treated; however, in-school healthcare provider education is limited. To address the latter issue, the New Jersey Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Association (NJME/CFSA) has developed an independent, incentive-driven, learning program for students of the health professions. NJME/CFSA offers a yearly scholarship program in which applicants write a scholarly paper on an ME/CFS-related topic. The efficacy of the program is demonstrated by the 2024–2025 first place scholarship winner’s essay, which addresses the biological basis of ME/CFS and how the healthcare provider can improve the quality of life of ME/CFS patients. For the reader, the essay provides an update on what is known regarding the biological underpinnings of ME/CFS, as well as a medical student’s perspective as to how the clinician can provide care and support for ME/CFS patients. The original essay has been slightly modified to demonstrate that ME/CFS is a worldwide problem and for publication. Full article

This study investigates how differing national research governance models impact academic performance by comparing European Research Council (ERC) grant winners in the social sciences and humanities from France and the Netherlands. Situated within the broader context of centralized versus decentralized research systems, the analysis aims to understand how these structures shape publication trends, thematic diversity, and collaboration patterns. Drawing on Scopus and SciVal data covering 9996 publications by 305 ERC winners between 2019 and 2023, we employed a multi-method approach, including latent Dirichlet allocation for topic modeling, compound annual growth rate analysis, and co-authorship network analysis. The results show that neuroscience, climate change, and psychology are dominant domains, with language and linguistics particularly prevalent in France and law and political science in the Netherlands. French ERC winners are more likely to be affiliated with national or sectoral institutions, whereas in the Netherlands, elite universities dominate. Collaboration emerged as a key success factor, with an average of four co-authors per publication and network analyses revealing central figures who bridge topical clusters. International collaborations were consistently linked with higher visibility, while single-authored publications showed limited impact. These findings suggest that institutional context and collaborative practices significantly shape research performance in both countries. Full article

Bivalves are nowadays represented by several thousand species of variable sizes and shapes. Additionally, thousands more species occurred during their 500-million-year long evolution. Present on Earth since the Cambrian, the class Bivalvia experienced periods of gradual evolution, interspersed with periods of rapid changes. Some groups of bivalves, namely clams, oysters, scallops, and marine mussels, managed to survive a series of extinctions, and their descendants still thrive in modern oceans and seas. Other groups, such as the rudists, completely disappeared from marine environments, after undergoing successful evolutionary radiation. In this study, we consider the possible reasons for the longevity of some bivalve orders and discuss the possible causes of demise of several once-successful clades. As expected, a small body size, large number of specimens, infaunal mode of life, motility, and long-living planktonic larvae proved to be evolutionary advantages during stress periods. The ability to harbor chemosymbionts could be an additional benefit during biotic crises. Full article

This study aimed to describe the training leading to the Zwift Academy (ZA) Finals of a world-class road cyclist who earned a professional contract after winning the contest. Four years of daily power meter data were analyzed (male, 25 years old, 68 kg, VO₂max: 85 mL·min⁻¹·kg⁻¹, and 20-min power: 6.37 W·kg⁻¹), focusing on load, volume, intensity, and strategies. Early training alternated between long, moderate-intensity sessions and shorter high-intensity sessions, with easy days in between. Gradually, the structure was progressively modified by increasing the duration of moderate-intensity (MIT) and high-intensity (HIT) and, subsequently, moving them to “high-volume days”, creating a sort of “all-in days” with low-intensity (LIT), MIT, and HIT. Moderate use of indoor training and a few double low-volume, low-intensity sessions were noted. These data provide a deep view of a 4-year preparation period of ZA, providing suggestions for talent identification and training, thereby highlighting the importance of gradual progression in MIT and HIT. Full article

Variable selection is important for developing accurate and interpretable prediction models. While classical and penalized methods are widely used, few simulation studies provide meaningful comparisons. This study compares their predictive performance and model complexity in low-dimensional data. Three classical methods (best subset selection, backward elimination, and forward selection) and four penalized methods (nonnegative garrote (NNG), lasso, adaptive lasso (ALASSO), and relaxed lasso (RLASSO)) were compared. Tuning parameters were selected using cross-validation (CV), Akaike information criterion (AIC), and Bayesian information criterion (BIC). Classical methods performed similarly and produced worse predictions than penalized methods in limited-information scenarios (small samples, high correlation, and low signal-to-noise ratio (SNR)), but performed comparably or better in sufficient-information scenarios (large samples, low correlation, and high SNR). Lasso was superior under limited information but was less effective in sufficient-information scenarios. NNG, ALASSO, and RLASSO outperformed lasso in sufficient-information scenarios, with no clear winner among them. AIC and CV produced similar results and outperformed BIC, except in sufficient-information settings, where BIC performed better. Our findings suggest that no single method consistently outperforms others, as performance depends on the amount of information in the data. Lasso is preferred in limited-information settings, whereas classical methods are more suitable in sufficient-information settings, as they also tend to select simpler models. Full article

Psychological momentum dynamics in tennis have triggered interest for a long time, but measuring their impact presents substantial obstacles. In this paper, we present an approach to quantify momentum that combines real-time winning probabilities, leverage, and an exponentially weighted moving average (EWMA). We test the method on a high-profile match between Carlos Alcaraz and Novak Djokovic, demonstrating how changes in leverage affect momentum. Furthermore, we use feature extraction methods from time series analysis to derive momentum-related characteristics, which are critical inputs for creating an eXtreme Gradient Boosting (XGBoost) binary classification model to predict game winners. The algorithm has an average accuracy of 84% and provides real-time predictions of each player’s chances of winning the match. Our findings indicate that momentum is a somewhat relevant element in forecasting match outcomes, highlighting its potential value in improving match prediction systems. Full article

Traditional approaches to constructing thermally conductive networks typically necessitate costly equipment and intricate processes, rendering them unsuitable for mass production and commercialization. Here, we propose a facile strategy to construct highly oriented boron nitride/polyacrylate pressure-sensitive adhesive frameworks by a calendering process. A UV light-based bulk polymerization method is adopted to prepare the pressure-sensitive adhesives (PSAs), which makes the preparation process solvent-free and volatile organic compound (VOC)-free, and environmentally friendly compared to emulsion and solvent-based pressure-sensitive adhesives. This simple, economical and scalable method provides new ideas and ways for the preparation of advanced thermal conductive networks. The highly oriented and flexible m-BNNSs/polyacrylate pressure-sensitive adhesive composites (m-BNNSs/PSAs-Ori) exhibited a significantly high thermal conductivity (TC) of 0.9552 W/(m·K) at 25 wt% filler content. Significantly, m-BNNSs/PSAs-Ori composites showed a better thermal response than the single-layer thermally conductive pressure-sensitive adhesive. Moreover, the composites also possess excellent electrical insulation and mechanical properties. This exploration not only provides a reasonable design scheme for thermal interface materials, but also promotes the practical application of polyacrylate pressure-sensitive adhesive composites in thermal management. Full article

In subsurface geological mapping, it is more than advisable to compare different solutions obtained with neural and other algorithms. Here, for such comparison, we used the previously published and well-prepared dataset of subsurface data collected from the Bjelovar Subdepression, a 2900 km² large regional macrounit in the Croatian part of the Pannonian Basin System. Data on depth were obtained for the youngest (the shallowest) Lonja Formation (Pliocene, Quaternary) and mapped using neural network (NN), inverse distance weighting (IDW), and ordinary kriging (OK) algorithms. The obtained maps were compared based on square error (using k-fold cross-validation) and the visual interpretation of isopaches. Two other algorithms were also tested, namely, random forest (RF) and extreme gradient boosting (XGB) algorithms, but they were rejected as inappropriate for this purpose solely based on the visuals of the obtained maps, which did not follow any interpretable geological structures. The results showed that NN is a highly adjustable method for interpolation, with adjustment for numerous hyperparameters. IDW showed its strength as one of the classical interpolators, and its results are always located close to the top if several methods are compared. OK is the relative winner, showing the flexibility of variogram analysis regarding the number of data points and possible clustering. The presented variogram model, even with a relatively high sill and occasional nugget effect, can be well fitted into OK, giving better results than other methods when applied to the presented area and datasets. This was not surprising because kriging is a well-established method used exclusively for interpolation. In contrast, NN and machine learning algorithms are used in many fields, and these algorithms, particularly the fitting of hyperparameters in NN, simply cannot be the best solution for all. Full article

Background: To achieve victory, kayaking and rowing athletes must develop optimal aerobic conditioning and the capacity to sustain anaerobic work production. To assess these characteristics, power output (PO), lactatemia response, and maximum oxygen uptake (VO₂max) are usually measured. The goal of this research is to report the values of PO, lactatemia, and VO₂max—expressed in relative, absolute, and body size-scaled values—in successful international-level athletes to provide reference values for those striving to compete at the highest level. Methods: A total of 15 international-level medallist boat sports athletes were recruited: 8 male kayakers (age 21 ± 3 years, height 181.7 ± 5.3 cm, body mass 78.7 ± 5.6 kg), 2 female kayakers (age 22 ± 2 years, height 168.0 ± 2.8 cm, body mass 64.9 ± 2.7 kg), and 5 male rowers (age 20 ± 1 years, height 181.9 ± 4.7 cm, body mass 83.9 ± 7.3 kg). The athletes’ PO, lactatemia, and VO₂max were assessed using an off-water, sport-specific cardiopulmonary test on a paddle and rowing ergometer. Results: Respectively, in male and female kayakers and male rowers, maximum lactatemia was 11.9 ± 2.2 mmol/L, 9.3 ± 3.6 mmol/L, and 13.2 ± 3.7 mmol/L; maximum PO was 225.0 ± 13.4 W, 162.5 ± 31.8 W and 432.0 ± 33.5 W; and VO₂max was 57.6 ± 5.4 mL/min/kg, 52.2 ± 1.0 mL/min/kg, and 63.7 ± 11.7 mL/min/kg. VO₂max scaled by body size was, respectively, 311 ± 39 mL/kg^0.67/min, 319 ± 15 mL/kg^0.67/min, and 330 ± 72 mL/kg^0.67/min. Conclusions: This study is the first to report the values of PO, lactatemia, and VO₂max—expressed in relative, absolute, and body size-scaled values—assessed during a sport-specific cardiopulmonary test in international-level boat sports athletes. These values could be a preliminary reference guideline for optimal cardiorespiratory conditioning in athletes aiming at international-level competitions. Full article

This study investigates the evolutionary mechanisms and equilibrium character-istics of the China–US trade dispute through an improved ecological competition model. By quantifying tariff policies as competition intensity regulators and introducing trade elasticity parameters, we construct a dynamic system that captures the nonlinear feedback between economic rivals. Key findings are as follows. (1) When both nations implement reciprocal tariff measures with similar economic sensitivities, the system converges to a stable equilibrium where bilateral economic outputs stabilize at reduced levels compared to pre-conflict states, provided the product of adjusted competition coefficients remains below critical thresholds. (2) Excessive tariff escalation beyond identifiable tipping points triggers winner-takes-all outcomes, validating the “Thucydides Trap” hypothesis in eco-nomic conflicts. (3) Empirical simulations using 2018–2023 trade data demonstrate that China’s tit-for-tat tariff strategy effectively maintains competitive balance, while domestic market expansion measures (evidenced by a 6.3% average annual growth in China’s do-mestic consumption) significantly mitigate trade diversion effects. The study establishes theoretical connections with optimal tariff theory and strategic trade policy literature while providing policymakers with quantitative tools to assess trade policy impacts. Our find-ings theoretically validate China’s policy combination of calibrated reciprocity and domestic demand stimulation, offering new insights into managing great-power economic competition. Full article

Along with the principal rare earth (REE) minerals such as monazite, xenotime, and bastnasite, Y-and REE-bearing zircon and associated minerals survive the combustion process and are found in coal-combustion fly ash. Beneficiated fly ash from a power plant burning an eastern-Kentucky-sourced coal blend was found to have zircon (ZrSiO₄), baddeleyite (ZrO₂), fergusonite (YNbO₄), yttriaite (Y₂O₃), and xenotime (YPO₄). Previous studies of the same fly had also identified monazite with a broad REE suite. Scanning electron microscopy–electron dispersive spectroscopy (EDS) and transmission electron microscopy (TEM)–EDS as well as other TEM-based techniques revealed a variety of zircon associations, including heavy-REE suites with Y, Nb, and Hf. Hafnium is a common accessory element in zircons and the Y and Nb may be present as fergusonite (YNbO₄) intermixed with zircon. Full article

A multi-strategy enhanced version of the escape algorithm (mESC, for short) is proposed to address the challenges of balancing exploration and development stages and low convergence accuracy in the escape algorithm (ESC). Firstly, an adaptive perturbation factor strategy was employed to maintain population diversity. Secondly, introducing a restart mechanism to enhance the exploration capability of mESC. Finally, a dynamic centroid reverse learning strategy was designed to balance local development. In addition, in order to accelerate the global convergence speed, a boundary adjustment strategy based on the elite pool is proposed, which selects elite individuals to replace bad individuals. Comparing mESC with the latest metaheuristic algorithm and high-performance winner algorithm in the CEC2022 testing suite, numerical results confirmed that mESC outperforms other competitors. Finally, the superiority of mESC in handling problems was verified through several classic real-world optimization problems. Full article

In 2023, the Ascon cipher suite was selected as the winner of the National Institute of Standards and Technology (NIST) standardization process for lightweight cryptography, and has emerged as the leading candidate for cryptographic algorithms in resource-constrained environments. This cipher suite provides authenticated encryption with associated data and hash functionality. NIST’s Ascon proposal consists of two symmetric ciphers, Ascon-128 and Ascon-128a, a hash function, Ascon-HASH, an extendible output function, Ascon-XOF, and a new cipher variant, Ascon-80pq, with increased resistance to quantum attacks. This study presents an overview of the mathematical background, security principles and key properties of the Ascon cipher suite. In addition, a comprehensive performance evaluation of Ascon on various Arduino platforms, such as Arduino DUE, Arduino Mega2560, Arduino Nano Every and Arduino Nano ESP32, is performed. A detailed comparative analysis of these implementations is also provided. Full article

The Help, winner of the 2009 Exclusive Books Boeke Prize, is the debut novel of American author Kathryn Stockett. Taking Jacques Derrida’s “Politics of Friendship” as the major theoretical framework, this research examines the transformation from the white community and the Black community to the trans-racial community through the emotional interaction between white mistresses and Black maids. The distinctively exclusive white community perpetuates racial discrimination and confronts Black others with hostility, while the racially injured Black people can only seek mutual refuge and friendly affection in the Black community. On the surface, the white community and the Black community are antagonistic. However, the racist system has entangled the emotions and fates of the three protagonists with different identities. In the book, when the Black people open their hearts to tell their stories and gain support and trust within the community, white people not only witness social injustice, but also unconditionally assume responsibility for the “other” when facing Black “others”. Based on the “law of unconditional love”, the novel breaks through the inherent limitations based on race, class, geography, etc., and calls for the advent of the politics of friendship and the formation of trans-racial communities. Full article