Browse Articles

Effects of the competition schedule in major-competition years on performance in major-competition: Evidence from speed- and power-type track and field events

Objective This study aimed to examine the association between competition schedules in major-competition years (Olympic or World Championships years, M-Years) and performance in major-competition (M-Performance) among athletes in speed- and power-type track and field events. Methods This was a retrospective observational study involving athletes who competed in speed- and power-type track and field events at the World Athletics Championships or the Olympic Games between 1993 and 2019, yielding 14,584 valid observations. First, a two-step cluster analysis was conducted to identify typical M-Year competition schedules based on the annual total number of competitions and the proportions of performance states at each level. Next, baseline regression models were used to identify differences in M-Performance across competition-schedule types and to determine the “optimal competition schedule.” Finally, fixed-effects models were employed to explore the association between adjusting from a “suboptimal competition schedule” to the “optimal competition schedule” and M-Performance. Results Athletes’ competition schedules in M-Years were classified into three types: “major-event–focused,” “competition-oriented,” and “competition-as-training.” Among these, athletes under the “competition-oriented” schedule exhibited significantly better M-Performance than those under the other two schedules. Further analysis showed that adjustment from a “competition-as-training” schedule to a “competition-oriented” schedule was associated with higher M-Performance, whereas adjustment from a “major-event–focused” schedule to a “competition-oriented” schedule showed no similar association. Conclusions In M-Years, even the optimal competition schedule may not be suitable for all athletes, and its effectiveness may vary by athlete type. For “competition-as-training” athletes, adjusting toward a “competition-oriented” schedule may be associated with higher M-Performance. However, such adjustment may have limited benefits for “major-event–focused” athletes. To the best of our knowledge, this study is the first to conduct a large-scale empirical analysis of competition scheduling in major-competition years. The findings provide an empirical basis for future studies to further examine the causal relationship between competition-schedule adjustments and M-Performance, while also offering practical reference for athletes and coaching teams preparing for major events such as the Olympic Games and the World Athletics Championships.

A qualitative approach to extract diagnostic patterns of cognitive impairment in Parkinson’s disease

Temperament, personality and decision-making accuracy in handball referees

Accurate decision-making is essential for effective handball officiating, yet little is known about how stable psychological traits relate to referees’ decision-making accuracy. This study examined whether temperament and personality characteristics are associated with decision-making accuracy in handball referees. Forty-one officials from three competition levels (Second League, First League, Superleague) completed the FCB-TI and NEO-FFI inventories. Decision-making accuracy was assessed using a video-based test of game situations scored against expert judgments. Sensory Sensitivity showed a positive bivariate correlation with decision-making accuracy ( r  = 0.32, p  < 0.05). Multiple regression analysis revealed that competitive level accounted for 24% of the variance in decision-making accuracy ( R 2  = 0.24, p  = 0.001). Adding Sensory Sensitivity increased the explained variance to 30%, although its unique contribution did not reach statistical significance. Activity, as a temperament trait, showed different associations with decision-making accuracy across competition levels. No significant relationships were observed between Big Five personality traits and decision-making accuracy. These findings suggest that, among the variables examined, competitive level was the main factor associated with decision-making accuracy, while selected temperament traits, particularly Sensory Sensitivity and, to a lesser extent, Activity, may also be relevant to this outcome.

Investigating lifelong learners’ adoption of generative artificial intelligence using PLS-SEM and fsQCA within the UTAUT2 framework

A survey of UK and Irish veterinary and veterinary nursing Students’ engagement with small animal nutrition information

The global prevalence of diet-related non-communicable disease is rising, along with popularity of unconventional and alternative diets and the availability of unsubstantiated information. Considerable confusion and misinformation exist regarding nutrition and dietary choices. The veterinary healthcare team needs to be a trusted and primary source of sound nutritional advice and be able to signpost clients to appropriate nutrition information. This study’s objective was to establish the sources of nutrition information used by first-year veterinary students (VS) and veterinary nursing students (VNS) in the UK and Republic of Ireland. Participants were recruited by non-probability, convenience purposive sampling, by email invitation from educational providers. Data were collected between October 2023 and January 2024. Participation was voluntary and informed consent obtained. 135 VS and 186 VNS completed the online survey. Most (82%, n = 211) expressed an interest in learning about small animal nutrition. Qualified veterinarians were perceived to be more knowledgeable about pet nutrition (73%, n = 270) than veterinary nurses (53%, n = 132). Veterinary healthcare professional and journal articles ranked most valued sources of information, with media, social media, and friends/family least valuable. Students considered evidence-based information for dietary decisions by pet caregivers (93%, n = 213) to be important, yet only 53% (n = 138) felt sufficiently knowledgeable to access evidence-based nutritional information. This investigation highlights the paradox that trusted nutrition information sources are not always the most used. This insight into the nutrition information-seeking behaviour of student veterinary professionals can help inform educators in the provision of skills and knowledge to evaluate information and utilise trustworthy sources.

Analysis of the effects of metabolic syndrome and periodontitis on cortical-trabecular bone structure of the mandible and periodontal inflammation

Defining the link between peripheral neuronal activity and neuropathic pain: observational study protocol to investigate in vivo neurophysiological properties of nociceptors in patients with chronic neuropathic pain

Introduction Neuropathic pain affects up to 10% of the population and remains difficult to diagnose and treat effectively. Peripheral nociceptor hyperexcitability is thought to drive pain in a substantial subset of patients, yet human studies have not fully defined which nociceptor populations are abnormal or how these abnormalities relate to clinical phenotype, sensory profiling, or genetic mechanisms. Microneurography uniquely enables direct in vivo recording from human C-fibres, offering a mechanistic approach to patient stratification. This observational study investigates the relationships between neuropathic pain, nociceptor excitability, somatosensory phenotype, and genetic variation. Methods and analysis We will conduct an observational controlled study at the University of Oxford (2022–2029) following STROBE guidelines. Adults with and without neuropathy or neuropathic pain will undergo deep phenotyping, including questionnaires, neurological examination, quantitative sensory testing, nerve conduction studies, microneurography, skin biopsy, and genetic and transcriptomic analyses. Microneurography recordings will quantify C-fibre axonal properties, excitability, spontaneous activity, and responses to electrical, thermal, and mechanical stimulation. Participants will be stratified by neuropathy grade, neuropathic pain status, somatosensory phenotype, and genetic variants. Primary analyses will compare axonal excitability and related microneurography measures between participants with and without neuropathic pain. Secondary analyses will evaluate the associations between microneurography-derived nociceptor functional profiles and quantitative sensory phenotypes, and will assess the impact of rare ion-channel variants on C-fibre excitability. Multivariable regression, dimensionality reduction, and unsupervised clustering methods will be applied to delineate mechanistically informed patient subgroups. Ethics and dissemination Ethical approval was obtained from the South Central – Oxford C Research Ethics Committee (18/SC/0263). All participants will provide informed consent. Findings will be disseminated through peer-reviewed publications, conference presentations, and data-sharing compliant with institutional and funding-body policies. Strengths and limitations of this study The study uses microneurography, the only technique that directly records from human nociceptors in vivo, enabling detailed mechanistic assessment of C-fibre function. A deep phenotyping framework, including quantitative sensory testing, skin biopsy, nerve conduction studies, and genetic analysis, allows multidomain integration of clinical, neurophysiological, and molecular data. Classification of C-fibre subtypes using activity-dependent slowing provides a reproducible method to distinguish functional nociceptor populations. Extended microneurography protocols may not be feasible for all participants due to tolerability or signal instability, potentially reducing completeness of some secondary measures. As an observational study, causal inference is limited, and confounding will require careful adjustment despite prespecified statistical analyses.

Surrogate-assisted robust design optimization of flexible capture nets in stochastic near-ground wind fields

AI models: one country’s fears become everyone’s constraint

Epidemiological and genomic analysis of the dengue virus isolate from Jeddah, Saudi Arabia: Implications for future therapeutic development

Background Dengue fever is one of the major mosquito-borne diseases worldwide, and studies have shown that more than half of the world population could be at risk of dengue in the future. To date, there are no universally effective vaccines or specific antiviral treatments for dengue virus (DENV). Dengue fever has reported in the Western region of Saudi Arabia since 1994. A comprehensive understanding of the molecular epidemiology of the DENV in Saudi Arabia, with implications for therapeutic development, is still absent. Aim The present study aimed to integrate analysis of the circulating DENV genome and mutations of the most prevalent dengue serotype in the therapeutic context. Methods Retrospective data were used to conduct analysis of dengue infections in Jeddah city in Saudi Arabia from January to October 2024. All Saudis, non-Saudis, and Hajj and Umrah visitors with a confirmed diagnosis of dengue fever were included in the study. The demographic factors and DENV serotypes were explored. The genome of the most prevalent DENV serotype was sequenced using Oxford Nanopore Technology. Closely related strains were searched using the BLAST NCBI tool, and the NGPhylogeny server was used to analyze the phylogenetic relationship. In order to provide a biologically appropriate template for drug-design initiative, the dengue structural protein (prM) of an isolated strain was optimized through receptor modeling and mutation analysis using ICM tool. Results Analysis of the circulating DENV serotypes showed that higher incidence rates occurred in young adults, males, and from the Middle Eastern region of origin. The majority (95.3%) of confirmed cases were caused by the serotype DENV-2. A high nucleotide sequence identity was noted for strains originating from Pakistan (99.68%). Five ligands containing nitrogen-rich chemical scaffolds (piperidine, azoles, and sulfonamides) with a variety of substituents were identified by the study as possible binding hits to both wild-type and mutant prM receptor structures. Although of limited sample size and preliminary docking results, the epidemiological and molecular data generated in the study provide useful information for epidemic preparedness and possible therapeutic interventions.

Fibration symmetries and cluster synchronization in multi-body systems

The Enhanced Games and the normalization of doping: a public health concern

Alpha-synuclein overexpression reduces neural activity within a basal ganglia vocal nucleus in a zebra finch model

Changes in vocal pitch, loudness, and timing are prevalent in Parkinson’s Disease (PD) and a target for early intervention and treatment. The neural mechanisms underlying these impairments are not understood, motivating work in animal models. The adult male zebra finch songbird is uniquely poised for these studies given vocally-dedicated brain nuclei and a quantifiable output (birdsong). Our prior publication revealed that injection of an adeno-associated virus (AAV5) expressing the human (h) alpha-synuclein (h SNCA , a-syn) gene into basal ganglia vocal nucleus Area X results in elevated insoluble a-syn protein and parkinsonian-like changes including softer, shorter, and reduced vocalizations compared to controls. Here, we test the hypothesis that AAV-h SNCA overexpression reduces the firing rate of specific neuronal sub-types in Area X using in vivo recordings in anesthetized finches. Five classes of neurons were differentiated in AAV-treated finches based on waveform width (narrow vs. wide) and firing rates (low vs. high). We found that neurons in the AAV-h SNCA group with wide waveforms exhibited reduced firing rates and enhanced post-peak rebound compared to AAV controls. No differences in firing rate nor waveform shape were detected for the narrow waveform neurons. Our findings provide the first characterization of early a-syn-driven neural activity changes in vocal control neurocircuitry.

Validity and reliability of the Turkish version of the early symptom measurement of post-stroke depression short form (ESMPSD-SF)

Routine milk records reveal novel two-way interactions shaping ketosis risk in German dairy cows

Ketosis is one of the most prevalent metabolic disorders in dairy herds, with significant economic and welfare implications. However, existing literature often examines risk predictors in isolation, and their interactions and dependencies remain poorly understood. This study investigated how production, health, and management factors – and their interactions – are associated with ketosis risk (KR) at the animal level in German dairy cows, with a focus on German Holstein (GH) and German Simmental (SIM) breeds. Data from 76,809 cows across 717 German dairy farms collected between 2015 and 2019 were analyzed using multivariable generalized linear mixed-effects logistic regression with two-way interactions and random forest algorithms. KR was predicted using a non-invasive, widely applicable approach based on milk composition thresholds derived from monthly test-day records. Key risk factors included breed, parity, energy-corrected milk (ECM) yield, body condition, lameness, housing, and lactation stage. Twelve significant two-way interactions were identified, highlighting the multifactorial and interdependent nature of KR, most frequently involving lactation stage (six interactions), followed by ECM yield (five interactions) and breed (four interactions). The overall predicted probability of KR was 7.1%. Although high-yielding multiparous cows showed the highest absolute KR (prob. = 13.6% [95% CI 12.5–14.8]), high-yielding primiparous cows exhibited an unexpectedly elevated KR (prob. = 11.4% [95% CI 9.9–13.1]). Elevated KR was also observed in underconditioned cows during mid-early lactation (days in milk [DIM] 30–99, prob. = 21.0% [95% CI 18.6–23.5]), and SIM cows producing high ECM yields (>35 kg/day; prob. = 19.5% [95% CI 16.2–23.4]). The highest predicted KR occurred in underconditioned, first-parity cows housed in tie stalls, lame, and producing high ECM yields during mid-early lactation, indicating that specific combinations of risk factors amplify KR beyond the sum of their individual contributions. These findings highlight the importance of modeling interactions among animal-level and environmental factors to enable context-specific risk assessment. Evaluating breed, lactation stage, body condition, production level, housing, and health status jointly may support more targeted prevention strategies, particularly during the first 99 DIM, and improve identification of cows at elevated ketosis risk.

Athletes’ action recognition and performance prediction based on TS-GCN-SAM

Sustainability of affordable housing programs in Kenya: A case of Meru and Embu Counties

Amid rising urbanization and population growth, Kenya faces a critical housing shortage that disproportionately affects low- and middle-income populations. In response, the government launched the Affordable Housing Program (AHP) under the Big Four Agenda to address this housing gap. This study evaluates the sustainability of AHP projects in Meru and Embu counties, focusing on economic, social, and environmental dimensions. Using a descriptive research design, data were collected from 215 purposively selected participants comprising members of the public, academics, and contractors. Quantitative data were analyzed using Stata 18, including descriptive statistics, factor analysis, and Generalised Linear Models (GLMs). The results indicate that while the AHP has made significant progress in improving housing affordability and social safety, challenges remain, particularly in environmental sustainability, stakeholder engagement, and the use of local materials. Safety, security, and affordability ranked highest across respondents, whereas features such as lift access and energy-efficient systems were ranked lower. The findings also highlight demographic differences in sustainability preferences: older respondents emphasized safety and infrastructure reliability, whereas postgraduate respondents prioritized environmental sustainability. The study recommends stronger stakeholder involvement, localization of policy frameworks, and integration of green building standards. These insights provide valuable guidance for policymakers and practitioners seeking to scale sustainable housing solutions in Kenya and similar developing contexts.

Beyond survival: a cross-sectional analysis of guideline recommendations for cognitive, sexual, and psychological problems in adult cancer survivors

Bird flu H5N1 in Australia: protect Australian species from bird flu virus

Stakeholders’ discourse on generative AI in higher education: Insights from topic modeling and sentiment analysis

Owing to their remarkable proficiency in academic tasks, generative AI (GenAI) systems have been widely embraced in the education sector, stimulating debate among academics about their opportunities and challenges. However, extant studies tend to be narrowly focused, typically drawing on micro-level observations from small samples of students and educators, which limits the scope of reported findings. The present study contributes to the literature by capturing stakeholders’ discussions on the role of GenAI in higher education at scale. It does so by employing over 230K tweets shared on the subject of GenAI and education and training a topic modeling algorithm on this corpus. The model identified seven major themes that encapsulate the use cases and implications of GenAI adoption in higher education as articulated by stakeholders: learning assistant, research tool, productivity tool, assessment and examination, educational technology, adoption policy, and resources . Additionally, the study performed sentiment analysis to reveal the specific themes on which stakeholders expressed disproportionately positive and disproportionately negative attitudes toward GenAI adoption. By combining stakeholder theory and a big data approach, the current findings highlight both the practical and institutional concerns of GenAI beyond immediate classroom implications, such as student learning and assessment.