Search Results (1,791)

In football, accurately pinpointing key events like passes is vital for analyzing player and team performance. Despite continuous technological advancements, existing tracking systems still face challenges in accurately synchronizing events and positional data accurately. This is a case study that proposes a new method to synchronize events and positional data collected during football matches. Three datasets were used to perform this study: a dataset created by applying a custom algorithm that synchronizes positional and event data, referred to as the optimized synchronization dataset (OSD); a simple temporal alignment between positional and event data, referred to as the raw synchronization dataset (RSD); and a manual notational data (MND) from the match video footage, considered the ground truth observations. The timestamp of the pass in both synchronized datasets was compared to the ground truth observations (MND). Spatial differences in OSD were also compared to the RSD data and to the original data from the provider. Root mean square error (RMSE) and mean absolute error (MAE) were utilized to assess the accuracy of both procedures. More accurate results were observed for optimized dataset, with RMSE values of RSD = 75.16 ms (milliseconds) and OSD = 72.7 ms, and MAE values RSD = 60.50 ms and OSD = 59.73 ms. Spatial accuracy also improved, with OSD showing reduced deviation from RSD compared to the original event data. The mean positional deviation was reduced from 1.59 ± 0.82 m in original event data to 0.41 ± 0.75 m in RSD. In conclusion, the model offers a more accurate method for synchronizing independent datasets for event and positional data. This is particularly beneficial for applications where precise timing and spatial location of actions are critical. In contrast to previous synchronization methods, this approach simplifies the process by using an automated technique based on patterns of ball velocity. This streamlines synchronization across datasets, reduces the need for manual intervention, and makes the method more practical for routine use in applied settings. Full article

Background/Introduction: Psychological inflexibility, which includes experiential avoidance, is a transdiagnostic process associated with multiple mental health issues in adolescence. Physical fitness (PF) has shown benefits for mental well-being, yet its specific relationship with psychological inflexibility remains understudied, particularly among youth. Objectives: To examine the association between components of PF and psychological inflexibility, measured by the Acceptance and Action Questionnaire-II (AAQ-II), in a representative sample of Spanish adolescents. Methods: A cross-sectional analysis was conducted using data from 631 adolescents (aged 12–17) participating in the Eating Healthy and Daily Life Activities (EHDLA) study. PF was assessed by the Assessing the Levels of PHysical Activity and Fitness (ALPHA-Fit) Test Battery (cardiorespiratory fitness, muscular strength, agility, and flexibility). Psychological inflexibility was measured using the AAQ-II. Generalized linear models (GLMs) were used to evaluate associations, adjusting for age, sex, body mass index, socioeconomic status, physical activity, sedentary behavior, sleep duration, and energy intake. Results: Unadjusted analyses showed weak but significant associations between psychological inflexibility and performance in the 20 m shuttle run test (p = 0.002), the 4 × 10 shuttle run test (p = 0.005), and the sit-and-reach test (p < 0.001). However, after adjusting for covariates, none of the PF components maintained a statistically significant association with the AAQ-II scores. Conclusions: In this adolescent sample, PF components were not independently associated with psychological inflexibility after adjustment for key confounders. These findings suggest that, while PF may contribute to general well-being, it is not a primary determinant of psychological inflexibility. Further longitudinal and intervention studies are needed to clarify the mechanisms linking physical and psychological health in youth. Full article

This discussion explores the (dis)engagement of Jamaican RastafarI from the party political process, using RastafarI elder Mortimo Planno’s notion of “politics without a party” as a strand shaping and tying together the multiple threads of the exploration. The discussion examines how RastafarI has engaged with partisan politics/political parties from Independence (1962) until today. It highlights the differing ways of approaching politics among Rastas, including the minority, who have entered representative politics in a bid to [as yet unsuccessfully] change the tribal and compromised state of Jamaican politics. The decentralized nature of the RastafarI movement allows for diverse expressions of RastafarI political thought and action, but can present challenges for unified political mobilization on a large scale. Nonetheless, with or without direct partisan involvement, RastafarI has adapted and re-presented itself in response to changes in the local and global context, thus becoming a potent political force. So, despite this general lack of engagement with “statical” matters, RastafarI is and continues to be a significant political movement on several fronts, through movements, music, and symbols rather than traditional electoral routes. Full article

Semiclassical (SC) approximations for various representations of a quantum state are constructed on a single (Lagrangian) surface in the phase space but such surface is not available for chaotic systems. An analogous evolution surface underlies SC representations of the evolution operator, albeit in a doubled phase space. Here, it is shown that corresponding to the Fourier transform on a unitary operator, represented as a Green function or spectral Wigner function, a Legendre transform generates a resolvent surface as the classical basis for SC representations of the resolvent operator in the double-phase space, independently of the integrable or chaotic nature of the system. This surface coincides with derivatives of action functions (or generating functions) depending on the choice of appropriate coordinates, and its growth departs from the energy shell following trajectories in the double-phase space. In an initial study of the resolvent surface based on its caustics, its complex nature is revealed to be analogous to a multidimensional sponge. Resummation of the trace of the resolvent in terms of linear combinations of periodic orbits, known as pseudo orbits or composite orbits, provides a cutoff to the SC sum at the Heisenberg time. Here, it is shown that the corresponding actions for higher times can be approximately included within true secondary periodic orbits, in which heteroclinic orbits join multiple windings of relatively short periodic orbits into larger circuits. Full article

Background: While several test-automation maturity models (e.g., CMMI, TMMi, TAIM) exist, none explicitly integrate ISO 9001-based quality management systems (QMS), leaving a gap for organizations that must align E2E test automation with formal quality assurance. Objective: This study proposes a test-automation maturity model (TAMM) that bridges E2E automation capability with ISO 9001/ISO 9004 self-assessment principles, and evaluates its reliability and practical impact in industry. Methods: TAMM comprises eight maturity dimensions, 39 requirements, and 429 checklist items. Three independent assessors applied the checklist to three software teams; inter-rater reliability was ensured via consensus review (Cohen’s κ = 0.75). Short-term remediation actions based on the checklist were implemented over six months and re-assessed. Synergy with the organization’s ISO 9001 QMS was analyzed using ISO 9004 self-check scores. Results: Within 6 months of remediation, mean TAMM score rose from 2.75 → 2.85. Inter-rater reliability is filled with Cohen’s κ = 0.75. Conclusions: The proposed TAMM delivers measurable, short-term maturity gains and complements ISO 9001-based QMS without introducing conflicting processes. Practitioners can use the checklist to identify actionable gaps, prioritize remediation, and quantify progress, while researchers may extend TAMM to other domains or automate scoring via repository mining. Full article

Triple-negative breast cancer (TNBC) is a highly aggressive and therapeutically challenging subtype of breast cancer due to its lack of estrogen receptors, progesterone receptors, and HER2 (Human epidermal growth factor receptor 2) expression, which severely limits available treatment options. Recently, Simvastatin—a widely used HMG-CoA (3-hydroxy-3-methylglutaryl-coenzyme A) reductase inhibitor for hyperlipidemia—has garnered interest for its potential anticancer effects. This study investigates the therapeutic potential of Simvastatin in triple-negative breast cancer (TNBC). The results demonstrate that Simvastatin significantly inhibits the proliferation of TNBC cells, particularly MDA-MB-231, in a dose- and time-dependent manner. Mechanistically, Simvastatin primarily induces G1 phase cell cycle arrest to exert its antiproliferative effects, with no significant evidence of apoptosis or necrosis. These findings support the potential repositioning of Simvastatin as a therapeutic agent to suppress TNBC cell growth. Further analysis shows that Simvastatin downregulates cyclin-dependent kinase 4 (CDK4), a key regulator of the G1/S cell cycle transition and a known marker of poor prognosis in breast cancer. These findings highlight a novel, apoptosis-independent mechanism of Simvastatin’s anticancer action in TNBC. Importantly, given that many breast cancer patients also suffer from hyperlipidemia, Simvastatin offers dual therapeutic benefits—managing both lipid metabolism and tumor cell proliferation. Thus, Simvastatin holds promise as an adjunctive therapy in the treatment of TNBC and warrants further clinical investigation. Full article

The Anti-Müllerian hormone (AMH) is widely recognized for promoting Müllerian duct regression in higher vertebrates and regulating key reproductive functions like steroidogenesis, folliculogenesis, and Leydig cell development. In teleost fish, which lack Müllerian ducts, Amh primarily influences male reproductive functions, including sex determination, testis differentiation, and germ cell proliferation. In adult fish, Amh supports gonad development and spermatogenesis, but its role in teleost gonadal physiology remains largely underexplored. This study reveals a novel steroidogenic function in the European sea bass (Dicentrarchus labrax) using in vitro testis culture, in vivo plasmid injection, and cell-based transactivation assays. The Amh-induced significant increase in androgen levels was also confirmed in Japanese medaka (Oryzias latipes) treated with recombinant sea bass Amh. Beyond activating the canonical Smad pathway, Amh also triggered the cAMP/PKA signalling pathway via its cognate type II receptor, Amhr2. Inhibitors of these pathways independently and synergistically counteracted Amh-induced CRE-Luc activity, indicating pathway crosstalk. Moreover, inhibition of the cAMP pathway suppressed Amh-induced androgen production in testis cultures, emphasizing the crucial role of protein kinase A in mediating Amh steroidogenic action. These findings uncover a novel steroidogenic function of Amh in teleosts and highlight its broader role in male reproductive physiology. Full article

Electricity distribution systems face increasing challenges due to demand growth, regulatory requirements, and the integration of distributed generation. In this context, distribution companies must make strategic and well-supported investment decisions, particularly in asset reinforcement actions such as reconductoring. This paper presents a multi-stage methodology to optimize reconductoring investments under load forecasting uncertainties. The approach combines a decomposition strategy with Monte Carlo simulation to capture demand variability. By discretizing a lognormal probability density function and selecting the largest loads in the network, the methodology balances computational feasibility with modeling accuracy. The optimization model employs exhaustive search techniques independently for each network branch, ensuring precise and consistent investment decisions. Tests conducted on the IEEE 123-bus feeder consider both operational and regulatory constraints from the Brazilian context. Results show that uncertainty-aware planning leads to a narrow investment range—between USD 55,108 and USD 66,504—highlighting the necessity of reconductoring regardless of demand scenarios. A comparative analysis of representative cases reveals consistent interventions, changes in conductor selection, and schedule adjustments based on load conditions. The proposed methodology enables flexible, cost-effective, and regulation-compliant investment planning, offering valuable insights for utilities seeking to enhance network reliability and performance while managing demand uncertainties. Full article

Water governance in Europe faces mounting challenges from climate change, demographic pressures, and aging infrastructure—especially in Southern regions increasingly affected by drought and institutional fragmentation. In contrast, Nordic countries such as Denmark and Sweden exhibit coherent, integrated governance systems with strong regulatory oversight. This study introduces the Water Governance Maturity Index (WGMI), a document-based assessment tool designed to evaluate national water governance across five dimensions: institutional capacity, operational effectiveness, environmental ambition, equity, and climate adaptation. Applying the WGMI to eight EU countries—four Nordic and four Southern—reveals a persistent North–South divide in governance maturity. Nordic countries consistently score in the “advanced” or “model” range, while Southern countries face systemic gaps in implementation, climate integration, and territorial inclusion. Based on these findings, the study offers actionable policy recommendations, including the establishment of independent regulators, strengthening of river basin coordination, mainstreaming of climate-water strategies, and expansion of affordability and participation mechanisms. By translating complex governance principles into measurable indicators, the WGMI provides a practical tool for benchmarking reform progress and supporting the EU’s broader agenda for just resilience and climate adaptation. Unlike broader frameworks like SDG 6.5.1, the WGMI’s document-based, dimension-specific approach provides granular, actionable insights for governance reform, enhancing its utility for EU and global policymakers. Full article

Educational admission systems, particularly in developing countries, often suffer from opaque decision processes, unstructured data, and limited analytic insight. This study proposes a novel methodology that integrates structural causal models (SCMs), ontological modeling, and machine learning to uncover and apply interpretable knowledge from an admission database. Using a dataset of 12,043 records from Benue State Polytechnic, Nigeria, we demonstrate this approach as a proof of concept by constructing a domain-specific SCM ontology, validate it using conditional independence testing (CIT), and extract features for predictive modeling. Five classifiers, Logistic Regression, Decision Tree, Random Forest, K-Nearest Neighbors (KNN), and Support Vector Machine (SVM) were evaluated using stratified 10-fold cross-validation. SVM and KNN achieved the highest classification accuracy (92%), with precision and recall scores exceeding 95% and 100%, respectively. Feature importance analysis revealed ‘mode of entry’ and ‘current qualification’ as key causal factors influencing admission decisions. This framework provides a reproducible pipeline that combines semantic representation and empirical validation, offering actionable insights for institutional decision-makers. Comparative benchmarking, ethical considerations, and model calibration are integrated to enhance methodological transparency. Limitations, including reliance on single-institution data, are acknowledged, and directions for generalizability and explainable AI are proposed. Full article

The introduction of mobile banking is essential in today’s financial sector, where technological innovation plays a critical role. To remain competitive in the current market, businesses must analyze client attitudes and perspectives, as these influence long-term demand and overall profitability. While previous studies have explored general adoption behaviors, limited research has examined how individual factors such as social influence, lifestyle compatibility, financial technology self-efficacy, and perceived usage cost affect mobile banking adoption among specific generational cohorts. This study addresses that gap by offering insights into these variables, contributing to the growing literature on mobile banking adoption, and presenting actionable recommendations for financial institutions targeting younger market segments. Using a structured questionnaire survey, data were collected from both users and non-users of mobile banking among the Gen Z population in the United States. The regression model significantly predicts mobile banking adoption, with an intercept of $-0.548$ ($p < 0.001$). Among the independent variables, perceived cost of usage has the strongest positive effect on adoption ($B=0.857$, $\beta =0.722$, $p < 0.001$), suggesting that adoption increases when mobile banking is perceived as more affordable. Social influence also has a significant positive impact ($B=0.642$, $\beta =0.643$, $p < 0.001$), indicating that peer influence is a central driver of adoption decisions. However, self-efficacy shows a significant negative relationship ($B=-0.343$, $\beta =-0.339$, $p < 0.001$), and lifestyle compatibility was found to be statistically insignificant ($p=0.615$). These findings suggest that reducing perceived costs, through lower fees, data bundling, or clearer communication about affordability, can directly enhance adoption among Gen Z consumers. Furthermore, leveraging peer influence via referral rewards, Partnerships with influencers, and in-app social features can increase user adoption. Since digital self-efficacy presents a barrier for some, banks should prioritize simplifying user interfaces and offering guided assistance, such as tutorials or chat-based support. Future research may employ longitudinal designs or analyze real-life transaction data for a more objective understanding of behavior. Additional variables like trust, perceived risk, and regulatory policies, not included in this study, should be integrated into future models to offer a more comprehensive analysis. Full article

Background/Objectives. This manuscript presents an overview of advances in oncological radiotherapy as an effective treatment method for cancerous tumors, focusing on mechanisms of action within metabolite–antimetabolite systems. The urgency of this topic is underscored by the fact that cancer remains one of the leading causes of death worldwide: as of 2022, approximately 20 million new cases were diagnosed globally, accounting for about 0.25% of the total population. Given prognostic models predicting a steady increase in cancer incidence to 35 million cases by 2050, there is an urgent need for the latest developments in physics, chemistry, molecular biology, pharmacy, and strict adherence to oncological vigilance. The purpose of this work is to demonstrate the relationship between the nature and mechanisms of past diagnostic and therapeutic oncology approaches, their current improvements, and future prospects. Particular emphasis is placed on isotope technologies in the production of therapeutic nuclides, focusing on the mechanisms of formation of simple and complex theranostic compounds and their classification according to target specificity. Methods. The methodology involved searching, selecting, and analyzing information from PubMed, Scopus, and Web of Science databases, as well as from available official online sources over the past 20 years. The search was structured around the structure–mechanism–effect relationship of active pharmaceutical ingredients (APIs). The manuscript, including graphic materials, was prepared using a narrative synthesis method. Results. The results present a sequential analysis of materials related to isotope technology, particularly nucleus stability and instability. An explanation of theranostic principles enabled a detailed description of the action mechanisms of radiopharmaceuticals on various receptors within the metabolite–antimetabolite system using specific drug models. Attention is also given to radioactive nanotheranostics, exemplified by the mechanisms of action of radioactive nanoparticles such as Tc-99m, AuNPs, wwAgNPs, FeNPs, and others. Conclusions. Radiotheranostics, which combines the diagnostic properties of unstable nuclei with therapeutic effects, serves as an effective adjunctive and/or independent method for treating cancer patients. Despite the emergence of resistance to both chemotherapy and radiotherapy, existing nuclide resources provide protection against subsequent tumor metastasis. However, given the unfavorable cancer incidence prognosis over the next 25 years, the development of “preventive” drugs is recommended. Progress in this area will be facilitated by modern medical knowledge and a deeper understanding of ligand–receptor interactions to trigger apoptosis in rapidly proliferating cells. Full article

Background: While timely blood transfusion is critical for restoring oxygen-carrying capacity after coronary artery bypass grafting (CABG), allogeneic blood product transfusions are independently associated with increased long-term mortality, necessitating a risk-stratified approach to balance oxygen delivery against immunological complications and infection risks. Methods: We retrospectively analyzed 3376 patients undergoing isolated CABG between 2005 and 2023 at a single tertiary center. Patients who died during their perioperative hospital stay within 30 days were excluded. Transfusion burden was assessed both as the absolute number of blood product units (packed red blood cells, platelet transfusion, fresh frozen plasma) and as a percentage of calculated patient blood volume. The primary outcome was all-cause mortality at 5 years. Flexible Cox regression with penalized smoothing splines, adjusted for EuroSCORE II, was used to model dose–response relationships. Results: From our cohort of 3376 patients, a total of 137 patients (4.05%) received >10 units of packed red blood cells (PRBC) perioperatively. These patients were older (median 71 vs. 68 years, p < 0.001), more often female (29% vs. 15%, p < 0.001), and had higher preoperative risk (EuroSCORE II: 2.53 vs. 1.41, p < 0.001). After 5 years, mortality was 42% in the massive transfusion group versus 10% in controls. Spline regression revealed an exponential increase in mortality with transfused units: 14 units yielded a 1.5-fold higher hazard of death (HR 1.46, 95% CI 1.31–1.64), rising to HR 2.71 (95% CI 2.12–3.47) at 30 units. When transfusion was indexed to blood volume, this relationship became linear and more tightly correlated with mortality, with lower maximum hazard ratios and narrower confidence intervals. Conclusions: Indexing transfusion burden to the percentage of patient blood volume replaced provides a more accurate and clinically actionable predictor of 5-year mortality after CABG than absolute unit counts. Our findings support a shift toward individualized, volume-based transfusion strategies to optimize patient outcomes and resource stewardship in a time of limited availability of blood products. Full article

Cybersecurity threats increasingly originate from human actions within organizations, emphasizing the need to understand behavioral factors behind non-compliance with information security policies (ISPs). Despite the presence of formal security policies, insider threats—whether accidental or intentional—remain a major vulnerability. This study addresses the gap in behavioral cybersecurity research by developing an integrated conceptual model that draws upon Operant Conditioning Theory (OCT), Protection Motivation Theory (PMT), and the Theory of Planned Behavior (TPB) to explore ISP compliance. The research aims to identify key cognitive, motivational, and behavioral factors that shape employees’ intentions and actual compliance with ISPs. The model examines seven independent variables of perceived severity: perceived vulnerability, rewards, punishment, attitude toward the behavior, subjective norms, and perceived behavioral control, with intention serving as a mediating variable and actual ISP compliance as the outcome. A quantitative approach was used, collecting data via an online survey from 302 employees across the public and private sectors. Structural Equation Modeling (SEM) with SmartPLS software (v.4.1.1.2) analyzed the complex relationships among variables, testing the proposed model. The findings reveal that perceived severity, punishment, attitude toward behavior, and perceived behavioral control, significantly and positively, influence employees’ intentions to comply with information security policies. Conversely, perceived vulnerability, rewards, and subjective norms do not show a significant effect on compliance intentions. Moreover, the intention to comply strongly predicts actual compliance behavior, thus confirming its key role as a mediator linking cognitive, motivational, and behavioral factors to real security practices. This study offers an original contribution by uniting three well-established theories into a single explanatory model and provides actionable insights for designing effective, psychologically informed interventions to enhance ISP adherence and reduce insider risks. Full article

This study included 221 patients with COVID-19 who were admitted to the emergency department of Avicenne Hospital in Rabat between August 2020 and August 2021. Patients were divided into three groups according to their D-dimer levels (<1, 1–2, and >2 µg/mL). Adjusted and unadjusted logistic regression analyses were performed to assess the association between elevated D-dimer levels and in-hospital mortality. Pearson’s correlation analysis was performed to explore the relationship between D-dimer levels and various biological and clinical parameters. The results revealed a statistically significant difference in the mean (SD) age among the three groups (p = 0.006). Analysis showed a statistically significant difference in the means (SD) of oxygen saturation, duration of hospital stay, and breathing rate among the three independent groups of COVID-19 patients. Patients with elevated D-dimer levels (greater than 2 µg/mL) experienced worse outcomes than those in the other groups, with severity, transfer to intensive care, and in-hospital mortality of 55 (40.7%), 35 (16%), and 24 (11%) patients, respectively, with p-values of 0.048, 0.002, and 0.002, respectively. Patients in the D-dimer > 2 µg/mL group had significantly higher C-reactive protein (CRP), lactate dehydrogenase, urea, cardiac troponin, B-type natriuretic peptide, and ferritin levels than those in the other two groups. The p-value was significant among the three groups (p = 0.044, p = 0.001, and p < 0.001). Age and elevated D-dimer levels (greater than 2 µg/mL) were associated with mortality in patients diagnosed with COVID-19. Correlation analysis indicated that D-dimer in COVID-19 patients is associated with worsening respiratory, hepatic, cardiac, and coagulation parameters, suggesting their utility as an integrative marker of disease severity. D-dimer levels > 2 µg/mL were identified as an independent risk factor for COVID-19 in-hospital mortality. Measuring and monitoring D-dimer levels can assist clinicians in taking timely actions and predicting the prognosis of patients with COVID-19. Full article