Search Results (13,450)

Blackground: Football performance analysis has grown rapidly in recent years, with increasing interest in advanced metrics to more accurately evaluate both individual and team performance. The aim of this study was to examine the utility of the Expected Shots Impact Timing (xSIT) metric as an indicator of shooting performance in English professional football, specifically in the men’s Premier League (PL) and the Women’s Super League (WSL). Methods: A total of 9831 shots from the PL (2015/16 season) and 3219 shots from the WSL (2020/21 season) were analyzed. Data were obtained from publicly accessible football databases. The variables examined included goals, Possession Value (PV), Expected Goals (xG), Expected Goals on Target (xGOT), and xSIT. All variables were normalized per match (90 min). Descriptive statistics, correlational analyses, and comparative analyses between leagues. Results: The WSL exhibited a significantly higher PV than the PL (p < 0.001), whereas the remaining metrics showed no significant differences between leagues (p > 0.05). Moreover, in the WSL, all performance indicators displayed very strong correlations with goals, while in the PL, similarly strong associations were observed, except for PV, which showed only a weak relationship. Conclusions: the xSIT metric, as an indicator of shooting performance, may be regarded as an influential factor in determining match outcomes across both leagues. Full article

This research investigates the impact of Environmental, Social, and Governance (ESG) practices on the financial performance of logistics firms, with a focus on the mediating role of stakeholder pressure. Utilizing survey data collected from Korean logistics firms (N = 256 valid responses) and employing structural equation modeling, the findings indicate that social practices exert a significant direct effect on financial outcomes. Conversely, environmental and governance practices impact financial performance indirectly, through stakeholder pressure. These findings suggest that ESG activities impact financial performance via distinct mechanisms, contingent upon the specific ESG dimension and the level of stakeholder engagement. The study advances ESG literature by providing a disaggregated analysis of ESG effectiveness and empirically confirming stakeholder pressure as a critical pathway. Practically, the results underscore the need for logistics firms to align their ESG strategies with stakeholder expectations and institutional pressures, thereby optimizing both sustainability and financial performance. Full article

This qualitative study examines trustees’ perspectives on effective presidential leadership in higher education institutions in Kazakhstan and the United States. Drawing on an integrative framework that combines established models of higher education leadership with the concepts of sustainable and adaptive leadership, the study identifies the attributes trustees consider essential for effective presidential leadership. The findings indicate that effective leaders are expected to demonstrate a blend of instrumental and interpretive skills, adaptability, and strong interpersonal competencies to address institutional challenges and foster long-term success while also engaging in balancing between competing values. Cross-national comparison reveals notable differences: trustees in Kazakhstan place stronger emphasis on instrumental leadership, particularly in relation to achieving state-defined performance indicators, whereas U.S. trustees highlight the alignment of strategy with institutional mission, culture, and values. Overall, the study shows that trustees in both contexts favor a hybrid model of presidential leadership, though the weight and interpretation of its dimensions are shaped by differing governance traditions, reform trajectories, and institutional histories Full article

Experimental measurement of dose distributions is a pivotal step in the quality assurance of radiotherapy treatments, especially for those relying on high delivery accuracy such as hadron therapy. This study investigated the response of a polymer gel dosimeter to determine its suitability in performing geometric beam characterizations for hadron therapy under high-quenching conditions. Different extraction energies of proton and carbon ion beams were considered. Gel dose–response linearity and long-term stability were confirmed through optical measurements. Gel phantoms were irradiated with pencil beams and analyzed via magnetic resonance imaging. A multi-echo T₂-weighted sequence was used to reconstruct depth–dose profiles and transversal distributions acquired by the gels, which were benchmarked against reference data. As expected, a response-quenching effect in the Bragg peak region was noted. Nonetheless, the studied gel formulation proved reliable in acquiring the geometric characteristics of the beams, even without correcting for the quenching effect. Indeed, depth–dose distributions acquired by the gels showed an excellent agreement with measured particle range with respect to reference values, with mean discrepancies of 0.5 ± 0.2 mm. Single-spot transverse FWHM values at increasing depths also presented an average agreement within 1 mm with values determined with radiochromic films, thus supporting the excellent spatial resolving capabilities of the dosimetric gel. Full article

As small–medium-sized enterprises (SMEs) increasingly adopt cloud technologies, understanding the factors influencing this shift is crucial as it helps to optimize cloud integration strategies, enabling SMEs to thrive in today’s digital economy. A cross-sectional, quantitative survey was conducted in February 2022 on 626 employees of SMEs in the USA, based on the TAM-2, TAM-3, and UTAUT-2 models. The questionnaire presented satisfactory reliability, as well as factorial and convergent validity. Employees presented positive behavioral intentions to use cloud technologies, particularly during the COVID-19 period. SMEs were satisfied with the use of Software as a Service (SaaS), Infrastructure as a Service (IaaS), and the public cloud development model in the wake of the COVID-19 period. Behavioral intention to use cloud technologies was linked with higher performance and effort expectancy, price, perceived enjoyment, computer self-efficacy, and social influence. A higher behavioral intention was observed in employees (a) with a mid–top-level role; (b) who worked in finance and insurance, information services data, construction, or software and in an SME with 26–500 employees; (c) who had a master’s degree; (d) were 35–44 years old; and (e) had family obligations. Higher experience with the use of cloud technologies enhanced the positive impacts of effort expectancy, computer self-efficacy, and perceived enjoyment on behavioral intention. Full article

Electric vehicle (EV) battery thermal management systems have gradually improved owing to the increasing power demand of EVs. This study aims to optimize the channel geometry of sandwich double-sided cold plates for EV battery cooling under 100% state of charge and 2C-rate charging conditions. For precise and accurate optimization, the conventional one-dimensional analysis model of the sandwich double-sided cold plate was converted into a three-dimensional computational fluid dynamics (CFD) model. Non-dimensional parameters were selected as the main variables of the channel geometry, and nine additional channel shapes were derived based on them. Battery modules with the derived channel shapes were subjected to CFD analysis in the Reynolds number range of 500 to 20,000. The goodness factor was calculated from these correlations, and optimization was performed using the Taguchi method. The results revealed that the wetted area of the channel had a greater impact on battery cooling than the number of channels. This study proposed more generalized design guidelines by employing non-dimensionalized parameters across a wide range of Reynolds numbers. The rectangular channel-based correlations developed in this study showed improved prediction accuracy compared to conventional annular pipe-based correlations and are expected to be applicable to various battery thermal management system designs in the future. Full article

This initial exploratory study examined the perceptions of teachers and school leaders in the Republic of Ireland regarding diversity in promotions to school principalship, framed by Equity Theory, Organisational Justice Theory, and Legitimacy Theory. A mixed-methods approach was utilised within this study. Data was collected from 123 participants via an online survey comprising Likert-type statements and open-ended questions. This data was analysed using descriptive statistics and quantitative analysis for the Likert-type statements and thematic analysis was used to examine the qualitative responses, allowing for the identification of recurring patterns and themes to complement the quantitative findings. Findings indicated disparities between perceived and desired prioritisation of diversity, alongside varied perceptions of its impact on school performance and leadership. Disability, social class, and religious diversity were perceived as the least prioritised in promotion practices, while gender and cultural diversity received greater support and were more frequently linked to positive leadership outcomes. Participants reported mixed perceptions across diversity dimensions, with gender, age, and cultural diversity associated with the most positive impacts. Concerns about tokenism and the perceived undermining of merit-based promotion were widespread, reflecting the importance of fairness, transparency, and alignment with stakeholder expectations. The study underscored the need for promotion processes that are both equitable and credible, and for organisational cultures that enable diverse leaders to thrive. These findings provided a foundation for further research and policy development to foster inclusive and representative school leadership in Ireland. Full article

Global food production must meet the dietary requirements of a growing population, which is expected to reach 8–11 billion by 2100, while reducing the environmental impact of agricultural practices. The agricultural sector accounts for 21–37% of global greenhouse gas emissions, 70% of freshwater, and contributes considerably to biodiversity loss and challenges that are further intensified by climate change. Controlled Environment Agriculture (CEA) serves as a sustainable strategy to address global food production and promote consistency and resource-efficient crop production. However, nutrient imbalances remain a key challenge in hydroponic CEA systems. To address these nutrient-related challenges, plant sap analysis is being considered as real-time monitoring tool and precise nutrient management in CEA systems. Compared to traditional nutrient tissue analysis, sap analysis shows stronger correlations with crop performance during active growth. For instance, petiole sap nitrate-nitrogen (NO₃⁻-N) and total nitrogen (N) in tomato leaves show correlation coefficients of r = 0.6–0.8 during their rapid vegetative growth stages. Sap analysis shows potential improvements in nutrient efficiency, crop quality, and sustainability within CEA. This review investigates the principles, methodologies, and advancements in plant sap analysis, contrasting it with traditional nutrient testing methods. It also addresses challenges such as variability in sap composition, the lack of standardized protocols, and economic considerations, while emphasizing real-time nutrient management to achieve and sustainability in CEA. Full article

This study evaluates the energy performance of a BOGE C 22-2 oil-injected rotary screw compressor under real industrial conditions. Using direct measurements with a power quality analyzer and thermodynamic modeling, key performance indicators such as compression work, mass flow rate, compressor efficiency, and motor efficiency were determined. The results revealed actual efficiencies of 27–48%, significantly lower than the expected 60–70% for this type of equipment, mainly due to partial-load operation and low airflow demand. A low power factor of approximately 0.72 was also observed, caused by a high share of reactive power consumption. To address these inefficiencies, the study recommends the installation of an automatic capacitor bank to improve power quality and the integration of a secondary variable speed compressor to enhance performance under low-demand conditions. These findings underscore the importance of assessing compressor behavior in real-world environments and implementing techno-economic strategies to increase energy efficiency and reduce industrial electricity consumption. Full article

Expectation Propagation (EP) has emerged as a promising detection algorithm for large-scale multiple-input multiple-output (MIMO) systems owing to its excellent performance and practical complexity. However, transmit antenna correlation significantly degrades the performance of EP detection, especially when the number of transmit and receive antennas is equal and high-order modulation is adopted. Based on the fact that the eigenvector matrix of the channel transmit correlation matrix approaches asymptotically to a discrete Fourier transform (DFT) matrix, a DFT precoder is proposed to effectively eliminate transmit antenna correlation. Simulation results demonstrate that for high-order, high-dimensional massive MIMO systems with strong transmit antenna correlation, employing the proposed DFT precoding can significantly accelerate the convergence of the EP algorithm and reduce the detection error rate. Full article

Background/Objectives: Erectile dysfunction (ED) is a prevalent and multifactorial condition influenced by psychological and sleep-related factors. This study aimed to evaluate the independent and combined associations of insomnia and benzodiazepine use with the risk of ED. Methods: An analytical cross-sectional study was conducted in adult men with and without ED. Logistic regression was used to estimate crude and adjusted odds ratios (ORs). Effect modification was assessed through stratified analyses. Additionally, an in silico analysis of 17 active compounds was performed using SwissADME and Molinspiration to explore physicochemical properties. Results: Insomnia (adjusted OR 2.05; 95% CI 1.13–3.74; p = 0.019) and benzodiazepine use (adjusted OR 2.14; 95% CI 1.10–4.15; p = 0.025) were each independently associated with ED. In contrast, antidepressant use was not significantly associated with ED in the sample analyzed. Participants with both insomnia and benzodiazepine use had a markedly higher risk (adjusted OR 3.96; 95% CI 1.51–10.40; p = 0.005). The joint association of insomnia and benzodiazepine use was consistent with the combined effect expected from their individual associations. The in silico analysis showed an overlapping profile, suggesting benzodiazepine properties may underline their link to ED, supporting the results of the cross-sectional study. Conclusions: Both insomnia and benzodiazepine use independently increased the odds of ED. Their co-occurrence was linked to a substantially higher likelihood of ED, highlighting the clinical importance of assessing both conditions concurrently in patients with sexual dysfunction. Full article

In higher education, institutional quality is traditionally assessed through metrics such as academic programs, research output, educational resources, and community services. However, it is important that their activities align with student expectations, particularly in relation to interactive learning environments, learning management system interaction, curricular and co-curricular activities, accessibility, support services and other learning resources that ensure academic success and, jointly, career readiness. The growing popularity of student engagement metrics as one of the key measures to evaluate institutional efficacy is now a feature across higher education. By monitoring student engagement, institutions assess the impact of existing resources and make necessary improvements or interventions to ensure student success. This study presents a comprehensive analysis of student feedback from the StudentSurvey.ie dataset (2016–2022), which consists of approximately 275,000 student responses, focusing on student self-perception of engagement in the learning process. By using classical topic modelling techniques such as Latent Dirichlet Allocation (LDA) and Bi-term Topic Modelling (BTM), along with the advanced transformer-based BERTopic model, we identify key themes in student responses that can impact institutional strength performance metrics. BTM proved more effective than LDA for short text analysis, whereas BERTopic offered greater semantic coherence and uncovered hidden themes using deep learning embeddings. Moreover, a custom Named Entity Recognition (NER) model successfully extracted entities such as university personnel, digital tools, and educational resources, with improved performance as the training data size increased. To enable students to offer actionable feedback, suggesting areas of improvement, an n-gram and bigram network analysis was used to focus on common modifiers such as “more” and “better” and trends across student groups. This study introduces a fully automated, scalable pipeline that integrates topic modelling, NER, and n-gram analysis to interpret student feedback, offering reportable insights and supporting structured enhancements to the student learning experience. Full article

Background: Key performance indicators (KPIs) are widely used to evaluate embryologist performance in IVF laboratories, yet they are sensitive to patient demographics, treatment indications, and case allocation. Artificial intelligence (AI) offers opportunities to benchmark personal KPIs against context-aware expectations. This study evaluated whether personal CPR-based KPIs are measurable or distorted when compared with AI-derived predictions. Methods: We retrospectively analyzed 474 ICSI-only cycles performed by a single senior embryologist between 2022 and 2024. A Random Forest trained on 1294 institutional cycles generated AI-predicted clinical pregnancy rates (CPRs). Observed and predicted CPRs were compared across age groups, BMI categories, and physicians using cycle-level paired comparisons and a grouped calibration statistic. Results: Overall CPRs were similar between observed and predicted outcomes (0.31 vs. 0.33, p = 0.412). Age-stratified analysis showed significant discrepancy in the >40 group (0.11 vs. 0.18, p = 0.003), whereas CPR in the 35–40 group exceeded predictions (0.39 vs. 0.33, p = 0.018). BMI groups showed no miscalibration (p = 0.458). Physician-level comparisons suggested variability (p = 0.021), while grouped calibration was not statistically significant (p = 0.073). Conclusions: Personal embryologist KPIs are measurable but influenced by patient and physician factors. AI benchmarking may improve fairness by adjusting for case mix, yet systematic bias can persist in high-risk subgroups. Multi-operator, multi-center validation is needed to confirm generalizability. Full article

Burns represent a significant medical challenge, and the development of theoretical models has the potential to contribute to the advancement of new diagnostic tools. This study aimed to perform numerical simulations of the Pennes bioheat transfer equation, incorporating heat generation terms due to the body’s immunological response to thermal injury, as well as changes in skin thermal parameters and blood perfusion for each burn type. We propose the incorporation of specific parameters and boundary conditions related to multilayer perfusion into the Pennes bioheat model. Using the proposed layered skin model, we evaluate temperature differences to establish correlations for determining burn depth. In this investigation, 1D and 3D algorithms based on the finite volume method were applied to capture transient and spatial thermal variations, with the resulting temperature distributions demonstrating the ability of the proposed models to describe the expected thermal variations in healthy and burned tissue. This work demonstrates the potential of the finite volume method to approximate the solution of the Pennes biothermal equation. Overall, this study provides a computational framework for analyzing heat transfer in burn injuries and highlights the relevance of mathematical simulations as a tool for future research on infrared thermography in medicine. Full article

Silicon photonic computing system is expected to replace traditional electronic computing systems in specific applications in the future, owing to its advantages in high speed, large bandwidth, low power consumption, and resistance to electro-magnetic interference. In this paper, we propose a tunable time-delay photonic computing architecture based on chirped Bragg gratings (CBG), which replaces traditional dispersion fibers to achieve the required delay function in system architecture, while providing reconfigurability capabilities of time delay control. Simulation results, using 3rd-order and 4th-order input matrices to convolve with 2nd-order convolution kernel matrices, demonstrates that the proposed photonic computing architecture can effectively perform matrix convolutional operations of various orders. Furthermore, the functionality and performance of design tunable time delay module based on CBG is also verified in the system. Therefore, our proposed scheme can be employed in the matrix multiplications of photonic computing architecture, which provides an optional efficient solution for future photonic convolutional neural networks. Full article