Search Results (245)

Background: Simulation-based training may offer a useful approach to support skill acquisition in neurointerventional stroke treatment without exposing patients to procedural risks. As the global demand for thrombectomy rises, training strategies that ensure procedural competence while addressing workforce constraints are increasingly important. With this pilot study, we aim to generate a hypothesis as to whether additional exposure of trainees to mechanical thrombectomy could benefit from simulator training on top of the standard training carried out on flow models. This study was designed as an exploratory pilot investigation and was not able to provide inferential or confirmatory statistical conclusions. Methods: Six novice participants (advanced clinical-year medical students with completed anatomical and preclinical training, but without previous exposure to catheter-based interventions) performed two neurointerventional tasks, vascular access and mechanical thrombectomy (MTE), on flow models. After a baseline assessment, three participants received standard model-based training (control group), and three received additional simulator training using a high-fidelity angiography simulator (Mentice VIST G5). Performance was reassessed after four weeks using technical and clinical surrogate metrics, which were ranked and descriptively analyzed. Results: No relevant differences were observed between groups for the vascular access task. In contrast, the simulator group demonstrated a trend toward improved performance in the MTE task, with greater gains in efficiency, autonomy, and procedural safety. Conclusions: Our findings indicate a possible benefit of even brief simulator exposure for skill acquisition for complex endovascular procedures such as MTE. While conventional training may suffice for basic skills, simulation may be particularly helpful in supporting learning in more advanced tasks. Full article

Support Vector Machines (SVMs) are widely used in critical decision-making applications, such as precision agriculture, due to their strong theoretical foundations and their ability to construct an optimal separating hyperplane in high-dimensional spaces. However, the effectiveness of SVMs is highly dependent on the efficiency of the optimization algorithm used to solve their underlying dual problem, which is often complex and constrained. Classical solvers, such as Sequential Minimal Optimization (SMO) and Stochastic Gradient Descent (SGD), present inherent limitations: SMO ensures numerical stability but lacks scalability and is sensitive to heuristics, while SGD scales well but suffers from unstable convergence and limited suitability for nonlinear kernels. To address these challenges, this study proposes a novel hybrid optimization framework based on Open Competency Optimization and Particle Swarm Optimization (OCO–PSO) to enhance the training of SVMs. The proposed approach combines the global exploration capability of PSO with the adaptive competency-based learning mechanism of OCO, enabling efficient exploration of the solution space, avoidance of local minima, and strict enforcement of dual constraints on the Lagrange multipliers. Across multiple datasets spanning medical (diabetes), agricultural yield, signal processing (sonar and ionosphere), and imbalanced synthetic data, the proposed OCO-PSO–SVM consistently outperforms classical SVM solvers (SMO and SGD) as well as widely used classifiers, including decision trees and random forests, in terms of accuracy, macro-F1-score, Matthews correlation coefficient (MCC), and ROC-AUC. On the Ionosphere dataset, OCO-PSO achieves an accuracy of $95.71\%$, an F1-score of $0.954$, and an MCC of $0.908$, matching the accuracy of random forest while offering superior interpretability through its kernel-based structure. In addition, the proposed method yields a sparser model with only 66 support vectors compared to 71 for standard SVC (a reduction of approximately $7\%$), while strictly satisfying the dual constraints with a near-zero violation of $1.3\times {10}^{-3}$. Notably, the optimal hyperparameters identified by OCO-PSO ($\mathrm{C}=2$, $\gamma \approx 0.062$) differ substantially from those obtained via Bayesian optimization for SVC ($\mathrm{C}=10$, $\gamma \approx 0.012$), indicating that the proposed approach explores alternative yet equally effective regions of the hypothesis space. The statistical significance and robustness of these improvements are confirmed through extensive validation using 1000 bootstrap replications, paired Student’s t-tests, Wilcoxon signed-rank tests, and Holm–Bonferroni correction. These results demonstrate that the proposed metaheuristic hybrid optimization framework constitutes a reliable, interpretable, and scalable alternative for training SVMs in complex and high-dimensional classification tasks. Full article

Background: p-values are ubiquitous in scientific research, yet they fundamentally fail to quantify the strength of evidence for or against competing hypotheses. This limitation is particularly problematic in neuroimaging meta-analyses, where researchers need to assess how strongly the available data support specific and spatially consistent patterns of brain activation across studies. Methods: In this work, we present a practical approach that transforms p-values into their corresponding upper bounds on the Bayes factor, which quantify the maximum plausible evidence in favor of the alternative hypothesis given the observed data. The method is illustrated within the framework of Activation Likelihood Estimation, the most widely used coordinate-based meta-analytic technique in neuroimaging and applied to a reference dataset comprising 73 finger-tapping experiments. Results: The results show that effects traditionally classified as statistically significant using the canonical Activation Likelihood Estimation framework actually span a wide range of evidential strengths, with Bayes factor bounds varying approximately from 46 to 410. This finding reveals substantial heterogeneity in weight of evidence that is concealed by conventional threshold-based inference. Conclusion: By enabling the construction of voxel-wise maps of evidential strength while remaining fully compatible with existing analysis pipelines, the proposed approach helps to avoid common misinterpretations of p-values and improves the interpretability and reliability of neuroimaging meta-analytic conclusions. It therefore provides a conservative, Bayesian-inspired complement to standard significance maps. Full article

This study investigates the impact of market structure on the performance of banks in Pakistan. It explicitly tests two competing hypotheses: the Structure–Conduct–Performance paradigm and the Efficient Structure Hypothesis, providing insights into whether profitability stems from market concentration or efficiency. The study employs the Data Envelopment Analysis approach to measure banking efficiency and uses the concentration ratio to capture market structure. A regression framework is applied, with efficiency and market structure as key explanatory variables. Further, bank-specific controls are included to examine their effects on performance, measured by Return on Assets. Results show that although the concentration of the five largest banks slightly declined, it remains relatively high at 58.5%. Banks, on average, operate at 67% efficiency with an upward trend over time. The findings lend more substantial support to the Efficient Structure Hypothesis, indicating that profitability is primarily driven by technical and scale efficiency rather than market concentration, with individual bank market share affecting performance only as an outcome of efficiency gains. The analysis highlights that efficiency improvements are crucial in enhancing banks’ performance in Pakistan. Over the years, the banking sector of Pakistan has evolved in terms of market structure, efficiency, and banks’ performance. This study interprets the changes in the market structure in the context of the structure conduct performance hypothesis and/or the efficient structure performance hypothesis and answers the question regarding whether market power and/or efficient structure is relevant to the banks’ performance. For policymakers, the results suggest that efforts to improve competitive efficiency, such as encouraging innovation, risk management, and capacity utilization, are more effective than focusing solely on altering market concentration. Full article

La Crosse virus (LACV) is a mosquito-borne virus (family Peribunyaviridae) that can result in severe human infection in children under sixteen. Historically, LACV comprised two lineages, predominantly in the Midwest and Appalachian regions of the US. In 2005, a virus of a third lineage was detected in the Northeast; however, this and subsequently isolated strains of lineage III have not, to date, been implicated in human disease. One hypothesis for this discrepancy is that vector mosquitoes have a reduced vector competency for LACV lineage III, thus preventing horizontal transmission and clinical cases. Here, we utilized two mosquito species, Aedes triseriatus, the native vector, and Aedes albopictus, an invasive potential vector, each from both a historic LACV range (Virginia) and from the region of lineage III (Connecticut). Utilizing oral feeding and intrathoracic inoculation methods of viral exposure, rates of LACV infection, dissemination, and transmission (proxied via salivary secretion) and capability for vertical transmission (proxied via virus-positive ovaries) were determined by harvesting mosquito bodies, legs, saliva, and ovaries, respectively. Overall, we did not detect consistent differences in transmission between any lineage, species, or state of origin, at day 14 post-infection. However, we highlight the transmission potential of LACV lineage III in all mosquito populations tested here, representing the first evidence of lineage III competency in Aedes triseriatus and Aedes albopictus, indicating the potential for human disease. We thus suggest that the absence of human cases of LACV lineage III is not modulated by a lack of vector competency in mosquitoes. Full article

The necessity of implementing a circular economy (CE) is critical for developing a sustainable economic environment with minimized adverse environmental impacts. Consequently, it is essential to identify the factors influencing the adoption and effectiveness of CE practices within businesses and SMEs. This study aims to address the knowledge gap regarding the integration of CE in Jordan’s business and management sectors. The research examines the impact of skills and competencies, inter- and intra-organizational factors, and corporate social responsibility (CSR) on innovation, and subsequently, how innovation influences the adoption of CE practices, ultimately leading to sustainable performance. A survey was conducted among employees of SMEs meeting specific criteria, and the collected data were analyzed. The results indicate that all the independent factors of skills and competencies, inter- and intra-organizational factors, and CSR—positively affect innovation. This finding supports the hypothesis derived from the literature review. Furthermore, innovation has a positive effect on the implementation of CE practices, which in turn significantly enhances sustainable performance. Full article

Italian Court of Cassation Ruling Decree 30032 of 30 October 2023 discusses a medical malpractice case concerning the diagnosis of dermatofibrosarcoma protuberans and the alleged diagnostic and therapeutic delay. By examining how the ruling frames the role of histopathology in proving pathology benignity, authors prompt to reflect on diagnostic path, the allocation of the burden of proof, and the role of dermatologist’s expertise in professional liability issues. Over a four-year period, five health professionals were involved in a claim concerning an initial diagnosis of an epidermoid cyst and a subsequent diagnosis of dermatofibrosarcoma protuberans. The plaintiff questioned the delay in diagnosis, and the Court of Cassation found two physicians liable because they could not prove that the treated pathology was initially benign. We argue that equating diagnostic correctness exclusively with histological confirmation is unnecessary, both clinically and legally, in typical cases, if the reasoning and findings are adequately documented. Additionally, we examine the value of dermatologists’ experience and the scope of professional competence as measures of liability. Finally, we outline the minimum standards of clinical documentation necessary to make the diagnostic pathway traceable and verifiable. The diagnostic process is a discretionary effort that integrates multiple sources of information, both instrumental and experiential, to reach the most reasonable hypothesis. While histopathology is a crucial tool, it is not the sole gateway to a correct diagnosis of every cutaneous alteration. Adequate disclosure and structured documentation of the diagnostic reasoning are fundamental to the care process and fair assessment of professional responsibility. Full article

This paper examines how Generative AI (GenAI) reshapes digital inclusion in e-government. We develop the E-Government Divide Measurement Indicator (EGDMI) across three dimensions: D1—Breadth of the Divide (foundational access, affordability, and basic skills), D2—Sectoral/Specific Divide (actual use, experience, and trust in e-government), and D3—GenAI Gap (access, task use, and competence). The index architecture specifies indicator lists, sources, units, transformations, uniform normalization, and a documented weighting strategy with sensitivity and basic uncertainty checks. Using official statistics and qualitative evidence for Serbia, we report D1 and D2 as composite indices and treat D3 as an exploratory, non-aggregated layer given current data maturity. Results show strong foundational readiness (D1 = 73.6) but very low e-government uptake (D2 = 19.9), indicating a shift of the divide from access to meaningful use, usability, and trust. GenAI capabilities are emergent and uneven (D3 sub-dimensions: access 47.8; task use 39.4; competence/verification 43.6). Cluster analysis identifies four user profiles—from “Digitally Excluded” to “GenAI-Augmented Citizens”— that support differentiated interventions. The initial hypothesis—that GenAI can widen disparities in the short run—receives partial confirmation: GenAI may lower interaction costs but raises verification and ethics thresholds for vulnerable groups. We outline a policy roadmap prioritizing human-centered service redesign, transparency, and GenAI literacy before automation, and provide reporting templates to support comparable monitoring and cross-country learning. Full article

The reduction in oocyte competence and ovarian reserve coincides with reproductive ageing; nevertheless, the molecular mechanisms underlying this phenomenon remain poorly understood. Our testable mechanistic hypothesis is that the oxidative stress–telomere axis is a crucial regulatory mechanism controlling meiotic stability, mitochondrial resilience, and granulosa cell integrity. This notion posits that granulosa and cumulus cells have accelerated telomere attrition and impaired DNA-damage responses due to elevated amounts of reactive oxygen species, which also induce oxidative guanine lesions, inhibit telomerase function, and generate telomeric replication stress. This telomere-dependent vulnerability is anticipated to compromise developmental competence, disrupt meiotic spindle integrity, and diminish metabolic support to the oocyte, prior to observable declines in AMH or follicle count. Data from human IVF cohorts supports the model: Conditions such as PCOS, endometriosis, and POI have unique oxidative-telomeric profiles, whereas diminished telomere length in granulosa cells, reduced telomerase activity, and worse fertilisation, blastulation, and pregnancy outcomes are associated with increased follicular oxidative DNA damage. The findings suggest that oxidative DNA damage (8-OHdG), telomerase activity, and the structure of granulosa-cell telomeres may serve as preliminary indicators of preclinical ovarian ageing. This theory may be directly evaluated in forthcoming longitudinal studies and specific treatments related to telomerase regulation, mitochondrial medicines, or redox modulation. Consequently, the oxidative stress–telomere axis may represent a vital physiologic factor affecting reproductive lifespan and a prospective target for personalised ART techniques. Full article

This article explores the potential of an integrated pedagogical approach that combines project-based learning (PBL) with Internet of Things (IoT) technologies to achieve the United Nations’ Sustainable Development Goals (SDGs). Within the context of Education for Sustainable Development (ESD), this model transforms students from passive consumers of information into active agents of change. The study demonstrates that leveraging IoT sensors enables students to tackle pressing and complex sustainability challenges by engaging them in a comprehensive problem-solving cycle—from collecting real-world data to developing innovative solutions. By analysing the existing scientific literature, the approach is shown to significantly improve critical thinking skills, systems thinking, creativity, and teamwork. The study also proposes a new conceptual framework (hypothesis), the EcoHabits model, whose effectiveness remains to be empirically validated. This model demonstrates IoT’s potential to enhance sustainability competencies, improve health literacy, and promote individual and collective behaviour change. Despite its significant pedagogical benefits, the article identifies key implementation challenges, including the need for adequate teacher training and community collaboration. In conclusion, this innovative framework offers a promising solution for preparing future generations to address global issues and become active, responsible citizens of the 21st century. Full article

The Ostwald ripening process in 3D and 2D systems has been studied in great detail over decades. In the application to surface nanoislands and nanodroplets, it is usually assumed that the capture coefficients of adatoms by supercritical nanoparticles of size $s$ scale as $s^{\alpha }$, where the growth index $\alpha$ is smaller than unity. Here, we study theoretically the Ostwald ripening of 3D and 2D nanoparticles whose capture coefficients scale linearly with $s$. This case includes submonolayer surface islands that compete for the flux of highly diffusive adatoms upon termination of the material influx. We obtain analytical solutions for the size distributions using the Lifshitz–Slezov scaled variables. The distributions over size $s$ and radius $R$ are monotonically decreasing, and satisfy the normalization condition for different values of the Lifshitz–Slezov constant $c$. The obtained size distributions satisfy the Family–Vicsek scaling hypothesis, although the material influx is switched off. The model is validated by fitting the monotonically decreasing size distributions of Au nanoparticles that serve as catalysts for the vapor–liquid–solid growth of III-V nanowires on silicon substrates. Full article

This study examines the key factors influencing the quality of distance learning in higher education during the COVID-19 pandemic, a period when online learning became the dominant mode of education. Using a descriptive method and a 26-item questionnaire, data were collected from a representative sample of 360 students in Vojvodina, Serbia. The factors analyzed include computer literacy and technology access (Ph1), students’ ability to balance life obligations with study demands (Ph2), and their motivation for distance learning (Ph3). The results show that 89% of students had adequate IT access, 47% were able to reconcile study and personal obligations, and 70% reported strong motivation. Correlation analysis confirmed a statistically significant positive relationship between all three factors and students’ perceptions of well-organized distance learning, thus supporting the main research hypothesis. Beyond these findings, this study interprets digital literacy as adaptability, time management as resilience, and motivation as value orientation and future thinking—core dimensions of sustainability competences outlined in the European GreenComp framework. Distance learning is therefore positioned not only as an emergency response but also as a transformative pedagogy that integrates brain (knowledge), hands (skills), heart (values), and spirit (purpose), contributing to sustainable and resilient higher education. Full article

The negative strand of the human immunodeficiency virus-1 (HIV-1) proviral genome contains an antisense open reading frame encoding a protein (ASP) with no known homologs. The presence of immune responses to ASP in people living with HIV-1 (PLWH) demonstrates its expression in vivo. Further, the predicted hydrophobicity of ASP is consistent with its association with the plasma membrane and viral envelope. Despite this body of evidence, the role of ASP in HIV-1 replication remains unknown. In this report, we investigated the hypothesis that the presence of ASP on the viral surface enhances HIV-1 entry into target cells. We generated an ASP-knockout replication-competent HIV-1 molecular clone in the NL4-3 background, which we used to perform cell–cell fusion, viral entry, and viral replication assays. Our results suggest that the presence of ASP on the plasma membrane of infected cells and the envelope of HIV-1 virions enhances viral transmission. Overall, our studies provide first evidence that ASP plays a role in the HIV-1 replication cycle. Further investigation into these observations may lead to the identification of new HIV-1 vulnerabilities that may be the target of novel interventions. Full article

Background: While rhinoviruses (RVs) typically cause mild respiratory infections, their persistence during the SARS-CoV-2 pandemic, particularly in Hong Kong’s strict zero-coronavirus disease 2019 policy, revealed unexpected epidemiological patterns. Two distinct RV surges emerged despite stringent public health measures, suggesting unique transmission advantages among circulating strains. We hypothesised that RV persistence during pandemic restrictions reflected strain-specific adaptations in respiratory tract replication efficiency and/or immune evasion. Methods: We analysed RV genotypes and conducted blinded clinical severity assessment for 96 paediatric hospitalisations during 2020–2021 outbreaks, compared with 180 age- and sex-matched control subjects from the corresponding weeks in pre-pandemic years (2018–2019). RV isolates from 2020 to 2021 outbreaks were characterised for their replication competence and transcriptomic responses in primary human nasal epithelial cell (HNEC) and environmental stability assays, using RV-A16 and RV-A1B as controls. Result: Minor group genotypes RV-A47 and RV-A49 were overrepresented during these two outbreaks. RV-A49 exhibited comparable replication efficiency to RV-A16 but induced significantly stronger transcriptomic responses, notably enhanced TNF and IL-1 signalling, in HNECs, alongside robust replication competence. Our data also suggests the association of RV-A49 with tachypnoea in 2021, particularly in younger males, though limited by a small sample size and single-centre design. Conclusion: The predominance of RV-A49 in hospitalised children during the SARS-CoV-2 pandemic potentially driven by its replication competence in HNECs and its capacity to enhanced inflammatory responses. The result is hypothesis-generating, warranting further studies with historical strains and broader populations to confirm strain-specific severity. Full article

Objectives: Clear cell renal cell carcinoma (ccRCC) may later metastasize despite curative surgery. This study asked whether transcriptomic alterations detectable at nephrectomy are associated with subsequent metastatic progression, and whether such signals retain prognostic relevance in overt metastatic disease. Methods: Bulk RNA sequencing was performed in 30 ccRCC patients without metastasis at surgery; 4 developed distant metastasis during follow-up. Differential expression, enrichment, and network analyses identified hub genes, which were screened by ROC analysis with bootstrap optimism correction. External validation used TCGA-KIRC focusing on patients metastatic at baseline (M1) to evaluate overall and disease-specific survival with multivariable Cox models (per-SD expression, adjusted for age, sex, and stage); Kaplan–Meier curves were shown for visualization only. Results: Fifty-nine DEGs distinguished patients who later metastasized from those who remained metastasis-free, with enrichment in mitotic and chromosomal-segregation pathways. Five hub genes (BASP1, CDCA8, KIF2C, LMNB1, TROAP) showed high discrimination in the discovery set (optimism-corrected AUC ~0.92–0.93). In TCGA-M1, CDCA8, and TROAP were consistently associated with worse survival and remained significant in multivariable models. Conclusions: Dysregulation of mitotic control may underlie latent metastatic competence in ccRCC. CDCA8 and TROAP emerge as candidate prognostic biomarkers, linking postoperative metastatic progression in an initially M0 cohort with survival in metastatic disease. These hypothesis-generating findings warrant validation in larger, prospective cohorts. Full article