Search Results (4,808)

A hybrid wave energy conversion (WEC) system, integrating a backward bent duct buoy (BBDB) with an oscillating buoy (OB) via a flexible mooring chain, is introduced in this study. Unlike existing hybrid WECs, the proposed system dispenses with rigid mechanical linkages and enables flexible offshore deployment. Flared BBDB and buoy models with spherical, cylindrical, and semi-capsule shapes are designed and tested experimentally in a wave flume using both regular and irregular wave conditions. The effects of nozzle ratio (NR), coupling distance, buoy draft, and buoy geometry are systematically examined to investigate the hydrodynamic performance and energy conversion characteristics. It is found that NR at 110 under unidirectional airflow produces an optimal balance between pressure response, free surface displacement, and energy conversion efficiency. Energy extraction is significantly influenced by the coupling distance, with the hybrid system achieving maximum performance at a specific normalized spacing. The semi-capsule buoy improves power extraction ability and expands effective bandwidth due to asymmetric shape and coupled motion. These findings provide valuable insights into the coupling mechanism and geometric optimization for hybrid WECs. Full article

This study investigates the predictive performance of financial indicators in forecasting stock prices within the automotive sector using an adaptive neuro-fuzzy inference system (ANFIS). In light of the growing complexity of global financial markets and the increasing demand for automated, data-driven forecasting models, this research aims to identify those financial ratios that most accurately reflect price dynamics in this specific industry. The model incorporates four widely used financial indicators, return on assets (ROA), return on equity (ROE), earnings per share (EPS), and profit margin (PM), as inputs. The analysis is based on real financial and market data from automotive companies, and model performance was assessed using RMSE, nRMSE, and confidence intervals. The results indicate that the full model, including all four indicators, achieved the highest accuracy and prediction stability, while the exclusion of ROA or ROE significantly deteriorated model performance. These findings challenge the weak-form efficiency hypothesis and underscore the relevance of firm-level fundamentals in stock price formation. This study’s sector-specific approach highlights the importance of tailoring predictive models to industry characteristics, offering implications for both financial modeling and investment strategies. Future research directions include expanding the indicator set, increasing the sample size, and testing the model across additional industry domains. Full article

Background: North Carolina Macular Dystrophy (NCMD) is a non-progressive inherited macular dystrophy characterized by marked phenotypic variability. The genetic etiology of NCMD remains largely unknown, and only a limited number of families have been reported in Europe. Methods: We performed an in-depth investigation of an Italian family affected by NCMD using an integrated approach that combined SNP-array analysis, whole-exome sequencing, and long-read whole-genome sequencing. Additionally, we conducted a comprehensive review of NCMD-related literature. Results: We identified a novel 98 Kb duplication involving both PRDM13 and CCNC genes in a three-generation kindred, where the proband exhibited severe macular alterations, while all other affected family members presented with a milder clinical phenotype. A review of the literature suggests different genotype–phenotype correlations and similar penetrance for duplications and single-nucleotide variants (SNVs) in described families. Specifically, smaller duplications may be associated with more severe phenotypes, while SNVs exhibit high phenotypic variability. Conclusions: In this study, we describe the first NCMD Italian family, in which the integration of second- and third-generation sequencing methods enabled the identification of a novel pathogenic PRDM13 and CCNC duplication, thereby expanding the mutational spectrum of NCMD. Overall, these findings, together with the literature review, highlight the importance of selecting appropriate genetic testing approaches that allow the detection of non-coding variants and CNVs and thus enable accurate diagnosis and effective clinical management of patients and their families. Full article

This study examines how Ontario’s Health and Physical Education curriculum addresses the needs of young adults with disabilities. A total of 54 individuals aged 18–35 years old with developmental, learning, or physical disabilities who had completed secondary school in Ontario participated in a cross-sectional mixed-methods survey. Participants were recruited through disability-focused community networks and a university psychology participant pool. They completed the Sex Education subscale of the Sexual Knowledge, Experience, Feelings and Needs Scale, a 35-item sexual knowledge questionnaire, and open-ended questions. Quantitative data were analyzed using descriptive statistics and independent samples t-tests; qualitative responses were examined using thematic analysis. Participants reported limited factual knowledge, minimal classroom representation, and heavy reliance on independent learning. Barriers included inaccessible materials, teacher discomfort, and the absence of disability narratives in sexuality units. Findings point to three priorities: revising curriculum content, expanding educator training, and creating disability-affirming resources. These measures will help ensure comprehensive and rights-based sexuality education that supports the autonomy and well-being of students with disabilities. Full article

In the context of global climate governance and the green transition, digital infrastructure serves as a critical enabler of resource allocation in the digital economy, offering strategic value in tackling synergistic pollution and carbon reduction challenges. Using panel data from 280 prefecture-level cities, this study employs a multiperiod difference-in-differences (DID) approach, leveraging smart city pilot policies as a quasinatural experiment, to assess how digital infrastructure affects urban synergistic pollution-carbon mitigation (SPCM). The empirical results show that digital infrastructure increases the urban SPCM index by 1.5%, indicating statistically significant effects. Compared with energy and income effects, digital infrastructure can influence this synergistic effect through indirect channels such as the energy effect, economic agglomeration effect, and income effect, with the economic agglomeration effect accounting for a larger share of the total effect. Additionally, fixed-asset investment has a nonlinear moderating effect on this relationship, with diminishing marginal returns on emission reduction when investment exceeds a threshold. Heterogeneity tests reveal greater impacts in eastern, nonresource-based, and environmentally regulated cities. This study expands the theory of collaborative environmental governance from the perspective of new infrastructure, providing a theoretical foundation for establishing a long-term digital technology-driven mechanism for SPCM. Full article

Introduction: The wellbeing of humans and the planet is negatively impacted by unhealthy eating behaviors and excessive food waste. Mindfulness approaches have the potential to help people modify their behavior to achieve healthier outcomes. Pilot testing methods to sustainably support healthy eating and reduce food waste are essential for identifying effective ways to promote human and planetary health. Methods: A pilot study was conducted to test a virtual mindful eating program to improve eating behaviors and reduce food waste among a small sample of U.S. adults. Mixed-methods approaches were used to identify the efficacy of the piloted intervention on mindfulness, eating behaviors, and food waste while identifying participant perspectives of the mindful eating program. Results: Quantitative study outcomes indicated positive intervention effects on hunger/satiety cues and food appreciation. No significant intervention effects were detected on mindfulness or food waste. Qualitative findings highlighted participant reports of experiencing greater self-awareness, an improved relationship with food, and a sense of creativity with meal preparation. Conclusions: This pilot study tested a novel mindful eating program that improved eating behaviors related to hunger/satiety and increased food appreciation. The program was accepted by participants, but it did not increase mindfulness or reduce food waste. Future iterations of this mindful eating program will require modifications to test different approaches for increasing mindfulness and reducing food waste while expanding the positive effects on healthy eating. Full article

We report a case of catheter-associated bloodstream infection caused by a putative novel species in the genus Erwinia, identified using whole-genome sequencing (WGS). A female adolescent receiving long-term home parenteral nutrition via a central venous catheter (CVC) presented with a fever. Gram-negative rods were isolated from two CVC-derived blood culture sets, while peripheral cultures remained negative. Conventional identification methods, including VITEK 2, Phoenix M50, MALDI-TOF MS, and 16S rRNA and rpoB gene sequencing, failed to achieve species-level identification. WGS was performed on the isolate using Illumina MiSeq. Genomic analysis revealed a genome size of 5.39 Mb with 56.8% GC content and high assembly completeness. The highest average nucleotide identity (ANI) was 90.3% with Pantoea coffeiphila, and ≤85% with known Erwinia species, suggesting that it represents a distinct taxon. Phylogenetic analyses placed the isolate within the Erwinia clade but separate from any known species. Antimicrobial susceptibility testing showed broad susceptibility. This case highlights the utility of WGS for the identification of rare or novel organisms not captured by conventional methods and expands the clinical spectrum of Erwinia species. While the criteria for species delineation were met, the phenotypic characterization remains insufficient to formally propose a new species. Full article

Cell-free biosensors harness the selectivity of cellular machinery without living cells’ constraints, offering advantages in environmental monitoring, medical diagnostics, and biotechnological applications. This review examines recent advances in cell-free biosensor development, highlighting their ability to detect diverse analytes including heavy metals, organic pollutants, pathogens, and clinical biomarkers with high sensitivity and specificity. We analyze technological innovations in cell-free protein synthesis optimization, preservation strategies, and field deployment methods that have enhanced sensitivity, and practical applicability. The integration of synthetic biology approaches has enabled complex signal processing, multiplexed detection, and novel sensor designs including riboswitches, split reporter systems, and metabolic sensing modules. Emerging materials such as supported lipid bilayers, hydrogels, and artificial cells are expanding biosensor capabilities through microcompartmentalization and electronic integration. Despite significant progress, challenges remain in standardization, sample interference mitigation, and cost reduction. Future opportunities include smartphone integration, enhanced preservation methods, and hybrid sensing platforms. Cell-free biosensors hold particular promise for point-of-care diagnostics in resource-limited settings, environmental monitoring applications, and food safety testing, representing essential tools for addressing global challenges in healthcare, environmental protection, and biosecurity. Full article

Background/Objectives: The integration of artificial intelligence (AI) in medical imaging is rapidly advancing, yet its application in gynecologic use remains limited. This proof-of-concept study presents the development and validation of a convolutional neural network (CNN) designed to automatically detect and classify endometrial polyps. Methods: A multicenter dataset (n = 3) comprising 65 hysteroscopies was used, yielding 33,239 frames and 37,512 annotated objects. Still frames were extracted from full-length videos and annotated for the presence of histologically confirmed polyps. A YOLOv1-based object detection model was used with a 70–20–10 split for training, validation, and testing. Primary performance metrics included recall, precision, and mean average precision at an intersection over union (IoU) ≥ 0.50 (mAP50). Frame-level classification metrics were also computed to evaluate clinical applicability. Results: The model achieved a recall of 0.96 and precision of 0.95 for polyp detection, with a mAP50 of 0.98. At the frame level, mean recall was 0.75, precision 0.98, and F1 score 0.82, confirming high detection and classification performance. Conclusions: This study presents a CNN trained on multicenter, real-world data that detects and classifies polyps simultaneously with high diagnostic and localization performance, supported by explainable AI features that enhance its clinical integration and technological readiness. Although currently limited to binary classification, this study demonstrates the feasibility and potential of AI to reduce diagnostic subjectivity and inter-observer variability in hysteroscopy. Future work will focus on expanding the model’s capabilities to classify a broader range of endometrial pathologies, enhance generalizability, and validate performance in real-time clinical settings. Full article

In this study, we examine the impact of mergers and acquisitions (M&As) on firm environmental performance, aiming to address the gap in research and guide firms, investors, and policymakers toward more environmentally conscious decision-making in M&A. Using panel data from Chinese A-share listed firms (2008–2022), we estimate a two-way fixed effect model. The Propensity Score Matching and the instrumental variable method address potential endogeneity concerns, and robustness checks validate the findings. We found that M&As have a significantly positive effect on firm environmental performance, with heterogeneous impacts across regions, industries, and M&A types. The environmental benefits are most pronounced in heavily polluting industries and hybrid M&A deals. Eastern China shows more modest improvements. The results of mechanism tests revealed that M&As enhance environmental performance primarily by boosting total factor productivity and fostering innovation. This study offers a novel perspective by linking M&A activities to environmental sustainability, enriching the literature on both M&As and corporate environmental performance. We show that even conventional M&A deals (not sustainability-focused) can improve environmental performance through operational synergies. Expanding beyond polluting industries, we reveal how sector characteristics shape M&A’s environmental impacts. We identify practical mechanisms through which standard M&A activities can advance sustainability goals, helping firms balance economic and environmental objectives. It provides empirical evidence from China, an emerging market with distinct institutional and regulatory contexts. The findings offer guidance for firms engaging in M&A to strategically improve sustainability performance. Policymakers can leverage these insights to design incentives for M&A in pollution-intensive industries, aligning economic growth with environmental goals. By demonstrating that M&As can enhance environmental outcomes, this study supports the potential for market-driven mechanisms to contribute to broader societal sustainability objectives, such as reduced industrial pollution and greener production practices. Full article

Nitriding of austenitic stainless steels at low temperatures hinders the precipitation of chromium nitrides and causes the formation of a supersaturated solid solution of nitrogen atoms in the austenite lattice, known as expanded austenite. In this study, the corrosion behavior of low-temperature nitrided AISI 316L is investigated in a NaCl solution using different electrochemical techniques, electrochemical impedance spectroscopy, cyclic potentiodynamic polarization and galvanostatic tests, in order to assess the effect of test conditions. The nitrided layer has an enhanced resistance to localized corrosion, but its ability to repassivate depends on the damage extent caused by the different tests. Full article

Originally introduced in the 1960s by DISA Elektronik as a calibration tunnel for hot-wire anemometers, the Type 55D41 has now been reengineered into a versatile and modern aerodynamic test platform. While retaining key legacy components, such as the converging nozzle and the 55D42 power unit, the upgraded system features a redesigned modular test section with optical-grade quartz windows. This enhancement enables compatibility with advanced flow diagnostics and visualization methods, including PTV, DIC, and schlieren imaging. The modernized facility maintains the precision and flow stability that made the original design widely respected, while expanding its functionality to meet the demands of contemporary experimental research. Its architecture supports the aerodynamic characterization of micro-scale static pressure probes used in aerospace, propulsion, and micro gas turbine applications. Special attention is given to assessing the influence of probe tip geometry (e.g., conical, ogive), port positioning, and stem interference on measurement accuracy. Full article

Person-centered navigation (PCN) in healthcare refers to a proactive collaboration among professionals, researchers, patients, and their families to guide individuals toward timely access to screening, treatment, follow-up, and psychosocial support. PCN—which includes professional, peer, and virtual guidance, is particularly crucial for rare cancers, where affected individuals face uncertainty, limited support, financial strain, and difficulties accessing relevant information, testing, and other services. The Canadian Cholangiocarcinoma Collaborative (C3) prioritizes PCN implementation to address these challenges in the context of Biliary Tract Cancers (BTCs). C3 uses a virtual PCN model and staffs a “C3 Research Navigator” who provides clinical and research navigation such as personalized guidance and support, facilitating access to molecular testing, clinical trials, and case reviews through national multidisciplinary rounds. C3 also supports a national network of BTC experts, a patient research registry, and advocacy activities. C3’s implementation strategies include co-design, timely delivery of support, and optimal outcomes across its many initiatives. Future priorities include expanding the C3 network, enhancing user engagement, and further integrating its innovative approach into routine care. Full article

This work expands the processing window of the laser powder bed fusion (LPBF) processing of WE43 magnesium alloy by evaluating laser powers and scanning speeds up to 400 W and 1200 mm/s, and their effect on densification, microstructure, and electrochemical performance. Relative density of 99.9% was achieved for 300 W and 800 mm/s, showing that the use of high laser power is not a limitation for the manufacturing of Mg alloys, as has been usually considered. Microstructural characterisation revealed refined grains and the presence of RE-rich intermetallic particles, while microhardness increased with height due to thermal gradients. Electrochemical testing in 3.5 wt.% NaCl solution, a more aggressive media than those already used, indicated that the corrosion of samples with density values below 99% is conditioned by the porosity; however, above this value, in the WE43, the corrosion evolution is more related to the microstructure of the samples, according to electrochemical evaluation. This study demonstrates the viability of high-energy LPBF processing for WE43, offering optimised mechanical and corrosion properties for biomedical and structural applications. Full article

The superb dynamic performance of steel-plate composite (SC) structures under unexpected impact loading depends on the good design of the connection between the SC wall and foundation. This study investigated the flexural behavior and dynamic responses of SC wall-to-foundation connections subjected to low-velocity impact. Impact tests were performed on three SC connection specimens to evaluate failure mode, impact force, deflection, and strain responses. The effects of concrete strength grade and impact energy were analyzed in detail. All specimens exhibited flexural failure, with three distinct stages observed during impact. The experimental results demonstrated that compared to the specimen with C30 concrete, the specimen with C50 concrete significantly reduced wall damage, decreased deflections, and enhanced deflection recovery ability. It can be concluded that increasing the concrete strength grade effectively improves the impact resistance of SC wall-to-foundation connections. In addition, peak impact force, global deflection response, residual strains, and interface crack length were highly sensitive to changes in impact energy, whereas deflection recovery exhibited lower sensitivity. Furthermore, a finite element model was developed and validated against experimental results. Parametric studies explored the influence of key parameters with expanded ranges on the impact responses of SC wall-to-foundation connections. Full article