Search Results (4,652)

Fabrazyme (agalsidase beta) is a therapeutic enzyme whose clinical efficacy is contingent upon its complex N-glycosylation patterns. Nevertheless, comprehensive glycosylation profiling remains challenging due to high site-specific heterogeneity. To address this, three orthogonal liquid chromatography–mass spectrometry (LC-MS) approaches were employed: (1) released N-glycan analysis with fluorescence detection and MS annotation, (2) site-specific glycopeptide mapping, and (3) intact protein MS. The released glycan profiling method was validated for reproducibility, intermediate precision, and inter-laboratory transferability, thereby enabling reliable separation and quantification of neutral, phosphorylated, and sialylated species. Glycopeptide mapping revealed distinct site-specific distributions: N108 was found to predominantly carry sialylated complex glycans; N161 was enriched in phosphorylated oligomannose structures; and N184 displayed the highest heterogeneity, including bisphosphorylated and sialylated glycans. Intact protein analysis was performed on both intact and desialylated Fabrazyme, thereby enabling confirmation of glycan assignments. Desialylation reduced spectral complexity, thereby facilitating accurate mass matching with a combinatorial library generated from glycopeptide-level data. The complementary use of these three analytical levels provides a comprehensive view of Fabrazyme glycosylation, offering a robust reference for quality control and biosimilar development. Full article

Sparse light field imaging often limits the quality of 3D scene reconstruction due to insufficient viewpoint coverage, resulting in incomplete or inaccurate reconstructions. This work introduces a hybrid CNN–LSTM-based framework to address this issue by generating novel camera poses and the corresponding synthesized novel views, effectively densifying the light field representation. The CNN extracts spatial features from the sparse input views, while the LSTM predicts temporal and positional dependencies, enabling smooth interpolation of novel poses and views. The proposed method integrates these synthesized views with the original sparse dataset to produce a comprehensive set of images. Our approach was evaluated on several datasets, including challenging datasets. The inference capability of our method was tested extensively, and it showed good generalization across diverse datasets. The effectiveness of the framework was evaluated not only with local light field fusion (LLFF) but also with NeRF and 3D Gaussian Splatting, which are considered state-of-the-art reconstruction methods. Overall, the enriched dataset generated by our method led to consistent improvements in 3D reconstruction quality, including higher depth estimation accuracy, reduced artifacts, and enhanced structural consistency. Most importantly, LSTM-based approaches have so far attracted limited attention in the context of generating novel views. While LSTMs have been widely applied in sequential data domains such as natural language processing, their use for image generation conditioned on camera poses remains largely unexplored, which underscores the novelty and significance of the proposed work. This approach provides a scalable and generalizable solution to the sparsity problem in light fields, advancing the capabilities of computational imaging, photorealistic rendering, and immersive 3D scene reconstruction. The results firmly establish the proposed method as a robust and versatile tool for improving reconstruction quality in sparse-view settings. Full article

Pedestrian gender recognition plays an important role in pedestrian analysis and intelligent video applications, for example, in demographic statistics, soft biometric analysis, and context-aware person retrieval. However, it remains a challenging task owing to viewpoint variations, illumination changes, occlusions, and low image quality in real-world imagery. To address these issues, an effective adaptive decision fusion framework, termed the Decision Fusion Learning Network (DFLN), is proposed in this paper. The key novel aspect of DFLN is that it effectively explores both an appearance-centered view that emphasizes detailed texture and clothing information and a structure-centered view that captures rich contour and structural information for pedestrian gender recognition. To realize DFLN, a Parallel CNN Prediction Probability Learning Module (PCNNM) is first constructed to independently learn modality-specific probabilities from color image and edge maps. Subsequently, a learnable Decision Fusion Module (DFM) is designed to fuse the modality-specific probabilities and explore their complementary merits for realizing accurate pedestrian gender recognition. The DFM can be easily coupled with the PCNNM, forming an end-to-end decision fusion learning framework that simultaneously learns the feature representations and carries out adaptive decision fusion. Experiments on two pedestrian benchmark datasets, named PETA and PA-100K, show that DFLN achieves competitive or superior performance compared with several state-of-the-art pedestrian gender recognition methods. Extensive experimental analysis further confirms the effectiveness of the proposed decision fusion strategy and its favorable generalization ability under domain shift. Full article

With accelerating global urbanization and increasingly diverse demands for public spaces, promoting urban low-carbon transitions and enhancing residents’ quality of life have become central missions of modern urban development. As one of the city’s primary arteries, streets—through their green landscapes, slow-moving transportation systems, and public facilities—play an indispensable role in reducing carbon emissions, promoting healthy living, and improving residents’ well-being. In this study, the Yubei District of Chongqing was selected as the research area, and an automated evaluation framework was proposed for street visual quality, based on multi-source street view data and ensemble learning. PSP-Net semantic segmentation model was employed to extract eight key visual indicators from street view images, including green view index, Visual Entropy (Entropy), sky view factor (SVF), drivable space, sidewalk, safety facilities, buildings, and enclosure. Based on these features, a Stacking-based ensemble learning model was constructed, integrating multiple base models such as Random Forest, XGBoost, and LightGBM, with Linear Regression as the meta-learner, to predict street visual quality. The results demonstrate that the ensemble model significantly outperforms any single model, achieving a correlation coefficient (r) of 0.77 and effectively capturing the complex perceptual features of street environments. This study provides a reliable, intelligent, and quantitative method for large-scale evaluation of urban street visual quality, while supplying data support and decision-making references for street renewal and spatial optimization. Full article

Distinguishing surfaces from underwater targets in complex marine environments is challenging when relying solely on physical sonar features. To address the high uncertainty inherent in single-modal features and the conflicts arising from heterogeneous data, we propose a Dual-View Entropy-Driven Negation Dempster–Shafer (DVE-NDS) fusion method that integrates AIS kinematic priors with passive sonar signals. First, a heterogeneous recognition framework is constructed. LOFAR and DEMON features are extracted via convolutional neural networks (CNNs), while a Negation Basic Probability Assignment (Negation BPA) strategy is introduced to transform AIS spatiotemporal mismatches into effective "negation support" for non-cooperative underwater targets. Instead of relying on a single conflict coefficient, the proposed method jointly considers evidence self-information and inter-source consistency. Evidence quality is quantified using improved Deng entropy and negation belief entropy, while mutual trust is evaluated via the Jousselme distance. Heterogeneous evidence is weighted and corrected by generated coupling weights, effectively suppressing low-quality evidence and sharpening decision boundaries. Simulation results confirm that DVE-NDS improves macro-F1 over classical fusion, indicating the framework’s potential for handling conflicting evidence, though the current validation remains simulation-based and should be regarded as a methodological proof-of-concept. Full article

This study explored pre-service teachers’ views on the use of generative artificial intelligence (Gen AI) in the production of misinformation, addressing the potential challenges posed by deepfakes generated by these online resources. A quantitative approach was used; 133 pre-service teachers participated in the study, all of them were enrolled in primary education degree programmes in the Region of Murcia, Spain. The results indicated a clear awareness of the risks posed by these digital tools in the generation of deepfakes. Respondents became aware of the potential threats this may pose on the internet, which can be further exacerbated when disseminated in educational environments. Recognising the relevance of pre-service teachers’ concerns can help educators and educational administrations take steps to limit Gen AI in accordance with ethical parameters and thus reduce the spread of misinformation. In social science teaching and learning, further research is needed to equip students with the essential skills to distinguish between accurate and inaccurate information. For all these reasons, it seems essential to improve research in media literacy education for the application of identification skills used in assessment processes. These improvements can take the form of evidence-based approaches, such as AI literacy programmes or media literacy modules, to facilitate student learning and ensure better quality education. Full article

In light of China’s dual national strategies of Healthy China and the Big Food View, this study examines the relationship between digital inclusive finance and residents’ dietary nutrition, with a focus on healthier and more sustainable dietary patterns. Using panel data from 31 Chinese provinces over the period 2015–2022, we employ a two-way fixed effects model to evaluate how digital inclusive finance is associated with food intake diversity and dietary structure balance. The empirical findings show that digital inclusive finance is positively associated with increased consumption of both plant-based foods (e.g., cereals) and animal-based foods (e.g., meat, milk and aquatic products), contributing to improved dietary structure balance. These findings remain robust after addressing potential endogeneity concerns and conducting a series of multiple robustness checks. Further heterogeneity analysis indicates that the depth of use and degree of digitization are significantly associated with dietary quality, while the breadth of coverage shows no significant effect. Moreover, the positive associations are more pronounced among rural residents, upper-middle income groups, and households with lower levels of human capital, groups with high e-commerce development and high levels of digitalization. These findings highlight the potential role of digital inclusive finance as a policy tool for promoting healthier and more sustainable dietary patterns, particularly among disadvantaged populations in rural China. Full article

This paper examines the impact of real effective exchange rate (REER) misalignment on banking stability, while emphasizing the moderating effect of institutional quality. We also aim to investigate the non-linearity of this relationship. Based on a panel of 40 emerging countries covering the period from 2000 to 2020, and using the system generalized method of moments (SGMM) estimator, we show that REER misalignment positively impacts banking stability. A second set of estimations provides a more nuanced view. The results reveal that overvaluation contributes to enhance banking stability, while undervaluation proves to be a source of instability. The results also suggest that institutional development boosts both the positive and negative effects. Further investigations show that the considered relationship is conditional on the magnitude of the exchange rate misalignment and on the level of banking stability. The empirical results reveal the existence of an inverted U-shaped relationship between REER misalignment and banking stability: low levels of exchange rate misalignment contribute to boost stability, while high levels of misalignment exacerbate instability. In addition, REER misalignment promotes stability during calm periods, while it contributes to fuel instability during financial turmoil. Misalignment thus proves to be a double-edged weapon, which should be used with great caution to avoid systemic crisis. Full article

Although urban streetscape visual esthetic quality (VAQ) assessment has progressed markedly, its findings are rarely operationalized in urban planning policy-making. The resulting discontinuity in the assessment–policy linkage is a critical impediment to streetscape VAQ enhancement. We propose an eye-tracking-enabled, end-to-end decision support framework that links evidence acquisition, intervention prioritization, design strategy formulation, and outcome feedback. Eye tracking is integrated to establish a three-dimensional assessment system spanning spatial, psychological, and physiological dimensions. Within this integrated system, we construct a three-level eye-tracking-based visual characteristics (ET-VC) framework across streetscape elements, formal characteristics, and public esthetic perception (PAP). Together, the three-dimensional system provides a theoretical basis for acquiring the multi-modal data required for VAQ enhancement. Building on this integrated assessment, we embed scenario planning theory to construct a planning facing decision model with PAP as the core outcome. The model combines importance-performance analysis (IPA) with the coupling coordination degree model (CCDM) to guide resource allocation decisions and intervention prioritization, and further uses eye-tracking evidence to support the development of refined, actionable enhancement strategies. A case study in Wudadao validates the framework’s robustness and feasibility. The ET-VC results provide additional evidence for interpreting esthetic perception: (1) ET-VC indicators differ significantly across streetscape elements, and “being viewed more” does not necessarily correspond to higher esthetic ratings; (2) four groups of key formal characteristic indicators—color configuration, naturalness, historicity and planning/regulatory control, and visual scale—systematically reshape fixation onset and maintenance patterns; and (3) PAP appears to involve partially nonlinear relationships between material landscape features and additional top-down influences (e.g., historical narratives and individual experience), rather than being fully explained by linear associations alone. Overall, this study provides both a theoretical basis and an applied demonstration for evidence-based streetscape VAQ enhancement. Full article

Adenine nucleotide translocase (ANT) has traditionally been defined as the ADP/ATP exchanger of the inner mitochondrial membrane. However, accumulating mechanistic evidence reveals a substantially broader functional spectrum that extends beyond nucleotide transport. In this review, we integrate these advances into a unified conceptual framework that positions ANT isoforms as modulators of mitochondrial bioenergetics, quality control, and cellular communication. Beyond its canonical exchange activity, ANT influences permeability transition thresholds and membrane potential stability, participates in regulated uncoupling and redox control, and contributes to inner membrane organization and cristae integrity. ANT further modulates TIMM23-dependent protein import and PINK1–Parkin-mediated mitophagy, thereby shaping mitochondrial quality control decisions. In addition, ANT regulates mitochondrial nucleic acid release and inflammasome activation, linking bioenergetic imbalance to innate immune signaling. Emerging evidence for alternative subcellular localizations suggests that ANT-dependent signaling extends mitochondrial state information to extracellular and intercellular contexts. Collectively, these findings support an expanded view of ANT as a multifunctional modulator linking mitochondrial energetic state to stress adaptation, inflammatory signaling, and tissue-level communication. Full article

The rapid expansion of digital and technology-enhanced assessments has enabled the capture of far more than final responses or total scores. As learners navigate traditional formats, such as multiple-choice, short-answer, and performance tasks, digital delivery platforms routinely capture response times, response revisions, navigation patterns, and item-level metadata. More advanced formats, including interactive simulations, scenario-based tasks, and game-based assessments, further record fine-grained actions such as mouse clicks, keystrokes, hint requests, sequence of operations, and decision pathways. These increasingly rich data streams provide a multidimensional view of test-taker behavior, offering evidence about cognitive processes, strategy use, persistence, and motivation that goes beyond what correctness alone can reveal. Assessment analytics refers to the systematic collection, integration, and analysis of such data generated during the assessment process. In practice, this emerging field combines principles from psychometrics, learning analytics, data science, and human-computer interaction to evaluate the quality, validity, and fairness of assessments in digital environments. The ultimate goal of assessment analytics is to produce actionable evidence about how assessments measure what they intend to measure in contemporary, technology-rich educational contexts. Full article

Male infertility has been viewed as a potential biomarker for systemic health and a predictor of future disease. With the global burden of neurodegenerative diseases (NDDs) on the rise, the current systematic review aims to synthesize the reported associations, risks, and shared molecular mechanisms between male infertility and NDDs. Following PRISMA 2020 guidelines, we systematically searched PubMed, Embase, Scopus, and Cochrane CENTRAL in January 2026. Studies examining the relationship between male infertility and NDDs were included. Screening and data extraction were performed by two independent reviewers with a third to resolve conflicts while quality appraisal (ROBINS-E and OHAT) was performed for all included studies. Studies used heterogeneous definitions of male infertility, including clinical diagnosis, semen parameters, and reproductive outcomes. Of the 1566 identified studies, 13 were included in this review including case-control studies, experimental investigations, in vitro studies, bioinformatic analyses, and pedigree studies. The available literature suggests possible mechanistic overlap between male infertility and neurodegenerative disease pathways, particularly in mitochondrial dysfunction, oxidative stress, and proteostasis. However, the evidence remains heterogeneous and preliminary, and large prospective studies are needed before male infertility assessment can be considered a marker of neurodegenerative risk. Registration: The study protocol was registered on PROSPERO (registration code: CRD420261301509). Full article

Purpose: Rapid bank digitisation has heightened cybersecurity risks and increased stakeholder expectations for transparent cyber risk governance and disclosure. However, research on whether women’s board involvement enhances financial success varies and depends on the context, particularly within different institutional settings. Therefore, this study investigates the impact of Women on Boards (WIB) on Earnings per Share (EPS) of Jordanian banks during 2010 to 2022 and further examines the moderating effect of Cyber Security Disclosure (CSD) on the relationship between WIB and EPS. Design: Combining manual content analysis of each Jordanian bank’s annual report with regression analysis to assess the correlation between EPS, WIB, and CSD. The study also controls for audit quality estimates, financial leverage, bank age, and size. Findings: Our results reveal a negative correlation between EPS and the increasing number of women on boards; thus, simply having more women on boards does not necessarily lead to higher EPS. Additionally, there is a positive interaction between WIB and CSD on EPS, indicating that strong cybersecurity practices can mitigate the negative effects of gender diversity on the board. The ongoing negative association between board diversity and EPS underscores the complexity of gender relations in corporate governance issues. Originality: This research is the first to examine both gender diversity and cybersecurity practices within the same context, as they jointly influence corporate governance and financial performance in new ways. It emphasises the importance of viewing cybersecurity disclosures as a strategic component that can positively impact the financial outcomes of board diversity. Full article

Sustainable tourism development requires more than well-designed human resource systems; it also relies on how leadership is demonstrated in daily interactions with employees, especially in high-contact service environments. While high-performance work systems (HPWSs) are widely recognized for enhancing employee performance and service quality, their effectiveness may depend on relational processes that occur at the supervisory level. This study examines resonant leadership as a relational mechanism that complements structural HR practices. Instead of viewing leadership as a background condition, we focus on how emotionally intelligent leader behaviors influence employees’ job satisfaction and, consequently, their organizational citizenship behavior (OCB). Based on Social Exchange Theory and Affective Events Theory, we propose that job satisfaction acts as a mediator linking resonant leadership to discretionary service behaviors. Survey data were gathered from hotel employees in Cyprus, with 337 valid questionnaires included in the final analysis. The results show that resonant leadership is positively related to job satisfaction and OCB. Additionally, job satisfaction partially mediates this relationship, suggesting that emotionally attuned leadership fosters stronger affective bonds and encourages voluntary behaviors that support service delivery. By including relational leadership in the sustainability discussion, this study expands the mostly system-focused HPWS literature. The findings imply that sustainable tourism outcomes are driven not only by formal HR structures but also by leadership practices that stabilize human capital and reinforce service consistency over time. Full article

Achieving gender parity in leadership remains a persistent challenge in the fintech industry, where women continue to be underrepresented in senior and C-suite roles. This paper argues that such disparity is not only a matter of equity but also a structural constraint on governance quality and sustainability outcomes. Building on insights from social role theory and the resource-based view, this paper develops a conceptual framework linking sustainable human resource management (HRM) practices to gender parity in organizational leadership and, in turn, to environmental, social, and economic sustainability outcomes. Drawing on interdisciplinary literature and illustrative case vignettes, the paper identifies key barriers to women’s advancement in fintech, including the broken rung in early promotions, tokenism driven by unconscious bias, and unequal access to venture capital. The model specifies how three dimensions of sustainable HRM—inclusive networking, diversity training, and mentorship programs can address these barriers by fostering equitable promotion pathways, credible merit-based leadership, and inclusive leadership pipelines. By positioning gender parity in leadership as a central mechanism through which HRM systems shape firm sustainability outcomes, the paper reframes gender equity as a strategic organizational capability, rather than a standalone diversity goal. The derived propositions offer a foundation for future empirical research and provide actionable insights for fintech organizations seeking to build resilient, inclusive, and sustainable leadership structures. Full article