Search Results (297)

This study examines how transnational online continuing professional development (CPD) supports language instructors’ technological pedagogical content knowledge (TPACK) in transnational higher education (TNHE). To assess this development, an existing TPACK self-report instrument was adapted to reflect cross-border online delivery, platform-mediated assessment and feedback, and collaborative course preparation. Survey data were collected from instructors at University of Southampton partner institutions in China (n = 431). Using exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation modeling (SEM), and paired-samples t-tests, the study examined the instrument’s measurement properties, the structural relations among knowledge domains, and changes over time. Results supported a stable four-factor structure—technological knowledge, content knowledge, pedagogical knowledge, and TPACK—with good model fit and acceptable reliability and validity. SEM showed that pedagogical knowledge and technological knowledge significantly predicted TPACK, whereas content knowledge did not directly predict it. Longitudinal analyses of matched pre–post responses (n = 172) indicated significant increases in technological knowledge, pedagogical knowledge, and TPACK after CPD participation, while content knowledge remained statistically stable. These findings suggest that routine online CPD is most responsive in strengthening instructors’ technology-related and pedagogical capacities, which in turn support integrative teaching competence in TNHE language teaching. Full article

Chimeric antigen receptor T (CAR-T) cell therapy has become a standard of care for many hematological malignancies, and has significantly transformed treatment outcomes. However, CAR-T therapy is associated with specific toxicities, including infections. Although the anti-CD19 CAR-T risks are well-characterized, infectious complications following B-cell maturation antigen (BCMA)-directed CAR-T in multiple myeloma (MM) remain under-researched. In this study, we evaluated the incidence and clinical impact of cytomegalovirus (CMV), Epstein–Barr virus (EBV), and adenovirus (ADV) reactivations in 75 patients receiving anti-BCMA CAR-T for MM, and compared them to 60 patients receiving commercial anti-CD19 CAR-T for B-cell lymphoma (BCL). The viral reactivation rates were 20% for CMV and 8% for EBV in the MM group, vs. 31.7% and 3%, respectively, in the BCL group. No ADV reactivations were seen in either cohort. Most of the CMV reactivations (87% in the MM cohort and 68.5% in the BCL cohort) were asymptomatic and clinically insignificant, and had no impact on progression-free survival (PFS) or overall mortality. Overall, these findings suggest that although CMV and EBV reactivations are relatively common after anti-BCMA CAR-T, they are rarely associated with meaningful disease, and the risks do not exceed those of CD19-directed therapy. Thus, routine pre-emptive screening for these viruses may be unwarranted in asymptomatic patients. Full article

Large-scale expansion of human mesenchymal stem cells (hMSCs) remains a major challenge due to the intrinsic trade-off between cell proliferation and the maintenance of multipotency in conventional culture systems. Stiff substrates, such as tissue culture polystyrene or rigid hydrogels, promote rapid proliferation but induce progressive loss of stemness, whereas very soft matrices preserve multipotency at the expense of cell growth. To overcome this limitation, we developed mechanically soft, phase-separated gelatin–phenol/hyaluronic acid–phenol (Gtn-Ph/HA-Ph) hydrogels with precisely controlled microstructures via enzyme-mediated crosslinking. These hydrogels consist of HA-rich, dot-like domains embedded within a continuous Gtn-rich network, allowing for independent tuning of stiffness and domain architecture. On single-component Gtn-Ph hydrogels, hMSC proliferation increased with substrate stiffness, whereas soft hydrogels with a storage modulus (G′) of approximately 0.6 kPa markedly suppressed proliferation while preserving stemness marker expression, confirming the stiffness-dependent trade-off. In contrast, phase-separated Gtn-Ph/HA-Ph hydrogels supported robust hMSC proliferation even under soft mechanical conditions while maintaining high expression of stemness-associated markers. During long-term culture, hMSCs achieved a 68- to 195-fold increase in cumulative cell yield on soft Gtn-Ph/HA-Ph hydrogels (G′ = 0.5 kPa) compared with tissue culture polystyrene. Expression of α-smooth muscle actin (α-SMA) mRNA, encoded by the ACTA2 gene and associated with cellular senescence and fibrotic activation, was completely suppressed, while hMSCs retained robust adipogenic, osteogenic, and chondrogenic differentiation capacities. These results demonstrate that phase-separated Gtn-Ph/HA-Ph hydrogels effectively resolve the proliferation–multipotency dilemma in hMSC expansion and provide a promising platform for scalable manufacturing of therapeutic stem cells. Full article

Roadmapping is widely used as a collaborative management tool for innovation planning; however, how stakeholders co-create value throughout the roadmapping process remains insufficiently evidenced and operationalized. Drawing on service-dominant (S-D) logic and stakeholder integration, this study examines how stakeholders co-create value in planning innovative technologies through a roadmapping process. We conducted an interpretive single-case study in a technology-oriented organization using seven facilitated workshops with 36 stakeholders, and analyzed workshop artefacts, facilitator notes, and follow-up communications captured via collaboration platforms. The findings show that stakeholder value co-creation is enacted through recurring interaction patterns observed across W1–W7 and across initiation, development, and integration, supported by collaboration platforms that enable continuity, transparency, and traceability from early ideation to integrated roadmap outputs. This study contributes an empirically grounded, traceable process model linking S-D logic to roadmapping practice and provides actionable guidance for organizations orchestrating stakeholder participation in innovation planning. Full article

The detection of deepfake speech has become a significant research area due to rapid advancements in generative AI for speech synthesis. These technologies pose significant security risks in applications such as biometric authentication, voice-controlled systems, and automatic speaker verification (ASV) systems. Therefore, enhancing the detection capabilities of such applications is essential to mitigate potential threats. This study investigates perceptual speech-pathological features, which are commonly used to evaluate the unnaturalness of voice disorders in clinical settings, as potential indicators for detecting deepfake speech. Specifically, the timbral attributes of hardness, depth, brightness, roughness, sharpness, warmth, boominess, and reverberation are examined. The analysis reveals that these attributes provide meaningful distinctions between genuine and synthetic speech. Furthermore, the detection performance is enhanced by extending the dimensional representation of timbral attributes, enabling a more comprehensive characterization of the speech signal. This paper proposes a method that combines two models: one utilizing the different dimensions of speech-pathological features with a deep neural network (DNN), and another employing a gammatone filterbank model that simulates the auditory processing mechanism of the human cochlea with ResNet-18 architecture, improving deepfake speech detection. The proposed method is evaluated on the Automatic Speaker Verification Spoofing and Countermeasures Challenge (ASVspoof) 2019 dataset. Experimental results demonstrate that the proposed approach outperforms baseline models in terms of Equal Error Rate (EER), achieving an EER of $5.93$%. Full article

This study examines how digital transformation (DX) unfolds in Small and Medium-sized Enterprises (SMEs) through an analytical integration of dynamic capabilities (DCs) and service-dominant logic (SDL). While DX research is abundant, existing studies tend to discuss internal organizational capabilities (DCs) and external value co-creation (SDL) in isolation, offering limited insight into how resource-constrained SMEs execute transformation in practice. Employing a multiple case study approach based on Japanese SMEs, this paper uses the micro-foundations of DC (sensing, seizing, and transforming) as an analytical lens to examine how the resource integration processes emphasized in SDL are operationalized through phased organizational decision-making. The findings illustrate that while DC provides the organizational process logic for change, SDL offers the perspective through which SMEs overcome internal resource scarcity by engaging in external collaboration. By bridging internal capability-based and external co-creation perspectives, this study contributes to a more granular and contextually grounded understanding of transformation processes under resource constraints. From a practical perspective, the findings highlight the importance of fostering dialogue and building external relationships as conditions for activating dynamic capabilities and mitigating organizational rigidity, offering practically relevant implications for SME managers and policymakers. Full article

Acute mesenteric ischemia (AMI) is a clinical condition caused by vascular insufficiency, resulting in intestinal damage. Is often underestimated, if not driven by clinical suspicion, due to the non-specific clinical symptoms (usually represented by acute abdominal pain) and the absence of reliable markers, which results in a poor prognosis and high mortality. We can identify three main forms of AMI: arterial, venous, and non-occlusive. Arterial AMI is the most frequent form, caused by occlusion of the superior mesenteric artery or one of its branches. Venous AMI is the least frequent, caused by thrombosis of the superior mesenteric vein or its branches. Non-occlusive AMI is due to a state of hypovolemia, which is frequent in patients who have undergone surgery. Given the difficulty of diagnosis based on the clinic alone, the radiologist plays a central role in identifying radiological signs of intestinal ischemia and in avoiding misdiagnosis. The radiologist’s role is mainly to identify factors predictive of necrosis, which allow us to stratify patients and direct them towards the proper management. The aim of this review is to provide indications for an adequate CT protocol, including an unenhanced phase, an arterial phase, and a venous phase, as well as to underline the features to investigate in the different forms of AMI, in order to increase the diagnostic capacity in this challenging disease. Full article

State-of-charge (SoC) balancing across multiple battery energy storage systems (BESS) is a central challenge in renewable-rich mini-grids. Heterogeneous battery capacities, differing states of health, stochastic renewable generation, and variable loads create a high-dimensional uncertain control problem. Conventional droop-based SoC balancing strategies are decentralized and computationally light but fundamentally reactive and limited, whereas model predictive control (MPC) is insightful but computationally intensive and prone to modeling errors. This paper proposes a Hierarchical Predictive–Adaptive Control (HPAC) framework for SoC balancing in mini-grids using deep reinforcement learning. The framework consists of two synergistic layers operating on different time scales. A long-horizon Predictive Engine, implemented as a federated Transformer network, provides multi-horizon probabilistic forecasts of net load, enabling multiple mini-grids to collaboratively train a high-capacity model without sharing raw data. A fast-timescale Adaptive Controller, implemented as a Soft Actor-Critic (SAC) agent, uses these forecasts to make real-time charge/discharge decisions for each BESS unit. The forecasts are used both to augment the agent’s state representation and to dynamically shape a multi-objective reward function that balances SoC, economic performance, degradation-aware operation, and voltage stability. The paper formulates SoC balancing as a Markov decision process, details the SAC-based control architecture, and presents a comprehensive evaluation using a MATLAB-(R2025a)-based digital-twin simulation environment. A rigorous benchmarking study compares HPAC against fourteen representative controllers spanning rule-based, MPC, and various DRL paradigms. Sensitivity analysis on reward weight selection and ablation studies isolating the contributions of forecasting and dynamic reward shaping are conducted. Stress-test scenarios, including high-volatility net-load conditions and communication impairments, demonstrate the robustness of the approach. Results show that HPAC achieves near-minimal operating cost with essentially zero SoC variance and the lowest voltage variance among all compared controllers, while maintaining moderate energy throughput that implicitly preserves battery lifetime. Finally, the paper discusses a pathway from simulation to hardware-in-the-loop testing and a cloud-edge deployment architecture for practical, real-time deployment in real-world mini-grids. Full article

Multi-target drug design represents a paradigm shift in tackling the complexity and heterogeneity of diseases such as cancer. Conventional single-target therapies frequently face limitations due to network redundancy, pathway compensation, and adaptive resistance mechanisms. In contrast, deep generative models, empowered by advanced artificial intelligence algorithms, provide scalable and versatile platforms for the de novo generation and optimization of small molecules with activity across multiple therapeutic targets. This review provides a comprehensive overview of the recent landscape of AI-driven deep generative modeling for multi-target drug discovery, highlighting breakthroughs in model architectures, molecular representations, and goal-directed optimization strategies. We also examine the emergence of self-improving learning systems, closed-loop frameworks that iteratively refine molecular candidates through integrated feedback, as a transformative approach to adaptive drug design. Finally, key challenges, current limitations, and emerging trends are discussed to guide the evolution of next-generation intelligent and autonomous drug discovery pipelines for multi-target therapeutics. Full article

To address demand–supply mismatches in traditional village human settlements (TVHSs), this study builds on existing human settlement research by introducing cultural landscape theory and constructing a comprehensive framework that includes the hard (infrastructure, living environment, ecological environment, and environmental sanitation) and soft environment (social services, economic environment, and cultural environment). Villagers’ and experts’ perceptions of importance are integrated through a hierarchical weighting system combining AHP, CRITIC, and GRA. In addition, cluster analyses, the importance–satisfaction (IS) model, the obstacle degree model, and mediation analyses are employed to identify village classifications, determine optimization indicators, and assess mechanism effects. The findings indicate the following: (1) The overall satisfaction with TVHSs in Northeast China is moderate, with a stepwise decline from northeast to southwest, and the economic environment significantly lags behind other dimensions. (2) Four village classifications are identified—demonstration, basic-level development, potential-focused, and priority improvement. (3) The optimization indicators across classifications include toilet conditions, village cleanliness, school accessibility, and access to medical services, resulting in strategies such as “cultural landscape empowerment” and “telemedicine coverage”. (4) Mediation analyses show that improvements in the hard environment enhance overall satisfaction both directly and indirectly through social services and the economic environment. These findings highlight the close link between satisfaction and regional development, underscoring the need for dynamic monitoring and greater emphasis on the cultural dimension to support TVHS optimization and rural revitalization. Full article

Renewable energy sources (RESs) such as photovoltaic (PV) and fuel cells (FCs) introduce variability that complicates reliable, loss-aware operation of distributed power-flow systems (DPFSs) in smart homes. Frequent charge/discharge cycling of energy storage systems (ESSs) can inflate losses and jeopardize user comfort when generation and demand are mismatched. This paper addresses the gap in multi-load, multi-source coordination under fluctuating RESs by proposing a Multiple-Load Power-Flow Assignment (MPFA) framework that explicitly minimizes storage-related losses while maintaining demand satisfaction. We evaluate four logical interconnection scenarios among generators (PGs), loads (PLs), and storage (PSs), and compare three control algorithms—total-demand-based (TDPF), adaptive-demand-based (ADPF), and grid-based (GBPF). Using measured PV/FC data across seasons, MPFA consistently reduces storage-related losses as interconnections increase, with GBPF guaranteeing full daily demand satisfaction by flexibly supplementing local generation with grid power. ADPF performs strongly when grid support is limited by prioritizing critical loads and optimizing storage utilization. The results provide actionable guidance for designing smart-home energy management that emphasizes sustainability, reliability, and user comfort. Full article

Objectives: This study aimed to compare the fit accuracy between retainers fabricated using conventional cold-curing resin (hereinafter referred to as “conventional retainers”) and those fabricated using three-dimensional (3D) printing based on computer-aided design/computer-aided manufacturing (CAD/CAM) technology (hereinafter referred to as “CAD/CAM retainers”). Furthermore, the study aimed to compare two different methods to evaluate the fit accuracy: the impression replica technique and the 3D triple-scan protocol. Methods: For each of the 20 working models derived from a maxillary typodont, one conventional retainer and one CAD/CAM retainer were fabricated. The fit accuracy was evaluated using the impression replica technique and the 3D triple-scan protocol. Measurements were taken at 12 points on each model, and the differences in thickness (gap) were analyzed using Wilcoxon’s signed-rank test. Moreover, the correlation between thickness and measurement site was evaluated using Spearman’s rank correlation coefficient. Results: In both evaluation methods, the CAD/CAM retainers exhibited superior fit accuracy compared to the conventional retainers. Notably, the 3D triple-scan protocol clearly demonstrated that the fit accuracy differed depending on the measurement site. Conclusions: CAD/CAM retainers demonstrated superior fit accuracy compared to conventional retainers, possibly because digital design can account for polymerization shrinkage. In the impression replica technique, the median (interquartile range) thickness for the conventional retainers was 0.169 (0.120–0.260) mm, whereas that for the CAD/CAM retainers was 0.136 (0.096–0.198) mm. The CAD/CAM retainers showed significantly smaller gap values (p < 0.001). Within the limitations of this in vitro study, CAD/CAM retainers showed significantly smaller gap values than conventional retainers, indicating improved fit accuracy. In particular, the 3D triple-scan protocol accurately captured site-specific variations in fit accuracy among the anterior, canine, and molar regions. Full article

Gacha games, particularly those using Free-to-Play (F2P) models, have become increasingly popular yet controversial due to their addictive mechanics, often likened to gambling. This study investigates the inherent addictive mechanisms of Gacha games, focusing on Genshin Impact, a leading title in the genre. We analyze the interplay between reward frequency, game attractiveness, and player addiction using the Game Refinement theory and the Motion in Mind framework. Our analysis identifies a critical threshold at approximately 55 pulls per rare item ($N\approx 55$), with a corresponding gravity-in-mind value of 7.4. Beyond this point, the system exhibits gambling-like dynamics, as indicated by Game Refinement and Motion in Mind metrics. This threshold was measured using empirical gacha data collected from Genshin Impact players and analyzed through theoretical models. While not claiming direct causal evidence of player behavior change, the results highlight a measurable boundary where structural design risks fostering addiction-like compulsion. The study contributes theoretical insights with ethical implications for game design, by identifying critical thresholds in reward frequency and game dynamics that mark the shift toward gambling-like reinforcement. The methodologies, including quantitative analysis and empirical data, ensure robust results contributing to responsible digital entertainment discourse. Full article

Learning and understanding of art are increasingly understood as dynamic processes in which emotion and cognition unfold over time. However, classroom-based evidence on how structured temporal intervals and guided prompts reshape students’ emotional experience remains limited. This study addresses these gaps by quantitatively examining changes in emotion over time in a higher education institution. Employing a comparative experimental design, third-year undergraduate art students participated in two structured courses, where emotional responses were captured using an emotion recognition approach (facial expression and self-reported text) during two sessions: initial impression and delayed impression (three days later). The findings reveal a high consistency in dominant facial expressions and substantial agreement in self-reported emotions across both settings. However, the delayed impression elicited greater emotional diversity and intensity, reflecting deeper cognitive engagement and emotional processing over time. These results reveal a longitudinal trajectory of emotion influenced by guided reflective re-view over time. Emotional dynamics extend medium theory by embedding temporal and affective dimensions into TBMA course settings. This study proposes an ethically grounded and technically feasible framework for emotion recognition that supports reflective learning rather than mere measurement. Together, these contributions redefine TBMA education as a temporal and emotional ecosystem and provide an empirical foundation for future research on how emotion fosters understanding, interest, and appreciation in higher media art education. Full article

This study aimed to evaluate cytokine profiling in a periapical lesion to provide a rationale for future treatment strategies for periapical lesions. Thirteen samples of exudative fluid were collected from such a lesion directly through the root canal. Cytokine profiling was performed using the Bio-Plex system. CXCL10 (C-X-C motif chemokine ligand 10, IP10) was found to be elevated in apical exudates of patients exhibiting favorable healing. To evaluate the role of CXCL10 in cell migration, a Transwell assay was conducted using bone marrow-derived mononuclear cells (BMMCs). Different types of cytokines were detected from the samples of periapical lesion at the initial visit. However, cytokine production varied across patient samples. Release of interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12, IL-13, IL-17, granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage colony-stimulating factor (GM-CSF), interferon gamma (IFN-γ), monocyte chemoattractant protein (MCP)-1, macrophage inflammatory protein (MIP)-1α, MIP-1β, and tumor necrosis factor (TNF)-α showed differential expression. Comparison of cytokine profiles indicated that cytokine production was variable before and after root canal treatment. In vitro, CXCL10 significantly improved BMMC migration in a dose-dependent manner, supporting clinical findings that elevated CXCL10 levels are associated with favorable healing in apical lesions. Although this study was limited by the small sample size and exploratory design, the cytokine profile of periapical lesions may be useful for assessing the condition of periapical lesions and modulating the immune response to bacterial infection. Full article