Purpose To address the lack of Chinese benchmark resources for detecting AI-generated (AIGC) multimodal fake reviews, we construct and validate a large-scale text–image dataset and benchmark to support platform governance and consumer protection. Design/methodology/approach Authentic restaurant reviews were curated and paired with synthetic deceptive counterparts generated by a large language–vision model, yielding a balanced Chinese multimodal dataset of over 20,000 text–image samples. Mainstream unimodal (text-only, image-only) and multimodal pre-trained models were evaluated under a unified protocol. We further conducted generalization tests via information-perturbation stress tests and cross-lingual transfer scenarios, and compared fusion strategies (early, intermediate, deep). Findings Multimodal models employing deep fusion consistently outperform unimodal and shallow-fusion baselines in accuracy and robustness. They retain superior performance under feature perturbations and demonstrate stronger transferability across languages, confirming the benefit of jointly leveraging complementary textual and visual cues for fake-review detection. Originality/value This work presents, to our knowledge, the first Chinese multimodal AIGC fake review dataset accompanied by a comprehensive benchmark. It provides an open, reproducible resource and empirical evidence that deep multimodal fusion substantially improves detection effectiveness and robustness, offering practical guidance for future research and real-world deployment.

Constraint-induced movement therapy (CIMT) is an intervention for hemiplegic cerebral palsy (CP) that has a strong evidence base. CIMT has been shown to be effective in improving functional use of the more impaired upper extremity, yet has not become standard practice. Toolkits have been effectively used in various settings to increase intervention implementation; however, no guide currently exists to support clinical decision-making related to CIMT. To provide an overview of the development of a practical guide for pediatric CIMT (pCIMT) that will aid therapists, other health care professionals, and families with children who may be eligible for pCIMT. Model development research. Virtual communication secured in accordance with the Health Insurance Portability and Accountability Act of 1996 (Pub. L. 104-191). Content experts (N = 12) with expertise related to pCIMT, hemiplegic CP, and occupational therapy who were recruited via purposive sampling to develop the practical guide. Development of the practical guide followed a toolkit developmental model. Field notes were used to record all verbal and written feedback provided by content experts. The participants provided recommendations to include in the guide during the developmental phase. In two rounds of the expert review phase, they recommended revisions related to readability, content, and visuals. The final practical guide included six sections. A practical guide was developed to support occupational therapists, health care professionals, and caregivers in making an informed decision about whether pCIMT is the right intervention for a particular child. Plain-Language Summary: Hemiplegic cerebral palsy is the most common motor disability that affects children, and it often causes difficulty moving one side of the body. Pediatric constraint-induced movement therapy (pCIMT) is an evidence-based intervention to help children use their more affected side. However, pCIMT is not widely available. With guidance from key informants, we designed a practical guide to support health care professionals and families in determining whether pCIMT could be an appropriate intervention. A three-phase toolkit development model was followed to design the practical guide. In this article, we report on Stages 1 and 2 (the development and expert review phases). Twelve experts and caregivers informed the development of the six sections of the practical guide. Future research should proceed to Stage 3 (the evaluation phase) to evaluate the effectiveness of the practical guide and identify implementation strategies for the guide to support pCIMT usage.

Modifiable risk factors significantly influence both perioperative safety and long-term success in total joint arthroplasty. A structured, patient-focused model should be used for optimizing high-impact factors, including obesity, malnutrition, anemia, and poorly controlled diabetes. Practical guidance on anesthesia selection and surgical technique adjustments is important to accommodate body habitus and reduce surgical complexity. Targeted medication dosing strategies are needed to avoid undertreatment or toxic exposures in patients with altered pharmacokinetics. It is also important to underscore the value of robust behavioral interventions, such as smoking cessation and alcohol reduction, to lower wound complication rates and enhance overall recovery. Central sensitization of pain with an emphasis on using specific therapeutic approaches, including neuromodulators, will improve postoperative comfort and patient satisfaction. In addition, there are recommendations for mitigating infection risk, ranging from careful glycemic control to selective methicillin-resistant Staphylococcus aureus decolonization protocols. By addressing these modifiable elements, surgeons and their care teams can substantially decrease complication rates, optimize implant longevity, and promote enhanced functional outcomes.

Chest computed tomography of trastuzumab-deruxtecan (T-DXd)-related interstitial lung disease: Key points for radiologists.

The effect of place-based nature interventions on human health: A systematic review.

Effectiveness and safety of phloroglucinol combined with oxytocin intravenous drip in delivery women: a systematic review and meta-analysis.

Clinical practice guidelines for the administration of third-generation anti-seizure medications.

Sewer misconnection: Recommendations for increasing sewer connections in low-income urban communities in Dhaka, Bangladesh.

Interactive experience design evaluation of community emotional healing installations based on analytic hierarchy process method.

Challenges and facilitators of electronic health record implementation: a scoping review.

From Promise to Practice: The Practical Buyer's Guide to AI-Enabled Chronic Care Management.

Jurisdictional scans: methodological considerations for systematically analyzing and comparing policy approaches across different jurisdictions.

Integrated assessment of arsenic and pathogen contamination in surface waters impacted by mining activities and sewage discharge: challenges and strategies for water quality management and treatment.

Exhaled CO2 and aerosol dispersion on a cruise ship: Airflow and infection risk insights.

Integrating the affinity and anion-exchange purification of AAV8: how the selective enrichment of full capsids at the affinity capture step enhances the downstream processing of gene therapies.

In the age of digital transformation, intelligent information and communication technologies (ICT) has become essential to tourism; yet, its function in geopark-based educational tourism has not been well examined. This research examines the Ciletuh–Palabuhanratu UNESCO global geopark to analyze how tourists use smart ICT for education on geoheritage and sustainability. A contextual and adaptable conceptual model is provided, enhancing the unified theory of acceptance and use of technology version 2 (UTAUT2) framework by integrating two new constructs, perceived learning value (PLV) and geo-heritage engagement (GHE), as well as two moderating variables, educational level and digital experience. A thorough literature assessment and bibliometric analysis revealed research gaps concerning the incorporation of educational components in technology uptake within geoparks. The results demonstrate that dimensions including performance anticipation, hedonic motivation, and habit are primary determinants of behavioral intention, whereas PLV and GHE substantially improve user engagement and learning outcomes. Furthermore, educational background and digital experience attenuate the impact of fundamental structures on technology adoption. The suggested approach enhances theoretical comprehension by situating UTAUT2 within educational tourism and offers practical guidance for developing inclusive, engaging, and sustainable ICT applications. These findings provide essential direction for geopark administrators and policymakers in advancing digital learning initiatives that foster cultural appreciation, environmental consciousness, and community engagement.

Purpose This study aims to explore how AI adoption and trust shape customer satisfaction in digital banking, emphasizing the mediating roles of behavioral intention and AI adoption. It seeks to understand how service quality and technology perceptions influence customer experiences in a digital environment. Design/methodology/approach A quantitative approach was adopted using data from 385 digital banking users. The measurement and structural models were analyzed using partial least squares structural equation modeling (PLS-SEM) in SmartPLS 4, with 5,000 bootstrap resamples to test significance. Findings Findings reveal that perceived usefulness, behavioral intention and AI adoption strongly enhance customer satisfaction. Behavioral intention mediates ease of use, usefulness and trust, while AI adoption links reliability, responsiveness and usefulness, emphasizing that trust and AI engagement together elevate digital satisfaction. Originality/value By integrating SERVQUAL and technology acceptance model, this study advances understanding of AI-driven service experiences, offering practical guidance for customer-centric digital banking strategies.

Regulation of nitrite accumulation in sulfur-corncob biofilters: Effects of sulfur-to-corncob ratios and free ammonia (FA) concentrations.

Stochastic dynamic programming model for liner international scheduling optimization under ECA policies.

To enhance the scientific rigor and user alignment of children’s furniture design, this study proposes a data-driven multi-criteria evaluation framework for design optimization. Focusing on wooden seating products for children, online product reviews were collected and preprocessed using Python and the Jieba word segmentation tool to extract authentic user needs. An evaluation index system was established by filtering indicators through expert focus group discussions and the coefficient of variation method. During the weighting phase, subjective weights were derived using an improved Analytic Hierarchy Process (AHP), while objective weights were calculated via the CRITIC method. A game-theoretic approach was employed to integrate both into a composite weight vector. Finally, the TOPSIS–RSR model was applied to rank and classify the performance levels of four wooden children’s seating designs. Based on the results, specific design guidance strategies were proposed. The proposed framework effectively captures user requirements, balances subjective and objective information, and provides a clear decision-making pathway for selecting optimal design solutions. The study not only advances theoretical research but also offers practical guidance for design, with strong potential for extension to other furniture categories and resource-driven product design domains.