Search Results (1,044)

Background/Objectives: Wheelchair users with multiple sclerosis (MS) often face barriers that restrict participation in physical activity and exercise training. This manuscript reports on participant feedback to guide evaluating and refining a novel exercise training program, Seated Physical activity INtervention (SPIN). SPIN was adapted from the Guidelines for Exercise in MS (GEMS) approach using a three-step community-engaged research framework based on meeting the needs of wheelchair users with MS. Methods: Semi-structured interviews were conducted with 9 participants who completed the 16-week SPIN intervention. The key SPIN intervention components were the exercise prescription, exercise equipment, and behavioral coaching grounded in Social Cognitive Theory. Formative interview domains included overall experience, enjoyable and missing components, delivery modifications, barriers, lessons learned, and additional research topics of interest. Data were analyzed and reported using a rapid qualitative analysis approach. Results: Interviews averaged 16 ± 10 min. Participants reported enjoying SPIN, noting program strengths as being flexible and appropriate for individuals with MS, receiving coaching calls by knowledgeable staff that offered support and accountability, and receiving exercise equipment and video demonstrations. Participants also identified strategies for enhancing the program such as including peer support, offering real-time feedback during exercise, and adding other wellness behavior topics (e.g., diet). Conclusions: The results offer helpful ideas to consider when developing exercise training programs for wheelchair users with MS and other disabilities that may improve health and well-being. Full article

Background/Objectives: Peri-implant diseases, encompassing peri-implant mucositis and peri-implantitis, affect 43% and 18.8–23% of implant-bearing patients, respectively, representing significant clinical challenges in implant dentistry. While mechanical debridement remains foundational, biologically active materials offer promising adjunctive regenerative strategies. This narrative review synthesises current evidence regarding five biologically active materials: enamel matrix derivative (EMD), platelet-rich fibrin (PRF), fibroblast growth factor-2 (FGF-2), recombinant human platelet-derived growth factor-BB (rhPDGF-BB/GEM 21S^®), and polynucleotide–hyaluronic acid combinations (Regenfast^®). Methods: The relevant literature was identified using electronic databases, including MEDLINE, PubMed, Scopus, and Google Scholar. This review focused on clinical studies and randomised controlled trials with a minimum follow-up of six months investigating biologically active materials in peri-implant disease management. Material mechanisms, clinical efficacy, therapeutic limitations, and evidence quality were systematically evaluated. Attention was directed toward identifying genuine biological distinctions between peri-implant and periodontal disease contexts. Results: EMD demonstrates efficacy exclusively within multimodal surgical protocols, with isolated application yielding limited benefits. rhPDGF-BB shows superior periodontal regenerative capacity; however, dedicated peri-implantitis trials remain absent. FGF-2 exhibits paradoxical osteogenic suppression despite bone fill achievement, limiting peri-implant applicability. PRF and Regenfast^® demonstrate a mechanistically sound rationale yet lack substantive peri-implant disease validation. The critical findings revealed that peri-implant regeneration fundamentally differs from periodontal regeneration: implants lack periodontal ligament anatomy, rendering ligamentogenic differentiation-promoting agents biologically inappropriate. Conclusions: Contemporary biologically active materials demonstrate compelling periodontal efficacy yet remain inadequately validated for peri-implantitis management. This disparity reflects authentic biological distinctions rather than insufficient investigation. Until multicentre randomised controlled trials stratify efficacy across distinct peri-implant disease presentations, practitioners must prioritise evidence-based surgical fundamentals—meticulous decontamination, strategic grafting, and optimised wound healing—integrating biologically active materials judiciously within comprehensive, anatomy-respecting treatment protocols. Full article

Data-driven models can be used to understand basin-wide hydrological processes and generate predictions for future conditions, particularly in cases of scarce data availability related to basin characteristics. Although they have long been applied in hydrological modeling, there is still limited information regarding their ability to produce reliable long-term projections under climate change conditions. This study evaluates the long-term predictive performance of data-driven models by employing a hybrid deep learning architecture combining Wavelet Transform (WT) and Deep Neural Network (DNN). The dataset used in this study was obtained from the Yamula Reservoir Basin, a semi-arid agricultural basin in Türkiye. Monthly streamflow was simulated based on climate projection data from the HadGEM2-ES model under the RCP4.5 and RCP8.5 scenarios. Results showed that the WT–DNN framework was successful in learning the system dynamics and reproducing observed streamflow behavior. The model produced continuous projections for the future period; however, these projections should be interpreted with caution due to the increasing uncertainty associated with long-term climate forcing and the sensitivity of data-driven approaches to shifts in climatic and hydrological regimes. Full article

Gas Electron Multiplier (GEM) detectors have become an indispensable component of modern tracking systems. The heart of a GEM detector is a thin polyimide foil (∼50 µm) clad with copper (∼5 µm) on both sides and containing an array of regularly spaced holes (typically diameter of ∼70 µm and pitch of ∼140 µm) fabricated using photolithographic techniques. The presence of the dielectric substrate (polyimide) within the amplification region introduces a time dependent response when the detector is exposed to external irradiation, a phenomenon commonly referred to as the charging-up effect. This effect arises from the accumulation of charge on the insulating polyimide surfaces, leading to a gradual modification of the local electric field configuration inside the GEM holes and, consequently, a variation in the detector gain over time. The charging-up behaviour has been systematically investigated for triple GEM chamber prototypes using an Fe-55 radioactive source (5.9 keV X-rays) with an activity of ∼20 mCi. The characteristic charging-up time constant has been extracted, and its dependence on detector gain and irradiation rate has been examined. In addition, the uniformity of detector performance in terms of count rate, gain, and energy resolution has been studied both before and after the charging-up process. In this review article, the experimental setup, data acquisition methodology, and analysis procedures developed and carried out by our group are summarised. The key findings reported by other groups, relevant Monte Carlo simulation efforts, and future outlook for the charging-up investigation on GEM based detectors are also discussed in this article. The investigations and their outcomes reviewed here provide valuable insight into the charging-up dynamics of GEM detectors and their dependence on operational parameters. Full article

The aim of this study is to analyse the factors associated with sustainable entrepreneurship in Spain from a systemic perspective, highlighting the interaction between economic, cognitive, occupational and axiological factors that shape innovation and sustainability in digital environments. Using microdata from the Global Entrepreneurship Monitor Spain 2021, a Probit model is estimated to identify which variables are associated with TEA environmental consideration (TEA-EC), defined as the probability that early-stage entrepreneurs report considering environmental implications when making decisions about the future of their business. The results show that age, certain occupations (particularly part-time work, unemployment and self-employment), self-perceived entrepreneurial skills and values associated with social impact are the main factors associated with environmentally oriented entrepreneurship. Conversely, education, income, innovation, internationalisation and technological intensity are not significant, while gender is statistically associated with TEA environmental consideration (TEA-EC) in a context-dependent manner, particularly through its interactions with sectoral affiliation and social-impact orientation. Significant sectoral differences are also observed. The variables most strongly associated with TEA-EC are concern with social impact and the prioritisation of socio-environmental outcomes over profitability, each of which is associated with a higher likelihood of environmentally oriented decision-making among early-stage entrepreneurs by more than 23 percentage points. The study concludes that sustainable entrepreneurship in Spain is primarily associated with internal capabilities and pro-environmental values, rather than with structural incentives, offering key implications for the design of policies aimed at sustainable entrepreneurial systems. Full article

Fish observation is a key component of marine ecological monitoring and is valuable for understanding ecological processes and fish population dynamics. In practical applications, observation equipment is often constrained by limited memory and computational resources, making it difficult to deploy visual detection models with large parameter counts and high computational complexity. Under limited computational resources, existing deep-learning-based fish detection models struggle to balance detection accuracy, model lightweighting, and real-time edge deployment. To address this issue, a lightweight GEM-YOLOv8n model based on YOLOv8n is proposed for fish detection. For high model complexity, insufficient feature representation, and limited bounding box regression accuracy in complex underwater observation scenarios, the model replaces C2f modules and some Conv modules with GhostC2f and GhostConv, introduces the EMA attention mechanism, and adopts MPDIoU loss instead of CIoU. Experimental results show that, compared with YOLOv8n, GEM-YOLOv8n improves Precision, Recall, mAP50, and mAP50–95 by 0.53%, 2.16%, 0.52%, and 0.34% while reducing parameters and FLOPs by 48.0% and 39.5%. These results demonstrate that the proposed model improves detection performance while reducing model complexity. Tests on Jetson Xavier NX demonstrate real-time performance and deployment feasibility, providing a lightweight deployment solution for resource-constrained underwater fish detection. Full article

The integration of Generative Artificial Intelligence (GenAI) in higher education has opened new possibilities for optimizing administrative and academic services, particularly in contexts characterized by high-demand communication processes. Within the framework of service science, this study addresses the challenge of efficiently managing high volumes of email inquiries in a university master’s program, aiming to improve service quality and operational efficiency. The study examines the implementation of GenAI-based assistants, specifically NotebookLM and custom Gem AI assistants, trained in regulatory, curricular, and historical data from the University Master’s in Teacher Training at Rey Juan Carlos University. A mixed analytical approach is adopted, combining elements of data science to quantify efficiency gains and service science to analyze organizational and service-related transformations. The implementation of GenAI assistants contributes to improved response times, enhanced accuracy of information provided, and a reduction in administrative workload. The results suggest that GenAI can support the scalability and quality of academic administrative services when integrated within a structured service framework. However, its effective adoption requires careful consideration of ethical, organizational, and governance dimensions to ensure sustainable and responsible implementation. Full article

Municipal solid waste (MSW) landfills are major sources of greenhouse gas (GHG) emissions, particularly methane (CH₄), which possesses a significantly higher global warming potential than carbon dioxide (CO₂). This study evaluates methane emission and energy recovery potential from the Okhla landfill site, South Delhi, India, using the Landfill Gas Emissions Model (LandGEM). Site-specific model parameters suitable for Indian landfill conditions (k = 0.032 year⁻¹ and L₀ = 70 m³ Mg⁻¹) were incorporated to improve prediction accuracy. The results showed that methane generation initiated in 1997 and is expected to continue until 2068. Peak methane emission of approximately 17.15 million m³ year⁻¹ was observed in 2020 due to rapid degradation of the biodegradable organic fraction, especially food waste. The corresponding peak total landfill gas (LFG) and CO₂ emissions were approximately 35.43 million m³ year⁻¹ and 17.71 million m³ year⁻¹, respectively. A strong correlation (R² = 0.9557) between cumulative waste deposition and methane generation confirmed model reliability. The estimated maximum energy recovery potential was approximately 46.19 million kWh year⁻¹. The study further discusses the applicability of the LandGEM under non-engineered landfill conditions commonly observed in developing countries. Overall, the findings emphasize the importance of methane recovery for greenhouse gas mitigation, sustainable waste management, and renewable energy generation in urban landfill systems. Full article

The Iranian Ground Jay (Podoces pleskei) is the endemic bird species inhabiting the deserts and steppes of Iran, a region experiencing severe ecological disturbances like habitat loss and fragmentation of preferred habitat. Despite its remarkable adaptation to arid environments, Iranian Ground Jay exhibits strong habitat specialization, making it both ecologically resilient and vulnerable—an intriguing case for evaluating how the species responds to climate-driven habitat shifts. The present study aims to assess the current and future distribution of Iranian Ground Jay under climatic change using MaxEnt incorporating presence records and bioclimatic variables. We modeled the species’ potential distribution under two climate models (HadGEM3-GC31-LL and MIROC6) for 2070. Then, using the predicted habitats, we estimated the coverage of protected areas in Iran. Among climatic variables, we predicted that the annual precipitation (bio12), precipitation of driest quarter (bio17), and temperature seasonality (bio4) significantly influenced the distribution of Iranian Ground Jays. The highly suitable distributions of the species are concentrated in Eastern, Southeastern, and Central Iran. Our results indicated that a vast range of potential distribution is located outside protected areas, emphasizing the importance of conservation efforts. Our investigation shed lighted the consequences of global warming, where the highly suitable habitat is expected to shift under predicted climatic changes, resulting in a reduction in suitable habitat extent projected for the future. Based on these insights, it becomes imperative to reassess current conservation policy and devise an action plan specifically tailored for the Iranian Ground Jay, particularly emphasizing the protection of its core habitats within anthropogenically altered landscapes and non-protected regions. Full article

This study describes five case of prostatic artery embolization (PAE) using n-butyl cyanoacrylate methylsulfone (NBCA; Glubran 2, GEM; Viareggio, Italy) to evaluate its technical advantages, against standard particulate embolization, in managing complex pelvic vascular anatomy while preserving non-target arteries, with particular focus on penile artery protection. NBCA was mixed with iodized oil (Lipiodol Ultra Fluid; Guerbet, Aulnay-sous-Bois, France) at 1:5 dilution and injected in small aliquots (0.1–0.3 mL) under fluoroscopy using a blocked-flow technique, with injection stopped at reflux into the horizontal PA segment. After a few seconds, before the complete polymerization of the glue, the microcatheter is quickly withdrawn, flushed, and reused for the contralateral side. NBCA allowed precise embolic control through distinct mechanisms (direct distal, indirect distal, proximal, reflux and controlateral control), avoiding the need for protective coiling. Glue-based PAE seems a reproducible, safe, and efficient alternative to particulate embolization, offering enhanced embolization control and non-target artery preservation in anatomically complex patients. Full article

This study revisits the winner’s curse hypothesis in Hong Kong’s Growth Enterprise Market, examining how public retail participation is associated with IPO first-day returns from 1999 to 2023. IPOs allocated through placement-only and placement plus sale methods deliver extraordinary first-day returns of 200.9% and 231.0%, while those with public subscription dropped to 32.5% and 10.5%. Regression analysis further confirms the negative correlation between retail allocation and first-day returns. The study also underscores policy implications of the 2018 reforms mandating at least 10% public allocation, which coincide with, and may have contributed to, the sharp decline in the number of Hong Kong’s GEM IPOs. Full article

Energetic materials face dual challenges of enhancing detonation performance and replacing toxic lead-based formulations. Triazole-based energetic potassium salts typically struggle to achieve simultaneous high-density and excellent detonation properties. Herein, a novel gem-dinitro-functionalized 1,2,3-triazole energetic salt, tripotassium 4,5-bis(gem-dinitromethyl)-2H-1,2,3-triazolate (3K₃BNOT·4H₂O), was rationally designed and synthesized via a six-step mild route using diaminomaleonitrile as the starting material. The structure was fully characterized by IR, NMR, elemental analysis, and single-crystal X-ray diffraction (SC-XRD). 3K₃BNOT·4H₂O crystallizes in the triclinic system (space group P-1) and forms a three-dimensional K-O/K-N ionic coordination network, delivering an ultra-high anhydrous crystal density of 2.077 g·cm⁻³ at 193K. It exhibits a peak decomposition temperature of 183.8 °C (10 °C·min⁻¹), impact sensitivity of 5 J, and friction sensitivity of 60 N (standard BAM methods). The calculated detonation velocity and pressure reach 8836 m·s⁻¹ and 28.6 GPa, respectively, outperforming the classical explosive RDX. This work provides a structural analysis of triazole-based energetic potassium salt hydrates, and 3K₃BNOT·4H₂O shows structural potential as a high-energy energetic material; its initiating performance needs further experimental verification. Full article

Texture classification remains challenging due to high inter-class similarity, scale variability, and limited labeled data. While handcrafted descriptors capture fine-grained microstructures and CNNs encode global semantics, existing hybrid approaches often rely on direct feature concatenation or heuristic fusion strategies that ignore the varying discriminative importance of texture scales. Moreover, many deep texture representations introduce high-dimensional redundant embeddings and require computationally expensive backbone adaptation, limiting their effectiveness in small-data scenarios. This paper introduces AsTexNet, a discriminative scale-aware hybrid representation framework that reformulates multi-scale feature integration as a structured weighting problem. The proposed method quantifies the class-separability contribution of each handcrafted scale using a data-driven weighting mechanism, enabling adaptive emphasis on informative texture patterns. In parallel, pretrained CNN features are enhanced using Generalized Mean (GeM) pooling and compacted via cross-validated PCA to improve separability while controlling redundancy. A normalized late-fusion formulation integrates local and global cues into a compact 512-dimensional embedding without requiring backbone fine-tuning. Extensive experiments on six benchmark datasets demonstrate consistent performance gains, achieving 100% accuracy on Kylberg and Brodatz, 99.4% on UIUC, 99.0% on UMD, 90.6% on KTH-TIPS2b, and 78.71% on FMD. These results demonstrate that explicitly modeling scale-wise discriminative contributions leads to more effective and compact texture representations, particularly in limited-data scenarios. Full article

Greenhouse environments with restricted air exchange favor the accumulation of gaseous elemental mercury (GEM), posing potential exposure risks. However, the exact contribution of soil–air mercury fluxes to ambient greenhouse GEM, and the mechanisms by which organic manure application regulates this process, represent a critical knowledge gap. To address this, a 90-day simulated greenhouse incubation experiment (incorporating 0%, 1%, 2%, and 3% sheep manure fertilizer (SMF) amendments) and continuous 24 h micro-meteorological monitoring were conducted to evaluate GEM dynamics, soil Hg(0) fluxes, and mercury valence-state partitioning. Furthermore, macroscopic Hg(II) adsorption–desorption experiments were performed to elucidate the retention mechanisms. Our results demonstrated that while mechanical fertilization disturbances caused a transient short-term release of pre-existing Hg(0) on Day 0, both ambient GEM concentrations and soil Hg(0) emission fluxes generally declined over the long-term incubation period. Soil Hg(0) emission was identified as the predominant source process driving greenhouse GEM dynamics. Crucially, SMF addition consistently decreased operationally defined soil Hg(0) while relatively increasing the oxidized Hg(I) and Hg(II) fractions. Macroscopic batch experiments corroborated that SMF significantly enhanced Hg(II) retention and reduced its reactivation potential. Overall, under controlled experimental conditions, SMF exhibited a strong time-dependent suppressive effect on soil Hg(0) release and ambient GEM accumulation. These findings highlight the potential of organic manure in mitigating mercury risks in protected agriculture, though future molecular-level spectroscopic validations remain necessary to deduce the precise binding mechanisms. Full article

The distribution of mercury (Hg) species in soils, as affected by (i) the physicochemical and biological properties of the soils, (ii) the lithogenic vs. anthropogenic sources of soil Hg pollution, and (iii) soil–plant interactions, was investigated in a model pot experiment in which Sinapis alba (Brassicaceae) was planted. The pseudototal (aqua regia-soluble) Hg contents in soils originating from the vicinity of the former cinnabar mine varied between 16.6 and 44.7 mg/kg, whereas in soils from sites where the amalgamation technique had been used for the extraction of gold from ore-bearing materials, the pseudototal Hg values varied between 1.63 and 10.1 mg/kg. However, Hg accessibility was low, with mobilizable Hg(II) accounting for 3–11% of total soil Hg and mobilizable methylmercury (MeHg) remaining below 1%, indicating a limited bioavailable pool under the studied conditions. Mobilizable Hg(II) showed significant negative relationships with total soil carbon and cation exchange capacity (CEC), reflecting its strong association with charged functional groups of the soil sorption complex. The low Hg accessibility in the soil resulted in low Hg contents in plants, not exceeding the feed safety thresholds, with a significant proportion of Hg taken up by the plants being retained in the roots. The results of the determination of gaseous elemental mercury (GEM) indicated its relevance in soil mercury cycling, where further research on the role of plants in GEM emissions is necessary. In this context, the GEM concentrations increased in plants found in soils collected close to the former cinnabar mine. These aspects should be investigated further in future studies. Full article