Search Results (295,188)

Background: Ganoderma lucidum triterpenes are bioactive compounds with recognized anti-inflammatory, antitumor, and immunomodulatory properties. This systematic review synthesizes evidence regarding the anti-inflammatory activity of these triterpenes based on studies from the last two decades. Methods: A systematic search was performed in PubMed, Medline, and Embase (2003–2025) for original in vitro and in vivo (non-clinical) studies evaluating G. lucidum triterpene extracts or isolated compounds. Clinical trials, reviews, and multi-species extracts were excluded. The review is registered on PROSPERO (CRD42024510982), and animal study quality was assessed using the SYRCLE Risk of Bias tool. Findings: From over 3000 records, 23 articles were included. Studies utilized diverse models, including macrophages, human PBMCs, and various animal strains (mice, rats, chickens). All studies reported significant anti-inflammatory effects via reduction in pro-inflammatory markers (TNF-α, IL-1β, IL-6), primarily through downregulation of MAPK and TLR-4/NF-κB signaling pathways. Meta-analysis of in vitro data confirmed significant reductions in NO levels (−3.29 [95% CI: −5.21, −1.37]; p = 0.0008), IL-6 (−3.51 [−4.73, −2.29]; p < 0.00001), and TNF-α (−2.20 [−2.93, −1.48]; p < 0.00001). Similar anti-inflammatory profiles were observed in vivo across hepatic and splenic tissues. Interpretation: Evidence consistently demonstrates the potent anti-inflammatory activity of G. lucidum triterpenes, highlighting their potential as therapeutic candidates for inflammatory diseases. However, the structural complexity and isomer diversity of these compounds remain significant barriers to pharmacological standardization. Future research must prioritize clinical translation by investigating compound synergism, bioavailability, and long-term toxicity profiles, which were notably absent in current non-clinical literature. Full article

A sustainable future is possible by educating children about the climate crisis and environmental issues. In this context, this study aims to examine the views of primary school teachers on integrating climate crisis awareness and nature-based learning into curricula. The sample of the study consisted of 15 primary school teachers working in the province of Adıyaman in the Southeastern Anatolia Region of Türkiye. Data were collected using a personal information form and a semi-structured interview form. The data were analyzed using the content analysis method. The results of the study revealed the perspectives of teachers on climate crisis awareness and the integration of nature-based learning into curricula. It is concluded that curricula are found inadequate in both quantitative and qualitative terms, while the integration of climate crisis awareness and nature-based teaching into curricula is viewed positively. Teachers criticize the lack of materials, low public awareness, and insufficient physical infrastructure in schools. In the educational process, whether conducted face-to-face or through digital tools, the aim is to present children with hopeful scenarios rather than fear and anxiety. It is observed that local, cultural, and ecological contexts guide the teaching process, and teachers require in-service training. Full article

Earthwork operations constitute a substantial share of infrastructure project costs and are critical to overall project efficiency. However, the construction industry still relies on conventional approaches and there is a lack of integrated fleet management systems for collaboratively working equipment. While telematics is widely used in other industries, its applications to monitor the complex interactions between excavators, dump trucks, and dozers in real time remain limited. This study proposes an intelligent fleet monitoring system that utilizes only satellite navigation data (GNSS) to analyze the real-time productivity of multiple earthwork machines without relying on additional sensors, such as IMU or accelerometers, thereby eliminating the need for separate measurement procedures. A lightweight site configuration step is required to define the work area/loading/dumping geofences on an existing site map. This research provides novel developed algorithms that facilitate a real-time productivity assessment for several earthwork equipment and provide planning-level recommendations for equipment deployment combinations. Dedicated motion classification algorithms were developed for excavators, dump trucks, and dozers to distinguish activity states, to compute working and idle times, and to quantify operational efficiency. The system integrates a web-based e-Fleet Management platform and a mobile e-Map application for visualization and equipment optimization. Field validation was conducted on two active earthwork projects to evaluate accuracy and feasibility. The results demonstrate that the developed algorithms achieved classification and productivity estimation errors within 2.5%, while enabling optimized equipment combinations and improved cycle time efficiency. The proposed system offers a practical, sensor-independent approach for enhancing productivity monitoring, real-time decision-making, and cost efficiency in large-scale earthwork operations. Full article

In the digital tourism marketplace, online reviews have become a decisive source of information for travelers who cannot directly assess the quality of hospitality services before purchase. However, it remains unclear how service-related and sustainability-related cues interact to shape guest perceptions in sustainable hotel contexts. This study investigates how intrinsic and extrinsic cues are reflected in online user reviews of sustainable hotels. Drawing on Cue Utilization Theory, a longitudinal content analysis was conducted on a worldwide online travel platform’s (OTP) reviews of hotels certified for their sustainability practices (2004–2024) by user selection. A coding framework was developed deductively based on prior studies on hotel service quality and sustainability practices, and data were analyzed using MAXQDA, Leximancer, and VADER sentiment analysis. Findings indicated that reviews primarily emphasize service quality attributes—particularly staff efficiency, food quality, and accommodation facilities—while sustainability themes appear less frequently, often in nature-related contexts. Sentiment analysis revealed a predominantly positive emotional tone shaped by service quality experiences. Overall, intrinsic cues play a central role in forming guest perceptions, highlighting the need for emotionally engaging sustainability communication strategies. Full article

In this study, the optical gain characteristics of a green laser sample based on a III-Nitride InGaN single-quantum-well structure were investigated. The Green gap phenomenon, caused by bandgap fluctuations due to inhomogeneous indium composition and the quantum-confined Stark effect (QCSE), has been a major obstacle in achieving high efficiency and high output in green-light-emitting devices. To address these issues, a sample grown on a (0001)-oriented GaN substrate with a single-quantum-well active layer was fabricated to suppress In composition non-uniformity and enhance the overlap of electron and hole wavefunctions. The optical gain behavior was analyzed using the Variable Stripe Length Method (VSLM) under various excitation densities and stripe lengths (L_cav). The results showed that as the stripe length increased, the spectral linewidth decreased and stimulated emission occurred at lower excitation densities. However, excessive cavity length led to gain saturation and a red shift in the peak wavelength due to Joule heating effects. These findings provide essential insights for determining the optimal cavity length in laser diode fabrication and are expected to serve as fundamental guidelines for improving the efficiency and output power of III-Nitride-based green laser diodes. Full article

The need for active biodegradable packaging materials with the ability to improve the microbiological stability of highly perishable foods was investigated in the present study. Specifically, wheat gluten-based films infused with spearmint (Mentha spicata L.) and clove (Syzygium aromaticum L.) essential oils (EOs)were studied by linking the physicochemical and mechanical properties of the film to the microbiological quality and shelf-life behavior of minced chicken under aerobic refrigerated storage. The packaged samples tested were packaging without film (Control), a wheat gluten film (WGF), WGF with 2% spearmint EO (WGF + 2% SPR), and 2% clove EO (WGF + 2% CL) stored at 4 ± 1 °C for 8 days, under aerobic conditions. Shelf-life extension was evaluated based on established microbiological spoilage criteria, indicating delayed microbial growth in samples packaged with EO-enhanced films compared with the Control. Microbiological analyses (TVC, yeast, Pseudomonas spp., B. Thermosphacta, Enterobacteriaceae, LAB) showed that WGF + 2% CL delayed the time required to reach the spoilage threshold for TVC (7 log CFU/g) by 2 days compared with the Control, while WGF and WGF + 2% SPR extended shelf life by 1 day. Physicochemical properties (pH and objective color) also showed better pH stability and limited color changes in the packaged samples. Mechanical properties resulted in improved film antioxidant activity and flexibility and reduced tensile strength for the EO-enhanced films. Overall, WGFs enhanced with EOs seem to improve minced chicken meat quality during refrigerated storage through the combined effect of antimicrobial activity and modified film properties, highlighting their potential as active packaging materials under the specific conditions studied. Full article

Diffusion-weighted imaging (DWI) has been increasingly utilized in the emergent evaluation of acute ischemic stroke (AIS) patients. DWI enhances sensitivity and specificity and enables the use of delayed reperfusion treatments in selected cases. However, DWI is not devoid of limitations. DWI-negative AIS is not uncommon in clinical practice and is reported in up to 1 of 4 AIS patients. We reviewed the relevant literature and searched the PubMed and Google Scholar databases for studies reporting on DWI-negative AIS prevalence during the 2021–2025 time period. Additionally, we included cases from our practice to highlight key points. DWI-negative AIS prevalence was 16% in one meta-analysis and ranged from 6.9% to 23.2% in identified studies that met our inclusion criteria. The biological, pathophysiological, technical, epidemiological and clinical factors that contribute to DWI-negative stroke are presented in detail. Overall, the application of diffusion imaging modalities for stroke is not bereft of blind spots despite enhanced sensitivity. Over-reliance on advanced neuroimaging and unfamiliarity with its limitations predispose DWI to errors in AIS assessment. Awareness of the predisposing factors, treatment effect, and prognosis guides appropriate decision-making, promoting good outcomes. Prospective appropriately designed trials should address the lingering questions identified, such as the association between time of imaging and DWI negativity. Full article

This study develops a comprehensive workflow integrating Headspace Solid-Phase Microextraction Gas Chromatography–Mass Spectrometry (HS-SPME-GC-MS) with advanced supervised machine learning to authenticate the botanical origin of honeys from five distinct floral sources—coriander, orange blossom, astragalus, rosemary, and chehelgiah. While HS-SPME-GC-MS combined with traditional chemometrics (e.g., PCA, LDA, OPLS-DA) is well-established for honey discrimination, the application and direct comparison of Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Neural Network (NN) models represent a significant advancement in multiclass prediction accuracy and model robustness. A total of 57 honey samples were analyzed to generate detailed volatile organic compound (VOC) profiles. Key chemotaxonomic markers were identified: anethole in coriander and chehelgiah, thymoquinone in astragalus, p-menth-8-en-1-ol in orange blossom, and dill ester (3,6-dimethyl-2,3,3a,4,5,7a-hexahydrobenzofuran) in rosemary. Principal component analysis (PCA) revealed clear separation across botanical classes (PC1: 49.8%; PC2: 22.6%). Three classification models—RF, XGBoost, and NN—were trained on standardized, stratified data. The NN model achieved the highest accuracy (90.32%), followed by XGBoost (86.69%) and RF (83.47%), with superior per-class F1-scores and near-perfect specificity (>0.95). Confusion matrices confirmed minimal misclassification, particularly in the NN model. This work establishes HS-SPME-GC-MS coupled with deep learning as a rapid, sensitive, and reliable tool for multiclass honey botanical authentication, offering strong potential for real-time quality control, fraud detection, and premium market certification. Full article

Visceral leishmaniasis (VL) is a serious vector-borne disease affecting humans and dogs, posing major public health challenges in endemic regions. Control efforts often target sandfly vectors, whose larvae and pupae develop in soil. Environmental management, such as removing organic matter, reducing moisture, and pruning vegetation, aims to limit breeding sites and reduce sandfly populations. This study evaluated the impact of integrated interventions on sandfly behavior in priority areas for VL control in Araçatuba, São Paulo, Brazil. The control strategy combined environmental management, canine surveys, and educational actions across seven local work areas (LWAs). Between 2019 and 2021, CDC-type light traps were installed in intra- and peridomiciliary settings at twelve properties in LWA 5. Spatial risk analysis for canine transmission was conducted in LWAs 3 and 5 using a Generalized Additive Model, with results presented as spatial odds ratios. Vector prevalence was analyzed using negative binomial regression compared to historical municipal data. Intervention coverage averaged 52.91% of visited properties (n = 15,905), ranging from 48% to 76.8% across LWAs. Adherence to environmental management exceeded 85%. Of the 150 sandflies collected, 98.67% were Lutzomyia longipalpis and 1.33% Nyssomyia neivai. A 6% reduction in vector density was observed compared with historical data, although this difference was not statistically significant. Spatial risk varied among LWAs, indicating heterogeneous transmission levels. These findings suggest that integrated environmental and educational interventions may contribute to reducing vector density and that identifying priority areas tends to support surveillance and the effectiveness of disease control actions. Full article

This study investigated how illuminance and spectrum in office lighting affect psychological fatigue, preference, visual comfort, and cognitive performance. Forty adults participated in a repeated-measures experiment under four conditions with two illuminance levels (500, 1000 lx) and two LED types (full-spectrum, conventional). For each condition, Karolinska Sleepiness Scale scores (fatigue), Office Lighting Survey ratings (preference, visual comfort), and Alphanumeric Verification Task performance (work speed, accuracy) were collected. Linear mixed-effects modeling was applied alongside correlation and regression analyses to examine condition effects and associations between variables. Compared to 500 lx, ΔKSS significantly decreased under 1000 lx, confirming that increased illuminance is associated with reduced psychological fatigue. At the same illuminance level, full-spectrum LEDs showed benefits, including lower fatigue and faster responses. Preference and visual comfort showed minimal direct sensitivity to lighting conditions but were moderately and positively correlated, while fatigue exhibited significant negative correlations with both preference and response speed. An interaction between illuminance and spectrum on accuracy suggested a speed–accuracy trade-off under high-illuminance full-spectrum lighting. Overall, the findings indicate that office lighting, particularly illuminance and spectral quality, acts as a human-centered factor shaping an interconnected response network linking fatigue, affective appraisal, and task performance. Full article

Construction on soft, highly compressible soils increasingly requires reliable ground improvement solutions. Among these, Rigid Inclusions (RIs) have emerged as one of the most efficient soil-reinforcement techniques. This paper synthesizes evidence from over 180 studies to provide a comprehensive state-of-the-art review of RI technology encompassing its governing mechanisms, design methodologies, and field performance. While the static behavior of RI systems has now been extensively studied and is supported by international design guidelines, the response under cyclic and seismic loading, particularly in liquefiable soils, remains less documented and subject to significant uncertainty. This review critically analyzes the degradation of key load-transfer mechanisms including soil arching, membrane tension, and interface shear transfer under repeated loading conditions. It further emphasizes the distinct role of RIs in liquefiable soils, where mitigation relies primarily on reinforcement and confinement rather than on drainage-driven mechanisms typical of granular columns. The evolution of design practice is traced from analytical formulations validated under static conditions toward advanced numerical and physical modeling frameworks suitable for dynamic loading. The lack of validated seismic design guidelines is high-lighted, and critical knowledge gaps are identified, underscoring the need for advanced numerical simulations and large-scale physical testing to support the future development of performance-based seismic design (PBSD) approaches for RI-improved ground. Full article

This research aims to investigate wind-induced effects numerically in full-scale Eastern Red Cedar tree (ERCT) forms under various wind speeds. A total of 72 model cases were carefully analyzed for variations in crown lengths (CLs), canopy diameters (CDs), bole lengths (BLs), and trunk diameters (TDs) at wind speeds ranging from 15 m/s to 30 m/s. The realizable k–ε turbulence model is employed to resolve the flow region and obtain drag force (FD), velocity, and pressure distributions within the computational fluid domain. The resulting aerodynamic loads are then transferred to ERCT models using a one-way fluid–structure interaction (one-way FSI) approach to predict deformation, stress, and strain in the solid zone. The accuracy of these findings was validated by comparing drag coefficient (C_D) results with those from previously conducted studies. Research results reveal that wind speed and the geometric dimensions of the tree notably influence the FD, deformation, strain, and stress experienced by the tree. When wind speed rises from 15 to 30 m/s, the amount of FD, deformation, strain, and stress increases on the ERCT. The present research helps improve the understanding of tree patterns impacted by wind, which is essential for urban design and planning. It provides guidance on how to choose and arrange necessary real trees for efficient windbreaks and comfortable surroundings in life. Full article

This study evaluates the effectiveness of integrating a Residual Shifting (ResShift)-based deep learning super-resolution (SR) technique with the Robust Dense Feature Matching (RoMa) algorithm for high-precision inter-satellite image registration. The key findings of this research are as follows: (1) Enhancement of Structural Details: Quadrupling image resolution via the ResShift SR model significantly improved the distinctness of edges and corners, leading to superior feature matching performance compared to original resolution data. (2) Superiority of Dense Matching: The RoMa model consistently delivered overwhelming results, maintaining a minimum of 2300 correct matches (NCM) across all datasets, which substantially outperformed existing sparse matching models such as SuperPoint + LightGlue (SPLG) (minimum 177 NCM) and SuperPoint + SuperGlue (SPSG). (3) Seasonal Robustness: The proposed framework demonstrated exceptional stability, maintaining registration errors below 0.5 pixels even in challenging summer–winter image pairs affected by cloud cover and spectral variations. (4) Geospatial Reliability: Integration of SR-derived homography with RoMa achieved a significant reduction in geographic distance errors, confirming the robustness of the dense matching paradigm for multi-sensor and multi-temporal satellite data fusion. These findings validate that the synergy between diffusion-based SR and dense feature matching provides a robust technological foundation for autonomous, high-precision satellite image registration. Full article

Maritime transport is responsible for 3% of global greenhouse gas (GHG) emissions, making it a focus of decarbonization efforts. Ro-pax ferries, operating in the domestic shipping, are particularly emission-intensive due to their high operational frequency, while advances in battery-powered propulsion suggest that electrification is feasible on short to medium distance routes. This paper uses a systematic literature review of studies published between 2014 and 2024 to investigate the application of battery-powered ferries from a maritime transport system perspective. Using the PRISMA 2020 guidelines, the authors identified 15 case-study-based papers on battery-powered ferries, with a specific focus on the methodological approaches applied to domestic shipping routes. The goal of this review is to identify and systematize the methodologies used in case study research to analyze the implementation of battery-powered ferries on specific routes. The review contributes a structured synthesis of (I) methodological approaches, grouped into four clusters, and (II) route framing and selection practices using a three-level route classification, revealing an increasing methodological complexity, from single-route feasibility assessments to diversified, maritime network-integrated approaches. The paper systematically links existing methodologies to operational and conceptual case studies, providing practical insights for future decarbonization projects. Full article

(1) Background: Information and Communication Technology (ICT) integration in secondary education remains a critical challenge despite substantial investments in teacher training and infrastructure. This study investigated ICT certification levels, implementation patterns, and barriers among Greek secondary school teachers to understand the disconnect between policy aspirations and classroom realities. (2) Methods: A quantitative cross-sectional survey design was employed with 108 secondary teachers (61.1% female; mean age 47.3 years; 70.4% with >10 years’ experience) in the Prefecture of Ilia, Greece (response rate: 87.7%). Participants were permanent secondary school teachers employed in public schools during the 2021–2022 academic year; substitute teachers and private school staff were excluded. A three-section structured questionnaire was developed through literature review, expert validation (n = 3), and pilot testing (n = 10). Section A assessed demographics (5 items), Section B measured perceived barriers using a 7-item Likert scale, and Section C assessed implementation practices using a 10-item frequency scale (Cronbach’s α = 0.942). Data were analyzed using descriptive statistics, Mann–Whitney U tests, Kruskal–Wallis tests, and correlation analyses. (3) Results: While 74.1% of teachers held Level A certification, only 25.9% achieved Level B, with overall implementation remaining moderate (M = 2.92/5.00). Leadership support deficiency emerged as the primary barrier (76.9%), followed by inadequate technical support (74.1%). Younger teachers (24–35 years) demonstrated significantly higher ICT implementation than their older colleagues (56+ years), and teachers with less experience showed greater implementation frequency than veteran teachers—a finding that paradoxically challenges the “digital natives” assumption, given the barriers they face. Teachers preferred flexible Internet resources to formal educational software, indicating strategic adaptation to institutional constraints. Key limitations include convenience sampling, cross-sectional design, self-reported measures, and regional specificity. (4) Conclusions: The certification–implementation gap reveals that individual competencies cannot overcome unsupportive institutional environments. Effective ICT integration requires systemic transformation, encompassing leadership development, technical support, and structural reforms beyond traditional teacher training approaches. Full article