Search Results (141)

The characteristics of litter combustion have a significant impact on the spread of surface fires in the central Yunnan Province, a high-risk forest fire zone. The burning behavior of individual and mixed-species litter samples from five dominant tree species (Pinus yunnanensis Franch., Keteleeria evelyniana Mast., Quercus variabilis Blume., Quercus aliena var. acutiserrata, and Alnus nepalensis D. Don.) was assessed in this study using cone calorimeter tests. Fern fronds and fine branches were included in additional tests to evaluate their effects on specific combustion parameters, such as Fire Performance Index (FPI), Flame Duration (FD), Time to Ignition (TTI), Mass Loss Rate (MLR), Residual Mass Fraction (RMF), Peak Heat Release Rate (PHRR), and Total Heat Release (THR). There were remarkable differences in the burning properties of the three types of litter (broadleaf, pine needles, and short pine needles). The THR and PHRR values of P. yunnanensis were the highest, whereas the PHRR of the other species varied very little. Short pine needle litter showed incomplete combustion and a long flame duration. When measured against pure pine needle litter, mixtures of P. yunnanensis and broadleaf litter showed lower PHRR. When set side by side to pure pine needle litter, P. yunnanensis and broadleaf litter showed lower PHRR. THR rose when fine branches were included, underlining the significance of fine woody fuels in fire behavior. The insertion of ferns increases the percentage of unburned biomass, prolongs TTI, and dramatically reduces PHRR. Full article

Background and Objectives: Transfusion-transmitted infections (TTIs) impose a considerable healthcare burden globally. Despite rigorous screening protocols, these infections can still be present among apparently healthy blood donors, potentially compromising the safety of transfusion recipients. Understanding the frequency of TTIs among blood donors is crucial for ensuring a healthy blood supply and gaining insights into the epidemiology of these infections within a community. Materials and Methods: The main objective of this study is to determine the frequency of TTIs among healthy blood donors, aged 18 to 60 years, at King Abdulaziz Hospital in Makkah City, Saudi Arabia. Data was collected retrospectively at the blood bank center from 1 January 2023, to 31 December 2023. Results: There were 8831 blood donors included. Saudi participants emerged as the dominant nationality, comprising 57% of the total sample (5036 out of 8831 donors). The prevalence of TTIs among blood donors varied according to the individual markers used. The overall TTI reactivity rates were low. Anti-HBc was the most common TTI-positive marker (7.5%), followed by syphilis (0.5%), HBV NAT (0.3%), HBsAg, and anti-HCV (0.3%). On the other hand, the lowest TTI-positive markers were HIV-1/-P2 and HTLV-1/-2 (0.04%). In Saudi participants, the most prevalent TTI marker was anti-HBc with a rate of 5.8% (293 out of 5036), followed by HBsAg (0.3%), syphilis (0.3%), and HBV NAT (0.2%). Conclusions: The present study found that HBV outperformed other TTI markers compared to the regional reports. However, in our research and the earlier reports, the rates of seropositive patients were noticeably low for HIV, HTLV, and malaria, while the rate for syphilis was higher, particularly among non-Saudi donors. NAT assays are crucial for screening blood donations for TTIs, which can help the early detection of infections and significantly reduce serological window periods. For a precise estimation of the frequency of TTIs, large prospective multicenter studies from various regions of the KSA are required. Full article

Smart city initiatives highlight the vital role of Intelligent Transportation Systems (ITS), which remain underexplored with limited AI-driven solutions integration in real-time urban traffic management across African cities. ITS is crucial to enhance urban mobility efficiency and sustainability to address growing mobility challenges in the era of swift African urbanization. This paper proposes an AI-driven predictive model for the Travel Time Index (TTI), a key metric quantifying urban traffic congestion and mobility performance. Using spatio-temporal analysis, neural networks, and advanced machine learning algorithms, the model processes real-time, multimodal traffic data, capturing congestion patterns, TTI fluctuations, and complex urban travel dynamics, focusing on Casablanca, Morocco, as a smart city case study. Five predictive modeling approaches were carefully selected and rigorously evaluated: Multivariate Linear Regression (MLR), Random Forest (RF), Gradient Boosting, Multilayer Perceptron (MLP), and Support Vector Regression (SVR). Their performance was assessed using standard evaluation metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R-squared (R²). All models achieved high accuracy, with Random Forest ranking highest (MAE = 0.315, R² = 0.985). Beyond prediction, the methodology incorporates feature importance analysis and hyperparameter tuning via GridSearchCV to improve operational performance and practical applicability across evolving traffic ecosystems. Hyperparameter optimization further enhanced Random Forest’s accuracy (MAE = 0.220, R² = 0.988). The findings demonstrate improved travel time estimation and congestion management capabilities, offering a scalable, adaptable framework to guide data-driven mobility strategies in diverse urban settings and provide actionable insights for urban planners, policymakers, and mobility stakeholders. Full article

In patients with inflammatory bowel disease (IBD), colorectal cancer (CRC) occurs with 20-to-30-fold higher frequency, is more advanced at diagnosis, and has a worse prognosis than in the general population. To improve their treatment options, we determined if targeting STAT3 with TTI-101, a small-molecule STAT3 inhibitor, was beneficial in the azoxymethane (AOM)-disodium sulfate (DSS) mouse model of colitis-associated CRC. C57BL/6 mice received a single intraperitoneal injection of AOM followed by three cycles of 5% DSS in drinking water before receiving TTI-101 (50 mg/kg by oral gavage, OG, and daily) or vehicle for 28 days. TTI-101 treatment reduced adenoma numbers by 89% from 1.14 ± 1.07 in vehicle-treated mice to 0.13 ± 0.35 in TTI-101-treated mice (p ≤ 0.05, Kruskal–Wallis test). Levels of activated STAT3 (pY-STAT3) were increased 3.3-fold in the epithelium and stroma of dysplastic mucosa (147 ± 46; mean ± SD; and n = 4) vs. normal mucosa (45 ± 26; n = 7; and p ≤ 0.05, Kruskal–Wallis test) and were correlated with the adenoma number. TTI-101 was detected at pharmacologically relevant levels in the plasma and colons of TTI-101-treated AOM-DSS mice and was concentrated within colon tissue; plasma TTI-101 levels inversely correlated to pY-STAT3 levels. Importantly, TTI-101 normalized the colon transcriptome of AOM-DSS mice and reduced the expression of STAT3- and STAT1-upregulated genes associated with CRC oncogenesis. Thus, TTI-101 treatment may benefit IBD patients with CRC. Full article

Understanding traffic congestion in urban areas is crucial for ensuring mobility, especially in metropolitan cities of developing countries. This study presents new spatial and temporal data to analyze congestion in Casablanca. Spatial data, collected using QGIS, covers 22 ZIP code areas and includes built environment factors such as land use, road types, and public transport stations. Temporal data consists of 440 randomly generated trajectories per commune, with real-time travel data collected hourly over one week using the Waze Route Calculator. A Python script was used to compute the Travel Time Index (TTI) for each zone. To classify zones based on congestion patterns, we applied fuzzy c-means clustering, allowing for nuanced grouping and interpretation of overlapping characteristics. This dataset supports traffic modeling, simulation, and congestion analysis in developing urban contexts. Full article

As a major source of high-quality protein in China, duck meat such as the renowned Beijing Duck plays a critical role in the poultry industry. Sansui duck, a prized native breed, is valued for its tender meat and rich flavor, yet molecular mechanisms underlying its meat quality remain poorly studied. This study employed metabolomics and proteomics techniques to conduct a comprehensive comparative analysis of the breast and thigh muscles from 90-day-old (90X, 90T) and 468-day-old (468X, 468T) Sansui ducks. The meat quality traits indicated that the shear force and redness (a*) were significantly higher in the 468T and 468X groups compared to the 90X and 90T groups (p < 0.05). Similarly, the shear force values of the 90T and 468T groups were significantly higher than those of the 90X and 468X groups (p < 0.05). Quantitative proteomics analysis revealed differentially expressed proteins (DEPs) significantly enriched in oxidative phosphorylation and ribosomal biogenesis pathways. Non-targeted metabolomics identified differentially expressed metabolites (DEMs) concentrated in amino acid and lipid metabolism pathways. Correlation analysis indicated that in the comparison between 90X and 468X, 18 DEPs and 10 DEMs were closely associated with fleshiness, whereas in the comparison between 468X and 468T, 23 DEPs and 19 DEMs were closely associated with fleshiness. Integrating proteomics and metabolomics data analysis, proteins such as A0A8B9TTI1, R0JRM6, and A0A8B9SQI5, along with metabolites including L-lysine, L-pyrrolidone, and γ-aminobutyric acid from lysine degradation, butanoate metabolism, and 2-oxocarboxylic acid metabolism pathways, can be proposed as key factors influencing meat quality through pathways including lysine degradation, butanoate metabolism, and 2-oxocarboxylic acid metabolism in older ducks. In contrast, the protein R0JXJ3 and metabolites choline and L-glutamine may determine meat quality differences between anatomical sites through the ABC transporter pathway. These findings provide molecular insights and potential biomarkers for genetic breeding and meat quality improvement in Sansui ducks. Full article

The ideal crystal symmetry of the 1T-TiS₂ lattice results in a non-magnetic structure. However, recent studies have demonstrated that it may become magnetic upon substitution with transition-metal (TM) atoms. In this study, we examine the mechanisms and interactions that allow magnetic exchange through the TiS₂ matrix. Using density functional theory, we model the substitutional TM-doped TiS₂ (TM = V, Cr, or Mn) system with varying spatial distances to examine the effects on the magnetic exchange. Since pristine 1T-TiS₂ is weakly semiconducting, there is a possibility that the introduction of metallic atoms may induce an RKKY-like interaction. We find that the substitution of vanadium produces a standard exchange through the orbital interactions. However, the introduction of chromium and manganese may generate RKKY interactions with the conduction electrons. Overall, a more comprehensive understanding of how different dopants affect magnetic behavior and communicate through the lattice can enable the design of spintronic devices, which offer the potential for more energy-efficient technologies and a deeper understanding of low-dimensional systems. Full article

The prevalence and the burden of neurodegenerative diseases is projected to increase in the future, but therapeutic options remain limited, relatively invasive, and not readily accessible. In this context, non-invasive brain stimulation (NIBS) techniques, mainly transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES), are emerging as safe and reliable instruments to enhance cognitive performance in asymptomatic individuals and patients with cognitive decline. Nevertheless, these techniques face some limitations that delay their deployment in clinical practice. Here, we describe the current status in the development of these technologies for the treatment of neurodegenerative diseases, and we present a novel promising approach for focally and non-invasively target deep brain regions. In light of these technological advances, we then propose a stepwise research roadmap to achieve an effective clinical translation of these techniques. Firstly, the constitution of open-access multimodal databases will allow to inform future interventions and design a new generation of clinical trials. Secondly, research efforts targeting symptomatic patients will need to assess the impact of NIBS techniques in different forms of dementias and probe their efficacy as disease-modifying therapies. In a future step, randomized clinical trials could focus on highly characterized at-risk populations to probe the impact of NIBS in secondary prevention. Once validated on research grounds, these techniques could enter clinical practice, enhancing cognitive performance in asymptomatic individuals and slowing disease progression in symptomatic patients, ultimately lowering the burden of neurodegenerative diseases. Eventually, NIBS techniques could be integrated into clinical practice within the framework of national Brain Health programs to provide early non-invasive interventions against cognitive decline to patients and individuals at risk. Full article

Background/Objectives: Grey zone serologic results in blood donor screening pose challenges for transfusion safety, donor management, and blood supply sustainability. In Saudi Arabia, standardized national protocols for managing grey zone outcomes remain lacking. This study aimed to evaluate the prevalence and follow-up outcomes of grey zone serologic results among blood donors at a Saudi hospital over a five-year period. Methods: Serological screening results of six transfusion-transmissible infections (TTIs) markers were extracted alongside nucleic acid testing (NAT) results for HBV, HCV, and HIV. The grey zone was defined as a signal-to-cutoff (S/CO) of 0.90–0.99. Repeat and follow-up results, including subsequent donations, were assessed for seroconversion. Results: A total of 48,241 donations from 38,524 donors were analyzed. Anti-HBc showed the highest reactivity (n = 2312; 4.8%), followed by HbsAg (n = 2292; 0.31%) and syphilis (n = 218; 0.5%). Grey zone results were rare, and most frequent in anti-HBc (n = 76; 0.16%), HCV (n = 39; 0.08%), and HBsAg (n = 28; 0.06%). Grey zone-to-reactive conversion upon subsequent donation was rare. Three donors who initially tested in the grey zone for anti-HBc later tested reactive in subsequent donations, but their HBV NAT remained negative. Conclusions: While grey zone outcomes were infrequent, a subset involving HBV markers showed low-level reactivity on repeat testing. For other TTIs markers, grey zone results likely reflected assay variability rather than true infection. We propose a six-month temporary deferral with follow-up serologic and NAT testing, allowing conditional re-entry for donors with consistently non-reactive results, supporting both transfusion safety and a more sustainable donor pool. Full article

Background/Objectives: Food technology neophobia (FTN), defined as the reluctance to accept or consume foods produced with novel or emerging food technologies, represents a psychological barrier to the adoption of sustainable and innovative dietary practices. This cross-sectional study investigated the prevalence of food technology neophobia and its associated factors among Italian university students. Methods: A total of 1788 undergraduates from 13 universities completed a validated online questionnaire between February and October 2024. The instrument included the Food Technology Neophobia Scale (FTNS), environmental attitude items, and demographic and dietary questions. Results: The mean FTNS score was 51.2 ± 14.0, suggesting moderate levels of neophobia. Multivariate logistic regression identified several factors inversely associated with neophobia: male gender (OR = 0.73, p = 0.003), paternal university education (OR = 0.73, p = 0.024), studying in Northern Italy (OR = 0.64, p < 0.001), dietary supplement use (OR = 0.74, p = 0.003), and pro-environmental attitudes (OR = 0.97, p < 0.001). Conversely, being a commuter student was associated with increased neophobia (OR = 1.29, p = 0.031). Conclusions: These findings highlight the influence of socio-demographic, behavioral, and attitudinal factors on the acceptance of new food technologies. Tailored strategies are recommended to address FTN in specific subgroups, particularly among female, commuter, and Southern Italian students, to enhance receptivity to food innovation and support sustainable dietary transitions. Full article

Maize, as a critical crop for China’s food security, is constantly challenged by weed infestations and environmental risks associated with herbicide overuse. Improving herbicide utilization efficiency through equipment optimization and intelligent control during spraying has become an essential strategy for weed management in Chinese maize fields. However, most current sprayers fail to achieve coordinated control of spray volume and nozzle parameters, and their performance is typically evaluated using single indices, such as the coefficient of variation (CV) for spray uniformity and deposition density. In this study, a split-split-plot experiment was conducted in 2022–2023 to assess the feasibility of herbicide reduction using intelligent variable-rate boom sprayers in summer maize fields on the North China Plain (NCP). The key variables included spray volume (225 vs. 180 L/ha), nozzle type (AI11003VS/LECHLER11003 in 2022; TTI11004/LECHLER11004 in 2023), and herbicide dose (recommended, −15%, and −30% reduction). Results showed that the coefficients of variation for droplet coverage and density remained below 12% for all treatments (n = 4), indicating stable spray performance. A higher spray volume (225 L/ha) significantly improved deposition uniformity (p < 0.01). In 2022, herbicide input could be reduced by 15–30% while maintaining efficacy above 90% when applied at the 3–4 leaf stage of dominant weeds. However, in 2023, efficacy dropped to 72.67% when the herbicide was applied at a 30% reduced dose with 180 L/ha and when dominant weeds had reached the 5–6 leaf stage or higher, indicating an agronomic risk. Reduced herbicide input decreased maize injury by 47–53%. Only the 30% reduced-dose treatment significantly increased maize yield by 3.05% in 2022 and 2.62% in 2023 compared to the control (both p < 0.05). Spray volume significantly influenced droplet deposition and weed control efficacy; thus, caution is warranted regarding herbicide reduction for later weed growth stages. This study demonstrates that real-time variable-rate boom sprayers, optimized for spray volume and nozzle type, can reduce herbicide use without compromising weed control efficacy or maize yield, providing both theoretical support and practical guidance for sustainable herbicide management in summer maize fields on the NCP. Full article

Melamine formaldehyde particle boards (MFPBs), commonly utilized as a wooden decorative material in traditional architecture, demonstrate considerable performance deterioration with extended age, with reductions in essential flame retardancy and structural integrity presenting substantial risks to fire safety in structures. This research examines the impact of thermo-oxidative aging on the flame retardancy of MFPBs. The morphological evolution, surface composition, and flame-retardant characteristics of aged MFPBs were examined via scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TG), limiting oxygen index (LOI), and cone calorimeter (CCT). The results indicate that thermo-oxidative aging (60 °C, 1440 h) markedly reduces the activation energy (E, by 17.05%), pre-exponential factor (A, by 68.52%), LOI value (by 4%, from 27.5 to 26.4), and time to ignition (TTI, by 17.1%, from 41 s to 34 s) while augmenting the peak mass loss rate (MHRR, by 4.7%) and peak heat release rate (pHRR, by 20.1%). Subsequent investigation indicates that aging impairs the char layer structure on MFPB surfaces, hastens the migration and degradation of melamine formaldehyde resin (MFR), and alters the dynamic equilibrium between “MFR surface enrichment” and “thermal decomposition”. The identified degradation thresholds and failure mechanisms provide essential parameters for developing aging-resistant fireproof composites, meeting the pressing demands of building safety requirements and sustainable material design. Full article

Optimizing last-mile delivery operations is an essential component in making a modern city livable, particularly in the face of rapid urbanization, increasing e-commerce activity, and the growing demand for fast deliveries. These factors contribute significantly to traffic congestion and pollution, especially in densely populated urban centers like Casablanca. This paper presents an innovative approach to optimizing last-mile delivery by integrating public transportation into the logistics network to address these challenges. A custom-built environment is developed, utilizing public transportation nodes as transshipment nodes for standardized packets of goods, combined with a realistic simulation of traffic conditions through the integration of the travel time index (TTI) for Casablanca. The pickup and delivery operations are optimized with the proximal policy optimization algorithm within this environment, and experiments are conducted to assess the effectiveness of public transportation integration and three different exploration strategies. The experiments show that scenarios integrating public transportation yield significantly higher mean rewards—up to 1.49 million—and more stable policy convergence, compared to negative outcomes when public transportation is absent. The highest-performing configuration, combining PPO with segmented training and public transport integration, achieves the best value loss (0.0129) and learning stability, albeit with a trade-off in task completion. This research introduces a novel, scalable reinforcement learning framework to optimize pickup and delivery with time windows by exploiting both public transportation and traditional delivery vehicles. Full article

Intelligent and antimicrobial packaging technologies are transforming meat preservation by enhancing food safety, enabling real-time quality monitoring, and extending shelf life. This review critically examines advancements in intelligent systems, including radio frequency identification (RFID), gas sensors, time-temperature indicators (TTIs), and colorimetric indicators for continuous freshness assessment. A key focus is natural compound-based chromogenic indicators, which establish visual spoilage detection via distinct color transitions. Concurrently, antimicrobial systems integrating inorganic compounds, organic bioactive agents, and natural antimicrobials effectively inhibit microbial growth. Strategic incorporation of these agents into polymeric matrices enhances meat safety, supported by standardized evaluation protocols for regulatory compliance and quality assurance. Future research should prioritize optimizing sensitivity, cost-efficiency, and sustainability, alongside developing biodegradable materials to balance food safety with reduced environmental impact, advancing sustainable food supply chains. Full article

This study addresses inversion challenges in tilted transverse isotropic (TTI) media affected by inclined fractures. A new method is proposed to derive the reflection coefficient for such media, combining scattering theory with the steady-phase method. To enhance inversion accuracy and stability, a scale normalization technique is introduced. The approach improves parameter consistency during the inversion process. The results highlight the potential of this method to offer valuable technical support for fractured reservoir exploration and development. Full article