Search Results (1,349)

Early and non-destructive detection of plant-parasitic nematodes is critical for implementing site-specific management in coffee production systems. This study evaluated the potential of unmanned aerial vehicle (UAV) multispectral and thermal imaging, combined with textural analysis, to detect Meloidogyne exigua infestation in Coffea arabica (Topázio variety). Field surveys were conducted in two contrasting seasons (dry and rainy), and nematode incidence was identified and quantified by counting root galls. Vegetation indices (NDVI, GNDVI, NGRDI, NDRE, OSAVI), individual spectral bands, canopy temperature, and Haralick texture features were extracted from UAV-derived imagery and correlated with gall counts. Under the conditions of this experiment, strong correlations were observed between gall number and the red spectral band in both seasons (R > 0.60), while GNDVI (dry season) and NGRDI (rainy season) showed strong negative correlations with gall density. Thermal imaging revealed moderate positive correlations with infestation levels during the dry season, indicating potential for early stress detection when foliar symptoms were absent. Texture metrics from the red and green bands further improved detection capacity, particularly with a 3 × 3 pixel window at 135°. These results demonstrate that UAV-based multispectral and thermal imaging, enhanced by texture analysis, can provide reliable early indicators of nematode infestation in coffee. Full article

A new family of highly uniform, cubic-shaped Cu₃VS_xSe_4−x (CVSSe; 0 ≤ x ≤ 4) nanocrystals based on earth-abundant materials with intermediate bandgaps (IB) in the visible range is reported, synthesized via a hot-injection method. The IB transitions and optical band gap of the novel CVSSe nanocrystals are investigated using ultraviolet-visible spectroscopy, revealing tunable band gaps that span the visible and near-infrared regimes. The composition-dependent relationships among the crystal phase, optical band gap, and photoluminescence properties of the novel IB semiconductors with progressive substitution of Se by S are examined in detail. High-resolution transmission electron microscopy and scanning electron microscopy characterization confirm the high crystallinity and uniform size (~19.7 nm × 17.2 nm for Cu₃VS₄) of the cubic-shaped nanocrystals. Density functional theory (DFT) calculations based on virtual crystal approximation support the experimental findings, showing good agreement in lattice parameters and band gaps across the CVSSe series and lending confidence that the targeted phases and compositions have been successfully realized. A current conversion efficiency, i.e., incident photon-to-current efficiency, of 14.7% was achieved with the p-type IB semiconductor Cu₃VS₄. These novel p-type IB semiconductor nanocrystals hold promise for enabling thin film solar cells with efficiencies beyond the Shockley–Queisser limit by allowing sub-band-gap photon absorption through intermediate-band transitions, in addition to the conventional direct-band-gap transition. Full article

Background/Objectives: Tuberculosis (TB) remains a major global health challenge influenced by social determinants of health (SDHs) such as poverty, overcrowding, malnutrition, and limited healthcare access. Although Central Asia (CA) has achieved progress through vaccination, screening, and treatment, the region continues to face severe disease consequences, unstable incidence patterns, and an escalating challenge of TB resistant to first-line drugs. This study aimed to analyze TB incidence dynamics in Kazakhstan, Tajikistan, the Kyrgyz Republic, Turkmenistan, and Uzbekistan from 2000–2023, forecast trends to 2030, and identify key SDHs shaping the epidemic. Methods: Data on TB incidence were obtained from the World Bank DataBank for 2000–2023. Of 61 socioeconomic, environmental, and health-related indicators, 29 were included in the analysis. Statistical procedures in SPSS (v24.0) involved time-series forecasting through 2030, calculation of average annual percentage change (AAPC), correlation testing, and linear regression, with significance set at p < 0.05. Results: TB incidence generally declined across CA during 2000–2023, though trends varied by country. Forecasts suggest continued decreases in Turkmenistan and Uzbekistan, while Kazakhstan, Tajikistan, and the Kyrgyz Republic display fluctuating or nonsignificant patterns, likely influenced by SDHs. Regression analyses indicated that anemia, undernourishment, and population density showed a positive relationship with TB incidence, while clean fuel access, physician density, and Gross Domestic Product per capita (GDP) were inversely related. Conclusions: The findings highlight the heterogeneous nature of TB dynamics in CA and the possible role of SDHs. Enhanced surveillance, nutritional and social interventions are required to sustain progress toward End TB targets. Full article

Effective mitigation of geotechnical risk and safety management of underground mine requires accurate estimation of rockburst damage potential. The inherent complexity of the rockburst phenomena due to nonlinear, high dimensional, and interdependent nature of the geological factors involved, however, makes predictive modeling a difficult task. The proposed research is based on the use of the K-Nearest Neighbor (KNN) algorithm to predict the risk of rockbursts with the use of microseismic monitoring data. Several key features like the ratio of total maximum principal stress to uniaxial compressive strength, energy capacity of support system, excavation span, geology factor, Richter magnitude of seismic event, distance between rockburst location and microseismic event, and rock density were applied as input parameters to extract critical rockburst precursor activities. In the test stage, the proposed KNN model recorded an accuracy of 75.50%, a precision of 0.913, a recall value of 0.509, and F1 Score of 0.576. The model is reliable with a significant performance indicating its efficacy in practice. The KNN model showed better classification results as compared to recently available models in literature and provided better generalization and interpretability. The model exhibited high prediction in classified low-risk incidents and had strong indicative capabilities towards high-risk situations, attributed to being a useful tool in rockburst hazard measurement. Full article

High-rise buildings present substantial challenges for firefighting and rescue operations owing to their considerable height. The stack effect, which becomes more pronounced with increasing building height, accelerates smoke propagation and significantly increases the likelihood of casualties. This study identifies and analyzes the risks associated with fire incidents in high-rise residential buildings. A 49-story building was selected as the reference model, and population density was applied to estimate occupant numbers for the risk assessment. For the damage scenario, one disaster-vulnerable individual per household was assumed. The simulation results revealed that firefighters and vulnerable occupants were exposed to smoke within 541 s. The findings of this study indicate that the stack effect, amplified by building height, exacerbates fire and smoke spread, thereby increasing firefighting risks and potential casualties. These results highlight fire incidents in high-rise structures as a critical category of urban disaster. Furthermore, the study underscores the limitations of existing firefighting facilities in addressing such scenarios and emphasizes the urgent need for new paradigms in firefighting strategies and smoke control technologies to mitigate the risks associated with the stack effect. Full article

In recent years, achieving ultra-wideband electromagnetic absorption has emerged as a critical challenge in confronting advanced broadband electromagnetic detection technologies. This capability is essential for effectively countering sophisticated radar systems. In this study, we present a novel multilayer metamaterial absorber that integrates an FR4 transmission layer, a periodic gradient dielectric structure designed for resonant impedance matching, and a magnetic skin layer for enhanced energy dissipation. By employing asymptotic gradients in both structure and composition, this design achieves dual-gradient electromagnetic parameter modulation, enabling efficient absorption across the X, Ku, and K bands (8.6–26.4 GHz) with a total thickness of 3.5 mm (effective thickness: 2 mm) and a density that is one-third that of conventional magnetic metamaterials. The proposed absorber demonstrates polarization insensitivity, stability across wide incident angles (up to 60°), and an absorption efficiency of 94%, as confirmed by full-wave simulations and experimental validation. Moreover, the fiber-reinforced hierarchical structure addresses the traditional trade-off between broadband absorption performance and mechanical load-bearing capacity. Full article

Objectives: The aim of this study was to stratify cardiovascular risk based on the mean and variability of non-high-density lipoprotein cholesterol (non-HDL-C) in patients undergoing hemodialysis. Methods: Data were analyzed for 453 hemodialysis patients without a history of myocardial infarction (MI) or stroke, who underwent at least five lipid profile measurements at any one of seven university hospitals in the Republic of Korea between March 2009 and December 2020. Visit-to-visit non-HDL-C variability was calculated using the coefficient of variation. The endpoints of the study were newly diagnosed MI, stroke, or all-cause death. Patients were divided into four groups according to quartiles of the mean and variability of non-HDL-C. Results: During a median follow-up of 97.0 months, there were 39 cases of MI, 99 cases of stroke, and 96 deaths. The cumulative incidence rate of MI was significantly highest in the low mean/high variability group (log-rank p = 0.0296). However, there were no significant differences between groups in the incidence rates of stroke (log-rank p = 0.9939) or all-cause mortality (log-rank p = 0.9373). In the multivariable Cox regression analysis, age and low mean/high variability (HR: 3.311, 95% CI: 1.380–7.944) were identified as independent risk factors for MI. However, for stroke and all-cause mortality, age was the only independent risk factor. Moreover, neither the mean nor the variability of non-HDL-C alone was associated with MI, stroke, or all-cause mortality. Conclusions: Our results suggest that the coexistence of low mean non-HDL-C and high variability is associated with an elevated risk of MI in hemodialysis patients. Full article

Background and Objectives: This study aimed to assess the pattern and quantity of bone regeneration after mandibular setback surgery using a novel modification of the low Z plasty (NM-Low Z plasty) technique by measuring bone density (Hounsfield unit) at the osteotomy site over a 12-month postoperative period using cone-beam computed tomography (CBCT). Materials and Methods: This retrospective cohort study included six patients with skeletal Class III deformity who underwent bilateral sagittal split osteotomy (BSSO) setback using the NM-Low Z plasty technique between 2021 and 2023 at Thammasat University Hospital. CBCT images were obtained preoperatively and at 1 month, 6 months, and 12 months postoperatively. Bone density at the buccal, cancellous, and lingual aspects of the osteotomy gap was measured using Blue Sky Plan 4 software. The intraclass correlation coefficient was used to determine reliability. Descriptive statistics, repeated-measures analysis of variance and multiple linear regression analysis were performed for comparisons. Results: At 12 months postoperatively, bone density in all measured regions was not significantly different compared to the postoperative measurements, indicating sufficient bone regeneration. The cancellous and lingual cortical regions exhibited earlier recovery than the buccal cortex. No postoperative complications such as wound infection, delayed union, or non-union were reported. Conclusions: BSSO using the NM-Low Z plasty technique offers reliable bone healing outcomes with stable bone regeneration, thereby providing a viable alternative to conventional BSSO techniques. Radiographic evidence confirmed its clinical applicability and potential to reduce the incidence of postoperative complications. Full article

In densely populated and traffic-congested major cities, medical emergency rescue incidents occur frequently, making the use of drones for emergency medical supplies delivery a new emergency distribution method. However, establishing drone transportation networks in urban areas requires balancing spatiotemporal fluctuations in emergency needs, meeting hospitals’ mandatory constraints on response time, and addressing factors like airspace restrictions and weather impacts. By analyzing the spatiotemporal distribution characteristics of medical emergency logistics in large cities, this study constructs a drone base station location optimization model integrating dynamic and static factors. The model combines multi-source data including emergency needs, geographic information, and airspace limitations. It employs kernel density estimation to identify hotspot areas, uses DBSCAN clustering to detect long-term stable demand hotspots, and applies LSTM methods to predict short-term and sudden demand fluctuations. The model optimizes coverage rate, response time, and cost budget control for drone transportation networks through a multi-objective genetic algorithm. Using Guangzhou as a case study, the results demonstrate that through “dynamic-static” collaborative deployment and multi-model drone coordination, the network achieves 96.18% demand coverage with an average response time of 673.38 s, significantly outperforming traditional vehicle transportation. Sensitivity analysis and robustness testing further validate the model’s effectiveness in handling demand fluctuations, weather changes, and airspace restrictions. This research provides theoretical support and decision-making basis for scientific planning of urban medical emergency drone transportation networks, offering practical significance for enhancing urban emergency rescue capabilities. Full article

Stem hollowness is a common disorder in broccoli, often reducing marketable yield. This study analyzed factors influencing its development and identified agronomic strategies for mitigation. Three field trials with the varieties ‘Parthenon’ and ‘Naxos’ investigated the effects of plant density, soil mineral nitrogen supply, and foliar boron application on plant growth, head characteristics, and hollow stem development. The proportion and severity of hollow stems were significantly affected by variety, plant density, and nitrogen supply. Increasing plant density markedly reduced the disorder, with symptoms nearly absent at close spacing. ‘Parthenon’ showed high susceptibility at wide spacing, showing 30–70% incidence depending on nitrogen supply, whereas ‘Naxos’ exhibit only 1–28%. Foliar boron application had no effect. The cavity formation correlated closely with head traits and varied with cultivation and weather conditions. Hardly any hollow stems occurred at stem diameters below 3.3–4.4 cm and head weights below 330–447 g. Above these values, the severity of damage increased linearly with increasing stem diameter (R² = 0.78–0.93) and head weight (R² = 0.74–0.84). Vegetative growth had only a minor influence. Overall, stem hollowness is mainly linked to head traits, with variety and plant density being the most effective factors for its reduction. Full article

Background and Objectives: Osteoporosis is a prevalent skeletal disorder characterized by decreased bone mass and compromised bone microarchitecture, leading to an elevated risk of fractures and significant morbidity, particularly among aging populations. Early diagnosis and personalized management are critical to reducing fracture incidence and associated healthcare burdens. Recent advances in artificial intelligence (AI) and machine learning (ML) have led to potential improvements in enhancing osteoporosis care by enabling accurate diagnostic imaging analysis, robust fracture risk prediction, and personalized therapeutic strategies. Materials and Methods: We performed a narrative review to summarize and critically evaluate the current literature on AI and ML applications in osteoporosis diagnosis and management. We searched relevant literature from inception to January 2025 to provide a comprehensive perspective, focusing on key themes, methodological approaches, and clinical implications. Results: Deep learning models, especially convolutional neural networks, facilitate rapid and accurate bone mineral density assessment from routine radiographs, expanding screening capabilities beyond conventional dual-energy X-ray absorptiometry (DXA). Machine learning algorithms harness clinical and demographic data to generate fracture risk models that often outperform traditional tools, enabling timely identification of high-risk individuals. Furthermore, AI-driven analyses of historical treatment responses coupled with real-time monitoring through wearable technologies and mobile applications allow for personalized therapeutic optimization and enhance patient engagement. Despite these promising advances, challenges remain regarding ethical considerations, data privacy, legal liability, incomplete model validation, lack of standardization, and the need for critical appraisal of real-world clinical efficacy for widespread clinical adoption. Conclusions: This narrative review indicates that AI and ML hold significant promise to revolutionize osteoporosis management by enabling early detection, precise risk stratification, and tailored interventions. However, the current evidence is heterogeneous, often lacking robust external validation and quantitative synthesis. Critical gaps include insufficient evaluation of model robustness across diverse populations, discussion of negative or conflicting results, and a comprehensive assessment of the limitations inherent in current AI evidence. Strategic efforts to validate, regulate, and critically integrate these technologies into routine clinical workflows are essential to realize their full potential and address the growing burden of osteoporosis worldwide. Full article

Background/Objectives: We investigated multimodal strategies to reduce neonatal ventilator-associated pneumonia (VAP) and antimicrobial use across three periods: period 1 (2014–2017), environmental cleaning with sodium hypochlorite, installation of heat and moisture exchangers, elective high frequency oscillatory ventilation (HFOV) as the primary invasive mode, and nasal HFOV after extubation; period 2 (2018–2020), oral care with maternal milk; and period 3 (2021–2024), nasal synchronized intermittent positive pressure ventilation after extubation. Methods: We conducted a quasi-experimental study of all neonates admitted to a neonatal intensive care unit in Thailand. We compared the trends in VAP and antimicrobial use rates using interrupted time-series analysis with segmented regression. Results: During the 11-year study period, 45.6% of neonates were intubated (2470/5414), and the ventilator utilization ratio was 0.19 (17,820 ventilator days/95,151 patient days). The overall VAP incidence was 4.55 per 1000 ventilator days. The yearly VAP incidence density ratio was significantly lower than in 2014. The baseline trend of VAP incidence and colistin use decreased significantly during period 1; nonetheless, the level and slope did not differ significantly between periods 1, 2, and 3. Conclusions: Tailored implementations, namely environmental decontamination, ventilator circuit care, elective HFOV, and nasal HFOV, reduced VAP and colistin use during period 1. Moreover, additive interventions, including oral care in period 2 and nasal synchronized intermittent positive pressure ventilation in period 3, achieved sustained VAP reduction and limited colistin prescriptions in period 1. Full article

Haemonchus contortus is a blood-feeding gastrointestinal nematode that significantly impacts the health and productivity of small ruminants. The burden of parasitism and the escalating incidence of anthelmintic resistance necessitate alternative control methods. Here, we characterize the enzymatic activities of five mammalian cell-expressed recombinant H. contortus cysteine proteases (HcCPs), which include two cathepsin B-like proteins (HcCBP1 and HcCBP2) and three cysteine protease 1 proteins (HcCP1a, HcCP1b, and HcCP1c). We hypothesize that these enzymes degrade host blood proteins, thereby facilitating the parasite’s nutrient acquisition and survival. Using synthetic cathepsin (cat) substrates, we show that HcCBP2 was the only protein that exhibited high catB/L but low catB or catK activity, which was inhibited by the cysteine protease inhibitor E-64. All mHcCPs degraded fibrinogen (Fg), which led to delayed plasma clotting, reduced clot density, and lysed plasma clots. All HcCPs partially degraded hemoglobin (Hb), except for mHcCBP2, which degraded Hb and bovine serum albumin completely and bovine IgG partially in the presence of a reducing agent. In conclusion, by sustaining blood feeding and facilitating immune evasion and nutrient acquisition, the HcCPs may play an essential role in the parasite’s survival. Thus, vaccines or cysteine protease inhibitors targeting these parasitic enzymes may mitigate or prevent infections. Full article

Neurodegenerative diseases (NDs) have emerged as a significant global health crisis, disproportionately affecting the aging population. As longevity increases, the incidence, healthcare costs, and caregiver burden associated with NDs are escalating at an alarming rate. As of recent data, NDs such as Alzheimer’s disease (AD) are not only significant health burdens but also reflect a complex interplay between socio-economic factors and healthcare systems worldwide. Gac fruit (Momordica cochinchinensis) is a rich source of bioactive compounds that has been used as food and traditional medicine. Gac fruit ameliorates memory deficits, enhances beta amyloid (Aβ)_1–42 clearance, and induces neurite outgrowth. In this study, we examined the anti-neurodegenerative and synaptic improvement effect of fresh gac fruit parts extracts (FGPEs) produced from different solvents. Results showed that the 80% ethanol extract of peel (PE-EtOH) and ethyl acetate extract of seed (SE-EtOAc) significantly protected HT-22 cells by attenuating Aβ-induced cell death, intracellular reactive oxygen species (ROS) production, mitochondrial dysfunction, and synaptic dysfunction. PE-EtOH protected synaptic functions by significantly increasing the postsynaptic density protein-95 (PSD-95) and reducing the neurexin 2 mRNA expression. In contrast, SE-EtOAc increased the PSD-95 and neurexin 3 and reduced the neurexin 2 expressions. These findings indicate that PE-EtOH and SE-EtOAc could have great potential in ameliorating Aβ-induced toxicity in an HT-22 cell model. Full article

Background: Androgen deprivation therapy (ADT) is a fundamental component of treatment for metastatic hormone-sensitive prostate cancer (mHSPC), but it accelerates bone mineral density loss and increases fracture risk. International guidelines recommend calcium and vitamin D supplementation, baseline dual-energy X-ray absorptiometry (DXA), and antiresorptive therapy in patients with osteoporosis. Methods: We conducted a retrospective review of 156 mHSPC patients treated with ADT at a tertiary hospital between January 2022 and December 2024. We assessed adherence to guideline-recommended bone health measures. Collected variables included age, ADT duration, calcium/vitamin D supplementation, DXA testing, antiresorptive treatment, and fracture events. Exploratory stratified analyses were performed, and proportions were reported with 95% confidence intervals (CIs). Results: Calcium/vitamin D supplementation was prescribed in 50.6% of patients (95% CI: 42.9–58.4), baseline DXA was performed in 12.8% (95% CI: 8.5–18.9), and denosumab was administered in 5.1% of the cohort (95% CI: 2.6–9.8). The median follow-up was 23 months, with a fracture incidence of 0.67 events per 100 person-years. Stratified analyses showed lower adherence in older patients, those with prolonged ADT exposure, and those with high metastatic burden. Conclusions: Adherence to guideline-recommended bone health measures in patients with mHSPC receiving ADT was markedly suboptimal. These findings underscore the need to implement standardized institutional protocols to ensure systematic supplementation, routine DXA monitoring, and appropriate antiresorptive therapy. Full article