Search Results (564)

House price prediction is crucial in real estate for informed decision-making. This paper presents an automated prediction system that combines genetic algorithms (GA) for feature optimization and Analysis of Variance (ANOVA) for statistical analysis. We apply and compare five ensemble machine learning (ML) models, namely Extreme Gradient Boosting Regression (XGBR), random forest regression (RFR), Categorical Boosting Regression (CBR), Adaptive Boosting Regression (ADBR), and Gradient Boosted Decision Trees Regression (GBDTR), on a comprehensive dataset. We used a dataset with 1000 samples with eight features and a secondary dataset for external validation with 3865 samples. Our integrated approach identifies Categorical Boosting with GA (CBRGA) as the best performer, achieving an R² of 0.9973 and outperforming existing state-of-the-art methods. ANOVA-based analysis further enhances model interpretability and performance by isolating key factors such as square footage and lot size. To ensure robustness and transparency, we conduct 10-fold cross-validation and employ explainable AI techniques such as Shapley Additive Explanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME), providing insights into model decision-making and feature importance. Full article

Background: Severe maternal hypertension is linked to adverse perinatal outcomes. Both nifedipine and hydralazine are commonly used antihypertensive agents in this setting. Methods: A comprehensive literature search was conducted in PubMed, Cochrane Library, and EMBASE from inception to April 2024 to identify randomized controlled trials comparing oral or sublingual nifedipine with intravenous hydralazine for the management of severe hypertension, with or without preeclampsia/eclampsia. A random-effects meta-analysis was performed using RevMan. Results: Seven randomized controlled trials were included. The pooled analysis demonstrated no significant difference between the two agents regarding time to achieve optimal blood pressure control (MD = −1.08 min, 95% CI = −6.66 to 4.49), caesarean delivery (OR = 0.62, 95% CI = 0.38 to 1.03), neonatal birth weight (MD = 57.65 g, 95% CI = −209.09 to −324.40), NICU admissions (OR = 0.90, 95% CI = 0.41 to 1.98), and 5-min APGAR scores (MD = 0.1, 95% CI = −0.20 to 0.39). However, patients receiving nifedipine had significantly lower odds of experiencing medication-related adverse events (OR = 0.62, 95% CI = 0.40 to 0.97). Conclusions: Nifedipine and intravenous hydralazine showed comparable efficacy in achieving optimal blood pressure control and similar maternal and neonatal outcomes. However, nifedipine was associated with significantly fewer maternal adverse effects, indicating superior tolerability. Full article

Background: Snake envenomation is a major public health issue in Nigeria, primarily due to bites from Echis ocellatus, Naja nigricollis, and Bitis arietans. Understanding their venom composition is essential for effective antivenom development. This study characterizes and compares the venom proteomes of these snakes using iTRAQ-based proteomics, focusing on key toxin families and their relative abundances. Methods: Venom samples were ethically collected from adult snakes, pooled by species, lyophilized, and stored for proteomic analysis. Proteins were extracted, digested with trypsin, and labeled with iTRAQ. Peptides were analyzed via mass spectrometry, and data were processed using Mascot and IQuant for protein identification and quantification. Results: E. ocellatus and B. arietans venoms had similar profiles, rich in C-type lectins, serine proteases, and phospholipase A₂s. These comprised 17%, 11%, and 5% in E. ocellatus and 47%, 10%, and 7% in B. arietans, with metalloproteinases dominating both (53% and 47%). In N. nigricollis, three-finger toxins (9%) were most abundant, followed by metalloproteinases (3%). All species shared four core protein families, with N. nigricollis also containing four uncharacterized proteins. Conclusions: This study highlights venom compositional differences, advancing snake venom biology and informing targeted antivenom development. Full article

Environmental air anomaly detection is crucial for ensuring the healthy growth of livestock in smart pig farming systems. This study focuses on four key environmental variables within pig housing: temperature, relative humidity, carbon dioxide concentration, and ammonia concentration. Based on these variables, it proposes a novel encoder–decoder architecture for anomaly detection based on continuous-time models. The proposed framework consists of two embedding layers: an encoder module built around a continuous-time neural network, and a decoder composed of multilayer perceptrons. The model is trained in a self-supervised manner and optimized using a reconstruction-based loss function. Extensive experiments are conducted on a multivariate multi-sequence dataset collected from real-world pig farming environments. Experimental results show that the proposed architecture significantly outperforms existing transformer-based methods, achieving 92.39% accuracy, 92.08% precision, 85.84% recall, and an F₁ score of 88.19%. These findings highlight the practical value of accurate anomaly detection in smart farming systems; timely identification of environmental irregularities enables proactive intervention, reduces animal stress, minimizes disease risk, and ultimately improves the sustainability and productivity of livestock operations. Full article

Background: Growth differentiation factor 15 (GDF-15), a member of the transforming growth factor-β (TGF-β) superfamily, is upregulated under cellular stress conditions and has emerged as a potential biomarker for metabolic disorders. However, its expression in relation to diabetes and obesity across different demographic groups remains understudied. This study investigated the association between plasma GDF-15 levels, diabetes mellitus, and obesity in individuals of varying ages, ethnicities, and genders. Methods: In a cross-sectional study, plasma GDF-15 concentrations were measured in 2083 participants enrolled in the Kuwait Diabetes Epidemiology Program (KDEP). The dataset included anthropometric, clinical, biochemical, and glycemic markers. Multivariate regression analysis was used to examine associations between GDF-15 levels and metabolic phenotypes. Results: Mean plasma GDF-15 levels were significantly higher in males than females (580.6 vs. 519.3 ng/L, p < 0.001), and in participants >50 years compared to those <50 years (781.4 vs. 563.4 ng/L, p < 0.001). Arab participants had higher GDF-15 levels than South and Southeast Asians (597.0 vs. 514.9 and 509.9 ng/L, respectively; p < 0.001). Positive correlations were found with BMI, waist and hip circumferences, blood pressure, insulin, and triglycerides; negative correlations were observed with HDL cholesterol. Median regression indicated that elevated GDF-15 levels were independently and significantly associated with male gender, older age, obesity, diabetes, and insulin resistance. Adjusted median regression indicated that male gender (β = 30.1, 95%CI: 11.7, 48.5), older age (β = 9.4, 95%CI: 8.0, 10.7), and insulin resistance (β = 7.73, 95%CI: 1.47, 14.0) indicated a significant positive association with GDF-15. South Asian participants (β= −41.7, 95%CI: −67.2, −16.2) had significantly but Southeast Asian participants (β= −23.3, 95%CI: −49.2, 2.56) had marginally significantly lower GDF-15 levels compared to participants of Arab ethnicity. Conclusions: Higher GDF-15 levels are associated with age, male gender, Arab ethnicity, obesity, and diabetic traits. These findings support the potential role of GDF-15 as a biomarker for metabolic disorders, particularly in high-risk demographic subgroups. Full article

Distribution systems’ vulnerability to power losses remains high, among other parts of the power system, due to the high currents and lower voltage ratio. Connecting distributed generation (DG) units can reduce power loss and improve the overall performance of the distribution networks if sized and located correctly. However, existing studies have usually assumed that DGs operate only at the unity power factor (i.e., type-I DGs) and ignored their dynamic capability to control reactive power, which is unrealistic when optimizing DG allocation in power distribution networks. In contrast, optimizing the allocation of DG units injecting reactive power (type-II), injecting both active and reactive powers (type-III), and injecting active power and dynamically adjusting (absorbing or injecting) reactive power (type-IV) is a more likely approach, which remains unexplored in the current literature. Additionally, various metaheuristic optimization techniques are employed in the literature to optimally allocate DGs in distribution networks. However, the no-free-lunch theorem emphasizes employing novel optimization approaches, as no method is best for all optimization problems. This study demonstrates the potential of optimally allocating different DG types simultaneously to improve power distribution network performance using a parameter-free Jaya optimization technique. The primary objective of optimally allocating DG units is minimizing the distribution network’s power losses. The simulation validation of this study is conducted using the IEEE 33-bus test system. The results revealed that optimally allocating a multiunit DG mix instead of a single DG type significantly reduces power losses. The highest reduction of 96.14% in active power loss was obtained by placing three type-II, two type-III, and three type-IV units simultaneously. In contrast, the minimum loss reduction of 87.26% was observed by jointly allocating one unit of the aforementioned three DG types. Full article

Microsporidia MB (MB), a promising biological control agent, suppresses Plasmodium falciparum transmission in Anopheles mosquitoes. This study examined the spatial distribution of MB infection in natural populations of An. gambiae s.l. mosquitoes collected in Nigeria and Niger Republic, and its association with insecticide susceptibility in the mosquitoes. Microsporidia MB has wide geographic distribution across Nigeria and Niger Republic. The overall prevalence of MB in F₀ mosquitoes was 12.25% (95% CI: 7.76–16.75%); 25 mosquitoes out of 204 were positive. Geographic variation was observed, with a higher prevalence (5/15 mosquitoes) in Ebonyi State (33.33%, CI: 9.48–57.19%, Fisher’s exact test, p = 0.008). Infection rates were higher in An. coluzzii mosquitoes (21/133 mosquitoes), estimated at 15.79% (CI: 9.59–21.99%) compared to An. gambiae s.s. mosquitoes (4/71), with approximately 5.63% (CI: 0.27–11.00%, χ² = 4.44; df = 1, p = 0.035). Resistant mosquitoes had a significantly higher prevalence of MB infection than susceptible mosquitos at 28.57% (CI: 16.74–40.40%) with an odds ratio of 3.33 (CI: 1.23–9.03, p = 0.017). These findings suggests that MB can be exploited as an alternative for vector control in Nigeria and Niger, but its possible association with pyrethroid resistance suggests that it should be taken into account as a potential confounder when designing insecticide resistance management strategies. Full article

Recently, morphing quadcopters have gained an unprecedented popularity due to their nature of flexibility, self-controlled arm management and diversified application. It has been established that in morphing quadcopter control, aerial morphing generally introduces time-varying parameters into the dynamic model, thereby increasing the complexity of the control problem, in addition to the non-linearity, coupling dynamics, and external disturbances present in the model. Thus, to address those challenges, this research aimed at developing a robust backstepping sliding mode controller (BSMC) for morphing quadcopter position and orientation control. to achieve the stated aim, mathematical model of an active morphing quadcopter (a foldable drone) was presented considering five morphing formations (X, H, T, O, and Y). Following the development of the system model, the proposed control method was designed in two stages: a high-performance sliding mode controller (HSMC) for attitude control to ensure chattering-free and fast convergence of the orientation angles and a backstepping controller for position control. The robustness and effectiveness of the proposed controller were investigated and benchmarked against a backstepping control approach. The simulation results obtained show the effectiveness of the developed controller against the backstepping approach in the presence of parameter variations and external disturbances. Full article

Soil salinization presents a significant challenge, driven by factors such as inadequate drainage, shallow aquifers, and high evaporation rates, threatening global food security. The sunflower emerges as a key cash crop in such areas, providing the opportunity to convert its straw into biochar, which offers additional agronomic and environmental benefits. This study investigates the effectiveness of biochar interlayers in enhancing salt leaching and suppressing upward salt migration through integrated laboratory and field experiments. The effectiveness of varying biochar interlayer application rates was assessed in promoting salt leaching, decreasing soil electrical conductivity (EC), and enhancing crop performance in saline soils through a systematic approach that combines laboratory and field experiments. The biochar treatments included a control (CK) and different applications of 20 (BL20), 40 (BL40), 60 (BL60), and 80 (BL80) tons of biochar per hectare, all applied below a depth of 20 cm, with each treatment replicated three times. The laboratory and field experimental setups maintained consistency in terms of biochar treatments and interlayer placement methodology. During the laboratory column experiments, the soil columns were treated with deionized water, and their leachates were analyzed for EC and major ionic components. The results showed that columns with biochar interlayers exhibited significantly higher efflux rates compared to those of the control and notably accelerated the time required for the effluent EC to decrease to 2 dS m⁻¹. The CK required 43 days for full discharge and 38 days for EC stabilization below 2 dS m⁻¹. In contrast, biochar treatments notably reduced these times, with BL80 achieving discharge in just 7 days and EC stabilization in 10 days. Elution events occurred 20–36 days earlier in the biochar-treated columns, confirming biochar’s effectiveness in enhancing leaching efficiency in saline soils. The field experiment results supported the laboratory findings, indicating that increased biochar application rates significantly reduced soil EC and ion concentrations at depths of 0–20 cm and 20–40 cm, lowering the EC from 7.12 to 2.25 dS m⁻¹ and from 6.30 to 2.41 dS m⁻¹ in their respective layers. The application of biochar interlayers resulted in significant reductions in Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl⁻, SO₄²⁻, and HCO₃⁻ concentrations across both soil layers. In the 0–20 cm layer, Na⁺ decreased from 3.44 to 2.75 mg·g⁻¹, K⁺ from 0.24 to 0.11 mg·g⁻¹, Ca²⁺ from 0.35 to 0.20 mg·g⁻¹, Mg²⁺ from 0.31 to 0.24 mg·g⁻¹, Cl⁻ from 1.22 to 0.88 mg·g⁻¹, SO₄²⁻ from 1.91 to 1.30 mg·g⁻¹ and HCO₃⁻ from 0.39 to 0.18 mg·g⁻¹, respectively. Similarly, in the 20–40 cm layer, Na⁺ declined from 3.62 to 3.05 mg·g⁻¹, K⁺ from 0.28 to 0.12 mg·g⁻¹, Ca²⁺ from 0.39 to 0.26 mg·g⁻¹, Mg²⁺ from 0.36 to 0.27 mg·g⁻¹, Cl⁻ from 1.18 to 0.80 mg·g⁻¹, SO₄²⁻ from 1.95 to 1.33 mg·g⁻¹ and HCO₃⁻ from 0.42 to 0.21 mg·g⁻¹ under increasing biochar rates. Moreover, the use of biochar interlayers significantly improved the physiological traits of sunflowers, including their photosynthesis rates, stomatal conductance, and transpiration efficiency, thereby boosting biomass and achene yield. These results highlight the potential of biochar interlayers as a sustainable strategy for soil desalination, water conservation, and enhanced crop productivity. This approach is especially promising for managing salt-affected soils in regions like California, where soil salinization represents a considerable threat to agricultural sustainability. Full article

Background: Intravenous magnesium sulfate (IV MgSO₄) may serve as an effective adjunct therapy to improve clinical outcomes in patients experiencing acute exacerbations of chronic obstructive pulmonary disease (AECOPDs). Methods: A comprehensive search was conducted on PubMed, Cochrane, and EMBASE from inception to April 2025 to find eligible studies comparing IV MgSO₄ plus standard treatment versus standard treatment alone. A random-effects meta-analysis was conducted using RevMan. Results: Nine studies (seven RCTs and two observational studies) met the inclusion criteria. Pooled analysis demonstrated that adjunctive IV MgSO₄ significantly improved peak expiratory flow rate at 45 min (MD = 18.50, 95% CI = 6.36 to 30.65) and significantly reduced hospital admission rates from the emergency department (OR = 0.45, 95% CI = 0.23 to 0.88). No significant differences were observed in the length of hospital stay (MD = −0.83, 95% CI = −2.99 to 1.33) and adverse events (OR = 0.79, 95% CI = 0.20 to 3.13; p = 0.73, I² = 25%) between the two groups. Conclusions: Adjunct MgSO₄ in AECOPD is associated with significant improvement in peak expiratory flow rate at 45 min and reduced hospitalization rates. Additional large-scale, multicenter randomized controlled trials are needed to validate and strengthen these findings. Full article

It is essential to emphasize the significant impacts of climate change, which are evident in the form of severe and prolonged droughts, hurricanes, snowstorms, and other climatic disturbances. These challenges are particularly pronounced in urban environments and among human populations. The situation is further aggravated by the increasing utilization of available open spaces for residential and industrial development, leading to heightened energy consumption, elevated pollution levels, and increased carbon emissions, all of which negatively affect public health. The primary objective of this review article is to provide a comprehensive evaluation of current research, with a particular focus on the innovative use of residual biomass from urban vegetation for biochar production in the United States. This research entails an exhaustive review of existing literature to assess the implementation of a carbon-negative wood biomass biochar system as a strategic approach to sustainable urban management. By transforming urban wood waste—including tree trimmings, construction debris, and storm-damaged timber—into biochar through pyrolysis, a thermochemical process that sequesters carbon while generating renewable energy, we can leverage this valuable resource. The resulting biochar offers a range of co-benefits: it enhances soil health, improves water retention, reduces stormwater runoff, and lowers greenhouse gas emissions when applied in urban green spaces, agriculture, and land restoration projects. This review highlights the advantages and potential of converting urban wood waste into biochar while exploring how municipalities can strengthen their green ecosystems. Furthermore, it aims to provide a thorough understanding of how the utilization of woody biomass biochar can contribute to mitigating urban carbon emissions across the United States. Full article

This study explores the relationship between land use and land cover (LULC) changes and a significant cyclogenesis event that occurred in Alabama’s Black Belt region from 6 to 7 October 2021. Utilizing the Weather Research and Forecasting (WRF) model, two scenarios were analyzed: the WRF Control Run, which maintained unchanged LULC, and the WRF Sensitivity Experiment, which converted 56.5% of forested areas into cropland to assess the impact on storm dynamics. Quantitative comparisons of predicted rainfall from both simulations were conducted against observed data. The control run demonstrated a Root Mean Square Error (RMSE) of 1.64, indicating accurate rainfall predictions. In contrast, the modified scenario yielded an RMSE of 2.01, suggesting lower reliability. The Mean Bias (MB) values were 1.32 for the control run and 1.58 for the modified scenario, revealing notable discrepancies in accuracy. The coefficient of determination (R²) was 0.247 for the control run and 0.270 for the modified scenario. The Nash–Sutcliffe Efficiency (NSE) value was 0.1567 for the control run but dropped to −0.2257 following LULC modifications. Sensitivity analyses revealed a 60% increase in heat flux and a 36% rise in precipitation, underscoring the significant impact of LULC on meteorological outcomes. While this study concentrated on the Black Belt region, the methodologies employed could apply to various other areas, though caution is advised when generalizing these results to different climates and socio-economic contexts. Further research is necessary to enhance the model’s applicability across diverse environments. Full article

Wearable sweat-sensing devices hold significant potential for non-invasive, continuous health monitoring. However, challenges such as ensuring data accuracy, sensor reliability, and measurement stability persist. This study presents the development of a wearable system for the real-time monitoring of human sweat sodium levels, addressing these challenges through the integration of a novel microfluidic chip and a compact potentiostat. The microfluidic chip, fabricated using hydrophilic materials and designed with vertical channels, optimizes sweat flow, prevents backflow, and minimizes sample contamination. The developed wearable potentiostat, as a measurement device, precisely measures electrical currents across a wide dynamic range, from nanoamperes to milliamperes. Validation results demonstrated accurate sodium concentration measurements ranging from 10 mM to 200 mM, with a coefficient of variation below 4% and excellent agreement with laboratory instruments (intraclass correlation = 0.998). During physical exercise, the device measured a decrease in sweat sodium levels, from 101 mM to 67 mM over 30 min, reflecting typical physiological responses to sweating. These findings confirm the system’s reliability in providing continuous, real-time sweat sodium monitoring. This work advances wearable health-monitoring technologies and lays the groundwork for applications in fitness optimization and personalized hydration strategies. Future work will explore multi-biomarker integration and broader clinical trials to further validate the system’s potential. Full article

In this study, a novel adsorbent was developed by synthesizing Zn-Al layered double hydroxide (LDH) incorporated with silver nanoparticles (Ag-NPs), and its effectiveness in bromide removal from aqueous solutions was systematically evaluated. The X-ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FTIR) analyses confirmed the integration of Ag-NPs within the LDH, ensuring uniform chemical composition and structural integrity. A series of controlled batch trials, each varying a single parameter (adsorbent dose, contact time, or temperature) confirmed that over 95% of bromide (initially 5320 μg/L) was removed under optimized conditions. LDH/Ag-NPs exhibited superior performance, with kinetics well described by a second-order reaction model. Thermodynamic analysis confirmed the spontaneous and exothermic nature of bromide adsorption, with ΔG° values ranging from −2.03 to −0.73 kJ/mol as the temperature increased from 22 °C to 52 °C. In continuous-flow experiments, packed-bed column tests illustrated that LDH/Ag-NPs maintained more effective bromide removal than LDH alone over extended periods. Conductivity measurements further supported this enhancement, with LDH/Ag-NPs reducing final conductivity to 139 µS/cm, compared to 212 µS/cm for LDH. Furthermore, this study revealed the notable antimicrobial activity of LDH/Ag-NPs, as evidenced by a significant reduction in bacterial growth compared to LDH alone, highlighting its dual functionality for both bromide adsorption and water disinfection. Overall, the incorporation of Ag-NPs into LDH offers a promising strategy for developing multifunctional and sustainable water treatment systems. Full article

This study employed a simple and cost-effective method for developing NiO with reduced optical band gaps that can be combined with nanostructured polyaniline (PANI). The composite systems were used as electrocatalytic and electrode materials in oxygen evolution reactions (OER) and in supercapacitor applications. We prepared the composite material in two stages: NiO was prepared with a reduced optical band gap by combining it with wheat peel extract. This was followed by the incorporation of PANI nanoparticles during the chemical oxidation polymerization process. A variety of structural characterization techniques were employed, including scanning electron microscopy (SEM), powder X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, UV-visible spectroscopy, and X-ray photoelectron spectroscopy (XPS). A surface-modified NiO/PANI composite with enhanced surface area, fast charge transfer rate, and redox properties was produced. When NiO/PANI composites were tested in KOH electrolytic solution, 0.5 mL of wheat peel extract-mediated NiO/PANI demonstrated excellent electrochemical performance. It was found that the asymmetric supercapacitor (ASC) device had the highest specific capacitance of 404 Fg⁻¹ at a current density of 4 Ag⁻¹. In terms of energy density and power density, the ASC device was found to have 140 Whkg⁻¹ and 3160 Wkg⁻¹, respectively. The ASC device demonstrated excellent cycling stability and charge storage rates, with 97.9% capacitance retention and 86.9% columbic efficiency. For the OER process, an overpotential of 320 mV was observed at a current density of 10 mA/cm². It was found that the NiO/PANI composite was highly durable for a period of 30 h. A proposed hypothesis suggested that reducing the optical band gap of NiO and making its composites with PANI could be an appealing approach to developing next-generation electrode materials for supercapacitors, batteries, and fuel cells. Full article