We examine the relationship between rural wealth and the consumption of nutritious and healthy foods. Our measure of rural wealth is based on productive assets and the ownership of livestock by households. We relate this to household dietary diversity and food based dietary guidelines (FBDGs) which is a government-led initiative to promote overall health and prevent chronic diseases by fostering the consumption of nutritious and healthy foods. Employing a rich balanced panel data of about 6626 farm households, we estimate different panel data estimators. Our results reveal a clear positive association between wealth and dietary diversity a s well as the FBDGs. As rural wealth increases, households tend to shift from starchy foods to more nutrient-rich sources, particularly those high in protein. Notably, individual food groups such as fruits, vegetables, dairy, legumes, and fish show increases in consumption as assets and livestock holdings grow, as do animal-sourced foods such as meat, milk, and eggs. Among livestock, large ruminants have the greatest impact on households' intake of nutritious foods. Further, our findings highlight the gendered nature of nutritional gains, with all households-including those headed by women benefiting from increased wealth. Nutritional improvements are especially pronounced when women have greater bargaining and decision-making power in the household. Overall, we show that livestock and asset ownership could be significant entry and leveraging points for improving the consumption of nutritious and healthy foods with implications for improved health and wellbeing.

Ranitidine is an H2-receptor antagonist that inhibits histamine activity, thereby decreasing gastric acid secretion. The presence of ranitidine in water resources poses environmental risks, potentially leading to disrupting aquatic ecosystems, and affecting human health through contaminated drinking water sources. Therefore, its removal from aquatic environments is essential. The maximum removal rate of 99.8% was achieved under best operating condition of a solution pH of 8.5, ranitidine concentration of 20mg L⁻¹, activated carbon (AC) /modified zeolite (AC/MZ) composite mass of 250mg L⁻¹, and a contact time of 35min, closely aligning with the predicted removal rate of 100% from the model. The proposed model accuracy evaluated by analysis of variance. Kinetic model studies indicate that the adsorption of ranitidine onto the AC/MZ composite follows a second-order model, with a R2 of 0.9998, suggesting a chemisorption mechanism. Equilibrium studies demonstrate a strong alignment with the Langmuir isotherm, exhibiting a correlation coefficient of 0.9993, which suggests monolayer and homogeneous adsorption characteristics. The maximum adsorption capacity (qₘ) and RL values were calculated as 463.0mg g⁻¹ and 0.0162, respectively.

The Semipalatinsk Test Site houses various contaminated water resources including lakes and rivers that support fish populations, which are caught for personal consumption and for commercial sale in nearby communities while farmers water their livestock from it. There is limited data available on the contamination of freshwater biota for multiple radionuclides. The presence of 137Cs, 90Sr, 241Am, 239+240Pu, and 3H at various levels in the different water bodies offers a unique opportunity to study the uptake of radionuclides in fish and to assure public safety. Additionally, information on the migration processes of cesium and strontium can be applied to other pollutants that exhibit similar behaviour in the environment. The observed radionuclides showed mostly a similar pattern to various other marine and freshwater species, with 137Cs concentrated in the muscle, 90Sr in the bones, however Crater No. 101 showed the gastrointestinal tract high pattern for Pu isotopes. The relatively highly contaminated Crater No.101 could serve as an outstanding site for future experimental investigations into radionuclide transfer and dynamics for fish and other freshwater biota, while other, less contaminated sites show a potential for commercial utilization as hosts for fisheries based on internationally accepted levels of radionuclides in food.

Change of direction is a core technical action in many competitive sports such as football and basketball, and it plays a crucial role in athletes' performance. Deceleration, which is the foundation of changing direction, has been proven to be a key element in athletes' rapid directional changes . This study collected electromyographic signals during the deceleration phase of a [Formula: see text] left change of direction in 16 male college football players, and analyzed their muscle synergies using non-negative matrix factorization to extract key indicators such as the number of synergy modules and muscle weights. The study found that two stable muscle synergy modules could be extracted during the deceleration phase of both [Formula: see text] changes of direction. synergy module 1 was dominated by the biceps femoris, semitendinosus, and vastus lateralis; synergy module 2 was dominated by the rectus femoris, vastus medialis, and tibialis anterior. When the change of direction angle increased from [Formula: see text], the weight of the tibialis anterior in synergy module 1 significantly decreased (P=0.029), and the weights of the vastus lateralis and biceps femoris in synergy module 2 significantly increased (P=0.014 and P=0.049). Other synergy parameters (such as the time to peak activation, the degree of synergy module activation, the proportion of obvious activation duration, overall activation degree, and co-activation duration) showed no significant differences ([Formula: see text]). This indicates that during deceleration in both [Formula: see text] changes of direction, there are two stable muscle synergy modules. synergy module 1 is dominated by the biceps femoris, semitendinosus, and vastus lateralis, while synergy module 2 is centered around the rectus femoris, vastus medialis, and tibialis anterior. These two elements are jointly responsible for deceleration, initial direction change, and joint stability maintenance. As the change of direction angle increases, the human lower limb prioritizes enhancing knee joint stability, at the expense of some ankle joint control. Therefore, targeted training should focus on optimizing knee joint stability, strengthening the eccentric force of the hamstring muscles, and improving dynamic control of the ankle joint.

This study investigates the mechanical, thermal, morphological, antibacterial, and water absorption characteristics of Ananas erectifolius fiber (AEF) reinforced epoxy composites filled with sawdust particulates, aiming to develop sustainable alternatives to conventional construction materials. Composites were fabricated using the hand layup method followed by compression molding, incorporating sawdust filler contents ranging from 0 to 24g while keeping the fiber mass constant at 300g. The composite containing 18g of sawdust (Sample C3) demonstrated superior overall performance, achieving a tensile strength of 51.09MPa, flexural strength of 54.98MPa, impact strength of 14.98kJ/m², and a Shore D hardness of 51. SEM analysis confirmed strong fiber-matrix interfacial bonding and uniform filler dispersion in the optimized formulation. Thermal assessments showed that Sample C3 exhibited the lowest thermal conductivity (0.72W/mK), a reduced coefficient of linear thermal expansion (62.1 × 10⁻⁶/°C), and the highest heat deflection temperature (123°C). TGA revealed enhanced thermal stability, with ~ 18% residual mass at 600°C. Antibacterial testing against E. coli produced a 26mm inhibition zone at 100µg concentration. The water absorption rate remained low at 5.99%, indicating good dimensional stability. The novelty of this work lies in the Integrated valorization of two underutilized bio-wastes Ananas erectifolius fiber and sawdust to engineer a high-performance, eco-friendly hybrid composite tailored for sustainable building applications.

Microbially induced carbonate precipitation (MICP) has proven to be an effective method for soil reinforcement. Sporosarcina pasteurii is widely used due to its high urease activity. However, being an alkaliphilic bacterium, its limitations in acidic soil environments tend to be overlooked. This study isolated a native urease-producing bacterial strain Bacillus aryabhattai with acid tolerance, and comparative analysis of the growth characteristics of B. aryabhattai and S. pasteurii. The grouting and spraying techniques were employed to reinforce granite residual soil by the B. aryabhattai and the S. pasteurii, and the reinforcement mechanisms were systematically investigated. Experimental results indicated that despite exhibiting slightly lower urease activity and growth, the indigenous urease-producing bacterium B. aryabhattai demonstrated superior environmental resilience in terms of both environmental temperature and pH range. The soil samples reinforced by grouting with B. aryabhattai and S. pasteurii exhibited increases in ultrasonic wave velocity, unconfined compressive strength, cohesion, and cumulative disintegration rate to varying degrees compared to the untreated soil samples. Meanwhile, the resistance value of the soil samples reinforced by spraying with B. aryabhattai and S. pasteurii decreased by 84.39% and 79.79%, respectively. Additionally, the calcium carbonate content in the upper section of soil reinforced with B. aryabhattai was comparable to that of S. pasteurii; however, while in the lower section, it exhibited a 36.22% higher precipitation rate than the S. pasteurii-treated soil. Overall, the indigenous strain B. aryabhattai demonstrated remarkable reinforcement effectiveness, attributed to its rapid adaptation to weakly acidic soil conditions and moderate urease activity, which promoted a homogeneous distribution of calcium carbonate. These findings provide significant insights for soil reinforcement applications through MICP.

The growing need for high-performance stretchable fabrics led scientists to innovate a new spinning technique, especially for manufacturing cotton/spandex core-spun yarns. This type of yarn is spun by using spandex monofilament or multifilament as a core, which is surrounded by a sheath of staple cotton fibers. The key covering process parameters include spindle speed, delivery roller speed, spandex drafting ratio, spandex linear density, and tension level, which simultaneously influence the core-spun yarn characteristics such as tensile properties, hairiness index, imperfection index, and fabric aesthetic and performance properties. Fine-tuning these multiple covering parameters achieves optimal performance of these types of yarns. This paper aimed at employing multi-objective optimization for the covering parameters of cotton/spandex composite yarn to maximize the yarn tensile properties and minimize both hairiness and imperfection indices using the robust Taguchi technique in conjunction with the grey relational analysis. A full factorial design composed of three factors, namely spandex monofilament drafting ratio, linear density, and core-spun yarn twist multiplier, with five, four, and two levels, was conducted. Average values of the grey relational grades of all combinations were estimated, and its highest value refers to the optimal combinations of the controllable factors, which yield the best performance of cotton/spandex core-spun yarn. This study revealed that core-spun yarn with a 4.2 twist multiplier, a 44 dtex linear density of spandex monofilament, and a 4.4 drafting ratio of spandex yielded the optimal yarn performance characteristics. This study provides a methodological breakthrough with beneficial ramifications for the textile industry seeking a multi-objective optimization of core-spun yarn manufacturing parameters.

Classification of time series data is of significant importance across various domains. In particular, an important issue is to ensure the proper operation of vehicles such as drones. In this study, we propose a novel approach that utilizes the paradigm of information granules for time series classification. The proposed methodology transforms consecutive time windows of the original vibration signal into information granules, which are compact statistical summaries describing the signal dynamics within each segment. These granules serve as the input for machine learning classifiers and provide a more interpretable and noise-robust representation of the data. The proposed method is tested on data collected during the operation of unmanned aerial vehicles (UAVs), demonstrating its effectiveness. Experimental results indicate that the classification accuracy significantly improves when using information granules compared to raw data. In this study, the classification task involves distinguishing five classes corresponding to different rotor fault levels (0%, 25%, 50%, 75%, and 100% faulty rotors). This allows for precise identification of UAV operational health. In the case of the Tree Ensemble method, classification accuracy increased from 57.5% (raw data) to 100% (using information granules from four combined time windows), highlighting the substantial enhancement achieved through the proposed approach. Additionally, the study explores the impact of different time window lengths and training set sizes on classification performance, providing insights into optimizing the proposed method for practical applications.

Ulcerative colitis (UC) is a chronic inflammatory disease of the colon, associated with gut microbiota dysbiosis. While global studies have explored this link, region-specific microbial profiles remain underreported. This pilot study aimed to characterize and compare, for the first time, the gut microbiota of Lebanese UC patients and healthy controls using 16S rRNA gene sequencing (V3-V4 region). Fecal samples from 11 UC patients and 11 healthy individuals were analyzed. Alpha and beta diversity metrics were computed, and gut microbial composition was assessed across taxonomic levels. Statistical comparisons used Mann-Whitney and Fisher's exact tests. UC patients showed significantly reduced microbial diversity based on Faith's Phylogenetic Diversity and Shannon index (p < 0.05), though evenness was unaffected. Beta diversity also revealed significant group-level dissimilarities (p < 0.05). At the phylum level, Bacteroidota was elevated in UC, while Bacillota and Actinomycetota were reduced. Genera such as Ruminococcus, Bacteroides, and Coprococcus were depleted in UC. Faecalibacterium, commonly reduced in UC, showed no significant difference. This first analysis of gut microbiota in Lebanese UC patients reveals a distinct microbial signature that partially diverges from global trends, supporting the need for region-specific microbiome studies and personalized microbiota-targeted therapies.