Physical Attributes Research Articles

Determining the Correlation of Fat-Free Mass, Power, and Maximum Hamstring Force in Female Basketball Athletes

Background. In competitive sports, especially basketball, physical attributes such as agility, speed, strength, and power are crucial for performance. Objectives. This study aimed to examine the correlation between fat-free mass (FFM), countermovement jump (CMJ) power, and maximum hamstring force in female basketball athletes, providing insights that could enhance performance and reduce injury risk. Materials and methods. This observational cross-sectional study investigates the relationship between fat-free mass (FFM), power, and maximum hamstring force in 45 female basketball athletes. The Anderson-Darling test for assessing normality and Spearman’s correlation for non-normally distributed data were used to conduct the study. Results. Significant correlations were found between FFM and maximum hamstring force in the both right (r = 0.585, p < 0.001) and left legs (r = 0.522, p < 0.001), as well as between (CMJ) power and maximum hamstring force for both legs (right: r = 0.467, p = 0.001; left: r = 0.434, p = 0.003). Additionally, power was significantly correlated with jump height (r = 0.604, p < 0.001). Conclusions. These findings suggest that FFM and power are critical determinants of hamstring strength and explosive performance in female basketball athletes.

Postharvest Management Techniques for Improved Shelf Life of Horticultural Crops: A Review

Postharvest management in horticulture is important for maintaining the quality, safety, and shelf life of produce, significantly impacting global food security and economic stability. This review explores critical advancements in postharvest practices, focusing on quality control, safety standards, and emerging technologies. Postharvest quality assessment involves the evaluation of physical, chemical, and sensory attributes, supported by microbiological testing to ensure food safety. Global standards like HACCP, GlobalG.A.P., and ISO 22000 provide frameworks for ensuring compliance and market access. Technological innovations, including near-infrared spectroscopy, hyperspectral imaging, and smart sensors, enable precise, real-time monitoring of produce quality, enhancing operational efficiency. Emerging technologies are revolutionizing the field; nanotechnology offers advanced packaging solutions that improve shelf life and food safety, while drones and AI enhance postharvest monitoring and logistics through real-time data collection and predictive analytics. Blockchain technology introduces unprecedented levels of traceability and transparency, ensuring accountability and rapid response to food safety issues. The integration of these technologies not only improves the efficiency and sustainability of postharvest systems but also aligns with consumer demands for high-quality, safe, and sustainably sourced produce. This holistic approach reduces post- harvest losses, enhances market competitiveness, and contributes to global efforts in ensuring food security. The synergy of traditional quality control methods with cutting-edge technologies paves the way for a resilient and adaptive post- harvest management system that meets the evolving challenges of the agricultural sector.

Similar adaptive responses in the upper body physical performance of table tennis players following the traditional and cluster set resistance and plyometric training.

Numerous studies have investigated the impact of resistance training (RT) and plyometric training (PT) set configurations (cluster sets [CS] and traditional sets [TS]) on lower body performance adaptations. However, the effects of these training modalities on upper body physical performance, particularly among Table Tennis (TT) players, remain unclear. Therefore, this study aimed to examine the effects of an 8-week RT and PT using CS and TS configurations on the physical performance attributes of male TT players. Forty young male players were recruited from a local academy and after determining their dominant hand, divided into CS-PT, TS-PT, CS-RT, TS-RT, and active control (CON) groups, each of eight. Pre- and post-interventions, the upper body muscular power (medicine ball throw), maximal strength (bench press), reaction time, and arm crank anaerobic power test were measured. Following the intervention, the CON group exhibited no changes; however, the CS-PT, TS-PT, CS-RT, and TS-RT groups displayed significant (p = 0.001) improvements in muscular power (effect size [ES] = 1.21 [large], 1.02 [medium], 0.81 [medium], 0.64 [medium]), strength (ES = 0.40 [small], 0.43 [small], 0.62 [medium], 0.63 [medium]), reaction time (ES = - 0.71 [medium], - 0.68 [medium], - 0.83 [medium], - 0.61 [medium]), peak power (ES = 1.83 [large], 1.66 [large], 0.90 [medium], 0.67 [medium]), and mean power (ES = 0.89 [medium], 0.89 [medium], 0.57 [small], 0.59 [small]), respectively. The PT groups indicated significantly greater changes than the RT groups in both muscular (CS, p = 0.021; TS, p = 0.018) and anaerobic power (peak power: CS, p = 0.017; TS, p = 0.011; mean power: CS, p = 0.024; TS, p = 0.042) performance, while the RT groups showed greater adaptive responses than the PT groups in maximal strength (CS, p = 0.033; TS, p = 0.048). In conclusion, PT is recommended for enhancing power performance, while RT is preferred for increasing strength. When various set configurations were incorporated, no further effects were noted.

Alginate Formulation for Wound Healing Applications.

Significance: Alginate, sourced from seaweed, holds significant importance in industrial and biomedical domains due to its versatile properties. Its chemical composition, primarily comprising β-D-mannuronic acid and α-L-guluronic acid, governs its physical and biological attributes. This polysaccharide, extracted from brown algae and bacteria, offers diverse compositions impacting key factors such as molecular weight, flexibility, solubility, and stability. Recent Advances: Commercial extraction methods yield soluble sodium alginate essential for various biomedical applications. Extraction processes involve chemical treatments converting insoluble alginic acid salts into soluble forms. While biosynthesis pathways in bacteria and algae share similarities, differences in enzyme utilization and product characteristics are noted. Critical Issues: Despite its widespread applicability, challenges persist regarding alginate's stability, biodegradability, and bioactivity. Further understanding of its interactions in complex biological environments and the optimization of extraction and synthesis processes are imperative. Additionally, concerns regarding immune responses to alginate-based implants necessitate thorough investigation. Future Directions: Future research endeavors aim to enhance alginate's stability and bioactivity, facilitating its broader utilization in regenerative medicine and therapeutic interventions. Novel approaches focusing on tailored hydrogel formations, advanced drug delivery systems, and optimized cellular encapsulation techniques hold promise. Continued exploration of alginate's potential in tissue engineering and wound healing, alongside efforts to address critical issues, will drive advancements in biomedical applications.

Artificial Neural Network Modeling to Predict Electrical Conductivity and Moisture Content of Milk During Non-Thermal Pasteurization: New Application of Artificial Intelligence (AI) in Food Processing

This study proposed applying artificial intelligence (AI) to predict the actual electrical conductivity (EC) of raw and pasteurized milk using moderate electric field (MEF) based on the electric field strength (EFS) and mass flow rate (MFR) along with modeling moisture content (MC) based on the EC. To this end, an artificial neural network (ANN) was implemented for conventionally (CP) and non-thermally (NP) pasteurized milk. The findings indicated no significant difference (p > 0.05) between the experimental and predicted data for EC and MC. The MFR and EFS affected the actual EC. The raw milk samples had an EC of 0.468812–0.46913 S/m and MC of 87.3218–87.35941%, while these values in NP pasteurized milk were 0.457441–0.638224 S/m and 87.33986–87.40851%. With correlation coefficients (R) of 0.736478106–0.951840323 and mean square errors (MSE) of 0.005539–0.0064, the ANN accurately predicted the raw and pasteurized milk MC based on the EC using the sixth-order polynomial model and the EC based on the EFS and MFR using a quadratic model. The EC of pasteurized milk by NP was significantly (p < 0.05) lower than that of CP and raw dairy by 15.44% and 11.30%, respectively. The results show that the EFS and MFR might be used for the online assessment of milk’s physical attributes (e.g., EC), followed by using the assessed parameter to determine other properties (e.g., MC) by developing AI approaches based on optimized models. These observations showcase the innovative use of ANN-based AI to predict milk’s EC and MC accurately. Integrating such AI platforms into non-thermal food processing could eventually develop more sustainable food production and enhance food security and quality through process innovation and sustainable manufacturing, contributing to the industrial revolution and sustainable development goals.

ASSESSMENT OF THE QUALITY OF LEISURE PARKS USING THE IPA-KANO INTEGRATIVE APPROACH TO SATISFACTION, CASE TITO PARK, ALGERIA

Leisure parks provide innumerable benefits in terms of social well-being and economic advantages, hence the importance for managers to assess their condition and determine the beneficial actions to be taken. The physical and functional attributes of parks are key indicators of quality; especially, if they are inspected from the perspective of user satisfaction. Although previous studies have incorporated satisfaction, few have used management tools together in developing countries. This paper proposes the simultaneous use of importance-performance analysis (IPA) and the Kano model as an integrative approach to satisfaction to assess the quality of recreational parks. Tito Park in Algiers used as a case study, was the subject of two methods: first qualitative-exploratory by 116 interviews (2016-2017) on the sociocultural variables of visitors, and quantitative-empirical by IPA-Kano statistical analysis against 36 attributes hierarchized in 7 families of quality criteria. The results reveal a divergence of visitors' opinions against these attributes within the same family of criteria; this is reinforced by a disparity between the degrees of importance and satisfaction that users allocate to them. This research offers a pragmatic tool to help with targeted and optimized decision-making and design as a means of requalification of the landscape. Because it elucidates the state of the recreational offer and points out the contextual characteristics to be promoted in order of priority by integrating the dimensions: perceptual and time. In the future, two or more parks can be compared using these or other tools by aggregating more attributes.

Enhancing the resilience of cement mortar: Investigating Nano-SiO2 size and hybrid fiber effects on sulfuric acid resistance

This article explores fortifying cement mortars against severe sulfuric acid (SLA) attacks by studying the impact of nano-SiO2 (NS), macro-steel (ST), and micro-polypropylene (PP) fibers. The aim is to assess their effects on workability, physical attributes, mechanical properties, and durability against SLA attacks when incorporated into mortar blends. Replacing 1 % of cement weight with NS, having average particle diameters of 15 nm (nm) (NS15) and 55 nm (NS55), and utilizing macro-ST and micro-PP fibers at volumes of 0.5 % and 1 % in singular and hybrid forms resulted in significant changes in mortar characteristics. While these additives increased fresh mortar viscosity and negatively affected workability, they substantially boosted mortar strength and durability against SLA attacks. The most substantial improvements were observed using smaller NS particle sizes and employing hybrid ST/PP fibers. The formation of calcium-silicate-hydrate (C-S-H) bonds by NS within the network emerged as a pivotal factor. NS's high pozzolanic activity and void-filling capacity significantly enhanced the mortars' strength and durability against SLA attacks. Furthermore, instead of their singular application, the combined use of ST and PP fibers proved more effective in restraining micro and macro cracks within the mortar matrix. The bridging effect of hybrid ST/PP fibers delayed crack propagation throughout the network, highlighting their superior efficiency against SLA attacks.Overall, these findings hold promise for designing cement-based composites resilient to harsh, acidic environments. Using smaller NS particles and hybrid fiber combinations presents potential pathways to prolong service life in challenging conditions.

Ionically crosslinked Sodium alginate – Galactoxyloglucan hydrogel beads as a controlled release system for sustainable urea delivery

The prolonged usage of chemical fertilizers often causes deleterious effects on the environment, and it remains an alarming issue in agricultural practices. Smart delivery of fertilizers achieved by hydrogels proved their efficiency in reducing risk in action. In this study, we investigated the optimization of urea-encapsulated hydrogel formulations and evaluated their physical and chemical attributes for agricultural applications. The proposed hydrogel formulation consists of ionically crosslinked two promising plant biopolymers (galactoxyloglucan and sodium alginate) which are specifically developed for the controlled release of urea fertilizer. The FT-IR analysis of the hydrogel beads confirmed the presence of biopolymer functional groups and urea. XRD analysis indicated the amorphous nature of the biopolymers. TGA revealed a thermal stability of up to 350°C. SEM images showed the porous structure of the hydrogel beads. To investigate the controlled release of urea, two kinetic models were employed: Korsmeyer-Peppas and Peppas-Sahlin. The results indicated a controlled release mechanism. The hydrogel beads demonstrated excellent water retention properties, maintaining soil moisture for up to 16 days. Additionally, degradability results demonstrated that in the soil environment, the hydrogel beads were degraded completely in 21 days. Therefore, we are confident that the formulated hydrogel bead exhibits eco-friendly and bio-compatible characteristics, which potentially mitigate the risks associated with urea fertilizers.

Primary Modes of Northern Hemisphere Snowfall Particle Size Distributions

Abstract A comprehensive understanding of snowfall microphysics is crucial for enhancing the accuracy of remote sensing snowfall retrievals. However, variations in regional and seasonal snow particle size distributions (PSDs) contribute substantial uncertainty. Here, we examine snowfall PSDs from across the Northern Hemisphere, applying Principal Component Analysis (PCA) to disdrometer observations with the aim of identifying dominant modes of variability across varying regional climates. The PCA revealed three Empirical Orthogonal Functions (EOFs) that account for a combined 95% of the variability across the dataset, which are attributed to latent linear embeddings of snowfall intensity (EOF1), snowfall character (EOF2) and snowfall regime (EOF3). Examining point clusters with the highest combined EOF values reveals six distinct modes of variability (i.e., Principal Component [PC] groups) with unique PSD traits. These groups are then correlated with environmental factors using data from collocated vertically pointing radar, surface meteorology, and reanalysis to assist in assigning physical attributes. The first and second PC groups, linked to EOF1’s intensity embedding, are described by their PSD intercepts, snowfall rates, and reflectivity and Doppler velocity values, representing low and high intensity snowfall modes, respectively. The third and fourth PC groups, associated with EOF2’s character embedding, are defined by temperature, fall speed, and density, indicative of cold, fluffy snowfall and warm, dense snowfall, respectively. The fifth and sixth PC groups, related to EOF3’s regime embedding, are distinguished by their PSD slope, snowfall rate, and reflectivity profiles, signifying shallow, weak convective systems with small particles, and deep, stratiform snowfall events with large aggregates, respectively.

Deep learning-assisted local resonance strategy for accurate internal damage imaging in composites

In this paper, we propose a deep neural network-assisted strategy to accurately and efficiently identify local defect resonance (LDR) modes and accurately image the internal damage in composites. A two-dimensional convolutional neural network (2D-CNN) model was constructed to identify LDR modes. The frequency-domain contour maps were used as input data, given that the LDR phenomenon exhibits discernible physical attributes in the frequency domain that are conducive to deep neural network assimilation. The obtained results demonstrate effective training outcomes and transferability, even with a limited number of samples. The LDR modes are efficiently extracted by the developed 2D-CNN model and used to obtain the accurate imaging of internal damages in composites.

Sugarcane bagasse derived biochar potential to improve soil structure and water availability in texturally different soils

Low organic matter content is one of the main constraints in arid and semiarid regions. This constraint and its negative influences on soils and plant growth may be alleviated by biochar (BC). Furthermore, improving soil physical and hydraulic attributes by application of biochar has received increased attention. Therefore, in the present study, the effects of sugarcane bagasse-derived biochar on the structural stability, water availability, and pore-size distribution (PSD) of three texturally different calcareous soils collected from different agro-climatologically regions were examined during a long-term experiment. Low and high-temperature biochars, produced in a muffle furnace by the traditional slow pyrolysis method at 300 °C (BC300) and 600 °C (BC600) were evaluated. Pots (15 kg) were filled with three different silty-clay Inceptisols (SCInc), silty-clay-loam Alfisols (SCLAlf), and loam Aridisols (LArid) soils mixed with 0 (control), 1, 2, and 3 w/w% of BC300 and BC600 during 540 days of incubation. The high energy moisture characteristic (HEMC) data was modeled using a modified van Genuchten function to quantify aggregate stability through stability ratio (SR) and structural stability index (SSI). The plant available water (PAW), least limiting water range (LLWR), and integral water capacity (IWC) were calculated with two matric suctions (h) of 330 cm for field capacity (FC) and 15,000 cm for permanent wilting point (PWP). Then the integral energy (EI) values were calculated (EIIWC). Results indicated that the incorporation of 3 w/w% biochar significantly (p < 0.01) increased SR (35 to 100%) and SSI (21 to 28%) indices in all three soils. Biochar significantly increased modal suction (MS) in LArid soils (5 to 158%); whereas, decreased MS of the other soils (3 to 43%). MS, SR, and SSI of BC300 and BC600-treated soils were not significantly different. PAW, LLWR, and IWC significantly decreased in the SCInc (18 to 61%, 8 to 44%, and 6 to 35%) and SCLAlf (8 to 44%, 18 to 35%, and 20 to 47%) soils and increased in LArid (4 to 54%, 3 to 61%, and 24 to 111%) soil with increasing biochar doses. There were no changes in EIIWC in biochar-treated LArid soil where PAW, LLWR, and IWC increased. Biochar increased EIIWC across the studied soil from 1% to 3.38 folds, thereby increasing the gradient of water potential to absorb the available water. Soil and soil-biochar mixtures exhibited heterogeneous and multimodal pore-size distribution (PSD). Biochar promoted the PSD peaks related to water-transmitting pores in SCInc and SCLAlf soils while decreased in LArid soil. In conclusion, results indicated that among the applied levels of biochar, the application of 3 w/w% biochar is suggested as a suitable way to improve soil physical behavior and structural stability.

Evaluation of Morphological, Physical and Functional Attributes of Agathi (Sesbania grandiflora) Leaves and Flowers

The study aimed to characterize the morphological, physical, and functional properties of agathi (Sesbania grandiflora) leaf and flower powders, highlighting their potential for food applications. Morphological assessments revealed that agathi leaves have an edible index of 76.20 ± 0.42 % and a waste index of 23.75 ± 0.65 %, while flowers showed an edible index of 63.79 ± 0.46% and a waste index of 36.21 ± 0.54 %. Physical properties showed that leaf powder had a higher bulk density (0.36 ± 0.02 g/cm³) and tapped density (0.59 ± 0.02 g/cm³) compared to flower powder (0.29 ± 0.03 g/cm³ and 0.48 ± 0.01 g/cm³, respectively). The flowability (Carr index) was slightly better for flower powder (40.24 ± 0.01 %) than for leaf powder (39.2 ± 0.01 %). Functional properties indicated that flower powder had significantly higher water absorption capacity (597.28 ± 1.22 %) and oil absorption capacity (224.21 ± 1.56%) compared to leaf powder (315.30 ± 1.28 % and 183.16 ± 1.34 %, respectively). Flower powder also exhibited greater solubility (28.77 ± 2.66 %) versus leaf powder (12.92 ± 1.59 %). These results suggest that both agathi powders are valuable ingredients for food formulations, providing functional and nutritional benefits, and are suitable for use in developing, handling, and packaging functional food products.

Optimizing Cookie Formulation Using a Composite Flour Blend of Soybean, Beetroot, and Wheat: Effects on Physicochemical and Phytonutrient Characteristics

This study aimed to optimize cookie formulation using a composite flour blend of soybean (SF), beetroot (BF), and wheat (WF). Four blends were formulated: 50% WF:45% SF:5% BF (T1), 50% WF:35% SF:15% BF (T2), 50% WF:25% SF:25% BF (T3), and 100% WF (Control) (T4) for cookie preparation. The inclusion of SF and BF had significant effects on the physical, chemical, and phytonutrient attributes of the cookies. Results showed an increase in diameter and height with the addition of beetroot and soy flour. T2 had the highest weight (9.57g), diameter (5.42cm), and spread ratio (6.46) among the blends, while T3 had the highest total color difference. T1 cookies had higher levels of protein, crude fiber, total phenolic content, and total antioxidant activity compared to the control. Statistical analysis indicated that the sensory characteristics of the cookies were not significantly affected by the addition of soy and beetroot flours. This study suggests that composite flour cookies enriched with nutritional and antioxidant properties can be developed by incorporating varying levels of beetroot and soy flour alongside wheat flour.

Impact of corn shredlage and crabtree-negative yeast on silage quality and rumen fermentation characteristics

The physical attributes of corn silage are enhanced by shredlage (SHR), while there is a rising interest in boosting its biological performance. This study aimed to assess and compare the impact of both the chopping method and different yeast strains on ensilage quality including the in vitro evaluation of corn silage. Both types of corn, including chopped and shredded, were harvested on the same day from the same field where the same corn hybrid (Suwan 5) was grown. Subsequently, whole-corn plants were fermented with additives. A 2 × 5 Factorial completely randomized design was employed, where factor A represents corn chopped (CON) and corn shredded (SHR), and factor B represents the additives: no additives, molasses + urea (M + U), M + U + Candida tropicalis KKU20, M + U + Pichia kudriavzevii KKU20, and M + U + saccharomyces cerevisiae. The results demonstrated that SHR fermentation with M + U and yeast significantly increased in vitro dry matter degradability (IVDMD) and organic matter degradability (IVOMD). Specifically, at 4 h post-incubation, the addition of Crabtree-negative yeast led to a 5.8% increase in total volatile fatty acids (TVFA) compared to the Crabtree-positive yeast group (P < 0.01). The C2 (acetic acid) + C4 (normal butyric acid and isobutyric acid): C3 (propionic acid) ratio showed a significant decrease without additives, but P. kudriavzevii KKU20 led to the highest ratio and methane production (P < 0.01). Based on this study, it could be concluded that SHR harvesting led to higher digestion efficiency in the rumen. The use of M + U + yeast also demonstrated uncertain effects on rumen fermentation efficiency, and the inclusion of P. kudriazevii KKU20 may potentially reduce rumen fermentation efficiency when used with corn silage.

Heat transport analysis of three-dimensional Magnetohydrodynamics nanofluid flow through an extending sheet with thermal radiation and heat source/sink

Regarding heat transformation efficiency, the hybrid nanofluid performs superior to the nanofluid. The majority of hybrid nanofluid uses are in the industrial sector, producing solar energy, cooling generators, and vehicle heat transformation. Heat transfer and nanofluid velocity are the two most crucial transport properties that must be evaluated before the first and second thermodynamics equations are applied to nanoscale fluids. The objective of this work is to investigate the characteristics of transmission of heat of magnetohydrodynamic (MHD) nanofluid (Ag/H2O)and hybrid nanofluid (Ag+Al2O3/H2O)flow on a linear extensible sheet when magnetic forces are present. Similarity variables are applied to transform a set of nonlinear dimensionless partial-differential equations to collection of ordinary-differential equations. The non-analytical solutions of these transformed equations are found utilizing the MATLAB mathematical program's bvp4c function. The impression of various physical attributes along skin friction coefficients and properties of heat transmission are analyzed. The behavior of key parameters, including surface stretching ratio, rotational and magnetic effects, for temperature and velocity, is shown using graphs and tables. In conclusion, hybrid nanofluids, which comprise silver and aluminum oxide nanoparticles dispersed in water, outperform silver-water nanofluids by around 10-15% under magnetohydrodynamic (MHD). The higher thermal conductivity of these hybrid nanofluids allows for better heat dissipation, making them an appealing option for applications that need optimal thermal management in the presence of magnetic fields.

Modeling Nonspherical Hailstones

Abstract Hail research and forecasting models necessarily involve explicit or implicit—and uncertain—physical assumptions regarding hailstones’ shape, tumbling behavior, fall speed, and thermal energy transfer. Whereas most models assume spherical hailstones, we relax this assumption by using hailstone shape data from field observations to establish empirical size–shape relationships with reasonable degrees of randomness considering hailstones’ natural shape variability, capturing the observed distribution of triaxial ellipsoidal shapes. We also incorporate explicit, random tumbling of individual hailstones during their growth to simulate their free-falling behavior and the resultant changes in cross-sectional area (which affects growth by hydrometeor collection). These physical attributes are incorporated in calculating hailstones’ fall speeds, using either empirical relationships or analytical relationships based on each hailstone’s Best and Reynolds numbers. Options for drag coefficient modification are added to emulate hailstones’ rough surfaces (lobes), which then modifies their thermal energy and vapor exchange with the environment. We investigate how applying these physical assumptions about nonspherical hail to the Penn State hail growth trajectory model, coupled with Cloud Model 1 supercell simulations, impacts hail production and examine the reasons behind the resulting variability in hail statistics. The choice of hailstone size–mass relation and fall speed scheme have the strongest influence on hail sizes. Using nonspherical, tumbling hailstones reduces the number of large hailstones produced. Applying shape-specific thermal energy transfer coefficients subtly increases sizes; the effects of lobes vary depending on the fall speed scheme used. These physical assumptions, although adding complexity to modeling, can be parameterized efficiently and potentially used in microphysics schemes. Significance Statement In numerical modeling of hailstorms, we usually consider hailstones to be spherical to simplify calculations, but in nature, hailstones generally are not spheres and can be rather lumpy and have spikes. The purpose of this study is to examine how the model result would change when nonspherical hailstone shape is implemented. We examine the relationship between hailstone shape and physical processes during hail growth in effort to explain why these changes occur and offer insights on how nonspherical hailstone shape may be parameterized in bulk microphysics schemes.

Ігрові амплуа в баскетболі: функції та вимоги до гравців

In modern basketball, effective team play requires players in different positions to perform specialized functions that match their physical, technical and psychological attributes. Understanding these functions is crucial to the success of the team. Identifying the functions and requirements of players at different positions is key to the success of any basketball team. This allows you to create an effective strategy where each player can maximize his or her potential. Purpose of the study: to consider the functions of basketball players playing in certain positions and to determine the requirements for players of different playing roles in basketball. Research methods: theoretical analysis and generalization of scientific and methodological literature. Results of the study. The functions of basketball players playing at certain positions are characterized. The requirements for players of different playing roles in basketball are revealed: point guard, attacking guard, light forward, heavy forward, center. Conclusions. The functions of basketball players playing in different positions are determined by their roles and responsibilities on the court. The distribution of players by function is an important aspect of organizing team play in basketball. This distribution allows to achieve an organized and purposeful game, taking into account the individual capabilities of each player. The distribution of playing roles among players depends on their physical and psychological characteristics. The anthropometric data and skills of a player are taken into account when determining his role. However, it is also important to take into account the psychological characteristics of the player and his ability to cooperate with his teammates. It is necessary to clearly assign roles in the team in order to achieve success. Intragroup rivalry can have a negative impact on teamwork, so it is important that each player understands his own capabilities and has the ability to assess the capabilities of his partners. The requirements for players of different playing roles in basketball are their understanding of roles and responsibilities, ability to cooperate with partners, individual skill and ability to assess the situation on the court. This helps to effectively build a team that can succeed.

Preparation of sunflower wax-based oleofoams and its application in inflatable reduced-fat mayonnaise

The present work aimed to prepare inflatable reduced-fat mayonnaise by using sunflower wax-based oleofoams (SWOF) as an oil phase. The effects of SW concentrations on the microstructure and the physical properties of oleofoams were investigated. Then the stable oleofoam formulations were chosen to prepare inflatable mayonnaise, and the functionality related to the physical (textural properties and thermal stability) and sensory attributes (appearance, color, and viscosity) of inflatable reduced-fat mayonnaise was compared with commercial low-fat mayonnaise (CLFM) & full-fat mayonnaise (CFFM). The microstructure study of SWOF indicated the presence of clearly visible SW crystals at the air-oil boundary and inside the continuous phase. This suggests that the stability of SWOF was accomplished through both Pickering and network crystallization. The SWOF exhibited a multi-layered sandwich structure, and the crystal layer thickness increased in oleofoams as the SW concentration rose. The oleofoams containing exceeded 6 wt% SW had better foamability and stability, a more elastic network, and a clear surface texture. Inflatable mayonnaise prepared by 10SWOF had comparable brightness, mouthfeel, and texture to CLFM, but sensitized to temperature. In general, the whipped mayonnaise prepared in this investigation had an acceptable appearance and textural properties and was suitable for foods that do not require heating.

Impacts of alfalfa nutrient concentrate on pellet physical attributes, growth performance, metabolism and nutritional quality of rainbow trout, Oncorhynchus mykiss

This study addresses the escalating demand for aquatic feed by exploring the potential of alfalfa nutrient concentrate (ANC) as feed ingredient for rainbow trout. Test diets contained varying ANC levels (0%, 5%, 10%, 15%, and 20%) to replace fishmeal (32% in the 0% ANC diet) to achieve equal digestible protein and were processed using a cooking extrusion method. Analysis of feed pellets showed that pellet density increased with ANC levels (P < 0.001), resulting in sinking pellets at 20% ANC. Water stability and durability were improved while oil leakage decreased with increasing ANC levels (P < 0.05). Two feeding trials were conducted to test the diets in flow-through water systems with three replicates per diet. The first 10-week trial evaluated their impact on feeding, fecal physical quality, and the apparent digestibility coefficient (ADC) of dietary nutrients in rainbow trout (initial body weight , 18.0 ± 0.2 g). ANC inclusion did not impact the palatability and satiety feed intake of the fish (P > 0.05). However, the ADC of dry matter and phosphorus significantly decreased in fish fed the 20% ANC diet (P < 0.05). The second 9-week trial investigated the growth performance, nutrition quality, and metabolism of rainbow trout (initial body weight, 19.0 ± 0.2 g). While all fish exhibited substantial growth, fish fed diets with 10% to 20% ANC displayed lower specific growth rate and higher feed conversion ratio compared to those fed with 0% or 5% ANC (P < 0.05). The whole body protein content was higher in fish fed 5% ANC compared to all other treatments (P = 0.030). The biochemical parameters of plasma were similar across treatments, except for a decrease in plasma phosphorus levels in fish fed a 10% ANC diet compared to those fed a 0% ANC diet. (P = 0.033). Significant changes were observed in liver metabolism including tricarboxylic acid cycle, amino acid and energy metabolism pathways in fish fed the 20% ANC diet versus the 0% ANC diet (P < 0.05). These results demonstrate that ANC inclusion improved pellet physical quality without impairing feeding behavior and nutritional quality of the fish but inclusion ≥10% in the diet reduced fish growth. This study offers the first comprehensive assessment of the potential of ANC used in fish feed involving feed management, feeding evaluation, and the biological response.

Assessment of Physicochemical attributes and variation in mass volume of Himalayan pears: Computer vision-based modeling

The current study attempts to examine the physicochemical properties of Himalayan pears and envision the relationship between mass and volume with various physical properties. These properties are measured using image processing techniques at different storage days (1st day, 4th day, 7th day, 10th day, and 13th day). The study employs both single and multivariable regression models, including linear, quadratic, rational, and exponential models to establish predictive relationships. Among the single variable models, the length-based linear and rational models demonstrated exceptional suitability for envisioning the mass and volume of pears, achieving higher R2 values of 0.92 and 0.90, respectively. For mass and volume prediction considering combined physical properties, the rational and exponential models exhibited the best fit with higher R2 values of 0.94 and 0.91, accompanied by low RMSE values of 0.217 and 0.141. Consequently, the established relationship between the mass and volume of Himalayan pears with its physical attributes contributes to the development of a faster, more authentic, and accurate grading system.