Search Results (13,330)

Background: University students are particularly vulnerable to psychological distress due to the transitional nature of this life phase and increasing academic, social, and financial pressures. Accumulating evidence indicates that lifestyle behaviors—especially nutrition and physical activity—play a critical role in shaping mental health, cognitive functioning, and overall well-being in this population. Methods: The objective of this scoping review was to systematically map the literature on the combined impacts of diet and physical activity on psychological well-being among university students. Following PRISMA-ScR guidelines, an initial search of three major databases (PubMed, Sciencedirect, and Wiley) yielded 718 articles. After a multi-stage screening process, 39 articles of various designs (including cross-sectional, interventional, and review studies) focusing on non-clinical student populations were included. The studies were then thematically analyzed. Results: While most research explored isolated behaviors, a smaller set of integrated studies revealed synergistic effects, reporting enhanced outcomes in mental health and quality of life. Notably, several articles proposed practical strategies—such as app-based tools, structured wellness initiatives, and interdisciplinary educational programs—as effective means to support healthier habits. Conclusions: The evidence strongly suggests that universities should prioritize holistic, multi-component wellness strategies over siloed, single-behavior initiatives. Developing integrated programs that combine nutritional education and physical activity support represents a practical and effective approach to enhance student well-being. Full article

Sustainable agriculture supports environmental protection, climate change mitigation, and forage security to meet the growing demands of livestock production. Given the critical role of macro- and microelements in animal health, diversified and balanced feed production is essential and can be achieved through the sustainable integration of legumes and cereals. This research evaluated the impact of soybean–common millet intercropping and biofertilizer application on the elemental composition and yield performance of forage biomass. Three intercropping patterns were tested: S1M1—alternating rows, S2M2—alternating two-row strips, and S2M4—alternating two-row soybean with four-row millet strips, alongside monoculture controls. The biofertilizer Coveron (BF) was also assessed. The S2M2 combination provided the highest land equivalent ratios for both fresh and dry biomass (1.10 and 1.12, respectively), despite a reduction in millet yield. Considering the elements, the S2M2 combination notably enhanced the accumulation of Ca and B (by 13.4% and 13.0%, respectively, compared to S1) in the soybean vegetative part and Cr and Mn in the reproductive part (by 53.0% and 17.1%, respectively). In contrast, sole soybean showed the highest P levels in both vegetative (3.45 mg kg⁻¹) and reproductive parts (4.56 mg kg⁻¹). Al accumulation was reduced in intercropped millet. The S1M1 combination increased Mg and S concentrations in both parts of millet biomass (up to 17.3% and 18.4% in the vegetative part, compared to M1). While BF generally had a limited impact on forage biomass yield and elemental accumulation, it increased Mg, P, and S concentrations in soybean pods, as well as concentrations of B, Mn, and Mo in the panicle, simultaneously decreasing P, Cr, and Zn concentrations in the vegetative part of millet. Accordingly, soybean–common millet intercropping in the S2M2 configuration offers a sustainable solution for efficient land utilization and element-enriched forage production. Full article

Forecasting electricity consumption is one of the most important scientific and practical tasks in the field of electric power engineering. The forecast accuracy directly impacts the operational efficiency of the entire power system and the performance of electricity markets. This paper proposes algorithms for source data preprocessing and tuning XGBoost models to obtain the most accurate forecast profiles. The initial data included hourly electricity consumption volumes and meteorological conditions in the power system of the Republic of Tatarstan for the period from 2013 to 2025. The novelty of the study lies in defining and justifying the optimal model training period and developing a new evaluation metric for assessing model efficiency—financial losses in Balancing Energy Market operations. It was shown that the optimal depth of the training dataset is 10 years. It was also demonstrated that the use of traditional metrics (MAE, MAPE, MSE, etc.) as loss functions during training does not always yield the most effective model for market conditions. The MAPE, MAE, and financial loss values for the most accurate model, evaluated on validation data from the first 5 months of 2025, were 1.411%, 38.487 MWh, and 16,726,062 RUR, respectively. Meanwhile, the metrics for the most commercially effective model were 1.464%, 39.912 MWh, and 15,961,596 RUR, respectively. Full article

This study examines the causal impact of China’s New Energy Demonstration City construction policy on corporate energy consumption. The results demonstrate that this policy effectively reduces corporate energy consumption. The policy significantly decreases the consumption of coal, natural gas, and diesel. Although the policy significantly reduces energy consumption in both local state-owned enterprises (SOEs) and non-SOEs, its effect does not show statistically significant variation across different types of controlling shareholders. The energy-saving effect is particularly pronounced in the following industries: Manufacturing, Electricity, Heat, Gas, and Water Production & Supply, Wholesale & Retail Trade, Information Technology Services, Leasing & Business Services, and Water Conservancy, Environment, and Public Infrastructure Management. The policy operates through multiple channels: internal mechanisms including direct innovation effect, accelerated green M&As effect as well as digital empowerment effect, and external moderators including marketization level and green finance environment. The findings yield important insights for scholars, policymakers and corporate stakeholders. Full article

Additive manufacturing involves numerous independent parameters, often leading to inconsistent print quality and necessitating costly trial-and-error approaches to optimize input variables. Machine learning offers a solution to this non-linear problem by predicting optimal printing parameters from a minimal set of experiments. Using Fused Deposition Modeling (FDM) as a case study, this work develops a machine learning-powered process to predict porosity defects. Specimens in two geometrical scales were 3D-printed and CT-scanned, yielding raw datasets of grayscale images. A machine learning image classifier was trained on the small-cube dataset (~2200 images) to distinguish exploitable images from defective ones, averaging over 97% accuracy and correctly classifying more than 90% of the large-cube exploitable images. The developed preprocessing scripts extracted porosity features from the exploitable images. A repeatability study analyzed three replicate specimens printed under identical conditions, and quantified the intrinsic process variability, showing an average porosity standard deviation of 0.47% and defining an uncertainty zone for quality control. A multi-layer perceptron (MLP) was independently trained on 1709 data points derived from the small-cube dataset and 3746 data points derived from the large-cube dataset. Its accuracy was 54.4% for the small cube and increased to 77.6% with the large-cube dataset, due to the larger sample size. A rigorous grouped k-fold cross-validation protocol, relying on splitting data per cube, strengthened the ML algorithms against data leakage and overfitting. Finally, a dimensional scalability study further assessed the use of the pipeline for the large-cube dataset and established the impact of geometrical scaling on defect formation and prediction in 3D-printed parts. Full article

Despite significant advances in understanding the genetics of Parkinson’s disease (PD) and Parkinsonism, the diagnostic yield remains low. Pathogenic variants of GBA1, which encodes the lysosomal enzyme β-glucocerebrosidase and causes recessive Gaucher dis-ease, are recognized as the most important genetic risk factor for PD in heterozygous carriers. This study focuses on the functional genomics of rare genetic variations in other lysosomal hydrolytic enzymes genes in patient-derived fibroblasts. We examined 49 early-onset PD patients using whole exome sequencing and in silico panel analysis based on a curated PD gene list. Two patients were found to carry the p.Asp313Tyr variant in the X-linked GLA gene (encoding GALA, typically associated with Fabry disease), and one patient carried the p.Arg419Gln variant in GLB1 (encoding β-Gal, linked to the recessive GM1 gangliosidosis and mucopolysaccharidosis type IVB). The in silico study of both variants supports a potentially damaging impact on the encoded protein function and structural destabilization. Additional candidate variants were found related to lysosomes, Golgi apparatus and neurodegeneration, suggesting a multifactorial contribution to the disease. However, none of these variants met diagnostic standards. Functional assays showed a significant decrease in GALA expression and partial retention of the enzyme in the trans-Golgi network in fibroblasts with GLA:p.Asp313Tyr, while altered Golgi morphology was observed in fibroblasts with GLB1:p.Arg419Gln. Moreover, all patients exhibited abnormalities in lysosomal morphology, altered lysosomal pH, and impaired autophagic flux. Our findings suggest that rare, heterozygous variants in lysosomal-related genes, even when individually insufficient for monogenic disease, can converge to impair lysosomal homeostasis and autophagic flux in EOPD. The underlying genetic and cellular heterogeneity among patients emphasizes the importance of combining genetic and functional approaches to better understand the mechanisms behind the EOPD, which could enhance both diagnosis and future treatments. Full article

For Linear Position Transducers (LPTs) to represent an ideal tool for velocity-based training, it needs to be both valid and reliable. Multiple studies assessed the reliability of LPT yet wrongfully incorporated biological variability. Moreover, all studies investigating validity conclude a negative impact of horizontal displacement, therefore constraining LPT use to solely multi-joint movement. The objectives were to assess the validity and the reliability of (1) the Tendo Sport LPT in a linear setting presenting almost no biological variability, and (2) an equation allowing the analysis of angular movement. (1) A weight of 10 kg was dropped vertically 100 times and both time and position measurement from the LPT were compared to motion equation. (2) Angular movements were performed first with a bike wheel and then by a human shoulder. The angles estimated with the equation, from LPT output, were compared to the angle measured from 3D motion capture. In the linear settings, bias, ULOA and LLOA are, respectively, equal to −0.008 s, +0.012 s and −0.016 s if errors come solely from the time measurement and 0.011 m, 0.029 m and −0.025 m if errors come solely from the distance. It is likely that error could come from both the time and the distance measurements. In the angular settings, the bike wheel condition yields excellent reliability (ICC = 0.9999) and good validity (RMSD = 9.12°), while the shoulder condition yields high validity (RMSD = 2.49°). LPT can be used to investigate angular kinematics in certain conditions described in this article and yield valid, reliable results for angles below 120°. Full article

This study details a biorefinery approach to valorize Dosidicus gigas squid pen waste. The process starts with the enzymatic deproteinization of squid pens, which prove effective with both Alcalase and Novozym, with the latter exhibiting a slightly higher efficiency to yield a material with 73% chitin content. Subsequent alkaline hydrolysis produces highly deacetylated chitosan (>90% degree of deacetylation), followed by controlled depolymerization to obtain polymers with molecular weights ranging from 50 to 251 kDa. Both native and depolymerized chitosan exhibit antimicrobial activity against Escherichia coli and Bacillus cereus, with B. cereus demonstrating greater resistance to chitosan compared to E. coli. The research also explores the bioconversion of deproteinization and deacetylation effluents. Deproteinization effluents prove superior in sustaining microbial growth, supporting comparable growth and lactic acid production for human probiotic strains (Lactobacillus plantarum and Leuconostoc mesenteroides) when substituting commercial peptones. Marine bacteria (Pseudomonas fluorescens and Phaeobacter sp.) show lower productivity. Integrating these processes into a biorefinery framework enables the conversion of 1 kg of dry squid pens into 350 g of chitosan, and facilitates the production of 937–949 g of lactic acid using human lactic acid bacteria cultures in media formulated with squid pen-derived effluents, glucose, yeast extract, and mineral salts. This integrated approach highlights the potential for maximizing resource utilization from squid pen waste, reducing environmental impact and generating high-value bioproducts. Full article

Edible mushrooms are increasingly recognized for their high nutritional value and contribution to a healthy diet. Among them, Agaricus bisporus is the most commercially important species in Europe and North America. However, the environmental impact of traditional peat use in A. bisporus cultivation necessitates the development of sustainable alternatives, given the ecological significance of peatlands. When evaluating casing materials, it is essential to consider not only yield but also other critical factors influencing marketability, such as nutritional value, appearance, and texture. This systematic review examines seventeen studies published between 1989 and 2025 that investigated various peat substitutes while assessing a range of quality criteria. The findings were categorized into seven groups, encompassing both chemical composition and phenotypic characteristics of the fruiting bodies. Most studies focused on the organic and inorganic content of the fruiting bodies, followed by measurements of size and weight. Some alternative casings, for example, increased dry matter contents, which indicates a high solid substance content, such as of proteins or minerals. However, this was not always beneficial, as it could negatively affect texture. Overall, the reviewed studies demonstrate that different casing materials can directly influence quality parameters, and even minor adjustments in casing composition can enhance fruiting body quality. Full article

The agro-industrial sector is a key pillar of the global economy, playing a central role in the supply of food, energy, and industrial inputs. However, its production chain generates significant amounts of residues and by-products, which, if not properly managed, may cause considerable environmental impacts. In this context, the search for alternatives to reuse these materials is essential, particularly when they can be converted into high-value products. One promising application is their use as a nutrient source for microorganisms in high-value biotechnological processes, such as the production of L-Asparaginase, an important enzyme used both in mitigating acrylamide formation in foods and as a biopharmaceutical in Acute Lymphoblastic Leukemia therapy. This approach offers a sustainable and competitive pathway, combining robust, scalable, and economical enzyme production with waste valorization and circular economy benefits. Although interest in developing more sustainable processes is growing, supported by international agreements and strategies for the valorization of agricultural residues, important challenges remain. The variability and impurity of residues pose significant challenges for producing biological products for the pharmaceutical and food industries. In addition, meeting regulatory requirements is essential to ensure product safety and traceability, while achieving high yields is crucial to maintain production viability compared to conventional media. Overcoming these barriers is critical to enable industrial-scale application of this approach. This review provides a residue-centered revision of the most relevant agro-industrial by-products used as substrates for L-asparaginase production, systematically comparing their compositional characteristics, fermentation strategies, and reported yields. Additionally, we present a novel SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis that critically examines the technical, regulatory, and economic challenges of implementing residue-based processes on an industrial scale. Full article

Maize (Zea mays) is a key crop, with its growth impacted by drought stress. Accurate, non-destructive assessment of drought severity is crucial for precision agriculture. VIS/NIR reflectance spectroscopy is widely used for estimating plant parameters and detecting stress. However, the relationship between key parameters—such as chlorophyll and water content—and VIS/NIR spectra under drought conditions in maize remains unclear, lacking comprehensive models and validation. This study aims to develop a non-destructive and accurate method for predicting chlorophyll and water content in maize leaves under drought stress using VIS/NIR spectroscopy. Specifically, maize leaf reflectance spectra were collected under varying drought stress conditions, and the effects of different spectral preprocessing methods, dimensionality reduction techniques, and machine learning algorithms were evaluated. An optimal data processing pipeline was systematically established and deployed on an edge computing unit to enable rapid, non-destructive prediction of chlorophyll and water content in maize leaves. The experimental results demonstrated that the combination of stepwise regression (SR) for feature selection and a stacking regression model achieved the best performance for chlorophyll content prediction (${\mathrm{R}}_{\mathrm{p}}^2$ = 0.8740, RMSE_p = 0.2768). For leaf water content prediction, random forest (RF) feature selection combined with a stacking model yielded the highest accuracy (${\mathrm{R}}_{\mathrm{p}}^2$ = 0.7626, RMSE_p = 4.12%). This study confirms the effectiveness and potential of integrating VIS/NIR spectroscopy with machine learning algorithms for monitoring drought stress in maize, offering a valuable theoretical foundation and practical reference for non-destructive crop physiological monitoring in precision agriculture. Full article

This study develops an incompressible two-phase flow solver based on the open-source OpenFOAM platform, employing the volume-of-fluid (VOF) method to track the gas–liquid interface and utilizing the MULES algorithm to suppress numerical diffusion. This study provides a comprehensive investigation of the spreading dynamics of droplet pairs near walls, along with the presentation of a corresponding mathematical model. The numerical model is validated through a two-dimensional axisymmetric computational domain, demonstrating grid independence and confirming its reliability by comparing simulation results with experimental data in predicting drConfirmedoplet collision, spreading, and deformation dynamics. The study particularly investigates the influence of surface wettability on droplet impact dynamics, revealing that increased contact angle enhances droplet retraction height, leading to complete rebound on superhydrophobic surfaces. Finally, a mathematical model is presented to describe the relationship between spreading length, contact angle, and Weber number, and the study proves its accuracy. Analysis under logarithmic coordinates reveals that the contact angle exerts a significant influence on spreading length, while a constant contact angle condition yields a slight monotonic increase in spreading length with the Weber number. These findings provide an effective numerical and mathematical tool for analyzing the spreading dynamics of droplet pairs. Full article

This study evaluated the effects of citric acid by-product (CABP), either alone or in combination with fibrolytic enzyme (F) and Lactobacillus spp. (L), in broiler diets. A total of 160 one-day-old male Arbor Acres broiler chicks (average initial body weight 43.0 ± 0.16 g) were randomly assigned to four CABP-based diets (4 replicates × 10 birds each): 12% CABP, CABP+F (0.05%), CABP+L (0.025%), and CABP+FL (0.05% F + 0.025% L). Birds were fed for 35 days in three phases: starter (days 1–10), grower (days 11–24), and finisher (days 25–35). Compared with the CABP-only group, broilers receiving CABP+F, CABP+L, or CABP+FL exhibited higher body weight and weight gain during the finisher and overall phases (p < 0.05). Carcass traits did not differ significantly among treatments, although meat hardness was reduced in the CABP+FL group (p < 0.05). Additive-supplemented groups also showed changes in intestinal morphology, with a lower villus height-to-crypt depth ratio compared with CABP alone. Red blood cell counts were not different between CABP and CABP+L, while hepatic enzyme activities (ALT, AST, ALP) remained unchanged across treatments, indicating no adverse effects on liver function. Overall, supplementation of CABP-based diets with fibrolytic enzymes and/or Lactobacillus spp. improved broiler performance and certain meat quality traits relative to CABP alone, without negative impacts on liver health or carcass yield. However, as no conventional corn–soy control diet was included, the results should be interpreted as comparisons within CABP-based diets. Full article

Closed hydroponic systems for strawberries (Fragaria × ananassa Duch.) are infrequently used because the crop is highly sensitive to salt accumulation and prone to root diseases, resulting in yield reduction. This study investigated semi-closed hydroponic systems using various drainage recycling ratios (30%, 50%, and 70% of drainage EC) to determine their impact on yield, fruit quality, and antioxidant properties. Recycling at moderate levels (30–50%) effectively maintained ionic balance, particularly with respect to K/N and K/Ca ratios, which enabled stable yields and increased fruit weight similar to the control (open hydroponic system) group. Conversely, a high recycling ratio (70%) led to ionic imbalances—characterized by increased K/N ratios and higher concentrations of Na⁺, Cl⁻, and SO₄²⁻—that were associated with decreased fruit size. Measures of antioxidant capacity, such as total phenol and flavonoid content, ferric reducing antioxidant power, and DPPH activity, were not significantly influenced by the recycling ratio alone. Nevertheless, the relatively elevated antioxidant activity observed at the 70% recycling level indicates a mild ionic and osmotic stress response likely caused by increased salt concentration. Changes related to the cropping system season, rather than ion variations from recycling, exerted a stronger influence on antioxidant accumulation. In summary, moderate drainage recycling facilitates optimal fruit production without negatively affecting quality, while excessive recycling may increase antioxidant activity but leads to reduced yields. The results provide practical recommendations for optimizing nutrient reuse in semi-closed strawberry hydroponic systems. Full article

A transition metal-free synthesis of 1,2,5-trisubstituted 1H-indoles by a deprotonation–S_NAr cyclization sequence from 1-aryl-2-(2-fluoro-5-nitrophenyl)ethan-1-one (deoxy-benzoin) Schiff bases is reported. The starting deoxybenzoins were prepared by Friedel-Crafts acylation of activated aromatic compounds by 2-(2-fluoro-5-nitrophenyl)acetyl chloride with AlCl₃ or the corresponding acid with (CH₃SO₂)₂O. The Schiff bases were generated by slow distillation of toluene (18–24 h) from a heated solution of each deoxybenzoin (1 equiv) with a benzyl- or phenethylamine, a high-boiling aliphatic amine, or an aniline derivative (5 equiv). Subsequent addition of N,N-dimethylformamide, 2 equiv of anhydrous K₂CO₃, and heating at 90–95 °C for 18–24 h completed the synthesis. Benzyl-, phenethyl-, and high-boiling amines gave excellent yields while the heating requirements for the initial condensation made volatile aliphatic amines difficult to use and gave low yields. Aniline reactivities correlated with substituent-derived base strength, although modified conditions allowed some yields to be improved. Several anticipated competing processes had minimal impact on the outcome of the cyclizations. Full article