Search Results (304)

The urinary sodium-to-potassium (Na/K) ratio is a clinically established predictor of blood pressure and cardiovascular risk. This study aimed to develop and rigorously evaluate machine learning models for estimating the urinary Na/K ratio using four easily obtainable physiological variables: body weight, systolic blood pressure, diastolic blood pressure, and pulse rate. A dataset of 82 participants was analyzed under a nested cross-validation framework to ensure strict generalization assessment. We first designed an attention-based deep learning model (MIDIP: Multi-Integrated Deep Ion Prediction). Although MIDIP showed reduced training error, nested validation revealed performance instability, indicating overfitting in this small-sample setting. We then compared classical machine learning models and ensemble strategies. Among all configurations, simple averaging of Random Forest, Gradient Boosting, and Linear Regression (Group A) achieved the best performance (MAE = 1.756, RMSE = 2.349, R² = 0.390). In contrast, incorporating a Transformer model (Group B) degraded performance (MAE = 1.855, R² = 0.294). Similarly, adaptive weighting (AWE) did not improve accuracy (Group A: MAE = 1.836, R² = 0.266; Group B: MAE = 2.133, R² = 0.035). These results demonstrate that, under limited sample conditions (N = 82), model simplicity and equal-weight ensemble integration provide superior generalization compared to attention-based or adaptively weighted deep architectures. The findings underscore the importance of strict validation and controlled model complexity when developing clinically applicable prediction models from small datasets. Full article

As the electrification of the automotive industry accelerates, the importance of small-scale motors used in applications such as HVAC systems and water pumps is growing. To design small motors that exhibit high efficiency and high output within limited spaces, applying axial flux motors (AFMs) instead of conventional radial flux motors (RFMs) can maximize the power density within the same volume, offering advantages in both weight reduction and miniaturization. This study proposes an optimized end-turn layout design to mitigate back-EMF imbalance in AFMs utilizing PCB stators. Optimization results demonstrated that the structure employing a non-adjacent end-turn layout with equalized average end-turn heights (BCAACB type) exhibited the best performance in terms of average resistance and phase resistance variance, effectively mitigating back-EMF imbalance. The validity of the optimized end-turn structure was verified through finite element analysis (FEA). The analysis confirmed that the motor’s back-EMF balance was improved, and the magnitude of phase resistance was reduced. This reduction led to lower copper loss, thereby increasing overall efficiency. Furthermore, the variance in resistance for each phase was minimized, resulting in enhanced electrical balance. The results of this study are expected to contribute to enhancing the applicability of PCB stators in small motor design. Full article

Background: Fructans are fructose-based polysaccharides with diverse biological activities; however, their direct activity on skin cells remains unresolved. This study investigated the biological activity of fructan extracted from rakkyo (Allium chinense) (RF) and examined its effects on extracellular matrix (ECM) metabolism, particularly collagen and hyaluronan synthesis, in human dermal fibroblasts. Methods: RF was prepared from fresh rakkyo bulbs by aqueous extraction, alkaline clarification, and membrane filtration. The average molecular weight and structural characteristics of RF were analyzed using size-exclusion chromatography and ¹³C NMR spectroscopy. Normal human dermal fibroblasts (NHDFs) were treated with RF by culturing cells in RF-supplemented medium (0.1–1.0 mg/mL). Cell viability and viable cell number were evaluated using the thiazolyl blue tetrazolium bromide and trypan blue exclusion assays, respectively. Expression of ECM-related genes was analyzed by qRT-PCR, and collagen and hyaluronan production were quantified by Sirius Red staining and ELISA. Results: RF had an average molecular weight of approximately 11,500 Da and consisted of nearly equal proportions of inulin- and levan-type fructans. RF (≤1 mg/mL) increased the number of viable cells and markedly upregulated collagen, type I, alpha 1 (COL1A1) and hyaluronic acid synthase 2 (HAS2) expression while downregulating Hyal1 expression. After 9 days of treatment, the cumulative production of type I collagen and hyaluronic acid increased by 3.8- and 1.3-fold, respectively, as compared with controls. Upregulation of lysyl oxidase (LOX) mRNA suggested enhanced collagen cross-linking, whereas MMP-1 showed only modest induction. Conclusions: Rakkyo-derived fructan directly stimulates collagen and hyaluronan synthesis in dermal fibroblasts, likely through regulation of ECM-related genes. These results suggest that rakkyo-derived fructan modulates ECM-related readouts in NHDFs under controlled in vitro conditions. Further validation in more complex skin models and in vivo studies is necessary. Full article

This study evaluated reproductive parameters, parturition characteristics, and early neonatal survival in 42 pregnant Labrador Retriever bitches and their 346 puppies between June and December 2024. The mean age of the bitches was 4.06 ± 1.59 years, and their average body weight was 33.14 ± 3.72 kg. Litter size averaged 8.24 ± 1.88 puppies, with an almost equal sex ratio (50.2% males; 49.8% females). Mean labour duration was 743 min, and intervals between successive births shortened initially before increasing in late parturition. In 57.1% of litters, all puppies were born alive. Early neonatal mortality was low: 0.6% within the first hour and 8.4% by day seven postpartum. A significant association was detected between prolonged parturition and a higher percentage of stillborn puppies (p = 0.001). Maternal body weight showed a substantial negative correlation with the number of live-born puppies (r = −0.554) and a positive correlation with stillbirths (r = 0.499). The exploratory Q coefficient, expressing the ratio between puppy and maternal body weight, differed significantly across survival categories (p = 0.0027), with surviving puppies displaying the highest ratio. Birth order significantly influenced mortality (p = 0.008), with a marked increase from the sixth puppy onwards. No effect of bitch age was observed on parturition length or puppy birth weight (p > 0.05). Overall, these findings suggest that maternal body weight, parturition duration, and birth order are important determinants of neonatal outcomes in Labrador Retrievers and may assist in improving perinatal management practices. Full article

Path planning for large-scale agricultural fields faces challenges such as irregular field shapes, uncertain boundaries, and the need to balance path efficiency, energy consumption, and coverage quality. To address these problems, this research introduces a strategy-aware hierarchical hybrid optimization framework (HANS) for autonomous agricultural operations. This framework introduces a global principal axis extraction method based on Principal Component Analysis (PCA), utilizing the statistical distribution of field boundaries to guide path direction, thereby improving robustness against boundary noise and irregular geometries. The framework integrates Adaptive Large Neighborhood Search (ALNS) for global exploration and Tabu Search (TS) for local optimization, forming a tightly coordinated hybrid structure. The framework further employs a Pareto-set-based decision support selection strategy to solve a multi-objective optimization model encompassing machine kinematics, turning patterns, and energy-aware cost evaluation. This strategy provides three methods: weighted preference-based compromise solution selection, crowding distance-based diversified solution selection, and single-objective extreme value-based dedicated optimization solution selection. To balance the impact of path length, energy consumption, and coverage rate, we assigned equal or nearly equal weights to them (i.e., (0.33, 0.33, 0.34)). Furthermore, the framework incorporates operators and feedback learning mechanisms specific to agricultural coverage path problems to enable adaptive operator selection and reduce reliance on manual parameter tuning. Simulation results under three representative field scenarios show that compared to fixed-direction planning, HANS improves the average coverage rate by 0.51 percentage points and reduces fuel consumption by 4.34%. Compared to Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Tabu Search (TS), and Simulated Annealing (SA), the proposed method shortens the working path length by 0.37–0.83%, improves coverage rate by 0.34–1.11%, and reduces energy consumption by 0.61–1.03%, while maintaining competitive computational costs. These results demonstrate the effectiveness and practicality of HANS in large-scale autonomous farming operations. Full article

This study examines the association between the formal (de jure) adoption of renewable energy source (RES) support instruments and observed RES deployment outcomes across 36 European countries. We assess whether broader legislative adoption—measured by a transparent breadth/coverage index (SIC/OIL) based on binary coding and equal sector weights—correlates with higher RES shares. The empirical design comprises three complementary steps: (i) hierarchical clustering (Ward’s method; Euclidean distance on standardised indicators) to classify countries by legislative adoption profiles; (ii) parallel clustering of countries by RES utilisation profiles using 10 z-score-standardised outcome indicators (total and sectoral RES shares and per capita RES use by source); and (iii) an integrated comparison of both typologies, followed by a cross-sectional regression test of the OIL–RES association. Legislative and utilisation clusters do not systematically coincide, and the baseline regression shows a weak, statistically insignificant association with very low explanatory power (R² = ≈ 0.015), supporting heterogeneity (H1) rather than a universal positive average relationship (H₂). Interpretation is conservative because SIC/OIL captures policy-mix coverage (not budgets, enforcement, or design stringency) and because some low/zero policy entries may reflect limited source coverage. Overall, the findings suggest that observed RES performance is primarily shaped by country-specific structural conditions (resource endowments, economic capacity, and sustained long-term investment), implying that context-sensitive instruments and stronger implementation capacities should complement formal policy adoption. Full article

As space systems evolve towards cis-lunar missions and beyond, the demand for precise yet low-size, -weight, and -power (SWaP) clocks and synchronization methods becomes increasingly critical. We introduce a novel clock synchronization approach based on the Kuramoto oscillator model that facilitates the creation of an ensemble timescale for satellite constellations. Unlike traditional ensembling algorithms, the proposed Kuramoto method leverages nearest-neighbor interactions to achieve collective synchronization. This method simplifies the communication architecture and data-sharing requirements, making it well suited for dynamically connected networks such as proliferated low Earth orbit (pLEO) and lunar or Martian constellations, where intersatellite links may frequently change. Through simulations incorporating realistic noise models for small-scale atomic clocks, we demonstrate that the Kuramoto ensemble can yield an improvement in stability on the order of 1/√N, while mitigating the impact of constellation fragmentation and defragmentation. The results indicate that the Kuramoto oscillator-based algorithm can potentially deliver performance comparable to established techniques like Equal Weights Frequency Averaging (EWFA), yet with enhanced scalability and resource efficiency critical for future spaceborne PNT and communication systems. Full article

In intensive farming systems, broilers are exposed to various stressors that trigger immune stress. Reduced glutathione is known to play a crucial role in modulating immune function. This study investigated the effects of different doses of reduced glutathione on the growth performance, intestinal immune function, and gut microbiota of broilers under immune stress. One-day-old broilers were randomly assigned to five groups: group K (control), group L (lipopolysaccharide), and three glutathione supplementation groups, Y1 (50 mg/kg), Y2 (100 mg/kg), and Y3 (200 mg/kg). Each group had four replicates, with 11 broilers per replicate. On days 16, 18, and 20, broilers in groups L and Y1-Y3 received intraperitoneal injections of 0.5 mg/kg of lipopolysaccharide, while group K received an equal volume of saline. On day 16, the average daily weight gain and final body weight of group Y3 were significantly higher than those of groups K and L, whereas on day 21, the average daily weight gain of group Y3 was still significantly higher than that of group L. On day 21 broilers were slaughtered, and samples were collected. In the jejunal mucosa, group Y3 showed significantly reduced levels of IL-2, IL-4, IL-1β, and TNF-α compared to group L. Additionally, group Y3 exhibited reduced relative expression levels of NF-κB, TLR4, IFN-γ, IL-1β, IL-6, IL-4, TNF-α, and IL-2 mRNA; a decreased abundance of Enterococcus, Proteobacteria, and Actinobacteria; and a restored abundance of Ligilactobacillus, Turicibacter, and Firmicutes to normal levels. These findings suggest that 200 mg/kg of reduced glutathione is the optimal dose for improving the gut microbiota composition and mitigating gut damage caused by immune stress by inhibiting the TLR4/NF-κB signaling pathway. Full article

To address the issues of imprecise user segmentation, inadequate handling of fuzzy evaluation information, and low recommendation accuracy in current electricity retail package recommendations, a novel recommendation method based on K-prototypes clustering and interval-valued intuitionistic fuzzy theory is proposed. First, a multi-dimensional user profile is constructed, incorporating five numerical tags—such as monthly average electricity consumption and monthly load factor—and two categorical tags: industry characteristics and value-added service demand. The K-prototypes algorithm is employed to cluster users, effectively resolving the profile distortion problem caused by the neglect of categorical features in traditional K-means clustering. Second, interval-valued intuitionistic fuzzy numbers are introduced to transform user linguistic evaluations into quantitative indicators. A projection measure-based model is established to objectively determine attribute weights, thereby eliminating subjective weighting bias. Finally, a comprehensive ranking of electricity retail packages is generated by integrating satisfaction levels of similar users and similar measures of new users. The recommendation performance is validated using Root Mean Square Error (RMSE), Kendall’s τ, Normalized Discounted Cumulative Gain (NDCG@5), and Discrimination Index (S). A case study involving users from a region in China demonstrates that the proposed method reduces the Root Mean Square Error (RMSE) to 0.32, which is 31.25% lower than the next best traditional method (K-prototypes + equal weight clustering with RMSE = 0.48), accurately addresses the core demands of diverse user groups, significantly improves recommendation precision and user satisfaction, and exhibits substantial practical application value. Full article

Among various statistical process-control (SPC) methods, control charts are widely employed as essential instruments for monitoring and improving process quality. This study focuses on a new modified exponentially weighted moving-average (New Modified EWMA) control chart that enhances detection capability under integrated and fractionally integrated time-series processes. Special attention is given to the effect of symmetry on the chart structure and performance. The proposed chart preserves a symmetric monitoring configuration, in which the two-sided design ($\mathrm{LCL}>0$) establishes control limits that are equally spaced around the center line, enabling balanced detection of both upward and downward shifts. Conversely, the one-sided version ($\mathrm{LCL}=0$) introduces a deliberate asymmetry to increase sensitivity to upward mean shifts, which is particularly useful when downward deviations are physically implausible or less critical. The efficacy of the control chart utilizing both models is assessed through Average Run Length (ARL). Herein, the explicit formula of ARL is derived and compared to the ARL obtained from the Numerical Integral Equation (NIE) in terms of both accuracy and computational time. The accuracy of the analytical ARL expression is validated by its negligible percentage difference ($\%diff$) in comparison to the results derived using the NIE approach, and the display processing time not exceeding 3 s. To confirm the highest capability, the suggested method is compared to both the classic EWMA and the modified EWMA charts using evaluation metrics such as ARL and SDRL (standard deviation run length), as well as RMI (relative mean index) and PCI (performance comparison index). Since asset values are volatile due to positive and negative market influences, symmetry is crucial in financial monitoring. Thus, symmetric control-chart structures reduce directional bias and better portray financial market activity by balancing upward and downward movements. Finally, examination of US stock prices illustrates performance, employing a symmetrical two-sided control chart for the rapid detection of changes through the new modified EWMA, in contrast to standard EWMA and modified EWMA charts. Full article

Background/Objectives: Nutrition is essential for both physiological and physical health. The study aimed to explore dietary habits, nutritional intake and supplementation in association with the indirect omega-3 index (ω-3I) magnitude in a cohort of professional athletes. Methods: A 3-day food record was used as an approach to document all the dishes and beverages consumed by athletes over three consecutive days. Additionally, in aiming to assess the dietary habits and supplementation as well as the estimated ω-3I, both a food frequency questionnaire and a valid equation proposed by Swiss scientists were applied. The body composition of athletes was assessed using the bioelectrical impedance analysis. Results: Given that carbohydrate-containing foods were relatively frequently consumed by athletes, the average daily carbohydrate content (5.5 g/kg of body weight/day) did not reach the minimum recommended limit. A Western pattern diet applied to professional athletes ensured a sufficient level of protein intake (1.7 g/kg of body weight/day) and resulted in the overconsumption of dietary fat (40.3% of energy intake (EI)), especially saturated fatty acids (FAs) (13.8% of EI). The frequency of the consumption of fish products was considered to fulfill the lowest rank, which in turn, led to the lowest average intakes for polyunsaturated (6.2% of EI), ω-6 (5.7% of EI), and ω-3 (0.3% of EI) FA. Also, the dietary ω-3 FA deficiency generated an unhealthy ω-6/ω-3 FA ratio of 18.4:1 which was not directly related to the intermediate-desirable level (5.5–9.8%) of the estimated ω-3I in a sample of professional athletes. Conclusions: Taking into account the predicted regression model which was adjusted for sports and sex, the estimated ω-3I was significantly and positively associated with the higher consumption of polyunsaturated FA supplementation (β 1.5, 95% confidence interval (CI): 1.3; 1.6, p < 0.001), fish products (β 1.1, 95% confidence interval (CI): 1.0; 1.2, p < 0.001), and the energy percentage obtained from the dietary ω-3 FA (β 0.8, 95% CI: 0.1; 1.6, p = 0.049) in a cohort of professional athletes. Therefore, whilst acknowledging that the increased fish consumption may serve as an equally strong potential predictor for the indirect ω-3I magnitude, the supplementation with polyunsaturated FA also becomes an important strategy for maintaining the optimum ω-3I levels among professional athletes. Full article

Background: premature birth is a significant public health problem, especially in developing countries such as Brazil. Premature newborns require special care from birth, often requiring prolonged hospitalization and continuous monitoring by various specialists after discharge. Infant Mortality among children under five years of age in Brazil is alarming, with prematurity being the main cause of death in this age group. Objectives: we aim to analyze the prevalence and temporal trend of premature live births in the state of São Paulo, Brazil, in the period 2000–2023. Methods: this is an Ecological, Time-Series Study with secondary data on premature live births in the state of São Paulo, Brazil, from 2000 to 2023. The variables in this study are aggregated measures by year. The Annual Percentage Change and the Average Annual Percentage Change in the percentage of premature live births were estimated by Joinpoint regression. Results: the percentage of premature live births in the period 2000 to 2023 was 9.71%. The average annual percentage change showed an increase of 2.30% per year. In the 2010 to 2013 segment, there was an increase of 12.58% per year (p ≤ 0.05), with subsequent stability in the 2013 to 2016 segment (p ≥ 0.05). The largest annual increases occurred in the number of 4 to 6 prenatal consultations and cesarean sections, with an annual percentage change of 4.51% per year and 2.68% per year, respectively. In the birth weight category equal to or greater than 2500 g, there was an increase in premature live births of 2.50% per year. All categories of the variables sex, type of pregnancy, and type of delivery increased in the period 2000–2023 (p ≤ 0.05). Conclusions: given the increase in the prematurity rate in the period 2000–2023, a long-term growing trend is expected in the largest and most developed state in Brazil. Full article

A prolonged dietary phosphorus (P) deficiency can result in reduced growth and vertebral deformities in farmed Atlantic salmon (Salmo salar). Severe deformities can impair swimming and lead to chronic stress associated with muscular fibrotic scarring. Conversely, excess dietary P contributes to farm effluents and environmental pollution. Vertebral centra ash content and mechanical strength both respond rapidly to suboptimal dietary P supply, but measuring all of salmon’s 59 vertebrae is time consuming. As such, this study assessed whether vertebrae from two commonly assessed regions (transitional and caudal) vary in their response to different dietary P levels. Atlantic salmon with an initial average weight of 1.8 kg (December 2022) were fed one of four experimental diets containing an increasing level of inorganic P (6.1–10.7 g/kg total P, 2.3–5.8 g/kg available P). Animals were distributed across 16 sea cages in a quadruplicated design. The regional differences in vertebral centra were assessed at two sampling points: in April 2023 following a slow growth period, and in July 2023 following a fast growth period. The growth of the caudal vertebrae in length surpassed the extension of the transitional vertebrae during the fast growth period. The bone mineralisation measured through vertebral centra ash and mechanical strength was however comparable between the regions, indicating that the rate of mineralisation was adjusted to the growth of the vertebrae. Only two parameters, yield point, which specifies the amount of energy that vertebra can absorb before it is permanently compressed, and toughness, a measure of stress per unit volume required to cause a fracture, showed regional differences. Considering transitional vertebrae, the estimated requirements were 4.1 g/kg available P in April and 4.4 g/kg in July, while the requirements based on caudal vertebrae were 3.7 g/kg in April and 4.6 g/kg in July. As such, both the transitional and caudal regions are equally suitable for a prompt recognition of suboptimal dietary P levels. Full article

The measurement of urban development in Latin American cities has historically relied on one-dimensional models focused on GDP or density, which are insufficient to guide policies in heterogeneous and unequal contexts. This study designs and applies an empirical and comparative model with a socioeconomic approach to evaluate urban development in Lima, Medellín, and San Salvador in 2020–2024. Seventeen indicators that are comparable, objective, and publicly available in the three cities are integrated and normalized using min–max, and composite indices are estimated using three methods: equal weighting, CRITIC, and Entropy. It was found that Lima consistently shows the greatest relative progress (≈6–7%); Medellín consolidates high levels with moderate increases (≈2–4%); and San Salvador records the highest proportional growth under the Entropy method (≈11%). These findings are consistent with citizen perceptions obtained from a survey of 1170 participants (April–August 2025), according to which, on average, 60% recognize the existence of urban growth in the three cities. The proposed model is reproducible and transparent, contributing significantly to year-on-year monitoring and the prioritization of interventions by local and national governments by enabling short- and medium-term readings, in line with the Sustainable Development Goals (SDGs). Full article

This paper examines how air pollution affects the distribution of labor income within firms. We build a within-firm incentive model and show that air pollution, treated as an exogenous shock, reduces production efficiency and increases operating uncertainty. In response, firms compress both employee and executive compensation. Because executive pay carries a larger weight on performance- and equity-based components and is therefore more sensitive to profit volatility, it declines by more, mechanically narrowing within-firm pay dispersion. At the same time, rank-and-file wages display downward rigidity. The result is a “synchronized decline with sharper cuts at the top,” a form of spurious equality. Using 2014–2022 data on non-financial A-share listed firms in China, we find that a 1% increase in air pollution is associated with a 0.37% average decline in labor income. Effects are stronger in labor-intensive firms and in firms with weaker unions. Two-stage least squares estimates indicate real consequences: talent outflows and reduced innovation. By linking air quality to wage setting, human capital, and innovation, our results reveal a sustainability channel through which pollution undermines decent work and inclusive growth—issues of global relevance for urban economies. The mechanisms we document are likely to generalize beyond China and inform integrated policies that combine environmental regulation with labor-market and innovation policy to support a just and sustainable transition. Full article