Search Results (70,229)

Steel structures that support machines and industrial process installations should ideally be flexible, adaptable, and easily reconfigurable. However, in current practice, new profiles are frequently used and discarded whenever layout modifications are required, leading to considerable material waste, increased costs, and environmental burdens. Such practices conflict with the principles of the circular economy, in which reusability is preferable to recycling. This paper presents a life cycle sustainability assessment (life cycle cost, LCC, and life cycle assessment, LCA) applied to six structural typologies: (a) welded IPE profiles, (b) bolted IPE profiles, (c) welded tubular profiles, (d) bolted tubular profiles, (e) clamped IPE profiles with demountable joints, and (f) flanged tubular profiles with demountable joints. The assessment integrates structural calculations with an updatable database of costs, operation times, and service lives, providing a systematic framework for evaluating both economic and environmental performance in medium-load industrial structures (0.5–9.8 kN/m²). Application to nine representative case studies demonstrated that demountable clamped and flanged joints become economically competitive after three life cycles, and after only two life cycles under high-load conditions (9.8 kN/m²). The findings indicate relative cost savings of up to 75% in optimized configurations and carbon-footprint reductions of approximately 50% after three cycles. These results provide quantitative evidence of the long-term advantages of demountable and reconfigurable steel structures. Their capacity for repeated reuse without loss of performance supports sustainable design strategies, reduces environmental impacts, and advances circular economy principles, making them an attractive option for modern industrial facilities subject to frequent modifications. Full article

The complex aquatic environment attenuates light transmission, thereby limiting the detection range of underwater laser systems. To address the challenges of limited operational distance and significant light energy attenuation, this study investigates optimized underwater lighting and imaging applications using a combined tricolor RGB (RED-GREEN-BLUE) white laser source. First, accounting for the attenuation characteristics of water, we propose a power-compensated white laser system based on transmission distance and underwater imaging theory. Second, underwater experiments are conducted utilizing both standard D65 white lasers and the proposed power-compensated white lasers, respectively. Finally, the theory is validated by assessing image quality metrics of the captured underwater imagery. The results demonstrate that a low-power (0.518 W) power-compensated white laser achieves a transmission distance of 5 m, meeting the requirements for a long-range, low-power imaging light source. Its capability for independent adjustment of the three-color power output fulfills the lighting demands for specific long-distance transmission scenarios. These findings confirm the advantages of power-compensated white lasers in long-range underwater detection and refine the characterization of white light for underwater illumination. Full article

A wheeled–legged robot has the advantage of stable and agile movement on flat ground and an excellent ability to overcome obstacles. However, when faced with a narrow footprint, there is a limit to its ability to move. We developed the control moment gyroscope (CMG) unicycle–legged robot to solve this problem. A scissored pair of CMGs was applied to control the roll balance, and the pitch balance was modeled as a double-inverted pendulum. We performed Linear Quadratic Regulator (LQR) control and model predictive control (MPC) in a system in which the control systems in the roll and pitch directions were separated. We also devised a method for controlling the rotation of the robot in the yaw direction using torque generated by the CMG, and the performance of these controllers was verified in the Gazebo simulator. In addition, forward driving control was performed to verify mobility, which is the main advantage of the wheeled–legged robot; it was confirmed that this control enabled the robot to pass through a narrow space of 0.15 m. Before implementing the verified controllers in the real world, we built a CMG test platform and confirmed that balancing control was maintained within $\pm 1^{\circ }$. Full article

Hormone replacement therapy (HRT) has been utilized in clinical practice for decades as a main therapeutic approach for mitigating menopausal symptoms. The symptoms mostly encompass vasomotor and genitourinary issues resulting from the deficiency of estrogen and progesterone. Initially identified as a universally advantageous and indispensable intervention, hormone replacement therapy subsequently became the subject of considerable scientific and clinical debate, especially after the publication of extensive epidemiological studies indicating potential adverse effects associated with cardiovascular and cancer risk. This study aims to reassess the role of HRT in clinical practice by analyzing its historical evolution, expanded clinical uses, and changes in guidelines necessitated by resent scientific studies. Current evidence from clinical studies and meta-analyses unequivocally demonstrates that hormone replacement therapy is the most efficacious treatment for vasomotor and urogenital symptoms, and also acknowledging its potential role in osteoporosis prevention. The administration of HRT requires careful individual assessment, considering the patient’s age, timing of initiation, existence of comorbidities. In this setting, therapy decisions have to be based on a combination of the most up-to-date clinical guidelines, risk stratification, and the patient’s preferences. In conclusion, the assessment of HRT confirms its primary role in reducing menopausal symptoms while also highlighting the imperative for a individual strategy that balances benefits and risks to improve outcomes for women. Full article

This article focuses on the negative evaluation losses resulting from consumers’ dissatisfaction with the traceability level in agricultural product logistics activities. Based on the supply chain (SC) under the “agricultural product cooperative + live-streaming e-commerce” model, and in accordance with previous research, combined with the differences in the dominant role and the bearers of profit and loss in the SC. By applying Stackelberg game theory, different types of decisions are analyzed and solved. The research results show: (1) Centralized decision-making has advantages in terms of traceability level and SC profit performance. (2) In non-centralized decision-making models, when manufacturers bear negative evaluation losses and retailers act as the leaders of the SC, the overall decision-making effect is more ideal. When manufacturers or retailers act as the leaders of the SC and both bear the traceability costs, the decision-making effect is basically the same. (3) The traceability level sensitivity coefficient and the traceability level effect on traceability both have positive effects on the growth of SC profits and the improvement of the traceability level. (4) The maximization of profits for both parties can be achieved through the coordination of contracts. This study can enhance the traceability level of the agricultural product SC, encourage SC members to increase their investment in the traceability, reduce the profit impact from negative evaluations, and provide a reference for the sustainable development of the agricultural product SC. Full article

Alternative housing systems for laying hens, such as the aviary, promote the expression of dustbathing behavior by providing substrate materials to improve their welfare. However, extensive litter areas in aviaries can lead to reduced air quality and increased incidence of diseases, making them unsuitable for deployment in new large cage aviary unit (LCAU) systems in China. Dust baths have advantages in terms of continuous availability, but their design lacks unified standards. This study explored the effects of different areas, shapes (circular and square), and substrate depths (1 cm, 5 cm, 9 cm) of dust baths on dustbathing behavior in LCAU systems by recording digital video. Each LCAU system was initially populated with 305 Jingfen No. 2 laying hens at 50 days of age. The dust baths were initially placed on the bottommost tier at 66 days of age. The results showed that after approximately 3 weeks of adaptation to dustbathing, the average daily proportion of dustbathing hens within the flock stabilized at approximately 10%. A 50 cm diameter circular dust bath could accommodate their dustbathing requirements. Increasing the number of circular dust baths to 2 did not significantly affect the daily proportion of dustbathing hens. Both the circular dust bath and a 5 cm depth substrate resulted in better expression of the hens' side rubbing behavior and the lower frequency of tossing behavior. Full article

Despite advances in diagnostics, the objective and repeatable assessment of patients with neurological deficits (e.g., stroke) remains a major challenge. Modern methods based on artificial intelligence (AI) are of interest to researchers and clinicians in this area. This study presents a comparative analysis of different AI approaches used to analyze gait of stroke patients using a retrospective dataset of 120 individuals. The main objective is to evaluate the effectiveness, accuracy, and clinical relevance of machine learning (ML) and deep learning (DL) models in identifying gait abnormalities and predicting rehabilitation outcomes. Multiple AI techniques—including support vector machines (SVM), random forests (RF), k-nearest neighbors (k-NN), and convolutional neural networks (CNN)—were trained and tested on time-series gait data with spatiotemporal parameters. Performance metrics such as accuracy, precision, recall, and area under the curve (AUC) were used to compare model results. Initial results indicate that DL models, particularly CNNs, outperform traditional ML methods in capturing complex gait patterns and providing reliable classification. However, simpler models showed advantages in interpretability and computational efficiency. This study highlights the potential and shortcomings of AI-based gait analysis tools in supporting clinical decision-making and planning personalized stroke rehabilitation. Full article

The important function of polar lipids in the biochemical chains of photosynthesis, the outstanding biochemical process on our planet, has been mentioned in many publications. Over the last several years, apart from the known function of lipids in creating a matrix for photosynthetic complexes, most attention has been paid to the role of lipids in building up and functioning of the photosynthetic complexes. The lipid molecules are found inside the complexes of photosystem II (PSII), photosystem I (PSI), and cytochrome b₆f (Cyt b₆f) together with other cofactors that accompany proteins and chlorophyll molecules. Super complexes PSII-light-harvesting complex II (PSII-LHCII) and PSI-light-harvesting complex I (PSI-LHCI) also include lipid molecules; part of the lipid molecules is located at the borders between the separate monomers of the complexes. Our interest is in the exact localization of lipid molecules inside the monomers: what are the protein subunits with the lipid molecules in between and how do the lipids contact directly with the amino acids of the proteins? The photosystems include very few classes of all the polar lipids, three groups of glyceroglycolipids, and one group of glycerophospholipids make up the quartet of polar lipids. What are the reasons they have been selected for the role? There are no doubts that the polar heads and the fatty acids chains of these lipids are taking part in the processes of photosynthesis. However, what are the distinct roles for each of them? The advantages and disadvantages of the head groups of lipids from thylakoid membranes and those lipids that for various reasons could not take their place are discussed. Attention is focused on those bound fatty acids that predominate or are characteristic for each class of thylakoid lipids. Emphasis is also placed on the content of each of the four lipids in all photosynthetic complexes, as well as on contacts of head groups and acyl chains of lipids with specific proteins, transmembrane chains, and their amino acids. This article is devoted to the search for answers to the questions posed. Full article

Turn-milling is a relatively new process which combines turning and milling operations, offering a number of advantages such as chip breaking and interrupted cutting, which improves tool life. In addition to providing the capability of producing eccentric forms or shapes, it increases productivity for difficult-to-machine material at lower cost. This study investigates the influence of cutting speed and feed on surface roughness and tool wear in conventional turning and turn-milling of H13 tool steel. The tests were conducted for longitudinal and face machining strategies. It was found that the range of surface roughness in turning is lower than in turn-milling. In longitudinal turning, face-turning, and face turn-milling operations, surface roughness is elevated in the higher feeds. However, the surface roughness in longitudinal turn-milling operations can be reduced by increasing the feed. Although the simultaneous rotation of the tool and workpiece in turn-milling could negatively affect the surface quality, this operation provides the advantage of an interrupted cutting mechanism that produces discontinuous chips. Also, the wear of the endmill in longitudinal and face turn-milling operations is lower than the wear of the inserts used in conventional longitudinal and face turning. Using Response Surface Methodology (RSM), mathematical models were developed for surface roughness and tool wear in each operation. The RSM models developed in this study achieved coefficients of determination (R²) above 90%, with prediction errors below 7% for surface roughness and below 3% for tool wear. The analysis of variance (ANOVA) revealed that the feed and cutting speed are the most influential parameters on the surface roughness and tool wear, respectively, with p-value < 0.05. The experimental results demonstrated that tool wear in turn-milling was reduced by up to 50% compared to conventional turning. Full article

Micro-hydropower technologies are increasingly attracting attention due to their potential to contribute to sustainable energy generation. With the growing global demand for electricity, it is essential to research and innovate in the development of devices capable of harnessing hydroelectric potential through such technologies. In this context, the Archimedes screw generator (ASG) stands out as a device that potentially offers significant advantages for micro-hydropower generation. This study aimed, through a simplified yet effective method, to analyze and determine the simultaneous effects of the number of blades, inclination angle, and flow rate on the torque, mechanical power, and efficiency of an ASG. Computational Fluid Dynamics (CFD) was employed to obtain the torque and perform the hydrodynamic analysis of the devices, in order to compare the results of the optimal geometric and operational characteristics with previous studies. This proposal also helps guide future work in the preliminary design and evaluation of ASGs, considering the geometric and flow conditions that take full advantage of the available water resources. Under the specific conditions analyzed, the most efficient generator featured three blades, a 20° inclination, and an inlet flow rate of 24.5 L/s, achieving a mechanical power output of 117 W with an efficiency of 71%. Full article

Background: Optimizing training load and recovery is crucial for achieving peak performance in competitive wrestling, a sport characterized by high physical, technical, and psychological demands. Methods: This study compared the effects of two different training programs—one emphasizing high-intensity interval training (HIIT) sessions and the other based on traditional volume-oriented training—on both competitive performance and autonomic regulation measured by heart rate variability (HRV). A total of 24 elite wrestlers were divided into two equal groups, each following a different weekly training regimen over a 3-month period. HRV was recorded using a wearable 3-channel ECG Holter before training, immediately after training, and during recovery phases (up to 2 h post-exercise). HRV parameters were analyzed to assess training-induced stress and recovery status. Competitive performance was evaluated using official national championship scores and ranking positions. Results: Both training programs improved competitive performance, the HIIT-based regimen induced greater short-term suppression of parasympathetic activity (RMSSD: −32% vs. −14%; HF power: −40% vs. −18%) and increased sympathetic dominance (LF/HF: +56% vs. +22%) after training. Wrestlers in the HIIT group achieved a mean competition score of 17.92 ± 4.50 points, compared to 15.08 ± 6.26 points in the volume-oriented group. These acute autonomic shifts may provide a higher readiness for intense and explosive actions, which is advantageous in short and dynamic matches. In contrast, the volume-oriented program induced smaller acute autonomic changes but showed a slower recovery to baseline. Conclusions: These findings suggest that HRV-derived measures can serve as sensitive indicators of training load tolerance, recovery capacity, and stress susceptibility in combat sports athletes. This study highlights the value of integrating HRV monitoring into the periodization of combat training to individualize the load, prevent overtraining, and optimize performance outcomes. Full article

Multispectral LiDAR (MSL) systems offer a significant advantage by actively capturing both spatial and spectral information. These systems offer significant promise in supporting the comprehensive analysis and precise classification of underwater targets. In this study, we build an MSL system based on an acousto-optic tunable filter (AOTF) to investigate the feasibility of underwater sphere classification. The MSL prototype features a spectral resolution of 20 nm and 13 spectral channels, covering a range from 560 to 800 nm. Laboratory-based experiments were conducted to evaluate the accuracy of range measurements and the classification performance of the system. The spectral curves of nine distinct spheres acquired by the MSL were utilized for classification using a support vector machine (SVM). The experimental results indicate that classification using multispectral data yields a higher accuracy and Kappa coefficient. Finally, the point cloud acquired from scanning experiments further validated the MSL system’s performance. This finding preliminarily validates the feasibility of multispectral LiDAR for classifying submerged spherical targets. Full article

Agriculture and its allied activities contribute to the primary sector in India and act as the basis for the country’s economy. Available agricultural landholdings are scattered as multiple plots across the country. Land fragmentation has led to problems achieving economies of scale and economies of scope; lower productivity, efficiency, and modernization; loss of biodiversity; and little scope for mechanization and technology. FPOs are small clusters of farmers who collaborate to enhance their bargaining strength through collective procurement, processing, and marketing efforts. To enhance the performance of FPOs at the grassroots level, the engagement of cluster-based business organizations (CBBOs) is vital. Millet FPOs are similar to voluntary farmer groups that are involved in the cultivation and promotion of millets. IIMR-promoted millet FPOs were selected purposively for the present study as they are involved in millet cultivation and farming. A total of 450 millet farmers from 15 FPOs and 3 states were randomly chosen for this action research study. The present research identified 10 key factors and collected farmers’ opinions toward member participation in millet FPOs using interpretive structural modeling. The ISM approach provided a clear understanding of how the selected factors interconnect hierarchically with each other as foundational drivers and dependent outcomes. The results from the MICMAC analysis demonstrated that foundational interventions, such as post-harvest technology availability (V2) and knowledge transfer by KVKs (V5), directly support higher-level objectives. Intermediate factors like economies of scale (V1) and market and credit linkages (V3) transform these services into operational advantages, while the outcome factors of business planning (V8), FPO branding (V7), and bargaining power (V9) emerge as dependent variables. The model demonstrates that V2 catalyzes improvements across the production, market, and institutional domains, cascading through intermediate enablers (V1, V4, V5, V6) to strengthen outcomes (V3, V7, V8, V9, V10). This hierarchy demonstrates that investing in post-harvest technology and complementary extension services is critical for building resilient millet FPOs and enhancing member participation. Full article

Classifying low-concentration Gas Sensor Array (GSA) data is hard due to low SNR, sensor heterogeneity, drift, and small samples. We benchmark time-series-to-image (TS2I) CNNs against time-series classifiers, after reproducing a strong FE-ELM baseline under a shared fold manifest. Using the GSA-LC and GSA-FM datasets, we compare FE-ELM, vector baselines, time-series methods, and TS2I-CNNs with 20 × 5 repeated stratified cross-validation (n = 100). ROCKET delivers the best accuracy on both datasets and is significantly better than TCN and MiniROCKET (paired tests with Holm–Bonferroni, p < 0.05): on GSA-FM, accuracy 0.9721 ± 0.0480 (95% CI [0.9627, 0.9815]) with Macro-F1 0.9757; on GSA-LC, 0.9578 ± 0.0433 (95% CI [0.9493, 0.9663]) with Macro-F1 0.9555. Among image-based models, CNN-RP is the most robust, whereas CNN-GASF lags, especially on GSA-LC. RGB fusion strategies (e.g., with MTF) are dataset-dependent and often inconsistent, and transfer learning with ResNet-18 offers no consistent advantage. Overall, ROCKET ranks first across folds, while CNN-RP is the most reliable TS2I alternative under low-concentration conditions. These results provide a reproducible, fair benchmark for e-nose applications and practical guidance for model selection, while clarifying both the potential and limitations of TS2I. Full article

Heike 88, a new soybean variety developed through strategic hybridization of Heijiao 08-1611 × Heihe 43 followed by pedigree selection, was evaluated across seven locations in Heilongjiang Province from 2019 to 2022. The variety demonstrated stable performance with a 10.3% average yield advantage over regional check varieties and mean yields of 3188 kg ha⁻¹. Principal component analysis revealed that genetic variation accounted for 43.4% and 32.6% of performance variance in the first two components, indicating successful transgressive segregation where the pure line exceeded both parental lines through complementary gene action. Performance relative to parental averages ranged from −20% to +40% across the temperature gradient, demonstrating strong genotype-environment interaction effects. Machine learning analysis identified year effect (13% importance), accumulated temperature (7.6% importance), and oil content (4% importance) as primary yield drivers. Complete resistance to soybean mosaic virous (SMV) and cyst nematode attack was observed across all locations, with excellent gray leaf spot resistance (grades 0–1) maintained under natural pathogen pressure. Seed quality parameters remained stable across environments, with protein content ranging from 41.69% to 42.25% and oil content from 19.74% to 20.13%, indicating minimal environmental effects on compositional traits. Yield stability improved progressively over the evaluation period, with the coefficient of variation decreasing from 18.7% in 2019 to 6.7% in 2022, while absolute yields increased from 2550 to 3200 kg ha⁻¹. These results demonstrate successful exploitation of transgressive segregation for regional adaptation through strategic parent selection and pedigree breeding, supporting commercial deployment in northern China’s challenging production environments while providing methodological guidance for future breeding programs targeting environmental specificity. Full article