Search Results (131)

Active vehicle systems integrate electromechanical actuators and advanced control strategies to improve driving comfort and safety. Their development requires coordinated mechanical, electrical, and software design, supported by early evaluation of system performance and driver acceptance. The automotive industry accelerates the development process by adopting multi-stage simulation workflows, from Model-in-the-Loop to hardware-in-the-loop and track testing, progressively reducing the virtualization level. Final testing stages require actuators with programmable control units, often unavailable in commercial products. This paper proposes a research-oriented steering actuator based on the modification of an existing system by introducing an additional torque sensor after the steering wheel. Results indicate that the additional compliance significantly alters the passive steering response, while the impact on active EPS operation is negligible, confirming the suitability of the modified actuator for experimental research applications. Full article

In the context of climate change and increased frequency of droughts, summer supplementation of grazing cattle may improve productivity and resilience of pastoral systems. However, the provision of supplements may increase the risk of heat stress in cattle. This study aimed to evaluate the productive and physiological response of grazing steers supplemented during summer. Three independent studies were conducted over three summers (2020–2023). In each experiment, steers grazing native grasslands with access to shade were allotted to one of two treatments: control (CONT) and supplementation (SUPPL), in a completely randomized block design. SUPPL steers were group-fed in the morning three days per week with an energy–protein ration at a level of 1.98% body weight (BW) on days of feeding. Pasture attributes, animal performance, respiration rate (RR), and body temperature (BT) were analyzed using a mixed model. According to the temperature–humidity index, cattle were exposed to heat stress 32% of the time. Summer supplementation increased average daily gain and final body weight of steers. Although supplementation temporarily increased BT (morning) and RR (afternoon), daily average RR and BT were similar for both treatments. These findings show that summer supplementation improves animal performance of grazing steers without increased risk of severe heat stress. These results are aligned with the concept of sustainable livestock intensification, which aims to enhance animal source foods to feed a growing population without causing collateral animal welfare issues. Full article

The agri-food sector is undergoing a profound transformation driven by the combined pressures of climate change, resource scarcity, policy frameworks, and evolving consumer expectations. In this context, digital and green technologies have emerged as key enablers of more sustainable, transparent, and resilient food systems. This review provides a comprehensive overview of the conceptual foundations, technological drivers, and policy frameworks shaping the digital and green transition of the agri-food sector. Digital technologies—including precision agriculture, sensing and data acquisition systems, artificial intelligence, blockchain, and data platforms—are examined in relation to their role in improving resource-use efficiency, traceability, and decision-making across the food value chain. In parallel, green technologies and sustainable practices in food production, processing, and waste management are discussed, with emphasis on resource optimization, circular economy approaches, and environmental impact reduction. This review further highlights the role of European and global policy frameworks, such as the European Green Deal and the Farm to Fork strategy, in steering technological adoption and aligning innovation with sustainability objectives. By synthesizing technological, environmental, and policy perspectives, this work underscores the importance of integrated digital–green strategies for achieving long-term sustainability, competitiveness, and resilience in agri-food systems. Full article

Background: Citrus components potentially suppress adipogenic differentiation and lipid accumulation, and exhibit anti-inflammatory and antioxidant effects. We hypothesized that the bioactive compounds in Citrus junos Sieb ex Tanaka (yuzu) fruit peel can alter the systemic metabolism and productivity of beef cattle. Methods: Japanese Brown (JBR) steers were fed with a diet supplemented with 2.5% yuzu peel during the last month of the finishing period. To investigate the effect of dietary yuzu supplementation (DYS) on beef and liver metabolism, we explored the metabolomic profiles of longissimus thoracis (LT, loin) muscle at 14 d postmortem using capillary electrophoresis (CE-TOF/MS) and high-performance liquid chromatography time-of-flight mass spectrometry (LC-TOF/MS). Results: The DYS treatment enhanced the beef fat score compared to that recorded in beef in the no-DYS (None) group (p = 0.050); however, the other carcass quality traits were not significantly different between the DYS and None groups. CE-TOF/MS and LC-TOF/MS revealed 242 and 107 annotated peaks, respectively, for the LT muscle. DYS significantly increased 9(S)-hydroxyoctadecadienoic acid (9-HODE, a beef flavor precursor), cyclo(-Leu-Pro), spermidine, asymmetric dimethylarginine, and 7α-hydroxycholesterol levels and reduced 2-ethylhydracrylic acid (2-EHAA), γ-tocopherol, coenzyme Q10 (CoQ10), sphingomyelin(d18:1/16:0), Cys-Gly, Tyr-Arg, and palmitoylcarnitine levels in postmortem LT muscle (p < 0.050). Concomitantly, in the fresh liver, DYS increased acetyl-CoA, 6-phosphogluconic acid, S-methylglutathione, ATP, ribulose 5-phosphate, and ADP levels and suppressed the content of thiamine, Ala-Ala, riboflavin, and ascorbate 2-sulfate (p < 0.050). Conclusion: Collectively, yuzu ingredients activated ATP production in the liver through the elevation of hepatic energy metabolism primarily in the citrate cycle and β-oxidation, and potentially altered muscle metabolism, including linoleic acid oxidation, FAD-mediated electron transport chain, and isoleucine catabolism, as demonstrated in the reduced accumulation of 2-EHAA and CoQ10 in DYS beef. Moreover, DYS likely affects the gut microbiome by enhancing the production of cyclo(-Leu-Pro), an antimicrobial dipeptide. Full article

This study examines a comprehensive class of coupled nonlinear $\varrho$-Hilfer fractional neutral impulsive integro-differential systems with mixed delays and non-local initial conditions. The primary contribution of this study is the creation of a unified analytical framework that encompasses coupled interactions, neutral-type dependencies, and impulsive disturbances, which have been studied separately by researchers. We utilize the Banach contraction principle and Krasnoselskii’s fixed-point theorem to provide suitable conditions for the existence and uniqueness of solutions within the product space of piecewise continuous weighted functions. In addition to existence, we examine Ulam–Hyers–Rassias (UHR) stability using a generalized Gronwall inequality, which guarantees the system’s robustness against functional perturbations. We also develop a controllability framework and a feedback control law that steer the system towards the desired terminal states. The theoretical results are supported by a numerical simulation using a complex kernel, implemented via a modified predictor-corrector algorithm, which validates the practical effectiveness of the proposed control and stability outcomes. Full article

The Ralstonia solanacearum species complex (RSSC) is a globally significant plant pathogenic bacterium. Given the lack of effective chemical controls, phage therapy has emerged as a promising biocontrol alternative. While combining phages with antibiotics can counteract phage resistance, RSSC may still evolve concurrent resistance to both agents. However, the fitness consequences and underlying mechanisms of such resistance remain unclear. In this study, a novel RSSC phage was isolated to experimentally investigate the trade-offs between resistance and virulence in evolved strains. Compared to the wild-type, phage-resistant, antibiotic-resistant, and dual-resistant mutants showed no significant differences in growth rate, exopolysaccharide and lipopolysaccharide production. However, their motility, soil survival, and biofilm formation were significantly impaired, with the most severe decline observed in the dual-resistant mutants. Furthermore, phage-resistant strains exhibited enhanced antibiotic resistance, while antibiotic-resistant strains displayed cross-resistance. The antibiotic resistance gene bla_OXA-249 was upregulated only in antibiotic-resistant strains. In phage-resistant bacteria, the abortive infection system was activated. A reduction in bacterial cell numbers post-infection indicated that phage resistance limits phage propagation via a “suicidal” mechanism. These findings reveal that resistance evolution in RSSC carries substantial fitness costs and highlight phage steering as a novel strategy for designing phage agents. Full article

Current generative AI systems primarily utilize a prompt–response interaction model that restricts user intervention during the creative process. This lack of granular control creates a significant disconnect between user intent and machine output, which we define as the “Agency Gap”. This paper introduces the Agency-First Framework (AFF), which combines cognitive engineering and co-active design approaches to formally define human-AI collaboration. This is operationalized through the development of ten Generative AI Agency (GAIA) Heuristics, a systematic method for evaluating agency-centric interactions within stochastic generative settings. By translating the theoretical layers of the AFF into measurable criteria, the GAIA heuristics provide the necessary instrument for the empirical auditing of existing systems and the guidance of agency-centric redesigns. Unlike existing assistive AI guidelines that focus on output-level usability, the AFF establishes agency as a first-class design construct, enabling mid-process intervention and the steering of the model’s latent reasoning trajectory. Validation of the AFF was conducted through a two-tiered empirical evaluation: (1) an expert heuristic audit of state-of-the-art platforms, such as ChatGPT-o1 and Midjourney v6, which achieved high inter-rater reliability, and (2) a controlled redesign study. The latter demonstrated that agency-centric interfaces significantly enhance the Sense of Agency and Intent Alignment Accuracy compared to baseline prompt-response models, even when introducing a deliberate increase in task completion time—a phenomenon we describe as “productive friction” or an intentional interaction slowdown designed to prioritize cognitive engagement and user control over raw speed. Overall, the findings suggest that the restoration of meaningful user agency requires a shift from “seamless” system efficiency towards “productive friction”, where controllability and transparency within the generative process are prioritized. The major contribution of this work is the provision of a scalable, empirically validated framework and set of heuristics that equip designers to move beyond prompt-centric interaction, establishing a methodological foundation for agency-preserving generative AI systems. Full article

Plant-parasitic nematodes (PPNs) cause big crop losses globally. Safe/reliable methods for their durable management strategies can harness various beneficial relationships among the plant immune system and related microbiomes. Molecular mechanisms basic to these relations reveal wide arrays of significant roles for plant-healthy growth. This review focuses on such relations of microbiomes to prime and immunize plants against PPNs. It also highlights molecular issues facing PPN-resistant varieties with possible solutions such as genetic breeding/engineering, grafting, PPN-antagonistic root exudates, and novel resistant cultivars. These issues call for optimal uses of various widespread groups of microbiomes. Related plant signaling hormones and transcription factors that regulate gene expression and modulate nematode-responsive genes to ease positive/negative adaptation are presented. Exploring PPN-resistance genes, their activation mechanisms, and signaling networks offers a holistic grasp of plant defense related to biotic/abiotic factors. Such factors relevant to systemic acquired resistance (SAR) via plant–microbe interactions to manage PPNs are stressed. The microbiomes can be added as inoculants and/or steering the indigenous rhizosphere ones. Consequently, SAR is mediated by the accumulation of salicylic acid and the subsequent expression of pathogenesis-related genes. To activate SAR, adequate priming and induction of plant defense against PPNs would rely on closely linked factors. They mainly include the engaged microbiome species/strains, plant genotypes, existing fauna/flora, compatibility with other involved biologicals, and methods/rates of the inoculants. To operationalize improved plant resistance and the microbiome’s usage, novel actionable insights for research and field applications are necessary. Synthesis of adequate screening techniques in plant breeding would better use multiple parameters (molecular and classical ones)-based ratings for PPN-host suitability designation. Sound statistical analyses and interpretation approaches can better identify genotypes with high-level, stable resistance to PPNs than the commonly used ones. Linking molecular mechanisms to consistent field relevance can be progressed via dissemination of many advanced techniques. The CRISPR/Cas9 system has been effective in knocking out both the OsHPP04 gene in rice to confer resistance against Meloidogyne graminicola and the GhiMLO3 gene in cotton to minimize the Rotylenchulus reniformis reproduction. Its genetic modifications in crops synthesized “transgene-free” PPN-resistant plants without decreased growth/yield. Characterizing microbiome species/strains needed to prime and immunize plants requires better molecular tools for fine-scale taxonomic resolution than the common ones used. The former can distinguish closely related ones that exhibit divergent phenotypes for key attributes like stability and production of enzymes and secondary metabolites. As PPN-control strategies via tritrophic interactions are more sensitive to the relevant settings than chemical nematicides, it is suggested herein to test these settings on a case-by-case basis to avoid erratic/contradictory results. Moreover, expanding the use of automated systems to expedite detection/count processes of PPN and related microbes with objectivity/accuracy is discussed. When PPNs and their related microbial distribution patterns were modeled, more aspects of their field distributions were discovered in order to optimize their integrated management. Hence, the feasibility of site-specific microbiome application in PPN–hotspot infections can be evaluated. The main technical challenges and controversies in the field are also addressed herein. Their conceptual revision based on harnessing novel techniques/tools is direly needed for future clear trends. This review also engages raising growers’ awareness to leverage such strategies for enhancing plant resistance and advancing the microbiome role. Microbiomes enjoy wide spectrum efficacy, low fitness cost, and inheritance to next generations in durable agriculture. Full article

While creative Artificial Intelligence (AI) tools offer unprecedented creative power, their outputs often create a “personalization gap” by converging towards a generalized “average aesthetic” that ignores nuanced user preferences. This study addresses this challenge with a proof-of-concept computational framework to model and predict subjective color choices, aiming to make creative systems more human-centered. Our dual-track methodology attempts to decouple user preference into “inherent aesthetic profiles” and “contextual design decisions.” Through a dual-level study with 111 participants, we quantified inherent aesthetics into a vector library and trained a Gradient Boosting Decision Tree (GBDT) model on contextual data to predict design choices. The model achieved a predictive accuracy of 40.8%, and a grouped permutation importance analysis revealed the Product Category (Importance = 0.416) as the dominant predictor, providing evidence that design context is paramount. Crucially, a subsequent exploratory user validation study, analyzed with a linear mixed-effects model, showed our personalized recommendations were rated as significantly more satisfying (β = 1.278, p < 0.001) than those of a non-personalized baseline. This research provides a foundational framework for modeling subjective preference by distinguishing between stable traits and dynamic choices, offering a potential pathway to steer creative AI beyond generic outputs towards more personal and context-aware creative partners. Full article

Gastrodia elata is a fully mycoheterotrophic orchid whose tuber development depends on carbon delivered by Armillaria fungi. Its formal inclusion in China’s “medicine and food homology” catalog has intensified demand for cultivated tubers combining high yield with consistent bioactive quality. Here, we tested whether Armillaria mellea strains steer host carbon allocation between biomass accumulation and phenolic glycoside biosynthesis. Using a standardized EPS symbiotic cultivation system (AM1, AM2, AM3; n = 3 biological replicates per strain), we integrated agronomic traits with widely targeted metabolomics and RNA-seq transcriptomics, including weighted gene co-expression network analysis (WGCNA). AM3 produced the highest tuber yield and higher primary carbon status (PCAI), but lower gastrodin/parishin-type phenolic glycosides and lower allocation efficiency (BER), whereas AM1 showed a quality-dominant profile with significantly higher BER. WGCNA highlighted an AM3-associated module enriched in starch-biosynthetic genes, and PCAI was strongly negatively correlated with the weighted Parishin-Gastrodin Index (wPGI) across samples (n = 9), consistent with a carbohydrate-storage versus phenolic-glycoside trade-off. These results indicate that fungal strain identity functions as an external regulator of source–sink dynamics in G. elata, supporting “precision symbiosis” for food-grade versus medicinal-grade production. Full article

Horticultural facilities can boost crop yields and quality. However, their structures, costs, and resource efficiency vary significantly. Many facility operators prioritize short-term economic gains at the expense of long-term investments in energy efficiency and environmental management, ultimately leading to increased energy consumption and higher greenhouse gas emissions. A systems-based assessment of tomato production is essential for optimizing resource use. This study integrated emergy analysis (EMA) and life cycle assessment (LCA) to evaluate the sustainability of three tomato production systems: polytunnels, solar greenhouses, and glass greenhouses. The Results demonstrated that polytunnels exhibited the best environmental performance, with the lowest environmental loading ratio (ELR, 19.06) and environmental final index (EFI, 1.62). Solar greenhouses showed the best environmental composite index (ECI), outperforming others in mitigating potential environmental impacts. Glass greenhouses imposed the greatest environmental pressure (ELR, 168.51), primarily due to substantial natural gas consumption and infrastructure investment. Scenario analyses revealed that environmental performance across all systems could be significantly enhanced through shortening transport distance, extending the service life of construction materials, and managing energy use. The maximum reduction potentials for the environmental composite index (ECI)were 23.80% for polytunnels, 18.60% for solar greenhouses, and 19.90% for glass greenhouses. This study confirms that polytunnels are the most environmentally friendly option, and targeted management strategies can effectively steer facility-based agriculture toward a more sustainable trajectory. Full article

Wheel load is a critical information source reflecting the status of vehicle load distribution and motion. Yet, existing in-wheel motor products are primarily designed as propulsion units and inherently lack the load-sensing capabilities required by intelligent vehicles. To address this research gap, this paper presents a novel intelligent electric drive wheel (i-EDW) with an integrated transmission system and a load-sensing unit (LSU). The i-EDW adopts an Axial Flux Permanent Magnet Synchronous Motor (AFPMSM), while the integrated LSU ensures high-precision measurement of six-dimensional wheel forces and moments. According to this multi-axis force information, a real-time estimation and stability control method based on the tire–road friction circle concept is proposed. Instead of the complex decoupling and multi-objective optimization with the multi-actuator systems, this paper focuses on minimizing the tire load rate of i-EDWs, which significantly advances the state of the art in terms of calculation efficiency and respond speed. To validate this theoretical framework, a full-vehicle model equipped with four i-EDWs is developed. In the MATLAB R2022A/Simulink co-simulation environment, a virtual prototype is tested under typical driving scenarios, including the straight-line acceleration and double-moving-lane (DML) steering. The simulation results prove a reliable safety margin from the friction circle boundaries, laying a solid foundation for precise motion control and improved system robustness in future intelligent vehicles. Full article

Integrated crop grazing systems can improve farm profitability due to enterprise complementarity. Utilizing the supply of N from legumes, livestock manure, and plant residues will result in improving grain yield and quality. A long-term 12-year integrated systems study evaluated continuous spring wheat (HRSW-CTRL) with spring wheat (HRSW-ROT) grown in a five-crop rotation: (1) spring wheat, (2) seven-species cover crop, (3) forage corn, (4) field pea/forage barley mix, and (5) sunflower. Yearling beef cattle steers grazed the field pea/forage barley mix, unharvested corn, and a seven-species cover crop. Spring wheat was marketed as a cash crop. Contrary to expectations, HRSW-ROT did not significantly increase grain yield or improve quality over HRSW-CTRL. Improved soil fertility was observed in the HRSW-ROT plots throughout the study relative to SOM, N, P, and K. However, the rotation with grazing management significantly reduced input costs but resulted in negligible gross and net returns over the 12-year period. Year-to-year weather variability was the cause of the differences between the two production management methods. Full article

With the advancement of intelligent technologies, industrial production systems are being profoundly transformed by artificial intelligence algorithms. To address persistent challenges, such as cargo swing and low operational efficiency during the lifting processes of all-terrain cranes, this research investigates an intelligent control algorithm designed for swing suppression and high-stability payload trajectory control. Firstly, a nonlinear dynamic model of the crane system was derived using the Euler–Lagrange formulation based on a simplified three-dimensional representation. A linear time-varying model predictive control (LTV-MPC) strategy was then designed to incorporate real-time feedback during luffing and slewing motions to monitor the payload’s swing state. On this basis, the controller predicts the desired trajectory and applies negative feedback to adjust the control input, thereby steering the system toward the optimal trajectory and aligning it with the target path. Secondly, a comparative analysis was conducted among four scenarios: the natural swing state of the payload and three control strategies—LTV-MPC, sliding mode control (SMC), and PID control—under both single-input and dual-input conditions. Finally, an experimental platform was established, employing the YOLOv12 algorithm for real-time detection and trajectory tracking of the suspended payload. The experimental results validate the effectiveness of LTV-MPC in suppressing cargo swing. Under single-input control, LTV-MPC achieved the best performance in both stabilization time (3.05 s for luffing condition one and 1.15 s for luffing condition two) and steady-state error (0.003–0.007°). The swing angle, θ₁, was reduced by 91.9%, 54.2%, and 59.3% compared to the natural swing state, SMC, and PID, respectively. In dual-input control, LTV-MPC attained a steady-state error of only 0.0008° under “luffing condition two,” while during slewing operations, it also outperformed SMC and PID in both settling time (26.05 s) and precision (0.008°). Full article

Mitigating enteric methane emissions through diet formulation remains a significant challenge in cattle nutrition. This study developed a system to evaluate the methane production potential of feeds, expressed as the effective ruminal methane production rate (eRMR, mL/g dry matter [DM]), using a discontinuous in vitro ruminal fermentation system using rumen fluid. Sixteen concentrate feeds and two forages were tested, with a reference diet (ryegrass straw:corn:corn gluten feed = 1:1:1) included in each batch to standardize conditions and account for associative effects among feeds. Test feeds were incubated with the reference diet in closed bottles under strictly anaerobic conditions. Methane and total gas production were measured at 2, 4, 6, and 24 h, and true dry matter digestibility was calculated after 6 and 24 h. For each batch, sample feed values were corrected and standardized using those of the reference diet. The eRMR value was calculated by integrating a differential equation with parameters incorporating ruminal digestion and passage dynamics. The test feed eRMR values ranged from 1.2 mL/g DM (soybean meal) to 56.7 mL/g DM (soybean hull), with the reference diet at 14.8 mL/g DM. Evaluation of feed eRMR using data from two in vivo studies demonstrated strong correlations between predicted diet-specific eRMR values and measured methane emissions from Hanwoo steers (r = 0.93 and 0.85). This system, incorporating rumen dynamics with a reduced sampling schedule, provides a precise and practical tool for predicting in vivo enteric methane production and optimizing diet formulations to mitigate methane emissions from cattle. Full article