Search Results (2,927)

The impact of maternal dietary restriction and hydroxytyrosol (HT) supplementation during the last third of gestation on plasma malondialdehyde (MDA) concentration, total antioxidant capacity (ABTS assay), and peripheral blood gene expression related to antioxidant defence, immune response, and energy metabolism was evaluated in beef cows and calves. Two feeding treatments in late gestation (T100% vs. T60% of nutrient requirements) and two HT levels (Control vs. HT at 180 mg/kg of diet) were evaluated during gestation (n = 46 cows) and lactation (n = 37 cows and calves). In pregnant cows, undernutrition led to inhibition of glucose oxidation (PDK4), decreased lipid synthesis (HMGCS1 and SCD) and TLR signalling; T60% cows showed higher plasma MDA (p < 0.05) with no positive effect of HT on antioxidant capacity. Contrarily, during lactation, earlier HT supplementation upregulated antioxidant capacity and modulated antioxidant gene expression (p < 0.05). In calves, there was an increase in SOD1, CAT, and GPX1, especially in the T60%-HT group (p < 0.05). Interestingly, HT supplementation increased glucose transport (SCLA2A1/GLUT1) during pregnancy and lactation (p < 0.05). However, it caused different effects on immunometabolic regulation in both dams and calves, depending on maternal diet. Overall, maternal HT supplementation under restricted nutritional conditions promoted postpartum antioxidant capacity and modulated immune and metabolic gene expression in cows and calves. Full article

Pet owners have become more aware of how their pet’s nutrition can influence the pet’s life expectancy, wellness, and energy. Evaluating the new ingredients claiming better pet health for nutrient contributions requires significant investment and targeted animal commitment while current research aims to find alternative approaches. Research on pet foods in universities is overseen by the Institutional Animal Care and Use Committee, which has restrictions on the use of vertebrates in testing but places no restrictions on the use of insects. The research reported here studied three species of beetles (Coleoptera: Dermestidae), Trogoderma variabile (Ballion), Trogoderma inclusum (LeConte), and Dermestes maculatus (DeGeer) as potential model organisms to evaluate pet food nutrient bioavailability. The larvae of all three species were fed a balanced pet food diet under various laboratory conditions to determine their protein efficiency ratios (PERs) over a 144 h period. Results suggested that D. maculatus larvae reared at 27 °C, 60–65% R.H. (relative humidity), and a photoperiod of 16:8 L:D were the most efficient at converting ingested protein into weight gain with an average protein efficiency ratio (PER) of 1.439. Further experiments were conducted using only D. maculatus larvae with shorter time windows of 48 h and 24 h. The 24 h feeding time was successful and yielded an average PER of 2.476. These findings suggest that D. maculatus larvae may be a useful model organism for pet food bioavailability studies. Full article

This study examines the effects and mechanisms of different Enzyme-Induced Carbonate Precipitation (EICP) treatments on loess structure improvement. The study focuses on ordinary EICP and three modified methods using MgCl₂, NH₄Cl, and CaCl₂. A series of unconfined compressive strength (UCS) tests, scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), and elemental mapping were used to assess both macroscopic performance and microscopic characteristics. The results indicate that ordinary EICP significantly enhances loess particle bonding by promoting calcite precipitation. MgCl₂-modified EICP achieves the highest UCS (820 kPa) due to delayed urea hydrolysis and the formation of aragonite alongside calcite, which results in stronger and more continuous cementation. In contrast, NH₄Cl reduces urease activity and reverses the reaction, which limits carbonate precipitation and weakens structural cohesion. Excessive CaCl₂ leads to a “hijacking mechanism” where hydroxide ions form Ca(OH)₂, restricting carbonate formation and diminishing the overall enhancement. This study highlights the mechanisms behind enhancement, degradation, and diversion in the EICP process. It also provides theoretical support for optimizing loess subgrade reinforcement. However, challenges such as uneven permeability, environmental variability, and long-term durability must be addressed before field-scale applications can be realized, necessitating further research. Full article

The Honeycomb Distribution Network is a new distribution network architecture that utilizes the Smart Power-Exchange Station (SPES) to enable power interconnection and mutual assistance among multiple microgrids/distribution units, thereby supporting high-proportion integration of distributed renewable energy and promoting a sustainable energy transition. To promote the continuous and reliable operation of the Honeycomb Distribution Network, this paper proposes a Hierarchical Switching Control Strategy to address the issues of DC bus voltage (U_dc) fluctuation in the SPES of the Honeycomb Distribution Network, as well as the state of charge (SOC) and charging/discharging power limitation of the energy storage module (ESM). The strategy consists of the system decision-making layer and the converter control layer. The system decision-making layer selects the main converter through the importance degree of each distribution unit and determines the control strategy of each converter through the operation state of the ESM’s SOC. The converter control layer restricts the ESM’s input/output active power—this ensures the ESM’s SOC and input/output active power stay within the power boundary. Additionally, it combines the Flexible Virtual Inertia Adaptive (FVIA) control method to suppress U_dc fluctuations and improve the response speed of the ESM converter’s input/output active power. A simulation model built in MATLAB/Simulink is used to verify the proposed control strategy, and the results demonstrate that the strategy can not only effectively reduce U_dc deviation and make the ESM’s input/output power reach the stable value faster, but also effectively avoid the ESM entering the unstable operation area. Full article

Chemical Looping Combustion (CLC) technology has emerged as a promising approach for carbon capture owing to its CO₂ separation capability, which addresses the pressing challenge of global climate change. Although iron-based oxygen carriers offer economic advantages owing to their abundance and low cost, their limited cyclic stability restricts their industrial deployment. This study focused on optimizing the performance of iron-based oxygen carriers through composite modification with Al₂O₃ and TiO₂. Using Cantera (2.5.0) software and the minimum Gibbs free energy principle, conversion rates and product distributions of Fe₂O₃, Fe₂O₃/Al₂O₃, and Fe₂O₃/TiO₂ were systematically analyzed under varying temperatures (800–950 °C), oxygen carrier-to-fuel molar ratios (O/C = 1–15), and pressures (0.1–1.0 MPa). The optimal conditions were identified as 900 °C, O/C = 8, and 0.1 MPa. After 50 simulation cycles, Fe₂O₃/Al₂O₃ and Fe₂O₃/TiO₂ achieved average total reaction counts of 503 and 543, respectively, substantially exceeding 296 cycles for Fe₂O₃. The results indicated that Al₂O₃ and TiO₂ improved cyclic stability via physical support and structural regulation mechanisms, thereby offering a practical carrier composite modification strategy. This study provides a theoretical basis for the development of high-performance oxygen carriers and supports the industrial application of CLC technology for efficient carbon capture and emission mitigation. Full article

Aggregation-induced emission (AIE) luminogens are materials that exhibit enhanced light emission in the aggregated state, primarily due to the restriction of intramolecular motions, which reduces energy loss through non-radiative pathways. Tetraphenylethylene (TPE) and its derivatives are prominent examples of AIE-active materials, owing to their ease of synthesis, tuneable photophysical properties, and strong aggregation tendencies. This review provides an overview of the fundamental AIE mechanisms in TPE-based systems, with a focus on the role of restricted intramolecular rotation (RIR) and π-twisting in governing their emission behaviour. It explores the influence of molecular structure, electronic configuration, and intermolecular interactions on fluorescence properties. Furthermore, recent advances in practical applications of TPE-based AIE luminogens are highlighted across a spectrum of biological imaging domains, including cellular imaging, tissue and in vivo imaging, and organelle-targeted imaging. Additionally, their integration into multifunctional and theranostic platforms, along with the development of stimuli-responsive and self-assembled systems, underscores their versatility and expanding potential in biomedical research and diagnostics. This review aims to offer valuable insights into the design principles and functional potential of TPE-based AIE luminogens, guiding the development of next-generation materials for advanced bioimaging technologies. Full article

Sulfur dioxide not only affects the ecological environment and endangers health but also restricts economic development. The reasonable prediction of sulfur dioxide emissions is beneficial for formulating more comprehensive energy use strategies and guiding social policies. To this end, this article uses a multiparameter combination optimization gray prediction model (PGM(1, N)), which not only defines the difference between the sequences represented by variables but also optimizes the order of all variables. To this end, this article proposes an improved algorithm for the Dung Beetle Optimization (DBO) algorithm, namely, CSLDDBO, to optimize two important parameters in the model, namely, the smoothing generation coefficient and the order of the gray generation operators. In order to overcome the shortcomings of DBO, four improvement strategies have been introduced. Firstly, the use of a chain foraging strategy is introduced to guide the ball-rolling beetle to update its position. Secondly, the rolling foraging strategy is adopted to fully conduct adaptive searches in the search space. Then, learning strategies are adopted to improve the global search capabilities. Finally, based on the idea of differential evolution, the convergence speed of the algorithm was improved, and the ability to escape from local optima was enhanced. The superiority of CSLDDBO was verified on the CEC2022 test set. Finally, the optimized PGM(1, N) model was used to predict China’s sulfur dioxide emissions. From the results, it can be seen that the error of the PGM(1, N) model is the smallest at 0.1117%, and the prediction accuracy is significantly higher than that of other prediction models. Full article

Allopregnanolone (allo) and isoallopregnanolone (isoallo) are neuroactive steroid epimers that differ in hydroxyl orientation at carbon three. Allo is a potent GABA-A receptor agonist, while isoallo acts as an antagonist, influencing brain function through their interconversion. Their metabolism varies across brain regions due to enzyme distribution, with AKR1C1–AKR1C3 active in the brain and AKR1C4 restricted to the liver. In rats, AKR1C9 (liver) and AKR1C14 (intestine) perform similar roles. Beyond AKR1Cs, HSD17Bs regulate steroid balance, with HSD17B6 active in the liver, thyroid, and lung, while HSD17B10, a mitochondrial enzyme, influences metabolism in high-energy tissues. Our current data obtained using the GC-MS/MS platform show that allo and isoallo in rats undergo significant metabolic conversion, suggesting a regulatory role in neurosteroid action. High allo levels following isoallo injection indicate brain interconversion, while isoallo clears more slowly from blood and undergoes extensive conjugation. Metabolite patterns differ between brain and plasma—allo injection leads to 5α-DHP and isoallo production, whereas isoallo treatment primarily yields allo. Human plasma contains mostly sulfate/glucuronided steroids (2.4–6% non-sulfate/glucuronided), whereas male rats exhibit much higher free steroid levels (29–56%), likely due to the absence of zona reticularis. These findings highlight tissue-specific enzymatic differences, which may impact neurosteroid regulation and CNS disorders. Full article

As a type of electrochemical energy storage, the vanadium redox flow battery system (VRFB) is currently one of the most promising large-scale energy storage methods. Nevertheless, the ability to accurately estimate the state of charge (SOC) is one of the critical factors restricting the commercialization of VRFBs. This review summarizes the estimation methods for the SOCs of VRFBs used by scholars in the past 10 years, comprehensively discusses the main factors affecting the accuracy of SOC estimation, and discusses the direct measurement methods, combined with modeling filter estimation methods and data-driven SOC estimation approaches currently investigated by mainstream scholars. Although several recent literature reviews describe the current modeling and estimation methods for VRFBs, there has been relatively little attention paid to the more common equivalent circuit modeling methods and parameter identification approaches. This review mainly focuses on common equivalent circuit model (ECM) modeling methods and filter estimation algorithms using modeling, and it summarizes their advantages and disadvantages. Finally, a description of potential research directions for VRFB modeling and SOC estimation in the future is presented. Full article

This paper proposes optimal sliding mode fault-tolerant control for multiple robotic manipulators in the presence of external disturbances and actuator faults. First, a quantitative prescribed performance control (QPPC) strategy is constructed, which relaxes the constraints on initial conditions while strictly restricting the trajectory within a preset range. Second, based on QPPC, adaptive gain integral terminal sliding mode control (AGITSMC) is designed to enhance the anti-interference capability of robotic manipulators in complex environments. Third, a critic-only neural network optimal dynamic programming (CNNODP) strategy is proposed to learn the optimal value function and control policy. This strategy fits nonlinearities solely through critic networks and uses residuals and historical samples from reinforcement learning to drive neural network updates, achieving optimal control with lower computational costs. Finally, the boundedness and stability of the system are proven via the Lyapunov stability theorem. Compared with existing sliding mode control methods, the proposed method reduces the maximum position error by up to 25% and the peak control torque by up to 16.5%, effectively improving the dynamic response accuracy and energy efficiency of the system. Full article

The self-starting capability of straight-bladed H-type Darrieus Vertical Axis Wind Turbines (VAWTs) remains a major constraint for deployment, particularly in urban, low speed, and turbulent environments. We conducted a systematic review of technological strategies to improve self-starting, grouped into five categories: (1) aerodynamic airfoil design, (2) rotor configuration, (3) passive flow control, (4) active flow control, and (5) incident flow augmentation. Searches in Scopus and IEEE Xplore (last search 20 August 2025) covered the period from 2019 to 2026 and included peer-reviewed journal articles in English reporting experimental or numerical interventions on H-type Darrieus VAWTs with at least one start-up metric. From 1212 records, 53 studies met the eligibility after title/abstract screening and full-text assessment. Data were synthesized qualitatively using a comparative thematic approach, highlighting design parameters, operating conditions, and performance metrics (torque and power coefficients) during start-up. Quantitatively, studies reported typical start-up torque gains of 20–30% for airfoil optimization and passive devices, about 25% for incident-flow augmentation, and larger but less certain improvements (around 30%) for active control. Among the strategies, airfoil optimization and passive devices consistently improved start-up torque at low TSR with minimal added systems; rotor-configuration tuning and incident-flow devices further reduced start-up time where structural or siting constraints allowed; and active control showed the largest laboratory gains but with uncertain regarding energy and durability. However, limitations included heterogeneity in designs and metrics, predominance of 2D-Computational Fluid Dynamics (CFDs), and limited 3D/field validation restricted quantitative pooling. Risk of bias was assessed using an ad hoc matrix; overall certainty was rated as low to moderate due to limited validation and inconsistent uncertainty reporting. In conclusions, no single solution is universally optimal; hybrid strategies, combining optimized airfoils with targeted passive or active control, appear most promising. Future work should standardize start-up metrics, adopt validated 3D Fluid–Structure Interaction (FSI) models, and expand wind-tunnel/field trials. Full article

With the rapid advancement of electronic devices, Internet of Things (IoT) technology has become increasingly integrated into everyday life. However, its broader development has been restricted by challenges related to long-term maintenance and the frequent need for power source replacements. Among the available power supply solutions, thermoelectric power generation has garnered significant interest due to its high reliability. Nevertheless, the widespread application of thermoelectric generators (TEGs) in IoT remains limited due to their relatively low conversion efficiency and structural fragility. This review systematically summarizes recent strategies aimed at enhancing the output performance and durability of TEGs through improvements in manufacturing processes and performance optimization techniques. It highlights several fabrication methods capable of endowing devices with superior flexibility and reliability, including screen printing, chemical vapor deposition (CVD), and electrospray deposition. Additionally, we discuss two key approaches for improving power generation performance: advanced material selection and multi-mechanism hybridization. Finally, the article explores the applications of TEGs in thermal energy harvesting from wearable devices, ambient environments, and aerospace fields, demonstrating their substantial potential to provide sustainable energy for IoT devices. Full article

Deep reinforcement learning (DRL)-based HVAC control has shown clear advantages over rule-based and model predictive methods. However, most prior studies remain limited to HVAC-only optimization or simple coordination with operable windows. Such approaches do not adequately address buildings with fixed glazing systems—a common feature in high-rise offices—where the lack of operable windows restricts adaptive envelope interaction. To address this gap, this study proposes a multi-zone control framework that integrates HVAC systems with electrochromic windows (ECWs). The framework leverages the Q-value Mixing (QMIX) algorithm to dynamically coordinate ECW transmittance with HVAC setpoints, aiming to enhance energy efficiency and thermal comfort, particularly in high-consumption buildings such as offices. Its performance is evaluated using EnergyPlus simulations. The results show that the proposed approach reduces HVAC energy use by 19.8% compared to the DQN-based HVAC-only control and by 40.28% relative to conventional rule-based control (RBC). In comparison with leading multi-agent deep reinforcement learning (MADRL) algorithms, including MADQN, VDN, and MAPPO, the framework reduces HVAC energy consumption by 1–5% and maintains a thermal comfort violation rate (TCVR) of less than 1% with an average temperature variation of 0.35 °C. Moreover, the model demonstrates strong generalizability, achieving 16.58–58.12% energy savings across six distinct climatic regions—ranging from tropical (Singapore) to temperate (Beijing)—with up to 48.2% savings observed in Chengdu. Our framework indicates the potential of coordinating HVAC systems with ECWs in simulation, while also identifying limitations that need to be addressed for real-world deployment. Full article

Weaning stress in piglets severely restricts swine production efficiency due to growth retardation, immune suppression, and intestinal dysfunction. This study investigated the effects of dietary pyrroloquinoline quinone (PQQ) on 36 weaned piglets (22 ± 1 days old) allocated to six groups (0, 1, 2, 4, 8 and 16 mg/kg PQQ) for 28 days. Results showed that 4–8 mg/kg PQQ improved average daily gain and feed conversion ratio (p < 0.05), enhanced serum immunoglobulin (IgA, IgG) and antioxidant enzyme (T-AOC, SOD, GSH-Px) levels, and reduced inflammatory cytokines (TNF-α, IL-1β, IL-6) (p < 0.05). PQQ modulated gut microbiota, increasing Lactobacillus and Bifidobacterium, and elevated short-chain fatty acid production (p < 0.05). Metabolomic analysis revealed upregulated tricarboxylic acid (TCA) cycle intermediates (citric acid, isocitric acid and malic acid), indicating improved mitochondrial function (p < 0.05). Overall, 4 mg/kg PQQ optimally alleviates weaning stress by enhancing immunity, gut health, and energy metabolism, offering a promising strategy for piglet nutrition. Full article

The current green building assessment system suffers from issues such as insufficient coverage of smart indicators, significant biases in subjective weighting, and weak dynamic adaptability, which restrict the scientific promotion of green buildings. This study focuses on the gaps in the quantitative assessment of smart technologies in China’s green building evaluation standards (such as the current Green Building Evaluation Standard). While domestic standards are relatively well-established in traditional dimensions like energy conservation and environmental protection, there are fragmentation issues in the assessment of smart technologies such as the Internet of Things (IoT) and BIM. Moreover, the coverage of smart indicators in non-civilian building fields is significantly lower than that of international systems such as LEED and BREEAM. This study determined the basic framework of the evaluation indicator system through the Delphi method. Drawing on international experience and contextualized within China’s (GB/T 50378-2019) standards, it systematically integrated secondary indicators including “smart security,” “smart energy,” “smart design,” and “smart services,” and constructed dual-drive evaluation dimensions of “greenization + smartization.” This elevated the proportion of the smartization dimension to 35%, filling the gap in domestic standards regarding the quantitative assessment of smart technologies. In terms of research methods, combined weighting using the Analytic Hierarchy Process (AHP) and entropy weight method was adopted to balance subjective and objective weights and reduce biases (the resource conservation dimension accounted for 39.14% of the combined weights, the highest proportion). By integrating the grey clustering model with the whitening weight function to handle fuzzy information, evaluations were categorized into four grey levels (D/C/B/A), enhancing the dynamic adaptability of the system. Case verification showed that Project A achieved a comprehensive evaluation score of 5.223, with a grade of B. Among its indicators, smart-related ones such as “smart energy” (37.17%) and “smart design” (37.93%) scored significantly higher than traditional indicators, verifying that the system successfully captured the project’s high performance in smart indicators. The research results indicate that the efficient utilization of resources is the core goal of green buildings. Especially under pressures of energy shortages and carbon emissions, energy conservation and resource recycling have become key priorities. The evaluation system constructed in this study can provide theoretical guidance and technical support for the promotion, industrial upgrading, and sustainable development of green buildings (including non-civilian buildings) under the dual-carbon goals. Its characteristic of “dynamic monitoring + smart integration” forms differentiated complementarity with international standards, making it more aligned with the needs of China’s intelligent transformation of buildings. Full article