Search Results (4,783)

Semi-humid subtropical montane regions face the dual pressures of climate change and water scarcity, making it essential to understand how soil carbon–water coupling varies among forest types. Focusing on seven representative forest types in the central Yunnan Plateau, this study analyzes the spatial distribution, trade-offs, and drivers of soil organic carbon storage (SOCS) and soil water storage (SWS) within the 0–60 cm soil layer, using sloping rainfed farmland (SRF) as a reference. We hypothesize that, relative to SRF, both SOCS and SWS increase across forest types; however, the direction and strength of the SOCS–SWS trade-off differ among plant communities and are regulated by litter traits and soil structural properties. The results show that SOCS in all forest types exceeded that in SRF, whereas a significant increase in SWS occurred only in ACF. Broadleaf stands were particularly prominent: SOCS rose most in the 23 yr SF and the 20 yr ACF (274.44% and 256.48%, respectively), far exceeding the 9–60 yr P. yunnanensis stands (44.01%–105.32%). Carbon–water trade-offs varied by forest type and depth. In conifer stands, SWS gains outweighed SOCS and trade-off intensity increased with stand age (RMSD from 0.48 to 0.53). In broadleaf stands, SOCS gains were larger, with RMSD ranging from 0.21 to 0.45 and the weakest trade-off in SF. Across depths, SOCS gains exceeded SWS in 0–20 cm, whereas SWS gains dominated in 40–60 cm. Regression analyses indicated a significant negative SOCS–SWS relationship in conifer stands and a significant positive relationship in 0–20 cm soils (both p < 0.05), with no significant correlations in other forest types or depths (p > 0.05). Correlation results further suggest that organic matter inputs, N availability, and soil physical structure jointly regulate carbon–water trade-off intensity across forest types and soil depths. We therefore recommend prioritizing native zonal broadleaf species, as well as protecting SF and establishing mixed conifer–broadleaf stands, to achieve synergistic improvements in SOCS and SWS. Full article

Visible near-infrared (VNIR) spectroscopy offers a cost-effective solution to quantify the spatiotemporal dynamics of soil organic carbon (SOC), especially in the context of rapid advances in spectra-based local modeling approaches using large-scale soil spectral libraries. And yet, direct temporal transferability of VNIR spectroscopic modeling (applying historical models to new spectral data) and its capability to monitor temporal changes in SOC remain underexplored. To address this gap, this study uses the LUCAS Soil dataset (2009 and 2015) from France to evaluate the effectiveness of localized spectral models in detecting SOC changes. Two local learning algorithms, memory-based learning (MBL) and GLOBAL-LOCAL algorithms, were adapted to integrate spectral and soil property similarities during local training set selection, while also incorporating LUCAS 2009 soil measurements (clay, silt, sand, CEC) as covariates. These adapted local learning algorithms were then compared against global partial least squares regression (PLSR). The results demonstrated that localized models substantially outperformed global PLSR, with MBL achieving the highest accuracy for croplands, grasslands, and woodlands (R² = 0.72–0.79, RMSE = 4.73–20.92 g/kg). Incorporating soil properties during the local learning procedure reduced spectral heterogeneity, leading to improved SOC prediction accuracy. This improvement was particularly pronounced after excluding organic soils from grasslands and woodlands, as evidenced by 13.3–21.1% decreases in the RMSE. Critically, for SOC monitoring, spectrally predicted SOC successfully identified over 70% of samples experiencing significant SOC changes (>10% loss or gain), effectively capturing the spatial patterns of SOC changes. This study demonstrated the potential of localized spectral modeling as a cost-effective tool for monitoring SOC dynamics, enabling efficient and large-scale assessments critical for sustainable soil management. Full article

We experimentally investigate the structural, magnetic, transport, and electronic properties of two d⁵ iridate double perovskite materials La₂BIrO₆ (B = Mg, Zn). Notably, despite similar crystallographic structure, the two compounds show distinctly different magnetic behaviors. The M = Mg compound shows an antiferromagnetic-like linear field-dependent isothermal magnetization below its transition temperature, whereas the M = Zn counterpart displays a clear hysteresis loop followed by a noticeable coercive field, indicative of ferromagnetic components arising from a non-collinear Ir spin arrangement. The local structure studies authenticate perceptible M/Ir antisite disorder in both systems, which complicates the magnetic exchange interaction scenario by introducing Ir-O-Ir superexchange pathways in addition to the nominal Ir-O-B-O-Ir super-superexchange interactions expected for an ideally ordered structure. While spin–orbit coupling (SOC) plays a crucial role in establishing insulating behavior for both these compounds, the rotational and tilting distortions of the IrO₆ (and MO₆) octahedral units further lift the ideal cubic symmetry. Finally, by measuring the Ir-L₃ edge resonant inelastic X-ray scattering (RIXS) spectra for both the compounds, giving evidence of spin–orbit-derived low-energy inter-J-state (intra t_2g) transitions (below ~1 eV), the charge transfer (O 2p → Ir 5d), and the crystal field (Ir t_2g → e_g) excitations, we put forward a qualitative argument for the interplay among effective SOC, non-cubic crystal field, and intersite hopping in these two compounds. Full article

As a critical technological foundation for electric vehicles, power battery state estimation primarily involves estimating the State of Charge (SOC), the State of Health (SOH) and the Remaining Useful Life (RUL). This paper systematically categorizes battery state estimation methods into three distinct generations, tracing the evolutionary progression from single-state to multi-state cooperative estimation approaches. First-generation methods based on equivalent circuit models offer straightforward implementation but accumulate SOC-SOH estimation errors during battery aging, as they fail to account for the evolution of microscopic parameters such as solid electrolyte interphase film growth, lithium inventory loss, and electrode degradation. Second-generation data-driven approaches, which leverage big data and deep learning, can effectively model highly nonlinear relationships between measurements and battery states. However, they often suffer from poor physical interpretability and generalizability due to the “black-box” nature of deep learning. The emerging third-generation technology establishes transmission mechanisms from microscopic electrode interface parameters via electrochemical impedance spectroscopy to macroscopic SOC, SOH, and RUL states, forming a bidirectional closed-loop system integrating estimation, prediction, and optimization that demonstrates potential to enhance both full-operating-condition adaptability and estimation accuracy. This progress supports the development of high-reliability, long-lifetime electric vehicles. Full article

Background: Trelegy Ellipta is a widely prescribed triple inhaler therapy for chronic obstructive pulmonary disease (COPD). Although its clinical efficacy is well established, evidence on sex-specific differences in adverse event (AE) profiles from real-world pharmacovigilance data remains limited. In addition, some AEs may reflect underlying disease characteristics rather than drug exposure, which complicates interpretation of safety signals. Objective: To explore sex-related differences in AEs associated with Trelegy Ellipta using the FDA Adverse Event Reporting System (FAERS). The study aimed to identify potential safety signals while accounting for alternative explanations, including comorbidity burden and disease-related variation. Methods: We retrospectively analyzed FAERS reports from January 2018 to April 2025, identifying 4555 AEs attributed to Trelegy Ellipta. Events were coded by System Organ Class (SOC) and stratified by patient sex. Frequencies were compared between male (n = 1621) and female (n = 2934) patients using chi-square tests, and associations were expressed as reporting odds ratios (RORs) with 95% confidence intervals (CIs). Results: Male patients more frequently reported hypertension (63.4% vs. 47.0%; p = 0.01), pneumonia (87.8% vs. 76.8%; p < 0.001), anxiety (91.0% vs. 66.9%; p < 0.001), sleep disorders (20.1% vs. 6.8%; p < 0.001), and hyperglycemia (92.7% vs. 52.1%; p < 0.001). Female patients more often reported headache (56.7% vs. 32.6%; p < 0.001), depression (33.1% vs. 9.0%; p < 0.001), and osteoporosis (41.7% vs. 2.4%; p < 0.001). Further variation was observed across neurological, musculoskeletal, and respiratory categories, suggesting a multidimensional pattern of sex differences. Conclusions: This FAERS-based analysis indicates distinct sex-specific safety signals for Trelegy Ellipta, particularly in cardiovascular, neuropsychiatric, and steroid-related domains. These findings are hypothesis-generating and highlight the importance of incorporating sex-disaggregated analyses into future pharmacovigilance and clinical studies. Full article

This study systematically investigated the structural damage and electrochemical performance changes in 18650 cylindrical lithium-ion batteries under multiple impacts through a 10 kg drop-hammer impact test. The experimental results showed that as the state of charge (SOC) increased from 25% to 75%, the battery’s stiffness increased and its impact resistance improved, but the electrolyte leakage intensified, with a higher risk of leakage at high SOCs. An increase in the impact force led to enhanced voltage fluctuations and a continuous increase in deformation. After an impact of 500 mm, the voltage decreased about 0.02 V, while after an impact of 1000 mm, it dropped about 0.04 V. Axial impacts caused a sudden voltage drop to 1.96 V, resulting in permanent failure; compared with planar impacts, cylindrical surface impacts are more likely to cause compression in the middle and warping at both ends, significantly increasing the risk of internal short circuits. CT scans revealed that the battery porosity can reach up to 3.09% under high impact energy, and the deformation rate can reach 28.39%. The research results provide a quantitative experimental basis for the impact-resistant design and safety assessment of power batteries. Full article

Nowadays, two major pathways seem to be responsible for the development and progression of atherosclerosis, namely, high levels of low-density lipoprotein-cholesterol (LDL-C) and low-grade vascular inflammation. Indeed, the concentration of C-reactive protein (CRP), mirroring low-grade systemic inflammation, has been recognized as a more powerful determinant of recurrent cardiovascular (CV) events, death, and all-cause mortality than LDL-C levels. Gut microbiota (GM) dysbiosis is a causal factor for the development of different inflammatory-based pathologies, such as CV disease (CVD). In addition, pre/probiotics showed beneficial effects on GM dysbiosis, by influencing both inflammation and immunity. It has been well documented that eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) exert triglyceride (TG)-lowering and antithrombotic effects and play a seminal role in the resolution of inflammatory processes. We showed the recent studies indicating the relationship between pharmacological reduction in inflammatory cytokines and CV outcomes. The principal aim of our review is to highlight the anti-inflammatory and immune-modulatory activities of GM, EPA, and DHA. Then, we pointed out how developing patient-specific pre/probiotic and EPA/DHA interventions alongside the standard of care (SOC) is needed in order to answer several of the questions raised, ranging from diminishing drug toxicity to including frailty individuals. Therefore, hypothetical tailored clinical studies are presented, aiming to treat all the patients at high-risk of CV events, as well as aged people. Full article

We present a theoretical model to explain how tubulin dimers in neuronal microtubules might achieve collective quantum coherence, resulting in wavefunction collapses that manifest as avalanches within a self-organized criticality (SOC) framework. Using the Orchestrated Objective Reduction (Orch-OR) theory as inspiration, we propose that microtubule subunits (tubulins) become transiently entangled via dipole–dipole couplings, forming coherent domains susceptible to sudden self-collapse. We model a network of tubulin-like nodes with scale-free (Barabási–Albert) connectivity, each evolving via local coupling and stochastic noise. Near criticality, the system exhibits power-law avalanches—abrupt collective state changes that we identify with instantaneous quantum wavefunction collapse events. Using the Diósi–Penrose gravitational self-energy formula, we estimate objective reduction times $T_{\mathrm{OR}}=\hslash /E_g$ for these events in the 10–200 ms range, consistent with the Orch-OR conscious moment timescale. Our results demonstrate that quantum coherence at the tubulin level can be amplified by scale-free critical dynamics, providing a possible bridge between sub-neuronal quantum processes and large-scale neural activity. Full article

In lithium-ion battery charging, balancing charging speed with efficiency and state of health (SOH) is paramount. First, a multi-state electric-thermal-aging coupling model was developed to accurately reflect battery operating conditions. Second, a voltage-based multi-stage constant current-constant voltage (VMCC-CV) strategy was implemented, incorporating an innovative V-SOC-R_int conversion mechanism—integrating voltage, state of charge (SOC), and internal resistance—to effectively mitigate thermal buildup during transitions. To optimize the VMCC-CV currents, an innovative enhancement was applied to the moth-flame optimization (MFO) algorithm, demonstrating superior performance over its traditional counterpart across diverse charging scenarios. Finally, three practical strategies were devised: rapid charging, multi-objective balanced charging, and enhanced safety performance charging. Relative to the manufacturer’s 0.75 C-CCCV protocol, the balanced strategy significantly accelerates charging, reducing time by 34.11%, while sustaining 93.54% efficiency and limiting SOH degradation to 0.006856%. Compared to conventional CCCV methods, the proposed approach offers greater versatility and applicability in varied real-world scenarios. Full article

Aiming at the problems of high-dimensional nonlinear constraints, multi-objective conflicts, and low solution efficiency in microgrid optimal scheduling, this paper proposes a multi-objective Harris Hawk–Grey Wolf hybrid intelligent algorithm (IMOHHOGWO). The problem of balancing the global exploration and local exploitation of the algorithm is solved by introducing an adaptive energy factor and a nonlinear convergence factor; in terms of the algorithm’s exploration scope, the stochastic raid strategy of Harris Hawk optimization (HHO) is used to generate diversified solutions to expand the search scope, and constraints such as the energy storage SOC and DG outflow are finely tuned through the α/β/δ wolf bootstrapping of the Grey Wolf Optimizer (GWO). It is combined with a simulated annealing perturbation strategy to enhance the adaptability of complex constraints and local search accuracy, at the same time considering various constraints such as power generation, energy storage, power sales, and power purchase. We establish the microgrid multi-objective operation cost and carbon emission cost objective function, and through the simulation examples, we verify and determine that the IMOHHOGWO hybrid intelligent algorithm is better than the other three algorithms in terms of both convergence speed and convergence accuracy. According to the results of the multi-objective test function analysis, its performance is superior to the other four algorithms. The IMOHHOGWO hybrid intelligent algorithm reduces the grid operation cost and carbon emissions in the microgrid optimal scheduling model and is more suitable for the microgrid multi-objective model, which provides a feasible reference for future integrated microgrid optimal scheduling. Full article

Ankyrin-repeat and SOCS-box protein 9 (ASB9) is a member of the ASB family of proteins, which act as a substrate recognition component of E3 ubiquitin ligases and regulate various reproductive processes. ASB9 was previously identified as being induced in bovine granulosa cells (GCs) by LH/hCG, and its binding partners, including protease-activated receptor 1 (PAR1), were reported. The aim of this study was to decipher ASB9’s mechanisms of action in GCs and determine whether ASB9 induction by LH/hCG is necessary for the regulation of PAR1 and the signaling pathways involved in GC function and activity. Cultured GCs were treated with different doses of FSH, LH, and thrombin. RT-qPCR analyses revealed that thrombin increased PAR1 expression, while FSH had no effect on PAR1. Treatment with LH significantly downregulated PAR1, even in the presence of thrombin, possibly via ASB9. The phosphorylation profile of MAPK3/1 in thrombin-treated GCs suggests PAR1-mediated control. ASB9 induction appeared to have a negative effect on the MAPK pathway, although thrombin treatment briefly (within an hour) blocked the negative effect of ASB9 on PAR1. Proliferation assays showed that ASB9 negatively regulated the GC number while increasing apoptosis. These data provide evidence of ASB9’s mode of action and its potent functional effects on PAR1 regulation, GC proliferation, and, potentially, the ovulatory process in bovine species. Full article

Battery cell balancing is crucial in series-connected lithium-ion packs to maximize usable capacity, ensure safe operation, and prolong cycle life. This paper presents a comprehensive study and a novel adaptive duty-cycled hybrid balancing system that combines passive bleed resistors and an active switched-capacitor (SC) balancer, specifically designed for a 4-cell series-connected battery pack. This work also explored open circuit voltage (OCV)-driven adaptive pulse-frequency modulation (PFM) active balancing to achieve higher efficiency and better balancing speed based on different system requirements. Finally, this paper compares passive, active (SC-based), and adaptive duty-cycled hybrid balancing strategies in detail, including theoretical modeling of energy transfer and efficiency for each method. Simulation showed that the adaptive hybrid balancer speeds state-of-charge (SoC) equalization by 16.24% compared to active-only balancing while maintaining an efficiency of 97.71% with minimal thermal stress. The simulation result also showed that adaptive active balancing was able to achieve a high efficiency of 99.86% and provided an additional design degree of freedom for different applications. The results indicate that the adaptive hybrid balancer offered an excellent trade-off between balancing speed, efficiency, and implementation simplicity for 4-cell Li-ion packs, making it highly suitable for applications such as high-voltage portable chargers. Full article

Changes in vegetation type shape the soil microenvironment, thereby regulating the changes in the organic carbon pool by influencing microbial communities and the accumulation of microbial necromass carbon (MNC). This study investigated microbial biomass—via phospholipid fatty acids (PLFAs) analysis—and MNC accumulation across three cold–temperate forest types: Larix gmelinii forest (L), Larix gmelinii–Betula platyphylla Sukaczev mixed forest (LB), and Betula platyphylla Sukaczev forest (B). The results showed that the L had the lowest contents of pH, water content (WC), soil organic carbon (SOC), total nitrogen (TN), available nitrogen (AN), and total phosphorus (TP), but the highest contents of dissolved organic carbon (DOC), available phosphorus (AP), and carbon to nitrogen ratio (C/N) (p < 0.05). LB had the lowest PLFAs content and the highest ratio of Gram-positive bacteria/Gram-negative bacteria (G+/G−), and total fungi/total bacteriai (F/B) of L was the highest. B had the highest alpha diversity index, and significantly positively correlated with pH, SOC, TN, AN, and TP. TP and C/N were the primary elements for significant differences in microbial community structure. The order of MNC content and its contribution to SOC was B > LB > L. MNC was significantly negatively correlated with PLFAs, DOC, and AP, and significantly positively correlated with pH, SOC, TN, AN, TP, Shannon–Wiener and Pielou indices. In conclusion, this study demonstrates that Betula platyphylla Sukaczev forest retains more carbon, nitrogen, and phosphorus, microbial alpha diversity, and acquires more MNC, which can provide a basis for subsequent forest management and carbon sequestration projects. Full article

Rural electrification in isolated communities requires reliable and affordable renewable solutions. This paper analyses a hybrid microgrid case study in a rural area integrating PV–biomass–BESS using mathematical models and simulations in MATLAB/Simulink Version 2025a, characterizing local resources (climate and biomass), and evaluating irradiance, temperature, and demand profiles. On typical days, the system meets demand with overall efficiencies of 93–103%; solar energy contributes 6.8–8.9 kWh/day (37–42%), biomass 9.5–13.2 kWh/day (54–62%), and BESS ≈ 0.6 kWh/day (≈3%), operating at 60–90% SoC. Between March and June, photovoltaic generation increased from 7.2 to 8.9 kWh/day (+23.6%), raising overall efficiency from 97% to 103%; in October, the contribution was 40% PV, 57% biomass, and 3% BESS. Coordinated operation—prioritizing solar and scheduling biomass at peaks—is robust and replicable. It is recommended to increase photovoltaic collection by ~20% and add ≥2.5 kWh of storage to reduce biomass dependence by 15–20% and improve nighttime autonomy. This integrated approach to solar generation, biomass management, and storage for efficient and sustainable supply is applied and validated in a theoretical case study developed in the rural area of Argelia-Viotá, Cundinamarca, Colombia. Full article

Soil contamination with heavy metals (HM) poses a risk to human health and can impact different soil functions. This study aimed to determine the influence of heavy metal pollution on the physical and physicochemical characteristics of the two profiles of alluvial–deluvial soil under grassland located at different distances from the Aurubis-Pirdop Copper smelter in Bulgaria. Data for soil particle-size distribution, soil bulk and particle densities, mineralogical composition, soil organic carbon contents, cation exchange properties, surface charge, soil water retention curves, pore size distribution—obtained by mercury intrusion porosimetry (MIP)—and thermal properties were obtained. The contents of Pb, Cu, As, Zn, and Cd were above the maximum permissible level in the humic horizon and decreased with depth and distance from the Copper smelter. Depending on HM speciation, the correlations are established with SOC and most physicochemical parameters. It can be concluded that the HMs impact the clay content, specific surface area, distribution of pores, and the water stability of soil aggregate fraction 1–3 mm to varying degrees. Full article