Search Results (2,236)

High-performance speed regulation of interior permanent magnet synchronous motor (IPMSM) drives in electric vehicle (EV) applications becomes particularly challenging in the field-weakening region, where voltage constraints, parameter variations, and nonlinear aerodynamic loads significantly affect the closed-loop stability. To address these challenges, this paper proposes a stability-aware adaptive fractional-order speed control framework for EV traction systems. The framework integrates a fractional-order PI (FOPI) core to provide iso-damping robustness, a bounded fuzzy gain-scheduling mechanism for real-time adaptation, and an offline multi-objective optimization layer for systematic parameter tuning. A Lyapunov-based qualitative analysis is provided to justify closed-loop ultimate boundedness under adaptive gain modulation and field-weakening constraints. The fuzzy scheduler is explicitly structured to regulate the error energy dissipation rate by modulating the proportional and integral gains while preserving the gain boundedness. The controller parameters are optimized using a diversity-driven fractional-order multi-objective PSO algorithm to balance the tracking accuracy and control effort. The proposed framework was validated using a high-fidelity MATLAB/Simulink–CarSim 2023 co-simulation platform under the aggressive US06 driving cycle. The results demonstrated a zero-overshoot transient response, robustness against a 2.5× inertia mismatch, and sustained performance under flux-linkage and inductance variations in deep field-weakening operation. Compared with conventional PI-based strategies, the proposed approach reduced the speed RMSE by 82%, lowered the current THD from 18.5% to 3.2%, and reduced the cumulative DC-link current-squared index by 6.7%. These results validate the practical robustness and computational feasibility of the proposed stability-aware framework for EV traction control. Full article

Background: Cholangiocarcinoma (CCA) is a highly heterogeneous malignancy in which numerous biomarker candidates have been reported, yet few progress to clinical use. Beyond biological complexity, this low translational yield reflects the lack of systematic criteria for prioritizing biomarkers during the discovery stage. In particular, tumor-derived signals identified in tissue often fail to persist in clinically accessible biofluids, as cross-compartment signal behavior is rarely evaluated explicitly. Methods: We developed an extracellular vesicle (EV)-guided, multi-compartment proof-of-concept framework to assess biomarker robustness and translatability early in discovery. EV proteomes from three biologically distinct CCA cell lines and a normal cholangiocyte were analyzed using multivariate and machine-learning-assisted approaches to identify conserved EV-associated features. These were integrated with public transcriptomic, epigenetic, copy-number, promoter usage, and miRNA regulatory data. Tissue relevance was assessed using TCGA/GTEx RNA-seq datasets, and exploratory signal behavior was examined in pooled serum- and urine-derived EVs from CCA patients and controls. Results: EV proteomics revealed marked molecular heterogeneity across CCA models but identified a small subset of conserved EV-associated proteins. SERPINF2 was used as a representative example, showing consistently reduced EV-associated abundance across all CCA models with coordinated regulation across multiple molecular layers. SERPINF2 expression was independent of patient sex and tumor stage and clearly distinguished tumor from normal bile duct tissue. Exploratory biofluid analyses demonstrated compartment-dependent signal behavior, with SERPINF2 depletion detectable in urine-derived EVs but not in serum-derived EVs. Conclusions: Rather than validating a single biomarker, this study presents an EV-guided, multi-compartment framework for prioritizing biomarker candidates at the discovery stage. By explicitly accounting for tumor heterogeneity and compartment-specific signal preservation, this proof-of-concept approach provides a practical decision-support strategy for identifying biomarkers with greater translational potential in heterogeneous cancers such as CCA. Full article

This study aims to experimentally evaluate and compare the electrical–thermal performance of a 20-cell 18650 lithium-ion battery pack cooled by a pure phase change material (PCM) and a PCM/TiO₂ nanoparticle composite to identify an effective passive thermal management approach for EV battery applications. Using a controlled charging–discharging system, thermocouple-based temperature mapping, and systematic tests across multiple C-rates (0.75 C–1.5 C), the study measures the variations in battery temperature, generated heat, and voltage behavior as functions of depth of discharge (DOD) and state of charge (SOC). The results show that the PCM/nanoparticle mixture markedly improves thermal conductivity, reduces peak temperature by approximately 8–10 °C compared with pure PCM, delays thermal saturation at higher C-rates, and enables a wider safe DOD range with reduced voltage sag and lower heat accumulation. Based on the experimental temperature/voltage trends in this study, limit DOD to ≤40–50% at high power (≈1.5 C), ≤50–60% at moderate power (≈1 C), and ≤60–70% at low power (≈0.75 C) (i.e., target SOC windows roughly 60–100% SOC at 1.5 C, 40–100% SOC at 1 C, and 30–100% SOC at 0.75 C), with an absolute practical upper DOD limit of ~70% to avoid frequent deep discharge damage; these limits keep peak temperatures below ~40–45 °C, reduce severe voltage sag near cutoff, and greatly extend cycle life because shallower cycling (e.g., 50% vs. 100% DOD) produces many times more cycles. These improvements enhance battery safety, performance stability, and cycle life, making the nanoparticle-enhanced PCM a practical, compact, and energy-efficient solution for passive battery thermal management in electric vehicles. Full article

Background/Objectives: Hand, foot and mouth disease (HFMD) caused by enterovirus 71 (EV71) may cause severe complications and death in children. It is also a common cause of outbreaks in the Asia-Pacific Region. Incidence among children 1 to <2 years was over 3000/100,000 population in China. A systematic review and meta-analysis was performed to review evidence on vaccine efficacy (VE), immunogenicity, and safety of two doses of EV71 vaccine in children. Methods: Randomized controlled trials (RCTs) comparing EV71 vaccine with placebo or with another EV71 vaccine in children and adolescents aged ≤18 years were searched on PubMed, Medline, Embase, CENTRAL, and CNKI (Chinese) in week 5 November 2024. The reference list of each study and the websites of vaccine manufacturers were also searched. The Cochrane Risk of Bias 2 tool (RoB2) was used to assess the risk of bias. VE, immunogenicity (including seropositive rate, seroconversion rate, geometric mean titer (GMT), Geometric Mean Fold Increase (GMFI)), and rate of adverse events were analyzed. Results: A total of 4199 articles were identified, and 25 studies were finally included. VE (%) against EV71 HFMD in children aged ≤5 years at 12 months was 94.8% (95%CI 87.2–97.9) for Sinovac and 90.9% (95%CI 70.4–97.2) for Wuhan Institute of Biological Products (WIBP), while the Chinese Academy of Medical Sciences (CAMS) reported 97.4% (95%CI 92.9–99.0) at 11 months. At 1 month after the second dose, 99.19% (95%CI 98.15–99.65) of children aged ≤5 years in the vaccine group were seropositive, and 96.30% (95%CI 92.71–98.17) achieved seroconversion. GMT at 1 month after the second dose in the vaccine group was 46.78 (95%CI 26.18–83.61) times that in the placebo group. GMFI at 1 month after the second dose in the vaccine group was 28.41 (95%CI 22.18–36.39) times that of the placebo group. The rate of serious adverse events (AEs) was lower in the vaccine group than the placebo group (1.23% (95%CI 0.58–2.69) vs. 1.34% (95%CI 0.58–3.07)) at 1 month after the second dose. There was no significant difference in other adverse events between the vaccine and placebo groups. Conclusions: EV71 vaccines were effective, immunogenic and safe. Areas with a high incidence of EV71 may consider introducing EV71 vaccines. Full article

Chronic alcohol exposure disrupts blood–brain barrier (BBB) integrity and promotes neuroinflammation, with P2X7 receptor (P2X7R) signaling playing a critical role. Our prior work in male mice linked P2X7R inhibition to reduced extracellular adenosine triphosphate (eATP) release, modulated extracellular vesicle (EV) cargo, and attenuated neuroinflammation in chronic intermittent ethanol (CIE)-exposed mice. However, sex-specific roles of P2X7R signaling and EV-mediated mechanisms in alcohol-induced neuroinflammation remain unclear. Male and female mice were exposed to ethanol vapor for three weeks and treated with Brilliant Blue G (BBG), a P2X7R inhibitor. Compared to their respective CIE-unexposed controls, brain gene expression of tumor necrosis factor–α (Tnf-α), interleukin-1 beta (Il-1b), interleukin-6 (Il-6), monocyte chemoattractant protein-1 (Mcp-1), and Fas ligand (Fasl) significantly increased in CIE-exposed males, while only Il-1b increased in females. P2X7R inhibition significantly reduced these cytokines. Pericyte immunostaining was decreased by CIE (indicating BBB injury) in male mice only and was restored by P2X7R inhibition with no difference between groups in females. Occludin staining (another BBB marker) did not differ between the treatment groups in male and female animals. Circulating cytokines (Macrophage inflammatory protein-1 alpha (MIP-1α), tumor necrosis factor–α (TNF-α), interleukin-1 beta (IL-1β), and interleukin-27 subunit p28/interleukin-30 (IL-27p28/IL-30) were significantly elevated in CIE-exposed males but not in females, with BBG treatment reducing cytokines in males. Circulating eATP, P2X7Rs, P-glycoprotein (P-gp), EVs, and EV-mtDNA, which we identified in our previous study, were increased in both sexes and partially decreased by P2X7R blockade. Spatial memory was impaired by CIE exposure in males but not females, and this deficit was reversed by BBG treatment. Our findings reveal sex differences in CIE-induced circulating cytokines, neuroinflammation, and memory impairment, with a stronger response in males. However, other markers of cell injury associated with CIE exposure were upregulated in both sexes; P2X7R inhibition effectively mitigated these effects, highlighting the functional relevance of targeting the P2X7R in alcohol-induced injury. Full article

Background: Extracellular vesicles (EVs) play an important role in tumor progression and intercellular communication, yet the contribution of specific cancer-related genes to EV secretion remains incompletely defined. Methods: To address this, we performed an siRNA-based loss-of-function screen targeting 30 frequently altered (proto-)oncogenes and tumor suppressor genes in the colorectal carcinoma cell line HCT-116 to assess their impact on EV release. EVs were isolated by sequential ultracentrifugation to obtain P14 and P100 fractions pelleting at 14,000× g or 100,000× g, respectively, and were characterized by nanoparticle tracking analysis, EV marker expression, and total protein quantification. Cell viability was assessed to control for potential apoptosis-related effects. Results: With few exceptions, knockdown of the investigated genes led to an increase in EV secretion. Silencing of KRAS and BRAF resulted in significantly elevated P14 EV levels, increased EV marker expression, and higher total protein content, while KRAS knockdown was additionally associated with a shift toward larger particle sizes. Downregulation of CTNNB1 increased P14 and decreased P100 EV secretion, whereas CDH1 knockdown reduced P14 EV levels and slightly increased P100 EVs. No general distinction between tumor suppressor genes and (proto-)oncogenes regarding their effects on EV secretion was observed, and cell viability was not significantly altered under the experimental conditions. Conclusions: These findings suggest that components of the Ras/Raf/MAPK and Wnt signaling pathways may contribute to the regulation of EV secretion in colorectal cancer cells. Full article

Mesenchymal stem cells (MSCs) exert biological effects in part through their secretome which includes extracellular vesicles. In this study, we isolated and characterized the secretome from clinically relevant stem cell lines: human embryonic stem cell–derived mesenchymal stem cell line (ES-MSCs) and Infrapatellar fat pad derived MSC (IPFP-MSC) cultured in xeno-free medium. We assessed the biological activity of concentrated cell secretome or isolated fractions of extracellular vesicles (EVs) on cell proliferation, microvascular formation, and cartilage degradation in a human osteoarthritic (OA) ex vivo model. Serum-free conditioned medium from ES-MSC (N = 1) or IPFP-MSC (N = 2) monolayer cultures were concentrated by ultrafiltration to generate concentrated conditioned medium (CCM). Size exclusion chromatography was used to fractionate extracellular vesicles (EVs). Vesicle size, concentration, morphology, and surface markers were characterized by nanoparticle tracking analysis, transmission electron microscopy, and flow cytometry. Biological activity was evaluated by treating human umbilical vein endothelial cells (HUVECs), IPFP-MSCs, and ES-MSCs with CCM and EVs at defined particle concentrations. Endothelial network formation was tested in fibrin gels with different cell and secretome combinations. For analysis of cartilage degradation, human cartilage explants (N = 4; 3.5 mm in diameter) were harvested from patients undergoing total knee arthroplasty and subjected to IL-1β stimulation to induce an OA phenotype. Explants were treated with varying doses from CCM or EVs. Release of glycosaminoglycan in the medium and RNA analysis of catabolic genes were used as readouts. Secretome preparations yielded on average approximately 50 billion vesicles per mL with a similar particle size distribution between 50–200 nm in ES-MSC and IPFP-MSC cultures. Transmission electron microscopy confirmed vesicle morphology and flow cytometry confirmed expression of exosomal surface markers (CD9, CD63, CD81). Functionally, CCM and EVs enhanced proliferation in a dose-dependent manner. Endothelial networks formed by HUVECs in fibrin were stabilized over 7 days by CCMs, most notably by hypoxic ES-MSC CCM relative to no CCM treatment (control). In the OA cartilage model, IL-1β stimulation increased glycosaminoglycan release, whereas ES-MSC CCM treatment and EV treatment reduced glycosaminoglycan release and ES-MSC CCM reduced gene expression of IL-1β, MMP-1, and MMP-3. We isolated and characterized the concentrated secretome and the isolated vesicle-enriched fractions from xeno-free ES-MSC and IPFP-MSC and demonstrated bioactivity in promoting cell proliferation, modulating endothelial network formation, and mitigating cartilage degradation in osteoarthritic tissue. These findings support the bioactivity and therapeutic potential of stem cell–derived secretomes for OA. Full article

Post-infectious Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a chronic disease with unresolved pathophysiology and limited diagnostic options. Extracellular vesicles (EVs) carry disease-specific protein and miRNA signatures and may enable improved disease profiling. We aimed to identify novel protein and miRNA markers as potential biomarkers in plasma EVs from female ME/CFS patients, including post-COVID-19 ME/CFS and post-infectious ME/CFS of other origins, compared with healthy controls. EVs were isolated from plasma by size-exclusion chromatography and characterized for number, size, morphology, and surface marker expression. Flow cytometry showed that small EVs strongly expressed tetraspanins, with only minor differences between ME/CFS patients and healthy donors. Proteomic profiling of EVs from ME/CFS patients identified altered cargo proteins, including hemoglobin subunit alpha and insulin-like growth factor-binding protein acid labile subunit compared with healthy controls (n ≤ 10/cohort). Small RNA sequencing followed by qPCR revealed significant downregulation of hsa-let-7b-5p in EVs from post-COVID-19 ME/CFS patients (n = 12) versus healthy controls (n = 15). Reduced hsa-let-7b-5p expression correlated with impaired physical functioning and increased fatigue, pain, and immune activation. These findings indicate that EV cargo differences, particularly hemoglobin subunit alpha and insulin-like growth factor-binding protein acid labile subunit, as well as hsa-let-7b-5p, represent promising candidates for ME/CFS diagnosis and patient stratification. Full article

In this paper, we propose a data-driven distributionally robust optimization (DRO) framework that ensures the economical and robust operation of solar photovoltaic (PV)-integrated battery charging swapping stations (BCSSs) for electric vehicles (EVs) under uncertainties in active distribution systems with stand-alone PV systems. In the proposed framework, multiple inventory batteries in each BCSS are used through their charging and discharging real and/or reactive power scheduling to perform Volt/VAR control (VVC) along with stand-alone PV systems, and to reduce the BCSS operational cost via battery-to-battery (B2B)-based real power exchange and demand response (DR) while satisfying the desired EV battery swapping load. To handle the uncertainties in both PV generation outputs and DR-induced maximum demand reduction capability, the proposed framework is formulated as a data-driven DRO problem based on the Wasserstein metric using historical samples of the probability distributions of the uncertainties. Using a duality theory, the original Wasserstein-based DRO problem is reformulated into a tractable optimization problem that calculates the distributionally robust bounds of uncertainties using their support information. The effectiveness of the proposed framework was assessed on an IEEE 33-node power distribution system in terms of real power loss reduction via VVC and BCSS operational cost savings via B2B/DR capability. Full article

This paper presents a novel optimization algorithm for electric vehicle (EV) aggregators aiming to maximize net revenue in demand response markets. Aggregated EV charging stations are modeled as a battery with time-varying capacity, enabling participation in these markets. Due to uncertainties in EV plug-in duration and energy demand, it is challenging for aggregators to fulfill bid capacities in real-time (RT). To address this, EV users specify minimum acceptable service levels, allowing aggregators to optimize both charging timing and energy demand in RT. The model is composed of two layers: (1) a Day-Ahead (DA) optimizer that determines optimal EV scheduling and DA demand response market bidding, and (2) a two-stage RT optimizer that fine-tunes the charging schedule using real-time flexibility to mitigate forecast errors. The RT optimizer leverages Model Predictive Control (MPC) in a two-stage structure to address the problem’s non-convexity, which arises from two coupled unknowns: the charging time and the charging energy demand. In the first stage, it determines a cost-optimal charging schedule that ensures full service levels. In the second stage, it optimizes the charging energy demand within a feasible range, bounded above by the first-stage trajectory and below by user-defined minimum service levels, to maximize demand response market revenue. A realistic baseline and a penalty term are integrated into the demand response market revenue term of the cost function to more accurately reflect real-world conditions. Simulation results demonstrate that the proposed method yields a net economic profit at least five times higher than that of immediate (or ‘dumb’) charging. During one month of simulations, the aggregator achieves revenue equivalent to $0.21 per kWh of demand reduction under forecast uncertainty, totaling $3441. Full article

CeO₂ particles were synthesized via a hydrothermal method to investigate the influence
of precursor molarity and reaction time on their structural, optical, and adsorption characteristics. Ce(NO₃)₃·6H₂O served as the cerium source, while PVP and Triton X-100
acted as surfactants to regulate nucleation and particle growth. XRD and Raman analyses
confirmed the formation of single-phase cubic fluorite CeO₂, whereas FTIR spectra verified
the presence of Ce–O bonding. SEM observations revealed that a decreasing precursor
molarity led to smaller and more uniform particles, while prolonged reaction times enhanced crystallinity. UV–Vis DRS and XPS analyses indicated that both the band gap
(3.06–3.12 eV) and the Ce³⁺/Ce⁴⁺ ratio were governed by oxygen vacancies, demonstrating defect-mediated redox behavior. Adsorption studies using methyl orange (MO) dye followed pseudo-second-order kinetics (R² > 0.99), indicating chemisorption as the dominant mechanism. The CP1-8 sample exhibited the highest dye removal efficiency (87%) under acidic conditions (pH < pHPZC). These findings demonstrate that controlled hydrothermal synthesis enables precise tuning of CeO₂ morphology, defect density, and surface chemistry, yielding efficient adsorbent materials for environmental remediation applications. Full article

The large-scale integration of electric vehicles (EVs) introduces significant operational challenges for power systems, particularly when grid-favourable operating periods coincide with high marginal carbon emissions. This paper proposes a carbon-aware rolling-horizon energy management framework for EV fleets coordinated through virtual power plants (VPPs), explicitly addressing such carbon–grid conflict conditions. The proposed framework prioritises grid-friendly scheduling through power and ramp constraints while enforcing energy-service equivalence and a policy-level carbon budget consistent with carbon peak and carbon neutrality objectives. Carbon awareness is incorporated as a secondary steering term within the rolling-horizon optimisation, enabling temporal shifting of EV charging toward low-carbon periods without compromising grid stability. A Pareto-based trade-off analysis is conducted to characterise the relationship between grid stress mitigation and carbon reduction, and a knee point is identified to select a balanced operating regime. Simulation results using real EV charging demand combined with a conflict-driven carbon intensity signal demonstrate that grid-oriented scheduling alone can increase emissions under carbon–grid mismatch. In the evaluated conflict scenario, the proposed carbon-aware rolling-horizon strategy achieves a 17.35% reduction in total CO₂ emissions relative to RH-NoCarbon scheduling while maintaining peak–valley load variation below 11.03 kW compared with 43.65 kW under uncontrolled charging. These results confirm that explicit carbon-aware coordination can significantly mitigate emissions without compromising grid operational stability. All control strategies are evaluated in a simulation environment using real EV charging demand data as exogenous inputs, ensuring realistic demand representation while enabling controlled assessment of operational performance. These findings highlight the necessity of embedding carbon considerations directly into operational EV scheduling and establish VPP-based rolling-horizon coordination as a practical mechanism for low-carbon power system operation. Full article

Extracellular vesicles, which carry bioactive cargos such as proteins, RNAs, and lipids, represent promising drug delivery vehicles owing to their biocompatibility, low immunogenicity, and inherent tissue-targeting capabilities. To address the current limitations in controlled cargo loading, we developed an abscisic acid (ABA)-inducible proximity system that directs proteins into exosomes during biogenesis. We engineered exosomal scaffolds by fusing the ABA receptor PYL1 to EV-enriched proteins—including BASP1, CD9, PTGFRN, and a truncated form PTGFRNΔ687—thereby creating docking sites within the exosomal lumen, while the target cargo (e.g., EGFP, firefly luciferase, or Cas9) was tagged with the ABI1 phosphatase domain. We demonstrate that ABA administration in producer cells induces PYL1–ABI1 complex formation, which recruits ABI1-fused cargo for selective encapsulation into EVs. Among the scaffolds tested, BASP1–PYL1 proved the most effective, enabling robust, ABA-dependent enrichment of cargo proteins. Purified EVs maintained canonical morphology, size, and marker expression (CD63, syntenin-1, CD9), confirming preserved biogenesis. Critically, these loaded exosomes efficiently delivered functional cargo to recipient cells, enabling Cas9/sgRNA-mediated genome editing. Together, our findings establish an ABA-triggered molecular switch for controllable EV protein loading, providing a versatile platform for next-generation therapeutic delivery. Full article

High-performance speed control of Permanent Magnet Synchronous Motor (PMSM) drives in Electric Vehicle (EV) applications faces significant challenges due to inherent nonlinearities, parameter variations, and signal non-idealities such as sensor noise and measurement latency. To address these issues, this paper proposes a robust PI-based Fractional-Order PSO-Fuzzy Weight Controller (PI-FOPSOFWC). The proposed strategy integrates a fractional-order PI (FOPI) core to ensure iso-damping robustness, a fuzzy inference mechanism for online gain scheduling against nonlinear load dynamics, and a novel Fractional-Order Particle Swarm Optimization (FOPSO) algorithm for optimal parameter tuning. A key contribution of this study is the validation of the control strategy within a high-fidelity co-simulation framework coupling MATLAB/Simulink with CarSim 2023, which incorporates realistic vehicle dynamics and time-varying road loads unavailable in conventional simplified simulations. Co-simulation results demonstrate that the proposed controller effectively eliminates overshoot in step responses and maintains stability under significant parameter mismatches ($2.0\times$ inertia). Furthermore, under the EPA urban driving cycle, the proposed method reduces the speed tracking Root Mean Square Error (RMSE) by 75.0% compared to the standard PI controller. Computational complexity analysis further confirms the feasibility of the proposed algorithm for real-time implementation in commercial EV traction drives. Full article