Search Results (3,185)

With the rapid penetration of electric vehicles (EVs) and renewable energy generation in distribution networks, the coordinated scheduling of flexible EV loads and uncertain renewable resources has become a critical research focus in modern power systems. This study investigates the collaborative optimal dispatch of thermal units, EVs, and renewable power generation. Different from conventional closed-loop game-based bi-level optimization, this paper constructs a transmission–distribution integrated scheduling framework and proposes a sequential hierarchical progressive optimization strategy for EV charging and discharging dispatch to fully tap the cross-level coordination potential of power grids. The upper transmission layer optimizes the joint operation of thermal units, wind power, and photovoltaic units to minimize the overall power supply cost, where the inequality power balance constraint is reasonably adopted to reserve power regulation margin for renewable fluctuation and meet practical engineering operation requirements. To effectively address the severe uncertainty of renewable power output without relying on accurate probability distribution information, information gap decision theory (IGDT) is employed to realize robust scheduling with risk-averse and opportunity-seeking decision adaptability. In the lower distribution layer, a theoretically grounded nodal electricity price (NEP) model integrating node loss sensitivity (NLS) and node load rate (NLR) is applied to substitute iterative power flow calculation, which realizes the spatial optimal allocation of EV charging and discharging nodes while significantly improving computational efficiency. The proposed framework comprehensively minimizes network power loss and user charging cost. Finally, extensive simulations based on the IEEE 33-node distribution system verify the effectiveness, computational superiority, and robustness of the proposed sequential hierarchical coordinated scheduling strategy. Full article

Objective: The aim of this systematic review was to evaluate the in vitro effects of LED-based photobiomodulation on fibroblasts and osteoblasts, with particular focus on cellular processes involved in soft- and hard-tissue regeneration. Methods: A comprehensive electronic search was conducted on 3 April 2026 in PubMed, Scopus, Web of Science, Embase, and WorldCat according to PRISMA guidelines. The analyzed outcomes included cell viability, proliferation, migration, collagen synthesis, oxidative stress, mitochondrial activity, and selected regeneration-related processes. A total of 745 records were initially identified, and 32 studies met the inclusion criteria and were included in the qualitative synthesis. Results: The biological effects of LED-PBM depended strongly on irradiation parameters, including wavelength, fluence, irradiance, exposure time, treatment schedule, and the initial condition of the cells. Most included studies focused on fibroblast models. Red and near-infrared light showed the most consistent beneficial effects, particularly by supporting fibroblast viability, proliferation, migration, mitochondrial activity, ATP production, collagen-related responses, and oxidative stress modulation. In osteoblast-related models, LED irradiation showed potential to influence cell number, metabolic activity, maturation markers, and mineralization-related outcomes; however, the number of studies was limited. Blue light demonstrated dose-dependent effects, with higher fluences reducing fibroblast metabolic activity, proliferation, or viability. Green light improved fibroblast proliferation and migration in one model but was associated with increased cell death in osteoblast-like cells. Conclusion: LED-PBM may positively modulate cellular processes involved in soft- and hard-tissue regeneration in vitro. However, the observed effects are strongly parameter-dependent, and further standardized studies are required to define optimal irradiation protocols and validate their potential clinical relevance. Full article

Electrochemical impedance spectroscopy (EIS) resolves the internal physicochemical processes of lithium-ion batteries across timescales—from ohmic conduction through charge-transfer kinetics to solid-state diffusion. Despite this analytical power, EIS deployment remains largely confined to laboratory electrochemical workstations that are bulky, expensive, and incapable of online multi-cell operation under dynamic DC bias conditions. This study presents a multi-channel EIS measurement device that simultaneously addresses three requirements for practical battery diagnostics: workstation-grade measurement accuracy, multi-cell synchronous acquisition, and tolerance to the DC bias voltage present across battery terminals during operation. The device employs a master–slave distributed architecture: each slave unit is built around the DNB1101 battery-dedicated impedance measurement chip with a Kelvin four-wire sensing configuration, while the STM32F407-based master controller coordinates measurement scheduling and data communication under FreeRTOS. A four-channel slave board with a differential daisy-chain communication topology and hardware broadcast trigger mechanism supports multi-cell synchronous acquisition. The device operates over a frequency range of 0.01 Hz to 5620 Hz with logarithmic spacing, and a C#-based host application provides real-time Nyquist and Bode visualization along with MATLAB R2024a-based post-processing for outlier rejection and data smoothing. Validation was conducted using Panasonic NCR18650 ternary (NCA) and LiFePO₄ (LFP) 18650 cells, benchmarked against a CorrTest CS350 electrochemical workstation at SOC = 40% and 25 °C. The device achieves a maximum impedance magnitude error of 1.55% and a maximum phase error of 1.22%. Equivalent circuit model fitting via ZSimpWin yields parameter differences below 1% between the device and the reference workstation. Under online conditions with a 3.6 V DC bias, the impedance measurement deviation of a 20 mΩ precision resistor remains below 0.69% across the full frequency range. Multi-channel synchronous measurements across four cells demonstrate inter-channel amplitude variance below 2.13%. Cross-chemistry validation with LiFePO₄ cells yields magnitude and phase errors below 0.92%. These results demonstrate that the proposed device provides laboratory-grade EIS accuracy with multi-channel, online, and cross-chemistry capabilities, offering a practical platform for integrating EIS-based diagnostics into next-generation battery management systems. Full article

Background: Brolucizumab is an intravitreal anti-vascular endothelial growth factor (anti-VEGF) agent developed to improve retinal drying and treatment durability in diabetic eye disease. However, its overall efficacy and safety in diabetic macular edema (DME) and diabetic retinopathy remain uncertain because available trials differ in population, comparator, dosing schedule, and follow-up. Methods: We searched PubMed, Cochrane Library, Scopus, and Web of Science from inception to 25 April 2026. Randomized controlled trials evaluating intravitreal brolucizumab in adults with DME, diabetic retinopathy, or proliferative diabetic retinopathy (PDR) were included. Comparators were aflibercept, panretinal photocoagulation, or other active/conventional treatments. The main efficacy outcomes were change in best-corrected visual acuity (BCVA) and central subfield thickness/central subfield foveal thickness (CST/CSFT). Safety outcomes included ocular, non-ocular, serious ocular, and serious non-ocular adverse events. Random-effects meta-analyses were performed. Results: Five reports representing four phase 3 randomized controlled trials were included, enrolling 2132 participants overall; the four-trial primary 6 mg analyses included 1942 participants. Brolucizumab was not associated with a significant improvement in BCVA compared with control treatment (mean difference [MD], 1.21 letters; 95% confidence interval [CI], −1.12 to 3.54; p = 0.3; I² = 85.1%). However, brolucizumab significantly reduced CST/CSFT (MD −24.45 µm, 95% CI −47.43 to −1.47; p = 0.0370; I² = 78.2%). No statistically significant differences were detected between groups in the assessed safety outcomes, including ocular adverse events (risk ratio [RR], 0.88), non-ocular adverse events (RR 1.00), serious ocular adverse events (RR 0.63), and serious non-ocular adverse events (RR 0.89). Separate analyses of brolucizumab-specific ocular events showed no statistically significant differences for intraocular inflammation (RR 2.35, 95% CI 0.36–15.42), retinal vasculitis (RR 2.10, 95% CI 0.22–20.10), or retinal vascular occlusion (RR 2.13, 95% CI 0.46–9.87); however, estimates were imprecise because of the small number of events. Conclusions: Across the four included trials, brolucizumab was not associated with a statistically significant difference in BCVA compared with control treatment. In the three DME trials, brolucizumab achieved a greater reduction in CST/CSFT. It may be useful for selected DME patients, while its role in PDR requires longer-term evidence. Full article

Accurate brain tumor segmentation from multi-modal magnetic resonance imaging (MRI) is essential for clinical diagnosis and treatment planning. However, effectively capturing long-range contextual information and fine lesion boundaries under limited computational budgets remains challenging. In this work, we propose SDFR-Net, a lightweight stage-asymmetric Spectral Diffusion and Frequency–Spatial Refinement Network for efficient 2.5D brain tumor MRI segmentation. Instead of applying identical processing across all hierarchical stages, SDFR-Net adopts stage-dependent spectral diffusion, stage-selective conditional refinement, and asymmetric cross-stage frequency-grid allocation to accommodate the distinct semantic and frequency characteristics of shallow and deep representations. The network consists of a Spectral Diffusion Encoder for spectral-domain contextual propagation, a Frequency–Spatial Enhancement Module for adaptive refinement of multi-scale skip features, and a lightweight Conditional Refinement Decoder for lesion-aware reconstruction. Experiments on the BraTS 2019 and BraTS 2020 datasets demonstrate that SDFR-Net achieves whole-tumor Dice scores of 0.856 and 0.880, respectively, while requiring only 1.33 M parameters. Ablation comparisons of stage-selective FiLM injection and symmetric versus asymmetric frequency-grid schedules further support the stage-asymmetric design. These results indicate that SDFR-Net provides a favorable accuracy–efficiency trade-off for resource-constrained brain tumor MRI segmentation. Full article

The decarbonization of maritime transportation requires shipboard energy systems to coordinate conventional generators, renewable energy sources, energy storage devices, and thermal energy units under voyage-dependent operating constraints. This paper develops a configurable hybrid multienergy ship system for coordinated electrical and thermal energy scheduling. The proposed framework functionally separates the propulsion subsystem from the service and thermal subsystem while retaining system-level coordination among photovoltaic generation, wind generation, diesel generators, micro gas turbines, energy storage batteries, and thermal energy units. A convolutional neural network is employed to provide short-term photovoltaic power forecasts for day-ahead scheduling. The resulting scheduling problem simultaneously considers voyage completion, power balance, equipment operating limits, ramp-rate constraints, battery charging and discharging restrictions, operating costs, and pollutant emission treatment costs. The nonlinear operating logic is reformulated as a mixed-integer optimization problem and solved using CPLEX. A representative coastal voyage case study is used to evaluate the proposed framework. The results demonstrate that the method can coordinate multiple shipboard energy sources, satisfy the prescribed electrical and thermal demands, and provide a set of Pareto-optimal solutions describing the trade-off between operating cost and emission-related cost. The proposed framework provides a system-level scheduling approach for supporting the economic and low-carbon operation of hybrid multienergy ships under increasingly stringent maritime emission reduction requirements. Full article

Background: Neoadjuvant systemic therapy (NST) enables tumor downsizing and increases the feasibility of breast-conserving surgery (BCS) in patients with early breast cancer (EBC). Reliable tumor localization after NST remains challenging, particularly in patients with a complete clinical response. If clips are not visible on ultrasound, stereotactic mammography-guided wire localization is required, which involves additional radiation exposure and may increase patient discomfort and procedural complexity. The 3D-shaped Tumark^® Vision clip may enable ultrasound-guided localization after NST. Methods: In this prospective multicenter registry study (NCT04468113), 324 patients with biopsy-proven EBC scheduled for NST and breast-conserving surgery were enrolled across 19 German centers. Clip placement was performed under ultrasound guidance prior to NST, and clip detectability was assessed at predefined time points during therapy (4–8, 9–12, and ≥13 weeks after treatment initiation). Detection rates, visualization, and preoperative localization methods were recorded. Non-detectable clips required stereotactic wire localization, whereas ultrasound-guided localization was performed for detectable clips. Results: The preoperative detection rate was 91.1%. Clip detectability was higher in patients with longer NST durations and partial response by imaging. Ultrasound-guided wire localization was feasible in 214 patients (83.9%); among these, 165 patients (64.7%) underwent localization without and 49 patients (19.2%) with post-procedural mammographic verification. Stereotactic localization was required in 41 patients (16.1%), primarily due to non-visualization of the clip on ultrasound. The accuracy of ultrasound for residual tumor assessment was moderate (72.0%), with a sensitivity of 70.7%, indicating limitations in its ability to reliably assess residual tumor extent as a standalone modality. Conclusions: The 3D nickel–titanium clip enables ultrasound-guided tumor localization after NST in the majority of patients with early breast cancer, although additional mammographic guidance remains necessary in a relevant proportion of cases. Full article

Continuous carbon anode roasting in industrial parks requires a stable high-temperature heat supply and remains highly dependent on grid electricity and natural gas. However, existing energy-system studies rarely coordinate hydrogen production and storage, volumetric hydrogen blending, and temperature-graded waste-heat recovery under continuous production constraints. To address this gap, this study proposes an electricity–heat–gas–hydrogen integrated energy system for carbon anode industrial parks and develops a 24 h multi-objective scheduling model. The model coordinates heat demands at different temperature levels with hourly electricity and hydrogen flows, using surplus photovoltaic power to produce hydrogen for later high-load periods. The selected scheme achieves a daily volumetric hydrogen-blending ratio of 10.79%, with an operating cost of 82,985.75 CNY and carbon emissions of 54,371.53 kg. Relative to an otherwise equivalent non-hydrogen configuration, hydrogen coupling provides additional reductions of 7.2% in operating cost and 2.3% in carbon emissions. Compared with a basic conventional configuration, operating cost and carbon emissions decrease by 27.9% and 26.0%, respectively. Cascade recovery also increases the daily waste-heat utilization rate by approximately 30 percentage points. These results show that the proposed scheduling framework can coordinate hydrogen utilization and graded waste-heat recovery while maintaining continuous carbon anode production. Full article

Background/Objectives: Hospital performance is a multidimensional construct that cannot be adequately assessed using isolated financial, clinical, organizational, or patient-reported indicators. This study aimed to develop and evaluate an Integrated Multidimensional Hospital Performance Assessment Framework combining organizational management, healthcare quality, patient satisfaction, and cost efficiency. Methods: An observational, descriptive, comparative study was conducted using data collected during 2018–2019 from two Romanian public hospitals with different organizational profiles: a multidisciplinary general hospital and a monospecialty hospital. Organizational, operational, financial, and clinical indicators were analyzed comparatively. Patient satisfaction was assessed in 184 hospitalized patients, including 130 from the general hospital and 54 from the monospecialty hospital, using a structured questionnaire with excellent internal consistency (Cronbach’s α = 0.92). Cost efficiency was estimated using Stochastic Frontier Analysis based on hospital expenditure, activity, resource utilization, case complexity, and quality-related variables. Results: Significant differences were identified between the hospitals in staff composition, bed occupancy, outpatient activity, case-mix complexity, surgical activity, healthcare quality, and financial performance. Patient satisfaction was generally high in both institutions, although several dimensions differed significantly, particularly overall satisfaction, waiting time, physician consultation, treatment received, and adherence to the prescribed medication schedule. The general hospital had a lower mean cost-inefficiency score than the monospecialty hospital (0.253 vs. 0.395), corresponding to higher estimated cost efficiency (0.747 vs. 0.605; p < 0.001). Conclusions: The proposed framework offers a comprehensive and practical approach to hospital performance assessment, and its application in two public hospitals provides a proof-of-concept demonstration of feasibility. Further multicenter studies are required for external validation and assessment of its generalizability across different hospital settings. Full article

Post-disaster emergency wireless access–backhaul recovery requires limited capacity to be allocated across affected regions under nonnegativity and fixed-total-capacity constraints. We propose Recovery-Limiting Signal-Conditioned Action Decoding (RLS-CAD). Critical-region access outage, backhaul shortfall, traffic backlog, and end-to-end recovery deficit form regional score bases, while a 15-dimensional policy controls signal fusion, score correction, and finite-support simplex projection. Experiments use five training seeds and 100 shared test scenarios and retain both training and scenario variability. RLS-CAD outperforms Graph-PPO and both information-matched controls on FinalCap, CTI, and TaskUtility. The evaluation concerns normalized planning-level simulation; physical-layer scheduling is outside its scope. Full article

Sustainable urban disaster response requires Earth observation (EO) resources to be selected according to event demands, environmental conditions, sensing capabilities, and urban targets. This study proposes an Observation Linked Open Data (O-LOD)-based Urban Disaster Observation Task (UDOT) enhancement framework for semantic EO resource configuration. O-LOD organizes heterogeneous data through four dimensions, Event, Context, Subject, and Object, which an instantiation algorithm populates as task graphs. Layered GeoSPARQL queries then match thematic and analytical capabilities, qualify orbit-derived observation opportunities against context and object constraints, and rank feasible alternatives using the Observation Capability Evaluation Model (OCEM). Evaluation on the 2020 Khartoum flood and Bobcat wildfire narrowed 202 satellite–sensor pairs to three flood-capable and four wildfire-capable pairs and returned two Khartoum and eight Bobcat ranked opportunities, with complete queries executing in 3.0 s and 0.07 s. Constraint ablation and resolution sensitivity analyses identified the conditions governing the feasible set. Publicly accessible Sentinel, Landsat, and MODIS products corroborated both retained and excluded results, supporting water-extent and burn-severity mapping where coverage, spectral bands, and image quality met the task requirements. O-LOD therefore provides a traceable semantic link from disaster observation demand to qualified and ranked EO opportunities and subsequent image assessment, supplying task-oriented inputs for downstream scheduling and supporting context-aware sensing for sustainable urban disaster response. Full article

Modern energy systems, including those supporting transportation electrification, are increasingly exposed to volatile market conditions and external events. Effective decision-making therefore requires the integration of structured operational data with unstructured contextual information. Existing studies on Large Language Model (LLM)-assisted energy systems have mainly applied LLMs to individual tasks such as forecasting, scheduling, or decision support, while forecasting and control are typically treated separately. As a result, semantic information extracted from external events is not consistently propagated from market prediction to operational decision-making. This paper proposes a unified dual-stage framework in which the LLM functions as a shared semantic information processor, converting raw event data into structured representations used by both forecasting and control modules. In the forecasting stage, these representations improve price prediction under non-stationary conditions. In the control stage, the same information provides an event-aware contextual action prior for reinforcement learning-based energy management. This design allows external event information to inform both future-state estimation and subsequent control decisions, establishing a consistent connection between prediction and decision-making. The framework is evaluated using real-world electricity market data and a battery energy management environment. The results show that the proposed framework achieves the highest average cumulative reward among the evaluated methods while maintaining greater robustness than the forecasting-only LLM configuration. Overall, this work demonstrates the benefit of consistently propagating structured semantic information across forecasting and control and provides a viable approach to event-aware intelligent energy management, with potential extensions to multi-energy transportation systems and electrified mobility applications. Full article

Integrated electricity–gas–heat systems require coordinated scheduling while limiting data sharing and representing network constraints. This paper develops a day-ahead model incorporating reactive power, voltage magnitudes, network losses, demand response, and CHP/P2G coupling. Piecewise linearization and second-order cone relaxation reformulate the model as a mixed-integer second-order cone program, while a hierarchical ATC–ADMM method coordinates the electricity–heat and natural gas subsystems by exchanging coupling variables. Residual checks verify approximation accuracy and original equation feasibility. In the test system, ATC–ADMM reached consensus within five iterations, with a total-cost deviation of 0.0075% from centralized optimization, whereas ATC did not converge within 500 iterations. Coordinated operation reduced the total cost by 1.13%, and Shapley allocation benefited both subsystems. Increasing demand-side flexibility from 5% to 9% reduced the total cost by 0.88% and wind curtailment from 6.02% to 4.86%; increasing reactive compensation from 40% to 60% reduced the total cost by 0.41% and wind curtailment to 5.70%. The results reveal non-monotonic penalty-update effects and diminishing marginal benefits of flexibility resources, providing guidance for parameter selection and capacity allocation. Full article

Fixed-view visual sensors require normal-image reconstruction that preserves structural detail while exposing a local deviation in a residual map. Standard denoising diffusion probabilistic models (DDPMs) use spatially uniform corruption. We study an image-derived, structure-aware noise schedule for reference-image reconstruction, where the input image is available and the same importance map can be fixed in the forward and reverse processes. A matched three-seed diagnostic further isolates the effect of the semantic-training/gradient-reverse map substitution and of a lower bound on local noise. Map consistency recovers much of the unconditional FID loss, but neither it nor the attenuation floor yields a universal advantage over DDPM. The six-category MVTec AD residual study is likewise category dependent: the gradient/edge special case improves selected texture-localization outcomes but degrades several object-level outcomes. We therefore present the method as a reconstruction diagnostic, not as a competitive industrial anomaly detector or a universally superior generator. Full article

This exploratory randomized trial evaluated an eight-week combined isometric and elastic-resistance program in community-dwelling women aged 70 years or older. Forty-nine participants were randomized to exercise (EG; n = 24) or control (CG; n = 25). Twenty-two EG participants completed the intervention and follow-up; two had no post-intervention measurements because of scheduling conflicts. All randomized participants were included in the intention-to-treat analysis using 50 data sets generated by predictive mean matching and baseline-adjusted analysis of covariance. Compared with the CG, the EG showed lower body weight (adjusted mean difference [AMD], −0.45 kg), BMI (−0.19 kg/m²), 4 m gait time (−0.96 s), and five-repetition chair-stand time (−1.60 s), and higher skeletal muscle mass (0.38 kg), calf circumference (0.80 cm), and handgrip strength (1.01 kg). The corresponding primary 95% confidence intervals excluded zero, although the skeletal-muscle-mass interval narrowly included zero under conservative imputation. Differences in body fat percentage (−0.33 percentage points; 95% CI, −1.24 to 0.58) and tandem-stance time (0.79 s; 95% CI, −0.42 to 2.00) were inconclusive. These preliminary findings suggest that the program may improve selected body-composition and functional outcomes. Larger prospectively powered trials are required to confirm their magnitude, clinical relevance, and durability. Full article