Search Results (1,946)

The electrification of regional railway lines using battery-electric trains requires accurate simulation tools to support energy management and thermal control design. This paper presents an integrated dynamic simulation model of the traction system of a Hitachi Caravaggio ETR 521 regional train operating in battery-electric mode, developed in MATLAB/Simulink 2024b. The model incorporates all key drivetrain components, including a train reference generator, speed controller, motor controller, three-phase inverter, induction motor, a Kokam Co., Ltd. lithium-ion battery pack, and a detailed battery thermal management system. The proposed framework enables simultaneous evaluation of traction performance, battery state of charge (SOC) evolution, and thermal behavior under realistic conditions. To validate the model, simulations of the Treviso–Vicenza route were conducted under two scenarios: traction-only operation and operation with a 160 kW auxiliary load. Simulation results demonstrate that auxiliary loads significantly affect energy consumption and battery thermal behavior, with energy consumption increased by 50%. The results highlight the importance of integrating thermal effects into energy management and sizing decisions for battery-electric regional trains. The developed model provides a practical tool for optimizing battery sizing, thermal management strategies, and overall energy performance, supporting the planning and design of sustainable electric railway solutions. The modular MATLAB/Simulink architecture is designed to be route-agnostic; extension to other regional lines with different gradients, speed profiles, or extreme climate conditions (e.g., alpine routes or high-temperature regions) requires only updated route data and adjusted ambient boundary conditions, demonstrating the model’s broad applicability beyond the Treviso–Vicenza case study. Full article

With the increasing integration of transportation and energy systems, highway energy replenishment facilities are gradually evolving into hybrid refueling stations that integrate photovoltaic generation, energy storage, battery charging, and hydrogen refueling. However, due to differences in resource conditions across stations, independently operated hybrid refueling stations find it difficult to simultaneously improve overall economic performance and renewable energy utilization. To address this issue, this paper investigates the coordinated operation and distributed optimization of highway hybrid refueling stations. First, an inter-station hydrogen–carbon–green certificate trading framework is established, and a trading model for a cluster of hybrid refueling stations is then developed on this basis. Then, the inter-station trading problem is decomposed into two subproblems: symmetric trading volume determination and asymmetric Nash bargaining-based price determination. These two subproblems are solved in a distributed manner using the alternating direction method of multipliers. In addition, a hydrogen transportation model is developed to translate trading decisions into feasible transportation arrangements under highway network and hydrogen tube trailer scheduling constraints. Finally, the case study demonstrates that the proposed model enables multi-resource sharing among hybrid refueling stations, reduces the overall system cost by 21.30%, and achieves a fairer distribution of benefits among stations. Full article

Remote communities in Canada face high electricity costs, energy insecurity, and significant greenhouse gas emissions due to heavy dependence on diesel generation. This study proposes and evaluates an AC-coupled hybrid distribution microgrid for remote off-grid communities, using Black Tickle, Newfoundland and Labrador as a representative case study. The system integrates two 200 kW wind turbines, a 200 kW diesel backup generator, a 16 MWh lithium-ion battery storage system, and a bidirectional converter, modeled and optimized in HOMER Pro 3.18.3 using local meteorological data, community load profiles, and a cycle-charging dispatch strategy. The optimized configuration achieves 86.7% wind penetration and 100% supply reliability with zero unmet load, yielding a total net present cost of USD 13.6 million and a levelized cost of energy of 0.999 USD/kWh over a 25-year horizon. Battery storage accounts for 73.5% of annualized costs, representing the primary economic challenge for wider deployment. Sensitivity analyses show that diesel price fluctuations exert approximately 4.1 times greater influence on system economics than equivalent carbon pricing changes, while the optimal configuration remains robust across all tested policy scenarios. These findings demonstrate that AC-coupled wind–diesel–battery microgrids offer a viable pathway for reducing fossil fuel dependence and supporting clean energy transition in remote, harsh-climate communities. Full article

The removal of excessive amounts of antibiotics from water systems is of great benefit due to their adverse effects on the ecosystems, living organisms and the persistent increase in antibiotic resistance cases. This study was focused on the adsorption of vancomycin from a simulated aqueous medium using seaweed, a sustainable and low-cost adsorbent. Also, the work focuses on assessing the influence of surface modification on adsorption behaviour and determining if chemical treatment provides improvements over untreated seaweed. In particular, chemically modified seaweed and raw (non-modified) seaweed were assessed as adsorbents suitable for removing traces of vancomycin from water, as gauged from the results of High-Performance Liquid Chromatography (HPLC). In addition, Scanning Electron Microscopy (SEM), Fourier Transform Infrared spectroscopy (FT-IR) and the pH point of zero charge (pHpzc) were used to measure the surface characteristics of these adsorbents. The degree of antibiotic adsorption was evaluated as a function of different factors, including the pH, adsorbent dosage, contact time, ionic strength and initial concentration of vancomycin. Thermodynamic parameters, such as the enthalpy change (∆H°), the entropy change (∆S°) and the free-energy change (∆G°), were calculated. The FTIR analysis indicates that functional groups, such as carbonyl and hydroxyl groups, were involved in the adsorption process, and their modification influenced adsorption behaviour. It was observed that the adsorption of vancomycin by the modified seaweed was slightly lower (±94%) compared to the level achieved for the raw seaweed (±97%). These figures were obtained with an initial concentration of vancomycin of 25 µg/mL, a pH of the aqueous solution of 7.0, an adsorbent dose of 0.2 g and a contact time of 120 min. The results showed that untreated seaweed exhibited slightly higher adsorption efficiency than the treated seaweed, suggesting that chemical modification might not have enhanced adsorption performance. The thermodynamic parameters suggested that the adsorption process was exothermic and that adsorption was favourable for the untreated seaweed and less favourable for the treated seaweed. Regeneration studies showed a decrease in adsorption efficiency over repeated cycles. Although the adsorption capacity is lower than that of advanced nanomaterials, the use of seaweed offers an advantage in terms of low cost, availability and environmental sustainability. The comparable efficiency of the modified and untreated seaweed adsorbent suggests that seaweed adsorbents can be used as viable bio-adsorbents for the decontamination of water. Full article

Background: Conducting research in emergency departments and critical care units is crucial for improving patient management through evidence-based practices. Healthcare professionals and researchers in the field of traumatic brain injury (TBI) have a moral and legal obligation to inform patients before conducting any diagnostic test or therapy as part of a clinical study. However, challenges and barriers to conducting research in these high-pressure environments must be acknowledged. Shall the pathway to obtain informed consent in TBI-related research be revisited? We sought to map literature, identify gaps, and clarify the bioethics that should be followed in TBI-related research. Methods: A Scoping review was conducted to identify the obstacles and challenges investigators encounter in clinical and translational TBI research, with a specific emphasis on informed consent and regulatory impediments that often serve as bottlenecks or rate-limiting steps for participant enrollment and overall study success. This review used google scholar and Midline from inception to 2025. Results: Patients with TBI or their surrogates may be unable to provide informed consent within limited therapeutic windows. Despite international regulations and national laws, restrictions on obtaining consent are often criticized as ambiguous in certain situations. Furthermore, the fast-paced, emotionally charged atmosphere in emergency settings poses a risk of delaying crucial research interventions. There are accepted alternatives to informed consent, such as proxy consent, deferred consent, exceptions from consent, and waivers of consent, which are ethically and socially acceptable and compliant with regulations. However, these alternatives are underutilized or may be abused in some cases. Conclusions: This review calls for clarifying and modifying arbitrary regulatory restrictions on research and streamlining the Common Rule. Scientists should also share their innovative solutions to strike a balance between ethical considerations and the minimization of research barriers. Full article

Electrohydrodynamic effects can significantly alter transport processes in reacting flows, even when the plasma is weakly ionized. However, predictive modeling of such plasma–flame interactions remains challenging due to the multiscale coupling among charge transport, fluid motion, and chemical kinetics. This study presents a charge-transport closure model to investigate electrohydrodynamic influences on laminar non-premixed flames. A two-dimensional computational framework in cylindrical coordinates is used to simulate plasma-assisted methane–air diffusion flames under weak electric-field conditions representative of practical combustion environments. To represent plasma–flow coupling in a computationally feasible yet physically consistent manner, a charge-transport formulation based on the drift–diffusion approximation is employed. The model solves transport equations for representative positive and negative charge carriers coupled with Poisson’s equation for the electric potential to obtain a self-consistent electric field. This formulation assumes a weakly ionized regime for low-temperature plasma-assisted combustion, in which neutral species dominate the mass and momentum transport, while ionization chemistry is simplified and charge transport primarily influences the flow through electrohydrodynamic body forces and Joule heating. Assuming a weak electric field, the steady flamelet model is applied, in which plasma effects primarily influence scalar transport and local thermal balance rather than inducing significant bulk ionization dynamics. The governing equations are discretized using a high-order compact finite-difference scheme that provides improved resolution of steep gradients in temperature, species concentration, and space-charge density near thin reaction zones. The canonical laminar flame model configuration was validated using the established laminar methane–air diffusion flame benchmark, and steady-state spatial profiles of key transport properties were evaluated. Two-dimensional analysis identified the discharge coupling location as an important factor. The application of discharge in the fuel-air mixing region leads to a clear restructuring of the flame. When the discharge is activated, electrohydrodynamic forcing and ion-driven momentum transfer produce a highly localized, columnar flame with sharp gradients and a confined reaction zone. Compared with the baseline case, the plasma-assisted flame localizes the OH-rich reaction zone, confines the high-temperature region into a narrow column, and enhances downstream H₂O formation. Full article

External electricity supplementation for islanded microgrids at expressway service areas is often settled under tiered electricity pricing based on cumulative energy consumption, where marginal prices increase discontinuously once tier thresholds are exceeded. This mechanism reshapes battery dispatch behavior and may alter economically optimal storage sizing. This paper proposes a unified planning—operation optimization framework for wind–PV–battery microgrids that jointly determines the storage capacity and hourly scheduling while enforcing power balance, battery state-of-charge dynamics, and tiered settlement costs. By introducing tier-wise energy allocation variables and tier cap constraints, the nonlinear settlement rule is reformulated into an equivalent piecewise-linear structure, leading to a mixed-integer linear programming (MILP) model that can be solved using standard optimization solvers. A season-weighted annualized case study using four typical seasonal days reveals critical cross-tier dispatch behaviors, where charging–discharging schedules shift near tier boundaries and external electricity purchases are actively suppressed from entering higher-priced tiers. The proposed framework quantifies the premium-avoidance value of storage and provides a practical decision support tool for premium risk-aware sizing and operation of islanded expressway service-area microgrids. Full article

Background/Objectives: Patients with adrenal insufficiency (AI) are at an increased risk of adverse events (AEs) during cardiovascular hospitalization. However, the association between AI and takotsubo cardiomyopathy (TCM) remains unclear. We investigated the association between AI and cardiovascular outcomes in patients with TCM. Methods: We analyzed data on patients with TCM included in the 2019 Nationwide Readmissions Database to compare in-hospital outcomes between patients with and without AI. The primary outcome measure was inpatient mortality. Secondary outcomes included the odds of all-cause 90-day readmission, acute kidney injury (AKI), mechanical ventilation use, vasopressor use, cardiogenic shock, length of stay (LOS), and total hospitalization charges (THC). Multivariate regression models were used to adjust for confounding variables. Results: Among 30,987 cases, 0.59% (n = 183) had concomitant AI. AI was associated with higher odds of in-hospital mortality (adjusted odds ratio [aOR] 3.32, 95% confidence interval [CI] 1.43–7.74, p = 0.005), cardiogenic shock (aOR 5.28, 95% CI 3.16–8.82, p < 0.001), mechanical ventilation use (aOR 3.20, 95% CI 1.78–5.74, p < 0.001), AKI (aOR 1.96, 95% CI 1.11–3.48, p = 0.021), vasopressor use (aOR 4.59, 95% CI 1.56–13.47, p = 0.006), longer LOS (6.84 vs. 3.67 days, p < 0.001), and higher THC ($97,419 vs. $54,574, p < 0.001). Additionally, AI was associated with lower odds of all-cause 90-day readmissions (aOR 0.44, 95% CI 0.25–0.79, p = 0.006). Conclusions: Among patients with TCM, AI was associated with higher odds of fatal and non-fatal adverse events. Further studies are required to confirm these findings and better understand how to improve outcomes in this high-risk population. Full article

To address the coupled challenges of renewable power volatility, high operating cost, and electrolyzer degradation in grid-connected wind–PV hydrogen production systems, this paper proposes a hierarchical day-ahead scheduling strategy under time-of-use (TOU) electricity prices. The upper layer performs price-responsive economic dispatch to coordinate renewable utilization, battery operation, grid transactions, and aggregate hydrogen-production power with the objective of minimizing lifecycle operating cost. The lower layer introduces a health-aware non-uniform rotation mechanism to allocate the aggregate power command among electrolyzer units, thereby reducing fluctuation exposure and balancing lifetime consumption across the array. Practical constraints, including multi-state electrolyzer operation, unit-commitment logic, battery state-of-charge dynamics, hydrogen storage limits, and system power balance, are explicitly considered. A case study of a wind–PV hydrogen production project in Northern China shows that the proposed strategy shifts electricity purchases to valley-price periods and promotes electricity export during peak-price periods. Compared with the benchmark strategy, hydrogen production during low wind–PV generation periods increases from 342,000 to 381,000 Nm³, the share of fluctuating operating time decreases from 62.5% to 12.5%, and the average daily start–stop frequency declines from 8.0 to 4.8. Consequently, the degradation penalty is reduced by about 40%, and lifecycle operating cost decreases by 27.3%. Full article

Under fault conditions, Photovoltaic-Storage-Charging Integrated Stations (PSCISs) are regarded as a key resource for enhancing distribution network resilience. However, traditional centralized optimization fails to account for conflicts of interest between the distribution network and PSCISs and neglects the actual response behavior of EV users. To address these issues, a coordinated emergency operation strategy for distribution networks and PSCISs based on the master–slave game is proposed. Firstly, a bilevel optimization framework based on the master–slave game is constructed, where the upper level performs system-level coordination and the lower level handles autonomous decision-making. For the upper level, the minimization of distribution network operation cost is set as the optimization objective by the dispatching center to determine power purchase prices and load shedding rates, which serve as guidance signals for lower-level PSCISs. In terms of the lower level, a dual-factor S-shaped response curve is introduced into the lower-level model to precisely characterize EV users’ nonlinear response behavior to price incentives. Furthermore, based on the signals received from the upper level, the maximization of each PSCIS’s profit is set as the optimization objective to determine the PV output, storage dispatch, and V2G incentive prices. Subsequently, Model Predictive Control (MPC) is employed to implement rolling optimization during the fault period, addressing the source-load uncertainties. Finally, an improved IEEE 33-node distribution network is used for case analysis and validation of the proposed operation strategy. The results indicate that the proposed strategy can effectively coordinate the interests of multiple parties, achieving synergistic improvements in both the economy and reliability of the distribution network. Full article

Amid the global decarbonization of urban transportation, the large-scale deployment of electric buses faces major challenges, including concentrated charging demand, increased peak electricity demand, and inefficient energy utilization at transit depots. Existing studies usually optimize depot energy system configuration and bus scheduling separately, which often leads to biased system-level decisions. To address this limitation, this study proposes a collaborative optimization framework that integrates cross-line scheduling with the configuration of photovoltaic–storage–charging systems at depots to improve overall resource utilization. Specifically, this study formulates a mixed-integer linear programming (MILP) model to minimize the total daily system cost. The proposed model comprehensively captures multiple factors, including the costs of bus investment, charging infrastructure, photovoltaic deployment, energy storage deployment, and carbon emissions. In this study, Benders decomposition is used as a solution framework to handle the coupling structure of the model. Case studies show that, compared with conventional operation modes, the combination of cross-line scheduling and fast charging technology produces a significant synergistic effect. This combination reduces the required fleet size from 17 to 14 buses and substantially lowers investment in depot infrastructure, thereby minimizing the total system cost. Sensitivity analysis further shows that the deployment scale of photovoltaic systems has a clear threshold effect on electricity costs, whereas the core economic value of energy storage systems depends on peak shaving and arbitrage under time-of-use electricity pricing. Overall, this study demonstrates the critical role of integrated planning in improving the economic efficiency and operational feasibility of electric bus systems. It provides important theoretical support and practical guidance for depot design and resource scheduling in low-carbon public transportation networks. Full article

X-ray imaging of dense breasts and breast implants often suffers from reduced lesion visibility because strong attenuation lowers contrast, while conventional rhodium (Rh) K-edge filtering suppresses part of the high-energy spectral tail. This study presents a Monte Carlo framework for spectroscopic mammography using a voxelated 1 mm thick cadmium telluride (CdTe) sensor and a first-order detector interaction model to evaluate energy-dependent image quality. The model reproduces fluorescence and inter-voxel energy redistribution in CdTe, but not the full detector chain, and remains idealized with respect to charge transport, carrier collection, threshold dispersion, and pile-up. Energy-resolved simulations in the 10–50 keV range were used to compute spectroscopic contrast-to-noise ratio (CNR) curves and to form integrated-spectrum (IS) images for four tested spectra. For the dense-breast calcium hydroxyapatite (HA) speck detection task considered here, and under the present simulation assumptions, replacing the standard 28 kVp + 50 μm Rh spectrum with 28 kVp + 1 mm Al increased the simulated IS image CNR by 23.11%, with an approximately 5% increase in estimated primary-incident air kerma at the phantom entrance plane. Preliminary experimental implant-phantom images were included as a qualitative feasibility check, showing a trend consistent with simulations. Within the limits of this task-specific simulation, the results suggest that preserving the transmitted high-energy tail can improve HA speck visibility for the present 1 mm CdTe photon-counting detector, with the 28 kVp + 1 mm Al spectrum outperforming the other tested cases. Full article

The growing flexibility of load dispatching in modern smart grids has exposed critical limitations in conventional capacity pricing mechanisms, which calculate charges based solely on monthly maximum demand without distinguishing when peak demand occurs. This approach fails to reflect the temporal value of capacity and provides insufficient incentives for demand-side optimization. To address these challenges, this paper proposes a time-of-use (TOU) capacity pricing method that integrates user load characteristics to enable more equitable cost allocation and optimized electricity consumption patterns. The methodology employs K-means clustering analysis of user load profiles to partition pricing periods, accurately capturing differential capacity value across temporal intervals. We validate the clustering approach through the elbow method and silhouette analysis, confirming k = 3 as optimal and demonstrating K-means superiority over hierarchical and density-based alternatives. This data-driven approach ensures that period delineation reflects actual consumption patterns of commercial and industrial users. A capacity cost allocation model is established using the Shapley value method, incorporating maximum demand in each designated period while maintaining revenue neutrality for the grid operator. The 80% load simultaneity factor is empirically validated using 12 months of Shanghai industrial data (May 2023–April 2024). A Stackelberg game-based pricing model for TOU capacity tariffs is developed, incentivizing users to deploy energy storage systems and optimize charging strategies. We prove game convergence theoretically and demonstrate equilibrium achievement within 3–5 iterations across diverse initialization scenarios. Energy storage capacity is optimized by sector (3.5–6.5% of peak demand) rather than uniformly, and realistic battery self-discharge rates (0.006%/hour) are incorporated. Case study analysis using real operational data from 11 commercial and industrial sub-sectors in Shanghai demonstrates effectiveness. Extended to 12 months with seasonal analysis, results show the proposed strategy reduces the peak-to-valley difference ratio by 2.4% [95% CI: 1.9%, 2.9%], p < 0.001; increases the system load factor by 1.3% [95% CI: 0.9%, 1.7%], p < 0.001; and achieves reductions in users’ total capacity costs of 3.6% [95% CI: −4.2%, −3.0%], p < 0.001. Comparative analysis shows the proposed method significantly outperforms simple TOU (improvement +1.2 pp) and peak-responsibility pricing (improvement +0.6 pp). Monte Carlo robustness analysis (1000 scenarios) confirms performance stability under demand uncertainty. This research provides theoretical foundations and practical methodologies for capacity cost allocation, offering valuable insights for policymakers and utilities seeking to enhance demand-side response mechanisms and improve power resource allocation efficiency. Full article

Wind–solar coupled hydrogen production DC microgrids have significant potential for improving renewable energy utilization and reducing the cost of hydrogen production. However, the randomness of wind–solar power causes frequent electrolyzer start–stop operations, accelerating lifetime degradation, while a single energy storage system cannot simultaneously suppress power fluctuations and regulate energy. Therefore, this study proposes a two-stage day-ahead energy scheduling optimization framework. A DBSCAN–K-means hybrid clustering method generates representative wind–solar power scenarios. A supercapacitor-based strategy mitigates high-frequency power fluctuations using empirical mode decomposition. Furthermore, a dual-scenario-driven electrolyzer scheduling strategy adapted to different wind–solar output conditions is developed, where power allocation is determined by battery state-of-charge and electrolyzer operating states, enabling stepwise power compensation and dynamic operating-state optimization. Case studies comparing wind–solar-only supply, a conventional strategy, and the proposed strategy demonstrate that the proposed strategy balances hydrogen production and economic objectives, and reduces annual electrolyzer start–stop cycles by 73%, thereby prolonging electrolyzer lifetime. Furthermore, the proposed framework enhances renewable energy utilization, reduces curtailment, and lowers lifecycle costs, thereby contributing to the development of sustainable hydrogen production systems. Full article

Steroid hormones (SHs) have a high estrogenic potential, and urban wastewater is one of their main ways into the aquatic environment. Constructed wetlands (CWs) are considered one of the most sustainable alternatives for the treatment of wastewater from small communities. However, the use of gravel and sand implies a significant environmental impact associated with their extraction and transport. A more sustainable alternative is the use of plant residues, as they are abundant, inexpensive, and readily available, and they can improve the efficiency of hormone removal through sorption. Thus, the sorption of 15 SHs was studied on conventional, mineral substrates (gravel, sand, and volcanic ash) and alternative vegetal wastes, i.e., mulches from giant reed, palm tree, balsa wood, and pine needles. These materials were characterized by determining their Point of Zero Charge (pH_PZC), ash content, content of leachable polycyclic aromatic hydrocarbons (PAH) and heavy metals, total surface area (BET), and pore characteristics. Results indicated that SH sorption on the mineral substrates was quite low, in most cases less than 10–15%. However, in the mulches it reached between 50 and 95%, except for corticosteroids (11–43%). The pseudo-second-order kinetics provided the best fit in all cases, with R² values between 0.97 and 0.9999. Experiments with a contact time of 7 days showed that the palm tree was the only substrate that completely removed the three corticosteroids studied (cortisone, prednisone, and prednisolone). Additionally, a significant correlation was observed between removal due to sorption (%) and log octanol–water partition coefficient (log Kow). Freundlich isotherm provided a higher number of best fits than Langmuir. Lastly, to compare sand with palm mulch under more realistic experimental conditions, four lab-scale CWs (two with palm mulch and two with sand, with/without plants) were studied. The sand-based CWs achieved faster SH percentage removals, while after 24 h, SH mass removals were significantly higher in the palm mulch-based CWs. Full article