Search Results (234)

The increasing penetration of renewable energy is driving the use of grid-forming energy storage (GFM-ES) for black start in pure renewable power grids. However, practical implementation is challenged by three coupled problems: transient voltage overshoot during bus energization, imbalance of state of charge (SOC) among distributed storage units during islanded operation, and synchronization shocks during grid reconnection. This paper proposes a coordinated multi-stage black-start strategy that integrates (1) an improved V/f startup control with a two-segment voltage reference to soften bus energization; (2) an SOC-aware adaptive droop law based on a bounded arcsine SOC index to balance the charge/discharge effort among distributed storage units; and (3) a virtual-capacitor-based phase-angle control to accelerate synchronization before grid connection. Compared with existing black-start schemes, the proposed framework provides stronger voltage regulation, better SOC consistency, and shorter synchronization time in a pure renewable scenario. The method is validated through PSCAD/EMTDC simulations and an engineering case study of the Ejina pure renewable grid. Full article

Tirzepatide, a dual glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide 1 (GLP-1) receptor agonist, introduces a mechanistically distinct approach within incretin-based therapies. While its efficacy is established, real-world data comparing post-marketing safety with established GLP-1 receptor agonists remain limited. This study assessed System Organ Class (SOC)-level reporting patterns for tirzepatide versus semaglutide and liraglutide using EudraVigilance data. Aggregated individual case safety reports (ICSRs) were analyzed using pairwise disproportionality analyses based on a case/non-case approach. Reporting odds ratios (RORs) with 95% confidence intervals were calculated. False discovery rate (FDR) correction using the Benjamini–Hochberg procedure and sensitivity analyses restricted to serious and healthcare professional–reported cases were performed to assess robustness. After FDR adjustment, 20 SOCs were significant in tirzepatide–semaglutide and 23 in tirzepatide–liraglutide comparisons; eight SOCs remained significant across all analytical conditions. Compared with semaglutide, tirzepatide showed higher reporting for immune (ROR 1.97, 95% CI 1.75–2.21) and hepatobiliary disorders (ROR 1.71, 95% CI 1.61–1.82). Versus liraglutide, higher odds occurred for musculoskeletal (ROR 2.02, 95% CI 1.85–2.21) and psychiatric disorders (ROR 2.14, 95% CI 1.99–2.30), and lower odds for neoplasms (ROR 0.28, 95% CI 0.26–0.31). Tirzepatide shows heterogeneous reporting patterns compared with GLP-1 receptor agonists, with consistent excess reporting for hepatobiliary, immune, and musculoskeletal disorders. These findings are hypothesis-generating and warrant confirmation in exposure-adjusted studies. Full article

High-resolution mapping of soil organic carbon (SOC) in arid regions remains challenging. Using Xinjiang as a case study, this research constructed a prediction framework integrating Boruta feature selection with the Random Forest (RF) algorithm to achieve refined mapping of topsoil SOC. Results indicated that: (1) Among the tested machine learning models, the Boruta–RF framework achieved the highest predictive performance (R² = 0.48, with the lowest RMSE); (2) Evapotranspiration (ET) and Vapor Pressure Deficit (VPD) were dominant drivers, with the stepwise increase in ET and negative inhibition of VPD confirming the decisive role of hydrothermal fluxes in regulating carbon input; (3) The total SOC storage was estimated at approximately 3.20 Pg C. Despite low carbon density, the desert ecosystem contributed 44.33% of the total storage, constituting a massive Sparse Carbon Pool. This study confirms the necessity of incorporating hydrothermal parameters and highlights that neglecting desert ecosystems leads to a significant underestimation of regional carbon storage. Full article

Battery-electric residential storage systems can increase the self-consumption of photovoltaic (PV) generation; however, economical sizing typically requires a high-resolution time series of PV production and household load behind the meter. In practice, such data are often unavailable. This work therefore presents a simulation model for determining the economically optimal residential storage capacity based exclusively on smart-meter data at the point of common coupling (PCC), i.e., hourly import and export time series. Economic performance is assessed using net present value (NPV) over a multi-year evaluation horizon. In addition, technical constraints (SoC limits, power limits, charging/discharging efficiencies) as well as capacity degradation are considered via a semi-empirical aging model. For validation, a reproducible reference scenario is constructed using PVGIS generation data and the standard load profile H23, enabling a direct comparison between the conventional approach (consumption/generation) and the PCC approach (import/export). The results show that the capacity optimum can be reproduced consistently using PCC data, even under smart-meter-like integer kWh quantization. At the same time, large parts of the investigated parameter space indicate that, under the assumed scenarios, foregoing a storage system is often not economically sensible. Sensitivity analyses further highlight the strong impact of load shifting, in particular due to the charging time of electric vehicles. A case study using real PCC measurement data, together with a two-week-window analysis, demonstrates practical applicability and robustness under limited measurement durations. Full article

This work presents the development and validation of a 1D finite-volume model for the simulation of planar solid oxide cells (SOCs), developed for integration in more complex systems and process simulations. The model allows to investigate the temperature, composition, and current density profiles along the channel. In this work, the Fick’s equations typically used to calculate the concentration overpotential due to H₂ and H₂O diffusion in the electrode are improved compared to 1D SOC models available in the literature. In particular, the approximate analytical solution of the dusty gas model (DGM) equations allows for a better definition of H₂ and H₂O mixture diffusion coefficients, which are relevant, for instance, in the case of solid oxide fuel cells (SOFCs) fed with reformate gas mixtures. Differently from other 1D models available in the literature, the model developed is validated using experimental SOFC polarization curves covering a wide range of operating conditions in terms of molar fraction of H₂ (21–93%) and H₂O (7–50%) in the fuel, temperature (550–750 °C), and fuel utilization factor (exceeding 90%), demonstrating that 1D SOC models retain a good description of the physical processes occurring within the cell. While this work focuses on a co-flow SOFC configuration, the model can simulate a counter-flow configuration and electrolysis operation without modifying the model equations. Full article

In this study, an adaptive state-of-charge (SOC) boundary strategy (ASBS) is proposed that dynamically adjusts the admissible upper and lower SOC limits of second-life lithium-ion batteries in off-grid photovoltaic battery energy storage systems (PV-BESSs) based on real-time state of health (SOH) and temperature feedback. The strategy is formulated using a unified electrical–thermal–aging model with an online state estimator and ensures both electrical safety and power feasibility while remaining fully compatible with standard energy management functions. Two representative simulations—a single-day operating profile and a continuous thirty-day sequence—demonstrate the effectiveness of the ASBS. In the twenty-four-hour case, the duration spent in high state-of-charge conditions is reduced by approximately 0.30–0.50 h, the abrupt end-of-charging transition is eliminated, and the temperature rise is slightly moderated, all without any loss of energy supply. Over thirty days, the difference between the ASBS and a fixed state-of-charge window remains effectively zero for almost all hours, with only a brief midday deviation of −4 to −5 percentage points and no cumulative drift. Indicators of electrical and thermal stress improve substantially, including an approximate 70% reduction in the root mean square charging current. These results confirm that the ASBS provides a practical and non-intrusive means of mitigating stress on second-life lithium-ion batteries while preserving full energy autonomy in off-grid photovoltaic systems. Full article

The development of urban green infrastructures (UGI) is considered among the main nature-based solutions for climate mitigation in cities; however, the role of soils in the carbon (C) balance of UGI ecosystems remains largely overlooked. Urban green spaces are typically dominated by constructed Technosols, created by adding organic materials on top of former natural or agricultural subsoils. The combined effects of land-use history and current UGI management result in a high spatial variation of soil organic carbon (SOC) stocks and soil CO₂ emissions. Our study aimed to explore this variation for the case of Wageningen University campus. Developed on a former agricultural land, the campus area includes green spaces dominated by trees, shrubs, lawns, and herbs, with well-documented management practices for each vegetation type. Across the campus area (~32 ha), a random stratified topsoil sampling (n = 90) was conducted to map the spatial variation of topsoil (0–10 cm) SOC stocks. At the key sites (n = 8), representing different vegetation types and time of development (old, intermediate, and recent), SOC profile distribution was analyzed including SOC fractionation in surface and subsequent horizons, as well as the dynamics in soil CO₂ emissions, temperature, and moisture. Topsoil SOC contents on campus ranged from 1.1 to 5.5% (95% confidence interval). On average, SOC stocks under trees and shrubs were 10–15% higher than those under lawns and herbs. The highest CO₂ emissions were observed from soil under lawns and coincided with a high proportion of labile SOC fraction. Temporal dynamics in soil CO₂ emissions were mainly driven by soil temperature, with the strongest relation (R² = 0.71–0.88) observed for lawns. Extrapolating this relationship to the calendar year and across the campus area using high-resolution remote sensing data on surface temperatures resulted in a map of the CO₂ emissions/SOC stocks ratio, used as a spatial proxy for C turnover. Areas dominated by recent and intermediate lawns emerged as hotspots of rapid C turnover, highlighting important differences in the role of various UGI types in the C balance of urban green spaces. Full article

Background/Objectives: Gastroenteritis remains a major global health concern, particularly in resource-limited regions, where rapid and accurate diagnosis is crucial for effective patient management. Syndromic multiplex PCR panels, such as the FilmArray gastrointestinal (FAGI) panel, offer the potential to significantly improve diagnostic yield and turnaround time, enabling more targeted treatments and reducing unnecessary antibiotic use. However, real-world data on their performance in low-resource settings remains scarce. This study evaluates the performance, clinical impact, and cost-effectiveness of the FAGI panel compared to standard of care (SOC) diagnostic methods in gastroenteritis cases at São José Hospital for Infectious Diseases in Fortaleza, Brazil, an HIV Reference Center, in a resource-limited region of a middle-income country. Methods: A retrospective observational study was conducted among patients tested with FAGI (n = 161) and a retrospective control group tested only with SOC methods (n = 166). Results: The FAGI panel was associated with a significant reduction in the turnaround time, antimicrobial use, and total treatment costs while increasing the pathogen detection rate. Specifically, the median diagnostic time was reduced by 18%, with an increase in pathogen detection compared to SOC methods (64% positivity compared to 32%). Moreover, the FAGI group experienced a 30% reduction in antibiotic use, with a corresponding 83% reduction in antimicrobial costs. Conclusions: These results suggest that the FilmArray panel may offer substantial benefits in terms of efficiency and cost savings, highlighting its potential for broader implementation in clinical practice, especially in resource-limited settings, to improve patient outcomes in infectious disease management. Full article

Background: Providing complex care and support for people with technology dependence (PwTD) is challenging, even under routine conditions. During disasters, when health and power infrastructure are disrupted, the complex care of PwTD must be maintained under extreme conditions. This research aims to summarize the specific needs of PwTD in disasters and to describe how these needs are addressed in real-life events. Methods: We conducted a scoping review, searching four databases (CINAHL, MEDLINE, PsycInfo, SocINDEX) and the websites of relevant disaster relief organizations. A total of 43 of 2625 screened records were included. Content analysis was used to identify and cluster the needs of PwTD and the response to these needs. Results: Case reports were the most reported types of literature. It was repeatedly stated that PwTD have complex care needs that are often difficult to meet in disaster situations. The review identified three interdependent clusters of needs: clinical and supportive care needs, aids and supply needs, and access needs. The needs of patients and relatives were, as far as the situation allowed, met in accordance with existing plans and guidelines and, where these were found to be inadequate, through creative solutions devised by frontline nurses. Conclusions: We conclude that addressing the complex care needs of PwTD in disasters requires a strategy integrating structural preparedness, professional adaptability, and user participation. Nurses could play a key role in developing and implementing such strategies. This review provides a starting point to develop a more practice-oriented research agenda to achieve inclusive disaster risk management. Full article

Background: Interleukin-1 (IL-1) inhibitors are approved for the treatment of various inflammatory diseases associated with immune system abnormalities. However, large-scale real-world studies to assess their security are still limited. Therefore, a pharmacovigilance study was conducted based on the data from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Methods: Adverse events (AEs) linked to IL-1 inhibitors were analyzed using the FAERS database from Q1 2004 to Q3 2024. Risk signals were identified through disproportionality analysis algorithms, including reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS). Results: Among 17,670 AE reports where an IL-1 inhibitor was the “primary suspected” drug, 27 significant system organ classes (SOCs) were identified. Notable signals included infections and infestations (ROR: 2.31, 95% CI: 2.25–2.37) and congenital, familial, and genetic disorders (ROR: 2.26, 95% CI: 2.05–2.48). At the preferred term (PT) level, 263 significant AE signals were detected, such as pyrexia (ROR: 5.27, 95% CI: 5.03–5.53), nasopharyngitis (ROR: 2.31, 95% CI: 2.10–2.54), and injection site erythema (ROR: 6.09, 95% CI: 5.67–6.55). Importantly, we also identified less common or previously unreported AEs, including cardiac disorders (e.g., postural orthostatic tachycardia syndrome with anakinra; pulmonary valve incompetence with rilonacept) and endocrine disorders (e.g., secondary adrenocortical insufficiency with canakinumab). Furthermore, 36.33% of cases emerged after more than 360 days of treatment with IL-1 inhibitors. Conclusions: This study revealed real-world safety data on IL-1 inhibitors, providing important insights to enhance the clinical use of IL-1 inhibitors and minimize potential AEs. Full article

The purpose of this study is to monitor the battery performance of plug-in hybrid electric vehicles (PHEVs) on a chassis dynamometer using the US06, NEDC, and EPA highway driving cycles. The chassis dynamometer simulates vehicle operation and driving conditions and allows for precise simulation of pre-defined driving cycles, including simulations of acceleration, deceleration, stopping, and re-acceleration on the road. In the case of the US06 driving cycle, the results for (EV mode) compared with energy consumption during electric testing revealed a consistent decrease in the SOC (state of charge) due to the rapid response of the electric motor distribution to the changing power, as well as electric power fluctuations during driving conditions. Under the NEDC, the test results for electric power (EV) compared with energy consumption during electric testing revealed that the SOC gradually decreased at the start of the test due to low driving speeds. Towards the end, at around 800 s, an increase in driving speed resulted in a noticeable drop in SOC. The electric power varied during the driving cycle in this test due to the motor’s rapid response to changes in power distribution while driving. For the EPA Highway driving cycle test, the test results for electric power (EV) compared with energy consumption during continuous electric testing indicated a gradual decrease in the SOC at first due to low driving speeds. As the driving speed increased after about 300 s, the SOC rapidly decreased. Because of the motor’s quick response to changes in the power distribution while driving, the electric power varied according to the driving cycle. Full article

The growing integration of plug-in electric vehicles (PEVs) into microgrids presents both challenges and opportunities, particularly through vehicle-to-grid (V2G) services. This paper proposes a dynamic horizon optimization (DHO) framework with adaptive pricing for real-time scheduling of PEVs in a renewable-powered microgrid. The system integrates solar and wind energy, V2G capabilities, and time-of-use (ToU) tariffs. The DHO strategy dynamically adjusts control horizons based on forecasted load, generation, and electricity prices, while considering battery health. A PEV-specific pricing scheme couples ToU tariffs with system marginal prices. Case studies on a microgrid with four heterogeneous EV charging stations show that the proposed method reduces peak load by 23.5%, lowers charging cost by 12.6%, and increases average final SoC by 12.5%. Additionally, it achieves a 6.2% reduction in carbon emissions and enables V2G revenue while considering battery longevity. Full article

Background/Objectives: Human immunodeficiency virus (HIV) continues to be a global public health concern. Several antiretroviral drugs have been approved for the treatment, post-exposure, and pre-exposure prophylaxis of HIV. Darunavir (DRV) is a protease inhibitor (PI) approved for the management of HIV globally. This study aims to generate safety signals for DRV through data mining and analysis of adverse events (AEs) reported to the United Kingdom (UK) Medicines and Healthcare products Regulatory Agency (MHRA) Yellow Card Scheme. Methods: Disproportionality analysis was conducted using reporting odds ratio (ROR), proportional reporting ratio (PRR), and Bayesian confidence propagation neural network (BCPNN) approaches to identify potential safety signals. Results: The MHRA database contained n = 779 reports (n = 1791 AEs) attributed to DRV. The majority of AEs were reported for males. Positive safety signals were identified at both the system organ class (SOC, n = 5) and preferred term level (PT, n = 95). At SOC level, endocrine disorders emerged as a signal of interest n = 33 cases (ROR: 8.17, 95% CI: 5.78–11.56; PRR:7.96, 95% CI: 5.68–11.15; and IC: 2.85, IC025: 2.51). Among the results, 40 new potential safety signals are not listed on the product labelling in the UK. These include serious AEs such as cerebrovascular accident, brain injury, thrombosis, and pregnancy, puerperium, and perinatal AEs. Conclusions: This study provides additional real-world safety data for DRV in the UK and paves the way for future observational studies to investigate the identified safety signals. Full article

The increasing deployment of islanded microgrids in disaster-prone and infrastructure-constrained regions has elevated the importance of resilient energy storage systems capable of supporting autonomous operation. Grid-forming energy storage (GFES) units—designed to provide frequency reference, voltage regulation, and black-start capabilities—are emerging as critical assets for maintaining both energy adequacy and dynamic stability in isolated environments. However, conventional storage planning models fail to capture the interplay between uncertain renewable generation, time-coupled operational constraints, and control-oriented performance metrics such as virtual inertia and voltage ride-through. To address this gap, this paper proposes a novel distributionally robust optimization (DRO) framework that jointly optimizes the siting and sizing of GFES under renewable and load uncertainty. The model is grounded in Wasserstein-metric DRO, allowing worst-case expectation minimization over an ambiguity set constructed from empirical historical data. A multi-period convex formulation is developed that incorporates energy balance, degradation cost, state-of-charge dynamics, black-start reserve margins, and stability-aware constraints. Frequency sensitivity and voltage compliance metrics are explicitly embedded into the optimization, enabling control-aware dispatch and resilience-informed placement of storage assets. A tractable reformulation is achieved using strong duality and solved via a nested column-and-constraint generation algorithm. The framework is validated on a modified IEEE 33-bus distribution network with high PV penetration and heterogeneous demand profiles. Case study results demonstrate that the proposed model reduces worst-case blackout duration by 17.4%, improves voltage recovery speed by 12.9%, and achieves 22.3% higher SoC utilization efficiency compared to deterministic and stochastic baselines. Furthermore, sensitivity analyses reveal that GFES deployment naturally concentrates at nodes with high dynamic control leverage, confirming the effectiveness of the control-informed robust design. This work provides a scalable, data-driven planning tool for resilient microgrid development in the face of deep temporal and structural uncertainty. Full article

Understanding the degradation behavior of lithium-ion batteries under realistic application conditions is critical for the design and operation of Battery Energy Storage Systems (BESS). This research presents a modular, cell-level simulation framework that integrates electrical, thermal, and aging models to evaluate system performance in representative utility and residential scenarios. The framework is implemented using Python and allows time-series simulations to be performed under different state of charge (SOC), depth of discharge (DOD), C-rate, and ambient temperature conditions. Simulation results reveal that high-SOC windows, deep cycling, and elevated temperatures significantly accelerate capacity fade, with distinct aging behavior observed between residential and utility profiles. In particular, frequency modulation and deep-cycle self-consumption use cases impose more severe aging stress compared to microgrid or medium-cycle conditions. The study provides interpretable degradation metrics and visualizations, enabling targeted aging analysis under different load conditions. The results highlight the importance of thermal effects and cell-level stress variability, offering insights for lifetime-aware BESS control strategies. This framework serves as a practical tool to support the aging-resilient design and operation of grid-connected storage systems. Full article