Search Results (4,415)

Effective thermal management is critical for high-power lithium-ion batteries to mitigate excessive heat generation and ensure operational reliability. Failure to maintain a uniform temperature distribution can lead to accelerated capacity fading and severe safety risks, such as thermal runaway. In this study, a ferrofluid-based magnetohydrodynamic (MHD) microchannel cooling system was numerically investigated to elucidate the influence of magnetic intensity, magnet geometry, and electrical boundary conditions on flow behavior and heat transfer performance for battery cooling applications. A fully coupled multiphysics model incorporating electromagnetic, fluid flow, and heat transfer phenomena was developed and validated against experimental and numerical data from the literature. The results show that increasing the applied voltage enhances current density and Lorentz force almost linearly, leading to significant flow acceleration and improved convective heat transfer. Electrical insulation effectively suppresses current leakage into the channel walls, increasing the average current density by up to 222% and the Lorentz force by more than 300%. Compared with a cylindrical magnet, a rectangular magnet provides a more uniform magnetic field distribution and stronger near-wall Lorentz forcing, resulting in superior cooling performance. Under a 4C discharge condition, the insulated rectangular magnet reduces the maximum battery temperature by approximately 30% and increases the average Nusselt number by up to 103% relative to the non-insulated case. The findings reveal the critical roles of magnetic-field-controlled flow symmetry and near-wall forcing in MHD-driven microchannels, and provide practical design guidelines for battery cooling systems with no moving mechanical parts and active electromagnetic flow control. Full article

The automotive sector is currently undergoing a rapid and complex transition from classic internal combustion engines to hybrid or fully electric propulsion systems, at the core of which is the battery pack. Currently, the battery packs of almost all electric vehicles on the road consist of lithium-ion cells. The thermal management of these cells represents a complex and fundamental challenge, essential not only to ensure optimal vehicle performance but also to guarantee passenger safety. Therefore, this paper examines and compares four main systems used for battery thermal management, highlighting their strengths, weaknesses, and overall effectiveness. First, a standard module comprising 21700 cylindrical cells, representative of automotive applications, is designed. Subsequently, computational fluid dynamics (CFD) thermal analyses of this module are performed to evaluate four different cooling methods: forced air cooling, bottom cold plate cooling, liquid tube cooling, and immersion cooling combined with tab cooling. Finally, an experimental validation is conducted by testing these systems on a physical module, which is subjected to the same electrical discharge profile simulated in the CFD analyses, to verify the effectiveness of the four considered methods. Full article

Background: Automated discharge instructions are increasingly used to support post-discharge communication, patient education, and nursing follow-up, yet the current state remains unidentified. This systematic review explores the types of automated discharge instructions used and their effectiveness in enhancing patient engagement and reducing readmission, emergency department visits and reoperation rates. Methods: A systematic search was conducted on 15 April 2025, using Embase, PubMed, Scopus, Web of Science, and CINAHL, following PRISMA guidelines. Inclusion criteria required peer-reviewed original research evaluating the utilization of automated patient discharge instructions following hospital admission or surgical stay. Exclusion criteria included correspondence, reviews, educational materials, not peer-reviewed, retracted reports, not retrievable, and no English translation. Risk of bias was assessed independently using NIH, JBI, ROB-2, and ROBINS-I tools. Two investigators independently conducted the screening, extraction, and synthesis of results using Endnote and Microsoft Excel. Results: Of the 1252 records identified, 13 studies were selected for analysis. There was a total of 34,386 patients across a diverse range of healthcare settings and clinical contexts. The average sample size per study was approximately 4912, with study samples ranging from 16 to 13,188 patients. The modalities of discharge instructions included automated phone calls (23.1%) and/or text messages (53.8%), as well as printed out auto-generated summaries (15.4%). Patient engagement was generally high, with automated phone calls showing the most consistent interaction, with completion rates ranging from 44% to 56%, often prompting clinical follow-up. SMS tools demonstrated strong scalability and response rates up to 87%. Two studies reported on hospital readmission outcomes and only a single study reported on emergency department revisit rates, while none assessed reoperation outcomes. Among those reporting readmission, automated phone calls and SMS were associated with lower or proxy-reduced readmission rates. Included studies had low to moderate levels of bias. Conclusions: While evidence on clinical outcomes such as readmissions, emergency department revisits, and reoperations remains limited and inconclusive, automated discharge tools—particularly phone calls and SMS—consistently demonstrated high patient engagement. Automated discharge tools show promise for supporting transitional care, discharge education, and post-discharge monitoring, highlighting the future role of automated tools in nursing workflows to support follow-up, escalation, and continuity of care. Full article

Pollution flashover accidents of transmission line insulators have a wide impact and low reclosing success rates, posing a serious threat to the safe and stable operation of the power grid. The existing pollution discharge and flashover models of insulator based on equivalent salt deposit density (ESDD) present significant differences from the actual situation. To address this issue, the conductivity of electrolyte solutions experiments is carried out in this paper, and the quantitative functional relationship between conductivity and concentration of typical components is obtained. On this basis, the concept of effective salt deposit density (SDD_e) is introduced to characterize the actual mass of pollution participating in surface conduction per unit area. A DC discharge dynamic model for polluted insulators is established and verified based on SDD_e combined with the discharge development process. Research results indicate that the average difference between the calculated flashover voltage and experimental value is less than 7%. The deviation of flashover voltage between the SDD_e basis model and measured salt deposit density (SDD_m) basis value increases with the increasing proportion of slightly soluble components. With the increase of insulator surface water adhesion, the flashover voltage obtained by the proposed model decreases while the corresponding SDD_m basis value remains constant. The effects of factors such as slightly soluble pollution and surface water adhesion are considered in the proposed model sufficiently. The application of the model based on SDD_e can improve the accuracy of the insulator discharge process and flashover voltage prediction, especially for the complex pollution area. During the generation and propagation of the arc, the leakage current under SDD_m is relatively higher and the pollution layer resistance is lower compared to that under SDD_e; the variations in the pollution layer resistance and leakage current with arc development under SDD_m do not adequately reflect the actual conditions. Full article

Background/Objectives: Traumatic brain injury (TBI) affects more than 50 million people annually worldwide. Challenges in managing moderate-to-severe TBI include high rates of hospital-acquired infections and substantial variability in discharge disposition, and these combined challenges contribute significantly to the cost and trajectory of health recovery. Although current strategies such as antibiotic-impregnated external ventricular drains (EVDs) offer some benefit in controlling infections, they remain limited by high cost and inconsistent implementation. A clearer understanding of clinical and demographic factors associated with infection risk and discharge disposition are essential for improving care pathways. This study aims to identify and quantify key determinants of infection and discharge outcomes in patients with TBI. Methods: The National Trauma Database (NTDB) was queried using structured query language (SQL) based on predefined inclusion criteria (adult patients with ICD-coded TBI), input variables (basic demographics, injury location and severity, and vital signs), and specified outcome variables (emergency department discharge disposition, infection, and sepsis) to identify and filter the eligible patient cohort. A set of machine learning models were trained for each outcome (e.g., Emergency Department (ED) discharge, types of infections, and sepsis). Results: Data from 310,494 patients were extracted. The prediction model we developed, the Predictive TBI-Disposition Model (PTDM), was able to predict the outcome of a patient’s discharge with 96% accuracy. The accuracy of the models for infection and sepsis was 93% and 94%, respectively. Conclusions: Demographic and clinical factors significantly influence the discharge disposition and infection risk among TBI patients. Machine learning models demonstrated strong predictive performance, suggesting their utility in early risk stratification and targeted clinical decision-making. Full article

Lithium–sulfur (Li–S) batteries have emerged as a promising next-generation energy storage solution as the capacity demands on lithium-ion systems begin to exceed practical limits. In a global push for renewable energy and sustainable practices, Li–S technology offers several compelling advantages. Both lithium and sulfur are relatively inexpensive (especially compared to the transition metals used in lithium-ion cells), and Li–S batteries are easier and less costly to recycle. Moreover, Li–S chemistry carries a theoretical energy density about five times greater than that of current lithium-ion batteries, making it attractive for high-energy-density applications. Because of these advantages, research interest in Li–S batteries remains high despite significant challenges that still limit their performance and lifespan. However, despite these advantages, several fundamental challenges limit the practical deployment of Li–S batteries, including the polysulfide shuttle effect, large volume expansion of sulfur during cycling, low intrinsic electrical conductivity of sulfur and its discharge products, and instability of the lithium metal anode caused by dendrite formation. This paper explains the working principles of Li–S batteries, analyzes the key challenges and recent achievements in their development, and surveys various mechanical engineering applications for which Li–S batteries are being explored, as well as prospects for their future commercialization and sustainability. Full article

Accurate estimation of lithium-ion battery state of health and capacity is critical for intelligent battery management. This study develops a multi-variable cross-condition capacity estimation model based on incremental capacity (IC) curve features. First, the IC curve area is extracted to construct a health indicator. To capture the coupled, non-linear effects of temperature and discharge current on capacity fade, a temperature-zoned modeling framework is implemented. Specifically, first-order linear polynomials are applied for room temperature conditions to prevent overfitting, while second-order polynomials with interaction terms are utilized for high and low temperature conditions to model complex degradation behaviors. Furthermore, to mitigate estimation errors caused by individual battery inconsistency and varying initial states across different operating conditions, the capacity retention rate (CRR) and health indicator retention rate metrics are defined and integrated into the estimation framework. Validation across multiple dynamic operating conditions demonstrates that the optimized CRR-based model achieves an average root mean square error of 0.0261 Ah and a mean absolute percentage error of 2.83%. The proposed temperature-zoned approach provides a robust, data-driven methodology for cross-condition battery health monitoring. Full article

Accurate state of health (SOH) assessment is the cornerstone for ensuring the safety, reliability, and lifecycle value prediction of electric vehicles. While extensive research has demonstrated the significant advantages of data-driven approaches in SOH evaluation, the vast majority of work still relies on standardized test data obtained under laboratory conditions. These ideal conditions, including complete charge–discharge cycles and constant temperatures, are often unattainable in real-world operation where EV batteries face highly irregular driving patterns, fragmented charging segments, and unpredictable environmental disturbances. This paper provides a comprehensive and systematic overview of data-driven SOH assessment based on real-vehicle data, aiming to address the current research gap in unified laboratory-to-vehicle transfer frameworks. This paper first reviews existing SOH evaluation methodologies and highlights the challenges encountered when transitioning to real-world vehicle data. It delves into core technical challenges and solutions across the entire real-world SOH assessment chain, closely examining the complex characteristics of real-world data. The paper thoroughly evaluates the role of cutting-edge paradigms including weakly supervised, self-supervised, and transfer learning in mitigating label scarcity. We summarize a unified evaluation framework tailored for real-world scenarios: Vehicles-Out, Time-Rolling, Domain-Stratified (VTDS). This framework aims to systematically assess models’ generalization limits and engineering deployability across vehicles, time, and operating conditions. This work provides systematic guidance for researchers and practitioners, advancing data-driven SOH evaluation methods from theoretical research to engineering applications. Full article

Background and Clinical Significance: Ensitrelvir is an oral inhibitor of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (3CL pro). Compared with remdesivir and molnupiravir, ensitrelvir achieves higher rates of SARS-CoV-2 antigen clearance and a more favorable viral shedding profile. Case Presentation: A 67-year-old Japanese man with follicular lymphoma had received obinutuzumab plus bendamustine, followed by obinutuzumab maintenance therapy. Hypogammaglobulinemia and profound B-cell depletion persisted for more than 1 year after the final maintenance dose. Three months prior to the current admission, the patient developed coronavirus disease 2019 (COVID-19) and was treated with a 10-day course of remdesivir and dexamethasone. The patient subsequently presented with recurrent COVID-19 pneumonia. Treatment with remdesivir and dexamethasone did not result in clinical improvement, and the SARS-CoV-2 antigen level increased despite adjunctive intravenous immunoglobulin. After ensitrelvir was added to remdesivir, the SARS-CoV-2 antigen levels declined rapidly, and clinical parameters, including fever, inflammatory markers (C-reactive protein), and oxygenation, improved promptly, allowing for discharge. Conclusions: Ensitrelvir may be an effective therapeutic option for the treatment of persistent or refractory COVID-19 in immunocompromised patients. Clinicians should recognize that patients treated with obinutuzumab may remain immunosuppressed for several years after therapy. Full article

Lightning-induced breaking accidents of medium-voltage insulated conductors pose a serious threat to the safety of distribution networks, and the key cause lies in the establishment and sustained combustion of the power-frequency follow-current arc after lightning overvoltage breakdown. This paper systematically investigates the formation mechanism and critical conditions of power-frequency follow-current arcs using combined simulation and experimental approaches. Based on the streamer discharge theory, a lightning breakdown model was established and combined with the arc energy balance equation, revealing that the establishment of power-frequency follow-current arcs is essentially determined by the post-breakdown energy competition process. The simulation results show that the required anode electric field strength for lightning breakdown is not less than 3 kV/mm. When the power-frequency voltage reaches 10 kV, Joule heating of the arc continuously exceeds heat dissipation loss, enabling restrike after zero-crossing and sustaining stable burning. Experiments verified this voltage threshold and further revealed that the arc establishment rate exhibits nonlinear growth with increasing power-frequency voltage, exceeding 90% at power-frequency voltages ≥ 10 kV. The study also reveals that increased gap distance reduces the arc establishment rate, while the introduction of insulators can enhance it by approximately 20%. This study clarifies the energy criterion for power-frequency follow-current arc establishment and the influence patterns of key parameters, providing theoretical basis and engineering reference for lightning protection design and arc suppression in medium-voltage insulated lines. Full article

Industrialization has caused extensive environmental change, including a global surge in plastic production and pollution. This has resulted in the accumulation of microplastics (MPs; <5 mm) and nanoplastics (NPs; <1 μm) in ecosystems worldwide. MPs originate from both primary sources, such as cosmetics and industrial applications, and secondary sources, through the degradation of larger plastic debris. As a result, MPs and NPs have become ubiquitous contaminants, posing significant toxicological risks to living organisms. These persistent pollutants are diverse polymers that vary in size, shape, and chemical composition, making their impacts on organism physiology complex and difficult to disentangle. Plastic pollution is particularly severe in aquatic environments, where particles accumulate from terrestrial sources such as urban dust, agricultural runoff, industrial discharges, and wastewater effluents. Although most research has centered on marine ecosystems, emerging evidence indicates that freshwater environments may contain comparable or even higher concentrations of MPs. Once inside the body, MPs can translocate into tissues and exert toxic effects on multiple organ systems. Collectively, plastic pollution poses not only physiological but also neurological and behavioral risks to aquatic life, with potential consequences for ecosystem stability and trophic interactions. Both MPs and NPs are sufficiently small to cross the blood–brain barrier, raising concerns about their potential impacts on the nervous system by interfering with neuronal function and brain development. Plastic particles can accumulate in neural tissues, inducing oxidative stress, neuroinflammation, and disruption of neurotransmitter signaling. Such neurotoxic effects are linked to altered locomotion, feeding, predator avoidance, and social behaviors across multiple species. This review examines current evidence on the neurotoxic effects of plastic pollution in aquatic organisms and underscores the urgent need for further research and action to mitigate its impact. In light of escalating plastic production and inadequate waste management, the growing evidence that MPs and NPs disrupt aquatic nervous systems, behavior, and ecosystem stability underscores an urgent need for intensified research, improved mitigation strategies, particularly for nanoplastics, and the accelerated development of truly safe and sustainable alternatives. Full article

Gas-insulated switchgear (GIS) is a critical component of modern power systems. During operation, internal defects increase the probability of partial discharge and flashover within the insulation system, thereby constituting a major cause of equipment failure. Considering the diversity of existing GIS insulation condition monitoring methods, it is of great significance to systematically review and evaluate current monitoring technologies. This paper summarizes the detection principles and recent advances in electrical, acoustic, optical, modal analysis, and gas component analysis techniques. Through a comparative analysis of the advantages, limitations, and application scenarios of different methods, in conjunction with failure cases induced by typical GIS insulation defects, the primary bottlenecks faced by various condition monitoring technologies are discussed. Furthermore, future research directions for GIS insulation condition detection are outlined. This study provides a reference for the development of GIS insulation monitoring technologies and the formulation of efficient operation and maintenance strategies. Full article

Background: Pancreatic trauma (PT) in children is rare and associated with significant morbidity. The optimal form of management—operative versus non-operative—remains controversial, particularly in the presence of acute post-traumatic peripancreatic fluid collection, which may later evolve into pancreatic pseudocysts. Isolated pancreatic injuries without associated organ damage are uncommon and pose diagnostic and therapeutic challenges. Case Presentation: We report a 5-year-old boy who sustained an isolated grade IB blunt pancreatic head contusion following blunt abdominal trauma after falling onto a wooden fence. He presented with epigastric pain, repeated emesis, and an abdominal wall bruise. Initial ultrasound (US) findings were subtle; however, serial imaging and contrast-enhanced computed tomography (CECT) revealed focal contusion of the pancreatic head/uncinate process with a small peripancreatic fluid collection. Pancreatic enzymes were markedly elevated, with peak serum lipase reaching approximately 6579 U/L. The child remained hemodynamically stable and was managed conservatively with bowel rest, intravenous fluids, octreotide, proton-pump inhibition, pancreatic enzyme replacement therapy (PERT), and antibiotics. Serial US demonstrated the dynamic evolution of an acute peripancreatic fluid collection (APFC) (~2 cm), which remained stable without complications. Clinical and biochemical parameters gradually improved, and no invasive intervention was required. The patient was discharged on hospital day 16 with planned outpatient imaging follow-up. Conclusions: This case demonstrates that isolated pediatric pancreatic contusions complicated by small, evolving peripancreatic fluid collections can be safely managed non-operatively in hemodynamically stable patients. Serial ultrasound plays a key role in monitoring lesion evolution and guiding management decisions. In accordance with current pediatric trauma guidelines, careful observation with structured follow-up may prevent unnecessary invasive interventions while achieving excellent clinical outcomes. Full article

Over the past two decades, numerous studies have examined the etiological significance of DNA fragmentation in human sperm using methods such as the comet assay (CA), the sperm chromatin structure assay, the sperm chromatin dispersion assay, and the TUNEL assay. We developed single-cell pulsed-field gel electrophoresis techniques, including one-dimensional (1D-SCPFGE) and angle-modulated two-dimensional (2D-SCPFGE), to detect early signs of naturally occurring DNA fragmentation. Comparative studies using purified human sperm with and without DNA fragmentation revealed some technical limitations in the conventional methods. This technical review outlines the procedures to ensure the quantitative performance of SCPFGE: (1) The mass of naked DNA was prepared through simultaneous in-gel swelling and proteolysis, which are highly sensitive to chemical and physical factors. Notably, these processes are vulnerable to reactive oxygen species (ROS). We developed the anti-ROS SCPFGE system to prevent artifactual cleavages. (2) 1D-SCPFGE discharges long-chain fibers from the origin, separating fibrous and granular segments beyond the tips of the fibers. (3) During continuous electrophoresis after 150° rotation (2D-SCPFGE-0-150), long-chain fibers unexpectedly extended diagonally backward from the origin, with long fibrous segments pulled out from a bundle that extended during the first electrophoresis, indicating some fibrous segments were embedded within the long-chain fibers. Even when SCPFGE was employed, one-directional current led to false negatives. (4) 2D-SCPFGE with angle rotation is currently the most sensitive imaging method for single-nuclear DNA fibers. However, without knowing the size of DNA fragments, it remains a semi-quantitative analysis. (5) To prevent artifactual DNA cleavage caused by ice crystals, low-temperature liquid storage is recommended. (6) The in-gel proteolyzed naked DNA is suitable as a substrate for chemical and enzymatic DNA cleavage analyses. Full article

Background: Invasive Aspergillosis (IA) is a rare but life-threatening fungal infection in immunocompromised hosts, including solid organ transplant (SOT) recipients. While extensively studied in other SOT populations, data on IA in pancreas transplant (PT) recipients are limited. Earlier studies reported mortality rates nearing 100%, whereas more recent data show that 12-week mortality still exceeds 20% despite improvements in antifungal therapy. Current prophylaxis strategies for PT recipients mainly focus on Candida species, and there are no clear, standardized recommendations for Aspergillus prevention. Given the paucity of focused data, the epidemiology, clinical characteristics, and outcomes of IA in PT recipients are not well defined. This study aimed to assess the incidence, clinical characteristics, and outcomes of IA among hospitalized PT patients using a nationally representative dataset. Methods: We conducted a descriptive analysis using the National Inpatient Sample (NIS) from 2016 to 2020. PT admissions were identified using International Classification of Diseases, Tenth Revision (ICD 10) codes for transplant status and procedures. IA was defined using validated ICD 10 codes. Baseline demographics, hospital characteristics, comorbidities, and outcomes, including sepsis, acute kidney injury (AKI), acute respiratory failure (ARF), invasive mechanical ventilation (IMV), all-cause in-hospital mortality, length of stay, and total hospitalization costs and charges were compared between PT admissions with and without IA. National estimates were calculated using discharge weights, and comparisons were performed using the chi-square test and adjusted Wald test. Multivariable analysis was performed to identify predictors of all-cause in-hospital mortality among PT admissions complicated by IA. Two-sided p values < 0.05 were considered statistically significant. Results: Between 2016 and 2020, 65,980 PT-related hospitalizations were identified, of which 250 (0.4%) had IA. PT admissions complicated by IA were more commonly aged 41 to 60 years (59% vs. 46%, p = 0.012) and were less likely to have a Charlson Comorbidity Index greater than 3 (54% vs. 68.6%, p < 0.001) compared with PT hospitalizations without IA. The PT with the IA cohort had higher rates of sepsis (100% vs. 46.1%, p < 0.001), AKI (60% vs. 36.7%, p < 0.001), ARF (28% vs. 9.4%, p < 0.001), and IMV use (18% vs. 4%, p < 0.001) compared with the PT without the IA cohort. Among PT hospitalizations with IA, IMV use was independently associated with higher all-cause in-hospital mortality (adjusted odds ratio 48.777, p = 0.009). Overall, in-hospital mortality was significantly higher in PT hospitalizations with IA compared with those without IA (12% vs. 2%, p < 0.001). Mean length of stay was longer (24.86 vs. 6.13 days, p < 0.001), and total charges ($378,494 vs. $94,938, p < 0.001), and total costs ($93,019 vs. $24,463, p = 0.023) were significantly higher compared with PT hospitalizations without IA. Conclusion: Although rare, IA in PT recipients is associated with higher rates of sepsis, AKI, ARF, venous thromboembolism, prolonged hospitalization, increased mortality, and greater healthcare utilization. Despite the inherent limitations of administrative datasets, this nationally representative analysis highlights the substantial clinical and economic burden of IA in this high-risk population. These findings emphasize the need for targeted surveillance, early diagnosis, and evidence-based antifungal strategies in this vulnerable population. Full article