Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for...Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for mitigating the energy crisis.A comprehensive review connecting the advancements in engineered radiative cooling systems(ERCSs),encompassing material and structural design as well as thermal and energy-related applications,is currently absent.Herein,this review begins with a concise summary of the essential concepts of ERCSs,followed by an introduction to engineered materials and structures,containing nature-inspired designs,chromatic materials,meta-structural configurations,and multilayered constructions.It subsequently encapsulates the primary applications,including thermal-regulating textiles and energy-saving devices.Next,it highlights the challenges of ERCSs,including maximized thermoregulatory effects,environmental adaptability,scalability and sustainability,and interdisciplinary integration.It seeks to offer direction for forthcoming fundamental research and industrial advancement of radiative cooling systems in real-world applications.展开更多
Gastric ulcer(GU)represents a clinically significant manifestation of peptic ulcer disease,driven by a complex interplay of microbial,environmental,and immuneinflammatory factors.A recent cross-sectional study by Shen...Gastric ulcer(GU)represents a clinically significant manifestation of peptic ulcer disease,driven by a complex interplay of microbial,environmental,and immuneinflammatory factors.A recent cross-sectional study by Shen et al systematically evaluated six complete blood count-derived inflammatory indices:Neutrophil-tolymphocyte ratio,monocyte-to-lymphocyte ratio,platelet-to-lymphocyte ratio,systemic immune-inflammation index,systemic inflammatory response index(SIRI),and aggregate index of systemic inflammation and demonstrated their positive associations with GU prevalence,identifying SIRI as the strongest predictor.This editorial contextualizes these findings within the broader literature,clarifies that these indices reflect systemic rather than GU-specific inflammation,highlights methodological strengths and major limitations,and proposes a conceptual clinical algorithm for integrating SIRI into GU risk assessment.Future multicenter studies incorporating Helicobacter pylori infection,non-steroidal antiinflammatory drug exposure,and prospective design are essential to validate and translate these findings into clinical practice.展开更多
The human retina,a complex and highly specialized structure,includes multiple cell types that work synergistically to generate and transmit visual signals.However,genetic predisposition or age-related degeneration can...The human retina,a complex and highly specialized structure,includes multiple cell types that work synergistically to generate and transmit visual signals.However,genetic predisposition or age-related degeneration can lead to retinal damage that severely impairs vision or causes blindness.Treatment options for retinal diseases are limited,and there is an urgent need for innovative therapeutic strategies.Cell and gene therapies are promising because of the efficacy of delivery systems that transport therapeutic genes to targeted retinal cells.Gene delivery systems hold great promise for treating retinal diseases by enabling the targeted delivery of therapeutic genes to affected cells or by converting endogenous cells into functional ones to facilitate nerve regeneration,potentially restoring vision.This review focuses on two principal categories of gene delivery vectors used in the treatment of retinal diseases:viral and non-viral systems.Viral vectors,including lentiviruses and adeno-associated viruses,exploit the innate ability of viruses to infiltrate cells,which is followed by the introduction of therapeutic genetic material into target cells for gene correction.Lentiviruses can accommodate exogenous genes up to 8 kb in length,but their mechanism of integration into the host genome presents insertion mutation risks.Conversely,adeno-associated viruses are safer,as they exist as episomes in the nucleus,yet their limited packaging capacity constrains their application to a narrower spectrum of diseases,which necessitates the exploration of alternative delivery methods.In parallel,progress has also occurred in the development of novel non-viral delivery systems,particularly those based on liposomal technology.Manipulation of the ratios of hydrophilic and hydrophobic molecules within liposomes and the development of new lipid formulations have led to the creation of advanced non-viral vectors.These innovative systems include solid lipid nanoparticles,polymer nanoparticles,dendrimers,polymeric micelles,and polymeric nanoparticles.Compared with their viral counterparts,non-viral delivery systems offer markedly enhanced loading capacities that enable the direct delivery of nucleic acids,mRNA,or protein molecules into cells.This bypasses the need for DNA transcription and processing,which significantly enhances therapeutic efficiency.Nevertheless,the immunogenic potential and accumulation toxicity associated with non-viral particulate systems necessitates continued optimization to reduce adverse effects in vivo.This review explores the various delivery systems for retinal therapies and retinal nerve regeneration,and details the characteristics,advantages,limitations,and clinical applications of each vector type.By systematically outlining these factors,our goal is to guide the selection of the optimal delivery tool for a specific retinal disease,which will enhance treatment efficacy and improve patient outcomes while paving the way for more effective and targeted therapeutic interventions.展开更多
Functional neurological recovery remains the primary objective when treating ischemic stroke.However,current therapeutic approaches often fall short of achieving optimal outcomes.One of the most significant challenges...Functional neurological recovery remains the primary objective when treating ischemic stroke.However,current therapeutic approaches often fall short of achieving optimal outcomes.One of the most significant challenges in stroke treatment is the effective delivery of neuroprotective agents across the blood–brain barrier to ischemic regions within the brain.The blood–brain barrier,while essential for protecting the brain from harmful substances,also restricts the passage of many therapeutic compounds,thus limiting their efficacy.In this review,we summarizes the emerging role of nanoparticle-based therapies for the treatment of ischemic stroke and investigate their potential to revolutionize drug delivery,enhance neuroprotection,and promote functional recovery.Recent advancements in nanotechnology have led to the development of engineered nanoparticles specifically designed to overcome the blood–brain barrier,thus enabling the targeted delivery of therapeutic agents directly to the affected brain areas.Preclinical studies have demonstrated the remarkable potential of nanoparticle-based therapies to activate key neuroprotective pathways,such as the phosphoinositide 3-kinase/protein kinase B/c AMP response element-binding protein signaling cascade,which is crucial for neuronal survival,synaptic plasticity,and post-stroke recovery.By modulating these pathways,nanoparticles could mitigate neuronal damage,reduce inflammation,and promote tissue repair.Furthermore,nanoparticles offer a unique advantage by enabling multimodal therapeutic strategies that simultaneously target multiple pathological mechanisms of ischemic stroke,including oxidative stress,neuroinflammation,and apoptosis.This multifaceted approach enhances the overall efficacy of treatment,addressing the complex and interconnected processes that contribute to stroke-related brain injury.Surface modifications,such as functionalization with specific ligands or targeting molecules,further improve the precision of drug delivery,enhance targeting specificity,and prolong systemic circulation,thereby optimizing therapeutic outcomes.Nanoparticlebased therapeutics represent a paradigm shift for the management of stroke and provide a promising avenue for reducing post-stroke disability and improving the outcomes of long-term rehabilitation.By combining targeted drug delivery with the ability to modulate critical neuroprotective pathways,nanoparticles hold the potential to transform the treatment landscape for ischemic stroke.However,while preclinical data are highly encouraging,significant challenges remain in translating these advancements into clinical practice.Further research is needed to refine nanoparticle designs,optimize their safety profiles,and ensure their scalability for widespread application.Rigorous clinical trials are essential to validate their efficacy,assess long-term biocompatibility,and address potential off-target effects.The integration of interdisciplinary approaches,combining insights from nanotechnology,neuroscience,and pharmacology,will be critical if we are to overcome these challenges.Ultimately,nanoparticle-based therapies offer a foundation for innovative,precision-based treatments that could significantly improve outcomes for stroke patients,thus paving the way for a new era in stroke care and neurological rehabilitation.展开更多
The rise of the aging population parallels the rapidly increasing cases of neurological disorders. This puts pressure on scientists and physicians to find novel methods that can prevent and treat neurodegeneration. Th...The rise of the aging population parallels the rapidly increasing cases of neurological disorders. This puts pressure on scientists and physicians to find novel methods that can prevent and treat neurodegeneration. The brain is made up of a complex network of different cell types that work in tandem to maintain systemic homeostasis.展开更多
Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(...Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].展开更多
Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Num...Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Numerous applications have been developed to support the challenges in intelligent healthcare systems.However,because mental health data is sensitive,privacy concerns have emerged.Federated learning has gotten some attention.This research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare systems.It explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health applications.This research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security concerns.The survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.展开更多
To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the ...To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the effectiveness of flexibility management strategies under different climate conditions and extreme weather events.Using both typical and extreme weather data from cities in five major climate zones of China,this study investigates the energy flexibility potential of an office building under three short-term HVAC management strategies in the context of different climates.The results show that the peak load flexibility and overall energy performance of the three short-term strategies were affected by the surrounding climate conditions.The peak load reduction rate of the pre-cooling and zone temperature reset strategies declined linearly as outdoor temperature increased.Under extreme climate conditions,the daily peak-load time was found to be over two hours earlier than under typical conditions,and the intensive solar radiation found in the extreme conditions can weaken the correlation between peak load reduction and outdoor temperature,risking the ability of a building’s HVAC system to maintain a comfortable indoor environment.展开更多
With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenu...With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenues for digital transformation and intelligent upgrading.Industry 5.0,a further extension and development of Industry 4.0,has become an important development trend in industry with more emphasis on human-centered sustainability and flexibility.Accordingly,both the industrial metaverse and digital twins have attracted much attention in this new era.However,the relationship between them is not clear enough.In this paper,a comparison between digital twins and the metaverse in industry is made firstly.Then,we propose the concept and framework of Digital Twin Systems Engineering(DTSE)to demonstrate how digital twins support the industrial metaverse in the era of Industry 5.0 by integrating systems engineering principles.Furthermore,we discuss the key technologies and challenges of DTSE,in particular how artificial intelligence enhances the application of DTSE.Finally,a specific application scenario in the aviation field is presented to illustrate the application prospects of DTSE.展开更多
Drug delivery systems(DDS)have recently emerged as a promising approach for the unique advantages of drug protection and targeted delivery.However,the access of nanoparticles/drugs to the central nervous system(CNS)re...Drug delivery systems(DDS)have recently emerged as a promising approach for the unique advantages of drug protection and targeted delivery.However,the access of nanoparticles/drugs to the central nervous system(CNS)remains a challenge mainly due to the obstruction from brain barriers.Immune cells infiltrating the CNS in the pathological state have inspired the development of strategies for CNS foundation drug delivery.Herein,we outline the three major brain barriers in the CNS and the mechanisms by which immune cells migrate across the blood–brain barrier.We subsequently review biomimetic strategies utilizing immune cell-based nanoparticles for the delivery of nanoparticles/drugs to the CNS,as well as recent progress in rationally engineering immune cell-based DDS for CNS diseases.Finally,we discuss the challenges and opportunities of immune cell-based DDS in CNS diseases to promote their clinical development.展开更多
The Intelligent Internet of Things(IIoT)involves real-world things that communicate or interact with each other through networking technologies by collecting data from these“things”and using intelligent approaches,s...The Intelligent Internet of Things(IIoT)involves real-world things that communicate or interact with each other through networking technologies by collecting data from these“things”and using intelligent approaches,such as Artificial Intelligence(AI)and machine learning,to make accurate decisions.Data science is the science of dealing with data and its relationships through intelligent approaches.Most state-of-the-art research focuses independently on either data science or IIoT,rather than exploring their integration.Therefore,to address the gap,this article provides a comprehensive survey on the advances and integration of data science with the Intelligent IoT(IIoT)system by classifying the existing IoT-based data science techniques and presenting a summary of various characteristics.The paper analyzes the data science or big data security and privacy features,including network architecture,data protection,and continuous monitoring of data,which face challenges in various IoT-based systems.Extensive insights into IoT data security,privacy,and challenges are visualized in the context of data science for IoT.In addition,this study reveals the current opportunities to enhance data science and IoT market development.The current gap and challenges faced in the integration of data science and IoT are comprehensively presented,followed by the future outlook and possible solutions.展开更多
The dynamics of phase separation in H–He binary systems within gas giants such as Jupiter and Saturn exhibit remarkable complexity, yet lack systematic investigation. Through large-scale machine-learning-accelerated ...The dynamics of phase separation in H–He binary systems within gas giants such as Jupiter and Saturn exhibit remarkable complexity, yet lack systematic investigation. Through large-scale machine-learning-accelerated molecular dynamics simulations spanning broad temperature-pressure-composition(2000–10000 K, 1–7 Mbar,pure H to pure He) regimes, we systematically determine self and mutual diffusion coefficients in H–He systems and establish a six-dimensional framework correlating temperature, pressure, helium abundance, phase separation degree, diffusion coefficients, and anisotropy. Key findings reveal that hydrogen exhibits active directional migration with pronounced diffusion anisotropy, whereas helium passively aggregates in response. While the conventional mixing rule underestimates mutual diffusion coefficients by neglecting velocity cross-correlations,the assumption of an ideal thermodynamic factor(Q = 1) overestimates them due to unaccounted non-ideal thermodynamic effects—both particularly pronounced in strongly phase-separated regimes. Notably, hydrogen's dual role, anisotropic diffusion and bond stabilization via helium doping, modulates demixing kinetics. Large-scale simulations(216,000 atoms) propose novel phase-separation paradigms, such as “hydrogen bubble/wisp” formation, challenging the classical “helium rain” scenario, striving to bridge atomic-scale dynamics to planetary-scale phase evolution.展开更多
Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectiv...Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.展开更多
Direct seawater splitting has emerged as a popular and promising research direction for synthesising clean,green,non-polluting,and sustainable hydrogen energy without depending on high-purity water in the face of the ...Direct seawater splitting has emerged as a popular and promising research direction for synthesising clean,green,non-polluting,and sustainable hydrogen energy without depending on high-purity water in the face of the world’s shortage of fossil energy.However,efficient seawater splitting is hindered by slow kinetics caused by the ultra-low conductivity and the presence of bacteria,microorganisms,and stray ions in seawater.Additionally,producing hydrogen on an industrial scale is challenging due to the high production cost.The present review addresses these challenges from the catalyst point of view,namely,that designing catalysts with high catalytic activity and stability can directly affect the rate and effect of seawater splitting.From the ion transfer perspective,designing membranes can block harmful ions,improving the stability of seawater splitting.From the energy point of view,mixed seawater systems and self-powered systems also provide new and low-energy research systems for seawater splitting.Finally,ideas and directions for further research on direct seawater splitting in the future are pointed out,with the aim of achieving low-cost and high-efficiency hydrogen production.展开更多
Dual-function communication radar systems use common Radio Frequency(RF)signals are used for both communication and detection.For better compatibility with existing communication systems,we adopt Multiple-Input Multip...Dual-function communication radar systems use common Radio Frequency(RF)signals are used for both communication and detection.For better compatibility with existing communication systems,we adopt Multiple-Input Multiple-Output(MIMO)Orthogonal Frequency Division Multiplexing(OFDM)signals as integrated signals and investigate the estimation performance of MIMO-OFDM signals.First,we analyze the Cramer-Rao Lower Bound(CRLB)of parameter estimation.Then,the transmit powers over different subcarriers are optimized to achieve the best tradeoff between the transmission rate and the estimation performance.Finally,we propose a more accurate estimation method that uses Canonical Polyadic Decomposition(CPD)of the third-order tensor to obtain the parameter matrices.Due to the characteristic of the column structure of the parameter matrices,we only need to use DFT/IDFT to recover the parameters of multiple targets.The simulation results show that tensor-based estimation method can achieve a performance close to CRLB,and the estimation performance can be improved by optimizing the transmit powers.展开更多
Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air poll...Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air pollution is crucial for mitigating climate change,improving air quality,and promoting the sustainable development of food systems.However,the literature lacks a comprehensive review of these interactions,particularly in the current phase of rapid development in the field.To address this gap,this study systematically reviews recent research on the impacts of climate change and air pollution on food systems,as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution.In addition,this study summarizes various strategies for mitigation and adaptation,including adjustments in agricultural practices and food supply chains.Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions.This review offers a critical overview of current research on the interactions among food systems,climate change,and air pollution and highlights future research directions to support the transition to sustainable food systems.展开更多
Background The emergence of antibiotic resistant microorganisms associated with conventional swine production practices has increased interest in acid-based compounds having antimicrobial properties and other biologic...Background The emergence of antibiotic resistant microorganisms associated with conventional swine production practices has increased interest in acid-based compounds having antimicrobial properties and other biological functions as nutritional interventions.Despite the interest in organic acids and monoglycerides,few studies have examined the effects of the combination of these acid-based additives in weaned pigs under disease challenge conditions.Therefore,this study aimed to investigate the effects of dietary supplementation with blend of organic acids and/or medium-chain fatty acid monoglycerides on intestinal health and systemic immunity of weaned pigs experimentally infected with an enterotoxigenic Escherichia coli(ETEC)F18 at 4-week of age.Results Dietary supplementation of organic acids,monoglycerides,or both organic acids and monoglycerides(combination)reduced(P<0.05)the diarrhea frequency of ETEC F18-infected pigs throughout the experimental period(d−7 to 21 post-inoculation).This is consistent with the reduced(P<0.05)proportion ofβ-hemolytic coliforms in feces observed for the organic acid and combination treatments on d 10 post-inoculation.Supplementation of organic acids,monoglycerides,or combination also reduced(P<0.05)bacterial translocation in mesenteric lymph nodes on d 21 post-inoculation.Pigs fed with monoglycerides or combination had lower(P<0.05)white blood cells on d 5 post-inoculation,and pigs fed the combination also had lower(P<0.05)lymphocytes than pigs in control group.Monoglyceride supplementation increased(P<0.05)white blood cells and neutrophils compared with control group on d 14 post-inoculation.However,supplementation with organic acid blend,monoglyceride blend,or combination did not affect growth performance in this experiment.Conclusions Supplementation with monoglycerides or organic acids alone or in combination improves the detrimental effects of ETEC F18 infection in weaned pigs,as indicated by reduced diarrhea,fecal shedding ofβ-hemolytic coliforms,and bacterial translocation,and thus enhancing disease resistance.Monoglycerides reduced the inflammatory response during peak infection,but their immunomodulatory and possible synergistic effects with organic acids need to be further investigated.展开更多
High-entropy materials(HEMs),an innovative class of materials with complex stoichiometry,have recently garnered consider-able attention in energy storage applications.While their multi-element compositions(five or mor...High-entropy materials(HEMs),an innovative class of materials with complex stoichiometry,have recently garnered consider-able attention in energy storage applications.While their multi-element compositions(five or more principal elements in nearly equiatom-ic proportions)confer unique advantages such as high configurational entropy,lattice distortion,and synergistic cocktail effects,the fun-damental understanding of structure-property relationships in battery systems remains fragmented across existing studies.This review ad-dresses critical research gaps by proposing a multidimensional design paradigm that systematically integrates synergistic mechanisms spanning cathodes,anodes,electrolytes,and electrocatalysts.We provide an in-depth analysis of HEMs’thermodynamic/kinetic stabiliza-tion principles and structure-regulated electrochemical properties,integrating and establishing quantitative correlations between entropy-driven phase stability and charge transport dynamics.By summarizing the performance benchmarking results of lithium/sodium/potassi-um-ion battery components,we reveal how entropy-mediated structural tailoring enhances cycle stability and ionic conductivity.Notably,we pioneer the systematic association of high-entropy effects to electrochemical interfaces,demonstrating their unique potential in stabil-izing solid-electrolyte interphases and suppressing transition metal dissolution.Emerging opportunities in machine learning-driven com-position screening and sustainable manufacturing are discussed alongside critical challenges,including performance variability metrics and cost-benefit analysis for industrial implementation.This work provides both fundamental insights and practical guidelines for advan-cing HEMs toward next-generation battery technologies.展开更多
BACKGROUND:The lack of a stable,easy-to-operate animal model for severe trauma has hindered the research progress.The aim of this study is to develop a mouse model that replicates the pathophysiological conditions of ...BACKGROUND:The lack of a stable,easy-to-operate animal model for severe trauma has hindered the research progress.The aim of this study is to develop a mouse model that replicates the pathophysiological conditions of severe trauma,providing a reliable research tool.METHODS:Male C57BL/6J mice(aged 8-10 weeks and weighting approximately 20 g)were used to establish the severe trauma model.Under anesthesia,a midshaft femoral fracture was created and packed with sterile cotton.A midline incision was made from the inguinal region to the sternum,exposing the abdominal organs for 30 min.The right femoral artery was cannulated to induce controlled blood loss at 30%,35%,40%,and 50%of the total blood volume.Survival rates were monitored for 24 h post-induction.In the mice that experienced 30%blood loss,the mean arterial pressure,body temperature,blood gas parameters,peripheral blood inflammatory markers,and major organ pathological changes were assessed.RESULTS:Mice with femoral fractures,soft tissue injuries,abdominal organ exposure,and 30%blood loss exhibited stable survival rates.Increased blood loss significantly reduced survival rates.Mean arterial pressure decreased initially,recovering within 0-15 min and returning to baseline by 50 min.Similarly,the body temperature decreased initially and gradually recovered to baseline within 50 min.Levels of peripheral blood inflammatory markers remained elevated for 12 h post-injury.Distant organs,including intestines,lungs,liver,spleen and kidneys,displayed varying degrees of injury.CONCLUSION:The established mouse model replicates the pathophysiological responses to severe trauma,indicating stability and reproducibility,which could be an useful tool for further trauma research.展开更多
Actuator faults can be critical in turbofan engines as they can lead to stall,surge,loss of thrust and failure of speed control.Thus,fault diagnosis of gas turbine actuators has attracted considerable attention,from b...Actuator faults can be critical in turbofan engines as they can lead to stall,surge,loss of thrust and failure of speed control.Thus,fault diagnosis of gas turbine actuators has attracted considerable attention,from both academia and industry.However,the extensive literature that exists on this topic does not address identifying the severity of actuator faults and focuses mainly on actuator fault detection and isolation.In addition,previous studies of actuator fault identification have not dealt with multiple concurrent faults in real time,especially when these are accompanied by sudden failures under dynamic conditions.This study develops component-level models for fault identification in four typical actuators used in high-bypass ratio turbofan engines under both dynamic and steady-state conditions and these are then integrated with the engine performance model developed by the authors.The research results reported here present a novel method of quantifying actuator faults using dynamic effect compensation.The maximum error for each actuator is less than0.06%and 0.07%,with average computational time of less than 0.0058 s and 0.0086 s for steady-state and transient cases,respectively.These results confirm that the proposed method can accurately and efficiently identify concurrent actuator fault for an engine operating under either transient or steady-state conditions,even in the case of a sudden malfunction.The research results emonstrate the potential benefit to emergency response capabilities by introducing this method of monitoring the health of aero engines.展开更多
基金support from the Contract Research(“Development of Breathable Fabrics with Nano-Electrospun Membrane”,CityU ref.:9231419“Research and application of antibacterial and healing-promoting smart nanofiber dressing for children’s burn wounds”,CityU ref:PJ9240111)+1 种基金the National Natural Science Foundation of China(“Study of Multi-Responsive Shape Memory Polyurethane Nanocomposites Inspired by Natural Fibers”,Grant No.51673162)Startup Grant of CityU(“Laboratory of Wearable Materials for Healthcare”,Grant No.9380116).
文摘Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for mitigating the energy crisis.A comprehensive review connecting the advancements in engineered radiative cooling systems(ERCSs),encompassing material and structural design as well as thermal and energy-related applications,is currently absent.Herein,this review begins with a concise summary of the essential concepts of ERCSs,followed by an introduction to engineered materials and structures,containing nature-inspired designs,chromatic materials,meta-structural configurations,and multilayered constructions.It subsequently encapsulates the primary applications,including thermal-regulating textiles and energy-saving devices.Next,it highlights the challenges of ERCSs,including maximized thermoregulatory effects,environmental adaptability,scalability and sustainability,and interdisciplinary integration.It seeks to offer direction for forthcoming fundamental research and industrial advancement of radiative cooling systems in real-world applications.
基金Supported by the National Natural Science Foundation of China,No.82170406 and No.81970238.
文摘Gastric ulcer(GU)represents a clinically significant manifestation of peptic ulcer disease,driven by a complex interplay of microbial,environmental,and immuneinflammatory factors.A recent cross-sectional study by Shen et al systematically evaluated six complete blood count-derived inflammatory indices:Neutrophil-tolymphocyte ratio,monocyte-to-lymphocyte ratio,platelet-to-lymphocyte ratio,systemic immune-inflammation index,systemic inflammatory response index(SIRI),and aggregate index of systemic inflammation and demonstrated their positive associations with GU prevalence,identifying SIRI as the strongest predictor.This editorial contextualizes these findings within the broader literature,clarifies that these indices reflect systemic rather than GU-specific inflammation,highlights methodological strengths and major limitations,and proposes a conceptual clinical algorithm for integrating SIRI into GU risk assessment.Future multicenter studies incorporating Helicobacter pylori infection,non-steroidal antiinflammatory drug exposure,and prospective design are essential to validate and translate these findings into clinical practice.
基金Hongguang Wu,Both authors contributed equally to this work and share first authorshipLing Dong,Both authors contributed equally to this work and share first authorship。
文摘The human retina,a complex and highly specialized structure,includes multiple cell types that work synergistically to generate and transmit visual signals.However,genetic predisposition or age-related degeneration can lead to retinal damage that severely impairs vision or causes blindness.Treatment options for retinal diseases are limited,and there is an urgent need for innovative therapeutic strategies.Cell and gene therapies are promising because of the efficacy of delivery systems that transport therapeutic genes to targeted retinal cells.Gene delivery systems hold great promise for treating retinal diseases by enabling the targeted delivery of therapeutic genes to affected cells or by converting endogenous cells into functional ones to facilitate nerve regeneration,potentially restoring vision.This review focuses on two principal categories of gene delivery vectors used in the treatment of retinal diseases:viral and non-viral systems.Viral vectors,including lentiviruses and adeno-associated viruses,exploit the innate ability of viruses to infiltrate cells,which is followed by the introduction of therapeutic genetic material into target cells for gene correction.Lentiviruses can accommodate exogenous genes up to 8 kb in length,but their mechanism of integration into the host genome presents insertion mutation risks.Conversely,adeno-associated viruses are safer,as they exist as episomes in the nucleus,yet their limited packaging capacity constrains their application to a narrower spectrum of diseases,which necessitates the exploration of alternative delivery methods.In parallel,progress has also occurred in the development of novel non-viral delivery systems,particularly those based on liposomal technology.Manipulation of the ratios of hydrophilic and hydrophobic molecules within liposomes and the development of new lipid formulations have led to the creation of advanced non-viral vectors.These innovative systems include solid lipid nanoparticles,polymer nanoparticles,dendrimers,polymeric micelles,and polymeric nanoparticles.Compared with their viral counterparts,non-viral delivery systems offer markedly enhanced loading capacities that enable the direct delivery of nucleic acids,mRNA,or protein molecules into cells.This bypasses the need for DNA transcription and processing,which significantly enhances therapeutic efficiency.Nevertheless,the immunogenic potential and accumulation toxicity associated with non-viral particulate systems necessitates continued optimization to reduce adverse effects in vivo.This review explores the various delivery systems for retinal therapies and retinal nerve regeneration,and details the characteristics,advantages,limitations,and clinical applications of each vector type.By systematically outlining these factors,our goal is to guide the selection of the optimal delivery tool for a specific retinal disease,which will enhance treatment efficacy and improve patient outcomes while paving the way for more effective and targeted therapeutic interventions.
基金supported by the National Natural Science Foundations of China,Nos.82272163,82472164(both MF)。
文摘Functional neurological recovery remains the primary objective when treating ischemic stroke.However,current therapeutic approaches often fall short of achieving optimal outcomes.One of the most significant challenges in stroke treatment is the effective delivery of neuroprotective agents across the blood–brain barrier to ischemic regions within the brain.The blood–brain barrier,while essential for protecting the brain from harmful substances,also restricts the passage of many therapeutic compounds,thus limiting their efficacy.In this review,we summarizes the emerging role of nanoparticle-based therapies for the treatment of ischemic stroke and investigate their potential to revolutionize drug delivery,enhance neuroprotection,and promote functional recovery.Recent advancements in nanotechnology have led to the development of engineered nanoparticles specifically designed to overcome the blood–brain barrier,thus enabling the targeted delivery of therapeutic agents directly to the affected brain areas.Preclinical studies have demonstrated the remarkable potential of nanoparticle-based therapies to activate key neuroprotective pathways,such as the phosphoinositide 3-kinase/protein kinase B/c AMP response element-binding protein signaling cascade,which is crucial for neuronal survival,synaptic plasticity,and post-stroke recovery.By modulating these pathways,nanoparticles could mitigate neuronal damage,reduce inflammation,and promote tissue repair.Furthermore,nanoparticles offer a unique advantage by enabling multimodal therapeutic strategies that simultaneously target multiple pathological mechanisms of ischemic stroke,including oxidative stress,neuroinflammation,and apoptosis.This multifaceted approach enhances the overall efficacy of treatment,addressing the complex and interconnected processes that contribute to stroke-related brain injury.Surface modifications,such as functionalization with specific ligands or targeting molecules,further improve the precision of drug delivery,enhance targeting specificity,and prolong systemic circulation,thereby optimizing therapeutic outcomes.Nanoparticlebased therapeutics represent a paradigm shift for the management of stroke and provide a promising avenue for reducing post-stroke disability and improving the outcomes of long-term rehabilitation.By combining targeted drug delivery with the ability to modulate critical neuroprotective pathways,nanoparticles hold the potential to transform the treatment landscape for ischemic stroke.However,while preclinical data are highly encouraging,significant challenges remain in translating these advancements into clinical practice.Further research is needed to refine nanoparticle designs,optimize their safety profiles,and ensure their scalability for widespread application.Rigorous clinical trials are essential to validate their efficacy,assess long-term biocompatibility,and address potential off-target effects.The integration of interdisciplinary approaches,combining insights from nanotechnology,neuroscience,and pharmacology,will be critical if we are to overcome these challenges.Ultimately,nanoparticle-based therapies offer a foundation for innovative,precision-based treatments that could significantly improve outcomes for stroke patients,thus paving the way for a new era in stroke care and neurological rehabilitation.
文摘The rise of the aging population parallels the rapidly increasing cases of neurological disorders. This puts pressure on scientists and physicians to find novel methods that can prevent and treat neurodegeneration. The brain is made up of a complex network of different cell types that work in tandem to maintain systemic homeostasis.
文摘Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].
文摘Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Numerous applications have been developed to support the challenges in intelligent healthcare systems.However,because mental health data is sensitive,privacy concerns have emerged.Federated learning has gotten some attention.This research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare systems.It explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health applications.This research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security concerns.The survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.
基金National Key R&D Program of China of the 13th Five-Year Plan(No.2018YFD1100704)。
文摘To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the effectiveness of flexibility management strategies under different climate conditions and extreme weather events.Using both typical and extreme weather data from cities in five major climate zones of China,this study investigates the energy flexibility potential of an office building under three short-term HVAC management strategies in the context of different climates.The results show that the peak load flexibility and overall energy performance of the three short-term strategies were affected by the surrounding climate conditions.The peak load reduction rate of the pre-cooling and zone temperature reset strategies declined linearly as outdoor temperature increased.Under extreme climate conditions,the daily peak-load time was found to be over two hours earlier than under typical conditions,and the intensive solar radiation found in the extreme conditions can weaken the correlation between peak load reduction and outdoor temperature,risking the ability of a building’s HVAC system to maintain a comfortable indoor environment.
基金Supported by Beijing Municipal Natural Science Foundation of China(Grant No.24JL002)China Postdoctoral Science Foundation(Grant No.2024M754054)+2 种基金National Natural Science Foundation of China(Grant No.52120105008)Beijing Municipal Outstanding Young Scientis Program of Chinathe New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenues for digital transformation and intelligent upgrading.Industry 5.0,a further extension and development of Industry 4.0,has become an important development trend in industry with more emphasis on human-centered sustainability and flexibility.Accordingly,both the industrial metaverse and digital twins have attracted much attention in this new era.However,the relationship between them is not clear enough.In this paper,a comparison between digital twins and the metaverse in industry is made firstly.Then,we propose the concept and framework of Digital Twin Systems Engineering(DTSE)to demonstrate how digital twins support the industrial metaverse in the era of Industry 5.0 by integrating systems engineering principles.Furthermore,we discuss the key technologies and challenges of DTSE,in particular how artificial intelligence enhances the application of DTSE.Finally,a specific application scenario in the aviation field is presented to illustrate the application prospects of DTSE.
基金supported by the National Natural Science Foundation of China(82204634,82174047,81622051)the Zhejiang Provincial Natural Science Foundation of China(LQ22H280010)the Foundation of Zhejiang Chinese Medical University(2021ZR03).
文摘Drug delivery systems(DDS)have recently emerged as a promising approach for the unique advantages of drug protection and targeted delivery.However,the access of nanoparticles/drugs to the central nervous system(CNS)remains a challenge mainly due to the obstruction from brain barriers.Immune cells infiltrating the CNS in the pathological state have inspired the development of strategies for CNS foundation drug delivery.Herein,we outline the three major brain barriers in the CNS and the mechanisms by which immune cells migrate across the blood–brain barrier.We subsequently review biomimetic strategies utilizing immune cell-based nanoparticles for the delivery of nanoparticles/drugs to the CNS,as well as recent progress in rationally engineering immune cell-based DDS for CNS diseases.Finally,we discuss the challenges and opportunities of immune cell-based DDS in CNS diseases to promote their clinical development.
基金supported in part by the National Natural Science Foundation of China under Grant 62371181in part by the Changzhou Science and Technology International Cooperation Program under Grant CZ20230029+1 种基金supported by a National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(2021R1A2B5B02087169)supported under the framework of international cooperation program managed by the National Research Foundation of Korea(2022K2A9A1A01098051)。
文摘The Intelligent Internet of Things(IIoT)involves real-world things that communicate or interact with each other through networking technologies by collecting data from these“things”and using intelligent approaches,such as Artificial Intelligence(AI)and machine learning,to make accurate decisions.Data science is the science of dealing with data and its relationships through intelligent approaches.Most state-of-the-art research focuses independently on either data science or IIoT,rather than exploring their integration.Therefore,to address the gap,this article provides a comprehensive survey on the advances and integration of data science with the Intelligent IoT(IIoT)system by classifying the existing IoT-based data science techniques and presenting a summary of various characteristics.The paper analyzes the data science or big data security and privacy features,including network architecture,data protection,and continuous monitoring of data,which face challenges in various IoT-based systems.Extensive insights into IoT data security,privacy,and challenges are visualized in the context of data science for IoT.In addition,this study reveals the current opportunities to enhance data science and IoT market development.The current gap and challenges faced in the integration of data science and IoT are comprehensively presented,followed by the future outlook and possible solutions.
基金supported by the National University of Defense Technology Research Fund Projectthe National Natural Science Foundation of China under Grant Nos. 12047561 and 12104507+1 种基金the NSAF under Grant No. U1830206the Science and Technology Innovation Program of Hunan Province under Grant No. 2021RC4026。
文摘The dynamics of phase separation in H–He binary systems within gas giants such as Jupiter and Saturn exhibit remarkable complexity, yet lack systematic investigation. Through large-scale machine-learning-accelerated molecular dynamics simulations spanning broad temperature-pressure-composition(2000–10000 K, 1–7 Mbar,pure H to pure He) regimes, we systematically determine self and mutual diffusion coefficients in H–He systems and establish a six-dimensional framework correlating temperature, pressure, helium abundance, phase separation degree, diffusion coefficients, and anisotropy. Key findings reveal that hydrogen exhibits active directional migration with pronounced diffusion anisotropy, whereas helium passively aggregates in response. While the conventional mixing rule underestimates mutual diffusion coefficients by neglecting velocity cross-correlations,the assumption of an ideal thermodynamic factor(Q = 1) overestimates them due to unaccounted non-ideal thermodynamic effects—both particularly pronounced in strongly phase-separated regimes. Notably, hydrogen's dual role, anisotropic diffusion and bond stabilization via helium doping, modulates demixing kinetics. Large-scale simulations(216,000 atoms) propose novel phase-separation paradigms, such as “hydrogen bubble/wisp” formation, challenging the classical “helium rain” scenario, striving to bridge atomic-scale dynamics to planetary-scale phase evolution.
基金supported in part by the National Natural Science Foundation of China(62173255,62188101)Shenzhen Key Laboratory of Control Theory and Intelligent Systems(ZDSYS20220330161800001)
文摘Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.
基金support by National Key Research and Development Program of China(2022YFB3803502)National Natural Science Foundation of China(52103076)+5 种基金Science and Technology Commission of Shanghai Municipality(23ZR1400300)special fund of Beijing Key Laboratory of Indoor Air Quality Evaluat ion and Control(NO.BZ0344KF21-02)State Key Laboratory of Electrical Insulation and Power Equipment(EIPE22203)JLF is a member of LSRE-LCM–Laboratory of Separation and Reaction Engineering-Laboratory of Catalysis and Materials,supported by national funds through FCT/MCTES(PIDDAC):LSRE-LCM,UIDB/50020/2020(DOI:10.54499/UIDB/50020/2020)UIDP/50020/2020(DOI:10.54499/UIDP/50020/2020)ALiCE,LA/P/0045/2020(DOI:10.54499/LA/P/0045/2020).
文摘Direct seawater splitting has emerged as a popular and promising research direction for synthesising clean,green,non-polluting,and sustainable hydrogen energy without depending on high-purity water in the face of the world’s shortage of fossil energy.However,efficient seawater splitting is hindered by slow kinetics caused by the ultra-low conductivity and the presence of bacteria,microorganisms,and stray ions in seawater.Additionally,producing hydrogen on an industrial scale is challenging due to the high production cost.The present review addresses these challenges from the catalyst point of view,namely,that designing catalysts with high catalytic activity and stability can directly affect the rate and effect of seawater splitting.From the ion transfer perspective,designing membranes can block harmful ions,improving the stability of seawater splitting.From the energy point of view,mixed seawater systems and self-powered systems also provide new and low-energy research systems for seawater splitting.Finally,ideas and directions for further research on direct seawater splitting in the future are pointed out,with the aim of achieving low-cost and high-efficiency hydrogen production.
基金supported by the National Natural Science Foundation of China under grants 62072229,U1936201,62071220,61976113joint project of China Mobile Research Institute&X-NET。
文摘Dual-function communication radar systems use common Radio Frequency(RF)signals are used for both communication and detection.For better compatibility with existing communication systems,we adopt Multiple-Input Multiple-Output(MIMO)Orthogonal Frequency Division Multiplexing(OFDM)signals as integrated signals and investigate the estimation performance of MIMO-OFDM signals.First,we analyze the Cramer-Rao Lower Bound(CRLB)of parameter estimation.Then,the transmit powers over different subcarriers are optimized to achieve the best tradeoff between the transmission rate and the estimation performance.Finally,we propose a more accurate estimation method that uses Canonical Polyadic Decomposition(CPD)of the third-order tensor to obtain the parameter matrices.Due to the characteristic of the column structure of the parameter matrices,we only need to use DFT/IDFT to recover the parameters of multiple targets.The simulation results show that tensor-based estimation method can achieve a performance close to CRLB,and the estimation performance can be improved by optimizing the transmit powers.
基金supported by the National Natural Science Foundation of China(42277087,42130708,42471021,42277482,and 42361144876)the Natural Science Foundation of Guangdong Province(2024A1515012550)+3 种基金the Hainan Institute of National Park grant(KY-23ZK01)the Tsinghua Shenzhen International Graduate School Cross-disciplinary Research and Innovation Fund Research Plan(JC2022011)the Shenzhen Science and Technology Program(JCYJ20240813112106009 and ZDSYS20220606100806014)the Scientific Research Start-up Funds(QD2021030C)from Tsinghua Shenzhen International Graduate School。
文摘Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air pollution is crucial for mitigating climate change,improving air quality,and promoting the sustainable development of food systems.However,the literature lacks a comprehensive review of these interactions,particularly in the current phase of rapid development in the field.To address this gap,this study systematically reviews recent research on the impacts of climate change and air pollution on food systems,as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution.In addition,this study summarizes various strategies for mitigation and adaptation,including adjustments in agricultural practices and food supply chains.Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions.This review offers a critical overview of current research on the interactions among food systems,climate change,and air pollution and highlights future research directions to support the transition to sustainable food systems.
基金supported by Animal Nutrition,Eastman Chemical Company,Kingsport,TN,USA.
文摘Background The emergence of antibiotic resistant microorganisms associated with conventional swine production practices has increased interest in acid-based compounds having antimicrobial properties and other biological functions as nutritional interventions.Despite the interest in organic acids and monoglycerides,few studies have examined the effects of the combination of these acid-based additives in weaned pigs under disease challenge conditions.Therefore,this study aimed to investigate the effects of dietary supplementation with blend of organic acids and/or medium-chain fatty acid monoglycerides on intestinal health and systemic immunity of weaned pigs experimentally infected with an enterotoxigenic Escherichia coli(ETEC)F18 at 4-week of age.Results Dietary supplementation of organic acids,monoglycerides,or both organic acids and monoglycerides(combination)reduced(P<0.05)the diarrhea frequency of ETEC F18-infected pigs throughout the experimental period(d−7 to 21 post-inoculation).This is consistent with the reduced(P<0.05)proportion ofβ-hemolytic coliforms in feces observed for the organic acid and combination treatments on d 10 post-inoculation.Supplementation of organic acids,monoglycerides,or combination also reduced(P<0.05)bacterial translocation in mesenteric lymph nodes on d 21 post-inoculation.Pigs fed with monoglycerides or combination had lower(P<0.05)white blood cells on d 5 post-inoculation,and pigs fed the combination also had lower(P<0.05)lymphocytes than pigs in control group.Monoglyceride supplementation increased(P<0.05)white blood cells and neutrophils compared with control group on d 14 post-inoculation.However,supplementation with organic acid blend,monoglyceride blend,or combination did not affect growth performance in this experiment.Conclusions Supplementation with monoglycerides or organic acids alone or in combination improves the detrimental effects of ETEC F18 infection in weaned pigs,as indicated by reduced diarrhea,fecal shedding ofβ-hemolytic coliforms,and bacterial translocation,and thus enhancing disease resistance.Monoglycerides reduced the inflammatory response during peak infection,but their immunomodulatory and possible synergistic effects with organic acids need to be further investigated.
基金supported by National Natural Science Foundation of China(No.5227130161).
文摘High-entropy materials(HEMs),an innovative class of materials with complex stoichiometry,have recently garnered consider-able attention in energy storage applications.While their multi-element compositions(five or more principal elements in nearly equiatom-ic proportions)confer unique advantages such as high configurational entropy,lattice distortion,and synergistic cocktail effects,the fun-damental understanding of structure-property relationships in battery systems remains fragmented across existing studies.This review ad-dresses critical research gaps by proposing a multidimensional design paradigm that systematically integrates synergistic mechanisms spanning cathodes,anodes,electrolytes,and electrocatalysts.We provide an in-depth analysis of HEMs’thermodynamic/kinetic stabiliza-tion principles and structure-regulated electrochemical properties,integrating and establishing quantitative correlations between entropy-driven phase stability and charge transport dynamics.By summarizing the performance benchmarking results of lithium/sodium/potassi-um-ion battery components,we reveal how entropy-mediated structural tailoring enhances cycle stability and ionic conductivity.Notably,we pioneer the systematic association of high-entropy effects to electrochemical interfaces,demonstrating their unique potential in stabil-izing solid-electrolyte interphases and suppressing transition metal dissolution.Emerging opportunities in machine learning-driven com-position screening and sustainable manufacturing are discussed alongside critical challenges,including performance variability metrics and cost-benefit analysis for industrial implementation.This work provides both fundamental insights and practical guidelines for advan-cing HEMs toward next-generation battery technologies.
基金supported by the National Natural Science Foundation of China(82102315).
文摘BACKGROUND:The lack of a stable,easy-to-operate animal model for severe trauma has hindered the research progress.The aim of this study is to develop a mouse model that replicates the pathophysiological conditions of severe trauma,providing a reliable research tool.METHODS:Male C57BL/6J mice(aged 8-10 weeks and weighting approximately 20 g)were used to establish the severe trauma model.Under anesthesia,a midshaft femoral fracture was created and packed with sterile cotton.A midline incision was made from the inguinal region to the sternum,exposing the abdominal organs for 30 min.The right femoral artery was cannulated to induce controlled blood loss at 30%,35%,40%,and 50%of the total blood volume.Survival rates were monitored for 24 h post-induction.In the mice that experienced 30%blood loss,the mean arterial pressure,body temperature,blood gas parameters,peripheral blood inflammatory markers,and major organ pathological changes were assessed.RESULTS:Mice with femoral fractures,soft tissue injuries,abdominal organ exposure,and 30%blood loss exhibited stable survival rates.Increased blood loss significantly reduced survival rates.Mean arterial pressure decreased initially,recovering within 0-15 min and returning to baseline by 50 min.Similarly,the body temperature decreased initially and gradually recovered to baseline within 50 min.Levels of peripheral blood inflammatory markers remained elevated for 12 h post-injury.Distant organs,including intestines,lungs,liver,spleen and kidneys,displayed varying degrees of injury.CONCLUSION:The established mouse model replicates the pathophysiological responses to severe trauma,indicating stability and reproducibility,which could be an useful tool for further trauma research.
基金support by the National Natural Science Foundation of China(Grant No.52402520)。
文摘Actuator faults can be critical in turbofan engines as they can lead to stall,surge,loss of thrust and failure of speed control.Thus,fault diagnosis of gas turbine actuators has attracted considerable attention,from both academia and industry.However,the extensive literature that exists on this topic does not address identifying the severity of actuator faults and focuses mainly on actuator fault detection and isolation.In addition,previous studies of actuator fault identification have not dealt with multiple concurrent faults in real time,especially when these are accompanied by sudden failures under dynamic conditions.This study develops component-level models for fault identification in four typical actuators used in high-bypass ratio turbofan engines under both dynamic and steady-state conditions and these are then integrated with the engine performance model developed by the authors.The research results reported here present a novel method of quantifying actuator faults using dynamic effect compensation.The maximum error for each actuator is less than0.06%and 0.07%,with average computational time of less than 0.0058 s and 0.0086 s for steady-state and transient cases,respectively.These results confirm that the proposed method can accurately and efficiently identify concurrent actuator fault for an engine operating under either transient or steady-state conditions,even in the case of a sudden malfunction.The research results emonstrate the potential benefit to emergency response capabilities by introducing this method of monitoring the health of aero engines.
