Simulating U(1) quantum gauge theories with spatial dimensions greater than one is of great physical significance. Here we propose a simple realization of U(1) gauge theory with Rydberg and Rydberg-dressed atom arrays...Simulating U(1) quantum gauge theories with spatial dimensions greater than one is of great physical significance. Here we propose a simple realization of U(1) gauge theory with Rydberg and Rydberg-dressed atom arrays. Within the experimentally accessible range, we find that the various aspects of the U(1) gauge theory can be well simulated, such as the emergence of topological sectors, incommensurability, and the Rokhsar–Kivelson point that hosts deconfined charge excitations and degenerate topological sectors. Our proposal is promising to implement experimentally and exhibits pronounced quantum dynamics.展开更多
The experimental realization of Rydberg dressing technology in ultracold atomic systems provides another superior platform for studying novel states of matter and macroscopic quantum phenomena.In this work,based on th...The experimental realization of Rydberg dressing technology in ultracold atomic systems provides another superior platform for studying novel states of matter and macroscopic quantum phenomena.In this work,based on the mean-field theory,we have investigated the ground-state phases of a two-component Bose–Einstein condensate with Rydberg interaction and confined in a toroidal trap.The effects of the Rydberg interaction and external potential,especially the Rydberg blockade radius,on the ground-state structure of such a system have been investigated in full parameter space.Our results show that the Rydberg blockade radius,which can be regarded as another controllable parameter,can be used to obtain a variety of ground-state phases.More interestingly,it is found that for weak Rydberg interactions,the Rydberg blockade radius breaks the spontaneous rotational symmetry of the system,leading to the formation of a discrete unit cell structure.For strongly interacting cases,it can be used to realize different orders of discrete rotational symmetry breaking.展开更多
This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key de...This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key design parameters including casing dimensions and detonation positions.The paper details the finite element analysis for fragmentation,the characterizations of the dynamic hardening and fracture models,the generation of comprehensive datasets,and the training of the ANN model.The results show the influence of casing dimensions on fragment velocity distributions,with the tendencies indicating increased resultant velocity with reduced thickness,increased length and diameter.The model's predictive capability is demonstrated through the accurate predictions for both training and testing datasets,showing its potential for the real-time prediction of fragmentation performance.展开更多
Methane(CH4),the predominant component of natural gas and shale gas,is regarded as a promising carbon feedstock for chemical synthesis[1].However,considering the extreme stability of CH4 molecules,it's quite chall...Methane(CH4),the predominant component of natural gas and shale gas,is regarded as a promising carbon feedstock for chemical synthesis[1].However,considering the extreme stability of CH4 molecules,it's quite challenging in simultaneously achieving high activity and selectivity for target products under mild conditions,especially when synthesizing high-value C2t chemicals such as ethanol[2].The conversion of methane to ethanol by photocatalysis is promising for achieving transformation under ambient temperature and pressure conditions.Currently,the apparent quantum efficiency(AQE)of solar-driven methane-to-ethanol conversion is generally below 0.5%[3,4].Furthermore,the stability of photocatalysts remains inadequate,offering substantial potential for further improvement.展开更多
Driven critical dynamics in quantum phase transitions holds significant theoretical importance,and also has practical applications in fast-developing quantum devices.While scaling corrections have been shown to play i...Driven critical dynamics in quantum phase transitions holds significant theoretical importance,and also has practical applications in fast-developing quantum devices.While scaling corrections have been shown to play important roles in fully characterizing equilibrium quantum criticality,their impact on nonequilibrium critical dynamics has not been extensively explored.In this work,we investigate the driven critical dynamics in a two-dimensional quantum Heisenberg model.We find that in this model the scaling corrections arising from both finite system size and finite driving rate must be incorporated into the finite-time scaling form in order to properly describe the nonequilibrium scaling behaviors.In addition,improved scaling relations are obtained from the expansion of the full scaling form.We numerically verify these scaling forms and improved scaling relations for different starting states using the nonequilibrium quantum Monte Carlo algorithm.展开更多
Diabetic wounds(DWs)are a major complication of diabetes mellitus,characterized by a complex patho-physiological microenvironment that is associated with elevated morbidity and mortality.Conventional management strate...Diabetic wounds(DWs)are a major complication of diabetes mellitus,characterized by a complex patho-physiological microenvironment that is associated with elevated morbidity and mortality.Conventional management strategies often fail to address the multifaceted nature of these wounds effectively.Recent advancements in understanding the mechanisms of DW healing have spurred the development of a plethora of bioactive dressings designed to interact with and modulate the DW microenvironment.These innovations have culminated in the introduction of the“microenvironment-sensitive with on-demand management”paradigm aimed at delivering precision therapy responsive to dynamic changes within DW.Despite these advancements,the current literature lacks a comprehensive review that cate-gorizes and evaluates active,passive,and on-demand approaches that address the DW microenviron-ment.Herein,we describe the unique pathogenic mechanisms and microenvironmental characteristics that distinguish DW from normal acute wounds.This review provides an extensive overview of contem-porary active and passive management strategies incorporating on-demand management principles designed for DW microenvironments.Furthermore,it addresses the principal challenges faced in this therapeutic domain and outlines the potential innovations that can enhance the efficacy and specificity of bioactive dressings.The insights presented here aim to guide further research and development in the on-demand management of DW to improve patient outcomes by aligning personalized therapy modali-ties with the pathophysiological realities of DW.展开更多
Despite significant progress in the Prognostics and Health Management(PHM)domain using pattern learning systems from data,machine learning(ML)still faces challenges related to limited generalization and weak interpret...Despite significant progress in the Prognostics and Health Management(PHM)domain using pattern learning systems from data,machine learning(ML)still faces challenges related to limited generalization and weak interpretability.A promising approach to overcoming these challenges is to embed domain knowledge into the ML pipeline,enhancing the model with additional pattern information.In this paper,we review the latest developments in PHM,encapsulated under the concept of Knowledge Driven Machine Learning(KDML).We propose a hierarchical framework to define KDML in PHM,which includes scientific paradigms,knowledge sources,knowledge representations,and knowledge embedding methods.Using this framework,we examine current research to demonstrate how various forms of knowledge can be integrated into the ML pipeline and provide roadmap to specific usage.Furthermore,we present several case studies that illustrate specific implementations of KDML in the PHM domain,including inductive experience,physical model,and signal processing.We analyze the improvements in generalization capability and interpretability that KDML can achieve.Finally,we discuss the challenges,potential applications,and usage recommendations of KDML in PHM,with a particular focus on the critical need for interpretability to ensure trustworthy deployment of artificial intelligence in PHM.展开更多
Acute lung injury(ALI)was characterized by excessive reactive oxygen species(ROS)levels and inflammatory response in the lung.Scavenging ROS could inhibit the excessive inflammatory response,further treating ALI.Herei...Acute lung injury(ALI)was characterized by excessive reactive oxygen species(ROS)levels and inflammatory response in the lung.Scavenging ROS could inhibit the excessive inflammatory response,further treating ALI.Herein,we designed a novel nanozyme(P@Co)comprised of polydopamine(PDA)nanoparticles(NPs)loading with ultra-small Co,combining with near infrared(NIR)irradiation,which could efficiently scavenge intracellular ROS and suppress inflammatory responses against ALI.For lipopolysaccharide(LPS)induced macrophages,P@Co+NIR presented excellent antioxidant and anti-inflammatory capacities through lowering intracellular ROS levels,decreasing the expression levels of interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)as well as inducing macrophage M2 directional polarization.Significantly,it displayed the outstanding activities of lowering acute lung inflammation,relieving diffuse alveolar damage,and up-regulating heat shock protein 70(HSP70)expression,resulting in synergistic enhanced ALI therapy effect.It offers a novel strategy for the clinical treatment of ROS related diseases.展开更多
Diabetic wounds represent a significant challenge in the medical field,significantly impacting patient quality of life and imposing a heavy burden on healthcare systems.Intelligent hydrogel dressings have attracted si...Diabetic wounds represent a significant challenge in the medical field,significantly impacting patient quality of life and imposing a heavy burden on healthcare systems.Intelligent hydrogel dressings have attracted significant attention in diabetic wound treatment due to their unique properties.This review systematically explores the three main categories of intelligent hydrogels(natural,synthetic,and composite),dissecting their composition,structure,and the mechanisms that enable their intelligent responses.The crucial roles of these dressings in maintaining a moist wound environment,efficiently absorbing exudate,and precisely delivering drugs are expounded.Moreover,their application advantages in combating bacteria and infections,regulating inflammation and immunity,promoting angiogenesis and tissue regeneration,as well as enabling real-time monitoring and personalized treatment,are explored in depth.Additionally,we discuss future research directions and the prospects for personalized precision medicine in diabetic wound care,aiming to inspire innovation and provide a comprehensive theoretical basis for the development of nextgeneration intelligent dressings.展开更多
The healing of diabetic wounds poses a significant healthcare burden due to persistent inflammation,M1 macrophage aggregation,and high glucose levels in the microenvironment.Previous studies have demonstrated that imm...The healing of diabetic wounds poses a significant healthcare burden due to persistent inflammation,M1 macrophage aggregation,and high glucose levels in the microenvironment.Previous studies have demonstrated that immunomodulatory hydrogel dressings can facilitate diabetic wound healing.However,current immunomodulatory hydrogels require costly and complex treatments such as cell therapy and cytokines.Herein,a hierarchical hydrogel dressing with continuous biochemical gradient based on glycyrrhizic acid(GA) was constructed to modulate immunomodulatory processes in diabetic wounds.The hydrogels present many desirable features,such as tunable mechanical properties,broad antibacterial ability,outstanding conductive,transparent,and self-adhesive properties.The resultant hydrogel can promote diabetic wound healing by preventing bacterial infection,promoting macrophage polarization,improving the inflammatory microenvironment,and inducing angiogenesis and neurogenesis.Furthermore,electrical stimulation(ES) can further promote the healing of chronic diabetic wounds,providing valuable guidance for relevant clinical practice.展开更多
Additive manufacturing(AM)technology has revolutionized engineering field by enabling the creation of intricate,high-performance structures that were once difficult or impossible to fabricate.This transformative techn...Additive manufacturing(AM)technology has revolutionized engineering field by enabling the creation of intricate,high-performance structures that were once difficult or impossible to fabricate.This transformative technology has particularly advanced the development of metamaterials-engineered materials whose unique properties arise from their structure rather than composition-unlocking immense potential in fields ranging from aerospace to biomedical engineering.展开更多
Mimicking the hierarchical structure of the skin is one of the most important strategies in skin tissue engineering.Monolayer wound dressings are usually not able to provide several functions at the same time and cann...Mimicking the hierarchical structure of the skin is one of the most important strategies in skin tissue engineering.Monolayer wound dressings are usually not able to provide several functions at the same time and cannot meet all clinical needs.In order to maximize therapeutic efficiency,herein,we fabricated a Tri-layer wound dressing,where the middle layer was fabricated via 3D-printing and composed of alginate,tragacanth and zinc oxide nanoparticles(ZnO NPs).Both upper and bottom layers were constructed using electrospinning technique;the upper layer was made of hydrophobic polycaprolactone to mimic epidermis,while the bottom layer consisted of Soluplus■ and insulin-like growth factor-1(IGF-1)to promote cell behavior.Swelling,water vapor permeability and tensile properties of the dressings were evaluated and the Tri-layer dressing exhibited impressive antibacterial activity and cell stimulation following by the release of ZnO NPs and IGF-1.Additionally,the Tri-layer dressing led to faster healing of full-thicknesswound in ratmodel compared to monolayer and Bilayer dressings.Overall,the evidence confirmed that the Trilayer wound dressing is extremely effective for full-thickness wound healing.展开更多
Accurate identification and effective support of key blocks are crucial for ensuring the stability and safety of rock slopes.The number of structural planes and rock blocks were reduced in previous studies.This impair...Accurate identification and effective support of key blocks are crucial for ensuring the stability and safety of rock slopes.The number of structural planes and rock blocks were reduced in previous studies.This impairs the ability to characterize complex rock slopes accurately and inhibits the identification of key blocks.In this paper,a knowledge-data dually driven paradigm for accurate identification of key blocks in complex rock slopes is proposed.Our basic idea is to integrate key block theory into data-driven models based on finely characterizing structural features to identify key blocks in complex rock slopes accurately.The proposed novel paradigm consists of(1)representing rock slopes as graph-structured data based on complex systems theory,(2)identifying key nodes in the graph-structured data using graph deep learning,and(3)mapping the key nodes of graph-structured data to corresponding key blocks in the rock slope.Verification experiments and real-case applications are conducted by the proposed method.The verification results demonstrate excellent model performance,strong generalization capability,and effective classification results.Moreover,the real case application is conducted on the northern slope of the Yanqianshan Iron Mine.The results show that the proposed method can accurately identify key blocks in complex rock slopes,which can provide a decision-making basis and rational recommendations for effective support and instability prevention of rock slopes,thereby ensuring the stability of rock engineering and the safety of life and property.展开更多
BACKGROUND Aloe vera has been used as a traditional herbal therapy for wound management and dermatological conditions worldwide for thousands of years.Scientific evidence has confirmed that acemannan,the bioactive com...BACKGROUND Aloe vera has been used as a traditional herbal therapy for wound management and dermatological conditions worldwide for thousands of years.Scientific evidence has confirmed that acemannan,the bioactive compound in aloe vera gel,exhibits significant anti-inflammatory and immunomodulatory properties that enhance tissue regeneration.This case report describes the successful application of an innovative acemannan-enriched glycolipid sphere dressing derived from aloe vera gel in diabetic foot ulcer(DFU)treatment,which achieved a clinically remarkable outcome.CASE SUMMARY An 80-year-old female patient with a 20-year history of type 2 diabetes mellitus experienced recurrent diabetic foot pain for 15 years.She had multiple hospitalizations due to acute infections and poorly controlled hyperglycemia.Long-term treatments included metformin and gliclazide.Upon presentation,she had a nonhealing wound on her left dorsal foot,diagnosed as a severe DFU(Texas classification:Grade II,stage D).She declined amputation and opted for conservative treatment.The medical team applied an acemannan-enriched glycolipid sphere dressing five times daily to the left calf and foot,avoiding the wound area.Frequency was reduced to three times daily after scab formation.Weight-bearing on the injured foot was avoided.Through in-person and online consultations,the team managed her lifestyle and diet,emphasizing natural foods.After 5 months,the DFU healed without significant scarring or functional loss.No recurrence was observed during the 2-year follow-up.Acemannan-enriched glycolipid sphere dressings promote DFU healing.This suggests the potential of these dressings for treating other refractory wounds.展开更多
The discovery of new superconducting materials,particularly those exhibiting high critical temperature(Tc),has been a vibrant area of study within the field of condensed matter physics.Conventional approaches primaril...The discovery of new superconducting materials,particularly those exhibiting high critical temperature(Tc),has been a vibrant area of study within the field of condensed matter physics.Conventional approaches primarily rely on physical intuition to search for potential superconductors within the existing databases.However,the known materials only scratch the surface of the extensive array of possibilities within the realm of materials.展开更多
Recently, high-precision trajectory prediction of ballistic missiles in the boost phase has become a research hotspot. This paper proposes a trajectory prediction algorithm driven by data and knowledge(DKTP) to solve ...Recently, high-precision trajectory prediction of ballistic missiles in the boost phase has become a research hotspot. This paper proposes a trajectory prediction algorithm driven by data and knowledge(DKTP) to solve this problem. Firstly, the complex dynamics characteristics of ballistic missile in the boost phase are analyzed in detail. Secondly, combining the missile dynamics model with the target gravity turning model, a knowledge-driven target three-dimensional turning(T3) model is derived. Then, the BP neural network is used to train the boost phase trajectory database in typical scenarios to obtain a datadriven state parameter mapping(SPM) model. On this basis, an online trajectory prediction framework driven by data and knowledge is established. Based on the SPM model, the three-dimensional turning coefficients of the target are predicted by using the current state of the target, and the state of the target at the next moment is obtained by combining the T3 model. Finally, simulation verification is carried out under various conditions. The simulation results show that the DKTP algorithm combines the advantages of data-driven and knowledge-driven, improves the interpretability of the algorithm, reduces the uncertainty, which can achieve high-precision trajectory prediction of ballistic missile in the boost phase.展开更多
Social behaviors,including social support and mating,play a critical role in survival and reproduction.Animals must make adaptive social decisions based on internal states and external contexts[1].The sex of a social ...Social behaviors,including social support and mating,play a critical role in survival and reproduction.Animals must make adaptive social decisions based on internal states and external contexts[1].The sex of a social partner is a crucial factor that shapes social decision-making,as oppositesex interactions are vital for fulfilling reproductive needs,whereas same-sex interactions are essential for both collaborative support and competitive behaviors.Under normal circumstances,mice typically exhibit a variety of prosocial behaviors that strengthen social bonds within their groups.展开更多
The 2025 National Energy Conference(hereinafter referred to as“the conference”)was held in Beijing on December 15,2024.The conference highlighted that“next year and the‘15th Five-Year Plan’period will be crucial ...The 2025 National Energy Conference(hereinafter referred to as“the conference”)was held in Beijing on December 15,2024.The conference highlighted that“next year and the‘15th Five-Year Plan’period will be crucial for accelerating the construction of a new energy system and promoting high-quality energy development and high-level security”.This marks the 16th national energy conference since the annual national energy conference was reinstated in January 2009 after a hiatus of over a decade.展开更多
Introduction Early cancer detection represents a critical evolution in healthcare,addressing a significant pain point in cancer treatment:the tendency for diagnoses to occur at advanced stages.Traditionally,many cance...Introduction Early cancer detection represents a critical evolution in healthcare,addressing a significant pain point in cancer treatment:the tendency for diagnoses to occur at advanced stages.Traditionally,many cancers are not identified until they have progressed to late stages,where treatment options become limited,less effective,and more costly.This late detection results in poorer prognoses,higher mortality rates,and increased healthcare costs.Without early detection tools like Fluorescence In Situ Hybridization(FISH),these challenges persist,leaving patients with fewer opportunities for successful outcomes.展开更多
基金supported by the National Key Research and Development Program of China (Grant Nos. 2022YFA1404204 and 2022YFA1403700)the National Natural Science Foundation of China (Grant Nos. 12274086, 11534001 and 11925402)+5 种基金funding from the National Science Foundation of China (Grant Nos. 12274046, 11874094, 12147102, and 12347101)Chongqing Natural Science Foundation (Grant No. CSTB2022NSCQ-JQX0018)the Fundamental Research Funds for the Central Universities (Grant No. 2021CDJZYJH-003)Xiaomi Foundation/Xiaomi Young Talents Programthe supports of the start-up funding of Westlake Universitysupport from the Natural Sciences and Engineering Research Council of Canada (NSERC) through Discovery Grants。
文摘Simulating U(1) quantum gauge theories with spatial dimensions greater than one is of great physical significance. Here we propose a simple realization of U(1) gauge theory with Rydberg and Rydberg-dressed atom arrays. Within the experimentally accessible range, we find that the various aspects of the U(1) gauge theory can be well simulated, such as the emergence of topological sectors, incommensurability, and the Rokhsar–Kivelson point that hosts deconfined charge excitations and degenerate topological sectors. Our proposal is promising to implement experimentally and exhibits pronounced quantum dynamics.
基金supported by the National Natural Science Foundation of China under Grants No.12005125,No.12105365,12175129the Key Research Program of Frontier Sciences of Chinese Academy of Sciences under Grant No.ZDBS-LY-7016+2 种基金Shaanxi Fundamental Science Research Project for Mathematics and Physics under Grant No.22JSY034Scientific Research Program Funded by Shaanxi Provincial Education Department Program No.23JP020the Youth Innovation Team of Shaanxi Universities。
文摘The experimental realization of Rydberg dressing technology in ultracold atomic systems provides another superior platform for studying novel states of matter and macroscopic quantum phenomena.In this work,based on the mean-field theory,we have investigated the ground-state phases of a two-component Bose–Einstein condensate with Rydberg interaction and confined in a toroidal trap.The effects of the Rydberg interaction and external potential,especially the Rydberg blockade radius,on the ground-state structure of such a system have been investigated in full parameter space.Our results show that the Rydberg blockade radius,which can be regarded as another controllable parameter,can be used to obtain a variety of ground-state phases.More interestingly,it is found that for weak Rydberg interactions,the Rydberg blockade radius breaks the spontaneous rotational symmetry of the system,leading to the formation of a discrete unit cell structure.For strongly interacting cases,it can be used to realize different orders of discrete rotational symmetry breaking.
基金supported by Poongsan-KAIST Future Research Center Projectthe fund support provided by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(Grant No.2023R1A2C2005661)。
文摘This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key design parameters including casing dimensions and detonation positions.The paper details the finite element analysis for fragmentation,the characterizations of the dynamic hardening and fracture models,the generation of comprehensive datasets,and the training of the ANN model.The results show the influence of casing dimensions on fragment velocity distributions,with the tendencies indicating increased resultant velocity with reduced thickness,increased length and diameter.The model's predictive capability is demonstrated through the accurate predictions for both training and testing datasets,showing its potential for the real-time prediction of fragmentation performance.
基金the support from the National Natural Science Foundation of China(52202306)Program from Guangdong Introducing Innovative and Entrepreneurial Teams(2019ZT08L101 and RCTDPT-2020-001)+1 种基金Shenzhen Key Laboratory of Eco-materials and Renewable Energy(ZDSYS20200922160400001)the Provincial Talent Plan of Guangdong(2023TB0012).
文摘Methane(CH4),the predominant component of natural gas and shale gas,is regarded as a promising carbon feedstock for chemical synthesis[1].However,considering the extreme stability of CH4 molecules,it's quite challenging in simultaneously achieving high activity and selectivity for target products under mild conditions,especially when synthesizing high-value C2t chemicals such as ethanol[2].The conversion of methane to ethanol by photocatalysis is promising for achieving transformation under ambient temperature and pressure conditions.Currently,the apparent quantum efficiency(AQE)of solar-driven methane-to-ethanol conversion is generally below 0.5%[3,4].Furthermore,the stability of photocatalysts remains inadequate,offering substantial potential for further improvement.
基金supported by the National Natural Science Foundation of China(Grant Nos.12104109,12222515,and 12075324)the Science and Technology Projects in Guangzhou(Grant No.2024A04J2092)the Science and Technology Projects in Guangdong Province(Grant No.211193863020).
文摘Driven critical dynamics in quantum phase transitions holds significant theoretical importance,and also has practical applications in fast-developing quantum devices.While scaling corrections have been shown to play important roles in fully characterizing equilibrium quantum criticality,their impact on nonequilibrium critical dynamics has not been extensively explored.In this work,we investigate the driven critical dynamics in a two-dimensional quantum Heisenberg model.We find that in this model the scaling corrections arising from both finite system size and finite driving rate must be incorporated into the finite-time scaling form in order to properly describe the nonequilibrium scaling behaviors.In addition,improved scaling relations are obtained from the expansion of the full scaling form.We numerically verify these scaling forms and improved scaling relations for different starting states using the nonequilibrium quantum Monte Carlo algorithm.
基金supported by the National Natural Science Foundation of China(22408078,82401057,32101170)the Zhejiang Province Postdoctoral Excellence Funding Program-Special Support(ZJ2024004).
文摘Diabetic wounds(DWs)are a major complication of diabetes mellitus,characterized by a complex patho-physiological microenvironment that is associated with elevated morbidity and mortality.Conventional management strategies often fail to address the multifaceted nature of these wounds effectively.Recent advancements in understanding the mechanisms of DW healing have spurred the development of a plethora of bioactive dressings designed to interact with and modulate the DW microenvironment.These innovations have culminated in the introduction of the“microenvironment-sensitive with on-demand management”paradigm aimed at delivering precision therapy responsive to dynamic changes within DW.Despite these advancements,the current literature lacks a comprehensive review that cate-gorizes and evaluates active,passive,and on-demand approaches that address the DW microenviron-ment.Herein,we describe the unique pathogenic mechanisms and microenvironmental characteristics that distinguish DW from normal acute wounds.This review provides an extensive overview of contem-porary active and passive management strategies incorporating on-demand management principles designed for DW microenvironments.Furthermore,it addresses the principal challenges faced in this therapeutic domain and outlines the potential innovations that can enhance the efficacy and specificity of bioactive dressings.The insights presented here aim to guide further research and development in the on-demand management of DW to improve patient outcomes by aligning personalized therapy modali-ties with the pathophysiological realities of DW.
基金Supported in part by Science Center for Gas Turbine Project(Project No.P2022-DC-I-003-001)National Natural Science Foundation of China(Grant No.52275130).
文摘Despite significant progress in the Prognostics and Health Management(PHM)domain using pattern learning systems from data,machine learning(ML)still faces challenges related to limited generalization and weak interpretability.A promising approach to overcoming these challenges is to embed domain knowledge into the ML pipeline,enhancing the model with additional pattern information.In this paper,we review the latest developments in PHM,encapsulated under the concept of Knowledge Driven Machine Learning(KDML).We propose a hierarchical framework to define KDML in PHM,which includes scientific paradigms,knowledge sources,knowledge representations,and knowledge embedding methods.Using this framework,we examine current research to demonstrate how various forms of knowledge can be integrated into the ML pipeline and provide roadmap to specific usage.Furthermore,we present several case studies that illustrate specific implementations of KDML in the PHM domain,including inductive experience,physical model,and signal processing.We analyze the improvements in generalization capability and interpretability that KDML can achieve.Finally,we discuss the challenges,potential applications,and usage recommendations of KDML in PHM,with a particular focus on the critical need for interpretability to ensure trustworthy deployment of artificial intelligence in PHM.
基金financially supported by the Key Research&Development Program of Guangxi(No.GuiKeAB22080088)the Joint Project on Regional High-Incidence Diseases Research of Guangxi Natural Science Foundation(No.2023GXNSFDA026023)+3 种基金the Natural Science Foundation of Guangxi(No.2023JJA140322)the National Natural Science Foundation of China(No.82360372)the High-level Medical Expert Training Program of Guangxi“139 Plan Funding(No.G202003010)the Medical Appropriate Technology Development and Popularization and Application Project of Guangxi(No.S2020099)。
文摘Acute lung injury(ALI)was characterized by excessive reactive oxygen species(ROS)levels and inflammatory response in the lung.Scavenging ROS could inhibit the excessive inflammatory response,further treating ALI.Herein,we designed a novel nanozyme(P@Co)comprised of polydopamine(PDA)nanoparticles(NPs)loading with ultra-small Co,combining with near infrared(NIR)irradiation,which could efficiently scavenge intracellular ROS and suppress inflammatory responses against ALI.For lipopolysaccharide(LPS)induced macrophages,P@Co+NIR presented excellent antioxidant and anti-inflammatory capacities through lowering intracellular ROS levels,decreasing the expression levels of interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)as well as inducing macrophage M2 directional polarization.Significantly,it displayed the outstanding activities of lowering acute lung inflammation,relieving diffuse alveolar damage,and up-regulating heat shock protein 70(HSP70)expression,resulting in synergistic enhanced ALI therapy effect.It offers a novel strategy for the clinical treatment of ROS related diseases.
文摘Diabetic wounds represent a significant challenge in the medical field,significantly impacting patient quality of life and imposing a heavy burden on healthcare systems.Intelligent hydrogel dressings have attracted significant attention in diabetic wound treatment due to their unique properties.This review systematically explores the three main categories of intelligent hydrogels(natural,synthetic,and composite),dissecting their composition,structure,and the mechanisms that enable their intelligent responses.The crucial roles of these dressings in maintaining a moist wound environment,efficiently absorbing exudate,and precisely delivering drugs are expounded.Moreover,their application advantages in combating bacteria and infections,regulating inflammation and immunity,promoting angiogenesis and tissue regeneration,as well as enabling real-time monitoring and personalized treatment,are explored in depth.Additionally,we discuss future research directions and the prospects for personalized precision medicine in diabetic wound care,aiming to inspire innovation and provide a comprehensive theoretical basis for the development of nextgeneration intelligent dressings.
基金supported by Natural Science Foundation of Jilin Province(No.SKL202302002)。
文摘The healing of diabetic wounds poses a significant healthcare burden due to persistent inflammation,M1 macrophage aggregation,and high glucose levels in the microenvironment.Previous studies have demonstrated that immunomodulatory hydrogel dressings can facilitate diabetic wound healing.However,current immunomodulatory hydrogels require costly and complex treatments such as cell therapy and cytokines.Herein,a hierarchical hydrogel dressing with continuous biochemical gradient based on glycyrrhizic acid(GA) was constructed to modulate immunomodulatory processes in diabetic wounds.The hydrogels present many desirable features,such as tunable mechanical properties,broad antibacterial ability,outstanding conductive,transparent,and self-adhesive properties.The resultant hydrogel can promote diabetic wound healing by preventing bacterial infection,promoting macrophage polarization,improving the inflammatory microenvironment,and inducing angiogenesis and neurogenesis.Furthermore,electrical stimulation(ES) can further promote the healing of chronic diabetic wounds,providing valuable guidance for relevant clinical practice.
文摘Additive manufacturing(AM)technology has revolutionized engineering field by enabling the creation of intricate,high-performance structures that were once difficult or impossible to fabricate.This transformative technology has particularly advanced the development of metamaterials-engineered materials whose unique properties arise from their structure rather than composition-unlocking immense potential in fields ranging from aerospace to biomedical engineering.
基金support of Isfahan University of Medical Sciences(Project code No.#1401262).
文摘Mimicking the hierarchical structure of the skin is one of the most important strategies in skin tissue engineering.Monolayer wound dressings are usually not able to provide several functions at the same time and cannot meet all clinical needs.In order to maximize therapeutic efficiency,herein,we fabricated a Tri-layer wound dressing,where the middle layer was fabricated via 3D-printing and composed of alginate,tragacanth and zinc oxide nanoparticles(ZnO NPs).Both upper and bottom layers were constructed using electrospinning technique;the upper layer was made of hydrophobic polycaprolactone to mimic epidermis,while the bottom layer consisted of Soluplus■ and insulin-like growth factor-1(IGF-1)to promote cell behavior.Swelling,water vapor permeability and tensile properties of the dressings were evaluated and the Tri-layer dressing exhibited impressive antibacterial activity and cell stimulation following by the release of ZnO NPs and IGF-1.Additionally,the Tri-layer dressing led to faster healing of full-thicknesswound in ratmodel compared to monolayer and Bilayer dressings.Overall,the evidence confirmed that the Trilayer wound dressing is extremely effective for full-thickness wound healing.
基金supported by the National Natural Science Foundation of China(Grant Nos.42277161,42230709).
文摘Accurate identification and effective support of key blocks are crucial for ensuring the stability and safety of rock slopes.The number of structural planes and rock blocks were reduced in previous studies.This impairs the ability to characterize complex rock slopes accurately and inhibits the identification of key blocks.In this paper,a knowledge-data dually driven paradigm for accurate identification of key blocks in complex rock slopes is proposed.Our basic idea is to integrate key block theory into data-driven models based on finely characterizing structural features to identify key blocks in complex rock slopes accurately.The proposed novel paradigm consists of(1)representing rock slopes as graph-structured data based on complex systems theory,(2)identifying key nodes in the graph-structured data using graph deep learning,and(3)mapping the key nodes of graph-structured data to corresponding key blocks in the rock slope.Verification experiments and real-case applications are conducted by the proposed method.The verification results demonstrate excellent model performance,strong generalization capability,and effective classification results.Moreover,the real case application is conducted on the northern slope of the Yanqianshan Iron Mine.The results show that the proposed method can accurately identify key blocks in complex rock slopes,which can provide a decision-making basis and rational recommendations for effective support and instability prevention of rock slopes,thereby ensuring the stability of rock engineering and the safety of life and property.
文摘BACKGROUND Aloe vera has been used as a traditional herbal therapy for wound management and dermatological conditions worldwide for thousands of years.Scientific evidence has confirmed that acemannan,the bioactive compound in aloe vera gel,exhibits significant anti-inflammatory and immunomodulatory properties that enhance tissue regeneration.This case report describes the successful application of an innovative acemannan-enriched glycolipid sphere dressing derived from aloe vera gel in diabetic foot ulcer(DFU)treatment,which achieved a clinically remarkable outcome.CASE SUMMARY An 80-year-old female patient with a 20-year history of type 2 diabetes mellitus experienced recurrent diabetic foot pain for 15 years.She had multiple hospitalizations due to acute infections and poorly controlled hyperglycemia.Long-term treatments included metformin and gliclazide.Upon presentation,she had a nonhealing wound on her left dorsal foot,diagnosed as a severe DFU(Texas classification:Grade II,stage D).She declined amputation and opted for conservative treatment.The medical team applied an acemannan-enriched glycolipid sphere dressing five times daily to the left calf and foot,avoiding the wound area.Frequency was reduced to three times daily after scab formation.Weight-bearing on the injured foot was avoided.Through in-person and online consultations,the team managed her lifestyle and diet,emphasizing natural foods.After 5 months,the DFU healed without significant scarring or functional loss.No recurrence was observed during the 2-year follow-up.Acemannan-enriched glycolipid sphere dressings promote DFU healing.This suggests the potential of these dressings for treating other refractory wounds.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.62476278,12434009,and 12204533)the National Key R&D Program of China(Grant No.2024YFA1408601)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0302402)。
文摘The discovery of new superconducting materials,particularly those exhibiting high critical temperature(Tc),has been a vibrant area of study within the field of condensed matter physics.Conventional approaches primarily rely on physical intuition to search for potential superconductors within the existing databases.However,the known materials only scratch the surface of the extensive array of possibilities within the realm of materials.
基金the National Natural Science Foundation of China (Grants No. 12072090 and No.12302056) to provide fund for conducting experiments。
文摘Recently, high-precision trajectory prediction of ballistic missiles in the boost phase has become a research hotspot. This paper proposes a trajectory prediction algorithm driven by data and knowledge(DKTP) to solve this problem. Firstly, the complex dynamics characteristics of ballistic missile in the boost phase are analyzed in detail. Secondly, combining the missile dynamics model with the target gravity turning model, a knowledge-driven target three-dimensional turning(T3) model is derived. Then, the BP neural network is used to train the boost phase trajectory database in typical scenarios to obtain a datadriven state parameter mapping(SPM) model. On this basis, an online trajectory prediction framework driven by data and knowledge is established. Based on the SPM model, the three-dimensional turning coefficients of the target are predicted by using the current state of the target, and the state of the target at the next moment is obtained by combining the T3 model. Finally, simulation verification is carried out under various conditions. The simulation results show that the DKTP algorithm combines the advantages of data-driven and knowledge-driven, improves the interpretability of the algorithm, reduces the uncertainty, which can achieve high-precision trajectory prediction of ballistic missile in the boost phase.
基金supported by grants from the National Natural Science Foundation of China(32471074 and 32200825)the STI2030-Major Projects(2021ZD0203000 and 2021ZD0203002)+1 种基金the Shandong Provincial Taishan Scholars Project(tsqn202306174)the Shandong Provincial Natural Science Foundation(ZR2022QC173).
文摘Social behaviors,including social support and mating,play a critical role in survival and reproduction.Animals must make adaptive social decisions based on internal states and external contexts[1].The sex of a social partner is a crucial factor that shapes social decision-making,as oppositesex interactions are vital for fulfilling reproductive needs,whereas same-sex interactions are essential for both collaborative support and competitive behaviors.Under normal circumstances,mice typically exhibit a variety of prosocial behaviors that strengthen social bonds within their groups.
文摘The 2025 National Energy Conference(hereinafter referred to as“the conference”)was held in Beijing on December 15,2024.The conference highlighted that“next year and the‘15th Five-Year Plan’period will be crucial for accelerating the construction of a new energy system and promoting high-quality energy development and high-level security”.This marks the 16th national energy conference since the annual national energy conference was reinstated in January 2009 after a hiatus of over a decade.
基金supported by Guangzhou Development Zone Science and Technology(2021GH10,2020GH10,2023GH02)the University of Macao(MYRG2022-00271-FST)The Science and Technology Development Fund(FDCT)of Macao(0032/2022/A).
文摘Introduction Early cancer detection represents a critical evolution in healthcare,addressing a significant pain point in cancer treatment:the tendency for diagnoses to occur at advanced stages.Traditionally,many cancers are not identified until they have progressed to late stages,where treatment options become limited,less effective,and more costly.This late detection results in poorer prognoses,higher mortality rates,and increased healthcare costs.Without early detection tools like Fluorescence In Situ Hybridization(FISH),these challenges persist,leaving patients with fewer opportunities for successful outcomes.
