Tau plays a crucial role in several neurodegenerative diseases,collectively referred to as tauopathies.Therefore,targeting potential pathological changes in tau could enable useful therapeutic interventions.However,ta...Tau plays a crucial role in several neurodegenerative diseases,collectively referred to as tauopathies.Therefore,targeting potential pathological changes in tau could enable useful therapeutic interventions.However,tau is not an easy target because it dynamically interacts with microtubules and other cellular components,which presents a challenge for tau-targeted drugs.New cellular models could aid the development of mechanism-based tau-targeted therapies.展开更多
Target-based and phenotype-based methods are the two main approaches for drug screening.Target-based drug screening focuses on specific targets CPA highly correlated with disease mechanisms,by detecting protein-ligand...Target-based and phenotype-based methods are the two main approaches for drug screening.Target-based drug screening focuses on specific targets CPA highly correlated with disease mechanisms,by detecting protein-ligand binding structure,dynamics and affinity.Currently,the four mainstream drug targets are G protein-coupled receptors(GPCRs),kinases,ion channels,and nuclear receptors,accounting for over 70%of effective drug targets,most of which are membrane proteins and enzymes.In recent years,various new drug targets have been continuously discovered,and the research focus has shifted from simple affinity analysis to high-throughput and high-content screening,as well as exploring drug-target interaction modes.These deepen reliance on the analytical techniques to have higher sensitivity,recognition specificity,and applicability to diversified target structures,which promoting the rapid development of novel screening methods.展开更多
Reversible data hiding(RDH)enables secret data embedding while preserving complete cover image recovery,making it crucial for applications requiring image integrity.The pixel value ordering(PVO)technique used in multi...Reversible data hiding(RDH)enables secret data embedding while preserving complete cover image recovery,making it crucial for applications requiring image integrity.The pixel value ordering(PVO)technique used in multi-stego images provides good image quality but often results in low embedding capability.To address these challenges,this paper proposes a high-capacity RDH scheme based on PVO that generates three stego images from a single cover image.The cover image is partitioned into non-overlapping blocks with pixels sorted in ascending order.Four secret bits are embedded into each block’s maximum pixel value,while three additional bits are embedded into the second-largest value when the pixel difference exceeds a predefined threshold.A similar embedding strategy is also applied to the minimum side of the block,including the second-smallest pixel value.This design enables each block to embed up to 14 bits of secret data.Experimental results demonstrate that the proposed method achieves significantly higher embedding capacity and improved visual quality compared to existing triple-stego RDH approaches,advancing the field of reversible steganography.展开更多
Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework f...Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.展开更多
Component-based Chinese Medicine(CCM)stands as a pivotal endeavor in modernizing traditional Chinese medicine(TCM).By integrating classical TCM theories with modern scientific methodologies,CCM aims to achieve herbal ...Component-based Chinese Medicine(CCM)stands as a pivotal endeavor in modernizing traditional Chinese medicine(TCM).By integrating classical TCM theories with modern scientific methodologies,CCM aims to achieve herbal formulas with“defined components,clarified mechanisms,and controllable quality.”This approach not only transitions TCM development from empirical tradition to evidence-based science but also positions it for global recognition.Drawing on recent advancements in CCM,this editorial explores key insights and challenges shaping its trajectory.展开更多
Magnesium-based materials,including magnesium alloys,have emerged as a promising class of biodegradable materials with potential applications in cancer therapy due to their unique properties,including biocompatibility...Magnesium-based materials,including magnesium alloys,have emerged as a promising class of biodegradable materials with potential applications in cancer therapy due to their unique properties,including biocompatibility,biodegradability,and the ability to modulate the tumor microenvironment.The main degradation products of magnesium alloys are magnesium ions(Mg^(2+)),hydrogen(H_(2)),and magnesium hydroxide(Mg(OH)_(2)).Magnesium ions can regulate tumor growth and metastasis by mediating the inflammatory response and oxidative stress,maintaining genomic stability,and affecting the tumor microenvironment.Similarly,hydrogen can inhibit tumorigenesis through antioxidant and anti-inflammatory properties.Moreover,Mg(OH)_(2) can alter the pH of the microenvironment,impacting tumorigenesis.Biodegradable magnesium alloys serve various functions in clinical applications,including,but not limited to,bonefixation,coronary stents,and drug carriers.Nonetheless,the anti-tumor mechanism associated with magnesium-based materials has not been thoroughly investigated.This review provides a comprehensive overview of the current state of magnesium-based therapies for cancer.It highlights the mechanisms of action,identifies the challenges that must be addressed,and discusses prospects for oncological applications.展开更多
In general,the rapid growth of α-Fe clusters is a challenge in high Fe-content Fe-based amorphous alloys,negatively affecting their physical properties.Herein,we introduce an efficient and rapid post-treatment techni...In general,the rapid growth of α-Fe clusters is a challenge in high Fe-content Fe-based amorphous alloys,negatively affecting their physical properties.Herein,we introduce an efficient and rapid post-treatment technique known as ultrasonic vibration rapid processing(UVRP),which enables the formation of high-density strong magnetic α-Fe clusters,thereby enhancing the soft magnetic properties of Fe_(78)Si(13)B_(9) amorphous alloy ribbon.展开更多
With the aid of multi-agent based modeling approach to complex systems, the hierarchy simulation models of carrier-based aircraft catapult launch are developed. Ocean, carrier, aircraft, and atmosphere are treated as ...With the aid of multi-agent based modeling approach to complex systems, the hierarchy simulation models of carrier-based aircraft catapult launch are developed. Ocean, carrier, aircraft, and atmosphere are treated as aggregation agents, the detailed components like catapult, landing gears, and disturbances are considered as meta-agents, which belong to their aggregation agent. Thus, the model with two layers is formed i.e. the aggregation agent layer and the meta-agent layer. The information communication among all agents is described. The meta-agents within one aggregation agent communicate with each other directly by information sharing, but the meta-agents, which belong to different aggregation agents exchange their information through the aggregation layer first, and then perceive it from the sharing environment, that is the aggregation agent. Thus, not only the hierarchy model is built, but also the environment perceived by each agent is specified. Meanwhile, the problem of balancing the independency of agent and the resource consumption brought by real-time communication within multi-agent system （MAS） is resolved. Each agent involved in carrier-based aircraft catapult launch is depicted, with considering the interaction within disturbed atmospheric environment and multiple motion bodies including carrier, aircraft, and landing gears. The models of reactive agents among them are derived based on tensors, and the perceived messages and inner frameworks of each agent are characterized. Finally, some results of a simulation instance are given. The simulation and modeling of dynamic system based on multi-agent system is of benefit to express physical concepts and logical hierarchy clearly and precisely. The system model can easily draw in kinds of other agents to achieve a precise simulation of more complex system. This modeling technique makes the complex integral dynamic equations of multibodies decompose into parallel operations of single agent, and it is convenient to expand, maintain, and reuse the program codes.展开更多
This study begins with the fabrication and simulation of high-performance back-illuminated AlGaN-based solar-blind ultraviolet(UV)photodetectors.Based on the photodetectors,a low-noise,high-gain UV detection system ci...This study begins with the fabrication and simulation of high-performance back-illuminated AlGaN-based solar-blind ultraviolet(UV)photodetectors.Based on the photodetectors,a low-noise,high-gain UV detection system circuit is designed and fabricated,enabling the detection,acquisition,and calibration of weak solar-blind UV signals.Experimental results demonstrate that under zero bias conditions,with a UV light power density of 3.45μW/cm^(2) at 260 nm,the sample achieves a peak responsivity(R)of 0.085 A·W^(−1),an external quantum efficiency(EQE)of 40.7%,and a detectivity(D^(*))of 7.46×10^(12) cm·Hz^(1/2)·W^(−1).The system exhibits a bandpass characteristic within the 240–280 nm wavelength range,coupled with a high signal-to-noise ratio(SNR)of 39.74 dB.展开更多
To solve the serious volume expansion problem of Sb-based anode materials in the alloying/dealloying process,a strategy combining electrospinning and hydrogen reduction is proposed to prepare a series of Sb-based allo...To solve the serious volume expansion problem of Sb-based anode materials in the alloying/dealloying process,a strategy combining electrospinning and hydrogen reduction is proposed to prepare a series of Sb-based alloys/carbon nanofiber composites(SbM/CNFs,M=Co,Zn,Ni).Inactive elements are innovatively introduced to form Sb based alloys with enhanced stability.The results show that the content of SbCo nanoparticles is high to 69.12%(mass),which are uniformly dispersed in carbon fibers.When evaluated as anode material for SIBs,SbCo/CNFs anode exhibits excellent sodium storage capacity,the initial discharge capacity is 580.0 mA h·g^(-1)at 0.1 A g^(-1),which can hold 483.5 mA h·g^(-1)after 100 cycles.Even the current density increases to 1.0 A g^(-1),the specific capacity still maintains at 344.5 mA h·g^(-1)after 150 cycles.The improved sodium storage capacity is attributed to the synergistic effect of conductive carbon fibers and SbCo nanoparticles with uniform dispersion,which not only provide excellent electronic conductivity,but also enhance structural stability to reduce volume change.展开更多
Economic violence is a form of domestic violence that extends beyond physical harm,affecting victims’economic stability and independence.This situation perpetuates gender inequality and also reinforces the cycle of g...Economic violence is a form of domestic violence that extends beyond physical harm,affecting victims’economic stability and independence.This situation perpetuates gender inequality and also reinforces the cycle of gender-based violence.With definitions of economic violence broadening to encompass a range of coercive and manipulative behaviors-from financial abuse in domestic violence scenarios to the economic harassment faced by stay-at-home moms-understanding this form of exploitation is crucial for crafting effective interventions.This article aims to delve into various facets of economic violence,including its definition,prevalence,and the stark realities it creates for its victims.Following the search of international databases:Social Work Abstracts(EBSCO),Psychology Abstracts,Family and Women Studies Worldwide,Psychiatry Online,Psych INFO(including Psych ARTICLES),PubMed,Wiley,and Scopus,60 peer-reviewed articles that met all inclusion criteria were included in the paper.Our review clarifies that looking forward,the call for a comprehensive understanding of economic violence,enhanced legal frameworks,and the strengthening of supportive networks underscore the multidisciplinary approach required to combat this issue effectively.展开更多
Magnesium(Mg)alloys are promising candidates for biodegradable implants and medical devices due to their biocompatibility,mechanical properties,and ability to degrade in vivo,thereby eliminating the need for secondary...Magnesium(Mg)alloys are promising candidates for biodegradable implants and medical devices due to their biocompatibility,mechanical properties,and ability to degrade in vivo,thereby eliminating the need for secondary removal surgeries[1,2].However,their clinical adoption is hindered by rapid corrosion in physiological environments[3–5].Due to the high chemical reactivity of magnesium substrates and the inability of primary corrosion degradation products to form ideal protective layers,no effective scientific guidance has yet been identified from fundamental material science to address the rapid degradation of bare Mg[6–8].Surface modification strategies equivalently create new materials wrapped in a matrix,which can thus be extensively explored to enhance the corrosion resistance of Mg alloys while endowing them with tailored biological functionalities[9,10].展开更多
To enhance the denoising performance of event-based sensors,we introduce a clustering-based temporal deep neural network denoising method(CBTDNN).Firstly,to cluster the sensor output data and obtain the respective clu...To enhance the denoising performance of event-based sensors,we introduce a clustering-based temporal deep neural network denoising method(CBTDNN).Firstly,to cluster the sensor output data and obtain the respective cluster centers,a combination of density-based spatial clustering of applications with noise(DBSCAN)and Kmeans++is utilized.Subsequently,long short-term memory(LSTM)is employed to fit and yield optimized cluster centers with temporal information.Lastly,based on the new cluster centers and denoising ratio,a radius threshold is set,and noise points beyond this threshold are removed.The comprehensive denoising metrics F1_score of CBTDNN have achieved 0.8931,0.7735,and 0.9215 on the traffic sequences dataset,pedestrian detection dataset,and turntable dataset,respectively.And these metrics demonstrate improvements of 49.90%,33.07%,19.31%,and 22.97%compared to four contrastive algorithms,namely nearest neighbor(NNb),nearest neighbor with polarity(NNp),Autoencoder,and multilayer perceptron denoising filter(MLPF).These results demonstrate that the proposed method enhances the denoising performance of event-based sensors.展开更多
Internet of things(IoT)field has emerged due to the rapid growth of artificial intelligence and communication technologies.The use of IoT technology in modern healthcare environments is convenient for doctors and pati...Internet of things(IoT)field has emerged due to the rapid growth of artificial intelligence and communication technologies.The use of IoT technology in modern healthcare environments is convenient for doctors and patients as it can be used in real-time monitoring of patients,proper administration of patient information,and healthcare management.However,the usage of IoT in the healthcare domain will become a nightmare if patient information is not securely maintainedwhile transferring over an insecure network or storing at the administrator end.In this manuscript,the authors have developed a secure IoT healthcare monitoring system using the Blockchainbased XOR Elliptic Curve Cryptography(BC-XORECC)technique to avoid various vulnerable attacks.Initially,thework has established an authentication process for patient details by generating tokens,keys,and tags using Length Ceaser Cipher-based PearsonHashingAlgorithm(LCC-PHA),EllipticCurve Cryptography(ECC),and Fishers Yates Shuffled Based Adelson-Velskii and Landis(FYS-AVL)tree.The authentications prevent unauthorized users from accessing or misuse the data.After that,a secure data transfer is performed using BC-XORECC,which acts faster by maintaining high data privacy and blocking the path for the attackers.Finally,the Linear Spline Kernel-Based Recurrent Neural Network(LSK-RNN)classification monitors the patient’s health status.The whole developed framework brings out a secure data transfer without data loss or data breaches and remains efficient for health care monitoring via IoT.Experimental analysis shows that the proposed framework achieves a faster encryption and decryption time,classifies the patient’s health status with an accuracy of 89%,and remains robust comparedwith the existing state-of-the-art method.展开更多
Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence,particularly during the COVID-19 pandemic.It enables the populatio...Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence,particularly during the COVID-19 pandemic.It enables the population-level monitoring of illicit drug use,pathogen prevalence,and environmental pollutant exposure.In this perspective,we summarize the key challenges specific to the Chinese context:(1)Sampling inconsistencies,necessitating standardized 24-hour composite protocols with high-frequency autosamplers(≤15 min/event)to improve the representativeness of samples.展开更多
The cooling rate of the center and edge of vacuum induction melting(VIM)or vacuum arc remelting(VAR)ingots exhibit substantial difference,leading to markedly distinct dendritic structures and precipitates.The current ...The cooling rate of the center and edge of vacuum induction melting(VIM)or vacuum arc remelting(VAR)ingots exhibit substantial difference,leading to markedly distinct dendritic structures and precipitates.The current lack of precise predictions for dendritic segregation and the distribution of precipitates in ingot makes it difficult to determine the annealing and homogenization heat treatment process.Thus,clarifying the impact of cooling rate on the solidification behavior of alloy is significantly important.The dendritic structure and precipitation characteristics of as-cast C-HRA-3 Ni–Cr–Co–Mo-based heat-resistant alloy were investigated using Thermo-Calc thermodynamic calculations,scanning electron microscopy observations,and electron probe microanalyzer.Based on high temperature observation system,the effects of cooling rate on the dendritic structure,dendritic segregation,and precipitation in this alloy were explored.The results showed that the precipitates in the as-cast C-HRA-3 alloy primarily consist of blocky Ti(C,N)phases,large-sized Ti(C,N)–M_(6)C–M_(23)C_(6) symbiotic phases and M_(6)C–M_(23)C_(6) carbides,and small-sized dispersed M_(6)C and M_(23)C_(6) carbides surronding these symbiotic phases.The primary constituent elements of these precipitates are Mo,Cr,C,and Ti,which predominantly concentrate in the interdendritic regions of the as-cast alloy.There is a clear power-law relationship between the secondary dendrite arm spacing and the cooling rate.The dendritic segregation ratio of Mo,Cr,and Ti exhibits a piecewise functional relationship with the cooling rate,under equiaxed dendritic solidification condition.These predictive models and theoretical analyses were validated using numerical simulations and experimental results from the 200 kg grade VIM electrode.展开更多
Traditional rule-based IntrusionDetection Systems(IDS)are commonly employed owing to their simple design and ability to detect known threats.Nevertheless,as dynamic network traffic and a new degree of threats exist in...Traditional rule-based IntrusionDetection Systems(IDS)are commonly employed owing to their simple design and ability to detect known threats.Nevertheless,as dynamic network traffic and a new degree of threats exist in IoT environments,these systems do not perform well and have elevated false positive rates—consequently decreasing detection accuracy.In this study,we try to overcome these restrictions by employing fuzzy logic and machine learning to develop an Enhanced Rule-Based Model(ERBM)to classify the packets better and identify intrusions.The ERBM developed for this approach improves data preprocessing and feature selections by utilizing fuzzy logic,where three membership functions are created to classify all the network traffic features as low,medium,or high to remain situationally aware of the environment.Such fuzzy logic sets produce adaptive detection rules by reducing data uncertainty.Also,for further classification,machine learning classifiers such as Decision Tree(DT),Random Forest(RF),and Neural Networks(NN)learn complex ways of attacks and make the detection process more precise.A thorough performance evaluation using different metrics,including accuracy,precision,recall,F1 Score,detection rate,and false-positive rate,verifies the supremacy of ERBM over classical IDS.Under extensive experiments,the ERBM enables a remarkable detection rate of 99%with considerably fewer false positives than the conventional models.Integrating the ability for uncertain reasoning with fuzzy logic and an adaptable component via machine learning solutions,the ERBM systemprovides a unique,scalable,data-driven approach to IoT intrusion detection.This research presents a major enhancement initiative in the context of rule-based IDS,introducing improvements in accuracy to evolving IoT threats.展开更多
Conversion and capture of carbon pollutants based on carbon dioxide to valuable green oil-field chemicals are target all over the world for controlling the global warming.The present article used new room temperature ...Conversion and capture of carbon pollutants based on carbon dioxide to valuable green oil-field chemicals are target all over the world for controlling the global warming.The present article used new room temperature amphiphilic imidazolium ionic liquids with superior surface activity in the aqueous solutions to convert carbon dioxide gas to superior amphiphilic calcium carbonate nanoparticles.In this respect,tetra-cationic ionic liquids 2-(4-dodecyldimethylamino)phenyl)-1,3-bis(3-dodecyldimethylammnonio)propyl)bromide-1-H-imidazol-3-ium acetate and 2-(4-hexyldimethylamino)phenyl)-1,3-bis(3-hexcyldimethylammnonio)propyl)bromide-1 H-imidazol-3-ium acetate were prepared.Their chemical structures,thermal as well as their carbon dioxide absorption/desorption characteristicswere evaluated.Theywere used as solvent and capping agent to synthesize calcium carbonate nanoparticles with controlled crystalline lattice,sizes,thermal properties and spherical surface morphologies.The prepared calcium carbonate nanoparticles were used as additives for the commercial water based drilling mud to improve their filter lose and rheology.The data confirm that the lower concentrations of 2-(4-dodecyldimethylamino)phenyl)-1,3-bis(3-dodecyldimethylammnonio)propyl)bromide-1-H-imidazol-3-ium acetate achieved lower seawater filter lose and improved viscosities.展开更多
Mason Reset(MR),a groundbreaking invention by Clesson E.Mason in 1930 that later became a part of“the universal approach to process control instrumentation”,is revisited in this paper and is shown to consists of thr...Mason Reset(MR),a groundbreaking invention by Clesson E.Mason in 1930 that later became a part of“the universal approach to process control instrumentation”,is revisited in this paper and is shown to consists of three actions:fast(errorcorrection),medium(negative feedback for expanded proportional band)and slow(reset for zero steady-state error).The focus of the paper is on the reset action,generated from a positive feedback loop,and its underlying principles with profound implications to our understanding and practice of automatic control,both basic and advanced.For example,we note that reset control and integral control,contrary to common belief,differ fundamentally in design principle and in practicality.Such difference comes to a head in the event of integrator windup:while reset windup is a problem of actuator saturation,the integrator windup is a runaway situation due to controller instability.In fact,there is no advantage gained in replacing MR with an integrator.In other words,one should not integrate the error directly as in standard PID,since doing so makes the closed-loop system internally unstable.With MR-based control formulated in this paper,there is no such threat of instability and,therefore,no need for any anti-windup mechanisms.Furthermore,the integral control is made scalable in this framework as a tradeoff between the steady-state accuracy and the controller stability.This leads to a novel MR-based control design,scalable in gain and in time to accommodate various process characteristics and design specifications.Simple in construction and transparent in principle,this MR-based control,as a basic framework of design,is readily deployable in scale.展开更多
The title of the online version of the original article was revised.The title of the original article has been revised to:Hydrochemical characterization of surface waters in Northern Tehran:Integrating cluster-based t...The title of the online version of the original article was revised.The title of the original article has been revised to:Hydrochemical characterization of surface waters in Northern Tehran:Integrating cluster-based techniques with Self-Organizing Maps.展开更多
文摘Tau plays a crucial role in several neurodegenerative diseases,collectively referred to as tauopathies.Therefore,targeting potential pathological changes in tau could enable useful therapeutic interventions.However,tau is not an easy target because it dynamically interacts with microtubules and other cellular components,which presents a challenge for tau-targeted drugs.New cellular models could aid the development of mechanism-based tau-targeted therapies.
文摘Target-based and phenotype-based methods are the two main approaches for drug screening.Target-based drug screening focuses on specific targets CPA highly correlated with disease mechanisms,by detecting protein-ligand binding structure,dynamics and affinity.Currently,the four mainstream drug targets are G protein-coupled receptors(GPCRs),kinases,ion channels,and nuclear receptors,accounting for over 70%of effective drug targets,most of which are membrane proteins and enzymes.In recent years,various new drug targets have been continuously discovered,and the research focus has shifted from simple affinity analysis to high-throughput and high-content screening,as well as exploring drug-target interaction modes.These deepen reliance on the analytical techniques to have higher sensitivity,recognition specificity,and applicability to diversified target structures,which promoting the rapid development of novel screening methods.
基金funded by University of Transport and Communications(UTC)under grant number T2025-CN-004.
文摘Reversible data hiding(RDH)enables secret data embedding while preserving complete cover image recovery,making it crucial for applications requiring image integrity.The pixel value ordering(PVO)technique used in multi-stego images provides good image quality but often results in low embedding capability.To address these challenges,this paper proposes a high-capacity RDH scheme based on PVO that generates three stego images from a single cover image.The cover image is partitioned into non-overlapping blocks with pixels sorted in ascending order.Four secret bits are embedded into each block’s maximum pixel value,while three additional bits are embedded into the second-largest value when the pixel difference exceeds a predefined threshold.A similar embedding strategy is also applied to the minimum side of the block,including the second-smallest pixel value.This design enables each block to embed up to 14 bits of secret data.Experimental results demonstrate that the proposed method achieves significantly higher embedding capacity and improved visual quality compared to existing triple-stego RDH approaches,advancing the field of reversible steganography.
基金supported by the National Natural Science Foundation of China (No.62202137)the China Postdoctoral Science Foundation (No.2023M730599)the Zhejiang Provincial Natural Science Foundation of China (No.LMS25F020009)。
文摘Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.
文摘Component-based Chinese Medicine(CCM)stands as a pivotal endeavor in modernizing traditional Chinese medicine(TCM).By integrating classical TCM theories with modern scientific methodologies,CCM aims to achieve herbal formulas with“defined components,clarified mechanisms,and controllable quality.”This approach not only transitions TCM development from empirical tradition to evidence-based science but also positions it for global recognition.Drawing on recent advancements in CCM,this editorial explores key insights and challenges shaping its trajectory.
文摘Magnesium-based materials,including magnesium alloys,have emerged as a promising class of biodegradable materials with potential applications in cancer therapy due to their unique properties,including biocompatibility,biodegradability,and the ability to modulate the tumor microenvironment.The main degradation products of magnesium alloys are magnesium ions(Mg^(2+)),hydrogen(H_(2)),and magnesium hydroxide(Mg(OH)_(2)).Magnesium ions can regulate tumor growth and metastasis by mediating the inflammatory response and oxidative stress,maintaining genomic stability,and affecting the tumor microenvironment.Similarly,hydrogen can inhibit tumorigenesis through antioxidant and anti-inflammatory properties.Moreover,Mg(OH)_(2) can alter the pH of the microenvironment,impacting tumorigenesis.Biodegradable magnesium alloys serve various functions in clinical applications,including,but not limited to,bonefixation,coronary stents,and drug carriers.Nonetheless,the anti-tumor mechanism associated with magnesium-based materials has not been thoroughly investigated.This review provides a comprehensive overview of the current state of magnesium-based therapies for cancer.It highlights the mechanisms of action,identifies the challenges that must be addressed,and discusses prospects for oncological applications.
基金supported by the Major Science and Technology Project of Zhongshan City(No.2022AJ004)the Key Basic and Applied Research Program of Guangdong Province(Nos.2019B030302010 and 2022B1515120082)Guangdong Science and Technology Innovation Project(No.2021TX06C111).
文摘In general,the rapid growth of α-Fe clusters is a challenge in high Fe-content Fe-based amorphous alloys,negatively affecting their physical properties.Herein,we introduce an efficient and rapid post-treatment technique known as ultrasonic vibration rapid processing(UVRP),which enables the formation of high-density strong magnetic α-Fe clusters,thereby enhancing the soft magnetic properties of Fe_(78)Si(13)B_(9) amorphous alloy ribbon.
基金Aeronautical Science Foundation of China (2006ZA51004)
文摘With the aid of multi-agent based modeling approach to complex systems, the hierarchy simulation models of carrier-based aircraft catapult launch are developed. Ocean, carrier, aircraft, and atmosphere are treated as aggregation agents, the detailed components like catapult, landing gears, and disturbances are considered as meta-agents, which belong to their aggregation agent. Thus, the model with two layers is formed i.e. the aggregation agent layer and the meta-agent layer. The information communication among all agents is described. The meta-agents within one aggregation agent communicate with each other directly by information sharing, but the meta-agents, which belong to different aggregation agents exchange their information through the aggregation layer first, and then perceive it from the sharing environment, that is the aggregation agent. Thus, not only the hierarchy model is built, but also the environment perceived by each agent is specified. Meanwhile, the problem of balancing the independency of agent and the resource consumption brought by real-time communication within multi-agent system （MAS） is resolved. Each agent involved in carrier-based aircraft catapult launch is depicted, with considering the interaction within disturbed atmospheric environment and multiple motion bodies including carrier, aircraft, and landing gears. The models of reactive agents among them are derived based on tensors, and the perceived messages and inner frameworks of each agent are characterized. Finally, some results of a simulation instance are given. The simulation and modeling of dynamic system based on multi-agent system is of benefit to express physical concepts and logical hierarchy clearly and precisely. The system model can easily draw in kinds of other agents to achieve a precise simulation of more complex system. This modeling technique makes the complex integral dynamic equations of multibodies decompose into parallel operations of single agent, and it is convenient to expand, maintain, and reuse the program codes.
基金supported by the Director’s Fund for the‘Climbing Plan’of the National Space Science Centre of the Chinese Academy of Sciences(No.E2PD10011S)the National Engineering Research Centre for Mobile Private Networks Project(No.BJTU20221102).
文摘This study begins with the fabrication and simulation of high-performance back-illuminated AlGaN-based solar-blind ultraviolet(UV)photodetectors.Based on the photodetectors,a low-noise,high-gain UV detection system circuit is designed and fabricated,enabling the detection,acquisition,and calibration of weak solar-blind UV signals.Experimental results demonstrate that under zero bias conditions,with a UV light power density of 3.45μW/cm^(2) at 260 nm,the sample achieves a peak responsivity(R)of 0.085 A·W^(−1),an external quantum efficiency(EQE)of 40.7%,and a detectivity(D^(*))of 7.46×10^(12) cm·Hz^(1/2)·W^(−1).The system exhibits a bandpass characteristic within the 240–280 nm wavelength range,coupled with a high signal-to-noise ratio(SNR)of 39.74 dB.
基金supported by National Natural Science Foundation of China(22379056,22479065)Industry foresight and common key technology research in Carbon Peak and Carbon Neutrality Special Project from Zhenjiang city(CG2023003)+1 种基金Industry-University-Research Cooperation Project of Jiangsu Province(BY20230347)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(24KJB150008).
文摘To solve the serious volume expansion problem of Sb-based anode materials in the alloying/dealloying process,a strategy combining electrospinning and hydrogen reduction is proposed to prepare a series of Sb-based alloys/carbon nanofiber composites(SbM/CNFs,M=Co,Zn,Ni).Inactive elements are innovatively introduced to form Sb based alloys with enhanced stability.The results show that the content of SbCo nanoparticles is high to 69.12%(mass),which are uniformly dispersed in carbon fibers.When evaluated as anode material for SIBs,SbCo/CNFs anode exhibits excellent sodium storage capacity,the initial discharge capacity is 580.0 mA h·g^(-1)at 0.1 A g^(-1),which can hold 483.5 mA h·g^(-1)after 100 cycles.Even the current density increases to 1.0 A g^(-1),the specific capacity still maintains at 344.5 mA h·g^(-1)after 150 cycles.The improved sodium storage capacity is attributed to the synergistic effect of conductive carbon fibers and SbCo nanoparticles with uniform dispersion,which not only provide excellent electronic conductivity,but also enhance structural stability to reduce volume change.
文摘Economic violence is a form of domestic violence that extends beyond physical harm,affecting victims’economic stability and independence.This situation perpetuates gender inequality and also reinforces the cycle of gender-based violence.With definitions of economic violence broadening to encompass a range of coercive and manipulative behaviors-from financial abuse in domestic violence scenarios to the economic harassment faced by stay-at-home moms-understanding this form of exploitation is crucial for crafting effective interventions.This article aims to delve into various facets of economic violence,including its definition,prevalence,and the stark realities it creates for its victims.Following the search of international databases:Social Work Abstracts(EBSCO),Psychology Abstracts,Family and Women Studies Worldwide,Psychiatry Online,Psych INFO(including Psych ARTICLES),PubMed,Wiley,and Scopus,60 peer-reviewed articles that met all inclusion criteria were included in the paper.Our review clarifies that looking forward,the call for a comprehensive understanding of economic violence,enhanced legal frameworks,and the strengthening of supportive networks underscore the multidisciplinary approach required to combat this issue effectively.
基金supported by grants from the State Key Laboratory for Modification of Chemical Fibers and Polymer Materials,Major/key program(No.23M1060280)the Fundamental Research Funds for the Central Universities(No.2232024D-34 and No 2232023A-10).
文摘Magnesium(Mg)alloys are promising candidates for biodegradable implants and medical devices due to their biocompatibility,mechanical properties,and ability to degrade in vivo,thereby eliminating the need for secondary removal surgeries[1,2].However,their clinical adoption is hindered by rapid corrosion in physiological environments[3–5].Due to the high chemical reactivity of magnesium substrates and the inability of primary corrosion degradation products to form ideal protective layers,no effective scientific guidance has yet been identified from fundamental material science to address the rapid degradation of bare Mg[6–8].Surface modification strategies equivalently create new materials wrapped in a matrix,which can thus be extensively explored to enhance the corrosion resistance of Mg alloys while endowing them with tailored biological functionalities[9,10].
基金supported by the National Natural Science Foundation of China(No.62134004).
文摘To enhance the denoising performance of event-based sensors,we introduce a clustering-based temporal deep neural network denoising method(CBTDNN).Firstly,to cluster the sensor output data and obtain the respective cluster centers,a combination of density-based spatial clustering of applications with noise(DBSCAN)and Kmeans++is utilized.Subsequently,long short-term memory(LSTM)is employed to fit and yield optimized cluster centers with temporal information.Lastly,based on the new cluster centers and denoising ratio,a radius threshold is set,and noise points beyond this threshold are removed.The comprehensive denoising metrics F1_score of CBTDNN have achieved 0.8931,0.7735,and 0.9215 on the traffic sequences dataset,pedestrian detection dataset,and turntable dataset,respectively.And these metrics demonstrate improvements of 49.90%,33.07%,19.31%,and 22.97%compared to four contrastive algorithms,namely nearest neighbor(NNb),nearest neighbor with polarity(NNp),Autoencoder,and multilayer perceptron denoising filter(MLPF).These results demonstrate that the proposed method enhances the denoising performance of event-based sensors.
基金This project has been funded by the Scientific Research Deanship at the University of Ha’il-Saudi Arabia through project number BA-2105.
文摘Internet of things(IoT)field has emerged due to the rapid growth of artificial intelligence and communication technologies.The use of IoT technology in modern healthcare environments is convenient for doctors and patients as it can be used in real-time monitoring of patients,proper administration of patient information,and healthcare management.However,the usage of IoT in the healthcare domain will become a nightmare if patient information is not securely maintainedwhile transferring over an insecure network or storing at the administrator end.In this manuscript,the authors have developed a secure IoT healthcare monitoring system using the Blockchainbased XOR Elliptic Curve Cryptography(BC-XORECC)technique to avoid various vulnerable attacks.Initially,thework has established an authentication process for patient details by generating tokens,keys,and tags using Length Ceaser Cipher-based PearsonHashingAlgorithm(LCC-PHA),EllipticCurve Cryptography(ECC),and Fishers Yates Shuffled Based Adelson-Velskii and Landis(FYS-AVL)tree.The authentications prevent unauthorized users from accessing or misuse the data.After that,a secure data transfer is performed using BC-XORECC,which acts faster by maintaining high data privacy and blocking the path for the attackers.Finally,the Linear Spline Kernel-Based Recurrent Neural Network(LSK-RNN)classification monitors the patient’s health status.The whole developed framework brings out a secure data transfer without data loss or data breaches and remains efficient for health care monitoring via IoT.Experimental analysis shows that the proposed framework achieves a faster encryption and decryption time,classifies the patient’s health status with an accuracy of 89%,and remains robust comparedwith the existing state-of-the-art method.
基金supported by the National Natural Science Foundation of China(Grant no.42307534)Discovery Project(DP220101790)+1 种基金The University of Queensland ScholarshipAustralian Research Council Discovery Project(DP220101790).
文摘Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence,particularly during the COVID-19 pandemic.It enables the population-level monitoring of illicit drug use,pathogen prevalence,and environmental pollutant exposure.In this perspective,we summarize the key challenges specific to the Chinese context:(1)Sampling inconsistencies,necessitating standardized 24-hour composite protocols with high-frequency autosamplers(≤15 min/event)to improve the representativeness of samples.
基金funded by the National Key R&D Program Funded Projects(No.2021YFB3704102).
文摘The cooling rate of the center and edge of vacuum induction melting(VIM)or vacuum arc remelting(VAR)ingots exhibit substantial difference,leading to markedly distinct dendritic structures and precipitates.The current lack of precise predictions for dendritic segregation and the distribution of precipitates in ingot makes it difficult to determine the annealing and homogenization heat treatment process.Thus,clarifying the impact of cooling rate on the solidification behavior of alloy is significantly important.The dendritic structure and precipitation characteristics of as-cast C-HRA-3 Ni–Cr–Co–Mo-based heat-resistant alloy were investigated using Thermo-Calc thermodynamic calculations,scanning electron microscopy observations,and electron probe microanalyzer.Based on high temperature observation system,the effects of cooling rate on the dendritic structure,dendritic segregation,and precipitation in this alloy were explored.The results showed that the precipitates in the as-cast C-HRA-3 alloy primarily consist of blocky Ti(C,N)phases,large-sized Ti(C,N)–M_(6)C–M_(23)C_(6) symbiotic phases and M_(6)C–M_(23)C_(6) carbides,and small-sized dispersed M_(6)C and M_(23)C_(6) carbides surronding these symbiotic phases.The primary constituent elements of these precipitates are Mo,Cr,C,and Ti,which predominantly concentrate in the interdendritic regions of the as-cast alloy.There is a clear power-law relationship between the secondary dendrite arm spacing and the cooling rate.The dendritic segregation ratio of Mo,Cr,and Ti exhibits a piecewise functional relationship with the cooling rate,under equiaxed dendritic solidification condition.These predictive models and theoretical analyses were validated using numerical simulations and experimental results from the 200 kg grade VIM electrode.
基金A research grant from the Multimedia University,Malaysia supports this work。
文摘Traditional rule-based IntrusionDetection Systems(IDS)are commonly employed owing to their simple design and ability to detect known threats.Nevertheless,as dynamic network traffic and a new degree of threats exist in IoT environments,these systems do not perform well and have elevated false positive rates—consequently decreasing detection accuracy.In this study,we try to overcome these restrictions by employing fuzzy logic and machine learning to develop an Enhanced Rule-Based Model(ERBM)to classify the packets better and identify intrusions.The ERBM developed for this approach improves data preprocessing and feature selections by utilizing fuzzy logic,where three membership functions are created to classify all the network traffic features as low,medium,or high to remain situationally aware of the environment.Such fuzzy logic sets produce adaptive detection rules by reducing data uncertainty.Also,for further classification,machine learning classifiers such as Decision Tree(DT),Random Forest(RF),and Neural Networks(NN)learn complex ways of attacks and make the detection process more precise.A thorough performance evaluation using different metrics,including accuracy,precision,recall,F1 Score,detection rate,and false-positive rate,verifies the supremacy of ERBM over classical IDS.Under extensive experiments,the ERBM enables a remarkable detection rate of 99%with considerably fewer false positives than the conventional models.Integrating the ability for uncertain reasoning with fuzzy logic and an adaptable component via machine learning solutions,the ERBM systemprovides a unique,scalable,data-driven approach to IoT intrusion detection.This research presents a major enhancement initiative in the context of rule-based IDS,introducing improvements in accuracy to evolving IoT threats.
基金supported by Science,Technology&Innovation Funding Authority(STDF)under grant(No.47062).
文摘Conversion and capture of carbon pollutants based on carbon dioxide to valuable green oil-field chemicals are target all over the world for controlling the global warming.The present article used new room temperature amphiphilic imidazolium ionic liquids with superior surface activity in the aqueous solutions to convert carbon dioxide gas to superior amphiphilic calcium carbonate nanoparticles.In this respect,tetra-cationic ionic liquids 2-(4-dodecyldimethylamino)phenyl)-1,3-bis(3-dodecyldimethylammnonio)propyl)bromide-1-H-imidazol-3-ium acetate and 2-(4-hexyldimethylamino)phenyl)-1,3-bis(3-hexcyldimethylammnonio)propyl)bromide-1 H-imidazol-3-ium acetate were prepared.Their chemical structures,thermal as well as their carbon dioxide absorption/desorption characteristicswere evaluated.Theywere used as solvent and capping agent to synthesize calcium carbonate nanoparticles with controlled crystalline lattice,sizes,thermal properties and spherical surface morphologies.The prepared calcium carbonate nanoparticles were used as additives for the commercial water based drilling mud to improve their filter lose and rheology.The data confirm that the lower concentrations of 2-(4-dodecyldimethylamino)phenyl)-1,3-bis(3-dodecyldimethylammnonio)propyl)bromide-1-H-imidazol-3-ium acetate achieved lower seawater filter lose and improved viscosities.
文摘Mason Reset(MR),a groundbreaking invention by Clesson E.Mason in 1930 that later became a part of“the universal approach to process control instrumentation”,is revisited in this paper and is shown to consists of three actions:fast(errorcorrection),medium(negative feedback for expanded proportional band)and slow(reset for zero steady-state error).The focus of the paper is on the reset action,generated from a positive feedback loop,and its underlying principles with profound implications to our understanding and practice of automatic control,both basic and advanced.For example,we note that reset control and integral control,contrary to common belief,differ fundamentally in design principle and in practicality.Such difference comes to a head in the event of integrator windup:while reset windup is a problem of actuator saturation,the integrator windup is a runaway situation due to controller instability.In fact,there is no advantage gained in replacing MR with an integrator.In other words,one should not integrate the error directly as in standard PID,since doing so makes the closed-loop system internally unstable.With MR-based control formulated in this paper,there is no such threat of instability and,therefore,no need for any anti-windup mechanisms.Furthermore,the integral control is made scalable in this framework as a tradeoff between the steady-state accuracy and the controller stability.This leads to a novel MR-based control design,scalable in gain and in time to accommodate various process characteristics and design specifications.Simple in construction and transparent in principle,this MR-based control,as a basic framework of design,is readily deployable in scale.
文摘The title of the online version of the original article was revised.The title of the original article has been revised to:Hydrochemical characterization of surface waters in Northern Tehran:Integrating cluster-based techniques with Self-Organizing Maps.
