The ubiquitous adoption of mobile devices as essential platforms for sensitive data transmission has heightened the demand for secure client-server communication.Although various authentication and key agreement proto...The ubiquitous adoption of mobile devices as essential platforms for sensitive data transmission has heightened the demand for secure client-server communication.Although various authentication and key agreement protocols have been developed,current approaches are constrained by homogeneous cryptosystem frameworks,namely public key infrastructure(PKI),identity-based cryptography(IBC),or certificateless cryptography(CLC),each presenting limitations in client-server architectures.Specifically,PKI incurs certificate management overhead,IBC introduces key escrow risks,and CLC encounters cross-system interoperability challenges.To overcome these shortcomings,this study introduces a heterogeneous signcryption-based authentication and key agreement protocol that synergistically integrates IBC for client operations(eliminating PKI’s certificate dependency)with CLC for server implementation(mitigating IBC’s key escrow issue while preserving efficiency).Rigorous security analysis under the mBR(modified Bellare-Rogaway)model confirms the protocol’s resistance to adaptive chosen-ciphertext attacks.Quantitative comparisons demonstrate that the proposed protocol achieves 10.08%–71.34%lower communication overhead than existing schemes across multiple security levels(80-,112-,and 128-bit)compared to existing protocols.展开更多
A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness.However,a large neglected issue is the sensing durability and accuracy without in...A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness.However,a large neglected issue is the sensing durability and accuracy without interference since the expiratory pressure always coupled with external humidity and temperature variations,as well as mechanical motion artifacts.Herein,a robust and biodegradable piezoresistive sensor is reported that consists of heterogeneous MXene/cellulose-gelation sensing layer and Ag-based interdigital electrode,featuring customizable cylindrical interface arrangement and compact hierarchical laminated architecture for collectively regulating the piezoresistive response and mechanical robustness,thereby realizing the long-term breath-induced pressure detection.Notably,molecular dynamics simulations reveal the frequent angle inversion and reorientation of MXene/cellulose in vacuum filtration,driven by shear forces and interfacial interactions,which facilitate the establishment of hydrogen bonds and optimize the architecture design in sensing layer.The resultant sensor delivers unprecedented collection features of superior stability for off-axis deformation(0-120°,~2.8×10^(-3) A)and sensing accuracy without crosstalk(humidity 50%-100%and temperature 30-80).Besides,the sensor-embedded mask together with machine learning models is achieved to train and classify the respiration status for volunteers with different ages(average prediction accuracy~90%).It is envisioned that the customizable architecture design and sensor paradigm will shed light on the advanced stability of sustainable electronics and pave the way for the commercial application in respiratory monitory.展开更多
Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring ...Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring the security of Industrial Control Production Systems(ICPSs)has become a critical challenge.These systems are highly vulnerable to attacks such as denial-of-service(DoS),eclipse,and Sybil attacks,which can significantly disrupt industrial operations.This work proposes an effective protection strategy using an Artificial Intelligence(AI)-enabled Smart Contract(SC)framework combined with the Heterogeneous Barzilai-Borwein Support Vector(HBBSV)method for industrial-based CPS environments.The approach reduces run time and minimizes the probability of attacks.Initially,secured ICPSs are achieved through a comprehensive exchange of views on production plant strategies for condition monitoring using SC and blockchain(BC)integrated within a BC network.The SC executes the HBBSV strategy to verify the security consensus.The Barzilai-Borwein Support Vectorized algorithm computes abnormal attack occurrence probabilities to ensure that components operate within acceptable production line conditions.When a component remains within these conditions,no security breach occurs.Conversely,if a component does not satisfy the condition boundaries,a security lapse is detected,and those components are isolated.The HBBSV method thus strengthens protection against DoS,eclipse,and Sybil attacks.Experimental results demonstrate that the proposed HBBSV approach significantly improves security by enhancing authentication accuracy while reducing run time and authentication time compared to existing techniques.展开更多
To obtain protease-and lipase-producing halotolerant/halophilic strains suitable for shrimp paste(SP)fermentation,the microbial community structure and enzyme-producing microbial species were analyzed and predicted us...To obtain protease-and lipase-producing halotolerant/halophilic strains suitable for shrimp paste(SP)fermentation,the microbial community structure and enzyme-producing microbial species were analyzed and predicted using metagenomics in 3 high-salt samples.Based on the linear salt gradient method,128 strains were screened.Eight halotolerant/halophilic strains highly producing 2 types of enzymes were identified and inoculated into lowsalt SP to assess the heterogeneity of SP.Physicochemical properties of SP indicated that Bacillus subtilis XJ-11,Virgibacillus halodenitrificans XJ-229,Piscibacillus halophilus XY-193,and Bacillus vallismortis HT-73 were more suitable for rapid fermentation of SP.Nutritional analysis showed that SP inoculated with V.halodenitrificans XJ-229 had the highest free amino acid content and SP inoculated with P.halophilus XY-193 had the highest unsaturated fatty acid content.The former had prominent umami,sweetness,and meaty aroma,weak bitterness and fishy flavor,and the closest flavor to the control(CP)based on sensory evaluation and E-nose analysis.A total of 61 volatile compounds were detected in all samples by SPME-GC-MS,of which 32,23,40,24,and 28 were detected in the CP and SP inoculated with B.subtilis XJ-11,V.halodenitrificans XJ-229,P.halophilus XY-193,and B.vallismortis HT-73,respectively,with 12,11,12,9,and 9 key flavor compounds.Among several samples,the highest levels of pyrazines,aldehydes,alcohols,and ketones were found in SP inoculated with B.subtilis XJ-11,V.halodenitrificans XJ-229,P.halophilus XY-193,and B.vallismortis HT-73,respectively.These results suggested that inoculation of different enzyme-producing halotolerant/halophilic strains resulted in differences in SP quality and main flavors.This study provides some references for process control and interpretation of heterogeneous mechanisms in low-salt SP fermented by inoculated strains.展开更多
Heterogeneous nucleation,characterized by its low nucleation barrier and controllable nucleation sites,has been widely employed to manipulate the microstructures and properties of metallic materials.In recent years,th...Heterogeneous nucleation,characterized by its low nucleation barrier and controllable nucleation sites,has been widely employed to manipulate the microstructures and properties of metallic materials.In recent years,the dispersion of inclusions,carbides,and microstructure refinement in steel have emerged as one of the key research directions in the development of high-quality steel.The current research status regarding the regulation of inclusions,carbides,and microstructures in steel through heterogeneous nucleation are reviewed.The key points and challenges in refining the second phase and microstructure in steel using inclusion particles are highlighted,aiming to provide inspiration and references for future scholars.Deoxidized inclusions,when refined and dispersed,exhibit favorable lattice matching with second phases(e.g.,nitrides,sulfides,carbides)in steel.This characteristic serves as the fundamental mechanism for achieving refinement of the second phase.Concurrently,the solid-solution alloying effect from deoxidizing metals contributes to second-phase refinement,an aspect that requires prioritized investigation.In addition to the single heterogeneous nucleation refinement effect,the two-stage heterogeneous nucleation refinement of the second phase and microstructure offers a new approach for follow-up research.Notably,second-phase particles added as heterogeneous nucleation sites via external addition often require surface modification to ensure their stable retention in steel at high temperatures,which remains a major challenge restricting the widespread application of this method.Currently,the explanation of heterogeneous nucleation phenomena primarily relies on empirical calculations of lattice mismatch between the substrate and the nucleating phase,which cannot fully elucidate the quantitative relationship on the interface between the substrate and the nucleation phase.On this basis,quantifying the electronic structure and nucleation barrier at the interface between the substrate and the nucleation phase is a critical direction worthy of increased attention in the future.展开更多
In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In additi...In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In addition,methods for deploying multiple cameras for motion capture of users(e.g.,performers)are widely used in computer graphics.As the need to minimize and optimize the number of cameras grows to reduce costs,various technologies and research approaches focused on Optimal Camera Placement(OCP)are continually being proposed.However,as most existing studies assume homogeneous camera setups,there is a growing demand for studies on heterogeneous camera setups.For instance,technical demands keep emerging in scenarios with minimal camera configurations,especially regarding cost factors,the physical placement of cameras given the spatial structure,and image capture strategies for heterogeneous cameras,such as high-resolution RGB cameras and depth cameras.In this study,we propose a pre-visualization and simulation method for the optimal placement of heterogeneous cameras in XR environments,accounting for both the specifications of heterogeneous cameras(e.g.,field of view)and the physical configuration(e.g.,wall configuration)in real-world spaces.The proposed method performs a visibility analysis of cameras by considering each camera’s field-of-view volume,resolution,and unique characteristics,along with physicalspace constraints.This approach enables the optimal position and rotation of each camera to be recommended,along with the minimum number of cameras required.In the results of our study conducted in heterogeneous camera combinations,the proposed method achieved 81.7%~82.7%coverage of the target visual information using only 2~3 cameras.In contrast,single(or homogeneous)-typed cameras were required to use 11 cameras for 81.6%coverage.Accordingly,we found that camera deployment resources can be reduced with the proposed approaches.展开更多
Heterogeneous polymerization represents a widely employed method in the polyolefin industry.In recent years,various heterogenization strategies for late transition metal catalysts have been developed,enabling effectiv...Heterogeneous polymerization represents a widely employed method in the polyolefin industry.In recent years,various heterogenization strategies for late transition metal catalysts have been developed,enabling effective control of polymer morphology and optimization of catalytic performance.However,while most studies have focused on designing anchoring groups and advancing support approaches,systematic investigations into how the support influences the catalytic behavior of the late transition metal catalysts.In this work,we fabricated supported α-diimine nickel catalysts by functionalizing the ligand with alkyl alcohol chains of varying lengths and supporting them onto MgCl_(2)supports.The ethylene polymerization behavior of these catalysts was then investigated.By precisely adjusting the alkyl alcohol chain length,the distance between the catalytically active metal center and the support surface was modulated.This approach demonstrates that support-induced steric hindrance effect can be effectively regulated by controlling the separation distance between the metal center and the support surface.展开更多
With the increasing complexity of malware attack techniques,traditional detection methods face significant challenges,such as privacy preservation,data heterogeneity,and lacking category information.To address these i...With the increasing complexity of malware attack techniques,traditional detection methods face significant challenges,such as privacy preservation,data heterogeneity,and lacking category information.To address these issues,we propose Federated Dynamic Prototype Learning(FedDPL)for malware classification by integrating Federated Learning with a specifically designed K-means.Under the Federated Learning framework,model training occurs locally without data sharing,effectively protecting user data privacy and preventing the leakage of sensitive information.Furthermore,to tackle the challenges of data heterogeneity and the lack of category information,FedDPL introduces a dynamic prototype learning mechanism,which adaptively adjusts the clustering prototypes in terms of position and number.Thus,the dependency on predefined category numbers in typical K-means and its variants can be significantly reduced,resulting in improved clustering performance.Theoretically,it provides a more accurate detection of malicious behavior.Experimental results confirm that FedDPL excels in handling malware classification tasks,demonstrating superior accuracy,robustness,and privacy protection.展开更多
Urban traffic generates massive and diverse data,yet most systems remain fragmented.Current approaches to congestion management suffer from weak data consistency and poor scalability.This study addresses this gap by p...Urban traffic generates massive and diverse data,yet most systems remain fragmented.Current approaches to congestion management suffer from weak data consistency and poor scalability.This study addresses this gap by proposing the Urban Traffic Congestion Unified Metadata Model(UTC-UMM).The goal is to provide a standardized and extensible framework for describing,extracting,and storing multisource traffic data in smart cities.The model defines a two-tier specification that organizes nine core traffic resource classes.It employs an eXtensible Markup Language(XML)Schema that connects general elements with resource-specific elements.This design ensures both syntactic and semantic interoperability across siloed datasets.Extension principles allow new elements or constraints to be introducedwithout breaking backward compatibility.Adistributed pipeline is implemented usingHadoop Distributed File System(HDFS)and HBase.It integrates computer vision for video and natural language processing for text to automate metadata extraction.Optimized row-key designs enable low-latency queries.Performance is tested with the Yahoo!Cloud Serving Benchmark(YCSB),which shows linear scalability and high throughput.The results demonstrate that UTC-UMM can unify heterogeneous traffic data while supporting real-time analytics.The discussion highlights its potential to improve data reuse,portability,and scalability in urban congestion studies.Future research will explore integration with association rulemining and advanced knowledge representation to capture richer spatiotemporal traffic patterns.展开更多
Computational phantoms play an essential role in radiation dosimetry and health physics.Although mesh-type phantoms offer a high resolution and adjustability,their use in dose calculations is limited by their slow com...Computational phantoms play an essential role in radiation dosimetry and health physics.Although mesh-type phantoms offer a high resolution and adjustability,their use in dose calculations is limited by their slow computational speed.Progress in heterogeneous computing has allowed for substantial acceleration in the computation of mesh-type phantoms by utilizing hardware accelerators.In this study,a GPU-accelerated Monte Carlo method was developed to expedite the dose calculation for mesh-type computational phantoms.This involved designing and implementing the entire procedural flow of a GPUaccelerated Monte Carlo program.We employed acceleration structures to process the mesh-type phantom,optimized the traversal methodology,and achieved a flattened structure to overcome the limitations of GPU stack depths.Particle transport methods were realized within the mesh-type phantom,encompassing particle location and intersection techniques.In response to typical external irradiation scenarios,we utilized Geant4 along with the GPU program and its CPU serial code for dose calculations,assessing both computational accuracy and efficiency.In comparison with the benchmark simulated using Geant4 on the CPU using one thread,the relative differences in the organ dose calculated by the GPU program predominantly lay within a margin of 5%,whereas the computational time was reduced by a factor ranging from 120 to 2700.To the best of our knowledge,this study achieved a GPU-accelerated dose calculation method for mesh-type phantoms for the first time,reducing the computational time from hours to seconds per simulation of ten million particles and offering a swift and precise Monte Carlo method for dose calculation in mesh-type computational phantoms.展开更多
The refinement of the as-cast grain structure in austenitic heat-resistant stainless steel depends on the formation of active solid nuclei during solidification.Titanium(Ti)additions successfully induced the formation...The refinement of the as-cast grain structure in austenitic heat-resistant stainless steel depends on the formation of active solid nuclei during solidification.Titanium(Ti)additions successfully induced the formation of Ti-containing inclusions,enhancing heterogeneous nucleation and promoting equiaxed dendritic growth in 347H stainless steel.Thermal simulation experiments indicated that the equiaxed crystal ratios increased notably with Ti content;samples with 0.06,0.12,and 0.36 wt.%Ti exhibited equiaxed ratios of 18%,24%,and 41%,respectively.Three primary inclusion types—TiN,Al_(2)O_(3)-TiN,and TiO_(x)-TiN—were identified at the cores of equiaxed dendrites,with nucleation core sizes predominantly ranging from 0.5 to 8μm.Among the tested samples,the 0.36 wt.%Ti addition produced the highest nucleation core density.Increasing Ti content significantly elevated dendrite tip undercooling from 2.6 K(0.06 wt.%Ti)to 10.8 K(0.36 wt.%Ti),accelerating solidification front instability and thus enhancing heterogeneous nucleation.Additionally,higher Ti content increased the divergence angle between adjacent columnar dendrites,further promoting the columnar-to-equiaxed transition(CET).展开更多
With the rapid advancement of electromagnetic launch technology,enhancing the structural stability and thermal resistance of armatures has become essential for improving the overall efficiency and reliability of railg...With the rapid advancement of electromagnetic launch technology,enhancing the structural stability and thermal resistance of armatures has become essential for improving the overall efficiency and reliability of railgun systems.Traditional aluminum alloy armatures often suffer from severe ablation,deformation,and uneven current distribution under high pulsed currents,which limit their performance and service life.To address these challenges,this study employs the Johnson–Cook constitutive model and the finite element method to develop armature models of aluminum matrix composites with varying heterogeneous graphene volume fractions.The temperature,stress,and strain of the armatures during operation were analyzed to investigate the effects of different graphene volume fractions on the deformation and damage behavior of aluminum matrix composite armatures under the multi-field coupling of electromagnetic,thermal,and structural interactions.The results indicate that,compared to the 6061 aluminum alloy matrix,the graphene-reinforced aluminum matrix composite armature significantly suppresses ablation damage at the tail and throat edges.The incorporation of graphene notably reduces the temperature rise during the armature emission process,increases the muzzle velocity under identical current excitation,and mitigates directional deformation of the armature.The 1 wt.% graphene-reinforced aluminum matrix composite armature demonstrates better agreement with experimental results at a strain rate of 2000 s^(-1),while simultaneously improving stress-strain response,reducing temperature rise,and improving velocity performance.展开更多
Fault-tolerant systems are crucial for ensuring the reliability and availability of missioncritical applications in modern computing environments.The dynamic heterogeneous redundancy(DHR)architecture is a key componen...Fault-tolerant systems are crucial for ensuring the reliability and availability of missioncritical applications in modern computing environments.The dynamic heterogeneous redundancy(DHR)architecture is a key component in constructing fault-tolerant systems,particularly in areas such as national security,power networks,and banking private networks.DHR is transforming the cyberspace security industry chain by accommodating a broader range of applications and increasingly capturing the market.However,the development of applications for DHR architecture encounters challenges due to the complexities of handling heterogeneity,managing dynamism,and maintaining usability.To address these issues,we introduce MimicStudio,a comprehensive development framework with a standardized workflow.To our knowledge,MimicStudio is the first effective solution for DHR software development.We present a detailed implementation of MimicStudio with a heterogeneous microcontroller unit project,encompassing three CPUs with different instruction set architectures.The paper evaluates MimicStudio’s support for essential features,including zero-copy synchronization,parallelized build,multi-core collaborative debugging,and dynamic adjustment of the software system’s structure.Our results show that MimicStudio provides a flexible and efficient solution for supporting the dynamic,heterogeneous,and redundant features of fault-tolerant systems.展开更多
Breast cancer is a malignant tumor originating from breast epithelial tissue.In essence,breast epithelial cells undergo gene mutation under the influence of carcinogenic factors,leading to abnormal cell proliferation ...Breast cancer is a malignant tumor originating from breast epithelial tissue.In essence,breast epithelial cells undergo gene mutation under the influence of carcinogenic factors,leading to abnormal cell proliferation and loss of organism regulation,ultimately leading to the formation of tumors with invasive and metastatic capabilities.Carcinogenic factors of breast cancer involve multiple cellular and molecular mechanisms.Among them,disseminated tumor cells(DTCs)are considered important for treating breast cancer.However,traditional bulk sequencing techniques have limitations,such as the inability to distinguish individual cell differences and dilution of information from key cell subpopulations(such as cancer stem cells and rare immune cells).Single-cell sequencing(scRNA-seq)overcomes the heterogeneity of tumors that traditional sequencing cannot capture by analysing the molecular characteristics of single cells,providing a highresolution perspective for precise typing of breast cancer,exploration of the mechanism of the microenvironment,and personalized treatment.Through this technology,researchers can identify specific gene expression profiles of different cell subpopulations,thus providing a new basis for the molecular typing and personalized treatment of breast cancer.This article explains how single-cell sequencing is used to describe the origin of disseminated tumor cells(DTCs),analyse tumor heterogeneity,metastasis,etc.,and review the current literature on the use of scRNA-seq in breast cancer treatment.In the future,cell separation and processing steps in single-cell sequencing will be further improved to ensure the accuracy of the results and broader application in clinical diagnosis and treatment.展开更多
Vitrimers belong to a class of polymeric materials capable of bond exchange reactions,showing great promise for environmental protection and sustainable development.However,studies on the coupling mechanism between th...Vitrimers belong to a class of polymeric materials capable of bond exchange reactions,showing great promise for environmental protection and sustainable development.However,studies on the coupling mechanism between the bond exchange kinetics and segmental dynamics near the glass transition temperature(T_(g))remain scarce.Herein,we employed molecular dynamics simulations to investigate the dynamic heterogeneity of the segment motion and bond exchange in vitrimers.The simulation results revealed that the bond exchange energy barrier exerts a much stronger influence on the bond exchange kinetics than on the segmental dynamics.At lower temperatures,slower segmental relaxation further constraind the bond exchange rate.Additionally,increasing the bond exchange energy barrier markedly enhanced the dynamic heterogeneity of segment motion.A close correlation was observed between heterogeneity and bond exchange.This study elucidated the coupling mechanism between bond exchange and segmental dynamics at the molecular scale,thereby providing a theoretical basis for designing vitrimer materials with tunable dynamic properties.展开更多
Effective groundwater management is crucial for economic sustainable development,particularly as climate change and population growth increase the uncertainty of aquifer dynamics.Due to limited geological data,Punjab&...Effective groundwater management is crucial for economic sustainable development,particularly as climate change and population growth increase the uncertainty of aquifer dynamics.Due to limited geological data,Punjab's complex hydrogeological conditions and Quaternary alluvial deposits present significant challenges for groundwater management.This study employs cost-effective numerical techniques as alternatives to traditional methods to safeguard groundwater quality,quantity,and accessibility.It introduces an edit-embedded transition frequency model that integrates regional datasets and utilizes algorithms such as GAMEAS,MCMOD,and TSIM to evaluate aquifer heterogeneity and simulate spatial variations using one-dimensional and three-dimensional Markov chains.Findings show that sand exhibits the highest self-transition(33.112 m),indicating strong stability,followed by silt,clay,and gravel,suggesting overall hydrofacies stability both horizontally and vertically.The model's predictions are largely consistent with actual material distribution,with a slight under-prediction of clay(-0.750%)and an over-prediction of sand(2.985%),which accounts for 58.77%of the aquifer material.It also highlights significant heterogeneity in the northern mountainous regions and minor variations in the south.The study emphasizes Punjab's severe water crisis,with groundwater reserves of 3502.3 BCM,declining water levels(0.38–33.62 m),and low hydraulic conductivity,urging government action on rainwater harvesting and sustainable groundwater management policies.展开更多
Colorectal cancer(CRC)is one of the most molecularly heterogeneous malignancies,with complexity that extends far beyond traditional histopathological classifications.The consensus molecular subtypes(CMS)established in...Colorectal cancer(CRC)is one of the most molecularly heterogeneous malignancies,with complexity that extends far beyond traditional histopathological classifications.The consensus molecular subtypes(CMS)established in 2015 brought a marked advancement in the taxonomy of CRC,consolidating six classification systems into four novel subtypes,which focus on vital gene expression patterns and clinical and prognostic outcomes.However,nearly a decade of clinical experience with CMS classification has revealed fundamental limitations that underscore the inadequacy of any single classification system for capturing the full spectrum of CRC biology.The inherent challenges of the current paradigm are multifaceted.In the CMS classification,mixed phenotypes that remain unclassifiable constitute 13%of CRC cases.This reflects the remarkable heterogeneity that CRC shows.The tumor budding regions reflect the molecular shift due to CMS 2 to CMS 4 switching,causing further heterogeneity.Moreover,the reliance on bulk RNA sequencing fails to capture the spatial organization of molecular signatures within tumors and the critical contributions of the tumor microenvironment.Recent technological advances in spatial transcriptomics,singlecell RNA sequencing,and multi-omic integration have revealed the limitations of transcriptome-only classifications.The emergence of CRC intrinsic subtypes that attempt to remove microenvironmental contributions,pathway-derived subtypes,and stem cell-based classifications demonstrates the field’s recognition that multiple complementary classification systems are necessary.These newer molecular subtypes are not discrete categories but biological continua,thus highlighting that the vast molecular landscape is a tapestry of interlinked features,not rigid subtypes.Multiple technical hurdles cause difficulty in implementing the clinical translation of these newer molecular subtypes,including gene signature complexity,platform-dependent variations,and the difficulty of getting and preserving fresh frozen tissue.CMS 4 shows a poor prognostic outcome among the CMS subtypes,while CMS 1 is associated with poor survival in metastatic cases.However,the predictive value for definitive therapy remains subdued.Looking forward,the integration of artificial intelligence,liquid biopsy approaches,and real-time molecular monitoring promises to enable dynamic,multi-dimensional tumor characterization.The temporal and spatial complexity can only be captured by complementary molecular taxonomies rather than a single,unified system of CRC classification.Such an approach recognizes that different clinical questions–prognosis,treatment selection,resistance prediction–may require different molecular lenses,each optimized for specific clinical applications.This editorial advocates for a revolutionary change from pursuing a single“best”classification system toward a diverse approach that welcomes the molecular mosaic of CRC.Only through such comprehensive molecular characterization can we hope to achieve the promise of precision oncology for the diverse spectrum of patients with CRC.展开更多
The dense heterogeneous network provides standardized connectivity and access guarantees for 5G communication services.However,the complex network environment and high level of dynamism pose challenges to network sele...The dense heterogeneous network provides standardized connectivity and access guarantees for 5G communication services.However,the complex network environment and high level of dynamism pose challenges to network selection decisions.Existing vertical handover algorithms often overlook the dynamic nature of user mobility and network condition,resulting in problems such as handover failure and frequent handover,ultimately impacting the quality of the user communication service.To address these problems,we propose an intelligent switching method,iMALSTM-DQN,which integrates an improved Multi-level Associative Long Short-Term Memory model(iMALSTM)with Deep Reinforcement Learning(DRL).The algorithm leverages iMALSTM to predict the global network state in the next moment based on the global user movement trajectory and historical network status information within a region,thereby enhancing the prediction accuracy of network states.Subsequently,based on the predicted network state,we employ the Deep Q Network(DON)model to make handover decisions,adaptively determining the optimal switching and network selection strategy through interaction with the environment.Experimental results demonstrate that the proposed algorithm enhances decision timeliness,significantly reduces the number of switch failures,and alleviates the problem of frequent handovers resulting from network dynamics.展开更多
Under equivalent stiffness conditions,material substitution based on a thin-walled design is crucial for the lightweight of components.Developing high-performance steels with both high-yield strength and excellent duc...Under equivalent stiffness conditions,material substitution based on a thin-walled design is crucial for the lightweight of components.Developing high-performance steels with both high-yield strength and excellent ductility has become a key focus in fields like aerospace and lowaltitude flight.The novel low-density steel presented here exhibits a yield strength of 1000 MPa,which is 2-3 times higher than conventional low-alloy high-strength steels,while maintaining an elongation of about 18.7%.By combining ex-situ experimental characterization with a phase mechanical response model based on the iso-work theory and the von Mises equivalent method,the role of heterogeneous deformation-induced strengthening was revealed.The calculated values align closely with experimental results.This exceptional performance is attributed to a multiphase heterogeneous microstructure,where fresh martensite,bainite/tempered martensite,and deformation-induced martensite act as hard regions.These regions release micro-stresses through inhomogeneous cooperative deformation with soft ferrite,enabling multiple plastic deformation mechanisms and stress concentration relief.This research offers new insights into optimizing microstructures through mechanical metallurgy,which is crucial for producing high-performance,lightweight components.展开更多
Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogen...Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogeneity remains challenging.To address this,this study first captures the morphology of large-scale(1000 mm × 1000 mm) slate and granite joints via 3D laser scanning.Analysis of these surfaces and corresponding push/pull tests on carved specimens revealed a potential correlation between the heterogeneity of roughness and shear strength.A comparative evaluation of five statistical metrics identified information entropy(Hs) as the most robust indicator for quantifying rock joint heterogeneity.Further analysis using Hsreveals that the heterogeneity is anisotropic and,critically,that shear strength heterogeneity is governed not only by roughness heterogeneity but is also significantly influenced by the mean roughness value,normal stress,and intact rock tensile strength.Consequently,a simple comparison of roughness Hsvalues is insufficient for reliably comparing shear strength heterogeneity.To overcome this limitation,a theoretical framework is developed to explicitly map fundamental roughness statistics(mean and heterogeneity) to shear strength heterogeneity.This framework culminates in a practical workflow that allows for the rapid,field-based assessment of shear strength heterogeneity using readily obtainable rock joint roughness data.展开更多
基金supported by the Key Project of Science and Technology Research by Chongqing Education Commission under Grant KJZD-K202400610the Chongqing Natural Science Foundation General Project Grant CSTB2025NSCQ-GPX1263.
文摘The ubiquitous adoption of mobile devices as essential platforms for sensitive data transmission has heightened the demand for secure client-server communication.Although various authentication and key agreement protocols have been developed,current approaches are constrained by homogeneous cryptosystem frameworks,namely public key infrastructure(PKI),identity-based cryptography(IBC),or certificateless cryptography(CLC),each presenting limitations in client-server architectures.Specifically,PKI incurs certificate management overhead,IBC introduces key escrow risks,and CLC encounters cross-system interoperability challenges.To overcome these shortcomings,this study introduces a heterogeneous signcryption-based authentication and key agreement protocol that synergistically integrates IBC for client operations(eliminating PKI’s certificate dependency)with CLC for server implementation(mitigating IBC’s key escrow issue while preserving efficiency).Rigorous security analysis under the mBR(modified Bellare-Rogaway)model confirms the protocol’s resistance to adaptive chosen-ciphertext attacks.Quantitative comparisons demonstrate that the proposed protocol achieves 10.08%–71.34%lower communication overhead than existing schemes across multiple security levels(80-,112-,and 128-bit)compared to existing protocols.
基金supported by the National Natural Science Foundation of China(22074072,22274083,52376199)the Shandong Provincial Natural Science Foundation(ZR2023LZY005)+1 种基金the Exploration Project of the State Key Laboratory of BioFibers and EcoTextiles of Qingdao University(TSKT202101)the Fundamental Research Funds for the Central Universities(2022BLRD13,2023BLRD01).
文摘A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness.However,a large neglected issue is the sensing durability and accuracy without interference since the expiratory pressure always coupled with external humidity and temperature variations,as well as mechanical motion artifacts.Herein,a robust and biodegradable piezoresistive sensor is reported that consists of heterogeneous MXene/cellulose-gelation sensing layer and Ag-based interdigital electrode,featuring customizable cylindrical interface arrangement and compact hierarchical laminated architecture for collectively regulating the piezoresistive response and mechanical robustness,thereby realizing the long-term breath-induced pressure detection.Notably,molecular dynamics simulations reveal the frequent angle inversion and reorientation of MXene/cellulose in vacuum filtration,driven by shear forces and interfacial interactions,which facilitate the establishment of hydrogen bonds and optimize the architecture design in sensing layer.The resultant sensor delivers unprecedented collection features of superior stability for off-axis deformation(0-120°,~2.8×10^(-3) A)and sensing accuracy without crosstalk(humidity 50%-100%and temperature 30-80).Besides,the sensor-embedded mask together with machine learning models is achieved to train and classify the respiration status for volunteers with different ages(average prediction accuracy~90%).It is envisioned that the customizable architecture design and sensor paradigm will shed light on the advanced stability of sustainable electronics and pave the way for the commercial application in respiratory monitory.
文摘Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring the security of Industrial Control Production Systems(ICPSs)has become a critical challenge.These systems are highly vulnerable to attacks such as denial-of-service(DoS),eclipse,and Sybil attacks,which can significantly disrupt industrial operations.This work proposes an effective protection strategy using an Artificial Intelligence(AI)-enabled Smart Contract(SC)framework combined with the Heterogeneous Barzilai-Borwein Support Vector(HBBSV)method for industrial-based CPS environments.The approach reduces run time and minimizes the probability of attacks.Initially,secured ICPSs are achieved through a comprehensive exchange of views on production plant strategies for condition monitoring using SC and blockchain(BC)integrated within a BC network.The SC executes the HBBSV strategy to verify the security consensus.The Barzilai-Borwein Support Vectorized algorithm computes abnormal attack occurrence probabilities to ensure that components operate within acceptable production line conditions.When a component remains within these conditions,no security breach occurs.Conversely,if a component does not satisfy the condition boundaries,a security lapse is detected,and those components are isolated.The HBBSV method thus strengthens protection against DoS,eclipse,and Sybil attacks.Experimental results demonstrate that the proposed HBBSV approach significantly improves security by enhancing authentication accuracy while reducing run time and authentication time compared to existing techniques.
基金supported by the National Natural Science Foundation of China(22138004)Shaoxing Science and Technology Plan Project(2022B43001,2023B43001).
文摘To obtain protease-and lipase-producing halotolerant/halophilic strains suitable for shrimp paste(SP)fermentation,the microbial community structure and enzyme-producing microbial species were analyzed and predicted using metagenomics in 3 high-salt samples.Based on the linear salt gradient method,128 strains were screened.Eight halotolerant/halophilic strains highly producing 2 types of enzymes were identified and inoculated into lowsalt SP to assess the heterogeneity of SP.Physicochemical properties of SP indicated that Bacillus subtilis XJ-11,Virgibacillus halodenitrificans XJ-229,Piscibacillus halophilus XY-193,and Bacillus vallismortis HT-73 were more suitable for rapid fermentation of SP.Nutritional analysis showed that SP inoculated with V.halodenitrificans XJ-229 had the highest free amino acid content and SP inoculated with P.halophilus XY-193 had the highest unsaturated fatty acid content.The former had prominent umami,sweetness,and meaty aroma,weak bitterness and fishy flavor,and the closest flavor to the control(CP)based on sensory evaluation and E-nose analysis.A total of 61 volatile compounds were detected in all samples by SPME-GC-MS,of which 32,23,40,24,and 28 were detected in the CP and SP inoculated with B.subtilis XJ-11,V.halodenitrificans XJ-229,P.halophilus XY-193,and B.vallismortis HT-73,respectively,with 12,11,12,9,and 9 key flavor compounds.Among several samples,the highest levels of pyrazines,aldehydes,alcohols,and ketones were found in SP inoculated with B.subtilis XJ-11,V.halodenitrificans XJ-229,P.halophilus XY-193,and B.vallismortis HT-73,respectively.These results suggested that inoculation of different enzyme-producing halotolerant/halophilic strains resulted in differences in SP quality and main flavors.This study provides some references for process control and interpretation of heterogeneous mechanisms in low-salt SP fermented by inoculated strains.
基金supported by the National Natural Science Foundation of China(No.52304358)Young Elite Scientists Sponsorship Program by CAST(No.YESS20230462).
文摘Heterogeneous nucleation,characterized by its low nucleation barrier and controllable nucleation sites,has been widely employed to manipulate the microstructures and properties of metallic materials.In recent years,the dispersion of inclusions,carbides,and microstructure refinement in steel have emerged as one of the key research directions in the development of high-quality steel.The current research status regarding the regulation of inclusions,carbides,and microstructures in steel through heterogeneous nucleation are reviewed.The key points and challenges in refining the second phase and microstructure in steel using inclusion particles are highlighted,aiming to provide inspiration and references for future scholars.Deoxidized inclusions,when refined and dispersed,exhibit favorable lattice matching with second phases(e.g.,nitrides,sulfides,carbides)in steel.This characteristic serves as the fundamental mechanism for achieving refinement of the second phase.Concurrently,the solid-solution alloying effect from deoxidizing metals contributes to second-phase refinement,an aspect that requires prioritized investigation.In addition to the single heterogeneous nucleation refinement effect,the two-stage heterogeneous nucleation refinement of the second phase and microstructure offers a new approach for follow-up research.Notably,second-phase particles added as heterogeneous nucleation sites via external addition often require surface modification to ensure their stable retention in steel at high temperatures,which remains a major challenge restricting the widespread application of this method.Currently,the explanation of heterogeneous nucleation phenomena primarily relies on empirical calculations of lattice mismatch between the substrate and the nucleating phase,which cannot fully elucidate the quantitative relationship on the interface between the substrate and the nucleation phase.On this basis,quantifying the electronic structure and nucleation barrier at the interface between the substrate and the nucleation phase is a critical direction worthy of increased attention in the future.
基金supported by the 2024 Research Fund of University of Ulsan.
文摘In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In addition,methods for deploying multiple cameras for motion capture of users(e.g.,performers)are widely used in computer graphics.As the need to minimize and optimize the number of cameras grows to reduce costs,various technologies and research approaches focused on Optimal Camera Placement(OCP)are continually being proposed.However,as most existing studies assume homogeneous camera setups,there is a growing demand for studies on heterogeneous camera setups.For instance,technical demands keep emerging in scenarios with minimal camera configurations,especially regarding cost factors,the physical placement of cameras given the spatial structure,and image capture strategies for heterogeneous cameras,such as high-resolution RGB cameras and depth cameras.In this study,we propose a pre-visualization and simulation method for the optimal placement of heterogeneous cameras in XR environments,accounting for both the specifications of heterogeneous cameras(e.g.,field of view)and the physical configuration(e.g.,wall configuration)in real-world spaces.The proposed method performs a visibility analysis of cameras by considering each camera’s field-of-view volume,resolution,and unique characteristics,along with physicalspace constraints.This approach enables the optimal position and rotation of each camera to be recommended,along with the minimum number of cameras required.In the results of our study conducted in heterogeneous camera combinations,the proposed method achieved 81.7%~82.7%coverage of the target visual information using only 2~3 cameras.In contrast,single(or homogeneous)-typed cameras were required to use 11 cameras for 81.6%coverage.Accordingly,we found that camera deployment resources can be reduced with the proposed approaches.
基金financially supported by the National Natural Science Foundation of China(No.52473338)the National Natural Science Foundation of China(Nos.52173004 and 51873055)+3 种基金Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA0540000)Advanced Materials-National Science and Technology Major Project(No.2025ZD0614000)Hebei Natural Science Foundation(No.E2022202015)Anhui Province Science and Technology Innovation Tackling Key Project(No.202423i08050025)。
文摘Heterogeneous polymerization represents a widely employed method in the polyolefin industry.In recent years,various heterogenization strategies for late transition metal catalysts have been developed,enabling effective control of polymer morphology and optimization of catalytic performance.However,while most studies have focused on designing anchoring groups and advancing support approaches,systematic investigations into how the support influences the catalytic behavior of the late transition metal catalysts.In this work,we fabricated supported α-diimine nickel catalysts by functionalizing the ligand with alkyl alcohol chains of varying lengths and supporting them onto MgCl_(2)supports.The ethylene polymerization behavior of these catalysts was then investigated.By precisely adjusting the alkyl alcohol chain length,the distance between the catalytically active metal center and the support surface was modulated.This approach demonstrates that support-induced steric hindrance effect can be effectively regulated by controlling the separation distance between the metal center and the support surface.
基金supported by the National Natural Science Foundation of China under Grant No.62162009the Key Technologies R&D Program of He’nan Province under Grant No.242102211065+2 种基金the Postgraduate Education Reform and Quality Improvement Project of Henan Province under Grant Nos.YJS2025GZZ36,YJS2024AL112,and YJS2024JD38the Innovation Scientists and Technicians Troop Construction Projects of Henan Province under Grant No.CXTD2017099the Scientific Research Innovation Team of Xuchang University under Grant No.2022CXTD003.
文摘With the increasing complexity of malware attack techniques,traditional detection methods face significant challenges,such as privacy preservation,data heterogeneity,and lacking category information.To address these issues,we propose Federated Dynamic Prototype Learning(FedDPL)for malware classification by integrating Federated Learning with a specifically designed K-means.Under the Federated Learning framework,model training occurs locally without data sharing,effectively protecting user data privacy and preventing the leakage of sensitive information.Furthermore,to tackle the challenges of data heterogeneity and the lack of category information,FedDPL introduces a dynamic prototype learning mechanism,which adaptively adjusts the clustering prototypes in terms of position and number.Thus,the dependency on predefined category numbers in typical K-means and its variants can be significantly reduced,resulting in improved clustering performance.Theoretically,it provides a more accurate detection of malicious behavior.Experimental results confirm that FedDPL excels in handling malware classification tasks,demonstrating superior accuracy,robustness,and privacy protection.
基金supported by the National Natural Science Foundation of China(Grant No.62172033).
文摘Urban traffic generates massive and diverse data,yet most systems remain fragmented.Current approaches to congestion management suffer from weak data consistency and poor scalability.This study addresses this gap by proposing the Urban Traffic Congestion Unified Metadata Model(UTC-UMM).The goal is to provide a standardized and extensible framework for describing,extracting,and storing multisource traffic data in smart cities.The model defines a two-tier specification that organizes nine core traffic resource classes.It employs an eXtensible Markup Language(XML)Schema that connects general elements with resource-specific elements.This design ensures both syntactic and semantic interoperability across siloed datasets.Extension principles allow new elements or constraints to be introducedwithout breaking backward compatibility.Adistributed pipeline is implemented usingHadoop Distributed File System(HDFS)and HBase.It integrates computer vision for video and natural language processing for text to automate metadata extraction.Optimized row-key designs enable low-latency queries.Performance is tested with the Yahoo!Cloud Serving Benchmark(YCSB),which shows linear scalability and high throughput.The results demonstrate that UTC-UMM can unify heterogeneous traffic data while supporting real-time analytics.The discussion highlights its potential to improve data reuse,portability,and scalability in urban congestion studies.Future research will explore integration with association rulemining and advanced knowledge representation to capture richer spatiotemporal traffic patterns.
基金supported by the National Natural Science Foundation of China(Nos.U2167209 and 12375312)Open-end Fund Projects of China Institute for Radiation Protection Scientific Research Platform(CIRP-HYYFZH-2023ZD001).
文摘Computational phantoms play an essential role in radiation dosimetry and health physics.Although mesh-type phantoms offer a high resolution and adjustability,their use in dose calculations is limited by their slow computational speed.Progress in heterogeneous computing has allowed for substantial acceleration in the computation of mesh-type phantoms by utilizing hardware accelerators.In this study,a GPU-accelerated Monte Carlo method was developed to expedite the dose calculation for mesh-type computational phantoms.This involved designing and implementing the entire procedural flow of a GPUaccelerated Monte Carlo program.We employed acceleration structures to process the mesh-type phantom,optimized the traversal methodology,and achieved a flattened structure to overcome the limitations of GPU stack depths.Particle transport methods were realized within the mesh-type phantom,encompassing particle location and intersection techniques.In response to typical external irradiation scenarios,we utilized Geant4 along with the GPU program and its CPU serial code for dose calculations,assessing both computational accuracy and efficiency.In comparison with the benchmark simulated using Geant4 on the CPU using one thread,the relative differences in the organ dose calculated by the GPU program predominantly lay within a margin of 5%,whereas the computational time was reduced by a factor ranging from 120 to 2700.To the best of our knowledge,this study achieved a GPU-accelerated dose calculation method for mesh-type phantoms for the first time,reducing the computational time from hours to seconds per simulation of ten million particles and offering a swift and precise Monte Carlo method for dose calculation in mesh-type computational phantoms.
基金supported by the National Key Research and Development Program of China(Grant No.2021YFB3700602)the Jiaxing Key Research and Development Program(Grant No.2022BZ10010).
文摘The refinement of the as-cast grain structure in austenitic heat-resistant stainless steel depends on the formation of active solid nuclei during solidification.Titanium(Ti)additions successfully induced the formation of Ti-containing inclusions,enhancing heterogeneous nucleation and promoting equiaxed dendritic growth in 347H stainless steel.Thermal simulation experiments indicated that the equiaxed crystal ratios increased notably with Ti content;samples with 0.06,0.12,and 0.36 wt.%Ti exhibited equiaxed ratios of 18%,24%,and 41%,respectively.Three primary inclusion types—TiN,Al_(2)O_(3)-TiN,and TiO_(x)-TiN—were identified at the cores of equiaxed dendrites,with nucleation core sizes predominantly ranging from 0.5 to 8μm.Among the tested samples,the 0.36 wt.%Ti addition produced the highest nucleation core density.Increasing Ti content significantly elevated dendrite tip undercooling from 2.6 K(0.06 wt.%Ti)to 10.8 K(0.36 wt.%Ti),accelerating solidification front instability and thus enhancing heterogeneous nucleation.Additionally,higher Ti content increased the divergence angle between adjacent columnar dendrites,further promoting the columnar-to-equiaxed transition(CET).
基金funded Basic Research Projects of Higher Education Institutions in Liaoning Province(JYTZD20230004)Future Industry Frontier Technology Project in Liaoning Province in 2025(2025JH2/101330141)Key Research and Development Program of Liaoning Province in 2025.
文摘With the rapid advancement of electromagnetic launch technology,enhancing the structural stability and thermal resistance of armatures has become essential for improving the overall efficiency and reliability of railgun systems.Traditional aluminum alloy armatures often suffer from severe ablation,deformation,and uneven current distribution under high pulsed currents,which limit their performance and service life.To address these challenges,this study employs the Johnson–Cook constitutive model and the finite element method to develop armature models of aluminum matrix composites with varying heterogeneous graphene volume fractions.The temperature,stress,and strain of the armatures during operation were analyzed to investigate the effects of different graphene volume fractions on the deformation and damage behavior of aluminum matrix composite armatures under the multi-field coupling of electromagnetic,thermal,and structural interactions.The results indicate that,compared to the 6061 aluminum alloy matrix,the graphene-reinforced aluminum matrix composite armature significantly suppresses ablation damage at the tail and throat edges.The incorporation of graphene notably reduces the temperature rise during the armature emission process,increases the muzzle velocity under identical current excitation,and mitigates directional deformation of the armature.The 1 wt.% graphene-reinforced aluminum matrix composite armature demonstrates better agreement with experimental results at a strain rate of 2000 s^(-1),while simultaneously improving stress-strain response,reducing temperature rise,and improving velocity performance.
基金supported by National Key Research and Development Program of China(No.2023YFB 4404200).
文摘Fault-tolerant systems are crucial for ensuring the reliability and availability of missioncritical applications in modern computing environments.The dynamic heterogeneous redundancy(DHR)architecture is a key component in constructing fault-tolerant systems,particularly in areas such as national security,power networks,and banking private networks.DHR is transforming the cyberspace security industry chain by accommodating a broader range of applications and increasingly capturing the market.However,the development of applications for DHR architecture encounters challenges due to the complexities of handling heterogeneity,managing dynamism,and maintaining usability.To address these issues,we introduce MimicStudio,a comprehensive development framework with a standardized workflow.To our knowledge,MimicStudio is the first effective solution for DHR software development.We present a detailed implementation of MimicStudio with a heterogeneous microcontroller unit project,encompassing three CPUs with different instruction set architectures.The paper evaluates MimicStudio’s support for essential features,including zero-copy synchronization,parallelized build,multi-core collaborative debugging,and dynamic adjustment of the software system’s structure.Our results show that MimicStudio provides a flexible and efficient solution for supporting the dynamic,heterogeneous,and redundant features of fault-tolerant systems.
文摘Breast cancer is a malignant tumor originating from breast epithelial tissue.In essence,breast epithelial cells undergo gene mutation under the influence of carcinogenic factors,leading to abnormal cell proliferation and loss of organism regulation,ultimately leading to the formation of tumors with invasive and metastatic capabilities.Carcinogenic factors of breast cancer involve multiple cellular and molecular mechanisms.Among them,disseminated tumor cells(DTCs)are considered important for treating breast cancer.However,traditional bulk sequencing techniques have limitations,such as the inability to distinguish individual cell differences and dilution of information from key cell subpopulations(such as cancer stem cells and rare immune cells).Single-cell sequencing(scRNA-seq)overcomes the heterogeneity of tumors that traditional sequencing cannot capture by analysing the molecular characteristics of single cells,providing a highresolution perspective for precise typing of breast cancer,exploration of the mechanism of the microenvironment,and personalized treatment.Through this technology,researchers can identify specific gene expression profiles of different cell subpopulations,thus providing a new basis for the molecular typing and personalized treatment of breast cancer.This article explains how single-cell sequencing is used to describe the origin of disseminated tumor cells(DTCs),analyse tumor heterogeneity,metastasis,etc.,and review the current literature on the use of scRNA-seq in breast cancer treatment.In the future,cell separation and processing steps in single-cell sequencing will be further improved to ensure the accuracy of the results and broader application in clinical diagnosis and treatment.
基金financially supported by the National Natural Science Foundation of China(Nos.52173020 and 52573023)。
文摘Vitrimers belong to a class of polymeric materials capable of bond exchange reactions,showing great promise for environmental protection and sustainable development.However,studies on the coupling mechanism between the bond exchange kinetics and segmental dynamics near the glass transition temperature(T_(g))remain scarce.Herein,we employed molecular dynamics simulations to investigate the dynamic heterogeneity of the segment motion and bond exchange in vitrimers.The simulation results revealed that the bond exchange energy barrier exerts a much stronger influence on the bond exchange kinetics than on the segmental dynamics.At lower temperatures,slower segmental relaxation further constraind the bond exchange rate.Additionally,increasing the bond exchange energy barrier markedly enhanced the dynamic heterogeneity of segment motion.A close correlation was observed between heterogeneity and bond exchange.This study elucidated the coupling mechanism between bond exchange and segmental dynamics at the molecular scale,thereby providing a theoretical basis for designing vitrimer materials with tunable dynamic properties.
基金supported by the K.C.Wong Education Foundation(GJTD-2020-14)the National Natural Science Foundation of China(42071245)+3 种基金Third Xinjiang Scientific Expedition Program(2021XJKK1400)the China-Pakistan Joint Research Center on Earth Sciences that supported the implementation of this studythe Chinese Academy of Sciences(CAS)the CSC Scholarship for Young Talents(Doctor Program)for the financial support of this study。
文摘Effective groundwater management is crucial for economic sustainable development,particularly as climate change and population growth increase the uncertainty of aquifer dynamics.Due to limited geological data,Punjab's complex hydrogeological conditions and Quaternary alluvial deposits present significant challenges for groundwater management.This study employs cost-effective numerical techniques as alternatives to traditional methods to safeguard groundwater quality,quantity,and accessibility.It introduces an edit-embedded transition frequency model that integrates regional datasets and utilizes algorithms such as GAMEAS,MCMOD,and TSIM to evaluate aquifer heterogeneity and simulate spatial variations using one-dimensional and three-dimensional Markov chains.Findings show that sand exhibits the highest self-transition(33.112 m),indicating strong stability,followed by silt,clay,and gravel,suggesting overall hydrofacies stability both horizontally and vertically.The model's predictions are largely consistent with actual material distribution,with a slight under-prediction of clay(-0.750%)and an over-prediction of sand(2.985%),which accounts for 58.77%of the aquifer material.It also highlights significant heterogeneity in the northern mountainous regions and minor variations in the south.The study emphasizes Punjab's severe water crisis,with groundwater reserves of 3502.3 BCM,declining water levels(0.38–33.62 m),and low hydraulic conductivity,urging government action on rainwater harvesting and sustainable groundwater management policies.
文摘Colorectal cancer(CRC)is one of the most molecularly heterogeneous malignancies,with complexity that extends far beyond traditional histopathological classifications.The consensus molecular subtypes(CMS)established in 2015 brought a marked advancement in the taxonomy of CRC,consolidating six classification systems into four novel subtypes,which focus on vital gene expression patterns and clinical and prognostic outcomes.However,nearly a decade of clinical experience with CMS classification has revealed fundamental limitations that underscore the inadequacy of any single classification system for capturing the full spectrum of CRC biology.The inherent challenges of the current paradigm are multifaceted.In the CMS classification,mixed phenotypes that remain unclassifiable constitute 13%of CRC cases.This reflects the remarkable heterogeneity that CRC shows.The tumor budding regions reflect the molecular shift due to CMS 2 to CMS 4 switching,causing further heterogeneity.Moreover,the reliance on bulk RNA sequencing fails to capture the spatial organization of molecular signatures within tumors and the critical contributions of the tumor microenvironment.Recent technological advances in spatial transcriptomics,singlecell RNA sequencing,and multi-omic integration have revealed the limitations of transcriptome-only classifications.The emergence of CRC intrinsic subtypes that attempt to remove microenvironmental contributions,pathway-derived subtypes,and stem cell-based classifications demonstrates the field’s recognition that multiple complementary classification systems are necessary.These newer molecular subtypes are not discrete categories but biological continua,thus highlighting that the vast molecular landscape is a tapestry of interlinked features,not rigid subtypes.Multiple technical hurdles cause difficulty in implementing the clinical translation of these newer molecular subtypes,including gene signature complexity,platform-dependent variations,and the difficulty of getting and preserving fresh frozen tissue.CMS 4 shows a poor prognostic outcome among the CMS subtypes,while CMS 1 is associated with poor survival in metastatic cases.However,the predictive value for definitive therapy remains subdued.Looking forward,the integration of artificial intelligence,liquid biopsy approaches,and real-time molecular monitoring promises to enable dynamic,multi-dimensional tumor characterization.The temporal and spatial complexity can only be captured by complementary molecular taxonomies rather than a single,unified system of CRC classification.Such an approach recognizes that different clinical questions–prognosis,treatment selection,resistance prediction–may require different molecular lenses,each optimized for specific clinical applications.This editorial advocates for a revolutionary change from pursuing a single“best”classification system toward a diverse approach that welcomes the molecular mosaic of CRC.Only through such comprehensive molecular characterization can we hope to achieve the promise of precision oncology for the diverse spectrum of patients with CRC.
基金National Key Research and Development Program of China(No.2022YFB3903404,2024YFC3015403)National Natural Science Foundation of China(NSFC No.42271431,42271425)Hubei Province Major Science and Technology Innovation Program(2024BAA011)。
文摘The dense heterogeneous network provides standardized connectivity and access guarantees for 5G communication services.However,the complex network environment and high level of dynamism pose challenges to network selection decisions.Existing vertical handover algorithms often overlook the dynamic nature of user mobility and network condition,resulting in problems such as handover failure and frequent handover,ultimately impacting the quality of the user communication service.To address these problems,we propose an intelligent switching method,iMALSTM-DQN,which integrates an improved Multi-level Associative Long Short-Term Memory model(iMALSTM)with Deep Reinforcement Learning(DRL).The algorithm leverages iMALSTM to predict the global network state in the next moment based on the global user movement trajectory and historical network status information within a region,thereby enhancing the prediction accuracy of network states.Subsequently,based on the predicted network state,we employ the Deep Q Network(DON)model to make handover decisions,adaptively determining the optimal switching and network selection strategy through interaction with the environment.Experimental results demonstrate that the proposed algorithm enhances decision timeliness,significantly reduces the number of switch failures,and alleviates the problem of frequent handovers resulting from network dynamics.
基金funded by the National Natural Science Foundation of China(No.51974134)the Innovation Ability Promotion Plan Project of Hebei Province,China(No.24461002D)。
文摘Under equivalent stiffness conditions,material substitution based on a thin-walled design is crucial for the lightweight of components.Developing high-performance steels with both high-yield strength and excellent ductility has become a key focus in fields like aerospace and lowaltitude flight.The novel low-density steel presented here exhibits a yield strength of 1000 MPa,which is 2-3 times higher than conventional low-alloy high-strength steels,while maintaining an elongation of about 18.7%.By combining ex-situ experimental characterization with a phase mechanical response model based on the iso-work theory and the von Mises equivalent method,the role of heterogeneous deformation-induced strengthening was revealed.The calculated values align closely with experimental results.This exceptional performance is attributed to a multiphase heterogeneous microstructure,where fresh martensite,bainite/tempered martensite,and deformation-induced martensite act as hard regions.These regions release micro-stresses through inhomogeneous cooperative deformation with soft ferrite,enabling multiple plastic deformation mechanisms and stress concentration relief.This research offers new insights into optimizing microstructures through mechanical metallurgy,which is crucial for producing high-performance,lightweight components.
基金supported by the National Natural Science Foundation of China (Nos.42422705,42207175,42177117 and 42577170)the Ningbo Youth Leading Talent Project (No.2024QL051)+1 种基金the Chinese Academy of Engineering Science and Technology Strategy Consulting Project (No.2025-XZ-57)the Central Government Funding Program for Guiding Local Science and Technology Development (No.2025ZY01028)。
文摘Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogeneity remains challenging.To address this,this study first captures the morphology of large-scale(1000 mm × 1000 mm) slate and granite joints via 3D laser scanning.Analysis of these surfaces and corresponding push/pull tests on carved specimens revealed a potential correlation between the heterogeneity of roughness and shear strength.A comparative evaluation of five statistical metrics identified information entropy(Hs) as the most robust indicator for quantifying rock joint heterogeneity.Further analysis using Hsreveals that the heterogeneity is anisotropic and,critically,that shear strength heterogeneity is governed not only by roughness heterogeneity but is also significantly influenced by the mean roughness value,normal stress,and intact rock tensile strength.Consequently,a simple comparison of roughness Hsvalues is insufficient for reliably comparing shear strength heterogeneity.To overcome this limitation,a theoretical framework is developed to explicitly map fundamental roughness statistics(mean and heterogeneity) to shear strength heterogeneity.This framework culminates in a practical workflow that allows for the rapid,field-based assessment of shear strength heterogeneity using readily obtainable rock joint roughness data.
