Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.P...Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.展开更多
In the heterogeneous power internet of things(IoT)environment,data signals are acquired to support different business systems to realize advanced intelligent applications,with massive,multi-source,heterogeneous and ot...In the heterogeneous power internet of things(IoT)environment,data signals are acquired to support different business systems to realize advanced intelligent applications,with massive,multi-source,heterogeneous and other characteristics.Reliable perception of information and efficient transmission of energy in multi-source heterogeneous environments are crucial issues.Compressive sensing(CS),as an effective method of signal compression and transmission,can accurately recover the original signal only by very few sampling.In this paper,we study a new method of multi-source heterogeneous data signal reconstruction of power IoT based on compressive sensing technology.Based on the traditional compressive sensing technology to directly recover multi-source heterogeneous signals,we fully use the interference subspace information to design the measurement matrix,which directly and effectively eliminates the interference while making the measurement.The measure matrix is optimized by minimizing the average cross-coherence of the matrix,and the reconstruction performance of the new method is further improved.Finally,the effectiveness of the new method with different parameter settings under different multi-source heterogeneous data signal cases is verified by using orthogonal matching pursuit(OMP)and sparsity adaptive matching pursuit(SAMP)for considering the actual environment with prior information utilization of signal sparsity and no prior information utilization of signal sparsity.展开更多
With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heter...With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heterogeneous data integration.In view of the heterogeneous characteristics of physical sensor data,including temperature,vibration and pressure that generated by boilers,steam turbines and other key equipment and real-time working condition data of SCADA system,this paper proposes a multi-source heterogeneous data fusion and analysis platform for thermal power plants based on edge computing and deep learning.By constructing a multi-level fusion architecture,the platform adopts dynamic weight allocation strategy and 5D digital twin model to realize the collaborative analysis of physical sensor data,simulation calculation results and expert knowledge.The data fusion module combines Kalman filter,wavelet transform and Bayesian estimation method to solve the problem of data time series alignment and dimension difference.Simulation results show that the data fusion accuracy can be improved to more than 98%,and the calculation delay can be controlled within 500 ms.The data analysis module integrates Dymola simulation model and AERMOD pollutant diffusion model,supports the cascade analysis of boiler combustion efficiency prediction and flue gas emission monitoring,system response time is less than 2 seconds,and data consistency verification accuracy reaches 99.5%.展开更多
Drug development for Alzheimer’s disease is extremely challenging,as demonstrated by the repeated failures of amyloid-β-targeted therapeutics and the controversies surrounding the amyloid-βcascade hypothesis.More r...Drug development for Alzheimer’s disease is extremely challenging,as demonstrated by the repeated failures of amyloid-β-targeted therapeutics and the controversies surrounding the amyloid-βcascade hypothesis.More recently,advances in the development of Lecanemab,an anti-amyloid-βmonoclonal antibody,have shown positive results in reducing brain A burden and slowing cognitive decline in patients with early-stage Alzheimer’s disease in the Phase Ⅲ clinical trial(Clarity Alzheimer’s disease).Despite these promising results,side effects such as amyloid-related imaging abnormalities(ARIA)may limit its usage.ARIA can manifest as ARIA-E(cerebral edema or effusions)and ARIA-H(microhemorrhages or superficial siderosis)and is thought to be caused by increased vascular permeability due to inflammatory responses,leading to leakages of blood products and protein-rich fluid into brain parenchyma.Endothelial dysfunction is an early pathological feature of Alzheimer’s disease,and the blood-brain barrier becomes increasingly leaky as the disease progresses.In addition,APOE4,the strongest genetic risk factor for Alzheimer’s disease,is associated with higher vascular amyloid burden,increased ARIA incidence,and accelerated blood-brain barrier disruptions.These interconnected vascular abnormalities highlight the importance of vascular contributions to the pathophysiology of Alzheimer’s disease.Here,we will closely examine recent research evaluating the heterogeneity of brain endothelial cells in the microvasculature of different brain regions and their relationships with Alzheimer’s disease progression.展开更多
The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initiall...The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.展开更多
Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different educ...Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different education stages is still limited.A new framework was established to evaluate the spatial heterogeneity and its influencing factors across all education stages(kindergarten,primary school,middle school,college)in 1100 schools at the urban scale of Xi’an,China.The research results show that:1)CGS is lower in the Baqiao district and higher in the Yanta and Xincheng districts of Xi’an City.‘Green wealthy schools are mainly concentrated in the Weiyang,Chang’an and Yanta districts.2)CGS of these schools in descending order is college(31.40%)>kindergarten(18.32%)>middle school(13.56%)>primary school(10.70%).3)Colleges have the most recreation sites(n(number)=2),the best education levels(11.93 yr),and the lowest housing prices(1.18×10^(4) yuan(RMB)/m^(2));middle schools have the highest public expenditures(3.97×10^(9) yuan/yr);primary schools have the highest CGS accessibility(travel time gap(TTG)=31.33).4)Multiscale Geographically Weighted Regression model and Spearman’s test prove that recreation sites have a significant positive impact on college green spaces(0.28–0.35),and education level has a significant positive impact on kindergarten green spaces(0.16–0.24).This research framework provides important insights for the assessment of school greening initiatives aimed at fostering healthier learning environments for future generations.展开更多
In recent years,advancements in single-cell and spatial transcriptomics,which are highly regarded developments in the current era,particularly the emerging integration of single-cell and spatiotemporal transcriptomics...In recent years,advancements in single-cell and spatial transcriptomics,which are highly regarded developments in the current era,particularly the emerging integration of single-cell and spatiotemporal transcriptomics,have enabled a detailed molecular comprehension of the complex regulation of cell fate.The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine.Currently,single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors.Start-ing from the perspective of RNA sequencing technology,this review outlined the signifcance of single-cell RNA sequencing(scRNA-seq)in prostate cancer research,encompassing preclinical medicine and clinical applications.We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies,as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis,treatment,and drug resistance characteristics of prostate cancer.These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer.Furthermore,we explore the potential clinical applications stemming from other single-cell technologies in this review,paving the way for future research in precision medicine.展开更多
Mature oligodendrocytes form myelin sheaths that are crucial for the insulation of axons and efficient signal transmission in the central nervous system.Recent evidence has challenged the classical view of the functio...Mature oligodendrocytes form myelin sheaths that are crucial for the insulation of axons and efficient signal transmission in the central nervous system.Recent evidence has challenged the classical view of the functionally static mature oligodendrocyte and revealed a gamut of dynamic functions such as the ability to modulate neuronal circuitry and provide metabolic support to axons.Despite the recognition of potential heterogeneity in mature oligodendrocyte function,a comprehensive summary of mature oligodendrocyte diversity is lacking.We delve into early 20th-century studies by Robertson and Río-Hortega that laid the foundation for the modern identification of regional and morphological heterogeneity in mature oligodendrocytes.Indeed,recent morphologic and functional studies call into question the long-assumed homogeneity of mature oligodendrocyte function through the identification of distinct subtypes with varying myelination preferences.Furthermore,modern molecular investigations,employing techniques such as single cell/nucleus RNA sequencing,consistently unveil at least six mature oligodendrocyte subpopulations in the human central nervous system that are highly transcriptomically diverse and vary with central nervous system region.Age and disease related mature oligodendrocyte variation denotes the impact of pathological conditions such as multiple sclerosis,Alzheimer's disease,and psychiatric disorders.Nevertheless,caution is warranted when subclassifying mature oligodendrocytes because of the simplification needed to make conclusions about cell identity from temporally confined investigations.Future studies leveraging advanced techniques like spatial transcriptomics and single-cell proteomics promise a more nuanced understanding of mature oligodendrocyte heterogeneity.Such research avenues that precisely evaluate mature oligodendrocyte heterogeneity with care to understand the mitigating influence of species,sex,central nervous system region,age,and disease,hold promise for the development of therapeutic interventions targeting varied central nervous system pathology.展开更多
Heterogeneous federated learning(HtFL)has gained significant attention due to its ability to accommodate diverse models and data from distributed combat units.The prototype-based HtFL methods were proposed to reduce t...Heterogeneous federated learning(HtFL)has gained significant attention due to its ability to accommodate diverse models and data from distributed combat units.The prototype-based HtFL methods were proposed to reduce the high communication cost of transmitting model parameters.These methods allow for the sharing of only class representatives between heterogeneous clients while maintaining privacy.However,existing prototype learning approaches fail to take the data distribution of clients into consideration,which results in suboptimal global prototype learning and insufficient client model personalization capabilities.To address these issues,we propose a fair trainable prototype federated learning(FedFTP)algorithm,which employs a fair sampling training prototype(FSTP)mechanism and a hyperbolic space constraints(HSC)mechanism to enhance the fairness and effectiveness of prototype learning on the server in heterogeneous environments.Furthermore,a local prototype stable update(LPSU)mechanism is proposed as a means of maintaining personalization while promoting global consistency,based on contrastive learning.Comprehensive experimental results demonstrate that FedFTP achieves state-of-the-art performance in HtFL scenarios.展开更多
To elucidate the fracturing mechanism of deep hard rock under complex disturbance environments,this study investigates the dynamic failure behavior of pre-damaged granite subjected to multi-source dynamic disturbances...To elucidate the fracturing mechanism of deep hard rock under complex disturbance environments,this study investigates the dynamic failure behavior of pre-damaged granite subjected to multi-source dynamic disturbances.Blasting vibration monitoring was conducted in a deep-buried drill-and-blast tunnel to characterize in-situ dynamic loading conditions.Subsequently,true triaxial compression tests incorporating multi-source disturbances were performed using a self-developed wide-low-frequency true triaxial system to simulate disturbance accumulation and damage evolution in granite.The results demonstrate that combined dynamic disturbances and unloading damage significantly accelerate strength degradation and trigger shear-slip failure along preferentially oriented blast-induced fractures,with strength reductions up to 16.7%.Layered failure was observed on the free surface of pre-damaged granite under biaxial loading,indicating a disturbance-induced fracture localization mechanism.Time-stress-fracture-energy coupling fields were constructed to reveal the spatiotemporal characteristics of fracture evolution.Critical precursor frequency bands(105-150,185-225,and 300-325 kHz)were identified,which serve as diagnostic signatures of impending failure.A dynamic instability mechanism driven by multi-source disturbance superposition and pre-damage evolution was established.Furthermore,a grouting-based wave-absorption control strategy was proposed to mitigate deep dynamic disasters by attenuating disturbance amplitude and reducing excitation frequency.展开更多
Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on co...Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.展开更多
The SiO_(2) inverse opal photonic crystals(PC)with a three-dimensional macroporous structure were fabricated by the sacrificial template method,followed by infiltration of a pyrene derivative,1-(pyren-8-yl)but-3-en-1-...The SiO_(2) inverse opal photonic crystals(PC)with a three-dimensional macroporous structure were fabricated by the sacrificial template method,followed by infiltration of a pyrene derivative,1-(pyren-8-yl)but-3-en-1-amine(PEA),to achieve a formaldehyde(FA)-sensitive and fluorescence-enhanced sensing film.Utilizing the specific Aza-Cope rearrangement reaction of allylamine of PEA and FA to generate a strong fluorescent product emitted at approximately 480 nm,we chose a PC whose blue band edge of stopband overlapped with the fluorescence emission wavelength.In virtue of the fluorescence enhancement property derived from slow photon effect of PC,FA was detected highly selectively and sensitively.The limit of detection(LoD)was calculated to be 1.38 nmol/L.Furthermore,the fast detection of FA(within 1 min)is realized due to the interconnected three-dimensional macroporous structure of the inverse opal PC and its high specific surface area.The prepared sensing film can be used for the detection of FA in air,aquatic products and living cells.The very close FA content in indoor air to the result from FA detector,the recovery rate of 101.5%for detecting FA in aquatic products and fast fluorescence imaging in 2 min for living cells demonstrate the reliability and accuracy of our method in practical applications.展开更多
This paper deeply discusses the causes of gear howling noise,the identification and analysis of multi-source excitation,the transmission path of dynamic noise,simulation and experimental research,case analysis,optimiz...This paper deeply discusses the causes of gear howling noise,the identification and analysis of multi-source excitation,the transmission path of dynamic noise,simulation and experimental research,case analysis,optimization effect,etc.,aiming to better provide a certain guideline and reference for relevant researchers.展开更多
Due to severe mass transfer limitations,the remediation efficiency of low-permeability contaminated sites often fails to meet expectations.Hydraulic fracturing technology has been utilized to enhance amendment deliver...Due to severe mass transfer limitations,the remediation efficiency of low-permeability contaminated sites often fails to meet expectations.Hydraulic fracturing technology has been utilized to enhance amendment delivery,but the influence of soil heterogeneity is commonly overlooked.To address this issue,this study develops a numerical model to simulate the enhanced transport of amendments,incorporating convection,diffusion,adsorption,and degradation processes.Within the model,random permeability fields are generated based on geostatistical methods to explore how soil heterogeneity affects amendment injection efficiency,distribution characteristics,and the underlying physical mechanisms.The results indicate that(1)soil heterogeneity significantly reduces the amendment injection efficiency,with stronger heterogeneity correlating to lower efficiency,(2)soil heterogeneity markedly alters the amendment distribution characteristics,leading to the formation of localized“nodes”,(3)the mechanism by which heterogeneity reduces injection efficiency involves decreasing the density of preferential flow paths in the soil,and(4)the adverse effects of heterogeneity can be mitigated by employing pressure compensation or adjusting well spacing.展开更多
Field tests have demonstrated that depressurization with controlled sand production is an effective technique for natural gas hydrate extraction.Variations in depositional environments and processes result in signific...Field tests have demonstrated that depressurization with controlled sand production is an effective technique for natural gas hydrate extraction.Variations in depositional environments and processes result in significant heterogeneity within subsea natural gas hydrate-bearing sediments.However,the influence of permeability heterogeneity on production performance during depressurization with controlled sand production remains inadequately understood.In this study,a multiphase,multi-component mathematical model is developed to simulate depressurization with controlled sand production in methane hydrate-bearing sediments,incorporating geological conditions representative of unconsolidated argillaceous siltstone hydrate deposits in the Shenhu area of the South China Sea.The effects of permeability heterogeneity-specifically,horizontal autocorrelation length and global permeability heterogeneity-on production performance during depressurization with sand production are investigated using geostatistical modeling combined with finite difference method based numerical simulations.Results show that as the horizontal autocorrelation length of permeability distribution increases,cumulative gas production first rises and then declines,reaching its peak at λ_(Dh)=0.1,whereas sand production steadily increases.In addition,higher formation permeability heterogeneity results in increased cumulative gas and sand production,suggesting that greater heterogeneity promotesmethane hydrate decomposition and gas recovery.These findings can offer valuable insights for optimizing future field development of hydrate-bearing sediments by depressurization with controlled sand production.展开更多
Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electron...Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electronic reviews and consumer data sourced from third-party restaurant platforms collected in 2021.By performing weighted processing on two-dimensional point-of-interest(POI)data,clustering hotspots of high-dimensional restaurant data were identified.A hierarchical network of restaurant hotspots was constructed following the Central Place Theory(CPT)framework,while the Geo-Informatic Tupu method was employed to resolve the challenges posed by network deformation in multi-scale processes.These findings suggest the necessity of enhancing the spatial balance of Shanghai’s urban centers by moderately increasing the number and service capacity of suburban centers at the urban periphery.Such measures would contribute to a more optimized urban structure and facilitate the outward dispersion of comfort-oriented facilities such as the restaurant industry.At a finer spatial scale,the distribution of restaurant hotspots demonstrates a polycentric and symmetric spatial pattern,with a developmental trend radiating outward along the city’s ring roads.This trend can be attributed to the efforts of restaurants to establish connections with other urban functional spaces,leading to the reconfiguration of urban spaces,expansion of restaurant-dedicated land use,and the reorganization of associated commercial activities.The results validate the existence of a polycentric urban structure in Shanghai but also highlight the instability of the restaurant hotspot network during cross-scale transitions.展开更多
Taking the Ming Tombs Forest Farm in Beijing as the research object,this research applied multi-source data fusion and GIS heat-map overlay analysis techniques,systematically collected bird observation point data from...Taking the Ming Tombs Forest Farm in Beijing as the research object,this research applied multi-source data fusion and GIS heat-map overlay analysis techniques,systematically collected bird observation point data from the Global Biodiversity Information Facility(GBIF),population distribution data from the Oak Ridge National Laboratory(ORNL)in the United States,as well as information on the composition of tree species in suitable forest areas for birds and the forest geographical information of the Ming Tombs Forest Farm,which is based on literature research and field investigations.By using GIS technology,spatial processing was carried out on bird observation points and population distribution data to identify suitable bird-watching areas in different seasons.Then,according to the suitability value range,these areas were classified into different grades(from unsuitable to highly suitable).The research findings indicated that there was significant spatial heterogeneity in the bird-watching suitability of the Ming Tombs Forest Farm.The north side of the reservoir was generally a core area with high suitability in all seasons.The deep-aged broad-leaved mixed forests supported the overlapping co-existence of the ecological niches of various bird species,such as the Zosterops simplex and Urocissa erythrorhyncha.In contrast,the shallow forest-edge coniferous pure forests and mixed forests were more suitable for specialized species like Carduelis sinica.The southern urban area and the core area of the mausoleums had relatively low suitability due to ecological fragmentation or human interference.Based on these results,this paper proposed a three-level protection framework of“core area conservation—buffer zone management—isolation zone construction”and a spatio-temporal coordinated human-bird co-existence strategy.It was also suggested that the human-bird co-existence space could be optimized through measures such as constructing sound and light buffer interfaces,restoring ecological corridors,and integrating cultural heritage elements.This research provided an operational technical approach and decision-making support for the scientific planning of bird-watching sites and the coordination of ecological protection and tourism development.展开更多
By employing micrometer-diameter microelectrodes, the metastable pitting corrosion behavior of Co_(68.15)Fe_(4.35)Si_(12.5)B_(12)Cr_(3) metallic glasses (MGs) exposed to 0.6 mol/L NaCl solution was investigated to cla...By employing micrometer-diameter microelectrodes, the metastable pitting corrosion behavior of Co_(68.15)Fe_(4.35)Si_(12.5)B_(12)Cr_(3) metallic glasses (MGs) exposed to 0.6 mol/L NaCl solution was investigated to clarify the correlation between metastable pitting and structural heterogeneity in MGs. Thermally induced degeneration of structural heterogeneity inhibits the initiation, decelerates the growth kinetics, and accelerates the repassivation kinetics of metastable pits while also decreasing the probability of transition from metastability to stability. This enhanced resistance to pitting corrosion is attributed to a reduction in active pitting precursor sites and a decrease in electrochemical activity caused by the structural homogenization of MGs.展开更多
As coal mining progresses to greater depths,controlling the stability of surrounding rock in deep roadways has become an increasingly complex challenge.Although four-dimensional(4D)support theoretically offers unique ...As coal mining progresses to greater depths,controlling the stability of surrounding rock in deep roadways has become an increasingly complex challenge.Although four-dimensional(4D)support theoretically offers unique advantages in maintaining the stability of rock mass,the disaster evolution processes and multi-source information response characteristics in deep roadways with 4D support remain unclear.Consequently,a large-scale physical model testing system and self-designed 4D support components were employed to conduct similarity model tests on the surrounding rock failure process under unsupported(U-1),traditional bolt-mesh-cable support(T-2),and 4D support(4D-R-3)conditions.Combined with multi-source monitoring techniques,including stress–strain,digital image correlation(DIC),acoustic emission(AE),microseismic(MS),parallel electric(PE),and electromagnetic radiation(EMR),the mechanical behavior and multi-source information responses were comprehensively analyzed.The results show that the peak stress and displacement of the models are positively correlated with the support strength.The multi-source information exhibits distinct response characteristics under different supports.The response frequency,energy,and fluctuationsof AE,MS,and EMR signals,along with the apparent resistivity(AR)high-resistivity zone,follow the trend U-1>T-2>4D-R-3.Furthermore,multi-source information exhibits significantdifferences in sensitivity across different phases.The AE,MS,and EMR signals exhibit active responses to rock mass activity at each phase.However,AR signals are only sensitive to the fracture propagation during the plastic yield and failure phases.In summary,the 4D support significantlyenhances the bearing capacity and plastic deformation of the models,while substantially reducing the frequency,energy,and fluctuationsof multi-source signals.展开更多
Although the spatial characteristics within the tumor microenvironment of lung adenocarcinoma(LUAD)have been identified,the mechanisms by which these factors promote LUAD progression and immune evasion remain unclear....Although the spatial characteristics within the tumor microenvironment of lung adenocarcinoma(LUAD)have been identified,the mechanisms by which these factors promote LUAD progression and immune evasion remain unclear.Using spatial transcriptomics and single-cell RNA-sequencing data from multi-regional LUAD biopsies consisting of tumor core,tumor edge,and normal area,we sought to delineate the spatial heterogeneity and driving factors of cell colocalization.Two cancer cell sub-clusters(Cancer_c1 and Cancer_c2),associated with LUAD initiation and metastasis,respectively,exhibit distinct spatial distributions and immune cell colocalizations.In particular,Cancer_c1,enriched within the tumor core,could directly interact with B cells or indirectly recruit B cells through macrophages.Conversely,Cancer_c2 enriched within the tumor edge exhibits colocalization with CD8^(+)T cells.Collectively,our work elucidates the spatial distribution of cancer cell subtypes and their interaction with immune cells in the core and edge of LUAD,providing insights for developing therapeutic strategies for cancer intervention.展开更多
基金supported by Natural Science Foundation of China(Nos.62303126,62362008,author Z.Z,https://www.nsfc.gov.cn/,accessed on 20 December 2024)Major Scientific and Technological Special Project of Guizhou Province([2024]014)+2 种基金Guizhou Provincial Science and Technology Projects(No.ZK[2022]General149) ,author Z.Z,https://kjt.guizhou.gov.cn/,accessed on 20 December 2024)The Open Project of the Key Laboratory of Computing Power Network and Information Security,Ministry of Education under Grant 2023ZD037,author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024)Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(No.ICT2024B25),author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024).
文摘Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.
基金supported by National Natural Science Foundation of China(12174350)Science and Technology Project of State Grid Henan Electric Power Company(5217Q0240008).
文摘In the heterogeneous power internet of things(IoT)environment,data signals are acquired to support different business systems to realize advanced intelligent applications,with massive,multi-source,heterogeneous and other characteristics.Reliable perception of information and efficient transmission of energy in multi-source heterogeneous environments are crucial issues.Compressive sensing(CS),as an effective method of signal compression and transmission,can accurately recover the original signal only by very few sampling.In this paper,we study a new method of multi-source heterogeneous data signal reconstruction of power IoT based on compressive sensing technology.Based on the traditional compressive sensing technology to directly recover multi-source heterogeneous signals,we fully use the interference subspace information to design the measurement matrix,which directly and effectively eliminates the interference while making the measurement.The measure matrix is optimized by minimizing the average cross-coherence of the matrix,and the reconstruction performance of the new method is further improved.Finally,the effectiveness of the new method with different parameter settings under different multi-source heterogeneous data signal cases is verified by using orthogonal matching pursuit(OMP)and sparsity adaptive matching pursuit(SAMP)for considering the actual environment with prior information utilization of signal sparsity and no prior information utilization of signal sparsity.
文摘With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heterogeneous data integration.In view of the heterogeneous characteristics of physical sensor data,including temperature,vibration and pressure that generated by boilers,steam turbines and other key equipment and real-time working condition data of SCADA system,this paper proposes a multi-source heterogeneous data fusion and analysis platform for thermal power plants based on edge computing and deep learning.By constructing a multi-level fusion architecture,the platform adopts dynamic weight allocation strategy and 5D digital twin model to realize the collaborative analysis of physical sensor data,simulation calculation results and expert knowledge.The data fusion module combines Kalman filter,wavelet transform and Bayesian estimation method to solve the problem of data time series alignment and dimension difference.Simulation results show that the data fusion accuracy can be improved to more than 98%,and the calculation delay can be controlled within 500 ms.The data analysis module integrates Dymola simulation model and AERMOD pollutant diffusion model,supports the cascade analysis of boiler combustion efficiency prediction and flue gas emission monitoring,system response time is less than 2 seconds,and data consistency verification accuracy reaches 99.5%.
基金supported by the National Natural Science Foundation of China,Nos.82404892(to QY),82061160374(to ZZ)the Science and Technology Development Fund,Macao Special Administrative Region,China,Nos.0023/2020/AFJ,0035/2020/AGJ+2 种基金the University of Macao Research Grant,Nos.MYRG2022-00248-ICMS,MYRG-CRG2022-00010-ICMS(to MPMH)the Natural Science Foundation of Guangdong Province,No.2024A1515012818(to ZZ)the Fundamental Research Funds for the Central Universities,No.21623114(to ZZ).
文摘Drug development for Alzheimer’s disease is extremely challenging,as demonstrated by the repeated failures of amyloid-β-targeted therapeutics and the controversies surrounding the amyloid-βcascade hypothesis.More recently,advances in the development of Lecanemab,an anti-amyloid-βmonoclonal antibody,have shown positive results in reducing brain A burden and slowing cognitive decline in patients with early-stage Alzheimer’s disease in the Phase Ⅲ clinical trial(Clarity Alzheimer’s disease).Despite these promising results,side effects such as amyloid-related imaging abnormalities(ARIA)may limit its usage.ARIA can manifest as ARIA-E(cerebral edema or effusions)and ARIA-H(microhemorrhages or superficial siderosis)and is thought to be caused by increased vascular permeability due to inflammatory responses,leading to leakages of blood products and protein-rich fluid into brain parenchyma.Endothelial dysfunction is an early pathological feature of Alzheimer’s disease,and the blood-brain barrier becomes increasingly leaky as the disease progresses.In addition,APOE4,the strongest genetic risk factor for Alzheimer’s disease,is associated with higher vascular amyloid burden,increased ARIA incidence,and accelerated blood-brain barrier disruptions.These interconnected vascular abnormalities highlight the importance of vascular contributions to the pathophysiology of Alzheimer’s disease.Here,we will closely examine recent research evaluating the heterogeneity of brain endothelial cells in the microvasculature of different brain regions and their relationships with Alzheimer’s disease progression.
基金supported by the National Key Research and Development Program of China(grant number 2019YFE0123600)。
文摘The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.
基金Under the auspices of Natural Science Basic Research Plan in Shaanxi Province of China(No.2024JC-YBMS-196)。
文摘Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different education stages is still limited.A new framework was established to evaluate the spatial heterogeneity and its influencing factors across all education stages(kindergarten,primary school,middle school,college)in 1100 schools at the urban scale of Xi’an,China.The research results show that:1)CGS is lower in the Baqiao district and higher in the Yanta and Xincheng districts of Xi’an City.‘Green wealthy schools are mainly concentrated in the Weiyang,Chang’an and Yanta districts.2)CGS of these schools in descending order is college(31.40%)>kindergarten(18.32%)>middle school(13.56%)>primary school(10.70%).3)Colleges have the most recreation sites(n(number)=2),the best education levels(11.93 yr),and the lowest housing prices(1.18×10^(4) yuan(RMB)/m^(2));middle schools have the highest public expenditures(3.97×10^(9) yuan/yr);primary schools have the highest CGS accessibility(travel time gap(TTG)=31.33).4)Multiscale Geographically Weighted Regression model and Spearman’s test prove that recreation sites have a significant positive impact on college green spaces(0.28–0.35),and education level has a significant positive impact on kindergarten green spaces(0.16–0.24).This research framework provides important insights for the assessment of school greening initiatives aimed at fostering healthier learning environments for future generations.
基金Chinese Scholarship Council(202206240086)National Natural Science Foundation of China(81974099,82170785,81974098,82170784)+4 种基金National Key Research and Development Program of China(2021YFC2009303)programs from Science and Technology Department of Sichuan Province(2021YFH0172)Young Investigator Award of Sichuan University 2017(2017SCU04A17)Technology Innovation Research and Development Project of Chengdu Science and Technology Bureau(2019-YF05-00296-SN)Sichuan University-Panzhihua science and technology cooperation special fund(2020CDPZH-4).
文摘In recent years,advancements in single-cell and spatial transcriptomics,which are highly regarded developments in the current era,particularly the emerging integration of single-cell and spatiotemporal transcriptomics,have enabled a detailed molecular comprehension of the complex regulation of cell fate.The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine.Currently,single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors.Start-ing from the perspective of RNA sequencing technology,this review outlined the signifcance of single-cell RNA sequencing(scRNA-seq)in prostate cancer research,encompassing preclinical medicine and clinical applications.We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies,as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis,treatment,and drug resistance characteristics of prostate cancer.These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer.Furthermore,we explore the potential clinical applications stemming from other single-cell technologies in this review,paving the way for future research in precision medicine.
基金supported by a grant from the Progressive MS Alliance(BRAVE in MS)Le Grand Portage Fund。
文摘Mature oligodendrocytes form myelin sheaths that are crucial for the insulation of axons and efficient signal transmission in the central nervous system.Recent evidence has challenged the classical view of the functionally static mature oligodendrocyte and revealed a gamut of dynamic functions such as the ability to modulate neuronal circuitry and provide metabolic support to axons.Despite the recognition of potential heterogeneity in mature oligodendrocyte function,a comprehensive summary of mature oligodendrocyte diversity is lacking.We delve into early 20th-century studies by Robertson and Río-Hortega that laid the foundation for the modern identification of regional and morphological heterogeneity in mature oligodendrocytes.Indeed,recent morphologic and functional studies call into question the long-assumed homogeneity of mature oligodendrocyte function through the identification of distinct subtypes with varying myelination preferences.Furthermore,modern molecular investigations,employing techniques such as single cell/nucleus RNA sequencing,consistently unveil at least six mature oligodendrocyte subpopulations in the human central nervous system that are highly transcriptomically diverse and vary with central nervous system region.Age and disease related mature oligodendrocyte variation denotes the impact of pathological conditions such as multiple sclerosis,Alzheimer's disease,and psychiatric disorders.Nevertheless,caution is warranted when subclassifying mature oligodendrocytes because of the simplification needed to make conclusions about cell identity from temporally confined investigations.Future studies leveraging advanced techniques like spatial transcriptomics and single-cell proteomics promise a more nuanced understanding of mature oligodendrocyte heterogeneity.Such research avenues that precisely evaluate mature oligodendrocyte heterogeneity with care to understand the mitigating influence of species,sex,central nervous system region,age,and disease,hold promise for the development of therapeutic interventions targeting varied central nervous system pathology.
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(No.2022D01B187).
文摘Heterogeneous federated learning(HtFL)has gained significant attention due to its ability to accommodate diverse models and data from distributed combat units.The prototype-based HtFL methods were proposed to reduce the high communication cost of transmitting model parameters.These methods allow for the sharing of only class representatives between heterogeneous clients while maintaining privacy.However,existing prototype learning approaches fail to take the data distribution of clients into consideration,which results in suboptimal global prototype learning and insufficient client model personalization capabilities.To address these issues,we propose a fair trainable prototype federated learning(FedFTP)algorithm,which employs a fair sampling training prototype(FSTP)mechanism and a hyperbolic space constraints(HSC)mechanism to enhance the fairness and effectiveness of prototype learning on the server in heterogeneous environments.Furthermore,a local prototype stable update(LPSU)mechanism is proposed as a means of maintaining personalization while promoting global consistency,based on contrastive learning.Comprehensive experimental results demonstrate that FedFTP achieves state-of-the-art performance in HtFL scenarios.
基金supported by the National Key R&D Program of China(No.2023YFB2603602)the National Natural Science Foundation of China(Nos.52222810 and 52178383).
文摘To elucidate the fracturing mechanism of deep hard rock under complex disturbance environments,this study investigates the dynamic failure behavior of pre-damaged granite subjected to multi-source dynamic disturbances.Blasting vibration monitoring was conducted in a deep-buried drill-and-blast tunnel to characterize in-situ dynamic loading conditions.Subsequently,true triaxial compression tests incorporating multi-source disturbances were performed using a self-developed wide-low-frequency true triaxial system to simulate disturbance accumulation and damage evolution in granite.The results demonstrate that combined dynamic disturbances and unloading damage significantly accelerate strength degradation and trigger shear-slip failure along preferentially oriented blast-induced fractures,with strength reductions up to 16.7%.Layered failure was observed on the free surface of pre-damaged granite under biaxial loading,indicating a disturbance-induced fracture localization mechanism.Time-stress-fracture-energy coupling fields were constructed to reveal the spatiotemporal characteristics of fracture evolution.Critical precursor frequency bands(105-150,185-225,and 300-325 kHz)were identified,which serve as diagnostic signatures of impending failure.A dynamic instability mechanism driven by multi-source disturbance superposition and pre-damage evolution was established.Furthermore,a grouting-based wave-absorption control strategy was proposed to mitigate deep dynamic disasters by attenuating disturbance amplitude and reducing excitation frequency.
基金supported by the Sichuan Science and Technology Program(Nos.2024JDRC0100 and 2023YFQ0091)the National Natural Science Foundation of China(Nos.U21A20167 and 52475138)the Scientific Research Foundation of the State Key Laboratory of Rail Transit Vehicle System(No.2024RVL-T08).
文摘Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.
基金supported by the National Natural Science Foundation of China(21663032 and 22061041)the Open Sharing Platform for Scientific and Technological Resources of Shaanxi Province(2021PT-004)the National Innovation and Entrepreneurship Training Program for College Students of China(S202110719044)。
文摘The SiO_(2) inverse opal photonic crystals(PC)with a three-dimensional macroporous structure were fabricated by the sacrificial template method,followed by infiltration of a pyrene derivative,1-(pyren-8-yl)but-3-en-1-amine(PEA),to achieve a formaldehyde(FA)-sensitive and fluorescence-enhanced sensing film.Utilizing the specific Aza-Cope rearrangement reaction of allylamine of PEA and FA to generate a strong fluorescent product emitted at approximately 480 nm,we chose a PC whose blue band edge of stopband overlapped with the fluorescence emission wavelength.In virtue of the fluorescence enhancement property derived from slow photon effect of PC,FA was detected highly selectively and sensitively.The limit of detection(LoD)was calculated to be 1.38 nmol/L.Furthermore,the fast detection of FA(within 1 min)is realized due to the interconnected three-dimensional macroporous structure of the inverse opal PC and its high specific surface area.The prepared sensing film can be used for the detection of FA in air,aquatic products and living cells.The very close FA content in indoor air to the result from FA detector,the recovery rate of 101.5%for detecting FA in aquatic products and fast fluorescence imaging in 2 min for living cells demonstrate the reliability and accuracy of our method in practical applications.
文摘This paper deeply discusses the causes of gear howling noise,the identification and analysis of multi-source excitation,the transmission path of dynamic noise,simulation and experimental research,case analysis,optimization effect,etc.,aiming to better provide a certain guideline and reference for relevant researchers.
基金supported by the National Natural Science Foundation of China(Grant Nos.42227804 and 42402279)the Natural Science Foundation of Shanghai(Grant No.24ZR1467500).
文摘Due to severe mass transfer limitations,the remediation efficiency of low-permeability contaminated sites often fails to meet expectations.Hydraulic fracturing technology has been utilized to enhance amendment delivery,but the influence of soil heterogeneity is commonly overlooked.To address this issue,this study develops a numerical model to simulate the enhanced transport of amendments,incorporating convection,diffusion,adsorption,and degradation processes.Within the model,random permeability fields are generated based on geostatistical methods to explore how soil heterogeneity affects amendment injection efficiency,distribution characteristics,and the underlying physical mechanisms.The results indicate that(1)soil heterogeneity significantly reduces the amendment injection efficiency,with stronger heterogeneity correlating to lower efficiency,(2)soil heterogeneity markedly alters the amendment distribution characteristics,leading to the formation of localized“nodes”,(3)the mechanism by which heterogeneity reduces injection efficiency involves decreasing the density of preferential flow paths in the soil,and(4)the adverse effects of heterogeneity can be mitigated by employing pressure compensation or adjusting well spacing.
基金funded by the National Key Research and Development Program of China(grant number 2023YFC3009204)the National Natural Science Foundation of China(grant number 52174015).
文摘Field tests have demonstrated that depressurization with controlled sand production is an effective technique for natural gas hydrate extraction.Variations in depositional environments and processes result in significant heterogeneity within subsea natural gas hydrate-bearing sediments.However,the influence of permeability heterogeneity on production performance during depressurization with controlled sand production remains inadequately understood.In this study,a multiphase,multi-component mathematical model is developed to simulate depressurization with controlled sand production in methane hydrate-bearing sediments,incorporating geological conditions representative of unconsolidated argillaceous siltstone hydrate deposits in the Shenhu area of the South China Sea.The effects of permeability heterogeneity-specifically,horizontal autocorrelation length and global permeability heterogeneity-on production performance during depressurization with sand production are investigated using geostatistical modeling combined with finite difference method based numerical simulations.Results show that as the horizontal autocorrelation length of permeability distribution increases,cumulative gas production first rises and then declines,reaching its peak at λ_(Dh)=0.1,whereas sand production steadily increases.In addition,higher formation permeability heterogeneity results in increased cumulative gas and sand production,suggesting that greater heterogeneity promotesmethane hydrate decomposition and gas recovery.These findings can offer valuable insights for optimizing future field development of hydrate-bearing sediments by depressurization with controlled sand production.
基金Under the auspices of the Key Program of National Natural Science Foundation of China(No.42030409)。
文摘Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electronic reviews and consumer data sourced from third-party restaurant platforms collected in 2021.By performing weighted processing on two-dimensional point-of-interest(POI)data,clustering hotspots of high-dimensional restaurant data were identified.A hierarchical network of restaurant hotspots was constructed following the Central Place Theory(CPT)framework,while the Geo-Informatic Tupu method was employed to resolve the challenges posed by network deformation in multi-scale processes.These findings suggest the necessity of enhancing the spatial balance of Shanghai’s urban centers by moderately increasing the number and service capacity of suburban centers at the urban periphery.Such measures would contribute to a more optimized urban structure and facilitate the outward dispersion of comfort-oriented facilities such as the restaurant industry.At a finer spatial scale,the distribution of restaurant hotspots demonstrates a polycentric and symmetric spatial pattern,with a developmental trend radiating outward along the city’s ring roads.This trend can be attributed to the efforts of restaurants to establish connections with other urban functional spaces,leading to the reconfiguration of urban spaces,expansion of restaurant-dedicated land use,and the reorganization of associated commercial activities.The results validate the existence of a polycentric urban structure in Shanghai but also highlight the instability of the restaurant hotspot network during cross-scale transitions.
基金Sponsored by Beijing Youth Innovation Talent Support Program for Urban Greening and Landscaping——The 2024 Special Project for Promoting High-Quality Development of Beijing’s Landscaping through Scientific and Technological Innovation(KJCXQT202410).
文摘Taking the Ming Tombs Forest Farm in Beijing as the research object,this research applied multi-source data fusion and GIS heat-map overlay analysis techniques,systematically collected bird observation point data from the Global Biodiversity Information Facility(GBIF),population distribution data from the Oak Ridge National Laboratory(ORNL)in the United States,as well as information on the composition of tree species in suitable forest areas for birds and the forest geographical information of the Ming Tombs Forest Farm,which is based on literature research and field investigations.By using GIS technology,spatial processing was carried out on bird observation points and population distribution data to identify suitable bird-watching areas in different seasons.Then,according to the suitability value range,these areas were classified into different grades(from unsuitable to highly suitable).The research findings indicated that there was significant spatial heterogeneity in the bird-watching suitability of the Ming Tombs Forest Farm.The north side of the reservoir was generally a core area with high suitability in all seasons.The deep-aged broad-leaved mixed forests supported the overlapping co-existence of the ecological niches of various bird species,such as the Zosterops simplex and Urocissa erythrorhyncha.In contrast,the shallow forest-edge coniferous pure forests and mixed forests were more suitable for specialized species like Carduelis sinica.The southern urban area and the core area of the mausoleums had relatively low suitability due to ecological fragmentation or human interference.Based on these results,this paper proposed a three-level protection framework of“core area conservation—buffer zone management—isolation zone construction”and a spatio-temporal coordinated human-bird co-existence strategy.It was also suggested that the human-bird co-existence space could be optimized through measures such as constructing sound and light buffer interfaces,restoring ecological corridors,and integrating cultural heritage elements.This research provided an operational technical approach and decision-making support for the scientific planning of bird-watching sites and the coordination of ecological protection and tourism development.
基金supported by the National Natural Science Foun-dation of China(No.52401222)Zhejiang Provincial Natural Sci-ence Foundation(LQN25E010011)+2 种基金Ningbo Natural Science Founda-tion(2024J073)Ningbo Major Special Projects of the Plan“Science and Technology Innovation 2025"(No.2022Z107)Ningbo Key Research and Development Program(No.2023Z097).
文摘By employing micrometer-diameter microelectrodes, the metastable pitting corrosion behavior of Co_(68.15)Fe_(4.35)Si_(12.5)B_(12)Cr_(3) metallic glasses (MGs) exposed to 0.6 mol/L NaCl solution was investigated to clarify the correlation between metastable pitting and structural heterogeneity in MGs. Thermally induced degeneration of structural heterogeneity inhibits the initiation, decelerates the growth kinetics, and accelerates the repassivation kinetics of metastable pits while also decreasing the probability of transition from metastability to stability. This enhanced resistance to pitting corrosion is attributed to a reduction in active pitting precursor sites and a decrease in electrochemical activity caused by the structural homogenization of MGs.
基金supported by the National Natural Science Foundation of China(Grant Nos.U22A20598 and 52104107)the"Qinglan Project"of Jiangsu Colleges and Universities,Young Elite Scientists Sponsorship Program of Jiangsu Province(Grant No.TJ-2023-086).
文摘As coal mining progresses to greater depths,controlling the stability of surrounding rock in deep roadways has become an increasingly complex challenge.Although four-dimensional(4D)support theoretically offers unique advantages in maintaining the stability of rock mass,the disaster evolution processes and multi-source information response characteristics in deep roadways with 4D support remain unclear.Consequently,a large-scale physical model testing system and self-designed 4D support components were employed to conduct similarity model tests on the surrounding rock failure process under unsupported(U-1),traditional bolt-mesh-cable support(T-2),and 4D support(4D-R-3)conditions.Combined with multi-source monitoring techniques,including stress–strain,digital image correlation(DIC),acoustic emission(AE),microseismic(MS),parallel electric(PE),and electromagnetic radiation(EMR),the mechanical behavior and multi-source information responses were comprehensively analyzed.The results show that the peak stress and displacement of the models are positively correlated with the support strength.The multi-source information exhibits distinct response characteristics under different supports.The response frequency,energy,and fluctuationsof AE,MS,and EMR signals,along with the apparent resistivity(AR)high-resistivity zone,follow the trend U-1>T-2>4D-R-3.Furthermore,multi-source information exhibits significantdifferences in sensitivity across different phases.The AE,MS,and EMR signals exhibit active responses to rock mass activity at each phase.However,AR signals are only sensitive to the fracture propagation during the plastic yield and failure phases.In summary,the 4D support significantlyenhances the bearing capacity and plastic deformation of the models,while substantially reducing the frequency,energy,and fluctuationsof multi-source signals.
基金supported by the National Natural Science Foundation of China(82002432 to J.W.,82302068 to M.Z.,and 32300568 to T.W.)the Natural Science Foundation of Shandong Province(ZR2024MH159 to Y.Z.,ZR2020QH179 to J.W.,ZR2022QH057 to M.Z.,and ZR2021QH005 to T.W.)the China Postdoctoral Science Foundation(2024M752006 to S.M.)。
文摘Although the spatial characteristics within the tumor microenvironment of lung adenocarcinoma(LUAD)have been identified,the mechanisms by which these factors promote LUAD progression and immune evasion remain unclear.Using spatial transcriptomics and single-cell RNA-sequencing data from multi-regional LUAD biopsies consisting of tumor core,tumor edge,and normal area,we sought to delineate the spatial heterogeneity and driving factors of cell colocalization.Two cancer cell sub-clusters(Cancer_c1 and Cancer_c2),associated with LUAD initiation and metastasis,respectively,exhibit distinct spatial distributions and immune cell colocalizations.In particular,Cancer_c1,enriched within the tumor core,could directly interact with B cells or indirectly recruit B cells through macrophages.Conversely,Cancer_c2 enriched within the tumor edge exhibits colocalization with CD8^(+)T cells.Collectively,our work elucidates the spatial distribution of cancer cell subtypes and their interaction with immune cells in the core and edge of LUAD,providing insights for developing therapeutic strategies for cancer intervention.
