The sustainability of the Internet of Things(IoT)involves various issues,such as poor connectivity,scalability problems,interoperability issues,and energy inefficiency.Although the Sixth Generation of mobile networks(...The sustainability of the Internet of Things(IoT)involves various issues,such as poor connectivity,scalability problems,interoperability issues,and energy inefficiency.Although the Sixth Generation of mobile networks(6G)allows for Ultra-Reliable Low-Latency Communication(URLLC),enhanced Mobile Broadband(eMBB),and massive Machine-Type Communications(mMTC)services,it faces deployment challenges such as the short range of sub-THz and THz frequency bands,low capability to penetrate obstacles,and very high path loss.This paper presents a network architecture to enhance the connectivity of wireless IoT mesh networks that employ both 6G and Wi-Fi technologies.In this architecture,local communications are carried through the mesh network,which uses a virtual backbone to relay packets to local nodes,while remote communications are carried through the 6G network.The virtual backbone is created using a heuristic distributed ConnectedDominating Set(CDS)algorithm.In this algorithm,each node uses information collected from its one-and two-hop neighbors to determine its role and find the set of expansion nodes that are used to select the next CDS nodes.The proposed algorithm has O(n)message and O(K)time complexities,where n is the number of nodes in the network,and K is the depth of the cluster.The study proved that the approximation ratio of the algorithmhas an upper bound of 2.06748(3.4306MCDS+4.8185).Performance evaluations compared the size of the CDS against the theoretical limit and recent CDS clustering algorithms.Results indicate that the proposed algorithm has the smallest average slope for the size of the CDS as the number of nodes increases.展开更多
Deep learning attentionmechanisms have achieved remarkable progress in computer vision,but still face limitations when handling images with ambiguous boundaries and uncertain feature representations.Conventional atten...Deep learning attentionmechanisms have achieved remarkable progress in computer vision,but still face limitations when handling images with ambiguous boundaries and uncertain feature representations.Conventional attention modules such as SE-Net,CBAM,ECA-Net,and CA adopt a deterministic paradigm,assigning fixed scalar weights to features without modeling ambiguity or confidence.To overcome these limitations,this paper proposes the Fuzzy Attention Network Layer(FANL),which integrates intuitionistic fuzzy set theory with convolutional neural networks to explicitly represent feature uncertainty through membership(μ),non-membership(ν),and hesitation(π)degrees.FANLconsists of four coremodules:(1)feature dimensionality reduction via global pooling,(2)fuzzymodeling using learnable clustering centers,(3)adaptive attention generation through weighted fusion of fuzzy components,and(4)feature refinement through residual connections.A cross-layer guidance mechanism is further introduced to enhance hierarchical feature propagation,allowing high-level semantic features to incorporate fine-grained texture information from shallow layers.Comprehensive experiments on three benchmark datasets—PathMNIST-30000,full PathMNIST,and Blood MNIST—demonstrate the effectiveness and generalizability of FANL.The model achieves 84.41±0.56%accuracy and a 1.69%improvement over the baseline CNN while maintaining lightweight computational complexity.Ablation studies show that removing any component causes a 1.7%–2.0%performance drop,validating the synergistic contribution of each module.Furthermore,FANL provides superior uncertainty calibration(ECE=0.0452)and interpretable selective prediction under uncertainty.Overall,FANL presents an efficient and uncertaintyaware attention framework that improves both accuracy and reliability,offering a promising direction for robust visual recognition under ambiguous or noisy conditions.展开更多
With the large-scale integration of new energy sources,various resources such as energy storage,electric vehicles(EVs),and photovoltaics(PV) have participated in the scheduling of active distribution networks(ADNs),po...With the large-scale integration of new energy sources,various resources such as energy storage,electric vehicles(EVs),and photovoltaics(PV) have participated in the scheduling of active distribution networks(ADNs),posing new challenges to the operation and scheduling of distribution networks.Aiming at the uncertainty of PV and EV,an optimal scheduling model for ADNs based on multi-scenario fuzzy set based charging station resource forecasting is constructed.To address the scheduling uncertainties caused by PV and load forecasting errors,a day-ahead optimal scheduling model based on conditional value at risk(CVaR) for cost assessment is established,with the optimization objectives of minimizing the operation cost of distribution networks and the risk cost caused by forecasting errors.An improved subtractive optimizer algorithm is proposed to solve the model and formulate day-ahead optimization schemes.Secondly,a forecasting model for dispatchable resources in charging stations is constructed based on event-based fuzzy set theory.On this basis,an intraday scheduling model is built to comprehensively utilize the dispatchable resources of charging stations to coordinate with the output of distributed power sources,achieving optimal scheduling with the goal of minimizing operation costs.Finally,an experimental scenario based on the IEEE-33 node system is designed for simulation verification.The comparison of optimal scheduling results shows that the proposed method can fully exploit the potential scheduling resources of charging stations,improving the operation stability of ADNs and the accommodution capacity of new energy.展开更多
The Edikan Mine,which consists of Fobinso and Esuajah gold deposits,lies within the Asankrangwa Gold Belt of the Birimian Supergroup in the Kumasi Basin.The metasedimentary rocks in the Basins and the faulted metavolc...The Edikan Mine,which consists of Fobinso and Esuajah gold deposits,lies within the Asankrangwa Gold Belt of the Birimian Supergroup in the Kumasi Basin.The metasedimentary rocks in the Basins and the faulted metavolcanic rocks in the Belts that make up the Birimian Supergroup were intruded by granitoids during the Eburnean Orogeny.This research aims to classify granitoids in the Edikan Mine and ascertain the petrogenetic and geochemical characteristics of some auriferous granitoids in the wider Kumasi Basin,Ghana,to understand the implications for geodynamic settings.A multi-methods approach involving field studies,petrographic studies,and whole-rock geochemical analysis was used to achieve the goal of the study.Petrographic studies revealed a relatively high abundance of plagioclase and a low percentage of K-feldspars(anorthoclase and orthoclase)in the Fobinso samples,suggesting that the samples are granodioritic in nature,while the Esuajah samples showed relatively low plagioclase abundance and a high percentage in K-feldspars,indicating that they are granitic.The granitoids from the study areas are co-magmatic.The granitoids in Esuajah and Fobinso are generally enriched in large ion lithophile elements and light rare earth elements than high field strength elements,middle rare earth elements,and heavy rare earth elements,indicating mixing with crustal sources during the evolution of the granitoids.The granitoids were tectonically formed in a syn-collisional+VAG setting,which implies that they were formed in the subduction zone setting.Fobinso granodiorites showed S-type signatures with evidence of extensive crustal contamination,while the Esuajah granites showed I-type signatures with little or no crustal contamination and are peraluminous.Gold mineralization in the study area is structurally and lithologically controlled with shear zones,faulting,and veining as the principal structures controlling the mineralization.The late-stage vein,V3,in the Edikan Mine is characterized by a low vein angle and is mineralized.展开更多
Owing to process conditions such as uneven clearance of base metal assembly and welding deformation,it is difficult to obtain well-formed structural welds with robot constant specification parameters welding.Determini...Owing to process conditions such as uneven clearance of base metal assembly and welding deformation,it is difficult to obtain well-formed structural welds with robot constant specification parameters welding.Determining how to extract a structured,anti-interference,concise,and dynamic knowledge model from measurable data,and then adjust the welding parameters with corresponding control methods in real time is a central problem to be solved in welding formation control.Hence,this paper proposes a welding penetration control method based on a Neighborhood Rough Set-Adaptive Neuro-Fuzzy Inference System(NRS-ANFIS)to achieve effective penetration control for the GMAW welding process.In orthogonal experiments,the NRS algorithm,which is based on visual sensing to obtain the properties of the weld pool and gap changes,is used to reduce the established frontal weld pool feature information decision table,and the minimum feature set of the weld pool tail width WTand the tail area coefficient CTSis obtained.The minimum feature set of the effective frontal weld pool,real-time line laser distance change,and real-time current information are used as the input for the ANFIS control system.The experimental results for the two groups of time-varying gaps demonstrate that under the condition of no preheating of the base metal,the complete welding penetration rate of the adjusted welding process parameters output by the trained ANFIS model reaches 87%,and the backside melting width is uniform and consistent,which meets the welding specification requirements.展开更多
Dear Editor,This letter deals with the distributed recursive set-membership filtering(DRSMF)issue for state-saturated systems under encryption-decryption mechanism.To guarantee the data security,the encryption-decrypt...Dear Editor,This letter deals with the distributed recursive set-membership filtering(DRSMF)issue for state-saturated systems under encryption-decryption mechanism.To guarantee the data security,the encryption-decryption mechanism is considered in the signal transmission process.Specifically,a novel DRSMF scheme is developed such that,for both state saturation and encryption-decryption mechanism,the filtering error(FE)is limited to the ellipsoid domain.Then,the filtering error constraint matrix(FECM)is computed and a desirable filter gain is derived by minimizing the FECM.Besides,the bound-edness evaluation of the FECM is provided.展开更多
Submodular optimization is primarily applied in multi-agent systems for tasks such as resource allocation,task assignment,collaborative decision-making,and optimization problems.Maximization of optimizing submodular s...Submodular optimization is primarily applied in multi-agent systems for tasks such as resource allocation,task assignment,collaborative decision-making,and optimization problems.Maximization of optimizing submodular set functions attracts much attention since the 1970s.A large body of work has been done using approximation algorithms.When the dimension of the independent variable of the set function changes from one tok,it is called ak-submodular set function.Thek-submodular set function,a generalization of the classical submodular set function,arises in diverse fields with varied applications.In many practical scenarios,quantifying the degree of closeness to submodularity becomes essential,leading to concepts such as approximately submodular set functions and the diminishing-return(DR) ratio.This paper investigates ak-dimensional set function under matroid constraints,which may lack full submodularity.Instead,we focus on an approximately non-ksubmodular set function characterized by its DR ratio.Employing a greedy algorithmic approach,we derive an approximation guarantee for this problem.Notably,when the DR ratio is set to one,our results align with existing findings in the literature.Experimental results demonstrate the superiority of our algorithm over the baselines.展开更多
Circumlunar abort trajectories constitute a vital contingency return strategy during the translunar phase of crewed lunar missions.This paper proposes a methodology for constructing the solution set of the circumlunar...Circumlunar abort trajectories constitute a vital contingency return strategy during the translunar phase of crewed lunar missions.This paper proposes a methodology for constructing the solution set of the circumlunar abort trajectory and leverages its advantageous properties to address the optimization design problem of abort trajectories.Initially,a solution set of all feasible abort trajectories,originating from an abort point on the nominal trajectory and complying with fundamental reentry constraints,is formulated through the introduction of two novel design parameters.Subsequently,the geometric characteristics of the solution set,as well as the distributional properties of key iterative constraint responses,including flight time and velocity increment,are analyzed.Finally,the characteristics exhibited in the solution set are employed to directly identify the design parameters of the abort trajectories with minimum flight time and velocity increment,thereby providing solutions to two distinct types of optimization problems.The simulation results for a variety of nominal trajectories,encompassing the reconstruction and redesign of the Apollo13 abort trajectory,validate the proposed method,demonstrating its ability to directly generate optimal abort trajectories.The method proposed in this paper investigates feasible abort trajectories from a global perspective,providing both a framework and convenience for mission planning and iterative optimization in abort trajectory design.展开更多
A discrete subset S of a topological gyrogroup G with the identity 0 is said to be a suitable set for G if it generates a dense subgyrogroup of G and S∪{0}is closed in G.In this paper,it is proved that each countable...A discrete subset S of a topological gyrogroup G with the identity 0 is said to be a suitable set for G if it generates a dense subgyrogroup of G and S∪{0}is closed in G.In this paper,it is proved that each countable Hausdorff topological gyrogroup has a suitable set;moreover,it is shown that each separable metrizable strongly topological gyrogroup has a suitable set.展开更多
Objectives:Tamoxifen is a key drug that provides endocrine therapy for estrogen receptor(ER)α-positive breast cancer;however,resistance remains a significant clinical challenge.This study aims to investigate the mole...Objectives:Tamoxifen is a key drug that provides endocrine therapy for estrogen receptor(ER)α-positive breast cancer;however,resistance remains a significant clinical challenge.This study aims to investigate the molecular mechanisms of tamoxifen resistance in ERα-positive breast cancer,with particular focus on the role of SET Domain Containing 1A(SETD1A)-driven forkhead box A2(FOXA2)as a key regulator of this resistance.Methods:FOXA2 expression and its regulation by SETD1A were assessed via(quantitative polymerase chain reaction),western blotting,transcriptome profiling,and chromatin immunoprecipitation analyses.The effects of FOXA2 on cell proliferation,migration,invasion,and cancer stem cell traits were evaluated using small interfering RNA(siRNA)-mediated silencing.Clinical relevance was examined by analyzing patient datasets and tumor tissue microarrays.Results:FOXA2 expression was significantly elevated in tamoxifen-resistant(TamR)and ERα-negative breast cancer cells compared to that in ERα-positive MCF-7 cells,regardless of tamoxifen treatment or ERαdepletion.Transcriptome and chromatin immunoprecipitation analyses revealed that SETD1A,a histone methyltransferase,directly regulated FOXA2 expression.Functionally,FOXA2 knockdown inhibited the proliferation,migration,invasion,and cancer stem cell properties of TamR cells while restoring tamoxifen sensitivity.High FOXA2 expression was correlated with poor survival and reduced responsiveness to tamoxifen in patients with ER-positive breast cancer.Conclusion:Our findings identified FOXA2 as a key mediator of tamoxifen resistance regulated by SETD1A and suggested that targeting the SETD1A-FOXA2 axis may offer a novel strategy for overcoming endocrine resistance in breast cancer.展开更多
To elucidate the geographical differentiation characteristics and driving mechanisms of Dissolved Organic Matter(DOM)in typical rivers,this study conducted a multi-spectral investigation on three representative river ...To elucidate the geographical differentiation characteristics and driving mechanisms of Dissolved Organic Matter(DOM)in typical rivers,this study conducted a multi-spectral investigation on three representative river types within Shandong Province:The mountainous Dawen River,the plain Tuhai River,and the artificial East Grand Canal.The DOM composition was analyzed using Ultraviolet-Visible(UV-Vis)absorption spectroscopy,Excitation-Emission Matrix(EEM)fluorescence spectroscopy,and parallel factor analysis(PARAFAC),while Principal Component Analysis(PCA)was employed to quantify the synergistic effects of natural processes and anthropogenic activities.Results revealed significant spatial heterogeneity in DOM composition and sources.The plain river exhibited the highest aromaticity(humic-like components:43.3%)due to long-term agricultural non-point source inputs and urban wastewater discharge.The mountain stream,shaped by complex terrain and relatively intact ecosystems,was dominated by autochthonous DOM derived from microbial metabolism,with higher Fluorescence Index(FI=2.12)and biological index(BIX=1.35)than other river types.The artificial canal retained protein-like components(64.2%),largely attributed to winter hydrological stagnation and disturbances from shipping activities.Further analysis demonstrated that geographical settings(e.g.,mountain terrain)and anthropogenic activities(e.g.,agriculture,shipping)jointly regulated DOM composition by altering the balance between input and transformation processes.Integrated fluorescence parameters and PCA results suggested differentiated management strategies:protecting ecological integrity in mountain streams to sustain selfpurification,enhancing non-point source interception in plain rivers,and mitigating shipping pollution in canals.This study systematically reveals the natural-anthropogenic coupling mechanisms driving DOM dynamics in northern China rivers,providing critical insights for precision water environment management at the watershed scale.展开更多
The quality of cardiopulmonary resuscitation(CPR) significantly influences survival and neurological outcomes in patients with cardiac arrest(CA).Although mechanical chest compression devices and extracorporeal cardio...The quality of cardiopulmonary resuscitation(CPR) significantly influences survival and neurological outcomes in patients with cardiac arrest(CA).Although mechanical chest compression devices and extracorporeal cardiopulmonary resuscitation(ECPR) have demonstrated some benefits,high-quality manual CPR remained the essential first step,particularly in resource-limited settings.In this study,we examined whether opportunities existed to improve manual CPR performance using preliminary data from our recent survey conducted in a province in western China.We aim to emphasize the importance of improving manual CPR quality before implementing advanced interventions.展开更多
A rough set based corner classification neural network, the Rough-CC4, is presented to solve document classification problems such as document representation of different document sizes, document feature selection and...A rough set based corner classification neural network, the Rough-CC4, is presented to solve document classification problems such as document representation of different document sizes, document feature selection and document feature encoding. In the Rough-CC4, the documents are described by the equivalent classes of the approximate words. By this method, the dimensions representing the documents can be reduced, which can solve the precision problems caused by the different document sizes and also blur the differences caused by the approximate words. In the Rough-CC4, a binary encoding method is introduced, through which the importance of documents relative to each equivalent class is encoded. By this encoding method, the precision of the Rough-CC4 is improved greatly and the space complexity of the Rough-CC4 is reduced. The Rough-CC4 can be used in automatic classification of documents.展开更多
To cope with the constraint problem of power consumption and transmission delay in the virtual backbone of wireless sensor network, a distributed connected dominating set （CDS） algorithm with （α,β）-constraints i...To cope with the constraint problem of power consumption and transmission delay in the virtual backbone of wireless sensor network, a distributed connected dominating set （CDS） algorithm with （α,β）-constraints is proposed. Based on the （α, β）-tree concept, a new connected dominating tree with bounded transmission delay problem（CDTT） is defined and a corresponding algorithm is designed to construct a CDT-tree which can trade off limited total power and bounded transmission delay from source to destination nodes. The CDT algorithm consists of two phases： The first phase constructs a maximum independent set（MIS）in a unit disk graph model. The second phase estimates the distance and calculates the transmission power to construct a spanning tree in an undirected graph with different weights for MST and SPF, respectively. The theoretical analysis and simulation results show that the CDT algorithm gives a correct solution to the CDTF problem and forms a virtual backbone with（ α,β）-constraints balancing the requirements of power consumption and transmission delay.展开更多
A channel allocation algorithm based on the maximum independent set is proposed to decrease network conflict and improve network performance. First, a channel allocation model is formulated and a series of the maximum...A channel allocation algorithm based on the maximum independent set is proposed to decrease network conflict and improve network performance. First, a channel allocation model is formulated and a series of the maximum independent sets （MISs） are obtained from a contention graph by the proposed approximation algorithm with low complexity. Then, a weighted contention graph is obtained using the number of contention vertices between two MISs as a weighted value. Links are allocated to channels by the weighted contention graph to minimize conflicts between independent sets. Finally, after channel allocation, each node allocates network interface cards （NICs） to links that are allocated channels according to the queue lengths of NICs. Simulations are conducted to evaluate the proposed algorithm. The results show that the proposed algorithm significantly improves the network throughput and decreases the end to end delay.展开更多
基金Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the project number RI-44-0028.
文摘The sustainability of the Internet of Things(IoT)involves various issues,such as poor connectivity,scalability problems,interoperability issues,and energy inefficiency.Although the Sixth Generation of mobile networks(6G)allows for Ultra-Reliable Low-Latency Communication(URLLC),enhanced Mobile Broadband(eMBB),and massive Machine-Type Communications(mMTC)services,it faces deployment challenges such as the short range of sub-THz and THz frequency bands,low capability to penetrate obstacles,and very high path loss.This paper presents a network architecture to enhance the connectivity of wireless IoT mesh networks that employ both 6G and Wi-Fi technologies.In this architecture,local communications are carried through the mesh network,which uses a virtual backbone to relay packets to local nodes,while remote communications are carried through the 6G network.The virtual backbone is created using a heuristic distributed ConnectedDominating Set(CDS)algorithm.In this algorithm,each node uses information collected from its one-and two-hop neighbors to determine its role and find the set of expansion nodes that are used to select the next CDS nodes.The proposed algorithm has O(n)message and O(K)time complexities,where n is the number of nodes in the network,and K is the depth of the cluster.The study proved that the approximation ratio of the algorithmhas an upper bound of 2.06748(3.4306MCDS+4.8185).Performance evaluations compared the size of the CDS against the theoretical limit and recent CDS clustering algorithms.Results indicate that the proposed algorithm has the smallest average slope for the size of the CDS as the number of nodes increases.
文摘Deep learning attentionmechanisms have achieved remarkable progress in computer vision,but still face limitations when handling images with ambiguous boundaries and uncertain feature representations.Conventional attention modules such as SE-Net,CBAM,ECA-Net,and CA adopt a deterministic paradigm,assigning fixed scalar weights to features without modeling ambiguity or confidence.To overcome these limitations,this paper proposes the Fuzzy Attention Network Layer(FANL),which integrates intuitionistic fuzzy set theory with convolutional neural networks to explicitly represent feature uncertainty through membership(μ),non-membership(ν),and hesitation(π)degrees.FANLconsists of four coremodules:(1)feature dimensionality reduction via global pooling,(2)fuzzymodeling using learnable clustering centers,(3)adaptive attention generation through weighted fusion of fuzzy components,and(4)feature refinement through residual connections.A cross-layer guidance mechanism is further introduced to enhance hierarchical feature propagation,allowing high-level semantic features to incorporate fine-grained texture information from shallow layers.Comprehensive experiments on three benchmark datasets—PathMNIST-30000,full PathMNIST,and Blood MNIST—demonstrate the effectiveness and generalizability of FANL.The model achieves 84.41±0.56%accuracy and a 1.69%improvement over the baseline CNN while maintaining lightweight computational complexity.Ablation studies show that removing any component causes a 1.7%–2.0%performance drop,validating the synergistic contribution of each module.Furthermore,FANL provides superior uncertainty calibration(ECE=0.0452)and interpretable selective prediction under uncertainty.Overall,FANL presents an efficient and uncertaintyaware attention framework that improves both accuracy and reliability,offering a promising direction for robust visual recognition under ambiguous or noisy conditions.
基金Supported by the Technology Project of State Grid Corporation Headquarters(No.5100-202322029A-1-1-ZN)the 2024 Youth Science Foundation Project of China (No.62303006)。
文摘With the large-scale integration of new energy sources,various resources such as energy storage,electric vehicles(EVs),and photovoltaics(PV) have participated in the scheduling of active distribution networks(ADNs),posing new challenges to the operation and scheduling of distribution networks.Aiming at the uncertainty of PV and EV,an optimal scheduling model for ADNs based on multi-scenario fuzzy set based charging station resource forecasting is constructed.To address the scheduling uncertainties caused by PV and load forecasting errors,a day-ahead optimal scheduling model based on conditional value at risk(CVaR) for cost assessment is established,with the optimization objectives of minimizing the operation cost of distribution networks and the risk cost caused by forecasting errors.An improved subtractive optimizer algorithm is proposed to solve the model and formulate day-ahead optimization schemes.Secondly,a forecasting model for dispatchable resources in charging stations is constructed based on event-based fuzzy set theory.On this basis,an intraday scheduling model is built to comprehensively utilize the dispatchable resources of charging stations to coordinate with the output of distributed power sources,achieving optimal scheduling with the goal of minimizing operation costs.Finally,an experimental scenario based on the IEEE-33 node system is designed for simulation verification.The comparison of optimal scheduling results shows that the proposed method can fully exploit the potential scheduling resources of charging stations,improving the operation stability of ADNs and the accommodution capacity of new energy.
文摘The Edikan Mine,which consists of Fobinso and Esuajah gold deposits,lies within the Asankrangwa Gold Belt of the Birimian Supergroup in the Kumasi Basin.The metasedimentary rocks in the Basins and the faulted metavolcanic rocks in the Belts that make up the Birimian Supergroup were intruded by granitoids during the Eburnean Orogeny.This research aims to classify granitoids in the Edikan Mine and ascertain the petrogenetic and geochemical characteristics of some auriferous granitoids in the wider Kumasi Basin,Ghana,to understand the implications for geodynamic settings.A multi-methods approach involving field studies,petrographic studies,and whole-rock geochemical analysis was used to achieve the goal of the study.Petrographic studies revealed a relatively high abundance of plagioclase and a low percentage of K-feldspars(anorthoclase and orthoclase)in the Fobinso samples,suggesting that the samples are granodioritic in nature,while the Esuajah samples showed relatively low plagioclase abundance and a high percentage in K-feldspars,indicating that they are granitic.The granitoids from the study areas are co-magmatic.The granitoids in Esuajah and Fobinso are generally enriched in large ion lithophile elements and light rare earth elements than high field strength elements,middle rare earth elements,and heavy rare earth elements,indicating mixing with crustal sources during the evolution of the granitoids.The granitoids were tectonically formed in a syn-collisional+VAG setting,which implies that they were formed in the subduction zone setting.Fobinso granodiorites showed S-type signatures with evidence of extensive crustal contamination,while the Esuajah granites showed I-type signatures with little or no crustal contamination and are peraluminous.Gold mineralization in the study area is structurally and lithologically controlled with shear zones,faulting,and veining as the principal structures controlling the mineralization.The late-stage vein,V3,in the Edikan Mine is characterized by a low vein angle and is mineralized.
基金Supported by National Natural Science Foundation of China(Grant Nos.52261044,51969001)the Guangxi Provincial Science and Technology Major Project(Grant No.Guike AA23062037)Research Foundation Ability Enhancement Project for Young and Middle Aged Teachers in Guangxi Universities of China(Grant No.2024KY0441)。
文摘Owing to process conditions such as uneven clearance of base metal assembly and welding deformation,it is difficult to obtain well-formed structural welds with robot constant specification parameters welding.Determining how to extract a structured,anti-interference,concise,and dynamic knowledge model from measurable data,and then adjust the welding parameters with corresponding control methods in real time is a central problem to be solved in welding formation control.Hence,this paper proposes a welding penetration control method based on a Neighborhood Rough Set-Adaptive Neuro-Fuzzy Inference System(NRS-ANFIS)to achieve effective penetration control for the GMAW welding process.In orthogonal experiments,the NRS algorithm,which is based on visual sensing to obtain the properties of the weld pool and gap changes,is used to reduce the established frontal weld pool feature information decision table,and the minimum feature set of the weld pool tail width WTand the tail area coefficient CTSis obtained.The minimum feature set of the effective frontal weld pool,real-time line laser distance change,and real-time current information are used as the input for the ANFIS control system.The experimental results for the two groups of time-varying gaps demonstrate that under the condition of no preheating of the base metal,the complete welding penetration rate of the adjusted welding process parameters output by the trained ANFIS model reaches 87%,and the backside melting width is uniform and consistent,which meets the welding specification requirements.
基金supported by the National Natural Science Foundation of China(12471416,12171124,12301567)the Heilongjiang Provincial Natural Science Foundation of China(PL2024F015)+2 种基金the Postdoctoral Science Foundation of Heilongjiang Province of China(LBH-Z22199)the Fundamental Research Foun-dation for Universities of Heilongjiang Province of China(2022-KYYWF-0141)the Alexander von Humboldt Foundation of Germany.
文摘Dear Editor,This letter deals with the distributed recursive set-membership filtering(DRSMF)issue for state-saturated systems under encryption-decryption mechanism.To guarantee the data security,the encryption-decryption mechanism is considered in the signal transmission process.Specifically,a novel DRSMF scheme is developed such that,for both state saturation and encryption-decryption mechanism,the filtering error(FE)is limited to the ellipsoid domain.Then,the filtering error constraint matrix(FECM)is computed and a desirable filter gain is derived by minimizing the FECM.Besides,the bound-edness evaluation of the FECM is provided.
基金Supported by the Natural Science Foundation of Shandong Province (No.ZR2023MA031)the Natural Science Foundation of China (No.12201619)。
文摘Submodular optimization is primarily applied in multi-agent systems for tasks such as resource allocation,task assignment,collaborative decision-making,and optimization problems.Maximization of optimizing submodular set functions attracts much attention since the 1970s.A large body of work has been done using approximation algorithms.When the dimension of the independent variable of the set function changes from one tok,it is called ak-submodular set function.Thek-submodular set function,a generalization of the classical submodular set function,arises in diverse fields with varied applications.In many practical scenarios,quantifying the degree of closeness to submodularity becomes essential,leading to concepts such as approximately submodular set functions and the diminishing-return(DR) ratio.This paper investigates ak-dimensional set function under matroid constraints,which may lack full submodularity.Instead,we focus on an approximately non-ksubmodular set function characterized by its DR ratio.Employing a greedy algorithmic approach,we derive an approximation guarantee for this problem.Notably,when the DR ratio is set to one,our results align with existing findings in the literature.Experimental results demonstrate the superiority of our algorithm over the baselines.
文摘Circumlunar abort trajectories constitute a vital contingency return strategy during the translunar phase of crewed lunar missions.This paper proposes a methodology for constructing the solution set of the circumlunar abort trajectory and leverages its advantageous properties to address the optimization design problem of abort trajectories.Initially,a solution set of all feasible abort trajectories,originating from an abort point on the nominal trajectory and complying with fundamental reentry constraints,is formulated through the introduction of two novel design parameters.Subsequently,the geometric characteristics of the solution set,as well as the distributional properties of key iterative constraint responses,including flight time and velocity increment,are analyzed.Finally,the characteristics exhibited in the solution set are employed to directly identify the design parameters of the abort trajectories with minimum flight time and velocity increment,thereby providing solutions to two distinct types of optimization problems.The simulation results for a variety of nominal trajectories,encompassing the reconstruction and redesign of the Apollo13 abort trajectory,validate the proposed method,demonstrating its ability to directly generate optimal abort trajectories.The method proposed in this paper investigates feasible abort trajectories from a global perspective,providing both a framework and convenience for mission planning and iterative optimization in abort trajectory design.
基金supported by Fujian Provincial Natural Science Foundation of China(2024J02022)the NSFC(11571158)+1 种基金supported by the NSFC(12071199)supported by the Young and middle-aged project in Fujian Province(JAT190397)。
文摘A discrete subset S of a topological gyrogroup G with the identity 0 is said to be a suitable set for G if it generates a dense subgyrogroup of G and S∪{0}is closed in G.In this paper,it is proved that each countable Hausdorff topological gyrogroup has a suitable set;moreover,it is shown that each separable metrizable strongly topological gyrogroup has a suitable set.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF),funded by the Ministry of Education(RS-2023-00248378 and NRF-2020R1A6A1A03043708).
文摘Objectives:Tamoxifen is a key drug that provides endocrine therapy for estrogen receptor(ER)α-positive breast cancer;however,resistance remains a significant clinical challenge.This study aims to investigate the molecular mechanisms of tamoxifen resistance in ERα-positive breast cancer,with particular focus on the role of SET Domain Containing 1A(SETD1A)-driven forkhead box A2(FOXA2)as a key regulator of this resistance.Methods:FOXA2 expression and its regulation by SETD1A were assessed via(quantitative polymerase chain reaction),western blotting,transcriptome profiling,and chromatin immunoprecipitation analyses.The effects of FOXA2 on cell proliferation,migration,invasion,and cancer stem cell traits were evaluated using small interfering RNA(siRNA)-mediated silencing.Clinical relevance was examined by analyzing patient datasets and tumor tissue microarrays.Results:FOXA2 expression was significantly elevated in tamoxifen-resistant(TamR)and ERα-negative breast cancer cells compared to that in ERα-positive MCF-7 cells,regardless of tamoxifen treatment or ERαdepletion.Transcriptome and chromatin immunoprecipitation analyses revealed that SETD1A,a histone methyltransferase,directly regulated FOXA2 expression.Functionally,FOXA2 knockdown inhibited the proliferation,migration,invasion,and cancer stem cell properties of TamR cells while restoring tamoxifen sensitivity.High FOXA2 expression was correlated with poor survival and reduced responsiveness to tamoxifen in patients with ER-positive breast cancer.Conclusion:Our findings identified FOXA2 as a key mediator of tamoxifen resistance regulated by SETD1A and suggested that targeting the SETD1A-FOXA2 axis may offer a novel strategy for overcoming endocrine resistance in breast cancer.
基金supported by the National Natural Science Foundation(42472325)the Fundamental Research Funds of Chinese Academy of Geological Science(SK202103).
文摘To elucidate the geographical differentiation characteristics and driving mechanisms of Dissolved Organic Matter(DOM)in typical rivers,this study conducted a multi-spectral investigation on three representative river types within Shandong Province:The mountainous Dawen River,the plain Tuhai River,and the artificial East Grand Canal.The DOM composition was analyzed using Ultraviolet-Visible(UV-Vis)absorption spectroscopy,Excitation-Emission Matrix(EEM)fluorescence spectroscopy,and parallel factor analysis(PARAFAC),while Principal Component Analysis(PCA)was employed to quantify the synergistic effects of natural processes and anthropogenic activities.Results revealed significant spatial heterogeneity in DOM composition and sources.The plain river exhibited the highest aromaticity(humic-like components:43.3%)due to long-term agricultural non-point source inputs and urban wastewater discharge.The mountain stream,shaped by complex terrain and relatively intact ecosystems,was dominated by autochthonous DOM derived from microbial metabolism,with higher Fluorescence Index(FI=2.12)and biological index(BIX=1.35)than other river types.The artificial canal retained protein-like components(64.2%),largely attributed to winter hydrological stagnation and disturbances from shipping activities.Further analysis demonstrated that geographical settings(e.g.,mountain terrain)and anthropogenic activities(e.g.,agriculture,shipping)jointly regulated DOM composition by altering the balance between input and transformation processes.Integrated fluorescence parameters and PCA results suggested differentiated management strategies:protecting ecological integrity in mountain streams to sustain selfpurification,enhancing non-point source interception in plain rivers,and mitigating shipping pollution in canals.This study systematically reveals the natural-anthropogenic coupling mechanisms driving DOM dynamics in northern China rivers,providing critical insights for precision water environment management at the watershed scale.
文摘The quality of cardiopulmonary resuscitation(CPR) significantly influences survival and neurological outcomes in patients with cardiac arrest(CA).Although mechanical chest compression devices and extracorporeal cardiopulmonary resuscitation(ECPR) have demonstrated some benefits,high-quality manual CPR remained the essential first step,particularly in resource-limited settings.In this study,we examined whether opportunities existed to improve manual CPR performance using preliminary data from our recent survey conducted in a province in western China.We aim to emphasize the importance of improving manual CPR quality before implementing advanced interventions.
基金The National Natural Science Foundation of China(No.60503020,60373066,60403016,60425206),the Natural Science Foundation of Jiangsu Higher Education Institutions ( No.04KJB520096),the Doctoral Foundation of Nanjing University of Posts and Telecommunication (No.0302).
文摘A rough set based corner classification neural network, the Rough-CC4, is presented to solve document classification problems such as document representation of different document sizes, document feature selection and document feature encoding. In the Rough-CC4, the documents are described by the equivalent classes of the approximate words. By this method, the dimensions representing the documents can be reduced, which can solve the precision problems caused by the different document sizes and also blur the differences caused by the approximate words. In the Rough-CC4, a binary encoding method is introduced, through which the importance of documents relative to each equivalent class is encoded. By this encoding method, the precision of the Rough-CC4 is improved greatly and the space complexity of the Rough-CC4 is reduced. The Rough-CC4 can be used in automatic classification of documents.
基金Major Program of the National Natural Science Foundation of China (No.70533050)High Technology Research Program ofJiangsu Province(No.BG2007012)+1 种基金China Postdoctoral Science Foundation(No.20070411065)Science Foundation of China University of Mining andTechnology(No.OC080303)
文摘To cope with the constraint problem of power consumption and transmission delay in the virtual backbone of wireless sensor network, a distributed connected dominating set （CDS） algorithm with （α,β）-constraints is proposed. Based on the （α, β）-tree concept, a new connected dominating tree with bounded transmission delay problem（CDTT） is defined and a corresponding algorithm is designed to construct a CDT-tree which can trade off limited total power and bounded transmission delay from source to destination nodes. The CDT algorithm consists of two phases： The first phase constructs a maximum independent set（MIS）in a unit disk graph model. The second phase estimates the distance and calculates the transmission power to construct a spanning tree in an undirected graph with different weights for MST and SPF, respectively. The theoretical analysis and simulation results show that the CDT algorithm gives a correct solution to the CDTF problem and forms a virtual backbone with（ α,β）-constraints balancing the requirements of power consumption and transmission delay.
基金The National High Technology Research and Development Program of China(863 Program)(No.2013AA013601)Prospective Research Project on Future Netw orks of Jiangsu Future Netw orks Innovation Institute(No.BY2013095-1-18)
文摘A channel allocation algorithm based on the maximum independent set is proposed to decrease network conflict and improve network performance. First, a channel allocation model is formulated and a series of the maximum independent sets （MISs） are obtained from a contention graph by the proposed approximation algorithm with low complexity. Then, a weighted contention graph is obtained using the number of contention vertices between two MISs as a weighted value. Links are allocated to channels by the weighted contention graph to minimize conflicts between independent sets. Finally, after channel allocation, each node allocates network interface cards （NICs） to links that are allocated channels according to the queue lengths of NICs. Simulations are conducted to evaluate the proposed algorithm. The results show that the proposed algorithm significantly improves the network throughput and decreases the end to end delay.
