Accurate fine-grained geospatial scene classification using remote sensing imagery is essential for a wide range of applications.However,existing approaches often rely on manually zooming remote sensing images at diff...Accurate fine-grained geospatial scene classification using remote sensing imagery is essential for a wide range of applications.However,existing approaches often rely on manually zooming remote sensing images at different scales to create typical scene samples.This approach fails to adequately support the fixed-resolution image interpretation requirements in real-world scenarios.To address this limitation,we introduce the million-scale fine-grained geospatial scene classification dataset(MEET),which contains over 1.03 million zoom-free remote sensing scene samples,manually annotated into 80 fine-grained categories.In MEET,each scene sample follows a scene-in-scene layout,where the central scene serves as the reference,and auxiliary scenes provide crucial spatial context for fine-grained classification.Moreover,to tackle the emerging challenge of scene-in-scene classification,we present the context-aware transformer(CAT),a model specifically designed for this task,which adaptively fuses spatial context to accurately classify the scene samples.CAT adaptively fuses spatial context to accurately classify the scene samples by learning attentional features that capture the relationships between the center and auxiliary scenes.Based on MEET,we establish a comprehensive benchmark for fine-grained geospatial scene classification,evaluating CAT against 11 competitive baselines.The results demonstrate that CAT significantly outperforms these baselines,achieving a 1.88%higher balanced accuracy(BA)with the Swin-Large backbone,and a notable 7.87%improvement with the Swin-Huge backbone.Further experiments validate the effectiveness of each module in CAT and show the practical applicability of CAT in the urban functional zone mapping.The source code and dataset will be publicly available at https://jerrywyn.github.io/project/MEET.html.展开更多
With the application of the articulated phase insulator, and the speed of electric locomotive rising, it is inevitable for the electric locomotive to adopt the technology automatic passing through the electric phase s...With the application of the articulated phase insulator, and the speed of electric locomotive rising, it is inevitable for the electric locomotive to adopt the technology automatic passing through the electric phase separation. However, when the locomotive passes the electric phase separation, a variety of overvoltages will be generated, such as the cut-off overvoltage and the closing overvoltage. In this paper, the causes of the two overvoltages above are analyzed theoretically and simulated in Simulink. Then this paper discusses the suppression effects on the cut-off overvoltage and the closing overvoltage by paralleling the nonlinear resistance and the main breaker, or parallelling the nonlinear resistance and the locomotive transformer. The simulation results show that parallelling the nonlinear resistance and the locomotive transformer has suppressive effects on the two overvoltages mentioned above.展开更多
Biphasic dynamics,the variable-dependent ability to enhance or restrain biological function,is prevalent in natural systems.Accompanied by biphasic dynamics,necroptosis signaling also appears emergent and coexistent d...Biphasic dynamics,the variable-dependent ability to enhance or restrain biological function,is prevalent in natural systems.Accompanied by biphasic dynamics,necroptosis signaling also appears emergent and coexistent dynamics.However,it remains elusive how the properties of these dynamics are characterized by specific circuit structures and components.Starting with necroptosis circuit modeling,we systematically analyzed the network topology for achieving RIP1-dependent biphasic,emergent,and coexistent(BEC)dynamics.RIP1-RIP3-Caspase-8(C8)incoherent feedforward loop embedded with positive feedback of RIP3 to RIP1 is identified as the core topology.The peak value of RIP3 phosphorylation is determined to present a scale-invariant feature,dictating BEC dynamics and the bell-shaped regulation of necroptosis biphasic dynamics.To quantitatively determine the uncertainty of necroptosis coexistent dynamics,potential landscape and Shannon entropy that measure entropy production during cell death are introduced for the first time.Further random necroptosis circuit analysis identifies the bell-shaped regulation of necroptosis biphasic dynamics by RIP3 auto-phosphorylation,which acts as a complementary process for robustly attaining BEC dynamics.Finally,we searched all possible two-and three-node circuit topologies to screen those that could perform BEC dynamics.A complete atlas of three-node circuit BEC dynamics is generated and only three minimal circuits emerge as robust solutions,confirming incoherent feedforward loop is the core topology.Analysis of the association between the minimal circuit structure and robustness proves that the identified optimal functional achievement structure is highly consistent with the experimental observed RIP1-RIP3-C8 topology.Overall,through highlighting a finite set of circuits,this study yields guiding principles that enable the mapping,modulation,and design of circuits for BEC dynamics in diverse synthetic biology applications.展开更多
By optimizing the Debye temperature,we identified two extremely efficient phosphors based on the S-P transition of Bi^(3+).The quantum yields of Sr_(0.99)Ga_(1.50)B_(2)O_(7):0.01Bi^(3+),0.50Al^(3+)and Ba_(0.995)Ga_(1....By optimizing the Debye temperature,we identified two extremely efficient phosphors based on the S-P transition of Bi^(3+).The quantum yields of Sr_(0.99)Ga_(1.50)B_(2)O_(7):0.01Bi^(3+),0.50Al^(3+)and Ba_(0.995)Ga_(1.60)B_(2)O_(7):0.005Bi^(3+),0.40Al^(3+)phosphors reach 96%and 99%,respectively.Moreover,Sr_(0.99)Ga_(1.50)B_(2)O_(7):0.01Bi^(3+),0.50Al^(3+)exhibits negative thermal quenching,which shows unique advantages for practical application.The blue phosphors with quantum efficiencies close to unity and superior thermal stability can be competitive candidates for practical applications.展开更多
基金supported by the National Natural Science Foundation of China(42030102,42371321).
文摘Accurate fine-grained geospatial scene classification using remote sensing imagery is essential for a wide range of applications.However,existing approaches often rely on manually zooming remote sensing images at different scales to create typical scene samples.This approach fails to adequately support the fixed-resolution image interpretation requirements in real-world scenarios.To address this limitation,we introduce the million-scale fine-grained geospatial scene classification dataset(MEET),which contains over 1.03 million zoom-free remote sensing scene samples,manually annotated into 80 fine-grained categories.In MEET,each scene sample follows a scene-in-scene layout,where the central scene serves as the reference,and auxiliary scenes provide crucial spatial context for fine-grained classification.Moreover,to tackle the emerging challenge of scene-in-scene classification,we present the context-aware transformer(CAT),a model specifically designed for this task,which adaptively fuses spatial context to accurately classify the scene samples.CAT adaptively fuses spatial context to accurately classify the scene samples by learning attentional features that capture the relationships between the center and auxiliary scenes.Based on MEET,we establish a comprehensive benchmark for fine-grained geospatial scene classification,evaluating CAT against 11 competitive baselines.The results demonstrate that CAT significantly outperforms these baselines,achieving a 1.88%higher balanced accuracy(BA)with the Swin-Large backbone,and a notable 7.87%improvement with the Swin-Huge backbone.Further experiments validate the effectiveness of each module in CAT and show the practical applicability of CAT in the urban functional zone mapping.The source code and dataset will be publicly available at https://jerrywyn.github.io/project/MEET.html.
文摘With the application of the articulated phase insulator, and the speed of electric locomotive rising, it is inevitable for the electric locomotive to adopt the technology automatic passing through the electric phase separation. However, when the locomotive passes the electric phase separation, a variety of overvoltages will be generated, such as the cut-off overvoltage and the closing overvoltage. In this paper, the causes of the two overvoltages above are analyzed theoretically and simulated in Simulink. Then this paper discusses the suppression effects on the cut-off overvoltage and the closing overvoltage by paralleling the nonlinear resistance and the main breaker, or parallelling the nonlinear resistance and the locomotive transformer. The simulation results show that parallelling the nonlinear resistance and the locomotive transformer has suppressive effects on the two overvoltages mentioned above.
基金supported by the National Natural Science Foundation of China(12090052)the Ministry of Science and Technology of the People’s Republic of China(STI2030-Major Projects 2021ZD0201900)+1 种基金the Natural Science Foundation of Fujian Province of China(2023J05002)the Fundamental Research funds for the Central Universities(20720230017).
文摘Biphasic dynamics,the variable-dependent ability to enhance or restrain biological function,is prevalent in natural systems.Accompanied by biphasic dynamics,necroptosis signaling also appears emergent and coexistent dynamics.However,it remains elusive how the properties of these dynamics are characterized by specific circuit structures and components.Starting with necroptosis circuit modeling,we systematically analyzed the network topology for achieving RIP1-dependent biphasic,emergent,and coexistent(BEC)dynamics.RIP1-RIP3-Caspase-8(C8)incoherent feedforward loop embedded with positive feedback of RIP3 to RIP1 is identified as the core topology.The peak value of RIP3 phosphorylation is determined to present a scale-invariant feature,dictating BEC dynamics and the bell-shaped regulation of necroptosis biphasic dynamics.To quantitatively determine the uncertainty of necroptosis coexistent dynamics,potential landscape and Shannon entropy that measure entropy production during cell death are introduced for the first time.Further random necroptosis circuit analysis identifies the bell-shaped regulation of necroptosis biphasic dynamics by RIP3 auto-phosphorylation,which acts as a complementary process for robustly attaining BEC dynamics.Finally,we searched all possible two-and three-node circuit topologies to screen those that could perform BEC dynamics.A complete atlas of three-node circuit BEC dynamics is generated and only three minimal circuits emerge as robust solutions,confirming incoherent feedforward loop is the core topology.Analysis of the association between the minimal circuit structure and robustness proves that the identified optimal functional achievement structure is highly consistent with the experimental observed RIP1-RIP3-C8 topology.Overall,through highlighting a finite set of circuits,this study yields guiding principles that enable the mapping,modulation,and design of circuits for BEC dynamics in diverse synthetic biology applications.
基金supported by the Key Laboratory for Green Chemical Process of Ministry of Education,Wuhan Institute of Technology,via grant GCP20190201。
文摘By optimizing the Debye temperature,we identified two extremely efficient phosphors based on the S-P transition of Bi^(3+).The quantum yields of Sr_(0.99)Ga_(1.50)B_(2)O_(7):0.01Bi^(3+),0.50Al^(3+)and Ba_(0.995)Ga_(1.60)B_(2)O_(7):0.005Bi^(3+),0.40Al^(3+)phosphors reach 96%and 99%,respectively.Moreover,Sr_(0.99)Ga_(1.50)B_(2)O_(7):0.01Bi^(3+),0.50Al^(3+)exhibits negative thermal quenching,which shows unique advantages for practical application.The blue phosphors with quantum efficiencies close to unity and superior thermal stability can be competitive candidates for practical applications.
