With the help of pre-trained language models,the accuracy of the entity linking task has made great strides in recent years.However,most models with excellent performance require fine-tuning on a large amount of train...With the help of pre-trained language models,the accuracy of the entity linking task has made great strides in recent years.However,most models with excellent performance require fine-tuning on a large amount of training data using large pre-trained language models,which is a hardware threshold to accomplish this task.Some researchers have achieved competitive results with less training data through ingenious methods,such as utilizing information provided by the named entity recognition model.This paper presents a novel semantic-enhancement-based entity linking approach,named semantically enhanced hardware-friendly entity linking(SHEL),which is designed to be hardware friendly and efficient while maintaining good performance.Specifically,SHEL's semantic enhancement approach consists of three aspects:(1)semantic compression of entity descriptions using a text summarization model;(2)maximizing the capture of mention contexts using asymmetric heuristics;(3)calculating a fixed size mention representation through pooling operations.These series of semantic enhancement methods effectively improve the model's ability to capture semantic information while taking into account the hardware constraints,and significantly improve the model's convergence speed by more than 50%compared with the strong baseline model proposed in this paper.In terms of performance,SHEL is comparable to the previous method,with superior performance on six well-established datasets,even though SHEL is trained using a smaller pre-trained language model as the encoder.展开更多
Sleep spindle is the characteristic waveform of electroencephalogram (EEG) which is important for clinical diagnosis. In this study, an automatic sleep spindle detection method was developed. The EEG signals were reco...Sleep spindle is the characteristic waveform of electroencephalogram (EEG) which is important for clinical diagnosis. In this study, an automatic sleep spindle detection method was developed. The EEG signals were recorded based on the standard polysomnogram (PSG) measurement. A preprocessing procedure is introduced to exclude the unnecessary data segments and normalized the necessary data segments. Complex demodulation method is adopted to detect the candidate sleep spindle waveforms and calculate the features. The sleep spindles are recognized based on a decision tree model. Finally, the detected sleep spindles were utilized to amend the sleep stage recognition results. The sleep EEG data from 3 patients with sleep disorders were analyzed. The obtained results showed that the detected sleep spindles in EEG signal improved the accuracy of sleep stage recognition.展开更多
The Covid-19 epidemic is an emerging infectious disease of the viral zoonosis type caused by the coronavirus strain SARS-CoV-2, it is classified as a human-to-human communicable disease and is currently a pandemic wor...The Covid-19 epidemic is an emerging infectious disease of the viral zoonosis type caused by the coronavirus strain SARS-CoV-2, it is classified as a human-to-human communicable disease and is currently a pandemic worldwide. In this paper, we propose conceptual mathematical models of the epidemic dynamics of four compartments. We have collected data from the Djibouti health ministry. We study the positivity, boundedness, existence and uniqueness of the weak solution. Next, we define the Basic reproduction number by the method of the DFE and EEP. Then, we study the local and global stability and the bifurcation analysis of equilibrium to examine its epidemiological relevance. Finally, we analyze the fit of the data in comparison with the result of our mathematical results, to validate the model and estimate the important model parameters and prediction about the disease. We consider the real cases of Djibouti from 15th March to 15th May 2021.展开更多
Objectives: Monocytes/macrophages accumulate in the synovial membrane in rheumatoid arthritis and play a key role in disease pathogenesis, contributing to inflammation, cartilage destruction and bone erosion. Identifi...Objectives: Monocytes/macrophages accumulate in the synovial membrane in rheumatoid arthritis and play a key role in disease pathogenesis, contributing to inflammation, cartilage destruction and bone erosion. Identification of molecules involved in monocyte/macrophage recruitment in inflammation is crucial for development of therapeutic interventions. Chemokine receptor CCR9 is up-regulated on these cells in peripheral blood and synovium of rheumatoid patients. This study investigated the course of antigen-induced arthritis in CCR9 deficient C57BL/6 mice in comparison to wild type animals to determine whether CCR9 is critical for disease severity and progression. Methods: Methylated bovine serum albumin was used for induction of uni-lateral arthritis by direct injection into the knee joints of preimmunized animals. Arthritis is confined to the injected joint allowing comparison with the normal opposing joint. Clinical severity of arthritis was assessed by measuring swelling in the arthritic joint in comparison to the normal joint. Histological analysis was performed to assess the extent of leukocyte infiltration and cartilage depletion. Results: Levels of swelling were not significantly different between wild type and CCR9 deficient mice. Similarly there was no significant difference in histological severity of arthritis when comparing CCR9-deficient mice to wild type mice. Conclusions: CCR9 was not required for development of synovial inflammation and cartilage destruction in the anti-gen-induced model of arthritis in C57BL/6 mice in this study. This may reflect a true lack of a pathogenic role of CCR9 on monocyte/macrophage function in vivo or it may reflect differences in the current antigen-induced arthritis model when compared to human RA.展开更多
The state of the physics of convective clouds and cloud seeding is discussed briefly. It is noted that at the present time there is a transition from the stage of investigation of “elementary” processes in the cloud...The state of the physics of convective clouds and cloud seeding is discussed briefly. It is noted that at the present time there is a transition from the stage of investigation of “elementary” processes in the clouds to the stage of studying the formation of macro- and microstructural characteristics of clouds as a whole, taking into account their system properties. The main directions of the development of cloud physics at the upcoming stage of its development are discussed. The paper points out that one of these areas is the determination of the structure-forming factors for the clouds and the study of their influence on their formation and evolution. It is noted that one of such factors is the interaction of clouds with their surrounding atmosphere, and the main method of studying its role in the processes of cloud formation is mathematical modeling. A three-dimensional nonstationary model of convective clouds is presented with a detailed account of the processes of thermohydrodynamics and microphysics, which is used for research. The results of modeling the influence of the wind field structure in the atmosphere on the formation and evolution of clouds are presented. It is shown that the dynamic characteristics of the atmosphere have a significant effect on the formation of macro- and microstructural characteristics of convective clouds: the more complex the structure of the wind field in the atmosphere (i.e., the more intense the interaction of the atmosphere and the cloud), the less powerful the clouds are formed.展开更多
This paper studies the part picking operations of a ut omated warehouse. It assumed the demand of picking orders of automated warehouse are dynamic generated. Once the picking orders of certain period of time are kn o...This paper studies the part picking operations of a ut omated warehouse. It assumed the demand of picking orders of automated warehouse are dynamic generated. Once the picking orders of certain period of time are kn own, it is necessary to decide an efficient order picking sequence and routing t o minimize the total travel distance to complete those orders. Assumed there are n i items to be picked in order O i. Each item in the picking ord er is located in different locations in the warehouse. Since it is possible the same items appear in the different picking orders, it will reduce the picking di stance if these orders can be batched and picked in one path. However, there are several constraints for the order batching and order picking operations. These constraint are (1) the crane of the automated warehouse has the carrying capacit y of C, and (2) for the management convenience, it is assumed that one picki ng order must be completed in one path. Because of the complexity of problem, it is inefficient to solve the problem by analytical approach. Although the heuristic method can significantly reduce of the computation time, the quality of the solution is always unacceptable. It is the intention of this paper to integrate the advantages of neural network and simulated annealing technique to develop the control mechanism for the planning of order picking operations of automated warehouse. A systematic computational simulation is conducted to evaluate the proposed method. The results show the pr oposed method can generate superior solution in most cased.展开更多
The purpose of this research is to define initial parameters of Khyargas Lake-Zavkhan River and its catchment area using satellite images. The study has been done by two datasets: 1) Shuttle Radar Topography Mission (...The purpose of this research is to define initial parameters of Khyargas Lake-Zavkhan River and its catchment area using satellite images. The study has been done by two datasets: 1) Shuttle Radar Topography Mission (SRTM) at a horizontal spatial resolution of 90 meters, 2) The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) at a horizontal spatial resolution of 30 meters, using two different models of ArcHydro and Integrated Land and Water Information System (ILWIS) softwares. Main methods of models, that were used in this research are the Deterministic-8, the steepest slope, the spread, the seek computations and the trace analysis. Moreover, input data of the modeling are digital elevation model (DEM) and lake position, outlet location of the river. DEM based ArcHydro model was run on the both datasets, and ILWIS model was run on SRTM data. Several intermediate results were produced while the models run, and initial parameters of the Zavkhan River, its catchment area have been defined at the end of the model. Moreover, final results of the models were compared with each other and with the result of previous research, and with the reality. The result of this study can be used in baseline and advanced research on the catchment area. Besides of that, the result can define a spatial boundary of study on Zavkhan River and its catchment area. Moreover, it would have support for decision-making on ground and surface water resource, distribution and management. Further research, which will cover the entire territory of Mongolia, has to be done using same methodology. The 332nd decision on “River catchment areas of Mongolia” of the Minister of Nature, Environment and Tourism in 2009 has to renew, if a result of that study would be accepted from vocational organization and experts.展开更多
基金the Beijing Municipal Science and Technology Program(Z231100001323004)。
文摘With the help of pre-trained language models,the accuracy of the entity linking task has made great strides in recent years.However,most models with excellent performance require fine-tuning on a large amount of training data using large pre-trained language models,which is a hardware threshold to accomplish this task.Some researchers have achieved competitive results with less training data through ingenious methods,such as utilizing information provided by the named entity recognition model.This paper presents a novel semantic-enhancement-based entity linking approach,named semantically enhanced hardware-friendly entity linking(SHEL),which is designed to be hardware friendly and efficient while maintaining good performance.Specifically,SHEL's semantic enhancement approach consists of three aspects:(1)semantic compression of entity descriptions using a text summarization model;(2)maximizing the capture of mention contexts using asymmetric heuristics;(3)calculating a fixed size mention representation through pooling operations.These series of semantic enhancement methods effectively improve the model's ability to capture semantic information while taking into account the hardware constraints,and significantly improve the model's convergence speed by more than 50%compared with the strong baseline model proposed in this paper.In terms of performance,SHEL is comparable to the previous method,with superior performance on six well-established datasets,even though SHEL is trained using a smaller pre-trained language model as the encoder.
文摘Sleep spindle is the characteristic waveform of electroencephalogram (EEG) which is important for clinical diagnosis. In this study, an automatic sleep spindle detection method was developed. The EEG signals were recorded based on the standard polysomnogram (PSG) measurement. A preprocessing procedure is introduced to exclude the unnecessary data segments and normalized the necessary data segments. Complex demodulation method is adopted to detect the candidate sleep spindle waveforms and calculate the features. The sleep spindles are recognized based on a decision tree model. Finally, the detected sleep spindles were utilized to amend the sleep stage recognition results. The sleep EEG data from 3 patients with sleep disorders were analyzed. The obtained results showed that the detected sleep spindles in EEG signal improved the accuracy of sleep stage recognition.
文摘The Covid-19 epidemic is an emerging infectious disease of the viral zoonosis type caused by the coronavirus strain SARS-CoV-2, it is classified as a human-to-human communicable disease and is currently a pandemic worldwide. In this paper, we propose conceptual mathematical models of the epidemic dynamics of four compartments. We have collected data from the Djibouti health ministry. We study the positivity, boundedness, existence and uniqueness of the weak solution. Next, we define the Basic reproduction number by the method of the DFE and EEP. Then, we study the local and global stability and the bifurcation analysis of equilibrium to examine its epidemiological relevance. Finally, we analyze the fit of the data in comparison with the result of our mathematical results, to validate the model and estimate the important model parameters and prediction about the disease. We consider the real cases of Djibouti from 15th March to 15th May 2021.
文摘Objectives: Monocytes/macrophages accumulate in the synovial membrane in rheumatoid arthritis and play a key role in disease pathogenesis, contributing to inflammation, cartilage destruction and bone erosion. Identification of molecules involved in monocyte/macrophage recruitment in inflammation is crucial for development of therapeutic interventions. Chemokine receptor CCR9 is up-regulated on these cells in peripheral blood and synovium of rheumatoid patients. This study investigated the course of antigen-induced arthritis in CCR9 deficient C57BL/6 mice in comparison to wild type animals to determine whether CCR9 is critical for disease severity and progression. Methods: Methylated bovine serum albumin was used for induction of uni-lateral arthritis by direct injection into the knee joints of preimmunized animals. Arthritis is confined to the injected joint allowing comparison with the normal opposing joint. Clinical severity of arthritis was assessed by measuring swelling in the arthritic joint in comparison to the normal joint. Histological analysis was performed to assess the extent of leukocyte infiltration and cartilage depletion. Results: Levels of swelling were not significantly different between wild type and CCR9 deficient mice. Similarly there was no significant difference in histological severity of arthritis when comparing CCR9-deficient mice to wild type mice. Conclusions: CCR9 was not required for development of synovial inflammation and cartilage destruction in the anti-gen-induced model of arthritis in C57BL/6 mice in this study. This may reflect a true lack of a pathogenic role of CCR9 on monocyte/macrophage function in vivo or it may reflect differences in the current antigen-induced arthritis model when compared to human RA.
文摘The state of the physics of convective clouds and cloud seeding is discussed briefly. It is noted that at the present time there is a transition from the stage of investigation of “elementary” processes in the clouds to the stage of studying the formation of macro- and microstructural characteristics of clouds as a whole, taking into account their system properties. The main directions of the development of cloud physics at the upcoming stage of its development are discussed. The paper points out that one of these areas is the determination of the structure-forming factors for the clouds and the study of their influence on their formation and evolution. It is noted that one of such factors is the interaction of clouds with their surrounding atmosphere, and the main method of studying its role in the processes of cloud formation is mathematical modeling. A three-dimensional nonstationary model of convective clouds is presented with a detailed account of the processes of thermohydrodynamics and microphysics, which is used for research. The results of modeling the influence of the wind field structure in the atmosphere on the formation and evolution of clouds are presented. It is shown that the dynamic characteristics of the atmosphere have a significant effect on the formation of macro- and microstructural characteristics of convective clouds: the more complex the structure of the wind field in the atmosphere (i.e., the more intense the interaction of the atmosphere and the cloud), the less powerful the clouds are formed.
文摘This paper studies the part picking operations of a ut omated warehouse. It assumed the demand of picking orders of automated warehouse are dynamic generated. Once the picking orders of certain period of time are kn own, it is necessary to decide an efficient order picking sequence and routing t o minimize the total travel distance to complete those orders. Assumed there are n i items to be picked in order O i. Each item in the picking ord er is located in different locations in the warehouse. Since it is possible the same items appear in the different picking orders, it will reduce the picking di stance if these orders can be batched and picked in one path. However, there are several constraints for the order batching and order picking operations. These constraint are (1) the crane of the automated warehouse has the carrying capacit y of C, and (2) for the management convenience, it is assumed that one picki ng order must be completed in one path. Because of the complexity of problem, it is inefficient to solve the problem by analytical approach. Although the heuristic method can significantly reduce of the computation time, the quality of the solution is always unacceptable. It is the intention of this paper to integrate the advantages of neural network and simulated annealing technique to develop the control mechanism for the planning of order picking operations of automated warehouse. A systematic computational simulation is conducted to evaluate the proposed method. The results show the pr oposed method can generate superior solution in most cased.
文摘The purpose of this research is to define initial parameters of Khyargas Lake-Zavkhan River and its catchment area using satellite images. The study has been done by two datasets: 1) Shuttle Radar Topography Mission (SRTM) at a horizontal spatial resolution of 90 meters, 2) The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) at a horizontal spatial resolution of 30 meters, using two different models of ArcHydro and Integrated Land and Water Information System (ILWIS) softwares. Main methods of models, that were used in this research are the Deterministic-8, the steepest slope, the spread, the seek computations and the trace analysis. Moreover, input data of the modeling are digital elevation model (DEM) and lake position, outlet location of the river. DEM based ArcHydro model was run on the both datasets, and ILWIS model was run on SRTM data. Several intermediate results were produced while the models run, and initial parameters of the Zavkhan River, its catchment area have been defined at the end of the model. Moreover, final results of the models were compared with each other and with the result of previous research, and with the reality. The result of this study can be used in baseline and advanced research on the catchment area. Besides of that, the result can define a spatial boundary of study on Zavkhan River and its catchment area. Moreover, it would have support for decision-making on ground and surface water resource, distribution and management. Further research, which will cover the entire territory of Mongolia, has to be done using same methodology. The 332nd decision on “River catchment areas of Mongolia” of the Minister of Nature, Environment and Tourism in 2009 has to renew, if a result of that study would be accepted from vocational organization and experts.
