Background: At present, in clinical practice, patients with primary hyperaldosteronism (PA) are mainly treated by surgery or medical drugs (spironolactone/spironolactone, epridone, etc.). Some studies show that the le...Background: At present, in clinical practice, patients with primary hyperaldosteronism (PA) are mainly treated by surgery or medical drugs (spironolactone/spironolactone, epridone, etc.). Some studies show that the left ventricular hypertrophy of patients can be significantly improved after treatment. However, at present, the relevant research is very limited, and there is still controversy on the improvement of cardiac structure and function between the two treatment methods. No reliable conclusions have been drawn. Objective: We conducted this meta-analysis to compare the improvement of cardiac structure of patients after surgical treatment and drug treatment, so as to clarify the efficacy of surgical treatment and drug treatment for PA patients. Methods: In order to examine the cardiac color ultrasound data of PA patients receiving surgical treatment and drug therapy (spironolactone, antisterone), randomized or observational studies were searched through Pubmed, Cochrane Library, and Embase. Meta-analysis was then carried out on the comprehensive and individual outcomes. The ROINBS-I scale is utilized to assess the offset risk of study inclusion. Outcomes: A total of nine studies involving 799 patients with PA into meta analysis, according to the results of the surgery in the treatment of patients with PA, left ventricular mass index (LVMI) changes in value (drop range) is significantly higher than drug therapy (Mean difference IV: —2.32, P In 6 studies, after surgical treatment of interventricular septal thickness (IVSD), changes in value (drop range) are also higher than drug therapy (Mean difference IV: —0.35, P In 2 studies, the surgical treatment of plasma aldosterone concentration (PAC) drop degree is superior to drug therapy (Mean difference IV: —12.63, P < 0.05), and blood pressure to improve the degree of surgery and drug treatment has no obvious difference. Conclusions: This meta-analysis result confirmed that after medical and surgical treatment of PA can obviously improve the patient’s blood pressure, and no difference between the two treatments. But for the heart structure improvement, including left ventricular hypertrophy and interventricular septum thickness, surgical treatment effect is significantly better than the medicine treatment, so the adrenalectomy can be used as unilateral PA optimal choice of treatment.展开更多
Bus bunching has been a persistent issue in urban bus system since it first appeared,and it remains a challenge not fully resolved.This phenomenon may reduce the operational efficiency of the urban bus system,which is...Bus bunching has been a persistent issue in urban bus system since it first appeared,and it remains a challenge not fully resolved.This phenomenon may reduce the operational efficiency of the urban bus system,which is detrimental to the operation of fast-paced public transport in cities.Fortunately,extensive research has been undertaken in the long development and optimization of the urban bus system,and many solutions have emerged so far.The purpose of this paper is to summarize the existing solutions and serve as a guide for subsequent research in this area.Upon careful examination of current findings,it is found that,based on the different optimization objects,existing solutions to the bus bunching problem can be divided into five directions,i.e.,operational strategy improvement,traffic control improvement,driver driving rules improvement,passenger habit improvement,and others.While numerous solutions to bus bunching are available,there remains a gap in research exploring the integrated application of methods from diverse directions.Furthermore,with the development of autonomous driving,it is expected that the use of modular autonomous vehicles could be the most potential solution to the issue of bus bunching in the future.展开更多
As the proliferation and development of automated container terminal continue,the issues of efficiency and safety become increasingly significant.The container yard is one of the most crucial cargo distribution center...As the proliferation and development of automated container terminal continue,the issues of efficiency and safety become increasingly significant.The container yard is one of the most crucial cargo distribution centers in a terminal.Automated Guided Vehicles(AGVs)that carry materials of varying hazard levels through these yards without compromising on the safe transportation of hazardous materials,while also maximizing efficiency,is a complex challenge.This research introduces an algorithm that integrates Long Short-Term Memory(LSTM)neural network with reinforcement learning techniques,specifically Deep Q-Network(DQN),for routing an AGV carrying hazardous materials within a container yard.The objective is to ensure that the AGV carrying hazardous materials efficiently reaches its destination while effectively avoiding AGVs carrying non-hazardous materials.Utilizing real data from the Meishan Port in Ningbo,Zhejiang,China,the actual yard is first abstracted into an undirected graph.Since LSTM neural network can efficiently conveys and represents information in long time sequences and do not causes useful information before long time to be ignored,a two-layer LSTM neural network with 64 neurons per layer was constructed for predicting the motion trajectory of AGVs carrying non-hazardous materials,which are incorporated into the map as background AGVs.Subsequently,DQN is employed to plan the route for an AGV transporting hazardous materials,aiming to reach its destination swiftly while avoiding encounters with other AGVs.Experimental tests have shown that the route planning algorithm proposed in this study improves the level of avoidance of hazardous material AGV in relation to non-hazardous material AGVs.Compared to the method where hazardous material AGV follow the shortest path to their destination,the avoidance efficiency was enhanced by 3.11%.This improvement demonstrates potential strategies for balancing efficiency and safety in automated terminals.Additionally,it provides insights for designing avoidance schemes for autonomous driving AGVs,offering solutions for complex operational environments where safety and efficient navigation are paramount.展开更多
文摘Background: At present, in clinical practice, patients with primary hyperaldosteronism (PA) are mainly treated by surgery or medical drugs (spironolactone/spironolactone, epridone, etc.). Some studies show that the left ventricular hypertrophy of patients can be significantly improved after treatment. However, at present, the relevant research is very limited, and there is still controversy on the improvement of cardiac structure and function between the two treatment methods. No reliable conclusions have been drawn. Objective: We conducted this meta-analysis to compare the improvement of cardiac structure of patients after surgical treatment and drug treatment, so as to clarify the efficacy of surgical treatment and drug treatment for PA patients. Methods: In order to examine the cardiac color ultrasound data of PA patients receiving surgical treatment and drug therapy (spironolactone, antisterone), randomized or observational studies were searched through Pubmed, Cochrane Library, and Embase. Meta-analysis was then carried out on the comprehensive and individual outcomes. The ROINBS-I scale is utilized to assess the offset risk of study inclusion. Outcomes: A total of nine studies involving 799 patients with PA into meta analysis, according to the results of the surgery in the treatment of patients with PA, left ventricular mass index (LVMI) changes in value (drop range) is significantly higher than drug therapy (Mean difference IV: —2.32, P In 6 studies, after surgical treatment of interventricular septal thickness (IVSD), changes in value (drop range) are also higher than drug therapy (Mean difference IV: —0.35, P In 2 studies, the surgical treatment of plasma aldosterone concentration (PAC) drop degree is superior to drug therapy (Mean difference IV: —12.63, P < 0.05), and blood pressure to improve the degree of surgery and drug treatment has no obvious difference. Conclusions: This meta-analysis result confirmed that after medical and surgical treatment of PA can obviously improve the patient’s blood pressure, and no difference between the two treatments. But for the heart structure improvement, including left ventricular hypertrophy and interventricular septum thickness, surgical treatment effect is significantly better than the medicine treatment, so the adrenalectomy can be used as unilateral PA optimal choice of treatment.
基金sponsored by State Key Laboratory of Intelligent Green Vehicle and Mobility under Project No.KFY2421,China.
文摘Bus bunching has been a persistent issue in urban bus system since it first appeared,and it remains a challenge not fully resolved.This phenomenon may reduce the operational efficiency of the urban bus system,which is detrimental to the operation of fast-paced public transport in cities.Fortunately,extensive research has been undertaken in the long development and optimization of the urban bus system,and many solutions have emerged so far.The purpose of this paper is to summarize the existing solutions and serve as a guide for subsequent research in this area.Upon careful examination of current findings,it is found that,based on the different optimization objects,existing solutions to the bus bunching problem can be divided into five directions,i.e.,operational strategy improvement,traffic control improvement,driver driving rules improvement,passenger habit improvement,and others.While numerous solutions to bus bunching are available,there remains a gap in research exploring the integrated application of methods from diverse directions.Furthermore,with the development of autonomous driving,it is expected that the use of modular autonomous vehicles could be the most potential solution to the issue of bus bunching in the future.
文摘As the proliferation and development of automated container terminal continue,the issues of efficiency and safety become increasingly significant.The container yard is one of the most crucial cargo distribution centers in a terminal.Automated Guided Vehicles(AGVs)that carry materials of varying hazard levels through these yards without compromising on the safe transportation of hazardous materials,while also maximizing efficiency,is a complex challenge.This research introduces an algorithm that integrates Long Short-Term Memory(LSTM)neural network with reinforcement learning techniques,specifically Deep Q-Network(DQN),for routing an AGV carrying hazardous materials within a container yard.The objective is to ensure that the AGV carrying hazardous materials efficiently reaches its destination while effectively avoiding AGVs carrying non-hazardous materials.Utilizing real data from the Meishan Port in Ningbo,Zhejiang,China,the actual yard is first abstracted into an undirected graph.Since LSTM neural network can efficiently conveys and represents information in long time sequences and do not causes useful information before long time to be ignored,a two-layer LSTM neural network with 64 neurons per layer was constructed for predicting the motion trajectory of AGVs carrying non-hazardous materials,which are incorporated into the map as background AGVs.Subsequently,DQN is employed to plan the route for an AGV transporting hazardous materials,aiming to reach its destination swiftly while avoiding encounters with other AGVs.Experimental tests have shown that the route planning algorithm proposed in this study improves the level of avoidance of hazardous material AGV in relation to non-hazardous material AGVs.Compared to the method where hazardous material AGV follow the shortest path to their destination,the avoidance efficiency was enhanced by 3.11%.This improvement demonstrates potential strategies for balancing efficiency and safety in automated terminals.Additionally,it provides insights for designing avoidance schemes for autonomous driving AGVs,offering solutions for complex operational environments where safety and efficient navigation are paramount.
