Hypertrophic cardiomyopathy(HCM)is a major contributor to cardiovascular diseases(CVD),the leading cause of death globally.HCM can precipitate heart failure(HF)by causing the cardiac tissue to weaken and stretch,there...Hypertrophic cardiomyopathy(HCM)is a major contributor to cardiovascular diseases(CVD),the leading cause of death globally.HCM can precipitate heart failure(HF)by causing the cardiac tissue to weaken and stretch,thereby impairing its pumping efficiency.Moreover,HCM increases the risk of atrial fibrillation,which in turn elevates the likelihood of thrombus formation and stroke.Given these significant clinical ramifications,research into the etiology and pathogenesis of HCM is intensifying at multiple levels.In this review,we discuss and synthesize the latest findings on HCM pathogenesis,drawing on key experimental studies conducted both in vitro and in vivo.We also offer our insights and perspectives on these mechanisms,while highlighting the limitations of current research.Advancing fundamental research in this area is essential for developing effective therapeutic interventions and enhancing the clinical management of HCM.展开更多
Hypertrophic cardiomyopathy(HCM)is a primary myocardial disease characterized by myocardial hypertrophy,excluding other cardiovascular or systemic/metabolic causes of ventricular wall thickening.Apical hypertrophic ca...Hypertrophic cardiomyopathy(HCM)is a primary myocardial disease characterized by myocardial hypertrophy,excluding other cardiovascular or systemic/metabolic causes of ventricular wall thickening.Apical hypertrophic cardiomyopathy(ApHCM)represents a special form of ventricular hypertrophy predominantly affecting the left ventricular apex below the papillary muscles,typically without significant left ventricular outflow tract obstruction.[1,2]ApHCM often coexists with mild coronary artery abnormalities,[3]and reports of acute myocardial infarction with coronary artery stenosis in ApHCM or HCM patients are uncommon.展开更多
The rise of hypersonic weapons,capable of traveling at speeds exceeding Mach 5 with unparalleled maneuverability,represents a transformative shift in modern warfare.These weapons,including HGVs(hypersonic glide vehicl...The rise of hypersonic weapons,capable of traveling at speeds exceeding Mach 5 with unparalleled maneuverability,represents a transformative shift in modern warfare.These weapons,including HGVs(hypersonic glide vehicles)and HCMs(hypersonic cruise missiles),challenge traditional defense systems due to their stealth-like speed,unpredictable flight paths,and low-altitude trajectories.Their ability to compress decision-making windows and evade conventional radar systems has sparked a global arms race,creating a critical need for advanced countermeasures.AI(artificial intelligence)emerges as a revolutionary solution to counter the stealth and speed of hypersonic threats.By leveraging AI-driven detection,tracking,and interception systems,defense mechanisms can overcome the limitations of conventional technology.AI enhances early detection through multi-sensor fusion,real-time data processing,and predictive modeling of hypersonic trajectories.It also facilitates the development of precision-guided interceptors and advanced systems like DEWs(directed energy weapons),offering effective avenues for neutralizing these fast-moving threats.Despite its promise,AI integration into hypersonic defense systems faces challenges,including data bias,cybersecurity risks,and potential escalation of conflicts.Ethical considerations and global collaboration are essential to address these concerns and ensure responsible deployment.As hypersonic weapons redefine the battlefield,AI stands as the linchpin for a robust,resilient,and future-proof defense strategy.This article explores the intersection of hypersonic technologies and AI,providing insights into how intelligent systems can safeguard global security against these next-generation threats.展开更多
Traditional Enterprise Resource Planning (ERP) systems with relational databases take weeks to deliver predictable insights instantly. The most accurate information is provided to companies to make the best decisions ...Traditional Enterprise Resource Planning (ERP) systems with relational databases take weeks to deliver predictable insights instantly. The most accurate information is provided to companies to make the best decisions through advanced analytics that examine the past and the future and capture information about the present. Integrating machine learning (ML) into financial ERP systems offers several benefits, including increased accuracy, efficiency, and cost savings. Also, ERP systems are crucial in overseeing different aspects of Human Capital Management (HCM) in organizations. The performance of the staff draws the interest of the management. In particular, to guarantee that the proper employees are assigned to the convenient task at the suitable moment, train and qualify them, and build evaluation systems to follow up their performance and an attempt to maintain the potential talents of workers. Also, predicting employee salaries correctly is necessary for the efficient distribution of resources, retaining talent, and ensuring the success of the organization as a whole. Conventional ERP system salary forecasting methods typically use static reports that only show the system’s current state, without analyzing employee data or providing recommendations. We designed and enforced a prototype to define to apply ML algorithms on Oracle EBS data to enhance employee evaluation using real-time data directly from the ERP system. Based on measurements of accuracy, the Random Forest algorithm enhanced the performance of this system. This model offers an accuracy of 90% on the balanced dataset.展开更多
创造低噪声的乘车环境,建立减振降噪环境友好型的地铁站区环境已成为轨道交通建设的发展趋势。测试分析一种陶粒混凝土制作的新型吸音结构HCM型吸声板的降噪效果。试验在北京交通大学轨道减振与振动控制实验室中进行,将吸声板铺设在轨...创造低噪声的乘车环境,建立减振降噪环境友好型的地铁站区环境已成为轨道交通建设的发展趋势。测试分析一种陶粒混凝土制作的新型吸音结构HCM型吸声板的降噪效果。试验在北京交通大学轨道减振与振动控制实验室中进行,将吸声板铺设在轨道的钢轨之间,在道床和隧道壁上布置测点,模拟干燥、潮湿、下雨以及潮湿后干燥的工况进行试验测试。分析结果表明：不同测点和工况下,减噪效果都能达到4~5 d BA;频域分析表明,吸声板具有较宽的降噪频段。对于隧道壁测点,吸声板对250 Hz以上频段噪声的降噪效果较优;对于道床测点,吸声板对500 Hz以上频段噪声的降噪效果较好。展开更多
基金supported by Henan Provincial Key Technologies R&D Program(Grant No.25202310242)Henan Provincial Medical Science and Technology Tackling Program(Grant No.LHGJ20240150).
文摘Hypertrophic cardiomyopathy(HCM)is a major contributor to cardiovascular diseases(CVD),the leading cause of death globally.HCM can precipitate heart failure(HF)by causing the cardiac tissue to weaken and stretch,thereby impairing its pumping efficiency.Moreover,HCM increases the risk of atrial fibrillation,which in turn elevates the likelihood of thrombus formation and stroke.Given these significant clinical ramifications,research into the etiology and pathogenesis of HCM is intensifying at multiple levels.In this review,we discuss and synthesize the latest findings on HCM pathogenesis,drawing on key experimental studies conducted both in vitro and in vivo.We also offer our insights and perspectives on these mechanisms,while highlighting the limitations of current research.Advancing fundamental research in this area is essential for developing effective therapeutic interventions and enhancing the clinical management of HCM.
文摘Hypertrophic cardiomyopathy(HCM)is a primary myocardial disease characterized by myocardial hypertrophy,excluding other cardiovascular or systemic/metabolic causes of ventricular wall thickening.Apical hypertrophic cardiomyopathy(ApHCM)represents a special form of ventricular hypertrophy predominantly affecting the left ventricular apex below the papillary muscles,typically without significant left ventricular outflow tract obstruction.[1,2]ApHCM often coexists with mild coronary artery abnormalities,[3]and reports of acute myocardial infarction with coronary artery stenosis in ApHCM or HCM patients are uncommon.
文摘The rise of hypersonic weapons,capable of traveling at speeds exceeding Mach 5 with unparalleled maneuverability,represents a transformative shift in modern warfare.These weapons,including HGVs(hypersonic glide vehicles)and HCMs(hypersonic cruise missiles),challenge traditional defense systems due to their stealth-like speed,unpredictable flight paths,and low-altitude trajectories.Their ability to compress decision-making windows and evade conventional radar systems has sparked a global arms race,creating a critical need for advanced countermeasures.AI(artificial intelligence)emerges as a revolutionary solution to counter the stealth and speed of hypersonic threats.By leveraging AI-driven detection,tracking,and interception systems,defense mechanisms can overcome the limitations of conventional technology.AI enhances early detection through multi-sensor fusion,real-time data processing,and predictive modeling of hypersonic trajectories.It also facilitates the development of precision-guided interceptors and advanced systems like DEWs(directed energy weapons),offering effective avenues for neutralizing these fast-moving threats.Despite its promise,AI integration into hypersonic defense systems faces challenges,including data bias,cybersecurity risks,and potential escalation of conflicts.Ethical considerations and global collaboration are essential to address these concerns and ensure responsible deployment.As hypersonic weapons redefine the battlefield,AI stands as the linchpin for a robust,resilient,and future-proof defense strategy.This article explores the intersection of hypersonic technologies and AI,providing insights into how intelligent systems can safeguard global security against these next-generation threats.
文摘Traditional Enterprise Resource Planning (ERP) systems with relational databases take weeks to deliver predictable insights instantly. The most accurate information is provided to companies to make the best decisions through advanced analytics that examine the past and the future and capture information about the present. Integrating machine learning (ML) into financial ERP systems offers several benefits, including increased accuracy, efficiency, and cost savings. Also, ERP systems are crucial in overseeing different aspects of Human Capital Management (HCM) in organizations. The performance of the staff draws the interest of the management. In particular, to guarantee that the proper employees are assigned to the convenient task at the suitable moment, train and qualify them, and build evaluation systems to follow up their performance and an attempt to maintain the potential talents of workers. Also, predicting employee salaries correctly is necessary for the efficient distribution of resources, retaining talent, and ensuring the success of the organization as a whole. Conventional ERP system salary forecasting methods typically use static reports that only show the system’s current state, without analyzing employee data or providing recommendations. We designed and enforced a prototype to define to apply ML algorithms on Oracle EBS data to enhance employee evaluation using real-time data directly from the ERP system. Based on measurements of accuracy, the Random Forest algorithm enhanced the performance of this system. This model offers an accuracy of 90% on the balanced dataset.
文摘创造低噪声的乘车环境,建立减振降噪环境友好型的地铁站区环境已成为轨道交通建设的发展趋势。测试分析一种陶粒混凝土制作的新型吸音结构HCM型吸声板的降噪效果。试验在北京交通大学轨道减振与振动控制实验室中进行,将吸声板铺设在轨道的钢轨之间,在道床和隧道壁上布置测点,模拟干燥、潮湿、下雨以及潮湿后干燥的工况进行试验测试。分析结果表明：不同测点和工况下,减噪效果都能达到4~5 d BA;频域分析表明,吸声板具有较宽的降噪频段。对于隧道壁测点,吸声板对250 Hz以上频段噪声的降噪效果较优;对于道床测点,吸声板对500 Hz以上频段噪声的降噪效果较好。
