TypeⅡdiabetes mellitus(T2DM)has experienced a dramatic increase globally across countries of various income levels over the past three decades.The persistent prevalence of T2DM is attributed to a complex interplay of...TypeⅡdiabetes mellitus(T2DM)has experienced a dramatic increase globally across countries of various income levels over the past three decades.The persistent prevalence of T2DM is attributed to a complex interplay of genetic and environmental factors.While numerous pharmaceutical therapies have been developed,there remains an urgent need for innovative treatment approaches that offer effectiveness without significant adverse effects.In this context,the exploration of the gut microbiome presents a promising avenue.Research has increasingly shown that the gut microbiome of individuals with T2DM exhibits distinct differences compared to healthy individuals,suggesting its potential role in the disease’s pathogenesis and progression.This emerging field offers diverse applications,particularly in modifying the gut environment through the administration of prebiotics,probiotics,and fecal microbiome transfer.These interventions aim to restore a healthy microbiome balance,which could potentially alleviate or even reverse the metabolic dysfunctions associated with T2DM.Although current results from clinical trials have not yet shown dramatic effects on diabetes management,the groundwork has been laid for deeper investigation.Ongoing and future clinical trials are critical to advancing our understanding of the microbiome’s impact on diabetes.By further elucidating the mechanisms through which microbiome alterations influence insulin resistance and glucose metabolism,researchers can develop more targeted interventions.The potential to harness the gut microbiome in developing new therapeutic strategies offers a compelling prospect to transform the treatment landscape of T2DM,potentially reducing the disease’s burden significantly with approaches that are less reliant on traditional pharmaceuticals and more focused on holistic,systemic health improvements.展开更多
Diabetes mellitus is associated with foot ulcers,which frequently pave the way to lower-extremity amputation.Neuropathy,trauma,deformity,high plantar pressures,and peripheral vascular disease are the most common under...Diabetes mellitus is associated with foot ulcers,which frequently pave the way to lower-extremity amputation.Neuropathy,trauma,deformity,high plantar pressures,and peripheral vascular disease are the most common underlying causes.Around 15%of diabetic patients are affected by diabetic foot ulcer in their lifetime.64 million people are affected by diabetics in India and 40000 amputations are done every year.Foot ulcers are evaluated and classified in a systematic and thorough manner to assist in determining the best course of therapy.This paper proposes a novel model which predicts the threat of diabetic foot ulcer using independent agents for various input values and a combination of fuzzy expert systems.The proposed model uses a classification system to distinguish between each fuzzy framework and its parameters.Based on the severity levels necessary prevention,treatment,and medication are recommended.Combining the results of all the fuzzy frameworks derived from its constituent parameters,a risk-specific medication is recommended.The work also has higher accuracy when compared to other related models.展开更多
Based on the observation data of meteorological stations,Doppler radar observation data of Ulanqab City,and ERA-5 reanalysis data,a snowstorm process in Ulanqab City from March 17 to 18,2022 was analyzed.The results s...Based on the observation data of meteorological stations,Doppler radar observation data of Ulanqab City,and ERA-5 reanalysis data,a snowstorm process in Ulanqab City from March 17 to 18,2022 was analyzed.The results show that this was a type Ⅱ snowstorm process generated under the joint influence of upper trough and ground low inverted trough and frontal cyclone.The main period of snowfall can be divided into two time stages,and the total snowfall was more in the south and less in the north,which was consistent with that of average specific humidity field.Water vapor conditions provided by strong water vapor transport and convergence,strong upward movement shown by large vertical velocity field,and the suction action of high-and low-layer divergence and convergence were the reasons for the hourly heavy snowfall on the 18^(th).During the process,radar echoes were mainly sheet-shaped,and composite reflectivity was 15-25 dBZ in most areas.The zero speed line in the first period was positively"S"-shaped,and there was warm advection and southwest wind.On the morning of the 18^(th),after the cold front transited the city,Ulanqab City was gradually controlled by northwest wind,and the snow tended to end.展开更多
针对逐步Ⅱ型删失数据下Burr Type X分布的参数估计问题,提出模型参数的一种新的贝叶斯估计及相应的最大后验密度(HPD)置信区间.假设伽玛分布为待估参数的先验分布,考虑待估参数的条件后验分布未知、单峰且近似对称,选取以正态分布为提...针对逐步Ⅱ型删失数据下Burr Type X分布的参数估计问题,提出模型参数的一种新的贝叶斯估计及相应的最大后验密度(HPD)置信区间.假设伽玛分布为待估参数的先验分布,考虑待估参数的条件后验分布未知、单峰且近似对称,选取以正态分布为提议分布的Metropolis-Hastings(MH)算法生成后验样本,基于后验样本在平方误差损失函数下得到待估参数的贝叶斯估计和HPD置信区间.将基于MH算法得到的贝叶斯估计和HPD置信区间与基于EM算法得到的极大似然估计和置信区间在均方误差准则和精度意义下进行比较.Monte-Carlo模拟结果表明,基于MH算法得到的估计在均方误差准则下优于基于EM算法得到的极大似然估计,基于MH算法得到的HPD置信区间长度小于基于EM算法得到的置信区间长度.展开更多
The current research aims to implement the numerical resultsfor the Holling third kind of functional response delay differential modelutilizing a stochastic framework based on Levenberg-Marquardt backpropagationneural...The current research aims to implement the numerical resultsfor the Holling third kind of functional response delay differential modelutilizing a stochastic framework based on Levenberg-Marquardt backpropagationneural networks (LVMBPNNs). The nonlinear model depends uponthree dynamics, prey, predator, and the impact of the recent past. Threedifferent cases based on the delay differential system with the Holling 3^(rd) type of the functional response have been used to solve through the proposedLVMBPNNs solver. The statistic computing framework is provided byselecting 12%, 11%, and 77% for training, testing, and verification. Thirteennumbers of neurons have been used based on the input, hidden, and outputlayers structure for solving the delay differential model with the Holling 3rdtype of functional response. The correctness of the proposed stochastic schemeis observed by using the comparison performances of the proposed and referencedata-based Adam numerical results. The authentication and precision ofthe proposed solver are approved by analyzing the state transitions, regressionperformances, correlation actions, mean square error, and error histograms.展开更多
文摘TypeⅡdiabetes mellitus(T2DM)has experienced a dramatic increase globally across countries of various income levels over the past three decades.The persistent prevalence of T2DM is attributed to a complex interplay of genetic and environmental factors.While numerous pharmaceutical therapies have been developed,there remains an urgent need for innovative treatment approaches that offer effectiveness without significant adverse effects.In this context,the exploration of the gut microbiome presents a promising avenue.Research has increasingly shown that the gut microbiome of individuals with T2DM exhibits distinct differences compared to healthy individuals,suggesting its potential role in the disease’s pathogenesis and progression.This emerging field offers diverse applications,particularly in modifying the gut environment through the administration of prebiotics,probiotics,and fecal microbiome transfer.These interventions aim to restore a healthy microbiome balance,which could potentially alleviate or even reverse the metabolic dysfunctions associated with T2DM.Although current results from clinical trials have not yet shown dramatic effects on diabetes management,the groundwork has been laid for deeper investigation.Ongoing and future clinical trials are critical to advancing our understanding of the microbiome’s impact on diabetes.By further elucidating the mechanisms through which microbiome alterations influence insulin resistance and glucose metabolism,researchers can develop more targeted interventions.The potential to harness the gut microbiome in developing new therapeutic strategies offers a compelling prospect to transform the treatment landscape of T2DM,potentially reducing the disease’s burden significantly with approaches that are less reliant on traditional pharmaceuticals and more focused on holistic,systemic health improvements.
文摘Diabetes mellitus is associated with foot ulcers,which frequently pave the way to lower-extremity amputation.Neuropathy,trauma,deformity,high plantar pressures,and peripheral vascular disease are the most common underlying causes.Around 15%of diabetic patients are affected by diabetic foot ulcer in their lifetime.64 million people are affected by diabetics in India and 40000 amputations are done every year.Foot ulcers are evaluated and classified in a systematic and thorough manner to assist in determining the best course of therapy.This paper proposes a novel model which predicts the threat of diabetic foot ulcer using independent agents for various input values and a combination of fuzzy expert systems.The proposed model uses a classification system to distinguish between each fuzzy framework and its parameters.Based on the severity levels necessary prevention,treatment,and medication are recommended.Combining the results of all the fuzzy frameworks derived from its constituent parameters,a risk-specific medication is recommended.The work also has higher accuracy when compared to other related models.
文摘Based on the observation data of meteorological stations,Doppler radar observation data of Ulanqab City,and ERA-5 reanalysis data,a snowstorm process in Ulanqab City from March 17 to 18,2022 was analyzed.The results show that this was a type Ⅱ snowstorm process generated under the joint influence of upper trough and ground low inverted trough and frontal cyclone.The main period of snowfall can be divided into two time stages,and the total snowfall was more in the south and less in the north,which was consistent with that of average specific humidity field.Water vapor conditions provided by strong water vapor transport and convergence,strong upward movement shown by large vertical velocity field,and the suction action of high-and low-layer divergence and convergence were the reasons for the hourly heavy snowfall on the 18^(th).During the process,radar echoes were mainly sheet-shaped,and composite reflectivity was 15-25 dBZ in most areas.The zero speed line in the first period was positively"S"-shaped,and there was warm advection and southwest wind.On the morning of the 18^(th),after the cold front transited the city,Ulanqab City was gradually controlled by northwest wind,and the snow tended to end.
文摘针对逐步Ⅱ型删失数据下Burr Type X分布的参数估计问题,提出模型参数的一种新的贝叶斯估计及相应的最大后验密度(HPD)置信区间.假设伽玛分布为待估参数的先验分布,考虑待估参数的条件后验分布未知、单峰且近似对称,选取以正态分布为提议分布的Metropolis-Hastings(MH)算法生成后验样本,基于后验样本在平方误差损失函数下得到待估参数的贝叶斯估计和HPD置信区间.将基于MH算法得到的贝叶斯估计和HPD置信区间与基于EM算法得到的极大似然估计和置信区间在均方误差准则和精度意义下进行比较.Monte-Carlo模拟结果表明,基于MH算法得到的估计在均方误差准则下优于基于EM算法得到的极大似然估计,基于MH算法得到的HPD置信区间长度小于基于EM算法得到的置信区间长度.
基金This research received funding support from the NSRF via the Program Management Unit for Human Resources&Institutional Development,Research and Innovation[Grant Number B05F650018].
文摘The current research aims to implement the numerical resultsfor the Holling third kind of functional response delay differential modelutilizing a stochastic framework based on Levenberg-Marquardt backpropagationneural networks (LVMBPNNs). The nonlinear model depends uponthree dynamics, prey, predator, and the impact of the recent past. Threedifferent cases based on the delay differential system with the Holling 3^(rd) type of the functional response have been used to solve through the proposedLVMBPNNs solver. The statistic computing framework is provided byselecting 12%, 11%, and 77% for training, testing, and verification. Thirteennumbers of neurons have been used based on the input, hidden, and outputlayers structure for solving the delay differential model with the Holling 3rdtype of functional response. The correctness of the proposed stochastic schemeis observed by using the comparison performances of the proposed and referencedata-based Adam numerical results. The authentication and precision ofthe proposed solver are approved by analyzing the state transitions, regressionperformances, correlation actions, mean square error, and error histograms.
