The classification of functional data has drawn much attention in recent years.The main challenge is representing infinite-dimensional functional data by finite-dimensional features while utilizing those features to a...The classification of functional data has drawn much attention in recent years.The main challenge is representing infinite-dimensional functional data by finite-dimensional features while utilizing those features to achieve better classification accuracy.In this paper,we propose a mean-variance-based(MV)feature weighting method for classifying functional data or functional curves.In the feature extraction stage,each sample curve is approximated by B-splines to transfer features to the coefficients of the spline basis.After that,a feature weighting approach based on statistical principles is introduced by comprehensively considering the between-class differences and within-class variations of the coefficients.We also introduce a scaling parameter to adjust the gap between the weights of features.The new feature weighting approach can adaptively enhance noteworthy local features while mitigating the impact of confusing features.The algorithms for feature weighted K-nearest neighbor and support vector machine classifiers are both provided.Moreover,the new approach can be well integrated into existing functional data classifiers,such as the generalized functional linear model and functional linear discriminant analysis,resulting in a more accurate classification.The performance of the mean-variance-based classifiers is evaluated by simulation studies and real data.The results show that the newfeatureweighting approach significantly improves the classification accuracy for complex functional data.展开更多
Background: Obesity has become a serious global public health challenge, given that it leads to various adverse health outcomes that include cardiovascular illnesses, diabetes, and certain types of cancer. The World H...Background: Obesity has become a serious global public health challenge, given that it leads to various adverse health outcomes that include cardiovascular illnesses, diabetes, and certain types of cancer. The World Health Organization (WHO) has estimated that, at the end of 2022, 1 out of every 8 individuals were obese, and that the global adult obesity rates have over doubled since 1990, even as the adolescent obesity rates have quadrupled. Thus, as of 2022, nearly 2.5 billion adults, aged 18 years and above, were overweight, with 890 million being obese. Obesity and overweight incidence rate has been gradually increasing over the years, presenting significant challenges to the healthcare systems throughout the globe. In this regard, the objective of this systematic review was to evaluate the effectiveness and safety of lifestyle modifications (diet and physical activity) and pharmacotherapy in promoting weight loss and improving metabolic health in overweight adults. Methodology: To attain the above stated study objective, a systematic evaluation of previous studies was carried out, particularly studies that assessed the effectiveness and safety of lifestyle modifications (diet and physical activity) and pharmacotherapy in promoting weight loss and improving metabolic health in overweight adults. The authors have used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) in the selection of eligible studies for inclusion in the study. Results: The findings indicate that lifestyle interventions resulted in 5% - 10% weight reduction and significant improvements in metabolic indicators, while pharmacotherapy (GLP-1 receptor agonists) achieved up to 15% weight reduction and considerable metabolic health benefits. Further, comparative studies show lifestyle modifications provide overall health benefits, while medication is necessary for non-responders. Conclusion: Individualized treatment strategies are crucial, and further research is needed on long-term consequences and combination therapies.展开更多
Objective This study employs the Geographically and Temporally Weighted Regression(GTWR)model to assess the impact of meteorological elements and imported cases on dengue fever outbreaks,emphasizing the spatial-tempor...Objective This study employs the Geographically and Temporally Weighted Regression(GTWR)model to assess the impact of meteorological elements and imported cases on dengue fever outbreaks,emphasizing the spatial-temporal variability of these factors in border regions.Methods We conducted a descriptive analysis of dengue fever’s temporal-spatial distribution in Yunnan border areas.Utilizing annual data from 2013 to 2019,with each county in the Yunnan border serving as a spatial unit,we constructed a GTWR model to investigate the determinants of dengue fever and their spatio-temporal heterogeneity in this region.Results The GTWR model,proving more effective than Ordinary Least Squares(OLS)analysis,identified significant spatial and temporal heterogeneity in factors influencing dengue fever’s spread along the Yunnan border.Notably,the GTWR model revealed a substantial variation in the relationship between indigenous dengue fever incidence,meteorological variables,and imported cases across different counties.Conclusion In the Yunnan border areas,local dengue incidence is affected by temperature,humidity,precipitation,wind speed,and imported cases,with these factors’influence exhibiting notable spatial and temporal variation.展开更多
The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the intera...The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.展开更多
Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation indust...Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.展开更多
BACKGROUND The benefit of adjuvant chemotherapy(ACT)for patients with no evidence of disease after pulmonary metastasis resection(PM)from colorectal cancer(CRC)remains controversial.AIM To assess the efficacy of ACT i...BACKGROUND The benefit of adjuvant chemotherapy(ACT)for patients with no evidence of disease after pulmonary metastasis resection(PM)from colorectal cancer(CRC)remains controversial.AIM To assess the efficacy of ACT in patients after PM resection for CRC.METHODS This study included 96 patients who underwent pulmonary metastasectomy for CRC at a single institution between April 2008 and July 2023.The primary end-point was overall survival(OS);secondary endpoints included cancer-specific survival(CSS)and disease-free survival(DFS).An inverse probability of treat-ment-weighting(IPTW)analysis was conducted to address indication bias.Sur-vival outcomes compared using Kaplan-Meier curves,log-rank test,Cox regre-ssion and confirmed by propensity score-matching(PSM).RESULTS With a median follow-up of 27.5 months(range,18.3-50.4 months),the 5-year OS,CSS and DFS were 72.0%,74.4%and 51.3%,respectively.ACT had no significant effect on OS after PM resection from CRC[original cohort:P=0.08;IPTW:P=0.15].No differences were observed for CSS(P=0.12)and DFS(P=0.68)between the ACT and non-ACT groups.Multivariate analysis showed no association of ACT with better survival,while sublobar resection(HR=0.45;95%CI:0.20-1.00,P=0.049)and longer disease-free interval(HR=0.45;95%CI:0.20-0.98,P=0.044)were associated with improved survival.CONCLUSION ACT does not improve survival after PM resection for CRC.Further well-designed randomized controlled trials are needed to determine the optimal ACT regimen and duration.展开更多
Clozapine is widely recognized as an effective antipsychotic medication for treatment-resistant schizophrenia, but it is typically associated with significant weight gain. This case report presents two unusual cases o...Clozapine is widely recognized as an effective antipsychotic medication for treatment-resistant schizophrenia, but it is typically associated with significant weight gain. This case report presents two unusual cases of patients with schizophrenia who experienced substantial weight loss while on long-term clozapine therapy. The first case involves a 35-year-old male who lost 21.3% of his initial body weight, and the second case describes a 54-year-old female who lost 30.2% of her initial weight, despite having comorbid hypothyroidism. Both patients showed improvement in psychiatric symptoms concurrent with the weight loss. Comprehensive investigations did not reveal other clear etiologies for the weight reduction. These cases challenge the conventional understanding of clozapine’s metabolic effects and highlight the potential for atypical responses in some individuals. The report discusses possible mechanisms for this unusual phenomenon, including genetic factors and altered pharmacokinetics. It also emphasizes the need for individualized monitoring and management strategies in clozapine therapy. These findings contribute to the growing body of evidence suggesting that metabolic responses to clozapine may be more complex and varied than previously thought, underscoring the importance of personalized approaches in schizophrenia treatment.展开更多
BACKGROUND A progressive decrease in exclusive breastfeeding(BF)is observed in Latin America and the Caribbean compared with global results.The possibility of being breastfed and continuing BF for>6 months is lower...BACKGROUND A progressive decrease in exclusive breastfeeding(BF)is observed in Latin America and the Caribbean compared with global results.The possibility of being breastfed and continuing BF for>6 months is lower in low birth weight than in healthy-weight infants.AIM To identify factors associated with BF maintenance and promotion,with particular attention to low-and middle-income countries,by studying geographic,socioeconomic,and individual or neonatal health factors.METHODS A scoping review was conducted in 2018 using the conceptual model of social determinants of health published by the Commission on Equity and Health Inequalities in the United States.The extracted data with common characteristics were synthesized and categorized into two main themes:(1)Sociodemographic factors and proximal determinants involved in the initiation and maintenance of BF in low-birth-weight term infants in Latin America;and(2)individual characteristics related to the self-efficacy capacity for BF maintenance and adherence in low-birth-weight term infants.RESULTS This study identified maternal age,educational level,maternal economic capacity,social stratum,exposure to BF substitutes,access to BF information,and quality of health services as mediators for maintaining BF.CONCLUSION Individual self-efficacy factors that enable BF adherence in at-risk populations should be analyzed for better health outcomes.展开更多
This study used Topological Weighted Centroid (TWC) to analyze the Coronavirus outbreak in Brazil. This analysis only uses latitude and longitude in formation of the capitals with the confirmed cases on May 24, 2020 t...This study used Topological Weighted Centroid (TWC) to analyze the Coronavirus outbreak in Brazil. This analysis only uses latitude and longitude in formation of the capitals with the confirmed cases on May 24, 2020 to illustrate the usefulness of TWC though any date could have been used. There are three types of TWC analyses, each type having five associated algorithms that produce fifteen maps, TWC-Original, TWC-Frequency and TWC-Windowing. We focus on TWC-Original to illustrate our approach. The TWC method without using the transportation information predicts the network for COVID-19 outbreak that matches very well with the main radial transportation routes network in Brazil.展开更多
Objective:This study analyzes the relationship between sociodemographic factors and low birth weight(LBW)in toddlers.Methods:The research design uses a correlational method.The population is 303 mothers with toddlers ...Objective:This study analyzes the relationship between sociodemographic factors and low birth weight(LBW)in toddlers.Methods:The research design uses a correlational method.The population is 303 mothers with toddlers aged 12-60 months in Lojejer Wuluhan Jember Village,East Java,Indonesia.The cluster sampling took 172 samples in total.The sociodemographic variables measured included the father’s and the mother’s age,the father’s and mother’s education,family income,the father’s occupation,the mother’s occupation,and the child’s gender.Data collection techniques used questionnaires and document studies in the Maternal Child Health(MCH)handbook.Data were analyzed using logistic regression.Results:The results showed that the variable age of the father and mother≥20 years was a protective factor for the incidence of LBW.Family income<IDR 3,000,000 per month,fathers with farm workers and fishermen as occupation,male sex,and low father’s education were predictor factors for LBW.Conclusions:This study concluded that the variable sociodemographic factors related to LBW in toddlers in Lojejer Wuluhan Village,Jember district,East Java Province,Indonesia.Therefore,the government needs to establish stricter policies in terms of maturing the age of marriage to reduce the incidence of LBW.展开更多
基金the National Social Science Foundation of China(Grant No.22BTJ035).
文摘The classification of functional data has drawn much attention in recent years.The main challenge is representing infinite-dimensional functional data by finite-dimensional features while utilizing those features to achieve better classification accuracy.In this paper,we propose a mean-variance-based(MV)feature weighting method for classifying functional data or functional curves.In the feature extraction stage,each sample curve is approximated by B-splines to transfer features to the coefficients of the spline basis.After that,a feature weighting approach based on statistical principles is introduced by comprehensively considering the between-class differences and within-class variations of the coefficients.We also introduce a scaling parameter to adjust the gap between the weights of features.The new feature weighting approach can adaptively enhance noteworthy local features while mitigating the impact of confusing features.The algorithms for feature weighted K-nearest neighbor and support vector machine classifiers are both provided.Moreover,the new approach can be well integrated into existing functional data classifiers,such as the generalized functional linear model and functional linear discriminant analysis,resulting in a more accurate classification.The performance of the mean-variance-based classifiers is evaluated by simulation studies and real data.The results show that the newfeatureweighting approach significantly improves the classification accuracy for complex functional data.
文摘Background: Obesity has become a serious global public health challenge, given that it leads to various adverse health outcomes that include cardiovascular illnesses, diabetes, and certain types of cancer. The World Health Organization (WHO) has estimated that, at the end of 2022, 1 out of every 8 individuals were obese, and that the global adult obesity rates have over doubled since 1990, even as the adolescent obesity rates have quadrupled. Thus, as of 2022, nearly 2.5 billion adults, aged 18 years and above, were overweight, with 890 million being obese. Obesity and overweight incidence rate has been gradually increasing over the years, presenting significant challenges to the healthcare systems throughout the globe. In this regard, the objective of this systematic review was to evaluate the effectiveness and safety of lifestyle modifications (diet and physical activity) and pharmacotherapy in promoting weight loss and improving metabolic health in overweight adults. Methodology: To attain the above stated study objective, a systematic evaluation of previous studies was carried out, particularly studies that assessed the effectiveness and safety of lifestyle modifications (diet and physical activity) and pharmacotherapy in promoting weight loss and improving metabolic health in overweight adults. The authors have used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) in the selection of eligible studies for inclusion in the study. Results: The findings indicate that lifestyle interventions resulted in 5% - 10% weight reduction and significant improvements in metabolic indicators, while pharmacotherapy (GLP-1 receptor agonists) achieved up to 15% weight reduction and considerable metabolic health benefits. Further, comparative studies show lifestyle modifications provide overall health benefits, while medication is necessary for non-responders. Conclusion: Individualized treatment strategies are crucial, and further research is needed on long-term consequences and combination therapies.
基金supported by National Science and Technology Infrastructure Platform National Population and Health Science Data Sharing Service Platform Public Health Science Data Center[NCMI-ZB01N-201905]。
文摘Objective This study employs the Geographically and Temporally Weighted Regression(GTWR)model to assess the impact of meteorological elements and imported cases on dengue fever outbreaks,emphasizing the spatial-temporal variability of these factors in border regions.Methods We conducted a descriptive analysis of dengue fever’s temporal-spatial distribution in Yunnan border areas.Utilizing annual data from 2013 to 2019,with each county in the Yunnan border serving as a spatial unit,we constructed a GTWR model to investigate the determinants of dengue fever and their spatio-temporal heterogeneity in this region.Results The GTWR model,proving more effective than Ordinary Least Squares(OLS)analysis,identified significant spatial and temporal heterogeneity in factors influencing dengue fever’s spread along the Yunnan border.Notably,the GTWR model revealed a substantial variation in the relationship between indigenous dengue fever incidence,meteorological variables,and imported cases across different counties.Conclusion In the Yunnan border areas,local dengue incidence is affected by temperature,humidity,precipitation,wind speed,and imported cases,with these factors’influence exhibiting notable spatial and temporal variation.
基金supported in part by the Central Government Guides Local Science and TechnologyDevelopment Funds(Grant No.YDZJSX2021A038)in part by theNational Natural Science Foundation of China under(Grant No.61806138)in part by the China University Industry-University-Research Collaborative Innovation Fund(Future Network Innovation Research and Application Project)(Grant 2021FNA04014).
文摘The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.
基金supported in part by the National Key Research and Development Program of China(2021YFC2902703)the National Natural Science Foundation of China(62173078,61773105,61533007,61873049,61873053,61703085,61374147)。
文摘Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.
基金Supported by the National Project for Clinical Key Specialty Development.
文摘BACKGROUND The benefit of adjuvant chemotherapy(ACT)for patients with no evidence of disease after pulmonary metastasis resection(PM)from colorectal cancer(CRC)remains controversial.AIM To assess the efficacy of ACT in patients after PM resection for CRC.METHODS This study included 96 patients who underwent pulmonary metastasectomy for CRC at a single institution between April 2008 and July 2023.The primary end-point was overall survival(OS);secondary endpoints included cancer-specific survival(CSS)and disease-free survival(DFS).An inverse probability of treat-ment-weighting(IPTW)analysis was conducted to address indication bias.Sur-vival outcomes compared using Kaplan-Meier curves,log-rank test,Cox regre-ssion and confirmed by propensity score-matching(PSM).RESULTS With a median follow-up of 27.5 months(range,18.3-50.4 months),the 5-year OS,CSS and DFS were 72.0%,74.4%and 51.3%,respectively.ACT had no significant effect on OS after PM resection from CRC[original cohort:P=0.08;IPTW:P=0.15].No differences were observed for CSS(P=0.12)and DFS(P=0.68)between the ACT and non-ACT groups.Multivariate analysis showed no association of ACT with better survival,while sublobar resection(HR=0.45;95%CI:0.20-1.00,P=0.049)and longer disease-free interval(HR=0.45;95%CI:0.20-0.98,P=0.044)were associated with improved survival.CONCLUSION ACT does not improve survival after PM resection for CRC.Further well-designed randomized controlled trials are needed to determine the optimal ACT regimen and duration.
文摘Clozapine is widely recognized as an effective antipsychotic medication for treatment-resistant schizophrenia, but it is typically associated with significant weight gain. This case report presents two unusual cases of patients with schizophrenia who experienced substantial weight loss while on long-term clozapine therapy. The first case involves a 35-year-old male who lost 21.3% of his initial body weight, and the second case describes a 54-year-old female who lost 30.2% of her initial weight, despite having comorbid hypothyroidism. Both patients showed improvement in psychiatric symptoms concurrent with the weight loss. Comprehensive investigations did not reveal other clear etiologies for the weight reduction. These cases challenge the conventional understanding of clozapine’s metabolic effects and highlight the potential for atypical responses in some individuals. The report discusses possible mechanisms for this unusual phenomenon, including genetic factors and altered pharmacokinetics. It also emphasizes the need for individualized monitoring and management strategies in clozapine therapy. These findings contribute to the growing body of evidence suggesting that metabolic responses to clozapine may be more complex and varied than previously thought, underscoring the importance of personalized approaches in schizophrenia treatment.
文摘BACKGROUND A progressive decrease in exclusive breastfeeding(BF)is observed in Latin America and the Caribbean compared with global results.The possibility of being breastfed and continuing BF for>6 months is lower in low birth weight than in healthy-weight infants.AIM To identify factors associated with BF maintenance and promotion,with particular attention to low-and middle-income countries,by studying geographic,socioeconomic,and individual or neonatal health factors.METHODS A scoping review was conducted in 2018 using the conceptual model of social determinants of health published by the Commission on Equity and Health Inequalities in the United States.The extracted data with common characteristics were synthesized and categorized into two main themes:(1)Sociodemographic factors and proximal determinants involved in the initiation and maintenance of BF in low-birth-weight term infants in Latin America;and(2)individual characteristics related to the self-efficacy capacity for BF maintenance and adherence in low-birth-weight term infants.RESULTS This study identified maternal age,educational level,maternal economic capacity,social stratum,exposure to BF substitutes,access to BF information,and quality of health services as mediators for maintaining BF.CONCLUSION Individual self-efficacy factors that enable BF adherence in at-risk populations should be analyzed for better health outcomes.
文摘This study used Topological Weighted Centroid (TWC) to analyze the Coronavirus outbreak in Brazil. This analysis only uses latitude and longitude in formation of the capitals with the confirmed cases on May 24, 2020 to illustrate the usefulness of TWC though any date could have been used. There are three types of TWC analyses, each type having five associated algorithms that produce fifteen maps, TWC-Original, TWC-Frequency and TWC-Windowing. We focus on TWC-Original to illustrate our approach. The TWC method without using the transportation information predicts the network for COVID-19 outbreak that matches very well with the main radial transportation routes network in Brazil.
文摘Objective:This study analyzes the relationship between sociodemographic factors and low birth weight(LBW)in toddlers.Methods:The research design uses a correlational method.The population is 303 mothers with toddlers aged 12-60 months in Lojejer Wuluhan Jember Village,East Java,Indonesia.The cluster sampling took 172 samples in total.The sociodemographic variables measured included the father’s and the mother’s age,the father’s and mother’s education,family income,the father’s occupation,the mother’s occupation,and the child’s gender.Data collection techniques used questionnaires and document studies in the Maternal Child Health(MCH)handbook.Data were analyzed using logistic regression.Results:The results showed that the variable age of the father and mother≥20 years was a protective factor for the incidence of LBW.Family income<IDR 3,000,000 per month,fathers with farm workers and fishermen as occupation,male sex,and low father’s education were predictor factors for LBW.Conclusions:This study concluded that the variable sociodemographic factors related to LBW in toddlers in Lojejer Wuluhan Village,Jember district,East Java Province,Indonesia.Therefore,the government needs to establish stricter policies in terms of maturing the age of marriage to reduce the incidence of LBW.
