For each real number x∈(0,1),let[a_(1)(x),a_(2)(x),…,a_n(x),…]denote its continued fraction expansion.We study the convergence exponent defined byτ(x)=inf{s≥0:∞∑n=1(a_(n)(x)a_(n+1)(x))^(-s)<∞},which reflect...For each real number x∈(0,1),let[a_(1)(x),a_(2)(x),…,a_n(x),…]denote its continued fraction expansion.We study the convergence exponent defined byτ(x)=inf{s≥0:∞∑n=1(a_(n)(x)a_(n+1)(x))^(-s)<∞},which reflects the growth rate of the product of two consecutive partial quotients.As a main result,the Hausdorff dimensions of the level sets ofτ(x)are determined.展开更多
Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the i...Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: M.A.R.I.E. enables the rational, quantified measurement of Emotional Visual Acuity (EVA) in an individual observer and a population aged 20 to 70 years. Meanwhile, it can measure the range and intensity of expressed emotions through three Face- Tests, quantify the performance of a sample of 204 observers with hypernormal measures of cognition, “thymia” (defined elsewhere), and low levels of anxiety, and perform analysis of the six primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual- Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Decision-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”, 6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Fingerprint-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.展开更多
In this paper,we study the asymptotic behavior of a class of inverse quotient curvature flow in the anti-de Sitter-Schwarzschild manifold.We prove that under suitable convex conditions for the initial hypersurface,one...In this paper,we study the asymptotic behavior of a class of inverse quotient curvature flow in the anti-de Sitter-Schwarzschild manifold.We prove that under suitable convex conditions for the initial hypersurface,one can get the long-time existence for the inverse curvature flow.Moreover,we also get that the principal curvatures of the evolving hypersurface converge to 1 when t→+∞.展开更多
BACKGROUND Down syndrome(DS)is one of the most common causes of intellectual disability.Children with DS have varying intelligence quotient(IQ)that can predict their learning abilities.AIM To assess the brain metaboli...BACKGROUND Down syndrome(DS)is one of the most common causes of intellectual disability.Children with DS have varying intelligence quotient(IQ)that can predict their learning abilities.AIM To assess the brain metabolic profiles of children with DS and compare them to standard controls,using magnetic resonance spectroscopy(MRS)and correlating the results with IQ.METHODS This case-control study included 40 children with DS aged 6-15 years and 40 age and sex-matched healthy children as controls.MRS was used to evaluate ratios of choline/creatine(Cho/Cr),N-acetyl aspartic acid/creatine(NAA/Cr),and myoinositol/creatine(MI/Cr(in the frontal,temporal,and occipital lobes and basal ganglia and compared to controls and correlated with IQ.RESULTS Children with DS showed significant reductions in NAA/Cr and MI/Cr and a non-significant reduction in Cho/Cr in frontal lobes compared to controls.Additionally,we observed significant decreases in NAA/Cr,MI/Cr,and Cho/Cr in the temporal and occipital lobes and basal ganglia in children with DS compared to controls.Furthermore,there was a significant correlation between IQ and metabolic ratios in the brains of children with DS.CONCLUSION Brain metabolic profile could be a good predictor of IQ in children with DS.展开更多
Diophantine equations have always fascinated mathematicians about existence, finitude, and the calculation of possible solutions. Among these equations, one of them will be the object of our research. This is the Pyth...Diophantine equations have always fascinated mathematicians about existence, finitude, and the calculation of possible solutions. Among these equations, one of them will be the object of our research. This is the Pythagoras’- Fermat’s equation defined as follows. (1) when , it is well known that this equation has an infinity of solutions but has none (non-trivial) when . We also know that the last result, named Fermat-Wiles theorem (or FLT) was obtained at great expense and its understanding remains out of reach even for a good fringe of professional mathematicians. The aim of this research is to set up new simple but effective tools in the treatment of Diophantine equations and that of Pythagoras-Fermat. The tools put forward in this research are the properties of the quotients and the Diophantine remainders which we define as follows. Let a non-trivial triplet () solution of Equation (1) such that . and are called the Diophantine quotients and remainders of solution . We compute the remainder and the quotient of b and c by a using the division algorithm. Hence, we have: and et with . We prove the following important results. if and only if and if and only if . Also, we deduce that or for any hypothetical solution . We illustrate these results by effectively computing the Diophantine quotients and remainders in the case of Pythagorean triplets using a Python program. In the end, we apply the previous properties to directly prove a partial result of FLT. .展开更多
随着工业化进程的加快和城市化的发展,大量污染物排入黄河流域,并被频繁检出,威胁生态系统和人类健康。为获取潜在生态环境风险污染物,该研究通过调研2000年1月1日−2022年12月31日Web of Science(WoS)和中国知网(CNKI)数据库中黄河流域...随着工业化进程的加快和城市化的发展,大量污染物排入黄河流域,并被频繁检出,威胁生态系统和人类健康。为获取潜在生态环境风险污染物,该研究通过调研2000年1月1日−2022年12月31日Web of Science(WoS)和中国知网(CNKI)数据库中黄河流域已报道的288篇污染物相关文献,使用多指标综合评分法筛选黄河流域的特征污染物,采用风险商值法获取水样和沉积物中的风险污染物。结果表明:①黄河流域共检出10类144种污染物,采用9类共13个筛选指标构建多指标综合评分法,对污染物各项指标进行评分,然后进行K-means聚类分析,按得分高低分为Ⅰ~Ⅵ级,选取得分较高的33种Ⅰ级和Ⅱ级高分值污染物作为黄河流域特征污染物,包括12种有机氯农药、10种多环芳烃、10种多氯联苯和1种邻苯二甲酸酯。②水样污染物浓度和沉积物含量前5种都是重金属、有机氯农药、邻苯二甲酸酯、多环芳烃以及药品和个人护理产品,而且二者顺序完全一致,且多数污染物的浓度之间存在显著相关性。③根据风险最大化原则,使用风险商值法(RQ)分别对水样和沉积物进行风险评估,将RQ≥0.1的污染物列为风险污染物,水样中共筛选出21种风险污染物,其中RQ≥1的高风险污染物有5种,包括硒、铅、苯并[a,h]蒽、苯并[a]蒽和邻苯二甲酸二丁酯。④沉积物中共筛选出19种风险污染物,其中有13种高风险污染物,包括8种多环芳烃(芘、蒽、荧蒽、苊、萘、芴、苯并[a]蒽、苯并[a,h]蒽)、4种重金属(汞、铅、硒、砷)和1种邻苯二甲酸酯(邻苯二甲酸二丁酯)。该研究对相关部门拟定黄河流域污染物监测方案和管控措施有重要参考意义。展开更多
基金supported by the Scientific Research Fund of Hunan Provincial Education Department(21B0070)the Natural Science Foundation of Jiangsu Province(BK20231452)+1 种基金the Fundamental Research Funds for the Central Universities(30922010809)the National Natural Science Foundation of China(11801591,11971195,12071171,12171107,12201207,12371072)。
文摘For each real number x∈(0,1),let[a_(1)(x),a_(2)(x),…,a_n(x),…]denote its continued fraction expansion.We study the convergence exponent defined byτ(x)=inf{s≥0:∞∑n=1(a_(n)(x)a_(n+1)(x))^(-s)<∞},which reflects the growth rate of the product of two consecutive partial quotients.As a main result,the Hausdorff dimensions of the level sets ofτ(x)are determined.
文摘Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: M.A.R.I.E. enables the rational, quantified measurement of Emotional Visual Acuity (EVA) in an individual observer and a population aged 20 to 70 years. Meanwhile, it can measure the range and intensity of expressed emotions through three Face- Tests, quantify the performance of a sample of 204 observers with hypernormal measures of cognition, “thymia” (defined elsewhere), and low levels of anxiety, and perform analysis of the six primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual- Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Decision-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”, 6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Fingerprint-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.
基金supported by the Postdoctoral Fund of Zhejiang Province,China (ZJ2022004).
文摘In this paper,we study the asymptotic behavior of a class of inverse quotient curvature flow in the anti-de Sitter-Schwarzschild manifold.We prove that under suitable convex conditions for the initial hypersurface,one can get the long-time existence for the inverse curvature flow.Moreover,we also get that the principal curvatures of the evolving hypersurface converge to 1 when t→+∞.
文摘BACKGROUND Down syndrome(DS)is one of the most common causes of intellectual disability.Children with DS have varying intelligence quotient(IQ)that can predict their learning abilities.AIM To assess the brain metabolic profiles of children with DS and compare them to standard controls,using magnetic resonance spectroscopy(MRS)and correlating the results with IQ.METHODS This case-control study included 40 children with DS aged 6-15 years and 40 age and sex-matched healthy children as controls.MRS was used to evaluate ratios of choline/creatine(Cho/Cr),N-acetyl aspartic acid/creatine(NAA/Cr),and myoinositol/creatine(MI/Cr(in the frontal,temporal,and occipital lobes and basal ganglia and compared to controls and correlated with IQ.RESULTS Children with DS showed significant reductions in NAA/Cr and MI/Cr and a non-significant reduction in Cho/Cr in frontal lobes compared to controls.Additionally,we observed significant decreases in NAA/Cr,MI/Cr,and Cho/Cr in the temporal and occipital lobes and basal ganglia in children with DS compared to controls.Furthermore,there was a significant correlation between IQ and metabolic ratios in the brains of children with DS.CONCLUSION Brain metabolic profile could be a good predictor of IQ in children with DS.
文摘Diophantine equations have always fascinated mathematicians about existence, finitude, and the calculation of possible solutions. Among these equations, one of them will be the object of our research. This is the Pythagoras’- Fermat’s equation defined as follows. (1) when , it is well known that this equation has an infinity of solutions but has none (non-trivial) when . We also know that the last result, named Fermat-Wiles theorem (or FLT) was obtained at great expense and its understanding remains out of reach even for a good fringe of professional mathematicians. The aim of this research is to set up new simple but effective tools in the treatment of Diophantine equations and that of Pythagoras-Fermat. The tools put forward in this research are the properties of the quotients and the Diophantine remainders which we define as follows. Let a non-trivial triplet () solution of Equation (1) such that . and are called the Diophantine quotients and remainders of solution . We compute the remainder and the quotient of b and c by a using the division algorithm. Hence, we have: and et with . We prove the following important results. if and only if and if and only if . Also, we deduce that or for any hypothetical solution . We illustrate these results by effectively computing the Diophantine quotients and remainders in the case of Pythagorean triplets using a Python program. In the end, we apply the previous properties to directly prove a partial result of FLT. .
文摘随着工业化进程的加快和城市化的发展,大量污染物排入黄河流域,并被频繁检出,威胁生态系统和人类健康。为获取潜在生态环境风险污染物,该研究通过调研2000年1月1日−2022年12月31日Web of Science(WoS)和中国知网(CNKI)数据库中黄河流域已报道的288篇污染物相关文献,使用多指标综合评分法筛选黄河流域的特征污染物,采用风险商值法获取水样和沉积物中的风险污染物。结果表明:①黄河流域共检出10类144种污染物,采用9类共13个筛选指标构建多指标综合评分法,对污染物各项指标进行评分,然后进行K-means聚类分析,按得分高低分为Ⅰ~Ⅵ级,选取得分较高的33种Ⅰ级和Ⅱ级高分值污染物作为黄河流域特征污染物,包括12种有机氯农药、10种多环芳烃、10种多氯联苯和1种邻苯二甲酸酯。②水样污染物浓度和沉积物含量前5种都是重金属、有机氯农药、邻苯二甲酸酯、多环芳烃以及药品和个人护理产品,而且二者顺序完全一致,且多数污染物的浓度之间存在显著相关性。③根据风险最大化原则,使用风险商值法(RQ)分别对水样和沉积物进行风险评估,将RQ≥0.1的污染物列为风险污染物,水样中共筛选出21种风险污染物,其中RQ≥1的高风险污染物有5种,包括硒、铅、苯并[a,h]蒽、苯并[a]蒽和邻苯二甲酸二丁酯。④沉积物中共筛选出19种风险污染物,其中有13种高风险污染物,包括8种多环芳烃(芘、蒽、荧蒽、苊、萘、芴、苯并[a]蒽、苯并[a,h]蒽)、4种重金属(汞、铅、硒、砷)和1种邻苯二甲酸酯(邻苯二甲酸二丁酯)。该研究对相关部门拟定黄河流域污染物监测方案和管控措施有重要参考意义。
