In contemporary society,film,as a significant form of cultural expression,bears profound ideological connotations and cultural significance.Religious films,as a distinct genre,serve as crucial avenues for humanity to ...In contemporary society,film,as a significant form of cultural expression,bears profound ideological connotations and cultural significance.Religious films,as a distinct genre,serve as crucial avenues for humanity to explore and contemplate religious beliefs,moral concepts,and the essence of existence.Plato’s philosophy,as a significant pillar of Western thought,exerted profound influence on the conception and depiction of religious films.This thesis aims to examine Plato’s philosophical impact on religious cinema,elucidating its significance and value via comprehensive analysis of his ideas and their manifestation in religious films.Platonic ideas transcend the realm of emotions,inciting moral conflicts and dilemmas in religious films,thereby probing the dynamics between good and evil,justice and injustice.Plato’s political concepts offer profound sociopolitical reflections within religious films,stimulating discourse on matters like authority,governance,and liberty.Additionally,it catalyzed inquiries into aesthetics and emotions.Plato’s appreciation and pursuit of beauty resonate extensively in religious films,guiding viewers into a transcendent aesthetic realm through depictions of beauty and emotion.This holds immense theoretical and practical significance in deepening individuals’comprehension of Plato’s philosophy,fostering cultural exchange and discourse,and augmenting the artistic merit and societal impact of religious films.展开更多
We first look at the possibility that the ideas of event horizons for black holes may have their application only in early universe conditions whereas Corda’s ground breaking work rejecting event horizons may be due ...We first look at the possibility that the ideas of event horizons for black holes may have their application only in early universe conditions whereas Corda’s ground breaking work rejecting event horizons may be due to the formation of quantum mechanics free of an embedding in 5 dimensions allowing for a simpler more direct approach, which rejects the idea of a firewall. First, we present the idea of classical black hole physics applied only once as for the early universe, whereas in such a setting, there may be a way to present NLED and structure formation due to an initial entropy approach as outlined. Then the ideas of Corda’s breakthrough are presented for the reasons he illuminated in his recent work, due to QM being fully formed separate from higher dimensional embedding after the initial evolution of the universe.展开更多
Water is the most abundant liquid on the surface of the earth. It is a liquid whose properties are quite surprising, both as a pure liquid and as a solvent. Water is a very cohesive liquid: its melting and vaporizatio...Water is the most abundant liquid on the surface of the earth. It is a liquid whose properties are quite surprising, both as a pure liquid and as a solvent. Water is a very cohesive liquid: its melting and vaporization temperatures are very high for a liquid that is neither ionic nor metallic, and whose molar mass is low. Thus, water remains liquid at atmospheric pressure up to 100C while similar molecules such as H2S, H2Se, H2Te for example would give a vaporization temperature close to 80C. This cohesion is in fact ensured by hydrogen bonds between water molecules. This type of bonds between neighboring molecules, hydrogen bonds, is quite often found in chemistry [1] [2]. Any change in the state of aggregation of a substance occurs with the absorption or release of a certain amount of latent heat of transformation. Latent heat of fusion, vaporization or sublimation is the ratio of the energy supplied as heat to the mass of the substance that is melted, vaporized or sublimated. As a result of the reversibility of the processes, the fusion heat is equal to the heat released in the reverse process: crystallization and solidification heat. And likewise the heat of vaporization is equal to the heat of condensation. This equality of heat is often used to determine experimentally either of these quantities. There are two main measurement methods: 1) Direct measurement using the calorimeter, 2) Indirect measure based on the use of the VantHoff relationship. The objective of this work is to measure the latent heat of water vaporization and verify the compatibility of the experimental values with the values given by the tables using the indirect method.展开更多
Efficient exploration in complex coordination tasks has been considered a challenging problem in multi-agent reinforcement learning(MARL). It is significantly more difficult for those tasks with latent variables that ...Efficient exploration in complex coordination tasks has been considered a challenging problem in multi-agent reinforcement learning(MARL). It is significantly more difficult for those tasks with latent variables that agents cannot directly observe. However, most of the existing latent variable discovery methods lack a clear representation of latent variables and an effective evaluation of the influence of latent variables on the agent. In this paper, we propose a new MARL algorithm based on the soft actor-critic method for complex continuous control tasks with confounders. It is called the multi-agent soft actor-critic with latent variable(MASAC-LV) algorithm, which uses variational inference theory to infer the compact latent variables representation space from a large amount of offline experience.Besides, we derive the counterfactual policy whose input has no latent variables and quantify the difference between the actual policy and the counterfactual policy via a distance function. This quantified difference is considered an intrinsic motivation that gives additional rewards based on how much the latent variable affects each agent. The proposed algorithm is evaluated on two collaboration tasks with confounders, and the experimental results demonstrate the effectiveness of MASAC-LV compared to other baseline algorithms.展开更多
Bayesian networks are a powerful class of graphical decision models used to represent causal relationships among variables.However,the reliability and integrity of learned Bayesian network models are highly dependent ...Bayesian networks are a powerful class of graphical decision models used to represent causal relationships among variables.However,the reliability and integrity of learned Bayesian network models are highly dependent on the quality of incoming data streams.One of the primary challenges with Bayesian networks is their vulnerability to adversarial data poisoning attacks,wherein malicious data is injected into the training dataset to negatively influence the Bayesian network models and impair their performance.In this research paper,we propose an efficient framework for detecting data poisoning attacks against Bayesian network structure learning algorithms.Our framework utilizes latent variables to quantify the amount of belief between every two nodes in each causal model over time.We use our innovative methodology to tackle an important issue with data poisoning assaults in the context of Bayesian networks.With regard to four different forms of data poisoning attacks,we specifically aim to strengthen the security and dependability of Bayesian network structure learning techniques,such as the PC algorithm.By doing this,we explore the complexity of this area and offer workablemethods for identifying and reducing these sneaky dangers.Additionally,our research investigates one particular use case,the“Visit to Asia Network.”The practical consequences of using uncertainty as a way to spot cases of data poisoning are explored in this inquiry,which is of utmost relevance.Our results demonstrate the promising efficacy of latent variables in detecting and mitigating the threat of data poisoning attacks.Additionally,our proposed latent-based framework proves to be sensitive in detecting malicious data poisoning attacks in the context of stream data.展开更多
Latent tuberculosis infection(LTBI)has become a major source of active tuberculosis(ATB).Although the tuberculin skin test and interferon-gamma release assay can be used to diagnose LTBI,these methods can only differe...Latent tuberculosis infection(LTBI)has become a major source of active tuberculosis(ATB).Although the tuberculin skin test and interferon-gamma release assay can be used to diagnose LTBI,these methods can only differentiate infected individuals from healthy ones but cannot discriminate between LTBI and ATB.Thus,the diagnosis of LTBI faces many challenges,such as the lack of effective biomarkers from Mycobacterium tuberculosis(MTB)for distinguishing LTBI,the low diagnostic efficacy of biomarkers derived from the human host,and the absence of a gold standard to differentiate between LTBI and ATB.Sputum culture,as the gold standard for diagnosing tuberculosis,is time-consuming and cannot distinguish between ATB and LTBI.In this article,we review the pathogenesis of MTB and the immune mechanisms of the host in LTBI,including the innate and adaptive immune responses,multiple immune evasion mechanisms of MTB,and epigenetic regulation.Based on this knowledge,we summarize the current status and challenges in diagnosing LTBI and present the application of machine learning(ML)in LTBI diagnosis,as well as the advantages and limitations of ML in this context.Finally,we discuss the future development directions of ML applied to LTBI diagnosis.展开更多
As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decompos...As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decomposition of the input space by DiPLS,there are false alarms in the actual industrial process during fault detection.To address the above problems,a dynamic modeling method based on autoregressive-dynamic inner total PLS(AR-DiTPLS)is proposed.The method first uses the regression relation matrix to decompose the input space orthogonally,which reduces useless information for the predic-tion output in the quality-related dynamic subspace.Then,a vector autoregressive model(VAR)is constructed for the predic-tion score to separate dynamic information and static informa-tion.Based on the VAR model,appropriate statistical indicators are further constructed for online monitoring,which reduces the occurrence of false alarms.The effectiveness of the method is verified by a Tennessee-Eastman industrial simulation process and a three-phase flow system.展开更多
In recent years,speculation of an increase in Internet Gaming Disorder(IGD)has surfaced with the growing popularity of internet gaming among Chinese children and adolescents.The detrimental impact of IGD on mental hea...In recent years,speculation of an increase in Internet Gaming Disorder(IGD)has surfaced with the growing popularity of internet gaming among Chinese children and adolescents.The detrimental impact of IGD on mental health cannot be denied,even though only a small portion of the screen-dependent population exhibits psychopathological and behavioral symptoms.The present study aimed to explore a latent profile analysis(LPA)of Internet Gaming Disorder on the mental health of Chinese school students.The data were collected from a sample of 1005 Chinese school students(49.8%male;age M=13.32,SD=1.34 years)using a paper-pencil survey through convenience sampling.LPA explored three latent profiles of internet gamers:regular gamers(62.4%),moderate gamers(28.1%),and probable disordered gamers(9.4%).Results showed that the probable disordered gamers had significantly higher levels of depression,anxiety,emotional and conduct problems,hyperactivity,and peer problem symptoms as well as lower life satisfaction,and pro-social symptoms compared to regular and moderate gamers(p<0.05).This study would be helpful to mental health professionals in designing interventions for gamers who present IGD symptoms.Future longitudinal studies should also be undertaken to assess whether mental health worsens for probable disordered gamers.展开更多
文摘In contemporary society,film,as a significant form of cultural expression,bears profound ideological connotations and cultural significance.Religious films,as a distinct genre,serve as crucial avenues for humanity to explore and contemplate religious beliefs,moral concepts,and the essence of existence.Plato’s philosophy,as a significant pillar of Western thought,exerted profound influence on the conception and depiction of religious films.This thesis aims to examine Plato’s philosophical impact on religious cinema,elucidating its significance and value via comprehensive analysis of his ideas and their manifestation in religious films.Platonic ideas transcend the realm of emotions,inciting moral conflicts and dilemmas in religious films,thereby probing the dynamics between good and evil,justice and injustice.Plato’s political concepts offer profound sociopolitical reflections within religious films,stimulating discourse on matters like authority,governance,and liberty.Additionally,it catalyzed inquiries into aesthetics and emotions.Plato’s appreciation and pursuit of beauty resonate extensively in religious films,guiding viewers into a transcendent aesthetic realm through depictions of beauty and emotion.This holds immense theoretical and practical significance in deepening individuals’comprehension of Plato’s philosophy,fostering cultural exchange and discourse,and augmenting the artistic merit and societal impact of religious films.
文摘We first look at the possibility that the ideas of event horizons for black holes may have their application only in early universe conditions whereas Corda’s ground breaking work rejecting event horizons may be due to the formation of quantum mechanics free of an embedding in 5 dimensions allowing for a simpler more direct approach, which rejects the idea of a firewall. First, we present the idea of classical black hole physics applied only once as for the early universe, whereas in such a setting, there may be a way to present NLED and structure formation due to an initial entropy approach as outlined. Then the ideas of Corda’s breakthrough are presented for the reasons he illuminated in his recent work, due to QM being fully formed separate from higher dimensional embedding after the initial evolution of the universe.
文摘Water is the most abundant liquid on the surface of the earth. It is a liquid whose properties are quite surprising, both as a pure liquid and as a solvent. Water is a very cohesive liquid: its melting and vaporization temperatures are very high for a liquid that is neither ionic nor metallic, and whose molar mass is low. Thus, water remains liquid at atmospheric pressure up to 100C while similar molecules such as H2S, H2Se, H2Te for example would give a vaporization temperature close to 80C. This cohesion is in fact ensured by hydrogen bonds between water molecules. This type of bonds between neighboring molecules, hydrogen bonds, is quite often found in chemistry [1] [2]. Any change in the state of aggregation of a substance occurs with the absorption or release of a certain amount of latent heat of transformation. Latent heat of fusion, vaporization or sublimation is the ratio of the energy supplied as heat to the mass of the substance that is melted, vaporized or sublimated. As a result of the reversibility of the processes, the fusion heat is equal to the heat released in the reverse process: crystallization and solidification heat. And likewise the heat of vaporization is equal to the heat of condensation. This equality of heat is often used to determine experimentally either of these quantities. There are two main measurement methods: 1) Direct measurement using the calorimeter, 2) Indirect measure based on the use of the VantHoff relationship. The objective of this work is to measure the latent heat of water vaporization and verify the compatibility of the experimental values with the values given by the tables using the indirect method.
基金supported in part by the National Natural Science Foundation of China (62136008,62236002,61921004,62173251,62103104)the “Zhishan” Scholars Programs of Southeast Universitythe Fundamental Research Funds for the Central Universities (2242023K30034)。
文摘Efficient exploration in complex coordination tasks has been considered a challenging problem in multi-agent reinforcement learning(MARL). It is significantly more difficult for those tasks with latent variables that agents cannot directly observe. However, most of the existing latent variable discovery methods lack a clear representation of latent variables and an effective evaluation of the influence of latent variables on the agent. In this paper, we propose a new MARL algorithm based on the soft actor-critic method for complex continuous control tasks with confounders. It is called the multi-agent soft actor-critic with latent variable(MASAC-LV) algorithm, which uses variational inference theory to infer the compact latent variables representation space from a large amount of offline experience.Besides, we derive the counterfactual policy whose input has no latent variables and quantify the difference between the actual policy and the counterfactual policy via a distance function. This quantified difference is considered an intrinsic motivation that gives additional rewards based on how much the latent variable affects each agent. The proposed algorithm is evaluated on two collaboration tasks with confounders, and the experimental results demonstrate the effectiveness of MASAC-LV compared to other baseline algorithms.
文摘Bayesian networks are a powerful class of graphical decision models used to represent causal relationships among variables.However,the reliability and integrity of learned Bayesian network models are highly dependent on the quality of incoming data streams.One of the primary challenges with Bayesian networks is their vulnerability to adversarial data poisoning attacks,wherein malicious data is injected into the training dataset to negatively influence the Bayesian network models and impair their performance.In this research paper,we propose an efficient framework for detecting data poisoning attacks against Bayesian network structure learning algorithms.Our framework utilizes latent variables to quantify the amount of belief between every two nodes in each causal model over time.We use our innovative methodology to tackle an important issue with data poisoning assaults in the context of Bayesian networks.With regard to four different forms of data poisoning attacks,we specifically aim to strengthen the security and dependability of Bayesian network structure learning techniques,such as the PC algorithm.By doing this,we explore the complexity of this area and offer workablemethods for identifying and reducing these sneaky dangers.Additionally,our research investigates one particular use case,the“Visit to Asia Network.”The practical consequences of using uncertainty as a way to spot cases of data poisoning are explored in this inquiry,which is of utmost relevance.Our results demonstrate the promising efficacy of latent variables in detecting and mitigating the threat of data poisoning attacks.Additionally,our proposed latent-based framework proves to be sensitive in detecting malicious data poisoning attacks in the context of stream data.
文摘Latent tuberculosis infection(LTBI)has become a major source of active tuberculosis(ATB).Although the tuberculin skin test and interferon-gamma release assay can be used to diagnose LTBI,these methods can only differentiate infected individuals from healthy ones but cannot discriminate between LTBI and ATB.Thus,the diagnosis of LTBI faces many challenges,such as the lack of effective biomarkers from Mycobacterium tuberculosis(MTB)for distinguishing LTBI,the low diagnostic efficacy of biomarkers derived from the human host,and the absence of a gold standard to differentiate between LTBI and ATB.Sputum culture,as the gold standard for diagnosing tuberculosis,is time-consuming and cannot distinguish between ATB and LTBI.In this article,we review the pathogenesis of MTB and the immune mechanisms of the host in LTBI,including the innate and adaptive immune responses,multiple immune evasion mechanisms of MTB,and epigenetic regulation.Based on this knowledge,we summarize the current status and challenges in diagnosing LTBI and present the application of machine learning(ML)in LTBI diagnosis,as well as the advantages and limitations of ML in this context.Finally,we discuss the future development directions of ML applied to LTBI diagnosis.
基金supported by the National Natural Science Foundation of China(62273354,61673387,61833016).
文摘As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decomposition of the input space by DiPLS,there are false alarms in the actual industrial process during fault detection.To address the above problems,a dynamic modeling method based on autoregressive-dynamic inner total PLS(AR-DiTPLS)is proposed.The method first uses the regression relation matrix to decompose the input space orthogonally,which reduces useless information for the predic-tion output in the quality-related dynamic subspace.Then,a vector autoregressive model(VAR)is constructed for the predic-tion score to separate dynamic information and static informa-tion.Based on the VAR model,appropriate statistical indicators are further constructed for online monitoring,which reduces the occurrence of false alarms.The effectiveness of the method is verified by a Tennessee-Eastman industrial simulation process and a three-phase flow system.
基金supported by the Postdoctoral Research Fund of School of Psychology,Zhejiang Normal University(No.ZC304022990).
文摘In recent years,speculation of an increase in Internet Gaming Disorder(IGD)has surfaced with the growing popularity of internet gaming among Chinese children and adolescents.The detrimental impact of IGD on mental health cannot be denied,even though only a small portion of the screen-dependent population exhibits psychopathological and behavioral symptoms.The present study aimed to explore a latent profile analysis(LPA)of Internet Gaming Disorder on the mental health of Chinese school students.The data were collected from a sample of 1005 Chinese school students(49.8%male;age M=13.32,SD=1.34 years)using a paper-pencil survey through convenience sampling.LPA explored three latent profiles of internet gamers:regular gamers(62.4%),moderate gamers(28.1%),and probable disordered gamers(9.4%).Results showed that the probable disordered gamers had significantly higher levels of depression,anxiety,emotional and conduct problems,hyperactivity,and peer problem symptoms as well as lower life satisfaction,and pro-social symptoms compared to regular and moderate gamers(p<0.05).This study would be helpful to mental health professionals in designing interventions for gamers who present IGD symptoms.Future longitudinal studies should also be undertaken to assess whether mental health worsens for probable disordered gamers.
