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
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: With M.A.R.I.E. enable a rational quantified measurement of Emotional-Visual-Acuity (EVA) of 1) a) an individual observer, b) in a population aged 20 to 70 years old, 2) measure the range and intensity of expressed emotions by 3 Face-Tests, 3) quantify the performance of a sample of 204 observers with hyper normal measures of cognition, “thymia,” (ibid. defined elsewhere) and low levels of anxiety 4) analysis of the 6 primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual-Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Deci-sion-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Finger-print-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
Candidiasis, also known as candidiasis vulvovaginitis, is an infection caused by different types of Candida fungi, the most frequent being Candida albicans. The present study reports an effective strategy, which opens...Candidiasis, also known as candidiasis vulvovaginitis, is an infection caused by different types of Candida fungi, the most frequent being Candida albicans. The present study reports an effective strategy, which opens new avenues for the treatment of this public health problem. The MAC<sup>®</sup> Methodology, conventional laser light-emitting (LLLT)/LED) methods are based on the biphasic response demonstrated many times in LLLT research and as with other forms of drugs, a “drug” (irradiation parameters) and a “dose” (irradiation times) and the “Arndt-Schulz Law” is often cited as a suitable model to describe the dose-dependent effects of LLLT. This method uses photopharmaceuticals, cell markers and the use of correct parameters for each case to induce the acceleration of tissue repair. The present study shows a case of a 32-year-old patient diagnosed with recurrent candidiasis 4 years ago. Eighteen sessions were performed (every other day) using a photoactivated component (Methylene blue 1% + Clotrimazole 1%) and LED phototherapy (red, blue and violet) with emission times of 60 - 260 seconds for each applicator, according to the dose recommendations of the scar acceleration method (MAC<sup>®</sup>). At the sixth treatment session there was a noticeable decrease in the itching sensation reported by the patient. In session 11 she reported feeling a great improvement, indicating that she no longer felt itching in any area after 18 sessions. The present case demonstrates new methodologies to treat common problems in the population that have a positive impact on the quality of life. This methodology has a promising future because it is non-invasive and requires a great biological transformation for inflammatory, fungal and viral control.展开更多
Professor M.A. （Alexandrovich） Guzev is a physics graduate of theUniversity of Leningrad （now Saint Petersburg, 1984）. He began hisscientific career at the Institute of Physics, Leningrad Universityin 1984. After ...Professor M.A. （Alexandrovich） Guzev is a physics graduate of theUniversity of Leningrad （now Saint Petersburg, 1984）. He began hisscientific career at the Institute of Physics, Leningrad Universityin 1984. After commencing his Ph.D. （Physics ＆ Mathematics） in1987, he continued his work as a researcher of Pacific OceanologicalInstitute, Far Eastern Branch of Russian Academy of Sciences（FEBRAS）, Vladivostok, Russia, from 1987 to 1991.展开更多
Ma Xiaoying, Assyriology, Ph.D., 1994.12 "Women’s Social Status in Old Babylonia Reflected in Marital Property" (Supervisors: Professors Lin Zhichun, Thomas Lee, Tova Meltzer, Wu Yuhong) Wang Liying, Cla...Ma Xiaoying, Assyriology, Ph.D., 1994.12 "Women’s Social Status in Old Babylonia Reflected in Marital Property" (Supervisors: Professors Lin Zhichun, Thomas Lee, Tova Meltzer, Wu Yuhong) Wang Liying, Classics, Ph.D., 1995.6 "Sallust’s Bellum Catilinae" (Supervisors: Porfessors Wang Dunshu, P.Ruth Taylor-Briggs, F. Ahlheid, Lin Zhichun)展开更多
Assyriology QI Xiao, MA The Reconstruction of the Archive of Ur-Kununna, the Scribe of Animal Center of Ur-III Dynasty (ulgi 43 ii - Ibbi-Sin 2 iv) (Supervisor: Wu Yuhong)
In terms of second language acquisition or learning, research on anxiety has primarily focused on foreign language classroom anxiety or test anxiety, with little attention paid to anxiety in the process of writing aca...In terms of second language acquisition or learning, research on anxiety has primarily focused on foreign language classroom anxiety or test anxiety, with little attention paid to anxiety in the process of writing academic theses. This study aims to explore to what extent anxiety affects the whole process of three English majors writing their M.A. theses, as well as testing the relationships between anxiety and self-regulation in the whole process. The findings indicate that anxiety appears with high degree atthe preparation stage, slumps at the writing stage and reaches another high level at the revision stage. Anxiety also exists when negotiating with supervisors. What’s more, self-regulation has been proved to alleviate anxiety in the process of writing. This studycontributes new knowledge to the field by relating anxiety to self-regulation in the process of writing M.A. theses, yielding a deepened understanding of self-regulation that reduces anxiety in terms of the progress gradually achieved in the writing process. It alsohas implications for supervisors to pay attention to the way of negotiating with students that may cause anxiety during the academictheses writing process.展开更多
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.
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: With M.A.R.I.E. enable a rational quantified measurement of Emotional-Visual-Acuity (EVA) of 1) a) an individual observer, b) in a population aged 20 to 70 years old, 2) measure the range and intensity of expressed emotions by 3 Face-Tests, 3) quantify the performance of a sample of 204 observers with hyper normal measures of cognition, “thymia,” (ibid. defined elsewhere) and low levels of anxiety 4) analysis of the 6 primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual-Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Deci-sion-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Finger-print-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.
文摘Candidiasis, also known as candidiasis vulvovaginitis, is an infection caused by different types of Candida fungi, the most frequent being Candida albicans. The present study reports an effective strategy, which opens new avenues for the treatment of this public health problem. The MAC<sup>®</sup> Methodology, conventional laser light-emitting (LLLT)/LED) methods are based on the biphasic response demonstrated many times in LLLT research and as with other forms of drugs, a “drug” (irradiation parameters) and a “dose” (irradiation times) and the “Arndt-Schulz Law” is often cited as a suitable model to describe the dose-dependent effects of LLLT. This method uses photopharmaceuticals, cell markers and the use of correct parameters for each case to induce the acceleration of tissue repair. The present study shows a case of a 32-year-old patient diagnosed with recurrent candidiasis 4 years ago. Eighteen sessions were performed (every other day) using a photoactivated component (Methylene blue 1% + Clotrimazole 1%) and LED phototherapy (red, blue and violet) with emission times of 60 - 260 seconds for each applicator, according to the dose recommendations of the scar acceleration method (MAC<sup>®</sup>). At the sixth treatment session there was a noticeable decrease in the itching sensation reported by the patient. In session 11 she reported feeling a great improvement, indicating that she no longer felt itching in any area after 18 sessions. The present case demonstrates new methodologies to treat common problems in the population that have a positive impact on the quality of life. This methodology has a promising future because it is non-invasive and requires a great biological transformation for inflammatory, fungal and viral control.
文摘Professor M.A. （Alexandrovich） Guzev is a physics graduate of theUniversity of Leningrad （now Saint Petersburg, 1984）. He began hisscientific career at the Institute of Physics, Leningrad Universityin 1984. After commencing his Ph.D. （Physics ＆ Mathematics） in1987, he continued his work as a researcher of Pacific OceanologicalInstitute, Far Eastern Branch of Russian Academy of Sciences（FEBRAS）, Vladivostok, Russia, from 1987 to 1991.
文摘Ma Xiaoying, Assyriology, Ph.D., 1994.12 "Women’s Social Status in Old Babylonia Reflected in Marital Property" (Supervisors: Professors Lin Zhichun, Thomas Lee, Tova Meltzer, Wu Yuhong) Wang Liying, Classics, Ph.D., 1995.6 "Sallust’s Bellum Catilinae" (Supervisors: Porfessors Wang Dunshu, P.Ruth Taylor-Briggs, F. Ahlheid, Lin Zhichun)
文摘Assyriology QI Xiao, MA The Reconstruction of the Archive of Ur-Kununna, the Scribe of Animal Center of Ur-III Dynasty (ulgi 43 ii - Ibbi-Sin 2 iv) (Supervisor: Wu Yuhong)
文摘In terms of second language acquisition or learning, research on anxiety has primarily focused on foreign language classroom anxiety or test anxiety, with little attention paid to anxiety in the process of writing academic theses. This study aims to explore to what extent anxiety affects the whole process of three English majors writing their M.A. theses, as well as testing the relationships between anxiety and self-regulation in the whole process. The findings indicate that anxiety appears with high degree atthe preparation stage, slumps at the writing stage and reaches another high level at the revision stage. Anxiety also exists when negotiating with supervisors. What’s more, self-regulation has been proved to alleviate anxiety in the process of writing. This studycontributes new knowledge to the field by relating anxiety to self-regulation in the process of writing M.A. theses, yielding a deepened understanding of self-regulation that reduces anxiety in terms of the progress gradually achieved in the writing process. It alsohas implications for supervisors to pay attention to the way of negotiating with students that may cause anxiety during the academictheses writing process.
