A Study of Static and Dynamic Mechanical Behavior of the Substrate in Ultrasonic Consolidation

A new 2-D FEM model is developed for a fundamental study of the time dependent mechanical behavior of the substrate in ultrasonic consolidation. The simulation shows that for a given vibration condition, the amplitude of contact friction stress and displacement stabilize to a saturated state after certain number of ultrasonic cycles. With the increased substrate height, the amplitude of contact frictional stress decreases, while that of contact interface displacement increases. The energy density and transfer coefficient at the contact interface with different substrate heights can be used as parameters to predict the potential for ultrasonic bonding. The reason for the decrease in the frictional stress and displacement at the contact interface for certain substrate height seems to be caused by the complicated wave interference occurring in the substrate. A specific substrate geometry generates a minimum strain state at the interface as a result of wave superposition. Such minimum strain state is believed to have produced the “lack of bonding” defect.Mechanical Engineerin

Residential Energy Consumption in Urban China

Residential energy consumption (REC) is the second largest energy use category (10%) in China and urban residents account for most of the REC. Understanding the underlying drivers of variations of urban REC thus helps to identify challenges and opportunities and provide advices for future policy measures. This paper applies the logarithmic mean Divisia index (LMDI) to a decomposition of China’s urban REC during the period of 1998-2007 at disaggregated product/activity level using data collected from a wide range of sources. Our results have shown an extensive structure change towards a more energy-intensive household consumption structure as well as an intensive structure change towards high-quality and cleaner energy such as electricity, oil, and natural gas, which reflects a changing life style and consumption mode in pursuit of a higher level of comfort, convenience and environmental protection. We have also found that China’s price reforms in the energy sector have contributed to a reduction of REC while scale factors including increased urban population and income levels have played a key role in the rapid growth of REC. We suggest that further deregulation in energy prices and regulatory as well as voluntary energy efficiency and conservation policies in the residential sector should be promoted.Residential Energy Consumption, Index Decomposition Analysis (IDA), China, Consumer/Household Economics, Resource /Energy Economics and Policy, Q32, Q43,

Schizophrenia research under the framework of predictive coding: body, language, and others

Although there have been so many studies on schizophrenia under the framework of predictive coding, works focusing on treatment are very preliminary. A model-oriented, operationalist, and comprehensive understanding of schizophrenia would promote the therapy turn of further research. We summarize predictive coding models of embodiment, co-occurrence of over- and under-weighting priors, subjective time processing, language production or comprehension, self-or-other inference, and social interaction. Corresponding impairments and clinical manifestations of schizophrenia are reviewed under these models at the same time. Finally, we discuss why and how to inaugurate a therapy turn of further research under the framework of predictive coding

Enabling self-identification in intelligent agent: insights from computational psychoanalysis

Building upon prior framework of computational Lacanian psychoanalysis with the theory of active inference, this paper aims to further explore the concept of self-identification and its potential applications. Beginning with two classic paradigms in psychology, mirror self-recognition and rubber hand illusion, we suggest that imaginary identification is characterized by an integrated body schema with minimal free energy. Next, we briefly survey three dimensions of symbolic identification (sociological, psychoanalytic, and linguistical) and corresponding active inference accounts. To provide intuition, we respectively employ a convolutional neural network (CNN) and a multi-layer perceptron (MLP) supervised by ChatGPT to showcase optimization of free energy during motor skill and language mastery underlying identification formation. We then introduce Lacan's Graph II of desire, unifying imaginary and symbolic identification, and propose an illustrative model called FreeAgent. In concluding remarks, we discuss some key issues in the potential of computational Lacanian psychoanalysis to advance mental health and artificial intelligence, including digital twin mind, large language models as avatars of the Lacanian Other, and the feasibility of human-level artificial general intelligence with self-awareness in the context of post-structuralism.Comment: 18 pages, 3 figure

An active inference model of Lacanian psychoanalysis

There has been a growing interest in exploring behavior, brain, and mind through the lens of complex systems theory. However, a unified and computational model that comprehensively encapsulates the properties of the human mind remains elusive. To address this gap, we propose a recurrent generative model drawing upon with Lacanian psychoanalysis and active inference. We conceptualize mechanism of desire as partial generalized synchronization, and then apply the model to suicidal dynamics to illustrate the theoretical and practical implications of our model. This work on computational psychoanalysis reveals its potential in unraveling complex mental phenomena

Research progress of exercise therapy for depressive disorder

Depressive disorder, as one of the major diseases in the world, has always received much attention for its prevention and treatment. As an emerging treatment, exercise therapy has optimistic application prospect with the advantages such as lower cost, fewer side effects and easier implementation, compared to conventional treatments such as drug therapy and physical therapy. Relevant studies have explored the mechanism of exercise in the treatment of depressive disorder, but the mechanism is not clear yet, which may involve improving the levels of neurobiochemical molecules, inhibiting inflammatory response, regulating neuroendocrine system, improving neuroplasticity, and other aspects. Exercise therapy has been proved to have similar biological effects with antidepressants, and may have overlapping effects with other treatments. Early intervention can benefit both non- diseased and already diseased populations to a certain extent. At present, there is still a gap in the clinical field related to exercise therapy for depressive disorder, and there are few high-quality studies. The design of exercise therapy plans is still in the exploratory stage, and there is no consensus on the design of exercise therapy plans. Additionally, there is a lack of relevant exercise therapy guidelines for clinicians to refer to. This review systematically introduces the biological mechanism of exercise therapy for depressive disorder, summarizes the clinical research results in this field carried out at home and abroad, and analyzes the current program and advantages and disadvantages of exercise therapy, in order to provide reference for the in-depth development of the exercise therapy researches

The Moderating Role of COMT and BDNF Polymorphisms on Transfer Effects Following Multi- and Single-Domain Cognitive Training Among Community-Dwelling Shanghainese Older Adults

Given the increase in research suggesting benefit following cognitive training in older adults, researchers have started to investigate the potential moderating role of genetic polymorphisms on transfer effects. The objective of this study was to evaluate the moderating effect of catechol-O-methyltransferase (COMT) and brain-derived neurotrophic factor (BDNF) polymorphisms on transfer effects following a single-domain or multi-domain training intervention in healthy community-dwelling older adults. A total of 104 men and women living in Shanghai were randomized to a multi-domain or a single-domain cognitive training (SDCT) group. COMT rs4818 SNP and the BDNF rs6265 SNP were analyzed from blood. At pre-intervention, post-intervention and at 6-month follow-up, participants completed the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), the Color-Word Stroop Test (CWST), the Trails Making Test (TMT) and the Visual Reasoning Test (VRT). COMT was found to moderate immediate memory transfer effects following single-domain training only, with G/- carriers displaying greater benefits than C/C carriers. BDNF was found to moderate attention and inhibition independent of the training, with Met/- carriers displaying better performance than Val/Val carriers. Overall, individualizing training methods with full consideration of genetic polymorphisms may promote the maximization of cognitive training benefits

Dissecting the Single-Cell Transcriptome Network of Immune Environment Underlying Cervical Premalignant Lesion, Cervical Cancer and Metastatic Lymph Nodes

Cervical cancer (CC) is one of the most common malignancy in women worldwide. It is characterized by a natural continuous phenomenon, that is, it is in the initial stage of HPV infection, progresses to intraepithelial neoplasia, and then develops into invasion and metastasis. Determining the complexity of tumor microenvironment (TME) can deepen our understanding of lesion progression and provide novel therapeutic strategies for CC. We performed the single-cell RNA sequencing on the normal cervix, intraepithelial neoplasia, primary tumor and metastatic lymph node tissues to describe the composition, lineage, and functional status of immune cells and mesenchymal cells at different stages of CC progression. A total of 59913 single cells were obtained and divided into 9 cellular clusters, including immune cells (T/NK cells, macrophages, B cells, plasma cells, mast cells and neutrophils) and mesenchymal cells (endothelial cells, smooth muscle cells and fibroblasts). Our results showed that there were distinct cell subpopulations in different stages of CC. High-stage intraepithelial neoplasia (HSIL) tissue exhibited a low, recently activated TME, and it was characterized by high infiltration of tissue-resident CD8 T cell, effector NK cells, Treg, DC1, pDC, and M1-like macrophages. Tumor tissue displayed high enrichment of exhausted CD8 T cells, resident NK cells and M2-like macrophages, suggesting immunosuppressive TME. Metastatic lymph node consisted of naive T cell, central memory T cell, circling NK cells, cytotoxic CD8+ T cells and effector memory CD8 T cells, suggesting an early activated phase of immune response. This study is the first to delineate the transcriptome profile of immune cells during CC progression using single-cell RNA sequencing. Our results indicated that HSIL exhibited a low, recently activated TME, tumor displayed immunosuppressive statue, and metastatic lymph node showed early activated phase of immune response. Our study enhanced the understanding of dynamic change of TME during CC progression and has implications for the development of novel treatments to inhibit the initiation and progression of CC