Local Model Checking Algorithm Based on Mu-calculus with Partial Orders

The propositionalμ-calculus can be divided into two categories, global model checking algorithm and local model checking algorithm. Both of them aim at reducing time complexity and space complexity effectively. This paper analyzes the computing process of alternating fixpoint nested in detail and designs an efficient local model checking algorithm based on the propositional μ-calculus by a group of partial ordered relation, and its time complexity is O(d2(dn)d/2+2) (d is the depth of fixpoint nesting,  is the maximum of number of nodes), space complexity is O(d(dn)d/2). As far as we know, up till now, the best local model checking algorithm whose index of time complexity is d. In this paper, the index for time complexity of this algorithm is reduced from d to d/2. It is more efficient than algorithms of previous research

Perturbation-based Self-supervised Attention for Attention Bias in Text Classification

In text classification, the traditional attention mechanisms usually focus too much on frequent words, and need extensive labeled data in order to learn. This paper proposes a perturbation-based self-supervised attention approach to guide attention learning without any annotation overhead. Specifically, we add as much noise as possible to all the words in the sentence without changing their semantics and predictions. We hypothesize that words that tolerate more noise are less significant, and we can use this information to refine the attention distribution. Experimental results on three text classification tasks show that our approach can significantly improve the performance of current attention-based models, and is more effective than existing self-supervised methods. We also provide a visualization analysis to verify the effectiveness of our approach

CKNet: A Convolutional Neural Network Based on Koopman Operator for Modeling Latent Dynamics from Pixels

With the development of end-to-end control based on deep learning, it is important to study new system modeling techniques to realize dynamics modeling with high-dimensional inputs. In this paper, a novel Koopman-based deep convolutional network, called CKNet, is proposed to identify latent dynamics from raw pixels. CKNet learns an encoder and decoder to play the role of the Koopman eigenfunctions and modes, respectively. The Koopman eigenvalues can be approximated by eigenvalues of the learned state transition matrix. The deterministic convolutional Koopman network (DCKNet) and the variational convolutional Koopman network (VCKNet) are proposed to span some subspace for approximating the Koopman operator respectively. Because CKNet is trained under the constraints of the Koopman theory, the identified latent dynamics is in a linear form and has good interpretability. Besides, the state transition and control matrices are trained as trainable tensors so that the identified dynamics is also time-invariant. We also design an auxiliary weight term for reducing multi-step linearity and prediction losses. Experiments were conducted on two offline trained and four online trained nonlinear forced dynamical systems with continuous action spaces in Gym and Mujoco environment respectively, and the results show that identified dynamics are adequate for approximating the latent dynamics and generating clear images. Especially for offline trained cases, this work confirms CKNet from a novel perspective that we visualize the evolutionary processes of the latent states and the Koopman eigenfunctions with DCKNet and VCKNet separately to each task based on the same episode and results demonstrate that different approaches learn similar features in shapes.Comment: 8 pages, 7 figure

Research on the Problem of Old-Age Care in China From the Perspective of Ethics

The elders are an important driving force for economic development, social progress and national prosperity. The care of the elderly, as a universal world problem, is related to their dignity, human rights and social stability. Since 2000, China has stepped into the threshold of an aging society. With the increasing aging population and the influence of population, economy, culture, politics and other uniquely national conditions, the conflicts and problems over providing for the aged are more complicated and severe. It has become an urgent issue in China how to solve a series of ethical dilemmas of providing for the aged caused by the aging population.Firstly, we use the data of the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) for positivist research, and then adopt the ordered Probit regression model for analysis. Secondly, we present and discuss the existing ethical problems of providing for the aged in society: firstly, the unfairness of allocation of resources in the society for providing for the aged; secondly, the dilution of concept of filial piety in family; thirdly, the weakening of the trend of respecting the elderly in society; last but not least, the lack of good in old-age security system. In view of the above-mentioned ethical problems of providing for the aged in China, we propose some solutions, namely, fairly distributing old-age resources in society; promoting the cultural tradition of filial piety; improving the system of endowment policy. Focusing on the ethical issues of old-age care, this paper provides some ethical thoughts for the solution of them

Kaposi’s Sarcoma-Associated Herpesvirus Reduces Cellular Myeloid Differentiation Primary-Response Gene 88 (MyD88) Expression via Modulation of Its RNA

Kaposi’s sarcoma (KS)-associated herpesvirus (KSHV) is a human gammaherpesvirus associated with several human malignancies. The replication and transcription activator (RTA) is necessary and sufficient for the switch from KSHV latency to lytic replication. Interleukin 1 (IL-1) is a major mediator for inflammation and plays an important role in both innate and adaptive immunity. Myeloid differentiation primary response gene 88 (MyD88) is an essential adaptor molecule for IL-1 as well as most Toll-like receptor signaling. In this study, we identified a novel mechanism by which KSHV interferes with host inflammation and immunity. KSHV RTA specifically reduces the steady-state protein levels of MyD88, and physiological levels of MyD88 are downregulated during KSHV lytic replication when RTA is expressed. The N-terminal region of RTA is required for the reduction of MyD88. Additional studies demonstrated that RTA targets MyD88 expression at the RNA level, inhibits RNA synthesis of MyD88, and may bind MyD88 RNA. Finally, RTA inhibits IL-1-mediated activation of NF-B. Because IL-1 is abundant in the KS microenvironment and inhibits KSHV replication, this work may expand our understanding of how KSHV evades host inflammation and immunity for its survival in vivo

Kaposi’s Sarcoma-Associated Herpesvirus Reduces Cellular Myeloid Differentiation Primary-Response Gene 88 (MyD88) Expression via Modulation of Its RNA

Kaposi’s sarcoma (KS)-associated herpesvirus (KSHV) is a human gammaherpesvirus associated with several human malignancies. The replication and transcription activator (RTA) is necessary and sufficient for the switch from KSHV latency to lytic replication. Interleukin 1 (IL-1) is a major mediator for inflammation and plays an important role in both innate and adaptive immunity. Myeloid differentiation primary response gene 88 (MyD88) is an essential adaptor molecule for IL-1 as well as most Toll-like receptor signaling. In this study, we identified a novel mechanism by which KSHV interferes with host inflammation and immunity. KSHV RTA specifically reduces the steady-state protein levels of MyD88, and physiological levels of MyD88 are downregulated during KSHV lytic replication when RTA is expressed. The N-terminal region of RTA is required for the reduction of MyD88. Additional studies demonstrated that RTA targets MyD88 expression at the RNA level, inhibits RNA synthesis of MyD88, and may bind MyD88 RNA. Finally, RTA inhibits IL-1-mediated activation of NF-B. Because IL-1 is abundant in the KS microenvironment and inhibits KSHV replication, this work may expand our understanding of how KSHV evades host inflammation and immunity for its survival in vivo

Kaposi’s Sarcoma-Associated Herpesvirus Reduces Cellular Myeloid Differentiation Primary-Response Gene 88 (MyD88) Expression via Modulation of Its RNA

Kaposi’s sarcoma (KS)-associated herpesvirus (KSHV) is a human gammaherpesvirus associated with several human malignancies. The replication and transcription activator (RTA) is necessary and sufficient for the switch from KSHV latency to lytic replication. Interleukin 1 (IL-1) is a major mediator for inflammation and plays an important role in both innate and adaptive immunity. Myeloid differentiation primary response gene 88 (MyD88) is an essential adaptor molecule for IL-1 as well as most Toll-like receptor signaling. In this study, we identified a novel mechanism by which KSHV interferes with host inflammation and immunity. KSHV RTA specifically reduces the steady-state protein levels of MyD88, and physiological levels of MyD88 are downregulated during KSHV lytic replication when RTA is expressed. The N-terminal region of RTA is required for the reduction of MyD88. Additional studies demonstrated that RTA targets MyD88 expression at the RNA level, inhibits RNA synthesis of MyD88, and may bind MyD88 RNA. Finally, RTA inhibits IL-1-mediated activation of NF-B. Because IL-1 is abundant in the KS microenvironment and inhibits KSHV replication, this work may expand our understanding of how KSHV evades host inflammation and immunity for its survival in vivo

Kaposi’s Sarcoma-Associated Herpesvirus Reduces Cellular Myeloid Differentiation Primary-Response Gene 88 (MyD88) Expression via Modulation of Its RNA

Kaposi’s sarcoma (KS)-associated herpesvirus (KSHV) is a human gammaherpesvirus associated with several human malignancies. The replication and transcription activator (RTA) is necessary and sufficient for the switch from KSHV latency to lytic replication. Interleukin 1 (IL-1) is a major mediator for inflammation and plays an important role in both innate and adaptive immunity. Myeloid differentiation primary response gene 88 (MyD88) is an essential adaptor molecule for IL-1 as well as most Toll-like receptor signaling. In this study, we identified a novel mechanism by which KSHV interferes with host inflammation and immunity. KSHV RTA specifically reduces the steady-state protein levels of MyD88, and physiological levels of MyD88 are downregulated during KSHV lytic replication when RTA is expressed. The N-terminal region of RTA is required for the reduction of MyD88. Additional studies demonstrated that RTA targets MyD88 expression at the RNA level, inhibits RNA synthesis of MyD88, and may bind MyD88 RNA. Finally, RTA inhibits IL-1-mediated activation of NF-B. Because IL-1 is abundant in the KS microenvironment and inhibits KSHV replication, this work may expand our understanding of how KSHV evades host inflammation and immunity for its survival in vivo

Compression of Deep Neural Networks for Image Instance Retrieval

Image instance retrieval is the problem of retrieving images from a database which contain the same object. Convolutional Neural Network (CNN) based descriptors are becoming the dominant approach for generating global image descriptors for the instance retrieval problem. One major drawback of CNN-based global descriptors is that uncompressed deep neural network models require hundreds of megabytes of storage making them inconvenient to deploy in mobile applications or in custom hardware. In this work, we study the problem of neural network model compression focusing on the image instance retrieval task. We study quantization, coding, pruning and weight sharing techniques for reducing model size for the instance retrieval problem. We provide extensive experimental results on the trade-off between retrieval performance and model size for different types of networks on several data sets providing the most comprehensive study on this topic. We compress models to the order of a few MBs: Two orders of magnitude smaller than the uncompressed models while achieving negligible loss in retrieval performance1