An investigation on the Factors Influencing the dissemination of WeChat Push Based on HSM and the Prediction of its Content Hotspot

With the continuous development of information technology, the carrier of we-media has emerged. The WeChat Subscription Accounts has quickly led the other we-media platforms. During the six years of its emergence, WeChat Subscription Accounts have attracted a lot of traffic and brought huge profit margins. Based on the above background, this study combines the heuristic-systematic model of information processing to classify the heuristic and systematic factors that influence the dissemination of WeChat push. Analyze the factors affecting WeChat push transmission, supplement relevant theories, and provide suggestions for WeChat Subscription Accounts operators

Application of Artificial Intelligence (AI) methods for designing and analysis of Reconfigurable Cellular Manufacturing System (RCMS)

This work focuses on the design and control of a novel hybrId manufacturing system: Reconfigurable Cellular Manufacturing System (RCMS) by using Artificial Intelligence (AI) approach. It is hybrid as it combines the advantages of Cellular Manufacturing System (CMS) and Reconfigurable Manufacturing System (RMS). In addition to inheriting desirable properties from CMS and RMS, RCMS provides additional benefits including flexibility and the ability to respond to changing products, product mix and market conditions during its useful life, avoiding premature obsolescence of the manufacturing system. The emphasis of this research is the formation of Reconfigurable Manufacturing Cell (RMC) which is the dynamic and logical clustering of some manufacturing resources, driven by specific customer orders, aiming at optimally fulfilling customers' orders along with other RMCs in the RCMS

Explaining differences in self-focused and other-involved public health preventive behaviors between the US and China: the role of self- construal and health locus of control

BackgroundThis study examined national similarities and differences in people's engagement in health preventive behaviors during a public health crisis, as well as investigated the underlying individual-level psychological mechanisms. A conceptual distinction was made between self-focused and other-involved preventive behaviors in response to public health crises.MethodTwo cross-sectional surveys were conducted in the United States (N = 888) and China (N = 844) during the early stage of the COVID-19 pandemic. Hayes' PROCESS was utilized to assess national differences in seven preventive behaviors, along with the mediating effects of self-construal and health locus of control.ResultsThe results showed that American participants reported greater engagement in self-focused preventive behaviors than Chinese, whereas Chinese participants reported greater engagement in other-involved preventive behaviors than Americans. Chinese participants also engaged more in other-involved than self-focused preventive behaviors. Self-construal and health locus of control partially explained the observed differences in engagement in preventive behaviors.DiscussionThis study introduces a culture-sensitive approach to provide insights for crafting communication interventions that can enhance the effectiveness of health campaigns in the context of a public health crisis

Unusual architecture of the p7 channel from hepatitis C virus

The Hepatitis C virus (HCV) has developed a small membrane protein, p7, which remarkably can self-assemble into a large channel complex that selectively conducts cations1-4. We are curious as to what structural solution has the viroporin adopted to afford selective cation conduction because p7 has no homology with any of the known prokaryotic or eukaryotic channel proteins. The p7 activity can be inhibited by amantadine and rimantadine2,5, which also happen to be potent blockers of the influenza M2 channel6 and licensed drugs against influenza infections7. The adamantane derivatives were subjects of HCV clinical trials8, but large variation in drug efficacy among the various HCV genotypes has been difficult to explain without detailed molecular structures. Here, we determined the structures of this HCV viroporin as well as its drug-binding site using the latest nuclear magnetic resonance (NMR) technologies. The structure exhibits an unusual mode of hexameric assembly, where the individual p7 monomers, i, not only interact with their immediate neighbors, but also reach farther to associate with the i+2 and i+3 monomers, forming a sophisticated, funnel-like architecture. The structure also alludes to a mechanism of cation selection: an asparagine/histidine ring that constricts the narrow end of the funnel serves as a broad cation selectivity filter while an arginine/lysine ring that defines the wide end of the funnel may selectively allow cation diffusion into the channel. Our functional investigation using whole-cell channel recording showed that these residues are indeed critical for channel activity. NMR measurements of the channel-drug complex revealed six equivalent hydrophobic pockets between the peripheral and pore-forming helices to which amantadine or rimantadine binds, and compound binding specifically to this position may allosterically inhibit cation conduction by preventing the channel from opening. Our data provide molecular explanation for p7-mediated cation conductance and its inhibition by adamantane derivatives

Demystifying Assumptions in Learning to Discover Novel Classes

In learning to discover novel classes (L2DNC), we are given labeled data from seen classes and unlabeled data from unseen classes, and we train clustering models for the unseen classes. However, the rigorous definition of L2DNC is unexplored, which results in that its implicit assumptions are still unclear. In this paper, we demystify assumptions behind L2DNC and find that high-level semantic features should be shared among the seen and unseen classes. This naturally motivates us to link L2DNC to meta-learning that has exactly the same assumption as L2DNC. Based on this finding, L2DNC is not only theoretically solvable, but can also be empirically solved by meta-learning algorithms after slight modifications. This L2DNC methodology significantly reduces the amount of unlabeled data needed for training and makes it more practical, as demonstrated in experiments. The use of very limited data is also justified by the application scenario of L2DNC: since it is unnatural to label only seen-class data, L2DNC is sampling instead of labeling in causality. Therefore, unseen-class data should be collected on the way of collecting seen-class data, which is why they are novel and first need to be clustered

TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation

In few-shot domain adaptation (FDA), classifiers for the target domain are trained with accessible labeled data in the source domain (SD) and few labeled data in the target domain (TD). However, data usually contain private information in the current era, e.g., data distributed on personal phones. Thus, the private information will be leaked if we directly access data in SD to train a target-domain classifier (required by FDA methods). In this paper, to thoroughly prevent the privacy leakage in SD, we consider a very challenging problem setting, where the classifier for the TD has to be trained using few labeled target data and a well-trained SD classifier, named few-shot hypothesis adaptation (FHA). In FHA, we cannot access data in SD, as a result, the private information in SD will be protected well. To this end, we propose a target orientated hypothesis adaptation network (TOHAN) to solve the FHA problem, where we generate highly-compatible unlabeled data (i.e., an intermediate domain) to help train a target-domain classifier. TOHAN maintains two deep networks simultaneously, where one focuses on learning an intermediate domain and the other takes care of the intermediate-to-target distributional adaptation and the target-risk minimization. Experimental results show that TOHAN outperforms competitive baselines significantly

PO-209 Effects of aerobic exercise on oxidant/anti-oxidant indexes and gut microbiota in young obese volunteers

  Objective The mean body mass index (BMI) and the prevalence of obese and overweight individuals increasing substantially worldwide during the previous three decades. Variation in gut microorganisms might play an important role in the pathogenesis of obesity, but the mechanisms by which gut microbiota promote metabolic disturbances are not well understood. Exercise is associated with altered gut microbial composition, but few studies have investigated whether the gut microbiota and associated metabolites are modulated by exercise training in humans. We explored the impact of 8 weeks aerobic exercise on serum oxidant and anti-oxidant indexes and gut microbiota. Methods All 40 young male volunteers are enrolled in the study, the lean ones (n=11), which BMI≤22 are as control group. And the obese ones (n=29), which BMI > 28 participated in the 8 weeks aerobic exercise. The body weight and BMI of each volunteers were recorded. The serum malondialdehyde (MDA), superoxide dismutase (SOD), glutathione peroxidase (GPx) and total antioxidant capacity (TAOC) were measured by ELISA. The composition and diversity of gut microbiota were analyzed with 16S rDNA sequencing. Results ① Compared with the control, the level of serum GPx, SOD and TAOC decreased significantly (P < 0.001), and the MDA increased significantly (P < 0.001) in the obese group. After the 8 weeks aerobic exercise intervention, the MDA level decreased significantly (P＜0.01), the TAOC level increased significantly (P < 0.01), and there were no significant changes in the level of GPX and SOD. ② Compared with the control, the ratio of Bifidobacteriaceae, Alcaligenaceae, Erysipelotrichaceae, and Verrucomicrobiaceae decreased significantly(p＜0.05) in the obese group, and the ratio of Ruminococcaceae, Helicobacteraceae increased significantly (P＜0.05). After the 8 weeks aerobic exercise intervention, the ratio of Bifidobacteriaceae, Alcaligenaceae increased significantly (P＜0.05)，and the ratio of Ruminococcaceae reduced remarkably (p＜0.05). The ACE index was significantly increased after the intervention (P < 0.05). ③ Through the correlation analysis of the data above, there was a certain correlation between the serum oxidant/anti-oxidant indexes and gut microbiota composition. After the aerobic exercise, there was a positive correlation between MDA and Ruminococcaceae、TAOC and Bifdobacteriace (P＜0.05)；a negative correlation between MDA and Bifdobacteriace、TAOC and Ruminococcaceae (P＜0.05). After 8 weeks of aerobic exercise, MDA level was negatively correlated with ACE index (r=-0.466，P＜0.05). Conclusions ① Compared with the control, there was a significant increase of serum oxidation index and the serum anti-oxidation index dropped significantly among the obese subjects, which indicated that the accumulation of serum free radicals might be one of the causes of obesity. The 8 weeks aerobic exercise intervention can enhance the antioxidant capacity effectively. ② Compared with the control, the proportion of Bifidobacteriaceae in the obese group was significantly decreased, and the proportion of the bacteria with direct correlation to obesity, such as Ruminococcaceae increased significantly. 8 weeks aerobic exercise could inverse these changes among the obese subjects, suggested that the improvement of body phenotype of obese subjects was closely related to the effective regulation of their gut microbiota structure.The change of ACE index indicated that aerobic exercise could increase the diversity of gut microbiota. ③ Combined the correlation analysis of gut microbiota diversity index showed that there were tight correlation between the serum oxidant/anti-oxidant indexes and the gut microbiota composition and structure. It might caused metabolic disorders and eventually increased fat accumulation and changed the host body phenotype.     &nbsp

A missense mutation in Pitx2 leads to early-onset glaucoma via NRF2-YAP1 axis.

Glaucoma is a leading cause of blindness, affecting 70 million people worldwide. Owing to the similarity in anatomy and physiology between human and mouse eyes and the ability to genetically manipulate mice, mouse models are an invaluable resource for studying mechanisms underlying disease phenotypes and for developing therapeutic strategies. Here, we report the discovery of a new mouse model of early-onset glaucoma that bears a transversion substitution c. G344T, which results in a missense mutation, p. R115L in PITX2. The mutation causes an elevation in intraocular pressure (IOP) and progressive death of retinal ganglion cells (RGC). These ocular phenotypes recapitulate features of pathologies observed in human glaucoma. Increased oxidative stress was evident in the inner retina. We demonstrate that the mutant PITX2 protein was not capable of binding to Nuclear factor-like 2 (NRF2), which regulates Pitx2 expression and nuclear localization, and to YAP1, which is necessary for co-initiation of transcription of downstream targets. PITX2-mediated transcription of several antioxidant genes were also impaired. Treatment with N-Acetyl-L-cysteine exerted a profound neuroprotective effect on glaucoma-associated neuropathies, presumably through inhibition of oxidative stress. Our study demonstrates that a disruption of PITX2 leads to glaucoma optic pathogenesis and provides a novel early-onset glaucoma model that will enable elucidation of mechanisms underlying the disease as well as to serve as a resource to test new therapeutic strategies