Web service is one of the key communications software services for the Internet. Web phishing is one of many security threats to web services on the Internet. Web phishing aims to steal private information, such as usernames, passwords, and credit card details, by way of impersonating a legitimate entity. It will lead to information disclosure and property damage. This paper mainly focuses on applying a deep learning framework to detect phishing websites. This paper first designs two types of features for web phishing: original features and interaction features. A detection model based on Deep Belief Networks (DBN) is then presented. The test using real IP flows from ISP (Internet Service Provider) shows that the detecting model based on DBN can achieve an approximately 90% true positive rate and 0.6% false positive rate.

Glycosphingolipid (GSL) metabolism is involved in various physiological processes, including all major cell signaling pathways, and its dysregulation is linked to some diseases. The four-phosphate adaptor protein FAPP2-mediated glucosylceramide (GlcCer) transport for complex GSL synthesis has been studied extensively. However, the molecular machinery of FAPP2 as a GlcCer-transferring protein remains poorly defined. Here, we identified a Golgi-resident protein, acyl-coenzyme A binding domain containing 3 (ACBD3), as an interacting partner of FAPP2. We found that ACBD3 knockdown leads to dramatic Golgi fragmentation, which subsequently causes FAPP2 dispersal throughout the cytoplasm and a decreased localization at trans-Golgi network (TGN). The further quantitative lipidomic analysis indicated that ACBD3 knockdown triggers abnormal sphingolipid metabolism. Interestingly, the expression of siRNA-resistant full-length ACBD3 could rescue these defects caused by ACBD3 knockdown. These data reveal critical roles for ACBD3 in maintaining the integrity of Golgi morphology and cellular sphingolipid homeostasis and establish the importance of the integrated Golgi complex for the transfer of GlcCer and complex GSL synthesis.

Three new energetic 2,2′,4,4′,6,6′-hexanitrostilbene (HNS) cocrystals, HNS/4,4′-bipyridine, HNS/trans-1,2bis(4-pyridyl)ethylene, and HNS/1,2-bis(4-pyridyl)ethane have been synthesized. A good geometric match and rich Hbonds have been observed between the selected coformer and HNS molecules in all three cocrystals. According to similar configuration and arrangement of HNS−coformer H-bonds, coformer−coformer π-stacking, and HNS−HNS H-bonding interactions, the three cocrystals have a common cocrystal architecture and show high thermal stability and improved sensitivity. This study is helpful for understanding the formation mechanism of energetic cocrystals and the design of new energetic cocrystals.

BackgroundType 2 Diabetes Mellitus (T2DM) is a chronic disease closely related to personal life style. Therefore, achieving effective self-management is one of the most important ways to control it. There is evidence that social support can help to improve the self-management ability of patients with T2DM, but which social support is more effective has been rarely explored. The purpose of this study is to construct an integrated model to analyze which social support has more significant impact on self-management of T2DM, and provide reasonable suggestions to health care providers on how to effectively play the role of social support.MethodsWe established a social support indicator evaluation system and proposed an integrated model that combines ANP (Analytical Network Process) and CRITIC (CRiteria Importance through Intercriteria Correlation) methods to evaluate the impact of social support on T2DM self-management from both subjective and objective perspectives. The weights calculated by the model will serve as the basis for us to judge the importance of different social support indicators.ResultsInformational support (weighting 49.26%) is the most important criteria, followed by tangible support (weighting 39.24%) and emotional support (weighting 11.51%). Among 11 sub-criteria, guidance (weighting 23.05%) and feedback (weighting 14.68%) are two most relevant with T2DM self-management. This result provides ideas and evidence for health care providers on how to offer more effective social support.ConclusionTo our knowledge, this is the first study in which Multi-Criteria Decision Making (MCDM) tools, specifically ANP and CRITIC, are used to evaluate the impact of social support on improving self-management of type 2 diabetes. The study suggests that incorporating two sub-indicators of guidance and feedback into the diabetes care programs may have great potential to improve T2DM self-management and further control patient blood glucose and reduce complications.

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