In recent years, the network has become more complex, and the attacker’s ability to attack is gradually increasing. How to properly understand the network security situation and improve network security has become a very important issue. In order to study the method of extracting information about the security situation of the network based on cloud computing, we recommend the technology of knowledge of the network security situation based on the data extraction technology. It converts each received cyber security event into (...) a standard format that can be defined as multiple brochures, creating a general framework for the cyber security situation. According to the large nature of network security situation data, the Hadoop platform is used to extract aggregation rules, and perform model extraction, pattern analysis, and learning on a network security event dataset to complete network security situation rule mining, and establish a framework for assessing the state of network security. According to the results of the federal rule extraction, the level of network node security risk is obtained in combination with signal reliability, signal severity, resource impact, node protection level, and signal recovery factor. A simulation test is performed to obtain the intrusion index according to the source address of the network security alarm. Through the relevant experiments and analysis of the results, the attack characteristics obtained in this study were obtained after manually reducing the network security event in the 295 h window. The results show that after the security event is canceled, the corresponding window attack index decreases to 0, indicating that this method can effectively implement a network security situation awareness. The proposed technique allows you to accurately sense changes in network security conditions. (shrink)

Introduction: Neurobiological systems engineering models are useful for treating patients. We show a model of “high opioid tone” autism and present a hypothesis about how autism is caused by administration of opioids during childbirth.Main Symptoms: Clinical diagnosis of autism in a 25 year old man was confirmed by a Social Responsiveness Scale self-rating of 79, severe, and a Social Communications Questionnaire by the patient's father scoring 27. Cold pressor time was 190 seconds—unusually long, consonant with the high pain tolerance of (...) autism.Therapeutic Intervention and Outcomes: At naltrexone 50 mg/day SRS fell to 54 and SCQ-−2–9; both non-significant. CPT fell to 28, repeat 39 s. Improved relatedness was experienced ambivalently, understood as feelings never before experienced—causing pain. Non-compliance with naltrexone was followed by cutting open his palm and drinking alcoholically. Transference focused psychotherapy has helped him remain naltrexone—compliant while he works on issues of identity and relatedness.Conclusion: The model suggests studies that could be conducted to both prevent and treat this form of autism. (shrink)

Deep neural networks (DNNs) have been playing a significant role in acoustic modeling. Convolutional neural networks (CNNs) are the advanced version of DNNs that achieve 4–12% relative gain in the word error rate (WER) over DNNs. Existence of spectral variations and local correlations in speech signal makes CNNs more capable of speech recognition. Recently, it has been demonstrated that bidirectional long short-term memory (BLSTM) produces higher recognition rate in acoustic modeling because they are adequate to reinforce higher-level representations of acoustic (...) data. Spatial and temporal properties of the speech signal are essential for high recognition rate, so the concept of combining two different networks came into mind. In this paper, a hybrid architecture of CNN-BLSTM is proposed to appropriately use these properties and to improve the continuous speech recognition task. Further, we explore different methods like weight sharing, the appropriate number of hidden units, and ideal pooling strategy for CNN to achieve a high recognition rate. Specifically, the focus is also on how many BLSTM layers are effective. This paper also attempts to overcome another shortcoming of CNN, i.e. speaker-adapted features, which are not possible to be directly modeled in CNN. Next, various non-linearities with or without dropout are analyzed for speech tasks. Experiments indicate that proposed hybrid architecture with speaker-adapted features and maxout non-linearity with dropout idea shows 5.8% and 10% relative decrease in WER over the CNN and DNN systems, respectively. (shrink)

Research on fair trade has flourished over the past decade as fair trade food products have gained popularity amongst consumers in many developed economies. This study examines the effects of recessionary economic conditions on fair trade consumers’ purchasing behaviour. An online survey was administered to 306 fair trade consumers from Canada, the United Kingdom and the United States of America. The results reveal a discrepancy among fair trade consumers as only consumers that purchase fair trade on an occasional basis adhered (...) to established consumer behaviour norms, i.e. decreasing their purchases of fair trade products and becoming significantly more price aware. Respondents who actively consume fair trade generally remained loyal to their purchase. While some active consumers altered their purchasing behaviour, this phenomenon was not common amongst this group as no statistically significant changes were observed. Differences were also noted among the three countries as the Canadian and US fair trade consumers significantly decreased their consumption of fair trade as a result of the recession, whereas the UK consumers did not. In addition to the research results, theoretical and managerial implications will be discussed along with future research directions. (shrink)

Since their introduction in the early 2000s, the use of social networking websites has exploded. Many businesses are seeing increased revenue due to their social commerce strategy. Despite the popularity of social commerce websites, some consumers are still hesitate to use them. This study aims to evaluate the factors that influence the adoption of social commerce. A sample of 721 Chinese We Chat users took part in the research. The findings reveal that social capital mediates the positive effect of social (...) commerce adoption and perceived ease of use on techno-stress and online impulse purchasing. Likewise, information overloading mediates the positive effect of social commerce adoption and PERU on techno-stress and online impulse purchasing. The findings have implications for both practice and research in understanding social commerce adoption in emerging economies. (shrink)

This examines the six drivers and twelve detailed practices of sustainable human resource development (S-HRD) before and during the COVID-19 pandemic across different organizations in Poland. The empirical strategy is based on explorative research conducted using surveys in Poland between 2020 and 2021. The results confirm that the surveyed organizations implemented S-HRD practices driven mainly by the expectations of external stakeholders. They neglected the areas of caring for employees’ well-being and developing environmental awareness before the COVID-19 pandemic. During the pandemic, (...) most companies maintained their approach to S-HRD. This research is unique because it adds to the body of literature advocating the significance of S-HRD for organizational resilience before, during, and after extreme events. Generalizing the results is challenging because the snowball sample has significant restrictions. However, future research may overcome these shortcomings by using larger samples based on probability or random sampling techniques. (shrink)

Interleukin‐1 receptor‐associated kinase‐1 (IRAK1) is linked to the pathogenesis of atherosclerosis; however, its role in macrophage foam cell formation is not known. Therefore, the present study investigated the role of IRAK1 in lipid uptake, biosynthesis, and efflux in THP‐1 derived macrophages and human monocyte‐derived macrophages (HMDMs). Ox‐LDL (40 μg/mL, 15 minutes–48 hours) treatment induced time‐dependent increase in IRAK1, IRAK4, and Stat1 activation in THP‐1 derived macrophages. IRAK1/4 inhibitor (INH) or IRAK1 siRNA significantly attenuated cholesterol accumulation, DiI‐Ox‐LDL binding, and uptake while (...) cholesterol efflux to apoAI and HDL was enhanced in THP‐1 derived macrophages and HMDMs. Ox‐LDL treatment significantly increased the mRNA expression of CD36, LOX‐1, SR‐A, ABCA1, ABCG1, Caveolin‐1, CYP27A1 while that of SR‐BI was decreased. IRAK1/4 inhibition or IRAK1 knockdown, however, attenuated Ox‐LDL‐induced CD36 expression; augmented ABCA1 and ABCG1 expression while expression of others was unaffected in THP‐1 derived macrophages and HMDMs. Moreover, IRAK1/4 inhibition had no significant effect on genes involved in lipid biosynthesis. In IRAK1/4 INH pre‐treated THP‐1 derived macrophages Ox‐LDL‐induced Stat1 phosphorylation and its binding to CD36 promoter was significantly attenuated while LXRα expression and its binding to the ABCA1/ABCG1 locus, NFATc2 activation and its binding to ABCA1 locus was enhanced. The present study thus demonstrates that IRAK regulates lipid accumulation by modulating CD36‐mediated uptake and ABCA1‐, ABCG1‐dependent cholesterol efflux. Therefore, IRAK1 can be a potential target for preventing macrophage foam cell formation. (shrink)

Vishal Gupta, FIRST AMONG EQUALS: ‘T-R-E-A-T’ Leadership for ‘L-E-A-P’ in a Knowledge-Based World. New Delhi: Bloomsbury India, 2020, 275 pp., ₹599 (paperback). ISBN: 978-93-87457-82-9; eBook: 978-93-87471-20-7.

Approaches to legal pluralism vary widely across the spectrum of different disciplines. They comprise normative and descriptive perspectives, focus both on legal pluralist realities as well as public debates, and address legal pluralism in a range of different societies with varying political, institutional and historical conditions. Emphasising an empirical research to contemporary legal pluralist settings in Muslim contexts, the present collected volume contributes to a deepened understanding of legal pluralist issues and realities through comparative examination. This approach reveals some common (...) features, such as the relevance of Islamic law in power struggles and in the construction of (state or national) identities, strategies of coping with coexisting sets of legal norms by the respective agents, or public debates about the risks induced by the recognition of religious institutions in migrant societies. At the same time, the studies contained in this volume reveal that legal pluralist settings often reflect very specific historical and social constellations, which demands caution towards any generalisation. The volume is based on papers presented at a conference in Münster (Germany) in 2016 and comprises contributions by Judith Koschorke, Karen Meeschaut, Yvonne Prief, Ulrike Qubaja, Werner de Saeger, Ido Shahar, Katrin Seidel, Konstantinos Tsitselikis, Vishal Vora and Ihsan Yilmaz. (shrink)