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Cloning and sequencing of the gene encoding WF146 protease, an extracellular subtilisin-like protease from the thermophile Bacillus sp. WF146, revealed that the WF146 protease was translated as a 416-amino acid precursor consisting of a putative 18-amino acid signal peptide, a 10-kDa N-terminal propeptide and a 32-kDa mature protease region. The mature WF146 protease shares a high degree of amino acid sequence identity with two psychrophilic subtilisins, S41 (68.2%) and S39 (65.4%), and a mesophilic subtilisin, SSII (67.1%). Significantly, these closely related proteases adapted to different temperatures all had four inserted surface loops not found in other subtilisins. However, unlike those of S41, S39 and SSII, the inserted loops of the WF146 protease possessed stabilizing features, such as the introduction of Pro residues into the loop regions. Interestingly, the WF146 protease contained five of the seven mutations previously found in a hyperstable variant of subtilisin S41 obtained by directed evolution. The proform of WF146 protease (pro-WF146 protease) was overexpressed in Escherichia coli in an inactive soluble form. After heat treatment, the 42-kDa pro-WF146 protease converted to a 32-kDa active mature form by processing the N-terminal propeptide. The purified mature WF146 protease hydrolyzed casein with an optimum temperature of 85 ‡C, and lost activity with a half-life of 30 min at 80 ‡C in the presence of 10 mM CaCl 2 .

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Purpose To better understand the success of an open source software (OSS) project, this study aims to examine the role of social dependency networks (i.e. social and technical dependencies) in online communities.Design/methodology/approach This study focuses on dependencies using three network metrics – degree centrality, betweenness centrality and closeness centrality – in developer and module networks. A longitudinal analysis from the projects hosted at Sourceforge.net is conducted to examine the effects of social and technical networks on the success of OSS projects. To address our research questions, we have constructed research models to investigate the social network effects in developer networks, the technical network effects in module networks, and the social-technical network effects in both types of networks.Findings The results reveal nonlinear relationships between degree centrality in both social and technical networks and OSS success, highlighting the importance of a moderate level of degree centrality in team structure and software architecture. Meanwhile, a moderate level of betweenness centrality and a lower level of closeness centrality between developers lead to a higher chance of OSS project success.Originality/value This study is the first attempt to consider the network metrics in both module networks of the technical sub-system and developer networks of the social sub-system to better understand their influences on project success.

With the emergence of artificial intelligence (AI), the technological revolution has transformed human lives and processes, empowering the products and services in today’s marketplaces. AI introduces new ways of doing jobs and business, and of exploring new global market opportunities. However, on the other hand, it provides many challenges to comprehend. Therefore, our study’s main objective was to examine the behavioral, cultural, ethical, social, and economic challenges of AI-enabled products and services in consumer markets and discuss how businesses might shape their approaches to address AI-related ethical issues. AI offers numerous social, ethical, and behavioral difficulties for people, organizations, and societies that endanger the sustainable development of economies. These fundamental challenges due to AI technologies have raised serious questions for the sustainable development of electronic markets. Based on this, the current study presents a framework highlighting these issues. Systematic reviewing was our research method; we looked for explicit information and methods that indicate the credibility of research or reduce biases. This paper is of great importance, as it highlights several behavioral, societal, ethical, and cultural aspects in electronic markets which were not presented in previous studies. Some key issues are the security and privacy of consumers, AI biases, individual autonomy, wellbeing, and issues of unemployment. Therefore, companies that use AI systems need to be socially responsible and make AI systems as secure as possible to promote the sustainable development of countries. The results suggest that AI has undoubtedly transformed life and has both positive and negative effects. However, the main aim regarding AI should be to use it for the overall goals of humanity. Moreover, authorities operating in e-business environments need to create proper rules and regulations and make the systems as secure as possible for people.

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