ACTS in Need: Automatic Configuration Tuning with Scalability Guarantees

To support the variety of Big Data use cases, many Big Data related systems expose a large number of user-specifiable configuration parameters. Highlighted in our experiments, a MySQL deployment with well-tuned configuration parameters achieves a peak throughput as 12 times much as one with the default setting. However, finding the best setting for the tens or hundreds of configuration parameters is mission impossible for ordinary users. Worse still, many Big Data applications require the support of multiple systems co-deployed in the same cluster. As these co-deployed systems can interact to affect the overall performance, they must be tuned together. Automatic configuration tuning with scalability guarantees (ACTS) is in need to help system users. Solutions to ACTS must scale to various systems, workloads, deployments, parameters and resource limits. Proposing and implementing an ACTS solution, we demonstrate that ACTS can benefit users not only in improving system performance and resource utilization, but also in saving costs and enabling fairer benchmarking

Measurement Equivalence of Web Surveys Based on Social Media

Web surveys have become a very important way of empirical research. The rise of social media provides a new platform for web surveys. Investigators can collect data based on different social media platforms to get more respondents of higher external validity at a lower cost. However, there is no domestic expert and scholar to conduct related researches on web surveys based on social media. This paper studies the measurement equivalence of surveys among BBS, micro blog and SNS using CFA. The result shows that three surveys have the same basic structure, factor loading matrix and factor covariance matrix; moreover, the intercepts are equivalent across micro blog and SNS

Structure and mechanism of two type III CRISPR defence nucleases activated by cyclic oligoadenylate

Prokaryotes have a wide range of antiviral strategies to defend against invading mobile genetic elements (MGEs). Type III CRISPR-Cas systems typically synthesise cyclic oligoadenylate (cOA) second messengers upon binding to cognate foreign RNA. These second messengers allosterically activate type III CRISPR ancillary proteins, potentiating a powerful immune response. Following the discovery of cOA signalling pathway, several ancillary proteins from Csx1/Csm6 family had been described. They sense cOA molecules with their CARF (CRISPR associated Rossman fold) domains and non-specifically cleave RNA with their effector domains. Here, we describe the structure and mechanism of two novel ancillary proteins Can1 and Can2. Can1 has a unique monomeric architecture that contains two CARF domains, a PD-(D/E)XK nuclease domain and a nuclease-like domain. It favours nicking scDNA in the presence of cyclic tetra-adenylate (cA₄) and metal ions. Can2 forms a canonical homodimer and each monomer contains a CARF domain and a PD-(D/E)XK nuclease domain. It exhibits both DNase and RNase activity in the presence of cA₄ and metal ions. It also provides effective immunity against plasmid and bacteriophage infection in a recombinant type III CRISPR-Cas system."This work was supported by grants from the Biotechnology and Biological Sciences Research Council (BB/S000313/1 to M.F.W., BB/R008035/1 to T.M.G. and BB/T004789/1 to M.F.W. and T.M.G.); grants from Wellcome Trust Institutional Strategic Support Funding (204821/Z/16/Z to M.F.W. and T.M.G.); grants from China Scholarship Council (201703780015 to W.Z.). Funding for open access charge: RCUK block grant." -- Fundin

Understanding the Relationship between Social Media Use and Depression: A Systematic Review

There have been many studies on the relationship between social media use and depression in recent years, but there are inconsistencies between their findings. Using the systematic review method, we analyzed the existing body of work on the relationship between social media use and depression in the information systems field. We selected the Web of Science, Emerald, JSTOR, Science Direct, Taylor & Francis Online and Wiley Online Library as search databases, and ended up with 24 papers that met all our requirements. We identified four possible reasons for the inconsistencies. First, the measurement indicators of social media use are different. Second, depression is not measured in the same way. Third, the studies considered different populations of social media users. Fourth, the mediating factors are different with regards to the relationship between social media use and depression. This study provides literature supported theoretical insights for further exploration and analysis