On reconsideration of IT governance structures to govern cloud computing services

There is an increase in the uptake of cloud computing services (CCS). CCS is adopted in the form of a utility, and it incorporates business risks of the service providers and intermediaries. Thus, the adoption of CCS will change the risk profile of an organization. In this situation, organisations need to develop competencies by reconsidering their IT governance structures to achieve a desired level of IT-business alignment and maintain their risk appetite to source business value from CCS. We use the resource-based theories to suggest that collaborative board oversight of CCS, competencies relating to CCS information and financial management, and a CCS-related continuous audit program can contribute to business process performance improvements and overall firm performance. Using survey data, we find evidence of a positive association between these IT governance considerations and business process performance. We also find evidence of positive association between business process performance improvements and overall firm performance. The results suggest that the suggested considerations on IT governance structures can contribute to CCS-related IT-business alignment and lead to anticipated business value from CCS. This study provides guidance to organizations on competencies required to secure business value from CCS.

Cloud computing services for the small and medium enterprises: Key considerations for sourcing sustainable business value

The concept of cloud computing services (CCS) is appealing to small and medium enterprises (SMEs). However, while there is a significant push by various authorities on SMEs to adopt the CCS, knowledge of the key considerations to adopt the CCS is very limited. We use the technology-organization-environment (TOE) framework to suggest that a strategic and incremental intent, understanding the organizational structure and culture, understanding the external factors, and consideration of the human resource capacity can contribute to sustainable business value from CCS. Using survey data, we find evidence of a positive association between these considerations and the CCS-related business objectives. We also find evidence of positive association between the CCS-related business objectives and CCS-related financial objectives. The results suggest that the proposed considerations can ensure sustainable business value from the CCS. This study provides guidance to SMEs on a path to adopting the CCS with the intention of a long-term commitment and achieving sustainable business value from these services.

R1STM: One-class support tensor machine with randomised kernel

Identifying unusual or anomalous patterns in an underlying dataset is an important but challenging task in many applications. The focus of the unsupervised anomaly detection literature has mostly been on vectorised data. However, many applications are more naturally described using higher-order tensor representations. Approaches that vectorise tensorial data can destroy the structural information encoded in the high-dimensional space, and lead to the problem of the curse of dimensionality. In this paper we present the first unsupervised tensorial anomaly detection method, along with a randomised version of our method. Our anomaly detection method, the One-class Support Tensor Machine (1STM), is a generalisation of conventional one-class Support Vector Machines to higher-order spaces. 1STM preserves the multiway structure of tensor data, while achieving significant improvement in accuracy and efficiency over conventional vectorised methods. We then leverage the theory of nonlinear random projections to propose the Randomised 1STM (R1STM). Our empirical analysis on several real and synthetic datasets shows that our R1STM algorithm delivers comparable or better accuracy to a state-of-the-art deep learning method and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

Directional dominance on stature and cognition in diverse human populations

Homozygosity has long been associated with rare, often devastating, Mendelian disorders1, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3, 4. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10−300, 2.1 × 10−6, 2.5 × 10−10 and 1.8 × 10−10, respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months’ less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5, 6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.

The importance of context in engaging students large first year management classes: A case study

Engaging large first year classes in tertiary education poses a number of significant challenges, most of which have been discussed by others. One area that has not received the kind of attention that it warrants is the context within which the engagement activities take place. This paper examines both the processes used to engage a large first year management class in a major city university and how the context of the classes shaped activities and student responses to these activities. It was recognised that students had certain types of learning styles, but given the total number of students (in excess of 1200) it was realised that is would be impossible to cater to all possibilities. A key outcome of the exercise was the importance of context in shaping student behaviours.

The emerging role of microRNAs in resistance to lung cancer treatments

One of the major challenges in the treatment of lung cancer is the development of drug resistance. This represents a major obstacle in the treatment of patients, limiting the efficacy of both conventional chemotherapy and biological therapies. Deciphering the mechanisms of resistance is critical to further understanding the multifactorial pathways involved, and in developing more specific targeted treatments. To date, numerous studies have reported the potential role of microRNAs (miRNAs) in resistance to various cancer treatments. MicroRNAs are a family of small non-coding RNAs that regulate gene expression by sequence-specific targeting of mRNAs causing translational repression or mRNA degradation. More than 1200 validated human miRNAs have been identified to date. While as little as one miRNA can regulate hundreds of targets, a single target can also be affected by multiple miRNAs. Evidence suggests that dysregulation of specific miRNAs may be involved in the acquisition of resistance to a number of cancer treatments, thereby modulating the sensitivity of cancer cells to such therapies. Therefore, targeting miRNAs may be an attractive strategy for developing novel and more effective individualized therapies, improving drug efficiency, and for predicting patient response to different treatments. In this review, we provide an overview on the role of miRNAs in resistance to current lung cancer therapies and novel biological agents.

Clinician perspective on molecular profiling of non-small-cell lung cancer

The article by Meric-Bernstam et al1 that was recently published in Journal of Clinical Oncology raises important questions about the clinical application of large-scale genomic testing. We congratulate the authors for this ambitious study, which successfully profiled 2,000 consecutive patients with advanced cancer. The next-generation sequencing (NGS) platform was used for 1,749 of 2,000 patients (87.5%). Of 789 patients with potentially actionable mutations, 83 (11%, or 4% of screened population) were enrolled in a genomically matched clinical study. As the editorial2 accompanying the article by Meric-Bernstam et al1 pointed out, the 4% figure, albeit disappointing, may be an underestimate because cancers such as lung adenocarcinoma and melanoma, for which ≥ 50% of patients have actionable mutations, were under-represented. ...