Engaging Élitism: the Mediating Effect of Work Engagement on Affective Commitment and Quit Intentions in Two Australian University Groups

Some universities rely on their élitism as one mechanism to attract and retain talented faculty. This paper examines two groups of élite and non-élite universities and the mediating effect that work engagement has on affective commitment and intention to quit. Findings indicate partial support for the mediating effect of work engagement in the non-élite group but no support in the élite university group. The implications of these diverse results are posed for the management of academics in élite and non-élite universities, suggesting that a ‘one size fits all approach’ to performance outcomes does not always fit.

Stress, inflammation, and cellular vulnerability during early stages of affective disorders: biomarker strategies and opportunities for prevention and intervention

The mood disorder prodrome is conceptualized as a symptomatic, but not yet clinically diagnosable stage of an affective disorder. Although a growing area, more focused research is needed in the pediatric population to better characterize psychopathological symptoms and biological markers that can reliably identify this very early stage in the evolution of mood disorder pathology. Such information will facilitate early prevention and intervention, which has the potential to affect a person’s disease course.This review focuses on the prodromal characteristics, risk factors, and neurobiological mechanisms of mood disorders. In particular, we consider the influence of early-life stress, inflammation, and allostatic load in mediating neural mechanisms of neuroprogression. These inherently modifiable factors have known neuroadaptive and neurodegenerative implications, and consequently may provide useful biomarker targets. Identification of these factors early in the course of the disease will accordingly allow for the introduction of early interventions which augment an individual’s capacity for psychological resilience through maintenance of synaptic integrity and cellular resilience. A targeted and complementary approach to boosting both psychological and physiological resilience simultaneously during the prodromal stage of mood disorder pathology has the greatest promise for optimizing the neurodevelopmental potential of those individuals at risk of disabling mood disorders.

Classification and optimization of product review information using soft computing models

A soft computing framework to classify and optimize text-based information extracted from customers' product reviews is proposed in this paper. The soft computing framework performs classification and optimization in two stages. Given a set of keywords extracted from unstructured text-based product reviews, a Support Vector Machine (SVM) is used to classify the reviews into two categories (positive and negative reviews) in the first stage. An ensemble of evolutionary algorithms is deployed to perform optimization in the second stage. Specifically, the Modified micro Genetic Algorithm (MmGA) optimizer is applied to maximize classification accuracy and minimize the number of keywords used in classification. Two Amazon product reviews databases are employed to evaluate the effectiveness of the SVM classifier and the ensemble of MmGA optimizers in classification and optimization of product related keywords. The results are analyzed and compared with those published in the literature. The outputs potentially serve as a list of impression words that contains useful information from the customers' viewpoints. These impression words can be further leveraged for product design and improvement activities in accordance with the Kansei engineering methodology.

The challenges of cloud computing technology adoption in e-government

 The endless transformation of technological innovation requires greater collaboration of Information Communication and Technology (ICT) in various areas especially in public sectors. Many attempts have been made in improving the quality of E-Government services; one of it is adopting the cloud computing technology. Successful implementation of cloud computing technology can benefit the public sector in many ways one of it is cost reduction. Most government organizations especially in the developing countries are committed in adopting the cloud technology based on the increased demands in cloud adoption in E Government services. Unfortunately, despite all the benefits, the cloud computing technology raises some major risks. The success of implementation of cloud computing technology is determined by how well the government tackles the challenges. Therefore, this paper specifically surveyed the associated challenges of adopting Cloud Technology for E-Government by choosing Malaysia as the case study.

Trust enhanced security in SaaS cloud computing

Trust problem in Software as a Service Cloud Computing is a broad range of a Data Owner’s concerns about the data in the Cloud. The Data Owner’s concerns about the data arise from the way the data is handled in locations and machines that are unknown to the Data Owner.