An empirical investigation into the construct redundancy of job evaluation and job redesign

This study addressed the question: To what extent is there convergence between job evaluation components which are associated with higher levels of pay and job design characteristics which are associated with higher levels of enrichment? Ten clerical jobs and ten professional/scientific jobs were the observational units for this investigation. Two professionally established job evaluation instruments and two widely accepted job characteristic inventories (JCI and JDS) were used to assess levels of job worth and job design, respectively. Average salary was obtained for the twenty jobs. Results indicated that there was moderate convergence between job evaluation and job design. The degree of convergence between job worth and job design was much higher for clerical jobs than for professional/scientific jobs. Furthermore, the degree of convergence between job design and job evaluation was higher with the JDS than the JCI. Also, job pay was shown to be highly related to job design, especially in the clerical job family. The only job characteristic that was strongly and consistently related to the job evaluation factors and job pay was variety. The varying results across job families provided evidence that these two constructs are not redundant. The implications of these and other findings and suggestions for future research are discussed

Shipbuilding and economic cycles: a non-linear econometric approach

Purpose Economic studies have always underlined the cyclical trends of many industries and their different relations to the macro-economic cycles. Shipping is one of those industries and it has been often characterised by peaks that have influenced both the trade patterns and industry investment structure (e.g. fleet, shipyard activity, freight rates). One of the main issues related with the cycles is the effect on overcapacity and prices for newbuilding and how the understanding of these patterns can help in preventing short-hand strategies. The purpose of this paper is to evaluate different effects of business elements on shipbuilding activity, in relation to different economic-cycle phases. Design/methodology/approach This paper proposes a non-linear econometric model to identify the relations between shipbuilding and economic cycles over the past 30 years. The research focuses on identifying the cycle characteristics and understanding the asymmetrical effect of economic- and business-related variables on its development. Findings The study underlines the presence of an asymmetric effect of several business variables on the shipbuilding productions, depending on the cyclical phases (i.e. market expansion or economic slowdown). Moreover, lagged effects seem to be stronger than contemporaneous variables. Originality/value The paper is a first attempt of using non-linear modelling to shipbuilding cycles, giving indications that could be included in relevant investment policies

HCV derived from sera of HCV-infected patients induces pro-fibrotic effects in human primary fibroblasts by activating GLI2

Hepatitis C virus (HCV) infection is a leading cause of liver fibrosis, especially in developing countries. The process is characterized by the excess accumulation of ECM that may lead, over time, to hepatic cirrhosis, liver failure and also to hepatocarcinoma. The direct role of HCV in promoting fibroblasts trans-differentiation into myofibroblasts, the major fibrogenic cells, has not been fully clarified. In this study, we found that HCV derived from HCV-infected patients infected and directly induced the trans-differentiation of human primary fibroblasts into myofibroblasts, promoting fibrogenesis. This effect correlated with the activation of GLI2, one of the targets of Hedgehog signaling pathway previously reported to be involved in myofibroblast generation. Moreover, GLI2 activation by HCV correlated with a reduction of autophagy in fibroblasts, that may further promoted fibrosis. GLI2 inhibition by Gant 61 counteracted the pro-fibrotic effects and autophagy inhibition mediated by HCV, suggesting that targeting HH/GLI2 pathway might represent a promising strategy to reduce the HCV-induced fibrosis

Smart transportation systems (STSs) in critical conditions

In the context of smart transportation systems (STSs) in smart cities, the use of applications that can help in case of critical conditions is a key point. Examples of critical conditions may be natural-disaster events such as earthquakes, hurricanes, floods, and manmade ones such as terrorist attacks and toxic waste spills. Disaster events are often combined with the destruction of the local telecommunication infrastructure, if any, and this implies real problems to the rescue operations.The quick deployment of a telecommunication infrastructure is essential for emergency and safety operations as well as the rapid network reconfigurability, the availability of open source software, the efficient interoperability, and the scalability of the technological solutions. The topic is very hot and many research groups are focusing on these issues. Consequently, the deployment of a smart network is fundamental. It is needed to support both applications that can tolerate delays and applications requiring dedicated resources for real-time services such as traffic alert messages, and public safety messages. The guarantee of quality of service (QoS) for such applications is a key requirement.In this chapter we will analyze the principal issues of the networking aspects and will propose a solution mainly based on software defined networking (SDN). We will evaluate the benefit of such paradigm in the mentioned context focusing on the incremental deployment of such solution in the existing metropolitan networks and we will design a "QoS App" able to manage the quality of service on top of the SDN controller

A computational approach for the discovery of protein–RNA networks

Protein–RNA interactions play important roles in a wide variety of cellular processes, ranging from transcriptional and posttranscriptional regulation of genes to host defense against pathogens. In this chapter we present the computational approach catRAPID to predict protein–RNA interactions and discuss how it could be used to find trends in ribonucleoprotein networks. We envisage that the combination of computational and experimental approaches will be crucial to unravel the role of coding and noncoding RNAs in protein networks