Edinburgh Napier University

About: Edinburgh Napier University is a education organization based out in Edinburgh, United Kingdom. It is known for research contribution in the topics: Population & Health care. The organization has 2665 authors who have published 6859 publications receiving 175272 citations.

Devolving human resource responsibilities to the line: Beginning of the end or a new beginning for personnel?

Abstract: Alternative hypotheses for the personnel function are presented, based on findings from four case study organisations which have devolved personnel responsibilities from a designated personnel department to line managers The views of line managers and employees are sought to assess the effects of these changes The study finds that devolved responsibilities of personnel are formally geared to securing commitment from employees by promoting an integrative culture of employee management through line managers In practice, though, we find little evidence that personnel has succeeded in catalysing such changes The case study findings do not point to any clear evidence of a general increase in influence for personnel practitioners following devolution Tensions exist between line managers and personnel and the function appears to be vulnerable to further contraction The study concludes that prospects for personnel following devolution are at best uncertain

Mechanisms and mediators in coal dust induced toxicity: a review.

Abstract: Chronic inhalation of coal dust can cause several lung disorders, including simple coal workers pneumoconiosis (CWP), progressive massive fibrosis (PMF), chronic bronchitis, lung function loss, and emphysema. This review focuses on the cellular actions and interactions of key inflammatory cells and target cells in coal dust toxicity and related lung disorders, i.e. macrophages and neutrophils, epithelial cells, and fibroblasts. Factors released from or affecting these cells are outlined in separate sections, i.e. (1) reactive oxygen species (ROS) and related antioxidant protection mechanisms, and (2) cytokines, growth factors and related proteins. Furthermore, (3) components of the extracellular matrix (ECM), including the modifying role of ROS, cytokines, proteases and antiproteases are discussed in relation to tissue damage and remodelling in the respiratory tract. It is recognised that inhaled coal dust particles are important non-cellular and cellular sources of ROS in the lung, and may be significantly involved in the damage of lung target cells as well as important macromolecules including alpha-1-antitrypsin and DNA. In vitro and in vivo studies with coal dusts showed the up-regulation of important leukocyte recruiting factors, e.g. Leukotriene-B4 (LTB4), Platelet Derived Growth Factor (PDGF), Monocyte Chemotactic Protein-1 (MCP-1), and Tumor Necrosis Factor-alpha (TNF alpha), as well as the neutrophil adhesion factor Intercellular Adhesion Molecule-1 (ICAM-1). Coal dust particles are also known to stimulate the (macrophage) production of various factors with potential capacity to modulate lung cells and/or extracellular matrix, including O2-., H2O2, and NO, fibroblast chemoattractants (e.g. Transforming Growth Factor-beta (TGF beta), PDGF, and fibronectin) and a number of factors that have been shown to stimulate and/or inhibit fibroblast growth or collagen production such as (TNF alpha, TGF beta, PDGF, Insulin Like Growth Factor, and Prostaglandin-E2). Further studies are needed to clarify the in vivo kinetics and relative impact of these factors.

TSDL: A Two-Stage Deep Learning Model for Efficient Network Intrusion Detection

Abstract: The network intrusion detection system is an important tool for protecting computer networks against threats and malicious attacks. Many techniques have recently been proposed; however, these techniques face significant challenges due to the continuous emergence of new threats that are not recognized by the existing detection systems. In this paper, we propose a novel two-stage deep learning model based on a stacked auto-encoder with a soft-max classifier for efficient network intrusion detection. The model comprises two decision stages: an initial stage responsible for classifying network traffic as normal or abnormal using a probability score value. This is then used in the final decision stage as an additional feature for detecting the normal state and other classes of attacks. The proposed model is able to learn useful feature representations from large amounts of unlabeled data and classifies them automatically and efficiently. To evaluate and test the effectiveness of the proposed model, several experiments are conducted on two public datasets: an older benchmark dataset, the KDD99, and a newer one, the UNSW-NB15. The comparative experimental results demonstrate that our proposed model significantly outperforms the existing models and methods and achieves high recognition rates, up to 99.996% and 89.134%, for the KDD99 and UNSW-NB15 datasets, respectively. We conclude that our model has the potential to serve as a future benchmark for deep learning and network security research communities.

Interspecies comparisons on the uptake and toxicity of silver and cerium dioxide nanoparticles

Abstract: An increasing number and quantity of manufactured nanoparticles are entering the environment as the diversity of their applications increases, and this will lead to the exposure of both humans and wildlife. However, little is known regarding their potential health effects. We compared the potential biological effects of silver (Ag; nominally 35 and 600–1,600 nm) and cerium dioxide (CeO2; nominally <25 nm and 1–5 µm) particles in a range of cell (human hepatocyte and intestinal and fish hepatocyte) and animal (Daphnia magna, Cyprinus carpio) models to assess possible commonalities in toxicity across taxa. A variety of analytical techniques were employed to characterize the particles and investigate their biological uptake. Silver particles were more toxic than CeO2 in all test systems, and an equivalent mass dose of Ag nanoparticles was more toxic than larger micro-sized material. Cellular uptake of all materials tested was shown in C3A hepatocytes and Caco-2 intestinal cells, and for Ag, into the intestine, liver, gallbladder, and gills of carp exposed via the water. The commonalities in toxicity of these particle types across diverse biological systems suggest that cross-species extrapolations may be possible for metal nanoparticle test development in the future. Our findings also suggest transport of particles through the gastrointestinal barrier, which is likely to be an important uptake route when assessing particle risk. Environ. Toxicol. Chem. 2012;31:144–154. © 2011 SETAC