Human error risk management methodology for rail crack incidents

The paper presents an innovative approach to modelling the causal relationships of human errors in rail crack incidents (RCI) from a managerial perspective. A Bayesian belief network is developed to model RCI by considering the human errors of designers, manufactures, operators and maintainers (DMOM) and the causal relationships involved. A set of dependent variables whose combinations express the relevant functions performed by each DMOM participant is used to model the causal relationships. A total of 14 RCI on Hong Kong’s mass transit railway (MTR) from 2008 to 2011 are used to illustrate the application of the model. Bayesian inference is used to conduct an importance analysis to assess the impact of the participants’ errors. Sensitivity analysis is then employed to gauge the effect the increased probability of occurrence of human errors on RCI. Finally, strategies for human error identification and mitigation of RCI are proposed. The identification of ability of maintainer in the case study as the most important factor influencing the probability of RCI implies the priority need to strengthen the maintenance management of the MTR system and that improving the inspection ability of the maintainer is likely to be an effective strategy for RCI risk mitigation.

Design based research methodology for teaching with technology in English

Design based research (DBR) is an appropriate method for small scale educational research projects involving collaboration between teachers, students and researchers. It is particularly useful in collaborative projects where an intervention is implemented and evaluated in a grounded context. The intervention can be technological, or a new program required by policy changes. It can be applied to educational contexts, such as when English teachers undertake higher degree research projects in their own or others’ sites; or for academics working collaboratively as researchers with teams of teachers. In the case described here the paper shows that DBR is designed to make a difference in the real world contexts in which occurs.

Welfare effects of aid under quantitative trade restrictions

The paper examines the effects of tied-aid on the welfare of both the donor and the recipient countries. We depart from the previous literature by assuming preexistence of quantitative trade distortions. To mitigate these distortions the donor country provides aid that is tied to the rationed good. Conditions for the presence of the transfer paradox and of the enrichment of both countries are derived and interpreted under the stability of the system. Furthermore, we show that whereas untied aid cannot increase global welfare, tied-aid unambiguously does so.

Simulation and modelling tools for quantitative safety assessments of unmanned aircraft systems and operations

This paper presents two simple simulation and modelling tools designed to aid in the safety assessment required for unmanned aircraft operations within unsegregated airspace. First, a fast pair-wise encounter generator is derived to simulate the See and Avoid environment. The utility of the encounter generator is demonstrated through the development of a hybrid database and a statistical performance evaluation of an autonomous See and Avoid decision and control strategy. Second, an unmanned aircraft mission generator is derived to help visualise the impact of multiple persistent unmanned operations on existing air traffic. The utility of the mission generator is demonstrated through an example analysis of a mixed airspace environment using real traffic data in Australia. These simulation and modelling approaches constitute a useful and extensible set of analysis tools, that can be leveraged to help explore some of the more fundamental and challenging problems facing civilian unmanned aircraft system integration.

Impact of chemotherapy on cancer-related fatigue and cytokines in 1312 patients: A systematic review of quantitative studies

Purpose of review: Cancer-related fatigue (CRF) is the most common psychosomatic distress experienced by cancer patients before, during and after chemotherapy. Its impact on functional status and Health Related Quality of Life is a great concern among patients, healthcare professionals and researchers. The primary objective of this systematic review is to determine whether the different chemotherapies affect the association of CRF with individual pro- and anti-inflammatory cytokines. The PRISMA statement guideline has been followed to systematically search and screen article from PubMed and Embase. Recent findings: This review has examined 14 studies which included a total of 1312 patients. These studies assayed 20 different kinds of cytokines. The cytokines interleukin-6, interleukin-1RA, TGF-[beta] and sTNF-R2 were associated with CRF in patients receiving anthracycline-based chemotherapy. However, only interleukin-13 was identified in the taxane-based chemotherapy. Similarly, different sets of cytokines were linked with CRF in patients with chemotherapy regimens containing platinum, cyclophosphamides, topotecan or bleomycin. Summary: This review has identified that cytokines are differentially linked with CRF according to the various types of chemotherapy regimens.

Towards a typology of hashtag publics: A large-scale comparative study of user engagement across trending topics

Twitter’s hashtag functionality is now used for a very wide variety of purposes, from covering crises and other breaking news events through gathering an instant community around shared media texts (such as sporting events and TV broadcasts) to signalling emotive states from amusement to despair. These divergent uses of the hashtag are increasingly recognised in the literature, with attention paid especially to the ability for hashtags to facilitate the creation of ad hoc or hashtag publics. A more comprehensive understanding of these different uses of hashtags has yet to be developed, however. Previous research has explored the potential for a systematic analysis of the quantitative metrics that could be generated from processing a series of hashtag datasets. Such research found, for example, that crisis-related hashtags exhibited a significantly larger incidence of retweets and tweets containing URLs than hashtags relating to televised events, and on this basis hypothesised that the information-seeking and -sharing behaviours of Twitter users in such different contexts were substantially divergent. This article updates such study and their methodology by examining the communicative metrics of a considerably larger and more diverse number of hashtag datasets, compiled over the past five years. This provides an opportunity both to confirm earlier findings, as well as to explore whether hashtag use practices may have shifted subsequently as Twitter’s userbase has developed further; it also enables the identification of further hashtag types beyond the “crisis” and “mainstream media event” types outlined to date. The article also explores the presence of such patterns beyond recognised hashtags, by incorporating an analysis of a number of keyword-based datasets. This large-scale, comparative approach contributes towards the establishment of a more comprehensive typology of hashtags and their publics, and the metrics it describes will also be able to be used to classify new hashtags emerging in the future. In turn, this may enable researchers to develop systems for automatically distinguishing newly trending topics into a number of event types, which may be useful for example for the automatic detection of acute crises and other breaking news events.