Progress and challenges of disaster health management in China : a scoping review

Background Despite the importance of an effective health system response to various disasters, relevant research is still in its infancy, especially in middle- and low-income countries. Objective This paper provides an overview of the status of disaster health management in China, with its aim to promote the effectiveness of the health response for reducing disaster-related mortality and morbidity. Design A scoping review method was used to address the recent progress of and challenges to disaster health management in China. Major health electronic databases were searched to identify English and Chinese literature that were relevant to the research aims. Results The review found that since 2003 considerable progress has been achieved in the health disaster response system in China. However, there remain challenges that hinder effective health disaster responses, including low standards of disaster-resistant infrastructure safety, the lack of specific disaster plans, poor emergency coordination between hospitals, lack of portable diagnostic equipment and underdeveloped triage skills, surge capacity, and psychological interventions. Additional challenges include the fragmentation of the emergency health service system, a lack of specific legislation for emergencies, disparities in the distribution of funding, and inadequate cost-effective considerations for disaster rescue. Conclusions One solution identified to address these challenges appears to be through corresponding policy strategies at multiple levels (e.g. community, hospital, and healthcare system level).

A case study in flood fatality : Beijing July 2012 flood

Background The aim of this study is to examine the flood fatality with a view to identifying risks which may inform public policy responses to future flood. On July 21st, 2012, Beijing suffered the heaviest rain since 1963. The average rainfall was 215 mm over a 24 hour period in the central city (301mm in Fangshan District). The rain resulted in a flood that caused severe health, social and financial impact. Results This flood caused 79 deaths. Of the 71 deaths for which a specific cause could be identified, 5 were rescue team members, 42 were killed by drowning (11 in the car), and the others by electricity shock, fallen house, falling items and lightning. The total financial cost was estimated to be US$ 1.7 billion. The causations of the deaths inform the risks associated with the flood. Discussion This flood had a catastrophic impact on Beijing, mainly due to the intensity of the rain (the rain was the heaviest in the modern Beijing history; possibly due to global warming and urban heat island effect), the vulnerability of the infrastructure (poor standards of drainage, disorganized water management systems and decreased permeability of the earth as a result of the city’s rapid development), and the capacity of the response system (mainly dependent on the awareness of the citizens, warning systems and the capacity of the emergency rescue). Implication Many risk management measures have been implemented as a result of this flood, including water level warning marks, flood safety education and warnings sent to mobile phones, a project to move about 74,500 farmers away from the flood-prone areas within 5 years. However, further measures targeted at the fundamental issues identified by this analysis are necessary, especially those targeting at health issues. These may include better planning, improved drainage systems and ecological development to increase permeability etc..

Psychological health of medical and dental students in Saudi Arabia : a longitudinal study

Introduction: Many studies have indicated the poor psychological health of medical and dental students. However, few studies have assessed the longitudinal trajectory of that psychological health at different times in an academic year. Aim: To evaluate the positive and negative aspects of psychological health among preclinical medical and dental students in Saudi Arabia prospectively. Methods: A total of 317 preclinical medical and dental students were recruited for a longitudinal study design from second and third-year students at Umm Al-Qura University in the 2012-2013 academic year. The students were assessed at the middle of the first term and followed up after 3-monthes at the beginning of the second term. Questionnaires included assessment of depression, anxiety, stress, self-efficacy, and satisfaction with life. Results: Depression, anxiety, stress, and satisfaction with life were improved significantly at the beginning of the second term, whereas self-efficacy did not change significantly. The medical, female, and third-year student subgroups had the most significant changes. Depression and stress were significantly changed at the beginning of the second term in most demographic subgroups. Conclusion: Preclinical medical and dental students have different psychological health levels at different times of the same academic year. It is recommended to consider time of data collection when analyzing the results of such studies.

Explanation of relevance judgement discrepancy with quantum interference

A key concept in many Information Retrieval (IR) tasks, e.g. document indexing, query language modelling, aspect and diversity retrieval, is the relevance measurement of topics, i.e. to what extent an information object (e.g. a document or a query) is about the topics. This paper investigates the interference of relevance measurement of a topic caused by another topic. For example, consider that two user groups are required to judge whether a topic q is relevant to a document d, and q is presented together with another topic (referred to as a companion topic). If different companion topics are used for different groups, interestingly different relevance probabilities of q given d can be reached. In this paper, we present empirical results showing that the relevance of a topic to a document is greatly affected by the companion topic’s relevance to the same document, and the extent of the impact differs with respect to different companion topics. We further analyse the phenomenon from classical and quantum-like interference perspectives, and connect the phenomenon to nonreality and contextuality in quantum mechanics. We demonstrate that quantum like model fits in the empirical data, could be potentially used for predicting the relevance when interference exists.

Text mining with semantic annotation : using enriched text representation for entity-oriented retrieval, semantic relation identification and text clustering

This project is a step forward in the study of text mining where enhanced text representation with semantic information plays a significant role. It develops effective methods of entity-oriented retrieval, semantic relation identification and text clustering utilizing semantically annotated data. These methods are based on enriched text representation generated by introducing semantic information extracted from Wikipedia into the input text data. The proposed methods are evaluated against several start-of-art benchmarking methods on real-life data-sets. In particular, this thesis improves the performance of entity-oriented retrieval, identifies different lexical forms for an entity relation and handles clustering documents with multiple feature spaces.

Robust clustering of multi-type relational data via a heterogeneous manifold ensemble

High-Order Co-Clustering (HOCC) methods have attracted high attention in recent years because of their ability to cluster multiple types of objects simultaneously using all available information. During the clustering process, HOCC methods exploit object co-occurrence information, i.e., inter-type relationships amongst different types of objects as well as object affinity information, i.e., intra-type relationships amongst the same types of objects. However, it is difficult to learn accurate intra-type relationships in the presence of noise and outliers. Existing HOCC methods consider the p nearest neighbours based on Euclidean distance for the intra-type relationships, which leads to incomplete and inaccurate intra-type relationships. In this paper, we propose a novel HOCC method that incorporates multiple subspace learning with a heterogeneous manifold ensemble to learn complete and accurate intra-type relationships. Multiple subspace learning reconstructs the similarity between any pair of objects that belong to the same subspace. The heterogeneous manifold ensemble is created based on two-types of intra-type relationships learnt using p-nearest-neighbour graph and multiple subspaces learning. Moreover, in order to make sure the robustness of clustering process, we introduce a sparse error matrix into matrix decomposition and develop a novel iterative algorithm. Empirical experiments show that the proposed method achieves improved results over the state-of-art HOCC methods for FScore and NMI.

Reliable Fault Diagnosis for Low-Speed Bearings Using Individually Trained Support Vector Machines With Kernel Discriminative Feature Analysis

This paper proposes a highly reliable fault diagnosis approach for low-speed bearings. The proposed approach first extracts wavelet-based fault features that represent diverse symptoms of multiple low-speed bearing defects. The most useful fault features for diagnosis are then selected by utilizing a genetic algorithm (GA)-based kernel discriminative feature analysis cooperating with one-against-all multicategory support vector machines (OAA MCSVMs). Finally, each support vector machine is individually trained with its own feature vector that includes the most discriminative fault features, offering the highest classification performance. In this study, the effectiveness of the proposed GA-based kernel discriminative feature analysis and the classification ability of individually trained OAA MCSVMs are addressed in terms of average classification accuracy. In addition, the proposedGA- based kernel discriminative feature analysis is compared with four other state-of-the-art feature analysis approaches. Experimental results indicate that the proposed approach is superior to other feature analysis methodologies, yielding an average classification accuracy of 98.06% and 94.49% under rotational speeds of 50 revolutions-per-minute (RPM) and 80 RPM, respectively. Furthermore, the individually trained MCSVMs with their own optimal fault features based on the proposed GA-based kernel discriminative feature analysis outperform the standard OAA MCSVMs, showing an average accuracy of 98.66% and 95.01% for bearings under rotational speeds of 50 RPM and 80 RPM, respectively.

Psychological well-being status among medical and dental students in Makkah, Saudi Arabia: A cross-sectional study

Objectives Medical and dental students experience poor psychological well-being relative to their peers. This study aimed to assess the psychological well-being among medical and dental students in Saudi Arabia, identify the high-risk groups and assess the association between the psychological well-being and the academic performance. Methods In this cross-sectional study, 422 preclinical medical and dental students at Umm Al-Qura University, Saudi Arabia, were recruited to assess their depression, anxiety, stress, self-efficacy and satisfaction with life levels using 21-items Depression Anxiety Stress Scale (DASS-21), General Self-Efficacy (GSE) scale and Satisfaction With Life Scale (SWLS). Students’ academic weighted grades were obtained later. Descriptive statistics and univariate general linear model were used to analyse data. Results High levels of depression (69.9%), anxiety (66.4%) and stress (70.9%) were indicated, whereas self-efficacy (mean = 27.22, sd = 4.85) and life satisfaction (mean = 23.60, sd = 6.37) were within the normal range. Female medical students had higher psychological distress in contrast to dental students. In general, third-year students were more depressed and stressed in comparison with second-year students, except for stress among dental students. Moreover, all females had higher self-efficacy than males. Life satisfaction was higher within the second-year and high family income students. Depression was the only psychological variable correlated with the academic performance. Conclusion High levels of psychological distress were found. Female medical students had higher psychological distress than males, whereas male dental students had higher distress than female. Medical students at third year were more depressed and stressed. Dental students were more depressed in the third year, but more stressed in the second year. Attention should be directed towards reducing the alarming levels of depression, anxiety and stress among medical and dental students.

Symmetry is an organizing principle in neuronal dendrotaxis

Symmetry is a fundamental property found in both the physical and natural worlds. Bilateral symmetry is also present in the organization of the brain, however the degree to which symmetry is also an organizing principal between and within the key constituent elements of the nervous system, neurons, is not known. We compared and contrasted the structural organization of principal neurons (PN) in the three subnuclei of the lateral amygdala (LA) of the rat and for comparison also from the infralimbic cortex (IL)...