10 research outputs found
State of Disaster Risk Reduction at the Local Level: A report on the Patterns of Disaster Risk Reduction Actions at Local Level
No full textContamination Status of Salmonella spp., Shigella spp. and Campylobacter spp. in Surface and Groundwater of the Kelani River Basin, Sri Lanka
No full textWaterborne diseases are a global problem that causes more than 2.2 million deaths annually. Therefore, the present study was focused on microbiological contamination of both ground and surface water by means of total coliform, Escherichia coli (E. coli), Salmonella spp., Shigella spp. and Campylobacter spp. Seventy two groundwater and 45 surface water sampling locations were selected to collect water from the head, transitional and meandering regions of the Kelani River Basin for a period of one year (both dry and wet seasons). The results of the study revealed that the entire Kelani River basin was contaminated with total coliform and E. coli bacteria and almost all the sampling locations exceed Sri Lanka Standards Institute (SLSI) guideline value given for drinking water (0 CFU/100 mL). Further, in groundwater, 17 locations were positive for Salmonella spp., whereas only 2 locations were positive for Campylobacter spp. In surface water, 26 and three sampling locations were positive for Salmonella spp. and Campylobacter spp., respectively. In this study, 23 different human pathogenic serovars were isolated and the Salmonella enterica serovar Kentucky was identified as the commonest type. Thus, the result of the study revealed that the consumption of raw water from the Kelani River Basin is unsafe and possible to cause gastrointestinal diseases
Scientometric Analysis of the Global Scientific Literature on Circularity Indicators in the Construction and Built Environment Sector
No full textThe circular-economy-related research has exponentially increased in recent years. The literature shows that circularity indicators represent a timely topic that requires an in-depth analysis. However, the trends and gaps in the literature in the area of the circular economy have not need analysed in depth. This study uses a scientometric analysis as the research methodology to examine the current literature on circularity and circular economic indicators. The publications were extracted from the Web of Science and were published until the end of the third quarter of 2022. The scientometric analysis was conducted using VOSviewer software to map the relationships between the 1117 articles selected on the topic. The findings revealed that the most productive author and university were Jorge de Brito and Delft University of Technology in the Netherlands. The overlay visualisation of the keywords identified a notable shift in research themes from dynamics, frameworks, models, and design in previous years to economy, barriers, and strategies in the current research context. The overlay visualisation of the keywords identified trending research hotspots within the current research context. This study is the first holistic and global overview of circularity and circular economic indicators in the construction context and identifies a critical need for further research to understand circularity and circular economic indicators under co-occurrence analysis conditions. This study offers academics, policymakers, and other circularity activists a guide for future research and valuable insight into circularity and circularity indicator themes.fals
The first case of prosthetic valve endocarditis due to Salmonella enterica Serovar Enteritidis infection in Sri Lanka
No full textProsthetic valve replacement is one of the predisposing factors for the development of infective endocarditis. Prosthetic valve infective endocarditis caused by non typhoidal Salmonellae is an uncommon manifestation. We report a case of a female patient with a history of bioprosthetic aortic valve replacement admitted due to prolonged fever with diarrhoea. The echocardiogram revealed a prosthetic valve vegetation with the etiological diagnosis of infective endocarditis by Salmonella enterica Serovar Enteritidis. She had a fulminant clinical course and died after 6 months despite prolonged antibiotic treatment.</p
Tonal detection thresholds in the presence of loud (80 dBA) noise : an empirical and computational ergonomics study
No full textIn a recent industrial consultation study, the author observed that workers could easily detect a 59 dBA train alarm in the presence of 77 dBA train noise; a signal-to-noise ratio (SNR) of -18 dB. A literature review indicated that little is known about alarm detection with SNRs of -18 dB or below. The first experiment of this study was designed to repeat the observations with 12 participants. Four stimuli conditions with alarms at -18, -21, -24 and -∞ dB SNRs were studied. The train alarm (2 kHz with harmonics at 4 kHz, 6 kHz, 8 kHz and 12 kHz) and the train noise (with pink spectrum) were similar to the observed signals. Results indicated that the subjects were able to detect the train alarm with -24 dB SNR and the perceived loudness of the train alarm was significantly different among all four conditions. The SNR level of -24 dB was further reduced to -28 dB (median value) in the second experiment with sixteen participants using a two interval forced choice (2IFC) testing protocol. This was referred to as the alarm-in-noise (AIN) detection threshold. In addition, results indicated that if free-field spatial information was removed by presenting the train alarm and the train noise monaurally and diotically, the median AIN levels raised back to -13 dB and -14.3 dB, respectively. There was a statistically significant difference between the detection thresholds collected at the monaural and free-field conditions (p<0.05). In the second experiment, train alarms of different durations were tested and found to have no significant effect on the detection thresholds. A large inter-subject variability was also observed ranging from -9 dB to -46 dB SNR. In an attempt to uncover the mechanism behind an AIN detection threshold of -28 dB SNR (or -46dB in one listener), a customized biologically inspired model for hearing was constructed. The model was based on the existing Matlab Auditory Periphery (MAP) model developed by Meddis (2006). It contains basic modules to simulate and predict sound transmission from the pinna to the middle ear, the cochlea and the subsequent excitations of auditory nerves. The simulation results of the initial model indicated subtle but repeatable changes in the basilar membrane (BM) displacements and auditory nerve firing patterns related to the stimuli conditions of the experiments. In particular, the effects of efferent feedback of the medial olivocochlear system (MOCS) were simulated because this type of efferent feedback had been shown to improve speech intelligibility in noise. A third experiment was conducted to test the hypothesis that the MOCS efferent feedback would help the detection of train alarm in loud train noise. Subjects of the second experiment were tested for their strength of efferent feedback in terms of their contralateral suppression of the transient-evoked otoacoustic emissions (TEOAEs). To our surprise, correlation analysis indicated a significant (p<0.05) but negative correlation between contralateral suppression of TEOAEs and masked detection thresholds. This implied that stronger MOCS efferent feedback worsens the detection performance in negative SNR conditions. The fourth experiment verified and confirmed that the negative SNR levels of AIN also held for tone-in-noise (TIN) detection thresholds (1 kHz and 2 kHz). The thesis contains novel and original results that are beneficial for both industrial and academic purposes. The customized and calibrated biologically-inspired MAP models can be a useful platform for testing and developing future auditory alarms in noisy environments.</p
A scientometric analysis of global scientific literature on learning resources in higher education
No full textThere is a significant increase in the literature on learning resources in Higher Education (HE) butvery limited evidence of studies that have taken a global overview of the context, range, andemerging trends from the previous research. This study aims to conduct a Scientometric analysisof research articles to accommodate a global overview and research trends under the theme oflearning resources in HE. 4489 scientific articles were obtained as the dataset from the Web OfScience database between 1970 and 2022. Network maps and critical data were obtained byconducting co-authorship analysis for authors, organisations and countries and co-occurrenceanalysis for keywords from the VOSviewer software. The study revealed that the USA had asignificant research input, and Salamin, N. from the University of Lausanne was recognised as themost frequently published author. The University of Illinois, USA, has the highest contribution toresearch articles, and the most popular research hotspots and trends were e-learning, Education,Academic libraries, Learning resources, and Cloud computing. However, the most critical findingfrom the study is that there needs to be real collaboration within the research theme and suggestsways to improve collaborations to enhance learning resources in HE. This study may be the first toconduct a scientometric analysis of Learning Resources in Higher education. This study offersvaluable insight to academics, academic institutions, researchers, policymakers and pedagogicalstatutory bodies to understand the current context of learning resources in HE and recognisefurther develop research, collaborations and policies by considering critical findings from thestudy
A scientometric analysis of global scientific literature on learning resources in higher education
No full textThere is a significant increase in the literature on learning resources in Higher Education (HE) but very limited evidence of studies that have taken a global overview of the context, range, and emerging trends from the previous research. This study aims to conduct a Scientometric analysis of research articles to accommodate a global overview and research trends under the theme of learning resources in HE. 4489 scientific articles were obtained as the dataset from the Web Of Science database between 1970 and 2022. Network maps and critical data were obtained by conducting co-authorship analysis for authors, organisations and countries and co-occurrence analysis for keywords from the VOSviewer software. The study revealed that the USA had a significant research input, and Salamin, N. from the University of Lausanne was recognised as the most frequently published author. The University of Illinois, USA, has the highest contribution to research articles, and the most popular research hotspots and trends were e-learning, Education, Academic libraries, Learning resources, and Cloud computing. However, the most critical finding from the study is that there needs to be real collaboration within the research theme and suggests ways to improve collaborations to enhance learning resources in HE. This study may be the first to conduct a scientometric analysis of Learning Resources in Higher education. This study offers valuable insight to academics, academic institutions, researchers, policymakers and pedagogical statutory bodies to understand the current context of learning resources in HE and recognise further develop research, collaborations and policies by considering critical findings from the study
Development and application of a deep learning–based sparse autoencoder framework for structural damage identification
No full text© The Author(s) 2018. This article proposes a deep sparse autoencoder framework for structural damage identification. This framework can be employed to obtain the optimal solutions for some pattern recognition problems with highly nonlinear nature, such as learning a mapping between the vibration characteristics and structural damage. Three main components are defined in the proposed framework, namely, the pre-processing component with a data whitening process, the sparse dimensionality reduction component where the dimensionality of the original input vector is reduced while preserving the required necessary information, and the relationship learning component where the mapping between the compressed dimensional feature and the stiffness reduction parameters of the structure is built. The proposed framework utilizes the sparse autoencoders based deep neural network structure to enhance the capability and performance of the dimensionality reduction and relationship learning components with a pre-training scheme. In the final stage of training, both components are jointly optimized to fine-tune the network towards achieving a better accuracy in structural damage identification. Since structural damages usually occur only at a small number of elements that exhibit stiffness reduction out of the large total number of elements in the entire structure, sparse regularization is adopted in this framework. Numerical studies on a steel frame structure are conducted to investigate the accuracy and robustness of the proposed framework in structural damage identification, taking into consideration the effects of noise in the measurement data and uncertainties in the finite element modelling. Experimental studies on a prestressed concrete bridge in the laboratory are conducted to further validate the performance of using the proposed framework for structural damage identification
A scientometric analysis of global scientific literature on learning resources in higher education
No full text© 2023 The Authors. Published by Elsevier. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1016/j.heliyon.2023.e15438There is a significant increase in the literature on learning resources in Higher Education (HE) but very limited evidence of studies that have taken a global overview of the context, range, and emerging trends from the previous research. This study aims to conduct a Scientometric analysis of research articles to accommodate a global overview and research trends under the theme of learning resources in HE. 4489 scientific articles were obtained as the dataset from the Web Of Science database between 1970 and 2022. Network maps and critical data were obtained by conducting co-authorship analysis for authors, organisations and countries and co-occurrence analysis for keywords from the VOSviewer software. The study revealed that the USA had a significant research input, and Salamin, N. from the University of Lausanne was recognised as the most frequently published author. The University of Illinois, USA, has the highest contribution to research articles, and the most popular research hotspots and trends were e-learning, Education, Academic libraries, Learning resources, and Cloud computing. However, the most critical finding from the study is that there needs to be real collaboration within the research theme and suggests ways to improve collaborations to enhance learning resources in HE. This study may be the first to conduct a scientometric analysis of Learning Resources in Higher education. This study offers valuable insight to academics, academic institutions, researchers, policymakers and pedagogical statutory bodies to understand the current context of learning resources in HE and recognise further develop research, collaborations and policies by considering critical findings from the study.Published versio
Intracerebral hemorrhage location and outcome among INTERACT2 participants
No full textObjective: To clarify associations between intracerebral hemorrhage (ICH) location and clinical outcomes among participants of the main phase Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trial (INTERACT2).
Methods: Associations between ICH sites and poor outcomes (death [6] or major disability [3–5] of modified Rankin Scale) and European Quality of Life Scale (EQ-5D) utility scores at 90 days were assessed in logistic regression models.
Results: Of 2,066 patients included in the analyses, associations were identified between ICH sites and poor outcomes: involvement of posterior limb of internal capsule increased risks of death or major disability (odds ratio [OR] 2.10) and disability (OR 1.81); thalamic involvement increased risks of death or major disability (OR 2.24) and death (OR 1.97). Involvement of the posterior limb of the internal capsule, thalamus, and infratentorial sites were each associated with poor EQ-5D utility score (≤0.7 [median]; OR 1.87, 2.14, and 2.81, respectively). Posterior limb of internal capsule involvement was strongly associated with low scores across all health-related quality of life domains. ICH encompassing the thalamus and posterior limb of internal capsule were associated with death or major disability, major disability, and poor EQ-5D utility score (OR 1.72, 2.26, and 1.71, respectively).
Conclusion: Poor clinical outcomes are related to ICH affecting the posterior limb of internal capsule, thalamus, and infratentorial sites. The highest association with death or major disability and poor EQ-5D utility score was seen in ICH encompassing the thalamus and posterior limb of internal capsule.
ClinicalTrials.gov registration: NCT00716079
