Investigating IoT Middleware Platforms for Smart Application Development

With the growing number of Internet of Things (IoT) devices, the data generated through these devices is also increasing. By 2030, it is been predicted that the number of IoT devices will exceed the number of human beings on earth. This gives rise to the requirement of middleware platform that can manage IoT devices, intelligently store and process gigantic data generated for building smart applications such as Smart Cities, Smart Healthcare, Smart Industry, and others. At present, market is overwhelming with the number of IoT middleware platforms with specific features. This raises one of the most serious and least discussed challenge for application developer to choose suitable platform for their application development. Across the literature, very little attempt is done in classifying or comparing IoT middleware platforms for the applications. This paper categorizes IoT platforms into four categories namely-publicly traded, open source, developer friendly and end-to-end connectivity. Some of the popular middleware platforms in each category are investigated based on general IoT architecture. Comparison of IoT middleware platforms in each category, based on basic, sensing, communication and application development features is presented. This study can be useful for IoT application developers to select the most appropriate platform according to their application requirement

Does health intervention improve socioeconomic inequalities of neonatal, infant and child mortality? Evidence from Matlab, Bangladesh

<p>Abstract</p> <p>Background</p> <p>Although there are wide variations in mortality between developed and developing countries, socioeconomic inequalities in health exist in both the societies. The study examined socioeconomic inequalities of neonatal, infant and child mortality using data from the Matlab Health and Demographic Surveillance System of the International Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR,B).</p> <p>Methods</p> <p>Four birth cohorts (1983–85, 1988–90, 1993–95, 1998–00) were followed for five years for death and out-migration in two adjacent areas (ICDDR,B-service and government-service) with similar socioeconomic but differ health services. Based on asset quintiles, inequality was measured through both poor-rich ratio and concentration index.</p> <p>Results</p> <p>The study found that the socioeconomic inequalities of neonatal, infant and under-five mortality increased over time in both the ICDDR,B-service and government-service areas but it declined substantially for 1–4 years in the ICDDR,B- service area.</p> <p>Conclusion</p> <p>The study concluded that usual health intervention programs (non-targeted) do not reduce poor-rich gap, rather the gap increases initially but might decrease in long run if the program is very intensive.</p

Integrated multi‑omics analysis of ovarian cancer using variational autoencoders

Cancer is a complex disease that deregulates cellular functions at various molecular levels (e.g., DNA, RNA, and proteins). Integrated multi‑omics analysis of data from these levels is necessary to understand the aberrant cellular functions accountable for cancer and its development. In recent years, Deep Learning (DL) approaches have become a useful tool in integrated multi‑omics analysis of cancer data. However, high dimensional multi‑omics data are generally imbalanced with too many molecular features and relatively few patient samples. This imbalance makes a DL based integrated multi‑omics analysis difficult. DL‑based dimensionality reduction technique, including variational autoencoder (VAE), is a potential solution to balance high dimensional multi‑omics data. However, there are few VAE‑based integrated multi‑omics analyses, and they are limited to pancancer. In this work, we did an integrated multi‑omics analysis of ovarian cancer using the compressed features learned through VAE and an improved version of VAE, namely Maximum Mean Discrepancy VAE (MMD‑VAE). First, we designed and developed a DL architecture for VAE and MMD‑VAE. Then we used the architecture for mono‑omics, integrated di‑omics and tri‑omics data analysis of ovarian cancer through cancer samples identification, molecular subtypes clustering and classification, and survival analysis. The results show that MMD‑VAE and VAE‑based compressed features can respectively classify the transcriptional subtypes of the TCGA datasets with an accuracy in the range of 93.2‑95.5% and 87.1‑95.7%. Also, survival analysis results show that VAE and MMD‑VAE based compressed representation of omics data can be used in cancer prognosis. Based on the results, we can conclude that (i) VAE and MMD‑VAE outperform existing dimensionality reduction techniques, (ii) integrated multi‑omics analyses perform better or similar compared to their mono‑omics counterparts, and (iii) MMD‑VAE performs better than VAE in most omics dataset

Blockade of advanced glycation end product formation attenuates bleomycin-induced pulmonary fibrosis in rats

<p>Abstract</p> <p>Background</p> <p>Advanced glycation end products (AGEs) have been proposed to be involved in pulmonary fibrosis, but its role in this process has not been fully understood. To investigate the role of AGE formation in pulmonary fibrosis, we used a bleomycin (BLM)-stimulated rat model treated with aminoguanidine (AG), a crosslink inhibitor of AGE formation.</p> <p>Methods</p> <p>Rats were intratracheally instilled with BLM (5 mg/kg) and orally administered with AG (40, 80, 120 mg/kg) once daily for two weeks. AGEs level in lung tissue was determined by ELISA and pulmonary fibrosis was evaluated by Ashcroft score and hydroxyproline assay. The expression of heat shock protein 47 (HSP47), a collagen specific molecular chaperone, was measured with RT-PCR and Western blot. Moreover, TGFβ1 and its downstream Smad proteins were analyzed by Western blot.</p> <p>Results</p> <p>AGEs level in rat lungs, as well as lung hydroxyproline content and Ashcroft score, was significantly enhanced by BLM stimulation, which was abrogated by AG treatment. BLM significantly increased the expression of HSP47 mRNA and protein in lung tissues, and AG treatment markedly decreased BLM-induced HSP47 expression in a dose-dependent manner (p < 0.05). In addition, AG dose-dependently downregulated BLM-stimulated overexpressions of TGFβ1, phosphorylated (p)-Smad2 and p-Smad3 protein in lung tissues.</p> <p>Conclusion</p> <p>These findings suggest AGE formation may participate in the process of BLM-induced pulmonary fibrosis, and blockade of AGE formation by AG treatment attenuates BLM-induced pulmonary fibrosis in rats, which is implicated in inhibition of HSP47 expression and TGFβ/Smads signaling.</p

Multimodal freight transportation: sustainability challenges

Due to globalization in trade, the development of multimodal cargo shipments and the related transport needs have created a range of challenges. Interestingly, sustainability of multimodal freight transportation is still subject to minor consideration, on the grounds that economic interests are frequently positioned much higher than social or environmental objectives. This proposed research plan is needed to assess whether and to what extent the multimodal freight system is achieving the results in the sustainability dimensions: economic, social and environmental. Thus, it will carry out a critical appraisal of the multimodal freight transportation sector to provide an up-to-date knowledge on the sustainability challenges and the potential solutions through doctoral research. This paper structured to present a review of existing literature on freight transportation and multimodal freight transport highlighting the sustainability concerns with multimodal freight transport systems. It also highlights the gaps in knowledge with a justification on the need to address these gaps for the system to function optimally. It also covers the methodology that would be applied and the sources of data that would be reviewed to ensure the aim and objectives are clearly addressed. The paper concludes by discussing the significance of the expected findings in the light of sustainability in multimodal freight transport to the academia, policy makers and the freight transportation industry

An investigation of factors associated with the health and well-being of HIV-infected or HIV-affected older people in rural South Africa

BackgroundDespite the severe impact of HIV in sub-Saharan Africa, the health of older people aged 50+ is often overlooked owing to the dearth of data on the direct and indirect effects of HIV on older people's health status and well-being. The aim of this study was to examine correlates of health and well-being of HIV-infected older people relative to HIV-affected people in rural South Africa, defined as participants with an HIV-infected or death of an adult child due to HIV-related cause. MethodsData were collected within the Africa Centre surveillance area using instruments adapted from the World Health Organization (WHO) Study on global AGEing and adult health (SAGE). A stratified random sample of 422 people aged 50+ participated. We compared the health correlates of HIV-infected to HIV-affected participants using ordered logistic regressions. Health status was measured using three instruments: disability index, quality of life and composite health score. ResultsMedian age of the sample was 60 years (range 50-94). Women HIV-infected (aOR 0.15, 95% confidence interval (CI) 0.08-0.29) and HIV-affected (aOR 0.20, 95% CI 0.08-0.50), were significantly less likely than men to be in good functional ability. Women's adjusted odds of being in good overall health state were similarly lower than men's; while income and household wealth status were stronger correlates of quality of life. HIV-infected participants reported better functional ability, quality of life and overall health state than HIV-affected participants. Discussion and Conclusions The enhanced healthcare received as part of anti-retroviral treatment as well as the considerable resources devoted to HIV care appear to benefit the overall well-being of HIV-infected older people; whereas similar resources have not been devoted to the general health needs of HIV uninfected older people. Given increasing numbers of older people, policy and programme interventions are urgently needed to holistically meet the health and well-being needs of older people beyond the HIV-related care system. <br/

Ecological Determinants of Highly Pathogenic Avian Influenza (H5N1) Outbreaks in Bangladesh

BACKGROUND: The agro-ecology and poultry husbandry of the south Asian and south-east Asian countries share common features, however, with noticeable differences. Hence, the ecological determinants associated with risk of highly pathogenic avian influenza (HPAI-H5N1) outbreaks are expected to differ between Bangladesh and e.g., Thailand and Vietnam. The primary aim of the current study was to establish ecological determinants associated with the risk of HPAI-H5N1 outbreaks at subdistrict level in Bangladesh. The secondary aim was to explore the performance of two different statistical modeling approaches for unmeasured spatially correlated variation. METHODOLOGY/PRINCIPAL FINDINGS: An ecological study at subdistrict level in Bangladesh was performed with 138 subdistricts with HPAI-H5N1 outbreaks during 2007-2008, and 326 subdistricts with no outbreaks. The association between ecological determinants and HPAI-H5N1 outbreaks was examined using a generalized linear mixed model. Spatial clustering of the ecological data was modeled using 1) an intrinsic conditional autoregressive (ICAR) model at subdistrict level considering their first order neighbors, and 2) a multilevel (ML) model with subdistricts nested within districts. Ecological determinants significantly associated with risk of HPAI-H5N1 outbreaks at subdistrict level were migratory birds' staging areas, river network, household density, literacy rate, poultry density, live bird markets, and highway network. Predictive risk maps were derived based on the resulting models. The resulting models indicate that the ML model absorbed some of the covariate effect of the ICAR model because of the neighbor structure implied in the two different models. CONCLUSIONS/SIGNIFICANCE: The study identified a new set of ecological determinants related to river networks, migratory birds' staging areas and literacy rate in addition to already known risk factors, and clarified that the generalized concept of free grazing duck and duck-rice cultivation interacted ecology are not significant determinants for Bangladesh. These findings will refine current understanding of the HPAI-H5N1 epidemiology in Bangladesh