An automated patient monitoring using discrete‐time wireless sensor networks

In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature.     

aiTPR: Attribute Interaction-Tensor Product Representation for Image Caption

Neural Processing Letters - Region visual features enhance the generative capability of the machines based on features. However, they lack proper interaction-based attentional perceptions and end...     

High-resolution image de-raining using conditional GAN with sub-pixel upscaling

Multimedia Tools and Applications - High-quality image de-raining is a challenging task that has been given considerable importance in recent times. To begin with, this problem is modeled as an...     

Validation of Tuba1a as Appropriate Internal Control for Normalization of Gene Expression Analysis during Mouse Lung Development

The expression ratio between the analysed gene and an internal control gene is the most widely used normalization method for quantitative RT-PCR (qRT-PCR) expression analysis. The ideal reference gene for a specific experiment is the one whose expression is not affected by the different experimental conditions tested. In this study, we validate the applicability of five commonly used reference genes during different stages of mouse lung development. The stability of expression of five different reference genes (Tuba1a, Actb Gapdh, Rn18S and Hist4h4) was calculated within five experimental groups using the statistical algorithm of geNorm software. Overall, Tuba1a showed the least variability in expression among the different stages of lung development, while Hist4h4 and Rn18S showed the maximum variability in their expression. Expression analysis of two lung specific markers, surfactant protein C (SftpC) and Clara cell-specific 10 kDA protein (Scgb1a1), normalized to each of the five reference genes tested here, confirmed our results and showed that incorrect reference gene choice can lead to artefacts. Moreover, a combination of two internal controls for normalization of expression analysis during lung development will increase the accuracy and reliability of results.     

Automated cell classification and visualization for analyzing remyelination therapy

Remyelination therapy is a state-of-the-art technique for treating spinal cord injury (SCI). Demyelination—the loss of myelin sheath that insulates axons, is a prominent feature in many neurological disorders resulting in SCI. This lost myelin sheath can be replaced by remyelination. In this paper, we propose an algorithm for efficient automated cell classification and visualization to analyze the progress of remyelination therapy in SCI. Our method takes as input the images of the cells and outputs a density map of the therapeutically important oligodendrocyte-remyelinated axons (OR-axons) which is used for efficacy analysis of the therapy. Our method starts with detecting cell boundaries using a robust, shape-independent algorithm based on iso-contour analysis of the image at progressively increasing intensity levels. The detected boundaries of spatially clustered cells are then separated using the Delaunay triangulation based contour separation method. Finally, the OR-axons are identified and a density map is generated for efficacy analysis of the therapy. Our efficient automated cell classification and visualization of remyelination analysis significantly reduces error due to human subjectivity. We validate the accuracy of our results by extensive cross-verification by the domain experts.     

Freshness and quality attributes of cold stored Atlantic bonito (Sarda sarda) gravad

Quality and safety parameters of Atlantic bonito gravad during 42 days of storage at 7 ± 1 °C were analysed using monitoring sensory quality, microbial contamination, nucleotide degradation products, biogenic amines (BA), trimethylamine (TMA) and thiobarbituric acid reactive substances (TBARS). The shelf‐life of vacuum packed Atlantic bonito gravad was found to be 28 days. Total viable count (TVC) did not exceed 6 log CFU g^?1. Malonodialdehyde (MDA) content did not surpass 10 mg kg^?1. Nine biogenic amines were detected. Histamine level at the end of the storage was 355.3 mg kg^?1. TMA increased from 53.9 to 619.1 mg kg^?1. Among indicators based on the products of nucleotide degradation, the H value is best correlated with the sensory assessment. It can be concluded that the storage temperature of bonito gravad must be below 7 °C to prevent the threat to safety and quality posed by biogenic amines, especially histamine.     

Inhibitory effect of sowthistle (Ixeris dentata) on development and expression of behavioral locomotor sensitization to nicotine in rats

The aim of this study was to investigate the effects of sowthistle (Ixeris dentata, IXD) on development and expression of nicotine-induced locomotor sensitization and underlying neuronal activation reflected by c-Fos expression in rats. Rats were pretreated with IXD 30 min before a daily injection of nicotine during an 8-day development phase and then challenged with nicotine after a 6-day withdrawal period. In another set of experiments, same IXD doses were administered once 30 min before nicotine challenge. Daily IXD treatment during development phase was not effective in blocking nicotine-induced locomotor sensitization in rats. However, a single IXD treatment after the development and withdrawal periods of nicotine sensitization significantly alleviated sensitized locomotor behavior on day 15. These behavioral results were coincident with significant inhibition of nicotineinduced c-Fos expression in the nucleus accumbens. These results indicated that IXD pretreatment significantly blocked the expression, but not the development of nicotine-induced locomotor sensitization in rats.     

Comprehending household cooking energy choice in rural India

Energy is essential to attain the quality of life and economic prosperity in a society. In the rural areas of India, cooking dominates the aggregate consumption of energy. This energy demand is mostly met by biomass fuels, which have many associated inherent disadvantages. Hence, it is important to understand the decision making process in rural households regarding the choice of cooking fuels. For this purpose, household information using the 61st round of National Sample Survey is analyzed for the rural parts of India. The logistic regression model is used to explain the determinants of clean fuel use for cooking purposes. The study shows that number of educated females between 10 and 50 years of age, average household education index, regular salary, and monthly per capita consumption expenditure have a positive and significant impact on probability of using clean cooking fuels, whereas possessing a Below Poverty Line ration card, belonging to reserved caste categories, family size and size of farm land have a significant negative linkage.