An improved finegrained ciphertext policy based temporary keyword search on encrypted data for secure cloud storage.

We present a temporary keyword search over sensitive and confidential health data in a cloud environment. The cloud constitutes a semi-trusted domain, making it necessary for data owners to secure their data before outsourcing it through techniques like encryption. Attribute-based keyword search techniques tend to perform a search operation using a search token generated by an authorized user.

Child development beyond the nutrition-specific models: bridging the pathways via psychosocial stimulation.

Background: Undernutrition has severe and lasting consequences on child development. Evidently, the interventions based on the biomedical model with food and direct supplementation have failed to produce the desired outcomes for decades. In light of the established positive effects of psychosocial stimulation on developmental outcomes, we propose that the observed failures relate to not including psychosocial stimulation within the interventions.

Design and application of potentiometric sensors for the determination of mefenamic and phenylanthranilic acids.

Characteristics, performance and applications of potentiometric membrane sensors are described for the determination of mefenamic and phenylanthranilic ions. Ion associates of mefenamic, ClO, and phenylanthranilic ions with crystal violet (counter-cation) as ion exchange sites have been used as ionophores in the plasticized one- and two-layer membrane ion-selective electrodes. The LOD is reported to be 8.

Substitution of carbonate by non-physiological synergistic anion modulates the stability and iron release kinetics of serum transferrin.

Serum transferrin (sTf) is a bi-lobal protein. Each lobe of sTf binds one Fe ion in the presence of a synergistic anion. Physiologically, carbonate is the main synergistic anion but other anions such as oxalate, malonate, glycolate, maleate, glycine, etc.

Predictors of Treatment Completion in an Inpatient Substance Use Treatment Service in India.

Introduction: Treatment completion is associated with a better outcome in substance use disorders. We examined the rates of treatment completion and its predictors in patients admitted to specialized addiction treatment settings over a 13-year period.

Methods: Ours was a retrospective cohort study.

Cyanobacteria blue-green algae prediction enhancement using hybrid machine learning-based gamma test variable selection and empirical wavelet transform.

This study aims to evaluate the usefulness and effectiveness of four machine learning (ML) models for modelling cyanobacteria blue-green algae (CBGA) at two rivers located in the USA. The proposed modelling framework was based on establishing a link between five water quality variables and the concentration of CBGA. For this purpose, artificial neural network (ANN), extreme learning machine (ELM), random forest regression (RFR), and random vector functional link (RVFL) are developed.

Applications and Challenges in Healthcare Big Data: A Strategic Review.

Big data has been a topic of interest for many researchers and industries for the past few decades. Due to the exponential growth of technology, a tremendous amount of data is generated every minute. This article provides a strategic review of big data in the healthcare sector.

A novel and efficient deep learning approach for COVID-19 detection using X-ray imaging modality.

With the exponential growth of COVID-19 cases, medical practitioners are searching for accurate and quick automated detection methods to prevent Covid from spreading while trying to reduce the computational requirement of devices. In this research article, a deep learning Convolutional Neural Network (CNN) based accurate and efficient ensemble model using deep learning is being proposed with 2161 COVID-19, 2022 pneumonia, and 5863 normal chest X-ray images that has been collected from previous publications and other online resources. To improve the detection accuracy contrast enhancement and image normalization have been done to produce better quality images at the pre-processing level.

A deep learning framework using CNN and stacked Bi-GRU for COVID-19 predictions in India.

The novel coronavirus infection (COVID-19) first appeared in Wuhan, China, in December 2019. COVID-19 declared as a global pandemic by the WHO was the most rapidly spreading disease all across the world. India, the second most populated nation in the world, is still fighting it, when coronavirus reached the stage where community transmission takes place at an exponential rate.

Predicting COVID-19 statistics using machine learning regression model: Li-MuLi-Poly.

In this paper, linear regression (LR), multi-linear regression (MLR) and polynomial regression (PR) techniques are applied to propose a model Li-MuLi-Poly. The model predicts COVID-19 deaths happening in the United States of America. The experiment was carried out on machine learning model, minimum mean square error model, and maximum likelihood ratio model.

UGT1A1 Gene Polymorphisms in Patients with Small Cell Lung Cancer Treated with Irinotecan-Platinum Doublet Chemotherapy and Their Association with Gastrointestinal Toxicity and Overall Survival.

Background: Irinotecan (CPT11) is an important drug for small cell lung cancer (SCLC) chemotherapy (CTx). UDP-glucuronosyltransferase 1A1 (UGT1A1) polymorphisms can influence CPT11-related toxicity. This study aimed to assess prevalence of UGT1A1 polymorphisms and their association with clinical outcomes in patients with SCLC on CPT11-CTx.

The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges.

Covid-19 is one of the biggest health challenges that the world has ever faced. Public health policy makers need the reliable prediction of the confirmed cases in future to plan medical facilities. Machine learning methods learn from the historical data and make predictions about the events.

Gauging the effectiveness of music and yoga for reducing stress among engineering students: An investigation based on Galvanic Skin Response.

Background: The purpose of this research is to examine the influence of music and yogic breathing for the management and control of stress.

Objective: To discover the most effective stimuli to handle stress by measuring the effect of types of musical drills and yogic breathing on engineering students using the Galvanic Skin Response Sensor Meter (GSRSM).

Methods: The present study attempts to study the effectiveness of music and yoga drills for relieving and managing stress.

XRCC1 632 as a candidate for cancer predisposition via a complex interaction with genetic variants of base excision repair and double strand break repair genes.

The DNA repair system safeguards integrity of DNA. Genetic alterations force the improper repair which in conjugation with other factors ultimately results in carcinogenesis. PCR-restriction fragment length polymorphism was used for genotyping, which was followed by statistical analysis using logistic regression analysis, multifactor dimensionality reduction and classification and regression analysis tree, elaborating the association with lung cancer subjects.

Mechanical properties of bioactive glasses, ceramics, glass-ceramics and composites: State-of-the-art review and future challenges.

The repair and restoration of bone defects in orthopaedic and dental surgery remains a major challenge despite advances in surgical procedures and post-operative treatments. Bioactive glasses, ceramics, glass-ceramics and composites show considerable potential for such applications as they can promote bone tissue regeneration. This paper presents an overview of the mechanical properties of various bioactive materials, which have the potential for bone regeneration.

The multi-faceted high order polymorphic synergistic interactions among nucleotide excision repair genes increase the risk of lung cancer in North Indians.

It is evident that gene-gene interactions are pervasive in the determination of the susceptibility of human diseases. Polymorphisms in nucleotide excision repair pathway (NER) genes can cause variations in the repair capacity and therefore, might lead to increase in susceptibility towards lung cancer through complex gene-gene and gene-smoking interactions. Logistic regression analysis, along with high order genetic interaction were analyzed using data mining tools such as multifactor dimensionality reduction (MDR) and classification and regression tree analysis (CART).

Synthesis and in vitro evaluation of naphthalimide-benzimidazole conjugates as potential antitumor agents.

A series of novel naphthalimide-benzimidazoles was designed and synthesized for the first time and studied for their effect on antiproliferative activity. Some of these compounds possessed good antitumor activity towards the tested cancer cell lines. Noticeably, (diethylamino)ethyl 15 and (dimethylamino)ethyl 23 derivatives displayed superior antiproliferative activity towards human cancer cell lines with MG_MID GI50 values of 1.

Diversity and phylogeny of resveratrol-producing culturable endophytic fungi from species in India.

In the present study, resveratrol producing culturable endophytes were recovered from the Indian vineyards. Of the 145 endophytic fungi recovered, only 30.3% were positive for resveratrol production in the preliminary screening.

Elucidation of microstructural changes in leaves during senescence using spectral domain optical coherence tomography.

Leaf senescence provides a unique window to explore the age-dependent programmed degradation at organ label in plants. Here, spectral domain optical coherence tomography (SD-OCT) has been used to study in vivo senescing leaf microstructural changes in the deciduous plant Acer serrulatum Hayata. Hayata leaves show autumn phenology and change color from green to yellow and finally red.