Impact of COVID-19 lockdown on food addiction in India

Food addiction (FA) has a long-term impact on the health of individuals. This study analyses the changes in FA and related behaviour in India in the wake of lockdown which started on 25th March 2020 as a response to the COVID-19 outbreak. This paper provides insight into the food consumption behavior of various segments of the population during this lockdown. It offers some new insights in this regard by establishing the relationship between a temporary pause in the consumption of palatable food and FA. This study was conducted between March and May 2020 in two stages. First, a quantitative study used the Yale Food Addiction Scale (YFAS) to identify food addicts from a sample of 150 respondents. In the second stage, in-depth telephone interviews were conducted with the food addicts; the responses were recorded, transcribed, and analysed to ascertain the changes in their overall consumption and addiction behavior towards palatable foods. This was done by conducting a thematic analysis with the help of the NVivo software where various tools like word cloud and cluster analysis were used. This study found that COVID-19 restrictions had significantly brought down the addiction to palatable food in India as the regular consumption chain had got broken during the lockdown. The consumption of palatable food is expected to remain low for a brief period after the lockdown due to hygiene issues like improper or lack of sanitization and cleanliness. However, in the long-run, the consumption of palatable food is expected to rise in India owing to its growing population, modernisation, increasing disposable income and changes in customer preferences. These findings have significant implications for the food, packaging and health industries as the changes in customer behavior will certainly impact them, and they need to duly change their strategy to adapt to the changes promptly

Ferroelectric relaxor behaviour in Pb(Fe0.5Ta0.5)O3

The relaxor ferroelectric lead iron tantalate, Pb(Fe0.5Ta0.5)O3 (PFT) is synthesized by Coulombite precursor method. The X-ray diffraction pattern of the sample at room temperature shows a cubic phase. The field dependence of dielectric response is measured in a frequency range 0.1 kHz – 1 MHz and in a temperature range from 173–373 K. The temperature dependence of permittivity (ε ′) shows broad maxima at various frequencies. The frequency dependence of the permittivity maximum temperature (Tm) has been modelled using Vogel-Fulcher relation.Ferroelectric relaxor behaviour in Pb(Fe0.5Ta0.5)O3 Chandrahas Bharti*, S N Choudhary and T P Sinha1 University Department of Physics, T M Bhagalpur University, Bhagalpur-812 007, Bihar, India 1Department of Physics, Bose Institute, 93/1, A P C Road, Kolkata-700 009, India E-mail : [email protected] Department of Physics, T M Bhagalpur University, Bhagalpur-812 007, Bihar, India 1Department of Physics, Bose Institute, 93/1, A P C Road, Kolkata-700 009, Indi

Trends in marine fish production in Tamil Nadu using regression and autoregressive integrated moving average (ARIMA) model

Tamil Nadu is situated in the south eastern coast of the Indian peninsula with a coastal line of 1076 km (13% of the country’s coast line), 0.19 million sq.km of EEZ (9.4 % of total national EEZ) and a continental shelf of about 41,412 sq. km. This is one of the country’s leading state in marine fish production and ranks third in marine fish production. In Tamil Nadu, Ramanathapuram district is a leading maritime district followed by Nagapattinam and Thoothukudi. The objective of this study was to investigate the trends in marine fish production in Tamil Nadu. Yearly fish production data for the period of 1988-1989 to 2012-2013 were analyzed using time-series method called Autoregressive Integrated Moving Average (ARIMA) model and Regression analysis (curve estimation). In our study, the developed best ARIMA model for Tamil Nadu marine fish production was found to be ARIMA (1, 1, 1) which have the minimum BIC (Bayesian Information Criterion). ARIMA model had got a slightly higher forecasting accuracy rate for forecasting marine fish production of Tamil Nadu than Regression trend analysis. The independent sample test showed there was no significant difference between the two models. The limitations of ARIMA model include its requirement of a long time series data for better forecast. It is basically linear model assuming that data are stationary and have a limited ability to capture non-stationarities and nonlinearities in series data. Both the models indicated that Tamil Nadu marine fish production has plateaued and fishermen should be encouraged to adopt sustainable fishing practices

Synthesis and characterization of biodegradable lignin nanoparticles with tunable surface properties

Lignin nanoparticles can serve as biodegradable carriers of biocidal actives with minimal environmental footprint. Here we describe the colloidal synthesis and interfacial design of nanoparticles with tunable surface properties using two different lignin precursors, Kraft (Indulin AT) lignin and Organosolv (high-purity lignin). The green synthesis process is based on flash precipitation of dissolved lignin polymer, which enabled the formation of nanoparticles in the size range of 45–250 nm. The size evolution of the two types of lignin particles is fitted on the basis of modified diffusive growth kinetics and mass balance dependencies. The surface properties of the nanoparticles are fine-tuned by coating them with a cationic polyelectrolyte, poly(diallyldimethylammonium chloride). We analyze how the colloidal stability and dispersion properties of these two types of nanoparticles vary as a function of pH and salinities. The data show that the properties of the nanoparticles are governed by the type of lignin used and the presence of polyelectrolyte surface coating. The coating allows the control of the nanoparticles’ surface charge and the extension of their stability into strongly basic regimes, facilitating their potential application at extreme pH conditions

Comparison of Artificial Intelligence based approaches to cell function prediction

Predicting Retinal Pigment Epithelium (RPE) cell functions in stem cell implants using non-invasive bright field microscopy imaging is a critical task for clinical deployment of stem cell therapies. Such cell function predictions can be carried out using Artificial Intelligence (AI) based models. In this paper we used Traditional Machine Learning (TML) and Deep Learning (DL) based AI models for cell function prediction tasks. TML models depend on feature engineering and DL models perform feature engineering automatically but have higher modeling complexity. This work aims at exploring the tradeoffs between three approaches using TML and DL based models for RPE cell function prediction from microscopy images and at understanding the accuracy relationship between pixel-, cell feature-, and implant label-level accuracies of models. Among the three compared approaches to cell function prediction, the direct approach to cell function prediction from images is slightly more accurate in comparison to indirect approaches using intermediate segmentation and/or feature engineering steps. We also evaluated accuracy variations with respect to model selections (five TML models and two DL models) and model configurations (with and without transfer learning). Finally, we quantified the relationships between segmentation accuracy and the number of samples used for training a model, segmentation accuracy and cell feature error, and cell feature error and accuracy of implant labels. We concluded that for the RPE cell data set, there is a monotonic relationship between the number of training samples and image segmentation accuracy, and between segmentation accuracy and cell feature error, but there is no such a relationship between segmentation accuracy and accuracy of RPE implant labels

Genetic analysis of SLC47A1, SLC22A1, SLC22A2, ATM gene polymorphisms among diabetics in an Indian population

Background: Metformin is a first-line therapy for type 2 diabetes mellitus. However, the glycaemic response to metformin is likely to be affected by polymorphisms of transporter genes. Therefore, the study was done with the  aim to assess demographic distribution of transporter genotypes involved in disposition and action of metformin.Methods: This cross-sectional, observational, single centre, clinical study was conducted in 80 diabetic patients recruited from medicine OPD. Descriptive analysis was done for distribution of the four transporter genotypes viz. SLC47A1 (rs2289669), ATM (rs11212617), SLC22A2 (rs316019) and SLC22A1 (rs622342). Genotyping was determined by DNA extraction, agarose gel electrophoresis, estimation of DNA concentration, polymerase chain reaction, DNA sequencing, sequencing analysis.Results: Transporter genotype analysis showed that for SLC47A1 (rs2289669) transporter, 31.25% and 26.25% were homozygous for AA and GG allele respectively, while 42.5% were heterozygous (AG). For ATM (rs11212617), SLC22A2 (rs316019) and SLC22A1 (rs622342) transporter, 45% and 10%, 1.25% and 80%, 58.75% and 7.50% were homozygous for AA and CC allele respectively; while 45%, 18.75%, 33.75% were heterozygous (AC) respectively. Interethnic differences in the genotype and allele frequencies of SLC22A1 (rs622342) and ATM (rs11212617) gene polymorphism were observed when compared with other major populations.Conclusions: In the genotypic distribution of four transporter genotype study showed that there was an ethnic variation in allelic distribution of allele A and C of ATM (rs11212617) and SLC22A1 (rs622342) while AA genotype of SLC22A2 (rs316019) was rare genotype and allele ‘A’ was major allele found in our study. The study data observed would justify further pharmacogenetic studies to evaluate the role of gene polymorphism in the therapeutic efficacy of metformin.

Catalytic decomposition of 2-chlorophenol using an ultrasonic-assisted Fe3O4-TiO2@MWCNT system: Influence factors, pathway and mechanism study.

As a reusable sonocatalyst, magnetically separable Fe3O4-TiO2@MWCNT (FMT) was synthesized by an ultrasound-assisted wet impregnation method and was evaluated in the removal of 2-chlorophenol (2CP). Physical and chemical properties of the catalyst composite materials were investigated by all catalysts were systematically characterized using Transmission Electron Microscopy (TEM), X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), X-ray Photoelectron Spectroscopy (XPS), Energy Dispersive X-ray Analysis (EDX), Dynamic light scattering (DLS), and N2-physisorption. The efficiency and kinetics of 2CP removal by FMT-assisted sonocatalysis (FMT-US) was systematically investigated under various operational parameters i.e. pH, FMT and 2CP concentration, temperature and ultrasonic power. The results indicated that 0.4gL-1 FMT dosage, pH 5, temperature of 35°C as well as 50 w ultrasound power are the most favorable conditions for the degradation of the 2CP. Furthermore, both of the superoxide and hydroxyl radicals were produced in the reaction, however, superoxide radicals were assumed to be the dominating reactive species for the 2CP degradation, according to the scavenging tests and electron paramagnetic resonance tests. Moreover, the FMT catalyst exhibited a high reusability and stability in the US/FMT system during the five repetitive experiments. The intermediate products were identified by GC-MS, thereby a possible degradation pathway is proposed. The chemical oxygen demand (COD) and corresponding total organic carbon (TOC) removal efficiencies were 64.9% and 56.7%, respectively. Finally, toxicity tests showed that the toxicity of the solution increased during the first 5min and then decreased significantly with the progress of the oxidation. The mechanisms of ultrasound irritation enhanced FMT activation were also proposed. Copyright © 2017 Elsevier Inc. All rights reserved

Enhanced Joule Heating in Umbral Dots

We present a study of magnetic profiles of umbral dots (UDs) and its consequences on the Joule heating mechanisms. Hamedivafa (2003) studied Joule heating using vertical component of magnetic field. In this paper UDs magnetic profile has been investigated including the new azimuthal component of magnetic field which might explain the relatively larger enhancement of Joule heating causing more brightness near circumference of UD.Comment: 8 pages, 1 figure, accepted in Solar Physic

Rhodovulum aestuarii sp. nov., isolated from a brackish water body

A yellowish brown, phototrophic, purple non-sulfur bacterium, strain JA924r, was isolated in pure culture from a brackish water sample collected from an estuary. Single cells were oval to rod-shaped, non-motile and Gram-stain-negative and had a vesicu!ar architecture of intracellular photosynthetic membranes. Bacteriochlorophyll-a and carotenoids of the spheroidene series were present as photosynthetic pigments. Photolithoautotrophy, chemo-organoheterotrophy and photo-organoheterotrophy were the growth modes observed. Strain JA924T had complex growth requ1rements. Strain JA924 T was mesophilic and moderate!y halophilic. The DNA G -t- C content was 64 mal% (HPLC). The major cellular fatty acids were C18 1f·)7c/C 18 : 11·)6c, Ct 6 0 and C 18 . 0 . The major quinone was ubiquinone-1 0 (0-1 0). Phosphatidylg!ycerol, phosphatidylethanolamine, sulfolipid and an aminolipid were the main polar Iipids of strain JA924r. EzTaxon-e BLAST searches based on the 168 rRNA gene sequence of JA924T revealed highest similarity with Rhodovulum mangrovi AK41 T (98.19 %) and other members of the genus Rhodovulum (5 oc). Phenotypic, chemotaxonomic and molecular differences indicate that strain JA924 T represents a novel species of the genus Rhodovulum, for which the name Rhodovulum aestuarii sp. nov. is proposed. The type strain is JA924 T ( = LMG 29031 T = KCTC 15485 T)

Spectropolarimetery of umbral fine structures from Hinode: Evidence for magnetoconvection

We present spectropolarimetric analysis of umbral dots and a light bridge fragment that show dark lanes in G-band images. Umbral dots show upflow as well as associated positive Stokes V area asymmetry in their central parts. Larger umbral dots show down flow patches in their surrounding parts that are associated with negative Stokes V area asymmetry. Umbral dots show weaker magnetic field in central part and higher magnetic field in peripheral area. Umbral fine structures are much better visible in total circularly polarized light than in continuum intensity. Umbral dots show a temperature deficit above dark lanes. The magnetic field inclination show a cusp structure above umbral dots and a light bridge fragment. We compare our observational findings with 3D magnetohydrodynamic simulations.Comment: Accepted for publication in MNRAS, 6 pages, 6 figure