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Gd2O3-In2O3 solid solutions were synthesized starting with powders of Gd2O3 and In2O3 in the appropriate stoichiometric ratio and heating them in air to temperatures of 1425 °C. Their crystalline structures were determined using high resolution x-ray diffractometry. Cubic, monoclinic, and hexagonal phases were observed for different compositions. The present study demonstrates that large quantities of the high pressure phases of either Gd2O3 or In2O3 can be obtained in the solid solutions of Gd2-xInxO3 (0 < x < 1.6). The solid solutions show increasing paramagnetic response with increasing Gd content deriving from the Gd3+:4f7 ground sate configuration. [ABSTRACT FROM AUTHOR] more...

Objectives: Housing is an important social determinant of health. However, limited studies have focused on the relationship between housing quality and sarcopenia, especially in low- and middle-income countries. This study aims to examine the association between housing quality and sarcopenia in older adults in China and India., Methods: The study was based on the China Health and Retirement Longitudinal Study and Longitudinal Aging Study in India. Housing quality was evaluated by five indicators, including housing materials, water sources, sanitation facilities, main fuel for cooking, and availability of electricity. Housing quality is divided into three types: good (0-1 poor housing indicators), medium (2-3 poor housing indicators), and poor (4-5 poor housing indicators). Sarcopenia was evaluated according to the Asian Working Group for Sarcopenia (AWGS) 2019 Consensus. The logistic regression model was performed to examine the association between housing quality and sarcopenia., Results: The medium (OR = 1.69, 95%CI = 1.49-1.90) and poor housing quality (OR = 2.19, 95%CI = 1.89-2.54) were associated with sarcopenia in CHARLS. Similar results were also observed in the LASI with significantly higher prevalence of sarcopenia in medium (OR = 1.22, 95%CI = 1.11-1.33), and poor housing quality (OR = 1.60, 95%CI = 1.43-1.79). Moreover, we observed a linear relationship between housing quality and the prevalence of sarcopenia both in CHARLS and LASI (all P for trend <0.001)., Conclusions: Poorer housing quality was associated with a higher prevalence of sarcopenia in older adults in China and India. Housing quality improvement plans such as access to tap water, promotion of clean energy may have a positive effect on reducing the prevalence of sarcopenia., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Masson SAS.. All rights reserved.) more...

The aim of this study is to examine the potential effects that Industry 4.0, often known as the Fourth Industrial Revolution, and its accompanying technology improvements may have on SCMP and SC performance. Industry 4.0 impacts both the methods and productivity of supply chain management. Therefore, this study conceptualizes and develops an operational framework backed by SEM to examine the impact of Industry 4.0 on S.C. performance. This study employs a structural equation model (SEM) to estimate variables in India between September 2021 and March 2022 owing to the many advantages of the SEM over other estimators. The research shows that by implementing Industry 4.0-enabled technologies, businesses can improve SCM performance significantly through a holistic strategy that emphasizes supply chain integration, information sharing, and transparency. First, the results indicate that the supply chain management practices influence the Industry 4.0 technologies adoption. Second, the results revealed that Industry 4.0 technologies significantly positively affect supply chain performance measures. Finally, Industry 4.0 technologies mediated the relations between supply chain management practices and supply chain performance measures. Moreover, these technologies allow for huge performance improvements within individual supply chain processes such as procurement, production, inventory management and retailing by enabling process integration, digitization and automation, and bringing about novel analytical capabilities., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.) more...

Background: COVID-19 poses a severe threat to global human health, especially the USA, Brazil, and India cases continue to increase dynamically, which has a far-reaching impact on people's health, social activities, and the local economic situation., Methods: The study proposed the ARIMA, SARIMA and Prophet models to predict daily new cases and cumulative confirmed cases in the USA, Brazil and India over the next 30 days based on the COVID-19 new confirmed cases and cumulative confirmed cases data set(May 1, 2020, and November 30, 2021) published by the official WHO, Three models were implemented in the R 4.1.1 software with forecast and prophet package. The performance of different models was evaluated by using root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE)., Results: Through the fitting and prediction of daily new case data, we reveal that the Prophet model has more advantages in the prediction of the COVID-19 of the USA, which could compose data components and capture periodic characteristics when the data changes significantly, while SARIMA is more likely to appear over-fitting in the USA. And the SARIMA model captured a seven-day period hidden in daily COVID-19 new cases from 3 countries. While in the prediction of new cumulative cases, the ARIMA model has a better ability to fit and predict the data with a positive growth trend in different countries(Brazil and India)., Conclusions: This study can shed light on understanding the outbreak trends and give an insight into the epidemiological control of these regions. Further, the prediction of the Prophet model showed sufficient accuracy in the daily COVID-19 new cases of the USA. The ARIMA model is suitable for predicting Brazil and India, which can help take precautions and policy formulation for this epidemic in other countries., (© 2022. The Author(s).) more...

Background: Rice is an important staple food that is consumed around the world. Like many foods, the price of rice varies considerably, from very inexpensive for a low-quality product to premium pricing for highly prized varieties from specific locations. Therefore, like other foods it is vulnerable to economically motivated adulteration through substitution or misrepresentation of inferior-quality rice for more expensive varieties., Objective: In this article we describe results of a research project focused on addressing potential food fraud issues related to rice supplies in China, India, Vietnam, and Ghana. Rice fraud manifests differently in each country; therefore, tailored solutions were required., Method: Here we describe a two-tiered testing regime of rapid screening using portable Near Infrared technology supported by second tier testing using mass spectrometry-based analysis of suspicious samples., Results: Portable Near Infrared spectroscopy models and laboratory-based Gas Chromatography-Mass Spectrometry methods were developed to differentiate between: high-value Basmati rice varieties and their potential adulterants; six Geographic Indicated protected rice varieties from specific regions within China; various qualities of rice in Ghana and Vietnam; and locally produced and imported rice in Ghana. Furthermore, an Inductively Coupled Plasma-Mass Spectrometry method was developed to support the Chinese rice varieties methods as well as a Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry method for quality differentiation in Vietnam., Conclusions/highlights: This two-tier approach can provide a substantially increased level of testing through rapid screening outside of the laboratory with the reassurance of corroborating mass spectrometry-based laboratory analysis to support decision making., (© AOAC INTERNATIONAL 2020. All rights reserved. For permissions, please email: journals.permissions@oup.com.) more...

Rice is one of the most important cereals for human nutrition and is a basic staple food for half of the global population. The assessment of rice geographical origins in terms of its authenticity is of great interest to protect consumers from misleading information and fraud. In the present study, a head space gas chromatography mass spectrometry (HS-GC-MS) strategy for characterising volatile organic compounds (VOCs) profiles to distinguish rice samples from China, India and Vietnam is described. Partial Least Square Discriminant Analysis (PLS-DA) model exhibited a good discrimination (R 2  = 0.98182, Q 2  = 0.9722, and Accuracy = 1.0) for rice samples from China, India and Vietnam. Moreover, Data-Driven Soft Independent Modelling of Class Analogy (DD-SIMCA) and K-nearest neighbors shown good specificity 100% and accuracy 100% in identifying the origin of samples. The present study established VOC fingerprinting as a highly efficient approach to identify the geographical origin of rice., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.) more...

Background: Differentiating between ulcerative colitis (UC), Crohn's disease (CD) and intestinal tuberculosis (ITB) using endoscopy is challenging. We aimed to realize automatic differential diagnosis among these diseases through machine learning algorithms., Methods: A total of 6399 consecutive patients (5128 UC, 875 CD and 396 ITB) who had undergone colonoscopy examinations in the Peking Union Medical College Hospital from January 2008 to November 2018 were enrolled. The input was the description of the endoscopic image in the form of free text. Word segmentation and key word filtering were conducted as data preprocessing. Random forest (RF) and convolutional neural network (CNN) approaches were applied to different disease entities. Three two-class classifiers (UC and CD, UC and ITB, and CD and ITB) and a three-class classifier (UC, CD and ITB) were built., Results: The classifiers built in this research performed well, and the CNN had better performance in general. The RF sensitivities/specificities of UC-CD, UC-ITB, and CD-ITB were 0.89/0.84, 0.83/0.82, and 0.72/0.77, respectively, while the values for the CNN of CD-ITB were 0.90/0.77. The precisions/recalls of UC-CD-ITB when employing RF were 0.97/0.97, 0.65/0.53, and 0.68/0.76, respectively, and when employing the CNN were 0.99/0.97, 0.87/0.83, and 0.52/0.81, respectively., Conclusions: Classifiers built by RF and CNN approaches had excellent performance when classifying UC with CD or ITB. For the differentiation of CD and ITB, high specificity and sensitivity were achieved as well. Artificial intelligence through machine learning is very promising in helping unexperienced endoscopists differentiate inflammatory intestinal diseases., Conference: The abstract of this article has won the first prize of the Young Investigator Award during the Asian Pacific Digestive Week (APDW) 2019 held in Kolkata, India. more...

There are two kinds of amelogenin gene mutation, including mutation in primer-binding region of amelogenin gene and micro deletion of Y chromosome encompassing amelogenin gene, and the latter is more common. The mechanisms of mutation in primer-binding region of amelogenin gene is nucleotide point mutation and the mechanism of micro deletion of Y chromosome encompassing amelogenin gene maybe non-allelic homologous recombination or non-homologous end-joining. Among the population worldwide, there is a notably higher frequency of amelogenin gene mutations in Indian population, Sri Lanka population and Nepalese population which reside within the Indian subcontinent. Though amelogenin gene mutations have little impact on fertility and phenotype, they might cause incorrect result in gender identification. Using composite-amplification kit which including autosomal STR locus, amelogenin gene locus and multiple Y-STR locus, could avoid wrong gender identification caused by amelogenin gene mutation., Competing Interests: The authors of this article and the planning committee members and staff have no relevant financial relationships with commercial interests to disclose., (Copyright© by the Editorial Department of Journal of Forensic Medicine.) more...