Detailed structural and topological analysis of SnBi2Te4 single crystal

We report herein the successful synthesis of the topological material SnBi2Te4 in single-crystal form. Phase purity and unidirectional growth are evident from X-ray diffraction (XRD) patterns acquired from a powdered sample and a crystal flake. The crystalline morphology has also been visualized by acquiring a field-emission scanning electron microscope (FESEM) image. The crystal has been thoroughly characterized by means of Raman spectroscopy and X ray photoelectron spectroscopy (XPS) measurements. The topological properties of SnBi2Te4 have been probed through magneto-transport measurements. SnBi2Te4 has been found to exhibit a small but non-saturating magneto-resistance (MR) up to 12 T. The low-field magnetoconductivity (MC) of SnBi2Te4 at 2 K can be well explained through the Hikami Larkin Nagaoka (HLN) formalism, which confirms the presence of a weak anti-localization (WAL) effect in its crystal. Moreover, the non-trivial topological character has been evidenced through first-principles calculations using density functional theory (DFT), with and without spin-orbit coupling (SOC) protocols. A significant change in the bulk electronic band structure is observed upon the inclusion of SOC parameters, signifying the topological properties of SnBi2Te4. Its topological non-trivial character has also been verified through the calculation of Z2 invariants and the surface states spectrum in the (111) plane.Comment: 24 Pages TEXT + Figs: J. Phys. Chem. Solid

Prevalence and determinants of hypertension in apparently healthy schoolchildren in India: a multi-center study

Background: Hypertension in children is often under recognized, especially in developing countries. Data from rural areas of developing countries is particularly lacking. Objectives: To study prevalence of hypertension and its determinants in apparently health school children from predominantly rural populations of India. Methods: Apparently healthy schoolchildren (n = 14,957) aged 5–15 years (mean (standard deviation) age 10.8 (2.8) years; 55.5% boys) at four predominantly rural sites in separate states of India were studied. Systolic and diastolic blood pressures were recorded by trained staff in addition to age, gender, height, weight, type of school and season. Waist circumference was also recorded in 12,068 children. Geographic location and type of school (government, government-aided or private) were used to determine socio-economic status. Results: Systolic and/or diastolic hypertension was present in 3443 (23%) children. Systolic hypertension was present in 13.6%, diastolic hypertension in 15.3% and both in 5.9%. Isolated systolic hypertension was present in 7.7% while isolated diastolic hypertension was present in 9.4%. On univariate analysis, age, gender, geographical location, socio-economic status, season and anthropometric parameters (z-scores of height, weight and waist circumference, waist/height ratio and body mass index) were all significantly related to risk of hypertension (p < 0.0001 for each). Similar association was observed with weight group (normal, overweight and obese). Multiple regression analysis showed lower age, female gender, richer socio-economic status, certain geographical locations, higher weight and larger waist circumference to be independently associated with a greater risk of hypertension. Conclusion: There is a high prevalence of hypertension in apparently healthy schoolchildren even in predominantly rural areas of India. Screening and management programs targeted to high risk groups identified may prove cost-effective

Nutrition, atherosclerosis, arterial imaging, cardiovascular risk stratification, and manifestations in COVID-19 framework: a narrative review.

Background: Atherosclerosis is the primary cause of the cardiovascular disease (CVD). Several risk factors lead to atherosclerosis, and altered nutrition is one among those. Nutrition has been ignored quite often in the process of CVD risk assessment. Altered nutrition along with carotid ultrasound imaging-driven atherosclerotic plaque features can help in understanding and banishing the problems associated with the late diagnosis of CVD. Artificial intelligence (AI) is another promisingly adopted technology for CVD risk assessment and management. Therefore, we hypothesize that the risk of atherosclerotic CVD can be accurately monitored using carotid ultrasound imaging, predicted using AI-based algorithms, and reduced with the help of proper nutrition. Layout: The review presents a pathophysiological link between nutrition and atherosclerosis by gaining a deep insight into the processes involved at each stage of plaque development. After targeting the causes and finding out results by low-cost, user-friendly, ultrasound-based arterial imaging, it is important to (i) stratify the risks and (ii) monitor them by measuring plaque burden and computing risk score as part of the preventive framework. Artificial intelligence (AI)-based strategies are used to provide efficient CVD risk assessments. Finally, the review presents the role of AI for CVD risk assessment during COVID-19. Conclusions: By studying the mechanism of low-density lipoprotein formation, saturated and trans fat, and other dietary components that lead to plaque formation, we demonstrate the use of CVD risk assessment due to nutrition and atherosclerosis disease formation during normal and COVID times. Further, nutrition if included, as a part of the associated risk factors can benefit from atherosclerotic disease progression and its management using AI-based CVD risk assessment

Performance Analysis of p/4 DQPSK for FrFT-OFDM System with Carrier Frequency Offset

The Orthogonal Frequency Division Multiplexing (OFDM) has widely been used in broadband wireless communication due to its ability to efficiently utilize the spectrum with multicarrier communication. In this paper BER expression for p/4 DQPSK modulation has been derived from FrFT based OFDM system in the presence of carrier frequency offset (CFO) under frequency selective Rayleigh fading channel. The performance of proposed system has been evaluated and compared with the FFT based OFDM system. It is found that the FrFT based OFDMsystem outperforms the FFT based OFDM. BER analysis has also been done for various values of a (FrFT angle parameter) on said FrFT based OFDM system, however the system responds best at a = 0.9 as compared with other values of a. Improvement as high as up to 23 dB in SNR has been achieved with the proposed FrFT based OFDM system at a = 0.9 for said modulation with carrier frequency offset of 0.1 under frequency selective Rayleigh fading channel

Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review

Diabetes is one of the main causes of the rising cases of blindness in adults. This microvascular complication of diabetes is termed diabetic retinopathy (DR) and is associated with an expanding risk of cardiovascular events in diabetes patients. DR, in its various forms, is seen to be a powerful indicator of atherosclerosis. Further, the macrovascular complication of diabetes leads to coronary artery disease (CAD). Thus, the timely identification of cardiovascular disease (CVD) complications in DR patients is of utmost importance. Since CAD risk assessment is expensive for low-income countries, it is important to look for surrogate biomarkers for risk stratification of CVD in DR patients. Due to the common genetic makeup between the coronary and carotid arteries, low-cost, high-resolution imaging such as carotid B-mode ultrasound (US) can be used for arterial tissue characterization and risk stratification in DR patients. The advent of artificial intelligence (AI) techniques has facilitated the handling of large cohorts in a big data framework to identify atherosclerotic plaque features in arterial ultrasound. This enables timely CVD risk assessment and risk stratification of patients with DR. Thus, this review focuses on understanding the pathophysiology of DR, retinal and CAD imaging, the role of surrogate markers for CVD, and finally, the CVD risk stratification of DR patients. The review shows a step-by-step cyclic activity of how diabetes and atherosclerotic disease cause DR, leading to the worsening of CVD. We propose a solution to how AI can help in the identification of CVD risk. Lastly, we analyze the role of DR/CVD in the COVID-19 framework