Search

Monocrystalline SnSe is one of the most promising thermoelectric materials with outstanding performance and a high abundance of constituting elements. However, polycrystalline SnSe, which is more robust for applications, only shows large figure‐of‐merit (zT) values in its high‐symmetry phase. Stabilizing the high‐symmetry phase at low temperatures can thus enhance the average zT value over a broad temperature range. In this work, the high‐symmetry rock‐salt SnSe phase is successfully obtained by alloying SnSe with AgVVI2 compounds (V = Sb, Bi; VI = Se, Te). These cubic SnSe phases show a unique portfolio of properties including a high optical dielectric constant, a large maximum of optical absorption, a large Born effective charge, and abnormal bond‐breaking behavior in laser‐assisted atom probe tomography. All of these characteristics are indicative of metavalent bonding. In contrast, the Pnma phase of SnSe employs covalent bonding. The enhanced symmetry at low temperatures is realized by tailoring chemical bonding. Concomitantly, zT near room temperature is increased by a factor of more than 10 from the pristine Pnma SnSe to Fm3¯${{\bar{3}}}$m SnSe alloys. This provides insights into the enhancement of the thermoelectric performance of SnSe and other chalcogenides over a broad temperature range by manipulating the chemical bonds. [ABSTRACT FROM AUTHOR]

Three new hetero-metallic CuII-LnIII complexes [(CuL)Gd(NO3)3(CH3OH)]n (1), [(CuL)Tb(NO3)3(H2O)]· [CuL] (2) and [(CuL)Dy(NO3)3(H2O)]·[CuL] (3) have been synthesized using a mono-nuclear Cu(II) complex, [CuL], of an unsymmetrically di-condensed N2O3 donor Schiff base ligand, N-(3-methoxysalicylidene)-N-(salicylidene)-1,2-ethylenediamine (H2L). Single crystal X-ray crystallography revealed that complex 1 is a nitrate bridged 1D chain of dinuclear Cu(II)-Gd(III) units whereas in 2 and 3, the dinuclear Cu(II)-Ln(III) units are co-crystallized with a [CuL] unit. The Ln(III) centers are nine coordinated with the geometry of a spherical capped square antiprism for Gd and spherical tricapped trigonal prism for Tb and Dy. The geometry of the Cu(II) center is distorted octahedral for complex 1 and distorted square planar for complexes 2 and 3. Temperature-dependent molar magnetic susceptibility measurements in 1-3 revealed the presence of overall ferromagnetic coupling between the Cu(II) and Ln(III) centers. Notably, field induced single-molecule magnet behavior was witnessed in the Tb(III) derivative (2). The ab initio calculations indicated that upon application of an external magnetic field, the tunneling in the ground state of complex 2 gets reduced and thereby field-induced SMM behaviour is observed. Besides, in the case of complex 1, BS-DFT calculations were carried out to gain further insights into the magnetic exchange coupling interactions between the Cu(II) and Gd(III) centers. [ABSTRACT FROM AUTHOR]

Machine learning (ML) and Artificial intelligence (AI) play pivotal roles in diverse domains, particularly in handling the vast influx of data in recent times. These technologies offer potential for more accurate and expedited decision-making, particularly in predicting diseases. A significant health concern is cardiovascular disease, a prominent factor contributing to mortality in recent times. Detecting heart disease in its early stages can significantly impact survival rates and quality of life. Prompt diagnosis is crucial, given the complexity and varied causes associated with this ailment. The inquiry primarily focuses on improving the accuracy of disease prognosis through the application of Machine Learning approaches like Support Vector Machine, Random Forest and XGBoost. A dedicated effort was made to refine the accuracy of SVM by fine-tuning hyperparameters through GridSearchCV. The comprehensive evaluation of these algorithms revealed that SVM achieved an accuracy of 80.22%, XGBoost exhibited 75.82% accuracy, while Random Forest notably outperformed both, boasting an accuracy of 85.71%. These results underscore the strong predictive abilities of Random Forest in detecting heart disease, outperforming the efficacy of the other models. The study's results highlight the capability of machine learning, particularly Random Forest, in forecasting heart disease. Collaborative efforts with medical professionals and ongoing research aim to further refine these models, pushing accuracy rates closer to 100%. This advancement could mark a significant breakthrough in machine learning-driven disease prediction algorithms. In summary, this study showcases the prognostic capacities of SVM, Random Forest, and XGBoost in heart disease prognosis. Emphasizing the superior performance of Random Forest, the findings advocate for its adoption in improving disease diagnostics and intervention strategies. [ABSTRACT FROM AUTHOR]

The present work includes the fabrication of pure BiFeO3 and Bi0.9Y0.1Fe1−xCuxO3 (x = 0.05, 0.10, 0.15) nanoparticles by the usual sol-gel route. The characterization of structural, morphological, optical, electrical, and magnetic properties of the synthesized samples was achieved through x-ray diffraction spectroscopy, Raman spectroscopy, Fourier transform infrared spectroscopy, scanning electron microscopy, an impedance analyzer, and a vibrating sample magnetometer. The Fourier transform infrared study confirmed the presence of Bi–O and Fe–O bonds. The x-ray diffraction patterns confirmed the rhombohedral (R3c) structure as a major phase with the orthorhombic (Pnma) structure as a secondary phase in all samples, and few amount of impurity phase of Bi25FeO40 was also determined. The surface morphology analysis showed the variation of particle size from 63 to 174 nm. The Raman spectra of 13 optical phonon modes, including 4A1 and 9E symmetric phonons, are observed for all samples, and the positions of these modes are almost similar, except the intensities of A1 modes. The optical measurements show a reduction in bandgap from 2.17 to 2.03 eV with co-doping, revealing itself as a more promising applicant in photovoltaics. An enhanced value of the dielectric constant is observed for different doped samples at different frequency regions from 100 Hz to 10 MHz. Magnetic investigation demonstrates the improved ferromagnetism with co-doping of Y and Cu due to distortion in the FeO6 octahedron. A maximum saturation magnetization of 0.26 emu/gm and a coercivity of 2915 Oe were found for Y concentration of 10% and Cu concentration of 15%. [ABSTRACT FROM AUTHOR]

Human-wildlife coexistence has increasingly been known for providing diverse ecological services to humans. However, the global repercussions of the Anthropocene epoch have changed the status and future of human-wildlife relationships. In this paper, we shed light on the significance of a positive attitude towards sharing space with animals in identifying and managing both conflict and ecological aspects of human-wildlife interactions in an agrarian landscape. We tried to understand how interactions between meso-carnivores like jungle cats (Felis chaus) and humans influence their survival in dense human populations. We evaluate the abundance and habitat use by jungle cats seasonally and diet, as well as their interactions with farmers in West Bengal, India. The mean encounter rate of jungle cats was assessed and used as a proxy for their abundance. Using a combination of direct sign surveys, we found that the habitat preference and seasonal distribution of jungle cats were influenced by the change in seasons with respect to different habitats. Our results indicate that jungle cats were more associated with human settlements during the monsoon. Scat analysis revealed the dominance of rodents in the diets of jungle cats. This activity helps to control the rodent population from destroying crops. However, our interactions with farmers showed their negative attitude towards the species due to the instances of livestock (poultry birds) depredation. We suggest that, more interdisciplinary researches are required to address how affectively socioeconomic structures shape up positive human-wildlife interaction. Planning and implementation of conservation education programmes are also necessary to help people for understanding the economic and ecological benefits provided by jungle cats and other wide-ranging carnivores. We chose an agrarian landscape to evaluate threats to jungle cats and their persistence with humans. The encounter rate of jungle cats indicated that the intensity of habitat use varies seasonally in different natural surroundings. People had a generally negative perception of jungle cats, despite the fact that they have been found to feed primarily on rodents in farmlands. [ABSTRACT FROM AUTHOR]

Recombination of commercially available hybrids could produce desirable segregants that act as sources of new alleles for tomato breeding. Seven commercial single cross (SC) hybrids of tomato (Solanum lycopersicum L.) were crossed in a half diallel fashion to obtain 21 double cross hybrids (DC) to estimate combining ability, mode of gene action and extent of heterobeltiosis for fruit yield, processing qualities and tomato leaf curl virus (ToLCV) disease severity traits. Predominance of non-additive gene action occurred in the control for all characters except for total soluble solids (TSS) content in fruit that was conditioned by both additive and non-additive gene action. Improvement of most traits in DC hybrids over SC hybrids occurred. Maximum heterotic effect in DC hybrids was for vitamin C content followed by lycopene content, fruit yield per plant, titratable acidity content, number of fruit per plant and percent disease index of ToLCV. Two good combiners, 'PAN-1286' and 'Devi' among SC hybrids were identified based on general combining ability effects and average performance. Commercial exploitation of DC hybrids, 'TO-1458 × L-37' and 'NS-501 × TO-1458' following multilocational testing in the tropics and subtropics might be useful. High yielding, ToLCV disease tolerant DC hybrids could be exploited in segregating generations to identify elite multi-parent advanced generation inter-cross (MAGIC) populations. [ABSTRACT FROM AUTHOR]

Low dietary diversity significantly interplays with children's growth failure. However, evidence of its crucial role in children's health remains inconclusive in developing countries such as India. This study attempts to find the association between dietary diversity and growth outcomes among children aged between 6 and 23 months in India using the fourth round of the National Family Health Survey (NFHS), 2015–2016. A total of 67,278 mother-child pairs of children between the ages of 6–23 months and mothers aged 15–49 years were included in this study. Pearson's chi-square significance test and multivariable logistic regression were used to determine the association between dietary diversity and child growth outcomes (stunted, wasted, and underweight). The study found that the prevalence of stunting and severe stunting among children aged between 6 and 23 months were 35.9% and 16.2%; 23.8% and 8.5% represented wasting, and severe wasting; and more than 32%, 10% were underweight and severely underweight respectively. This present study found that having an inadequate minimum dietary diversity (<4 food groups) significantly increases the risk of being stunted (adjusted odds ratio (AOR) = 1.29; 95% confidence interval (CI); 1.21–1.38), wasted (AOR = 1.29; 95% CI; 1.21–1.38), and underweight (AOR = 1.47; 95% CI; 1.39–1.56). Further, it was noted that children who did not intake dairy products, eggs, and other fruits and vegetables were more likely to be stunted, wasted, and underweight and more likely to be severely stunted, wasted, and underweight. Therefore, additional nutrition-specific interventions are urgently needed to strengthen and enhance existing feeding interventions aimed at improving infant and young child feeding (IYCF) practices, including complementary feeding practices among children aged between 6 and 23 months in India. The Government should focus such interventions more on states or regions where the prevalence of adequate minimum dietary diversity (MDD) and malnutrition is high. [ABSTRACT FROM AUTHOR]

Understanding the inheritance pattern of bacterial wilt (BW) disease tolerance is important to maximize genetic potential in eggplant (Solanum melongena L.). The study was conducted employing populations P1, P2, F1, F2, BC1, and BC2 of the crosses 'Utkal Anushree × Bidhan Suphala,' 'Utkal Anushree × Garia,' and 'Utkal Madhuri × Bidhan Super' to understand genetic control of BW disease tolerance. The inheritance study indicated that tolerance to BW disease was conditioned by a single dominant gene in 3 Tolerant × Susceptible crosses. The nature, and magnitude, of gene action controlling inheritance of bacterial wilt-related traits (days to 1st appearance of BW disease and disease incidence of BW) differed between crosses and traits, mostly conditioned by nonadditive gene action and duplicate epistasis. The disparity between results from the chi-square goodness of fit test and other quantitative methods indicated that the chi-square goodness of fit test alone could be misleading in the study of genetic control of bacterial wilt related traits due to its subjectivity. Complementary epitasis in 2 crosses for days to 1st appearance of BW disease would be helpful in improvement of this trait through backcrossing. Duplicate epistasis controlling BW disease incidence suggested selection of desirable recombinants from the segregating population developed from bi-parental mating. The BW-tolerant plants, with an acceptable fruit weight, can be isolated from segregating generations with involvement of susceptible plants having a higher fruit weight. [ABSTRACT FROM AUTHOR]

The occurrence of overweight and obesity has increased in recent years in India. In this study, we investigate the prevalence and associated risk factors of overweight/obesity among children aged 0–59 months in India. Using data from the 2015–2016 National Family Health Survey-4 (NFHS-4), the research sample included 176,255 children aged 0 to 59 months. Bivariate and multivariate techniques were used to analyze children's risk factors for overweight/obesity. We identified that the prevalence of overweight/obesity among children aged 0–59 was 2.6% in India. The study findings reveal that factors such as child sex, age, birth weight, birth rank, maternal education, number of children, age at marriage, mother's BMI, media exposure, social group, and dietary diversity score were most significantly correlated with childhood overweight and obesity in India. Furthermore, we found that male children (ARR: 1.08) aged between 0 and 11 months (ARR: 3.77) with low birth rank (ARR: 1.24), obese (ARR: 1.81) children whose mothers married after the age of 18 (ARR: 1.15), children who belong to a scheduled tribe family (ARR: 1.46), and children who consumed 7–9 food items (ARR: 1.22) were at highest risk of being overweight and obese. However, breastfeeding (ARR: 0.85) and Muslim families (ARR: 0.87) appeared to be protective factors with respect to childhood overweight and obesity in India. Pertinent public health programs, clinical follow-up, and awareness about sedentary lifestyles can help to reduce overweight/obesity risks in children. [ABSTRACT FROM AUTHOR]