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Śri Śaṅkarācārya, a wise and intelligent man, interpreted ten Upaniṣads- Īśāvāsya Upaniṣad, Kena Upaniṣad, Kaṭha Upaniṣad, Praśna Upaniṣad, Muṇḍaka Upaniṣad, Māṇḍūkya Upaniṣad, Taittirīya Upaniṣad, Aitareya Upaniṣad, Chāndogya Upaniṣad and Bṛhadāraṇyaka Upaniṣad, which are considered to be the most important and significant. His Upaniṣad writings and interpretations are legendary. Śaṅkara gives a lot of material information in this main Upaniṣads commentary. One of them is heart-centred wisdom. The circulatory system’s pumping organ is the heart. The current review article covers Ādi Śaṅkarācārya’s commentary on the idea of the heart, including its etymology, meaning, anatomy, and position in the heart and venous drainage.

Childhood Obesity is defined as excess or abnormal increase of fat accumulation in the body. Early, developed countries were facing this childhood obesity but now it has moved to developing countries. According to World Health Organization (WHO), 39 million children under the age of 5 are obese and overweight in 2020 and 340 million adolescents and children aged between 5-19 were obese and overweight in 2016. According to Center for Disease Control, prevalence of obesity in United States was 19.3% and affected about 14.4 million adolescents and children in 2018. Moreover, in the adult population morbidity and mortality is increased in individuals who were overweight in adolescence, even if they lose the extra weight during adulthood. Diabetes, high blood pressure and high cholesterol, gastro intestinal disturbance, respiratory problems, orthopedic disorders once considered as adult problems now has become major health issue in children’s. Timely action must be initiated to combat the rising epidemic of childhood obesity and its consequences. However, by periodic surveillance on nutrition and childhood obesity in community, using various strategies at home and providing needy based intervention by schools care services, formulating and implementing structured policies will reduce the impact of childhood obesity worldwide.

Infertility is considered to be a global concern that affects many aspects of life for both sexes. The infertility epidemic is fast approaching and its numbers have reached 186 million people worldwide. The negative aspects of an unhealthy diet can be linked to reproductive health in women and adequate nutritional support can improve fertility. Most health expert recommendations and dietary guidelines acknowledge that certain foods or diet plans can actually improve fertility specifically, diet plans involving accumulated fruit and vegetable intake. However, the amount of nutrients varies significantly among fruits and vegetables, and not all fruit and vegetable choices are thought of “nutrient-rich”.Butter Fruit are distinctive, they contain abundant higher amounts of the key nutrients like folate and potassium, that are usually under-consumed in maternal diets and are coupled to spice up fertility and as well as cut back various sorts of diseases and deficiency as they contain essential nutrients and bioactive compounds.The present review article aims at addressing the proof that Butter Fruit could also be a singular nutrition for reinforcing fertility during pre-conception period.

Psychosocial risk exposure in childhood is associated with a greater probability of emotional, behavioral, and academic problems. It is not surprising that children who experience homelessness, a marker of high cumulative risk, show significant emotional and behavioral problems and lower academic achievement than other children, including impoverished children who are not homeless. Nonetheless, some children manifest positive adjustment despite the hazards associated with homelessness, and it is important to identify protective influences that might be targeted for intervention. One potential factor is mastery motivation (MM), or the drive to control and master challenges, theoretically associated with resilience and empirically linked to adaptive cognitive outcomes in low-risk children. Currently, there is little research on MM in high-risk young children overall, and data are particularly limited on the key question of whether MM is associated with better outcomes in domains crucial for school readiness, including socioemotional adjustment, self-regulation, and academic competence. This study examined observed MM in 85 young children ages 3 to 5 living with their parents in an emergency shelter. Children completed behavioral tasks to assess MM, and measures linked with school readiness were assessed directly or by parent report. Higher MM was associated with better social and emotional functioning and emotion regulation but not math achievement or executive functioning. Follow-up analyses indicated that MM was indirectly associated with prosocial behavior through better emotion-regulation abilities. Implications are discussed for further research and for interventions designed to address educational disparities and promote school success for children experiencing homelessness. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Few studies have explored the implications of parent socialization of positive emotions in children. Further, when considering outcomes of children, the focus has been primarily on links between parental emotion socialization and maladaptive child outcomes such as psychological distress, rather than adaptive outcomes such as life satisfaction. This study investigated whether recollection of supportive and unsupportive maternal and paternal responses to one’s expressions of positive and negative emotions in childhood was linked with life satisfaction and psychological distress in young adulthood, and consideration of whether parent emotion socialization and young adult outcomes were indirectly associated via young adult emotional experience. 262 college students completed instruments evaluating parental emotion socialization practices in childhood, emotional experience, life satisfaction, and psychological distress. Fathers’ supportive responses to positive emotions in childhood was indirectly associated with greater young adult life satisfaction through greater young adult positive emotional experience. Fathers’ supportive responses to negative emotions in childhood was indirectly associated with less young adult distress through less young adult negative emotional experience. Mothers’ supportive responses to negative emotions in childhood was indirectly associated with greater young adult life satisfaction through greater young adult positive emotional experience. Finally, fathers’ unsupportive responses to negative emotions in childhood was indirectly associated with greater young adult distress through greater young adult negative emotional experience. These results, if replicated with prospective longitudinal methodology, suggest that mother and father figures play unique roles in shaping the emotional lives of children, with long-term implications for mental health and well-being.

Computer vision is the science that aims to contribute a similar, if not better, capability to a machine or computer. It is also interested with the idea and technology for building artificial systems that secure information from images. The digital image processing, image analysis and computer vision have become a principle part of artificial intelligence and the interface between the human and the machine grounded theory and enforced technologies. Implementing machine learning such as deep neural networks on agricultural data as immense attention in recent times. Convolution Neural Networks (CNN) are most commonly used in pattern and image detection problems as they have a number of advantages compared to other techniques. This paper proposes CNN architecture to segregate different plant images from the sequences collected. Following the preprocessing steps that will be including the elimination of blurriness or introducing the illumination change; CNN architecture is employed to extract the traits of the images that are present in the dataset that is created. Image classification using CNN involves dataset creation, training CNN, validating, testing CNN, prediction and at last classification. Here we use Keras software with backend as Theano and Tensor flow and we are able to predict the overall classification report with the accuracy of 43.98% for one cast of field photographs.

The data here consists of time-dependent experimental parameters from chemical and biophysical methods used to characterize Aβ monomeric reactants as well as soluble oligomer and amyloid fibril products from a slow (3–4 week) assembly reaction under biologically-relevant solvent conditions. The data of this reaction are both of a qualitative and quantitative nature, including gel images from chemical cross-linking and Western blots, fractional solubility, thioflavin T binding, size exclusion chromatograms, transmission electron microscopy images, circular dichroism spectra, and fluorescence resonance energy transfer efficiencies of donor–acceptor pair labels in the Aβ chain. This data enables future efforts to produce the initial monomer and eventual soluble oligomer and amyloid fibril states by providing reference benchmarks of these states pertaining to physical properties (solubility), ligand-binding (thioflavin T binding), mesoscopic structure (electron microscopy, size exclusion chromatography, cross-linking products, SDS and native gels) and molecular structure (circular dichroism, FRET donor-acceptor distance).Aβ1-40 soluble oligomers are produced that are suitable for biophysical studies requiring sufficient transient stability to exist in their “native” conformation in biological phosphate-saline buffers for extended periods of time. The production involves an initial preparation of highly monomeric Aβ in a phosphate saline buffer that transitions to fibrils and oligomers through time incubation alone, without added detergents or non-aqueous chemicals. This criteria ensures that the only difference between initial monomeric Aβ reactant and subsequent Aβ oligomer products is their degree of peptide assembly. A number of chemical and biophysical methods were used to characterize the monomeric reactants and soluble oligomer and amyloid fibril products, including chemical cross-linking, Western blots, fraction solubility, thioflvain T binding, size exclusion chromatography, transmission electron micrscopy, circular dichroism spectroscopy, and fluorescence resonance energy transfer.

Surface plasmon resonance was used to investigate the kinetics, affinity, and specificity of binding between anti-Aβ (beta-amyloid) IgG antibodies and oligomeric Aβ. Two factors were needed to accurately characterize the IgG binding kinetics. First, a bivalent model was necessary to properly fit the kinetic association and dissociation sensograms. Second, a high concentration of IgG was necessary to overcome a significant mass transport limitation that existed regardless of oligomer density on the sensor surface. Using high IgG concentrations and bivalent fits, consistent kinetic parameters were found at varying sensor surface ligand densities. A comparison of binding specificity, affinity, and kinetic flux between monoclonal and natural human anti-Aβ IgG antibodies revealed the following findings. First, monoclonal antibodies 6E10 and 4G8 single-site binding affinity is similar between Aβ oligomers and monomers. Second, natural human anti-Aβ IgG binding readily binds Aβ oligomers but does not bind monomers. Third, natural human anti-Aβ IgG binds Aβ oligomers with a higher affinity and kinetic flux than 6E10 and 4G8. Both the current analytical methodology and antibody binding profiles are important for advances in antibody drug development and kinetic biomarker applications for Alzheimer's disease.

Polyglutamine repeats in proteins are highly correlated with amyloid formation and neurological disease. To better understand the molecular basis of glutamine repeat diseases, structural analysis of polyglutamine peptides as soluble monomers, oligomers, and insoluble amyloid fibrils is necessary. In this study, fluorescence resonance energy transfer (FRET) experiments and molecular dynamics simulations using different theoretical models of polyglutamine were conducted. This study demonstrates that a previously proposed simple CαCβ model of polyglutamine, denoted as FCO, accurately reproduced the present FRET results and the results of previously published FRET, triplet-state quenching, and fluorescence correlation studies. Other simple CαCβ models with random coil and extended β-strand parameters, and all-atom models with parm96 and parm99SB force fields, did not match the FRET result well. The FCO is an intrinsically disordered model with a high-effective persistence length producing extended peptides at short lengths (QN 16. Proteins 2011. © 2010 Wiley-Liss, Inc.

In large classrooms with limited teacher time, there is a need for automatic evaluation of text answers and real-time personalized feedback during the learning process. In this paper, we discuss Amrita Test Evaluation & Scoring Tool (A-TEST), a text evaluation and scoring tool that learns from course materials and from human-rater scored text answers and also directly from teacher input. We use latent semantic analysis (LSA) to identify the key concepts. While most AES systems use LSA to compare students’ responses with a set of ideal essays, this ignores learning the common misconceptions that students may have about a topic. A-TEST also uses LSA to learn misconceptions from the lowest scoring essays using this as a factor for scoring. ‘A-TEST’ was evaluated using two datasets of 1400 and 1800 pre-scored text answers that were manually scored by two teachers. The scoring accuracy and kappa scores between the derived ‘A-TEST’ model and the human raters were comparable to those between the human raters.

Formation of ripples or laser induced periodic surface structures (LIPSS) on semiconductor material like Silicon (Si) and on metals like Aluminum (Al) and Copper (Cu) and fabrication Silver (Ag) nanostructures in polymer matrix by femtosecond (fs) laser direct writing are reported in this paper. Laser irradiation was performed at normal incidence in air using linearly polarized Ti:Sapphire fs laser pulses of ~ 110 fs pulse duration and ~ 800 nm wavelength. Field emission scanning electron microscopy (FESEM) is utilized for imaging surface morphologies of laser written structures, revealing that surface morphology depends on various material processing parameters like laser fluence, polarization, material properties and number of applied pulses. Formation of polymer capped Ag nanoparticles inside the laser written microstructures is confirmed by the appearance of surface plasmon absorption band at 448 nm in the UV-Vis extinction spectrum. Nanoparticles formed were spherical in shape with an average particle size less than 20 nm. This technique is efficient, universal, cost-effective, and environmental friendly, which has potential applications in the fabrication of micro/nanostructures on variety of materials for microelectromechanical systems, nanoelectronics and nanophotonics.