A Data Driven Machine Learning Approach to Prediction of Stacking Fault Energy in Austenitic Steels

The Material Genome Initiative (MGI) calls for establishing frameworks and adopting methodologies to accelerate materials discovery and deployment. The Integrated Computational Materials Engineering (ICME) approach and Materials Informatics leveraging materials data are two very important pillars to the initiative. This research is a data driven materials informatics approach to enable an ICME project on steel alloy design. For the alloy design problem there was a need to predict Stacking Fault Energy (SFE) for any untested alloy composition. SFE is a crucial parameter in determining different deformation regimes in austenitic steels. The SFE itself is dependent on the chemical composition and temperature in steels. There has been considerable study on determination of SFE in steels by experimental and computational methods. While the experimental methods investigate an alloy to find SFE, computational models have been constructed to predict SFE for a given composition and temperature. However, it is shown in this thesis that there are large inconsistencies in experimental data, as well as unavailability of robust computational models to predict SFE in truly multicomponent steel alloys. In this work, a data-driven machine learning approach to mine the literature of SFE in steels with the final aim of predicting deformation regimes for potentially unknown and untested alloy compositions has been demonstrated. Algorithms at the fore-front of Machine Learning have been used to visualize the SFE data and then construct classifiers to predict SFE regime in steels. This machine-learning modeling approach can help accelerate alloy discovery of austenitic steels by linking composition to desired mechanical behavior

International Consensus Statement on Rhinology and Allergy: Rhinosinusitis

Background: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods: ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results: ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion: This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS

Influence of antimony dopant on CuIn(S,Se)2 solar thin absorber layer deposited via solution-processed route

This paper reports the hydrazine-free solution processing of antimony doping in CuIn(S,Se)2 solar cells using thiol-amine as solvents. The Sb-doped CuIn(S,Se)2 absorbers layer is fabricated using low-cost atmospheric spray deposition route. The morphological, optical, and electrical properties of Sb-doped CuIn(S,Se)2 are investigated using XRD, FE-SEM, UV–Vis-IR spectrophotometer, and solar simulator. Results suggest that the power conversion efficiency of fabricated CuIn(S,Se)2 solar cells is significantly improved by introducing antimony dopant. Results infers plausible way of future manufacturing and processing of chalcopyrite thin films solar cells at lower temperature using non-vacuum deposition route

The role of polymorphism in various potential genes on polycystic ovary syndrome susceptibility and pathogenesis

Abstract Polycystic ovary syndrome (PCOS) is the most common endocrinopathies affecting the early reproductive age in women, whose pathophysiology perplexes many researchers till today. This syndrome is classically categorized by hyperandrogenism and/or hyperandrogenemia, menstrual and ovulatory dysfunction, bulky multi follicular ovaries on Ultrasonography (USG), and metabolic abnormalities such as hyperinsulinemia, dyslipidemia, obesity. The etiopathogenesis of PCOS is not fully elucidated, but it seems that the hypothalamus-pituitary-ovarian axis, ovarian, and/or adrenal androgen secretion may contribute to developing the syndrome. Infertility and poor reproductive health in women’s lives are highly associated with elevated levels of androgens. Studies with ovarian theca cells taken from PCOS women have demonstrated increased androgen production due to augmented ovarian steroidogenesis attributed to mainly altered expression of critical enzymes (Cytochrome P450 enzymes: CYP17, CYP21, CYP19, CYP11A) in the steroid hormone biosynthesis pathway. Despite the heterogeneity of PCOS, candidate gene studies are the widely used technique to delineate the genetic variants and analyze for the correlation of androgen biosynthesis pathway and those affecting the secretion or action of insulin with PCOS etiology. Linkage and association studies have predicted the relationship between genetic variants and PCOS risk among families or populations. Several genes have been proposed as playing a role in the etiopathogenesis of PCOS, and the presence of mutations and/or polymorphisms has been discovered, which suggests that PCOS has a vital heritable component. The following review summarizes the influence of polymorphisms in crucial genes of the steroidogenesis pathway leading to intraovarian hyperandrogenism which can result in PCOS

Multi-Threaded User Space Network Stack For Intrusion Prevention System

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Association of FTO gene variant rs9939609 with polycystic ovary syndrome from Gujarat, India

Abstract Background Polycystic ovary syndrome is a multifactorial endocrine disorder impacting women of reproductive age. Variations within the FTO gene have been linked to both obesity and type 2 diabetes mellitus. Given that PCOS is frequently associated with obesity and compromised glucose tolerance, we investigated the prevalence of the rs9939609 variant within the FTO gene among women diagnosed with PCOS and a control group. Our aim is to uncover potential correlations between this genetic variant, metabolic attributes, and endocrine markers within the Gujarat province of India. Method We enrolled a total of 114 participants, (62 individuals diagnosed with PCOS and 52 healthy controls). DNA extraction from venous blood was conducted for all participants. The rs9939609 polymorphism was investigated through tetra-primer amplification refractory mutation system-polymerase chain reaction. Furthermore, we performed biochemical assessments to quantify levels of estradiol, luteinizing hormone (LH), follicle-stimulating hormone (FSH), thyroid-stimulating hormone (TSH), total testosterone, prolactin (PRL), and Dehydroepiandrosterone sulfate (DHEAS). Statistical analyses were carried out utilizing SPSS version 21 (IBM, USA). Results The present study did not reveal any noteworthy association between cases and controls. The frequencies of genotypes and alleles within the cohorts displayed no statistically significant differences (p = 0.25, p = 0.68, and p = 0.78, respectively). The dominant model indicated a modest risk (OR:1.13, 95%CI: 0.55 to 2.38) toward PCOS development. There was a noticeable statistical difference observed in the levels of total testosterone, DHEAS, and BMI between the case and control groups (p < 0.002, p < 0.0002, p < 0.0008). However, no variations in clinical variables were observed among genotypes within the PCOS group. Conclusion This is the first study to investigate the association of FTO gene polymorphism and PCOS in Gujarati population. Our study findings indicate that the FTO gene variant is not directly linked to the onset of PCOS. However, it appears to exert an influence on metabolic factors such as obesity and insulin resistance. Notably, our results suggest that insulin resistance is more frequently observed among PCOS patients who are obese, as compared to those with non-obese PCOS patients

A checklist of the flowering plants of Katerniaghat Wildlife Sanctuary, Uttar Pradesh, India

Katerniaghat Wildlife Sanctuary, a tropical moist deciduous forest along the Indo-Nepal boarder comprises of 778 species of angiosperms, out of which 613 species are dicots under 386 genera and 91 families and 165 species are monocots under 103 genera and 23 families.  It contains 82 species that are in cultivation and/or growing as alien invasives.  The species include 149 trees, 81 shrubs, 445 herbs and 103 climbers.  Fabaceae with 100 species and Poaceae with 65 species occupy the first position in dicots and monocots, respectively.  Cyperus with 14 species has been found to be the largest genus represented while 355 genera are represented by solitary species.  The present study enumerates all species of flowering plants occurring in the sanctuary area with their correct name along with first citation and some important references pertaining to the flora of the study area.  Important synonyms have also been provided.  For majority of species the representative voucher specimens have also been supplied.  The paper also briefly deals with the vegetation types of the area. The outcome of the work is based on extensive field survey of the area conducted during 2008–2011, study of literature and examination of specimens of earlier collections housed at BSA, BSIP, CDRI and LWG.</div

A checklist of the flowering plants of Katerniaghat Wildlife Sanctuary, Uttar Pradesh, India

Katerniaghat Wildlife Sanctuary, a tropical moist deciduous forest along the Indo-Nepal boarder comprises of 778 species of angiosperms, out of which 613 species are dicots under 386 genera and 91 families and 165 species are monocots under 103 genera and 23 families.  It contains 82 species that are in cultivation and/or growing as alien invasives.  The species include 149 trees, 81 shrubs, 445 herbs and 103 climbers.  Fabaceae with 100 species and Poaceae with 65 species occupy the first position in dicots and monocots, respectively.  Cyperus with 14 species has been found to be the largest genus represented while 355 genera are represented by solitary species.  The present study enumerates all species of flowering plants occurring in the sanctuary area with their correct name along with first citation and some important references pertaining to the flora of the study area.  Important synonyms have also been provided.  For majority of species the representative voucher specimens have also been supplied.  The paper also briefly deals with the vegetation types of the area. The outcome of the work is based on extensive field survey of the area conducted during 2008–2011, study of literature and examination of specimens of earlier collections housed at BSA, BSIP, CDRI and LWG.</div

Additional file 1 of Association of FTO gene variant rs9939609 with polycystic ovary syndrome from Gujarat, India

Additional file 1: Supplementary Figure 1. Recruitment of PCOS samples and healthy controls. Supplementary Table 1. Risk factors for PCOS

Using artificial intelligence for improving stroke diagnosis in emergency departments: a practical framework.

Stroke is the fifth leading cause of death in the United States and a major cause of severe disability worldwide. Yet, recognizing the signs of stroke in an acute setting is still challenging and leads to loss of opportunity to intervene, given the narrow therapeutic window. A decision support system using artificial intelligence (AI) and clinical data from electronic health records combined with patients presenting symptoms can be designed to support emergency department providers in stroke diagnosis and subsequently reduce the treatment delay. In this article, we present a practical framework to develop a decision support system using AI by reflecting on the various stages, which could eventually improve patient care and outcome. We also discuss the technical, operational, and ethical challenges of the process