PCROD: Context Aware Role based Offensive Detection using NLP/ DL Approaches

With the increased use of social media many people misuse online platforms by uploading offensive content and sharing the same with vast audience. Here comes controlling of such offensive contents. In this work we concentrate on the issue of finding offensive text in social media. Existing offensive text detection systems treat weak pejoratives like ‘idiot‘ and extremely indecent pejoratives like ‘f***‘ as same as offensive irrespective of formal and informal contexts . In fact the weakly pejoratives in informal discussions among friends are casual and common which are not offensive but the same can be offensive when expressed in formal discussions. Crucial challenges to accomplish the task of role based offensive detection in text are i) considering the roles while classifying the text as offensive or not i) creating a contextual datasets including both formal and informal roles. To tackle the above mentioned challenges we develop deep neural network based model known as context aware role based offensive detection(CROD). We examine CROD on the manually created dataset that is collected from social networking sites. Results show that CROD gives better performance with RoBERTa with an accuracy of 94% while considering the context and role in data specifics

Simultaneous optimization of machine and tool parameters for EDM using WC/Co P/M electrode made with micron and nano sized particles

Multi-response characteristic optimization is the most desired aspect of the components produced from electric discharge machining (EDM). Obtaining the optimal combination of parameters for surface roughness (SR) and micro-hardness (MH) is always a challenging task as the machining parameters favourable to one performance measure adversely affects the other. The present paper deals with the simultaneous optimization of SR and MH of D2 alloy steel during EDM with tungsten carbide (WC)/cobalt (Co) P/M electrode by considering electrode and machine tool parameters. Experimental run order was planned with Taguchi’s orthogonal arrays (OA) and in the present investigation, it is based on L18 OA. The analysis of variance (ANOVA) performed for the grey relational grade (GRG) showed that the tool parameter “particle size” (PS) is the most influential factor (61.43%) for simultaneous improvement of performance measures. The P/M electrode made of fine particle size (i.e., at nano level) has improved the process stability and reduced the arcing and short-circuiting results in reduced surface roughness. Simultaneously, the formation of the hard intermetallic phase’s viz., Fe3C, Cr23C6, W2C, Fe6W6C, and Cr2Fe14C on the EDMed surface has increased the surface hardness. The optimal set of parameters was validated through confirmation experiments

A rare case of Gingival Myeloid sarcoma in a child

Myeloid sarcoma is a rare tumour composed of immature myeloid cells. Its occurrence in childhood is rare. Only a few cases of intraoral myeloid sarcoma have been reported in literature. We present a case of myeloid sarcoma with simultaneous involvement of intraoral soft tissues and lymph node. Here, importance is given to suspect this frequently misdiagnosed disease. </p

Importance of tyrosine residues of Bacillus stearothermophilus serine hydroxymethyltransferase in cofactor binding and L-allo-Thr cleavage

Serine hydroxymethyltransferase (SHMT) from Bacillus stearothermophilus (bsSHMT) is a pyridoxal 5&#8242;-phosphate-dependent enzyme that catalyses the conversion of L-serine and tetrahydrofolate to glycine and 5,10-methylene tetrahydrofolate. In addition, the enzyme catalyses the tetrahydrofolate-independent cleavage of 3-hydroxy amino acids and transamination. In this article, we have examined the mechanism of the tetrahydrofolate-independent cleavage of 3-hydroxy amino acids by SHMT. The three-dimensional structure and biochemical properties of Y51F and Y61A bsSHMTs and their complexes with substrates, especially L-allo-Thr, show that the cleavage of 3-hydroxy amino acids could proceed via C&#945; proton abstraction rather than hydroxyl proton removal. Both mutations result in a complete loss of tetrahydrofolate-dependent and tetrahydrofolate-independent activities. The mutation of Y51 to F strongly affects the binding of pyridoxal 5&#8242;-phosphate, possibly as a consequence of a change in the orientation of the phenyl ring in Y51F bsSHMT. The mutant enzyme could be completely reconstituted with pyridoxal 5&#8242;-phosphate. However, there was an alteration in the &#955;max value of the internal aldimine (396 nm), a decrease in the rate of reduction with NaCNBH3 and a loss of the intermediate in the interaction with methoxyamine (MA). The mutation of Y61 to A results in the loss of interaction with C&#945; and C&#946; of the substrates. X-Ray structure and visible CD studies show that the mutant is capable of forming an external aldimine. However, the formation of the quinonoid intermediate is hindered. It is suggested that Y61 is involved in the abstraction of the C&#945; proton from 3-hydroxy amino acids. A new mechanism for the cleavage of 3-hydroxy amino acids via C&#945; proton abstraction by SHMT is proposed

Validez de las categorías relacionadas con la identidad de genero en la CIE-11 y el DSM-5 entre personas transgenero que buscan procedimientos medicos que afirmen su genero

BACKGROUND/OBJECTIVE : The most recent versions of the two main mental disorders classifications-the World Health Organization's ICD-11 and the American Psychiatric Association's DSM-5-differ substantially in their diagnostic categories related to transgender identity. ICD-11 gender incongruence (GI), in contrast to DSM-5 gender dysphoria (GD), is explicitly not a mental disorder; neither distress nor dysfunction is a required feature. The objective was compared ICD-11 and DSM-5 diagnostic requirements in terms of their sensitivity, specificity, discriminability and ability to predict the use of gender-affirming medical procedures. METHOD : A total of 649 of transgender adults in six countries completed a retrospective structured interview. RESULTS : Using ROC analysis, sensitivity of the diagnostic requirements was equivalent for both systems, but ICD-11 showed greater specificity than DSM-5. Regression analyses indicated that history of hormones and/or surgery was predicted by variables that are an intrinsic aspect of GI/GD more than by distress and dysfunction. IRT analyses showed that the ICD-11 diagnostic formulation was more parsimonious and contained more information about caseness than the DSM-5 model. CONCLUSIONS : This study supports the ICD-11 position that GI/GD is not a mental disorder; additional diagnostic requirements of distress and/or dysfunction in DSM-5 reduce the predictive power of the diagnostic model.Partially funded by unrestricted grants by the World Health Organization Department of Mental Health and Substance Abuse to participating institutions in Brazil, India, Lebanon, Mexico, and South Africa for the development and implementation of ICD-11 field studies. Financial support for the French study was provided by the Direction Générale de la Santé (DGS), Ministry of Health, France.http://www.elsevier.es/ijchpam2023Psychiatr

Validity of categories related to gender identity in ICD-11 and DSM-5 among transgender individuals who seek gender-affirming medical procedures

Background/Objective: The most recent versions of the two main mental disorders classifications—the World Health Organization's ICD-11 and the American Psychiatric Association's DSM–5—differ substantially in their diagnostic categories related to transgender identity. ICD-11 gender incongruence (GI), in contrast to DSM-5 gender dysphoria (GD), is explicitly not a mental disorder; neither distress nor dysfunction is a required feature. The objective was compared ICD-11 and DSM-5 diagnostic requirements in terms of their sensitivity, specificity, discriminability and ability to predict the use of gender-affirming medical procedures. Method: A total of 649 of transgender adults in six countries completed a retrospective structured interview. Results: Using ROC analysis, sensitivity of the diagnostic requirements was equivalent for both systems, but ICD-11 showed greater specificity than DSM-5. Regression analyses indicated that history of hormones and/or surgery was predicted by variables that are an intrinsic aspect of GI/GD more than by distress and dysfunction. IRT analyses showed that the ICD-11 diagnostic formulation was more parsimonious and contained more information about caseness than the DSM-5 model. Conclusions: This study supports the ICD-11 position that GI/GD is not a mental disorder; additional diagnostic requirements of distress and/or dysfunction in DSM-5 reduce the predictive power of the diagnostic model

A study on factors driving the capital structure decisions of small and medium enterprises (SMEs) in India

The prime focus of the study is to empirically examine the factors affecting the capital structure decisions of small and medium enterprises (SMEs) in India. The sample consists of 174 non-financial firms. Generalised method of moments (GMM) has been applied to find out the firm specific factors affecting financing decisions of SMEs in India. The study specifically examines the effect of firm's profitability, tangibility, size, age, growth, liquidity, non-debt tax shield, cash flow ratio, and return on equity on the leverage of the firm. It confirms the applicability of the pecking order theory for SMEs in India. Keywords: Capital structure, SMEs, Generalised method of moments, Leverag

Modeling transcriptional activation changes to Gal4 variants via structure-based computational mutagenesis

As a DNA binding transcriptional activator, Gal4 promotes the expression of genes responsible for galactose metabolism. The Gal4 protein from Saccharomyces cerevisiae (baker’s yeast) has become a model for studying eukaryotic transcriptional activation in general because its regulatory properties mirror those of several eukaryotic organisms, including mammals. Given the availability of a crystallographic structure for Gal4, here we implement an in silico mutagenesis technique that makes use of a four-body knowledge-based energy function, in order to empirically quantify the structural impacts associated with single residue substitutions on the Gal4 protein. These results were used to examine the structure-function relationship in Gal4 based on a recently published experimental mutagenesis study, whereby functional changes to a uniformly distributed set of 1,068 single residue Gal4 variants were obtained by measuring their transcriptional activation levels relative to wild-type. A significant correlation was observed between computed (scalar) structural effect data and measured activity values for this collection of single residue Gal4 variants. Additionally, attribute vectors quantifying position-specific environmental impacts were generated for each of the Gal4 variants via computational mutagenesis, and we implemented supervised classification and regression statistical machine learning algorithms to train predictive models of variant Gal4 activity based on these structural changes. All models performed well under cross-validation testing, with balanced accuracy reaching 91% among the classification models, and with the actual and predicted activity values displaying a correlation as high as r = 0.80 for the regression models. Reliable predictions of transcriptional activation levels for Gal4 variants that have yet to be studied can be instantly generated by submitting their respective structure-based feature vectors to the trained models for testing. Such a computational pre-screening of Gal4 variants may potentially reduce costs associated with running large-scale mutagenesis experiments