Extent of Empowerment of Women Entrepreneurs on Entrepreneurial and Technological Empowerment

Empowerment of women entrepreneurs in the context of technology entails building up the abilities and skills of women to gain insight into the issues affecting them and also building up their capacity to voice their concerns. Technological empowerment of women entrepreneurs will open up avenues to further nrichment. By the use of technology women can broaden the scope of their activities. Hence the present paper focused on analyzing the entrepreneurial and technological empowerment of women entrepreneurs. Majority of the women entrepreneurs had medium level of entrepreneurial and low level of technological empowerment

Fractional difference inequalities of Gronwall-Bellman type

Discrete inequalities, in particular the discrete analogues of the Gronwall–Bellman inequality, have been extensively used in the analysis of nite difference equations. The aim of the present paper is to establish some fractional difference inequalities of Gronwall–Bellman type which provide explicit bounds for the solutions of fractional difference equations

Fractional Order Difference Equations

A difference equation is a relation between the differences of a function at one or more general values of the independent variable. These equations usually describe the evolution of certain phenomena over the course of time. The present paper deals with the existence and uniqueness of solutions of fractional difference equations

Chemopreventive Effects of the p53-Modulating Agents CP-31398 and Prima-1 in Tobacco Carcinogen-Induced Lung Tumorigenesis in A/J Mice

AbstractLung cancer is the leading cause of cancer deaths worldwide. Expression of the p53 tumor suppressor protein is frequently altered in tobacco-associated lung cancers. We studied chemopreventive effects of p53-modulating agents, namely, CP-31398 and Prima-1, on 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK)-induced lung adenoma and adenocarcinoma formation in female A/J mice. Seven-week-old mice were treated with a single dose of NNK (10 µmol/mouse) by intraperitoneal injection and, 3 weeks later, were randomized to mice fed a control diet or experimental diets containing 50 or 100 ppm CP-31398 or 150 or 300 ppm Prima-1 for either 17 weeks (10 mice/group) or 34 weeks (15 mice/group) to assess the efficacy against lung adenoma and adenocarcinoma. Dietary feeding of 50 or 100 ppm CP-31398 significantly suppressed (P < .0001) lung adenocarcinoma by 64% and 73%, respectively, after 17 weeks and by 47% and 56%, respectively, after 34 weeks. Similarly, 150 or 300 ppm Prima-1 significantly suppressed (P < .0001) lung adenocarcinoma formation by 56% and 62%, respectively, after 17 weeks and 39% and 56%, respectively, after 34 weeks. Importantly, these results suggest that both p53 modulators cause a delay in the progression of adenoma to adenocarcinoma. Immunohistochemical analysis of lung tumors from mice exposed to p53-modulating agents showed a significantly reduced tumor cell proliferation and increased accumulation of wild-type p53 in the nucleus. An increase in p21- and apoptotic-positive cells was also observed in lung tumors of mice exposed to p53-modulating agents. These results support a chemopreventive role of p53-modulating agents in tobacco carcinogen-induced lung adenocarcinoma formation

Development of stable blackgram [Vigna mungo (L.) Hepper] genotypes by deciphering genotype × environment interaction using Eberhart-Russell and AMMI models

The genotype and environment (G × E) interaction is a key area of research for creating stable cultivars as it has a major impact on crop yield performance. In this study, we examined the stability and adaptability of the seed yields of elite blackgram genotypes in four Agricultural Research Centers of PJTSAU consisting of diverse environments in Telangana, India during Rabi 2019-20 using Eberhart-Russell and Additive Main effects and Multiplicative Interaction (AMMI) models. A combined analysis of variance showed significant differences between the varieties and the interactions between the varieties and locations for seed yield. Both Eberhart and Russell and AMMI1 model analyses of G×E interaction identified G1 (LBG-752) as the stable variety with respect to yielding ability suitable for cultivation under diverse conditions. Environments A, B, and C were found to be ideal environments for genotypes G7, G8, and G6, respectively, based on AMMI 2. The selected elite varieties based on different stability analyses could be used for further exploitation for cultivar release

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Modelling a deep network using CNN and RNN for accident classification

There is a rapid evolution in highway investigation due to the increased usage of vehicles. Recently, various investigators have huge attention to the Intelligent Transportation System (ITS). Predicting a particular image plays a crucial role in digital image processing. However, this process is more challenging due to its changing viewpoints, illumination, colour, shape, etc. This work concentrates on modelling a novel deep learning (DL) approach. Initially, a deep-Convolutional Neural Network (D–CNN)–based sample-level classifier is proposed iteratively to measure the sampling uncertainty. Here, the uncertainty evaluation method is integrated with the sample learning process for training the robust sample classifier. The proposed D-CNN model has the competency to identify the abnormal activities and feature representation simultaneously. Subsequently, Deep Recurrent Neural Network (D-RNN) is proposed to examine the feature representation from the bag of samples and generates the final classification output by considering the local and global sampling aggregately. The simulation is performed using MATLAB 2020a and the proposed D-CNN and D-RNN model provides better trade-off with the classification accuracy compared to other approaches. The model accuracy is 92.9%, sensitivity is 76.40%, and specificity is 100% which is substantially higher than other approaches

Extent of Empowerment of Women Entrepreneurs on Entrepreneurial and Technological Empowerment

Empowerment of women entrepreneurs in the context of technology entails building up the abilities and skills of women to gain insight into the issues affecting them and also building up their capacity to voice their concerns. Technological empowerment of women entrepreneurs will open up avenues to further nrichment. By the use of technology women can broaden the scope of their activities. Hence the present paper focused on analyzing the entrepreneurial and technological empowerment of women entrepreneurs. Majority of the women entrepreneurs had medium level of entrepreneurial and low level of technological empowerment