Search

Groundnut (Arachis hypogaea L.), is the sixth-most significant leguminous oilseed crop grown all over worldwide. Groundnut, due to its high content of various dietary fibers, is classified as a valuable cash, staple and a feed crop for millions of households around the world. However, due to varied environmental factors, the crop is quite prone to many kinds of diseases, identifiable through its leaves, for which Groundnut producers have to suffer major losses every year. An early detection of such diseases is essential in order to save this significant crop and avoid huge losses. This paper presents a novel Machine Learning based Deep Convolution Neural Network (CNN) model 'CNN8GN'. The model uses transfer learning technique for detection of such diseases in Groundnuts at an early stage of crop production. A Groundnut real image data set containing a total of 5322 real images for six different classes of Groundnut leaf diseases, captured in the fields of Gujarat state (India) during September 2022 to February 2023, is generated for training, testing and evaluation of the proposed model. The proposed deep learning model architecture is designed on eight different layers and can be used on varied sized images using simple ReLu and Softmax activation functions. The performance of the proposed CNN8GN model on Groundnut real image dataset is examined using a detailed experimental analysis with other six pre-trained models: VGG16, InceptionV3, Resnet50, ResNet152V2, VGG19, and MobileNetV2. CNN8GN results are also examined in detail using different sets of input parameters values. The proposed model has shown significant improvements for disease detection in comparative analysis with 99.11% training and 91.25% testing accuracy. [ABSTRACT FROM AUTHOR]

Since the inception of the corporate world, employees have never been asked to work from home, therefore this situation has created an unprecedented situation for organisations. The distressful situation caused by Covid-19 has posed a peculiar kind of challenge for human resources such as insufficient IT infra, no physical interaction with superiors, colleagues and subordinates, lack of infrastructure, etc. The research study consisted of a sample of 116 individuals employed in various industries in Uttarakhand. Data analysis was done with the help of the Correlation and Regression method by using the Statistical Packages SPSS and Microsoft Excel. Using correlation and regression, the study found a significant positive relationship between five stressors of human resources (Job insecurity, remote working, unemployment, psychological distress and organisation performance) and covid-19 at the level of p<0.001. [ABSTRACT FROM AUTHOR]

Introduction: The problem of infertility is experienced as a crisis or major life stressor with potentially serious negative effects on the couple's relationship and preparation toward the parenthood. According to Sharlip et al., it has been estimated that about 15% of couple would have trouble in conception, and at present, 48.5 million couples experience infertility globally. To decrease the stress among parents to be and to promote healthy parenting for bringing out healthy parent–child relationships, an intervention of Parent Education Program was planned and executed. A study was conducted with the aim to assess the effectiveness of parental preparedness package (PPP) on physical health among couple conceived with artificial reproductive techniques (ART). Materials and Methods: The study was conducted to evaluate the effectiveness of PPP in fifty couples conceived with ART at Dayanand Medical College and Hospital, Ludhiana. Quantitative approach was used to collect the data of couples by doing pre- and postinterventional assessment of physical health of couple using the Structured Physical Health Assessment Scale. Analysis was done with the help of descriptive and inferential statistics. Results: The study revealed that mean score of physical health of couple (both husband and wife) increased significantly after the intervention which infers the effectiveness of PPP (P = 0.001). Conclusion: Our study concludes that PPP should be incorporated in the antenatal care protocol in all couples who conceive using ART. [ABSTRACT FROM AUTHOR]

Sickle cell disease (SCD) is a known risk factor for the development of severe dengue, however, literature documenting dengue in SCD is scarce. Dengue fever further triggers the sickling process in a patient with SCD by augmenting endothelial dysfunction, the main identifiable cause behind organ dysfunction. Hepatic involvement in SCD due to enhanced sickling can be in the form of acute viral hepatitis, cholecystitis, acute sickle hepatic crisis, and more severe sickle cell intrahepatic cholestasis (SCIC). Initially starting as an acute sickle hepatic crisis, SCIC progresses to striking jaundice, enhanced bleeding tendency coupled with mostly renal failure. We report a rare case of a female, native of Chhattisgarh with SCD and dengue shock syndrome who had fatal hepatic complications resulting from accelerated severe endothelial dysfunction due to concurrent illnesses. [ABSTRACT FROM AUTHOR]