MSMEs in COVID-19 Crisis and India’s Economic Relief Package: A Critical Review

MSMEs (Micro, Small and Medium Enterprise) are the backbone of Indian economy as it contributes more than 30% in the India’s GDP (Gross Domestic Product). The present research studies the current conditions of MSMEs amid corona virus crisis and the economic relief package, specifically for MSMEs, entitled as “Atmanirbhar Bharat (Self-Dependent India)” in order to revive the business activities of MSMEs. Critical review of the economic package and modification needed in terms of MSMEs issues in the further announcements were discussed in this paper. Former RBI (Reserve Bank of India) governor Raghuram Rajan and Nobel Prize winner in economics Prof. Abhijit Banerjee has also contributed in the discussion in order to revive the Indian economy

Combating unemployment through skill development

In this paper, we propose and analyze a nonlinear mathematical model to study the effect of skill development on unemployment. We assume that government promulgates different levels of skill development programs for unemployed persons through which two different categories of skilled persons, namely, the low-skilled and the highly-skilled persons, are coming out and the highly-skilled persons are able to create vacancies. The model is studied using stability theory of nonlinear differential equations. We find analytically that there exists a unique positive equilibrium point of the proposed model system under some conditions. Also, the resulting equilibrium is locally as well as globally stable under certain conditions. The effective use of implemented policies to control unemployment by providing skills to unemployed persons and the new vacancies created by highly-skilled persons are identified by using optimal control analysis. Finally, numerical simulation is carried out to support analytical findings

Effect of Ceramic/Graphite Reinforcement on Dry Sliding Wear Behavior of Copper Metal Matrix Hybrid Composites

In the present investigation, effect of ceramic/graphite addition on the dry sliding wear behavior of copper-based hybrid composites have been assessed at three different normal loads of 9.81, 19.62 and 29.43 N. Wear test is performed by using pin-on-disc test rig at sliding speeds of 1.30 and 1.84 m/s under ambient conditions. The copper-based hybrid composites are successfully synthesized by using stir casting route. The samples are characterized by various techniques such as X-rays diffraction (XRD), high resolution-scanning electron microscopy (HR-SEM), scanning electron microscope (SEM) equipped with energy dispersive analysis of X-ray spectroscopy (EDAX). Microstructural investigations reveal the presence of the WC, TiC and graphite particles in the hybrid composites. It is observed that graphite reinforced hybrid composite shows better wear resistance than hybrid composite without graphite addition. In all the cases cast copper specimen shows highest wear rate. The observed friction and wear behavior have been explained on the basis of the presence tribofilm on the worn surface. Microstructural characterization of the worn surface and wear debris show that the mechanism of wear is primarily adhesive and oxidative in case of cast copper, where as it is a mix of adhesive and abrasive wear in case of hybrid composites. Wear debris analysis also helps to understand the wear mechanism involved during dry sliding

Dynamically adaptive data-driven simulation of extreme hydrological flows

Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Datadriven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The data assimilation system is implemented on various test cases that delve into the aspects of ensemble based assimilation filters. Additionally, data assimilation on tsunami models is analyzed and a methodology to map the uncertainties in the seabed deformation due to the associated earthquake to the water surface elevation forecast has been presented. Further, using other simulated environments such as the Chile tsunami event of February 2010, a systematic way to calibrate the assimilation system is presented. Finally, the technology is tested by assimilating actual gauge data from the Tohoku tsunami event. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.Engineering Mechanic

Manufacturing of Large Metallic Components through Wire and Arc Additive Manufacturing(WAAM)

Metal additive manufacturing have been in trend due to its ability to produce components at reduced cost and low buy-to- y ratio. There are various techniques employed for metal additive manufacturing depending on energy source and type of raw materials used. Based on raw materials, metal additive manufacturing can be classi ed as wire-based, powder-based and sheet-based (laminated object manufacturing). Amongst these three, wire based systems have higher material e ciency and high deposition rates. They also better suited for continious and uncluttered material supply. Hence, they are most suitable for large components. These wire based systems can be used in conjuction to di erent energy sources like Laser, Electron Beam and Arc. WLAM (wire and laser based additive manufacturing), EBAM (electron beam additive manufacturing) and WAAM (wire and arc based additive manufacturing) are examples of each of these energy sources respectively. In this study, Weld-depsotion based WAAM is chosen. The objective of this work is to fabricate large (greater than 1m in size) metallic components using WAAM process. Parameter study, kinematic setup for such working volumes and thermal analysis of deposition process to minimize distortions are some of the related aspects. Sample components in both multi-pass and single-pass geometries were also fabricated successfuly. This work was mainly carried out for mild steel (ER70S6); some priliminary studies on extending this to IN625 are also presented. Overall, this thesis presents the sutiability of WAAM in conjuction with a robotic or CNC type kinemetic setup to produce large metallic components

Analysing workplace spirituality as a mediator in the link between job satisfaction and organisational citizenship behaviour

Purpose – Without competent and talented employees, no organisation can grow and sustain for a long time. It becomes essential for every organisation to retain and satisfy the employees to achieve their predetermined organisational goals. The present study examines the mediating effect of workplace spirituality dimensions (i.e. meaningful work, compassion, transcendence, mindfulness and sense of community) in the link between job satisfaction and organisational citizenship behaviour (OCB) among managerial employees of selected manufacturing firms of Chhattisgarh state. Design/methodology/approach – Correlational research design was incorporated. Employees working at managerial positions at different private manufacturing firms of Chhattisgarh state were chosen as a sample for the present study. Regression analysis and confirmatory factor analysis tools were used to analyse the primary data collected from 400 respondents. Findings – The results revealed that all the dimensions of workplace spirituality, i.e. meaningful work, compassion, transcendence, mindfulness and sense of community, were found statistically significant and partially mediated between job satisfaction and OCB among managerial employees of Chhattisgarh. The authors discussed the results thoroughly and provided avenues for the future research. Research limitations/implications – The findings of the present research study will assist all private organisations in rethinking their employee retention and satisfaction strategies, since the presence of workplace spirituality in the organisation has a significant and beneficial impact on its environment. The current research will assist organisations in creating circumstances for OCB for employee via the introduction of workplace spirituality. Originality/value – Creating spirituality in the current situation, where Covid-19 has suddenly affected all organisations around the world, would be extremely beneficial in terms of employee retention and satisfaction, which would eventually aid in the development of an environment conducive to citizenship behaviour at the workplace. However, the role of workplace spirituality as a mediator in the link between job satisfaction and OCB is innovative and has received little attention in the research community

Taguchi based Design of Sequential Convolution Neural Network for Classification of Defective Fasteners

Fasteners play a critical role in securing various parts of machinery. Deformations such as dents, cracks, and scratches on the surface of fasteners are caused by material properties and incorrect handling of equipment during production processes. As a result, quality control is required to ensure safe and reliable operations. The existing defect inspection method relies on manual examination, which consumes a significant amount of time, money, and other resources; also, accuracy cannot be guaranteed due to human error. Automatic defect detection systems have proven impactful over the manual inspection technique for defect analysis. However, computational techniques such as convolutional neural networks (CNN) and deep learning-based approaches are evolutionary methods. By carefully selecting the design parameter values, the full potential of CNN can be realised. Using Taguchi-based design of experiments and analysis, an attempt has been made to develop a robust automatic system in this study. The dataset used to train the system has been created manually for M14 size nuts having two labeled classes: Defective and Non-defective. There are a total of 264 images in the dataset. The proposed sequential CNN comes up with a 96.3% validation accuracy, 0.277 validation loss at 0.001 learning rate.Comment: 13 pages, 6 figure

Knowledge Regarding Biological Terrorism among Medical Physicians in Goa

Introduction: The danger of using biological warfare for mass destruction is a serious threat to this country. Thus, it is necessary that our health care services are prepared to efficiently manage any such unfortunate events that we may have to face in future. Physicians in the public and private sector of health services are the first point of contact between public and health services. Thus, the present study examines the awareness of medical physicians in Goa about biological terrorism to evaluate the need for further education in this field.Methods: The present cross-sectional study was conducted among the medical physicians in Goa using purposive sampling method. The self-administered questionnaire collected information regarding the qualification, work setting of the study participants and knowledge regarding biological terrorism. Data was entered and analysed using SPSS version 22. Descriptive statistics was utilized to study frequencies and proportion of various study variables.Results: Of the 200 study participants, 128 (64%) were Specialist doctors, 65 (32.5%) were General physicians, while 7 (3.5%) were Super-specialist doctors. Of the 200 study participants, 174 (87%) reported that they were aware of the use of biological agent for mass destruction of human lives. As much as 34 (17%) study participants could not list any agent of bioterrorism.Conclusion: The knowledge of medical physician in Goa regarding bioterrorism is low, which is a matter of concern as these medical professionals are the first point of contact for the patients affected by an attack of bioterrorism

A compendium of molecules involved in vector-pathogen interactions pertaining to malaria

Malaria is a vector-borne disease causing extensive morbidity, debility and mortality. Development of resistance to drugs among parasites and to conventional insecticides among vector-mosquitoes necessitates innovative measures to combat this disease. Identification of molecules involved in the maintenance of complex developmental cycles of the parasites within the vector and the host can provide attractive targets to intervene in the disease transmission. In the last decade, several efforts have been made in identifying such molecules involved in mosquito-parasite interactions and, subsequently, validating their role in the development of parasites within the vector. In this study, a list of mosquito proteins, which facilitate or inhibit the development of malaria parasites in the midgut, haemolymph and salivary glands of mosquitoes, is compiled. A total of 94 molecules have been reported and validated for their role in the development of malaria parasites inside the vector. This compendium of molecules will serve as a centralized resource to biomedical researchers investigating vector-pathogen interactions and malaria transmission. © 2013 Sreenivasamurthy et al.; licensee BioMed Central Ltd

Giant cells: multiple cells unite to survive

Multinucleated Giant Cells (MGCs) are specialized cells that develop from the fusion of multiple cells, and their presence is commonly observed in human cells during various infections. However, MGC formation is not restricted to infections alone but can also occur through different mechanisms, such as endoreplication and abortive cell cycle. These processes lead to the formation of polyploid cells, eventually resulting in the formation of MGCs. In Entamoeba, a protozoan parasite that causes amoebic dysentery and liver abscesses in humans, the formation of MGCs is a unique phenomenon and not been reported in any other protozoa. This organism is exposed to various hostile environmental conditions, including changes in temperature, pH, and nutrient availability, which can lead to stress and damage to its cells. The formation of MGCs in Entamoeba is thought to be a survival strategy to cope with these adverse conditions. This organism forms MGCs through cell aggregation and fusion in response to osmotic and heat stress. The MGCs in Entamoeba are thought to have increased resistance to various stresses and can survive longer than normal cells under adverse conditions. This increased survival could be due to the presence of multiple nuclei, which could provide redundancy in case of DNA damage or mutations. Additionally, MGCs may play a role in the virulence of Entamoeba as they are found in the inflammatory foci of amoebic liver abscesses and other infections caused by Entamoeba. The presence of MGCs in these infections suggests that they may contribute to the pathogenesis of the disease. Overall, this article offers valuable insights into the intriguing phenomenon of MGC formation in Entamoeba. By unraveling the mechanisms behind this process and examining its implications, researchers can gain a deeper understanding of the complex biology of Entamoeba and potentially identify new targets for therapeutic interventions. The study of MGCs in Entamoeba serves as a gateway to exploring the broader field of cell fusion in various organisms, providing a foundation for future investigations into related cellular processes and their significance in health and disease