Motivational Factors Relating to Entrepreneurial Intention: A Study of Postgraduate Management Students in India

With the growing importance of entrepreneurship all over the world, and particularly in Asia, this paper aims at studying the motivational factors relating to the entrepreneurial intention of postgraduate management students in India. What are the factors which motivate university students to start a new business venture after completing their studies? Are they related solely to the personality of the individual or are they related to his/her support systems or is it a combination of both? The objective of this study is to examine the relationship between entrepreneurial intention and the given variables like attitude towards self-employment, subjective norms, perceived behavioral control, perceived educational support and perceived structural support. For this purpose, a model based on the theory of planned behavior and entrepreneurial support models was proposed and empirically tested on a sample of 382 postgraduate management students in India. The sample was collected from across seven management colleges in Kerala. The findings reveal that all the five factors, namely attitude towards self-employment, subjective norms, perceived behavioral control, perceived educational support and perceived structural support, have a positive effect on the entrepreneurial intention of an individual

Assessment of response of microdermabrasion with 2% kojic acid in melasma

Background: Melasma is an acquired disorder of hypermelanosis and several therapeutic modalities is in use to treat melasma. Kojic acid is a popular depigmenting agent, but its hydrophilic nature limits its transepidermal penetration. Microdermabrasion has been reported to increase the penetration of topical preparations. The objective of the study was to compare the efficacy of daily kojic acid (2%) gel along with biweekly microdermabrasion versus daily kojic acid (2%) gel alone in Indian patients.Methods: This study was carried out in 60 patients with melasma which were randomised into 2 groups of 30 patients each. The group I patients were treated with kojic acid 2% gel along with biweekly microdermabrasion, and group II patients were treated with kojic acid 2% gel alone. The results were assessed and compared after 12 weeks.Results: Both objective assessment and subjective assessment did not reveal a statistically significant difference in the treatment efficacy of two groups. However, the patients who received biweekly microdermabrasion were significantly more satisfied than those who did not.Conclusions: Microdermabrasion does not appear to have any synergistic effect with kojic acid in decreasing pigmentation in melasma. However, it does have a placebo effect on the patient.

Autoimplantation therapy for the management of extensive molluscumcontagiosum: a novel treatment approach

Background: Molluscumcontagiosum (MC) is a common cutaneous viral infection which usually affects children. Inspite of the multiple treatment options such as curettage, expression, electrodessication and different topical agents, in some cases lesions become extensive and persist for more than 3 to 4 years. The role of immunomodulatory therapy in management of MC has been well documented. Autoimplantation has emerged as a useful immunomodulatory therapy for warts. The objective of the study is to assess the efficacy and safety of autoimplantation in treatment of extensive MC.Methods: Patients of   either sex having more than six MC lesions were included. Molluscum body removed, crushed & implanted in a small dermal pocket as described in cases of warts. Patients were evaluated at four weeks, 12 weeks & subsequent 24 weeks.Results: Twenty two patients completed the study. Complete clearance of the MC was seen in 17 (77.2%) patients, 2 (9.1%) had no response, 1 (4.5%) had partial remission & 2 patients (9.1%) showed recurrence.Conclusions: Autoimplantation may be effective& alternative modalities for extensive MC. However, more randomized controlled trial for automplantation therapy in extensive MC need to be warranted

Post-operative atrial fibrillation in off pump coronary artery bypass graft: association with medication

Background: Post-operative atrial fibrillation is a common post-operative complication and has significant morbidity and mortality. This study was done with an objective to determine the association of various medication use in patients undergoing coronary artery bypass graft (CABG) with post-operative atrial fibrillation (POAF).Methods: This was a prospective observational study done in the department of cardiovascular and thoracic surgery of GMC Kottayam from December 2019 to December 2020 after obtaining institutional review board clearance. A sample size of 334 was fixed and patients undergoing off pump (OP) CABG were consecutively recruited in the study. The association of intraoperative and postoperative medication use with occurrence of POAF were analysed using the univariate analysis with a p<0.05 using the SPSS 16 software.Results: Peri-operative inotrope use was found to be significantly associated with post operative atrial fibrillation odds ratio 1.08 (95% CI 1.02-1.13). We could not find any association with preoperative use of beta blockers/agonist, antidiabetics, levothyroxine, ACE inhibitors or antiplatelet drugs. All the patients 60 (18%) who developed POAF were given amiodarone as per protocol.Conclusions: Perioperative inotrope use was found to have significant association with the development of post operative atrial fibrillation following OPCABG. More multi-institutional studies with determination of association with individual drugs and doses with POAF need to be conducted in future

Towards Early Prediction of Human iPSC Reprogramming Success

This paper presents advancements in automated early-stage prediction of the success of reprogramming human induced pluripotent stem cells (iPSCs) as a potential source for regenerative cell therapies.The minuscule success rate of iPSC-reprogramming of around $0.01$ to $0.1$ makes it labor-intensive, time-consuming, and exorbitantly expensive to generate a stable iPSC line. Since that requires culturing of millions of cells and intense biological scrutiny of multiple clones to identify a single optimal clone. The ability to reliably predict which cells are likely to establish as an optimal iPSC line at an early stage of pluripotency would therefore be ground-breaking in rendering this a practical and cost-effective approach to personalized medicine. Temporal information about changes in cellular appearance over time is crucial for predicting its future growth outcomes. In order to generate this data, we first performed continuous time-lapse imaging of iPSCs in culture using an ultra-high resolution microscope. We then annotated the locations and identities of cells in late-stage images where reliable manual identification is possible. Next, we propagated these labels backwards in time using a semi-automated tracking system to obtain labels for early stages of growth. Finally, we used this data to train deep neural networks to perform automatic cell segmentation and classification. Our code and data are available at https://github.com/abhineet123/ipsc_prediction.Comment: Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2023:01

Technologies for the global energy transition

The availability of reliable, affordable and mature technologies is at the basis of an effective decarbonization strategy, that should be in turn supported by timely and accurate policies. Due to the large differences across sectors and countries, there is no silver bullet to support decarbonization, but a combination of multiple technologies will be required to reach the challenging goal of decarbonizing the energy sector. This chapter presents a focus on the current technological solutions that are available in four main sectors: power generation, industry, transport and buildings. The aim of this work is to highlight the main strengths and weaknesses of the current technologies, to help the reader in understanding which are the main opportunities and challenges related to the development and deployment of each of them, as well as their potential contribution to the decarbonization targets. The chapter also provides strategies and policy recommendations from a technology point of view on how to decarbonize the global energy systems by mid-century and of the necessity to take a systems approach

A Small Molecule Swertisin from Enicostemma littorale

Aim. Stem cell therapy is one of the upcoming therapies for the treatment of diabetes. Discovery of potent differentiating agents is a prerequisite for increasing islet mass. The present study is an attempt to screen the potential of novel small biomolecules for their differentiating property into pancreatic islet cells using NIH3T3, as representative of extra pancreatic stem cells/progenitors. Methods. To identify new agents that stimulate islet differentiation, we screened various compounds isolated from Enicostemma littorale using NIH3T3 cells and morphological changes were observed. Characterization was performed by semiquantitative RT-PCR, Q-PCR, immunocytochemistry, immunoblotting, and insulin secretion assay for functional response in newly generated islet-like cell clusters (ILCC). Reversal of hyperglycemia was monitored after transplanting ILCC in STZ-induced diabetic mice. Results. Among various compounds tested, swertisin, an isolated flavonoid, was the most effective in differentiating NIH3T3 into endocrine cells. Swertisin efficiently changed the morphology of NIH3T3 cells from fibroblastic to round aggregate cell cluster in huge numbers. Dithizone (DTZ) stain primarily confirmed differentiation and gene expression studies signified rapid onset of differentiation signaling cascade in swertisin-induced ILCC. Molecular imaging and immunoblotting further confirmed presence of islet specific proteins. Moreover, glucose induced insulin release (in vitro) and decreased fasting blood glucose (FBG) (in vivo) in transplanted diabetic BALB/c mice depicted functional maturity of ILCC. Insulin and glucagon expression in excised islet grafts illustrated survival and functional integrity. Conclusions. Rapid induction for islet differentiation by swertisin, a novel herbal biomolecule, provides low cost and readily available differentiating agent that can be translated as a therapeutic tool for effective treatment in diabetes

Recent Walker Circulation strengthening and Pacific cooling amplified by Atlantic warming

An unprecedented strengthening of Pacific trade winds since the late 1990s (ref. 1) has caused widespread climate perturbations, including rapid sea-level rise in the western tropical Pacific, strengthening of Indo-Pacific ocean currents, and an increased uptake of heat in the equatorial Pacific thermocline. The corresponding intensification of the atmospheric Walker circulation is also associated with sea surface cooling in the eastern Pacific, which has been identified as one of the contributors to the current pause in global surface warming. In spite of recent progress in determining the climatic impacts of the Pacific trade wind acceleration, the cause of this pronounced trend in atmospheric circulation remains unknown. Here we analyse a series of climate model experiments along with observational data to show that the recent warming trend in Atlantic sea surface temperature and the corresponding trans-basin displacements of the main atmospheric pressure centres were key drivers of the observed Walker circulation intensification, eastern Pacific cooling, North American rainfall trends and western Pacific sea-level rise. Our study suggests that global surface warming has been partly offset by the Pacific climate response to enhanced Atlantic warming since the early 1990s

Machine Learning Heuristics on Gingivobuccal Cancer Gene Datasets Reveals Key Candidate Attributes for Prognosis

Delayed cancer detection is one of the common causes of poor prognosis in the case of many cancers, including cancers of the oral cavity. Despite the improvement and development of new and efficient gene therapy treatments, very little has been carried out to algorithmically assess the impedance of these carcinomas. In this work, from attributes or NCBI’s oral cancer datasets, viz. (i) name, (ii) gene(s), (iii) protein change, (iv) condition(s), clinical significance (last reviewed). We sought to train the number of instances emerging from them. Further, we attempt to annotate viable attributes in oral cancer gene datasets for the identification of gingivobuccal cancer (GBC). We further apply supervised and unsupervised machine learning methods to the gene datasets, revealing key candidate attributes for GBC prognosis. Our work highlights the importance of automated identification of key genes responsible for GBC that could perhaps be easily replicated in other forms of oral cancer detection.publishedVersionPeer reviewe