A Structural Equation Model on Work Design in Relation to Authentic Leadership, Workplace Spirituality, and Practical Emotional Intelligence of Public Elementary Teachers

The study determined the best fit model for the work design based on authentic leadership, workplace spirituality, and practical emotional intelligence of public elementary teachers. Using e-survey through Google Forms, data was collected from the teachers using a set of modified survey questionnaires that were tested for content validity and reliability. This study used a quantitative descriptive and causal method of research. The statistical tools employed in analyzing the data includes the mean, Pearson-r, and structural equation model (SEM). Results of the study revealed the following: the level of authentic leadership was very high; the level of workplace spirituality was high; the level of practical emotional intelligence was high; and, the level of work design for teachers was high. Moreover, a significant relationship was established between the exogenous and endogenous variables. In addition, authentic leadership, workplace spirituality, and practical emotional intelligence significantly influence work design for teachers. Of the five (5) generated models, Model 5 best fits work design among public elementary teachers with practical emotional intelligence bringing the biggest impact. The model successfully passed all the conventions of a reasonable fit; hence, it is deemed the most parsimonious model

Community based Sustainable Tourism Development - A tool for fostering and promoting peace: A case study of Odisha, India.

Much has been analyzed, discussed and written about tourism, its interdisciplinary approach and multidimensional concepts, but one of the most significant roles that the tourism has been playing for a while now and which has not come into the limelight is the fostering and promotion of peace. Tourism is regarded as one of the most pioneering sectors, and has not only made socio economic contributions but also created a harmonious platform for all to exchange, share, and understand each other better in order to gain co-operation, mutual understanding, a sense of belonging, and integrity. In the backdrop of a peaceful society where justice, equality, human rights and prosperity stand firm, this is in part due to the remarkable contributions of tourism in assimilating people into a common platform of thought. Society and its people have witnessed socio economic development, the creation of equal opportunities for everyone to live in, and sustainability which to a greater extent has been achieved due to the catalytic nature of tourism which in turn fosters and promotes a peaceful existence. This paper emphasizes and explores the role of tourism in enhancing peace through community based sustainable tourism development by interconnecting the environment, the local community, the tourists, and other important aspects .The paper cites some of the key examples of Odisha in terms of its community participation and their involvement in sustainable development initiatives leading to the harmonious inter-existence between locals and visitors

Challenges and Solution for Identification of Plant Disease Using Machine Learning & IoT

Internet of Thing (IoT) is a groundbreaking technology that has been introduced in the field of agriculture to improve the quality and quantity of food production. As agriculture plays a vital role in feeding most of the world\u27s population, the increasing demand for food has led to a rise in food grain production. The identification of plant diseases is a critical task for farmers and agronomists as it enables them to take proactive measures to prevent the spread of diseases, protect crops, and maximize yields. Traditional methods of plant disease detection involve visual inspections by experts, which can be time-consuming and often subject to human error. However, with technological advancements, IoT and Machine Learning (ML) has emerged as promising solution for automating and improving plant disease identification. This paper explores the challenges and solutions for identifying plant diseases using IoT and ML. The challenges discussed include data collection, quality, scalability, and interpretability. The proposed solutions include using sensor networks, data pre-processing techniques, transfer learning, and explainable AI

The poly-omics of ageing through individual-based metabolic modelling

Abstract Background Ageing can be classified in two different ways, chronological ageing and biological ageing. While chronological age is a measure of the time that has passed since birth, biological (also known as transcriptomic) ageing is defined by how time and the environment affect an individual in comparison to other individuals of the same chronological age. Recent research studies have shown that transcriptomic age is associated with certain genes, and that each of those genes has an effect size. Using these effect sizes we can calculate the transcriptomic age of an individual from their age-associated gene expression levels. The limitation of this approach is that it does not consider how these changes in gene expression affect the metabolism of individuals and hence their observable cellular phenotype. Results We propose a method based on poly-omic constraint-based models and machine learning in order to further the understanding of transcriptomic ageing. We use normalised CD4 T-cell gene expression data from peripheral blood mononuclear cells in 499 healthy individuals to create individual metabolic models. These models are then combined with a transcriptomic age predictor and chronological age to provide new insights into the differences between transcriptomic and chronological ageing. As a result, we propose a novel metabolic age predictor. Conclusions We show that our poly-omic predictors provide a more detailed analysis of transcriptomic ageing compared to gene-based approaches, and represent a basis for furthering our knowledge of the ageing mechanisms in human cells

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

An Awareness towards Greenwashing of Product and its Impact on Consumers’ Buying Behaviour in Surat City

In today’s era Greenwashing refers to the practice of making untruthful or misleading environmental claims about a product or service in order to appeal eco-conscious consumers. The consumer awareness about greenwashing has increased in present-day as people have become more alarmed about the environment and their impact on their buying behaviour. This increased awareness has headed to a change in buying behavior, as consumers are more likely to pursue out those products which are actually environmentally friendly and avoid those that are misleadingly advertised as such. This study aims to study consumers' awareness of green washing and how it creates impact on their purchase behavior. Organizations have keeping in mind their social responsibility concerning for general people and how brands are using this as a strong marketing tactic in intensifying their business. This paper also studies its impact on the environment and the general public. This study was conducted in Surat city. 200 responses were collected over a period of 2 months. Frequency analysis was done in this research paper. Primary data was collected through questionnaire method

Monitoring land use changes associated with urbanization: An object based image analysis approach

Land use/land cover (LULC) change occurs due to natural and anthropogenic causes. In developing countries, rapid industrialization and urbanization imposes a major threat to natural environment. Present study was carried out to monitor the LULC changes due to urbanization in a rapidly changing river basin, India. The purpose of choosing the river basin was to analyze past changes and predict possible consequences within a defined natural boundary. Multi-temporal images acquired from Landsat and Indian Remote Sensing (IRS) satellites between 1992-2009 as well as a digital elevation model was used to generate historical and current LULC pattern in the basin. An object based image analysis technique was employed for precise classification of multi-temporal images followed by GIS-based change detection studies. The study reveals that the built up area has increased significantly and added 288 km(2) between 1992 - 2009. Increase in built up area is attributed to decrease in wastelands and agricultural land. The expansion of built up area along major transportation networks, specifically after the year 2000 shows the rapid rate of urbanization in the basin