On Multi-Objective Minimum Spanning Tree Problem under Uncertain Paradigm

Minimum spanning tree problem (MSTP) has allured many researchers and practitioners due to its varied range of applications in real world scenarios. Modelling these applications involves the incorporation of indeterminate phenomena based on their subjective estimations. Such phenomena can be represented rationally using uncertainty theory. Being a more realistic variant of MSTP, in this article, based on the principles of the uncertainty theory, we have studied a multi-objective minimum spanning tree problem (MMSTP) with indeterminate problem parameters. Subsequently, two uncertain programming models of the proposed uncertain multi-objective minimum spanning tree problem (UMMSTP) are developed and their corresponding crisp equivalence models are investigated, and eventually solved using a classical multi-objective solution technique, the epsilon-constraint method. Additionally, two multi-objective evolutionary algorithms (MOEAs), non-dominated sorting genetic algorithm II (NSGAII) and duplicate elimination non-dominated sorting evolutionary algorithm (DENSEA) are also employed as solution methodologies. With the help of the proposed UMMSTP models, the practical problem of optimizing the distribution of petroleum products was solved, consisting in the search for symmetry (balance) between the transportation cost and the transportation time. Thereafter, the performance of the MOEAs is analyzed on five randomly developed instances of the proposed problem.

Effect of Shear/Axial Stress Ratio on Multiaxial Non-Proportional Loading Fatigue Damage on AISI 303 Steel

In this paper, we investigate the cyclic response of AISI 303 stainless steel subjected to non-proportional loads with different amplitude ratios between shear stresses and normal stresses. Based on the experiments, a relationship between the proportional reference load and a varied range of non-proportional loads was established. To achieve this objective, an experimental program was implemented to evaluate the non-proportional parameter Y. Then, the evolution of this parameter was analyzed with the number of cycles to failure and with the ratio between shear and normal stresses, finally, the evolution of the non-proportional parameter Y was mapped by two functions. The results show that the non-proportional response of the AISI 303 can be estimated using the two functions obtained. This allows the estimation of the relationship between non-proportional and proportional stresses as a function of the number of cycles to failure together with the relationship between shear and normal stresses. The results obtained have direct application in the evaluation of accumulated damage, assessed in real-time, resulting from variable amplitude loading spectra. This is of particular interest for the evaluation of structural health monitoring of structures and mechanical components.

Effect of Zinc Sources on Nutrient Content and Uptake in Soybean [Glycine max (L.) Merril] under the Acidic Soil Conditions of Nagaland

Background: Soybean is an important legume as well as oil seed crop grown in a varied range of climate and soils. Zinc is an important micronutrient required for plants, animals and human. Its deficiency in soil is a worldwide concern for production of food crops. Therefore two years reseach in two locations were conducted in 2019 and 2020 to study the nutrient content and uptake of NPK and Zn in soybean with zinc fertilization. Methods: A two years research was conducted in two locations under the acidic soil conditions of Nagaland. Nutrient content and uptake of N, P, K and Zn were recorded at first, second year and pooled. The location, climate, altitude and soil fertility status were recorded in both the sites. Altogether there were 13 treatments and 3 replications.The experimental design used was simple RBD. The datas were recorded, analysed and computed statistically. Result: The nutrient uptake of N, K and Zn except P in soybean were significantly found to be increased @ 5 kg ha-1 ZnSO4 H2O + RDF (T9) followed by T8 and T10 as compared to control in both the years and pooled.

Evolutionary traits of Tick-borne encephalitis virus: Pervasive non-coding RNA structure conservation and molecular epidemiology

Tick-borne encephalitis virus (TBEV) is the etiological agent of tick-borne encephalitis, an infectious disease of the central nervous system that is often associated with severe sequelae in humans. While TBEV is typically classified into three subtypes, recent evidence suggests a more varied range of TBEV subtypes and lineages that differ substantially in their 3'UTR architecture. Building on comparative genomics approaches and thermodynamic modeling, we characterize the TBEV 3'UTR structureome diversity and propose a unified picture of pervasive non-coding RNA (ncRNA) structure conservation. Moreover, we provide an updated phylogeny of TBEV, building on more than 220 publicly available complete genomes, and investigate the molecular epidemiology and phylodynamics with Nextstrain, a web-based visualization framework for real-time pathogen evolution.

Exploring the preconception of the first year of medical students on medicine before entering medical school

Purpose: First-year students can form a preconception based on life experiences before entering college and identifying learners’ existing characteristics can be useful foundation data for curriculum development. This study examines what preconceptions freshman students had about medicine before entering medical school.Methods: A total of 110 first-year students were asked about what preconceptions they had about “medicine”. A total of 1,124 data were used in the content analysis method.Results: The results were extracted into 5, and 12 twelve categories. On the theme of “scientific discipline”, the knowledge students had about general health was based on scant expertise and little evidence. Students perceived medicine as Western and scientific, considering Korean traditional medicine as unscientific. Students believed that “medical practice” should be a “disease treatment” and “patient-centered” approach rather than a “social responsibility”. In “the role of the doctor”, students were concerned about the doctor's being financially stable on the positive side, and about the high-intensity workload on the negative side. In “medical education”, students believed that studying medicine would be “hard and difficult” because of the “importance of memorizing” and “extensive study load”. In “specialty stereotype”, students had biases that were mostly concentrated on “psychiatry” and “surgery”Conclusion: Perception of “medicine” has been revealed to a varied range of themes, but some have been inaccurate or unrealistic. These prejudices and groundless beliefs have a gap with the learning outcomes that students should achieve in the curriculum, and these preconceptions seem to have been influenced by South Korea’s unique cultural context.

Historicizing Fashion: Clothing, Culture, and Chores

The present paper is a study on the history of clothing in ancient India to historicize fashion in the Ancient Indian context. Relying primarily on textual sources of the period The Kāmasūtra of Vatsyayana ( 4-5th CE) and The Nātyaśāstra of Bharata (200 BCE-200CE), the paper seeks to examine the implications on patterns of dressing: clothing and accessorizing on different social categories based on gender, class, and caste being governed by the power relations operating within the social milieu of the texts. By looking at varied range of social and gendered categories the essence of clothing and dressing has been observed and commented upon. It has been primarily argued that dressing patterns reveal homogeneity in a particular group, who were part of a heterogeneous whole.

The Devadasis, Dance Community of South India: A Legal and Social Outlook

The devadasi community of south India are originators of a popular dance form called bharatanatyam. This paper explores several dimensions of this community including legal and social angles. A misjudged and misunderstood community, the modern-day devadasi’s circumstances can be described as fraught with social disabilities ranging from a lack of economic opportunities and the resultant poverty to an increased propensity for delinquency. The paper presents an unbiased view of the history of the devadasi system that attempts to use a varied range of sources so as to paint a clear narrative. The paper proposes a mechanism to move forward through truth commissions as a form of restorative justice that is likely to help both policymakers as well as artists.

Assessing the societal value of a service-learning project in information studies during the COVID-19 pandemic

The purpose of this work is to assess the societal value of a Service-Learning (SL) project carried out during the Covid-19 pandemic by the Faculty of Information Science of the *⁣** University of *⁣** in collaboration with two Senior Centers of the City of *⁣**. The aim of the project was to support elderly’s integration in the online activities carried out during the Covid-19 pandemic and to train them in the use of Information and Communication Technologies (ICT). The analysis of societal value is based on a case study and a varied range of data whose purpose is to provide multiple insights into the experience, emphasizing communicative processes. The results corroborate the educational value of experiential learning for students, although the impact on the community appears limited by the role of consumers of a service that participating elderly ended up playing. The evaluation of the project by the faculty leading the activities was corroborated by the institutional partner and provides evidence of the capacity for societal transformation of higher education institutions.

AKSELERASI PENGEMBANGAN AGRIBISNIS, KELEMBAGAAN KEMITRAAN IMPLEMENTASI MEWUJUDKAN PENSEJAHTERAAN PETANI HORTIKULTURA

For farmers, the partnership relationship has great benefits, which are relatively stable with market certainty. While the benefits for partners are the certainty of obtaining raw materials in accordance with the required specifications. Using a qualitative description method, this paper aims to examine and present the conditions and institutional performance of the processing industry partnership in the marketing of horticultural products. Market certainty is the hope and main goal of farmers in pursuing each of their farming activities, in addition to obtaining maximum yields of course. Various agro-industry business actors, directly or indirectly in the procurement of raw materials, mostly still come from traders/suppliers. In a cooperative partnership relationship, farmer groups / farmer group associations are more burdened with obligations while their rights are still limited. The benefits of studying marketing partnership institutions and their development perspectives related to efforts to accelerate and implement agribusiness development to improve the welfare of their farmers, of course, are needed, especially as a liaison between farmers and users of their farm products. The perspective of partnership development is still very open, among others due to: (a) both parties obtain mutually beneficial benefits; (b) demand for processed products is increasing along with population growth. Institutional partnerships act as partners to market farm production in a wider and varied range. The partners are indicated to continue to provide the opportunity to sell to the free market if the price is better.

Machine Learning Approach to Estimate the Diffusion Coefficient of CO2 in Hydrocarbons

Diffusion of the gas into the liquids is a critical part in understanding multiphase systems and engineering applications associated with these multiphase systems. The study couples multiphase pendant drop experiments and computational modelling to calculate the CO2 diffusion coefficient in n-decane. Experiments were carried out at a varied range of pressure and temperature 25–45°C and 25–65 bar. During the experiments, the change in the volume of the hydrocarbon drop due to CO2 diffusion was dynamically measured, and numerical model was developed which used the experimental data to estimate the diffusion coefficient. The current study brings in the capability of machine learning as a replacement of the computational part for prediction of the diffusion coefficient of the process. The feasibility of various machine learning models such as Gradient boosting, Gaussian Process Regression (GPR), k-NN, Decision tree etc. are checked. Firstly different algorithms were trained on the dataset and finally evaluated on the test dataset, using various statistical metrics). Finally, the most accurate algorithm is used as a surrogate model for predicting the diffusion coefficient. The chosen ML algorithm was fairly accurate in predicting the diffusion coefficient with a maximum inaccuracy of 7.5%. Therefore, ML may then be employed as an alternative to experiments and numerical methods. A case study is performed to demonstrate the proposed methodology.