Design of PVT System for Typical Indian Village and its Analysis for the Reduction of Co2 Emission

This dissertation work outline is that by using Solar Photovoltaic (SPV) System in typical Indian villages, how we can remove the CO2 emissions. Requirement of PVT system is calculated according to the actual energy demand of a village population and its impact on CO2 reduction is assessed. It is, therefore, important to consider the possibility of utilizing the renewable energy resources, which do not degrade the environment. It is a well-known fact that the average living standard of rural population is lower than that of urban population. One way of improving the living standards is to provide better energy facilities. This will also check the migration of population from rural to urban area. This migration causes social and economic imbalances and is, there on, not desirable

E-Classroom for an Underserved Institution

The E-Class Room system is a web based project. An educational institution in India is understaffed and has limited interaction among faculty, student and industry experts. The project is to provide an online platform for the students and faculty of the institution to enhance their educational needs and to share their learning with their fellow students, faculty or industrial experts. It aims to provide a platform for mutual cooperation between different kinds of learning. The new system will provide directional way for online learning between faculty, student and industrial experts

Mishandling of COVID-19 Pandemic: A Challenge to the International Order

The paper examines the mishandling of the COVID-19 pandemic, and the extent to which it had affected the international order, particularly where it had exposed the contradictions, injustices, and fragility of the order. The sacrifices needed to be made by the great powers were not made during the pandemic for the international system to maintain its balance and provide the support needed by the global south, as many of the weaker states found it difficult to survive, while elitism on the part of the global north had its day. The paper, through the document and thematic analysis, found that the marketization of the international system has impacted the ethics of life and death, deciding who is to live and who is to die, when and even how? Another key finding is the depiction by COVID-19 of human hierarchies that the liberal international system fails to consider, thus challenging the claim that sacrifices are made in support of the system by the developed world. In the context of the foregoing, the paper recommends that the current international order should be restructured with a view to addressing the lopsidedness, gaps, and inequalities to make the world balanced and more just, in accordance with the liberal norms and value

The Russia-Ukraine War: Shaking the Foundation of the Global System

After several months of posturing, the Russian army was stationed on the Ukrainian border, and the Kremlin denying any intention to invade or attack Ukraine, and the west kept escalating the situation. The world experienced a crucial moment on the 24th of February; when the Russian President, Vladimir Putin announced a special military operation against Ukraine. Since the eruption of the war, it has continued until this moment without cessation of hostilities or its stoppage, as diplomatic efforts have thus far not brought an end to it. Several global actors were involved in this crisis and the outcome of this war is going to have a major impact on the entire globe. This paper examines who handles this crisis and the implications of it for the International System, politically and economically. The paper, through the qualitative research framework, particularly document analysis and thematic analysis, secondary data were collected from academic works relevant to the paper, which were logically and thematically analyzed. The findings include disruption to the relative stability of the international system, changing global and regional geopolitical calculations and slower global economic growth and development. The paper recommends that urgent steps and strategies should be taken by the international community, especially the most influential state and non-state actors to bring a swift end to the ongoing Russia�Ukraine war

WISER: Weak supervISion and supErvised Representation learning to improve drug response prediction in cancer

Cancer, a leading cause of death globally, occurs due to genomic changes and manifests heterogeneously across patients. To advance research on personalized treatment strategies, the effectiveness of various drugs on cells derived from cancers (`cell lines') is experimentally determined in laboratory settings. Nevertheless, variations in the distribution of genomic data and drug responses between cell lines and humans arise due to biological and environmental differences. Moreover, while genomic profiles of many cancer patients are readily available, the scarcity of corresponding drug response data limits the ability to train machine learning models that can predict drug response in patients effectively. Recent cancer drug response prediction methods have largely followed the paradigm of unsupervised domain-invariant representation learning followed by a downstream drug response classification step. Introducing supervision in both stages is challenging due to heterogeneous patient response to drugs and limited drug response data. This paper addresses these challenges through a novel representation learning method in the first phase and weak supervision in the second. Experimental results on real patient data demonstrate the efficacy of our method (WISER) over state-of-the-art alternatives on predicting personalized drug response.Comment: ICML 202

A comparative study of eggshell and commercial sorbent-based catalysts through synthesis and characterization for SESR process.

Hydrogen is a clean and valuable energy carrier, and there is growing consensus that a hydrogen-based economy could be the key to ensuring the long-term reliability and environmental friendliness of the world's energy supply. There are a variety of methods and technologies that may be used to produce hydrogen; among them, sorption-enhanced steam reforming is regarded as the way that is the most effective. For the purpose of making a decision about which catalysts to employ in SESR in the future, this study compared three distinct kinds of catalysts. The wet impregnation method was used to manufacture the waste-derived CaO-implemented Ni-based catalysts, which were then used in sorption-enhanced steam reforming (SESR) to produce hydrogen (H2). X-ray diffractometry (XRD), field emission scanning electron microscopy (FESEM), and thermogravimetric analyses (TGA) were used to analyze the catalysts. XRD results showed that the crystallinity behavior for all types of catalysts such as 10NMA, 10NCMA-E, and 10NCMA was identical. The spinel compounds such as NiAl2O4 and MgAl2O4 were identified in all three types of catalysts. At high temperatures, such as at 800°C, all catalysts were stable, evident from TGA results. During three sorption cycles, the 10NCMA-based catalyst demonstrated the highest sorption capacity among the three varieties of catalysts, followed by the 10NCMA-E catalyst. During the first, second, and third calcination cycles, the 10NCMA-based catalyst released 23.88%, 22.05%, and 23.33% CO2, respectively. 10NCMA-E can be a potential catalyst for the SESR process by decreasing the material manufacturing cost and overall cost of the SESR process

Determination of the anti-polo like kinase 1 potential of novel derivatives of thiophene using oncoinformatics approach

Purpose: To explore the anticancer mechanistic aspect of thiophene derivatives via targeting Polo like kinase 1 (PLK1). Methods: The PLK1 enzyme is primarily expressed in cancer cells, and blocking its active site is one of the plausible ways to target cancer. Thus, in the present study, the thiophene derivatives were tested against PLK1 by molecular docking approach. Results: Thiophene derivatives, named 8A, 8B and 14, exhibited better interactions with PLK1 active site than the positive control, doxorubicin. Molecular docking experiments revealed that 8A, 8B and 14 interacted efficiently with PLK1, and demonstrated binding energy and inhibition constant scores of ꞌ- 8.02 kcal/mol and 1.33 μMꞌ, ꞌ-8.65 kcal/mol and 0.454 μMꞌ and ꞌ-8.33 kcal/mol and 0.788 μMꞌ, respectively. In contrast, doxorubicin-PLK1 interaction had binding energy of -7.95 kcal/mol and inhibition constant of 2.75 μM. Conclusion: These results predict that thiophene derivatives 8A, 8B and 14 might exert anticancer effect by inhibiting PLK1 activity. Although, wet lab experiments are required to validate the data, however, these results may pave the way for the development of novel PLK1 inhibitors for anticancer therapy

Glycerol Conversion to Diglycerol via Etherification under Microwave Irradiation

According to Grand View Research in polyglycerol market size, demand for diglycerol is expected to grow by 50% from 2012 to 2022 due to its extensive use in various industries, thus validating the importance and value addition of producing diglycerol. Due to the volatility of refined glycerine market price and increasing demand of diglycerol, research has been conducted to upgrade glycerol via various processes. Etherification is a single-step process of catalytic conversion of glycerol into polyglycerols, involving the condensation of two glycerol molecules to form the simplest oligomer which is diglycerol with linear, branched, or cyclic isomers. Thus, this chapter will discuss on the methods of synthesizing diglycerol followed by the type of catalyst to be used. These include homogenous and heterogenous catalyst with their subdivision of acid and base type, respectively. Besides, this chapter does include on the method for the etherification process where it highlighted the advantage of advance technology microwave irradiation over conventional heating

Optimizing Prediction of YouTube Video Popularity Using XGBoost

YouTube is a source of income for many people, and therefore a video’s popularity ultimately becomes the top priority for sustaining a steady income, provided that the popularity of videos remains the highest. Analysts and researchers use different algorithms and models to predict the maximum viewership of popular videos. This study predicts the popularity of such videos using the XGBoost model, considering features selection, fusion, min-max normalization and some precision parameters such as gamma, eta, learning_rate etc. The XGBoost gives 86% accuracy and 64% precision. Moreover, the Tuned XGboost also shows enhanced accuracy and precision. We have also analyzed the classification of unpopular videos for a comparison with our results. Finally, cross-validation methods are also used to evaluate certain combination of parameter’s values to validate our claims. Based on the obtained results, it can be said that our proposed models and techniques are very useful and can precisely and accurately predict the popularity of YouTube videos