The Internal Administration of Lord Lytton, With Special Reference to Social and Economic Policy, 1876-1880.

This is a study of some aspects of Lord Lytton's social and economic policy. Lytton was very anxious to reduce, if not totally abolish, the cotton duties. His anxiety was due primarily to his wish to help the Conservative Party through this tariff reform. Besides, he believed in the economic wisdom of free trade principles. It was "because of his belief in the latter principles that he did not allow any interference in the free play of private trade during the famine in Bombay and Madras. In addition, he wanted the two famines to be managed as economically as possible, for he knew that unless there were a surplus, he could not reduce the cotton duties. This, in its turn, led to much trouble between the Supreme Government and the two Presidency Governments. The chief aim of Lytton's social policy was his belief in the wisdom of befriending the Indian aristocracy. With this purpose in view, he constituted the statutory Civil Service, which was to attract and employ the sons of rich and influential Indians. At the same time, his action in the Puller Case demonstrated that he was not prepared to tolerate the ill-treatment of Indians, especially the lower classes, by the Europeans resident in India. But he was disposed to regard the educated Indians with suspicion, for they were the authors of the semi-seditious articles in the vernacular Press. And to curt this, he passed the Vernacular Press Act. This study is based on Lord Lytton's private papers, as well as on official archives, contemporary newspapers and published books

Cost variation analysis of antimalarial drugs available in India

Background: Malaria has been a problem in India for centuries. There are innumerable brands of antimalarial present in the market. Malaria can be extremely fatal if not treated promptly. Costly drugs can lead to economic burden which results in decreased compliance or even non-compliance. Non-compliance leads to incomplete treatment which tends to increase morbidity. Increase in the patient medication cost was found to be associated with decreased adherence to prescription medication. Hence this study was done to assess the cost variation of malaria therapy.Methods: The maximum and minimum price of each brand of the drug in INR was noted by using CIMS January to April 2017 edition and Drug Today January to March 2017, Vol 2. The cost ratio and the percentage cost variation for individual drug brands was calculated. The cost of 10 tablets was calculated in case of oral drug and the cost of 1 ampoule or vial was noted in case of injectable drug. At last the cost ratio and % cost variation of various brands was compared.Results: The analysis of data reflected a considerable cost variation among antimalarial drugs. Artemether injection showed the highest cost ratio and cost variation (cost ratio = 16.96 and % cost variation = 1596). Overall injectable antimalarials showed considerable cost variation as compared to oral antimalarial agents. Chloroquine which is one of the most used antimalarial showed very low values for cost variation and cost ratio.Conclusions: The analysis showed that there is not much significant price variation among oral antimalarial drugs. The maximum variation shown by oral antimalarial was found to be for fixed dose combination of Artemether and Lumefantrine [cost ratio>2 (2.03) and % price variation >100 (103.7)]. But there was significant price variation among injectable antimalarial. Injectable antimalarials are often the choice of drug when dealing with critically ill malaria patients specially when suffering from complicated malaria. So, such significant price variation creates burden on poor patients economically which leads to non-compliance and hence increased morbidity and mortality due to incomplete treatment

Bio-fuels from biomass

Biofuels are alcohols, ethers, esters and other chemicals made from cellulosic biomass, large portions of municipal solid and industrial wastes. Biofuels are renewable since they are produced from biomass i.e. from organic matter such as plants . Biomass does not add carbon dioxide to the atmosphere as it absorbs the same amount of carbon in growing as it releases when consumed as a fuel. Biomass recycles carbon from the air and spares the use of fossil fuels, reducing the need to pump additional fossil carbon from ground into the atmosphere. Pyrolysis of biomass consists of heating solid biomass in the absence of air to produce solid, liquid and gaseous fuels. In this experimental work rapid pyrolysis of wood and some agricultural residues at high temperature (400ºC – 700ºC) is carried out. The composition of the biomass influences the product distribution. Longer residence time in rapid pyrolysis increases the time for contact between tar and char which makes the char less reactive. The main product obtained by the rapid pyrolysis of wood is bio-oil which acts as an alternative to petroleum products

Quantum Computing Algorithms for Solving Complex Mathematical Problems

The power of quantum mechanics, that is too complex for conventional computers, can be solved by an innovative model of computing known as quantum computing. Quantum algorithms can provide exponential speedups for some types of problems, such as many difficult mathematical ones. In this paper, we review some of the most important quantum algorithms for hard mathematical problems. When factoring large numbers, Shor's algorithm is orders of magnitude faster than any other known classical algorithm. The Grover's algorithm, which searches unsorted databases much more quickly than conventional algorithms, is then discussed. &nbsp

Some relations satisfied by Hermite-Hermite matrix polynomials

summary:The classical Hermite-Hermite matrix polynomials for commutative matrices were first studied by Metwally et al. (2008). Our goal is to derive their basic properties including the orthogonality properties and Rodrigues formula. Furthermore, we define a new polynomial associated with the Hermite-Hermite matrix polynomials and establish the matrix differential equation associated with these polynomials. We give the addition theorems, multiplication theorems and summation formula for the Hermite-Hermite matrix polynomials. Finally, we establish general families and several new results concerning generalized Hermite-Hermite matrix polynomials

Exploring Quantum Machine Learning Algorithms for Enhanced Data Analysis

The rapid increase of records generation throughout diverse domain names has necessitated the development of superior records analysis techniques. Quantum gadget mastering (QML) has emerged as a promising paradigm that harnesses the computational power of quantum systems to beautify information evaluation duties. This studies paper explores the software of quantum machine getting to know algorithms to cope with demanding situations in information analysis, highlighting their capacity for progressed performance and scalability. We provide an overview of key QML algorithms, talk their blessings, and gift case research demonstrating their effectiveness in actual-global statistics evaluation eventualities. Finally, we outline the cutting-edge kingdom of QML research and speak destiny directions for its software in records evaluation

Application of Neural Networks for Avalanche Forecasting

Application of neural networks is investigated for the prediction of avalanches on Chowkibal-Tangdhar road axis in Jammu and Kashmir. The networks are developed and trained monthwiseusing the past snow and weather parameters recorded at the Stage-II Observatory on the axisto generate an assessment of avalanche and non-avalanche activities. Two approaches havebeen considered for training the network. In the first approach, only avalanche activities observedin the axis were taken for training, and in the second approach, along with the observed activities,the opinion of expert forecasters were also considered. The performance of the networks variesfrom 67 to 82 per cent for correct predictions. Winter data for 2001-2002 has been used to validatethe network performance

Critical analysis of classification techniques for polarimetric synthetic aperture radar data

Full polarimetry SAR data known as PolSAR contains information in terms of microwave energy backscattered through different scattering mechanisms (surface-, double- and volume-scattering) by the targets on the surface of land. These scattering mechanisms information is different in different features. Similarly, different classifiers have different capabilities as far as identification of the targets corresponding to these scattering mechanisms. Extraction of different features and the role of classifier are important for the purpose of identifying which feature is the most suitable with which classifier for land cover classification. Selection of suitable features and their combinations have always been an active area of research for the development of advanced classification algorithms. Fully polarimetric data has its own advantages because its different channels give special scattering feature for various land cover. Therefore, first hand statistics HH, HV and VV of PolSAR data along with their ratios and linear combinations should be investigated for exploring their importance vis-à-vis relevant classifier for land management at the global scale. It has been observed that individually first hand statistics yield low accuracies. And their ratios are also not improving the results either. However, improved accuracies are achieved when these natural features are stacked together

Corrosion and Scaling problems with process Cooling Water

Water is the most abundant of our natural resources. Without it, life would perish. Without it, many industrial processes cannot function. some of its important uses are in Air Conditioning and Refrigeration, Diesel Genenating Sets, Air Compressors, Power Plant Condensers, Chemical Plants, Heat Exchangers, Furnaces, Steel Plants, etc. In effect, today the process cooling water in any modern Industry, is as essential as the raw material