Visualizing Google Scholar Profile of Dr. S.R. Ranganathan using PoP and VOSviewer: a tribute to Father of Library Science in India

Dr. Shiyali Ramamrita Ranganathan was the well-known librarian and mathematician from India. He was also called the father of Indian librarianship. He made India library conscious in particular and he influenced the thinking of library world in general. It is mainly because of his efforts that library & information science became a subject of study and research. Dr S.R. Ranganathan has recorded 307 publications since 1931 including his contributed books, book chapters, reports, and journal articles, texts of invited speeches or special lecture. He received a total of 5455 citations with h-index 27. Highest citations (306) were received in the year 2017. Also, it was observed, “The Five Laws of Library Science” published in the year 1931 received highest citation 1213. Most of his collaborative works or articles in total, are with Neelameghan, A and Gopinath, M A

Oral Sustained Release Tablets: An Overview With A Special Emphasis On Matrix Tablet

Among the various routes of drug delivery, oral route is the most preferred route. But conventional dosage form offers a few limitations which could be resolved by modifying the existing dosage form. Sustained and controlled drug delivery system helps in the maintenance of constant plasma drug concentration and retards the release rate of drug, thereby extending the duration of action. There are various formulation strategies for sustained-release tablets, among which matrix tablet serves as an important tool. Hence the problem like poor patient compliance, multiple dosing, see-saw fluctuations can be easily minimized. Matrix tablets can be formulated by either direct compression or wet granulation method by using a variety of hydrophilic or hydrophobic polymers. The rate of drug release from the matrix is primarily governed by rate and extent of water penetration, swelling of polymer, dissolution, and diffusion of the drug. Thus, a sustained release matrix tablet can offer better patient compliance and could be quite helpful in the treatment of chronic diseases. The present article concentrates on oral sustained-release tablets with a special emphasis on matrix tablets

Detection of Breast Cancer using AI Techniques – A Survey

Cancer refers to any one of a large number of diseases characterized by the development of abnormal cells that divide uncontrollably and have the ability to infiltrate and destroy normal body tissue.Without treatment, it can cause serious health issues andresult in a loss of life. Breast cancer is the most common cancer among women around the world. Despite enormous medical progress, breast cancer has still remained the second leading cause of death worldwide. Early detection of cancer may reduce mortality and morbidity. This paper presents a review of the detection methods for cancer through Artificial Intelligence (AI) in different ways. Previously Microscopic reviews of tissues on glass slides are used for cancer diagnostics to improve diagnostic accuracy. We can use different techniques such as digital imaging and artificial intelligence algorithm. Cancer care is also advancing thanks to AI’s ability to collect and process data. Due to the nature of processing this information, the task is often a time-consuming and tedious job for doctors. This process may be made much easier, quicker and efficient through the advancement as well as by using modified technologies

Bankrupting Sybil Despite Churn

A Sybil attack occurs when an adversary pretends to be multiple identities (IDs). Limiting the number of Sybil (bad) IDs to a minority permits the use of well-established tools for tolerating malicious behavior, such as protocols for Byzantine consensus and secure multiparty computation. A popular technique for enforcing this minority is resource burning; that is, the verifiable consumption of a network resource, such as computational power, bandwidth, or memory. Unfortunately, prior defenses require non-Sybil (good) IDs to consume at least as many resources as the adversary, unless the rate of churn for good IDs is sufficiently low. Since many systems exhibit high churn, this is a significant barrier to deployment. We present two algorithms that offer useful guarantees against Sybil adversary under a broadly-applicable model of churn. The first is GoodJEst, which estimates the number of good IDs that join the system over any window of time, despite the adversary injecting bad IDs. GoodJEst applies to a broad range of system settings, and we demonstrate its use in our second algorithm, a new Sybil defense called ERGO. Even under high churn, ERGO guarantee (1) there is always a minority of bad IDs in the system; and (2) when the system is under attack, the good IDs burn resources at a total rate that is sublinear in the adversary's consumption. To evaluate the impact of our theoretical results, we investigate the performance of ERGO alongside prior defenses that employ resource burning. Based on our experiments, we design heuristics that further improve the performance of ERGO by up to four orders of magnitude over these previous Sybil defenses.Comment: 41 pages, 6 figures. arXiv admin note: text overlap with arXiv:2006.02893, arXiv:1911.0646

DIFFERENT MODELS TO EVALUATE ANTIMICROBIAL AGENTS-A REVIEW

Antimicrobial models have played a critical role in the history of modern drug development for microbial infections. Such antimicrobial models complement human investigations to study in detail pathogenic hypothesis and therapeutic strategies. To achieve this several new screening models have been produced. Various methods have been used for this purpose by using several microbes on different culture media. Such methods would help to provide new antimicrobial agents for the treatment of various microbial diseases of human. The present study therefore is focused on the review of such antimicrobial models

On the Power of Choice for k-Colorability of Random Graphs

In an r-choice Achlioptas process, random edges are generated r at a time, and an online strategy is used to select one of them for inclusion in a graph. We investigate the problem of whether such a selection strategy can shift the k-colorability transition; that is, the number of edges at which the graph goes from being k-colorable to non-k-colorable. We show that, for k ? 9, two choices suffice to delay the k-colorability threshold, and that for every k ? 2, six choices suffice