Birla Institute of Technology and Science, Pilani

Abstract: SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

Abstract The Astropy Project supports and fosters the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package astropy , which serves as the foundation for more specialized projects and packages. In this article, we provide an overview of the organization of the Astropy project and summarize key features in the core package, as of the recent major release, version 2.0. We then describe the project infrastructure designed to facilitate and support development for a broader ecosystem of interoperable packages. We conclude with a future outlook of planned new features and directions for the broader Astropy Project.

Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely. An important impediment to the widespread adoption of Bayesian tests is arguably the lack of user-friendly software for the run-of-the-mill statistical problems that confront psychologists for the analysis of almost every experiment: the t-test, ANOVA, correlation, regression, and contingency tables. In Part II of this series we introduce JASP ( http://www.jasp-stats.org ), an open-source, cross-platform, user-friendly graphical software package that allows users to carry out Bayesian hypothesis tests for standard statistical problems. JASP is based in part on the Bayesian analyses implemented in Morey and Rouder's BayesFactor package for R. Armed with JASP, the practical advantages of Bayesian hypothesis testing are only a mouse click away.

Abstract Recent years have seen a tremendous growth in Artificial Intelligence (AI)-based methodological development in a broad range of domains. In this rapidly evolving field, large number of methods are being reported using machine learning (ML) and Deep Learning (DL) models. Majority of these models are inherently complex and lacks explanations of the decision making process causing these models to be termed as 'Black-Box'. One of the major bottlenecks to adopt such models in mission-critical application domains, such as banking, e-commerce, healthcare, and public services and safety, is the difficulty in interpreting them. Due to the rapid proleferation of these AI models, explaining their learning and decision making process are getting harder which require transparency and easy predictability. Aiming to collate the current state-of-the-art in interpreting the black-box models, this study provides a comprehensive analysis of the explainable AI (XAI) models. To reduce false negative and false positive outcomes of these back-box models, finding flaws in them is still difficult and inefficient. In this paper, the development of XAI is reviewed meticulously through careful selection and analysis of the current state-of-the-art of XAI research. It also provides a comprehensive and in-depth evaluation of the XAI frameworks and their efficacy to serve as a starting point of XAI for applied and theoretical researchers. Towards the end, it highlights emerging and critical issues pertaining to XAI research to showcase major, model-specific trends for better explanation, enhanced transparency, and improved prediction accuracy.

The Internet of Things (IoT) is the next era of communication. Using the IoT, physical objects can be empowered to create, receive, and exchange data in a seamless manner. Various IoT applications focus on automating different tasks and are trying to empower the inanimate physical objects to act without any human intervention. The existing and upcoming IoT applications are highly promising to increase the level of comfort, efficiency, and automation for the users. To be able to implement such a world in an ever-growing fashion requires high security, privacy, authentication, and recovery from attacks. In this regard, it is imperative to make the required changes in the architecture of the IoT applications for achieving end-to-end secure IoT environments. In this paper, a detailed review of the security-related challenges and sources of threat in the IoT applications is presented. After discussing the security issues, various emerging and existing technologies focused on achieving a high degree of trust in the IoT applications are discussed. Four different technologies, blockchain, fog computing, edge computing, and machine learning, to increase the level of security in IoT are discussed.

The most widely used methods for transdermal administration of the drugs are hypodermic needles, topical creams, and transdermal patches. The effect of most of the therapeutic agents is limited due to the stratum corneum layer of the skin, which serves as a barrier for the molecules and thus only a few molecules are able to reach the site of action. A new form of delivery system called the microneedles helps to enhance the delivery of the drug through this route and overcoming the various problems associated with the conventional formulations. The primary principle involves disruption of the skin layer, thus creating micron size pathways that lead the drug directly to the epidermis or upper dermis region from where the drug can directly go into the systemic circulation without facing the barrier. This review describes the various potential and applications of the microneedles. The various types of microneedles can be fabricated like solid, dissolving, hydrogel, coated and hollow microneedles. Fabrication method selected depends on the type and material of the microneedle. This system has increased its application to many fields like oligonucleotide delivery, vaccine delivery, insulin delivery, and even in cosmetics. In recent years, many microneedle products are coming into the market. Although a lot of research needs to be done to overcome the various challenges before the microneedles can successfully launch into the market.

The unprecedented outbreak of the 2019 novel coronavirus, termed as COVID-19 by the World Health Organization (WHO), has placed numerous governments around the world in a precarious position. The impact of the COVID-19 outbreak, earlier witnessed by the citizens of China alone, has now become a matter of grave concern for virtually every country in the world. The scarcity of resources to endure the COVID-19 outbreak combined with the fear of overburdened healthcare systems has forced a majority of these countries into a state of partial or complete lockdown. The number of laboratory-confirmed coronavirus cases has been increasing at an alarming rate throughout the world, with reportedly more than 3 million confirmed cases as of 30 April 2020. Adding to these woes, numerous false reports, misinformation, and unsolicited fears in regards to coronavirus, are being circulated regularly since the outbreak of the COVID-19. In response to such acts, we draw on various reliable sources to present a detailed review of all the major aspects associated with the COVID-19 pandemic. In addition to the direct health implications associated with the outbreak of COVID-19, this study highlights its impact on the global economy. In drawing things to a close, we explore the use of technologies such as the Internet of Things (IoT), Unmanned Aerial Vehicles (UAVs), blockchain, Artificial Intelligence (AI), and 5G, among others, to help mitigate the impact of COVID-19 outbreak.

Purpose – The advent of recession at the beginning of twenty-first century forced many organizations worldwide to reduce cost and to be more responsive to customer demands. Lean Manufacturing (LM) has been widely perceived by industry as an answer to these requirements because LM reduces waste without additional requirements of resources. This led to a spurt in LM research across the globe mostly through empirical and exploratory studies which resulted in a plethora of LM definitions with divergent scopes, objectives, performance indicators, tools/techniques/methodologies, and concepts/elements. The purpose of this paper is to review LM literature and report these divergent definitions, scopes, objectives, and tools/techniques/methodologies. Design/methodology/approach – This paper highlights various definitions by various researchers and practitioners. A total of 209 research papers have been reviewed for the research contribution, research methodology adopted, tools/techniques/methodologies used, type of industry, author profile, country of research, and year of publication. Findings – There are plethora of LM definitions with divergent objectives and scope. Theory verification through empirical and exploratory studies has been the focus of research in LM. Automotive industry has been the focus of LM research but LM has also been adopted by other types of industries also. One of the critical implementation factors of LM is simultaneous adoption of leanness in supply chain. LM has become an integrated system composed of highly integrated elements and a wide variety of management practices. There is lack of standard LM implementation process/framework. Originality/value – The paper reviews 209 research papers for their research contribution, research methodology, author profile, type of industry, and tools/techniques/methodology used. Various characteristics of LM definitions are also reviewed.

In recent years, nanobiotechnology has emerged as an elementary division of modern science and a noval epoch in the fields of material science and is receiving global attention due to its ample applications. Various physical, chemical, and biological methods have been employed to synthesize nanomaterials. Biological systems such as bacteria, fungi, actinomycetes, yeasts, viruses, and plants have been reported to synthesize various metal and metal oxide nanoparticles. Among these, biosynthesis of nanoparticles from plants seems to be a very effective method in developing a rapid, clean, nontoxic, and eco-friendly technology. The use of plant biomass or extracts for the biosynthesis of novel metal nanoparticles (silver, gold, platinum, and palladium) would be more significant if the nanoparticles are synthesized extracellularly and in a controlled manner according to their dispersity of shape and size. Owing to the rich biodiversity of plants, their potential use toward the synthesis of these nobel metal nanoparticles is yet to be explored. The aim of this review is to provide the recent trends involved in the phytosynthesis of nobel metal nanoparticles in the past decade.

Breast cancer has ranked number one cancer among Indian females with age adjusted rate as high as 25.8 per 100,000 women and mortality 12.7 per 100,000 women. Data reports from various latest national cancer registries were compared for incidence, mortality rates. The age adjusted incidence rate of carcinoma of the breast was found as high as 41 per 100,000 women for Delhi, followed by Chennai (37.9), Bangalore (34.4) and Thiruvananthapuram District (33.7). A statistically significant increase in age adjusted rate over time (1982-2014) in all the PBCRs namely Bangalore (annual percentage change: 2.84%), Barshi (1.87%), Bhopal (2.00%), Chennai (2.44%), Delhi (1.44%) and Mumbai (1.42%) was observed. Mortality-to-incidence ratio was found to be as high as 66 in rural registries whereas as low as 8 in urban registries. Besides this young age has been found as a major risk factor for breast cancer in Indian women. Breast cancer projection for India during time periods 2020 suggests the number to go as high as 1797900. Better health awareness and availability of breast cancer screening programmes and treatment facilities would cause a favorable and positive clinical picture in the country.

In the present work, we report compilation and analysis of 245 drugs, including small and macromolecules approved by the U.S. FDA from 2015 until June 2020. Nearly 29% of the drugs were approved for the treatment of various types of cancers. Other major therapeutic areas of focus were infectious diseases (14%); neurological conditions (12%); and genetic, metabolic, and cardiovascular disorders (7-8% each). Itemization of the approved drugs according to the year of approval, sponsor, target, chemical class, major drug-metabolizing enzyme(s), route of administration/elimination, and drug-drug interaction liability (perpetrator or/and victim) is presented and discussed. An effort has been made to analyze the pharmacophores to identify the structural (e.g., aromatic, heterocycle, and aliphatic), elemental (e.g., boron, sulfur, fluorine, phosphorus, and deuterium), and functional group (e.g., nitro drugs) diversity among the approved drugs. Further, descriptor-based chemical space analysis of FDA approved drugs and several strategies utilized for optimizing metabolism leading to their discoveries have been emphasized. Finally, an analysis of drug-likeness for the approved drugs is presented.

Flaxseed is emerging as an important functional food ingredient because of its rich contents of α-linolenic acid (ALA, omega-3 fatty acid), lignans, and fiber. Flaxseed oil, fibers and flax lignans have potential health benefits such as in reduction of cardiovascular disease, atherosclerosis, diabetes, cancer, arthritis, osteoporosis, autoimmune and neurological disorders. Flax protein helps in the prevention and treatment of heart disease and in supporting the immune system. As a functional food ingredient, flax or flaxseed oil has been incorporated into baked foods, juices, milk and dairy products, muffins, dry pasta products, macaroni and meat products. The present review focuses on the evidences of the potential health benefits of flaxseed through human and animals' recent studies and commercial use in various food products.

Th antibacterial activity of metal oxide nanoparticles has received marked global attention as they can be specifically synthesized to exhibit significant toxicity to bacteria. The importance of their application as antibacterial agents is evident keeping in mind the limited range and effectiveness of antibiotics, on one hand, and the plethora of metal oxides, on the other, along with the propensity of nanoparticles to induce resistance being much lower than that of antibiotics. Effective inhibition against a wide range of bacteria is well known for several nano oxides consisting of one metal (Fe3O4, TiO2, CuO, ZnO), whereas, research in the field of multi-metal oxides still demands extensive exploration. This is understandable given that the relationship between physicochemical properties and biological activity seems to be complex and difficult to generalize even for metal oxide nanoparticles consisting of only one metal component. Also, despite the broad scope that metal oxide nanoparticles have as antibacterial agents, there arise problems in practical applications taking into account the cytotoxic effects. In this respect, the consideration of polymetallic oxides for biological applications becomes even greater since these can provide synergetic effects and unify the best physicochemical properties of their components. For instance, strong antibacterial efficiency specific of one metal oxide can be complemented by non-cytotoxicity of another. This review presents the main methods and technological advances in fabrication of nanostructured metal oxides with a particular emphasis to multi-metal oxide nanoparticles, their antibacterial effects and cytotoxicity.

Nanoparticles as drug delivery system have received much attention in recent years, especially for cancer treatment. In addition to improving the pharmacokinetics of the loaded poorly soluble hydrophobic drugs by solubilizing them in the hydrophobic compartments, nanoparticles allowed cancer specific drug delivery by inherent passive targeting phenomena and adopted active targeting strategies. For this reason, nanoparticles-drug formulations are capable of enhancing the safety, pharmacokinetic profiles and bioavailability of the administered drugs leading to improved therapeutic efficacy compared to conventional therapy. The focus of this review is to provide an overview of various nanoparticle formulations in both research and clinical applications with a focus on various chemotherapeutic drug delivery systems for the treatment of cancer. The use of various nanoparticles, including liposomes, polymeric nanoparticles, dendrimers, magnetic and other inorganic nanoparticles for targeted drug delivery in cancer is detailed.

Large language models have recently been shown to attain reasonable zero-shot generalization on a diverse set of tasks (Brown et al., 2020). It has been hypothesized that this is a consequence of implicit multitask learning in language models' pretraining (Radford et al., 2019). Can zero-shot generalization instead be directly induced by explicit multitask learning? To test this question at scale, we develop a system for easily mapping any natural language tasks into a human-readable prompted form. We convert a large set of supervised datasets, each with multiple prompts with diverse wording. These prompted datasets allow for benchmarking the ability of a model to perform completely held-out tasks. We fine-tune a pretrained encoder-decoder model (Raffel et al., 2020; Lester et al., 2021) on this multitask mixture covering a wide variety of tasks. The model attains strong zero-shot performance on several standard datasets, often outperforming models up to 16x its size. Further, our approach attains strong performance on a subset of tasks from the BIG-bench benchmark, outperforming models up to 6x its size. All trained models are available at https://github.com/bigscience-workshop/t-zero and all prompts are available at https://github.com/bigscience-workshop/promptsource.

Betulinic acid is a naturally occurring pentacyclic triterpenoid and has been shown to exhibit a variety of biological activities including inhibition of human immunodeficiency virus (HIV), antibacterial, antimalarial, antiinflammatory, anthelmintic and antioxidant properties. This article reports a survey of the literature dealing with betulinic acid related biological properties that has appeared from the 1990s to the beginning of 2003. A broad range of medical and pharmaceutical disciplines are covered, including a brief introduction about discovery, phytochemical aspects, organic synthesis, anti-HIV and cytotoxic mechanisms of action. Various structural modifications carried out and their biological and pharmacokinetic profiles are also incorporated. Keywords: betulinic acid, anti-hiv derivatives, anti-hiv mechanism, anticancer derivatives, anticancer mechanism, antiinflammatory, antimalarial, biotransformation

The present study demonstrates an eco-friendly and low cost protocol for synthesis of silver nanoparticles using the cell-free filtrate of Aspergillus flavus NJP08 when supplied with aqueous silver (Ag+) ions. Identification of the fungal isolate was based on nuclear ribosomal DNA internal transcribed spacer (ITS) identities. Transmission electron microscopy (TEM) and energy dispersive spectroscopy (EDS) revealed the formation of spherical metallic silver nanoparticles. The average particle size calculated using Dynamic Light Scattering measurements (DLS) was found to be 17±5.9 nm. UV-Visible and Fourier transform infrared (FTIR) spectroscopy confirmed the presence of extracellular proteins. SDS-PAGE profiles of the extracellular proteins showed the presence of two intense bands of 32 and 35 kDa, responsible for the synthesis and stability of silver nanoparticles, respectively. A probable mechanism behind the biosynthesis is discussed, which leads to the possibility of using the present protocol in future "nano-factories".

Induction generators are increasingly being used in nonconventional energy systems such as wind, micro/mini hydro, etc. The advantages of using an induction generator instead of a synchronous generator are well known. Some of them are reduced unit cost and size, ruggedness, brushless (in squirrel cage construction), absence of separate dc source, ease of maintenance, self-protection against severe overloads and short circuits, etc. In isolated systems, squirrel cage induction generators with capacitor excitation, known as self-excited induction generators (SEIGs), are very popular. This paper presents an exhaustive survey of the literature over the past 25 years discussing the process of self-excitation and voltage buildup, modeling, steady-state, and transient analysis, reactive power control methods, and parallel operation of SEIG.

The purpose of this paper is to perform the analysis of literature review of lean production (LP). The analysis involved studying 546 research articles published from 1988 to 2011 in selected 24 operations research journals. The articles are classified by: time distribution of articles, research methodology, research stream, authorship patterns, sector-wise focus, popular elements in lean literature, focus of the articles on lean waste, and implementation status and performance measurement of various existing frameworks/models. Then, the suggestions for the future scope of research possibilities and development are identified. The study provides a taxonomical and integrated review of articles, puts up perspective into the conceptualisation and various critical parameters for research. The findings include: increase in empirical approach research articles, need of applying lean principles in the field of product development and enterprise level areas, need of more interregional research collaborations, need of lean elements as group instead of individual element, need of avoiding seven lean wastes instead of specific waste and lack of testing and validation of the proposed frameworks/models by researchers. The study results shall help researchers, academicians and professionals to focus on the growth, pertinence and research developments in the LP system field.

A simple approach for the deposition of Au and Ag nanoparticles on ZnO surface and to investigate their application in pollutant degradation.