scispace - formally typeset
Search or ask a question
Author

Abhishek Kaushik

Bio: Abhishek Kaushik is an academic researcher from Dublin City University. The author has contributed to research in topics: Computer science & Sentiment analysis. The author has an hindex of 7, co-authored 40 publications receiving 182 citations. Previous affiliations of Abhishek Kaushik include Dublin Business School & New York University.

Papers published on a yearly basis

Papers
More filters
Journal ArticleDOI
11 Jun 2021-Science
TL;DR: In this article, the authors identified cystathionine γ-lyase (CSE) as the primary generator of H2S in two major human pathogens, Staphylococcus aureus and Pseudomonas aeruginosa, and discovered small molecules that inhibit bacterial CSE.
Abstract: Emergent resistance to all clinical antibiotics calls for the next generation of therapeutics. Here we report an effective antimicrobial strategy targeting the bacterial hydrogen sulfide (H2S)-mediated defense system. We identified cystathionine γ-lyase (CSE) as the primary generator of H2S in two major human pathogens, Staphylococcus aureus and Pseudomonas aeruginosa, and discovered small molecules that inhibit bacterial CSE. These inhibitors potentiate bactericidal antibiotics against both pathogens in vitro and in mouse models of infection. CSE inhibitors also suppress bacterial tolerance, disrupting biofilm formation and substantially reducing the number of persister bacteria that survive antibiotic treatment. Our results establish bacterial H2S as a multifunctional defense factor and CSE as a drug target for versatile antibiotic enhancers.

73 citations

Journal ArticleDOI
12 Apr 2019
TL;DR: In this article, the authors explored the major factors in adopting new technology among Irish farmers and found that Cloud Computing adoption among the young farmers is greater while it is lower among the old farmers in Ireland.
Abstract: The primary objective of this research is to find the disparity for slow adoption of Smart Farming Technologies (SFT) in Ireland. The usage of Cloud Computing technology among Irish farmers would help to find out the adoption behaviour barrier and way to enhance from the present system. The research will also help us to indicate the reasons for farmers in adopting and not adopting any technology. The research followed a mixed method where both surveys and interviews were used to collect the data from Irish farmers. A total sample of 32 farmers were selected through snowball sampling with the help of social websites. This study explored the major factors in adopting new technology among Irish farmers. It also helped to find the perception of farmers and ways to improve from the present system. The result shows that Cloud Computing adoption among the young farmers is greater while it is lower among the old farmers in Ireland.

52 citations

Journal ArticleDOI
03 Jul 2019
TL;DR: This study focuses on the sentiment analysis of Hinglish comments on cookery channels in India using the unsupervised learning technique DBSCAN and modelled and evaluated both parametric and non-parametric learning algorithms.
Abstract: The success of Youtube has attracted a lot of users, which results in an increase of the number of comments present on Youtube channels. By analyzing those comments we could provide insight to the Youtubers that would help them to deliver better quality. Youtube is very popular in India. A majority of the population in India speak and write a mixture of two languages known as Hinglish for casual communication on social media. Our study focuses on the sentiment analysis of Hinglish comments on cookery channels. The unsupervised learning technique DBSCAN was employed in our work to find the different patterns in the comments data. We have modelled and evaluated both parametric and non-parametric learning algorithms. Logistic regression with the term frequency vectorizer gave 74.01% accuracy in Nisha Madulika’s dataset and 75.37% accuracy in Kabita’s Kitchen dataset. Each classifier is statistically tested in our study.

25 citations

01 Jan 2015
TL;DR: The purpose of social media has created many chances for people to publicly voice their beliefs, simply when they are employed to deliver an opinion hit a vital problem.
Abstract: The purpose of social media has created many chances for people to publicly voice their beliefs, simply when they are employed to deliver an opinion hit a vital problem. Sentiment Analysis is a case of natural language processing which could mark the mood of the people about any specific product by analysis. Sentiment Analysis is a process of automatic extraction of features by mode of notions of others about specific product, services or experience. The Sentiment Analysis tool is to function on a series of expressions for a given item based on the quality and features. Sentiment analysis is also called Opinion mining due to the significant volume of opinion. Analyzing customer opinion is very important to rate the product. To automate rate the opinions in the form of unstructured data is been a challenging problem today. Thus, this paper discusses about Sentiment analysis methods and tools used.

21 citations

Journal ArticleDOI
TL;DR: Crystal structures of enzyme·inhibitor·substrate ternary complexes reveal a competitive allosteric binding mechanism in which the substrate intrudes into the inhibitor-bound active site and disengages the inhibitor before occupying the site vacated by the inhibitor.
Abstract: By classical competitive antagonism, a substrate and competitive inhibitor must bind mutually exclusively to the active site. The competitive inhibition of O-acetyl serine sulfhydrylase (OASS) by the C-terminus of serine acetyltransferase (SAT) presents a paradox, because the C-terminus of SAT binds to the active site of OASS with an affinity that is 4–6 log-fold (104–106) greater than that of the substrate. Therefore, we employed multiple approaches to understand how the substrate gains access to the OASS active site under physiological conditions. Single-molecule and ensemble approaches showed that the active site-bound high-affinity competitive inhibitor is actively dissociated by the substrate, which is not consistent with classical views of competitive antagonism. We employed fast-flow kinetic approaches to demonstrate that substrate-mediated dissociation of full length SAT–OASS (cysteine regulatory complex) follows a noncanonical “facilitated dissociation” mechanism. To understand the mechanism by w...

19 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

Journal ArticleDOI
07 Mar 2020
TL;DR: The conclusion is that IoT and UAV are two of the most important technologies that transform traditional cultivation practices into a new perspective of intelligence in precision agriculture.
Abstract: Internet of Things (IoT) and Unmanned Aerial Vehicles (UAVs) are two hot technologies utilized in cultivation fields, which transform traditional farming practices into a new era of precision agriculture. In this paper, we perform a survey of the last research on IoT and UAV technology applied in agriculture. We describe the main principles of IoT technology, including intelligent sensors, IoT sensor types, networks and protocols used in agriculture, as well as IoT applications and solutions in smart farming. Moreover, we present the role of UAV technology in smart agriculture, by analyzing the applications of UAVs in various scenarios, including irrigation, fertilization, use of pesticides, weed management, plant growth monitoring, crop disease management, and field-level phenotyping. Furthermore, the utilization of UAV systems in complex agricultural environments is also analyzed. Our conclusion is that IoT and UAV are two of the most important technologies that transform traditional cultivation practices into a new perspective of intelligence in precision agriculture.

301 citations

Journal ArticleDOI
TL;DR: The agricultural supply chains (ASCs) are exposed to unprecedented risks following COVID-19 and it is necessary to investigate the impact of risks and to create resilient ASC organizations as discussed by the authors.
Abstract: The agricultural supply chains (ASCs) are exposed to unprecedented risks following COVID-19. It is necessary to investigate the impact of risks and to create resilient ASC organisations. In this st...

181 citations

Journal ArticleDOI
TL;DR: The role of ppGpp and pppGpp in bacterial pathogenesis is reviewed, providing examples of how these nucleotides are involved in regulating many aspects of virulence and chronic infection.
Abstract: The stringent response is a stress signalling system mediated by the alarmones guanosine tetraphosphate (ppGpp) and guanosine pentaphosphate (pppGpp) in response to nutrient deprivation. Recent research highlights the complexity and broad range of functions that these alarmones control. This Review provides an update on our current understanding of the enzymes involved in ppGpp, pppGpp and guanosine 5'-monophosphate 3'-diphosphate (pGpp) (collectively (pp)pGpp) turnover, including those shown to produce pGpp and its analogue (pp)pApp. We describe the well-known interactions with RNA polymerase as well as a broader range of cellular target pathways controlled by (pp)pGpp, including DNA replication, transcription, nucleotide synthesis, ribosome biogenesis and function, as well as lipid metabolism. Finally, we review the role of ppGpp and pppGpp in bacterial pathogenesis, providing examples of how these nucleotides are involved in regulating many aspects of virulence and chronic infection.

130 citations

Journal ArticleDOI
TL;DR: A survey of the last research on IoT and UAV technology applied in agriculture can be found in this paper , where the authors describe the main principles of IoT technology, including intelligent sensors, IoT sensor types, networks and protocols used in agriculture, as well as IoT applications and solutions in smart farming.
Abstract: Internet of Things (IoT) and Unmanned Aerial Vehicles (UAVs) are two hot technologies utilized in cultivation fields, which transform traditional farming practices into a new era of precision agriculture. In this paper, we perform a survey of the last research on IoT and UAV technology applied in agriculture. We describe the main principles of IoT technology, including intelligent sensors, IoT sensor types, networks and protocols used in agriculture, as well as IoT applications and solutions in smart farming. Moreover, we present the role of UAV technology in smart agriculture, by analyzing the applications of UAVs in various scenarios, including irrigation, fertilization, use of pesticides, weed management, plant growth monitoring, crop disease management, and field-level phenotyping. Furthermore, the utilization of UAV systems in complex agricultural environments is also analyzed. Our conclusion is that IoT and UAV are two of the most important technologies that transform traditional cultivation practices into a new perspective of intelligence in precision agriculture.

126 citations