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Hycons Renewable Private Limited: Viable Biogas Production from Paddy Straws: A Capital Budgeting Decision
The case revolves around the decision to be taken by Mr Sashikant Hegde, Managing Director, Hycons Renewable Private Ltd, on the project viability of a business proposal. The proposal was to start a manufacturing plant in Punjab to produce compressed biogas using paddy straws. Hegde firmly believed that the company would do well considering the growth of the CNG market in India, as the oil and natural gas sector in India is among the top 10 core industries in the country and plays an important role in the existence of other important sectors as well. The proposal would benefit Hycons to establish its presence in northern India, but the project viability and funding of the investment remained an unanswered question. 2023 Lahore University of Management Sciences. -
Hydrogen Sulfide-Induced Activatable Photodynamic Therapy Adjunct to Disruption of Subcellular Glycolysis in Cancer Cells by a Fluorescence-SERS Bimodal Iridium Metal-Organic Hybrid
The practical application of photodynamic therapy (PDT) demands targeted and activatable photosensitizers to mitigate off-target phototoxicity common in always on photosensitizers during light exposure. Herein, a cyclometalated iridium complex-based activatable photodynamic molecular hybrid, Cy-Ir-7-nitrobenzofurazan (NBD), is demonstrated as a biomedicine for molecular precision. This design integrates a hydrogen sulfide (H2S)-responsive NBD unit with a hydroxy-appended iridium complex, Cy-Ir-OH. In normal physiological conditions, the electron-rich Ir metal center exerts electron transfer to the NBD unit, quenches the excited state dynamics, and establishes a PDT-off state. Upon exposure to H2S, Cy-Ir-NBD activates into the potent photosensitizer Cy-Ir-OH through nucleophilic substitution. This mechanism ensures exceptional specificity, enabling targeted phototherapy in H2S-rich cancer cells. Additionally, we observed that Cy-Ir-NBD-induced H2S depletion disrupts S-sulfhydration of the glyceraldehyde-3-phosphate dehydrogenase enzyme, impairing glycolysis and ATP production in the cellular milieu. This sequential therapeutic process of Cy-Ir-NBD is governed by the positively charged central iridium ion that ensures mitochondria-mediated apoptosis in cancer cells. Dual-modality SERS and fluorescence imaging validate apoptotic events, highlighting Cy-Ir-NBD as an advanced theranostic molecular entity for activatable PDT. Finally, as a proof of concept, clinical assessment is evaluated with the blood samples of breast cancer patients and healthy volunteers, based on their H2S overexpression capability through SERS and fluorescence, revealing Cy-Ir-NBD to be a promising predictor for PDT activation in advanced cancer phototherapy. 2024 American Chemical Society. -
Hydrogen Sulfide: A new warrior in assisting seed germination during adverse environmental conditions
Seed, being a truly static period of the plant's existence, is exposed to a variety of biotic and abiotic shocks during dormancy that causes many cellular alterations. To improve its germination and vigor, the seed industry employs a variety of invigoration techniques, which are commonly referred to as seed priming procedures. The treatment with an exogenous H2S donor such as sodium hydrosulfide (NaHS) has been proven to improve seed germination. The H2S molecule is not only a key contributor to the signal transduction pathway meant for the sensation of seed exposure to various biotic and abiotic stresses but also contribute toward the alleviation of different abiotic stress. Although it was initially recognized as a toxic molecule, later its identification as a third gaseous transmitter molecule unveiled its potential role in seed germination, root development, and opening of stomata. Its involvement in cross talks with several other molecules, including plant hormones, also guides numerous physiological responses in the seeds, such as regulation of gene expression and enzymatic activities, which contribute to reliving various biological and non-biological stresses. However, the other metabolic pathways that could be implicated in the dynamics of the germination process when H2S is used are unclear. These pathways possibly may contribute to the seed germinability process with improved performance and stress tolerance. The present review briefly addresses the signaling and physiological impact of H2S in improving seed germination on exposure to various stresses. Graphical abstract: [Figure not available: see fulltext.] 2022, The Author(s), under exclusive licence to Springer Nature B.V. -
HydroIoT: An IoT and Edge Computing based Multi-Level Hydroponics System
The depleting area of cultivable lands is increasing demands for implementing improved techniques that could use less space and produce more than traditional farming. This situation is common in all the developing and under developed countries. With a motivation to contribute towards providing solution to this growing problem of food scarcity, a Multi-Level Hydroponics System is proposed. The proposed system combines best of all trending technologies like IoT, Edge Computing and Computer Vision and applies it to Hydroponics. A cultivation estimation system based on image processing is implemented and accuracy of the same is tested with actual produce. The crop used for the proposed system is corn as it serves as best fodder for cattle. It was observed that with proposed system up to 95% accuracy in estimating fodder produce was achieved. 2021 IEEE. -
Hydrothermally synthesized mesoporous Co3O4 nanorods as effective supercapacitor material
Mesoporous Co3O4 nanomaterial in rod-shape morphology has been synthesized via a hydrothermal method, and heat treated at 350 C for 2 h to develop a phase. Phase purity, morphology, specific surface area and chemical composition of as-obtained Co3O4 material were studied using XRD, Raman, TEM, N2-adsoprtion/desorption and XPS techniques. XRD and Raman analyses indicate single phase material formation with nano-structure, and cubic normal spinel-type structure with a cell parameter of 8.123 The spinel particles are of rod-shape morphology and the specific surface area, estimated through BET studies, is obtained as 47 m2/g. Cyclic voltammogram (CV) recorded at different scan rates evidently demonstrate pseudocapacitance nature of the synthesized material. Maximum specific capacitance (CS) is computed and the value is 261 F/g at 0.25 A/g. These materials have shown longer cycle stability at lower KOH concentration and lower current density. Synthesized Co3O4 nanomaterial could be used as electrode material for energy storage applications. 2023 Elsevier B.V. -
Hyperledger Fabric as a Secure Blockchain Solution for Healthcare 4.0 Framework
The healthcare sector deals with extremely sensitive information that must be administered in a safe and confidential way. The objective of the proposed framework is to utilize Blockchain Technology (BT) for tracking medical prescriptions and the implementation is carried out using the Hyperledger Fabric platform, an enterprise-grade open-source distributed ledger technology platform designed for Bigdata applications. Multiple entities, including patients, e-pharmacies, pharmacies, doctors and hospitals can establish connections by introducing several nodes in the Fabric chain. A web-centered application is provided for doctors, connecting them with participating pharmacies, hospitals and e-pharmacies through which, they can share patient prescription. Pharmacies and e-pharmacies have access to this data and can notify patients about the availability of prescribed medicines. Additionally, reminders for refills, such as heart medication, can be sent for patients requiring long-term medication. Patients can also try with nearby pharmacies and the availability of their prescribed medicines. The inclusion of a wallet feature in the application enables patients to use mobile tokens for making purchases. Patient data is treated with the utmost confidentiality, kept private, and accessed only upon request and with the consent of the concerned parties. This privacy is ensured through the use of zero-knowledge proof. Patients retain access to their complete medical history, facilitating interactions with doctors without the need for repetitive information sharing. 2023 IEEE. -
Hyperspectral Image Classification Using Denoised Stacked Auto Encoder-Based Restricted Boltzmann Machine Classifier
This paper proposes a novel solution using an improved Stacked Auto Encoder (SAE) to deal with the problem of parametric instability associated with the classification of hyperspectral images from an extensive training set. The improved SAE reduces classification errors and discrepancies present within the individual classes. The data augmentation process resolves such constraints, where several images are produced during training by adding noises with various noise levels over an input HSI image. Further, this helps in increasing the difference between multiple classes of a training set. The improved SAE classifies HSI images using the principle of Denoising via Restricted Boltzmann Machine (RBM). This model ambiguously operates on selected bands through various band selection models. Such pre-processing, i.e., band selection, enables the classifier to eliminate noise from these bands to produce higher accuracy results. The simulation is conducted in PyTorch to validate the proposed deep DSAE-RBM under different noisy environments with various noise levels. The simulation results show that the proposed deep DSAE-RBM achieves a maximal classification rate of 92.62% without noise and 77.47% in the presence of noise. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Hyperspectral multi-level image thresholding using qutrit genetic algorithm
Hyperspectral images contain rich spectral information about the captured area. Exploiting the vast and redundant information, makes segmentation a difficult task. In this paper, a Qutrit Genetic Algorithm is proposed which exploits qutrit based chromosomes for optimization. Ternary quantum logic based selection and crossover operators are introduced in this paper. A new qutrit based mutation operator is also introduced to bring diversity in the off-springs. In the preprocessing stage two methods, called Interactive Information method and Band Selection Convolutional Neural Network are used for band selection. The modified Otsu Criterion and Masi entropy are employed as the fitness functions to obtain optimum thresholds. A quantum based disaster operation is applied to prevent the quantum population from getting stuck in local optima. The proposed algorithm is applied on the Salinas Dataset, the Pavia Centre Dataset and the Indian Pines dataset for experimental purpose. It is compared with classical Genetic Algorithm, Particle Swarm Optimization, Ant Colony Optimization, Gray Wolf Optimizer, Harris Hawk Optimization, Qubit Genetic Algorithm and Qubit Particle Swarm Optimization to establish its effectiveness. The peak signal-to-noise ratio and Sensen-Dice Similarity Index are applied to the thresholded images to determine the segmentation accuracy. The segmented images obtained from the proposed method are also compared with those obtained by two supervised methods, viz., U-Net and Hybrid Spectral Convolutional Neural Network. In addition to this, a statistical superiority test, called the one-way ANOVA test, is also conducted to judge the efficacy of the proposed algorithm. Finally, the proposed algorithm is also tested on various real life images to establish its diversity and efficiency. 2021 Elsevier Ltd -
I am lost in that reality, and I'm just playing the game: a qualitative study exploring gaming behaviour and its effect on young adults in India
The current study aims to explore gaming behaviour among young adults in India and its effects on their physical and emotional health, productivity, interactions, and social life. Data were collected from 12 avid gamers through in-depth semi-structured interviews. A thematic analysis was conducted to identify the global theme and organise themes from the data. The global theme was the exploration of contemporary gaming behaviour. The habit theme included the origin of the game, practice, and change over time, while the effects theme focused on the physical and emotional health, productivity, interactions, and social life of young adults who engaged in gaming. The findings suggest that gaming behaviour has become an established habit among young adults in India, significantly affecting various aspects of their lives. The study highlights the need for increased awareness of the potential negative consequences of excessive gaming and emphasises the importance of moderation in gaming. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
I Can Live Without Banks, but Not Without Banking: Role of Trust on Loyalty and Evangelism
The purpose of this paper is to examine the antecedents of e-banking loyalty and evangelism via threefold construct of WEQUAL (usability, information quality, and service interaction) of public sector banks operating in India. Moreover, it also investigates the mediating role of consumers' trust on the website quality of these banks and their impact on e-banking loyalty and evangelism. The data was collected from 243 respondents through online questionnaire. In order to develop the model and test the hypotheses, partial least square structural equation modeling (PLS-SEM) was done through Smart PLS version 3.2.9. Results assert that website quality of banks positively influences the trust of consumers via usability, information quality, and service interaction. Also, consumer trust plays a mediation role between WEBQUAL constructs and e-banking loyalty and evangelism. 2021 IGI Global. All rights reserved. -
I Dont Play Games: Migrant Workers and Digital Media in Bengaluru
The great impact of media technologies in reordering almost every facet of modern life has been noted by theorists for over a century now, particularly since the idea of the global village imagined by media theorists, and enabled by globalisation and digital technology has become an inescapable reality. The new experience of time and space bears upon various dimensions of life, including the nature of work, the organisation of time and the place of leisure within these rhythms. This article attempts to engage with this very weighty body of scholarship in a modest way, through ethnographic research, to understand how mobile phones and internet technologies structure the experience of everyday life for low-income migrant workers in Bengaluru. The sites include a construction site and a hookah bar, and the study focuses on mobile gaming and the structuring of migrant social networks. 2024 South Asian University. -
IBA Graph Selector Algorithm for Big Data Visualization using Defence Dataset
International Journal of Scientific & Engineering Research Vol.4,Issue 3 pp. 1-5 ISSN No. 2229-5518 -
ICT as a driver of women's social and economic empowerment
The role of information and communication technologies as a tool for development has attracted the sustained attention of various agencies worldwide. If the gender dimensions of information and communication technologies-in terms of access and use, capacity-building opportunities, employment, and potential for empowerment-are explicitly identified and addressed, information and communication technologies can be a powerful catalyst for the political and social empowerment of women and the promotion of gender equality. ICT as a Driver of Women's Social and Economic Empowerment contributes to the growing body of literature and present state of knowledge by offering evidence on how new information and communication technologies impact women's economic and social empowerment and overall welfare creation leading to inclusive growth. Covering key topics such as economics, entrepreneurship, digital technologies, and inclusion, this premier reference source is ideal for industry professionals, policymakers, administrators, business owners, managers, researchers, academicians, scholars, practitioners, instructors, and students. 2023 by IGI Global. All rights reserved. -
ICT Policy Reforms for Innovation and Economic Development: A Comparative Study of India and China
The widespread adoption of Information and Communication Technologies (ICTs) has become essential for economic and social growth across the world. This paper aims to examine the impact of ICT policies and reforms on the level of economic development and adoption of ICTs in two countries, India and China. Previous studies have shown the positive impact of ICT adoption on economic growth, productivity, and innovation. However, the effectiveness of specific policy measures in promoting ICT adoption and economic development remains ambiguous to the users of ICT. This paper presents a comparative analysis of the ICT policies and reforms implemented in India and China from 2010 to 2021 and their impact on GDP per capita and internet usage. The study aims to identify and analyze the key ICT policies and reforms implemented in the two countries and examine their impact on economic development. The data for this study have been collected from the World Bank indicators database. The sample consists of the two fastest-growing economies in the world, India and China. The data analysis involves conducting descriptive statistics, correlation, and regression analysis to examine the relationship between ICT policies and reforms and their impact on GDP per capita, internet usage, and research and development expenditure. The findings of this study will contribute to the existing literature on the relationship between ICTs and economic development and provide insights into the policy measures that can promote ICT adoption and economic growth in different contexts. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Ideal co-secure domination in graphs
A set S ? V of a graph G = (V, E) is a co-secure dominating set if for every u ? S, there exists v ? V \ S such that uv ? E and (S \ {u}) ? {v} is a dominating set of G. The minimum cardinality of a co-secure dominating set of G is the co-secure domination number and is denoted by ?cs(G). In this paper we initiate the evaluation of a domination parameter known as the ideal co-secure domination and is defined as follows: A set D ? V is an ideal co-secure dominating set of a graph G = (V, E) if for every u ? D and for every v ? V \ D such that uv ? E, (D \ {u}) ? {v} is a dominating set of G. The minimum cardinality of an ideal co-secure dominating set of G is the ideal co-secure domination number and is denoted by ?ics(G). We look to determine the ideal co-secure domination number of some families of standard graphs and obtain sharp bounds. We also provide the conditions necessary for the trees to have ideal co-secure domination number equal to n - 2. 2020 Author(s). -
Idealised Bilinear Moment-Curvature Curves of Reinforced Masonry (RM) Walls
In this paper, an analytical investigation of the axial loadflexural strength interaction of reinforced masonry walls is carried. The curvature ductility of masonry walls is evaluated for walls with different modes of reinforcement configurations under different levels of axial loads. An analytical expression for evaluating the curvature ductility of masonry walls at varying axial loads is proposed in this paper. Value of curvature ductility obtained from the proposed expression is compared with existing methods. Results indicate the proposed model can be used to determine the ductility of reinforced masonry walls. 2020, Springer Nature Singapore Pte Ltd. -
Identification and structure-activity relationship studies of small molecule inhibitors of the human cathepsin D
Cathepsin D, an aspartyl protease, is an attractive therapeutic target for various diseases, primarily cancer and osteoarthritis. However, despite several small molecule cathepsin D inhibitors being developed, that are highly potent, most of them show poor microsomal stability, which in turn limits their clinical translation. Herein, we describe the design, optimization and evaluation of a series of novel non-peptidic acylguanidine based small molecule inhibitors of cathepsin D. Optimization of our hit compound 1a (IC50 = 29 nM) led to the highly potent mono sulphonamide analogue 4b (IC50 = 4 nM), however with poor microsomal stability (HLM: 177 and MLM: 177 ?l/min/mg). To further improve the microsomal stability while retaining the potency, we carried out an extensive structureactivity relationship screen which led to the identification of our optimised lead 24e (IC50 = 45 nM), with an improved microsomal stability (HLM: 59.1 and MLM: 86.8 ?l/min/mg). Our efforts reveal that 24e could be a good starting point or potential candidate for further preclinical studies against diseases where Cathepsin D plays an important role. 2020 Elsevier Ltd -
Identification of ambulance in traffic videos using image processing techniques
Traffic congestion is one of the commonly faced problems in the Urban areas. To eliminate these problems, there is a need for an Intelligent Transportation System (ITS) that proposes an efficient method to reduce the traffic problems and introduces the priority system for the Emergency vehicles. This paper proposes two frameworks that identify ambulance in traffic videos based on features such as color, siren and text. Frames are extracted from videos to employ methods like multilevel thresholding and region matching. Multilevel thresholding is used for segmenting the ambulance from the other occurring vehicles based on the white color. Region matching for text detection method is employed in the segmented vehicle. Color space thresholding is used for the detection of siren based on red or blue color feature. Optical character recognition (OCR) is employed to extract the text in the frame. Word comparison and Matching detects the ambulance text based on the outcome of OCR. The performance of Framework 1 and Framework 2 are evaluated based on Word accuracy and from the experimental results it is observed that Framework 2 is better from 75% word accuracy. 2018, Institute of Advanced Scientific Research, Inc. All Rights reserved. -
Identification of broken characters in degraded documents
Optical Character Recognition (OCR) deals with the recognition of characters in a text document. Steps like Preprocessing, Segmentation and Recognition are embedded in the OCR machine. When a document is scanned it will be taken into OCR and will recognize the characters. But noisy scanning of documents, low-quality printed documents and thresholding error leads to the generation of broken characters. When these documents are given as inputs into OCR, the recognition becomes a tedious process since the broken characters are misunderstood by the OCR machine. So the broken characters have to be identified and segmented separately. This work aims to enhance the degraded documents with broken characters using image processing techniques. For identifying or recognizing the broken character from the image various techniques like vertical projection profile, horizontal projection profile, chain code, mean based thresholding are used. The lines from the document are separated using line segmentation. Separate characters are extracted using Vertical Projection Profile and Horizontal Projection Profile. The character is identified using chain coding. The broken characters are found from them using Mean-based Thresholding and is merged using Heuristic information. The proposed method achieves an accuracy of 92.88% and also performs well for color image documents as well as black and white image documents also because of the effective preprocessing. 2018 Intelligent Network and Systems Society. -
Identification of Consumer Buying Patterns using KNN in E-Commerce Applications
In recent days, with the advancement of technologies, people use electronic medium to carry out their businesses. E-commerce is a process of allowing people to buy and sell products online using electronic medium. E-commerce has a wide range of customer base as well. The data generated through transaction helps the enterprises to develop the marketing strategy. The growth of this e-commerce application depends on several factors. Some of the factors are follows 1) Customer demand, 2) Analyzing buying pattern of the users, 3) Customer retention, 4) dynamic pricing etc. It is very difficult to analyze the buying pattern of customers as there is a wide range of customer base in the online platform. To overcome this problem, this research study discusses about the challenges and issues in e-commerce applications, also identifies and analyses the buying patterns of customer using various machine learning techniques. From the implementation it is identified that, KNN algorithm performed well while comparing it with various other machine learning algorithms. Performances of these algorithms have been analyzed using various matrices. For analyzing, the model is tested using e-commerce dataset (Amazon dataset downloaded from Kaggle.com). From the analysis it found that KNN algorithm computes and predicts better compared to other machine learning algorithms either Nae Bayes, or Random Forest, or Logistic Regression etc. 2023 IEEE.