Browse Items (14421 total)
Sort by:
-
Green credibility: Unlocking employee engagement through environmental responsibility
Today, the adoption of environmental policies has gained significance in the corporate scenario not only for sustainability but to also improve organizational dynamics. These environmental policies are discussed in terms of their effects on the overall performance, satisfaction, and general well-being of the employees, thus forming the company culture and behavior. Another objective of this book chapter is to come up with a developmental model, other than what exists so far, which will study the impact of environmental policies using Organizational image as a moderator. Also, including how employee motivation, organizational communication, and leadership can create an enabling environment for sustainable development. This book chapter aims at offering useful insights and recommendations to companies keen to exploit environmental efforts not only as a means of complying with the requirement but also as a stimulant for a motivated and engaged workforce in the modern corporate climate. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Growth and characterization of glycine potassium nitrate NLO crystals
Single crystals of glycine potassium nitrate were grown using slow evaporation technique. The solutions were prepared mixing glycine with potassium nitrate in different ratios stirring continuously for an hour to get a saturated solution. It was then kept at room temperature for controlled evaporation. Optically clear and well shaped crystals were obtained and these were characterized by (FTIR) studies, EDAX and X-ray powder diffraction. 2011 American Institute of Physics. -
Determinants of employee eco-initiatives in Indian hotel industry
Results of a questionnaire survey completed by 402 respondents who were all employees of hotels that have adopted eco-friendly practices showed that eco-initiatives are significantly and positively correlated to conservatism, commitment to the cause of the environment, and monetary rewards and recognition; significantly and negatively correlated to self-transcendence and environmental training; and bear no significant relationship with environmental communication and self-enhancement. Future research should consider the role of guests in promoting employee eco-initiatives. Copyright 2019 Inderscience Enterprises Ltd. -
Analytics in e-learning
Predictive analytics play an important role in the evolving dynamics of higher education. There has been a steady up rise in use of technology in the field of education. e-learning is seen as a futuristic approach of learning. Hence, the study of factors influencing success in e-learning courses is relevant to the current scenario. Use of predictive analytics in virtual learning environment would provide insight on learning patterns of students. The learning data available in the traditional teaching environment is different from the one, which is available from virtual learning. This paper tries to identify various attributes associated with e learning which can help in making the learning process effectual. International Research Publication House. -
Tag indicator: a new predictive tool for stock trading
In this paper, TAGan indicator for stock market prediction in which volume-based means for measuring potential trading and investing decision-making is introduced. This task has been in correlation of the changes in the volume with the changes in the actual trade volume. Using this, a concise trading strategy is formulated. Hoping to outperform the market and analyze the results by back testing across intraday, price data for the last 1 year, 2019, is performed. It was discovered that about 48.9% of the time, the volume-based trading strategy outperformed and the returns from market are also healthy enough to support the claim. Statistical methods like linear regression, mean square error in prediction and stochastic gradient descent are applied. Furthermore, while the scope of the study was limited to a few stocks in Nifty in order to mitigate selection bias, nonetheless, we hypothesize that numerous other assets that similarly possess a predictable correlation to volumes based on daily high and low are likely to exist. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. -
Implementation of integer factorization algorithm with pisano period
The problem of factorization of large integers into the prime factors has always been of mathematical interest for centuries. In this paper, starting with a historical overview of integer factorization algorithms, the study is extended to some recent developments in the prime factorization with Pisano period. To reduce the computational complexity of Fibonacci number modulo operation, the fast Fibonacci modulo algorithm has been used. To find the Pisano periods of large integers, a stochastic algorithm is adopted. The Pisano period factorization method has been proved slightly better than the recently developed algorithms such as quadratic sieve method and the elliptic curve method. This paper ideates new insights in the area of integer factorization problems. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. -
Evaluating the impact of BRICS+ trade policies: A comparative analysis before and after the Russia-Ukraine conflict
This chapter explores shifts in trade dynamics among BRICS+ nations (Brazil, Russia, India, China, South Africa, and extended partners) in response to the Russia-Ukraine conflict. The study assesses changes in trade volumes and patterns between Russia and other BRICS+ nations, comparing pre-conflict (2018-2021) and post-conflict (2022 onwards) periods. Utilizing secondary data from credible sources like Bloomberg, WTO, and national trade statistics, the research ensures data authenticity and reliability. The findings reveal significant growth in trade activities between Russia and certain BRICS+ nations post-conflict. Moreover, a comparative analysis with other trade blocs like the European Union highlights contrasting geopolitical strategies, showcasing the resilience and adaptability of BRICS+ in navigating global challenges. The study offers strategic insights for policymakers within the alliance to effectively adjust to evolving trade dynamics. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Bioconvective flow of nanofluid past a cylinder subject to ThompsonTroian slip
The bioconvective flow of a nanofluid across a cylinder under the impact of ThompsonTroian slip conditions is studied in this work. The nonzero velocity at the boundary, which affects the distribution of shear stress and, in turn, the overall flow pattern, is explained by this slip condition. Additionally, the paper covers the dynamics of nanofluid flow and its mass and heat transfer characteristics. Partial differential equations (PDEs) that characterize the momentum, energy, concentration and species movement in the fluid, are used to simulate the flow. Through similarity transformations, these PDEs are transformed into a system of ordinary differential equations (ODEs), simplifying the intricate flow phenomena. After applying the similarity transformations, the resulting system of ODEs is solved via the RungeKuttaFehlberg (RKF45) technique. The study emphasizes how important precise modeling and numerical solutions are for managing and predicting bioconvective flows in real-world applications, including cooling systems, chemical reactors and microfluidic devices. The results provide a basis for further research into more complex flow scenarios as well as for the creation of cutting-edge materials and technologies that take advantage of nanofluid dynamics. The changes in the slip parameter resulted in 12.23% changes in the Nusselt number, whereas the changes in the magnetic field parameter accounted for 1.22.4%. However, the velocity of the nanofluid was found to decrease for a stronger magnetic field. 2025 World Scientific Publishing Company. -
Visualization of Data Structures and Algorithms with Dynamic Memory Allocation
Data Structures and Algorithms (DSA) is fundamental to computer science education, yet novice learners face significant challenges in grasping abstract concepts and their system-level implications, such as dynamic memory allocation. This paper presents a novel web-based platform designed to enhance learning outcomes for beginner to intermediate students through interactive step-by-step visualizations of DSA, including arrays, linked lists, stacks, queues, and searching and sorting algorithms. A distinctive feature is the integration of dynamic memory allocation visualization, illustrating stack and heap to elucidate system-level operations. Developed using Next.js, Tailwind CSS, D3.js, and Framer Motion, the platform offers a space-themed responsive interface with synchronized code, data structure, and memory views. By addressing pedagogical gaps in tools like VisuAlgo, this work aligns with Sustainable Development Goal 4- Quality Education, promoting accessible and equitable learning. 2025 IEEE. -
Biochemical and Rapid Paper Sensory Detection of Heavy Metals in Milk Based on Biosynthesized Silver Nanoparticles
Milk is an emulsion of proteins and fats in water that contributes to a nutritious diet and enhances our immune system. However, contamination of heavy metals in milk due to an increase in industrialization and urbanization can be a serious threat to human health. This study focused on the rapid detection of heavy metals particularly lead and mercury in milk using biochemical assays as well as paper-based colorimetric sensor based on green synthesized silver nanoparticles (AgNPs) from leaf extract of Hemigraphis colorata. Biochemical assays such as the lead chromate test and sodium hydroxide test were employed to detect lead and mercury in milk samples. The biogenic AgNPs were characterized by UVVis spectroscopy, scanning electron microscope, Fourier transform infrared spectroscopy, energy dispersive X-ray analysis (EDX) and X-ray diffraction. The unique properties of silver nanoparticles (AgNPs) like surface plasma resonance (SPR), large surface area and visible colour change upon aggregation when metal ions interact, enable them to detect heavy metals. This is a portable and affordable method of detection that ensures safer milk consumption and sustainable environmental practices. 2025 Asian Publication Corporation. All rights reserved. -
Raman spectroscopy: an introduction, instrumentation, and its applications in polymer composites and nanocomposites
Raman spectroscopy, a nondestructive technique based on molecular vibrations, offers insights into molecular structures and interactions through the inelastic scattering of monochromatic light. This method facilitates the identification of chemicals by using unique molecular fingerprints. The ability of this technique to analyze samples in situ, in any form, is very advantageous. Over the years, improvements have been made in the sensitivity and resolution of Raman spectroscopy in instrumentation and data analysis, which has broadened its range of applications in chemistry, biology, and materials research. Raman spectroscopy has become a vital tool for applied research and basic sciences. In the area of composites and nanocomposites, it offers tremendous possibilities, such as material identification, phase separation, and defect analysis, reinforcement agent characterization, stress and strain analysis, crystallinity and orientation, and micromechanical deformation. 2026 Elsevier Ltd. All rights reserved. -
Identification of Dynamics of Tractor Chassis Structure through Ground Vibration Testing
This study investigates the vibrations arising from mass imbalance and variable inertia forces within dynamic systems, specifically focusing on agricultural tractors. Impulse test method is used to determine the modal characteristics of the tractors structure, including its frequencies, damping and mode shapes. The random responses of various components, such as the chassis, bonnet, muffler, seat and axle, were measured at engine speeds of 800, 1500 and 2500 rpm. The results indicate that the vibration amplitude depends on material properties and operational conditions, with the maximum random vibration response observed at the highest engine speed of 2500rpm. The overall root-mean-square acceleration (grms) was used to quantify vibration levels, revealing significant acceleration values of 2-4 grms across the entire tractor structure. Increased vibrations, particularly at high engine speeds, lead to amplified noise, dynamic stresses and accelerated wear on the chassis and subsystems, necessitating periodic maintenance and part replacements. The study also assessed the impact of road and field surface conditions on the vibration levels. The dynamic modes identified provide insights into potential improvements in tractor performance by implementing semiactive or active vibration control mechanisms utilizing smart materials without changing the existing engine dynamics. 2025. Carbon Magics Ltd. -
Circular Economy in the Construction Industry: Promoting Environmental Sustainability in the Context of SDG 12
The construction industry in particular is experiencing a time of fast expansion as a result of the circular economy (CE), which is causing firms all over the globe to go through this transformation. The purpose of this research is to investigate the practise of incorporating CE principles into the construction industry, with a particular emphasis on the advancement of environmentally sustainable activities. The purpose is to lessen the negative effect that it has on the environment, which is the objective of SDG 12, which is being carried out simultaneously. We perform an analysis of the most recent developments, obstacles, and possibilities in the construction industry in order to assess the ways in which CE practices have the potential to bring about a decrease in the amount of waste that is produced, the preservation of resources, and a lessening of the effect on the environment. We use a mixed-methods approach, which includes data analysis, case studies, and interviews, in order to give insights on the progress that the construction sector has accomplished towards CE. 2026 by IGI Global Scientific Publishing. -
AI-Driven Lead Scoring: Enhancing Real Estate Decisions with Predictive Analytics
Lead optimization remains underutilized in customer acquisition, with businesses often focusing on new models rather than refining existing processes. Many overlook automation, real-time data, and feedback loops that enhance insight into lead behavior. Automated optimization continuously improves lead scoring by fine-tuning models over time. Current approaches rely on basic lead scoring without real-time data integration or continuous updates. This research focuses on machine learning-driven lead optimization to improve scoring accuracy and personalized communication. We propose an AI-enhanced system that integrates CRM data with predictive models using ensemble techniques like Random Forest and XGBoost. Our approach achieves high accuracy in property hotspot and ROI prediction, with R2 values up to 0.99. However, a 5% uncertainty exists, requiring carefully generated synthetic datasets. This methodology improves lead prioritization, decision-making and data-driven strategies, ultimately increasing conversion rates and revenue growth. 2025 IEEE. -
Phyto- and zoomass-derived nanostructured carbon as efficient catalysts for oxygen reduction reaction in fuel cells: a review
Abstract: The oxygen reduction reaction (ORR) plays a pivotal role in several energy storage and conversion technologies, including metal-air batteries, microbial fuel cells, and low-temperature hydrogen and alcohol fuel cells. Fuel cells, in particular, have gained significant traction as a feasible alternative energy source due to their efficiency, cleanliness, adaptability, and ability to reuse exhaust heat. However, the complex nature of ORR requires highly efficient electrocatalysts for optimal fuel cell performance. While Pt-based electrocatalysts are widely regarded as the most suitable for both the cathode and anode in fuel cells, their high cost, scarcity, and susceptibility to fuel crossover have driven the search for alternative ORR catalysts. In this context, carbon materials have emerged as promising candidates due to their low cost, long-term stability, and strong electrocatalytic activity. Recent advancements in biomass-derived carbon nanostructures align with the global push for sustainable energy and a pollution-free environment. This review examines carbon structures derived from the carbonization of plant and animal biomass and evaluates their performance as noble metal supports, non-noble metal electrocatalysts, and metal-free electrocatalysts for ORR. Graphical abstract: (Figure presented.) The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Cobalt Embedded N-Doped Carbon Spheres Derived From Cassava Starch for Enhanced Oxygen Reduction Reaction in Alkaline Medium
Cathodic oxygen reduction reaction (ORR) is essential for fuel cells and metal-air batteries. The sluggishness of ORR necessitates the synthesis of effective and durable catalysts to intensify the reaction process without compromising cost-effectiveness. Here, cobalt and cobalt oxides were embedded on N-doped carbon microspheres (Co?N?C/CS) using cassava starch as a carbon source. The catalyst exhibits a surface area of 388.73 m2 g?1, with a predominantly mesoporous texture. The presence of the Co?N bond, along with pyridinic and graphitic nitrogen, contributes to the ORR activity by enhancing the density of active sites. The catalyst achieves a limiting current density of ?4.64mA cm?2 with an onset potential of 0.91V (vs RHE). The calculated electron transfer value of 3.74 indicates the 4e- pathway ORR mechanism supported by Co?N?C/CS. Moreover, the catalyst demonstrates a high stability in 0.1M KOH with 99% of current retention after 14000 s, exceeding commercial Pt/C. Relatively high methanol tolerance was also observed for Co?N?C/CS by the addition of 3M methanol in the electrolyte during current-time response, highlighting its suitability as a cathode catalyst for direct methanol fuel cells (DMFC). 2026 Wiley-VCH GmbH. -
Functional response, host stage preference and development of Rhynocoris fuscipes (Fab.) (Heteroptera: Reduviidae) for two cotton pests
Considering the indispensable role of reduviid predators in ecofriendly pest management programme, the relationship between a predatory reduviid, Rhynocoris fuscipes, and three prey species viz., red cotton bug Dysdercus koenigii Fab. (Heteroptera: Pyrrhocoridae), cotton mealybug Phenacoccus solenopsis (Tinsley) (Hemiptera: Pseudococcidae) and rice flour moth Corcyra cephalonica Stainton (Lepidoptera: Pyralidae), were scrutinized and studied to determine the influence of host species on biology, host stage preference and biological control efficiency under laboratory conditions. Rhynocoris fuscipes completed nymphal stage in 41 days when feeding on C. cephalonica, 45 on D. koenigii, and 50 days on P. solenopsis. Adult longevity, fecundity and egg viability were higher in C. cephalonica fed category and the lowest on P. solenopsis. Life table parameters were in favor of C. cephalonica. Third instars of D. koenigii were favored by third and fourth instars of the predator. Fifth instars and adults of the predator had chosen fourth and fifth instars of D. koenigii, respectively. All instars of predator preyed on adults of P. solenopsis. It is observed that the reduviid responded to increased D. koenigii and P. solenopsis density with type II functional response. Positive interactions distinctly imply that there is a salutary effect on the pest as well. 2021, Crop Protection Research Centre. All rights reserved. -
Entomotoxic proteins of Beauveria bassiana Bals. (Vuil.) and their virulence against two cotton insect pests
Entomopathogenic fungi are widely used as biocontrol agents against several agricultural pests. Among them, Beauveria bassiana is considered the important one against insect and other arthropod pests. The entomotoxic proteins of B. bassiana were extracted by Sephadex G-25 column, and fractionated using HPLC (BBI, BBII and BBIII) and tested against two hemipteran insect pests i.e., Dysdercus cingulatus Fab. and Phenacoccus solenopsis Tinsely (Hemiptera: Pseudococcidae). Results indicated that protein content was higher in fraction BBII than BBI and BBIII. The vibration frequency in FT-IR obtained with a range of 1650 to 1580 cm?1. Bioassays of fractions (I, II and III) reveal that BBII was highly virulent against third nymphal instar of D. cingulatus (LC50 = 800.2 ppm) and adults of P. solenopsis adult (LC50 = 713.3 ppm). Considering the high virulence of BBII subjected to SDS-PAGE, HPLC and MALDI-TOF analyses. Analyses reveals the presence of 174 kDa and designated as BBF2. These results concluded that the entomotoxic protein of B. bassiana can be utilized for management of these investigated hemipreran pests. Further investigations are necessary for the field application of this entomotoxin against these pests or other insect pests. These results also could be helpful for establishing novel biotechnological uses for this fungus. 2021 The Authors -
Power quality improvement strategy for non-linear load in single phase system
Widespread use of non-linear loads in today's world scenario, increased the harmonic current injection into the grid. The harmonic current play a vital role in deteriorating the power quality of the grid. The non-linear loads may be either, single phase or a Three phase loads. In this paper, a control strategy for single phase shunt active filter is discussed, in mitigating the harmonics flowing into the grid. The extraction of reference signal of shunt active filter is designed, using instantaneous reactive power theory. Here load is considered as diode rectifier which is feeding a resistive inductive load. A complete control strategy and analysis is done in MATLAB/Simulink environment. 2016 IEEE. -
The Truncated Modified Lindley Generated Family of Distributions
In this paper, two contributions to the modified Lindley distribution are provided. First, we bend the truncation scheme to this model to introduce a new distribution on the interval (0, 1). Theory and practice are provided. In particular, we show that it can be an interesting alternative to the analogous truncated exponential and Lindley distributions. Then, we employ this truncated distribution to develop a new generalized family of distributions. We examine its main theoretical properties, and show how it can be applied quite efficiently to analyse various data sets. 2023 Mir Masoom Ali, Irfan Ali, Haitham M. Yousof and Mohamed Ibrahim.