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A rapid and selective on-off fluorescence detection of lethal pulmonary agent phosgene supplemented with theoretical approach: a cost-effective sensing tool for household bleach and soil analysis
A fluorescent probe, 4-(di-phenylamino)-benzaldehyde oxime (DPBO), was developed comprising 4-(diphenylamino) benzaldehyde as the fluorophore and hydroxyl amine, where the resultant oxime group leads to the formation of a recognition site for the selective on-off fluorescence detection of lethal phosgene with the dimer formation of DPBO through carbonate linkage generated from phosgene. The probe DPBO also exhibits notable spectrofluorometric response in different solvents, as demonstrated by SEM analysis. The detection limit of the probe DPBO towards phosgene was calculated as 21.53 ?M, with a fast reaction response time within 30 s and the fluorescence quenching efficiency of DPBO by phosgene was measured through the Stern-Volmer quenching constant (KSV) estimated at 1.03 104 M?1. Confirmation of the sensing mechanism was achieved through various spectroscopic techniques such as UV-vis, emission spectroscopy, mass spectrometry, and computational studies. For practical applications, the sensor DPBO can be utilized for the detection of phosgene in household bleach, soil analysis and dipstick method. 2024 The Royal Society of Chemistry. -
A rapid investigation of near-infrared (NIR) fluorescent switch-on probes for detection and in cellulo tracking of G-quadruplex and double-stranded DNA
This review provides a comprehensive overview of the recent advancements in Near Infrared (NIR) fluorescence switch-on probes designed for the detection and in cellulo tracking of G-quadruplex and double-stranded DNA (dsDNA). G-quadruplexes, non-canonical DNA structures, play pivotal roles in regulating various biological processes, making them critical targets for therapeutic and diagnostic applications. The unique properties of NIR fluorescence probes, such as deep tissue penetration, minimal photodamage, and low autofluorescence background, offer significant advantages for bioimaging. We critically analyze the design strategies, photophysical properties, and binding mechanisms of various NIR fluorescence switch-on probes. Additionally, we discuss their efficacy and specificity in identifying G-quadruplexes and dsDNA within cellular environments. Key challenges and future directions for improving the sensitivity, selectivity, and biocompatibility of these probes are also highlighted. This review aims to underscore the potential of NIR fluorescence probes in advancing our understanding of DNA dynamics and their applications in biomedical research. 2024 The Royal Society of Chemistry. -
A ratiometric fluorescent sensor based on dual-emissive carbon dot for the selective detection of Cd2+
Cadmium (Cd2+), a heavy metal ion used in numerous industries, has toxic adverse effects on the environment; it is crucial to develop a quick and reliable method for Cd2+ determination. Fluorescent biomass-derived carbon quantum dots (CD) with rich carboxyl groups on the surface were synthesized using water amaranth leaves by hydrothermal method with a 12.1% quantum yield. The surface of CD was further modified with 1-pyrene carboxaldehyde (PC) to synthesize pyrene carboxaldehyde-carbon quantum dots (PC-CD). This study developed a fluorescent ratiometric nanosensor using a covalently functionalized CD with pyrene derivative and demonstrates highly selective identification capability towards Cd2+ over competing metal ions. The Nano sensor has significant selectivity towards Cd2+ in an excellent linear range of 0-70 ?M with a detection limit as low as 15 nM and demonstrates excellent water solubility and biocompatibility. Transmission electron spectroscopy (TEM), Fourier Transform infrared spectroscopy (FT-IR), and X-ray photon spectroscopy (XPS) were used to identify the surface functionalization of PC-CD. Finally, the developed ratiometric sensor was used for detecting Cd2+ metal ions from various water effluents. 2023 Elsevier Ltd. -
A ratiometric luminescence thermometer based on lanthanide encapsulated complexes
Lanthanide-containing complexes have been widely developed as ratiometric luminescence thermometers, which are non-invasive, contactless and accurate. The synthesis of these Ln complexes generally requires high temperatures, multiple steps and other harsh conditions. Moreover, bimetallic lanthanide complexes, which have been reported to be better thermometers, are even more challenging to synthesize. This complexity can be simplified by preparing a host-guest complex of lanthanides. In this work, Tb or both Tb and Eu are encapsulated in an MOF host, making them emissive. The ratio of Tb/Eu was also easily tuned by simply changing their ratio in the solution, resulting in a tunable emission. Accordingly, we were able to synthesise both the emissive Tb complex and Tb/Eu complexes at different ratios using a single host. The complexes were found to be suitable as ratiometric luminescent thermometers in the temperature range of 160-380 K, with reasonably good sensitivity and uncertainty. The thermometer's sensitivity and uncertainty were significantly improved using bimetallic Tb and Eu host-guest complexes. Calculations using the host and Eu emission ratio were found to provide better thermometer parameters than the commonly reported Tb and Eu emission ratio. Thus, using a single host, we were able to synthesise different lanthanide complexes that can sense temperature, and we improved the thermometer parameters by incorporating multiple lanthanides in a single host. This research will enable the scientific community to reexamine the applicability of unexplored host-guest lanthanide complexes. 2025 The Royal Society of Chemistry. -
A real time fog computing applications their privacy issues and solutions
Edge Computing (EC) has brought cloud technology to the channel's edge. It inherits some qualities from cloud services, but it also has some distinctive features such as geo-distribution, network connectivity, and reduced power. Along with the genetic inheritance, it also acquires the issues and concerns cloud computing services, such as renewable energy and resource allocation. This work provides a critical analysis of the fog architectural design in terms of security. Since 2018, the state of the artwork has been critically analyzed in terms of security mechanisms and security threats. The existing security methods are classified based on the security objectives they achieved. It would provide a complete and coherent difference between both the security areas investigated and those that have not. 2021 IEEE. -
A Real-Time Approach with Deep Learning for Pandemic Management
It has never been so critical to managing pandemic situations created by a virus like COVID-19, which has brought the world almost to a standstill, claiming millions of lives. Learning from all earlier viruses and building a quick tackling mechanism is a need of the hour. There is a greater need for technology to collaborate with healthcare and leverage each of the domains expertise. With less time in hand, this collaboration must happen in a short time. There is a need to study the exiting progression in technology and the healthcare landscape to bring them to a common path for practical solutions. In the chapter, an attempt was made to put together some thoughts in both fields to relate them to pandemic managements frequent subject. Caution is drawn towards some crucial aspects, such as security and transparency, that cannot be compromised in this journey. Artificial intelligence (AI), being at the forefront of the technology supporting lives, provides a greater hope in this direction. Some of the prominent approaches can be looked at from a pandemic management point of view, which can start a more in-depth discussion on AI and healthcare going hand in hand in managing this pandemic situation. Essential areas of pandemic management, such as building on the knowledge gathered over a period, plugging in the real-time data from the society, building efficient data management systems and building transparent and interpretable solutions are the focus areas of exploration in this chapter. 2022, Springer Nature Switzerland AG. -
A reconfigurable integrated level shifted carrier based PWM method for modular multilevel converters
This article presents a reconfigurable integrated level shifted carrier-based pulse width modulation (ILSC-PWM) method for modular multilevel converters (MMCs). The principles of basic level shifted carrier-based PWM (LSC-PWM) methods such as phase disposition PWM (PD-PWM), phase opposition disposition PWM (POD-PWM) and alternate phase opposition disposition PWM (APOD-PWM) methods are combined to develop the concept of reconfigurable ILSC-PWM method. The main objectives of the proposed reconfigurable ILSC-PWM method is to develop the pulse width modulated output voltage with both half-wave and quarter-wave symmetries and to reduce the total harmonic distortion (THD). A simplified mathematical approach is developed to formulate reconfigurable single ILSC wave for MMC with N number of submodules (SMs) per arm. The functionality and performance of the reconfigurable ILSC-PWM method are carried out on three-phase five-level MMC in MATLAB/Simulink. A hardware prototype of single-phase five-level MMC is designed for experimental validation. The proposed ILSC-PWM method is implemented on an Altera/Cyclone I series (EP1C12Q240C8N) field programmable gate array (FPGA). Computer Simulations and laboratory experimental results are presented. 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. -
A Reconfigurable Multilevel Inverters with Minimal Switches for Battery Charging and Renewable Energy Applications
In recent years, classical inverters such as the H-bridged cascaded multilevel inverter, flying capacitor, and flying capacitor multilevel inverter have contributed in electric vehicle and non-conventional energy applications. Due to higher switching and conduction losses, as well as a greater number of power switches and driver circuits, conventional multilevel inverters do not achieve the highest performance. To obtain higher performance while reducing power losses and total harmonic distortion, individual switches are controlled by logic gates. In this proposed work, one of the inverters is considered symmetrical voltage another is asymmetrical voltage for implementing these effective topologies. The proposed single-phase seven-level voltage output and current for both symmetric and asymmetric multilevel inverters are employed to test the intended computation. The MATLAB/Simulink tool is used to implement and investigate the various parameters of proposed topologies. 2022 IEEE. -
A Reflection on the Current Status of Animal-Assisted Therapy in India
The field of animal-assisted therapy is advancing quickly throughout the world gaining popularity as a complementary therapy. Several countries, especially in the East, are still in their nascent phase in utilizing animal-assisted therapy and a more realistic presentation of their status should drive them towards effective initiatives to promote the field. The primary objective of this paper is to throw light on the current scenario of animal-assisted therapy in India. The relevant databases such as Scopus, Google Scholar, Proquest, PubMed, and JSTOR were searched to identify the research literature. The organizational websites, news, and blog articles, as well as institutional repositories, were explored to maximize the evidence. A total of 24 articles were found which included published research articles as well as unpublished conference papers. Results found a dearth of practice and research throughout the country indicating an urgent need to direct steps in promoting the growth of the field. The contemporary issues in the implementation of animal-assisted therapy such as cultural and religious beliefs, lack of awareness, lack of practising organizations and therapists warrant immediate attention. Reducing the research and practice gap alongside focusing on creating awareness, changing public perception, introducing coursework in educational institutions, the publication of evidence-based research will help in the acceptance and growth of this novel therapeutic field. 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
A Relative Analysis on the Spotting of Cardiovascular Disease Employing Machine Learning Techniques
Heart is one of the significant segments in the human body since it powers blood to the all the pieces of the body. Blood courses through the vein. Cardiovascular sickness is corresponded with the blockage of vein. The sign of heart sickness depends whereupon condition is impacting an individual. The term coronary illness is ordinarily utilized instead of cardiovascular infection. Dilated cardiomyopathy, Heart failure, Arrhythmia, Pulmonary stenosis, Mitral regurgitation, Coronary artery disease, Myocardial infraction, Mitral valve prolapse, Hypertrophic cardiomyopathy are the sorts of coronary illness. The several machine learning techniques are analyzed to spot heart disease. This paper gives relative investigation of coronary illness expectation utilizing machine learning. 2021 IEEE. -
A Relative Reference Responsive LRU based Page Replacement Algorithm for NAND Flash Memory
The acceptance of NAND flash memories in the electronic world, due to its non-volatility, high density, low power consumption, small size and fast access speed is hopeful. Due to the limitations in life span and wear levelling, this memory needs special attention in its management techniques compared to the conventional techniques used in hard disks. In this paper, an efficient page replacement algorithm is proposed for NAND flash based memory systems. The proposed algorithm focuses on decision making policies based on the relative reference ratio of pages in memory. The size adjustable eviction window and the relative reference based shadow list management technique proposed by the algorithm contribute much to the efficiency in page replacement procedure. The simulation tool based experiments conducted shows that the proposed algorithm performs superior to the well-known flash based page replacement algorithms with regard to page hit ratio and memory read/write operations. 2021, Webology. All Rights Reserved. -
A reliable inter-domain routing framework for autonomous systems using hybrid Blockchain
Inter-domain networks face several routing challenges, such as security, scalability, and reliability concerns in existing BGP-based systems. These challenges are exacerbated by the increasing number of interconnected networks and the lack of a standardized approach for routing data between them. Hybrid Blockchain-based framework has proposed for inter-domain routing in autonomous systems in this research. The framework combines the use of traditional routing protocols with the distributed ledger technology of Blockchain. It leverages the salient features of both to create a more secure and efficient routing framework. The Blockchain component provides a decentralized and tamper-proof ledger for storing routing information, while the traditional routing protocols handle the actual exchange of data between autonomous systems. The framework is designed to enhance the security of inter-domain routing by incorporating the use of digital signatures and information sharing among participating autonomous systems. Each participating system maintains a copy of the distributed ledger and can verify the authenticity of routing information using digital signatures. It ensures that only legitimate and authorized data is transmitted between autonomous systems, mitigating the risk of malicious attacks or illegitimate routing. The proposed framework obtained 87.73 % Route calculation Speed, 90.41 % Route filtering, 93.77 % Fault tolerance, 94.10 % Load balancing, 95.54 % Hop count, 95.13 % bandwidth consumption, 93.94 % Security Management and 96.29 % Convergence time. The framework employs a consensus mechanism for updating and validating the routing information, ensuring consistency and accuracy in the routing decisions. It also reduces the reliance on a single central authority and distributes the decision-making process among participating systems. 2024 Elsevier Ltd -
A Reliable Method of Predicting Water Quality Using Supervised Machine Learning Model
Water contributes to around 70% of the world's exterior and is perhaps the primary source essential to supporting life. The rapid growth of urban and industrial geographies has prompted a disintegration of the quality of water at a concerning pace, bringing about nerve-racking sicknesses. Water quality has been expectedly assessed through costly and tedious lab and measurable examinations, which render the contemporary thought of continuous observing disputable. The disturbing results of helpless water quality require an elective strategy, which is speedier and more economical. With this inspiration, this exploration investigates a progression of administered AI calculations to appraise the Water Quality Index (WQI), which acts as a unique attribute to express the generic nature of water. The proposed system utilizes multiple info boundaries, specifically, temperature, pH, dissolved O2 concentration, and all-out broken down molecules. Of the multitude of utilized regression calculations and slope boosting, the water quality index can be expected most productively, with an MSE of 0.27. The propositioned study accomplishes acceptable precision by utilizing a minimum number of features to improve the chances of it getting implemented progressively in water quality recognition frameworks. 2022 IEEE. -
A Representation-Based Query Strategy to Derive Qualitative Features for Improved Churn Prediction
The effectiveness of any Machine Learning process depends on the accuracy of annotated data that is used to train a learner. However, manual annotation is expensive. Hence, researchers adopt a semi-supervised approach called active learning that aims to achieve state-of-the-art performance using minimal number of samples. Although it boosts classifier performance, the underlying query strategies are unable to eliminate redundancy in selected samples. Redundant samples lead to increased cost and sub-optimal performance of learner. Inspired by this challenge, the study proposes a new representation-based query strategy that selects highly informative and representative subsets of samples for manual annotation. Data comprises messages of a set of customers sent to a service provider. Series of experiments are conducted to analyze the effectiveness of the proposed query strategy, called 'Entropy-based Min Max Similarity' (E-MMSIM), in the context of topic classification for churn prediction. The foundation of E-MMSIM is an algorithm that is popularly used to sequence proteins in protein databases. The algorithm is modified and utilized to select the most representative and informative samples. The performance is evaluated using F1-score, AUC and accuracy. It is observed that 'E-MMSIM' outperforms popular query strategies, and improves performance of topic classifiers for each of the 4 topics of churn prediction. The trained topic classifiers are used to derive qualitative features. These features are further integrated with structured variables for the same group of customers to predict churn. Experiments provide evidence that inclusion of qualitative features derived using E-MMSIM, enhance the performance of churn classifiers by 5%. 2013 IEEE. -
A research note: More to ponder on the perspectives of sustainability of tourism destinations
This research note focused on tapping the research opportunities on the perspectives of sustainability on tourism destinations. Being a short communication, the research note was created using the literary sources that concentrated only on the sustainability of tourism destinations. Growing tourism attributes; need for positioning destinations in competitive industrial markets; rapid changes in tourism market characteristics, motives, and opportunities; and mainly to sustain the tourism resources for better future consumption and preservation were the primitive forces to undertake the research note, which would facilitate further research works in the arena. The communications highlighted the integral and in-depth aspects such as centrality of sustainability, tourists knowledge about sustainability, tourists responsibility towards sustainability of destinations and natural resources, destination behavior towards sustainability, blending culture and sustainability, and rural destinations and their relevance on a sustainable future. Beneficial keynotes for policy makers and others thereof were enumerated throughout the note. 2021, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
A research on profitability and dividend using Arima model with reference to steel sector
In India Indian, Iron and Steel Industry plays significantly for the overall growth and development of the country. Based on the budget of Ministry of Steel declares that steel industry contributes 2% of the Indias GDP, and its weight is 6.2% in the Index of Industrial Production(IPP). The sector able to grow by itself globally. In India steel production in one Million Tones in 1947, now its become the world's 2nd largest producer next to China. India's GDP declines 5% in 2019 on account of rising Inflation, GST and strict monetary control. This medium made the domestic demand weeker which grew 3.3% in 2019, Despite the rise in last Quater. BEIESP. -
A Retrospection on Mercury Contamination, Bioaccumulation, and Toxicity in Diverse Environments: Current Insights and Future Prospects
Owing to various industrial applications of mercury (Hg), its release into the environment at high concentration is becoming a great threat to living organisms on a global scale. Human exposure to Hg is greatly correlated with contamination in the food chain through cereal crops and sea foods. Since Hg is a non-essential component and does not possess a biological role and exhibits carcinogenic and genotoxic behaviour, biomonitoring with a focus on biomagnification of higher living animals and plants is the need of the hour. This review traces the plausible relationship between Hg concentration, chemical form, exposure, bioavailability, bioaccumulation, distribution, and ecotoxicology. The toxicity with molecular mechanisms, oxidative stress (OS), protein alteration, genomic change, and enzymatic disruptions are discussed. In addition, this review also elaborates advanced strategies for reducing Hg contamination such as algal and phytoremediation, biochar application, catalytical oxidation, and immobilization. Furthermore, there are challenges to overcome and future perspectives considering Hg concentrations, biomarkers, and identification through the nature of exposures are recommended. 2023 by the authors. -
A reverse logistics model for optimization in waste collection
Sustainability has become a major concern in the development of human society. This requires solution of certain issues and involves social, technical, legislative, and other factors. An important concern is to minimize the generation of wastes, prevent environmental deterioration caused by the generation of wastes, and to enhance the value of recovery from the wastes. The reverse logistics network is helpful in this regard as its mission is to collect and transport used products and packages based on the balance of cost and environment. A good reverse logistics network is important for firms to gain more profits. This paper proposed a linear programming model for reverse logistics in which collection is done when the recyclables bin is half full. This limit can be varied from place to place, depending on the collection of recyclables. The model aimed to reduce transportation cost by setting up a schedule for collection and took into account the profit obtained by recycling. It also considered a penalty for late collection so that there is no piling up of waste, thus reducing the probability of items deteriorating due to weather or moisture content. 2015. -
A Reversible Hybrid Architecture forMultilayer Memory Cell inQuantum-Dot Cellular Automata withMinimized Area andLess Delay
CMOS innovation shows limited features when diminishing the size and region of a circuit. The burden of such a technology incorporates higher force utilization and also shows some temperature issues. Quantum-Dot Cell Automata is another innovation which is useful to defeat any of its weaknesses. The reversible rationale is innovation used to diminish the force misfortune in QCA. QCAs are utilized to plan recollections requiring a high working rate. In the following research, construction of reversible memory is proposed in QCA. It is designed by using a 3-layer innovation that altogether has an effect on the decreased size of the circuit. The reversible memory proposed here has 61% increase in cell number, with a 74% enhancement in the territory inhabitance, and 59% decrease in delay contrasted with any previous optimal designs. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Review and Comparative Study on Surface Vehicle Path Planning Algorithm
Autonomous Surface Vehicles (ASV) is very active area of robotics. There are so many projects are going on and doing research on monitoring and surveying on environment. There are significant studies on AS V's reverie, sea and coastal environments. Many algorithms are used by different researchers for path planning or route planning. Programmed recreation projects of boat route can be a useful asset for operational arranging and Layout investigations of conduits. In such a recreation framework the key undertakings of self-ruling course finding, and impact evasion are done by a reproduction program itself without or minimum interaction of a human pilot. That is from numerous points of view like programmed route frameworks in that they are intended to do self-governing route securely and proficiently without the requirement for Human intercession or to offer exhortation to the guide in regard to the best game-plan to take in certain circumstances. There are two key errands of programmed transport route frameworks: course finding and Collision evasion. 2021 ACM.