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A review of innovative bond instruments for sustainable development in Asia
Purpose: Advancing the economies in Asia toward meeting sustainable development goals (SDGs) needs an unprecedented investment in people, processes and the planet. The participation of the private sector is necessary to bridge the financing gap to attain this objective. Engaging the private sector can contribute significantly to attaining the 2030 agenda for SD. However, the financial markets in Asian economies are yet to realize this potential. In this context, this paper aims to discuss the state of finance for SD in Asia and identifies innovative financial instruments for attracting private investments for SDs in these economies. Design/methodology/approach: This study relies on published articles, reports and policy documents on financing mechanisms for SD. The literature review covered journal data sources, reports from global institutions such as the UN, World Bank, International Monetary Fund and think-tanks operating in the field of climate change policies. Though the topic was specific to financial market instruments, a broader search was conducted to understand the different sources of sustainable finance available, particularly in Asia. Findings: The investments that are required for meeting the SDGs remain underfunded. Though interest in sustainability is growing in the Asian economies, the financial markets are yet to transition to tap the growing interest in sustainable investing among global investors. This paper concludes that to raise capital from private investors the Asian economies should ensure information availability, reduce distortions and unblock regulatory obstacles. It would also need designing policies and introducing blended financing instruments combining private and public funds. Research limitations/implications: Though the study has grouped Asian economies, the financing strategy for SDGs should be developed at the country-level considering the domestic financial markets, local developmental stage, fiscal capacity and nationally determined contributions. Further research can focus on developing country-specific strategies for using innovative financial instruments. Originality/value: Mobilizing funds for implementing the 2030 Agenda for SD is a major challenge for Asian economies. The paper is addressed to national policymakers in Asian economies for developing strategies to raise capital for SD through private participation. It provides opportunities for revisiting national approaches to sustainable finance in these economies. 2021, Emerald Publishing Limited. -
A Review on Flood Prediction Algorithms and A Deep Neural Network Model for Estimation of Flood Occurrence
Flood occurs as often as possible happens due to many environmental changes in our planet in the present years. The occurrence and damages caused by flood is very high. Major cause of flood is due to heavy rainfall which in turn increases the water level of the rivers and other water bodies. The various factors that play a major role in the occurrence of rainfall are rise in temperature, humidity level, dew point, pressure in and around the area of concern, wind speed, etc. In order to reduce the number of victims due to flood it is necessary to have a system to predict flood occurrence. In this paper, we classify and analyzed the various prediction algorithms which show usage of Deep Neural Network produces better results. In addition, a design model has been proposed to predict the flood by training the Deep Neural Network with the above-mentioned factors. 2020, Asian Research Association. All rights reserved. -
A review on metal nanoparticles from medicinal plants: Synthesis, characterization and applications
Plant extracts contain secondary metabolites which have the potential to act as reducing and stabilizing agents contributing to a greener and more efficient method to synthesize nanoparticles. Rapid growth of Nanotechnology has led to an increased demand in various fields. This review summarizes the use of potent medicinal plant extracts to synthesize metal nanoparticles, methods employed to characterize the properties of the nanoparticles and its application. Characterization of the nanoparticle based on its shape, size, chemical bonds, surface properties, hydrodynamic diameter and crystalline structure using techniques such as UV-Visible Spectroscopy, XRD (X-ray Diffraction), TEM (Transmission Electron Microscopy), SEM (Scanning Electron Microscopy), EDS (X-ray energy dispersive spectroscopy), DLS (Dynamic Light Scattering), Zeta Potential and FTIR (Fourier Transform-Infrared Spectroscopy) are elaborated. The synthesized metal nanoparticles have wide ranges of applications such as antimicrobial activity, antioxidative capability, anticancer effect, antidiabetic properties, plant growth enhancement, dye degradation effects and anti-larval properties. Recent advances in nanotechnology with special emphasis on plant metabolites provide an insight into their usage as plant-derived edible nanoparticles (PDNPs). Applications, limitations and future prospects of this technology have also been briefly discussed. 2021 Bentham Science Publishers. -
A review on quantum utility for secure authentication protocol towards cryptographic standard in quantum dot cellular automata
QCA, which stands for Quantum Dot-Cellular Automata, is a nanotechnology model that offers an alternative solution to the widely used CMOS technology. Unlike CMOS, QCA is a semiconductor-less technology that transmits information based on the charge of electrons and the electrostatic repulsion between them. This technology provides several advantages over CMOS, including higher device density, faster switching speed, and lower power consumption. When it comes to cryptographic applications, QCA circuits can be extremely useful. Both encryption and decryption processes can be implemented using logic circuits based on QCA. The research paper describes a basic method for generating ciphertext in QCA, which is useful in secure nano communication based on QCA. The paper discusses how to achieve secure authentication in encrypted communication using QCA. To evaluate the performance and test the proposed method, the researchers used the QCA Designer-2.0.3 tool. This is a software tool specifically designed for designing and simulating QCA circuits. It enables researchers to model and analyze the behavior of QCA-based systems, allowing them to evaluate the effectiveness and feasibility of their proposed encryption technique. Overall, the research paper aims to present a secure encryption method using QCA and demonstrates its implementation and testing using the QCA Designer-2.0.3 tool. By leveraging the unique properties of QCA, such as high device density and low power consumption, the researchers aim to provide a novel approach for secure nano communication and cryptographic applications. Taru Publications. -
A review on semiconductor nanoparticles in photovoltaic cells /
International Journal of Advanced Scientific Research And Management, Vol.4, Issue 4, pp.43-50, ISSN No: 2455-6378. -
A review on serverless architectures-Function as a service (FaaS) in cloud computing
Emergence of cloud computing as the inevitable IT computing paradigm, the perception of the compute reference model and building of services has evolved into new dimensions. Serverless computing is an execution model in which the cloud service provider dynamically manages the allocation of compute resources of the server. The consumer is billed for the actual volume of resources consumed by them, instead paying for the pre-purchased units of compute capacity. This model evolved as a way to achieve optimum cost, minimum configuration overheads, and increases the application's ability to scale in the cloud. The prospective of the serverless compute model is well conceived by the major cloud service providers and reflected in the adoption of serverless computing paradigm. This review paper presents a comprehensive study on serverless computing architecture and also extends an experimentation of the working principle of serverless computing reference model adapted by AWS Lambda. The various research avenues in serverless computing are identified and presented. Universitas Ahmad Dahlan. -
A road map on nanostructured surface tuning strategies of carbon fiber paper electrode: Enhanced electrocatalytic applications /
Journal of Science: Advanced Materials and Devices, Vol.7, Issue 3, ISSN No: 2468-2179.
Impressive characteristics of carbon fiber paper (CFP) electrodes propound greater demand in electrochemical applications. CFP has a network structure composed of interwoven carbon fibers (CFs). The macroporous structure, chemical inertness, high conductivity, low cost, corrosion resistance, good electrical properties, mechanical strength, and self-standing capabilities have led to the large-scale acceptance of CFP. This review appraises the current progress of CFP based electrodes for electrocatalytic applications in the field of electrochemical sensors, electrochemical capacitors, batteries, electro Fenton oxidation, electrooxidation of alcohols, water splitting, hydrogen evolution reaction (HER), and oxygen evolution reaction (OER) together with the different fabrication strategies on the CFP substrate in an organized manner. -
A road map on synthetic strategies and applications of biodegradable polymers /
Polymer Bulletin, Vol.79, ISSN No: 0170-0839 ( print) 1436-2449 (Online).
Biodegradable polymers have emerged as fascinating materials due to their non-toxicity, environmentally benign nature and good mechanical strength. The toxic effects of non-biodegradable plastics paved way for the development of sustainable and biodegradable polymers. The engineering of biodegradable polymers employing various strategies like radical ring opening polymerization, enzymatic ring opening polymerization, anionic ring opening polymerization, photo-initiated radical polymerization, chemoenzymatic method, enzymatic polymerization, ring opening polymerization and coordinative ring opening polymerization have been discussed in this review. -
A Sampling-Based Stack Framework for Imbalanced Learning in Churn Prediction
Churn prediction is gaining popularity in the research community as a powerful paradigm that supports data-driven operational decisions. Datasets related to churn prediction are often skewed with imbalanced class distribution. Data-level solutions, like over-sampling and under-sampling, have been commonly used by researchers to address this problem. There are limited number of case studies that attempt to evolve these data-level solutions by integrating them with computationally advanced frameworks, like ensembles. Ensembles primarily employ algorithmic diversity using a fixed set of training instances to achieve superior performance. This study aims to introduce algorithmic diversity in ensembles by modifying the fixed set of training instances using diverse sampling strategies to increase predictive performance in imbalanced learning. Data is acquired from the world's largest open hotel commerce platform company. A four-part series of experiments is conducted to analyze the effectiveness of sampling techniques and ensemble solutions on model performance. A new sampling-based stack framework called 'Stacking of Samplers for Imbalanced Learning' is proposed. The framework combines the prediction capabilities of sampling solutions to stimulate the information gain of the meta features in ensemble. It is observed that the proposed framework leads to improvement in model performance with AUC of 86.4% and top-decile lift of 4.7 for customers of the hotel technology provider. Additionally, results show that the framework records a higher information gain for meta features used in a stack, compared to commonly used stack frameworks. 2013 IEEE. -
A scientometric analysis of social entrepreneurship
Impactful studies in social entrepreneurship area has garnered attention of the researchers in recent times. The interest and importance is generated in this area because of its nature in addressing social problems and welfare of the communities and societies. The study aims at providing insight on scientometric analysis in the domain of social entrepreneurship. The study further identifies researchers exploring sub domai ns considering parameters like publication language, outlook of publication patterns that changed every year, contextual journals to perform a literature review, primary subject areas in which research is being conducted, most productive institutes/universities, most productive countries where research is being conducted in the domain of social entrepreneurship and the most prolific authors in the area of social entrepreneurship. This study is a pathfinder for researchers with plans to conduct studies in social entrepreneurship domain by leading them to relevant scholarly journals and authors for greater impact. IJSTR 2019. -
A Scoping Review of Formal Care to Children with Special Needs during the Covid-19 Pandemic
The Covid-19 pandemic caused an unprecedented closure of direct service for children with special needs (CSNs), which shifted service to remote mode. This scoping review analyzed the strategies adopted by different formal care services for CSNs, their strengths and weaknesses, and the challenges faced by the formal care providers (FCPs). This study identified relevant articles through academic databases and Google searches using appropriate search strings and keywords. It included ten journal articles (n=10) and eight pieces (n=8) of grey literature through a meticulous selection process and extracted data. This review drew results by collating the descriptive numerical data analysis and qualitative thematic analysis and interpreting them. Reporting incor-porated all the possible items recommended by the PRISMA-ScR guidelines. This review demonstrated that pediatric rehabilitation adopted the telehealth approach and that special education changed to remote learning. When childcare programs in the USA functioned according to specific guidelines, residential care in South Asian countries faced a financial crunch. FCPs faced personal and professional challenges that required systematic training to deal with pandemic situations. This scoping review made suggestions for relevant policy formulations for equitable and effective service delivery to CSNs during pandemic situations, and it exposed new avenues for research. 2022 Authors. -
A Scoping Review on Integration of Electroencephalogram Neurofeedback Training for Alcohol Use Disorder: Clinical and Neurocognitive Outcomes
Background. The conventional treatment for alcohol use disorder (AUD) consists of dual treatment encompassing pharmacotherapy and psychotherapy. Nonetheless, the impact of these treatments on clinical and neurocognitive outcomes is only low to medium efficacy. Research studies substantiate the integration of electroencephalogram neurofeedback training (EEG-NFT) as an add-on tool with significant improvements in clinical and neurocognitive outcomes. Methods. A scoping review of the existing literature on EEG-NFT and AUD, which are open access, including review papers and empirical studies in the English language, and with human subjects are deemed worthy of the scope of this study. The keywords electroencephalogram neurofeedback training, alcohol use disorder, stress, neurocognition, and relapse were used. The primary sources of the literature search were Science Direct, Scopus, PubMed, and Google Scholar. A total of 35 articles have been included in the scoping review. Studies from the last 15 years were considered for the same. Results. This review revealed that EEG-NFT is a promising tool with significant improvements in stress levels, cognitive deficits, and relapse rates for individuals with AUD when used in integration with conventional treatments. Conclusion. Chronic alcohol use affects cognitive functions, escalates relapse rate, and increases stress experienced by the individual. The present study highlights the significance of NFT as a potent add-on treatment modality to improve clinical and cognitive outcomes, thereby facilitating abstinence and reducing relapse rates in individuals with AUD. Copyright: 2023. -
A Search for X-Ray/UV Correlation in the Reflection-dominated Seyfert 1 Galaxy Markarian 1044
Correlated variability between coronal X-rays and disk optical/UV photons provides a very useful diagnostic of the interplay between the different regions around an active galactic nucleus (AGN) and how they interact. AGNs that reveal strong X-ray reflection in their spectra should normally exhibit optical/UV to X-ray correlation consistent with reprocessingwhereas the optical/UV emission lags behind the X-rays. While such correlated delay has been seen in some sources, it has been absent in others. Mrk 1044 is one such source that has been known to reveal strong X-ray reflection in its spectra. In our analysis of three long XMM-Newton and several Swift observations of the source, we found no strong evidence for correlation between its UV and X-ray lightcurves both on short and long timescales. Among other plausible causes for the nondetection, we posit that higher X-ray variability rather than UV and strong general relativistic effects close to the black hole may also be responsible. We also present results from the spectral analysis based on XMM-Newton and NuSTAR observations, which show the strong soft X-ray excess and iron K? line in the 0.3-50 keV spectrum that can be described by relativistic reflection. 2023. The Author(s). Published by the American Astronomical Society. -
A secure and light weight privacy preserving data aggregation algorithm for wireless sensor networks
WSN is a collection of sensors, which senses critical information related to military, opponent tracking, patient health details etc. These sensed critical and private data will be collected and aggregated by aggregators and forward it to the base station. Due to the involvement of sensitive data, there is a demand for secure transmission and privacy preserving data aggregation. In this paper, we propose a light weight, secure, multi party, privacy preserving data aggregation scheme, in which one or more sensors share their private data with aggregator securely without revealing the original content. The aggregators also perform the aggregation operation without knowing the original content. 2020 Alpha Publishers. -
A Selective Excited-State Intramolecular-Proton-Transfer (ESIPT) Sensor for Copper(II) Based on Chelation-Enhanced Quenching and Off-On Detection of Amino Acids
We report the synthesis of 2-(4,5-diphenyl-1H-imidazole-2-yl)phenol (TPI-9) as an interesting fluorescent molecule displaying Excited-State Intramolecular-Proton-Transfer (ESIPT) with stokes shift of 120 nm. Phenolic compounds with the ability to form intramolecular hydrogen bonds and subsequent proton transfer are known as ESIPT fluorophores. Proton accepting ability can increase significantly by tailoring electron-donating groups. With the assistance of an environment-friendly organocatalyst, 10-camphor sulfonic acid (10-CSA), TPI-9 was synthesized to introduce substituents with electron-donating abilities to develop an efficient ESIPT mechanism. Factors influencing the emission, such as solvent, pH, and metal ions, are investigated. Quenching of fluorescence by Cu2+ through chelation enhancement quenching effect with a high selectivity allowed the establishment of a Cu2+ sensor with an LoD of 0.57 ppm and a ratiometric estimation with an LoD of 0.73 ppm. Metal binding (2 : 1) stoichiometry and quenching constant (0.0072 mol?1s?1) are calculated from Job's and Stern-Volmer plots. Density functional theory (DFT) calculations are in accordance with the experimental results. Competitive replacement of TPI-9 by amino acids restores ESIPT, consequently, the fluorescence. Thus, an off-on fluorescence sensor for amino acid estimation is developed under 1 minute incubation. A linear relationship between amino acid concentration and fluorescence intensity is in 0-20 ?g/mL range, and the LoD is less than 2.2 ?g/mL. 2023 Wiley-VCH GmbH. -
A self-cooperative trust scheme against black hole attacks in vehicular ad hoc networks
The main objective of the Vehicular Adhoc NETwork (VANET) is to provide secure communications for the vehicles in the network without fixed infrastructures. It inherits all the properties of the MANET. Achieving reliable routing to avoid various routing attacks is the major concern in the vehicular network. Routing attacks degrade the performance of the network. Black hole attack is one of the routing attacks, which drops the data packets without forwarding them to the destination vehicle. Different routing schemes are proposed to provide security against these attacks, which still have security issues. Hence a new self-cooperative trust scheme is proposed in this paper, to detect single as well as collaborative black hole attackers in the network. Two processes: self-detection and cooperative detection, are used to detect attackers in the network. Results show that the proposed scheme has better performance in terms of throughput, PDR and delay. Copyright 2021 Inderscience Enterprises Ltd. -
A short review on environmental impacts and application of iron ore tailings in development of sustainable eco-friendly bricks
Increased mining activity of iron ore has led to the generation of voluminous wastes of various nature, especially during the different stages of its extraction and production. The improper disposal of such waste causes negative impact on the environment. One such waste which is generated during the beneficiation process of iron ore is waste iron ore tailings, which is also termed as IOT. Further, dumping of IOT on open ground creates huge dumping sites. This dumping sites have been a concern to the environment and human population in its close vicinity. Therefore, a need to effectively use IOT has become one of the subjects of interest for many researchers. This article provides a short review of environmental problems caused due to improper disposal of IOT, and also reviews on the reuse methods of IOT in the construction sector, which helps to alleviate the environmental pollution associated with improper disposal of IOT. Furthermore, reuse of IOT in construction sector reduces the exploitation of the virgin materials for production of construction material, and thus reducing depletion of natural resources. Based on the existing literatures and findings it was observed that the use of IOT to develop stable building blocks using unconventional methods showed great potential and improved performance, when compared with conventional materials such as clay fired bricks. 2021 -
A Signature-Based Mutual Authentication Protocol for Remote Health Monitoring
Remote health monitoring can offer a lot of advantage to all the players in healthcare industry and it can contribute to reduced healthcare expenses. Wireless medical sensor networks capable of accumulating and transferring vital parameters of patients play a crucial role in remote health monitoring. Security and privacy are major concerns preventing the patients from adopting this technology with an open mind. This paper presents a signature-based authentication protocol for remote health monitoring. The work also discusses an authentication protocol for the mutual authentication of users and medical server. The protocol does not require the server to maintain a password table. The proposed algorithms are resistant to various attacks such as replay attack, stolen verifier attack, and privileged insider attack. The work includes the informal and formal security analysis of the proposed protocols. Scyther tool is used for formal security analysis and the results show that the protocol is resistant to various common and automated attacks. 2019, Springer Nature Singapore Pte Ltd. -
A Simple and Efficient [(n-Bu3Sn)2MO4]n Catalyzed Synthesis of Quinazolinones and Dihydroquinazolinones
A novel unprecedented approach for the synthesis of various quinazolinones and dihydroquinazolinones has been using [(n-Bu3Sn)2MO4]n as a catalyst. The reaction has been screened in various solvents and a gram scale experiment has also been demonstrated under given conditions. Further, the substrate scope of the reaction and the recyclability of the catalyst have also been studied. 2021 Taylor & Francis Group, LLC.