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Can Renewable Energy Be a Driving Factor for Economic Stability? An In-Depth Study of Sector Expansion and Economic Dynamics
India has emerged as one of the world's most appealing locations for renewable energy development. It has set lofty renewable energy goals to reach 450 gigawatts (GW) capacity by 2030. These aims indicate India's determination to move to greener and more sustainable energy sources. India has been investing in R&D to promote technological innovation in renewable energy. This includes improvements to solar photovoltaic technology, wind energy, energy storage technologies, and smart grid systems. Innovation is critical for improving efficiency, lowering prices, and increasing the reliability of renewable energy sources. This paper aims to analyse the linkages between economic growth and renewable energy usage in India. For this, the Granger Causality technique is adopted, and it is found that no short-run causality exists among the economic growth and RE installed capacity. However, Industrial Production Granger Causes both GDP and Renewable Energy Capacity. When the stock price data of the last five years of top renewable energy companies was also collected, it was found that all the companies are showing an upward trend. While renewable energy is growing rapidly, especially solar and wind power, it is insufficient to meet the bulk of India's energy demands. Renewables contribute to reducing carbon emissions and diversifying the energy mix, but they still account for a smaller percentage compared to thermal power. 2024, Creative Publishing House. All rights reserved. -
Can we improve the outcome of pregnancies with low serum PAPP-A in the first trimester?
Low birth weight is associated with various complications, and recent findings rely on the fact that micronized progesterone supplementation leads to improved birth weight, which is crucial for addressing concerns related to fetal growth. Objective: This study aimed to assess the impact of micronized progesterone (VMP4) supplementation on pregnancies with low serum pregnancy-associated plasma protein-A (PAPP-A) multiples of the median (MoM) values during first-trimester screening. Methods: Out of 8933 patients evaluated, 116 pregnant women with low PAPP-A concentrations in their blood and no fetal chromosomal anomalies (CAs) were included. Three groups were formed: group 1 received VMP4 from 11 to 16weeks (29 women, 25%), group 2 received VMP4 from 11 to 36weeks (25 women, 21.5%), and group 3 (62 women, 53.5%) served as controls without receiving progesterone. Results: Results indicated that group 3 had higher rates of complications, including miscarriages (16.37%), preterm delivery (17.8%), and fetal developmental abnormalities (19.4%). Birthweight variations were elevated in pregnancies without progesterone, contrasting with lower variations in VMP4 groups. Group 2, receiving VMP4 until 36weeks, reported the lowest incidence of abortion and preterm birth (PB), along with the highest mean birth weight. Conclusions: The conclusion suggests that 200 mg per day of VMP4 up to 36weeks of supplementation led to fewer placental-related complications in women with very low PAPP-A at first-trimester screening (0.399 MoM). By reporting lower rates of miscarriages, PBs, and fetal developmental abnormalities in the micronized progesterone-treated groups, the study suggests a potential reduction in complications. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Cancer Prognosis by Using Machine Learning and Data Science: A Systematic Review
Cancer is one of the most fatal diseases in the world and the leading cause for most deaths worldwide. Diagnosing cancer early has become the need of the day for doctors and researchers as it allows them to categorize patients as high-risk and low-risk categories which will eventually help them in correct diagnosis and treatment. Machine learning is a subset of artificial intelligence that makes use of raw data to make predictions and insights. Using machine learning for cancer prognosis has been under study for a long time and several papers have been published regarding the same. Even though many papers have been published on the usage of statistical methods for cancer prognosis, it has been proved that machine learning models provide more accuracy when compared to conventional statistical methods of detection. These machines can be trained to detect abnormalities such as a tumour by looking at real-world examples. Models such as artificial neural networks, decision trees, clustering techniques, and K-Nearest-Neighbours (KNNs) are being used for cancer prediction, prognosis and also research purposes. The key aim of this article is to go through the popular key trends in using machine learning algorithms for cancer prognosis, types of input datasets to be fed, different types of cancers that can be studied and also the performance of these models. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Cancer Tumor Detection Using Genetic Mutated Data and Machine Learning Models
Early detection of a disease is a crucial task because of unavailability of proper medical facilities. Cancer is one of the critical diseases that needs early detection for survival. A cancer tumor is caused due to thousands of genetic mutations. Understanding the genetic mutations of cancer tumor is a tedious and time-consuming task. A list of genetic variations is analysed manually by a molecular pathologist. The clinical strips of indication are of nine classes, but the classification is still unknown. The objective of this implementation is to suggest a multiclass classifier which classifies the genetic mutations with respect to the clinical signs. The clinical evidences are text-evidences of gene mutations and analysed by Natural Language Processing (NLP). Various machine learning concepts like Naive Bayes, Logistic Regression, Linear Support Vector Machine, Random Forest Classifier applied on the collected dataset which contain the evidence based on genetic mutations and other clinical evidences that pathology or specialists used to classify the gene mutations. The performances of the models are analysed to get the best results. The machine learning models are implemented and analyzed with the help of gene, variance and text features. Based on the variants of gene mutation, the risk of the cancer can be detected and the medications can be prescribed accordingly. 2022 IEEE. -
Canine-assisted Therapy in Neurodevelopmental Disorders: A Scoping Review
Introduction: Animal-Assisted Therapy has been advocated to benefit individuals with neurodevelopmental disorders. Among all the various kinds of animals used in the therapy, dogs are the most utilized because of their temperament and accessibility. Methods: This systematic scoping review was carried out to present the existing literature employing canine-assisted therapy in the diverse population of neurodevelopmental disorders. The study used the Arksey and O'Malley framework for scoping reviews. Several databases including the gray literature were searched for publications on animal-assisted therapy. Results: The search yielded 4898 articles of which 41 articles were eliigible for inclusion into the review. Conclusions: Scrutiny of the articles suggested a dearth of studies in the various sub-diagnostic categoriesfor neurodevelopmental disorders along with a lack of focus on adult populations with this diagnosis. In addition, the critical need for standardization of therapy guidelines and promotion of animal welfare is reaffirmed. 2022 Elsevier GmbH -
Canopy removal on satellite images using classification and contrast enhancement
The increasing the usage of satellite remote sensing for a civilian purpose has proved to be the most cost-effective mapping environmental changes with regard to natural resources, particularly in developing countries. Forests as one part of the wildlife of human societies in economic growth and permanency of natural resources in the countries of the world. But because of various details such as the growth of population, progressively varying forest to the other unfitting applications such as agriculture, providing energy and fuel, millions of hectares from the natural means are destroyed every year, and the remainder of the surface changes quantitatively and qualitatively. For better management of the forests, the evolution of forest area and rate of forest concentration should be examined. It is achievable that, there isnt any change in the field of the forest during the time, but the density of forest canopy is changed. Estimation of forest canopy cover has recently become an essential part of the forest. Therefore, the research study is to develop Forest Canopy Remover, which is used to get an accurate result of Forest and deforested area from the satellite earth images. It is used to calculate forest density using vegetation. Then, the changes in area and forest density during a particular period can be distinguished. 2020 IJSTR. -
Capacitive Behaviour of Imidazole Azo Modified Carbon Nanotubes/Polypyrrole Composite in Aqueous Electrolytes
Here, we reported imidazole azo (Im) modified carbon nanotubes (CNT) grafted polypyrrole (PPy) via the chemical oxidation method. The synthesized hybrid material has shown a unique structure consisting of carbon nanotubes with a conductive network via polypyrrole. The presence of Im derivatives has helped CNTs to enhance their electrochemical performances. The as synthesized composite was characterized using various techniques like FT-IR, XRD, XPS, and Raman spectroscopy. The morphological studies were performed using SEM technique which also confirmed the nature of the composite. The electrochemical performances of the electrode material were investigated using cyclic voltammetry, galvanostatic charge-discharge, and electrochemical impedance spectroscopy in various electrolytes. The best performance of the electrode material was observed in 1 M H2SO4 with a specific capacitance of 305 F g?1 at a current density of 1 A g?1. The electrode material also showed a coulombic efficiency of 96% even after 5000 cycles. 2023 The Electrochemical Society (ECS). Published on behalf of ECS by IOP Publishing Limited. -
Capacitive dominated charge storage in supermicropores of self-activated carbon electrodes for symmetric supercapacitors
The present work demonstrates a systematic study of pore size and specific surface area (SSA) of biomass-derived carbon and the choice of electrolyte concentrations affecting charge-storage mechanism (surface controlled and diffusion controlled) and electrochemical behaviour. Porous nanocarbons derived from Caesalpinia Sappan pods were synthesized by pyrolysis at 400, 600, and 800 C. Pyrolysis at 800 C was found suitable for the self-activation mechanism which formed bimodal porous nanocarbons with a high SSA of 675 m2/g. A maximum specific capacitance of 261.8 F/g at 0.5 A/g in 5.0 M KOH was observed for electrode materials synthesized at 800 C. The highlight of the study is the porous nanocarbon synthesized at 800 C which was found to possess micropores of size 0.71.0 nm playing a pivotal role in enhancing capacitance. The effect of electrolyte concentration on capacitance and charge storage mechanisms was also analyzed. A diffusion-controlled self-discharge model is established for supercapacitor devices. The single cell can power a red LED for 15 min; exemplifying the sustainable strategy of the utilization of abundant bio-waste to efficient energy storage devices. 2022 Elsevier Ltd -
Capacity Aware Active Monitoring Load Balancing Principle for Private Cloud
Virtual machines (VMs) are the basic compute elements in cloud computing. There are load balancing principles associated with a job scheduler assigns the requests to these computing elements. Deploying an effective load balancing principle enhances better performance that ultimately achieves users satisfaction at the high level. Assigning an equal requests load appropriate to the capacity of the VMs will be a fair principle that can be the objective of any load balancing principle. Active monitoring load balancing principle assigns the requests to a server based on the pre-computed threshold limit. This paper presents a technique for assessing the capacity of the VMs based on a common attribute. This work measures each VMs processing ability as a percentage using the statistical method called Z-score. A threshold is quantified and the requests are proportioned based on this threshold value. Each server is then assigned with the proportioned requests. Suitable experiments were conducted Requests Assignment Simulator (RAS), a customized cloud simulator. The results prove that the performance of the proposed principle is comparatively better than a few load balancing principles. Areas of future extension of this work were also identified. 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Captcha-Based Defense Mechanism to Prevent DoS Attacks
The denial of service (DoS) attack, in the current scenario, is more vulnerable to the banking system and online transactions. Conventional mechanism of DoS attacks consumes a lot of bandwidth, and there will always be performance degradation with respect to the traffic in any of the communication networks. As there is an advent over the network bandwidth, in the current era, DoS attacks have been moved from the network to servers and API. An idea has been proposed which is CAPTCHA-based defense, a purely system-based approach. In the normal case, the protection strategy for DDoS attacks can be achieved with the help of many session schedulers. The main advantage is to efficiently avoid the DoS attacks and increase the server speed as well as to avoid congestion and data loss. This is majorly concerned in a wired network to reduce the delays and to avoid congestion during attacks. 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Capturing non-financial information in integrated reporting
In the contemporary business scenario, integrated reporting is a transformational form of corporate reporting. Integrated reporting provides material and substantial information about an entitys prospects, governance, strategy and actions that serve as a reflection of social and commercial viability within the holistic environment in which it operates (IIRC, 2013). Thus, in integrated reports, along with financial information the critical non-financial aspects that affect the reputation, performance and sustainability of the firm are also required to be reported by companies. While regulations are instituted for compulsory divulgence of non-financial information as part of annual reports, there is a lot of ambiguity regarding the non- financial items to be included and the manner of reporting. This paper delineates the non-financial capital components for disclosure in integrated reports. It also discusses the current practices of integrated reporting world over, which will help organisations gain clarity in presenting the non-financial items under different heads of non-financial capitals. Copyright 2022 Inderscience Enterprises Ltd. -
Carbon Dioxide Neutralization across the Global Supply Chain
The increased impacts of climatic changes and global warming has led many organizations to adopt green initiatives in several areas of their business processes. Many multinational companies are moving towards reduction of carbon emission across its various operations. Carbon neutrality is the process where steps are taken to achieve net zero carbon dioxide emissions. This article proposes measures to achieve carbon neutrality across the supply chain globally. As part of its sustainability initiative, organizations have decided to reduce carbon consumption across their plants. This calls for estimation of carbon dioxide emissions and reducing the carbon footprint in the entire supply chain process. It also involves gauging Green House CO2 emissions during the transportation process for all TMC regions and Transportation models used by various companies. The main calculations include total CO2 emissions, CO2 Emissions per Ton. Of Goods Transported, CO2 Emissions per Transport Km. These calculations are done based on factors such as Full Truck Load, Less Truck Load, Sea mode of transportation and Air mode of transportation. An analysis is performed on the resulting calculation figures for different modes of transportation such as road, air and sea. The analysis shows that there is an increase in overall CO2e for Air mode of transportation. The least increase in overall Co2 is Sea mode of transportation. Through this analysis, it helps the company to take better decisions regarding the mode of transportation that they need to adopt to achieve carbon neutrality. The Electrochemical Society -
Carbon Disclosure and Organization Performance: A Literature Review
As a response to the threat of climate change, a growing number of businesses are voluntarily reporting carbon statistics. This article provides a comprehensive understanding of carbon disclosure, organization performance (OP), and cost of capital. This study aims to map the landscape of existing carbon disclosure and firm performance research completed over the past 10 years (2013-2022) utilizing bibliometric analysis. Sparked by the growing political, social, academic, and practical significance of controlling and reporting on climate-related concerns worldwide, this study analyzes the production and acquisition of information about significant regions and territories, institutions, publications, and channels for carbon disclosure and firm performance research using data from 878 publications retrieved from the Scopus database. To identify themes and subthemes in the research on carbon disclosure and firm performance, network analysis was utilized to reveal connections between the topics represented by keywords. Further, critical gaps have been highlighted in the literature, such as: the lack of carbon disclosure research across cross-sector settings, the lack of sectorial comparisons on the carbon disclosure practices, and the dearth of analyses of both pre-carbon disclosure and after-carbon disclosure practices and their impact on various financial and nonfinancial issues (for example, cost of capital and firm performance, sustainability, and climate change). Finally, this study makes specific recommendations for future carbon disclosure and firm performance research. 2023 Mary Ann Liebert, Inc., publishers. -
Carbon Dot-Based Fluorescence Resonance Energy Transfer (FRET) Systems for Biomedical, Sensing, and Imaging Applications
Carbon dots (CDs) emerge as a potential group of photo-luminescent nano-materials due to their excellent optical, electrical, and chemical properties, as well as their competence in a wide range of environmental applications. CDs have unique and appealing properties such as excellent stability, low toxicity, water solubility, and derivability. When coupled with CDs, fluorescence resonance energy transfer (FRET) results in the development of highly sensitive ratiometric fluorescence sensor probes with potential applications in bio-imaging, metal sensing, membrane dynamics, and environmental sensing. In this review, the progress and recent developments in CDs based FRET systems utilized for various environmental applications are conferred. An in-depth description is provided regarding the numerous donor/acceptor systems which when integrated with CDs generate efficient FRET systems. The review enables researchers to identify and develop specific systems which can be utilized to generate a FRET pair with potential physicochemical properties that aid the development of the same for various applications. 2023 Wiley-VCH GmbH. -
Carbon dots as an effective material in enzyme immobilization for sensing applications
In carbon dots (CDs), both graphene quantum dots and carbon quantum dots were the latest entrants to the carbon family, all of which are spherical carbon nanoparticles of size <10nm. CDs have found their way in the various applications in the field of chemical sensing, biosensing, bioimaging, photocatalysis, nanomedicine, and electrocatalysis ever since their discovery. CDs provide interesting attributes to electrochemical and optical biosensing using enzyme biosensor due to they have desired advantages of biocompatibility, excellent physicochemical properties, high resistance to photo bleaching, intrinsic non/low-toxicity, high solubility, large specific surface area for the binding of enzymes, and low quantum yields, as well as their ability for modification with the attractive surface area. Surface active functional groups such as epoxide, hydroxyl(OH), and carboxylic acid (COOH) groups can be used for the immobilizing biomolecules on CDs. The enzyme immobilization is a process which is generally carried out by ionic/covalent interaction, encapsulation, and adsorption. The process of adsorption is considered to be a simple, effective, and economical method for enzyme immobilization. Thus enzymes immobilized on CDs have shown significant improvement in both activity and stability. This chapter aims to throw light on the progress and development of enzyme immobilization (e.g., laccase, bovine serum albumin, and horseradish peroxidase) in the CDs, which acts as a probe for sensing application, with laying emphasis on their synthesis along with the challenges faced in this exciting and promising field. 2023 Elsevier Inc. All rights reserved. -
Carbon dots derived from frankincense soot for ratiometric and colorimetric detection of lead (II)
We report a simple one-pot hydrothermal synthesis of carbon dots from frankincense soot. Carbon dots prepared from frankincense (FI-CDs) have narrow size distribution with an average size of 1.80 nm. FI-CDs emit intense blue fluorescence without additional surface functionalization or modification. A negative surface charge was observed for FI-CDs, indicating the abundance of epoxy, carboxylic acid, and hydroxyl functionalities that accounts for their stability. A theoretical investigation of the FI-CDs attached to oxygen-rich functional groups is incorporated in this study. The characteristics of FI-CDs signify arm-chair orientation, which is confirmed by comparing the indirect bandgap of FI-CDs with the bandgap obtained from Tauc plots. Also, we demonstrate that the FI-CDs are promising fluoroprobes for the ratiometric detection of Pb2+ ions (detection limit of 0.12 ?M). The addition of Pb2+ to FI-CD solution quenched the fluorescence intensity, which is observable under illumination by UV light LED chips. We demonstrate a smartphone-assisted quantification of the fluorescence intensity change providing an efficient strategy for the colorimetric sensing of Pb2+ in real-life samples. 2022 IOP Publishing Ltd. -
Carbon Dots from Natural Sources for Biomedical Applications
Carbon dots (CD), a class of 0D nanomaterials, have gained much research attention over the years due to their uniqueness in properties such as tunable photoluminescence, biocompatibility, low toxicity, water-solubility, and chemical stability. Converting inexpensive biomass to valuable materials highlights the synthesis and applications of biomass-derived CDs. This review summarizes the research and development related to the synthesis, properties, and applications of biomass-derived CDs, furnishing a comprehensive list of biomass-derived CDs with their properties and potential applications. This review's discussions and references span the properties that equip CDs for their diverse biomedical applications, such as bioimaging, sensing, drug delivery, phototherapy, and nanomedicine. 2022 Wiley-VCH GmbH. -
Carbon dots-Zno/TiO2 ternary nanocomposite as a proficient material to enhance the performance of natural DSSC
A novel sustainable approach for enhancing the efficiency of dye-sensitized solar cells (DSSCs) involves the utilization of a combination of ZnO and carbon dots (CDs) derived from Citrus medica fruit extract, along with microwave-synthesized TiO2 nanoparticles for the preparation of the photoanode. Natural dyes such as Hibiscus rosa-sinensis and Allium Cepa peel are employed as sensitizers to reduce production costs. This co-activation method has demonstrated a significant improvement in the output parameters of the devices. Notably, the photoanode co-activated with ZnO-CD composite (ZnO-CD/TiO2) exhibits the most favorable output parameters when combined with Hibiscus rosa-sinensis dye (open circuit voltage (Voc) = 0.80 V, short circuit current density (Jsc) = 6.62 mA/cm2, fill factor (FF) = 64.20 %, photo conversion efficiency (PCE) = 3.40 %) and Allium Cepa peel dye (Voc = 0.81 V, Jsc = 6.79 mA/cm2, FF = 65.70 %, PCE = 3.61 %). When paired with Allium Cepa dye, the CD modified photoanode (CD/TiO2) offers Voc = 0.73 V, Jsc = 6.64 mA/cm2, FF = 61.27 % and PCE = 2.97 %. Similarly, when combined with Hibiscus rosa-sinensis dye, the output parameters of the CD/TiO2 photoanode are Voc = 0.72 V, Jsc = 6.54 mA/cm2, FF = 64.4 % and PCE = 3.03 %. In comparison to all tested devices, the unmodified photoanode (TiO2) displayed the lowest performance, with parameters such as Voc = 0.59 V, Jsc = 6.45 mA/cm2, FF = 52.5 %, PCE = 2.10 % using Allium Cepa peel dye, and Voc = 0.66 V, Jsc = 6 mA/cm2, FF = 51.60 %, PCE = 2.04 % using Hibiscus rosa-sinensis dye. Furthermore, the co-activation process has been shown to enhance the stability of the devices. While the unmodified photoanodes ceased to operate after eight days, the ZnO-CD composite co-activated photoanodes retained their initial efficiencies up to 61.50 % and 68.53 % with the Allium Cepa peel dye and Hibiscus rosa-sinensis dye, respectively. Therefore, this study underscores the potential of the synthesized composite material in enhancing the performance of natural DSSCs. 2024 Elsevier Ltd -
Carbon Nanotube-Polymer Nanocomposites for Energy Storage and Conversion
A large global commitment is necessary to scale up the deployment of renewable energy, engage in research and development, and implement energy-efficient practices. The development of large-scale energy storage technologies is crucial to fully harness renewable resources, ensure grid stability, and facilitate a more sustainable and reliable energy future. This becomes increasingly important as the demand for clean and renewable energy grows. Polymer nanocomposites have demonstrated considerable promise in energy storage and conversion. These nanocomposites can have better mechanical strength, electrical conductivity, thermal stability, and electrochemical performance due to adding nanoparticles or nanofillers to polymer matrices. Although carbon nanotubes (CNTs) cansignificantly enhance the characteristics of polymers at extremely low filler loadings, they are the perfect filler for both structural and functional applications. An extensive review of current studies on the synthesis and modification of polymer nanocomposites reinforced with CNTs is given in this chapter. To promote this new subject, it also severely evaluates a number of applications pertaining to energy conversion and storage. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Carbon Nanotubes for Supercapacitors
Supercapacitors are energy storage devices that boast significant capacitance, enhanced energy density, rapid charge/discharge cycles, minimal heat generation, safety, sustainability with no expendable components, and extended durability. Supercapacitors, due to their unique characteristics, are increasingly favoured in consumer electronics and as alternate energy solutions. Carbon nanotubes (CNTs) have emerged as a promising material for supercapacitor electrodes, thanks to their remarkable features like exceptional conductivity, large surface area, robust mechanical strength, and chemical stability. The objective is to offer a comprehensive understanding of the pros and cons of supercapacitor materials involving CNTs and to pinpoint ways to boost their efficiency. This also entails examining how the inherent physical and chemical traits of pure CNTs, such as their size, quality, imperfections, shape, modifications, and treatment processes, influence their capacitance. Moreover, a deeper dive into composites, like CNTs combined with oxides, polymers, and other hybrid materials, aims to customize their composition and characteristics to optimize capacitance while ensuring the devices longevity. This section also compiles the latest studies on various CNT composites as potential supercapacitor electrode materials. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.