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Cellular agriculture research progress and prospects: Insights from bibliometric analysis
World agriculture is facing a daunting task to feed the burgeoning population against multiple production and environmental threats. The alarming growth in population vis-vis current food production is expected to increase the global food insecurity levels. Inter alia, cellular agriculture an incipient technology is being considered as a potential alternative to cater for the growing demand for food and nutrition. The technology aims to develop edible agricultural products including meat with reduced environmental footprint against conventional farm production. In this context, an attempt has been made to review the progress of cellular agriculture research in four decades (19812020) through a bibliometric analysis and to suggest a roadmap for future research. The study sourced data from the Web of Science during October 2020. Using keywords, the database showed 212 searches pertaining to cellular agriculture from 135 journals worldwide. Of the journals, seven had at least five published articles and 33 had two articles each. Subsequently, the bibliographic coupling among the identified journals was carried out. It is found that the Journals: Appetite, Meat Science, and Journal of Agricultural and Environmental Ethics had the largest circles corresponding to their respective number of publications coupled with notable linkages with other journals. Also, a detailed analysis was performed on categories, growth trend, keywords, institutions, regions and leading researchers of cellular agriculture. The findings indicate that the Appetite Journal followed by the Journal of Agricultural and Environmental Ethics had published a significant percentage of articles on cellular agriculture, and Environmental Science and Technology was identified as the highly cited journal. The USA, England and the Netherlands were identified as the progressive regions in cellular agriculture research. The bibliometric analysis points to sluggish progress in cellular agriculture research and production despite its potential benefits. Future research should focus on the cost-effectiveness of the technology, consumer willingness to buy, development of food safety protocols on its merit and regional policy governance coupled with popularising its paybacks in the context of ensuring food security. 2021 The Author(s) -
Centrality measures-based sensitivity analysis and entropy of nonzero component graphs
The nonzero component graph of a finite-dimensional vector space over a finite field is a graph whose vertices are the nonzero vectors in the vector space, and any two vertices are adjacent if the corresponding linear combination contains a common basis vector. In this paper, we discuss the centrality measures and entropy of the nonzero component graph and also analyze the sensitivity of the graph using the centrality measures. 2024 World Scientific Publishing Company. -
Centring African indigenous knowledge: Afro-feminist perspectives on women's empowerment
This chapter explores the Afro-feminist perspective of the significance of African indigenous knowledge in the context of women's emancipation. The recognition of gender inequities in Africa prompts a need for the incorporation of intersectionality in feminist discussions that include a wide range of cultural contexts. The chapter emphasizes the significance of intergenerational learning in preserving knowledge and empowering older women via examining power relations, colonial legacies, and the integration of Western-traditional medicine. This chapter examines the impact of indigenous community and feminist organization involvement on legislative progress, focusing on protecting indigenous women. Global connections, cross-cultural discussions, and unity facilitate the empowerment of Afro-feminism. These elements surpass geographical boundaries and incorporate indigenous traditions. 2024, IGI Global. All rights reserved. -
Ceramic-Polymer-Carbon Composite Coating on the Truncated Octahedron-Shaped LNMO Cathode for High Capacity and Extended Cycling in High-Voltage Lithium-Ion Batteries
Long-term electrochemical cycle life of the LiNi0.5Mn1.5O4 (LNMO) cathode with liquid electrolytes (LEs) and the inadequate knowledge of the cell failure mechanism are the eloquent Achilles heel to practical applications despite their large promise to lower the cost of lithium-ion batteries (LIBs). Herein, a strategy for engineering the cathode-LE interface is presented to enhance the cycle life of LIBs. The direct contact between cathode-active particles and LE is controlled by encasing sol-gel-synthesized truncated octahedron-shaped LNMO particles by an ion-electron-conductive (ambipolar) hybrid ceramic-polymer electrolyte (IECHP) via a simple slot-die coating. The IECHP-coated LNMO cathode demonstrated negligible capacity fading in 250 cycles and a capacity retention of ?90% after 1000 charge-discharge cycles, significantly exceeding that of the uncoated LNMO cathode (a capacity retention of ?57% after 980 cycles) in 1 M LiPF6 in EC:DMC at 1 C rate. The difference in stability between the two types of cathodes after cycling is examined by focused ion beam scanning electron microscopy and time-of-flight secondary ion mass spectrometry. These studies revealed that the pristine LNMO produces an inactive layer on the cathode surface, reducing ionic transport between the cathode and the electrolyte and increasing the interface resistance. The IECHP coating successfully overcomes these limitations. Therefore, the present work underlines the adaptability of IECHP-coated LNMO as a high-voltage cathode material in a 1 M LiPF6 electrolyte for prolonged use. The proposed strategy is simple and affordable for commercial applications. 2024 The Authors. Published by American Chemical Society. -
Cerebral Stroke Classification Using Over Sampling Technique and Machine Learning Models
In recent years, cerebral stroke has ascended as a paramount concern in global public health. Proactive strategies emphasizing metabolic control over salient risk factors present a superior approach compared to relying solely on physiological indicators, which may not delineate clear preventive directives. In this research, we present the SPX-CerebroPredict modela novel machine learning framework designed to classify imbalanced cerebral stroke data for clinical diagnostics. The study delves into feature selection methodologies, employing both information gain and principal component analysis (PCA). To address the class imbalance dilemma, the Synthetic Minority Over-sampling Technique (SMOTE) was harnessed. The empirical evaluation, conducted on the cerebral stroke prediction dataset from Kagglecomprising 43,400 medical records with 783 stroke instancespitted well-established algorithms such as support vector machine, logistic regression, decision tree, random forest, XGBoost, and K-nearest neighbor against one another. The results evince that our SPX-CerebroPredict model, integrating SMOTE, PCA, and XGBoost, surpasses its contemporaries, achieving an impressive accuracy rate of 95%. This discovery underscores the models potential for clinical applicability in cerebral stroke diagnostics. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Ceria doped titania nano particles: Synthesis and photocatalytic activity
Ceria (0.5, 1 and 2 mol%) doped titania nano catalysts were prepared by combustion synthesis method, using titanium isopropoxide as the starting material. The prepared catalysts were characterized by X-ray diffraction (XRD), Energy dispersive X-ray analysis (EDX), Scanning electron microscopy (SEM) and Infra red spectroscopy (FTIR). Total acidity of the prepared catalysts were determined by temperature programmed desorption of ammonia (TPD - NH3). XRD pattern of 1% ceria doped titania obtained by calcinations at 873 K indicated that the samples were crystalline with a mixture of anatase and rutile phase. No peaks corresponding to cerium oxide were observed XRD patterns indicating that the amount of cerium is negligible on the surface of titania catalyst. The photo catalytic activity was evaluated for the degradation of methylene blue (MB) under visible light irradiation. The degradation rates of MB on cerium doped TiO2 samples were higher than that of pure TiO2. The introduction of structural defects (cationic ceria dopant) into the titania crystal lattice leads to the change of band gap energy. As a result, the excitation energy is expanded from UV light of anatase TiO2 to visible light for ceria doped titania. 2016 Elsevier Ltd. -
Cerium-doped Co3O4 spinel structures synthesized by modified combustion route as an excellent material for electrochemical applications
This work shed light on the impact of cerium doping on the structural and electrochemical features of Co3-xCexO4(x = 0, 0.02, 0.04) synthesized via a facile and cost-effective modified combustion route. The structural, morphological and compositional investigations unveiled the formation of nanocrystalline structures with promising morphologies. BET and XPS methodologies explored the materials' porosity and electronic state of the materials. The electrochemical performance of the synthesized materials was evaluated by Cyclic Voltammetry (CV) at various scan rates, Galvanostatic Charge-Discharge (GCD) at different current densities, and Electrochemical Impedance Spectroscopic (EIS) techniques. GCD studies depicted an exquisite specific capacitance of 498 Fg-1 for Co2.98Ce0.02O4 at a current density of 1 Ag-1 and it displayed a capacitance retention of 95 % for over 2000 GCD cycles further it retains up to 90 % even after 3000 GCD cycles at a current density of 1Ag-1 juxtapose to other compositions. Our work emphasizes the importance of the material for energy storage applications. 2024 Elsevier Ltd and Techna Group S.r.l. -
Certain results on trans-paraSasakian 3-manifolds
Let M be a trans-paraSasakian 3-manifold. In this paper, the necessary and sufficient condition for the Reeb vector field of a trans-paraSasakian 3-manifold to be harmonic is obtained. Also, it is proved that the Ricci operator of M is invariant along the Reeb flow if and only if M is a paracosymplectic manifold, an ?-paraSasakian manifold or a space of negative constant sectional curvature. 2022 Walter de Gruyter GmbH, Berlin/Boston. -
Certain types of metrics on almost coKler manifolds
In this paper, we study an almost coKler manifold admitting certain metrics such as ? -Ricci solitons, satisfying the critical point equation (CPE) or Bach flat. First, we consider a coKler 3-manifold (M,g) admitting a ? -Ricci soliton (g,X) and we show in this case that either M is locally flat or X is an infinitesimal contact transformation. Next, we study non-coKler (?, ?) -almost coKler metrics as CPE metrics and prove that such a g cannot be a solution of CPE with non-trivial function f. Finally, we prove that a (?, ?) -almost coKler manifold (M,g) is coKler if either M admits a divergence free Cotton tensor or the metric g is Bach flat. In contrast to this, we show by a suitable example that there are Bach flat almost coKler manifolds which are non-coKler. 2021, Fondation Carl-Herz and Springer Nature Switzerland AG. -
Certificate Generation and Validation Using Blockchain
Verifying academic credentials is a standard procedure for employers when making job offers. After the interview procedure is complete, the employer takes a long time to supply the offer letter. The employer must have the certificate authenticated by the organization that issued it to confirm its originality. While confirming the authenticity of a certificate, the employer takes a long time. The selection procedure takes longer overall because of the long process involved in certificate verification. Blockchain offers a verified distributed ledger with a cryptography technique to combat academic certificate forgery to address this issue. The blockchain also offers a standard platform for document storage, access, and minimization of verification time. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Challenges and concerns of assisted reproductive treatments: A systematic review
India, once a highly populated country with a Total fertility rate of 5.7 1(year 1960) now has one of the least fertility rates of the world around 2.3 1 (year 2015). In just one decade, with the rising economy, improving life expectancy and lifestyle, we have embraced a new disease Infertility 2. There are numerous reasons for rising infertility amongst Indians, some related to life style changes, some infections and some are occupational hazards. As a remedy to this new disease, hospitals in India were quick enough to learn Assisted Reproductive Technologies from foreign countries and practice the same in our home country. There are many ART clinics in every city however; this solution to the problem of infertility is a problem in itself. The paper uses a systematic review process to unravel the causes of infertility and highlights the concerns revolving around infertility treatments and finally presents suggestions to policy makers. 2019, Institute of Advanced Scientific Research, Inc.. All rights reserved. -
Challenges and Issues in Health Care and Clinical Studies Using Deep Learning
Deep learning is a subset of machine learning, which has more than three layers of neural networks. Neural networks resemble the functioning of human behavior in nature. These neural networks are capable of producing results with single layers, but multiple layers help in producing accurate results with increased precision rate. Deep learning supports a number of artificial intelligence (AI)-based applications and services, which helps in increased automated devices, data analysis, and many more physical tasks in various fields. Deep learning technology has become part of human day-to-day life. It is involved in every aspect of daily routine like voice-based searches, operating a device, baking transactions, and many more. Deep learning allows the healthcare industry to examine data quickly without compromising accuracy. Deep learning uses mathematical models designed to work almost like the human brain. Multiple layers of networking and technology enable unmatched computing capability and the ability to traverse and analyze through vast sets of data that would have previously been lost, forgotten, or missed. 2024 Taylor & Francis Group, LLC. -
Challenges and Opportunities: Quantum Computing in Machine Learning
Many computing applications are being developed and applied in almost every aspect of life and in every discipline. With increasing number of problems and complexities, there is requirement for more computational power, faster speed and better results. To overcome these computational barriers, quantum computers, which are based on principles of quantum mechanics were introduced. Faster computation is the main reason behind the evolution of quantum computers which is achieved by using quantum bits instead of bits as quantum bits store both the values 1 and 0 together in superposition. The article focuses on basics of quantum computing in brief and the underlying phenomenon behind quantum computers. Also this article exposes recent trends and the problems that are being faced in this quantum technology. The major impact of quantum machine learning is also discussed. The quantum machine learning is providing better application in this modern field. This article analyses the different research gaps and possible solutions in quantum computing. Recent days quantum computing is implemented in different applications which is also described. 2019 IEEE. -
Challenges and Solutions of Using Social Internet of Things (SIoT) in Healthcare and Medical Domains
The revolutionary idea that combines social networks with the Internet of Things (IoT) is called the Social Internet of Things (SIoT). SIoT is a term that refers to the modelling of social networks formed by connecting people and things. SIoT was designed to assist organizations in achieving specific goals, such as boosting usability, scalability, and productivity and satisfying business service requirements. The application layer of the SIoT model performs several tasks like managing the relationship, discovering the services, configuring services, and managing reliability among the devices. The information collected about SIoT is categorized by identifying the relationships between devices. SIoT creates an event identity based on data from IoT applications. This identity may then be transferred with the SIoT network and made available to other IoT apps. Thus, the SIoT network offers guidance services for reusing data from IoT applications across many IoT applications and customizing IoT solutions to meet the unique needs of individual users, hence boosting overall communication. SIoT technology entails the more efficient use of recent data to create favorable patient outcomes in healthcare and medicine. The enormous volume of data generated by SIoT-connected devices has allowed various developments and applications in the healthcare domain. SIoT leverages sensors and other connected devices in these domains to boost social solutions efficiency. Without question, sensors used for creating this kind of network model that can collect vast amounts of data are on the verge of becoming a pervasive part of our lives. If the processing and management are not carried out optimally in SIoT, there is a significant risk that the data will lose its efficacy. This chapter examines SIoT challenges and approaches in the healthcare and medical domain. SIoT approaches may assist users in detecting a patients aberrant behaviour. These approaches are capable of detecting and forecasting patients health states. The SIoTs relational models, such as community sharing, equality matching, and equality matching, also provide IoT services to users. The sensing layers functionalities are compared to those of the network layer and application when assessing SIoT services. The proposed hierarchical network model uses gateways, switches, and IoT devices to establish social relationships. CISCO packet tracer is used to construct and operate this mainly built social network for healthcare. This specially designed social network for the healthcare domain can easily be implemented and controlled by any hospital management. 2023 selection and editorial matter, Gururaj H L, Pramod H B, and Gowtham M; individual chapters, the contributors. -
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Challenges in Plasma Spraying of 8%Y2O3-ZrO2 Thermal Barrier Coatings on Al Alloy Automotive Piston and Influence of Vibration and Thermal Fatigue on Coating Characteristics
Although Thermal Barrier Coatings (TBCs) have found extensive application in automotive engines to enhance performance and to reduce fuel consumption and pollution, challenges of obtaining uniform and consistent coatings on non-uniform and irregularly shaped components are overcome only when the coatings are deposited via robot controlled APS or EBPVD. Atmospheric Plasma Spraying (APS) is the most commonly used and relatively cost-effective method to make TBCs: but not all APS facilities are equipped with comprehensive coating accessories. In a reciprocating diesel engine, the bowl at the piston crown forms one side of the combustion chamber and includes the space between piston crown (generally 9% Si-Al alloy in light - medium duty diesel fuel vehicle) and cylinder head. To achieve maximum effective fuel spray distribution and combustion, normally the crown of the piston has complex contours. One of the many service related parameters to be monitored to reduce the innumerable faults contributing to the performance of the engine is vibration. This paper addresses the issue related with the challenges associated with the plasma spraying of consistent and adherent TBC on Al-9% Si research pistons and its complex contours by APS, subjecting the coated pistons to thermal fatigue tests and evaluation of the coating characteristics after subjecting to vibration. 2018 Elsevier Ltd. -
Challenges of Digital Transformation in Education in India
Online learning has been present since the 1960s and has risen in popularity over time. World-class universities have been using online teaching-learning methodologies to fulfill the needs of students who reside far away from academic institutions for more than a decade. Many people predicted that online education would be the way of the future, but with the arrival of COVID-19, online education was imposed upon stakeholders far sooner and more suddenly than expected. When the COVID-19 pandemic broke out, educational institutions began to explore digital ways to keep students studying even when they couldn't be together in person as governments enacted legislation prohibiting large groups of people from gathering for any reason, including education. The future of such a transition looks promising. However, transitioning from one mode of education to another is not easy. Historically, when educators adopt new tools, learning still continues in the conventional manner. Based on the responses of 176 students, this paper studies the challenges of Digital transformation in the Education sector. The research is extremely beneficial in evaluating the scope of societal opposition to change. 2022 IEEE. -
Challenges of Indian girls with maternal schizophrenia
Schizophrenia, earlier known as dementia praecox, is considered to be one of the most devastating mental illnesses due to its impact on the individual as well as family members. The Indian context characterized by ones rootedness to family, warrant enquiry about difficulties and burnouts faced by girl children.When it is the mother who is suffering from the illness, there tends to be a huge lag in terms of primary care giving. A disturbed home environment along with inadequate parenting have shown to adversely affect the girl children. The present qualitative research study aimed to explore challenges faced by the girl children with maternal schizophrenia with the help of 43 Mental Health Professionals (MHPs) across India. Interpretative Phenomenological Approach (IPA)was adopted and interviews were conducted using a validated interview guide. Thematic analysis revealed that girl children whose mothers are diagnosed with schizophrenia faced challenges in self, family and social sphere of life. Neglect, self blame and the question why me were recurrent themes.They experienced difficulties in cognitive, behavioral and social domains. The added burden of family responsibilities and social stigma made the surroundings challenging.Exploring the world of girls with maternal schizophrenia would deepen our understanding about impact of schizophrenia on family members and aid us develop interventions to support the care givers. 2019 Oriental Scientific Publishing Company. All rights reserved. -
Challenges of Treating Bilingual and Multilingual Stuttering
[No abstract available] -
Challenges To Democratic Consolidation In Ecuador - Space For Opposition And Indigenous Representation Under Rafael Correa And Lenin Moreno
The illiberal democratic trend currently sweeping the world has emerged as a major obstacle for democratic consolidation, leading to its acceptance as the new normal of democracy. This trend has been successfully reversed in Ecuador, but the country has encountered and still grapples with several obstacles that must be overcome in order to return to the democratic consolidation route. The study focuses on the issues of consolidation, emphasizing the space allotted for participatory democracy by the ruling elites. The study examines Rafael Correas and Lenin Morenos governments in the context of the democratic consolidation framework to determine their strategic actions, behavior, and interests. The scope of the investigation will be limited with the focus made-on the space allowed for the opposition and indigenous community representation, from 2008 to 2021, to determine the extent to which Ecuadors liberal democratic process is being consolidated. 2021 Taylor & Francis Group, LLC.