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Bromelain improves the growth, biochemical, and hematological profiles of the fingerlings of Nile Tilapia, Oreochromis niloticus
A 6-week-long feeding trial experiment was conducted to study the efficacy of Bromelain, a blend of proteolytic enzymes present in pineapple wastes on growth performance, biochemical, and hematological profiles of the fingerlings of Nile tilapia, Oreochromis niloticus. For this, 240 Nile tilapia fingerlings (9 0.11 cm) were fed a commercial diet, supplemented with different levels of pineapple peel extract (PPE) at 1:0, 1:1, 1:2, and 1:3 ratios. After 45 days of the feeding trial, growth parameters, biochemical constituents, and the level of blood cells were assessed. It was found that the growth parameters such as weight gain, feed efficiency ratio, and specific growth rate were increased (p < 0.05) along with the total protein and amino acid content and few hematological parameters; whereas the feed conversion ratio was found to be reduced significantly (p > 0.05) without changing the white blood cell count with PPE supplementation. Thus, the PPE can be a potential feed supplement in Nile tilapia aquaculture. 2022 Gopal Raaj et al. -
Bronchop Neumonia Detection Using Novel Multilevel Deep Neural Network Schema
Pneumonia is a dangerous disease that can occur in one or both lungs and is usually caused by a virus, fungus or bacteria. Respiratory syncytial virus (RSV) is the most common cause of pneumonia in children. With the development of pneumonia, it can be divided into four stages: congestion, red liver, gray liver and regression. In our work, we employ the most powerful tools and techniques such as VGG16, an object recognition and classification algorithm that can classify 1000 images in 1000 different groups with 92.7% accuracy. It is one of the popular algorithms designed for image classification and simple to use by means of transfer learning. Transfer learning (TL) is a technique in deep learning that spotlight on pre-learning the neural network and storing the knowledge gained while solving a problem and applying it to new and different information. In our work, the information gained by learning about 1000 different groups on Image Net can be used and strive to identify diseases. 2023 EDP Sciences. All rights reserved. -
BSLnO: Multi-agent based distributed intrusion detection system using Bat Sea Lion Optimization-based hybrid deep learning approach
Intrusion detection system (IDS) is a robust model that plays an essential role in dealing with intrusion detection, especially in detecting abnormal anomalies and unknown attacks. The major challenges faced by IDS are the computation time required for analysis, and the exchange of a huge amount of data from one division of the network to another. For the sake of tackling such limitations, this probe proposes a multi-agent enabled IDS for detecting intrusions using the Bat Sea Lion Optimization (BSLnO) algorithm. The proposed strategy consists of five phases, namely pre-processor agent, reducer agent, augmentation agent, classifier agent, and decision agent. Initially, input data is subjected to pre-processor agent, where pre-processing is carried out using data normalization and missing value imputation. Thereafter, the pre-processed result is fed up to the reducer agent, where dimension reduction is carried out using mutual information. The third step is data augmentation in which the dimensionality of data is enhanced. After that, the augmented result is subjected to classifier agent to classify intrusions or malicious activities present in the network based on hybrid deep learning strategies, namely deep maxout network and deep residual network. A developed BSLnO is implemented by incorporating Bat Algorithm (BA) and Sea Lion Optimization (SLnO) algorithm to train the hybrid classifier. The proposed scheme has acquired a higher precision of 0.936, recall of 0.904, and F-measure of 0.920. 2022 John Wiley & Sons Ltd. -
BSSA: Binary Salp Swarm Algorithm with Hybrid Data Transformation for Feature Selection
Feature selection is a technique commonly used in Data Mining and Machine Learning. Traditional feature selection methods, when applied to large datasets, generate a large number of feature subsets. Selecting optimal features within this high dimensional data space is time-consuming and negatively affects the system's performance. This paper proposes a new binary Salp Swarm Algorithm (bSSA) for selecting the best feature set from transformed datasets. The proposed feature selection method first transforms the original data-set using Principal Component Analysis (PCA) and fast Independent Component Analysis (fastICA) based hybrid data transformation methods; next, a binary Salp Swarm optimizer is used for finding the best features. The proposed feature selection approach improves accuracy and eliminates the selection of irrelevant features. We validate our technique on fifteen different benchmark data sets. We conduct an extensive study to measure the performance and feature selection accuracy of the proposed technique. The proposed bSSA is compared to Binary Genetic Algorithm (bGA), Binary Binomial Cuckoo Search (bBCS), Binary Grey Wolf Optimizer (bGWO), Binary Competitive Swarm Optimizer (bCSO), and Binary Crow Search Algorithm (bCSA). The proposed method attains a mean accuracy of 95.26% with 7.78% features on PCA-fastICA transformed datasets. The results show that bSSA outperforms the existing methods for the majority of the performance measures. 2013 IEEE. -
Bt cotton and the voices of the widows in the face of farmer-suicides
This article deploys the culture-centered approach to foreground the everyday constructions of farmer-suicides amid the agrarian epidemic among the farmer-widows to attend to the everyday structures that constitute the meanings of the suicides. The depictions of the patriarchal structures of decision-making in agriculture are intertwined with the broader erasure of the interplays of inequality in farmers experiences from the discursive sites of neoliberal agriculture. Furthermore, the voices of the widows disrupt the monolithic construction of agricultural technologies as tools of modernization and progress dominant in the development communication scholarship, instead, depicting the ways in which new technologies (such as Bt cotton) are constituted within, and reproduce, the overarching inequalities. 2020 National Communication Association. -
BTS: Belonging and Becoming
[No abstract available] -
Buffer zones in Wayanad: A social constructivist exploration into farmers mental health
Buffer zones are regions set aside to border protected areas to preserve biodiversity, control interactions between people and wildlife, and foster sustainable development. The majority of research on buffer zones focuses on ecological issues, and little is known about how they affect local communities mental health. This study explores buffer zones potential consequences on farmers mental health in Wayanad. Through purposive sampling, eleven participants residing in Wayanad were recruited for the study. The socio-demographics of participants were collected through printed translated questionnaires. The qualitative exploration of their lived experiences, perceptions, and coping strategies was conducted using semi-structured, in-depth interviews. Thematic analysis by Braun and Clarke was used to gain a clearer understanding of the data collected. Through in-depth analysis of the data, it was identified that Mental Health Factors, Communication Factors, Financial Impact, Operational Stress, Interference of Judiciary and Legislature, and Seclusion of the Tribal Community were the issues the farmers faced in Wayanad. The results will contribute to the expanding mental health field and give policymakers, conservationists, and mental health professionals information about the potential psychological effects of buffer zones and guide them in creating suitable interventions and support systems to improve mental health. The Author(s) 2024. -
BUILDING A DATA ETHICAL FUTURE: Data Policies and Frameworks
Technology-driven choices are shaping the digital engagement of individuals and policymakers. Rapid technological advancements and the increasing utilisation of Big Data and Artificial Intelligence (AI) have presented profound ethical challenges concerning privacy, accountability, and transparency. Existing Data Acts, internet policies, and government frameworks fall short of protecting individuals and states from violations of their digital footprints. This article advocates for a human-centric approach to data ethics, drawing on the concept of the common good, as articulated by John Rawls. Through a systematic review of global data privacy laws, acts, guidelines, and practices, the article examines potential disparities and emphasises the need for universal data legislation, guidelines, and policies. It highlights the significance of data policies and frameworks in fostering ethical data usage, trust, and integrity. By applying Kants philosophy of respecting individuals autonomy, the article emphasises the importance of informed consent and recommends ethical guidelines for both users and content creators. 2023, Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore) -
Building a resilient future: collaborative sustainability regulation
The challenge of sustainability lies in achieving a balance between satisfying present needs and protecting resources for future generations with an emphasis on its three pillars - environmental, social and governance. This study explored sustainable development encompassing environmental, social and governance aspects along with sustainability reporting through various sustainability frameworks. A systematic review of literature for the period 2010-23 on major worldwide sustainability frameworks was conducted, by offering insights into enhancing reporting mechanisms for a sustainable future. Secondary data related to sustainability reports were obtained from the Sustainability Accounting Standards Board and International Integrated Reporting Council, which helped in examining sector and year variations across countries. The results reflected that mandatory sustainability disclosures help to meet the United Nations Sustainable Development Goals and global sustainability frameworks help to set standards, disseminate information and promote transparency. Collaboration of investment, company action and sustainability organizations can lead to a sustainable global economy. The adoption of sustainability reporting can help organizations by fostering a proper understanding of sustainability practices, improving transparency and identifying potential business opportunities in sectors with lower sustainability. The paper provided insights into sustainability reporting published across various countries in both advanced as well as emerging and developing economies. The analysis showed which sectors and time periods have had the most sustainability reports and which areas needed to be targeted for action to advance sustainable development. 2024 The Author(s). Published by Oxford University Press on behalf of National Institute of Clean-and-Low-Carbon Energy. -
Building a sustainable relationship between customers and marketers
Finding new customers is costlier than retaining the existing customers for the business. Therefore, building a strong relationship with customers helps marketers to retain their existing customers. Incorporating ethical and moral values into marketing activities offer a way to build a strong relationship. This study identifies the factors that bind customers and marketers into a sustainable relationship in the Indian context. This study constitutes a framework to understand and apply sustainable relationship marketing in the personal care industry. This study touches certain marketing disciplines such as marketing mix policy, transparency in trades, building trust, product delivery, promises delivery, and sustainable relationship. The convenience sampling technique used for the selection of respondents from the Mohali City of Punjab, and interview them. The finding suggests that promises delivery is the most important factor for a sustainable relationship. If promises are delivered effectively then the life of the relationship will be longer. Copyright 2024 Inderscience Enterprises Ltd. -
Building an Industry Standard Novel Language Model Using Named Entities
In every Industry, there is a significant amount of text used in their specific domains. As these are less prevalent in the testing set, anticipating entity names in a language model is a problem faced by the entire industry. In this research a unique and very effective strategy for creating exclusionary classification models that could map entity names based on entity type information is provided. A group of benchmark datasets based on Mortgage is presented, which we used to test the below-presented model. According to experimental findings, our model achieves a perplexity level that is 64% higher than that of the most advanced language models. 2022 IEEE. -
Building an International Entrepreneurship Index using the PSR framework
This paper builds an International Index for Entrepreneurship (IIE) for the year 2018, by using a conceptual framework named PSR (Pressures-State-Response) to encapsulate the contextual aspect of entrepreneurship globally. In the past, the indices have used a methodological framework of composite indices. This paper uses the PSR framework to show how these indicators fall into the categories of pressure, state, and response, and concentrates on how these subsystems are interrelated. The study considers 41 countries for the construction of the index. We also check the correlation between the IIE and other growth indicators such as the corruption perception index, the economic freedom summary index, GDP per capita, and trade openness using suitable statistical tools.The correlation analysis demonstrates that the IIE and the Economic Freedom Summary Index have a positive association. 2022 IEEE. -
Building capabilities and workforce for metaverse-driven retail formats
The metaverse, a breakthrough virtual reality environment, offers boundless retail potential. Metaverse-driven retail needs a good strategy to succeed in a time of changing consumer expectations and the digital revolution. This chapter covers metaverse-driven retail preparation tactics. The metaverse allows retail innovation and adaptation during e-commerce and COVID-19 pandemic upheavals. Understanding metaverse dynamics and developing the abilities is crucial. Determine metaverse applicability to retail, define requisite capabilities, analyze staff competencies, and establish practical training and development programs. Examples include understanding metaverse technology, immersive shopping, datadriven personalization, and strong cybersecurity. Digital fluency, collaboration, design, and cybersecurity awareness are workforce competencies. This chapter stresses metaverse readiness through training, growth, and strategic alignment. It emphasizes that the metaverse transforms reality and opens up new possibilities. 2024, IGI Global. -
Building Global Teaching Capacity Among Pre-Service Teachers: Epistemological and Positional Framing in an Internationally Paired, Authentic Practicum
Building the capacity of pre-service teachers to work in globalized cross-cultural environments is essential to cope with the challenges of the 21st century. This study establishes the value of internationally paired, authentically collaborative practicums with strong epistemological and positional framing in pursuing such capacity development. It was conducted among 90 pre-service teachers from three different universities in Australia and India who participated in a three-week paired practicum in three schools in India. The practicum included the collaborative production of an integrated Australian and Indian combined theme presented in a whole school forum. Mixed methods and a design-based research approach yielded data affirming that such a model did indeed provide pre-service teachers with the confidence to teach in increasingly diverse classrooms and contexts, while also identifying which aspects of this practicum model were most influential in this regard. 2021 European Association for International Education. -
Building Robust FinTech Applications and Reducing Strain on Strategic Data Centers using the LoTus Model
Agile is a well-known project management approach that has been used for many years. It places a strong emphasis on client satisfaction, adaptability, and teamwork. Agile was first developed as a software development approach, but it has now been modified for application in other sectors including marketing and finance. The Agile Manifesto, which was released in 2001 and explains the principles and ideals of Agile development, is the foundation of the Agile ideology. One or more of the guiding principles is to adapt to change instead of following a plan, prioritize functional software over thorough documentation, and collaborate with customers over negotiating contracts. Agile has gained popularity over time as businesses try to be adaptable and responsive to their customers' constantly changing business demands. The lack of predictability in Agile is one of its key drawbacks. Agile stresses client cooperation and adaptation, therefore the finished product could differ somewhat from what was originally planned. For businesses that depend on meticulous planning and a rigid schedule, this lack of predictability can be problematic. It faced a serious problem during the process of building a finance application called JazzFinance. This has led to build another robust and systematic software development method called as LoTus model. The proposed LoTus is an acronym for two abbreviations. Those are lean optimization TypeFace for Unified Systems (LoTus) and Locate dependencies, optimize for reusability, Test-Driven environment, Unify Design and Scalability. This article goes through the development of LoTus and how it has helped us build a stable finance application within a small amount of stipulated time. 2023 IEEE. -
Building trust in policing: challenges and strategy; [Construindo confian no polia: desafios e estratia]
In recent years, trust has gained significant importance when discussing the evolution of policing. This shift in focus has been acknowledged by scholars, policymakers, and law enforcement officials who are responsible for ensuring public safety. Unlike the traditional emphasis on crime reduction, there is now a shared recognition that building trust is a fundamental objective in the relationship between policing agencies and the communities they serve. This article discusses three commonly employed methods by policing agencies and their personnel to enhance public trust in the police: policy changes, police training, and citizen oversight boards. Further, it focuses to a less conventional avenue for change, which involves re-evaluating the laws enforced by the police. To achieve meaningful transformation within the police system, it is necessary not only to modify how officers perform their duties but also to examine and potentially revise the laws they are obligated to enforce. 2024 Centro Universitario de Brasilia. All rights reserved. -
Bulirsch-Stoer computations for bioconvective magnetized nanomaterial flow subjected to convective thermal heating and Stefan blowing: a revised Buongiorno model for theranostic applications
Theranostics is a novel procedure that integrates therapy and diagnosis in a single platform. For its application in theranostic and photothermal therapy for melanoma skin cancer, the hydromagnetic bioconvective flow of a nanomaterial over a lengthening surface is investigated. Realistic nanomaterial modeling is achieved by incorporating passive control of the nanoparticles at the boundary. The impact of the Newtonian heating and Stefan blowing constraints are also accounted. Apposite transformations are employed and then transmuted nonlinear ODEs are resolved using the Bulirsch-Stoer and Newton-Raphson methods. The influence of Stefan blowing parameter (Formula presented.), the magnetic field parameter (Formula presented.), and the Biot number (Formula presented.) on the heat transfer rate has been scrutinized and optimized utilizing the response surface methodology (RSM). The sensitivity of heat transport rate is computed. It is found that the Newtonian thermal condition intensifies the nanomaterial temperature that serves asa crucial role in the termination of cancerous cells or tumors. The maximum drag coefficient is experienced for the insignificant intensity of the magnetic field and Stefan blowing. Further, the heat transfer rate is maximum when the Stefan blowing and Biot numbers are at a high level and the Hartmann number is at a low level. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Business and Environmental Perspectives of Submarine Cables in Global Market
If an individual uses any of the social media networking sites, such as Facebook, Instagram, YouTube, Twitter and the like, a subsea cable is involved there. Submarine cables are considered as critical global communications infrastructure. These cables are used by various telecom providers and content provider companies such as Google, Facebook, and Microsoft to provide seamless transmission of data for their services. Growing internet users and increasing internet traffic for various social media sites is the major reason for the growth of this market. Submarine cables enable data services such as the email, internet banking, social media networking, search engines and all other aspects related to internet that are taken for granted in daily life. These submarine cables scales up the ubiquity of cloud computing and builds digitization of activities. Undersea cable network is the new economic trade route and acts a commodity in Information age. This paper reviews the business and environmental impacts of submarine cables in the global market. Springer Nature Switzerland AG 2020. -
Business and Society: A Symbiotic Relationship
Business can be a for-profit, not-for-profit or hybrid organization. But all these businesses focus on the satisfaction of their stakeholders. Although many businesses adopt a limited perspective of their stakeholders, focusing primarily on the interests of their investors, customers and, in some cases, their employees, it is a fact that the long-term sustainability of any business will depend on its contributions to the society. The long-term objective of all businesses is to serve and support the society and contribute to the socioeconomic development of their people. Therefore, this chapter presents a comprehensive review of the relationship between business and society, with special reference to the three main types of businesses: commercial businesses, social enterprises and non-governmental organizations. As in the case of biological systems, the relationship between business and society may be characterized predominantly by one of the three types of symbiotic relationships: mutualism, commensalism and parasitism. However, the successful co-existence of business and society, in the long run, would depend on the degree of mutualism in their relationship. 2024 by World Scientific Publishing Co. Pte. Ltd. -
Business Forecasting and Error Handling Using AI
Business forecasting is the technique of accurately predicting the future of a business and outcomes using historical data and present trends. To evaluate historical data and find patterns, trends, and other elements that might be used to forecast future events, a variety of analytical tools and techniques are used. Business forecasting is a crucial component of strategic planning because it enables businesses to foresee market changes, spot possible risks and opportunities that may arise in the future, and make wise resource allocation and investment decisions. Businesses that use effective business forecasting can plan and carry out their programs that help them stay competitive, expand their operations, and meet their objectives. According to Glueck [1], Forecasting is a formal process of predicting future events that will significantly affect the functioning of an enterprise.. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar.