eChapters

Introduction

Canine epilepsy, a prevalent neurological disorder, significantly impacts the quality of life for both dogs and their owners. Traditional anticonvulsant therapies often yield inconsistent outcomes, necessitating the exploration of alternative treatments such as homeopathy [1][2]. Homeopathy’s individualized approach aligns with the principles of unicism, focusing on holistic care tailored to each patient’s unique symptom profile [3]. However, the subjective nature of remedy selection and response assessment poses challenges for practitioners.

The integration of Artificial Intelligence (AI) and Machine Learning (ML) offers a promising avenue to address these challenges [4]. Predictive models can analyze complex datasets to uncover patterns that guide remedy selection and treatment strategies. This study evaluates the comparative performance of Logistic Regression, Random Forest, and XGBoost in predicting treatment outcomes for canine epilepsy managed with homeopathic remedies.

1. Introduction

Library enhances socioeconomic development by creating a knowledgeable society, empowering marginalized people, and promoting economic activity, skill learning, cultural identity enrichment, and decision-making participation. These services are supported by infrastructure, ICT, media. Libraries are responsible for knowledge, acquisition, management, fostering mutual relationships between librarians, the publics, and stakeholders. Its role as a storehouse of resources worldwide, including acquiring, organizing, preserving, storing, and making information available. Public libraries are important for public infrastructure, community health, and supporting social development goals. The contributions of the various types of libraries are discussed below:

1.1. National Library

A country's reference library is called its national library. It is the resource that all kinds of libraries utilize since it has a collection of all books published by Academic Library nationals in every subject area, as well as writings about the nation written by both nationals and non-citizens and by people in need of materials made in the nation. As a result, it is responsible for maintaining the country's cultural legacy and making the national bibliography available each year.

Abstract

Last few decades have witnessed an immense technological advancement in the education sector in India. With an advancement of technology, new gadgets are flooding the Indian market continuously bringing an immense opportunity for the education sector to improve upon the course delivery system. Higher education sector in India is adopting such new technologies in course delivery at a slow pace; however, there remains still a far way to traverse for the Indian education sector in order to achieve a perceptible and effective technology-infusion in the academic delivery arena. This paper is devoted to present an expository review on the usefulness of new gadgets, like smart phones, e-book reader as well as tablet PC, in both class-room education-delivery segments as well as in distance education sector in India.

8.1 Introduction

The objective of this chapter is to develop a smart control for site-specific management of fixed irrigation system with Blynk app. Mobile app is designed to control the water management in field. The complete system comprises of two sections field device and mobile app. Field device comprises of Arduino, Node MCU, Power supply, LCD, Relay board, soil moisture sensor, temperature & humidity sensor, water level sensor, motor1, motor2. The system is designed to establish control and communication with specific agricultural field to take sensory data from the sensors and control the PUMP IN motor and PUMP OUT motor with the help of mobile app. Fig.8.1 shows a block diagram for a system.

1. Introduction

Libraries play a crucial role as community centers that promote education, culture, and individual growth at a time when information is the currency of advancement. Rural libraries, however, confront unique difficulties that set them apart from their urban counterparts. Rural libraries often struggle with limited funding, being geographically isolated, and having difficulty obtaining technology infrastructure. Yet, in order to guarantee that rural libraries can provide the same caliber of service as their counterparts in larger cities, pricing and accessibility become vital factors. And in light of all of that, they continue to be vital community hubs that contribute significantly to education, cultural enrichment, and lifelong learning.

Open source solutions hold a lot of promise for addressing these problems.Open source software solutions are more affordable and flexible than proprietary software systems, allowing them to be tailored to the specific needs of any rural library. Among other reasons, the library staff finds it easier to catalog documents when they use these kinds of systems. Because these systems use simpler circulation techniques, they assist them with saving expenses while guaranteeing higher user involvement.

ABSTRACT

It is very important for every library to have all the resources/materials necessary to fulfil its target. The working of a library can be classified into two forms: dealing with the users and behind the scene. There are numerous different sections in a library divided on the basis of their functions. Most important of these is the Acquisition section. A library’s success lies in a well organized acquisition section. Main aim of the library is the contentment of the users. However, collection development is the primary task of the acquisition section which further contributes to user satisfaction itself. It performs the process of selection, procurement and accessioning of reading materials as well as maintains records. It organizes the monetary as well as human resources in such a manner that collection is facilitated more and that too in an economic and less time consuming way. All this is the responsibility of the librarian. Before acquiring the reading materials, the librarian is supposed to decide that which items are actually required in the library and which are to be rejected. A librarian must study the requirements of the library and acquire materials as per the priorities of the institution to achieve its goal.

Introduction and Importance of active site

Proteins are polymers of amino acids coupled by peptide bonds. The constituency of a protein that interacts with a ligand is habitually referred to as the “active site.” Ligands can be proteins, DNA or smaller molecules, such as pharmaceutical compounds [1]. The active site generally lies on the surface of the protein. In some cases, the active site is buried within the protein. Residues with reactive groups (ASP, GLU, SER, CYS, HIS, LYS, ARG) tend to be profuse in protein active sites [2]. The SER-HIS-ASP (sometimes SER-HIS-GLU) named as “catalytic triad” which is a motif, generally found in enzyme active site. Enzymes chip in a significant role in scheming the flow of metabolites within a cell, they catalyze virtually all of the reactions that make and modify the molecules mandatory for biological pathways [3]. The identification of catalytic residues is a key step in recognizing the function of enzymes. The site on the surface of an enzyme molecule that binds and acts on the substrate molecule are called as active site.

The success of a TTO relies on a systematic approach encircling factors like assessment, valuation, marketing, negotiation, and post-transfer management (fi gure 8). This chapter covers the activities that are essential for the effective functioning of a TTO. Other activies Technology Assessement /Valuation Financial Managemnt Major Activities of technology transfer office Commercialization IP Management Fostering Innovation
Fig 8: Various activities of TTOs.
3.1 Technology assessment - A pillar of innovation commercialization
The process of transitioning an innovative technology to commercial reality requires a stringent and formal process known as technology assessment. This early stage is crucial as it determines the viability of an invention by analysing practicability of the invention as well as its uniqueness and the likelihood of it being adopted in the target markets. In the absence of this preliminary examination, the chance of technology’s potential being mismatched to the market can arise.
a) Scientific merit and technical feasibility
A key benchmark in assessing technologies involves the identification of
scientific validity and technical performance. An innovation’s viability depends on the fact that it complies with good scientific practice or the innovative application of a new paradigm that has empirically confirmable validity. It is important to determine whether the invention’s underlying mechanism can be reliably proven through established scientific practice. A working prototype allows for empirical testing in different conditions and serves as proof of practical application. In addition to that, scalability has to be tested critically. It often happens that innovations perform well in a controlled laboratory setting but lose efficiency or cost-effectiveness in the case of mass production. The viability of the implementation on a grand scale becomes a core concern in this phase of the evaluation.

Additive manufacturing is increasingly important for developing resource-efficient and customized products while reducing material waste associated with conventional manufacturing. This chapter examines the role of additive manufacturing in supporting green and sustainable production systems. It covers environmental benefits, economic and operational advantages, additive manufacturing technologies, sustainable applications, life-cycle assessment, environmental impact analysis, challenges, and design strategies. Industry trends, case studies, sustainability standards, and future research directions are also considered. In the context of green composites, additive manufacturing can support flexible fabrication and potentially improve material utilization and product customization. The chapter emphasizes the need to evaluate manufacturing technologies across their complete environmental and economic life cycle.

Biomedical signals provide valuable information about physiological conditions and support continuous health monitoring. This chapter introduces ECG, EEG, EMG, PPG, respiratory and blood-pressure signals and examines the challenges associated with their acquisition and interpretation. It discusses noise removal, filtering, normalization, resampling and artifact correction before presenting time-domain, frequency-domain, time–frequency, wavelet and nonlinear feature-extraction methods. Feature selection and dimensionality reduction are considered in relation to model accuracy and clinical interpretability. The chapter also explores machine learning, deep learning and hybrid approaches through applications involving arrhythmia detection, seizure prediction and wearable cardiovascular monitoring, highlighting their importance in intelligent and personalized healthcare.

Renal failure is one of the most commonly presented conditions in veterinary clinics world over. Although the potential for recovery is favorable, most animals die due to multisystemic effects induced by azotemia. Hence, extracorporeal removal of endogenous and exogenous toxins is very essential for expanding the window of recovery. Hemodialysis has been used in treatment of veterinary patients for the last 50 years and is still one of the most expensive and technically demanding treatment modalities in veterinary medicine. It is an advanced extracorporeal renal replacement therapy which has recently transitioned from a clinical curiosity to a more advanced standard for management of acute kidney injury (AKI) and chronic kidney disease (CKD) in companion animals particularly dogs and cats.

In addition to eliminating selective toxins that cause AKI, regardless of renal function, hemodialysis is also effective in the removal of pharmacokinetically active soluble uremic substances in CKD to enhance life expectancy and quality of life (Singh, 2021). Other common indications of hemodialysis in veterinary medicine include fluid overload, dysregulated body fluid composition, drug overdose or intoxications (Foster, 2020; Singh et al?, 2024). Medical management alone is often insufficient to control the clinical signs and metabolic abnormalities associated with uremia when AKI is severe or when there is involvement of acute on chronic kidney disease. Consequently, animals are at risk of death within a short therapeutic window, despite the potential reversibility of AKI and the improvement of life expectancy in CKD.

Abstract

Fusion is a well known entity in various fields (e.g. medical imaging, weapon detection, flood monitoring etc.) that surmises information originating from several modalities. This chapter is an attempt to assort the various image fusion techniques available for human face recognition and to put a review of the advancements being made by the different researchers. The various types of fusion those have been used or may be used for face recognition have also been discussed here.

Tissue Doppler Imaging

Doppler echocardiography relies on detection of the shift in frequency of ultrasound signals reflected from moving objects. With this principle, conventional Doppler techniques assess the velocity of blood flow by measuring high-frequency, low amplitude signals from small, fast-moving blood cells. In TDI, the same Doppler principles are used to quantify the higher-amplitude, lower-velocity signals of myocardial tissue motion.

There are important limitations to TD interrogation. As with all Doppler techniques, TDI measures only the vector of motion that is parallel to the direction of the ultrasound beam. In addition, TDI measures absolute tissue velocity and is unable to discriminate passive motion (related to translation or tethering) from active motion (fiber shortening or lengthening). The emerging technology of Doppler strain imaging provides a means to differentiate true contractility from passive myocardial motion by looking at relative changes in tissue velocity.

Precision agriculture depends on information collected through ground sensors, satellites, IoT systems and other connected devices. However, these data sources differ in spatial resolution, timing, quality and technical compatibility. This chapter introduces a computational framework for acquiring, harmonizing and analysing heterogeneous agricultural data. Preprocessing methods address noise, missing values and inconsistencies, while machine learning, deep learning and ensemble models identify useful environmental, spectral and temporal patterns. Applications include crop-health assessment, soil-moisture estimation, yield prediction and climate-resilience planning. Edge and cloud computing support scalability and real-time operation. Integrating multiple data sources can improve model accuracy, robustness and the practical usefulness of intelligent farming systems.

Agricultural robotics is transforming farming by introducing automated machinery capable of performing agricultural operations with greater precision and efficiency. This chapter explores the role of robotics in planting, irrigation, spraying, crop monitoring, weed management, harvesting, and other farm activities. Integration of artificial intelligence, machine learning, sensors, cameras, and IoT enables robots to collect information, analyse field conditions, and perform tasks with limited human intervention. The chapter discusses the major applications, benefits, and limitations of agricultural robotics. Robotics can address labour shortages, improve resource-use efficiency, reduce operational time, and support sustainable farming. However, high investment costs, technical complexity, infrastructure requirements, and skill shortages remain important adoption barriers

Artificial intelligence is providing new opportunities to accelerate plant breeding and develop improved crop varieties capable of meeting changing agricultural demands. This chapter examines AI applications in genomic selection, phenotypic prediction, stress tolerance modelling and crop improvement. Machine learning, deep learning and predictive analytics enable researchers to analyze large genomic and phenotypic datasets and identify desirable traits. High-throughput phenotyping, image analysis, sensors, remote sensing and IoT technologies further support accurate monitoring of plant performance. The chapter also discusses AI-enabled precision agriculture, decision-support systems and sustainable crop management. Challenges involving data quality, computational requirements and model interpretability are addressed, alongside emerging opportunities involving genomics, biotechnology, robotics and digital twins.

Plant physiological processes determine growth, development, productivity and adaptation to changing environmental conditions. This chapter examines how artificial intelligence can improve understanding of plant physiology and stress responses. It considers physiological processes including photosynthesis, transpiration, nutrient dynamics and hormonal regulation and explores how AI can analyze complex biological, environmental and phenotypic datasets. Machine learning, deep learning, computer vision and predictive analytics support interpretation of information obtained through sensors, imaging, remote sensing and omics technologies. The chapter emphasizes early detection and prediction of stresses such as drought, salinity, temperature extremes, nutrient imbalance and pathogen pressure. It also discusses explainable AI, digital twins and federated learning as emerging approaches for plant stress research.

AI-based content creation refers to the use of Artificial Intelligence technologies to generate, edit, optimize, and publish content automatically or semi-automatically. Content can include text, images, videos, audio, presentations, reports, emails, and social media posts. AI content creation tools use technologies such as Machine Learning, Natural Language Processing (NLP), Computer Vision, and Deep Learning to create content that looks like it was created by humans. In the modern digital world, content plays a very important role in education, business, marketing, communication, and entertainment. Earlier, content creation was completely manual and required a lot of time, effort, and human resources. Writers, designers, editors, and analysts had to work for many hours to create a single report, article, or presentation. But now, with the help of AI tools, content can be created in minutes instead of hours

Effective crop monitoring is essential for maintaining plant health, optimizing farm operations, and improving agricultural productivity. This chapter explores the application of artificial intelligence for real-time crop monitoring and farm management. AI systems integrate information from sensors, satellites, drones, mobile devices, and other sources to assess crop conditions and identify emerging problems. Machine learning and deep learning techniques can analyse crop images, environmental parameters, growth patterns, and field conditions to provide actionable insights. The chapter examines real-time monitoring, image analysis, crop health assessment, anomaly detection, and decision-support applications. It also highlights the role of IoT and multimodal agricultural data in developing intelligent and responsive farming systems.