eChapters

If the 1990s were the decade of genomics, the first ten years of the new century are set to become the decade of proteomics. For the first time, the technologies of proteomics make it possible to generate quantitative protein expression data on a scale and sensitivity comparable to that achieved at the genetic level. This advance has major implications for our understanding of cellular organisation in health and disease and for pharmaceutical and agricultural biotechnology. Indeed, proteomics is already yielding important findings, across a wide range of applications. Most proteomics research, however, is directed towards the more proximal goal of investigating protein expression and function under specified physiological conditions.

The rapid evolution of proteomics has continued during the past years with a series of innovations in the core technologies of two-dimensional electrophoresis and mass spectrometry, and a diversity of productive research programmes. Well annotated proteomics databases are now emerging in a number of fields to provide a platform for systematic research, with particularly promising progress in clinical applications such as cardiology and oncology. Large-scale quantitative research, comparable in power and sensitivity to that achieved for gene expression, is thus becoming a reality at the protein level.

1. Introduction
The era of genome sequencing was exploded by the upcoming of Human Genome Project (1989), coordinated by the U.S. Department of Energy and the National Institute of Health to identify all the approximately 20,000-25,000 genes, 3 billion chemical base pairs, store this information in databases, improve the tools for data analysis, transfer related technologies to the private sector, and address the ethical, legal, and social issues (ELSI) that may arise from the project. The dawn of genome sequencing began with Fredric Sanger’s sequencing almost twenty-five years ago. The time consuming and labor intensive gel preparation and their running, as well as the cost of such experiments replaced the conventional sequencing by “shotgun” sequencing.

The importance of Plant Pathology has been realized over the years owing to number of crop failures in different parts of the world. Plant disease control is indispensable for qualitative production and to compete in global agricultural trade. There is great need of sensitization of our research in various aspects which shall guide the generation to come for managing plant diseases not only for enhancing crop production but also in facilitating trade by conserving the biodiversity and environment.

Research Trend in Plant Pathology

Like in other sciences, there has been a change in the trend of research in Plant Pathology with passage of time. Up to the late 1960s most of the interest in plant pathology was concentrated in crop diseases mostly caused by fungi. Physiology of microorganisms and physiology of parasitism became increasingly popular fields of interest in 1960s.

Sequence Alignment

Sequence Alignment is the procedure of comparing two (Pair-wise Alignment) or more (Multiple Sequence Alignment) sequences by searching for a series of individual characters or character patterns that are in the same order in the sequences.

Significance: Discovering functional, structural and evolutionary information in biological sequences.

A genome is an organism’s complete genetic signature and the collection of information that an organism can pass on to its offspring. Genomics, the study of the structure, function, and evolution of entire genomes is principally dealing with genetic information which helps us to understand how organisms and ecosystems work, how theymalfunction, or how they might be melded to human needs. The model organisms used in genomics have, in general, small genomes and short generation times. To meaningfully analyze the gene-to-phenotype relationships, a large amount of sequencing information is necessary. Progress in DNA sequencing technologies leads to accumulate Information about structures of genomes (Mohan Kumar, 2007).

HISTORY OF INSECT GENOMICS

Commencing from the publication of the entire nucleotide sequence of the genome of Haemophilus influenzae in 1995, a complete genome sequence of many organisms, including lower and higher eukaryotes, have been reported. The cost-effective way to get sufficient sequence information to address the questions is to sequence a high-quality reference genome and then map sequences from other genomes onto the reference sequence. Insects constitute the vast majority of known species with their importance including biodiversity, agricultural, and human health concerns. Hence, a study of Insect genomics is imperative to elucidate information to other organisms.

Biology is in the middle of a major paradigm shift driven by computing technology. Due to the impact of information technology, biological sciences have been rapidly becoming much more computational and analytical. Rapid progress in research in the field of genetics and related field combined with the tools provided by modern biotechnology has generated massive volumes of genetic and protein sequence data over last two decades. Compilation, storage, analysis for extraction of information and knowledge from this data becomes a challenging task as usual analytical procedures are not directly applicable to these data sets.
 
Bioinformatics has been defined as a means for analysing, comparing, graphically displaying, modeling, storing, systemising, searching, and ultimately distributing biological information, which includes sequences, structures, functions, and phylogeny. Thus, bioinformatics may be defined as a discipline that generates computational tools, databases, and methods to support genomic and post-genomic research. It comprises the study of DNA structure and function, gene and protein expression, protein production, structure and function, genetic regulatory systems, and clinical applications. Bioinformatics applications need knowledge from computer science, mathematics, statistics, medicine, chemistry and biology.

Soil is formed by disintegration and decomposition of rocks, minerals and organic matter, Soil is a habitant for plant growth and serves as a storehouse of water and food nutrients for plants, Soil is not same everywhere and varies morphologically, physically, chemically and mineralogically from one point to another both in horizontal and vertical directions. Development of soil informatics is necessary to classify the soils, to assess the productivity of soils for various crop productions and to use the soil for various purposes such as land capability classification, soil irrigability classification, soil rating and soil mapping.

Morphologically soil may appear red, yellow, black, brown or ashy in colour. Soil may vary from sandy to clayey in texture. Depending upon the nutrient reserve capacity, the soil may be fertile or infertile. On the basis of climate, a soil may be classified as laterite soil. Red earth and red loam soil, podzol soil or desert soil.

Different kinds of soil contain minerals of various types and amounts and so exhibit distinct physio co-chemical properties. Although various methods have been used in the past to classify the soils, the most modern and scientific methods is based on dominants pedogenic processes acting on a place to from a soil. The new method of soil classification has two important characteristics-Firstly soil classification is based on certain diagnostic parameters which could be estimated quantatively, and secondly depending on diagnostic parameters, a scientific method is being followed to classify a soil from higher to lower levels such as order, suborder, great group, subgroup, family and series.

Today, when the collection of biological data has been increasing at explosive rate, the processing of these data is needed. It would be extremely valuable if the specialists who know what the data mean were also able to imagine ways to collect, process and exploit these data. Biological and agricultural scientists should note that concepts from computer science, discrete mathematics and statistics are being used increasingly to study and describe biological systems. The specialists, who know the subjects of mathematics, statistics and computer programming, are needed for solving the computational problems in biology. Statistical data mining approaches seem ideally suited for bioinformatics, since it is data rich, but lacks a comprehensive theory of life organization at molecular level, or in the words of I.E. Alcamo “ Keeping up with the directions and application of DNA is a never ending job.” Starting with possible definitions of statistical data mining and bioinformatics, this chapter will give a general side view of both the fields on the statistical data mining part and its technologies and discuss how statistical data mining may be used in bioinformatics.

ANALYSIS OF CODON USAGE VARIATION

Multivariate analysis methods such as Correspondence Analysis and Principle Component Analysis have often been used to identify major trends of variation in synonymous codon usage among inter or intra specific genes. Genetic codes are degenerate meaning most of amino acids can be encoded by more than one codon (triplet of nucleotides); such codons are synonymous and usually differ by one nucleotide in the third position. The alternative synonymous codons are not used with similar frequency and their usage varies among different genes. Hence there is the presence of Relative Synonymous Codon Usage values. 

SEQUENCE DATA

The gene sequences downloaded from Genbank of National Center for Biotechnology Information that is the nucleotide sequence repository known worldwide, serves as the secondary data used for analysis. Relative synonymous codon usage value of each gene is extracted separately using the Codon Usage software of Sequence Manipulation Suite. These are the raw data which needs to be normalized to be used before application of various multivariate analysis.

Bioinformatics can be defined as “the collection, archiving, organization and interpretation of biological data” (Orengo et al., 2003). By extension, structural bioinformatics deals with the collection, archiving, organization and interpretation of 3-D structural data of bio macromolecules. Structural bioinformatics emerged with the first crystal structures of haemoglobin and myoglobin. These structures were analyzed and contributed significantly to our understanding of the principles of life at a molecular level. A repository of all publicly accessible protein crystal structures, the Protein Data Bank (PDB) was established by Walter Hamilton et al., at Brookhaven National Laboratory in 1971. Until the late 1980s, structural biologists often knew all the available structures of bio macromolecules and much of the analysis, such as structure comparison and hydrogen-bonding analysis was done manually without much computer intervention. As the number of available structures increased, so did the need for software tools for structure analysis. Structural bioinformatics encompasses a wide variety of applications, including structure visualization, validation, classification, structure-based function prediction, identification of targets for structural genomics projects and prediction of the structures of individual bio macromolecules and complexes as well the binding modes of small molecules inside proteins of pharmaceutical or biotechnological interestStructural and theoretical analyses of proteins are central to the understanding of complex molecular mechanisms and are fundamental to the drug discovery process.

Introduction

Zymomonas mobilis, a gram negative, anaerobic, micro aerotolerant, ethanologenic bacterium metabolizes glucose, fructose, and sucrose. One of the major factor that limits the usage of Z. mobilis is the narrow substrate range. Moreover, there are no obvious genes reported for using lactose, maltose or cellobiose. Our preliminary sequence analysis of the Zymomonas mobilis ZM4 genome indicated the presence of a putative beta-galactosidase (bga) gene. However, the mechanism of beta-galactosidase (Bga) function is still unknown. Hence, Bioinformatics analysis was made to predict the physicochemical, biochemical and biophysical properties, domains, secondary and tertiary structures of the putative beta-galactosidase. These studies suggested that the putative beta-galactosidase gene was poorly expressed from its native promoter in Z. mobilis. The absence of beta-galactoside transacetylase and permease genes in Z. mobilis led to its inability to metabolize lactose. Hence, function predictions of Bga are performed because of the fact that it has a homologous partner.

A fundamental problem facing researchers today is how to make effective use of available wealth of online background domain knowledge to improve their understanding of complex biological system. Effective use of such online background domain knowledge plays a crucial role in all stages of integrated biological studies.

In the past years, research in molecular biology and molecular medicine has accumulated enormous amounts of data. This includes genomic sequences gathered by the Human Genome Project, gene expression data from micro array experiments, protein identification and quantification data from proteomics experiments, and SNP data from high-throughput SNP arrays. However, the understanding of the biological processes underlying these data lags behind. There is a strong interest in employing methods of knowledge discovery and data mining to generate models of biological systems. Mining biological databases put forward challenges which knowledge discovery and data mining have to address in the future. Important background knowledge in bioinformatics is often contained in documents, such as scientific publications or database annotations. Analyzing data from biological databases often requires the consideration of data from multiple relations rather than from one single table. Recently, approaches (such as propositionalization algorithms) are being studied that utilize multi-relational data and yet meet the efficiency requirements of large-scale data mining problems.

Abstract
This paper presents a lucid and application-oriented delineation of the theory of probability which has proved itself as a basic tool in the theoretical and applied researches in almost all disciplines of science, specially, in the problems encompassing the real-life issues. Bio-informatics has recently emerged as a potential discipline of science and, needless to mention that the application of the probability theory has delved deep to elucidate the laws under its ambit. The inference procedures based on biochemical systems require the formulation of stochastic models (owing to the prevalence of low to moderate levels of stochasticity and noise in their dynamics) which, in turn, are developed using the probability laws in abundance. In Systems Biology, the estimation of parameters poses a prime task in biokinetic models developed on experimental data, and such estimation procedures have been possible only by applying appropriate tools derived using probability. Likelihood-free Bayesian inference that explicitly accounts for discrepancies between the model and the data, termed Approximate Bayesian Computation under model uncertainty is an off-shoot of the celebrated, Bayes' theorem of probability.

Advancement of both biological sciences and computer technology gave birth today’s one of the hottest area known as bioinformatics. Gradually bioinformatics analysis has become an essential component to the continued improvement and development of any kind of biological research work. It has various applications in medicine, biotechnology, agriculture etc. Some of the applications of bioinformatics related to biological information analysis are as follows [1]
    
·    Information related to bio-molecules can be mapped (e.g.), the sequences can be parsed to find sites where so-called “restriction enzymes” will cut them.
    
·    Sequences can be compared, usually by aligning corresponding segments and looking for matching and mismatching letters in their sequences. Genes or proteins that are sufficiently similar are likely to be related and are therefore said to be “homologous” to each other.
    
·    If a homologous exists then a newly discovered protein may be modeled - that is 3D structure of the gene product can be predicted without doing laboratory experiments.
    
·    Bioinformatics is used to attempt to predict the function of actual gene products.

The advances in science and technology are deeply intertwined. Researchers can use the semiconductor manufacturing techniques that underlie miniaturization to build radios and exceptionally small mechanical structures that sense fields and forces in the physical world. These inexpensive, low-power communication devices can be deployed throughout a physical space, providing dense sensing close to physical phenomena, processing and communicating this information, and coordinating actions with other nodes. These multifunction devices are battery operated and are connected wirelessly with sensing, processing and communicating capabilities and are known as the wireless sensors. If we use these sensors with biological issues or Biotechnology, then we can find the new concepts biosensors. If we really implement these concepts in real life we can get rid of many diseases like heart attack, blood sugar level, gene reaction and other changes that happens in our body much before its shows to outside.

Accurate crop-yield forecasting supports food-security planning, resource allocation and farm decision-making. Yield is influenced by interacting factors such as weather, soil, irrigation, fertilizer and pesticide use, making reliable prediction challenging. This chapter presents an algorithmic framework using historical agricultural and environmental data. It covers cleaning, missing-value treatment, categorical encoding, normalization and feature extraction. Decision Tree, Gradient Boosting, AdaBoost and XGBoost regression models are evaluated individually and combined through soft voting. Performance is measured using standard prediction-error metrics. The case study demonstrates that ensemble modelling can improve accuracy and robustness, helping farmers and planners optimize inputs, anticipate production and strengthen agricultural productivity.

Punjab, known as the “breadbasket of India,” relies heavily on livestock, particularly cattle and buffalo, for its agricultural prosperity. These animals play a crucial role in the region’s dairy industry, contributing significantly to milk production and rural livelihoods. However, like all livestock, cattle and buffalo in Punjab are susceptible to a range of diseases that can impact their health, productivity, and overall well-being. Timely and accurate diagnosis is essential for effective treatment and prevention. This article explores some of the most common diseases affecting cattle and buffalo in Punjab, along with the diagnostic procedures used to detect and manage these health issues, ensuring the sustainability and growth of the dairy sector.

Hydatidosis

Hydatidosis is a zoonotic disease caused by metacestode stages of parasite Echinococcus granulosus and is recognized as a major public health problem worldwide. This tapeworm is found in small intestine of the canid (definitive host) where it produce proglottids containing eggs. Upon shedding through faeces the later are ingested by the cattle, buffaloes and other intermediate hosts including man. These hatch in their intestine and the oncosphere invade circulatory system and lodge in various organs (liver, lung, brain etc.) where they develop into large thick walled unilocular cavity called hydatid cyst, which expands and can reach very large size and buds hundreds and thousands of protoscoleces endogenously. In a survey on hydatid cysts, a prevalence rate of around 5% has been recorded in more than 4000 meat samples of different animals in Punjab.

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.

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.

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

Artificial intelligence can detect subtle changes in animal health before they become apparent through conventional observation. This chapter examines machine learning, deep learning and predictive analytics for livestock disease prediction and diagnosis. Models use physiological signals, diagnostic images, behaviour patterns, environmental conditions and historical records to recognize abnormalities and estimate disease risk. Wearable sensors and IoT devices enable continuous monitoring and early-warning systems, supporting preventive veterinary care and outbreak management. AI-based detection can reduce mortality, treatment costs and production losses while improving decision-making. The chapter also evaluates challenges involving inconsistent data, model interpretability, rural infrastructure, technical accessibility and the practical implementation of diagnostic systems.

Introduction 
The evolution of public administration in the digital age has been anything but linear. As governments worldwide grapple with waves of technological advancement, the boundaries between reform phases such as e-government, e-governance, digital government, and digital governance often blur. Transformations occur unevenly across sectors and regions, with older paradigms coexisting with or even outlasting newer innovations. As Dunleavy, Margetts, Bastow, and Tinkler (2006, p. 216) perceptively observe: “Defining periods in the evolution of any complex system, such as public management systems in advanced industrial countries, is tricky. New developments accumulate while older trends are still playing out and flourishing. Relatively established ideas move from leading-edge countries or sectors to implementation in previous laggard areas, even as the same ideas are being repudiated or reversed in the erstwhile pioneering locations. Moreover, a confusing welter of changes goes on simultaneously, amongst which it is difficult to distinguish ephemeral and hyped-up innovations from those that are fundamental and longerlasting”. This observation aptly captures the administrative reforms’ non-linear and layered character in the digital era. The coexistence of multiple reform paradigms ranging from early e-government initiatives focused on service delivery, to broader e-governance aimed at leveraging technologies for participatory governance, and finally to the strategic integration seen in digital governance illustrates how public sector innovation is cumulative and contested. Digital governance, in particular, cannot replace previous phases. Instead, it serves as their expansion and convergence, wherein technology, data, and citizen-centricity are embedded in policymaking, service design, and institutional accountability. To fully understand the rise of digital governance, examining the broader historical trajectory of administrative reforms is important. Since the 1960s and 1970s, such reforms have consistently remained a focal point for both

ABSTRACT

This paper presents an outline on the patenting system prevailing in India. 

INTRODUCTION

Ideas and knowledge are increasingly important parts of trade. Most of the value of new medicines and other high technology products lies in the amount of invention, innovation, research, design and testing involved. Hence, protection of such values is paramount. This paper details how these values are protected in India.

11.1 Introduction

The analysis of variance is a powerful statistical tool for tests of significance.  The test of significance based on t-distribution is an adequate procedure only for testing the significance of the difference between two sample means. In a situation when we have three or more samples to consider at a time an alternative procedure is needed for testing the hypothesis that all the samples are drawn from the same population, i.e., they have the same mean. For example five fertilizers are applied of four plots each of wheat and yield of wheat on each of the plot is given we may be interested in finding out whether the effect of these fertilizers on the yields is significantly different or in other words, whether the samples have come from the same normal population. The answer to this problem is provided by the technique of analysis of variance. Thus basic purpose of the analysis of variance is to test the homogeneity of several means.

Animal behaviour provides valuable information about health, welfare, reproduction, environmental adaptation and social interaction. Traditional observation is labour-intensive, time-consuming and vulnerable to observer bias. This chapter explains how machine learning automates behavioural analysis using video, sensor and bioacoustic data. It covers preprocessing, feature extraction, classification, clustering and recurrent neural networks for temporal analysis. Computer-vision techniques—including object detection, tracking and pose estimation—enable continuous and non-invasive monitoring. Case studies demonstrate applications in livestock management, wildlife conservation and laboratory research. The chapter also examines data labelling, model generalization, ethics, explainable AI, real-time processing and the integration of multiple behavioural data sources

Veterinary oncology is an upcoming field in recent years due to the integration of the importance of spontaneous canine cancers in understanding and developing novel strategies for human cancer management. We are stepping towards a very exciting era in veterinary oncology, where comparative oncology has played a significant role for many decades in understanding the molecular basis of cancer in companion animals. The comparative animal models have generated remarkable interest in both academia and industry. Studies have demonstrated the utility of comparative oncology in understanding drug resistance and tumor biology, contributing to the translational research[1]. This has yielded breakthrough discoveries, from advanced diagnostics to novel therapies, providing opportunities to improve the longevity and quality of life of the pets. These inputs have led to advancements such as the first conditionally approved chemotherapeutic agent for lymphoma, novel BRAF testing for canine urothelial carcinoma, tyrosine kinase inhibitors for mast cell tumors, updates in stereotactic/FLASH radiation, and novel immunotherapeutics. As the understanding of cancer biology has advanced, the field of veterinary oncology has grown significantly, paralleling developments in human oncology. Veterinary oncologists treat a variety of cancers in domestic animals, particularly dogs and cats, but also in exotic animals, horses, and even zoo animals. While the types of cancers in animals share similarities with human cancers, treatment strategies can differ significantly due to species-specific differences in anatomy, physiology, and response to therapies [2, 3].

AMR is undoubtedly the most serious challenge ever faced by the world health community because of its multifaceted complex nature and its overwhelming impact over the human and veterinary communities. Livestock sector is no exception to have the serious and devastating impact from the emergence and spread of AMR. Because of a steady shift towards intensive farming and increased stocking density there has been increase occurrence of infectious diseases. Growing world population, rapid urbanization, and deforestation, shrinkage of grazing land all aided to this process. This leads to increased usage of antimicrobials in food animals – cause of concern for the scientific community as AMU is known the single most important driver of AMR.

Smart Farming is a hi-tech and effective system of doing agriculture and growing food in a sustainable way. It is an application of implementing connected devices and innovative technologies together into agriculture. Smart Farming majorly depends on IoT thus eliminating the need of physical work of farmers and growers and thus increasing the productivity in every possible manner.

With the recent agriculture trends dependent on agriculture, Internet of Things has brought huge benefits like efficient use of water, optimization of inputs and many more. 

ABSTRACT

The concept of the Kissan Call Centres-KCCs (Farmers’ Call Centres-FCCs)) was a logical outcome of the Government of India’s (GOI’s) commitment to leverage the ICT for overcoming the constraints of distance and time in providing new generation extension services to the farmers of the country by facilitating their direct virtual contact with the agricultural extension and expert personnel. The study on KCC has shown that farmers in the age group of 29 to 48 years are the biggest user group of KCC helpline. In terms of academic background, farmers with a minimum exposure of six to seven years to formal schooling (86%) seek to utilize the KCC support and relatively inexperienced farmers with less than 10 years of experience are more likely (47.5%) to call the KCC. The scope to enhance awareness and access among women farmers to the KCC helpline is huge as their current levels of participation are negligible. As regards the performance of KCCs, 84% of the farmers who called the KCCs expressed overall satisfaction from the advice provided through the helpline.

Livestock wealth is very precious for a developing country like India. In India, animal husbandry is no longer a subsidiary to agriculture or a backyard vocation. Animal husbandry has metamorphosed into an industry and the latest reports suggest that the contribution of animal husbandry sector to the GDP of the nation is substantially higher despite the meager input. Animal husbandry offers a better scope for marginal farmers whose income from agriculture is dwindling fast due to vagaries of monsoon, fragmentation of landholdings, pest problems, poor pricing etc. Though the growth of livestock industry is very promising, in order to make India a global leader in animal husbandry, it is imperative to integrate it with developments in other fields. The developments in Information Technology over the past few decades are tremendous and offer great potential in improving animal health through various measures like effective disease forecasting, rapid and accurate disease diagnosis, modern therapeutic measures etc.

Veterinary Informatics is the discipline concerned with the application of information science, engineering, and computer technology to support veterinary health care. Veterinary informatics and the larger field of medical informatics is often called health care informatics or biomedical informatics and forms part of the wider domain of e-health. Applications of Information Technology in different aspects of animal health are discussed below.

A nimal disease monitoring describes the ongoing efforts directed at assessing the health and disease status of a given population. The disease can be a specific infectious disease/diseases or health in general, whereas the monitoring activities are the routine recording, analyses and distribution of information related to the disease (or health). The term disease surveillance is used to describe a more active system and implies that some form of directed action will be taken if the data indicates a disease level above a certain threshold.

In today’s click-and-access kind of world, Information Technology is finding applications in every field and animal disease monitoring & surveillance is no exception. The various technologies which are applied are Geographic Information Systems, Global Positioning System, database management, computer aided design (CAD), computer network technologies, artificial intelligence (AI), expert systems etc.

Asiatic Elephant (Elephas maximus) is the national heritage animal of India. This particular species now exists in 13 Asian countries including India. As per 2017 census, India is home to an estimated figure of 29,964 elephants that is >60% wild population of the globe. Once distributed across the country, now they are squeezed to 14 states grouped in four regions ie., southern (14,612), north-eastern (10,139), east-central (3,128) and northern regions (2,085). There are 2675 captive elephants across different states under both private and government custody. This largest terrestrial mammal is protected under Seclude I species of Indian Wild Life Protection Act, 1972.

Both central and state Government are implementing short- and long-term programmes for health and well-being of captive as well as free-range elephants. The Central Government has established an ‘Elephant Cell’ at the Wildlife Institute of India (WII), Dehradun to provide technical inputs to the ministry for strengthening the efforts towards conservation of elephants. Add-on, the ‘Project Elephant’ was launched in 1991-92 in the Ministry of Environment, Forests and Climate Change to restore the elephant habitats and reduce their sufferings. Elephant habitats are notified as Elephant Reserves that are basic management units for elephant conservation and managements. A total of 33 Elephant Reserves has been notified in the country. A book titled, ‘Caring for elephants: Managing health and welfare in captivity’ is edited for field officers, veterinary professionals and elephant handlers.

History of Social Networking Services

The notion that individual computers linked electronically could form the basis of computer mediated social interaction and networking was suggested early on. There were many early efforts to support social networks via computer-mediated communication, including Usenet, ARPANET, LISTSERV, bulletin board services (BBS) etc.

Early social networking websites included Classmates.com(1995), focusing on ties with former school mates, and SixDegrees.com(1997), focusing on indirect ties. User profiles could be created, messages sent to users held on a “friends list” and other members could be sought out who had similar interests to yours in their profiles. Whilst these features had existed in some form before SixDegrees.com came about, this would be the first time these functions were available in one package. Despite these new developments (that would later catch on and become immensely popular), the website simply wasn’t profitable and eventually shut down. It was even described by the website’s owner as “simply ahead of its time.” Two different models of social networking that came about in 1999 were trust-based, developed by Epinions.com, and friendship-based, such as those developed by Jonathan Bishop and used on some regional UK sites between 1999 and 2001. Innovations included not only showing who is “friends” with whom, but giving users more control over content and connectivity.

Introduction

“Quality” of fish refers to the aesthetic appearance and freshness or degree of spoilage which the fish has undergone or involves safety aspects such as being free from harmful bacteria, parasites or chemicals. “Quality’’ is a term which must be defined in association with an individual product type. For example, it is often thought that the best quality fish is the one which is consumed within the first few hours of post mortem. However, very fresh fish which are in rigor mortis will be of hard texture and difficult to fillet and skin are often unsuitable for smoking or drying. Thus, for the processor, a slightly older fish which have passed through the rigor process are more desirable.

SANTOSH P. SARANGAMATH & VIVEK M. PATIL

While System Software like device drivers and utilities enables the application software to interact with the computer hardware, Programming Software like compilers, debuggers and interpreters provides tools to assist a programmer in writing computer programs. However, most common users interact with their computers using Application Software, which enables them to carry out various daily tasks.

Application Software

Application software is programs that work with the operating system software to help the computer to do specific types of work. Applications are the pieces of software that perform tasks for the user besides helping the computer to operate (i.e. the task of system software). Applications range from games, calculators, and word processors (document creation programs). Application software can be easily divided by looking at exactly what function they serve. Listed below are some common types of software which one may encounter while using a computer. Application Software can be categorized into :

Introduction

The role of knowledge management as the key source for competitive advantage in our organizations has become a hotly debated topic. Indeed, it is a core competency for creating competitive advantage. In this environment that knowledge management is vital, therefore, at first we should determine knowledge management situation, and then to achieve a desired point, formulate a knowledge management strategy.

Abstract

The paper discusses patentability aspect of subject matter. Patentable subject matter must satisfy three basic criteria i.e. novelty, inventiveness and industrial applicability, though few subject matter satisfying all the three basic criteria stated above may still be not patentable in specific jurisdiction based on certain circumstances or as stated in the patent act of the specified jurisdiction. Therefore grant of a patent is subject to certain limitations mentioned in the section 3 and 4 of the Indian Patent Act for Indian jurisdiction. The aim of this paper is to study such limitations in detail.