eChapters

Introduction
 
Electronic resources for libraries includes online databases , electronic( e-) journals , electronic(e-) books ,full text articles and web sites, where online journals have firmly established themselves as essential resources for libraries and information centers  and their users, as appointed books in most of disciplines. Electronic books (e-books) have not found the same favour. The potential of e-books to support learning activity has been acknowledged, and new services have emerged in recent years, but uptake has been slow.

1. Introduction

An expert system is defined as “a computer program designed to model the problem solving ability of a human expert” (Durkin, 1994). It is also defined as “a system that uses human knowledge captured in a computer to solve problems that ordinarily require human expertise”. An intelligent computer program that uses knowledge and inference procedures to solve problems that was difficult enough to acquire significant human expertise for their solutions. It is a computer application that solves complicated problems that would require extensive human expertise. To do so, it simulates the human reasoning process by applying specific knowledge and interfaces. Expert system also uses human knowledge to solve problems that normally

Starting from the middle of the 20^th Century, information has become a commodity. Those best able to access information will be more successful than their peers in their future careers. Technological competence will be as important as medical competence to practice at the highest levels. Advances in computer technology have made access to veterinary and medical databases much simpler than in the past. It is quite likely that in the future, it will be a malpractice for practitioners not to access online information essential to the treatment of their patients. Wireless digital transfer of information will make access to necessary information independent of time and place.

Veterinary medicine and educational delivery are becoming an increasingly international market. Those who are prepared to deliver material in this manner will have a competitive advantage. Use of digital technologies will allow veterinary colleges to share information, including class material, more efficiently. This will enable each college to market specific educational information for students at other veterinary colleges or continuing education modules to graduate veterinarians around the world. On-line certificate programmes in specific veterinary topics will be developed. Use of computer technologies can enrich the teaching environment. By digitizing library, classroom, and laboratory visual images, students can access these materials at any time or place, freeing them from library and classroom schedules. Medical colleges have found that students heavily use these image resources. Computer technologies provide both horizontal and vertical integration of the professional curriculum, allowing students to explore information to the depth at which they are comfortable, without regard to their “year of study” in a traditional “linear” curriculum. Allowing students to see future applications of current learning material provides additional incentive to master basic material. Computers are a tool, just like a textbook, notebook, or calculator.

3.1 Introduction

Internet of Things (IoT) allows computational devices and sensory support to connect with each other and access services on the Internet. The IoT idea was introduced to connect devices through the Internet and facilitate access to information for users. The potential application of IoT includes agriculture. The aim of this chapter is to explain the role of NodeMCU in the agriculture field. NodeMCU is IoT module which can be used to present the IoT concept as a basis for monitoring and control. The systems used in farm production processes. NodeMCU play a key role, with a focus on their realization by available microcontroller platforms and appropriate sensors. IoT based system provides opportunity to users to monitor and control the process remotely.

1. Introduction

Universal development through Education for all had been a prominent feature earlier during Millennium Development Goals and recently it has gained a fresh momentum when United Nations General Assembly set 17 inspirational Sustainable development Goals. Quality Education is the focus of SDG 4, “Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all” (Sustainable Development Goals, 2023). Role of education in achieving these sustainable development goals in developing countries is well recognized by OECD. OECD in its report on ‘Education at a Glance 2013’ states that “Educational attainment is frequently used as a measure of human capital and the level of an Individual’s skills. The level of educational attainment is the percentage of population that has reached a certain level of education. Higher levels of educational attainment are strongly associated with higher employment rates” (OECD, 2013). Furthermore, OECD in its report published in 2017 explains that “Making SDG 4 a reality will transform lives around the globe. Education is so central to the achievement of a sustainable, prosperous, and equitable planet that failure to achieve this particular SDG puts at risk the achievement of the 17 SDGs as a Whole” (OECD, 2017).

Establishment of databases and data warehouse; knowledge discovery from database/data warehouse (KDD) and development of the mechanism of dissemination of knowledge on information networks as per requirements of user groups is gaining importance now a days. Since there is a large number of data collection agencies and equally diverse resources for which the information is collected, it is easy to visualize the heterogeneity of information. The problem is compounded by the fact that there are no common standards that are applied in data collection. Designing data warehouses to integrate the collected information poses a formidable challenge to any data warehouses architect. In order to use the information for planning and decision-making level, data have to be integrated and aggregated properly.

Introduction

The libraries of 2020 become multi-media centres of information resources, leaving behind their dull and drab image of repositories of old dusty books materials like micro-films, audio and video cassettes. Various electronic products for use both off line and on line representing the special type of materials need special equipments of different makes for their effective use.

Introduction

The library and information centre is an important component of any educational institution. It is a hub of specific information where the end users can explore the vast resources of information. In the era of old age libraries users had to spend more time for searching a small piece of information and for that had to depend on library professionals. But now we are living in the age of information and communication technology, computers are being used for day-to-day work of library which saves the time of users and avoid the redundancy work of library staff.

Abstract
    
The amount of data being collected across a wide variety of fields today far exceeds our ability to reduce and analyze without the use of automated analysis techniques. In addition, the whole data may not be of user interest and imperfect. Therefore, it is very challenging to organize this data in formal system, which provides outputs in more relevant, useful, and structured manner. There are many techniques available to retrieve knowledge from this voluminous data. This paper discusses different rough computing based information retrieval techniques to obtain meaningful knowledge from large amount of datasets. We also discuss a real life example to show the viability of proposed research.

Introduction 
The transformative potential of digital technologies in reshaping governance and development paradigms is increasingly evident, particularly in rural contexts. In India, where nearly 65% of the population resides in rural areas, the imperative to leverage digital tools for inclusive growth has never been more critical. Rural digital governance refers to the strategic use of information and communication technologies (ICTs) to enhance service delivery, improve livelihoods, and foster participatory development in rural areas. It encompasses various applications from digital health, education, and financial inclusion to precision agriculture, market linkages, and entrepreneurial enablement, each designed to address long-standing structural inequities. Historically, rural regions have been perceived as passive recipients of policy support and welfare interventions. However, with the advent of digital technologies, these areas are increasingly positioned to become both demand drivers through rising incomes and service consumption and supply hubs, contributing to national productivity through digitally enabled livelihoods and enterprises. By enhancing access to essential services, improving the efficiency of traditional sectors such as agriculture and handicrafts, and facilitating diversification into non-farm activities like rural tourism and agri-processing, digital governance catalyzes rural transformation. However, the success of rural digital governance is contingent upon adopting a holistic and contextualized approach. One-size-fits-all digital interventions often fail to address the nuanced realities of rural economies. Effective rural technology deployment requires carefully diagnosing local needs, infrastructural capabilities, and livelihood profiles. In this regard, a participatory approach to technology selection and design grounded in the realities of rural life ensures greater relevance, uptake, and impact. Publicprivate partnerships (PPPs) play a pivotal role in scaling such initiatives, with governments providing scale and legitimacy while private actors contribute innovation, technical know-how, and financial investment.

7.1 Meaning of Sampling
    
Before we consider sampling theory, we first define the terms population and sample.
 
The word ‘population’ or ‘universe’ in statistics is used to refer to any collection of individuals or of their attributes or of results of operations which can be numerically specified. For example the assemblage of heights of all the individuals in the population is called a population of heights.  Similarly we may consider the population of weights, wages, yields of grain; prices of wheat, mileages of automobile tyres, etc. a population containing a finite number of individuals or members is called a finite population.  For instance the population f ages of the workers in a factory constitute a finite population of ages. A population with infinite number of members is known as infinite population.  For example the population of pressures of temperatures at various points in the atmosphere is an infinite population. 

ABSTRACT

Village Resource Centre (VRC) provides information services to the rural population to empower them to face day to day challenges. In this line, the Department of Space, ISRO & RRSSC is bringing its space technology to common man by setting up of Village Resource Centres, with a view to integrate the capabilities of communication and remote sensing satellites to address the changing and critical needs of rural communities. VRC is totally interactive VSAT based network for providing space enabled information related to land records, natural resources, drinking water wells, ground water recharge, soil types, alternate cropping pattern, waste lands, etc. VRCs also provide  variety of services in its tele-education and tele-medicine programmes, online decision support, weather forecasting, water management, interactive farmers advisory services (video conferencing) etc.

10.1 Introduction

The objective of this chapter is to develop a data logger and indicator for fire detection in agriculture field. The data logger is designed with the help of Scilab. The system comprises of Ardiuini Nano, light sensor, MQ6, MQ135, IR sensor, temperature sensor, power supply. The system is designed to take sensory data on Scilab with serial communication. Fig.10.1 shows block diagram for a system. Table.10.1 shows the component list required to develop the system.

1. Introduction

Today, all the organisations rely on assessments of data provided by their users, consumers, internal procedures, and day to day operations to find new avenues for betterment and expansion of the product and services. These insights provide a large and intricate set of professionally generated, maintained, analyzed, and modified facts. "Big Data" refers to the vast amount of data (Bansal, 2022, April 6). For instance, social media platforms facilitate human contact every day and millions of people connect and share a vast array of diverse types of information through these platforms. Big Data is viewed as "incredibly significant" in academic research. In the Big Data context, data visualization tools and technologies are essential for analyzing large amounts of data and making decisions based on facts (Adilin Beatrice, 2021, March 2). Information and data are represented graphically in data visualization. By using visual components like charts, graphs, and maps, data visualization tools provide an intuitive way to observe and understand trends, outliers, and patterns in data. The process is called Big Data Analytics that describes the process of uncovering trends, patterns, and correlations in large amounts of raw data to help make data-informed decisions in various research works.

One of the major goals in agricultural crop management is to achieve maximum yield with minimum investment while maintaining a good quality of the crop produce. Crop infestation due to insects, diseases, and weeds are some of the major factors responsible for loss in crop yield. Further, an efficient Precision Agriculture Crop Management System is one, which is capable of precisely detecting the crop yield indicators (or crop health parameters) at an early stage and can predict the yield at any point of time of the crop cycle.

Sensor is a physical device used to detect manifestations or variations in a process value and collect data in real time assessment mode for measuring and predicting system/device performance and finally analyzing it to attain a specific task or application. Sensor technology is now-a-days used for interdisciplinary applications for data collection, system analysis and monitoring.

Abstract

Sequence alignment is the positioning of DNA, RNA, or protein sequences with each other to identify the regions of identity, which may be the result of functional, structural, or evolutionary relationships between the sequences. Therefore, sequence alignment is the process of aligning two sequences to achieve the maximum levels of identity and conservation. This chapter deals with the basic concept of sequence alignment and the tools associated with multiple sequence alignment. Further, it describes various matrices used in sequence alignment.

Learning objectives

1. Recognise inflammatory cell types

2. Recognise common skin pathogens

3. Diagnostic test are best for each case

4. Gain experience in interpretation

5. Recognise important artefacts

″The most crucial step towards healing is having the right diagnosis″. While approaching a case, a clinician should follow appropriate steps in a systematic way for accurate diagnosis of dermatological disorders. A careful history is a first step to choose appropriate diagnostic tests.

By 2050, the global population is projected to reach approximately 9.8 billion, requiring a 70% increase in food production to meet the growing dietary demands. The livestock sector will play a crucial role in addressing this rising need through sustainable animal production, contributing to food security, poverty alleviation, public health, and food safety. To tackle the challenges posed by population growth and to achieve the United Nations Sustainable Development Goals (SDGs), technological advancements and innovations will be essential in transforming the food and agriculture sectors.

In light of these challenges, Veterinary Services are more critical than ever. They are essential for enhancing livestock health and productivity, ensuring high-quality food that meets safety standards, and mitigating risks associated with animal diseases and public health. Additionally, Veterinary Services must contribute to global efforts in addressing issues such as food security, antimicrobial resistance, climate change, and the depletion of natural resources.

Cloud-based software is used for the management of financial and field activities of farms. Prior to computers, farmers maintained data manually by keeping lengthy records on papers. This method was prone to human calculation errors. After the computer boom in the 1980s, it was not long before finance software such as Money Counts came to market. 

11.1 Introduction

The application of greenhouse in agriculture is vast. Greenhouses are used for growing flowers, vegetables, fruits, transplants and varieties of certain crops in a controlled environment which is appropriate for the plants. The edible flowers are served in some good restaurants to grow them precise calculation is required. Sensor network can help to monitor and automate the activities in greenhouse. The objective of this chapter is to discuss the development of sensor nodes to monitor the growth of flower plants through XBee and internet of things. The system comprises of three sections- sensor nodes, local server and main server. Sensor nodes communicate to local server with XBee and then local server communicates the same data to main server through IoT.Fig.11.1 shows the generalized block diagram, sensor node is to be implemented on each flower pot and communicating to local and main server.

Introduction

Studies have indicated that four significant forces viz. IT, Mobile, Cloud and Social Media would create unique work environment in the coming years. Social media presents both opportunities and challenges. It has reached a stage where a single tweet can make or mar an organization. It has emerged as a force to reckon with.

Soil health determines agricultural productivity, resource efficiency and long-term sustainability. Conventional laboratory and field-assessment methods provide valuable information but can be time-consuming and difficult to scale. This chapter presents a computational approach combining soil sensors, remote sensing and historical agronomic records. Indicators such as moisture, nutrients, pH and organic matter are processed using data-cleaning and feature-extraction techniques. Random Forest, Support Vector Machine and neural-network models estimate soil-quality parameters and identify degradation patterns. Explainable artificial intelligence improves the transparency and usefulness of predictions. Integration with edge computing enables real-time soil evaluation and supports targeted fertilization, efficient irrigation and sustainable soil-management decisions.

This chapter focuses on split plot and strip plot designs, essential tools in experimental design known for effectively handling complex experiments. It covers the key principles and applications of these designs, emphasizing how they can be used to address specific research challenges. The chapter also provides practical guidance on conducting analyses of split and strip plot designs using R software, making it a valuable resource for researchers seeking to apply these methods in their work.

Split Plot Design

The split-plot design is a statistical approach widely used in experiments where specific conditions apply:

• Hierarchical arrangement of treatments: This design is ideal for experiments involving two levels of experimental units, typically “whole plots” and “subplots.” The main treatments are applied to the whole plots, while the sub-treatments are applied within these to the subplots.

• Adherence to experimental design principles: The split-plot design follows the principles of randomization, replication, and local control, but with a hierarchical twist. The main treatments are randomized across the whole plots, and the sub-treatments are randomized within these main plots. • Resource management in unequal experimental conditions: This design is particularly useful when some factors require larger experimental units or when changing levels of one factor is more resource-intensive than changing levels of another factor.

In factorial experiment it may sometime happen that certain factors require bigger plots than other for convenience of operation of the experiment.  For example, in an agricultural experiment involving two factors, say, irrigation and fertilizer, it is organizationally very inconvenient to apply different levels of irrigation to small neighbouring plots.  But there is no such difficulty for the application of different levels of fertilizer. To meet such situations it is desirable to have different sizes of the experimental units in the same experiment.

SQL, or Structured Query Language, is a fundamental component in the domains of Machine Learning and Artificial Intelligence, serving as a powerful tool for managing, retrieving, and manipulating data stored in relational databases. In an era where data drives intelligent systems, SQL plays a crucial role in preparing and organizing datasets that form the backbone of machine learning models and AI applications. Its ability to efficiently handle large volumes of structured data makes it indispensable for data scientists, analysts, and engineers working in these fields. Originally developed in the 1970s at IBM by researchers Donald D. Chamberlin and Raymond F. Boyce, SQL was designed to provide a standardized way to interact with relational databases. Over time,

SQL, or Structured Query Language, provides a powerful framework for querying, aggregating, and transforming financial data stored in relational databases, which is essential for constructing accurate and dynamic financial models. Unlike spreadsheet-based models, SQL enables automation, repeatability, and scalability, making it particularly useful when dealing with complex datasets or real-time financial information. The first step in financial modeling with SQL is understanding the structure of the database. Financial data is often stored across multiple tables, including transactions, accounts, customers, and market data. Effective financial modeling requires familiarity with relational database concepts such as primary keys, foreign keys, and normalization. By using SQL joins, analysts can merge these tables to create a unified dataset that captures all necessary information, such as revenues, expenses, and cash flows, which are essential for forecasting and valuation exercises. Data extraction in SQL

Financial modeling programs integrated with data analytics using SQL provide a strong foundation for managing, analyzing, and transforming financial data in a structured and scalable manner. SQL, or Structured Query Language, is essential in environments where large volumes of financial data are stored in relational databases, enabling analysts to build reliable and data-driven financial models. Its ability to efficiently query, aggregate, and manipulate data makes it a critical tool in modern financial analytics. The process begins with understanding the database architecture. Financial data is typically distributed across multiple tables such as transactions, accounts, customers, budgets, and market indicators. SQL enables the integration of these datasets through joins, allowing analysts to

Abstract

Crop cultivation is a complex process and involves a set of activities like land preparation, planting, pest control, irrigation, nutrient management, harvesting, marketing, etc. Entire cycle of crop production requires multitude of information by the farmers. Despite many efforts over the years to disseminate and transfer agriculture knowledge to the stakeholders, large amounts of expertise and knowledge are still out of reach to most of them. Agriculture knowledge may be contained in the corporate database, or it may reside undocumented inside the brain of the researchers or even stored in locations unknown to the majority of the people in the organization. Large sections of the farming community, particularly the rural folk, do not have access to the huge knowledge base acquired by agricultural universities, extension-centers and businesses. In this respect the main challenge is to find this knowledge and apply it to the decision making process involved in agriculture development.

5.1 String Statement

String in python is stored as individual characters i.e. indexed wise. The index by default starts with 0.

So, here P will be represented by str[0] or str[-6], y will be represented by str[1] or str[-5]

Note: strings are immutable and hence you cannot change the individual letters of string using assignment operator.

Example:

name=“shyam”

Name[0]=“A”

Result error

Introduction

Northeastern Region of India consists of eight States, viz., Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Tripura and Sikkim.  The northeastern states are located between geographical ordinates, 21° to 29°30' N and 89°46' to 97°30' E. The region, surrounded almost on all sides by Bhutan, China, Myanmar and Bangladesh, which can be broadly divided into two characteristic zones viz., Mountainous and Plain. Although distinguished in the altitude differences, both the mountain and plain are closely interrelated in terms of natural resource sharing and economic flow. According to the physiographic characters this region is divided into five physiographic units, the Assam Himalayas, the Brahmaputra valley, the Shillong plateau, the Barak valley and the Southeastern hill region. Except the Brahmaputra and Barak valleys in Assam and the Imphal valley in Manipur, the terrain is hilly and mountainous, only making 65% of the northeast an undulating land with elevations ranging from 200 to 900 m above MSL

ABSTRACT

This paper presents few measures to be taken up by academic institutions, professional societies, industrial bodies and governmental agencies for the propagation of information of IPR in terms of encouragement of publication of books on IPR, establishment of IPR cells in academic and professional institutions and making IPR education as part of curriculum in Universities and institutions of higher learning.

1. Introduction

Information is necessary for the economic, social, and cultural development of individuals and communities, and libraries play a significant role in providing access to information, which is essential for this growth. These institutions function as centers of knowledge, offering a wide range of resources to their users, including books, journals, databases, and multimedia materials, in order to meet the varied requirements of their users.

In this day and age, the function of libraries has evolved beyond the confines of physical locations to encompass activities such as online platforms and digital collections. Because of the large amount of information that is accessible on the internet, people rely on libraries to help them navigate through this sea of data and locate sources that are credible and reliable.

Introduction
Sustainable agriculture refers to farming practices that meet current food production needs without compromising the ability of future generations to meet their own needs. It aims to balance environmental health, economic profitability, and social equity, ensuring that agricultural systems can be productive, resource-efficient, and resilient over time. The role of Information Technology (IT) in achieving these objectives has become increasingly crucial as it provides innovative solutions to optimize agricultural practices, minimize resource consumption, and improve overall productivity while safeguarding the environment. Through the integration of IT tools such as Geographic Information Systems (GIS), Internet of Things (IoT), Big Data analytics, Artificial Intelligence (AI), and cloud computing, sustainable agriculture can be advanced in ways that were previously unimaginable. These technologies facilitate precision farming, enhance resource management, monitor crop health, predict weather patterns, and provide farmers with the information to make data-driven decisions that foster sustainability.

The goal of sustainable agriculture is to meet society’s food and textile needs in the present without compromising the ability of future generations to meet their own needs.

Practitioners of sustainable agriculture seek to integrate three main objectives into their work: a healthy environment, economic profitability, and social and economic equity. Every person involved in the food system—growers, food processors, distributors, retailers, consumers, and waste managers—can play a role in ensuring a sustainable agricultural system.

Abstract

Synthetic biology is a multidisciplinary field of study that seeks to understand living systems and organisms, and utilizes engineering principles to design and create new biological components, devices, and systems, as well as modify existing natural systems. This chapter provides an introduction to synthetic biology and describes the procedures and methodologies involved in the design and construction of novel biological systems. The applications of synthetic biology are vast and include the development of biosensors, gene circuits, metabolic pathways, and genetically modified organisms for use in a variety of industries, including healthcare, agriculture, energy, and environmental remediation.

Introduction

Training is the crucial and expensive component of HRD, intended to improve the efficiency and effectiveness of performance of the members of organization through planned learning efforts, transfer of such learning at work place and in turn improvement of the organizational performance. Given such objectives, most of the training programmes fail to inculcate the transfer component in trainees (Subedi 2004). Hence, there is an increasing concern over training transfer at work place and the resultant improved organizational performance in terms of productivity, efficiency, effectiveness and turn over etc (Howard 1995, Huselid 1995, Martocchio and Baldwin 1997 and Salas et al.. 2000, Thayer1997).

Abstract

Systems biology is an interdisciplinary field that combines computer and mathematical analysis with biological research to understand the complex interactions within biological systems. This chapter explores the history and evolution of systems biology and its significant impact on modern biology. Systems biology uses a holistic approach to analyze biological systems at the molecular, cellular, and organismal levels, providing a better understanding of biological processes and the interactions between genes, proteins, and other molecules. Systems biology has immense potential in improving human health, agriculture, and the environment, and this chapter explores the ongoing efforts to translate systems biology research into practical applications.

ABSTRACT

Jharkhand state is endowed with vast and rich natural resources. It’s 80 per cent population resides in 32,620 villages and depends mainly on agriculture and allied activities for their livelihood. Rural population in Jharkhand still suffers from several ailments, weakness and constraints which come in the way of the use of ICT for agricultural development. Low level of literacy, poor socio-economic status, low penetration of extension services, language barrier, lack of electricity, etc., are some of the problems due to which  the farmers are unable to access the latest techniques in farming through different ICT services and are using the traditional knowledge and techniques which yields very less.

ABSTRACT

Veterinarians, appointed in field, rarely get the opportunity to update their knowledge and skills, through trainings or courses, due to their working conditions. More over, they feel isolated and neglected from colleges due to poor interactions. Looking to this need, the courses on Post Mortem Techniques and Diagnosis of Parasitic Diseases in Livestock were developed, based on the Need Assessment survey. The courses were developed on interactive CD ROM with audio, video clips and photographs along with some reading material. The courses were of one credit each and had minimum one face-to-face session. The response by the veterinarians was tremendous and around 210 veterinarians offered for the courses by paying fees. Participants and stakeholders expressed the need for additional courses and accordingly two more courses on surgical techniques in large and small animals were launched which also received good response.

I. INTRODUCTION

Nations are growing with pace in technology and technological advancements. Till the end of 20th century development was the priority of entire planet earth but in the ending of the 20th century it was realized by almost all countries that development cannot go alone but it has to have the social, economic and environmental concerns. It was realized by the United Nations in Rio Conference on Environment and Development, 1992 that there is need of sustainable development. Now in 21st century the technological advancements are needed to be utilized for saving the planet earth from the curse of climate change and global warming reducing the carbon emissions across the entire planet earth. The argument in this paper is based on, how far technological advancements and technology transfer, by developed countries to developing countries can be facilitated in reduction of the carbon emission and greenhouse gases, through legally binding norms? How there should be synergy in between technologies reducing carbon emission and IPR issues?

5.1 Technology readiness levels- Introduction
Technology readiness levels (TRLs) is measurement of the maturity level of a particular technology. These are based on a scale from 1 to 9, with 9 being the most mature technology. It is a map that shows whether a given technology is in a conceptual state or can be used in real-world applications and ensures innovations are thoroughly tested before being applied on a large scale. The TRL scale uses a set of questions designed to measure progress of a technology toward maturity. They help in reducing risks and improving efficiency. TRLs were initially designed in the 1970s for use by NASA to assess how prepared a technology was for space missions. Technology for space travel is always extremely sophisticated and with a high degree of risk. NASA required a system to assess systematically whether or not a new technology was ready to implement. By breaking down development into different levels, NASA was able to provide informed decisions on which innovations were ready to incorporate (figure 12). In due course, TRL proved to be so effective that other industries began to use it. Other entities like the European Space Agency (ESA), U.S. Department of Defense (DoD), BIRAC, DRDO and many other agencies have taken , to using TRL to guide R&D strategies. TRL helps in simplifying development, decreasing risks, and maximizing resource utilization.

Technology Assessment and Refinement
What is Technology Assessment?
Technology assessment serves as a method or tool for forecasting future technological needs. It helps in envisioning or predicting potential technological developments required by users and in identifying areas where existing technologies can be improved. In agriculture, evaluating a technology means understanding its worth or effectiveness. This evaluation can be done by researchers, farmers, or other relevant stakeholders. The knowledge obtained from such evaluations is essential for creating new technologies, improving existing ones, and ensuring their successful adoption by end users.
The approach to technology assessment varies depending on who is conducting the evaluation, the purpose behind it, and the specific characteristics of the technology being assessed. It is commonly defined as the organized and intentional use of knowledge, skills, and experience to carry out a task or deliver a service that contributes to the well-being of society.
Technology Assessment: Definition and Objectives
According to Strasser (1972), technology assessment is a structured approach to planning and forecasting that identifies various options and associated costs. It considers not only economic factors but also environmental and social impacts, both internal and external to the technology being evaluated. The assessment places emphasis on analyzing both the positive and negative consequences of technologies. As such, institutions involved in the development, refinement, and dissemination of agricultural technologies have a significant stake in conducting technology assessments.

Basics of Technology Commercialization
Technology, a ubiquitous force shaping our world, can be understood from various angles. Here’s a breakdown of its definition, functions, and the fascinating process of its advancement.
Definition
At its core, technology is the application of scientific knowledge for practical purposes. It’s not just about gadgets and gizmos; it encompasses a vast array of systems, processes, and tools that we use to transform the world around us and solve problems. This includes everything from the humble wheel to the intricate workings of artificial intelligence.
Functions
Technology serves a multitude of functions, broadly categorized into:
Simplifying tasks: From automated manufacturing to self-driving cars, technology automates and streamlines processes, saving time and effort.
Enhancing communication and connection: From the internet to social media, technology bridges geographical barriers and fosters global interaction.
Expanding our knowledge and understanding: Scientific instruments, telescopes, and advanced data analysis tools enable us to explore the universe, delve into the microscopic world, and gain deeper insights into various fields.

Basics of Technology Incubation
Technology incubation is a fascinating process that fosters the growth of innovative startups and businesses with high-potential technology. It provides a supportive environment and resources for early-stage companies to develop their ideas, validate their business models, and navigate the challenges of commercialization.
Here’s a breakdown of the key aspects of technology incubation: What happens in a technology incubation?
Pre-incubation: Startups with promising ideas can receive initial guidance and support to refine their concepts and develop a business plan.
Incubation: Selected startups gain access to shared office space, mentorship from experienced professionals, networking opportunities, and access to funding sources.
Post-incubation: Graduated startups continue to receive support in areas like marketing, legal advice, and investor relations as they scale their businesses.
Benefits of Technology Incubation
Reduced risks: Startups can test their ideas and validate their market potential before investing significant resources.
Access to resources: Incubators provide vital resources like office space, equipment, and software, reducing the financial burden on startups.

Technology Promotion
The activity of promoting the transfer of technology by creating opportunities, advertising and organizing technology events.
Promotion is a marketing tool, used as a strategy to communicate between the sellers and buyers. Through this, the seller tries to influence and convince the buyers to buy their products or services. It assists in spreading the word about the product or services or company to the people. The company uses this process to improve its public image. This technique of marketing creates an interest in the mindset of the customers and can also retain them as a loyal customer.
Promotion is a fundamental component of the marketing mix, which has 4 Ps:
1. Product (Warranty, features, variety, quality, design, packaging, brand name)
2. Price (List price, discounts, payment terms, credit)
3. Place (channels, coverage, Types of promotion locations, transportation, inventory)
4. Promotion (advertising, self-marketing/personal, sales promotion, public relations, direct marketing, trade shows, events).

Telemedicine is a rapidly developing application of clinical medicine wherein medical information is transferred via telephone, the Internet or other networks for the purpose of consulting, and sometimes remote medical procedures or examinations. Telemedicine may be as simple as two health professionals discussing a case over the telephone, or as complex as using satellite technology and video-conferencing equipment to conduct a real-time consultation between medical specialists in two different countries. Telemedicine generally refers to the use of communications and information technologies for the delivery of clinical care.

Care at a distance (also called in absentia care), is an old practice which was often conducted via post; there has been a long and successful history of in absentia health care, which, thanks to modern communication technology, has metamorphosed into what we now know as modern telemedicine.

The terms e-health and tele-health are at times wrongly interchanged with telemedicine. Like the terms “medicine” and “health care”, telemedicine often refers only to the provision of clinical services while the term tele-health can refer to clinical and non-clinical services such as medical education, administration, and research. The term e-health is often, particularly in the UK and Europe, used as an umbrella term that includes tele-health, electronic medical records, and other components of health IT.

8.1 Statistical Hypotheses

in attempting to reach decisions about the populations, it is useful to make assumptions or guesses about the populations involved. When the assumption or statement about a phenomenon occurring under certain conditions is formulated as proposition it is called a scientific hypotesis. We can construct criteria by which a scientific hypothesis may be ‘the  yield of a new paddy variety will be 3500 kg per hectare’. In statistical language it may be stated as ‘the random variable (yield of paddy) is distributed normally with mean 3500 kg/ha’. Such a statement or proposition about the probability distribution of a random variable is called the statistical hypothesis.

Introduction

Canine atopic dermatitis (CAD) is a chronic inflammatory skin disease marked by itching (pruritus), redness (erythema), and recurrent infections. While traditionally considered an immune-mediated condition, recent studies highlight the significant role of skin barrier dysfunction in its development. A key aspect of CAD is the compromised skin barrier, which increases permeability to allergens, irritants, and microorganisms, thereby worsening the disease. The skin barrier is a complex, dynamic structure essential for protecting dogs from environmental challenges. The stratum corneum—the outermost layer of the epidermis—serves as a crucial defense against environmental insults, allergens, and pathogens. In dogs with atopic dermatitis, this barrier often becomes impaired, leading to increased transepidermal water loss (TEWL), greater allergen penetration, and secondary infections. This dysfunction both results from and contributes to the condition, creating a self-perpetuating cycle of barrier disruption, inflammation, and immune dysregulation.

1. Introduction

Climate change includes higher temperatures, changes in rainfall patterns, alterations in the frequency and distribution of weather events such as droughts, storms, floods, and heatwaves, sea-level rise, and the consequent impacts on human and natural systems (Riedy, 2018). Climate is the average weather in a given area over a longer time. A description of climate includes information on, for example, “the average temperature in different seasons, rainfall, and sunshine. Also, a description of the chance of experiencing extremes is often included. Climate change is any systematic change in the long-term statistics of climate variables such as temperature, precipitation, pressure, or wind sustained over several decades or longer. Climate change can be due to natural external forcings (changes in solar emission or changes in the Earth’s orbit, natural internal processes of the climate system), or it can be human-induced” (Buonocore, 2022).