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      <title>The Art of Islamic Management.</title>
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      <author>Sahfi, M, Q., 10/09/2026.</author>
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		&lt;p&gt;Date Published:2026&lt;/p&gt;	&#xD;
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      <title>Building agentic AI systems   : Create intelligent, autonomous AI agents that can reason, plan, and adapt</title>
      <link>https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=Building agentic AI systems   : Create intelligent, autonomous AI agents that can reason, plan, and adapt&amp;LibraryID=0001</link>
      <author>Biswas, Anjanava,</author>
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		&lt;a href='https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=Building agentic AI systems   : Create intelligent, autonomous AI agents that can reason, plan, and adapt&amp;LibraryID=0001'&gt;&#xD;
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		&lt;p&gt;     Gain unparalleled insights into the future of AI autonomy with this comprehensive guide to designing and deploying autonomous AI agents that leverage generative AI (GenAI) to plan, reason, and act. Written by industry-leading AI architects and recognized experts shaping global AI standards and building real-world enterprise AI solutions, it explores the fundamentals of agentic systems, detailing how AI agents operate independently, make decisions, and leverage tools to accomplish complex tasks. Starting with the foundations of GenAI and agentic architectures, you&amp;apos;ll explore decision-making frameworks, self-improvement mechanisms, and adaptability. The book covers advanced design techniques, such as multi-step planning, tool integration, and the coordinator, worker, and delegator approach for scalable AI agents. Beyond design, it addresses critical aspects of trust, safety, and ethics, ensuring AI systems align with human values and operate transparently. Real-world applications illustrate how agentic AI transforms industries such as automation, finance, and healthcare. With deep insights into AI frameworks, prompt engineering, and multi-agent collaboration, this book equips you to build next-generation adaptive, scalable AI agents that go beyond simple task execution and act with minimal human intervention. &lt;/p&gt;&#xD;
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		&lt;p&gt;Date Published:2025&lt;/p&gt;	&#xD;
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      <title>ACCA taxation exam kit    : (exam sittings session computer based exams (CBEs) - June 2026 - March 2027).</title>
      <link>https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=ACCA taxation exam kit    : (exam sittings session computer based exams (CBEs) - June 2026 - March 2027).&amp;LibraryID=0001</link>
      <author>Kaplan Publishing</author>
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		&lt;a href='https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=ACCA taxation exam kit    : (exam sittings session computer based exams (CBEs) - June 2026 - March 2027).&amp;LibraryID=0001'&gt;&#xD;
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		&lt;p&gt;     The ACCA Taxation Exam Kit complements the Study Text, and tests your knowledge of tax relating to individuals, companies, and groups of companies. In the Exam Kit you’ll get practice questions with answers, paper-specific information, analysis of past tax papers, our recommend revision approach and exam technique, tutor debriefs, and worked examples. The Exam Kit is approved by ACCA and covers the full syllabus. &lt;/p&gt;&#xD;
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		&lt;p&gt;Date Published:2025&lt;/p&gt;	&#xD;
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      <title>ACCA taxation (TX-UK) FA25      : study text</title>
      <link>https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=ACCA taxation (TX-UK) FA25      : study text&amp;LibraryID=0001</link>
      <author>Kaplan Publishing</author>
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		&lt;p&gt;  Includes index.&#xD;
&amp;quot;Valid from 1 April 2026 to 30 June 2027&amp;quot;--Front cover.   The ACCA Taxation Study Text will teach you about the tax system relating to individuals, companies, and groups of companies. The Study Text contains exam guidance from ACCA, knowledge check tests to strengthen your understanding, and official past paper to give you exam practice. The Study Text is approved by ACCA, so you can be assured the material covers the full syllabus. &lt;/p&gt;&#xD;
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		&lt;p&gt;Date Published:2025&lt;/p&gt;	&#xD;
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      <title>Climate finance        : a comprehensive guide to financial strategies in a changing climate</title>
      <link>https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=Climate finance        : a comprehensive guide to financial strategies in a changing climate&amp;LibraryID=0001</link>
      <author>Chen, Jian,</author>
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		&lt;a href='https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=Climate finance        : a comprehensive guide to financial strategies in a changing climate&amp;LibraryID=0001'&gt;&#xD;
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		&lt;p&gt;     &amp;quot;In a world confronting the urgent realities of climate change, Jian Chen&amp;apos;s Climate Finance offers an indispensable guide for professionals tackling our greatest global challenge. This comprehensive textbook seamlessly connects environmental science with financial innovation, empowering students, investors, business leaders, and policymakers to address the dual crises of climate risk and economic disruption. Through a structured five-part framework, Chen demystifies the complexities of mobilizing capital for climate solutions -- from renewable energy investments and risk modeling to disclosure frameworks and portfolio management. With clear insights into physical and transition risks, cutting-edge financing mechanisms, and emerging trends, this book transforms climate challenges into actionable financial opportunities. Whether you&amp;apos;re managing assets, shaping policy, or studying sustainability, Climate Finance equips you with the knowledge to drive meaningful change in the transition to a resilient, low-carbon economy. Take the first step toward building a sustainable future -- your journey begins here.&amp;quot; -- &lt;/p&gt;&#xD;
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		&lt;p&gt;Date Published:2025&lt;/p&gt;	&#xD;
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      <title>Decoupling data and linguistic knowledge for spontaneous tabular Q/A</title>
      <link>https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=Decoupling data and linguistic knowledge for spontaneous tabular Q/A&amp;LibraryID=0001</link>
      <author>Farhan,</author>
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		&lt;p&gt;  A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science to the Department of Computer Science at the National University of Computer and Emerging Sciences. Chapter 1:	Introduction
Chapter 2:	Related Work
Chapter 3:	Materials and Methods
Chapter 4:	Results and Discussion
Chapter 5:	CASE STUDY: A Custom QA Tool for Pun Translation in Tabular Data
Chapter 6:	Conclusion and Future Work.  Table Question Answering (Tabular Q/A) is the task of understanding user-given queries in natural language and reasoning over input tables to provide accurate answers. This thesis presents a heuristic-driven solution called Agentic Table Talk, which utilizes general-purpose Large Language Models (LLMs) to solve the problem of Tabular Q/A. Earlier approaches required whole tables to prompt LLMs. As tables can grow infinitely large, directly incorporating entire tables into prompts becomes computationally infeasible due to the finite context window of LLMs, which can only handle a limited number of input tokens. In contrast, some approaches are entirely driven by Retrieval Augmented Generation (RAG) to ground the LLMs with K relevant records, where the value of K is predefined and hard coded. The main drawback of such approaches is that they do not yield satisfactory results for Tabular Q/A, where data is structured and cellular. Additionally, the meaning of individual cells is often context-dependent and can vary substantially based on the values of neighboring cells. This contrast introduces the challenge of designing prompts that efficiently utilize the available token budget while preserving essential information, thereby ensuring the scalability of the proposed approach irrespective of the input table size. To address these challenges, this thesis proposes an iterative novel combination of a lightweight heuristic called RAGular SubGraph Retrieval combined with the ReAct Agentic Framework powered by general-purpose LLMs. This combination effectively preserves scalability by decoupling the global comprehension of the input table, handled by the ReAct agent, from local understanding of neighborhoods, managed by the proposed heuristic. The heuristic adopts the core principles of traditional RAG while placing greater emphasis on preserving the neighborhood relationships of the selected cells. The ReAct Agent receives the user query along with the filtered tabular data as a subgraph that is assumed to be part of a larger, unknown graph. The output from the heuristic guides the subsequent ReAct Agent with a focused input context that consists of only relevant cells and their neighborhood, based on the given input query. The primary objective of the ReAct Agent is to use explicit reasoning to identify the facts necessary to answer the provided user query. This may involve reasoning over the known subgraph or taking actions (such as re-triggering the heuristic with a slightly modified query or finding the closest K-Adjacent neighbors of a relevant cell) to explore new, unexplored cells based on the structure of the already known regions. Both components work together iteratively to discover relevant facts for generating an authentic answer to the user query based on the provided reference table, until the process successfully locates all the necessary information or sufficient confidence in the query&amp;apos;s unanswerability is achieved. In addition, this thesis has also presented a unique approach to perform sophisticated operations with the agent by integrating a set of custom tools to perform low-level tasks (such as translation) that are not supported directly by the underlying LLM. As an example case-study, we have addressed the challenge of translating named entities containing a wordplay into a given target language using small-scale open sourced transformer-based language models and OPUS corpus. The proposed approach is evaluated using general-purpose LLMs (such as Gemnni/Qwen/Gemma) of varying parameter sizes on benchmarked HiTab and AIT-QA datasets, along with a synthetic dataset featuring large tables. Furthermore, we have explicitly used the JOKER dataset to evaluate performance of custom tools for the translation of English named entities to French. &lt;/p&gt;&#xD;
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		&lt;p&gt;Date Published:2026&lt;/p&gt;	&#xD;
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      <title>Strategic management          : concepts and cases : a competitive advantage approach</title>
      <link>https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=Strategic management          : concepts and cases : a competitive advantage approach&amp;LibraryID=0001</link>
      <author>David, Fred R.,</author>
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		&lt;p&gt;     &amp;quot;This college textbook shows how to gain and sustain a competitive advantage in today&amp;apos;s complex business world. The text helps you develop your own cutting-edge strategy through skill-developing exercises. It also offers coverage on issues related to business ethics, social responsibility, global operations, and sustainability&amp;quot;--
The 18th Edition features updated research, cases and examples. As a result, you&amp;apos;ll be able to effectively create and implement a plan that can lead to a sustainable competitive advantage for any type of business. &lt;/p&gt;&#xD;
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		&lt;p&gt;Date Published:2025&lt;/p&gt;	&#xD;
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      <title>Enterprise architecture at work             : modelling, communication and analysis</title>
      <link>https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=Enterprise architecture at work             : modelling, communication and analysis&amp;LibraryID=0001</link>
      <author>Lankhorst, Marc,</author>
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		&lt;p&gt;   Introduction to Enterprise Architecture.-State of the Art -- Foundations -- Communication of Enterprise Architectures -- A Language for Enterprise Modelling -- Combining ArchiMate with Other Standards and Approaches -- Guidelines for Modelling -- Viewpoints and Visualisation -- Architecture Analysis -- Architecture Alignment -- Tool Support -- Case Studies -- Beyond Enterprise Architecture -- Appendix -- References -- Index.  Lankhorst and his co-authors present ArchiMate® 3.0, enterprise modelling language that captures the complexity of architectural domains and their relations and allows the construction of integrated enterprise architecture models. They provide architects with concrete instruments that improve their architectural practice. As this is not enough, they additionally present techniques and heuristics for communicating with all relevant stakeholders about these architectures. Since an architecture model is useful not only for providing insight into the current or future situation but can also be used to evaluate the transition from &amp;apos;as-is&amp;apos; to &amp;apos;to-be&amp;apos;, the authors also describe analysis methods for assessing both the qualitative impact of changes to an architecture and the quantitative aspects of architectures, such as performance and cost issues. The modelling language presented has been proven in practice in many real-life case studies and has been adopted by The Open Group as an international standard. So this book is an ideal companion for enterprise IT or business architects in industry as well as for computer or management science students studying the field of enterprise architecture. This fourth edition of the book has been completely reworked to be compatible with ArchiMate® 3.0, and it includes a new chapter relating this new version to other standards. New sections on capability analysis, risk analysis, and business architecture in general have also been introduced. Features and Benefits · Introduces the ArchiMate® 3.0 modelling language for enterprise architecture, an Open Group standard · Describes quantitative analysis methods to assess the impact of architectural changes · Provides new insights on the use of architecture models in capability-based planning, portfolio management and risk management · Briefly introduces industry standards and approaches like BPMN, UML, the Business Model Canvas, the Business Motivation Model and TOGAF 9.1 and relates them to ArchiMate® 3.0 · Extensive industry support. &lt;/p&gt;&#xD;
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		&lt;p&gt;Date Published:2017&lt;/p&gt;	&#xD;
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      <title>Keras 3            : the comprehensive guide to deep learning with the keras api and python</title>
      <link>https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=Keras 3            : the comprehensive guide to deep learning with the keras api and python&amp;LibraryID=0001</link>
      <author>Nauman, Mohammad,</author>
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		&lt;a href='https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=Keras 3            : the comprehensive guide to deep learning with the keras api and python&amp;LibraryID=0001'&gt;&#xD;
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		&lt;p&gt;  Includes index.   &amp;quot;Harness the power of AI with this guide to using Keras! Start by reviewing the fundamentals of deep learning and installing the Keras API. Next, follow Python code examples to build your own models, and then train them using classification, gradient descent, and regularization. Design large-scale, multilayer models and improve their decision making with reinforcement learning. With tips for creating generative AI models, this is your cutting-edge resource for working with deep learning!&amp;quot;-- Provided by publisher. &lt;/p&gt;&#xD;
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      <title>The Pakistan national bibliography 2022 =   : پاکستان قومی کتابیات 2022</title>
      <link>https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=The Pakistan national bibliography 2022 =   : پاکستان قومی کتابیات 2022&amp;LibraryID=0001</link>
      <author>National Library of Pakistan ,</author>
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		&lt;p&gt;  This record is bilingual &amp;amp; published annualy.    &lt;/p&gt;&#xD;
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		&lt;p&gt;Date Published:2025&lt;/p&gt;	&#xD;
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      <title>The Pakistan national bibliography 2021 =                 : قومی کتابیات پاکستان ۲۰۲۱.</title>
      <link>https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=The Pakistan national bibliography 2021 =                 : قومی کتابیات پاکستان ۲۰۲۱.&amp;LibraryID=0001</link>
      <author>National Library of Pakistan,</author>
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		&lt;a href='https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=The Pakistan national bibliography 2021 =                 : قومی کتابیات پاکستان ۲۰۲۱.&amp;LibraryID=0001'&gt;&#xD;
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		&lt;p&gt;  This record is bilingual &amp;amp; published annualy.   The Pakistan National Bibliography 2021 is an official comprehensive record of books, government publications, and serials printed and published in Pakistan during 2021. Compiled and issued by the National Bibliographical Unit of the National Library of Pakistan, it serves as a core tool for national bibliographic control, research, and literary archiving.
Records the intellectual and literary output produced in the country during the year 2021.
Legal Deposit: Based on publications received under the Copyright Ordinance of 1962.
Research Guide: Assists scholars, librarians, and historians in tracking Pakistani imprints, subject areas, and language publications. &lt;/p&gt;&#xD;
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		&lt;p&gt;Date Published:2023&lt;/p&gt;	&#xD;
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      <title>Judgement on child marriage restraint act     : sariat petition no. 10/I of 2020</title>
      <link>https://nu.insigniails.com/Library/Index?SearchType=titles&amp;PassedInValue=Judgement on child marriage restraint act     : sariat petition no. 10/I of 2020&amp;LibraryID=0001</link>
      <author>Pakistan Federal shariat court,</author>
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		&lt;p&gt;   Judgment of the Federal Shariat Court on the prohibition of child marriage = أحكام المحكمة الشرعية الاتحادية بشأن حظر زواج الأطفال.&#xD;
Analysis of Article 16 of CEDAW.&#xD;
تحليل المادة ١٦ من اتفاقية سيداو.   &lt;/p&gt;&#xD;
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		&lt;p&gt;Date Published:2026&lt;/p&gt;	&#xD;
	&lt;/td&gt;&#xD;
&lt;/tr&gt;&#xD;
&lt;/table&gt;</description>
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