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Nutritive Value and Nitrate Content of Fruits and Vegetables of Pakistan

Thesis Info

Author

Anwar Ahmad Siddiqui

Department

Faculty of Science,Institute of Chemistry Studies

Program

PhD

Institute

University of the Punjab

Institute Type

Public

City

Lahore

Province

Punjab

Country

Pakistan

Thesis Completing Year

1980

Thesis Completion Status

Completed

Subject

Chemistry

Language

English

Added

2021-02-17 19:49:13

Modified

2023-01-06 19:20:37

ARI ID

1676728998440

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ماہرؔ القادری

 ماہرؔ القادری
جناب ماہر القادری کی وفات کی خبر سے بہت ہی دل گیر اور دل فگار ہوکر جب یہ تحریر لکھنے بیٹھا ہوں تو کراچی کی ساری علمی و ادبی مجلسیں یاد آرہی ہیں۔
کراچی بارہا جانے کا اتفاق ہوا، وہاں کی ممتاز شخصیتوں کی یادوں کی قندلیں روشن کرتا رہتا ہوں، ان میں بہت سے اﷲ کو پیارے بھی ہوگئے، اختر جونا گڑھی مرحوم یاد آتے ہیں، ان کی کتاب ’’طبقات الامم‘‘ دارالمصنفین سے شائع ہوئی تھی، معارف میں مولانا شبلیؒ پر اچھے مضامین لکھے، وہ بزرگ محترم مولانا سید ابوظفر ندوی مرحوم کے ساتھ جونا گڑھ سے شہاب رسالہ بھی نکالا کرتے تھے، دارالمصنفین کے بڑے قدردان رہے، وہ جس محبت سے کراچی میں ملے اس کی یاد برابر باقی رہے گی، ان ہی کے یہاں کھانے پر حفیظ ہوشیار پوری مرحوم سے ملا تھا، ان کے پرکیف نغمہ شعری سے بھی محظوظ ہوا تھا، ان کی محبت بھری باتوں میں بڑی کیفیت تھی، ممتاز حسن مرحوم (ریٹائرڈ سکریٹری محکمہ فنانس حکومت پاکستان) یاد آتے ہیں تو ان کی علم نوازی، کرم گستری اور دوست پروری کے معطر اور نکہت بیز پھولوں کے بار سے دبتا چلا جاتا ہوں، ایک رات جناب جمیل عالی کے دستر خوان پر میں جناب ممتاز حسن مرحوم، ابن انشاء مرحوم اور یادش بخیر پیر حسام الدین راشدی کے ساتھ شریک ہوا، رات کو ایک بجے تک علمی و ادبی باتیں ہوتی ہیں، وہ رات بھی کیسی حسین اور بہار آفریں تھی، ممتاز حسن مرحوم ایک تناور سایہ دار علمی برگد تھے، اسی کے چھاؤں کے نیچے کراچی کے ارباب علم جمع ہوتے اور ان کے سایہ عاطفت میں اپنے علمی و ادبی ذوق کو پھلتے پھولتے محسوس کرتے، جناب ابن انشاء مجلسوں میں ملتے اور خاموش بنے رہتے، مگر اخبار کے کالم میں شب برات کی پھلجڑی اور...

ڈاکٹر فاروق احمدخان کی تفسیری خدمات اور آپ کے تفردات کا تجزیاتی مطالعہ An Analytical Study of Dr. Farooq Ahmed's Tafsir Services and His Distinctions

For the guidance of humanity, God revealed the Holy Quran. It is the only book which is recited the most. Those who read and teach this book have been called the best people. From the blessed life of the Holy Prophet (ﷺ) till today, scholars have tried their best to make common sense for the less educated people. And Muhadithin have to bind chapters of "Kitab al-Tafseer and Chapters of Commentary" in their own books. Companions and many commentators interpreted. Some of the interpretations were translated into different languages ​​so that common people can benefit from it. Scholars of the Indian sub-continent also interpreted the Holy Quran for the understanding of common people. A link in the same series is Dr. Muhammad Faruk Khan's "Asan Tarin Tarjuma Wa Tafsir" which is written in simple Urdu language. Dr. Sahib's distinctions on special topics make the reader ponder.  In this article, Dr. Farooq Ahmad Khan's services regarding Tafsir and his distinctions about (Alphabets, prohibited trees, forgetfulness of Adam, etc.) will be examined. Along with the opinions of different commentators will also be present. Keywords:               Qura’n, Dr. Farooq Ahmad, Asan Tarin Tarjuma wa Tafsir, distinctions, Commentators.

Recommending Relevant Papers Using In-Text Citation Frequencies and Patterns

Scientific publications are growing exponentially. For example, more than 50 million journal papers have been published till now, and more than 2 million journal papers are added to the scientific knowledge every year. The published conference papers are in billions, and millions others are added every year. The world famous scientific databases such as Web of Science, Scopus, and PubMed etc index millions of such scientific papers, and that also despite the fact that their index either belongs to specialized domain or it is selective. There is another comprehensive index known as Google Scholar, indexes huge scientific knowledge from different domains. These systems make available the scientific knowledge to researchers. The advancement in research is always possible by standing on the shoulders of others. However, when users attempt to identify relevant papers from the mentioned systems or other similar systems, they are given millions of papers and are asked to select the most relevant papers manually by skimming those millions of papers. This creates frustration, and generally all of the selected papers do not belong to the list of papers which the users must read. In this task, many important papers are overlooked by the users as well. The identification of relevant papers from such a big data has attracted a number of researchers across the globe to find solutions to this problem. The contemporary approaches use a variety of techniques for the identification of the relevant documents such as content based approaches, metadata based approaches, collaborative filtering based approaches, co-citation analysis, and bibliographic analysis etc. However, the state-of-the-art research lacks in many directions such as its inability to find the nature of relationship between scientific documents and its failure to find how strongly two scientific documents are linked up, based on their relationship strength. To address these issues, this thesis designs, implements, and evaluates a novel approach that facilitates researchers to identify the most relevant papers in their domains. The proposed approach identifies the most relevant papers from the list of cited-by papers for the cited paper. This thesis works on the in-text citation frequencies and in-text citation patterns to identify the most relevant papers. In-text citation frequency is the number of occurrences of citations of one paper in the text of the other paper. In-text citation frequency patterns are the in-text citation evidences in different sections of the paper. The system has been implemented as a prototype for 3 CiteSeer. The proposed system has been evaluated using a number of user studies. The proposed approach shows encouraging results and assists the scientific community to identify the most relevant papers from a huge list of papers.