3 ۔معاشرتی اصلاح میں ذرائع ابلاغ کا کردار
قرآن مجید کے مطالعہ سے معلوم ہوتا ہے کہ اسلام نے سب سے پہلا ابلاغ کا تصور پیش کیا ۔ تخلیق آدم کے وقت اللہ تعالیٰ اور ملائکہ کے درمیان ہونے والا مکالمہ یہ ہے
﴿وَإِذْ قَالَ رَبُّكَ لِلْمَلَائِكَةِ إِنِّي جَاعِلٌ فِي الْأَرْضِ خَلِيفَةً۔ ﴾ 407
"اور جب تمہارے رب نے فرشتوں سے فرمایا کہ میں زمین پر ایک خلیفہ بنانے والا ہوں ۔ "
عمل ابلاغ کی پہلی صورت تھی ، پھر جب حضرت آد م ؑنے اللہ تعالیٰ کے حکم سے سب اشیاء کے نام بتائے تو گویا یہ حضرت آد مؑ کی طرف سے پہلے انسانی عمل ابلاغ کا آغاز تھا ، جس کا تذکر ہ قرآن نے یوں کیا
﴿وَعَلَّمَ آَدَمَ الْأَسْمَاءَ كُلَّهَا ثُمَّ عَرَضَهُمْ عَلَى الْمَلَائِكَةِ۔﴾408
" اور اللہ تعالیٰ نے آدم ؑ کو ساری چیزوں کے نام سکھائے ، پھر آدم ؑ نے ان کو فرشتوں کے سامنے پیش کیا ۔ "
حضرت آد م ؑ کے بعد جو سلسلہ نبوت جاری ہوا تو ہر نبی علیہ السلام نے حق وصداقت کے ابلاغ اور دین فرقان کی تبلیغ کا فریضہ سرانجام دیا اور اس فریضہ کی ادا ئیگی میں اپنے عہد کے تمام ممکنہ ذرائع ابلاغ (تحریر اور تقریر ) استعمال کیے ۔مقاصد نبوت، مقاصد انسانیت اور مقاصد ربانی ابلاغ کی بدولت ہی انسان تک پہنچے۔ احسن اختر ناز اس حوالے سے لکھتے ہیں
"خدا نے جب حضرت آد م ؑ کو تخلیق کیا تو اس کے نزدیک مقصد یہ تھا کہ یہ میری بندگی کرے گا اور میرا پیغام دوسری مخلوق تک پہنچائے گا ۔ اسی طرح دنیا کے پہلے انسان کو سب سے پہلے ابلاغ کا فریضہ ہی سپر د کیا گیا۔ بعد میں آنے والے تمام انبیا ئے کرام اور پھر نبی آخر الزمان پیغمبر اعظم ﷺ...
Introduction: Adaptive expertise is the ability of individuals to create innovative solutions when they come across novel problems or workplace challenges. Clinicians are often adept at handling routine clinical procedures but lack confidence and a proper strategy when previously un-encountered situations arise. Lots of research has been conducted on basic concepts and development of adaptive expertise however major chunk of literature belongs to non- medical fields. Little is studied about assessment of adaptive expertise in medical professionals and postgraduate residents. Objective: To measure adaptive expertise (AE) of radiology residents and to assess any association between the AE of postgraduate radiology residents (PGR) and their years of training. Methods: This multicenter correlational study involved 181 radiology residents from nine major teaching hospital of Lahore, Pakistan from May to October 2019. Katerina Bohle Carbonell Adaptive Expertise Inventory was used as a data collection tool. The questionnaire contained a total of eleven items encompassing two dimensions of AE: domain-specific and innovative skills. Total scores representing AE of PGRs were measured. AE scores and years of training were correlated using Spearman rho correlation. One-way ANOVA was conducted to further evaluate the association between AE and years of postgraduate training. Results: Out of 181 residents there were 78 (43.1%) males and 103 (56.9%) females. Most of them, 97 (53.6%) were enrolled in four years fellowship (FCPS) program and 62 (34.3%) were in the first year of their residency. Total AE scores of all radiology residents ranged from 33 to 54. AE scores and years of residency were positively correlated (rs= 0.4, p < 0.01). One-way ANOVA and Post hoc comparisons using Tukey HSD test further revealed significant pairwise differences between mean scores of residents’ groups (p = < 0.05) rejecting the null hypothesis. Conclusion: Overall, this study concludes that residents acquire adaptive expertise perpetually with progression in their training. KEYWORDS: Adaptive Expertise (AE), Radiology, Postgraduate Residents (PGRs)
Biological sequences consist of A C G and T in a DNA structure and contain vital information of living organisms. The development of computing technologies, especially NGS technologies have increased genomic data at a rapid rate. The increase in genomic data presents significant research challenges in bioinformatics, such as sequence alignment, short-reads error correction, phylogenetic inference, etc. Next-generation high-throughput sequencing technologies have opened new and thought-provoking research opportunities. In particular, Next-generation sequencers produce a massive amount of short-reads data in a single run. However, these large amounts of short-reads data produced are highly susceptible to errors, as compared to shotgun sequencing. Therefore, there is a peremptory demand to design fast and more accurate statistical and computational tools to analyze these data. This research presents a novel and robust algorithm called HaShRECA for genome sequence short reads error correction. The developed algorithm is based on a probabilistic model that analyzes the potential errors in reads and utilizes the Hadoop-MapReduce framework to speed up the computation processes. Experimental results show that HaShRECA is more accurate, as well as time and space efficient as compared to previous algorithms.