تولیدی اور جنسی صحت: اسلامی تعلیمات کی روشنی میں

Human is the combination of body and spirit, Islām pays attention to the balanced growth and construction of the human personality considering the health of both body and spirit. As Muslims, we believe that Islām is the perfect code of life, which provides guidance for the solutions of all individual and collective problems of human beings. Therefore, we believe that Islām has a complete system of instructions for the development and reformation of spirit on the one hand, and, on the other hand, it has prescribed guidelines for the upkeeping and maintenance of the body. Reproductive and sexual health is one of the major problems of human beings. Eastern societies are comparatively shy to discuss this problem, unless necessary, while the western societies have introduced sex education in their schools to teenagers. We being Muslims tend to look towards our religion to guide us in such a way, that it may educate us, on the one hand, and on the other, it may guide us to adopt the required attitude to avoid the negativity of its awareness. Although the issue of reproductive health is considered as the specialty of the modern age, however, Islamic instructions very obviously discuss them from the beginning. In this article, the author has explored and elaborated Islamic teachings regarding the reproductive health and sexual instructions and discussed them in order to prove that Islām has the full capacity to solve the current social problems of reproductive health and sexual health.

Robust Algorithm for Genome Sequence Short Read Error Correction Using Hadoop-Mapreduce

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.