Association of consanguineous marriages with congenital anomalies Cousin marriages and birth defects

Congenital anomalies are a major health problem all over the world; especially it is important cause of deaths and birth defects, chronic illness and disability in infants. The major cause of this is consanguineous marriages. Generation of cousin marriages have significant association with congenital anomalies Objective: To find out the association of consanguineous marriages with congenital anomaliespresent at the time of birthMethods: A cross sectional study was conducted at District Head Quarter Hospital, Okarafrom May to August, 2018. 100 adult individuals aged between 19 to 55 years, with and without cousin marriage of both genders were consecutively enrolled. Participants were assessed through pre-tested questionnaire, with prior written informed consent. Unwilling married individuals and individuals from other hospitals were not selected Results: According to resultsthere was a significant association between generation of cousin marriages with congenital anomalies present at the time of birth, as p value was 0.002Conclusions: Study concluded that the generation of cousin marriages has significant association with congenital anomalies present at the time of birth and due to cousin marriage 59% of the couples had congenital abnormalities in their children and 85% had genetic disorders.

Intelligent Logical Error Detection and Mitigation Model for Python

Logical errors (LE) are the most common problem in overall programming languages. Logical fallacies are not shown as regular errors in the programming because their result is only different than planned and its detection is possible only by reviewing the code and determining the flaw. Each programming language (PL) has its logical error challenges on different hardware architectures. However, these models primarily focus on the software-based logical error solution and must integrate into the existing IDEs as an intelligent Unit. 90% logical error can be solved by the software and the rest by correcting hardware design or creating capability between hardware and software. Intelligent logical error detection and mitigation model for python (ILEDMP) is live logical error detection system which saves much time, energy, cost, efforts, enhances coding experience, increases productive, accuracy, memory preservation, additional resources usage, and processing power. These are other benefits of model besides detecting logical errors. Research goes further to enhance Software Design (SD), Software Quality Assurance, Software debugging, Software Security, and various additions to improve the coding ability for all kind of users. The tool is created in the python programming language (PL) and detects the python bugs. Spyder, Thonny, Eclipse Python (LiClipse), Win Python, Pycharm (Intellij Ultimate) and Wing IDEs are weak in detecting the logical errors. Though, Model has initially detected nine types of bugs with live error detection. Intelligent logical error detection and mitigation model for python (ILEDMP) are capable of all powers which python is offering it for its programs support in the computation.