Evolution, Medicine, and Public Health (EMPH) is an open access journal that publishes original, rigorous applications of evolutionary thought to issues in medicine and public health.
This template may be used to prepare your submission to EMPH. It contains instructions on how to include text, figures and references, and when you are ready to submit your manuscript please click the Submit to EMPH button on the topbar of the Overleaf editor and follow the instructions provided. We hope you find Overleaf useful for your EMPH submission, and please let us know if you have any feedback.
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EMPH aims to connect evolutionary biology with the health sciences to produce insights that may reduce suffering and save lives. Because evolutionary biology is a basic science that reaches across many disciplines, this journal is open to contributions on a broad range of topics, including relevant work on non-model organisms and insights that arise from both research and practice. All material to be considered for publication in Evolution, Medicine, and Public Health should be submitted in electronic form via the journal's online submission system. Full instructions for manuscript preparation and submission can be found at http://emph.oxfordjournals.org/
Evolution, Medicine, and Public Health (EMPH) is pioneering a new category of contributions called Clinical Briefs for which we are soliciting further submissions. Briefs are of two types: 1) Clinical—that take an explicitly evolutionary perspective to address a specific condition or pathology and 2) Foundational—that deal with basic topics underpinning an understanding of evolutionary principles that shed light on clinical conditions.
This novel type of publication is restricted to a one-page, 600-word summary, including references and figures, designed to be accessible in style and useful for practitioners. Both kinds of briefs use a standard template with three columns: Clinical Briefs use the first to discuss the targeted pathology, the second to discuss an evolutionary perspective on this pathology and the third to discuss future implications. Foundational Briefs use the first column to give a definition and background to the topic discussed, the second to give relevant examples from human biology and public health and the third to give specific examples from clinical medicine. Briefs can be easily downloaded and read from tablets and mobile phones. As with other contributions to EMPH, Briefs are peer-reviewed and searchable online.
Testing is both technically and economically an important part of high quality software production. It has been estimated that testing accounts for half of the expenses in software production. Much of the testing is done manually or using other labor-intensive methods. It is thus vital for the software industry to develop efficient, cost effective, and automatic means and tools for software testing. Researchers have proposed several methods over years to generate automatically solution which have different drawbacks. This study examines automatic software testing optimization by using genetic algorithm approaches. This study will cover two approaches: a) obtain the sequence of regression tests that cover the greatest amount of code and b) once it is achieved another genetic algorithm will eliminate tests cases that cover the same section of code on the basis of still get the maximum code coverage. The overall aim of this research is to reduce the number of test cases that need to be run with the greatest amount of code covered.
We will form a proof of the Arzela-Ascoli Theorem through use of the Heine-Borel theorem. We will also be considering some notions of compactness on metric spaces. The Arzela-Ascoli Theorem then allows us to show compactness, letting us state and prove Peano's existence theorem, pertaining to the existence of the solutions of a type of ODE. Then we will state the Kolmogorov-Riesz compactness theorem, allowing us to show compactness in $L^p$ spaces, building from the Arzela-Ascoli Theorem.
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