Forensic entomology is considered a branch of general entomology which was recently founded and ruled by the Entomology Society of America in the 1990s, followed by this ruling the society approval came to establish what is known today as the American Board of Forensic Entomology (ABFE) in 1996. \nIt can be also called forensic biology which is the field of science that depends on different kinds of insects as a fundamental base to reveal the mystery of a crime circumstances especially violence crimes in general and homicides in specific. As many insects start their life cycle when the death of a living creature occurs, criminology have used many ways to reveal the mystery of a crime facts and circumstances, but even with the great scientific evolution a medical examiner is still unable to estimate the exact precise time of death after the passage of 72 hours corpse decomposition, however by using forensic entomology the exact time of death can be precisely estimated. \nIt is for sure that forensic science depends on more than field of science and method to solve and reveal the mysteries of crimes, and for every case there is a way or more that can be more analytically accurate for an incident, and sometimes more than one method are used for the same crime to reveal the identity of a murderer or the time of death in a more positively accurate way. \nConsequently insects are used in forensic science in combination with other critical important fields of science in criminal investigation like criminological psychology, Toxicology, Forensic Identification, fingerprint, hair print and memory print identification, and most importantly the DNA profiling.

Genetic Algorithm (GA) has been found successful in implementing the solution of a significant number of optimization tasks associated with machine learning, computer vision, pattern recognition, knowledge discovery and so on due to its robust global search strategy. This article explores the development of a robust framework on selecting features in urban land cover analysis for high resolution images using GA. The approach is focused on object based classification by detecting the object area in a given image with the help of visual information of the object from remote sensing images. The classification scheme has been organized with a multilayer perceptron (MLP) with back propagation algorithm. Experimental results reveal that this MLPGA based hybrid feature selection approach achieves better than the relevant counterpart approaches considering classification accuracy.

Escherichia coli is a commensal bacteria in the digestive tract of animals that is very influential on health. There has been a lot of research on Escherichia coli, but no studies have addressed the idea of publishing Escherichia coli in Veterinary Medicine which shows the big overview using data from all countries. This study aims to map the status of Escherichia coli publications in Veterinary Medicine which are published internationally and indexed by Scopus using bibliometric visualization. Bibliometric methods and research data analysis were implemented using analysis search results services from Scopus and VOSviewer applications. In this study, the details collected apply to 5836 documents published from 2011 to 2020. Research reveals that Kim, I. H., Universiteit Gent, the United States and Veterinary Microbiology are individual scientists, affiliated, country and sources of dissemination most active in Escherichia coli publications in Veterinary Medicine. There are six maps of collaborative research groups in Escherichia coli publications in Veterinary Medicine around the world. To identify a body of knowledge created from ten years of publication, this study builds a convergence axis grouping consisting of Escherichia coli studies: Immunology, Virulence Factors, Microbiology and Molecular Examination, and Animal abbreviated with the theme IVMA.

The purpose of this study was to detect and compare the incidence rates of Methicillin Resistant Staphylococcus aureus (MRSA) with Methicillin Resistant - coagulase negative staphylococci (MR-CNS) that contaminated the milk of dairy cows in East Java. A total of 220 cow\'s milk samples were collected from at 4 dairy farms in East Java Province, then followed by isolation and identification of S. aureus and CNS by standar laboratory methods. The Methicillin Resistant test was carried out on Mueller Hinton Agar (MHA) by the Kirby Bauer disc diffusion Cefoxitin 30 μg and Oxacillin 30 μg preparations, then confirmed with the Oxacillin Resistance Screen Agar Base (ORSAB). The results showed that there were 114 S. aureus with confirmed MRSA strains of 30 isolates and 106 CNS with confirmed MR-CNS strains of 12 isolates. It was concluded that the raw milk from dairy farms can be a potential reservoir for spreading of MRSA strains and MR-CNS strains to threat public health.