Fire incidences are classed as catastrophic events, which mean that persons may experience mental distress and trauma. The development of a robotic vehicle specifically designed for fire extinguishing purposes has significant implications, as it not only addresses the issue of fire but also aims to safeguard human lives and minimize the extent of damage caused by indoor fire occurrences. The primary goal of the AFRC is to undergo a metamorphosis, allowing it to operate autonomously as a specialized support vehicle designed exclusively for the task of identifying and extinguishing fires. Researchers have undertaken the tasks of constructing an autonomous vehicle with robotic capabilities, devising a universal algorithm to be employed

The conservation for biodiversity in Iraqi freshwater environments is important to protecting native species from the environmental impacts of alien species. Clarias gariepinus (Burchell, 1822) (Siluriformes, Clariidae) has been recognized as an alien species in Iraqi water bodies. This study aims to use molecular DNA to identify this catfish and trace its origins using. The DNA sequences of C. gariepinus were done using the mitochondrial DNA cytochrome c oxidase subunit 1 (COI) gene, and a specific primer set. The polymerase chain reaction (PCR) amplification was used to align the COI gene as a barcoding marker. After analysis, the sequences were compared with sequences in the National Center for Biology Information (NCBI) database

Sea level rise (SLR) due to climate change is affecting the coastline, causing shoreline changes, the degradation of mangrove forests, and the destruction of coastal resources. This is the cause of a huge amount of mangrove degradation in many parts of the Ganges–Brahmaputra–Meghna delta. A total of 90% of people have been forced to migrate from the island due to extreme weather conditions. In this study, remote sensing (RS) and geographic information system (GIS) techniques were used for LULC change and shoreline shift analyses of Ghoramara Island. LULC classification was carried out using thirty years of Landsat datasets with intervals of ten years (1990 and 2000) and intervals of five years (2005, 2010, 2015, and 2020). The classific