A political perusal of Initiations in Declaring Middle East a District vacant of mass Destruction weapons

Classifying butterfly species is crucial in biodiversity studies and environmental monitoring. However, manual classification is often a laborious process that requires specialized expertise and is prone to error, especially when species have similar visual characteristics. To address these drawbacks, this paper presents a hybrid approach that combines machine learning with deep learning for feature extraction. To enhance the visibility of important features, preprocessing techniques such as background removal and binarization are applied to butterfly images. Feature extraction was performed using the SqueezeNet convolutional neural network, pretrained on the ImageNet dataset. By discarding the final classification layer, the networ

Adult of dipterous flies were collected monthly from exposed animals carcasses during the period from February 2006 to January 2007 in Baghdad city. The results obtained showed that flies could be collected all over the year with variation of their population density in different seasons. The majority of the collected species were abundant during Spring and late Autumn (at lowest numbers) . In this investigation, nineteen species confined to four families were collected; these families are: Calliphoridae, Muscidae, Sarcophagidae and Fanniidae. The species Musca domestica Linn .was the most abundant followed by Chrysomya megacephala ( Fabricius ) , while Pollenia sp . and Fannia sp . were the least abundant species.

Background: Malaria remains a leading cause of mortality in sub-Saharan Africa (including Sudan). C-reactive protein (CRP) is useful as   a marker of severity in malaria. African studies have shown that serum CRP levels correlate with parasite burden and complications in malaria, especially falciparum. However, there are no data on CRP levels in Sudanese malaria patients.

This study aims to evaluate the association between CRP levels with comorbidities, species, and complications of severe malaria

Subjects and Methods: A cross-sectional study enrolled 65 severe malaria patients at Khartoum state hospitals during the period from April to June2021. Manifestations of severe

   Molecular barcoding was widely recognized as a powerful tool for the identification of organisms during the past decade; the aim of this study is to use the molecular approach to identify the diatoms by using the environmental DNA. The diatom specimens were taken from Tigris River. The environmental DNA(e DNA) extraction and analysis of sequences using the Next Generation Sequencing (NGS) method showed the highest percentage of epipelic diatom genera including Achnanthidium minutissimum (Kützing) Czarnecki, 1994 (21.1%), Cocconeis placentula Ehrenberg, 1838 (21.3%) and Nitzschia palea (Kützing) W. Smith, 1856 (16.3%).

   Five species of diatoms: Achnanthidiu