The humid and warm conditions in greenhouses provide an excellent environment for pests’ living conditions, and therefore, they provide ideal medium for alien introductions. Molluscs are among the most significant pests that infest plastic covered greenhouses. To identify and report their mollusc species, 23 greenhouses in Iraq were surveyed between March 2023 and April 2024. Of these, 11 were found to be infested with snails. A total of 158 specimens were collected and morphologically identified to seven species: Monacha obstructa (L. Pfeiffer, 1842), Eobania vermiculata (O.F. Müller, 1774), Xeropicta krynickii (Krynicki, 1833), Rumina decollata (Linnaeus, 1758), Polygyra cereolus (Megerle Von Mühlfeld, 1818), Cochlicella barba

This research attempts to shed light on a topic that is considered one of the most important topics of HRMs management, which is the Employee centric approach by examining its philosophy and understanding . To achieve the goal, the research relied on the philosophical analytical method, which is one of the approaches used in theoretical studies. The research reached a set of conclusions, the most important of which are the theoretical studies that addressed this entry in the English language and the lack of it in the Arabic language, according to the researcher's knowledge. The research reached a set of recommendations, the most important of which was that this approach needs more research, analysis and study at the practical and th

This paper deals with constructing mixed probability distribution from mixing exponential

0

The dangerous and potentially blinding condition known as Acanthamoeba keratitis is caused by free-living amoebae of the genus Acanthamoeba. The prevalence of AIDS patients and contact lens wearers has increased in recent years, making cannaeba infections more significant. It's interesting to note that, depending on the parasite, host, and environmental conditions, the pathways linked to Acanthamoeba pathogenesis are frequently extremely complex. Notwithstanding our progress in antibiotic therapy and supportive care, the prevalence of Acanthamoeba keratitis has not decreased

The current study is a taxonomic account of three gastrotrich species that belong to Chaetonotidae (Phylum Gastrotricha) namely Ichthydium auritum Brunson, 1950 Lepidodermella squamata (Dujardin, 1841) and Chaetonotus anomalus Brunson, 1950. These species are registered as a new record from Iraq and were collected from several locations along the main outfall drain (MOD) in south of Baghdad, from January to December 2020. The species described in this article were found to be related to Hydrilla and Ceratophyllum and prefer environments rich in detritus and decomposing organic matter. The worms preferred water that is salty, hard, alkaline, and had good oxygen content.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class