The present study is considered a pioneer investigation that deal with the terrestrial brown garden snail Cornu aspersum (Müller), in Iraq. Cornu aspersum however is considered an exotic species in many parts of the world ,The species is most probably infiltrates with plants transferred from one place to another. The species has gained importance in many ways. Nutritionally, the species is consumed as food item in many countries, but in other cases it is considered as pest for the damage it causes when feeding on valuable plant shoots. It also has medical importance for its role and ability in healing wounds, burns and remedy of other skin problems. This snail species however may act as a vector for some parasitic nematodes that cause serious diseases. The species is also important in scientific research, usually referred to as ‘ecological indicator’ employed in environmental pollution problems such as the one caused by heavy metals. A great deal of research on this species has been carried out in different parts of the world, however, in Iraq, the scientific attention given to land snails in general and to Cornu aspersum in particular is rare and may be negligible in comparison with the research carried out on aquatic Mollusca species. A total of 1880 individuals of Cornu aspersum were collected from all sampling sites. The study was carried out for the period November 2007 to November 2008 on three sites within the Jadiriya district in Baghdad.. Growth, size classes and shell dimensions of Cornu aspersum populations, and their relationship with major environmental factors; ambient temperature; soil pH, moisture, texture; and the soil content of organic matter have been also investigated. Identification of the species was confirmed by the British Natural History Museum.The data were analyzed by means of standard statistical procedures.
In this work, an efficient energy management (EEM) approach is proposed to merge IoT technology to enhance electric smart meters by working together to satisfy the best result of the electricity customer's consumption. This proposed system is called an integrated Internet of things for electrical smart meter (2IOT-ESM) architecture. The electric smart meter (ESM) is the first and most important technique used to measure the active power, current, and energy consumption for the house’s loads. At the same time, the effectiveness of this work includes equipping ESM with an additional storage capacity that ensures that the measurements are not lost in the event of a failure or sudden outage in WiFi network. Then then these measurement
... Show MoreThe dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of
... Show MoreThe aim of this investigation is to evaluate the experimental and numerical effectiveness of a new kind of composite column by using Glass Fiber‐Reinforced Polymer (GFRP) I‐section as well as steel I‐section in comparison to the typical reinforced concrete one. The experimental part included testing six composite columns categorized into two groups according to the slenderness ratio and tested under concentric axial load. Each group contains three specimens with the same dimensions and length, while different cross‐section configurations were used. Columns with reinforced concrete cross‐section (reference column), encased GFRP I‐section, and encased steel I‐section were adopted in each
Among the many modern skill-enhancing work practices, machine learning is among the mostskill-enhancing practices in the workplace, as it helps students remember more of what they havelearned, hone the technical talents and skills of football players, and make better use of theirmotor skills. The use of machine learning and its practical applications in football could havesignificant benefits by improving talent development and making better use of scientifictechniques. The primary objective of this study was to determine the effectiveness of machinelearning in improving soccer dribbling and passing accuracy in children aged 10-12 years. Thestudy authors hypothesized that soccer players in the Al-Zohour Neighborhood Youth Forumwould greatly
... Show MoreThis study investigated the bioethanol production from green algae Chlorella vulgaris depending on its carbohydrate-enriched biomass. Four different phosphorous concentrations were employed to stimulate bioethanol production from Chlorella vulgaris. The impact of various phosphorous values on Chlorella vulgaris growth rate as well as primary product (carbohydrate) were evaluated. High performance liquid chromatography was utilized in this work. The stationary phase was identified as day 14, 12, 10 and 6 in treatments 6, 4, 2 and g/L, respectively. The findings suggest that the treatment without phosphorous addition had the highest record of carbohydrate content (22.64% dry weight) as well as the highest bioethanol yield (20.66% dry weight).
... Show MoreIn this research various of 2,5-disubstituted 1,3,4-oxadiazole (Schiff base, oxo-thiazolidine , and other compounds) were synthesized from 2,5-di(4,4?- amino-1,3,4-oxadiazole ) which use quently synthesized from mixture of 4-amino benzoic acid and hydrazine in the presence of polyphosphorus acid. The synthesized compounds were characterized by using some Spectral data (UV, FT-IR, and 1H-NMR).