The following dilution 5×10-1, 10-1, 10?2 , 10-3 gm/L for the indigenous isolate of Bacillus thuringiensis bacteria and the commercially isalate were used for experiments against the different stages of fig moth of E.cautella which exposed by filter paper method. The results showed that mortality of larval stages was increased with the increasing concentration of the biocide, in addition to increase in the mortality of the larval stages reached to the highest percentage in the third days of treatment of the larval stage in comparison with the first and second days of exposure. The results also showed that the sensitivity of larval stages was increased in first and second instars while reduced in the last instars .The high percentage

The present study evaluated the anti- Helicobacter pylori IgG, IgA and the role of virulence factor of H. pylori Vacuolating associated cytotoxin gene (Vac A) as a risk factors for CAD. The levels of serum IgG and IgA was done by indirect immunofluorescent (IIF) whereas Vac A measured by enzyme linked immunosorbent assay (ELISA). Ibn Al-Bitar specialist center for cardiac surgery laboratory and Ministry of Health/ Baghdad/ Iraq, between May and October 2018. Seventy Iraqi patients with CAD were enrolled in this study, their ages ranged between 40-84 years ; and 20 individuals as a control group which was divided into 2 subgroups: 10 apparently healthy volunteers (negative control) and the other subgroup contained 10 with normal coronary art

This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod

Morus alba, member of the Moraceae family, is a perennial tree utilized in folk medicine, preparing the modern drug, and considered the main food for silkworms. However, data on chemical content in the leaves is still limited; the main objective of this study is to detect the presence and determine the concentration of different polyphenolic constituents in the leaves of the Morus alba plant by reverse phase-high performance liquid chromatography (RP-HPLC) and evaluate the cytotoxic effect of ethyl acetate extract of this plant on human breast cancer (AMJ-13) cell line. Phytochemical analysis of the Morus alba leaves ethyl acetate extract led to identifying and quantification of six polyphenolic constituents designated as phenolic a

To accommodate utilities in buildings, different sizes of openings are provided in the web of reinforced concrete deep beams, which cause reductions in the beam strength and stiffness. This paper aims to investigate experimentally and numerically the effectiveness of using carbon fiber reinforced polymer (CFRP) strips, as a strengthening technique, to externally strengthen reinforced concrete continuous deep beams (RCCDBs) with large openings. The experimental work included testing three RCCDBs under five-point bending. A reference specimen was prepared without openings to explore the reductions in strength and stiffness after providing large openings. Openings were created symmetrically at the center of spans of the other specimens

In this paper, fire resistance and residual capacity tests were carried out on encased pultruded glass fiber-reinforced polymer (GFRP) I-beams with high-strength concrete beams. The specimens were loaded concurrently under 25% of the ultimate load and fire exposure (an increase in temperature of 700 °C) for 70 min. Subsequently, the fire-damaged specimens were allowed to cool and then were loaded statically until failure to explore the residual behaviors. The effects of using shear connectors and web stiffeners on the residual behavior were investigated. Finite Element (FE) analysis was developed to simulate the encased pultruded GFRP I-beams under the effect of fire loading. The thermal analyses were performed using the general-pu

D-mannose sugar was used to prepare [benzoic acid 6-formyl-2,2-dimethyl-tetrahydrofuro[3,4-d][1,3]dioxol-4-yl ester] (compound A). The condensation reaction of folic acid with (compound A) resulted in the formation of new ligand [L]. These compounds were characterized by elemental analysis CHN, atomic absorption A.A, (FT-I.R.), (U.V.-Vis), TLC, E.S. mass (for electrospray), molar conductance, and melting point. The new tetradentate ligand [L], reacted with two moles of some selected metal ions and two moles of (2-aminophenol), (metal : ligand : 2-aminophenol) at reflux in water medium to give a series of new complexes of the general formula K2[M2(L)(HA)2] where M= Co(II), Ni(II), Cu(II) and Cd(II). These complexes were characterized by elem

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol