ABSTRACT

Background: primary school age obesity and overweight are increasing in developed countries like the Sudan. Primary school age underweight has been shown to rise a child’s risk of fast weight gain and so obesity, because of life style. Studies concerning obesity among Damazin children are rare. The aim of our study was to assess body mass index of primary school age   in Damazin town, Blue Nile region, Sudan. Method: A cross sectional study was conducted in Damazin town in 2025. A total of 140 primary school age students (100 (50 male & 50 female) case and 40(20male & 20 female) control). Any questionnaire was filled out by the leader of the student family.
Anthropometric indexes were measured and categorized according to the Center for Disease Control and prevention (CDC) – Sudan. Findings: Our findings indicate the deployments of underweight, overweight and obesity among the infants were approximately 32%, 12%, 6% respectively. Conclusion: The last findings of our study show the increase in the deployments of underweight compared to overweight and obesity among Damazin primary school age students.

Keywords: Primary School Age Children, Obesity, Overweight, Underweight, BMI.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 

ABSTRACT

The study aimed to examine the impact of accounting intelligence on financial technology: an analytical investigation in the Jordanian business environment. To achieve the study objectives, a descriptive-analytical approach was employed, whereby a questionnaire was designed and distributed to the study sample, which was selected using a convenience sampling method. The sample included Jordanian financial and banking service providers (commercial and Islamic banks, electronic payment companies, and microfinance institutions). The results of the multiple regression analysis revealed that the five dimensions of accounting intelligence (analytical, technological, cognitive, strategic, and competitive intelligence) have a significant effect on financial technology, explaining 78.6% of the variance. The adjusted coefficient of determination (Adjusted R² = 0.780) indicated that approximately 78% of the changes in the dependent variable can be explained by the studied dimensions, while 22% remain attributed to other factors beyond the scope of this research. The significance tests confirmed that the effects of all independent variables were statistically significant at the 0.05 level, and some at the 0.01 level, reflecting a strong relationship between the dimensions of accounting intelligence and financial technology. Moreover, the Durbin-Watson test results fell within the acceptable range (1.5–2.5), ruling out any serious autocorrelation problems in the residuals and affirming the reliability of the model. These findings highlight that investing in the development of accounting intelligence dimensions effectively contributes to enhancing the adoption and performance of financial technology. They also emphasize the critical role of analytical, cognitive, technological, strategic, and competitive capabilities in improving financial technology outcomes.

Keywords: Accounting Intelligence, Analytical Intelligence, Technological Intelligence, Cognitive Intelligence, Strategic Intelligence, Competitive Intelligence, Financial Iechnology.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 

ABSTRACT

This study examines the effect of film thickness (250, 300, and 350 nm) on the structural, morphological, optical, and sensing properties of nanostructured NiO thin films prepared via the sol-gel method. XRD analysis confirmed the cubic phase of NiO (JCPDS 04-0835), with dominant peaks at (111), (200), and (220) planes. Increasing thickness improved crystallinity, as evidenced by a rise in grain size (from 19.58 to 23.61 nm) and a reduction in dislocation density (from 39.73 to 32.52 × 10¹⁴ lines/m²). Atomic force microscopy (AFM) revealed smoother surfaces for thicker films (average roughness decreased from 8.72 nm to 4.03 nm). Optical studies revealed a reduction in bandgap (3.49 to 3.38) eV and transmittance (from 78% to ~65%) with increasing thickness, attributed to enhanced light absorption and the formation of defect states. The gas-sensing performance against H₂ (300 ppm) demonstrated that thinner films (250 nm) exhibited higher sensitivity (35.6%) due to their larger surface-to-volume ratio, whereas thicker films (350 nm) showed increased resistance but reduced responsiveness.

Keywords:  NiO; Thin Films; Sol-Gel Method; Thickness Variation; Vtructural Properties; Optical Properties.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 

ABSTRACT

The adverse effects of chemical insecticides-based intervention measures for the control of mosquito vectors have received wide public apprehension because of several problems like insecticide resistance, resurgence of pest species, environmental pollution, toxic hazards to humans, and non-target organisms. These problems have necessitated the need to explore and develop alternative strategies using eco-friendly, environmentally safe, bio-degradable plant products which are non-toxic to non-target organisms too. Therefore, it was aimed by this study to evaluate some extracts(acetone, chloroform, ethanol, ethyl acetate and water) O. baislicum (Rehan)  under 6 concentrations (0.01,0.02,0.03,0.04,0.05 and0.1) as natural larvicides against 3rd instar larva of The different larval mortality were recorded after 24 hours. Tested plant extracts in their different concentrations have shown larvicidal effects on An. Arabiensis and C. quinquefasciatus larvae. The repellent action of the plant extracts tested varied depending on the plant species and solvent used in extraction and the extract dose. The ethanol extraction was more effective in exhibiting the repellent action against the An. Arabiensis and C. quinquefasciatus larvae as compared with acetone, chloroform , ethyl acetate and water extraction. followed by ethyl acetate , acetone, chloroform and water extraction respectively. Statistical analysis showed  significant differences between  concentration of  plant  extract and control

Keywords: Non-commuting graph, Metacyclic group, Conjugacy class, Centralizer, Hamiltonian graph, Capable Group.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 

ABSTRACT

This project studied the properties of non - Newtonian fluids. According to that, ten samples were prepared. These samples have a constant volume of water which was 350 cc, with different concentrations of weighting material which was a bentonite. According to that the concentrations of Bentonite will became (10, 14, 18, 22, 26, 30, 35, 37, 40, 44) gm A Bingham plastic model was used to study the flow behavior of these non - Newtonian samples. It was noticed that the shear stress increases with the increasing of Bentonite concentration for each shear rate, and also the shear stress - shear rate Relationship is coincide with Bingham -plastic model. The result show that the increasing of the bentonite concentration will increase the plastic ⁸viscosity & yield point of these samples, also increasing the concentration of a weighting material will increase the specific gravity of the prepared samples.

Keywords: Non-Newtonian Fluids, Flow Model, Bingham Plastic Fluid.  

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 

ABSTRACT

This study examines the long-term spatiotemporal relationship between Land Surface Temperature (LST) and vegetation dynamics in Al-Kut City, Iraq, over the period 2000–2024, using an integrated framework that combines remote sensing, cloud computing, and deep learning techniques. Land surface temperature was derived from the MODIS MOD11A2 product at a spatial resolution of 1 km, while vegetation conditions were represented by the Normalized Difference Vegetation Index (NDVI) extracted from Landsat-7 ETM+ imagery at a 30 m spatial resolution. All datasets were processed within the Google Earth Engine (GEE) platform to ensure temporal consistency and efficient handling of long-term satellite archives, whereas statistical analyses were implemented using Python in the Google Colab environment. The results reveal pronounced spatial and temporal variability in surface thermal patterns, with persistently elevated temperatures observed over urbanized and barren areas, compared with relatively lower temperatures in agricultural lands and zones adjacent to the Tigris River. A statistically significant inverse relationship between NDVI and LST was consistently observed throughout the study period. The strength of this relationship increased over time, as indicated by the coefficient of determination (R²), which rose from approximately 0.55 in the early years to nearly 0.75 in recent periods, highlighting the growing role of vegetation in moderating surface thermal conditions. Furthermore, LSTM-based forecasting suggests that localized vegetation gains may not fully offset the broader surface warming trend toward 2030. Overall, the proposed framework provides a robust and transferable approach for urban thermal assessment and supports climate-adaptive planning in semi-arid environments.

Keywords: Land Surface Temperature, NDVI, MODIS, Landsat, Google Earth Engine, Remote Sensing, Urban Heat Island, Vegetation Dynamics.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).