The Mediation Role of Resource Accessibility between Perceived Social Support and e-Entrepreneurial Intention of Female Students in Saudi Arabia

Entrepreneurship has become highly popular among younger people due to the booming of cyber platforms, specifically in online businesses. However, the motivation behind students’ aspirations to start online businesses is yet to be rarely examined within the extant literature. Consequently, the current study seeks to explore the mediating role of resource accessibility on the relationship between perceived social support and e-entrepreneurial intention among female students in Saudi Arabia. The study involved distribution of 376 online questionnaires among undergraduate female students studying business related subjects in public and private universities in Saudi Arabia. The study findings suggest that perceived social support has a positive influence on e-entrepreneurial intention and resource accessibility among the students. Moreover, there is an indication from the findings that resource accessibility plays a significant mediating role between perceived social support and e-entrepreneurial intention. The study findings contribute to the extant literature of e-entrepreneurship, demonstrating the significance of supporting students to start their own online businesses by providing them full access to the available resources. Keywords: Management, e-Entrepreneurship, Social Support, Resource Accessibility, Female Intentio

PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network

           يعتمد الاقتصاد بشكل استثنائي على الإنتاجية الزراعية. لذلك ، في مجال الزراعة ، يعد اكتشاف عدوى النبات مهمة حيوية لأنه يعطي تقدماً واعداً نحو تطوير الزراعة. في هذا العمل، تم اقتراح نظام لتصنيف أمراض البطاطا بالاعتماد على الشبكة العصبية. يهدف النظام إلى كشف وتصنيف أربعة أنواع من أمراض درنات البطاطا وهي: النقطة السوداء ، الجرب الشائع، فيروس البطاطا Y واللفحة المبكرة بالاعتماد على صورهم. يتكون النظام من ثلاثة مستويات: مستوى المعالجة المسبقة هو المستوى الاول، والذي يعتمد على K-means clustering  لاكتشاف المنطقة المصابة من صورة البطاطا، المستوى الثاني هو مستوى استخراج الميزات والذي يستخرج الميزات من المنطقة المصابة بالاعتماد على طريقتين:  grey level run  length matrix  و  first order histogram based features. الميزات المستخرجة من المستوى الثاني تستخدم في المستوى الثالث في تغذية الشبكة العصبية الأمامية لإجراء عملية التصنيف . 120 صورة ملونة استخدمت, 80 صورة استخدمت في تدريب الشبكة و40 صورة استخدمت في عملية الاختبار . النظام المقترح فعال للغاية في تصنيف أربعة أنواع من أمراض درنات البطاطا وكانت نسبة التمييز 91,3 %  .         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The second level is features extraction which extracts features from the infected area based on hybrid features: grey level run length matrix and 1st order histogram based features. The attributes that extracted from second level are utilized in third level using FFNN to perform the classification process. The proposed framework is applied to database with different backgrounds, totally 120 color potato images, (80) samples used in training the network and the rest samples (40) used for testing. The proposed PDCNN framework is very effective in classifying four types of potato tubers diseases with 91.3% of efficiency

Route Discovery Development for Multiple Destination Using Artificial Ant Colony

Smart cities need a smart applications for the citizen, not just digital devices. Smart applications will provide a decision-making to users by using artificial intelligence. Many real-world services for online shopping and delivery systems were used and attracted customers, especially after the Covid-19 pandemics when people prefer to keep social distance and minimize social places visiting. These services need to discover the shortest path for the delivery driver to visit multiple destinations and serve the customers. The aim of this research is to develop the route discovery for multiple-destination by using ACO Algorithm for Multiple destination route planning. ACO Algorithm for Multiple destination route planning develops the Google MAP application to optimize the route when it is used for multiple destinations and when the route is updated with a new destination. The results show improvement in the multiple destination route discovery when the shortest path and the sequence order of cities are found. In conclusion, the ACO Algorithm for Multiple destination route planning simulation results could be used with the Google Map application and provide an artificial decision for the citizen of Erbil city.  Finally, we discuss our vision for future development

Seasonal dynamics of heavy metal uptake in some aquatic plants of the Tigris River

This work aimed to study the accumulation of heavy metals Cadmium, Lead, Chromium, and Nickel in different aquatic plants along the Tigris River. The research focused on the seasonal variations in heavy metal uptake by Phragmites australis, Typha domingensis, Persicaria salicifolia, Azolla filiculoides, and Ceratophyllum demersum. Samples were collected from three distinct locations along the river, each characterized by varied environmental conditions. Using Atomic Absorption Spectrophotometry, the quantified metal concentrations were measured, revealing significant differences across seasons and locations. The study provides crucial insights into the dynamics of heavy metal accumulation in riverine ecosystems, underscoring the role of environmental factors and plant species in metal uptake

Effect of Some Medicinal Plants as Feed Additives on Growth Performance, Blood Constituents and Carcass Characteristics of Broilers

The present work aimed to study the effect of feeding broiler chicks on diets containing different levels of fenugreek, anise and curcuma seeds powder, as natural feed additive on productive performance, carcass characteristics, some blood constituents and economic feed efficiency. One hundred and forty, one-day old (Ross 38) unsexed broiler chicks were obtained from local commercial source, weighed and randomly distributed to 7 equal groups, each of 20. The birds were fed with two basal diets (starter and finisher diets). The experimental diets were as follows: basal control diet without any feed additives (G1), basal diets supplemented with 0.2 and 0.5% fenugreek (G2 and G3 respectively), basal diets supplemented with 0.3 and 0.6% anise seeds (G4 and G5 respectively), and lastly basal diets supplemented with 0.3 and 0.5% curcuma (G6 and G7 respectively). During the experiment the body weight and feed intake were measured and consequently, weight gain and feed conversion ratio were calculated. At the end of the experiment, three birds from each group were slaughtered for blood sampling and serum extraction then. Finally, economical evaluation of the diets was calculated. The results showed that, dietary inclusion of fenugreek, anise and curcuma, had significant (P <0.05) improvement in the live body weight, total weight gain and feed conversion ratio, While, the feed intake was not affected by the dietary inclusion of them. Some blood constituents were affected with these additions. The relative economic feed efficiency was increased by dietary inclusion of the three additives

Embedded disposable functionalized electrochemical biosensor with a 3D-printed flow cell for detection of hepatic oval cells (HOCs)

Hepatic oval cells (HOCs) are considered the progeny of the intrahepatic stem cells that are found in a small population in the liver after hepatocyte proliferation is inhibited. Due to their small number, isolation and capture of these cells constitute a challenging task for immunosensor technology. This work describes the development of a 3D-printed continuous flow system and exploits disposable screen-printed electrodes for the rapid detection of HOCs that over-express the OV6 marker on their membrane. Multiwall carbon nanotube (MWCNT) electrodes have a chitosan film that serves as a scaffold for the immobilization of oval cell marker antibodies (anti-OV6-Ab), which enhance the sensitivity of the biomarker and makes the designed sensor specific for oval cells. The developed sensor can be easily embedded into the 3D-printed flow cell to allow cells to be exposed continuously to the functionalized surface. The continuous flow is intended to increase capture of most of the target cells in the specimen. Contact angle measurements were performed to characterize the nature and quality of the modified sensor surface, and electrochemical measurements (cyclic voltammetry (CV) and square wave voltammetry (SWV)) were performed to confirm the efficiency and selectivity of the fabricated sensor to detect HOCs. The proposed method is valuable for capturing rare cells and could provide an effective tool for cancer diagnosis and detection

Location-aware deep learning-based framework for optimizing cloud consumer quality of service-based service composition

The expanding propensity of organization users to utilize cloud services urges to deliver services in a service pool with a variety of functional and non-functional attributes from online service providers. brokers of cloud services must intense rivalry competing with one another to provide quality of service (QoS) enhancements. Such rivalry prompts a troublesome and muddled providing composite services on the cloud using a simple service selection and composition approach. Therefore, cloud composition is considered a non-deterministic polynomial (NP-hard) and economically motivated problem. Hence, developing a reliable economic model for composition is of tremendous interest and to have importance for the cloud consumer. This paper provides “A location-aware deep learning framework for improving the QoS-based service composition for cloud consumers”. The proposed framework is firstly reducing the dimensions of data. Secondly, it applies a combination of the deep learning long short-term memory network and particle swarm optimization algorithm additionally to considering the location parameter to correctly forecast the QoS provisioned values. Finally, it composes the ideal services need to reduce the customer cost function. The suggested framework's performance has been demonstrated using a real dataset, proving that it superior the current models in terms of prediction and composition accuracy

Neuroprotective effects of thymoquinone against cerebellar histopathological changes in propylthiouracilinduced hypothyroidism in adult rats

Purpose: To evaluate the effects of thymoquinone (TQ) on histological and immunohistochemical changes in the cerebellar cortex induced by propylthiouracil (PTU) treatment in rats.Methods: Thirty-two adult male albino rats were randomly divided into four groups: C, control; PTU, treatment with oral PTU to induce hypothyroidism; TQ, treatment with TQ; and PTU + TQ, concomitant treatment with oral PTU and TQ for 6 weeks. Cavalieri’s principle and physical dissector methods were employed for unbiased deduction of cerebellar granular layer volume, numerical density, and number of granular cells.Results: In the PTU group, hematoxylin and eosin (H&E)-stained sections revealed degeneration of Purkinje cells, neuronal loss, and spongiosis in the white matter. A decrease in the number of astrocytes-expressing glial fibrillary acidic protein (GFAP) and a significant decrease in granular layer cell density were also seen. Concomitant administration of TQ ameliorated histopathological changes, increased the proportion of GFAP-positive astrocytes, increased granular cell density, and significantly (p < 0.05) increased the levels of thyroid-stimulating hormones, T3 and T4.Conclusion: TQ treatment significantly decreases cerebellar changes resulting from PTU-induced hypothyroidism, and results in the retention of neuronal structural integrity in the cerebellar cortex.Keywords: Hypothyroidism, Cerebellum, Thymoquinone, Stereology, Glial fibrillary acidic protein, Neuronal structural integrit

Enhancing the mental image of the institution through modern packaging technics as a branch of the institutional identity

Visual identity has an important role regarding trade, industry and advertising nowadays, this is to be able to differentiate every service or product from its similar all over the world, in the era of information technology, international trade and widely spread advertising and because of the wide variety of brand names it became a necessity to have a clear visual identity which helps it have a clear mark in its customers minds in addition to expected customers too, so designers rely on building a specific visual identity through analyzing and creating a specific concept because building that specific concept can relate to a visual identity that can be part of special visual identity for a certain product or service, so it is crucial to know how to enhance the visual identity of an institution through modern technics of packaging being considered as one of the identity specifications of the institution, and because the number of researches handling this matter is scarce, this research aims at enhancing the mental image of the institution through modern packaging technics as one of the branches of the institution identity and to achieve this we elaborate (the concept of the mental image, its formed kinds towards institutions, what it consists of, its forming tools, steps of building it and the requirements for a successful formation of it) visual identity and its analysis through some models that can enhance the mental image of any institution (brand life cycle - AIDA model - Maslow's hierarchy of human needs - SWOT Analysis), Casting light over modern packaging technics as a branch of institutional identity after then we reach the complementary relation between these models and being able to use them in a way that enhances the mental image of the institution through database and analysis resulting from these models and advertising analysis in addition to using the complementary relation between them to keep clients loyal to the institution