How mobile phone application enhance human interaction with e-retailers in the middle east

The paper aims to provide a critical in-depth analysis of Mobile Phone Application's role in enhancing human interaction with E-Retailers, and more specifically, in the Middle East. First, the paper provides an outlook description of the definition and history of Mobile Phone Applications and human interaction and how the two complement each other. Next, the study outlines the various instances that human interaction with Mobile Phone Applications has led to E-retailer success and how it has come about. Then, the discourse provides an analytical look at the E-retailing Business in the Middle East while focusing on the history of E-retailing, business startups in the Middle East, and the revolution of E-retailing in the Middle East. Additionally, the research emphasizes the merits and demerits of using Mobile Phone Applications to promote and enhance E-commerce business in Middle East countries. Using relevant sources and credible references, the analysis will highlight the numerous instances Mobile Phone applications have been used by clients to connect with businesses that maintain an online presence. Using anthological, historical, and descriptive research methods, the arguments portrayed in this paper will heavily reflect on various case studies provided in the article. The case studies feature data representation from research conducted in the Middle East concerning Mobile Phone applications and E-commerce. Through focused approaches, this paper discerns, comprehend, and establishes the framework of the Middle East E-Commerce scene over the years, and outlines how far the industry has made progress through online platforms. Furthermore, emphasis will be laid on the market gaps left to fill in the E-commerce sector in the Middle East and the several approaches to better the industry. Lastly, this paper will conclude by providing my recommendations on the betterment of Mobile Phone Applications and how E-retailing can improve in the Middle East

Resilience of modern power distribution networks with active coordination of EVs and smart restoration

Abstract In this modern era of cyber–physical–social systems, there is a need of dynamic coordination strategies for electric vehicles (EVs) to enhance the resilience of modern power distribution networks (MPDNs). This paper proposes a two‐stage EV coordination framework for MPDN smart restoration. The first stage is to introduce a novel proactive EV prepositioning model to optimize planning prior to a rare event, and thereby enhance the MPDN survivability in its immediate aftermath. The second stage involves creating an advanced spatial–temporal EV dispatch model to maximize the number of available EVs for discharging, thereby improving the MPDN recovery after a rare event. The proposed framework also includes an information system to further enhance MPDN resilience by effectively organizing data exchange among intelligent transportation system and smart charging system, and EV users. In addition, a novel bidirectional geographic graph is proposed to optimize travel plans, covering a large penetration of EVs and considering variations in traffic conditions. The effectiveness is assessed on a modified IEEE 123‐node test feeder with real‐world transportation and charging infrastructure. The results demonstrate a significant improvement in MPDN resilience with smart restoration strategies. The validation and sensitivity analyses evidence a significant superiority of the proposed framework

Gender recognition from unconstrained selfie images: a convolutional neural network approach

Human gender recognition is an essential demographic tool. This is reflected in forensic science, surveillance systems and targeted marketing applications. This research was always driven using standard face images and hand-crafted features. Such way has achieved good results, however, the reliability of the facial images had a great effect on the robustness of extracted features, where any small change in the query facial image could change the results. Nevertheless, the performance of current techniques in unconstrained environments is still inefficient, especially when contrasted against recent breakthroughs in different computer vision research. This paper introduces a novel technique for human gender recognition from non-standard selfie images using deep learning approaches. Selfie photos are uncontrolled partial or full-frontal body images that are usually taken by people themselves in real-life environment. As far as we know this is the first paper of its kind to identify gender from selfie photos, using deep learning approach. The experimental results on the selfie dataset emphasizes the proposed technique effectiveness in recognizing gender from such images with 89% accuracy. The performance is further consolidated by testing on numerous benchmark datasets that are widely used in the field, namely: Adience, LFW, FERET, NIVE, Caltech WebFaces andCAS-PEAL-R1

A genetic algorithm for shortest path with real constraints in computer networks

The shortest path problem has many different versions. In this manuscript, we proposed a muti-constrained optimization method to find the shortest path in a computer network. In general, a genetic algorithm is one of the common heuristic algorithms. In this paper, we employed the genetic algorithm to find the solution of the shortest path multi-constrained problem. The proposed algorithm finds the best route for network packets with minimum total cost, delay, and hop count constrained with limited bandwidth. The new algorithm was implemented on four different capacity networks with random network parameters, the results showed that the shortest path under constraints can be found in a reasonable time. The experimental results showed that the algorithm always found the shortest path with minimal constraints

GEANT4 Simulation for Radioactive Particle Tracking (RPT) Technique

In the past two decades, the radioactive particle tracking (RPT) measurement technique has been proven to visualize flow fields of most multiphase flow systems of industrial interest. The accuracy of RPT, and hence the data obtained, depend largely on the calibration process, which stands here as a basis for two subsequent processes: tracking and reconstruction. However, limitations in the RPT calibration process can be found in different experimental constrains and in assumptions made in the classical Monte Carlo approach used to simulate number of counts received by the detectors. Therefore, in this work, we applied a GEANT4-based Monte Carlo code to simulate the RPT calibration process for an investigated multiphase flow system (i.e., gas–liquid bubble column). The GEANT4 code was performed to simulate the number of counts received by 28 scintillation detectors for 931 known tracer positions while capturing all the types of photon interaction and overcoming solids\u27 angle limitations in classical approaches. The results of the simulation were validated against experimental data obtained using an automated RPT calibration device. The results showed a good agreement between the simulated and experimental counts, where the maximum absolute average relative deviation detected was about 5%. The GEANT4 model typically predicted the number of counts received by all the detectors; however, it over-estimated the counts when the number of primary events applied in the model was not the optimal

Physicochemical characterization of natural hydroxyapatite/ cellulose composite

The natural hydroxyapatite (HAp, activated at different temperatures)/ cellulose composites have been prepared by usingsonication method to improve the physical properties of the cellulose fibre. The molecular level interaction and the physicalproperties of the hydroxyapatite/cellulose composite are examined using FTIR, X-ray diffraction, SEM, and thermalanalysis. The absorption bands at around 660 cm1 confirm the O–P–O bending vibration in the HAp/cellulose composites.There is a difference in the d-spacing of the HAp /cellulose composite, indicating that the HAp is reactive towards cellulose.SEM indicates that HAp could penetrate the cellulose network structure to form particles that is helpful to improve themechanical properties of the cellulose. The porosities of HAp/cellulose composites decrease, and their compressive strengthincrease as compared to those of cellulose. Thermogravimetric analysis confirms the highest thermal stability of theprepared composites

Neuroprotective effect of ranolazine improves behavioral discrepancies in a rat model of scopolamine-induced dementia

BackgroundRanolazine (Rn), an antianginal agent, acts in the central nervous system and has been used as a potential treatment agent for pain and epileptic disorders. Alzheimer’s disease (AD) is one of the most prevalent neurodegenerative diseases and the leading factor in dementia in the elderly.AimWe examined the impact of Rn on scopolamine (Sco)-induced dementia in rats.MethodsThirty-two albino male rats were divided into four groups: control, Rn, Sco, and Rn + Sco.ResultsA significant decrease in the escape latency in the Morris water maze test after pre-treatment with Rn explained better learning and memory in rats. Additionally, Rn significantly upregulated the activities of the antioxidant enzymes in the treated group compared to the Sco group but substantially reduced acetylcholinesterase activity levels in the hippocampus. Moreover, Rn dramatically reduced interleukin-1 β (IL-1β) and IL-6 and upregulated the gene expression of brain-derived neurotrophic factor (BDNF). Furthermore, in the Sco group, the hippocampal tissue’s immunohistochemical reaction of Tau and glial factor activating protein (GFAP) was significantly increased in addition to the upregulation of the Caspase-3 gene expression, which was markedly improved by pre-treatment with Rn. The majority of pyramidal neurons had large vesicular nuclei with prominent nucleoli and appeared to be more or less normal, reflecting the all-beneficial effects of Rn when the hippocampal tissue was examined under a microscope.ConclusionOur findings indicated that Rn, through its antioxidative, anti-inflammatory, and anti-apoptotic effects, as well as the control of the expression of GFAP, BDNF, and Tau proteins, has a novel neuroprotective impact against scopolamine-induced dementia in rats

CAUSES AND MANAGEMENT OF VIRAL EYE INFECTION

Introduction: The eye is a fascinating organ for several reasons. It is not only have a composite structure, however it is considered an immune-privileged organ. The anatomy of the eye is composed of the anterior and posterior parts, the line of division is posterior to the lens. The anterior chamber lies within the anterior segment and is an immuneprivileged anatomical location, this is due to the fact that the T-cell response in this area is suppressed This protects the eye from potentially destructive immune attacks however it also makes defence against infectious agents challenging, particularly where T-cell responses are critical for immunological defence. Viruses could get into the eye by direct inoculation, or through haematogenous or neuronal spread. The diagnoses of viral eye infections are usually clinical one, helped by taking a thorough history and performing ophthalmic examination. But in challenging cases the lab tests are essential. In this review, we will discuss the most recent evidence regarding Causes and management of viral eye infection Aim of work: In this review, we will discuss the most recent evidence regarding Causes and management of viral eye infection Methodology: We did a systematic search for Causes and management of viral eye infection using PubMed search engine (http://www.ncbi.nlm.nih.gov/) and Google Scholar search engine (https://scholar.google.com). All relevant studies were retrieved and discussed. We only included full articles. Conclusions: A wide range of of viruses can affect the eye and cause viral eye infections, either as a primary infection or reactivation. Some affect the eye directly while the others indirectly but may still manifest with eye disease. One virus may affect several parts of the eye, while different viruses may cause the same eye disease. This could complicate the clinical diagnosis of viral eye disease, but the lab tests like PCR and antibody tests could assist in challenging cases where there may be diagnostic dilemma. The HIV epidemic has had an huge impact on ophthalmology clinics, this is because the virus can cause different eye diseases, and the associated decrease in cell-mediated immunity makes the person highly susceptible to opportunistic viral eye infections, sometimes with severe morbidity. There could be other viruses that may affect the eye that we did not discuss. Key words: Causes, management, viral eye infection

Production of renewable diesel from Jatropha curcas oil via pyrolytic-deoxygenation over various multi-wall carbon nanotube-based catalysts

Jatropha curcas is a highly toxic plant that produces seed containing viscous oil with productivity (2 ton/ha), it grows in tropical and sub-tropical regions and offer greater adaptability to a wide range of climatic and soil conditions. Its oils have been noted as an important alternative to produce green diesel via deoxygenation reaction. This study, deoxygenation of jatropha curcas oil (JCO) was carried out over NiO–Fe2O3 and NiO–ZnO catalysts that supported onto multi-walled carbon nanotube (MWCNT). It had found that high Fe and Zn dosages were ineffective in deoxygenation and greatest activity was observed on NiO(20) Fe2O3(5)/MWCNT catalyst. Structure-activity correlations revealed that low metal loading, large density of weak + medium acidic sites and strong basic sites play key role in enhancing the catalytic activities and n-(C15+C17) selectivity. Comparing carbon nanostructures and carbon micron size supported NiO-Fe2O3 revealed that green diesel obtained from NiO–Fe2O3/MWCNT catalysed deoxygenation had the highest heating value and the lowest amounts of oxygen content. Thereby, it confirmed the importance of carbon nanostructure as the catalyst support in improving the diesel quality. Considering the high reusability of NiO-Fe2O3/MWCNT (6 consecutive runs) and superior green diesel properties (flash point, cloud properties and cetane index) demonstrated the NiO–Fe2O3/MWCNT catalyst offers great option in producing excellent properties of green diesel for energy sector