The study aimed to identify the treatment of the press image of the Great Return Marches in the French international news agency AFP by knowing the most important issues, their direction and the degree of interest in them. The study belongs to the descriptive research, and used the survey method, within the context of the content analysis method, and the researcher relied on the content analysis form tool and the interview tool to collect data. The study population is represented in the photos published by the French News Agency about the Great Return Marches during the period (end of March / 2018 until the end of November / 2019. The researcher chose an intentional sample using the Complete Census method. The study material represented all the photos related to the Great Return Marches. The researcher relied on the agenda theory of "priority order''. Among the most important results: The study showed photos of the political issues of the Great Return Marches by (81.7%); The sources of the press photo came from the agency’s photographers themselves (96.7%); The negative trend of the press image Great Return March came (91.2%); Among its most important recommendations: The French agency AFP should pay attention to the press pictures with a positive trend; increasing interest towards the different types of press photos according to its content and focusing on the personal image.
Promoting the production of industrially important aromatic chloroamines over transition-metal nitrides catalysts has emerged as a prominent theme in catalysis. This contribution provides an insight into the reduction mechanism of p-chloronitrobenzene (p-CNB) to p-chloroaniline (p-CAN) over the γ-Mo2N(111) surface by means of density functional theory calculations. The adsorption energies of various molecularly adsorbed modes of p-CNB were computed. Our findings display that, p-CNB prefers to be adsorbed over two distinct adsorption sites, namely, Mo-hollow face-centered cubic (fcc) and N-hollow hexagonal close-packed (hcp) sites with adsorption energies of −32.1 and −38.5 kcal/mol, respectively. We establish that the activation of nit
... Show MoreThis study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (
This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed
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Ground Penetrating Radar (GPR) is a nondestructive geophysical technique that uses electromagnetic waves to evaluate subsurface information. A GPR unit emits a short pulse of electromagnetic energy and is able to determine the presence or absence of a target by examining the reflected energy from that pulse. GPR is geophysical approach that use band of the radio spectrum. In this research the function of GPR has been summarized as survey different buried objects such as (Iron, Plastic(PVC), Aluminum) in specified depth about (0.5m) using antenna of 250 MHZ, the response of the each object can be recognized as its shapes, this recognition have been performed using image processi |
فدهي قوس يف ةيداصتقلاا تادحولا ضعب يف نيرمثتسملا تارارق ىلع ءارضخلا ةبساحملا ريثأت ةسارد ىلا ثحبلا نم يلمعلا بناجلا تانايب عمج ىلع دامتعلااب ناثحابلا ماق ثحبلا فده قيقحتلو ، ةيلاملا قارولأل قارعلا نايبتسا ميمصت للاخ ىلا اهميدقتو يف ) نيرمثتسملاو , نييلخادلا نيققدملاو , نيبساحملاو , نييلاملا ءاردملا( ثحبلا ةنيع يف ةلجسملا تاكرشلا ضعب ةيلاملا قارولأل قارعلا قوس متو ثحبلا ناونعب قلعتت يتلا جئاتنلا جارخت
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