The implicit is the narrative technique used to give indirect hidden messages. To read between the lines means to understand the implicit meaning that is not directly indicated. This technique is expressed in two forms: the hypothesis and the implications of linguistic and non-linguistic rules. Nathalie Sarraute’s "Pour un oui ou pour un non" states this narrative method through her character’s verbal and non-verbal dialogue. The present paper discusses the implicit method and shows the reason behind which  the author uses it in her play "Pour un oui ou pour un non".

Résumé

This study is concerned with the effect of Deep Cryogenic Treatment (DCT) at liquid nitrogen temperature (-196 o C) on the mechanical properties and performance of low carbon steel (A858). The tests specimens were divided in to two groups, the first group was subjected to the conventional heat treatment of normalizing, and the second group was also normalized then subjected to (DCT). The results have shown that after (DCT), the Hardness, Tensile properties and the impact energy absorbed were all slightly increased. However the fatigue test showed some positive improvement in fatigue limit by 20(N/mm2 ), and the volume wear rates at different loads were significantly decreased after (DCT). The changes in microstructure due to (DCT) were c

CuInSe2 (CIS)thin films have been prepared by use vacuum thermal evaporation technique, of 750 nm thickness, with rate of deposition 1.8±0.1 nm/sec on glass substrate at room temperature and pressure (10-5) mbar. Heat treatment has been carried out in the range (400-600) K for all samples. The optical properties of the CIS thin films are been studied such as (absorption coefficient, refractive index, extinction coefficient, real and imaginary dielectric constant)by determined using Measurement absorption and transmission spectra. Results showed that through the optical constants we can made to control it is wide applications as an optoelectronic devices and photovoltaic applications.

CuInSe2(CIS) thin films have been prepared by use vacuum thermal evaporation technique, of thickness750 nm with rate of deposition 1.8±0.1 nm/sec on glass substrate at room temperature and pressure (10-5) mbar. Heat treatment has been carried out in the range (400-600) K for all samples. The optical properties of the CIS thin films are been studied such as (absorption coefficient, refractive index, extinction coefficient, real and imaginary dielectric constant) by determined using Measurement absorption and transmission spectra. Results showed that through the optical constants we can make to control it are wide applications as an optoelectronic devices and photovoltaic applications.

In this work, the copper metal was treated using Nd:YAG laser with energy 1Joul to enhance corrosion resistance and improve surface properties. The copper metal has many applications in industry as well as water, oil and gas pipes. The same conditions, (laser power density, scan speed, distance between paths, medium gas-air) were applied in the laser surface treatment, After laser treatment, the samples microstructures were investigated using optical microscope (OM) to examine micro structural changes due to laser irradiation. Specimen surfaces were investigated using atomic force microscopy (AFM), X-ray diffraction (XRD), macro hardness, and corrosion test before and after laser treatment to

This study illustrates the impact of non-thermal plasma (Cold Atmospheric Plasma CAP) on the lipids blood, the study in vivo. The lipids are (cholesterol, HDL-Cholesterol, LDL-Cholesterol and triglyceride) are tested. (FE-DBD) scheme of probe diameter 4cm is used for this purpose, and the output voltage ranged from (0-20) kV with variable frequency (0-30) kHz. The effect of non-thermal atmospheric plasma on lipids were studied with different exposure durations (20,30) sec. As a result, the longer plasma exposure duration decreases more lipids in blood.

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and