This study unveils the ideologies of women empowerment encoded in the Mona Lisa Smile movie (2003). It reveals how the stereotypical image of women born only to be wives and do the duties of upbringing and housework is challenged. Katherine Ann Watson (Julia Roberts), the main character in the movie, wants to make a difference in the next generation of women. She rejects the imposed traditional ideologies. Linguistically, she opposes conventional thinking and seeks to persuade her students that life is about more than getting married. The primary focus of this study is to examine and clarify how the characters’ linguistic choices convey their ideologies concerning the notion of women empowerment. To do this, the researchers apply Jeffries`s (2010) critical stylistics, using of five stylistic tools: Negation, Hypothesizing, Equating and Contrasting, Exemplifying and Enumerating, and lastly, Representing Actions/Events/States. The data for this study consists of four extracts taken from the movie Mona Lisa Smile (2003). The analysis shows that the critical stylistic tools account for a significant portion of the meaning of the text under consideration and contributes to the linguistic formulation of the notion of women empowerment, especially Negation and Hypothesizing processes, which score the highest frequencies while Exemplifying and Enumerating score the lowest.
An experiment was conducted in pots under field conditions during fall seasons of 2017 and 2018. This study aimed to improve a weak growth of seedlings under salt stress in sorghum. Three factors were studied. 1st factor was three cultivars (Inqath, Rabeh, and Buhoth70). 2nd factor was seed priming (primed and unprimed seed). Seed were primed by soaking for 12 hours in a solution containing 300 + 70 mg L−1 of gibberellic (GA3) and salicylic (SA) acids, respectively. 3rd factor was irrigation with saline water (6, 9 and 12 dS m−1) resulting from dissolving sodium chloride in distilled water in addition to control treatment (distilled water). Randomized complete block design was used with four replications. In both seasons: the results sh
... Show MoreA total of 150 deep eutectic solvents (DESs) with varying salt, hydrogen bond donor, and molar ratios were studied to develop a screening tool for separating toluene-heptane mixtures. The activity coefficient at infinite dilution (γ∞) of each DES was predicted using COSMO-RS, and selectivity (S∞), capacity (C∞), and performance index (PI) were calculated. Key DES properties, including density, viscosity, melting/freezing point, surface tension, and conductivity, were compiled from the literature to create a DES property library. A comprehensive screening tool with four evaluation criteria was developed, which identified ethyl triphenylphosphonium bromide:ZnCl2 (1:4) as the optimal solvent for toluene-heptane separation. Tetrabutyl- b
... Show MoreWe aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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