The applications of hot plasma are many and numerous applications require high values of the temperature of the electrons within the plasma region. Improving electron temperature values is one of the important processes for using this specification in plasma for being adopted in several modern applications such as nuclear fusion, plating operations and in industrial applications. In this work, theoretical computations were performed to enhance electron temperature under dense homogeneous plasma. The effect of   power and duration time of pulsed Nd:YAG laser   was studied on the heating of   plasmas  by inverse bremsstrahlung  for  several values for the electron density ratio. There results for these ca

This study aimed to extract, purify, and characterize the protease of local Okra Abelmoschus esculentus pods. The extraction process was conducted using ten extraction solutions with different pH and ionic strength values. Phosphate buffer solution with (pH 7, 0.05M, containing 2% sodium chloride) gave the highest activity which was (7.2 Unit/ml) as compared to other solutions, which ranged from 0.8-5.9 Unit/ml. The extracted enzyme purified by several stages. Being, precipitation by gradual addition of Ammonium sulphate from 20 to 85% saturation, then the precipitated enzyme was dialyzed and fractionated through DEAE-Cellulose (22X1.1cm), the enzymic fractions were pooled. The specific activity, purification fold and the enzyme yield value

In the present paper, a simply* compact spaces was introduced it defined over simply*- open set previous knowledge and we study the relation between the simply* separation axioms and the compactness, in addition to introduce a new types of functions known as 𝛼𝑆 𝑀∗ _irresolte , 𝛼𝑆 𝑀∗ __𝑐𝑜𝑛𝑡𝑖𝑛𝑢𝑜𝑢𝑠 and 𝑅 𝑆 𝑀∗ _ continuous, which are defined between two topological spaces.

This study was aimed to determine a phytotoxicity experiment with kerosene as a model of a total petroleum hydrocarbon (TPHs) as Kerosene pollutant at different concentrations (1% and 6%) with aeration rate (0 and 1 L/min) and retention time (7, 14, 21, 28 and 42 days), was carried out in a subsurface flow system (SSF) on the Barley wetland. It was noted that greatest elimination 95.7% recorded at 1% kerosene levels and aeration rate 1L / min after a period of 42 days of exposure; whereas it was 47% in the control test without plants. Furthermore, the percent of elimination efficiencies of hydrocarbons from the soil was ranged between 34.155%-95.7% for all TPHs (Kerosene) concentrations at aeration rate (0 and 1 L/min). The Barley c

This study investigated the bioethanol production from green algae Chlorella vulgaris depending on its carbohydrate-enriched biomass. Four different phosphorous concentrations were employed to stimulate bioethanol production from Chlorella vulgaris. The impact of various phosphorous values on Chlorella vulgaris growth rate as well as primary product (carbohydrate) were evaluated. High performance liquid chromatography was utilized in this work. The stationary phase was identified as day 14, 12, 10 and 6 in treatments 6, 4, 2 and g/L, respectively. The findings suggest that the treatment without phosphorous addition had the highest record of carbohydrate content (22.64% dry weight) as well as the highest bioethanol yield (20.66% dry weight).

This study aims to enhance the RC5 algorithm to improve encryption and decryption speeds in devices with limited power and memory resources. These resource-constrained applications, which range in size from wearables and smart cards to microscopic sensors, frequently function in settings where traditional cryptographic techniques because of their high computational overhead and memory requirements are impracticable. The Enhanced RC5 (ERC5) algorithm integrates the PKCS#7 padding method to effectively adapt to various data sizes. Empirical investigation reveals significant improvements in encryption speed with ERC5, ranging from 50.90% to 64.18% for audio files and 46.97% to 56.84% for image files, depending on file size. A substanti

The aim of present work is to study the removal of phenol present in aqueous feed solution by the emulsion liquid membrane technique using kerosene as a diluent, sodium hydroxide as a stripping agent, and sorbitan monooleate (Span 80) as a surfactant. The parameters studied were: surfactant concentration, volume ratio of membrane phase to internal phase, and stirring speed. It was found that more than 98% of phenol can be removed at the conditions were surfactant concentration 2% (v/v), volume ratio of membrane phase to internal phase 5:1 and stirring speed 400 rpm. Maximum phenol extraction efficiency at 7 minutes of process time was observed. It was found that there was a good agreement between the standard kerosene an

   Theobromine, theophylline, and caffeine retention times in a C18 HPLC column (stationary phase) were investigated as a function of mobile phase flow rate, mobile phase composition, and column temperature. When the mobile phase flow rate increased from 0.1 to 1 mL/min and the methanol concentration increased from 5 to 30%, the retention time and peak width of these three compounds were found to be reduced. While there was a small influence of increasing the mobile phase flow rate on the resolution, decreasing the methanol concentration in the mobile phase considerably reduced the resolution. In addition, the mobile phase flow rate and composition were determined to have a more significant impact than the column temperature. Acco

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be