Université Djillali Liabes

Abstract In order to enhance the performance and feasibility of the large-scale process, the goal of this study was to evaluate the impact of important factors and optimize ozonation settings for the efficient degradation of salicylic acid, a challenging-to-remove industrial pollutant. The circulating solution was infused with ozone, which was created from pure oxygen in a dielectric barrier discharge reactor (DBD). The study examined the effects of oxygen flow rate (1 to 5 ), starting concentration (28 to 85 ), solution volume (3 to 10 L), and pH (1.5 to 13) on process efficiency. According to the results, 94% degradation is attained in 30 minutes at a maximum oxygen flow rate of 5 , but only 17% is attained at 1 . Efficiency stays close to 95% between 28 and 85 , and it only slightly declines as the initial concentration rises. Efficiency and volume are negatively correlated; for example, 3 L has a 99.5% elimination rate while 10 L has a 94% elimination rate. In contrast to an acid medium (pH 1.5), which yields a yield of 75.6%, an alkaline pH (pH 13) promotes optimal degradation (99.7%). Degradation is kinetically consistent with the pseudo-first-order model, with a rate constant k that depends linearly on the amount of salicylic acid and the rate of oxygen flow (k), ranging from 0.006 to 0.190 .

Abstract Numerous probability distributions are utilized to predict and model real-world phenomena across diverse applied domains, including reliability engineering, environmental studies, medical sciences, economics , actuarial science, finance, and insurance. However, the authors have developed no flexible probability distribution in the literature that accommodates every phenomenon because phenomena are complex. In the present study, we develop a new version of the inverse Rayleigh model using the new odd type-G family of distributions. The proposed model is very flexible and offers different behaviors in terms of its density and hazard functions. We study the mathematical properties of this new model such as moments, quantile function, moment generating function, skewness, kurtosis, and entropy measures. The unknown parameters of the proposed distribution are estimated using the well-known maximum likelihood estimation technique. A simulation experiment is evaluated to assess the effectiveness of the applied estimation method. Finally, the superiority and flexibility of the newly presented distribution are examined by analyzing two real data sets. The application of the proposed model is made with the other existing probability distributions, and based on certain evaluation criteria, we observe that the proposed distribution offers optimal fitting compared to other rival distributions.

Background: Herbalists sell extracts of Pistacia lentiscus, prepared by small businesses to treat certain dermatological and digestive problems, without side effects. Very little research has discussed the main compounds and biological activities of the leaves of this species. Aim: Phytochemical screening, quantify phenolic compounds, and evaluate the biological activities of Pistacia lentiscus. L. Setting: The leaves are taken from the female plants of P. lentiscus L., which grow in the forest of Canastel, Oran, (Algeria). Methods: A phytochemical screening was performed on P. lentiscus. L leaves and two extraction techniques were used for a comparative study. The total polyphenolic compounds, condensed tannins and flavonoids was quantified by the spectrophotometric methods. The antioxidant activity of the extracts was determined by two different techniques. The minimum inhibitory concentration of the extracts against Fusarium sp causing onychomycosis, was determined using the microdilution method. Results: Phytochemical screening indicates the presence of flavonoids, gallic tannins, saponins, anthocyanins, cardiac glycosides, leucoanthocyanins and quinones. The hydroalcoholic extract contained the highest amounts of total phenols, flavonoids, and condensed tannins and the most potent antioxidant and anti-Fusarim activities. Conclusion: Condensed tannins were found to be the most abundant phytochemical constituents. This suggests that the biological activities observed in this study may be largely attributed to the presence of condensed tannins. Contribution: The results of this study justify the use of P. lentiscus extracts in phytotherapy, especially for treating dermatological (onychomycosis) and digestive diseases, and open new research perspectives to promote this species in different sectors.

Breast milk, aside from its well-established nutritional and immunological attributes, constitutes a vital factor in infant developmental progression. The continuity of breastfeeding, an essential element during the postpartum phase, can be jeopardized when maternal antibiotic therapy is initiated to address conditions such as endometritis, mastitis, urinary tract infections, respiratory tract infections, or other ailments. The actual implications of antibiotic utilization during breastfeeding necessitate meticulous evaluation encompassing various factors influencing the level of antibiotic diffusion in mother’s milk. These factors encompass the composition of breast milk, the physical and chemical antibiotic characteristics (such as lipid solubility, molecular weight, pH, and protein binding), the length of feeding time, and the mother's metabolic profile. Moreover, considerations pertaining to infant factors, encompassing their capacity to absorb, metabolize, excrete, and tolerate antibiotic exposure, are imperative before maternal antibiotic administration. The ratio of milk to plasma concentration (M/P) is often referenced as a measure for predicting the transfer of drugs into the mother’s milk. Nevertheless, its effectiveness is questionable and it is frequently misunderstood. A different method, applicable when the concentration of the antibiotic in breast milk can be measured (through clinical studies), involves calculating the estimated or expected drug exposure for the infant. This calculation takes into account factors such as the expected amount of milk intake, the concentration of the drug in the milk, and its bioavailability.

ABSTRACT A major advance in the recycling of conductive and non-conductive materials contained in granular mixtures originating from industrial waste has been achieved thanks to the development of an innovative corona-electrostatic separator. The aim of this paper is to prove that the new device, equipped with two coaxial vertical cylindrical electrodes, offers a reliable and efficient solution for the selective sorting of copper and plastics from shredded small electrical cables waste. Careful control of operating parameters, such as voltage and air flow, is crucial to achieving optimum separation. Experiments conducted according to the response surface modeling methodology have shown that using a voltage of 30 kV and a flow rate of 1690 m3/min gives the highest recovery rates (beyond 90% for both products) and at purity levels of roughly 80% for plastics and 98% for copper. Further testing under various environmental conditions is recommended to assess the robustness of the electrostatic separation process.

Abstract Through monoazo‐coupling processes, H ‐imidazol and 2,4‐dichloroaniline were linked to 4‐amino acetophenone to create two novel azo dyes: ( E )‐1‐(4‐((1 H ‐imidazol‐2‐yl)diazenyl) phenyl) ethan‐1‐one (IDPE) and ( E )‐1‐(4‐((2‐amino‐3,5‐dichlorophenyl)diazenyl)phenyl) ethan‐1‐one (APDE). The electronic transitions spectra in the visible and UV ranges, FT‐IR spectra and 1 H NMR, were used to confirm the structures of prepared azo dyes. The pH‐sensitive chemical sensors based on the IDPE and APDE were investigated. Excellent sensitivity in the pH range of 3–9 and a significant wavelength shift (>85 nm) was demonstrated by these chemical sensors. It was demonstrated that these chemical pH sensors were fully reversible, which is essential for chemical pH sensors in practical applications. Additionally, the produced compounds were used in a bioimaging assay with mouse ovarian cells under confocal fluorescence microscopy to explore their potential as an effective cell staining agent.

Abstract The purpose of this work is to use the mixed fractional Brownian motion with parameter H ∈ ( 0 , 1 2 ) {H\in(0,\frac{1}{2})} as a modeling tool in financial mathematic, specifically in stochastic volatility modeling. We employ high frequency data from Oxford-Man Institute of Quantitative Finance Realized Library to estimate the smoothness of log-volatility. We show through empirical experiments that the measured smoothness of log-volatility is similar to that of mixed fractional Brownian motion when 0.09 ≤ H ≤ 0.2 {0.09\leq H\leq 0.2} . We propose to model the log-volatility by a mixed Fractional Brownian motion with H < 1 2 {H<\frac{1}{2}} and we construct a stationary mixed fractional Ornstein–Uhlenbeck process d ⁢ X t = - λ ⁢ ( X t - μ ) ⁢ d ⁢ t + γ ⁢ d ⁢ M t H , t ∈ [ 0 , T ] {dX_{t}=-\lambda(X_{t}-\mu)dt+\gamma dM_{t}^{H},t\in[0,T]} as a stationary model of log-volatility X t {X_{t}} and we show that it tends in distribution to the mixed fractional Brownian motion when λ → 0 {\lambda\rightarrow 0} .