Survival analysis is the analysis of data that are in the form of times from the origin of time until the occurrence of the end event, and in medical research, the origin of time is the date of registration of the individual or the patient in a study such as clinical trials to compare two types of medicine or more if the endpoint It is the death of the patient or the disappearance of the individual. The data resulting from this process is called survival times. But if the end is not death, the resulting data is called time data until the event. That is, survival analysis is one of the statistical steps and procedures for analyzing data when the adopted variable is time to event and time. It could be d

With the increasing rate of unauthorized access and attacks, security of confidential data is of utmost importance. While Cryptography only encrypts the data, but as the communication takes place in presence of third parties, so the encrypted text can be decrypted and can easily be destroyed. Steganography, on the other hand, hides the confidential data in some cover source such that the existence of the data is also hidden which do not arouse suspicion regarding the communication taking place between two parties. This paper presents to provide the transfer of secret data embedded into master file (cover-image) to obtain new image (stego-image), which is practically indistinguishable from the original image, so that other than the indeed us

The effect of operating parameters on the batch scale separation of hydrocarbon mixture (benzene and hexane) using
emulsion liquid membrane technique is reported. Sparkleen detergent was used as surfactant and heavy mineral oil as
solvent to receive the permeates.
From the experimental results, the parameters that influenced the permeation are, composition of feed, contact time
with solvent, ratio of volume of solvent to volume of hydrocarbon feed, ratio of volume of surfactant solution to volume
of hydrocarbon feed, surfactant concentration, mixing intensity and glycerol as polar additive in the surfactant solution
to eliminate drop breakup.
The best conditions for the separation in this study were found to be: comp

The aim of this study is to investigate the ability of malachite green (MG) combined with 650nm diode laser to kill Candida albicans and to spectrally study the MG photodegradation after photodynamic therapy (PDT) spectrally. Cultures of Candida albicans were exposed to 40mW, 650 nm diode laser in the absence of MG. In PDT group, the MG was added to the Candida suspension for 5 min then exposed to diode laser for (5, 10, 15, 20) min at power density of 0.59W/cm2. The absorption spectrum of the photosensitized fungal suspension was obtained. The data were submitted to T-test (p<0.05). A 650nm diode laser in the presence of MG reduced the number of CFU/ml in 98.4%. Laser with 650nm alone and MG alone did not reduce significantly the num

Adsorption experiments were carried out using two different low-cost sorbent materials, date seeds and olive seeds. These sorbents used as a single phase (not as mixture) to remove cadmium ions from simulated wastewater by adsorption process. The equilibrium time was found at 2 hr. The experiments include different parameters such sorbent type and weight and contact time. It was found that both of olive seed and date seed have approximately the same adsorption capacity (qm) with 15.644 mg/g and 15.2112 mg/g, respectively. Equilibrium isotherms and kinetic studies have been carried out. Langmuir isotherm model better fits the experimental data compared with the Freundlich isotherm for olive seed, while Freundlich isotherm fits for date se

Abstract

       The current study was carried out to reveal the plasma parameters such as ,the electron temperature ( ), electron density (n_e) , plasma frequency (fp), Debye length ( ) , Debye number (   for  CdS to employ the LIBS for the purpose of analyzing and determining spectral emission lines using . The results of electron temperature for CdS range (0.746-0.856) eV , the electron density(3.909-4.691)×10¹⁸ cm^-3. Finally ,we discuss plasma parameters of CdS  through  nano second  laser generated plasma .

Copper nanoparticles (CuNPs) were prepared with different diameters by sonoelectrodeposition technique using Electrodeposition process coupled with high-power ultrasound horn (Sonoelectrodeposition). The particle diameter of the CuNPs was adjusted by varying CuSO4 solution acidity (pH) and current density. The morphology and structure of the CuNPs were examined by X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM). It was found that the size of the produced copper nanoparticles ranged between 22 to 77 nm, where the diameter of CuNPs increases with reduction the solution acidity from 0.5 to 1.5 pH and increasing the current density of the deposition from 100 to 400 nm. Finally the produced CuNPs were pressed to fabricate disc

In this paper the behavior of the quality of the gradient that implemented on an image as a function of noise error is presented. The cross correlation coefficient (ccc) between the derivative of the original image before and after introducing noise error shows dramatic decline compared with the corresponding images before taking derivatives. Mathematical equations have been constructed to control the relation between (ccc) and the noise parameter.

The biochar prepared from sawdust raw material was applied in this study for the treatment of wastewater polluted with methyl orange dye. The effect of pH (2-11), initial concertation (50-250 mg/L) and time were studied. The isotherm of Langmuir, Frendluch and temkin models studied. The Langmuir model was the best to explain the adsorption process, maximum uptake was 136.67 mg/g at 25C^o of methyl orange dye. Equilibrium reached after four hours of contact for most adsorbents.The values of thermodynamic parameters ∆G were negative at various temperatures, so the process spontaneous, while ∆H values were 16683 j/mol and ∆S values was 60.82 j/mol.k.

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w