Several  amine  liquid selective  electrodes  were prepared based on

two  active   materials,   phenol  sulfonic   acid  and   l ,2-dihydroxy-3,5- disulfonic  acid   disodium   salt   with  several   plasticizers,  di-n-butyl phthalate(ORPH),  tri-n-butyl   phosphate   (TBP)   and  a-nitro   phenyl octyl  ether   (NPOE).   Electrode   parameters   were  studied   including, concentration range,  detection  limit,  slope,  life  time,  response  time and  

A new, simple, accurate, fast and sensitive spectrophotometric method has been
developed for the analysis of Pyrocatechol, Resorcinol, and pyrogallolin pure
commercial samples by continuous flow injection analysis. The method was based on
the oxidation of the organic compounds with Ce(IV)sulfate in acidic medium to
formed a brown colored species which determined using homemade Ayah 3SBGR x3-
3D solar cell flow injection microphotometer. Optimum conditions were obtained
using a high intensity green light emitted diode as an irradiation source
forPyrocatechol, Resorcinol, whileblue light emitted diode as an irradiation source for
pyrogallol. The linear dynamic range for the instrument response versus Pyrocatechol,

Date palm silver nanoparticles are a green synthesis method used as antibacterial agents. Today,
there is a considerable interest in it because it is safe, nontoxic, low costly and ecofriendly. Biofilm bacteria
existing in marketed local milk is at highly risk on population health and may be life-threatening as most
biofilm-forming bacteria are multidrug resistance. The goal of current study is to eradicate biofilm-forming
bacteria by alternative treatment green synthesis silver nanoparticles. The biofilm formation by bacterial
isolates was detected by Congo red method. The silver nanoparticles were prepared from date palm
(khestawy) fruit extract. The formed nanoparticles were characterized with UV-Vis

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.

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

Background: Polymer surfaces usually present problems in bonding and finishing due to their low hydrophilicity. The aim of this study is to investigate the effect of plasma treatment with the use of two types of gases (oxygen and argon) on surface roughness, and chemical surface properties of acrylic resin denture base polymer material. Materials and Methods: Three heat cured acrylic resin specimens of (2*8*30 mm) dimensions were prepared for each test carried out in this study. Two tests were conducted, surface roughness test and chemical surface analysis test. Results: Application of plasma treatment increased surface roughness for both oxygen and argon plasma treated acrylic resin specimen groups compared with control untreated group,

    In data mining and machine learning methods, it is traditionally assumed that training data, test data, and the data that will be processed in the future, should have the same feature space distribution. This is a condition that will not happen in the real world. In order to overcome this challenge, domain adaptation-based methods are used. One of the existing challenges in domain adaptation-based methods is to select the most efficient features so that they can also show the most efficiency in the destination database. In this paper, a new feature selection method based on deep reinforcement learning is proposed. In the proposed method, in order to select the best and most appropriate features, the essential policies

The study included the investigation of fungi ringed and inventory and Aflatoxins in rice and recorded average temperatures and humidity 22.75 degree Celsius and 13.2% respectively were obtained 1356 isolation innate possible diagnosis 15 species inherent in rice imported back to 8 races represented races b Fusarium , Cladosporium, Aspergillus and Alternaria