In this article we study the variance estimator for the normal distribution when the mean is un known depend of the cumulative function between unbiased estimator and Bays estimator for the variance of normal distribution which is used include Double Stage Shrunken estimator to obtain higher efficiency for the variance estimator of normal distribution when the mean is unknown by using small volume equal volume of two sample .

Tin oxide films (SnO2) of thickness (1 ?m) are prepared on glass substrate by post oxidation of metal films technique. Films were irradiated with Nd:YAG double frequency laser of wavelength (532 nm) pulses of three energies (100, 500, 1000) mJ. The optical absorption, transmission, reflectance, refractive index and optical conductivity of these films are investigated in the UV-Vis region (200-900) nm. It was found that the average transmittance of the films is around (80%) at wavelength (550 nm) and showed high transmission (? 90 %) in the visible and near infrared region. The absorption edge shifts towards higher energies, which is due to the Moss-Burstien effect and it lies at (4 eV). The optical band gap increased with increasing of ene

This study investigates the possibility of removing ciprofloxacin (CIP) using three types of adsorbent based on green-prepared iron nanoparticles (Fe.NPs), copper nanoparticles (Cu. NPS), and silver nanoparticles (Ag. NPS) from synthesized aqueous solution. They were characterized using different analysis methods. According to the characterization findings, each prepared NPs has the shape of a sphere and with ranges in sizes from of 85, 47, and 32 nanometers and a surface area of 2.1913, 1.6562, and 1.2387 m²/g for Fe.NPs, Cu.NPs and Ag.NPs, respectively. The effects of various parameters such as pH, initial CIP concentration, temperature, NPs dosage, and time on CIP removal were investigated through batch experiments. The res

Academic chemical laboratories (ACL) are considered public places  the employees come in contact with a variety of pollutants. The aim of the current study was to detect heavy metals levels in the indoor air of ACL in two universities in Baghdad city and assess their levels in the academic employees’ scalp hair as biomarkers. Air samples inside ACL were collected to detect Fe, Cd, Zn, Pb and Cu. Scalp hair samples were collected from 40 adult chemical laboratory employees aged 30-60 years, who worked 5 days/week for 6 hours a day. Personal information relating to employees such as age, duration of exposure, smoking habit and sex, was collected as a questionnaire. The results of this study concluded that academic laboratory employ

Background: The aim of this study was to comparatively evaluate the push out bond strength (PBS) of root canal fillings using four different obturation techniques (single cone (SC), cold lateral compaction (CLC), continuous wave (CW), and carrier based gutta percha (CBG)). Materials and Methods: Forty mandibular premolar decoronated and instrumented with rotary ProTaper to F3 then teeth were divided randomly into 4 groups of 10 teeth for each as follow: group (I) single- cone obturation with matched-taper gutta-percha, group (II) cold lateral compaction technique, group (III) continuous wave of obturation technique, and group( IV) carrier based gutta-percha technique. Zinc oxide eugenol (ZOE) sealer was used as a root canal sealer for the

It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological