A mercury porosimeter has been used to measure the intrusion volume of the three types mercury positive lead acid-battery plates. The intrusion volumes were used to calculate the pore diameter, pore volume, pore area, and pore size distribution. The variation of the pore area in positive lead acid-battery plates as well as of the pore volume has the following sequence. Paste positive > Uncured positive > Cured positive

Biofilm formation is one of the biggest challenges of scientists. Role of heavy metals in forming biofilm is not clear enough. Here, the effect of lead on biofilm formation by Bacillus spp. isolated from soil in terms of biofilm formation and remove was studied. In present study, 10 isolates of Bacillus spp were isolated from soil. The ability of all isolates to form biofilm was evaluated. The effect of lead on biofilm formation was studied by adding lead (pb) before forming biofilm. In another experiment the lead was added after biofilm formation to study the effect of lead on biofilm remove. The current study, showed the ability of all studied isolates to form biofilm. Maximum biofilm formation by Bacillus spp isolate number 8 (B8) follow

In this study, dependence of gamma-ray absorption coefficient on the size of Pb particle size ranging from 200µm up to 2.5mm, using different weights of each particle size. The results show that gamma-ray attenuation coefficient is inversely proportional with the size of Pb particle size due to the reduction of the spaces between the lead particles.

A mercury porosimeter has been used to measure the intrusion volume of the three types mercury positive lead acid-battery plates. The intrusion volumes were used to calculate the pore diameter, pore volume, pore area, and pore size distribution. The variation of the pore area in positive lead acid-battery plates as well as of the pore volume has the following sequence. Paste positive > Uncured positive > Cured positive

Two main grand bus national stations in Baghdad ( Alawi-alhila and Bab-almudam) were chosen as examples to determine lead effect on its drivers. This lead came from ethyl tetra lead or ethyl tri lead which used to improve gasoline quality ,so these two stations could be consider as two of the most polluted places due to gasoline burned by hundreds cars located in these stations .The determination of environmental lead pollution was measured in blood and urines drivers. Drivers were divided in two main groups due to their ages ( 30 persons in each group). The first group for men of 22-30 years old. The second group for men of 40-60 years old. Those men were carefully chosen in order to be non-fumiers or non-alcoholics persons because of

In this paper the use of a circular array antenna with adaptive system in conjunction with modified Linearly Constrained Minimum Variance Beam forming (LCMVB) algorithm is proposed to meet the requirement of Angle of Arrival (AOA) estimation in 2-D as well as the Signal to Noise Ratio (SNR) of estimated sources (Three Dimensional 3-D estimation), rather than interference cancelation as it is used for. The proposed system was simulated, tested and compared with the modified Multiple Signal Classification (MUSIC) technique for 2-D estimation. The results show the system has exhibited astonishing results for simultaneously estimating 3-D parameters with accuracy approximately equivalent to the MUSIC technique (for estimating elevation and a

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.