This article publishes seven cuneiform tablets in the collection of the Iraq Museum Baghdad. Six of the tablets have an Irisagrig/Al Sarraki provenance, the seventh is of uncertain origin. They are dated to the reigns of Amar-Suen (AS) and Ibbi-Suen (IS) of the Ur III Dynasty. The texts represent administrative texts of the governing institutions and account for economic activities including the assignment of female workers for wool plucking, the remuneration of canal work with barley and the selection of wool for textiles. Three tablets record offerings in respect of cultic observances, two of which describe the disbursement of foodstuffs for the king's monthly 83-63 offerings to the new moon.

The ground state proton, neutron, and matter density distributions and corresponding root-mean-square (rms) of P19PC exotic nucleus are studied in terms of two-frequency shell model (TFSM) approach. The single-particle wave functions of harmonic-oscillator (HO) potential are used with two different oscillator parameters bRcoreR and bRhaloR. According to this model, the core nucleons of P18PC nucleus are assumed to move in the model space of spsdpf. The shell model calculations are carried out for core nucleons with w)20(+ truncations using the realistic WBPinteraction. The outer (halo) neutron in P19PC is assumed to move in the pure 2sR1/2R-orbit. The halo structure in P19PC is confirmed with 2sR1/2R-dominant configuration.Elastic electr

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

Background: The COVID-19 infection is a more recent pandemic disease all over the world and studying the pulmonary findings on survivors of this disease has lately commenced.

Objective: We aimed to estimate the cumulative percentage of whole radiological resolution after 3 months from recovery and to define the residual chest CT findings and exploring the relevant affecting factors.

Subjects and Methods: Patients who had been previously diagnosed with COVID-19 pneumonia confirmed by RT-PCR test and had radiological evidence of pulmonary involvement by Chest CT during the acute illness were included in the present study. The radiol

Contours extraction from two dimensional echocardiographic images has been a challenge in digital image processing. This is essentially due to the heavy noise, poor quality of these images and some artifacts like papillary muscles, intra-cavity structures as chordate, and valves that can interfere with the endocardial border tracking. In this paper, we will present a technique to extract the contours of heart boundaries from a sequence of echocardiographic images, where it started with pre-processing to reduce noise and produce better image quality. By pre-processing the images, the unclear edges are avoided, and we can get an accurate detection of both heart boundary and movement of heart valves.

Cuneiform texts are the most important sources for our knowledge of ancient history and in all political, economic, social and religious fields, as the ancients left us thousands of these texts, which were found through excavations, and hundreds of these texts were stolen and smuggled out of Iraq, and some of these texts were returned after the Jordanian government confiscated them and returned them to the Iraqi Museum. Most of these cuneiform texts were economic texts. In this research, a group of these confiscated cuneiform texts was studied (their number was six texts bearing the following museum numbers, respectively (160609 - 160103 - 160290 - 160102 - 206650 - 206637) dating back to the time of the king of the Larsa dynasty, Rim-Sin (

Enhancing quality image fusion was proposed using new algorithms in auto-focus image fusion. The first algorithm is based on determining the standard deviation to combine two images. The second algorithm concentrates on the contrast at edge points and correlation method as the criteria parameter for the resulted image quality. This algorithm considers three blocks with different sizes at the homogenous region and moves it 10 pixels within the same homogenous region. These blocks examine the statistical properties of the block and decide automatically the next step. The resulted combined image is better in the contras