Rudimentary non-communicating functional uterine horn with unicornuate uterus, originating from anomalous embryological development of one Mullerian duct, is prone to different complications either at the gynecological or obstetrical level such as chronic pelvic pain, hematometra, subfertility and decreased quality of life. This unique case report presents a 14-year-old female with a history of severe chronic pelvic pain. She was diagnosed with Familial Mediterranean Fever (FMF) and had an appendectomy for suspected appendicitis within the symptoms’ interval. Ultrasound showed a right 5*6 cm right complex cystic mass assuming ovarian in place. She underwent a suspected endometrioma cystectomy operation and was diagnosed with left unico

This research study experimentally the effect of air flow rate on humidification process
parameters. Experimental data are obtained from air conditioning study unit T110D. Results obtained
from experimental test, calculations and psychometrics software are discussed. The effect of air flow rate
on steam humidification process parameters as a part of air-conditioning processes can be explained
according to obtained results. Results of the steam humidification processes (1,2) with and without
preheating with 5A and 7.5A shows decreasing in dry bulb temperature, humidity ratio, and heat add to
moist air with increasing air flow rate, but humidification load, and total energy of moist air increase with
increasing air flo

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In this search, we examined the factorial experiments and the study of the significance of the main effects, the interaction of the factors and their simple effects by the F test (ANOVA) for analyze the data of the factorial experience. It is also known that the analysis of variance requires several assumptions to achieve them, Therefore, in case of violation of one of these conditions we conduct a transform to the data in order to match or achieve the conditions of analysis of variance, but it was noted that these transfers do not produce accurate results, so we resort to tests or non-parametric methods that work as a solution or alternative to the parametric tests , these method

Background: Beta-thalassemia major is the most common monogenic known disorder in the Middle East, characterized by anomalies in the synthesis of the beta chains of hemoglobin resulting in variable phenotypes ranging from severe anemia to clinically asymptomatic Individuals. This study aimed to evaluate salivary flow rate and salivary IgA in β-thalassemia major patients. Since many oral and systemic conditions manifest themselves as changes in the flow and composition of saliva the dental practitioner is advised to remain up-to-date with this issue. Materials and methods: The study samples consist of (60) subjects, patients group composed of (30) patients with β –thalassemia major, age rang (5-23) years and (30) healthy locking

The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte