Background: Many thymoma classifications have been followed and have been updated by newer or alternative schemes. Many classifications were based on the morphology and histogenesis of normal thymus as the backbone, while other classifications have followed a more simplified scheme, whereby thymomas were grouped based on biological behavior. The WHO classification is currently the advocated one, which is based on “organotypical” features (i.e. histological characteristics mimicking those observed in the normal thymus) including cytoarchitecture (encapsulation and a “lobular architecture”) and the cellular composition, mostly the nuclear morphology is generally appreciated.

Objectives: Thi

Background: Squamous carcinoma accounts for majority of esophaged cancinoma Most patients with esophaged cancer are middle aged or elderly with make to female ratio 2.5:1.
Aim of study : to present a fairly representative picture of the carcinoma of esophagus in' yemen.
Patients& Methods: Seventy-six patients were treated for carcinoma of esophagus over a 5 - year period by cardiothoracic and vascular surgeon working in Sana a - Yemen. Amongst them there were thirty one men and forty-five women, with male/female ratio 1:1.45, age incidence (range 38 - 40year).
Results:. Adenocarcinoma was 65% of cases and other 35% was squamous cel! carcinoma. The major risk factors were founded chewing quat, silicon particles, thermal injur

          In this paper, the survival function has been estimated for the patients with lung cancer using different parametric estimation methods depending on sample for completing real data which explain the period of survival for patients who were ill with the lung cancer based on the diagnosis of disease or the entire of patients in a hospital for a time of two years (starting with 2012 to the end of 2013). Comparisons between the mentioned estimation methods has been performed using statistical indicator mean squares error, concluding that the estimation of the survival function for the lung cancer by using pre-test singles stage shrinkage estimator method was the best   . <

Objective(s): To determine the impact of psychological distress in women upon coping with breast cancer.

Methodology: A descriptive design is carried throughout the present study. Convenient sample of (60) woman with breast cancer is recruited from the community. Two instruments, psychological distress scale and coping scale are developed for the study. Internal consistency reliability and content validity are obtained for the study instruments. Data are collect through the application of the study instruments. Data are analyzed through the use of descriptive statistical data analysis approach and inferential statistical data analysis approach.

Results: The study findings depict that women with breast cancer have experien

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

Support Vector Machine (SVM) is supervised machine learning technique which has become a popular technique for e-mail classifiers because its performance improves the accuracy of classification. The proposed method combines gain ratio (GR) which is feature selection method with one-class training SVM to increase the efficiency of the detection process and decrease the cost. The results show high accuracy up to 100% and less error rate with less number of feature to 5 features.

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

The surplus glycerol produced from biodiesel production process as a by-product with high quantity can be considered as a good source to prepare glycerol carbonate (GC) whereas with each 1000 kg from biodiesel obtains 100 kg from glycerol. Glycerol converted to glycerol carbonate over bio-char as a catalyst prepared by slow pyrolysis process under various temperatures from 400 ᴼC to 800 ᴼC. The char prepared at 700 ᴼC considered as a best one between the others which was manufactured to activate the transesterification reaction. GC have large scale of uses such as liquid membrane in gas separation, surfactants ,detergents , blowing agent , in plastics industry, in  Pharmaceutical industry and electrolytes in lithium batteries.

The experiment was conducted at field of garden of Department of Biology, Collage
of Education (Ibn-Al-Haitham) University of Baghdad during winter season of 2009-2010.
The aim of present study is the effect of growth regulator Gibberellins by using two
concentrations (100, 200) ppm and also Thiamine in two concentrations (10, 50) ppm, on the
some yield component characters and active component of volatile oil Cumin (Cuminum
cyminum L.).
The results showed that GA3 in (100) ppm increased the yield component, protein
concentration and increased in Cuminaldehyde, Perillaldehyde and Thyoml concentration.
The results showed that the best concentration was (50) ppm of Thiamine showed an
increasing concentratio

The temperature control process of electric heating furnace (EHF) systems is a quite difficult and changeable task owing to non-linearity, time delay, time-varying parameters, and the harsh environment of the furnace. In this paper, a robust temperature control scheme for an EHF system is developed using an adaptive active disturbance rejection control (AADRC) technique with a continuous sliding-mode based component. First, a comprehensive dynamic model is established by using convection laws, in which the EHF systems can be characterized as an uncertain second order system. Second, an adaptive extended state observer (AESO) is utilized to estimate the states of the EHF system and total disturbances, in which the observer gains are updated