Background: Colorectal cancer (CRC) is one of the top ten most common cancers worldwide. There are multiple risk factors for CRC, one of which is aging. However, in recent years, CRC has been reported in children. Objective: To describe the main characteristics and symptoms of CRC as well as highlight pathologic data for early-onset CRC. Methods: 79 CRC patients were recruited from the Oncology Teaching Hospital in the period February–December 2022. A questionnaire was used to collect demographic and clinical data. Results: 25 (31.6%) of patients were below 50 years of age. 52 (65.8%) patients had tumors in the colon. The most common symptom is bleeding per rectum in both age groups. There was no significant difference in patholog

The research topic is summarized in the importance of studying the measuring the extent of the university youth’s exposure in the Emirati Society to those series and the resulting achieved satisfaction. The most important results and recommendations of the study are as follows: a high rate of the respondents’, sample individuals, exposure to the dubbed Turkish series since it is evident that almost three-fourths of the study individuals watch the dubbed Turkish series,.”. The most significant positive aspects of the dubbed Turkish series are: “they focus on the most important tourist attractions in Turkey” and “ improving the audience›s knowledge and information on the traditions of the Turkish society”. The most apparent

The research consists of five chapters, and in the first chapter, it addresses the introduction and importance of the research, where the researcher explained the importance of bio-motor abilities and their role in achieving a high level through their connection to the skill performance of standing on the hands followed by the forward roll, and the research problem: Do these bio-motor abilities have an impact on the level of skill performance? Handstand followed by forward roll.

The microbend sensor is designed to experience a light loss when force is applied to the sensor. The periodic microbends cause propagating light to couple into higher order modes, the existing higher order modes become unguided modes. Three models of deform cells are fabricated at (3, 5, 8) mm pitchand tested by using MMF and laser source at 850 nm. The maximum output power of (8, 5, 3)mm model is (3, 2.7, 2.55)nW respectively at applied force 5N and the minimum value is (1.9, 1.65, 1.5)nW respectively at 60N.The strain is calculated at different microbend cells ,and the best sensitivity of this sensor for cell 8mm is equal to 0.6nW/N.

Aspect-based sentiment analysis is the most important research topic conducted to extract and categorize aspect-terms from online reviews. Recent efforts have shown that topic modelling is vigorously used for this task. In this paper, we integrated word embedding into collapsed Gibbs sampling in Latent Dirichlet Allocation (LDA). Specifically, the conditional distribution in the topic model is improved using the word embedding model that was trained against (customer review) training dataset. Semantic similarity (cosine measure) was leveraged to distribute the aspect-terms to their related aspect-category cognitively. The experiment was conducted to extract and categorize the aspect terms from SemEval 2014 dataset.

Objectives. The current study aimed to predict the combined mesiodistal crown widths of maxillary and mandibular canines and premolars from the combined mesiodistal crown widths of maxillary and mandibular incisors and first molars. Materials and Methods. This retrospective study utilized 120 dental models from Iraqi Arab young adult subjects with normal dental relationships. The mesiodistal crown widths of all teeth (except the second molars) were measured at the level of contact points using digital electronic calipers. The relation between the sum mesiodistal crown widths of the maxillary and mandibular incisors and first molars and the combined mesiodistal crown widths of the maxillary and mandibular canines and premolars was as

This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima