Background: Irritable bowel syndrome (IBS) is one of the most common GI disorders in people under 50 years of age.
Objective: To Formulate an overview about demographics of IBS and patterns of presentation, to determine IBS patients severity ranking, and to recognize the main regimens with their patient satisfaction.
Methods: This is a cross sectional clinical study that is conducted in Outpatient Consultant Internal Medicine Clinic in Al-Kindy Teaching Hospital from 11/12/2017 to 24/12/2017. The patients suffering from IBS are diagnosed by a consultant according to the symptom-based Rome criteria for functional GI disorders, by implementing a questionnaire collecting thorough information. 77 cases of IBS patients were collected (24 male and 53 female).
Results: This study revealed that majority of patients were female (68.8%). Most of the patients were married, employees and housewives, aged between (20-30 yrs). Most patients use anxiolytics, muscle relaxants and proton pump inhibitor. There is a high IBS prevalence among low educational level (high school graduates and non-school graduates).
Most patients in our study had constipation.
Aggravating factors Psychological factors (stress) are intrinsically associated with IBS and symptoms in a large percentage of patients.
Antispasmodics usage in our study show high effectiveness for IBS patients especially those with crampy abdominal pain and diarrhea.
Conclusions: Diagnosing and managing IBS can be a big challenge since many drugs used to reduce symptoms and severity, but also, they could be unnecessary medication that could aggravate bowel symptoms and have adverse effects on the long term.
The removal of cadmium ions from simulated groundwater by zeolite permeable reactive barrier was investigated. Batch tests have been performed to characterize the equilibrium sorption properties of the zeolite in cadmium-containing aqueous solutions. Many operating parameters such as contact time, initial pH of solution, initial concentration, resin dosage and agitation speed were investigated. The best values of these parameters that will achieved removal efficiency of cadmium (=99.5%) were 60 min, 6.5, 50 mg/L, 0.25 g/100 ml and 270 rpm respectively. A 1D explicit finite difference model has been developed to describe pollutant transport within a groundwater taking the pollutant sorption on the permeable reactive barrier (PRB), which i
... Show MoreSIFCON is characterized as a construction material of high ductility and very high strength. It is suitable for concrete structures used for special applications. However, the density of SIFCON is much higher than that of Fiber Reinforced Concrete (FRC) due to the need for a large amount of high-density steel fibers. This work examines the split tensile behavior of modified weight slurry infiltrated fiber concrete utilizing a mixture of two types of fibers, steel fiber, and polyolefin fiber. For the investigation, 30 cylinders and 15 cubes were poured. The used volume fraction (V.F) is (6 %) and the use of five series once as each type separately and once a hybrid in proportions of 2/3 polyolefin with 1/3 steel fiber and
... Show MoreAl-Chibayish Marsh (CM) is considered as the major part of Central Marshes area of this marsh is 1050 Km². The water quality of these marshes is suffering from salt accumulation due to intensive dam construction, limited supply of water from sources, climate change impacts, and the absence of outlet flow from these marshes, specifically at low flow periods. So, the current research aims to assess and improve these marshes' hydraulic behavior and water quality and define the best location for outlet drains. Field measurements and laboratory tests were conducted for two periods (November 2020 and February 2021) to define the (TDS) concentrations at nine different locations. Samples were also examined for water's phy
... Show MoreThis study investigates the influence of fear, refuge, and migration in a predator–prey model, where the interactions between the species follow an asymmetric function response. In contrast to some other findings, we propose that prey develop an anti-predator response in response to a concentration of predators, which in turn increases the fear factor of the predators. The conditions under which all ecologically meaningful equilibrium points exist are discussed in detail. The local and global dynamics of the model are determined at all equilibrium points. The model admits several interesting results by changing the rate of fear of predators and predator aggregate sensitivity. Numerical simulations have been performed to verify our theoret
... Show MoreThis research delves into the realm of asphalt technology, exploring the potential of nano-additives to enhance traditional asphalt binder properties. Focusing on Nano-Titanium Dioxide (NT), Nano-Aluminum Oxide (NA), and Nano-Silica Oxide (NS), this study investigates the effects of incorporating these nanomaterials at varying dosages, ranging from 0% to 8%, on the asphalt binder’s performance. This study employs a series of experimental tests, including consistency, storage stability, rotational viscosity, mass loss due to aging, and rheological properties, to assess the impact of nano-additives on asphalt binder characteristics. The findings indicate a substantial improvement in the consistency of the asphalt binder with the add
... Show More This paper concerns with openness concept in contemporary learning environment, which ranges from physical characters to its relation with learning efficiency and its output. Previous literatures differ to clear the effect of openness on the engagement between learner within themselves, and with this kind of spaces. Engagement means: active participation, the ability of making dialogue, self-reflection and the ability to explore and communicate with them and
within learning space. Research roblem was: The lack of knowledge about the effect of Openness on learner engagement with learning spaces. The two concepts were applied on three types of learning spaces in the Department of the Architectu
Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c
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