Effects of dopamine on ion transport across rat colon

Dopamine (5.10-6 – 5.10-4 mol.l-1) when added serosally induced a concentrationdependent decrease in short-circuit current (Isc) across rat distal and proximal colon. This response was preceded by a transient and inconsistent increase in Isc. A part of the catecholamine action is mediated by subepithelial actions sites as it was indicated by the inhibiton of dopamine effects by the cyclooxygenase inhibitor, indomethacin (10-6 mol.l-1), and the neuronal blocker, tetrodotoxin (10-6 mol.l-1). The positive Isc evoked by dopamine was due to chloride secretion as indicated when both Cl- and HCO3- were substituted (using HEPES as buffer) and when of the basolateral membrane was depolarizing by high potassium concentration. The negative Isc evoked by dopamine was due to potassium secretion. This was demonstrated by unidirectional flux experiments. 86Rb+ efflux experiments revealed a redistribution of cellular K+ efflux in favour of the apical K+ conductance in the presence of dopamine. The negative Isc evoked by dopamine was inhibited by the blocker of apical K+ channels, quinine (10-3 mol.l-1), indicating that a stimulation of K+ secretion underlies the measured current. Both the alpha-adrenoceptor blocker phentolamine (10-4 mol.l-1) and as well as inhibitors of D2-like receptors such as L-741,626 (10-5 mol.l-1) and L-745,870 (10-5 mol.l-1) inhibited the dopamine response. All these observations indicate similarities between dopamine and the other catecholamines derivatives in their effect on ions transport in rat colon

The level of utilizing blended learning in teaching science from the point of view of science teachers in private schools of Ajman Educational Zone

This study aims to define the level of utilizing blended learning in teaching science from the point of view of science teachers (85 male and female teachers) who are working in private schools of Ajman Educational Zone. The study also aims to find if there are significant differences according to gender, years of experience, or the fact that those teachers attended training courses in the field of smart learning. To achieve the goals of this study, an instrument was used to measure the level of utilizing blended learning in teaching science. The study showed the following main results: the level of utilizing blended learning in teaching science was high. There are statistically significant differences in utilizing blended learning according to the years of experience and training courses (in favor of less experienced teachers and teachers who attended training courses in the field of smart learning). The results did not show any statistically significant difference according to the gender. In the light of the study findings and their interpretation, the study highly recommends holding training courses in the field of blended learning and providing the necessary tools to implement it. Key words: Blended learning, science teachers, science educatio

Ground Response Analysis for Two Selected Sites in Al-Hilla City in the Middle of Iraq

يصف تحليل الاستجابة الأرضية أيضا دراسة تضخيم التربة ويتضمن حساب الفترات الطبيعية للموقع، وتضخيم الحركة الأرضية، وتقييم قابلية تمييع التربة، وتحليل الاستقرارية. الميزات المهمة التي يتم أخذها في الاعتبار للتحليل هي خصائص صخور الاساس التحتية، موقع وميل حجر الأساس، تضاريس حجر الاساس ورواسب التربة، والفوالق في رواسب التربة. في هذا البحث، تم اختيار موقعين في مدينة الحلة للبحث في تحليل الاستجابة الأرضية. وتضمنت الفحوصات المختبرية محتوى الرطوبة، وحدود اتيربيرغ، وبمعرفة توزيع حجم الحبيبات تم رسم منحنيات توزيع الحجم الحبيبي للرواسب النهرية المتواجدة، في حين شمل العمل الميداني: قياسات سرعة موجة القص vs وحساب قيمة N -  من فحص الاختراق القياسي (قيم ال SPT) لكل موقع. التوصيف الجيوتقني، اوضح أن التربة في الموقعين تسود عليها الرمال الغرينية والطين الغريني. تحليل استجابة الموقع لحركة الأرض طبق باستخدام برنامج Proshake. نتائج التحليل الخطي المكافئ بينت أن قمة تسارع سطح الأرض تتراوح بين 0.0523g إلى 0.0639g. عامل التضخيم للتسارع في مدى ما بين 1.048 إلى 1.27.Ground response analysis also termed as soil amplification study comprises the calculation of site natural periods, ground motion amplification, evaluation of liquefaction potential, and stability analysis. The important features that are considered for analysis are characteristics of soil overlying bedrock, bedrock location and inclination, topography of bedrock and soil deposits, faults in the soil deposits. In this paper, two sites within Al-Hilla city were selected to investigate the ground response analysis. Laboratory tests  included moisture content, Aterbberg limits , and  the  grain size distribution curves have been developed to understand the particle size distribution of the alluvium present, while field work included: shear wave velocity measurements and N-value calculation. From geotechnical characterization, it has been observed that the soil profile in the two sites is dominated by silty sand and silty clay. The site response analysis of ground motion was carried out using Proshake software. The results of the equivalent linear analysis show that the peak surface ground acceleration ranges between 0.0523g to 0.0639g. The amplification factor for acceleration is in the range between 1.048 to 1.27

Rodent models of neuroinflammation for Alzheimer\u27s disease

Alzheimer\u27s disease remains incurable, and the failures of current disease-modifying strategies for Alzheimer\u27s disease could be attributed to a lack of in vivo models that recapitulate the underlying etiology of late-onset Alzheimer\u27s disease. The etiology of late-onset Alzheimer\u27s disease is not based on mutations related to amyloid-beta (A beta) or tau production which are currently the basis of in vivo models of Alzheimer\u27s disease. It has recently been suggested that mechanisms like chronic neuroinflammation may occur prior to amyloid-beta and tau pathologies in late-onset Alzheimer\u27s disease. The aim of this study is to analyze the characteristics of rodent models of neuroinflammation in late-onset Alzheimer\u27s disease. Our search criteria were based on characteristics of an idealistic disease model that should recapitulate causes, symptoms, and lesions in a chronological order similar to the actual disease. Therefore, a model based on the inflammation hypothesis of late-onset Alzheimer\u27s disease should include the following features: (i) primary chronic neuroinflammation, (ii) manifestations of memory and cognitive impairment, and (iii) late development of tau and A beta pathologies. The following models fit the pre-defined criteria: lipopolysaccharide-and PolyI:C-induced models of immune challenge; streptozotocin-, okadaic acid-, and colchicine neurotoxin-induced neuroinflammation models, as well as interleukin-1 beta, anti-nerve growth factor and p25 transgenic models. Among these models, streptozotocin, PolyI:C-induced, and p25 neuroinflammation models are compatible with the inflammation hypothesis of Alzheimer\u27s disease

Measuring E-learning Readiness of the Students in Tishk International University

With the advancement of technology, almost every aspect of our life is started to have an electronic version, the availability of such technologies used to be the challenge but more recently, the readiness of the user is growing bigger. E-learning and the students' readiness to use such a tool in Tishk International University is the topic of this study. The study used a questionnaire, which is consisted of 31 items with demographic data as well to collect the required data. Results showed that the students are at the expected level of E-learning readiness. Although some improvements are needed to meet the minimum requirements to perform e-learning. The study selected three factors, the availability of needed technology for e-learning, the student’s technical skills to use e-learning, the acceptance of students to use E-learning to conduct the study

Face mask detection using deep learning on NVIDIA Jetson Nano

In December 2019, the coronavirus pandemic started. Coronavirus desease-19 (COVID-19) is transmitted directly from contaminated surfaces via direct touch. To combat the virus, a multitude of equipment is needed. Masks are a vital element of personal protection in crowded places. As a result, determining if a person is wearing a face mask is critical to assimilating to contemporary society. To accomplish the objective, the model presented in this paper used deep learning libraries and OpenCV. This approach was chosen for safety concerns due to its high resource efficiency during deployment. The classifier was built using the MobileNetV2 structure, which was designed to be lightweight and capable of being utilized in embedded devices such as the NVIDIA Jetson Nano to do real-time mask recognition. The stages of model construction were collecting, pre-processing, splitting data, creating the model, training the model, and applying the model. This system utilized image processing techniques and deep learning to process a live video feed. When someone is not wearing a mask, the output eventually produces an alarm sound through a built-in buzzer. Experimental results and testing were used to verify the suggested system's performance. Including both training and testing, the achieved recognition rate was 99%