This research investigated the effect of adding two groups of reinforcement materials, including bioactive materials Hydroxyapatite (HA) and halloysite nanoclay and bioinert materials Alumina (AL2O3) and Zirconia (ZrO2), each of them with various weight ratios (1,2,3,4 &5)% to the polymer matrix PMMA. The best ratios were selected, and then a hybrid was preparing Composite red from the best ratios from each group. Thermal properties, including thermal conductivity and Thermomechanical Analysis (TMA) technology, have been studied. The results showed that adding 3% Hydroxyapatite (HA) and 5% halloysite nanoclay to the polymethacrylate (PMMA) mer leads to an increase in thermal conductivity. It was also found from the Thermomechanical Analysis

             Bioindicators have an important role in assessing the quality of water bodies. Aquatic oligocheates, was used as a bioindicator to assess the sediment quality of Al-Hindyia and AL-Abbasyia river (branches of Euphrates River in Iraq). Two sites in each river have been   chosen for this purpose, site S1 was located at Al-Hindyia River and S2 at Al-Abbasyia River. Some kinds of biological indices were used in this study, comprising the percentage of oligochaetes in benthic invertebrates, ranged from 20.3-60.16%. While the percentage of Tubificidae within benthic invertebrates was close 43.3-43.9%.Index of pollution D ranged from 0.13-0.21. The maximum percentage of aquatic oligochaetes to insects larvae of family

تضمن هذا العمل تحضير ليكند قاعدة شيف جديدة مشتقة من مادة البولي أكريلاميد والكلوترالديهايد [(2S, 2'S) – N, N' - (pentane-1, 5-diylidene) bis (2- methylbutan amide)]  مع بعض المعادن الثقيلة (Cr + 3 Mn + 3 , Fe + 3 , ,Co + 2,  Ni + 2 ,Cu + 2  Zn + 2 , Cd + 2,) لتنتج المعقدات المقابلة. تم تشخيص قواعد شيف ومعقداتها المعدنية بأستخدام طيف الأشعة تحت الحمراء والأشعة المرئية وفوق البنفسجية، والتوصيلية ,وقيم المغناطيسية والتحليل الحراري الوزني وحيود الأشعة السينية ومجه

COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduce

The research aims to identify the requirements of banking Entrepreneurial in Saudi Arabia and Singapore, where banking Entrepreneurial is an important way to lead employees to acquire the experience and knowledge required by the banking environment, so we note the pursuit of the banking management to acquire new technology proactively and distinctively to compete with others through the introduction of modern technologies that help senior management to develop new banking methods adaptable to the surrounding environmental changes. The problem of research highlights the extent to which the requirements of banking Entrepreneurial are applied in Saudi Arabia and the Republic of Singapore and will be addressed through three investigation

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par