Water scarcity is one of the most important problems facing humanity in various fields such as economics, industry, agriculture, and tourism. This may push people to use low-quality water like industrial-wastewater. The application of some chemical compounds to get rid of heavy metals such as cadmium is an environmentally harmful approach. It is well-known that heavy metals as cadmium may induce harmful problems when present in water and invade to soil, plants and food chain of a human being. In this case, man will be forced to use the low quality water in irrigation. Application of natural materials instead of chemicals to remove cadmium from polluted water is an environmental friendly approach. Attention was drawn in this research wor

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

     Lately, a growing interest has been emerging in age estimation from face images because of the wide range of potential implementations in law enforcement, security control, and human computer interactions. Nevertheless, in spite of the advances in age estimation, it is still a challenging issue. This is due to the fact that face aging process is not only set by distinct elements, such as genetic factors, but by extrinsic factors, such as lifestyle, expressions, and environment as well. This paper applied machine learning technique to intelligent age estimation from facial images using J48 classifier on FG_NET dataset. The proposed work consists of three phases; the first phase is image preprocessing which include

     Bioethanol is an attractive fuel with higher potential for energy security and environmental safety. Olive solid residues were used as a raw material for the production of bioethanol through the use of different preliminary treatments . Separate treatments with cellulose, hydrochloric acid (HCl 5%), sulfuric acid (H₂SO₄ 2%), and liquid ammonia NH₄OH (20%) were used to convert cellulose and hemicellulose into monosaccharaides. The production of ethanol was observed during the fermentation process using R. minuta under anaerobic conditions.  After 3 days of fermentation, lowest concentrations of ethanol of  0.233, 0.249, 0.261, and 0.275 g/ l were produced from ol

    By using precipitation polymerization, liquid electrodes of polymers imprinted with Mebeverine hydrochloride and metronidazole benzoate were created whereas the imprinted polymer (MIP) and non imprinted (NIP) polymers were prepared by using Mebeverine hydrochloride and Metronidazole benzoate qua a template. In the polymerization process, 2-Acrylamido-2-methyl-1-propane Sulphonic acid (AMPS) or 1-Vinylimidazole (VIZ) was used qua monomer, pentaerythritol triacrylate (PETRA) or Divinylbanzene (DVB) was used qua a cross-linker while benzoyl peroxide (BPO) was used as an initiator. The MIP membranes and the membranes of NIP were created by using Dibutyl Sebacate (DBS) and Tris(2-ethylhexyl)phosphate(TEHP) qua plasticizers

Background. Endodontic infections caused by remaining biofilm following disinfection with chemical fluids encourage secondary bacterial infection; hence, employing laser pulses to activate the fluids is advised to improve microbial biofilm clearance. This study investigated the performance of Er,Cr:YSGG laser in photon-induced photoacoustic streaming (PIPS) agitation of 5.25% sodium hypochlorite (NaOCl) to enhance the removal of mature Enterococcus faecalis (E. faecalis) biofilms in complex root canal systems. Methods. The mesial roots of the lower first and second molars were separated and inoculated with E. faecalis bacteria for 30 days. The roots were irrigated with 5.25% NaOCl, some of them were agitated with passive ultrasonic

Abstract

The analysis of Least Squares: LS is often unsuccessful in the case of outliers ​​in the studied phenomena. OLS will lose their properties and then lose the property of Beast Linear Unbiased Estimator (BLUE), because of the Outliers have a bad effect on the phenomenon. To address this problem, new statistical methods have been developed so that they are not easily affected by outliers. These methods are characterized by robustness or (resistance). The Least Trimmed Squares: LTS method was therefore a good alternative to achieving more feasible results and optimization. However, it is possible to assume weights that take into consideration the location of the outliers ​​in the data and det