Polyaromatic hydrocarbons (PAHs) are a group of aromatic compounds that contain at least two rings. These compounds are found naturally in petroleum products and are considered the most prevalent pollutants in the environment. The lack of microorganism capable of degrading some PAHs led to their accumulation in the environment which usually causes major health problems as many of these compounds are known carcinogens. Xanthene is one of the small PAHs which has three rings. Many xanthene derivatives are useful dyes that are used for dyeing wood and cosmetic articles. However, several studies have illustrated that these compounds have toxic and carcinogenic effects. The first step of the bacterial degradation of xanthene is conducted by dioxygenase enzymes that introduces two oxygen atoms in the structure of the aromatic rings. In this study we focused on the bacterial bioremediation of xanthene via Sphingobium yanoikuyae B1DR, an engineered strain carrying the dioxin angular dioxygenase from Sphingomonas wittichii RW1. HPLC analysis of supernatant from resting cells of S. yanoikuyae B1DR grown on xanthene and succinate showed the ability of this strain to transform xanthene to 2-hydroxyphenylacetate that was not produced by the wild type of Sphingobium yanoikuyae B1. Production of 2-hydroxyphenylacetate was confirmed by GC-MS. Our results show the importance of this strain in reducing the toxic effects of xanthene in the environment and showed for the first time that ring-hydroxylation enzymes and hydrolases for biphenyl degradation in S. yanoikuyae B1 may function on metabolites generated from the degradation pathway of xanthene. By analyzing our results we were able to draw a novel pathway for xanthene degradation in S. yanoikuyae B1DR.
With the recent developments of technology and the advances in artificial intelligent and machine learning techniques, it becomes possible for the robot to acquire and show the emotions as a part of Human-Robot Interaction (HRI). An emotional robot can recognize the emotional states of humans so that it will be able to interact more naturally with its human counterpart in different environments. In this article, a survey on emotion recognition for HRI systems has been presented. The survey aims to achieve two objectives. Firstly, it aims to discuss the main challenges that face researchers when building emotional HRI systems. Secondly, it seeks to identify sensing channels that can be used to detect emotions and provides a literature review
... Show MoreVisible light communication (VLC) is an upcoming wireless technology for next-generation communication for high-speed data transmission. It has the potential for capacity enhancement due to its characteristic large bandwidth. Concerning signal processing and suitable transceiver design for the VLC application, an amplification-based optical transceiver is proposed in this article. The transmitter consists of a driver and laser diode as the light source, while the receiver contains a photodiode and signal amplifying circuit. The design model is proposed for its simplicity in replacing the trans-impedance and transconductance circuits of the conventional modules by a simple amplification circuit and interface converter. Th
... Show MorePurpose: The concept of complete street is one of the modern trends concerned with diversifying means of transportation and reducing the disadvantages of mechanical transportation modes. This paper discusses the role of complete streets can play in developing the urban environment in the Alyarmok District of Baghdad. Method/design/approach: The linear regression method used to analyze the opinions of 100 respondents surveyed in the study area in order to find the relationship between the urban environment and the complete street elements. Theoretical framework: The Modern trends in urban planning aim to find alternatives to the policies of traditional transportation planning that focus on vehicular mobi
... Show MoreThe aim of this work is to design an algorithm which combines between steganography andcryptography that can hide a text in an image in a way that prevents, as much as possible, anysuspicion of the hidden textThe proposed system depends upon preparing the image data for the next step (DCT Quantization)through steganographic process and using two levels of security: the RSA algorithm and the digitalsignature, then storing the image in a JPEG format. In this case, the secret message will be looked asplaintext with digital signature while the cover is a coloured image. Then, the results of the algorithmare submitted to many criteria in order to be evaluated that prove the sufficiency of the algorithm andits activity. Thus, the proposed algorit
... Show MoreKE Sharquie, AA Noaimi, WK Al-Janabi, Journal of Cosmetics, Dermatological Sciences and Applications, 2013
Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
... Show MoreAbstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS
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