In this investigation, water-soluble N-Acetyl Cysteine Capped-Cadmium Telluride QDs (NAC/CdTe nanocrystals), utilizing N-acetyl cysteine as a stabilizer, were prepared to assess their potential in differentiating between DNA extracted from pathogenic bacteria (e.g. Escherichia coli isolated from urine specimen) and intact DNA (extracted from blood of healthy individuals) for biomedical sensing prospective. Following the optical characterization of the synthesized QDs, the XRD analysis illustrated the construction of NAC-CdTe-QDs with a grain size of 7.1 nm. The prepared NAC-CdTe-QDs exhibited higher PL emission features at of 550 nm and UV-Vis absorption peak at 300 nm. Additionally, the energy gap quantified via PL and UV–Vis were 2.2 eV and 2.3 eV, respectively. The interconnection between the synthesized QDs and the different types of the extracted genomic DNA (both Escherichia coli and healthy subjects) was analyzed optically. This is resulted in a clear shift in the maximum fluorescence emission intensities (observed at 533 nm for an Escherichia coli DNA and 541 for healthy DNA). Overall, the present study findings suggest that prepared QDs could be employed as probes for the detection of pathogenic bacteria DNA from that of healthy subjects.
Current study was carried out to determine the adsorption ability of the Multiwall carbon nanotubes (MWCNTs) by adsorption Malachite Green dye from an aqueous solution. Crystal structure of the materials was measured using powder X-rays diffraction (PXRD), UV–Vis diffuse reflectance and specific surface area (BET). Many parameters that affecting the adsorption process such as contact time, pH, adsorbent dosage, initial dye concentration and temperature were studied. The outcome showed that an increasing occurred in the adsorbent dosage and the rate of dye removal, and the best efficiency for Malachite Green dye removal was amounted 99. 11 %. The results were obtained at optimal reaction conditions were pH = 5.5, cata
... Show MoreIn general, path-planning problem is one of most important task in the field of robotics. This paper describes the path-planning problem of mobile robot based on various metaheuristic algorithms. The suitable collision free path of a robot must satisfies certain optimization criteria such as feasibility, minimum path length, safety and smoothness and so on. In this research, various three approaches namely, PSO, Firefly and proposed hybrid FFCPSO are applied in static, known environment to solve the global path-planning problem in three cases. The first case used single mobile robot, the second case used three independent mobile robots and the third case applied three follow up mobile robot. Simulation results, whi
... Show MoreThis investigation proposed an identification system of offline signature by utilizing rotation compensation depending on the features that were saved in the database. The proposed system contains five principle stages, they are: (1) data acquisition, (2) signature data file loading, (3) signature preprocessing, (4) feature extraction, and (5) feature matching. The feature extraction includes determination of the center point coordinates, and the angle for rotation compensation (θ), implementation of rotation compensation, determination of discriminating features and statistical condition. During this work seven essential collections of features are utilized to acquire the characteristics: (i) density (D), (ii) average (A), (iii) s
... Show MoreThis paper proposes a new structure for a Fractional Order Sliding Mode Controller (FOSMC) to control a Twin Rotor Aerodynamic System (TRAS). The new structure is composed by defining two 3-dimensional sliding mode surfaces for the TRAS model and introducing fractional order derivative integral in the state variables as well as in the control action. The parameters of the controller are determined so as to minimize the Integral of Time multiplied by Absolute Error (ITAE) performance index. Through comparison, this controller outperforms its integer counterpart in many specifications, such as reducing the delay time, rise time, percentage overshoot, settling time, time to reach the sliding surface, and amplitude of chattering in control inpu
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreIn order to save natural resources, recycling necessarily becomes a top priority for all of us, to save exhaustible resources, produce green energy and preserve the environment.
In this perspective, we are trying to valorize a waste of animal origin, largely neglected by the actors of materials, through an industrial transformation into a biological charge to make new sustainable bio-composite materials.
Using a tensile test bench, we try to mechanically characterize this biomaterial of renewable resources that, unlike eco-composites, has been neglected by the material actors.
Obtained from waste, with a high recycling potential and from renewable resources, the bio-charge to be analyzed will be injected, later in different poly