The present study aims to detection optimal conditions of production of amylase enzyme from isolate of B. subtillis A4. Nine carbonic sources were represented by starch, maltose, fructose, sucrose, glucose, arabinose, xylose, sorbitol and mannitol) at concentration of 1% for each source. It was found that the best was represented by starch carbonic, which showed higher activity and qualitative activity of 7.647 Unit/ ml and 461.56 Unit/ mg. Ten nitrogen sources were selected, including yeast extract, peptone, trypton, gelatin, urea and meat extract as organic sources Ammonium sulphate, Sodium nitrate, Potassium nitrate and Ammonium chloride as inorganic sources. These sources were added at aconcentration of 0.5% to the production medium. Th

This experiment was carried out at the Grdarash field belongs to the Agricultural researches directorate/general Agriculture directorate-Erbil in September (2007)، 27 Arabic lambs aged (5-6 months) With average initial weight (39.178 Kg/lamb) were used. Lambs were divided in to (3) groups (9 lambs/group). Control group was fed on (85% barely، 10% bran and 5% straw)، and second and third groups were fed on various by-product in replacement with barely in loss and block shape respectively.

The total gain of three groups were (392708.32، 634826.52 & 445613.72 ID resp

Objective: Evaluate the effects of different storage periods on flexural strength (FS) and degree of conversion (DC) of Bis-Acryl composite and Urethane dimethacrylate provisional restorative materials. Material and Methods: A total of 60 specimens were prepared from four temporary crown materials commercially available and assigned to four tested groups (n = 15 for each group): Prevision Temp, B&E CROWN, Primma Art, and Charm Temp groups. The specimens were stored in artificial saliva, and the FS was tested after 24 h, 7 d, and 14 d. A standard three-point bending test was conducted using a universal testing machine. Additionally, the DC was determined using a Fourier transform infrared spectroscopy (FTIR) device. The data were analyzed st

Comparison is the most common and effective technique for human thinking: the human mind always judges something new based on its comparison with similar things that are already known. Therefore, literary comparisons are always clear and convincing. In our daily lives, we are constantly forced to compare different things in terms of quantity, quality, or other aspects. It is known that comparisons are used in literature in order for speech to be clear and effective, but when these comparisons are used in everyday speech, it is in order to convey the meaning directly and quickly, because many of these expressions used daily are comparisons. In our research, we discussed this comparison as a means of metaphor and expression in Russia

Recently, wireless charging based RF harvesting has interfered our lives [1] significantly through the different applications including biomedical, military, IoT, RF energy harvesting, IT-care, and RFID technologies. Wirelessly powered low energy devices become significantly essential for a wide spectrum of sensing applications [1]. Such devices require for low energy resources from sunlight, mechanical vibration, thermal gradients, convection flows or other forms of harvestable energy [2]. One of the emerging power extraction resources based on passive devices is harvesting radio frequency (RF) signals powers [3]–[5]. Such applications need devices that can be organized in very large numbers, so, making separate node battery impractical.

Internet paths sharing the same congested link can be identified using several shared congestion detection techniques. The new detection technique which is proposed in this paper depends on the previous novel technique (delay correlation with wavelet denoising (DCW) with new denoising method called Discrete Multiwavelet Transform (DMWT) as signal denoising to separate between queuing delay caused by network congestion and delay caused by various other delay variations. The new detection technique provides faster convergence (3 to 5 seconds less than previous novel technique) while using fewer probe packets approximately half numbers than the previous novel technique, so it will reduce the overload on the network caused by probe packets.

          The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed