Enhanced anti-biofilm activity of facile synthesized silver oxide nanoparticles against K. pneumoniae

Journal of Inorganic and Organometallic Polymers and Materials - The silver oxide nanoparticle was successfully synthesized using floral waste by simple one pot, cost effective method. The complete...     

Experimental study on the compressive resistance of stress-relieved solid round steel members

The Canadian Standard for Antenna Towers and Antenna Supporting Structures, CSA-S37-01, specifies expressions for the compressive resistance of solid rounds based on the Structural Stability Research Council (SSRC) Column Curves for non-solid-round members and the results from experimental investigations on the compressive resistance of solid rounds carried out back to 1965. Similar Standard in USA (TIA/EIA-222-G.0) specifies design criteria for such members as derived from the superseded AISC-LRFD-94 Standard, which is independent of the shape of the member cross-section. The European Standard, Eurocode 3, provides column curves for the compressive resistance of various structural steel members, and assumes the applicability of one of them to solid rounds. As such, it is necessary to conduct an experimental study on solid round stress-relieved steel members to refine the available design equations for such members. This paper provides a summary of the literature review on solid rounds as well as a recent test program conducted on stress-relieved steel solid rounds. Correlation between the results from these tests and the current practice for the design of solid rounds is investigated. The paper concludes with a proposed compressive resistance equation for economical design of such members.     

Compact high-pulse-energy ultraviolet laser source for ozone lidar measurements

An all solid-state Ti:sapphire laser differential absorption lidar transmitter was developed. This all-solid-state laser provides a compact, robust, and highly reliable laser transmitter for potential application in differential absorption lidar measurements of atmospheric ozone. Two compact, high-energy-pulsed, and injection-seeded Ti:sapphire lasers operating at a pulse repetition frequency of 30 Hz and wavelengths of 867 and 900 nm, with M2 of 1.3, have been experimentally demonstrated and their properties compared with model results. The output pulse energy was 115 mJ at 867 nm and 105 mJ at 900 nm, with a slope efficiency of 40% and 32%, respectively. At these energies, the beam quality was good enough so that we were able to achieve 30 mJ of ultraviolet laser output at 289 and 300 nm after frequency tripling with two lithium triborate nonlinear crystals.     

Disposition of the flavonoid quercetin in rats after single intravenous and oral doses

The pharmacokinetic and mean time tissue distribution parameters, after a single 50-mg/kg dose of quercetin administered as intravenous bolus, oral solution, and oral suspension, were determined using rat as an animal model. Following intravenous administration, the elimination rate constant and the elimination half-life were found to be 0.0062 min^-1 and 111 min, respectively. Examining the mean time tissue distribution parameters reflected a strong binding affinity of the drug molecules to both plasma and tissue proteins. In addition, the low permeability rate of drug molecules in the peripheral system was demonstrated. Following the oral administration of the drug, the extent of absorption was greater from solution than from suspension. Moreover, the solution showed a shorter T_max and a higher C_max than suspension. The absolute bioavailability for the solution was 0.275 and that for suspension was 0.162. The mean residence time (MRT) and the mean absorption time (MAT) were higher for suspension, reflecting the need for dissolving the drug in order to be absorbed. The mean (in-vivo) dissolution time (MDT_in-vivo) was 34.5 min. Thus, an oral quercetin formulation that can readily form a drug solution in the gastrointestinal tract may enhance the absorption of the drug.     

Analysis of deformations and stresses in balanced and unbalanced adhesively bonded single-strap joints

Adhesively bonded joints are increasingly being used in joining various structural components. Adequate understanding of the behaviour of adhesively bonded joints is necessary to ensure efficiency, safety and reliability of such joints. While several joint configurations, such as the single- and double-lap joints have received considerable consideration, the single-strap joint configuration has received little attention, partly because earlier studies have shown it to be the least efficient.

One of the objectives of this paper is to demonstrate that strap joints can be as efficient as lap joints, as long as they are properly designed. This will be done through a detailed analytical investigation into influence of the parameters that govern peak stresses in the adhesive. The next objective is to produce simple equations by which the design of strap joint could be facilitated in an effective manner. For this, the developed analytical expressions are simplified and shown to provide accurate results. The derived solutions provide better insight into understanding the parameters that most influence the edge forces.     

Direct adaptive neural network controller for a class of nonlinear systems based on fuzzy estimator of the control error

A new approach of direct adaptive control of single input single output nonlinear systems in affine form using single-hidden layer neural network (NN) is introduced. In contrast to the algorithms in the literature, the weights adaptation laws are based on the control error and not on the tracking error or its filtered version. Since the control error is being expressed in terms of the NN controller, hence its weights updating laws are obtained via back-propagation concept. A fuzzy inference system (FIS) with heuristically defined rules is introduced to provide an estimate of this error based on the past history of the system behaviour. The stability of the closed loop is studied using Lyapunov theory. A fixed structure is then proposed for the FIS and the design parameters reduce to the parameters of the NN. The method is reproducible and does not require any pre-training of the network weights.     

Nonlinear generalized equations of motion for multi-link inverted pendulum systems

In this paper, the equations of motion for a general multi-link inverted pendulum system are derived. Assumptions previously employed to simplify such formulation are removed. The pendulum system is more general and includes nonlinear friction terms to suit various engineering applications. The generalized equations are first developed in the absolute coordinate system using Lagrange's technique, then a simple linear transformation is proposed to obtain the set of nonlinear equations in the DevanitHartenberg coordinate system. The equations of motion for double and triple link inverted pendulum systems are given as examples for such dynamics equations.     

The role of porous media in modeling flow and heat transfer in biological tissues

Flow and heat transfer in biological tissues are analyzed in this investigation. Pertinent works are reviewed in order to show how transport theories in porous media advance the progress in biology. The main concepts studied in this review are transport in porous media using mass diffusion and different convective flow models such as Darcy and the Brinkman models. Energy transport in tissues is also analyzed. Progress in development of the bioheat equation (heat transfer equation in biological tissues) and evaluation of the applications associated with the bioheat equation are analyzed. Prominent examples of diffusive applications and momentum transport by convection are discussed in this work. The theory of porous media for heat transfer in biological tissues is found to be most appropriate since it contains fewer assumptions as compared to different bioheat models. A concept that is related to flow instabilities caused by swimming of microorganisms is also discussed. This concept named bioconvection is different from blood convection inside vessels. The works that consider the possibility of reducing these flow instabilities using porous media are reviewed.     

Speech emotion recognition using optimized genetic algorithm-extreme learning machine

Multimedia Tools and Applications - Automatic Emotion Speech Recognition (ESR) is considered as an active research field in the Human-Computer Interface (HCI). Typically, the ESR system is...     

Recognizing arabic handwritten characters using deep learning and genetic algorithms

Automated techniques for Arabic content recognition are at a beginning period contrasted with their partners for the Latin and Chinese contents recognition. There is a bulk of handwritten Arabic archives available in libraries, data centers, historical centers, and workplaces. Digitization of these documents facilitates (1) to preserve and transfer the country’s history electronically, (2) to save the physical storage space, (3) to proper handling of the documents, and (4) to enhance the retrieval of information through the Internet and other mediums. Arabic handwritten character recognition (AHCR) systems face several challenges including the unlimited variations in human handwriting and the leakage of large and public databases. In the current study, the segmentation and recognition phases are addressed. The text segmentation challenges and a set of solutions for each challenge are presented. The convolutional neural network (CNN), deep learning approach, is used in the recognition phase. The usage of CNN leads to significant improvements across different machine learning classification algorithms. It facilitates the automatic feature extraction of images. 14 different native CNN architectures are proposed after a set of try-and-error trials. They are trained and tested on the HMBD database that contains 54,115 of the handwritten Arabic characters. Experiments are performed on the native CNN architectures and the best-reported testing accuracy is 91.96%. A transfer learning (TF) and genetic algorithm (GA) approach named “HMB-AHCR-DLGA” is suggested to optimize the training parameters and hyperparameters in the recognition phase. The pre-trained CNN models (VGG16, VGG19, and MobileNetV2) are used in the later approach. Five optimization experiments are performed and the best combinations are reported. The highest reported testing accuracy is 92.88%.