Bimetallic Zn/Ag doped polyurethane spider net composite nanofibers: A novel multipurpose electrospun mat

The objective of this study was to develop a new class of bimetallic ZnO/Ag embedded polyurethane multi-functional nanocomposite by a straightforward approach. Bimetallic nanomaterials, composed of two unlike metal elements, are of greater interest than the monometallic materials because of their improved characteristics. In the present study the bimetallic composite was prepared using sol–gel via the facile electrospinning technique. The utilized sol–gel was composed of zinc oxide, silver and poly(urethane). The physicochemical properties of as-spun composite mats were determined by X-ray diffraction pattern, field emission scanning electron microscopy, energy dispersive X-ray spectroscopy and transmission electron microscopy. The antibacterial activity was tested using Escherichia coli as model organism. The antibacterial test showed that ZnO:Ag/polyurethane composite possesses superior antimicrobial activity than pristine PU and ZnO/PU hybrids. Furthermore, our results illustrate that the synergistic effect of ZnO and Ag resulted in the advanced antimicrobial action of bimetallic ZnO/Ag composite mat. The viability and proliferation properties of NIH 3T3 mouse fibroblast cells on the ZnO:Ag/polyurethane composite nanofibers were analyzed by in vitro cell compatibility test. Our results indicated the non-cytotoxic behavior of bimetallic ZnO:Ag/polyurethane nanofibers towards the fibroblast cell culture. In summary, novel ZnO:Ag/polyurethane composite nanofibers which possess large surface to volume ratio with excellent antimicrobial activity were fabricated. The unique combination of ZnO and Ag nanoparticles displayed potent bactericidal effect due to a synergism. Hence the electrospun bimetallic composite indicates the huge potential in water filtration, clinical and biomedical applications.     

Multi-reservoir Operation Rules: Multi-swarm PSO-based Optimization Approach

Reservoir operation rules are intended to help an operator so that water releases and storage capacities are in the best interests of the system objectives. In multi-reservoir systems, a large number of feasible operation policies may exist. System engineering and optimization techniques can assist in identifying the most desirable of those feasible operation policies. This paper presents and tests a set of operation rules for a multi-reservoir system, employing a multi-swarm version of particle swarm optimization (MSPSO) in connection with the well-known HEC-ResPRM simulation model in a parameterization–simulation–optimization (parameterization SO) approach. To improve the performance of the standard particle swarm optimization algorithm, this paper incorporates a new strategic mechanism called multi-swarm into the algorithm. Parameters of the rule are estimated by employing a parameterization–simulation–optimization approach, in which a full-scale simulation model evaluates the objective function value for each trial set of parameter values proposed with an efficient version of the particle swarm optimization algorithm. The usefulness of the MSPSO in developing reservoir operation policies is examined by using the existing three-reservoir system of Mica, Libby, and Grand Coulee as part of the Columbia River Basin development. Results of the rule-based reservoir operation are compared with those of HEC-ResPRM. It is shown that the real-time operation of the three reservoir system with the proposed approach may significantly outperform the common implicit stochastic optimization approach.     

A robust unified approach to analyzing methylation and gene expression data

Microarray technology has made it possible to investigate expression levels, and more recently methylation signatures, of thousands of genes simultaneously, in a biological sample. Since more and more data from different biological systems or technological platforms are being generated at an incredible rate, there is an increasing need to develop statistical methods that are applicable to multiple data types and platforms. Motivated by such a need, a flexible finite mixture model that is applicable to methylation, gene expression, and potentially data from other biological systems, is proposed. Two major thrusts of this approach are to allow for a variable number of components in the mixture to capture non-biological variation and small biases, and to use a robust procedure for parameter estimation and probe classification. The method was applied to the analysis of methylation signatures of three breast cancer cell lines. It was also tested on three sets of expression microarray data to study its power and type I error rates. Comparison with a number of existing methods in the literature yielded very encouraging results; lower type I error rates and comparable/better power were achieved based on the limited study. Furthermore, the method also leads to more biologically interpretable results for the three breast cancer cell lines.     

PiSHi: click the images and I tell if you are a human

This paper introduces pictorial intelligent system for human identification (PiSHi), an image-based captcha which uses three human cognitive abilities to distinguish humans from machines. The first is the human ability to easily recognise the image’s upright orientation. The second is the human brain’s ability in recognising a picture’s content when it is only partially visible. And the third is the human ability in unconscious decision making when encountering pictorial challenges. This work models such complicated human patterns in problem solving for the first time. In order to extract these behavioural patterns and save them in a pattern database, we have implemented our own captcha and performed a series of experiments. PiSHi’s interface presents the user with a set of distorted pictures and asks her to click on the upright orientation of all the pictures in any preferred order. Next, it captures the user’s interaction patterns, compares them with the ones saved in the pattern database, and grants her a corresponding credit. Based on this credit, the user either passes or fails the test, and participates in updating the picture database. Our experiments indicate that human users can solve our proposed captcha effectively—with an accuracy of 99.44 %. Besides, our proposed system is secure against several types of attacks including random guessing and reverse image search engines. The results offer the possibility of utilising the identified human behavioural models in practical captchas.     

Simplified soft value extraction for M-PPM-modulated signals in FSO systems

In the following paper we propose a new approach for extracting soft values from Mth order pulse position modulation (M-PPM). A new low-complexity algorithm is developed, where soft information for each data bit is calculated based on the power received within the PPM time slots. In order to decrease the computational complexity we simplify the calculation of the conditional probability of data vector a given that PPM symbol Y is received. The Monte Carlo simulations applied to analyze the properties of the algorithm for turbo-coded M-PPM transmission in free space optic communication systems show acceptable degradation of system performance with regard to system simplification.     

Accurate analysis of spectral regrowth of nonlinear power amplifier driven by cyclostationary modulated signals

In this paper we present an exact analytical expression to calculate the spectral regrowth at the output of a nonlinear power amplifier (PA) using the higher order cumulants and Poisson summation formula. This PA is driven by the filtered digitally modulated signals. To improve the accuracy of the calculations, the cyclosationarity of the input signal is considered. Moreover, closed-form expressions for the 1-dB compression and saturation points are extracted as a function of the PA model parameters, higher order statistics of the input signal, and the transfer function of the pulse shaping filter. In addition, an analytical expression for the adjacent channel power (ACP) and a closed-form expression of the ACP ratio are derived. This is followed by investigation of the effect of the PA nonlinearity on the performance of receiver. Simulation studies are carried out to verify the accuracy of the derived expressions. Excellent agreement between the analytical and simulation results is achieved.     

An integrated supervised learning solution for monitoring process mean vector

When an out-of-control condition is detected by a control chart, a search begins to identify and eliminate the source(s) of the signal. Identification of the time when a process first changed is an important step in root cause analysis which helps a process engineer to eliminate the source(s) of assignable cause effectively. The time when a change takes place in the process is referred to as the change point. In multivariate environment, since there is more than one variable involved, then root cause analysis is relatively harder compared to the case of univariate because it is not clear exactly which variable has contributed to the out-of-control condition and in what direction its mean has shifted. Hence, a procedure that identifies the change point, performs diagnostic analysis, and specifies the direction of the shift in the mean of the contributing variable(s) all simultaneously could help to conduct root cause analysis effectively. Although different multivariate methods exist in the literature that allow to either estimate change point in the process mean vector or identify the contributing variables leading to the out-of-control condition, but in this research, an integrated supervised learning solution is proposed, which helps to (1) detect of an out-of-control condition, (2) identify the change point leading to shift in the mean vector, (3) specify the variable(s) contributing to the out-of-condition, and (4) identify the direction of the shift in the mean of each contributing variable simultaneously. A real case study is used to evaluate and compare the performance of the proposed integrated approach to existing methods in the literature.     

Natural Vibrations of Open-Variable Thickness Circular Cylindrical Shells in High Temperature Field

The feasibility of using the transfer matrix method (TMM) to analyze open-variable thickness circular cylindrical shells exposed to a high-temperature field is explored theoretically. In the approach to the problem, the thermal degradation (TG) of thermoelastic characteristics of the material is considered. Natural frequencies and mode shapes for the cylindrical shells are investigated in detail by combining the vibration theory with the TMM. The governing equations of vibration for this system are expressed by the matrix differential equations, and the coefficient matrices are derived. After the relationship between the transfer matrix and the coefficient matrix is established, the fourth-order Runge-Kutta method is used numerically to solve the matrix equation. Once the transfer matrix of single component has been obtained, the product of each component matrix can compose the matrix of the entire structure. The frequency equations and mode shape are formulated in terms of the elements of the structural matrices. Finite-element numerical simulation has validated the present formulas of natural frequencies. Numerical illustrations, supplying pertinent information on the implications of the TG, are presented for various curvatures, aspect ratios, boundary conditions, and thickness ratios, and the pertinent conclusions are outlined.     

Preparation and properties of probiotic concentrated yoghurt (labneh) fortified with conjugated linoleic acid

Milk of high conjugated linoleic acid (CLA) level (1.25 g per 100 g milk fat) was produced by inclusion of fish oil and rousted soy bean in the ration of Holstein cows as compared to 0.55 g per 100 g milk fat in the milk of animals receiving control diet. Milk of normal (control) and high CLA content (treatment) was spray‐dried. Labneh was made from 20 g L^?1 reconstituted milk using 3 mL per 100 mL yoghurt starter and 2 mL per 100 mL of probiotic cultures of Lactobacillus casei or Lactobacillus acidophilus. The control (C) and high CLA (T) labneh were analysed chemically and microbiologically, and their viscosities were determined during cold storage for 15 days. The fat content of labneh of high CLA was less than that of the control, but the total solids (TS) were unaffected by the CLA level. Labneh made with Lb. acidophilus had lower TS and higher acidity, exopolysaccharides and acetaldehyde contents and viscosity than that made with the use of Lb. casei. Labneh from the different treatments retained high counts of the added probiotic (>10⁸ cfu g^?1) throughout the storage period. The storage period had significant effects on all parameters determined.