Rotation Rate of Particle Pairs in Homogeneous Isotropic Turbulence

Understanding the dynamics of particles in turbulent flow is important in many environmental and industrial applications. In this paper, the statistics of particle pair orientation is numerically studied in homogeneous isotropic turbulent flow, with Taylor microscale Reynolds number of 300. It is shown that the Kolmogorov scaling fails to predict the observed probability density functions (PDFs) of the pair rotation rate and the higher order moments accurately. Therefore, a multifractal formalism is derived in order to include the intermittent behavior that is neglected in the Kolmogorov picture. The PDFs of finding the pairs at a given angular velocity for small relative separations reveals extreme events with stretched tails and high kurtosis values. Additionally, The PDFs are found to be less intermittent and follow a complementary error function distribution for larger separations.Comment: 16 pages, 3 figures, accepted for publication in European Journal of Mechanics / B Fluid

Towards Real-World BCI: CCSPNet, A Compact Subject-Independent Motor Imagery Framework

A conventional subject-dependent (SD) brain-computer interface (BCI) requires a complete data-gathering, training, and calibration phase for each user before it can be used. In recent years, a number of subject-independent (SI) BCIs have been developed. However, there are many problems preventing them from being used in real-world BCI applications. A weaker performance compared to the subject-dependent (SD) approach, and a relatively large model requiring high computational power are the most important ones. Therefore, a potential real-world BCI would greatly benefit from a compact low-power subject-independent BCI framework, ready to be used immediately after the user puts it on. To move towards this goal, we propose a novel subject-independent BCI framework named CCSPNet (Convolutional Common Spatial Pattern Network) trained on the motor imagery (MI) paradigm of a large-scale electroencephalography (EEG) signals database consisting of 21600 trials for 54 subjects performing two-class hand-movement MI tasks. The proposed framework applies a wavelet kernel convolutional neural network (WKCNN) and a temporal convolutional neural network (TCNN) in order to represent and extract the diverse spectral features of EEG signals. The outputs of the convolutional layers go through a common spatial pattern (CSP) algorithm for spatial feature extraction. The number of CSP features is reduced by a dense neural network, and the final class label is determined by a linear discriminative analysis (LDA) classifier. The CCSPNet framework evaluation results show that it is possible to have a low-power compact BCI that achieves both SD and SI performance comparable to complex and computationally expensive.Comment: 15 pages, 6 figures, 6 tables, 1 algorith

Effect of Acid-Base Balance on Cytokines Serum Levels and Short-Term Outcomes in Kidney Transplant Recipients; a Randomized Clinical Trial

Background: Control of blood acids and bases can help prevent many potentially life-threatening disorders in end stage renal disease (ESRD) patients. Aim of this study was to assess the effect of acid-base balance on cytokines serum levels and short-term outcomes in kidney transplant recipients.Materials and Methods: In this randomized clinical trial study, 40 patients with end-stage renal disease aged 18 to 70 who had undergone a kidney transplant from a living donor in Modarres hospital during 2016-2017 were included. The primary outcomes measured in this study were sera levels of cytokine such as IL-2, IL-10, IFN-γ and BUN and Cr serum after the treatment of acidosis in kidney transplant recipients.Results: Mean±SD of the patient’s age was 42±12.6 years. Results showed that there is a significant difference in means of IL-2, IL-10, and IFN-γ between the intervention and control groups over the time (for all p<0.05). We also found that correction of acidosis occurred with reduces of IFN-γ to -1.74 in the intervention group compared to the group receiving saline (P=0.011); and reduction for IL-2 was -1.37 (p=0.025). The concentration of anti-inflammatory cytokine of IL-10 was increased to 2.85 (P<0.001).Conclusion: The results clearly suggest that correction of acidosis in renal transplant patients during surgery helps improve the performance of allograft in the short run; however, more studies are recommended, taking into account the long-term and short-term effects of this intervention.Keywords: Cytokines, Kidney Transplantation, Acid-Base Balance, Randomized Controlled Tria

PV Maximum Power-Point Tracking by Using Artificial Neural Network

In this paper, using artificial neural network (ANN) for tracking of maximum power point is discussed. Error back propagation method is used in order to train neural network. Neural network has advantages of fast and precisely tracking of maximum power point. In this method neural network is used to specify the reference voltage of maximum power point under different atmospheric conditions. By properly controling of dc-dc boost converter, tracking of maximum power point is feasible. To verify theory analysis, simulation result is obtained by using MATLAB/SIMULINK

The Harmful Impacts of Microplastics in the Marine Environment- A Review

Microplastics as emerging and unfamiliar contaminants have been considered by researchers during the last decades. These small particles and fragments, typically have a size less than 5 mm and could penetrate into the marine environments by different ways, threatening the environment and animal health. Therefore, in this study, according to the studies by different researchers, this pollutant is introduced and some of its effects are mentioned in marine environments. One impacts of microplastics on marine organisms, such as marine vertebrates and invertebrates, arise from direct ingestion of plastic fragmentS by the marine biota leading into internal injuries. They also can have negative effects on the distribution of certain species of marine organisms, which they oviposit on the surface of these contaminants. Chemical adsorption is the most important impact of microplastics in marine environments, which not only transfers pollution, but also increases environmental resistance of these contaminants. Recent research works on the effects of microplastics pollution in the marine environment emphesis that permanent and continous monitoring of these materials and discovery of the pollution hotspots is crucial in environmental issues

Electrically doped nanoscale devices using first-principle approach: a comprehensive survey

Doping is the key feature in semiconductor device fabrication. Many strategies have been discovered for controlling doping in the area of semiconductor physics during the past few decades. Electrical doping is a promising strategy that is used for efective tuning of the charge populations, electronic properties, and transmission properties. This doping process reduces the risk of high temperature, contamination of foreign particles. Signifcant experimental and theoretical eforts are demonstrated to study the characteristics of electrical doping during the past few decades. In this article, we frst briefy review the historical roadmap of electrical doping. Secondly, we will discuss electrical doping at the molecular level. Thus, we will review some experimental works at the molecular level along with we review a variety of research works that are performed based on electrical doping. Then we fgure out importance of electrical doping and its importance. Furthermore, we describe the methods of electrical doping. Finally, we conclude with a brief comparative study between electrical and conventional doping methods

Synthesis of carbon nanotube-carbon nanosphere on the CF surface by CVD

In the current work, the synthesis of carbon nanotubes (CNTs) and carbon nanospheres (CNS’s) has been investigated by applying the chemical vapor deposition method in a one-step sample preparation. In this method, iron nitrate non-hydrate (Fe(NO3)3.9H2O) and acetylene (C2H2) have been used as the catalyst source and carbon source, respectively, to grow CNT directly on the CF surface at 700°C and then CNS’s were synthesized on the CNT layers at 900°C under a 250sccm gas flow rate (40%N2, 40%H2, 20% C2H2). According to the SEM and TEM micrographs from the resultant carbon nanoparticles, the diameters of the CNTs and CNS’s have been estimated about 30-50nm and 300-400nm, respectively

QCA based error detection circuit for nano communication network

This paper outlines low power nano-scale circuit design for even parity generator as well as even parity checker circuit using quantum-dot cellular automata (QCA). The proposed even parity generator and even parity checker is achieved by using a new layout of XOR gate. This new XOR gate is much denser and faster than existing ones in the state of the art. The proposed parity generator has out shined the existing design by reducing the cell count as 10proposed parity checker has also out shined the existing design with an improvement in cell count as 17.94circuits are denser and faster than existing one. Nanocommunication architecture with the proposed circuits is also demonstrated. The bit-error coverage by the proposed method is described. Besides, the defects in the circuits are explored to facilitate guide to proper implementation. The tests vectors are proposed to identify the defects in the designs and the defect coverage by those test vector are also described. The estimation of dissipated energy by the layouts established the very low energy dissipation nature of the designs. Different parameters like logic gate, density and latency are utilized to evaluate the designs that demonstrate the faster processing speed at nano-scale

Few-and multi-layer graphene on carbon fibers: synthesis and application

In the current study, we investigated the influences of chemical vapor deposition parameters on the formation of uniform structures of few- and multi-layer graphene (FLG and MLG) as a coating phase on carbon fiber (CF). To this end, the process conditions of the chemical vapor deposition method, such as catalyst concentration, reaction temperature and time, and also carbon source flow rate, were optimized. The resulting FLG and MLG with high yields led to the modification of the CF surface by improving its properties. By applying scanning electronic microscopy, transmission electron microscopy and Raman spectroscopy, the surface morphology and structural information of the G–CF were analyzed. It was observed that under different conditions the FLG–CF and MLG–CF were obtained with 54%, 58% yields and also 10.21 m2 g−1, 8.78 m2 g−1 BET surface areas, respectively. Besides that, the FLG–CF and MLG–CF were used as fillers in the polypropylene (PP) composite and the effects of the number of graphene layers on the mechanical and thermal properties of the composite were analyzed. It is noteworthy to mention, composites based on the CF coated with G with only a few layers presented the highest surface area, strength and thermal resistance compared to those based on multi layers