Ultra-broadband piezoelectric energy harvesting via bistable multi-hardening and multi-softening

Nonlinear Dynamics - An electromechanical coupled distributed parameter model is derived for a broadband piezoelectric energy harvester with nonlinear magnetic interaction and...     

Simulated likelihood inference for stochastic volatility models using continuous particle filtering

Discrete-time stochastic volatility (SV) models have generated a considerable literature in financial econometrics. However, carrying out inference for these models is a difficult task and often relies on carefully customized Markov chain Monte Carlo techniques. Our contribution here is twofold. First, we propose a new SV model, namely SV–GARCH, which bridges the gap between SV and GARCH models: it has the attractive feature of inheriting unconditional properties similar to the standard GARCH model but being conditionally heavier tailed. Second, we propose a likelihood-based inference technique for a large class of SV models relying on the recently introduced continuous particle filter. The approach is robust and simple to implement. The technique is applied to daily returns data for S&P 500 and Dow Jones stock price indices for various spans.     

Birefringence via Doppler broadening and prevention of information hacking

We propose a new scheme for the coherent control of birefringent light pulses propagation in a four-level atomic medium. We modify the splitting of a light pulse by controlling the electric and magnetic responses. The Doppler broadening effect is also noted on the propagation of the birefringent pulses. The dispersions of the birefringence beams are oppositely manipulated for delay and advancement of time at a Doppler width of 10γ. A time gap is created between the birefringence beams, which protects from hacking of information. The time gap is then closed to restore the pulse into the original form by a reverse manipulation of the dispersion of the birefringence beams, i.e., introducing another medium whose transfer function is the complex conjugate of that of the original medium. The results are useful for secure communication technology.     

Graphene and Carbon Nanotube-based Electrochemical Sensing Platforms for Dopamine

Dopamine (DA) is an important neurotransmitter, which is created and released from the central nervous system. It plays a crucial role in human activities, like cognition, emotions, and response to anything. Maladjustment of DA in human blood serum results in different neural diseases, like Parkinson's and Schizophrenia. Consequently, researchers have started working on DA detection in blood serum, which is undoubtedly a hot research area. Electrochemical sensing techniques are more promising to detect DA in real samples. However, utilizing conventional electrodes for selective determination of DA encounters numerous problems due to the coexistence of other materials, such as uric acid and ascorbic acid, which have an oxidation potential close to DA. To overcome such problems, researchers have put their focus on the modification of bare electrodes. The aim of this review is to present recent advances in modifications of most used bare electrodes with carbonaceous materials, especially graphene, its derivatives, and carbon nanotubes, for electrochemical detection of DA. A brief discussion about the mechanistic phenomena at the electrode interface has also been included in this review.     

Experimental investigation and optimization of loop heat pipe performance with nanofluids

Journal of Thermal Analysis and Calorimetry - High heat generation from electronic devices needs to cool down properly to prevent overheating. Loop heat pipe (LHP) is one of the excellent cooling...     

Computational study on the effects of variable viscosity of micropolar liquids on heat transfer in a channel

Journal of Thermal Analysis and Calorimetry - A numerical model is developed to study the effects of temperature-dependent viscosity on heat transfer in magnetohydrodynamic flow of micropolar fluid...     

Purification of low-abundance lysozyme in egg white via free-flow electrophoresis with gel-filtration chromatography

As an effective separation tool, free-flow electrophoresis has not been used for purification of low-abundance protein in complex sample matrix. Herein, lysozyme in complex egg white matrix was chosen as the model protein for demonstrating the purification of low-content peptide via an FFE coupled with gel fitration chromatography (GFC). The crude lysozyme in egg while was first separated via free-flow zone electrophoresis (FFZE). After that, the fractions with lysozyme activity were condensed via lyophilization. Thereafter, the condensed fractions were further purified via a GFC of Sephadex G50. In all of the experiments, a special poly(acrylamide- co-acrylic acid) (P(AM-co-AA)) gel electrophoresis and a mass spectrometry were used for identification of lysozyme. The conditions of FFZE were optimized as follows: 130 μL/min sample flow rate, 4.9 mL/min background buffer of 20 mM pH 5.5 Tris-Acetic acid, 350 V, and 14 °C as well as 2 mg/mL protein content of crude sample. It was found that the purified lysozyme had the purity of 80% and high activity as compared with its crude sample with only 1.4% content and undetectable activity. The recoveries in the first and second separative steps were 65% and 82%, respectively, and the total recovery was about 53.3%. The reasons of low recovery might be induced by diffusion of lysozyme out off P(AM-co-AA) gel and co-removing of high-abundance egg ovalbumin. All these results indicated FFE could be used as alternative tool for purification of target solute with low abundance.