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1 Fluidic mechanism for dual-axis gyroscope 2018-02-19             

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Publication date: August 2018
Source:Mechanical Systems and Signal Processing, Volume 108

Author(s): Van Thanh Dau, Thien Xuan Dinh, Canh Dung Tran, Phong Nhu Bui, Du Dinh Vien, Hoa Thanh Phan

In this paper, we report a further study of flow-network generating four jet flows which circulate in a sealed device to experimentally investigate the feasibility and efficiency of a dual-axis gyroscope. The experiment is carried out successfully and the experimental results reasonably agreed with those obtained by numerical analysis using OpenFOAM. The flow rectifying coefficient is determined using the mathematical lump model for a vibrating system, which takes into account of the device geometry and resonant frequency. Experimental and numerical results demonstrate that the coefficient of the new system developed in this study is significantly higher than those of conventional designs. The hotwire-integrated device which can function as a dual-axis gyroscope is tested using a turntable with speeds up to 1900 rpm. The scale factor and cross-sensitivity of the system are 0.26 μV s/° and 1.2%, respectively. The cross-sensitivity and the effects of linear acceleration, actuating voltage on the diaphragm, heating power and position of hotwires are also investigated.





2 Supervised machine learning scheme for electromyography-based pre-fall detection system 2018-02-17             

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Publication date: 15 June 2018
Source:Expert Systems with Applications, Volume 100

Author(s): Gabriele Rescio, Alessandro Leone, Pietro Siciliano

Falls are the leading cause of disability and death among the elderly. Over the years, several inertial-based wearable devices for automatic fall and pre-fall detection have been devised. Under controlled condition, these systems show a high performance for unbalance detection (up to 100% of specificity and sensitivity), however the mean lead time before the impact is about 200–400 ms. Although this period of time is enough to active an impact reduction system (i.e wearable airbag) to minimize injury, it is necessary to increase it so as to improve the system efficiency and reliability. A user's muscle behavior analysis could be more strategic than that of a kinematic evaluation one, permitting a rapid recognition of an imbalance event. This also holds true for several research studies on muscles response during a state of imbalance, whereas a limit number of them deal with the development of wearable electromyography (EMG)-based systems for human imbalance detection, suitable for predicting a lack of balance in real time. With respects these limitations, the main purpose of this work has been the development of a low computational cost expert system for real time and automatic fall risk detection. The analysis of this is achieved through lower limb muscles behavior monitoring. A Machine Learning scheme has been chosen in order to overcome the well-known drawbacks of threshold approaches widely used in pre-fall systems, in which the algorithm parameters have to be set according to the users’ specific physical characteristics. Ten kinds of time-domain features, commonly used in the analysis of the lower-limb muscle activity, have been investigated. With a view to reducing the processing complexity, the Markov Random Field (MRF) based Fisher-Markov feature selector was tested. It showed a high degree of accuracy in the EMG-based features selection for lack of balance detection. The Co-Contraction Index, Integrated EMG and Willison Amplitude features have been also considered. The supervised classification phase has been obtained through a low computational cost and a high classification accuracy level Linear Discriminant Analysis. The developed system shows high performance in terms of sensitivity and specificity (about 90%) in controlled conditions, with a mean lead-time before the impact of about 775 ms. Therefore, the feasibility of a quick and wearable surface EMG-based unbalance detection system, by using Machine Learning methodology, has been demonstrated. The system may recognize a fall event during the initial phase, increasing the decision making time and minimizing the incorrect and inappropriate activations of the protection system, in real life scenario.





3 Zinc oxide nanotetrapods with four different arm morphologies for versatile nanosensors 2018-02-17             

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Publication date: 1 June 2018
Source:Sensors and Actuators B: Chemical, Volume 262

Author(s): Ingo Paulowicz, Vasile Postica, Oleg Lupan, Niklas Wolff, Sindu Shree, Ala Cojocaru, Mao Deng, Yogendra Kumar Mishra, Ion Tiginyanu, Lorenz Kienle, Rainer Adelung

The structural morphology of metal oxide nano- and microstructures plays a crucial role in the performances of sensors and especially of nanosensors. Here, a simple approach on the synthesis of three-dimensional (3D) highly porous ZnO nano- and microstructure networks with four different arm morphologies in the same process is reported. Systematic studies about the growth of micro- and nanotetrapods were performed and the corresponding mechanism has been discussed in detail. The difference in the morphologies of the obtained structures was understood on the basis of synthesis temperature variations, content of Zn vapor and oxygen in the furnace at different locations, which result in different growth rates along the ZnO c-axis. The approach developed in this work gives the possibility to simultaneously grow the interconnected networks of nano-ZnO-tetrapods (T), ZnO-T, with complex arm morphologies, ZnO-T-nanosheets, and ZnO nanowires (NW)-T. The obtained free-standing network material was integrated in an electronic device for gas/vapor sensing investigations. The individual structures with different morphologies (NW with a diameter down to 30 nm, two interconnected NWs, microsheets, and nanotetrapods with a diameter of the arms in the range of 40–80 nm) were integrated into nanosensor devices in order to investigate the influence of the morphology on the electrical and gas sensing properties. The results showed higher (S ≈ 510–2500 ppm) ammonia vapor sensing properties of ZnO-T compared to ZnO-T-nanosheets and ZnO-NW-T, revealing the importance of nano-junctions in nano-sensor devices. The presented approach offers the possibility to understand the importance of exposed facets and junctions on the sensing properties of such nanostructures. These results offer new opportunities for further experimental and fundamental studies of oxide morphologies in the context of nanosensor applications for environmental monitoring.

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4 An integrated micro-chip with Ru/Al2O3/ZnO as sensing material for SO2 detection 2018-02-17             

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Publication date: 1 June 2018
Source:Sensors and Actuators B: Chemical, Volume 262

Author(s): Yingying Liu, Xinyue Xu, Ying Chen, Yuan Zhang, Xinghua Gao, Pengcheng Xu, Xinxin Li, Jianhui Fang, Weijia Wen

SO2 sensor is highly demanded in the application fields such as environmental protection and food manufactory. Herein, an integrated microsensor is developed for SO2 gas detection. For the fabrication of microsensor, ZnO nanosheets sensing material is firstly loaded onto the sensing area of the microsensor by using inkjet printing technology. Then, Al2O3 loaded with Ru nanoparticles (Ru/Al2O3) as catalyst are locally deposited onto the surface of ZnO nanosheets layer. Gas sensing performance measurements indicate that the fabricated microsensor exhibits a selective response to SO2, and a good linear relationship in the range of 5–115 ppm SO2 gases. Besides, this integrated microsensor has short response and recovery time. On-line mass spectrometry (on-line MS) experiment further reveals the formation of sulfur monoxide (SO) radical as an intermediate product for SO2 sensing. During the sensing process, Ru/Al2O3 as catalyst layer brings SO2 molecules to be broken down into easily detectable species (i.e. SO), and then ZnO nanosheets with abundant gas transport channels capture the produced SO generating output signals. Therefore, this kind of sensing material configuration exploits the advantage of each element, and makes it possible for trace and selective detection of SO2 gas.





5 Multicolorful fluorescent-nanoprobe composed of Au nanocluster and carbon dots for colorimetric and fluorescent sensing Hg2+ and Cr6+ 2018-02-17             

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Publication date: 1 June 2018
Source:Sensors and Actuators B: Chemical, Volume 262

Author(s): Liying Yu, Lingyu Zhang, Guojuan Ren, Shuang Li, Baoya Zhu, Fang Chai, Fengyu Qu, Chungang Wang, Zhongmin Su

In this article, we reported a dual emissive multicolorful fluorescent-nanoprobe which was composed of gold nanocluster (BSA-Au NCs) and carbon dots (CDs) with a certain proportion, i.e. Au NCs-CDs. The dual emissive Au NCs-CDs showed pink fluorescence under UV light, and the dual emission peaks at 625 nm and 444 nm were corresponded to the existence of Hg2+ and Cr6+ respectively. The fluorescence color transformed from pink to blue when in presence of Hg2+. The blue fluorescence emission of CDs selectively quenched by Cr6+, whereas the red fluorescence of BSA-Au NCs was stable against Cr6+, which can be treated as internal reference. The difference response of the two emissions to Hg2+ and Cr6+ resulted in a distinguished fluorescent color change, which can be noticed by the naked eyes clearly. When the Hg2+ and Cr6+ were exposed to the Au NCs-CDs simultaneously, the dual-emission of the Au NCs-CDs were all reduced and exhibited the complete quenching of the pink emission. The detection limits for Hg2+ and Cr6+ were 1.85 nM and 5.34 nM, respectively. Significantly, it was successfully applied to determine the existence of Hg2+ and Cr6+ in real samples, which offered the advantages of simplicity, environmentally friendly and cost saving efficiency.

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6 Fabrication of whole-thermoplastic normally closed microvalve, micro check valve, and micropump 2018-02-17             

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Publication date: 1 June 2018
Source:Sensors and Actuators B: Chemical, Volume 262

Author(s): Adel Pourmand, Seyed Ali Mousavi Shaegh, Habib Badri Ghavifekr, Esmaiel Najafi Aghdam, Mehmet Remzi Dokmeci, Ali Khademhosseini, Yu Shrike Zhang

There is a critical need to develop fabrication methods for rapid and cost-effective prototyping of thermoplastics-based microfluidics in academic research laboratories. This paper presents a method for the fabrication of whole-thermoplastic microfluidic functional elements, including a pneumatic (gas-actuated) normally closed microvalve, a micro-check valve, and a pneumatic dual-phase micropump. All devices were made from thermoplastic polyurethane (TPU) and poly(methyl methacrylate) (PMMA). The fabrication process consisted of only laser micromachining and thermal fusion bonding without need to perform any particular chemical treatment or use a master mold. These features enable the widespread adaptation of this method in academic research settings. Characterizations revealed that the fabricated normally closed microvalve could stop liquid flows at pressures lower than 2 psi in its passive operation mode where no pressure was used for valve actuation. The check valve could block liquid flows with liquid pressures of up to 30 psi in its reverse mode of operation while it could allow liquid to pass through in its forward mode. In addition, the micropump, which consisted of two check valves and a pneumatic uni-diaphragm displacement chamber, could pump liquid at an average flow rate of 87.6 ± 5.0 μL/min using an actuation frequency and pressure of 1 Hz and ±5 psi, respectively. Taken together, the developed low-cost whole-thermoplastic microfluidic functional elements could be employed for the fabrication of various lab-on-a-chip applications.





7 Proximity effect induced spin filtering and gap opening in graphene by half-metallic monolayer Cr2C ferromagnet 2018-02-16             

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Publication date: June 2018
Source:Carbon, Volume 132

Author(s): Baozeng Zhou, Shiwen Ji, Zhen Tian, Weijia Cheng, Xiaocha Wang, Wenbo Mi

The idea of spin injection into graphene by proximity effect is an interesting and timely topic. Furthermore, using 2D materials to induce such an effect instead of bulk materials is a recent targeted route towards better solution for 2D spintronics. We report on first-principle calculations of the spin-dependent properties in graphene induced by its interaction with a nearby half-metallic Cr2C (2D MXene). Spin polarization can be induced in graphene by the interfacial proximity of half-metallic Cr2C ferromagnet. The average spin polarization in the graphene can reach to 74%, which is much larger than the graphene/magnetic metal or graphene/magnetic insulator heterostructures. The observed spin splitting comes from the interaction between C-p z and Cr-3d states. Except for a n-doped feature by charge transfer, the linear dispersion of Dirac cone is modified with a band gap opening of 80 meV between the bonding and antibonding states. Especially, the electronic structure, charge transfer and gap opening are shown to depend strongly on the graphene/Cr2C interlayer, which can be tailored by strain. Moreover, a strain modulated spin filter based on the graphene/Cr2C heterostructure has been proposed. These results strongly revive this novel system as a candidate for future graphene-based spintronic devices.

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8 The mechanics of energy dissipation in a three-dimensional graphene foam with macroporous architecture 2018-02-16             

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Publication date: June 2018
Source:Carbon, Volume 132

Author(s): Pranjal Nautiyal, Benjamin Boesl, Arvind Agarwal

The three-dimensional porous architecture of graphene foam combines extraordinary mechanical properties of graphene with a unique structural organization to produce a strong, lightweight material. In this study, mechanisms for energy dissipation in graphene foam are investigated by localized nano-scale dynamic mechanical testing. Mechanical response of the material subjected to cyclic loading-unloading is captured as loss tangent (tan δ), characterizing the energy dissipation. Indentation tips with different geometries and dimensions (from 100 nm to 100 μm) are employed, which translate into variable stress-states with mechanical stresses ranging from a few kilo-Pascals to a few giga-Pascals. Formation of dynamic ripples, flattening of intrinsic corrugations, kink band formation, inter-layer van der Waals spring-like action, and membrane vibration are proposed as the key energy dissipation mechanisms in graphene foam. The relative contribution of these mechanisms towards energy dissipation is compared and quantified, with tan δ values varying from about 0.1 to 0.45. The energy dissipation behavior of the material is found to be highly stable, as the loss tangent values are retained for as high as 50,000 cycles. The fundamental understanding of intrinsic mechanics will enable engineering of impact-tolerable foam structure with desirable and predictable mechanical performance.

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9 Spontaneous activity forms a foundation for odor-evoked activation maps in the rat olfactory bulb 2018-02-16             

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Publication date: 15 May 2018
Source:NeuroImage, Volume 172

Author(s): Garth J. Thompson, Basavaraju G. Sanganahalli, Keeley L. Baker, Peter Herman, Gordon M. Shepherd, Justus V. Verhagen, Fahmeed Hyder

Fluctuations in spontaneous activity have been observed by many neuroimaging techniques, but because these resting-state changes are not evoked by stimuli, it is difficult to determine how they relate to task-evoked activations. We conducted multi-modal neuroimaging scans of the rat olfactory bulb, both with and without odor, to examine interaction between spontaneous and evoked activities. Independent component analysis of spontaneous fluctuations revealed resting-state networks, and odor-evoked changes revealed activation maps. We constructed simulated activation maps using resting-state networks that were highly correlated to evoked activation maps. Simulated activation maps derived by intrinsic optical signal (IOS), which covers the dorsal portion of the glomerular sheet, significantly differentiated one odor's evoked activation map from the other two. To test the hypothesis that spontaneous activity of the entire glomerular sheet is relevant for representing odor-evoked activations, we used functional magnetic resonance imaging (fMRI) to map the entire glomerular sheet. In contrast to the IOS results, the fMRI-derived simulated activation maps significantly differentiated all three odors' evoked activation maps. Importantly, no evoked activation maps could be significantly differentiated using simulated activation maps produced using phase-randomized resting-state networks. Given that some highly organized resting-state networks did not correlate with any odors' evoked activation maps, we posit that these resting-state networks may characterize evoked activation maps associated with odors not studied. These results emphasize that fluctuations in spontaneous activity form a foundation for active processing, signifying the relevance of resting-state mapping to functional neuroimaging.





10 Regularization method for large eddy simulations of shock-turbulence interactions 2018-02-15             

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Publication date: 15 May 2018
Source:Journal of Computational Physics, Volume 361

Author(s): N.O. Braun, D.I. Pullin, D.I. Meiron

The rapid change in scales over a shock has the potential to introduce unique difficulties in Large Eddy Simulations (LES) of compressible shock-turbulence flows if the governing model does not sufficiently capture the spectral distribution of energy in the upstream turbulence. A method for the regularization of LES of shock-turbulence interactions is presented which is constructed to enforce that the energy content in the highest resolved wavenumbers decays as k 5 / 3 , and is computed locally in physical-space at low computational cost. The application of the regularization to an existing subgrid scale model is shown to remove high wavenumber errors while maintaining agreement with Direct Numerical Simulations (DNS) of forced and decaying isotropic turbulence. Linear interaction analysis is implemented to model the interaction of a shock with isotropic turbulence from LES. Comparisons to analytical models suggest that the regularization significantly improves the ability of the LES to predict amplifications in subgrid terms over the modeled shockwave. LES and DNS of decaying, modeled post shock turbulence are also considered, and inclusion of the regularization in shock-turbulence LES is shown to improve agreement with lower Reynolds number DNS.





 
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