Mapping low-Reynolds-number microcavity flows using microfluidic screening devices

Low-Reynolds-number flows in cavities, characterized by separating and recirculating flows are increasingly used in microfluidic applications such as mixing and sorting of fluids, cells, or particles. However, there is still a lack of guidelines available for selecting the appropriate or optimized microcavity configuration according to the specific task at hand. In an effort to provide accurate design guidelines, we investigate quantitatively low-Reynolds-number cavity flow phenomena using a microfluidic screening platform featuring rectangular channels lined with cylindrical cavities. Using particle image velocimetry (PIV), supported by computational fluid dynamics (CFD) simulations, we map the entire spectrum of flows that exist in microcavities over a wide range of low-Reynolds numbers (Re = 0.1, 1, and 10) and dimensionless geometric parameters. Comprehensive phase diagrams of the corresponding microcavity flow regimes are summarized, capturing the gradual transition from attached flow to a single vortex and crossing through two- and three-vortex recirculating systems featuring saddle-points. Finally, we provide design insights into maximizing the rotational frequencies of recirculating single-vortex microcavity systems. Overall, our results provide a complete and quantitative framework for selecting cavities in microfluidic-based microcentrifuges and vortex mixers.     

Segmentation of multiple sclerosis lesions in brain MRI: A review of automated approaches

Automatic segmentation of multiple sclerosis (MS) lesions in brain MRI has been widely investigated in recent years with the goal of helping MS diagnosis and patient follow-up. However, the performance of most of the algorithms still falls far below expert expectations. In this paper, we review the main approaches to automated MS lesion segmentation. The main features of the segmentation algorithms are analysed and the most recent important techniques are classified into different strategies according to their main principle, pointing out their strengths and weaknesses and suggesting new research directions. A qualitative and quantitative comparison of the results of the approaches analysed is also presented. Finally, possible future approaches to MS lesion segmentation are discussed.     

Silver versus white sheet as a back reflector for microcrystalline silicon solar cells deposited on LPCVD‐ZnO electrodes of various textures

We compare the performance of two back reflector designs on the optoelectrical properties of microcrystalline silicon solar cells. The first one consists of a 5‐µm‐thick low‐pressure chemical vapor deposition (LPCVD)‐ZnO electrode combined with a white sheet; the second one incorporates an Ag reflector deposited on a thin LPCVD‐ZnO layer (with thickness below 200 nm). For this latter design, the optical loss in the nano‐rough Ag reflector can be strongly reduced by smoothing the surface of the thin underlying ZnO layer, by means of an Ar‐plasma treatment. Because of its superior lateral conductivity, the thin‐ZnO/Ag back reflector design provides a higher fill factor than the dielectric back reflector design. When decreasing the roughness of the front electrode with respect to our standard front LPCVD‐ZnO layer, the electrical cell performance is improved; in addition, the implementation of the thin‐ZnO/Ag back reflector leads to a significant relative gain in light trapping. Applying this newly optimized combination of front and back electrodes, the conversion efficiency is improved from 8.9% up to 9.4%, for cells with an active‐layer thickness of only 1.1 µm. We thereby highlight the necessity to optimize simultaneously the front and back electrodes. Copyright © 2014 John Wiley & Sons, Ltd.     

Cooperative OFDM for semi distributed detection in wireless sensor networks

In this paper, parallel distributed detection in wireless sensor network (WSN) is investigated. Sensors are assumed to be transmitting their local decisions to a fusion center through a wireless fading channel using cooperative transmission. To enable cooperative transmission, sensors are divided into groups where sensors in each group help each other in transmitting their decisions in a way that the fusion center receives each local decision as an orthogonal frequency division multiplexed (OFDM) block. The fusion center detects all OFDM blocks sent by all groups to process them in order to obtain a final (global) decision. Using this cooperative transmission scheme enables the fusion center to apply diversity combining methods in order to reduce the fading effects of the channel. Optimal and sub-optimal fusion rules are derived for such system. Simulation results are provided to show the performance improvement that can be obtained compared to the conventional system where each local decision is transmitted to the fusion center individually and no diversity technique is applied at the fusion center.     

Experimental characterization and performance study of an ammonia–water–hydrogen refrigerator

We present in this paper an experimental study of a commercial diffusion-absorption refrigeration machine (DAR) operating on the Platen and Munters cycle. The temperatures at the inlet and outlet of every component of the machine, as well as the cabinet and ambient temperature are measured continuously. The tests are repeated for various electric power inputs to the refrigerator. The global heat transfer coefficient of the cabinet (UA)_cab is determined using both theoretical and experimental methods. This coefficient is found equal to 0.2 W/°C. The global heat transfer coefficient of the evaporator (UA)_evap is deduced using dynamic and steady state methods. This global heat transfer coefficient (UA)_evap is found equal to 0.3 W/°C. Finally the cooling capacity of the unit and the coefficient of performance are evaluated. The heating power supply to the generator necessary to ensure the desired state of this machine is found to be in the range of 35 W–45 W.     

Deep penetration analysis with dynamic cylindrical cavitation fields

Dynamic cylindrical cavitation fields are studied for a family of plastic orthotropic solids with arbitrary strain hardening response. Analysis is within the framework of plane-strain, steady state flow theory of associated plasticity. New formulae for cavitation pressure are validated against accurate numerical analysis and contact is made with existing studies. A uniform procedure is presented for estimating penetration depth of rigid axisymmetric projectiles at normal impact. Comparison with available experimental data reveals a very good agreement for both spherical and cylindrical dynamic cavitation models. Quasi-static cavitation pressure formulae can predict penetration depth with an appropriate scaling of the yield stress. The scaling factors appear to be independent of material properties but reflect the shape of head profile.     

On the Effect of the Machine Saturation on SSR in Power Systems

A bifurcation analysis is performed to investigate the influence of iron saturation on the complex dynamics of a heavily loaded single-machine-infinitebusbar power system modeling the characteristics of the CHOLLA# 4 generator with respect to the SOWARO station. The system has five mechanical and two electrical modes. The results show that as the compensation level increases, the operating condition loses stability via a supercritical Hopf bifurcation. As a result, the power system oscillates subsynchronously with a small limit-cycle attractor. The instability is due to the interaction of the subsynchronous electrical mode with one of the torsional modes. When the machine saturation is considered, again the system loses stability via a supercritical Hopf bifurcation; however, it occurs at a slightly lower level of compensation, indicating that the influence of machine saturation is slightly destabilizing.     

Experimental study about the effects of disc chipper settings on the distribution of wood chip size

Nowadays wood should be of principal sources of biomass. This wood is transformed into chips in order to increase automatic operations and to decrease the technical effort needed at the energy conversion plant. Typical high quality chips, which are used to feed small woodchip boilers, vary in size from 10 × 10 × 5 mm to 15 × 15 × 8 mm. Chips that are relatively square and flat are easily conveyed, augured, and fed into the system smoothly. We are mainly interested in the raw material of inferior quality. A disc chipper test bench was constructed in our laboratory to study the chipping process in cutting conditions which are similar to those used in the industry. The test bench design allows many factors to be varied include cutting speed, feed per tooth, cutting angles, anvil height and cutting direction. In this paper, we attempt to understand the effect of several factors on chip size distribution. Four feeds per tooth, four cutting angles, two sharpness angles and three cutting speeds were chosen to cut wet logs of oak and fir wood, while the other factors remained constant. The results are similar for both oak and fir. The proportion of small chips decreases when we increase the feed per tooth, the cutting angle and the sharpness angle, whereas it increases when the cutting speed is increased. The feed per tooth and the cutting speed have a linear effect on the variations in the size distribution, while the cutting angle has a non-linear effect on these variations.     

Feature subset selection using differential evolution and a statistical repair mechanism

One of the fundamental motivations for feature selection is to overcome the curse of dimensionality problem. This paper presents a novel feature selection method utilizing a combination of differential evolution (DE) optimization method and a proposed repair mechanism based on feature distribution measures. The new method, abbreviated as DEFS, utilizes the DE float number optimizer in the combinatorial optimization problem of feature selection. In order to make the solutions generated by the float-optimizer suitable for feature selection, a roulette wheel structure is constructed and supplied with the probabilities of features distribution. These probabilities are constructed during iterations by identifying the features that contribute to the most promising solutions. The proposed DEFS is used to search for optimal subsets of features in datasets with varying dimensionality. It is then utilized to aid in the selection of Wavelet Packet Transform (WPT) best basis for classification problems, thus acting as a part of a feature extraction process. Practical results indicate the significance of the proposed method in comparison with other feature selection methods.     

Consumer neuroscience: Assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking

Application of neuroscience methods to analyze and understand human behavior related to markets and marketing exchange has recently gained research attention. The basic aim is to guide design and presentation of products to optimize them to be as compatible as possible with consumer preferences. This paper investigates physiological decision processes while participants undertook a choice task designed to elicit preferences for a product. The task required participants to choose their preferred crackers described by shape (square, triangle, round), flavor (wheat, dark rye, plain) and topping (salt, poppy, no topping). The two main research objectives were (1) to observe and evaluate the cortical activity of the different brain regions and the interdependencies among the Electroencephalogram (EEG) signals from these regions; and (2) unlike most research in this area that has focused mainly on liking/disliking certain products, we provide a way to quantify the importance of different cracker features that contribute to the product design based on mutual information. We used the commercial Emotiv EPOC wireless EEG headset with 14 channels to collect EEG signals from participants. We also used a Tobii-Studio eye tracker system to relate the EEG data to the specific choice options (crackers). Subjects were shown 57 choice sets; each choice set described three choice options (crackers). The patterns of cortical activity were obtained in the five principal frequency bands, Delta (0–4 Hz), Theta (3–7 Hz), Alpha (8–12 Hz), Beta (13–30 Hz), and Gamma (30–40 Hz). There was a clear phase synchronization between the left and right frontal and occipital regions indicating interhemispheric communications during the chosen task for the 18 participants. Results also indicated that there was a clear and significant change (p < 0.01) in the EEG power spectral activities taking a place mainly in the frontal (delta, alpha and beta across F3, F4, FC5 and FC6), temporal (alpha, beta, gamma across T7), and occipital (theta, alpha, and beta across O1) regions when participants indicated their preferences for their preferred crackers. Additionally, our mutual information analysis indicated that the various cracker flavors and toppings of the crackers were more important factors affecting the buying decision than the shapes of the crackers.