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.     

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.     

The use of RO to remove emerging micropollutants following CAS/UF or MBR treatment of municipal wastewater

The removal of various organic micropollutants (OMPs), including six antibiotics (ERY, ROX, CLA, SMX, SMZ, and TMP), three pharmaceuticals (ibuprofen, salicylic acid, and diclofenac), one industrial product (BPA), and one hormone (cholesterol), was investigated in two pilot plants treating the same raw sewage of the Tel-Aviv WWTP. The effluent production by CAS-UF was 45 m³/h while that of MBR was 40 L/h. Each system's effluent constituted the feed for its RO, which comprised three RO steps after the CAS/UF and a semi-batch RO system after the MBR. Despite significant molecular differences between the selected OMPs, high removal rates were achieved after the RO stage (> 99% for macrolides, pharmaceuticals, cholesterol, and BPA, 95% for diclofenac, and > 93% removal of sulfonamides). However, low antibiotics concentrations and 28–223 ng/L residuals of ibuprofen, diclofenac, salicylic acid, cholesterol, and BPA in the MBR/RO and CAS-UF/RO permeates showed that although RO is an efficient removal solution, it cannot serve as an absolute barrier to OMPs. Therefore, additional treatment techniques should be considered to be incorporated aside the RO to ensure complete removal of such substances.     

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.     

Active (air-cooled) vs. passive (phase change material) thermal management of high power lithium-ion packs: Limitation of temperature rise and uniformity of temperature distribution

The effectiveness of passive cooling by phase change materials (PCM) is compared with that of active (forced air) cooling. Numerical simulations were performed at different discharge rates, operating temperatures and ambient temperatures of a compact Li-ion battery pack suitable for plug-in hybrid electric vehicle (PHEV) propulsion. The results were also compared with experimental results. The PCM cooling mode uses a micro-composite graphite–PCM matrix surrounding the array of cells, while the active cooling mode uses air blown through the gaps between the cells in the same array. The results show that at stressful conditions, i.e. at high discharge rates and at high operating or ambient temperatures (for example 40–45 °C), air-cooling is not a proper thermal management system to keep the temperature of the cell in the desirable operating range without expending significant fan power. On the other hand, the passive cooling system is able to meet the operating range requirements under these same stressful conditions without the need for additional fan power.     

Characterization of Palladium Nanoparticles Adsorpt on Polyacrylic Acid Particles as Hydrogenation Catalyst

Palladium particles can be prepared in sizes of a few nanometers from Pd(OAc)₂in the presence of a block copolymer in aromatic unpolar solvents with suitable reducing agents like NaBH₄ or LiAlH₄. After mixing the organic metal solution with a polyacrylic acid (PAA) dispersion of defined concentration and following a crosslinking process with an epoxide, reactive membranes with a well-defined pore diameter were obtained. The catalytic activity of the prepared palladium particles incorporated in the crosslinked PAA network has been proven by the gas phase hydrogenation of propyne in a special membrane reactor.     

Thermoelastic sloping thin-walled shell structures deformed without bending

We have derived a nonlinear integrodifferential equation to find the unbent shape of the middle surface of a sloping shell of constant thickness, subjected to a given temperature and force field.Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 59, No. 2, pp. 314–316, August, 1990.     

Inhibition of Aluminum Alloy Corrosion in 0.5 M Nitric Acid Solution by 4-4-Dimethyloxazolidine-2-thione

The corrosion inhibition of Al-Alloy (Al2024) in 0.5 M nitric acid solution at 30 °C was achieved using 4-4-dimethyloxazolidine-2-thione (DMT) as a corrosion inhibitor. The electrochemical performance of the DMT was studied by electrochemical impedance spectroscopy (EIS), potentiodynamic polarization measurements, and scanning electron microscopic study (SEM). The results indicated that DMT acts as an inhibitor for Al2024 in 0.5 M nitric acid. Polarization curves indicated that DMT was a mixed-type inhibitor. Inhibition efficiencies were observed to be increased with an increase in DMT concentration and attains approximately to 93.4% at 2 mM of DMT in 0.5 M nitric acid. The adsorption of DMT model on Al2024 surface obeyed in accordance with Langmuir adsorption isotherm model. The value of the free energy of adsorption ΔG _ads indicated that the adsorption of DMT molecule was a spontaneous process and was typical of physical and chemical adsorption.     

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.