Although beer is widely consumed around the world and has the largest market share among alcoholic beverages, there is a paucity of studies on consumers' preferences for beer compared to wine. In this study, consumers were asked to select the best and worst favorable beer from choice sets of a labeled choice experiment, in which choice options were labeled by brand names. Data collected from face-to-face interviews with Vietnamese beer-drinkers were used to estimate latentclass ranking logit models with alternative specific-effects, i.e. consumers' preferences for beer attributes are allowed to vary between beer brands and across four segments. In general, consumers prefer international brands to local ones, possibly due to sales promotion effects, experience, brand image or reflecting the mental representation. Consumers' favors for packaging format (canned vs. bottled beer) are subject to brands and are heterogeneous across segments. Surprisingly, alcohol percent has the least significant effects on the choice. The paper also discusses the implication of the findings for policy making and business strategy development.
Cloud and cloud shadow cause information loss in optical remote sensing analysis. South East Asia, especially Vietnam, Sentinel-2 imagery has short re-visit cycle and observations tend to be contaminated with cloud and cloud shadow. Traditional cloud removal methods require close date multi-temporal data to avoid seasonal land cover changes. In this study, a method of integrating Deep Convolutional Neural Networks (DCNN) and Generative Adversarial Network (GAN) was proposed. This machine learning model estimates the information loss over cloud contaminated areas on a single Sentinel-2 image. The results show that for images with cloud cover rate under 25%, our model can reconstruct cloudless images with PSNR (25 – 40 dB) and SSIM (0.86 – 0.93) compared to real clear images. On the other hand, with cloud cover rate up to 40%, the model performance will be affected heavily by the distribution of cloud and cloud shadow areas. By investigating DCNN and GAN, our method has proven to be an effective tool to remove cloudy images with low and medium rates, which enriches the clear optical remote sensing data sources for environment monitoring.
<p>In the present paper, the traditional co-precipitation method in synthesis of magnetite (Fe<sub>3</sub>O<sub>4</sub>) nanoparticles have been procedurally and ultrasonically altered. The effects of NH<sub>3</sub> solution adding paths to precursor solution, and ultrasonic assistance were indicated and demonstrated through specific experiments, and suggested explanations for observed phenomena. Characteristic information has proved the enhanced performance of the alternative procedure, illustrated by archived magnetite nanoparticles as the product with uniform nano-crystallised spherical morphology, narrow small-size distribution (10 nm), high magnetisation (57.7 emu·g<sup>-1</sup>), and negligibly low coercivity (5 Oe).</p>
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