The influence of key determinants on consumers’ choice in tourism destination

This study aims at developing a model that explains the effect of different stimuli types (ST) (i.e. online reviews and advertising) on a tourist’s intention to visit (ITV) a new destination. Two separate studies were conducted to establish and validate the model that consists of stimulus mediators (SM): destination trust (DT) and interest (DI). 113 surveys were obtained in study 1 which focused on the effect of the different stimuli types. Study 2 used the Elaboration Likelihood Model (ELM) to explore how advertising could persuade consumers to make purchasing decisions and how tourists could be persuaded to visit attraction sites. 146 surveys were obtained in study 2. Structured equation model (SEM) technique was adopted in the data analysis. The result of the first study showed that advertising has a stronger effect than positive online reviews. The second study showed that peripheral route of elaborate likelihood model has a stronger effect than central route in the context of tourism. That is, peripheral route that could generate a strong spontaneous impact by providing a vivid portrait of what a tourist would experience through an image cue

DeepSF: deep convolutional neural network for mapping protein sequences to folds

Motivation Protein fold recognition is an important problem in structural bioinformatics. Almost all traditional fold recognition methods use sequence (homology) comparison to indirectly predict the fold of a tar get protein based on the fold of a template protein with known structure, which cannot explain the relationship between sequence and fold. Only a few methods had been developed to classify protein sequences into a small number of folds due to methodological limitations, which are not generally useful in practice. Results We develop a deep 1D-convolution neural network (DeepSF) to directly classify any protein se quence into one of 1195 known folds, which is useful for both fold recognition and the study of se quence-structure relationship. Different from traditional sequence alignment (comparison) based methods, our method automatically extracts fold-related features from a protein sequence of any length and map it to the fold space. We train and test our method on the datasets curated from SCOP1.75, yielding a classification accuracy of 80.4%. On the independent testing dataset curated from SCOP2.06, the classification accuracy is 77.0%. We compare our method with a top profile profile alignment method - HHSearch on hard template-based and template-free modeling targets of CASP9-12 in terms of fold recognition accuracy. The accuracy of our method is 14.5%-29.1% higher than HHSearch on template-free modeling targets and 4.5%-16.7% higher on hard template-based modeling targets for top 1, 5, and 10 predicted folds. The hidden features extracted from sequence by our method is robust against sequence mutation, insertion, deletion and truncation, and can be used for other protein pattern recognition problems such as protein clustering, comparison and ranking.Comment: 28 pages, 13 figure

Generalising Deep Learning MRI Reconstruction across Different Domains

We look into robustness of deep learning based MRI reconstruction when tested on unseen contrasts and organs. We then propose to generalise the network by training with large publicly-available natural image datasets with synthesised phase information to achieve high cross-domain reconstruction performance which is competitive with domain-specific training. To explain its generalisation mechanism, we have also analysed patch sets for different training datasets.Comment: Accepted for ISBI2019 as a 1-page abstrac

Development of High-Productivity Continuous Ethanol Production using PVA-Immobilized Zymomonas mobilis in an Immobilized-Cells Fermenter

Ethanol as one of renewable energy was being considered an excellent alternative clean-burning fuel to replace gasoline. Continuous ethanol fermentation systems had offered important economic advantages compared to traditional systems. Fermentation rates were significantly improved, especially when continuous fermentation was integrated with cell immobilization techniques to enrich the cells concentration in fermentor. Growing cells of Zymomonas mobilis immobilized in polyvinyl alcohol (PVA) gel beads were employed in an immobilized-cells fermentor for continuous ethanol fermentation from glucose. The glucose loading, dilution rate, and cells loading were varied in order to determine which best condition employed in obtaining both high ethanol production and low residual glucose with high dilution rate. In this study, 20 g/L, 100 g/L, 125 g/L and 150 g/L of glucose concentration and 20% (w/v), 40% (w/v) and 50% (w/v) of cells loading were employed with range of dilution rate at 0.25 to 1 h-1. The most stable production was obtained for 25 days by employing 100 g/L of glucose loading. Meanwhile, the results also exhibited that 125 g/L of glucose loading as well as 40% (w/v) of cells loading yielded high ethanol concentration, high ethanol productivity, and acceptable residual glucose at 62.97 g/L, 15.74 g/L/h and 0.16 g/L, respectively. Furthermore, the dilution rate of 4 hour with 100 g/L and 40% (w/v) of glucose and cells loading was considered as the optimum condition with ethanol production, ethanol productivity and residual glucose obtained were 49.89 g/L, 12.47 g/L/h, and 2.04 g/L, respectively. This recent study investigated ethanol inhibition as well. The present research had proved that high sugar concentration was successfully converted to ethanol. These achieved results were promising for further study

Three-loop HTL QCD thermodynamics

The hard-thermal-loop perturbation theory (HTLpt) framework is used to calculate the thermodynamic functions of a quark-gluon plasma to three-loop order. This is the highest order accessible by finite temperature perturbation theory applied to a non-Abelian gauge theory before the high-temperature infrared catastrophe. All ultraviolet divergences are eliminated by renormalization of the vacuum, the HTL mass parameters, and the strong coupling constant. After choosing a prescription for the mass parameters, the three-loop results for the pressure and trace anomaly are found to be in very good agreement with recent lattice data down to $T \sim 2-3\,T_c$, which are temperatures accessible by current and forthcoming heavy-ion collision experiments.Comment: 27 pages, 11 figures; corresponds with published version in JHE

The relationship between brand trust, online customer reviews and willingness to purchase

This research investigates how online customer reviews, a particular form of electronic word of mouth (eWOM), affect consumer decision-making (willingness to purchase) during a first time purchase of services or products. Using brand trust as a mediating variable in the relationship between online customers reviews and the consumer’s willingness to buy, data was collected through a quasi-experiment approach and then analyzed using Structural Equation Modelling. The findings demonstrated that the reliable dimension of brand trust has a mediating effect on online customer reviews valance to willingness to buy while the intentionality dimension had little effect

Feminist Perspectives on Digitally Enabled Sustainable Fashion Consumerism

Fast fashion is not only an issue apropos of environmental pollution and feminism (Maynard, 2021), but also an area where HCI can make a difference. Fashion – comprising garment or apparel design, its supply chains and retail, and associated cultural ecosystem of fashion-related digital communications (see Harris et al., 2021) – has supported the position of women, as a powerful visual tool and by promoting their innovation, self-expression and social change (McRobbie, 2020).However, the relationship between fashion and feminism has recently become strained, due to ambiguity of claims that fashion promotes women’s empowerment, when fashion is also responsible for mass consumerism, further enabled by the rise of fintec

Exploring the Conformational Transitions of Biomolecular Systems Using a Simple Two-State Anisotropic Network Model

Biomolecular conformational transitions are essential to biological functions. Most experimental methods report on the long-lived functional states of biomolecules, but information about the transition pathways between these stable states is generally scarce. Such transitions involve short-lived conformational states that are difficult to detect experimentally. For this reason, computational methods are needed to produce plausible hypothetical transition pathways that can then be probed experimentally. Here we propose a simple and computationally efficient method, called ANMPathway, for constructing a physically reasonable pathway between two endpoints of a conformational transition. We adopt a coarse-grained representation of the protein and construct a two-state potential by combining two elastic network models (ENMs) representative of the experimental structures resolved for the endpoints. The two-state potential has a cusp hypersurface in the configuration space where the energies from both the ENMs are equal. We first search for the minimum energy structure on the cusp hypersurface and then treat it as the transition state. The continuous pathway is subsequently constructed by following the steepest descent energy minimization trajectories starting from the transition state on each side of the cusp hypersurface. Application to several systems of broad biological interest such as adenylate kinase, ATP-driven calcium pump SERCA, leucine transporter and glutamate transporter shows that ANMPathway yields results in good agreement with those from other similar methods and with data obtained from all-atom molecular dynamics simulations, in support of the utility of this simple and efficient approach. Notably the method provides experimentally testable predictions, including the formation of non-native contacts during the transition which we were able to detect in two of the systems we studied. An open-access web server has been created to deliver ANMPathway results.</p