8,307 research outputs found
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 , 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
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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
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