Improving the service quality of cross-border e-commerce: How to understand online consumer reviews from a cultural differences perspective

IntroductionCross-border e-commerce (CBEC) consumers come from different countries; thus, cultural differences may affect their evaluations and perceptions of service quality. This paper follows Hofstede’s framework as a theoretical anchor to explore how to use online consumer reviews that reflect cultural differences to improve the service quality of CBEC.MethodsFirst, based on a latent Dirichlet allocation model, 14 service quality issues that consumers are concerned about in CBEC were identified. Second, a generalized ordered logistic regression model was explored to analyze the cultural influences on consumer sentiment orientation. Finally, the effect of each cultural dimension on consumer service quality perception in CBEC was evaluated by employing a binary logistic regression model.ResultsThe results showed that consumers paid more attention to the service quality of logistics service, customs efficiency and tariff, shopping experience, and so on. Cultural dimensions significantly impacted consumers’ emotional tendencies. Moreover, cultural dimensions had significant impacts on consumers’ service quality perception (e.g., logistics service, trust in sellers, customs disputes, and cell phone performance). Still, consumers’ quality perceptions of some services (e.g., cell phone functions, items as described, logistics package quality, and gifts) were less affected by cultural dimensions.DiscussionOur findings not only provide new perspectives for CBEC consumer behavior studies on quality improvement but also provide practical implications for CBEC enterprises

Hierarchical Pointer Net Parsing

Transition-based top-down parsing with pointer networks has achieved state-of-the-art results in multiple parsing tasks, while having a linear time complexity. However, the decoder of these parsers has a sequential structure, which does not yield the most appropriate inductive bias for deriving tree structures. In this paper, we propose hierarchical pointer network parsers, and apply them to dependency and sentence-level discourse parsing tasks. Our results on standard benchmark datasets demonstrate the effectiveness of our approach, outperforming existing methods and setting a new state-of-the-art.Comment: Accepted by EMNLP 201

PIN-mediated polar auxin transport regulations in plant tropic responses

Tropisms, growth responses to environmental stimuli such as light or gravity, are spectacular examples of adaptive plant development. The plant hormone auxin serves as a major coordinative signal. The PIN auxin exporters, through their dynamic polar subcellular localizations, redirect auxin fluxes in response to environmental stimuli and the resulting auxin gradients across organs underly differential cell elongation and bending. In this review, we discuss recent advances concerning regulations of PIN polarity during tropisms, focusing on PIN phosphorylation and trafficking. We also cover how environmental cues regulate PIN actions during tropisms, and a crucial role of auxin feedback on PIN polarity during bending termination. Finally, the interactions between different tropisms are reviewed to understand plant adaptive growth in the natural environment

Robust object representation by boosting-like deep learning architecture

This paper presents a new deep learning architecture for robust object representation, aiming at efficiently combining the proposed synchronized multi-stage feature (SMF) and a boosting-like algorithm. The SMF structure can capture a variety of characteristics from the inputting object based on the fusion of the handcraft features and deep learned features. With the proposed boosting-like algorithm, we can obtain more convergence stability on training multi-layer network by using the boosted samples. We show the generalization of our object representation architecture by applying it to undertake various tasks, i.e. pedestrian detection and action recognition. Our approach achieves 15.89% and 3.85% reduction in the average miss rate compared with ACF and JointDeep on the largest Caltech dataset, and acquires competitive results on the MSRAction3D dataset

Action Recognition Using 3D Histograms of Texture and A Multi-Class Boosting Classifier

Human action recognition is an important yet challenging task. This paper presents a low-cost descriptor called 3D histograms of texture (3DHoTs) to extract discriminant features from a sequence of depth maps. 3DHoTs are derived from projecting depth frames onto three orthogonal Cartesian planes, i.e., the frontal, side, and top planes, and thus compactly characterize the salient information of a specific action, on which texture features are calculated to represent the action. Besides this fast feature descriptor, a new multi-class boosting classifier (MBC) is also proposed to efficiently exploit different kinds of features in a unified framework for action classification. Compared with the existing boosting frameworks, we add a new multi-class constraint into the objective function, which helps to maintain a better margin distribution by maximizing the mean of margin, whereas still minimizing the variance of margin. Experiments on the MSRAction3D, MSRGesture3D, MSRActivity3D, and UTD-MHAD data sets demonstrate that the proposed system combining 3DHoTs and MBC is superior to the state of the art

An Efficient Universal Bee Colony Optimization Algorithm

The artificial bee colony algorithm is a global optimization algorithm. The artificial bee colony optimization algorithm is easy to fall into local optimal. We proposed an efficient universal bee colony optimization algorithm (EUBCOA). The algorithm adds the search factor u and the selection strategy of the onlooker bees based on local optimal solution. In order to realize the controllability of algorithm search ability, the search factor u is introduced to improve the global search range and local search range. In the early stage of the iteration, the search scope is expanded and the convergence rate is increased. In the latter part of the iteration, the algorithm uses the selection strategy to improve the algorithm accuracy and convergence rate. We select ten benchmark functions to testify the performance of the algorithm. Experimental results show that the EUBCOA algorithm effectively improves the convergence speed and convergence accuracy of the ABC algorithm

Power Optimization of Wave Energy Converter (WEC) Arrray Based on Sea Conditions of a Wind Farm

[Introduction] In order to respond to the national initiative of intensive sea use, develop clean energy, and contribute to carbon neutralization, a preliminary analysis was conducted on the multi-energy integration mode of offshore wind power and wave energy devices, and the WEC was optimized to achieve higher power output. [Method] Based on potential flow theory, the floating fan platform - WEC array was simulated to analyze the influence of the dimension and the inherent period of the WEC on the output power of the WEC. [Result] The simulation results show that under the same inherent period, the flatter the WEC is, the greater the total power of the WEC array is, and the economic difference of the WEC is small. For sea conditions, the economic difference of WEC array under different inherent periods is great, so it should be considered comprehensively. [Conclusion] In the known sea conditions, the inherent period and the dimenson of WECs can be optimized to achieve higher power output and increase energy output per unit sea area

Cast Shadow Detection for Surveillance System Based on Tricolor Attenuation Model

Abstract. Shadows bring some undesirable problems in computer vision, such as object detecting in outdoor scenes. In this paper, we propose a novel method for cast shadow detecting for moving target in surveillance system. This measure is based on tricolor attenuation model, which describes the relationship of three color channel's attenuation in image when shadow happens. According to this relationship, the cast shadow is removed from the detected moving area, only the target area is left. Some experiments were done, and their results validate the performance of our method

Animal resource exploitation in the northern Guanzhong region during the mid-to-late Holocene: A zooarchaeological case study of the Xitou site

Zooarchaeological approach has been effective in providing insights into human subsistence practices, which laid essential economic foundation for social, cultural, and political developments in the past. The Guanzhong region in northern China played a crucial role in the origins and evolution of ancient Chinese civilization. Previous research on subsistence economies of ancient societies in the Guanzhong region, human exploitation of animal resources in particular, has largely focused on the late Neolithic period or the Bronze Age. Insufficient work has been done for historical periods post-dating the end of the first millennium BCE. There is also a dearth of research on the long-term chronological changes. Here, we present a preliminary analysis of animal remains from the Nantou Locale of the Xitou site, a large settlement located in the northern Guanzhong region. Results show that pigs played a dominant role in the site’s animal economy during the Neolithic Yangshao and Longshan periods (ca. 5000–2000 BCE). The growing importance of cattle and caprines was documented for the Bronze Age Western Zhou period (ca. 11th-8th centuries BCE). In the Han-Tang periods (ca. second century BCE-tenth century CE), pigs regained their significance in local subsistence practices. Differences in the strategies for animal resource exploitation were possibly associated with changing social and environmental factors. Alongside other relevant archaeological evidence, our zooarchaeological data demonstrate the contribution of diversified animal use strategies to sustained development of subsistence economy in the northern Guanzhong region across millennia. The examination of long-term human-animal interactions in the Guanzhong region allows for a better understanding of changing economic, social, and political landscapes in ancient China

MOF-derived ultrathin cobalt molybdenum phosphide nanosheets for efficient electrochemical overall water splitting

Altres ajuts: IREC is funded by the CERCA Programme/Generalitat de Catalunya. ICN2 is funded by the CERCA Programme/Generalitat de Catalunya.The development of high-performance and cost-effective earth-abundant transition metal-based electrocatalysts is of major interest for several key energy technologies, including water splitting. Herein, we report the synthesis of ultrathin CoMoP nanosheets through a simple ion etching and phosphorization method. The obtained catalyst exhibits outstanding electrocatalytic activity and stability towards oxygen and hydrogen evolution reactions (OER and HER), with overpotentials down to 273 and 89 mV at 10 mA cm −2, respectively. The produced CoMoP nanosheets are also characterized by very small Tafel slopes, 54.9 and 69.7 mV dec −1 for OER and HER, respectively. When used as both cathode and anode electrocatalyst in the overall water splitting reaction, CoMoP-based cells require just 1.56 V to reach 10 mA cm −2 in alkaline media. This outstanding performance is attributed to the proper composition, weak crystallinity and two-dimensional nanosheet structure of the electrocatalyst