Gathering Customer’s Demand Data through Web 2.0 Community: Process and Architecture

It’s one of the most critical tasks for businesses to keep track customer’s responses to their products and services in this competitive business environment. With the emergence of Web 2.0 communities and social networking websites, a relatively new media in personal communication and knowledge sharing websites, firms can leverage this additional channel to their advantage by implementing a system to monitor and collect customer’s response data. The purpose of this paper is to introduce a data collection process and a system design architecture which can be used for such purpose

26P. Enterprise Blog Categorization and Business Value

As more enterprises adopt Web 2.0 technologies, enterprise blog (EB) has become a popular and an important business tool not only for internal management but also for external interfacing with suppliers, business partners, and customers. For customer management, EB brings together two contemporary business developments, enhanced customer involvement and new forms of customer experience management. EB has been adopted by many organizations for the purpose of involving customers in product development, acquiring new customers, and providing customer with interactive experiences. However, in addition to the EB infrastructure, the effectiveness and success of such tool is largely dependent on the content. The purpose of this paper is to present a framework categorizing a rather complex and fragmented EB content domain. The framework was verified using data of 78 large multinational corporation’s enterprise blogs. A systematic overview of EB’s value and business model is explored

An inquiry beyond the technology acceptance model

Liu, Y., Henseler, J., & Liu, Y. (2022). What makes tourists adopt smart hospitality? An inquiry beyond the technology acceptance model. Digital Business, 2(2), 1-10. [100042]. https://doi.org/10.1016/j.digbus.2022.100042.----- Funding: Jorg ¨ Henseler acknowledges a financial interest in the composite based SEM software ADANCO and its distributor, Composite Modeling. Moreover, he gratefully acknowledges financial support from FCT Fundaçãopara a Ciência e a Tecnologia (Portugal), national funding through a research grant from the Information Management Research Center – MagIC/NOVA IMS (UIDB/04152/2020). This research was supported by iFRG fund (FRG-22-004-INT) at Macau University of Science and Technology. Ms. Wenting FU provided support for data collection.Smart hospitality has become an attractive project in tourism. Extant research has studied smart technology as a contingency but has neglected to conceptualize smartness and investigate its consequences. This study conceptualizes and operationalizes smart hospitality and explores the relationships among smartness, perceived usefulness, perceived ease of use, overall image of a hotel and tourists' behavioral intention to stay in a smart hotel. The proposed model incorporated technology acceptance model (TAM) and image theory. With a sample of 348 respondents in Macau, this study tested the model using partial least squares path modeling (PLS-PM), which indicates that the proposed model fits the data. In spite of a high inter-construct correlation, the results showed that smartness does not have a direct effect on behavioral intention. According to mediation analysis, indirect effects made up of significant direct effects and assigned them to TAM, image theory, and a combination of both. This paper contributes to hospitality management theory by providing additional insight into smart hospitality, it demonstrates the applicability of PLS-PM with composite and common factor models in technological change research, and it suggests smartness as a business strategy that can change tourists' choices in practice.publishersversionpublishe

A commentary on Yuan and Fang (2023)

Schuberth, F., Schamberger, T., Rönkkö, M., Liu, Y., & Henseler, J. (2023). Premature conclusions about the signal‐to‐noise ratio in structural equation modeling research: A commentary on Yuan and Fang (2023). British Journal of Mathematical and Statistical Psychology, 1-13. https://doi.org/10.1111/bmsp.12304 --- Funding Information: Jörg Henseler served as a reviewer for Yuan and Fang's ( 2023 ) manuscript. He gratefully acknowledges financial support from FCT Fundação para a Ciência e a Tecnologia (Portugal), national funding through a research grant from the Information Management Research Center – MagIC/NOVA IMS (UIDB/04152/2020). We thank Hao Wu, Associate Editor of the , for giving us the opportunity to write this commentary. Moreover, we thank Alexandra Elbakyan for her efforts in making science accessible. Finally, we thank Yves Rosseel for his support in replicating Yuan and Fang's results in lavaan. British Journal of Mathematical and Statistical PsychologyIn a recent article published in this journal, Yuan and Fang (British Journal of Mathematical and Statistical Psychology, 2023) suggest comparing structural equation modeling (SEM), also known as covariance-based SEM (CB-SEM), estimated by normal-distribution-based maximum likelihood (NML), to regression analysis with (weighted) composites estimated by least squares (LS) in terms of their signal-to-noise ratio (SNR). They summarize their findings in the statement that “[c]ontrary to the common belief that CB-SEM is the preferred method for the analysis of observational data, this article shows that regression analysis via weighted composites yields parameter estimates with much smaller standard errors, and thus corresponds to greater values of the [SNR].” In our commentary, we show that Yuan and Fang have made several incorrect assumptions and claims. Consequently, we recommend that empirical researchers not base their methodological choice regarding CB-SEM and regression analysis with composites on the findings of Yuan and Fang as these findings are premature and require further research.publishersversionepub_ahead_of_prin

Chaotic Systems with Hyperbolic Sine Nonlinearity

In recent years, exploring and investigating chaotic systems with hyperbolic sine nonlinearity has gained the interest of many researchers. With two back-to-back diodes to approximate the hyperbolic sine nonlinearity, these chaotic systems can achieve simplicity of the electrical circuit without any multiplier or sub-circuits. In this chapter, the genesis of chaotic systems with hyperbolic sine nonlinearity is introduced, followed by the general method of generating nth-order (n > 3) chaotic systems. Then some derived chaotic systems/torus-chaotic system with hyperbolic sine nonlinearity is discussed. Finally, the applications such as random number generator algorithm, spread spectrum communication and image encryption schemes are introduced. The contribution of this chapter is that it systematically summarizes the design methods, the dynamic behavior and typical engineering applications of chaotic systems with hyperbolic sine nonlinearity, which may widen the current knowledge of chaos theory and engineering applications based on chaotic systems

TKwinFormer: Top k Window Attention in Vision Transformers for Feature Matching

Local feature matching remains a challenging task, primarily due to difficulties in matching sparse keypoints and low-texture regions. The key to solving this problem lies in effectively and accurately integrating global and local information. To achieve this goal, we introduce an innovative local feature matching method called TKwinFormer. Our approach employs a multi-stage matching strategy to optimize the efficiency of information interaction. Furthermore, we propose a novel attention mechanism called Top K Window Attention, which facilitates global information interaction through window tokens prior to patch-level matching, resulting in improved matching accuracy. Additionally, we design an attention block to enhance attention between channels. Experimental results demonstrate that TKwinFormer outperforms state-of-the-art methods on various benchmarks. Code is available at: https://github.com/LiaoYun0x0/TKwinFormer.Comment: 11 pages, 7 figure

The cadmium–mercaptoacetic acid complex contributes to the genotoxicity of mercaptoacetic acid-coated CdSe-core quantum dots

Quantum dots (QDs) have many potential clinical and biological applications because of their advantages over traditional fluorescent dyes. However, the genotoxicity potential of QDs still remains unclear. In this paper, a plasmid-based system was designed to explore the genotoxic mechanism of QDs by detecting changes in DNA configuration and biological activities. The direct chemicobiological interactions between DNA and mercaptoacetic acid-coated CdSecore QDs (MAA–QDs) were investigated. After incubation with different concentrations of MAA–QDs (0.043, 0.13, 0.4, 1.2, and 3.6 μmol/L) in the dark, the DNA conversion of the covalently closed circular (CCC) DNA to the open circular (OC) DNA was significantly enhanced (from 13.9% ± 2.2% to 59.9% ± 12.8%) while the residual transformation activity of plasmid DNA was greatly decreased (from 80.7% ± 12.8% to 13.6% ± 0.8%), which indicated that the damages to the DNA structure and biological activities induced by MAA–QDs were concentration-dependent. The electrospray ionization mass spectrometry data suggested that the observed genotoxicity might be correlated with the cadmium–mercaptoacetic acid complex (Cd–MAA) that is formed in the solution of MAA–QDs. Circular dichroism spectroscopy and transformation assay results indicated that the Cd–MAA complex might interact with DNA through the groove-binding mode and prefer binding to DNA fragments with high adenine and thymine content. Furthermore, the plasmid transformation assay could be used as an effective method to evaluate the genotoxicities of nanoparticles

16S rRNA gene sequencing reveals the correlation between the gut microbiota and the susceptibility to pathological scars

The gut microbiome profile in patients with pathological scars remains rarely known, especially those patients who are susceptible to pathological scars. Previous studies demonstrated that gut microbial dysbiosis can promote the development of a series of diseases via the interaction between gut microbiota and host. The current study aimed to explore the gut microbiota of patients who are prone to suffer from pathological scars. 35 patients with pathological scars (PS group) and 40 patients with normal scars (NS group) were recruited for collection of fecal samples to sequence the 16S ribosomal RNA (16S rRNA) V3-V4 region of gut microbiota. Alpha diversity of gut microbiota showed a significant difference between NS group and PS group, and beta diversity indicated that the composition of gut microbiota in NS and PS participants was different, which implied that dysbiosis exhibits in patients who are susceptible to pathological scars. Based on phylum, genus, species levels, we demonstrated that the changing in some gut microbiota (Firmicutes; Bacteroides; Escherichia coli, etc.) may contribute to the occurrence or development of pathological scars. Moreover, the interaction network of gut microbiota in NS and PS group clearly revealed the different interaction model of each group. Our study has preliminary confirmed that dysbiosis exhibits in patients who are susceptible to pathological scars, and provide a new insight regarding the role of the gut microbiome in PS development and progression

Contrasting Soil Bacterial Community, Diversity, and Function in Two Forests in China

Bacteria are the highest abundant microorganisms in the soil. To investigate bacteria community structures, diversity, and functions, contrasting them in four different seasons all the year round with/within two different forest type soils of China. We analyzed soil bacterial community based on 16S rRNA gene sequencing via Illumina HiSeq platform at a temperate deciduous broad-leaved forest (Baotianman, BTM) and a tropical rainforest (Jianfengling, JFL). We obtained 51,137 operational taxonomic units (OTUs) and classified them into 44 phyla and 556 known genera, 18.2% of which had a relative abundance >1%. The composition in each phylum was similar between the two forest sites. Proteobacteria and Acidobacteria were the most abundant phyla in the soil samples between the two forest sites. The Shannon index did not significantly differ among the four seasons at BTM or JFL and was higher at BTM than JFL in each season. The bacteria community at both BTM and JFL showed two significant (P < 0.05) predicted functions related to carbon cycle (anoxygenic photoautotrophy sulfur oxidizing and anoxygenic photoautotrophy) and three significant (P < 0.05) predicted functions related to nitrogen cycle (nitrous denitrificaton, nitrite denitrification, and nitrous oxide denitrification). We provide the basis on how changes in bacterial community composition and diversity leading to differences in carbon and nitrogen cycles at the two forests