Effects of Emoticons on the Acceptance of Negative Feedback in Computer-Mediated Communication

Delivering negative performance feedback is inevitable in the workplace. However, recipients may feel uncomfortable and behave defensively, and may be unwilling to accept negative feedback mainly because they fear losing face. Such unproductive responses are heightened when negative feedback is delivered through computer-mediated communication (CMC) channels in which many nonverbal cues in face-to-face communication cannot be used to alleviate the concerns of losing face. This study examines the effectiveness of emoticons, which are designed as surrogates for facial expressions in CMC environments, in conveying social and emotional signals of the feedback provider. Specifically, based on the feedback process model and the dissonance reduction theory, this study investigates the differing effects of two types of emoticons (i.e., liking and disliking ones) on the acceptance of negative feedback by considering feedback specificity as a contingent factor. Our results suggest that using liking emoticons increases perceived good intention of the feedback provider and decreases perceived feedback negativity when the feedback is specific; however, it has no significant effect for unspecific feedback. By contrast, our results suggest that using disliking emoticons decreases perceived good intention of the feedback provider and increases perceived feedback negativity when the feedback is unspecific, whereas such effects are not significant for specific feedback. In turn, both perceived good intention of the feedback provider and perceived feedback negativity affect acceptance of the negative feedback

An Investigation into Post-Implementation Success of ERP: An Empirical Study of the Chinese Retail Industry

Significant growth in the Chinese retail industry has boosted utilization of Enterprise Resource Planning (ERP) systems among Chinese retailers. However, due to the weak information infrastructure of organizations and the inherent complexity of ERP systems, many Chinese retailers have encountered difficulties in achieving the benefits at the post-implementation stage of the ERP deployment. The post-implementation success of the ERP is under researched, though. Therefore, based on the Technology-Organization-Environment (TOE) theory, we develop an integrated model of the post-implementation success of ERP, and empirically test it in the Chinese retail industry. The results show that implementation quality and organizational readiness positively affect the post-implementation success of the ERP, while external support does not exert significant impacts. The research and practical implications of the findings are discussed

What Accounts for Organizations’ Different Usage of B2B E-Marketplaces?

A business to business (B2B) e-marketplace is an Internet-based inter-organizational system that facilitates online businesses. It provides two basic functions: search and transaction. Accordingly, organizational usage of B2B e-marketplaces varies across these two functions. The previous research mainly applies the Diffusion of Innovation (DOI) theory to predict the usage of B2B e-marketplaces, but this theory is insufficient in explaining the unbalanced usage of search versus transaction. This research attempts to fill this gap. We identify a cognitive limitation associated with each usage, i.e., insufficient knowledge of B2B e-marketplaces corresponds to the usage of search and incapability of foreseeing all consequences corresponds to the usage of transaction. Then, we incorporate perceived institutional norm and organizational trust as two remedies into the DOI theory, and argue that the former will affect the use of B2B e-marketplaces for search while the latter will affect the usage of transaction. A field survey is conducted to collect the data, and structural equation modeling is employed to test the research model. The results confirm the hypotheses. Besides, relative advantage and perceived compatibility from the DOI theory also affect both types of usage. This research implies that the usage of Internet-based inter-organizational systems may encounter cognitive limitations, and highlights how the DOI theory can be extended to account for the usage of information systems that provide multiple uses at different adoption stages

DNA methylation in lung cancer patients: Opening a "window of life" under precision medicine

DNA methylation is a work of adding a methyl group to the 5th carbon atom of cytosine in DNA sequence under the catalysis of DNA methyltransferase (DNMT) to produce 5-methyl cytosine. Some current studies have elucidated the mechanism of lung cancer occurrence and causes of lung cancer progression and metastasis from the perspective of DNA methylation. Moreover, many studies have shown that smoking can change the methylation status of some gene loci, leading to the occurrence of lung cancer, especially central lung cancer. This review mainly introduces the role of DNA methylation in the pathogenesis, early diagnosis and screening, progression and metastasis, treatment, and prognosis of lung cancer, as well as the latest progress. We point out that methylation markers, sample tests, and methylation detection limit the clinical application of DNA methylation. If the liquid biopsy is to become the main force in lung cancer diagnosis, it must make efficient use of limited samples and improve the sensitivity and specificity of the tests. In addition, we also put forward our views on the future development direction of DNA methylation

Slit2N/Robo1 Inhibit HIV-gp120-Induced Migration and Podosome Formation in Immature Dendritic Cells by Sequestering LSP1 and WASp

Cell-mediated transmission and dissemination of sexually-acquired human immunodeficiency virus 1 (HIV-1) in the host involves the migration of immature dendritic cells (iDCs). iDCs migrate in response to the HIV-1 envelope protein, gp120, and inhibiting such migration may limit the mucosal transmission of HIV-1. In this study, we elucidated the mechanism of HIV-1-gp120-induced transendothelial migration of iDCs. We found that gp120 enhanced the binding of Wiskott-Aldrich Syndrome protein (WASp) and the Actin-Related Protein 2/3 (Arp2/3) complex with β-actin, an interaction essential for the proper formation of podosomes, specialized adhesion structures required for the migration of iDCs through different tissues. We further identified Leukocyte-Specific Protein 1 (LSP1) as a novel component of the WASp-Arp2/3-β-actin complex. Pretreating iDCs with an active fragment of the secretory glycoprotein Slit2 (Slit2N) inhibited HIV-1-gp120-mediated migration and podosome formation, by inducing the cognate receptor Roundabout 1 (Robo1) to bind to and sequester WASp and LSP1 from β-actin. Slit2N treatment also inhibited Src signaling and the activation of several downstream molecules, including Rac1, Pyk2, paxillin, and CDC42, a major regulator of podosome formation. Taken together, our results support a novel mechanism by which Slit2/Robo1 may inhibit the HIV-1-gp120-induced migration of iDCs, thereby restricting dissemination of HIV-1 from mucosal surfaces in the host

Slit2/Robo4 Signaling Modulates HIV-1 gp120-Induced Lymphatic Hyperpermeability

Dissemination of HIV in the host involves transit of the virus and virus-infected cells across the lymphatic endothelium. HIV may alter lymphatic endothelial permeability to foster dissemination, but the mechanism is largely unexplored. Using a primary human lymphatic endothelial cell model, we found that HIV-1 envelope protein gp120 induced lymphatic hyperpermeability by disturbing the normal function of Robo4, a novel regulator of endothelial permeability. HIV-1 gp120 induced fibronectin expression and integrin α5β1 phosphorylation, which led to the complexing of these three proteins, and their subsequent interaction with Robo4 through its fibronectin type III repeats. Moreover, pretreatment with an active N-terminus fragment of Slit2, a Robo4 agonist, protected lymphatic endothelial cells from HIV-1 gp120-induced hyperpermeability by inhibiting c-Src kinase activation. Our results indicate that targeting Slit2/Robo4 signaling may protect the integrity of the lymphatic barrier and limit the dissemination of HIV in the host

Slit2N and Robo4 regulate lymphangiogenesis through the VEGF-C/VEGFR-3 pathway

Background: Signaling through vascular endothelial growth factor C (VEGF–C) and VEGF receptor 3 (VEGFR-3) plays a central role in lymphangiogenesis and the metastasis of several cancers via the lymphatics. Recently, the Slit2/Robo4 pathway has been recognized as a modulator of vascular permeability and integrity. Signaling via the Robo receptor inhibits VEGF-mediated effects; however, its effects on lymphatic endothelial cell function have not been well characterized. Results: We found that pretreatment with Slit2N, an active fragment of Slit2, inhibited VEGF-C-mediated lung-derived lymphatic endothelial cell (L-LEC) proliferation, migration, and in vitro tube formation. Slit2N induced the internalization of VEGFR-3, which blocked its activation, and inhibited the activation of the PI3K/Akt pathway by VEGF-C in L-LECs. Moreover, we found that inhibition of VEGF-C-induced effects by Slit2N was Robo4-dependent. Conclusion: These results indicate that Slit2N/Robo4 modulates several key cellular functions, which contribute to lymphangiogenesis, and identify this ligand-receptor pair as a potential therapeutic target to inhibit lymphatic metastasis of VEGF-C-overexpressing cancers and manage lymphatic dysfunctions characterized by VEGF-C/VEGFR-3 activation

Lagrange coded federated learning (L-CoFL) model for Internet of Vehicles

In Internet-of-Vehicles (IoV), smart vehicles can efficiently process various sensing data through federated learning (FL) - a privacy-preserving distributed machine learning (ML) approach that allows collaborative development of the shared ML model without any data exchange. However, traditional FL approaches suffer from poor security against the system noise, e.g., due to low-quality trained data, wireless channel errors, and malicious vehicles generating erroneous results, which affects the accuracy of the developed ML model. To address this problem, we propose a novel FL model based on the concept of Lagrange coded computing (LCC) - a coded distributed computing (CDC) scheme that enables enhancing the system security. In particular, we design the first L-CoFL (Lagrange coded FL) model to improve the accuracy of FL computations in the presence of lowquality trained data and wireless channel errors, and guarantee the system security against malicious vehicles. We apply the proposed L-CoFL model to predict the traffic slowness in IoV and verify the superior performance of our model through extensive simulations

Hidden species diversity in Pachyhynobius: a multiple approaches species delimitation with mitogenomes

The lack of distinct morphological features of cryptic species is a hard problem for taxonomy, especially when the taxa are closely related with considerable amounts of ancestral polymorphism. Lately, intensive coalescent-based analyses involving multiple loci have become the preferred method to assess the extent of genetic distinctiveness in otherwise phenotypically similar populations. Previously, phylogenetic studies on Pachyhynobius shangchengensis uncovered five extremely deeply divergent clades, which suggested that this species may be a cryptic species complex. In this study, we used the complete mitochondrial genome data and samples from the entire range of stout salamander (Pachyhynobius), as well as publicly available mitochondrial genomes to assess species boundaries within this genus using a suite of diverse methodologies (e.g. general mixed Yule coalescent model, Automatic Barcode Gap Discovery). The phylogenetic relationships recovered two major groups within P. shangchengensis, with one group formed by four of the six extant populations and corresponding to the central and eastern range of the Dabie mountains, while the other group encompassed two other lineages in the north west of the Dabie mountain range. The species delimitation comparison within Pachyhynobius supported the presence of recognized species within the genus, and consensus was observed across methods for the existence of up to five cryptic species within what has been traditionally considered to be P. shangchengensis. While this implies the existence of four taxa in addition to the described P. shangchengensis species, morphological data and life history information are further required to contribute to the species definition. The observed pattern of genetic variation is likely the outcome of a discontinuous habitat combined with niche conservatism, which produced the sky-island effect observed in Pachyhynobius, and which led to formation of a hidden species diversity in this genus

TencentPretrain: A Scalable and Flexible Toolkit for Pre-training Models of Different Modalities

Recently, the success of pre-training in text domain has been fully extended to vision, audio, and cross-modal scenarios. The proposed pre-training models of different modalities are showing a rising trend of homogeneity in their model structures, which brings the opportunity to implement different pre-training models within a uniform framework. In this paper, we present TencentPretrain, a toolkit supporting pre-training models of different modalities. The core feature of TencentPretrain is the modular design. The toolkit uniformly divides pre-training models into 5 components: embedding, encoder, target embedding, decoder, and target. As almost all of common modules are provided in each component, users can choose the desired modules from different components to build a complete pre-training model. The modular design enables users to efficiently reproduce existing pre-training models or build brand-new one. We test the toolkit on text, vision, and audio benchmarks and show that it can match the performance of the original implementations