Measuring Product Type With Dynamics of Online Product Review Variance

The concept of “product type” (experience versus search product) is increasingly important in business research and practice. However, it is not defined or measured precisely in the Internet age due to significantly lower search cost and changes in consumer information search behavior resulting from reliance on information and communications technology. We take advantage of the greatly available micro level online word-of-mouth data and infer product type based on statistical properties of online word of mouth (specifically, online product reviews). We draw on the theories from statistics and literature on informational content of online product reviews to analytically propose a mechanism to classify products. We further collect archival data to categorize the products and services. Implications of this analytical tool and empirical findings for research, theory and managerial practice are discussed

Effect of Auction Design on Bidder Entry: Evidence from An Online Labor Market

We propose that auction duration and auction description are two important auction design parameters that could serve as screening mechanisms for quality in online auctions. Using data from an online labor matching platform that connects buyers with IT service vendors, we examine the effects of auction duration and auction descriptions on auction outcomes (i.e., number of bids, bidder quality, bidding price) and project outcomes (i.e., project being contracted and being completed). Our empirical analyses show that, in buyer-determined reverse auctions of online labor matching, auctions with a longer duration and a longer description attract more bids, but they also attract more low quality bidders with less experience and lower completion rate, and hence result in a lower probability of successful contracting and completion of software service projects. Our research provides empirical evidence highlighting the strategic roles of auction design parameters like auction duration and descriptions as a potential screening mechanism for online labor matching platforms

Curvature-based Transformer for Molecular Property Prediction

The prediction of molecular properties is one of the most important and challenging tasks in the field of artificial intelligence-based drug design. Among the current mainstream methods, the most commonly used feature representation for training DNN models is based on SMILES and molecular graphs, although these methods are concise and effective, they also limit the ability to capture spatial information. In this work, we propose Curvature-based Transformer to improve the ability of Graph Transformer neural network models to extract structural information on molecular graph data by introducing Discretization of Ricci Curvature. To embed the curvature in the model, we add the curvature information of the graph as positional Encoding to the node features during the attention-score calculation. This method can introduce curvature information from graph data without changing the original network architecture, and it has the potential to be extended to other models. We performed experiments on chemical molecular datasets including PCQM4M-LST, MoleculeNet and compared with models such as Uni-Mol, Graphormer, and the results show that this method can achieve the state-of-the-art results. It is proved that the discretized Ricci curvature also reflects the structural and functional relationship while describing the local geometry of the graph molecular data

NF-Atlas: Multi-Volume Neural Feature Fields for Large Scale LiDAR Mapping

LiDAR Mapping has been a long-standing problem in robotics. Recent progress in neural implicit representation has brought new opportunities to robotic mapping. In this paper, we propose the multi-volume neural feature fields, called NF-Atlas, which bridge the neural feature volumes with pose graph optimization. By regarding the neural feature volume as pose graph nodes and the relative pose between volumes as pose graph edges, the entire neural feature field becomes both locally rigid and globally elastic. Locally, the neural feature volume employs a sparse feature Octree and a small MLP to encode the submap SDF with an option of semantics. Learning the map using this structure allows for end-to-end solving of maximum a posteriori (MAP) based probabilistic mapping. Globally, the map is built volume by volume independently, avoiding catastrophic forgetting when mapping incrementally. Furthermore, when a loop closure occurs, with the elastic pose graph based representation, only updating the origin of neural volumes is required without remapping. Finally, these functionalities of NF-Atlas are validated. Thanks to the sparsity and the optimization based formulation, NF-Atlas shows competitive performance in terms of accuracy, efficiency and memory usage on both simulation and real-world datasets

Effects of Tea Residue Extracts with Different Molecular Weight on the Pasting Characteristics of Potato Starch

Tea residues are the remaining residue of tea after processing and utilization, which are rich in multiple active components. To investigate the effects of different types and molecular weights of tea residue extracts on the pasting characteristics of potato starch (PS), the ethanol extract (TRE), water extract (TRW) and alkali extract (TRA) of tea residue were obtained by continuous extraction method. On this basis, the different molecular weights of ethanol extract (TRE-1, 30 kDa) and water extract (TRW-1, 100 kDa) were prepared by a membrane separation. The effects of different tea residue extracts on the viscosity properties were investigated, and the microstructure of potato starch added with tea residue extract was observed by scanning electron microscopy (SEM). The results showed that different types and molecular weights of tea residue extracts could significantly (PTRW-2>TRE-2>TRW-1>TRE-1. The peak viscosity of potato starch was gradually decreased with the increase of different extracts. After adding 10% TRA, TRW-2, TRE-2, TRW-1 and TRE-1, the peak viscosity of potato starch was 4624, 5013, 5431, 5911 and 6195 cP, respectively. TRE-2, TRW-2 and TRA could better promote the link between potato starch fragments and result in a more complete and smooth lamellar structure, compared with TRE-1, TRW-1. In summary, the addition of different types and molecular weights of tea residue extracts could effectively inhibit the gelatinization of potato starch, and the inhibitory effect of 10% alkali extract was the best

The multivalent adhesion molecule SSO1327 plays a key role in Shigella sonnei pathogenesis : SSO1327 is an adhesin required for S. sonnei pathogenesis

Shigella sonnei is a bacterial pathogen and causative agent of bacillary dysentery. It deploys a type III secretion system to inject effector proteins into host epithelial cells and macrophages, an essential step for tissue invasion and immune evasion. Although the arsenal of bacterial effectors and their cellular targets have been studied extensively, little is known about the prerequisites for deployment of type III secreted proteins during infection. Here, we describe a novel S. sonnei adhesin, SSO1327 which is a Multivalent Adhesion Molecule (MAM) required for invasion of epithelial cells and macrophages and for infection in vivo. The S. sonnei MAM mediates intimate attachment to host cells, which is required for efficient translocation of type III effectors into host cells. SSO1327 is non-redundant to IcsA; its activity is independent of type III secretion. In contrast to the up-regulation of IcsA-dependent and independent attachment and invasion by deoxycholate in S. flexneri, deoxycholate negatively regulates IcsA and MAM in S. sonnei resulting in reduction in attachment and invasion and virulence attenuation in vivo. A strain deficient for SSO1327 is avirulent in vivo but still elicits a host immune response

The Creation of Local Entrepreneurial Clusters : Study based on the Observations on the Merchants of Wenzhou

温州市の産業集積には，必ずその背景に当該地域に大量の企業家が同一産業に従事する「企業家クラスター」が存在する．企業家クラスターは単に製造業の産業集積という形で顕現するだけでなく，例えば温州市永嘉県橋頭鎮の出身者で広東省に事務所を構えて国際的なアパレルや革靴のブランド代理業を営む企業家が非常に多い．永嘉県花坦郷の出身者は中国各地の都市近郊でスーパーを営んでいる．こうした企業家クラスターの輩出を説明するには社会ネットワークと温州特有の文化の影響を考える必要がある．Behind all the industrial clusters in Wenzhou, which is famous for having many industrial clusters, there exist “entrepreneurial clusters”, which denote that a lot of local entrepreneurs engage in the same kind of business. “Entrepreneurial clusters” not only manifest themselves as manufacturing industrial clusters but also in other forms. For example, many entrepreneurs from Qiaotou Town, Yongjia County, Wenzhou, engage in the agency business of international apparel and shoe brands, having their headquarters in Guangdong Province. Many people from Huadan Town, Yongjia County, run supermarkets at the suburbs throughout China. The emergence of such “entrepreneurial clusters” can be explained by social networks and the peculiar culture of Wenzhou.特集　中国沿海部の産業集

Potential effects of specific gut microbiota on periodontal disease: a two-sample bidirectional Mendelian randomization study

IntroductionPeriodontal disease (PD) presents a substantial global health challenge, encompassing conditions from reversible gingivitis to irreversible periodontitis, often culminating in tooth loss. The gut-oral axis has recently emerged as a focal point, with potential gut microbiota dysbiosis exacerbating PD.MethodsIn this study, we employed a double-sample bidirectional Mendelian randomized (MR) approach to investigate the causal relationship between specific gut microbiota and periodontal disease (PD) and bleeding gum (BG) development, while exploring the interplay between periodontal health and the gut microenvironment. We performed genome-wide association studies (GWAS) with two cohorts, totalling 346,731 (PD and control) and 461,113 (BG and control) participants, along with data from 14,306 participants’ intestinal flora GWAS, encompassing 148 traits (31 families and 117 genera). Three MR methods were used to assess causality, with the in-verse-variance-weighted (IVW) measure as the primary outcome. Cochrane’s Q test, MR-Egger, and MR-PRESSO global tests were used to detect heterogeneity and pleiotropy. The leave-one-out method was used to test the stability of the MR results. An F-statistic greater than 10 was accepted for instrument exposure association.Results and conclusionSpecifically, Eubacterium xylanophilum and Lachnoclostridium were associated with reduced gum bleeding risk, whereas Anaerotruncus, Eisenbergiella, and Phascolarctobacterium were linked to reduced PD risk. Conversely, Fusicatenibacter was associated with an elevated risk of PD. No significant heterogeneity or pleiotropy was detected. In conclusion, our MR analysis pinpointed specific gut flora with causal connections to PD, offering potential avenues for oral health interventions