Network Externality and Trust in Agent-Based Social Commerce

The social commerce platform engages users in an agent-led network, leveraging local ties and communal trust. Agents are neighborhood influencers facilitating user referral, community engagement, and product marketing. We study the economic value of the agents to the platform based on their native endowed network externality and the trust formulated from the interaction with the users. Using detailed performance and referral data from a leading social commerce platform in Indonesia, we find that (1) agents with a higher level of endowed network externality outperform the ones with a lower level; (2) a more trustworthy and, surprisingly, less connected agent produces higher community sales; and (3) user’s perceived benevolence of the agent positively moderates the referral effect. The results suggest that the platform faces a trade-off between capitalizing on agents’ social connections and nurturing community trust

Efficiently Disassemble-and-Pack for Mechanism

In this paper, we present a disassemble-and-pack approach for a mechanism to seek a box which contains total mechanical parts with high space utilization. Its key feature is that mechanism contains not only geometric shapes but also internal motion structures which can be calculated to adjust geometric shapes of the mechanical parts. Our system consists of two steps: disassemble mechanical object into a group set and pack them within a box efficiently. The first step is to create a hierarchy of possible group set of parts which is generated by disconnecting the selected joints and adjust motion structures of parts in groups. The aim of this step is seeking total minimum volume of each group. The second step is to exploit the hierarchy based on breadth-first-search to obtain a group set. Every group in the set is inserted into specified box from maximum volume to minimum based on our packing strategy. Until an approximated result with satisfied efficiency is accepted, our approach finish exploiting the hierarchy.Comment: 2 pages, 2 figure

E3 ligase ligand optimization of Clinical PROTACs

Proteolysis targeting chimeras (PROTACs) technology can realize the development of drugs for non-druggable targets that are difficult to achieve with traditional small molecules, and therefore has attracted extensive attention from both academia and industry. Up to now, there are more than 600 known E3 ubiquitin ligases with different structures and functions, but only a few have developed corresponding E3 ubiquitin ligase ligands, and the ligands used to design PROTAC molecules are limited to a few types such as VHL (Von-Hippel-Lindau), CRBN (Cereblon), MDM2 (Mouse Doubleminute 2 homolog), IAP (Inhibitor of apoptosis proteins), etc. Most of the PROTAC molecules that have entered clinical trials were developed based on CRBN ligands, and only DT2216 was based on VHL ligand. Obviously, the structural optimization of E3 ubiquitin ligase ligands plays an instrumental role in PROTAC technology from bench to bedside. In this review, we review the structure optimization process of E3 ubiquitin ligase ligands currently entering clinical trials on PROTAC molecules, summarize some characteristics of these ligands in terms of druggability, and provide some preliminary insights into their structural optimization. We hope that this review will help medicinal chemists to develop more druggable molecules into clinical studies and to realize the greater therapeutic potential of PROTAC technology

Visual saliency guided textured model simplification

Mesh geometry can be used to model both object shape and details. If texture maps are involved, it is common to let mesh geometry mainly model object shapes and let the texture maps model the most object details, optimising data size and complexity of an object. To support efficient object rendering and transmission, model simplification can be applied to reduce the modelling data. However, existing methods do not well consider how object features are jointly represented by mesh geometry and texture maps, having problems in identifying and preserving important features for simplified objects. To address this, we propose a visual saliency detection method for simplifying textured 3D models. We produce good simplification results by jointly processing mesh geometry and texture map to produce a unified saliency map for identifying visually important object features. Results show that our method offers a better object rendering quality than existing methods

Skyrmion-Bubble Bundles in an X-type Sr2Co2Fe28O46 Hexaferrite above Room Temperature

Magnetic skyrmions are spin swirls that possess topological nontriviality and are considered particle-like entities. They are distinguished by an integer topological charge Q. The presence of skyrmion bundles provides an opportunity to explore the range of values for Q, which is crucial for the advancement of topological spintronic devices with multi-Q properties. In this study, we present a new material candidate, Sr2Co2Fe28O46 hexaferrite of the X-type, which hosts small dipolar skyrmions at room temperature and above. By exploiting reversed magnetic fields from metastable skyrmion bubbles at zero fields, we can incorporate skyrmion-bubble bundles with different interior skyrmion/bubble numbers, topological charges, and morphologies at room temperature. Our experimental findings are consistently supported by micromagnetic simulations. Our results highlight the versatility of topological spin textures in centrosymmetric uniaxial magnets, thereby paving the way for the development of room-temperature topological spintronic devices with multi-Q characteristics.Comment: https://doi.org/10.1002/adma.20230611