How Does the Winner-selection Mechanism Affect Users’ Participation in Online Brand Communities: The Moderating Role of Power Distance Beliefs

The advent of Web 2.0 has led to the utilization of online brand communities (OBCs) as a critical marketing tool for companies to disseminate information on their latest products, offer customer support, and build relationships with customers. However, many OBCs face challenges in retaining active users\u27 participation. To address this issue, some OBCs have recently incorporated contests into their platforms to incentivize community members to participate. Nonetheless, there is a dearth of research on the impact of winner-selection mechanisms in these competitions. This study seeks to investigate the effect of these mechanisms on community members\u27 intention to participate and to examine how power distance beliefs (PDBs) moderate this relationship. The findings of this study can expand our understanding of the impact of the winner-selection mechanism on users’ participation in OBCs and offer recommendations to OBCs’ organizers on how and when to leverage the factors to enhance user participation

Whole-Body Lesion Segmentation in 18F-FDG PET/CT

There has been growing research interest in using deep learning based method to achieve fully automated segmentation of lesion in Positron emission tomography computed tomography(PET CT) scans for the prognosis of various cancers. Recent advances in the medical image segmentation shows the nnUNET is feasible for diverse tasks. However, lesion segmentation in the PET images is not straightforward, because lesion and physiological uptake has similar distribution patterns. The Distinction of them requires extra structural information in the CT images. The present paper introduces a nnUNet based method for the lesion segmentation task. The proposed model is designed on the basis of the joint 2D and 3D nnUNET architecture to predict lesions across the whole body. It allows for automated segmentation of potential lesions. We evaluate the proposed method in the context of AutoPet Challenge, which measures the lesion segmentation performance in the metrics of dice score, false-positive volume and false-negative volume

Seismic system reliability analysis of bridges using the multiplicative dimensional reduction method

A combined method of finite element reliability analysis and multiplicative dimensional reduction method (M-DRM) is proposed for systems reliability analysis of practical bridge structures. The probability distribution function of a structural response is derived based on the maximum entropy principle. To illustrate the accuracy and efficiency of the proposed approach, a simply supported bridge structure is adopted and the failure probability obtained are compared with the Monte Carlo simulation method. The validated method is then applied for the system reliability analysis for a practical high-pier rigid frame railway bridge located at the seismic-prone region. The finite element model of the bridge is developed using OpenSees and the M-DRM method is used to analyse the structural system reliability under earthquake loading

Highly Stable Luminous "snakes" from CsPbX3 Perovskite Nanocrystals Anchored on Amine-Coated Silica Nanowires

CsPbX3 (X = Cl, Br, and I) perovskite nanocrystals (NCs) are known for their exceptional optoelectronic properties, yet the material's instability toward polar solvents, heat, or UV irradiation greatly limits its further applications. Herein, an efficient in situ growing strategy has been developed to give highly stable perovskite NC composites (abbreviated CsPbX3@CA-SiO2) by anchoring CsPbX3 NCs onto silica nanowires (NWs), which effectively depresses the optical degradation of their photoluminescence (PL) and enhances stability. The preparation of surface-functionalized serpentine silica NWs is realized by a sol-gel process involving hydrolysis of a mixture of tetraethyl orthosilicate (TEOS), 3-aminopropyltriethoxysilane (APTES), and trimethoxy(octadecyl)silane (TMODS) in a water/oil emulsion. The serpentine NWs are formed via an anisotropic growth with lengths up to 8 μm. The free amino groups are employed as surface ligands for growing perovskite NCs, yielding distributed monodisperse NCs (∼8 nm) around the NW matrix. The emission wavelength is tunable by simple variation of the halide compositions (CsPbX3, X = Cl, Br, or I), and the composites demonstrate a high photoluminescence quantum yield (PLQY 32-69%). Additionally, we have demonstrated the composites CsPbX3@CA-SiO2 can be self-woven to form a porous 3D hierarchical NWs membrane, giving rise to a superhydrophobic surface with hierarchical micro/nano structural features. The resulting composites exhibit high stability toward water, heat, and UV irradiation. This work elucidates an effective strategy to incorporate perovskite nanocrystals onto functional matrices as multifunctional stable light sources