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Predicting depth maps from monocular images has made an impressive performance in the past years. However, most depth estimation methods are trained with paired image-depth map data or multi-view images (e.g., stereo pair and monocular sequence), which suffer from expensive annotation costs and poor transferability. Although unsupervised domain adaptation methods are introduced to mitigate the reliance on annotated data, rare works focus on the unsupervised cross-scenario indoor monocular depth estimation. In this article, we propose to study the generalization of depth estimation models across different indoor scenarios in an adversarial-based domain adaptation paradigm. Concretely, a domain discriminator is designed for discriminating the representation from source and target domains, while the feature extractor aims to confuse the domain discriminator by capturing domain-invariant features. Further, we reconstruct depth maps from latent representations with the supervision of labeled source data. As a result, the feature extractor learned features possess the merit of both domain-invariant and low source risk, and the depth estimator can deal with the domain shift between source and target domains. We conduct the cross-scenario and cross-dataset experiments on the ScanNet and NYU-Depth-v2 datasets to verify the effectiveness of our method and achieve impressive performance. [ABSTRACT FROM AUTHOR]

Dynamic liquid crystal elastomers (LCEs) are a class of polymer networks characterized by the inclusion of both liquid crystalline monomers and dynamic covalent bonds. The unique properties realized through the combination of these moieties has produced a plethora of stimuli‐responsive materials to address a range of emerging technologies. While previous works have studied the incorporation of different dynamic bonds in LCEs, few (if any) have studied the effect of the specific placement of the dynamic bonds within an LCE network. A series of dynamic LCE networks were synthesized using a generalizable approach that employs a tandem thiol‐ene/yne chemistry which allows the location of the dynamic disulfide bond to be varied while maintaining similar network characteristics. When probing these systems in the LC regime, the thermomechanical properties were found to be largely similar. It is not until elevated temperatures (160–180 °C) that differences in the relaxation activation energies of these systems begin to materialize based solely on differences in placement of the dynamic bond throughout the network. This work demonstrates that through intentional dynamic bond placement, stress relaxation times can be tuned without affecting the LCE character. This insight can help optimize future dynamic LCE designs and achieve shorter processing times. [ABSTRACT FROM AUTHOR]

This article investigates a long-term optimal spatial pricing strategy for a ride-sourcing platform that serves a particular (possibly populated) area with profit-driven service providers (i.e., drivers) and time- and price-sensitive customers (i.e., passengers). By observing that oftentimes, the price strategy is anisotropic and spatial-dependent, both the supply and request are endogenous, and we build an analytical bi-level optimization mode. In the upper-level formulation, the ride-sourcing platform aims at setting up the spatially heterogeneous pricing strategy to maximize its total profit. However, in the lower level, we solve the trip distribution model that characterizes the flow rates among zones given the travel demand rate at each zone. We prove that when the platform seeks to expand its business, the optimal number of participating drivers and their optimal wages will be influenced not only by the pricing strategy but also by the level of service of the entire platform. Our further investigation shows that the profit at a particular zone can be influenced by the potential customers' service requests from other zones. Finally, we use the real-world data provided by DiDi Chuxing to numerically illustrate our model and theoretical results., Author(s): Wei Tang [1,2,3]; Heng Wang [4]; Yang Wang [1]; Chuqiao Chen [5]; Xiqun (Michael) Chen (corresponding author) [3] 1. Introduction The emergence of ride-sourcing companies such as Uber, Lyft, [...]

The emerging ride-sourcing service has become an important element of urban mobility. A challenging question underlying the provision of such service is how and to what extent the built environment affects origin-destination (OD) travel flows. This paper employs the geographically weighted regression (GWR) model to analyze the OD-based ride-sourcing travel flow. It makes a comparison with the existing ordinary least square (OLS) model and spatial autocorrelation model (SAM). We have collected ride-sourcing order data in Hangzhou, China, to provide an accurate source for acquiring ride-sourcing travel flow. We investigate the effects of the residential area, points of interest (POIs), and transit stations on ride-sourcing travel flow among traffic analysis zones (TAZs). The results show the following: (a) GWR has better goodness-of-fit than SAM and OLS. (b) Residential area, enterprise, and bus stations have positive correlations with ride-sourcing OD flows, but education and subway stations have negative correlations. We have further investigated the issue and found that it is not a causal relationship between the bus station and OD flow, due to collinearity between the two variables. The bus station builds on locations with high demand, but its capacity is not large enough to reduce the ride-sourcing flow to a low level, which results in a positive coefficient. (c) Based on the estimated coefficients, the prediction of ride-sourcing flows is feasible, supporting the impact analysis for urban land use and transportation planning. This paper contributes to understanding OD-based ride-sourcing travel flow distributions and provides a framework of long-term OD flow prediction for urban land use and transportation planning., Author(s): Chuqiao Chen [1]; Simon Hu [2]; Washington Y. Ochieng [3]; Na Xie [4]; Xiqun (Michael) Chen (corresponding author) [1] 1. Introduction The government agencies and urban planning department attach [...]

Background: Cervical cancer is prevalent throughout the world, and microRNA-497-5p (miR-497-5p) plays an important role in its development. However, the specific mechanism by which miR-497-5p targets the transferrin receptor (TFRC) during cervical cancer development has not been clarified., Objectives: The aim of the study was to unravel TFRC expression and its role in cervical cancer cells, as well as the impact of the miR-497-5p/TFRC axis on cervical cancer cells., Material and Methods: The target mRNA was determined through differential analysis, followed by the evaluation of its impact on survival and clinical staging. Then, quantitative real-time polymerase chain reaction (qPCR) was conducted to analyze the TFRC mRNA level in cervical cancer cells and normal cervical epithelial cells. Western blot (WB) was utilized to examine the expression levels of TFRC, cleaved caspase-3, cleaved caspase-9, and epithelial-mesenchymal transition (EMT)-related proteins. The miRNAs upstream of the target mRNA were predicted, and Pearson correlation analysis was performed, followed by the validation through the dual-luciferase reporter assay. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and colony formation assays were performed to analyze cancer cell viability, followed by a transwell assay aimed at measuring cell migratory and invasive abilities. Finally, flow cytometry was conducted to examine cell apoptosis and cell cycle., Results: The transferrin receptor was significantly increased in cervical cancer cells and positively associated with clinical T and N stages. Silencing TFRC could constrain cell proliferative, migratory and invasive abilities, arrest the cell cycle and facilitate cell apoptosis in cervical cancer cells. The bioinformatics analysis showed a significantly negative correlation between miR-497-5p and TFRC in cervical cancer. Moreover, upregulated miR-497-5p hampered cervical cancer progression and decreased TFRC expression. The overexpression of TFRC reversed the suppressive impact of miR-497-5p overexpression on cervical cancer progression., Conclusions: The modulatory role of the miR-497-5p/TFRC axis was confirmed in cervical cancer cells. This axis may present a new avenue for the diagnosis of cervical cancer and provide a novel target for cervical cancer treatment.

Vinylogous urethane (VU O ) based polymer networks are widely used as catalyst-free vitrimers that show rapid covalent bond exchange at elevated temperatures. In solution, vinylogous ureas (VU N ) undergo much faster bond exchange than VU O and are highly dynamic at room temperature. However, this difference in reactivity is not observed in their respective dynamic polymer networks, as VU O and VU N vitrimers prepared herein with very similar macromolecular architectures show comparable stress relaxation and creep behavior. However, by using mixtures of VU O and VU N linkages within the same network, the dynamic reactions can be accelerated by an order of magnitude. The results can be rationalized by the effect of intermolecular hydrogen bonding, which is absent in VU O vitrimers, but is very pronounced for vinylogous urea moieties. At low concentrations of VU N , these hydrogen bonds act as catalysts for covalent bond exchange, while at high concentration, they provide a pervasive vinylogous urea - urethane (VU) network of strong non-covalent interactions, giving rise to phase separation and inhibiting polymer chain dynamics. This offers a straightforward design principle for dynamic polymer materials, showing at the same time the possible additive and synergistic effects of supramolecular and dynamic covalent polymer networks., (© 2024 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH.)

CD38 was first identified as a lymphocyte-specific antigen and then has been found to be widely expressed in a variety of cell types. The functions of CD38 are involved in numerous biological processes including immune responses. Here, we showed the downregulations of both TLR2 mRNA and protein in macrophages from CD38 -/- mice and in CD38 knockdown RAW264.7 cells. Several NF- κ B-binding motifs in the promoter region of the TLR2 gene were identified by the bioinformatics analysis and were confirmed by the luciferase activity assay with the different truncated TLR2 promoters. CD38 deficiency resulted in the reduction of NF- κ B p65 and acetyl-NF- κ B p65 (Ac-p65) levels as determined by Western blot. The expression of Sirt1 did not change, but an increased activity of Sirt1 was observed in CD38-deficient macrophages. Inhibition of the Sirt1/NF- κ B signaling pathway resulted in downregulation of TLR2 expression in RAW264.7 cells. However, re-expression of CD38 in the knockdown clones reversed the effect on Sirt1/NF- κ B/TLR2 signaling, which is NAD-dependent. Moreover, the inflammatory cytokines including G-CSF, IL-1alpha, IL-6, MCP-1, MIP-1alpha, and RANTES were increased in CD38 knockdown RAW264.7 cells. Taken together, our data demonstrated that CD38 deficiency enhances inflammatory response in macrophages, and the mechanism may be partly associated with increased Sirt1 activity, which promoted NF- κ B deacetylation and then inhibited expression of the TLR2 gene. Obviously, our study may provide an insight into the molecular mechanisms in CD38-mediated inflammation.