373 research outputs found

    A comparative study of two molecular mechanics models based on harmonic potentials

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    We show that the two molecular mechanics models, the stick-spiral and the beam models, predict considerably different mechanical properties of materials based on energy equivalence. The difference between the two models is independent of the materials since all parameters of the beam model are obtained from the harmonic potentials. We demonstrate this difference for finite width graphene nanoribbons and a single polyethylene chain comparing results of the molecular dynamics (MD) simulations with harmonic potentials and the finite element method with the beam model. We also find that the difference strongly depends on the loading modes, chirality and width of the graphene nanoribbons, and it increases with decreasing width of the nanoribbons under pure bending condition. The maximum difference of the predicted mechanical properties using the two models can exceed 300% in different loading modes. Comparing the two models with the MD results of AIREBO potential, we find that the stick-spiral model overestimates and the beam model underestimates the mechanical properties in narrow armchair graphene nanoribbons under pure bending condition.Comment: 40 pages, 21 figure

    Route Selection and Distribution Cost of Express Delivery: An Urban Metro Network Based Study

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    Route selection and distribution costs of express delivery based on the urban metro network, referred to as metro express delivery (MeD), is addressed in this study. Considering the characteristics of express delivery transportation and the complexity of the urban metro network, three distribution modes of different time periods are proposed and a strict integrated integer linear programming model is developed to minimize total distribution costs. To effectively solve the optimal problem, a standard genetic algorithm was improved and designed. Finally, the Ningbo subway network is used as an example to confirm the practicability and effectiveness of the model and algorithm. The results show that when the distribution number of express delivery packages is 1980, the three different MeD modes can reduce transportation costs by 40.5%, 62.0%, and 59.0%, respectively. The results of the case analysis will help guide express companies to collaborate with the urban metro network and choose the corresponding delivery mode according to the number of express deliveries required

    A Transformer-based Framework for POI-level Social Post Geolocation

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    POI-level geo-information of social posts is critical to many location-based applications and services. However, the multi-modality, complexity and diverse nature of social media data and their platforms limit the performance of inferring such fine-grained locations and their subsequent applications. To address this issue, we present a transformer-based general framework, which builds upon pre-trained language models and considers non-textual data, for social post geolocation at the POI level. To this end, inputs are categorized to handle different social data, and an optimal combination strategy is provided for feature representations. Moreover, a uniform representation of hierarchy is proposed to learn temporal information, and a concatenated version of encodings is employed to capture feature-wise positions better. Experimental results on various social datasets demonstrate that three variants of our proposed framework outperform multiple state-of-art baselines by a large margin in terms of accuracy and distance error metrics.Comment: Full papers are 12 pages in length plus additional 4 pages for references (turns to 18 pages in total after submitting to arxiv). One figure and 5 tables are contained. This paper was submitted to ECIR 2023 for revie

    Optimization of Location-Routing for the Waste Household Appliances Recycling Logistics under the Uncertain Condition

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    Waste household appliances and electronic products usually contain harmful substances which need scientific and reasonable collection, classification, processing, recovery and disposal to achieve sustainable and effective recycling and utilization. In recent years, due to the poor management of waste household appliances recycling logistics system, safety accidents occur frequently, which seriously harm the health and life safety of the society. This paper studies the risk management of recycling waste household appliances under uncertain conditions and establishes a risk measurement model under fuzzy population density. Considering the multi-stage and classification diversity of waste household appliances recycling logistics, the multi-objective location routing model and location - routing model are established respectively. Based on the model complexity analysis, the solution method of multi-objective model is designed. Finally, the validity of the model and algorithm is verified by examples and tests

    Exploring the Cosmic Reionization Epoch in Frequency Space: An Improved Approach to Remove the Foreground in 21 cm Tomography

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    Aiming to correctly restore the redshifted 21 cm signals emitted by the neutral hydrogen during the cosmic reionization processes, we re-examine the separation approaches based on the quadratic polynomial fitting technique in frequency space to investigate whether they works satisfactorily with complex foreground, by quantitatively evaluate the quality of restored 21 cm signals in terms of sample statistics. We construct the foreground model to characterize both spatial and spectral substructures of the real sky, and use it to simulate the observed radio spectra. By comparing between different separation approaches through statistical analysis of restored 21 cm spectra and corresponding power spectra, as well as their constraints on the mean halo bias bb and average ionization fraction xex_e of the reionization processes, at z=8z=8 and the noise level of 60 mK we find that, although the complex foreground can be well approximated with quadratic polynomial expansion, a significant part of Mpc-scale components of the 21 cm signals (75% for 6h1\gtrsim 6h^{-1} Mpc scales and 34% for 1h1\gtrsim 1h^{-1} Mpc scales) is lost because it tends to be mis-identified as part of the foreground when single-narrow-segment separation approach is applied. The best restoration of the 21 cm signals and the tightest determination of bb and xex_e can be obtained with the three-narrow-segment fitting technique as proposed in this paper. Similar results can be obtained at other redshifts.Comment: 33 pages, 14 figures. Accepted for publication in Ap

    A Damage Identification Approach for Offshore Jacket Platforms Using Partial Modal Results and Artificial Neural Networks

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    This paper presents a damage identification method for offshore jacket platforms using partially measured modal results and based on artificial intelligence neural networks. Damage identification indices are first proposed combining information of six modal results and natural frequencies. Then, finite element models are established, and damages in structural members are assumed by reducing the structural elastic modulus. From the finite element analysis for a training sample, both the damage identification indices and the damages are obtained, and neural networks are trained. These trained networks are further tested and used for damage prediction of structural members. The calculation results show that the proposed method is quite accurate. As the considered measurement points of the jacket platform are near the waterline, the prediction errors keep below 8% when the damaged members are close to the waterline, but may rise to 16.5% when the damaged members are located in deeper waters.publishedVersionNivå

    Upregulation of tetraspanin 8 may contribute to LPSinduced acute lung injury by activation of the MAPK and NF-κB pathways

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    Purpose: To investigate the effect of tetraspanin8 (Tspan8, also known as TM4SF3 or CO-029) on lipopolysaccharide (LPS)-induced acute lung injury (ALI) and the related signaling pathways.Methods: Treatment with LPS was used to induce lung damage in mice and a lung epithelial cell line. The wet-to-dry weight ratio of lung tissue, hematoxylin and eosin (H&E) staining, and quantification of cytokine concentrations were conducted to validate the model. Enzyme-linked immunosorbent assays (ELISA) and quantitative polymerase chain reaction (qPCR) were used to measure levels of tumor necrosis factor alpha, interleukin (IL)-1β, and IL-6. Tspan8 levels were knocked down using shRNAs. Mitogen-activated protein kinase (MAPK) and nuclear factor kappa B (NF-κB) pathway levels were assessed after LPS-induced injury in this cellular model.Results: Levels of Tspan8 were upregulated in the LPS-induced ALI model. Additionally, LPS treatment of mouse lung epithelial cells resulted in Tspan8 upregulation. Tspan8 knockdown alleviated the effects of LPS on lung epithelial injury by inhibiting the upregulation of MAPK and NF-κB signaling pathways.Conclusion: The upregulation of Tspan8 may promote the progression of ALI
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