Green Vehicle Routing Optimization Based on Carbon Emission and Multiobjective Hybrid Quantum Immune Algorithm

© 2018 Xiao-Hong Liu et al. Green Vehicle Routing Optimization Problem (GVROP) is currently a scientific research problem that takes into account the environmental impact and resource efficiency. Therefore, the optimal allocation of resources and the carbon emission in GVROP are becoming more and more important. In order to improve the delivery efficiency and reduce the cost of distribution requirements through intelligent optimization method, a novel multiobjective hybrid quantum immune algorithm based on cloud model (C-HQIA) is put forward. Simultaneously, the computational results have proved that the C-HQIA is an efficient algorithm for the GVROP. We also found that the parameter optimization of the C-HQIA is related to the types of artificial intelligence algorithms. Consequently, the GVROP and the C-HQIA have important theoretical and practical significance

Minimal basilar membrane motion in low-frequency hearing

Low-frequency hearing is critically important for speech and music perception, but no mechanical measurements have previously been available from inner ears with intact low-frequency parts. These regions of the cochlea may function in ways different from the extensively studied high-frequency regions, where the sensory outer hair cells produce force that greatly increases the sound-evoked vibrations of the basilar membrane. We used laser interferometry in vitro and optical coherence tomography in vivo to study the low-frequency part of the guinea pig cochlea, and found that sound stimulation caused motion of a minimal portion of the basilar membrane. Outside the region of peak movement, an exponential decline in motion amplitude occurred across the basilar membrane. The moving region had different dependence on stimulus frequency than the vibrations measured near the mechanosensitive stereocilia. This behavior differs substantially from the behavior found in the extensively studied high-frequency regions of the cochlea

A generalized Drucker–Prager viscoplastic yield surface model for asphalt concrete

A Generalized Drucker-Prager (GD-P) viscoplastic yield surface model was developed and validated for asphalt concrete. The GD-P model was formulated based on fabric tensor modified stresses to consider the material inherent anisotropy. A smooth and convex octahedral yield surface function was developed in the GD-P model to characterize the full range of the internal friction angles from 0 to 90 degrees. In contrast, the existing Extended Drucker-Prager (ED-P) was demonstrated to be applicable only for a material that has an internal friction angle less than 22 degrees. Laboratory tests were performed to evaluate the anisotropic effect and to validate the GD-P model. Results indicated that 1) the yield stresses of an isotropic yield surface model are greater in compression and less in extension than that of an anisotropic model, which can result in an under-prediction of the viscoplastic deformation; and 2) the yield stresses predicted by the GD-P model matched well with the experimental results of the octahedral shear strength tests at different normal and confining stresses. By contrast, the ED-P model over-predicted the octahedral yield stresses, which can lead to an under-prediction of the permanent deformation. In summary, the rutting depth of an asphalt pavement would be underestimated without considering anisotropy and convexity of the yield surface for asphalt concrete. The proposed GD-P model was demonstrated to be capable of overcoming these limitations of the existing yield surface models for the asphalt concrete.Financial support was provided by the U.S. Department of Transportation (USDOT) and the Texas state general revenue funds through Southwest Region University Transportation Center (SWUTC No. 600451-00006). The validation shear tests of this study are based upon the work supported by the National Science Foundation under Grant No. 0943140.This is the accepted manuscript version. The final version is available from Springer at http://dx.doi.org/10.1617/s11527-014-0425-1

Provenance-Centered Dataset of Drug-Drug Interactions

Over the years several studies have demonstrated the ability to identify potential drug-drug interactions via data mining from the literature (MEDLINE), electronic health records, public databases (Drugbank), etc. While each one of these approaches is properly statistically validated, they do not take into consideration the overlap between them as one of their decision making variables. In this paper we present LInked Drug-Drug Interactions (LIDDI), a public nanopublication-based RDF dataset with trusty URIs that encompasses some of the most cited prediction methods and sources to provide researchers a resource for leveraging the work of others into their prediction methods. As one of the main issues to overcome the usage of external resources is their mappings between drug names and identifiers used, we also provide the set of mappings we curated to be able to compare the multiple sources we aggregate in our dataset.Comment: In Proceedings of the 14th International Semantic Web Conference (ISWC) 201

Password-conditioned Anonymization and Deanonymization with Face Identity Transformers

Cameras are prevalent in our daily lives, and enable many useful systems built upon computer vision technologies such as smart cameras and home robots for service applications. However, there is also an increasing societal concern as the captured images/videos may contain privacy-sensitive information (e.g., face identity). We propose a novel face identity transformer which enables automated photo-realistic password-based anonymization as well as deanonymization of human faces appearing in visual data. Our face identity transformer is trained to (1) remove face identity information after anonymization, (2) make the recovery of the original face possible when given the correct password, and (3) return a wrong--but photo-realistic--face given a wrong password. Extensive experiments show that our approach enables multimodal password-conditioned face anonymizations and deanonymizations, without sacrificing privacy compared to existing anonymization approaches.Comment: ECCV 202

Dual pulse shaping transmission with complementary nyquist pulses

© 2019 IEEE. The concept of complementary Nyquist pulse is introduced in this paper. Making use of a half rate Nyquist pulse and its complementary one, a dual pulse shaping transmission scheme is proposed, which achieves full Nyquist rate transmission with only a half of the sampling rate required by conventional Nyquist pulse shaping. This is essential for realizing high-speed digital communication systems with available and affordable data conversion devices. The condition for cross-symbol interference free transmission with the proposed dual pulse shaping is proved in theory, and two classes of ideal complementary Nyquist pulses are formulated assuming raised-cosine pulse shaping. Simulation results are also presented to demonstrate the improved spectral efficiency with dual pulse shaping and compare other system performance against conventional Nyquist pulse shaping

Topological Homogeneity for Electron Microscopy Images

In this paper, the concept of homogeneity is defined, from a topological perspective, in order to analyze how uniform is the material composition in 2D electron microscopy images. Topological multiresolution parameters are taken into account to obtain better results than classical techniques.Ministerio de Economía y Competitividad MTM2016-81030-PMinisterio de Economía y Competitividad TEC2012-37868-C04-0

EveTAR: Building a Large-Scale Multi-Task Test Collection over Arabic Tweets

This article introduces a new language-independent approach for creating a large-scale high-quality test collection of tweets that supports multiple information retrieval (IR) tasks without running a shared-task campaign. The adopted approach (demonstrated over Arabic tweets) designs the collection around significant (i.e., popular) events, which enables the development of topics that represent frequent information needs of Twitter users for which rich content exists. That inherently facilitates the support of multiple tasks that generally revolve around events, namely event detection, ad-hoc search, timeline generation, and real-time summarization. The key highlights of the approach include diversifying the judgment pool via interactive search and multiple manually-crafted queries per topic, collecting high-quality annotations via crowd-workers for relevancy and in-house annotators for novelty, filtering out low-agreement topics and inaccessible tweets, and providing multiple subsets of the collection for better availability. Applying our methodology on Arabic tweets resulted in EveTAR , the first freely-available tweet test collection for multiple IR tasks. EveTAR includes a crawl of 355M Arabic tweets and covers 50 significant events for which about 62K tweets were judged with substantial average inter-annotator agreement (Kappa value of 0.71). We demonstrate the usability of EveTAR by evaluating existing algorithms in the respective tasks. Results indicate that the new collection can support reliable ranking of IR systems that is comparable to similar TREC collections, while providing strong baseline results for future studies over Arabic tweets

Neutron Electric Dipole Moment Constraint on Scale of Minimal Left-Right Symmetric Model

Using an effective theory approach, we calculate the neutron electric dipole moment (nEDM) in the minimal left-right symmetric model with both explicit and spontaneous CP violations. We integrate out heavy particles to obtain flavor-neutral CP-violating effective Lagrangian. We run the Wilson coefficients from the electroweak scale to the hadronic scale using one-loop renormalization group equations. Using the state-of-the-art hadronic matrix elements, we obtain the nEDM as a function of right-handed W-boson mass and CP-violating parameters. We use the current limit on nEDM combined with the kaon-decay parameter $\epsilon$ to provide the most stringent constraint yet on the left-right symmetric scale $M_{W_R} > (10 \pm 3)$ TeV.Comment: 20 pages and 8 figure

Simultaneous determination of natural and synthetic steroid estrogens and their conjugates in aqueous matrices by liquid chromatography / mass spectrometry

An analytical method for the simultaneous determination of nine free and conjugated steroid estrogens was developed with application to environmental aqueous matrices. Solid phase extraction (SPE) was employed for isolation and concentration, with detection by liquid chromatography/mass spectrometry (LC/MS) using electrospray ionisation (ESI) in the negative mode. Method recoveries for various aqueous matrices (wastewater, lake and drinking water) were determined, recoveries proving to be sample dependent. When spiked at 50 ng/l concentrations in sewage influent, recoveries ranged from 62-89 % with relative standard deviations (RSD) < 8.1 %. In comparison, drinking water spiked at the same concentrations had recoveries between 82-100 % with an RSD < 5%. Ion suppression is a known phenomenon when using ESI; hence its impact on method recovery was elucidated for raw sewage. Both ion suppression from matrix interferences and the extraction procedure has bearing on the overall method recovery. Analysis of municipal raw sewage identified several of the analytes of interest at ng/l concentrations, estriol (E3) being the most abundant. Only one conjugate, estrone 3-sulphate (E1-3S) was observe