Discrete Multi-modal Hashing with Canonical Views for Robust Mobile Landmark Search

Mobile landmark search (MLS) recently receives increasing attention for its great practical values. However, it still remains unsolved due to two important challenges. One is high bandwidth consumption of query transmission, and the other is the huge visual variations of query images sent from mobile devices. In this paper, we propose a novel hashing scheme, named as canonical view based discrete multi-modal hashing (CV-DMH), to handle these problems via a novel three-stage learning procedure. First, a submodular function is designed to measure visual representativeness and redundancy of a view set. With it, canonical views, which capture key visual appearances of landmark with limited redundancy, are efficiently discovered with an iterative mining strategy. Second, multi-modal sparse coding is applied to transform visual features from multiple modalities into an intermediate representation. It can robustly and adaptively characterize visual contents of varied landmark images with certain canonical views. Finally, compact binary codes are learned on intermediate representation within a tailored discrete binary embedding model which preserves visual relations of images measured with canonical views and removes the involved noises. In this part, we develop a new augmented Lagrangian multiplier (ALM) based optimization method to directly solve the discrete binary codes. We can not only explicitly deal with the discrete constraint, but also consider the bit-uncorrelated constraint and balance constraint together. Experiments on real world landmark datasets demonstrate the superior performance of CV-DMH over several state-of-the-art methods

The Cognitive Processes of Image Schema in Sino-American Economic News on The Belt and Road

This contrastive study decodes the language applications employed in news reports through image schematization to reproduce the ‘cognitive map’ of news writers in their ways of perceiving the world and exerting influence on news readers’ ways of perception. By analysing American economic news (AEN) and Chinese economic news (CEN) on the issue of ‘The Belt and Road’ (B&R) from the perspective of cognitive linguistics, the authors uncover and sketch out the hidden epistemic cognitive patterns and processes of both the Chinese and American writers. The study demonstrates that the schematic images and their constructions are organized in the mind of an individual as a network, with both metaphorical and formulaic schemas at different schematic levels, presenting a different process of cognitive entrenchment through which, in news discourses, image schema is utilized as a projection lens, projecting the covert cognitive processes onto overt language use and function

Predictive task assignment in spatial crowdsourcing: A data-driven approach

With the rapid development of mobile networks and the widespread usage of mobile devices, spatial crowdsourcing, which refers to assigning location-based tasks to moving workers, has drawn increasing attention. One of the major issues in spatial crowdsourcing is task assignment, which allocates tasks to appropriate workers. However, existing works generally assume the static offline scenarios, where the spatio-temporal information of all the workers and tasks is determined and known a priori. Ignorance of the dynamic spatio-temporal distributions of workers and tasks can often lead to poor assignment results. In this work we study a novel spatial crowdsourcing problem, namely Predictive Task Assignment (PTA), which aims to maximize the number of assigned tasks by taking into account both current and future workers/tasks that enter the system dynamically with location unknown in advance. We propose a two-phase data-driven framework. The prediction phase hybrids different learning models to predict the locations and routes of future workers and designs a graph embedding approach to estimate the distribution of future tasks. In the assignment component, we propose both greedy algorithm for large-scale applications and optimal algorithm with graph partition based decomposition. Extensive experiments on two real datasets demonstrate the effectiveness of our framework

Biphasic activation of PI3K/Akt and MAPK/Erk1/2 signaling pathways in bovine herpesvirus type 1 infection of MDBK cells

Many viruses have been known to control key cellular signaling pathways to facilitate the virus infection. The possible involvement of signaling pathways in bovine herpesvirus type 1 (BoHV-1) infection is unknown. This study indicated that infection of MDBK cells with BoHV-1 induced an early-stage transient and a late-stage sustained activation of both phosphatidylinositol 3-kinase (PI3K)/Akt and mitogen activated protein kinases/extracellular signal-regulated kinase 1/2 (MAPK/Erk1/2) signaling pathways. Analysis with the stimulation of UV-irradiated virus indicated that the virus binding and/or entry process was enough to trigger the early phase activations, while the late phase activations were viral protein expression dependent. Biphasic activation of both pathways was suppressed by the selective inhibitor, Ly294002 for PI3K and U0126 for MAPK kinase (MEK1/2), respectively. Furthermore, treatment of MDBK cells with Ly294002 caused a 1.5-log reduction in virus titer, while U0126 had little effect on the virus production. In addition, the inhibition effect of Ly294002 mainly occurred at the post-entry stage of the virus replication cycle. This revealed for the first time that BoHV-1 actively induced both PI3K/Akt and MAPK/Erk1/2 signaling pathways, and the activation of PI3K was important for fully efficient replication, especially for the post-entry stage

Quantitative assessment of damage during MCET: a parametric study in a rodent model

Abstract Background Myocardial cavitation-enabled therapy (MCET) has been proposed as a means to achieve minimally invasive myocardial reduction using ultrasound to produce scattered microlesions by cavitating contrast agent microbubbles. Methods Rats were treated using burst mode focused ultrasound at 1.5 MHz center frequency and varying envelope and pressure amplitudes. Evans blue staining indicated lethal cardiomyocytic injury. A previously developed quantitative scheme, evaluating the histologic treatment results, provides an insightful analysis for MCET treatment parameters. Such include ultrasound exposure amplitude and pulse modulation, contrast agent dose, and infusion rate. Results The quantitative method overcomes the limitation of visual scoring and works for a large dynamic range of treatment impact. Macrolesions are generated as an accumulation of probability driven microlesion formations. Macrolesions grow radially with radii from 0.1 to 1.6 mm as the ultrasound exposure amplitude (peak negative) increases from 2 to 4 MPa. To shorten treatment time, a swept beam was investigated and found to generate an acceptable macrolesion volume of about 40 μL for a single beam position. Conclusions Ultrasound parameters and administration of microbubbles directly influence lesion characteristics such as microlesion density and macrolesion dimension. For lesion generation planning, control of MCET is crucial, especially when targeting larger pre-clinical models.http://deepblue.lib.umich.edu/bitstream/2027.42/115462/1/40349_2015_Article_39.pd

Preparation and evaluation of ofloxacin-loaded palmitic acid solid lipid nanoparticles

The purpose of this study was to use solid lipid nanoparticles (SLN) to improve the pharmacological activity of ofloxacin. Ofloxacin-loaded SLN were prepared using palmitic acid as lipid matrix and poly vinyl alcohol (PVA) as emulsifier by a hot homogenization and ultrasonication method. The physicochemical characteristics of SLN were investigated by optical microscope, scanning electron microscopy, and photon correlation spectroscopy. Pharmacokinetics was studied after oral administration in mice. In vitro antibacterial activity and in vivo antibacterial efficacy of the SLN were investigated using minimal inhibitory concentrations (MIC) and a mouse protection model. The results demonstrated that the encapsulation efficiency, loading capacity, diameter, polydispersivity index, and zeta potential of the nanoparticles were 41.36% ± 1.50%, 4.40% ± 0.16%, 156.33 ± 7.51 nm, 0.26 ± 0.04, and −22.70 ± 1.40 mv, respectively. The SLN showed sustained release and enhanced antibacterial activity in vitro. Pharmacokinetic results demonstrated that SLN increased the bioavailability of ofloxacin by 2.27-fold, and extended the mean residence time of the drug from 10.50 to 43.44 hours. Single oral administrations of ofloxacin-loaded nanoparticles at 3 drug doses, 5 mg/kg, 10 mg/kg, and 20 mg/kg, all produced higher survival rates of lethal infected mice compared with native ofloxacin. These results indicate that SLN might be a promising delivery system to enhance the pharmacological activity of ofloxacin