Cell receptor-independent infection by a neurotropic murine coronavirus.

The cellular receptors for a coronavirus, mouse hepatitis virus (MHV), have been recently identified as one or more members of the carcinoembryonic antigen (CEA) family. The neurotropic JHM strain of MHV (MHV-JHM) possesses a highly fusogenic surface (S) glycoprotein. This protein is now shown to promote the spread of MHV into cells lacking the specific CEA-related MHV receptor. Resistant cells are recruited into MHV-induced syncytium with consequent production of progeny virus. Cell-to-cell spread of virus via membrane fusion without the requirement for specific cell surface receptor offers a novel way for virus to spread within infected hosts

Open-world Person Re-Identification by Multi-Label Assignment Inference.

(c) 2014. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms

Regional differences in willingness to pay for organic vegetables

The concern about vegetable safety, together with a booming population and the rise of the middle class has made Vietnam become a potential market for organic vegetables. This paper investigates the determinants of willingness to pay (WTP) for organic vegetables in Hanoi, Vietnam with a particular attention to regional differences and the effect of risk perception. Using Contingent Valuation Method to analyze the data from a sample of 498 consumers in Hanoi, the paper shows that the perceived use values of organic vegetables, trust in organic labels, and disposable family income increased WTP for organic vegetables in both urban and rural regions.Though risk perception of conventional vegetables was high in both regions, such heightened risk perception just translated into the WTP in the rural region. In addition, the percentage of home-grown vegetables in the total vegetable consumption of the family influenced the WTP in the rural region only. Moreover, being an organic purchaser was positively related to the WTP in the urban region but not in the rural region. The paper also discusses three policy implications for Vietnam to boost the demand for organic food.fals

A biologically inspired spiking model of visual processing for image feature detection

To enable fast reliable feature matching or tracking in scenes, features need to be discrete and meaningful, and hence edge or corner features, commonly called interest points are often used for this purpose. Experimental research has illustrated that biological vision systems use neuronal circuits to extract particular features such as edges or corners from visual scenes. Inspired by this biological behaviour, this paper proposes a biologically inspired spiking neural network for the purpose of image feature extraction. Standard digital images are processed and converted to spikes in a manner similar to the processing that transforms light into spikes in the retina. Using a hierarchical spiking network, various types of biologically inspired receptive fields are used to extract progressively complex image features. The performance of the network is assessed by examining the repeatability of extracted features with visual results presented using both synthetic and real images

Transductive Multi-View Zero-Shot Learning

(c) 2012. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms

Learning Multimodal Latent Attributes

Abstract—The rapid development of social media sharing has created a huge demand for automatic media classification and annotation techniques. Attribute learning has emerged as a promising paradigm for bridging the semantic gap and addressing data sparsity via transferring attribute knowledge in object recognition and relatively simple action classification. In this paper, we address the task of attribute learning for understanding multimedia data with sparse and incomplete labels. In particular we focus on videos of social group activities, which are particularly challenging and topical examples of this task because of their multi-modal content and complex and unstructured nature relative to the density of annotations. To solve this problem, we (1) introduce a concept of semi-latent attribute space, expressing user-defined and latent attributes in a unified framework, and (2) propose a novel scalable probabilistic topic model for learning multi-modal semi-latent attributes, which dramatically reduces requirements for an exhaustive accurate attribute ontology and expensive annotation effort. We show that our framework is able to exploit latent attributes to outperform contemporary approaches for addressing a variety of realistic multimedia sparse data learning tasks including: multi-task learning, learning with label noise, N-shot transfer learning and importantly zero-shot learning

An Iterative Cyclic Algorithm for Designing Vaccine Distribution Networks in Low and Middle-Income Countries

The World Health Organization's Expanded Programme on Immunization (WHO-EPI) was developed to ensure that all children have access to common childhood vaccinations. Unfortunately, because of inefficient distribution networks and cost constraints, millions of children in many low and middle-income countries still go without being vaccinated. In this paper, we formulate a mathematical programming model for the design of a typical WHO-EPI network with the goal of minimizing costs while providing the opportunity for universal coverage. Since it is only possible to solve small versions of the model optimally, we describe an iterative heuristic that cycles between solving restrictions of the original problem and show that it can find very good solutions in reasonable time for larger problems that are not directly solvable.Comment: International Joint Conference on Industrial Engineering and Operations Management- ABEPRO-ADINGOR-IISE-AIM-ASEM (IJCIEOM 2019). Novi Sad, Serbia, July 15-17t

Strain- and Adsorption-Dependent Electronic States and Transport or Localization in Graphene

The chapter generalizes results on influence of uniaxial strain and adsorption on the electron states and charge transport or localization in graphene with different configurations of imperfections (point defects): resonant (neutral) adsorbed atoms either oxygen- or hydrogen-containing molecules or functional groups, vacancies or substitutional atoms, charged impurity atoms or molecules, and distortions. To observe electronic properties of graphene-admolecules system, we applied electron paramagnetic resonance technique in a broad temperature range for graphene oxides as a good basis for understanding the electrotransport properties of other active carbons. Applied technique allowed observation of possible metal-insulator transition and sorption pumping effect as well as discussion of results in relation to the granular metal model. The electronic and transport properties are calculated within the framework of the tight-binding model along with the Kubo-Greenwood quantum-mechanical formalism. Depending on electron density and type of the sites, the conductivity for correlated and ordered adsorbates is found to be enhanced in dozens of times as compared to the cases of their random distribution. In case of the uniaxially strained graphene, the presence of point defects counteracts against or contributes to the band-gap opening according to their configurations. The band-gap behaviour is found to be nonmonotonic with strain in case of a simultaneous action of defect ordering and zigzag deformation. The amount of localized charge carriers (spins) is found to be correlated with the content of adsorbed centres responsible for the formation of potential barriers and, in turn, for the localization effects. Physical and chemical states of graphene edges, especially at a uniaxial strain along one of them, play a crucial role in electrical transport phenomena in graphene-based materials.Comment: 16 pages, 10 figure

Can adenine nucleotides predict primary nonfunction of the human liver homograft?

Sixty-eight primary liver grafts were analyzed to see whether adenine nucleotides (AN: ATP, ADP, and AMP) or purine catabolites (PC: adenosine, inosine, hypoxanthine, and xanthine) of tissue or effluent can predict primary graft nonfunction. AN, PC, and nicotinamide adenine dinucleotide, oxidized form (NAD+) of the tissue before (pretransplant) and after graft reperfusion (post-transplant) and of the effluent were analyzed. The graft outcome was classified into two groups (group A: successful, n = 64; group B: primary nonfunctioning, n = 4). No significant differences were observed in pretransplant measurements between groups A and B, whereas ATP, ADP, total AN, total AN + total PC (T) and NAD+, in post-transplant tissues, were significantly higher in group A. Xanthine in the effluent was significantly higher in group B than in group A. ATP, ADP, total AN, T, and NAD+ in post-transplant tissue were significantly associated with primary graft nonfunction by logistic regression analysis