3,829 research outputs found
Direct observation of ordered trimers on Si(111)√3×√3 R30°-Au by scanned-energy glancing-angle Kikuchi electron wave-front reconstruction
We report the first atomically resolved images of ordered Au trimers on Si(111)√3×√3R30°-Au using wave-front reconstruction of scanned-energy glancing-angle Kikuchi electron spectra. Each Au image has a resolution (full width at half magnitude) of less than 1 Å . The images indicate that Au trimers are ordered and nonrotated within the surface plane and with respect to the second-layer Si plane providing direct evidence of the conjugate honeycomb-chained-trimer model for the Au-√3 system. © 1996 The American Physical Society.published_or_final_versio
Phenotypic and functional modulation of porcine monocyte-derived dendritic cells for foot-and-mouth disease virus
Dendritic cells (DCs) play an important role in inducing primary antigen-specific immune responses to viral antigens. In this study, the peripheral blood monocyte-derived (PBMC) were cultured in the presence of granulocyte-macrophage colony-stimulating factor (GM-CSF) and interleukin (IL)-4. After 6 days of culture, immature monocyte-derived dendritic cells (Mo-DCs) were generated. The addition of lipopolysaccharide (LPS) during differentiation of Mo-DCs enhanced their ability to stimulate allogeneic mixed lymphocyte reaction (MLR) and alter their ability to produce cytokines. Then, we investigated the interaction between foot-and-mouth disease virus (FMDV) and porcine Mo-DCs in vitro and confirmed that the immunological phenotype and function of porcine Mo-DCs were modulated during FMDV infection. A down-regulated expression of MHC II and CD1 were observed at 48 h post FMDV infection. In addition, the infected porcine Mo-DCs exhibited ultrastructural morphological changes, FMDV-infected porcine Mo-DCs failed to stimulate T cell proliferation in vitro. Moreover, infection of porcine Mo-DCs in vitro induced the secretion of IFN-γ and the suppressive cytokine IL-10 in porcine Mo-DCs. Results indicated that the down-regulation of MHC II and CD1 molecules and the increased secretion of the IFN-γ and IL-10 cytokines might be the mechanisms that FMDV uses to evade the host immune responses.Key words: Dendritic cells, foot-and-mouth disease virus, MHC II, modulation, cytokines
Longitudinal Image Registration with Temporal-order and Subject-specificity Discrimination
Morphological analysis of longitudinal MR images plays a key role in
monitoring disease progression for prostate cancer patients, who are placed
under an active surveillance program. In this paper, we describe a
learning-based image registration algorithm to quantify changes on regions of
interest between a pair of images from the same patient, acquired at two
different time points. Combining intensity-based similarity and gland
segmentation as weak supervision, the population-data-trained registration
networks significantly lowered the target registration errors (TREs) on holdout
patient data, compared with those before registration and those from an
iterative registration algorithm. Furthermore, this work provides a
quantitative analysis on several longitudinal-data-sampling strategies and, in
turn, we propose a novel regularisation method based on maximum mean
discrepancy, between differently-sampled training image pairs. Based on 216 3D
MR images from 86 patients, we report a mean TRE of 5.6 mm and show
statistically significant differences between the different training data
sampling strategies.Comment: Accepted at MICCAI 202
Promoting influenza prevention for elderly people in Hong Kong using health action process approach: Study protocol
Background: People 65 years or older are at greater risk of serious complications from the seasonal influenza compared with young. To promote elderly people's behavioral compliance toward influenza prevention, the aim of the current project is to develop, implement, and evaluate a theory-based low-administration-cost intervention building on a leading psychological theory, the Health Action Process Approach (HAPA). Methods: The target group is Hong Kong Chinese elderly people aged 65 or older who rarely or never adopt any preventive actions. This project will be conducted in three phases over 24 months. In phase 1, intervention program will be developed building on the HAPA theoretical framework which comprises both the initiation and maintenance of influenza prevention behaviors. In phase 2, intervention will be implemented and evaluated using a randomized controlled trial, including: (a) behavior initiation only, (b) behavior initiation + behavior maintenance, and (c) control group. Both the initiation and maintenance components will comprise weekly-delivered telephone-based individual intervention sessions in 3 months. In phase 3, outcome evaluation of behavioral and psychological variables and process evaluation will be conducted. The effectiveness of the intervention will be analyzed using a series of linear mixed models on each behavioral and psychological outcome variable. Structural equation modelling will be used to test the hypothesized theoretical sequence in the HAPA model. Discussion: The proposed project is expected to design theory-based intervention materials to promote the influenza prevention behaviors in Hong Kong elderly people and provide information on its effectiveness and the potential changing mechanism of behavior initiation and maintenance. Trial registration: This randomized controlled trial was funded by the Health and Medical Research Fund (HMRF), Food and Health Bureau of the Government of the Hong Kong Special Administrative Region (Ref: 16151222) and was registered on 13/10/2017 at CCRB Clinical Trials Registry of the Chinese University of Hong Kong, a Partner Registry of a WHO Primary Registry (Ref: CUHK-CCRB00567)
Numerical ABL Wind Tunnel Simulations with Direct Modeling of Roughness Elements through Immersed Boundary Condition Method
Reproduction of atmospheric boundary layer wind tunnel experiments by numerical simulation is achieved in this work by directly modeling with immersed boundary method the geometrical elements placed in the wind tunnel's floor to induce the desired characteristics to the boundary layer.The wind tunnel has a cross section of 2.2 m x 2.25 m, with an inlet region 14 m long and a working region 2 m long. Boundary layer development is shaped up with a series of cubical elements, 3 cm in side, placed in a regular staggered arrangement with a 15 cm spacement. Vortex induction, Standen spires type elements, of 13,4 cm height, and a wall of 31.5 cm height are placed at the inlet. This arrangement is used to reproduce a representative urban site boundary layer (figure 1).The numerical model is implemented on the basis of the open source modelcaffa3d.MBRi [Usera et al 2008], which uses a finite volume method over block structured grids,
coupled with various LES approaches for turbulence modeling and parallelization through domain decomposition with MPI [Mendina et al 2013]. Simulations were setup with approximately 2 million cells per block, with a 26 block arrangement. The computational grid is horizontally uniform with a resolution of 1.04 cm x 1.04 cm and nonuniform in vertical direction with the grid points concentrated near the floor . The grid spacing is geometrically stretched away from the floor with a minimum value of 1mm. The time step is 0.1 second and the computation is distributed in 26 cores on the Cluster-FING infraestructure [www.fing.edu.uy/cluster]. The Immersed boundary method approach followed the work of [Liao et al 2009]. Numerical simulation results are compared to wind tunnel measurements for the mean velocity profiles (figure 2), rms profiles and spectrums, providing good overall agreement. We conclude that the Immersed Boundary Condition method is a promising approach to numerically reproduce ABL Boundary Layer development methods used in physical modeling.Agencia Nacional de Investigación e Innovació
Conscious monitoring and control (reinvestment) in surgical performance under pressure.
Research on intraoperative stressors has focused on external factors without considering individual differences in the ability to cope with stress. One individual difference that is implicated in adverse effects of stress on performance is "reinvestment," the propensity for conscious monitoring and control of movements. The aim of this study was to examine the impact of reinvestment on laparoscopic performance under time pressure
Upregulated ankyrin repeat-rich membrane spanning protein contributes to tumour progression in cutaneous melanoma
Tailoring force sensitivity and selectivity by microstructure engineering of multidirectional electronic skins
Electronic skins (e-skins) with high sensitivity to multidirectional mechanical stimuli are crucial for healthcare monitoring devices, robotics, and wearable sensors. In this study, we present piezoresistive e-skins with tunable force sensitivity and selectivity to multidirectional forces through the engineered microstructure geometries (i.e., dome, pyramid, and pillar). Depending on the microstructure geometry, distinct variations in contact area and localized stress distribution are observed under different mechanical forces (i.e., normal, shear, stretching, and bending), which critically affect the force sensitivity, selectivity, response/relaxation time, and mechanical stability of e-skins. Microdome structures present the best force sensitivities for normal, tensile, and bending stresses. In particular, microdome structures exhibit extremely high pressure sensitivities over broad pressure ranges (47,062 kPa(-1) in the range of < 1 kPa, 90,657 kPa(-1) in the range of 1-10 kPa, and 30,214 kPa(-1) in the range of 10-26 kPa). On the other hand, for shear stress, micropillar structures exhibit the highest sensitivity. As proof-of-concept applications in healthcare monitoring devices, we show that our e-skins can precisely monitor acoustic waves, breathing, and human artery/carotid pulse pressures. Unveiling the relationship between the microstructure geometry of e-skins and their sensing capability would provide a platform for future development of high-performance microstructured e-skins
Detecting Distributed Denial of Service Attacks in Neighbour Discovery Protocol Using Machine Learning Algorithm Based on Streams Representation
© 2018, Springer International Publishing AG, part of Springer Nature. The main protocol of the Internet protocol version 6 suites is the neighbour discovery protocol, which is geared towards substitution of address resolution protocol, router discovery, and function redirection in Internet protocol version 4. Internet protocol version 6 nodes employ neighbour discovery protocol to detect linked hosts and routers in Internet protocol version 6 network without the dependence on dynamic host configuration protocol server, which has earned the neighbour discovery protocol the title of the stateless protocol. The authentication process of the neighbour discovery protocol exhibits weaknesses that make this protocol vulnerable to attacks. Denial of service attacks can be triggered by a malicious host through the introduction of spoofed addresses in neighbour discovery protocol messages. Internet version 6 protocols are not well supported by Network Intrusion Detection System as is the case with Internet Protocol version 4 protocols. Several data mining techniques have been introduced to improve the classification mechanism of Intrusion detection system. In addition, extensive researches indicated that there is no Intrusion Detection system for Internet Protocol version 6 using advanced machine-learning techniques toward distributed denial of service attacks. This paper aims to detect Distributed Denial of Service attacks of the Neighbour Discovery protocol using machine-learning techniques, due to the severity of the attacks and the importance of Neighbour Discovery protocol in Internet Protocol version 6. Decision tree algorithm and Random Forest Algorithm showed high accuracy results in comparison to the other benchmarked algorithms
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Projected WIMP sensitivity of the LUX-ZEPLIN dark matter experiment
LUX-ZEPLIN (LZ) is a next-generation dark matter direct detection experiment that will operate 4850 feet underground at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, USA. Using a two-phase xenon detector with an active mass of 7 tonnes, LZ will search primarily for low-energy interactions with weakly interacting massive particles (WIMPs), which are hypothesized to make up the dark matter in our galactic halo. In this paper, the projected WIMP sensitivity of LZ is presented based on the latest background estimates and simulations of the detector. For a 1000 live day run using a 5.6-tonne fiducial mass, LZ is projected to exclude at 90% confidence level spin-independent WIMP-nucleon cross sections above 1.4×10-48 cm2 for a 40 GeV/c2 mass WIMP. Additionally, a 5σ discovery potential is projected, reaching cross sections below the exclusion limits of recent experiments. For spin-dependent WIMP-neutron(-proton) scattering, a sensitivity of 2.3×10-43 cm2 (7.1×10-42 cm2) for a 40 GeV/c2 mass WIMP is expected. With underground installation well underway, LZ is on track for commissioning at SURF in 2020
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