19,370 research outputs found
Animal models of Zika virus infection, pathogenesis, and immunity
Zika virus (ZIKV) is an emerging mosquito-transmitted flavivirus that now causes epidemics affecting millions of people on multiple continents. The virus has received global attention because of some of its unusual epidemiological and clinical features, including persistent infection in the male reproductive tract and sexual transmission, an ability to cross the placenta during pregnancy and infect the developing fetus to cause congenital malformations, and its association with Guillain-Barré syndrome in adults. This past year has witnessed an intensive effort by the global scientific community to understand the biology of ZIKV and to develop pathogenesis models for the rapid testing of possible countermeasures. Here, we review the recent advances in and utility and limitations of newly developed mouse and nonhuman primate models of ZIKV infection and pathogenesis
Wind Turbine Wakes, Wake Effect Impacts, and Wind Leases: Using Solar Access Laws as the Model for Capitalizing on Wind Rights During the Evolution of Wind Policy Standards
Mean anisotropy of homogeneous Gaussian random fields and anisotropic norms of linear translation-invariant operators on multidimensional integer lattices
Sensitivity of output of a linear operator to its input can be quantified in various ways. In Control Theory, the input is usually interpreted as disturbance and the output is to be minimized in some sense. In stochastic worst-case design settings, the disturbance is considered random with imprecisely known probability distribution. The prior set of probability measures can be chosen so as to quantify how far the disturbance deviates from the white-noise hypothesis of Linear Quadratic Gaussian control. Such deviation can be measured by the minimal Kullback-Leibler informational divergence from the Gaussian distributions with zero mean and scalar covariance matrices. The resulting anisotropy functional is defined for finite power random vectors. Originally, anisotropy was introduced for directionally generic random vectors as the relative entropy of the normalized vector with respect to the uniform distribution on the unit sphere. The associated a-anisotropic norm of a matrix is then its maximum root mean square or average energy gain with respect to finite power or directionally generic inputs whose anisotropy is bounded above by a >= 0. We give a systematic comparison of the anisotropy functionals and the associated norms. These are considered for unboundedly growing fragments of homogeneous Gaussian random fields on multidimensional integer lattice to yield mean anisotropy. Correspondingly, the anisotropic norms of finite matrices are extended to bounded linear translation invariant operators over such fields
Low-energy finite field arithmetic primitives for implementing security in wireless sensor networks
In this paper we propose the use of identity based encryption (IBE) for ensuring a secure wireless sensor network. In this context we have implemented the arithmetic operations required for the most computationally expensive part of IBE, which is the Tate pairing, in 90 nm CMOS and obtained area, timing and energy figures for the designs. Initial results indicate that a hardware implementation of IBE would meet the strict energy constraint of a wireless sensor network nod
Breathing feedback system with wearable textile sensors
Breathing exercises form an essential part of the treatment for respiratory illnesses such as cystic fibrosis. Ideally these exercises should be performed on a daily basis. This paper presents an interactive system using a wearable textile sensor to monitor breathing patterns. A graphical user interface provides visual real-time feedback to patients. The aim of the system is to encourage the correct performance of prescribed breathing exercises by monitoring the rate and the depth of breathing. The system is
straightforward to use, low-cost and can be installed easily within a clinical setting or in the home. Monitoring the user with a wearable sensor gives real-time feedback to the user as they perform the exercise, allowing them
to perform the exercises independently. There is also potential for remote monitoring where the user’s overall performance over time can be assessed by a clinician
Information Carried by Population Spike Times in the Whisker Sensory Cortex can be Decoded Without Knowledge of Stimulus Time
Computational analyses have revealed that precisely timed spikes emitted by somatosensory cortical neuronal populations encode basic stimulus features in the rat's whisker sensory system. Efficient spike time based decoding schemes both for the spatial location of a stimulus and for the kinetic features of complex whisker movements have been defined. To date, these decoding schemes have been based upon spike times referenced to an external temporal frame – the time of the stimulus itself. Such schemes are limited by the requirement of precise knowledge of the stimulus time signal, and it is not clear whether stimulus times are known to rats making sensory judgments. Here, we first review studies of the information obtained from spike timing referenced to the stimulus time. Then we explore new methods for extracting spike train information independently of any external temporal reference frame. These proposed methods are based on the detection of stimulus-dependent differences in the firing time within a neuronal population. We apply them to a data set using single-whisker stimulation in anesthetized rats and find that stimulus site can be decoded based on the millisecond-range relative differences in spike times even without knowledge of stimulus time. If spike counts alone are measured over tens or hundreds of milliseconds rather than milliseconds, such decoders are much less effective. These results suggest that decoding schemes based on millisecond-precise spike times are likely to subserve robust and information-rich transmission of information in the somatosensory system
Pump less wearable microfluidic device for real time pH sweat monitoring
This paper presents the fabrication and the performance of a novel, wearable, robust, flexible and disposable
microfluidic device which incorporates micro-Light Emitting Diodes (μ-LEDs) as a detection system, for
monitoring in real time mode the pH of the sweat generated during an exercising period
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