A gravity model approach to forecasting tuberculosis transmission in cattle

Bovine tuberculosis (bTB) in cattle has caused significant economic losses to livestock producers and has proven difficult to eradicate. It is suspected that cattle movement across different farms and regions is one of the key factors of bTB transmission in the United States. Prior attempts to model the epidemiology of bTB infection within cattle to predict disease transmission have not adequately captured the behavioral aspects of trade. A better understanding of livestock trade patterns would help in predicting disease transmission and the associated economic effects. In this paper, we develop a gravity model of livestock trade and link it to an epidemiological model of bTB transmission, with the goal being that this information could lead to improved disease surveillance and management. Our findings suggest that feedbacks between jointly determined disease dynamics and trade system matter and should be considered together for efficient disease management.Bovine tuberculosis, Gravity model, disease management, Resource /Energy Economics and Policy,

Model-based Reinforcement Learning with Parametrized Physical Models and Optimism-Driven Exploration

In this paper, we present a robotic model-based reinforcement learning method that combines ideas from model identification and model predictive control. We use a feature-based representation of the dynamics that allows the dynamics model to be fitted with a simple least squares procedure, and the features are identified from a high-level specification of the robot's morphology, consisting of the number and connectivity structure of its links. Model predictive control is then used to choose the actions under an optimistic model of the dynamics, which produces an efficient and goal-directed exploration strategy. We present real time experimental results on standard benchmark problems involving the pendulum, cartpole, and double pendulum systems. Experiments indicate that our method is able to learn a range of benchmark tasks substantially faster than the previous best methods. To evaluate our approach on a realistic robotic control task, we also demonstrate real time control of a simulated 7 degree of freedom arm.Comment: 8 page

Study of Physical Layer Security and Teaching Methods in Wireless Communications

In most wireless channels, the signals propagate in all directions. For the communication between Alice and Bob, an Eavesdropper can receive the signals from both Alice and Bob as far as the Eavesdropper is in the range determined by the transmitting power. Through phased array antenna with beam tracking circuits or cooperative iteration, the signals are confined near the straight line connecting the positions of Alice and Bob, so it will largely reduce the valid placement of an Eavesdropper. Sometimes, this reduction can be prohibitive for Eavesdropper to wiretap the channel since the reduced space can be readily protected. Two course modules have been developed for students to understand signal propagation in physical layer and how it is used to enhance channel security along with natural and man-made noise

Charge writing at the LaAlO3/SrTiO3 surface

Biased conducting-tip atomic force microscopy (AFM) has been shown to write and erase nanoscale metallic lines at the LaAlO3/SrTiO3 interface. Using various AFM modes, we show the mechanism of conductivity switching is the writing of surface charge. These charges are stably deposited on a wide range of LaAlO3 thicknesses, including bulk crystals. A strong asymmetry with writing polarity was found for 1 and 2 unit cells of LaAlO3, providing experimental evidence for a theoretically predicted built-in potential.Comment: 12 pages, 4 figures, plus supplementary information, submitted to Nano Letter

Magnetic resonance multitasking for motion-resolved quantitative cardiovascular imaging.

Quantitative cardiovascular magnetic resonance (CMR) imaging can be used to characterize fibrosis, oedema, ischaemia, inflammation and other disease conditions. However, the need to reduce artefacts arising from body motion through a combination of electrocardiography (ECG) control, respiration control, and contrast-weighting selection makes CMR exams lengthy. Here, we show that physiological motions and other dynamic processes can be conceptualized as multiple time dimensions that can be resolved via low-rank tensor imaging, allowing for motion-resolved quantitative imaging with up to four time dimensions. This continuous-acquisition approach, which we name cardiovascular MR multitasking, captures - rather than avoids - motion, relaxation and other dynamics to efficiently perform quantitative CMR without the use of ECG triggering or breath holds. We demonstrate that CMR multitasking allows for T1 mapping, T1-T2 mapping and time-resolved T1 mapping of myocardial perfusion without ECG information and/or in free-breathing conditions. CMR multitasking may provide a foundation for the development of setup-free CMR imaging for the quantitative evaluation of cardiovascular health

Snapshot High Dynamic Range Imaging with a Polarization Camera

High dynamic range (HDR) images are important for a range of tasks, from navigation to consumer photography. Accordingly, a host of specialized HDR sensors have been developed, the most successful of which are based on capturing variable per-pixel exposures. In essence, these methods capture an entire exposure bracket sequence at once in a single shot. This paper presents a straightforward but highly effective approach for turning an off-the-shelf polarization camera into a high-performance HDR camera. By placing a linear polarizer in front of the polarization camera, we are able to simultaneously capture four images with varied exposures, which are determined by the orientation of the polarizer. We develop an outlier-robust and self-calibrating algorithm to reconstruct an HDR image (at a single polarity) from these measurements. Finally, we demonstrate the efficacy of our approach with extensive real-world experiments.Comment: 9 pages, 10 figure

The Curvilinear Relationships Between Top Decision Maker Goal Orientations and Firm Ambidexterity: Moderating Effect of Role Experience

Ambidextrous firms are those that can simultaneously manage exploitative and explorative innovation, which is why ambidexterity is key for firms that desire to pursue strategic entrepreneurship. Researchers have explored many of the reasons why some firms are more ambidextrous than others. However, little attention has been devoted to understanding how attributes of top decision makers can influence their firms\u27 ambidexterity. By drawing on upper echelons theory and goal orientations research, we explain how firms\u27 ambidexterity can be affected by top decision makers\u27 motivations in achievement situations (i.e., goal orientations). Testing our hypotheses on a sample of 274 top decision makers of firms in the United States, we find that top decision makers\u27 learning goal orientation - their desire to take risks and maximize learning-has an inverted U-shaped relationship with ambidexterity while top decision makers\u27 performance prove goal orientation - their desire to demonstrate competence with existing skills - has a U-shaped relationship with ambidexterity. These effects are weaker for top decision makers who have greater role experience