Modelling the effects of past and future climate on the risk of bluetongue emergence in Europe

Vector-borne diseases are among those most sensitive to climate because the ecology of vectors and the development rate of pathogens within them are highly dependent on environmental conditions. Bluetongue (BT), a recently emerged arboviral disease of ruminants in Europe, is often cited as an illustration of climate''s impact on disease emergence, although no study has yet tested this association. Here, we develop a framework to quantitatively evaluate the effects of climate on BT''s emergence in Europe by integrating high-resolution climate observations and model simulations within a mechanistic model of BT transmission risk. We demonstrate that a climate-driven model explains, in both space and time, many aspects of BT''s recent emergence and spread, including the 2006 BT outbreak in northwest Europe which occurred in the year of highest projected risk since at least 1960. Furthermore, the model provides mechanistic insight into BT''s emergence, suggesting that the drivers of emergence across Europe differ between the South and the North. Driven by simulated future climate from an ensemble of 11 regional climate models, the model projects increase in the future risk of BT emergence across most of Europe with uncertainty in rate but not in trend. The framework described here is adaptable and applicable to other diseases, where the link between climate and disease transmission risk can be quantified, permitting the evaluation of scale and uncertainty in climate change''s impact on the future of such diseases.     

A class of low-pass FIR input shaping filters achieving exact residual vibration cancelation

This paper describes the construction of low-pass FIR filters for application as command input shapers in motion control systems. The filters are designed to operate on an arbitrary command input signal to ensure a finite settling time for system modes with known natural frequency and damping ratio. In addition, the required roll-off rate of the filter frequency response may be prescribed in the design. Excitation of unmodeled high-frequency modes can thereby be reduced. The filters also produce an input-smoothing effect that is useful in situations where discontinuities in the input signal or its derivatives would be detrimental to system performance or function. Numerical case studies are presented to clarify these effects.     

Tracer design for magnetic particle imaging (invited)

Magnetic particle imaging (MPI) uses safe iron oxide nanoparticle tracers to offer fundamentally new capabilities for medical imaging, in applications as vascular imaging and ultra-sensitive cancer therapeutics. MPI is perhaps the first medical imaging platform to intrinsically exploit nanoscale material properties. MPI tracers contain magnetic nanoparticles whose tunable, size-dependent magnetic properties can be optimized by selecting a particular particle size and narrow size-distribution. In this paper we present experimental MPI measurements acquired using a homemade MPI magnetometer: a zero-dimensional MPI imaging system designed to characterize tracer performance by measuring the derivative of the time-varying tracer magnetization, M'(H(t)), at a driving frequency of 25 kHz. We show that MPI performance is optimized by selecting phase-pure magnetite tracers of a particular size and narrow size distribution; in this work, tracers with 20 nm median diameter, log-normal distribution shape parameter, σ(v), equal to 0.26, and hydrodynamic diameter equal to 30 nm showed the best performance. Furthermore, these optimized MPI tracers show 4?×?greater signal intensity (measured at the third harmonic) and 20% better spatial resolution compared with commercial nanoparticles developed for MRI.     

Coercivity Control of Variable-Length Iron Chains in Phthalocyanine Thin Films

The magnetic characteristics of iron phthalocyanine thin films are studied with a vibrating sample magnetometer, identifying a ferromagnetic transition temperature at 4.5?K. The metal ions at the center of the molecule are self-assembled along chains producing quasi one-dimensional magnetic chains of variable length in the thin films. The average chain length is varied from 20 to 300?nm via substrate temperature during deposition. Below the critical transition temperature, the magnetization curves have the shape of wasp-waisted or constricted loops. The in-plane chain length modulates the coercivity and saturation field and larger grains increase the coercivity significantly. First-order reversal curves of the wasp-waisted hysteresis loops reveal a long narrow strip that suggests a broad distribution of coercive fields and weak intergrain magnetic interactions. These findings are also supported through simulations based on the Preisach model.     

A decision model for the analysis of ergonomic investments

Costs associated with worker injuries can be high and some suggest investments in ergonomic solutions can lower those costs. However, many employers are still unsure if investing in various ergonomic solutions will generate benefits such as increased production and/or reduce workmen's compensation expenses. Estimating current losses and predicting possible gains provide most of the information needed to decide upon ergonomic investment. This paper presents a model employers can use to predict cost savings from ergonomic investments given certain input factors, including current losses, cost of implementation, and success of implementation.     

Terrain classification and identification of tree stems using ground‐based LiDAR

To operate autonomously in forested terrain, unmanned ground vehicles must be able to identify the load‐bearing surface of the terrain (i.e., the ground) and obstacles in the environment. To travel long distances, they must be able to track their position even when the forest canopy obstructs GPS signals, e.g., by tracking progress relative to tree stems. This paper presents a novel, robust approach for modeling the ground plane and tree stems in forests from a single viewpoint using a lightweight LiDAR scanner. Ground plane identification is implemented using a two‐stage approach. The first stage, a local height‐based filter, discards most nonground points. The second stage, based on a support vector machine classifier, identifies which of the remaining points belong to the ground. Main tree stems are modeled as cylinders or cones to estimate the diameter 130 cm above the ground plane. To fit these models, candidate main stem data are selected by finding points approximately 130 cm above the ground. These points are clustered into separate point clouds for each stem. Cylinders and cones are fit to each point cloud, and heuristic filters identify which fits correspond to tree stems. Experimental results from five forested environments demonstrate the effectiveness of this approach. For ground plane estimation, the overall classification accuracy was 86.28% with a mean error for the ground height of approximately 4.7 cm. For stem estimation, up to 50% of the main stems were accurately modeled using cones, with a root mean square diameter error of 13.2 cm.© 2012 Wiley Periodicals, Inc.     

Ion Electrodiffusion Governs Silk Electrogelation

Silk electrogelation involves the transition of an aqueous silk fibroin solution to a gel state (E-gel) in the presence of an electric current. The process is based on local pH changes as a result of water electrolysis - generating H(+) and OH(-) ions at the (+) and (-) electrodes, respectively. Silk fibroin has a pI=4.2 and when local pH相似文献   

The Influence of Crystal Habit on the Prediction of Dry Powder Inhalation Formulation Performance Using the Cohesive–Adhesive Force Balance Approach

The aim of this investigation was to study the influence of crystalline habit of active pharmaceutical ingredients on the cohesive–adhesive force balance within model dry powder inhaler (DPI) formulations and the corresponding affect on DPI formulation performance. The cohesive–adhesive balance (CAB) approach to colloid probe atomic force microscopy (AFM) was employed to determine the cohesive and adhesive interactions of micronized budesonide particles against the {102} and {002} faces of budesonide single crystals and crystalline substrates of different sugars (cyclodextrin, lactose, trehalose, raffinose, and xylitol), respectively. These data were used to measure the relative level of cohesion and adhesion via CAB and the possible influence on in vitro performance of a carrier-based DPI formulation. Varying the crystal habit of the drug had a significant effect on the cohesive measurement of micronized budesonide probes, with the cohesive values on the {102} faces being approximately twice that on the {002} crystal faces. However, although different CAB values were measured with the sugars with respect to the crystal faces chosen for the cohesive-based measurement, the overall influence on the rank order of the CAB values was not directly influenced. For these data sets, the CAB gradient indicated that a decrease in the dominance of the adhesive forces led to a concomitant increase in fine particle delivery, reaching a plateau as the cohesive forces became dominant. The study suggested that crystal habit of the primary drug crystals influences the cohesive interactions and the resulting force balance measurements of colloid probe CAB analysis.