Payroll Taxes in Colombia

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Upper airway symptoms among workers with work-related respiratory complaints

Background Work-related rhinitis and asthma symptoms frequently co-exist. Aims To determine the prevalence and nature of nasal, pharyngeal, laryngeal and sinus symptoms among individuals with work-related respiratory symptoms. Methods Individuals referred to a tertiary occupational asthma clinic for investigations with specific inhalation challenges were evaluated using the RHINASTHMA quality of life questionnaire and a questionnaire that assessed the nature and frequency of upper airway symptoms, their relationship to the workplace and their temporal relationship with the onset of asthma symptoms. Results There were 83 study participants. At least one upper airway symptom was reported by all of these individuals: nasal in 92%; pharyngeal in 82%; laryngeal in 65% and sinus in 53% of participants. Overall, there were no significant differences in the frequencies of nasal, pharyngeal, laryngeal and sinus symptoms when comparing these with occupational asthma (OA), work-exacerbated asthma (WEA) and work-related respiratory symptoms (WRS), except that nasal bleeding was most frequent among those with WRS. The presence of laryngeal symptoms was significantly associated with rhinitis-specific quality of life impairment. Individuals with workplace exposures to high molecular weight agents had greater impaired quality of life than those who were exposed to low molecular weight agents (RHINASTMA Upper Airway sub-scores: 24.0±10.4 versus 19.8±6.8; P < 0.05). Conclusions Individuals who were referred for work-related respiratory symptoms experienced high rates of work-related nasal, pharyngeal, laryngeal and sinus symptoms, regardless of having OA, WEA or WR

Model checker execution reports

Software model checking constitutes an undecidable problem and, as such, even an ideal tool will in some cases fail to give a conclusive answer. In practice, software model checkers fail often and usually do not provide any information on what was effectively checked. The purpose of this work is to provide a conceptual framing to extend software model checkers in a way that allows users to access information about incomplete checks. We characterize the information that model checkers themselves can provide, in terms of analyzed traces, i.e. sequences of statements, and safe canes, and present the notion of execution reports (ERs), which we also formalize. We instantiate these concepts for a family of techniques based on Abstract Reachability Trees and implement the approach using the software model checker CPAchecker. We evaluate our approach empirically and provide examples to illustrate the ERs produced and the information that can be extracted

Sparse Superpixel Unmixing for Hyperspectral Image Analysis

Software was developed that automatically detects minerals that are present in each pixel of a hyperspectral image. An algorithm based on sparse spectral unmixing with Bayesian Positive Source Separation is used to produce mineral abundance maps from hyperspectral images. A superpixel segmentation strategy enables efficient unmixing in an interactive session. The algorithm computes statistically likely combinations of constituents based on a set of possible constituent minerals whose abundances are uncertain. A library of source spectra from laboratory experiments or previous remote observations is used. A superpixel segmentation strategy improves analysis time by orders of magnitude, permitting incorporation into an interactive user session (see figure). Mineralogical search strategies can be categorized as supervised or unsupervised. Supervised methods use a detection function, developed on previous data by hand or statistical techniques, to identify one or more specific target signals. Purely unsupervised results are not always physically meaningful, and may ignore subtle or localized mineralogy since they aim to minimize reconstruction error over the entire image. This algorithm offers advantages of both methods, providing meaningful physical interpretations and sensitivity to subtle or unexpected minerals

Switching of +/-360deg domain wall states in a nanoring by an azimuthal Oersted field

We demonstrate magnetic switching between two $360^\circ$ domain wall vortex states in cobalt nanorings, which are candidate magnetic states for robust and low power MRAM devices. These $360^\circ$ domain wall (DW) or "twisted onion" states can have clockwise or counterclockwise circulation, the two states for data storage. Reliable switching between the states is necessary for any realistic device. We accomplish this switching by applying a circular Oersted field created by passing current through a metal atomic force microscope tip placed at the center of the ring. After initializing in an onion state, we rotate the DWs to one side of the ring by passing a current through the center, and can switch between the two twisted states by reversing the current, causing the DWs to split and meet again on the opposite side of the ring. A larger current will annihilate the DWs and create a perfect vortex state in the rings.Comment: 5 pages, 5 figure

Metric Learning to Enhance Hyperspectral Image Segmentation

Unsupervised hyperspectral image segmentation can reveal spatial trends that show the physical structure of the scene to an analyst. They highlight borders and reveal areas of homogeneity and change. Segmentations are independently helpful for object recognition, and assist with automated production of symbolic maps. Additionally, a good segmentation can dramatically reduce the number of effective spectra in an image, enabling analyses that would otherwise be computationally prohibitive. Specifically, using an over-segmentation of the image instead of individual pixels can reduce noise and potentially improve the results of statistical post-analysis. In this innovation, a metric learning approach is presented to improve the performance of unsupervised hyperspectral image segmentation. The prototype demonstrations attempt a superpixel segmentation in which the image is conservatively over-segmented; that is, the single surface features may be split into multiple segments, but each individual segment, or superpixel, is ensured to have homogenous mineralogy

Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery

Many current and future NASA missions are capable of collecting enormous amounts of data, of which only a small portion can be transmitted to Earth. Communications are limited due to distance, visibility constraints, and competing mission downlinks. Long missions and high-resolution, multispectral imaging devices easily produce data exceeding the available bandwidth. To address this situation computationally efficient algorithms were developed for analyzing science imagery onboard the spacecraft. These algorithms autonomously cluster the data into classes of similar imagery, enabling selective downlink of representatives of each class, and a map classifying the terrain imaged rather than the full dataset, reducing the volume of the downlinked data. A range of approaches was examined, including k-means clustering using image features based on color, texture, temporal, and spatial arrangemen

Centralized Alert-Processing and Asset Planning for Sensorwebs

A software program provides a Sensorweb architecture for alert-processing, event detection, asset allocation and planning, and visualization. It automatically tasks and re-tasks various types of assets such as satellites and robotic vehicles in response to alerts (fire, weather) extracted from various data sources, including low-level Webcam data. JPL has adapted cons iderable Sensorweb infrastructure that had been previously applied to NASA Earth Science applications. This NASA Earth Science Sensorweb has been in operational use since 2003, and has proven reliability of the Sensorweb technologies for robust event detection and autonomous response using space and ground assets. Unique features of the software include flexibility to a range of detection and tasking methods including those that require aggregation of data over spatial and temporal ranges, generality of the response structure to represent and implement a range of response campaigns, and the ability to respond rapidly