Scaling up antiretroviral therapy in Malawi-implications for managing other chronic diseases in resource-limited countries.

The national scale-up of antiretroviral therapy (ART) in Malawi is based on the public health approach, with principles and practices borrowed from the successful DOTS (directly observed treatment, short course) tuberculosis control framework. The key principles include political commitment, free care, and standardized systems for case finding, treatment, recording and reporting, and drug procurement. Scale-up of ART started in June 2004, and by December 2008, 223,437 patients were registered for treatment within a health system that is severely underresourced. The Malawi model for delivering lifelong ART can be adapted and used for managing patients with chronic noncommunicable diseases, the burden of which is already high and continues to grow in low-income and middle-income countries. This article discusses how the principles behind the successful Malawi model of ART delivery can be applied to the management of other chronic diseases in resource-limited settings and how this paradigm can be used for health systems strengthening

Quality control of laser welds based on the weld surface and the weld profile

2D or 3D sensor technology can be used for data acquisition to monitor the weld quality during laser welding. Compared to a 2D camera image, the 3D height data contains additional relevant information for quality inspection. However, the disadvantages are system complexity, higher costs, and longer acquisition times. Therefore, we compare two image-based methods with the quality assessment based on height data. The first method uses feature vectors of coaxial acquired grayscale images. The significant advantage is that a camera is often integrated into the laser system, so no additional hardware is required. In the second approach, we use an AI-based single-view 3D reconstruction method. The height profile is calculated from a camera image and used for further quality assessment. Thus, we combine the advantages of 2D data acquisition with higher accuracy in evaluating 3D data. In this paper, we analyze a dataset of welded hairpins with different defect types and compare the quality assessment using the height data acquired with OCT, the feature vectors from the camera images, and the reconstructed height data

Structural record of an oblique impact: the central uplift of the Upheaval Dome impact structure, Utah, USA

Most asteroids strike their target at an oblique angle (Pierazzo & Melosh 2000). The common criterion for identifying craters formed by an oblique impact is the pattern of the ejecta blanket. On Earth, however, ejecta blankets are rarely preserved and morphological, structural, geophysical as well as depositional criteria were used to infer an oblique impact (e.g. for Chicxulub, Schultz & D’Hondt 1996, Ries- Steinheim, Stöffler et al. 2003, Mjölnir & Tsikalas 2005). However, the significance of such criteria in predicting impact angle or direction is a matter of debate (c.f. Schultz & Anderson, 1996, Ekholm & Melosh 2001). Particularly, it is not yet known whether there is an influence of the impact angle on the displacement field during the collapse of large transient cavities, and thus, the final crater. For most impact angles, the shape of the final crater is controlled by its size. At a critical diameter (ca. 2–5 km on Earth), simple bowl shaped craters are getting gravitationally unstable and collapse to form complex craters, with a flat floor and a terraced rim (Melosh 1989). During collapse, the crater floor rises to form a central uplift, that may or may not be visible as a central peak, or, when the peak in turn collapses, as a peak ring at yet larger diameters.conferenc

jCompoundMapper: An open source Java library and command-line tool for chemical fingerprints

<p>Abstract</p> <p>Background</p> <p>The decomposition of a chemical graph is a convenient approach to encode information of the corresponding organic compound. While several commercial toolkits exist to encode molecules as so-called fingerprints, only a few open source implementations are available. The aim of this work is to introduce a library for exactly defined molecular decompositions, with a strong focus on the application of these features in machine learning and data mining. It provides several options such as search depth, distance cut-offs, atom- and pharmacophore typing. Furthermore, it provides the functionality to combine, to compare, or to export the fingerprints into several formats.</p> <p>Results</p> <p>We provide a Java 1.6 library for the decomposition of chemical graphs based on the open source Chemistry Development Kit toolkit. We reimplemented popular fingerprinting algorithms such as depth-first search fingerprints, extended connectivity fingerprints, autocorrelation fingerprints (e.g. CATS2D), radial fingerprints (e.g. Molprint2D), geometrical Molprint, atom pairs, and pharmacophore fingerprints. We also implemented custom fingerprints such as the all-shortest path fingerprint that only includes the subset of shortest paths from the full set of paths of the depth-first search fingerprint. As an application of jCompoundMapper, we provide a command-line executable binary. We measured the conversion speed and number of features for each encoding and described the composition of the features in detail. The quality of the encodings was tested using the default parametrizations in combination with a support vector machine on the Sutherland QSAR data sets. Additionally, we benchmarked the fingerprint encodings on the large-scale Ames toxicity benchmark using a large-scale linear support vector machine. The results were promising and could often compete with literature results. On the large Ames benchmark, for example, we obtained an AUC ROC performance of 0.87 with a reimplementation of the extended connectivity fingerprint. This result is comparable to the performance achieved by a non-linear support vector machine using state-of-the-art descriptors. On the Sutherland QSAR data set, the best fingerprint encodings showed a comparable or better performance on 5 of the 8 benchmarks when compared against the results of the best descriptors published in the paper of Sutherland et al.</p> <p>Conclusions</p> <p>jCompoundMapper is a library for chemical graph fingerprints with several tweaking possibilities and exporting options for open source data mining toolkits. The quality of the data mining results, the conversion speed, the LPGL software license, the command-line interface, and the exporters should be useful for many applications in cheminformatics like benchmarks against literature methods, comparison of data mining algorithms, similarity searching, and similarity-based data mining.</p