The increasing incidence of melanoma has recently promoted the development of computer-aided diagnosis systems for the classification of dermoscopic images. Unfortunately, the performance of such systems cannot be compared since they are evaluated in different sets of images by their authors and there are no public databases available to perform a fair evaluation of multiple systems. In this paper, a dermoscopic image database, called PH², is presented. The PH² database includes the manual segmentation, the clinical diagnosis, and the identification of several dermoscopic structures, performed by expert dermatologists, in a set of 200 dermoscopic images. The PH² database will be made freely available for research and benchmarking purposes.

In NMT, words are sometimes dropped from the source or generated repeatedly in the translation. We explore novel strategies to address the coverage problem that change only the attention transformation. Our approach allocates fertilities to source words, used to bound the attention each word can receive. We experiment with various sparse and constrained attention transformations and propose a new one, constrained sparsemax, shown to be differentiable and sparse. Empirical evaluation is provided in three languages pairs. Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014.Sequence to sequence learning with neural networks. In Advances in neural information processing systems. pages 3104-3112. . 2017b. Neural machine translation with reconstruction. In AAAI. pages 3097-3103. Macherey, et al. 2016. Google's neural machine translation system: Bridging the gap between human and machine translation. arXiv preprint arXiv:1609.08144 .

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The HIIFRM was shown to be a useful tool in predicting falls by patients. Nevertheless, the research model suggested that only four risk factors affected the occurrence of falls significantly on admission and two risk factors at discharge. Further research is required in Portuguese hospital settings.

The articles in this issue of MRS Bulletin provide a sample of what is novel and unique in the field of in situ transmission electron microscopy (TEM). The advent of improved cameras and continued developments in electron optics and stage designs have enabled scientists and engineers to enhance the capabilities of previous TEM analyses. Currently, novel in situ experiments observe and record the behavior of materials in various heating, cooling, straining, or growth environments. In situ TEM techniques are invaluable for understanding and characterizing dynamic microstructural changes. They can validate static TEM experiments and inspire new experimental approaches and new theories.