Giant Hemosiderotic Dermatofibroma: A Case Report and Review of the Literature

Dermatofibroma is a common benign fibrohistiocytic lesion that usually appears as a slow-growing, firm dermal nodule with a predilection for the legs of middle-aged women. They are usually smaller than 2 cm in diameter. Many histological variants have been described. Generally, the clinical and histological diagnosis is straightforward, but differentiating it from other cutaneous tumors can be difficult in atypical cases and rare variants. Giant dermatofibroma is a rare clinical variant of dermatofibroma and less than 25 cases have been reported. It is characterized essentially by its unusually large size, which often mimics malignant tumors clinically. We first present the case of a giant hemosiderotic dermatofibroma in a 54-year-old patient, who presented with a large ulcerated mass of the left foot which was excised, and then review the literature briefly

Experimental results of Hooper's gravity-electromagnetic coupling concept

Experiments were conducted to test assertions from Patent 3,610,971, by W.J. Hooper that self-canceling electromagnetic coils can reduce the weight of objects placed underneath. No weight changes were observed within the detectability of the instrumentation. More careful examination of the patent and other reports from Hooper led to the conclusion that Hooper may have misinterpreted thermal effects as his 'Motional Field' effects. There is a possibility that the claimed effects are below the detection thresholds of the instrumentation used for these tests

Cross-validation based adaptive sampling for Gaussian process models

In many real-world applications, we are interested in approximating black-box, costly functions as accurately as possible with the smallest number of function evaluations. A complex computer code is an example of such a function. In this work, a Gaussian process (GP) emulator is used to approximate the output of complex computer code. We consider the problem of extending an initial experiment (set of model runs) sequentially to improve the emulator. A sequential sampling approach based on leave-one-out (LOO) cross-validation is proposed that can be easily extended to a batch mode. This is a desirable property since it saves the user time when parallel computing is available. After fitting a GP to training data points, the expected squared LOO (ES-LOO) error is calculated at each design point. ES-LOO is used as a measure to identify important data points. More precisely, when this quantity is large at a point it means that the quality of prediction depends a great deal on that point and adding more samples nearby could improve the accuracy of the GP. As a result, it is reasonable to select the next sample where ES-LOO is maximised. However, ES-LOO is only known at the experimental design and needs to be estimated at unobserved points. To do this, a second GP is fitted to the ES-LOO errors and where the maximum of the modified expected improvement (EI) criterion occurs is chosen as the next sample. EI is a popular acquisition function in Bayesian optimisation and is used to trade-off between local/global search. However, it has a tendency towards exploitation, meaning that its maximum is close to the (current) "best" sample. To avoid clustering, a modified version of EI, called pseudo expected improvement, is employed which is more explorative than EI yet allows us to discover unexplored regions. Our results show that the proposed sampling method is promising

Lignes directrices pour de meilleures pratiques en matière d’inventaire et de suivi des populations de grands singes

From Executive Summary: The combination of threats currently facing the remaining great apes requires immediate conservation action at all scales — from site-level initiatives, through national and regional strategies, to international conventions and action plans. Baseline density estimates and subsequent monitoring of ape populations are essential for assessing the impacts of particular threats and measuring whether conservation programmes are succeeding.  Available at: https://portals.iucn.org/library/node/922

Deterministic mathematical models of the cAMP pathway in Saccharomyces cerevisiae

<p>Abstract</p> <p>Background</p> <p>Cyclic adenosine monophosphate (cAMP) has a key signaling role in all eukaryotic organisms. In <it>Saccharomyces cerevisiae</it>, it is the second messenger in the Ras/PKA pathway which regulates nutrient sensing, stress responses, growth, cell cycle progression, morphogenesis, and cell wall biosynthesis. A stochastic model of the pathway has been reported.</p> <p>Results</p> <p>We have created deterministic mathematical models of the PKA module of the pathway, as well as the complete cAMP pathway. First, a simplified conceptual model was created which reproduced the dynamics of changes in cAMP levels in response to glucose addition in wild-type as well as cAMP phosphodiesterase deletion mutants. This model was used to investigate the role of the regulatory Krh proteins that had not been included previously. The Krh-containing conceptual model reproduced very well the experimental evidence supporting the role of Krh as a direct inhibitor of PKA. These results were used to develop the Complete cAMP Model. Upon simulation it illustrated several important features of the yeast cAMP pathway: Pde1p is more important than is Pde2p for controlling the cAMP levels following glucose pulses; the proportion of active PKA is not directly proportional to the cAMP level, allowing PKA to exert negative feedback; negative feedback mechanisms include activating Pde1p and deactivating Ras2 via phosphorylation of Cdc25. The Complete cAMP model is easier to simulate, and although significantly simpler than the existing stochastic one, it recreates cAMP levels and patterns of changes in cAMP levels observed experimentally <it>in vivo </it>in response to glucose addition in wild-type as well as representative mutant strains such as <it>pde1Δ, pde2Δ</it>, <it>cyr1Δ</it>, and others. The complete model is made available in SBML format.</p> <p>Conclusion</p> <p>We suggest that the lower number of reactions and parameters makes these models suitable for integrating them with models of metabolism or of the cell cycle in <it>S. cerevisiae</it>. Similar models could be also useful for studies in the human pathogen <it>Candida albicans </it>as well as other less well-characterized fungal species.</p

Dalek -- a deep-learning emulator for TARDIS

Supernova spectral time series contain a wealth of information about the progenitor and explosion process of these energetic events. The modeling of these data requires the exploration of very high dimensional posterior probabilities with expensive radiative transfer codes. Even modest parametrizations of supernovae contain more than ten parameters and a detailed exploration demands at least several million function evaluations. Physically realistic models require at least tens of CPU minutes per evaluation putting a detailed reconstruction of the explosion out of reach of traditional methodology. The advent of widely available libraries for the training of neural networks combined with their ability to approximate almost arbitrary functions with high precision allows for a new approach to this problem. Instead of evaluating the radiative transfer model itself, one can build a neural network proxy trained on the simulations but evaluating orders of magnitude faster. Such a framework is called an emulator or surrogate model. In this work, we present an emulator for the TARDIS supernova radiative transfer code applied to Type Ia supernova spectra. We show that we can train an emulator for this problem given a modest training set of a hundred thousand spectra (easily calculable on modern supercomputers). The results show an accuracy on the percent level (that are dominated by the Monte Carlo nature of TARDIS and not the emulator) with a speedup of several orders of magnitude. This method has a much broader set of applications and is not limited to the presented problem.Comment: 6 pages;5 figures submitted to AAS Journals. Constructive Criticism invite

Ape socioecology

First paragraph: This section presents an overview of the socioecology of the seven species of nonhuman apes: bonobos, chimpanzees, gibbons (including siamangs), eastern and western gorillas, and Bornean and Sumatran orangutans. For more detailed information, see Wich et al. (2009b), Emery Thompson and Wrangham (2013), Reinartz, Ingmanson and Vervaecke (2013), Williamson and Butynski (2013a, 2013b), and Williamson, Maisels and Groves (2013)

Best Practice Guidelines for Surveys and Monitoring of Great Ape Populations

First paragraph: Les menaces qui touchent aujourd'hui les grands singes appellent &agrave; des actions imm&eacute;diates de conservation &agrave; tous les niveaux : initiatives locales, strat&eacute;gies nationales et r&eacute;gionales, conventions internationales et plans d'action. Une estimation pr&eacute;alable de la densit&eacute; des grands singes est n&eacute;cessaire pour avoir une base de suivi des impacts de menaces sp&eacute;cifiques et pour &eacute;valuer le succ&egrave;s des programmes de conservation