207 research outputs found

    Optimality Clue for Graph Coloring Problem

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    In this paper, we present a new approach which qualifies or not a solution found by a heuristic as a potential optimal solution. Our approach is based on the following observation: for a minimization problem, the number of admissible solutions decreases with the value of the objective function. For the Graph Coloring Problem (GCP), we confirm this observation and present a new way to prove optimality. This proof is based on the counting of the number of different k-colorings and the number of independent sets of a given graph G. Exact solutions counting problems are difficult problems (\#P-complete). However, we show that, using only randomized heuristics, it is possible to define an estimation of the upper bound of the number of k-colorings. This estimate has been calibrated on a large benchmark of graph instances for which the exact number of optimal k-colorings is known. Our approach, called optimality clue, build a sample of k-colorings of a given graph by running many times one randomized heuristic on the same graph instance. We use the evolutionary algorithm HEAD [Moalic et Gondran, 2018], which is one of the most efficient heuristic for GCP. Optimality clue matches with the standard definition of optimality on a wide number of instances of DIMACS and RBCII benchmarks where the optimality is known. Then, we show the clue of optimality for another set of graph instances. Optimality Metaheuristics Near-optimal

    Modeling genomic diversity and tumor dependency in malignant melanoma

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    The classification of human tumors based on molecular criteria offers tremendous clinical potential; however, discerning critical and "druggable" effectors on a large scale will also require robust experimental models reflective of tumor genomic diversity. Here, we describe a comprehensive genomic analysis of 101 melanoma short-term cultures and cell lines. Using an analytic approach designed to enrich for putative "driver" events, we show that cultured melanoma cells encompass the spectrum of significant genomic alterations present in primary tumors. When annotated according to these lesions, melanomas cluster into subgroups suggestive of distinct oncogenic mechanisms. Integrating gene expression data suggests novel candidate effector genes linked to recurrent copy gains and losses, including both phosphatase and tensin homologue (PTEN)-dependent and PTEN-independent tumor suppressor mechanisms associated with chromosome 10 deletions. Finally, sample-matched pharmacologic data show that FGFR1 mutations and extracellular signal-regulated kinase (ERK) activation may modulate sensitivity to mitogen-activated protein kinase/ERK kinase inhibitors. Genetically defined cell culture collections therefore offer a rich framework for systematic functional studies in melanoma and other tumors

    Spatial heterogeneity of habitat suitability for Rift Valley fever occurrence in Tanzania: an ecological niche modelling approach

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    Despite the long history of Rift Valley fever (RVF) in Tanzania, extent of its suitable habitat in the country remains unclear. In this study we investigated potential effects of temperature, precipitation, elevation, soil type, livestock density, rainfall pattern, proximity to wild animals, protected areas and forest on the habitat suitability for RVF occurrence in Tanzania. Presence-only records of 193 RVF outbreak locations from 1930 to 2007 together with potential predictor variables were used to model and map the suitable habitats for RVF occurrence using ecological niche modelling. Ground-truthing of the model outputs was conducted by comparing the levels of RVF virus specific antibodies in cattle, sheep and goats sampled from locations in Tanzania that presented different predicted habitat suitability values. Habitat suitability values for RVF occurrence were higher in the northern and central-eastern regions of Tanzania than the rest of the regions in the country. Soil type and precipitation of the wettest quarter contributed equally to habitat suitability (32.4% each), followed by livestock density (25.9%) and rainfall pattern (9.3%). Ground-truthing of model outputs revealed that the odds of an animal being seropositive for RVFV when sampled from areas predicted to be most suitable for RVF occurrence were twice the odds of an animal sampled from areas least suitable for RVF occurrence (95% CI: 1.43, 2.76, p < 0.001). The regions in the northern and central-eastern Tanzania were more suitable for RVF occurrence than the rest of the regions in the country. The modelled suitable habitat is characterised by impermeable soils, moderate precipitation in the wettest quarter, high livestock density and a bimodal rainfall pattern. The findings of this study should provide guidance for the design of appropriate RVF surveillance, prevention and control strategies which target areas with these characteristics

    Dwelling in Strangeness: accounts of the Kingsley Hall Community, London (1965-1970)

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    This article explores archival accounts of the experimental community, Kingsley Hall (1965-70), established by R. D. Laing, the radical Scottish psychiatrist. The paper contributes to renewed interest in Kingsley Hall, R. D. Laing's radical psychiatry and UK counterculture. Archival sources enable not only the further exploration of already known figures but also let us hear previously unheard voices. Following a discussion of archival materials, the Hall is analyzed thematically and historically as (i) an inner spaceship; (ii) an embattled middle-class countercultural plantation; (iii) a site of spiritual renewal and development; (iv) a single-building arts colony; and (v) a countercultural experiment. Finally, it is argued that with re-evaluation of 1960s and 1970s counterculture now underway on the Left, the Hall’s experiment in Laingian countercultural psychiatry—as we may fittingly call it—may yet inform future radical projects (in mental health and beyond)

    Climate Change Hastens the Conservation Urgency of an Endangered Ungulate

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    Global climate change appears to be one of the main threats to biodiversity in the near future and is already affecting the distribution of many species. Currently threatened species are a special concern while the extent to which they are sensitive to climate change remains uncertain. Przewalski's gazelle (Procapra przewalskii) is classified as endangered and a conservation focus on the Qinghai-Tibetan Plateau. Using measures of species range shift, we explored how the distribution of Przewalski's gazelle may be impacted by projected climate change based on a maximum entropy approach. We also evaluated the uncertainty in the projections of the risks arising from climate change. Modeling predicted the Przewalski's gazelle would be sensitive to future climate change. As the time horizon increased, the strength of effects from climate change increased. Even assuming unlimited dispersal capacity of gazelles, a moderate decrease to complete loss of range was projected by 2080 under different thresholds for transforming the probability prediction to presence/absence data. Current localities of gazelles will undergo a decrease in their occurrence probability. Projections of the impacts of climate change were significantly affected by thresholds and general circulation models. This study suggests climate change clearly poses a severe threat and increases the extinction risk to Przewalski's gazelle. Our findings 1) confirm that endangered endemic species is highly vulnerable to climate change and 2) highlight the fact that forecasting impacts of climate change needs an assessment of the uncertainty. It is extremely important that conservation strategies consider the predicted geographical shifts and be planned with full knowledge of the reliability of projected impacts of climate change

    Identification of CD4+ T Cell Epitopes in C. burnetii Antigens Targeted by Antibody Responses

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    Coxiella burnetii is an obligate intracellular Gram-negative bacterium that causes acute Q fever and chronic infections in humans. A killed, whole cell vaccine is efficacious, but vaccination can result in severe local or systemic adverse reactions. Although T cell responses are considered pivotal for vaccine derived protective immunity, the epitope targets of CD4+ T cell responses in C. burnetii vaccination have not been elucidated. Since mapping CD4+ epitopes in a genome with over 2,000 ORFs is resource intensive, we focused on 7 antigens that were known to be targeted by antibody responses. 117 candidate peptides were selected from these antigens based on bioinformatics predictions of binding to the murine MHC class II molecule H-2 IAb. We screened these peptides for recognition by IFN-γ producing CD4+ T cell in phase I C. burnetii whole cell vaccine (PI-WCV) vaccinated C57BL/6 mice and identified 8 distinct epitopes from four different proteins. The identified epitope targets account for 8% of the total vaccination induced IFN-γ producing CD4+ T cells. Given that less than 0.4% of the antigens contained in C. burnetii were screened, this suggests that prioritizing antigens targeted by antibody responses is an efficient strategy to identify at least a subset of CD4+ targets in large pathogens. Finally, we examined the nature of linkage between CD4+ T cell and antibody responses in PI-WCV vaccinated mice. We found a surprisingly non-uniform pattern in the help provided by epitope specific CD4+ T cells for antibody production, which can be specific for the epitope source antigen as well as non-specific. This suggests that a complete map of CD4+ response targets in PI-WCV vaccinated mice will likely include antigens against which no antibody responses are made

    Do Stacked Species Distribution Models Reflect Altitudinal Diversity Patterns?

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    The objective of this study was to evaluate the performance of stacked species distribution models in predicting the alpha and gamma species diversity patterns of two important plant clades along elevation in the Andes. We modelled the distribution of the species in the Anthurium genus (53 species) and the Bromeliaceae family (89 species) using six modelling techniques. We combined all of the predictions for the same species in ensemble models based on two different criteria: the average of the rescaled predictions by all techniques and the average of the best techniques. The rescaled predictions were then reclassified into binary predictions (presence/absence). By stacking either the original predictions or binary predictions for both ensemble procedures, we obtained four different species richness models per taxa. The gamma and alpha diversity per elevation band (500 m) was also computed. To evaluate the prediction abilities for the four predictions of species richness and gamma diversity, the models were compared with the real data along an elevation gradient that was independently compiled by specialists. Finally, we also tested whether our richness models performed better than a null model of altitudinal changes of diversity based on the literature. Stacking of the ensemble prediction of the individual species models generated richness models that proved to be well correlated with the observed alpha diversity richness patterns along elevation and with the gamma diversity derived from the literature. Overall, these models tend to overpredict species richness. The use of the ensemble predictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-prediction, although more research is needed. The randomisation test proved to be a promising method for testing the performance of the stacked models, but other implementations may still be developed

    One-year follow-up of patients of the ongoing Dutch Q fever outbreak: clinical, serological and echocardiographic findings

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    Contains fulltext : 89915.pdf (publisher's version ) (Open Access)PURPOSE: In 2007, a large goat-farming-associated Q fever outbreak occurred in the Netherlands. Data on the clinical outcome of Dutch Q fever patients are lacking. The current advocated follow-up strategy includes serological follow-up to detect evolution to chronic disease and cardiac screening at baseline to identify and prophylactically treat Q fever patients in case of valvulopathy. However, serological follow-up using commercially available tests is complicated by the lack of validated cut-off values. Furthermore, cardiac screening in the setting of a large outbreak has not been implemented previously. Therefore, we report here the clinical outcome, serological follow-up and cardiac screening data of the Q fever patients of the current ongoing outbreak. METHODS: The implementation of a protocol including clinical and serological follow-up at baseline and 3, 6 and 12 months after acute Q fever and screening echocardiography at baseline. RESULTS: Eighty-five patients with acute Q fever were identified (male 62%, female 38%). An aspecific, flu-like illness was the most common clinical presentation. Persistent symptoms after acute Q fever were reported by 59% of patients at 6 months and 30% at 12 months follow-up. We observed a typical serological response to Coxiella burnetii infection in both anti-phase I and anti-phase II IgG antibodies, with an increase in antibody titres up to 3 months and a subsequent decrease in the following 9 months. Screening echocardiography was available for 66 (78%) out of 85 Q fever patients. Cardiac valvulopathy was present in 39 (59%) patients. None of the 85 patients developed chronic Q fever. CONCLUSIONS: Clinical, serological and echocardiographic data of the current ongoing Dutch Q fever outbreak cohort are presented. Screening echocardiography is no longer part of the standard work-up of Q fever patients in the Netherlands.1 december 201
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