Optimality Clue for Graph Coloring Problem

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

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

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)

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

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

Presence of Antibodies Against Coxiella burnetii and Risk of Spontaneous Abortion: A Nested Case-Control Study

BACKGROUND AND AIMS: Q fever is a bacterial zoonosis caused by infection with Coxiella burnetii. It is well established that Q fever causes fetal loss in small ruminants. The suspicion has been raised that pregnant women may also experience adverse pregnancy outcome when the infection is acquired or reactivated during pregnancy. The purpose of this study was to assess the potential association between serologic markers of infection with C. burnetii and spontaneous abortion. METHODS: A nested case-control study within the Danish National Birth Cohort, a cohort of 100,418 pregnancies recruited from 1996-2002. Women were recruited in first trimester of pregnancy and followed prospectively. Median gestational age at enrolment was 8 weeks (25 and 75 percentiles: 7 weeks; 10 weeks). During pregnancy, a blood sample was collected at gestational week 6-12 and stored in a bio bank. For this study, a case sample of 218 pregnancies was drawn randomly among the pregnancies in the cohort which ended with a miscarriage before 22 gestational weeks, and a reference group of 482 pregnancies was selected in a random fashion among all pregnancies in the cohort. From these pregnancies, serum samples were screened for antibodies against C. burnetii in a commercial enzyme-linked immunosorbent assay (ELISA). Samples that proved IgG or IgM antibody positive were subsequently confirmatory tested by an immunofluorescence (IFA) test. RESULTS: Among cases, 11 (5%) were C. burnetii positive in ELISA of which one was confirmed in the IFA assay compared to 29 (6%) ELISA positive and 3 IFA confirmed in the random sample. CONCLUSIONS: We found no evidence of a higher prevalence of C. burnetii antibodies in serum samples from women who later miscarried and the present study does not indicate a major association between Q fever infection and spontaneous abortion in humans. Very early first trimester abortions were, however, not included in the study

Complexes Formed in Solution Between Vanadium(IV)/(V) and the Cyclic Dihydroxamic Acid Putrebactin or Linear Suberodihydroxamic Acid

The ability of microbial siderophores to coordinate metal ions, particularly Fe(III), continues to generate interest in the poten-tial applications of these bioligands in the environment and medicine.13 Siderophores produced by terrestrial and marin

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

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

Do Stacked Species Distribution Models Reflect Altitudinal Diversity Patterns?

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

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

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

Effects of the Training Dataset Characteristics on the Performance of Nine Species Distribution Models: Application to Diabrotica virgifera virgifera

Many distribution models developed to predict the presence/absence of invasive alien species need to be fitted to a training dataset before practical use. The training dataset is characterized by the number of recorded presences/absences and by their geographical locations. The aim of this paper is to study the effect of the training dataset characteristics on model performance and to compare the relative importance of three factors influencing model predictive capability; size of training dataset, stage of the biological invasion, and choice of input variables. Nine models were assessed for their ability to predict the distribution of the western corn rootworm, Diabrotica virgifera virgifera, a major pest of corn in North America that has recently invaded Europe. Twenty-six training datasets of various sizes (from 10 to 428 presence records) corresponding to two different stages of invasion (1955 and 1980) and three sets of input bioclimatic variables (19 variables, six variables selected using information on insect biology, and three linear combinations of 19 variables derived from Principal Component Analysis) were considered. The models were fitted to each training dataset in turn and their performance was assessed using independent data from North America and Europe. The models were ranked according to the area under the Receiver Operating Characteristic curve and the likelihood ratio. Model performance was highly sensitive to the geographical area used for calibration; most of the models performed poorly when fitted to a restricted area corresponding to an early stage of the invasion. Our results also showed that Principal Component Analysis was useful in reducing the number of model input variables for the models that performed poorly with 19 input variables. DOMAIN, Environmental Distance, MAXENT, and Envelope Score were the most accurate models but all the models tested in this study led to a substantial rate of mis-classification