Where will conflicts between alien and rare species occur after climate and land-use change? A test with a novel combined modelling approach

Protecting native biodiversity against alien invasive species requires powerful methods to anticipate these invasions and to protect native species assumed to be at risk. Here, we describe how species distribution models (SDMs) can be used to identify areas predicted as suitable for rare native species and also predicted as highly susceptible to invasion by alien species, at present and under future climate and land-use scenarios. To assess the condition and dynamics of such conflicts, we developed a combined predictive modelling (CPM) approach, which predicts species distributions by combining two SDMs fitted using subsets of predictors classified as acting at either regional or local scales. We illustrate the CPM approach for an alien invader and a rare species associated to similar habitats in northwest Portugal. Combined models predict a wider variety of potential species responses, providing more informative projections of species distributions and future dynamics than traditional, non-combined models. They also provide more informative insight regarding current and future rare-invasive conflict areas. For our studied species, conflict areas of highest conservation relevance are predicted to decrease over the next decade, supporting previous reports that some invasive species may contract their geographic range and impact due to climate change. More generally, our results highlight the more informative character of the combined approach to address practical issues in conservation and management programs, especially those aimed at mitigating the impact of invasive plants, land-use and climate changes in sensitive regions

Including the workload effect in the parallel program signature

Performance prediction and application behavior modeling have been the subject of exten- sive research that aim to estimate applications performance with an acceptable precision. A novel approach to predict the performance of parallel applications is based in the con- cept of Parallel Application Signatures that consists in extract an application most relevant parts (phases) and the number of times they repeat (weights). Executing these phases in a target machine and multiplying its exeuction time by its weight an estimation of the application total execution time can be made. One of the problems is that the performance of an application depends on the program workload. Every type of workload affects differently how an application performs in a given system and so affects the signature execution time. Since the workloads used in most scientific parallel applications have dimensions and data ranges well known and the behavior of these applications are mostly deterministic, a model of how the programs workload affect its performance can be obtained. We create a new methodology to model how a program’s workload affect the parallel application signature. Using regression analysis we are able to generalize each phase time execution and weight function to predict an application performance in a target system for any type of workload within predefined range. We validate our methodology using a synthetic program, benchmarks applications and well known real scientific applications.

Combining probabilistic land-use change and tree population dynamics modelling to simulate responses in mountain forests

Altitudinal tree lines are mainly constrained by temperature, but can also be influenced by factors such as human activity, particularly in the European Alps, where centuries of agricultural use have affected the tree-line. Over the last decades this trend has been reversed due to changing agricultural practices and land-abandonment. We aimed to combine a statistical land-abandonment model with a forest dynamics model, to take into account the combined effects of climate and human land-use on the Alpine tree-line in Switzerland. Land-abandonment probability was expressed by a logistic regression function of degree-day sum, distance from forest edge, soil stoniness, slope, proportion of employees in the secondary and tertiary sectors, proportion of commuters and proportion of full-time farms. This was implemented in the TreeMig spatio-temporal forest model. Distance from forest edge and degree-day sum vary through feed-back from the dynamics part of TreeMig and climate change scenarios, while the other variables remain constant for each grid cell over time. The new model, TreeMig-LAb, was tested on theoretical landscapes, where the variables in the land-abandonment model were varied one by one. This confirmed the strong influence of distance from forest and slope on the abandonment probability. Degree-day sum has a more complex role, with opposite influences on land-abandonment and forest growth. TreeMig-LAb was also applied to a case study area in the Upper Engadine (Swiss Alps), along with a model where abandonment probability was a constant. Two scenarios were used: natural succession only (100% probability) and a probability of abandonment based on past transition proportions in that area (2.1% per decade). The former showed new forest growing in all but the highest-altitude locations. The latter was more realistic as to numbers of newly forested cells, but their location was random and the resulting landscape heterogeneous. Using the logistic regression model gave results consistent with observed patterns of land-abandonment: existing forests expanded and gaps closed, leading to an increasingly homogeneous landscape.

Effect of a Road Safety Training Program on Drivers' Comparative Optimism

Reducing comparative optimism regarding risk perceptions in traffic accidents has been proven to be particularly difficult (Delhomme, 2000). This is unfortunate because comparative optimism is assumed to impede preventive action. The present study tested whether a road safety training course could reduce drivers' comparative optimism in high control situations. Results show that the training course efficiently reduced comparative optimism in high control, but not in low control situations. Mechanisms underlying this finding and implications for the design of road safety training courses are discussed.

Quantification of in vivo short echo-time proton magnetic resonance spectra at 14.1 T using two different approaches of modelling the macromolecule spectrum

Reliable quantification of the macromolecule signals in short echo-time H-1 MRS spectra is particularly important at high magnetic fields for an accurate quantification of metabolite concentrations (the neurochemical profile) due to effectively increased spectral resolution of the macromolecule components. The purpose of the present study was to assess two approaches of quantification, which take the contribution of macromolecules into account in the quantification step. H-1 spectra were acquired on a 14.1 T/26 cm horizontal scanner on five rats using the ultra-short echo-time SPECIAL (spin echo full intensity acquired localization) spectroscopy sequence. Metabolite concentrations were estimated using LCModel, combined with a simulated basis set of metabolites using published spectral parameters and either the spectrum of macromolecules measured in vivo, using an inversion recovery technique, or baseline simulated by the built-in spline function. The fitted spline function resulted in a smooth approximation of the in vivo macromolecules, but in accordance with previous studies using Subtract-QUEST could not reproduce completely all features of the in vivo spectrum of macromolecules at 14.1 T. As a consequence, the measured macromolecular 'baseline' led to a more accurate and reliable quantification at higher field strengths.

Schistosomiasis mansoni: follow-up of control program based on parasitologic and serologic methods in a Brazilian community of low endemicity

A field survey on schistosomiais was carried out in 1998, in the municipality of Pedro de Toledo, a low endemic area in the state of São Paulo, Brazil. According to the parasitologic Kato-Katz method, the prevalence rate was 1.6%, with an infection intensity of 40.9 eggs per gram of stool. By the immunofluorescence test (IFT) for detection of IgG and IgM antibodies in the serum, IgG-IFT and IgM-IFT, respectively, prevalence indices of 33.2% and 33.5% were observed. To assess the impact of the schistosomiasis control program in the area, parasitologic and serologic data obtained in 1998, analyzed according to the age, sex, and residence zone, were compared to previous data obtained in a epidemiologic study carried out in 1980, when prevalence indices were of 22.8% and 55.5%, respectively by Kato-Katz and IgG-IFT. A significant fall of the prevalence was observed, indicating that the control measures were effective. Nonetheless, residual transmission was observed, demonstrating the need for a joint effort to include new approaches for better understanding the real situation and improving the control of the disease in low endemic areas.

Modelling the mechanical aspects of the curing process of magneto-sensitive elastomeric materials

In this paper, a phenomenologically motivated magneto-mechanically coupled finite strain elastic framework for simulating the curing process of polymers in the presence of a magnetic load is proposed. This approach is in line with previous works by Hossain and co-workers on finite strain curing modelling framework for the purely mechanical polymer curing (Hossain et al., 2009b). The proposed thermodynamically consistent approach is independent of any particular free energy function that may be used for the fully-cured magneto-sensitive polymer modelling, i.e. any phenomenological or micromechanical-inspired free energy can be inserted into the main modelling framework. For the fabrication of magneto-sensitive polymers, micron-size ferromagnetic particles are mixed with the liquid matrix material in the uncured stage. The particles align in a preferred direction with the application of a magnetic field during the curing process. The polymer curing process is a complex (visco) elastic process that transforms a fluid to a solid with time. Such transformation process is modelled by an appropriate constitutive relation which takes into account the temporal evolution of the material parameters appearing in a particular energy function. For demonstration in this work, a frequently used energy function is chosen, i.e. the classical Mooney-Rivlin free energy enhanced by coupling terms. Several representative numerical examples are demonstrated that prove the capability of our approach to correctly capture common features in polymers undergoing curing processes in the presence of a magneto-mechanical coupled load.

The UniProtKB/Swiss-Prot Tox-Prot program: A central hub of integrated venom protein data.

Animal toxins are of interest to a wide range of scientists, due to their numerous applications in pharmacology, neurology, hematology, medicine, and drug research. This, and to a lesser extent the development of new performing tools in transcriptomics and proteomics, has led to an increase in toxin discovery. In this context, providing publicly available data on animal toxins has become essential. The UniProtKB/Swiss-Prot Tox-Prot program (http://www.uniprot.org/program/Toxins) plays a crucial role by providing such an access to venom protein sequences and functions from all venomous species. This program has up to now curated more than 5000 venom proteins to the high-quality standards of UniProtKB/Swiss-Prot (release 2012_02). Proteins targeted by these toxins are also available in the knowledgebase. This paper describes in details the type of information provided by UniProtKB/Swiss-Prot for toxins, as well as the structured format of the knowledgebase.

Antimicrobial susceptibility patterns of unusual nonfermentative gram-negative bacilli isolated from Latin America: report from the SENTRY Antimicrobial Surveillance Program (1997-2002)

The antimicrobial susceptibility of 176 unusual non-fermentative gram-negative bacilli (NF-GNB) collected from Latin America region through the SENTRY Program between 1997 and 2002 was evaluated by broth microdilution according to the National Committee for Clinical Laboratory Standards (NCCLS) recommendations. Nearly 74% of the NF-BGN belonged to the following genera/species: Burkholderia spp. (83), Achromobacter spp. (25), Ralstonia pickettii (16), Alcaligenes spp. (12), and Cryseobacterium spp. (12). Generally, trimethoprim/sulfamethoxazole (MIC50, < 0.5 µg/ml) was the most potent drug followed by levofloxacin (MIC50, 0.5 µg/ml), and gatifloxacin (MIC50, 1 µg/ml). The highest susceptibility rates were observed for levofloxacin (78.3%), gatifloxacin (75.6%), and meropenem (72.6%). Ceftazidime (MIC50, 4 µg/ml; 83.1% susceptible) was the most active beta-lactam against B. cepacia. Against Achromobacter spp. isolates, meropenem (MIC50, 0.25 µg/ml; 88% susceptible) was more active than imipenem (MIC50, 2 µg/ml). Cefepime (MIC50, 2 µg/ml; 81.3% susceptible), and imipenem (MIC50, 2 µg/ml; 81.3% susceptible) were more active than ceftazidime (MIC50, >16 µg/ml; 18.8% susceptible) and meropenem (MIC50, 8 µg/ml; 50% susceptible) against Ralstonia pickettii. Since selection of the most appropriate antimicrobial agents for testing and reporting has not been established by the NCCLS for many of NF-GNB species, results from large multicenter studies may help to guide the best empiric therapy.

Debris flow hazard modelling on medium scale: Valtellina di Tirano, Italy

Debris flow hazard modelling at medium (regional) scale has been subject of various studies in recent years. In this study, hazard zonation was carried out, incorporating information about debris flow initiation probability (spatial and temporal), and the delimitation of the potential runout areas. Debris flow hazard zonation was carried out in the area of the Consortium of Mountain Municipalities of Valtellina di Tirano (Central Alps, Italy). The complexity of the phenomenon, the scale of the study, the variability of local conditioning factors, and the lacking data limited the use of process-based models for the runout zone delimitation. Firstly, a map of hazard initiation probabilities was prepared for the study area, based on the available susceptibility zoning information, and the analysis of two sets of aerial photographs for the temporal probability estimation. Afterwards, the hazard initiation map was used as one of the inputs for an empirical GIS-based model (Flow-R), developed at the University of Lausanne (Switzerland). An estimation of the debris flow magnitude was neglected as the main aim of the analysis was to prepare a debris flow hazard map at medium scale. A digital elevation model, with a 10 m resolution, was used together with landuse, geology and debris flow hazard initiation maps as inputs of the Flow-R model to restrict potential areas within each hazard initiation probability class to locations where debris flows are most likely to initiate. Afterwards, runout areas were calculated using multiple flow direction and energy based algorithms. Maximum probable runout zones were calibrated using documented past events and aerial photographs. Finally, two debris flow hazard maps were prepared. The first simply delimits five hazard zones, while the second incorporates the information about debris flow spreading direction probabilities, showing areas more likely to be affected by future debris flows. Limitations of the modelling arise mainly from the models applied and analysis scale, which are neglecting local controlling factors of debris flow hazard. The presented approach of debris flow hazard analysis, associating automatic detection of the source areas and a simple assessment of the debris flow spreading, provided results for consequent hazard and risk studies. However, for the validation and transferability of the parameters and results to other study areas, more testing is needed.

A randomized controlled trial of the effectiveness of a Computer-Assisted Cognitive Remediation (CACR) program in adolescents with psychosis or at high risk of psychosis: Short term and long term outcomes

The present study investigates the short- and long-term outcomes of a computer-assisted cognitive remediation (CACR) program in adolescents with psychosis or at high risk. 32 adolescents participated in a blinded 8-week randomized controlled trial of CACR treatment compared to computer games (CG). Clinical and neuropsychological evaluations were undertaken at baseline, at the end of the program and at 6-month. At the end of the program (n = 28), results indicated that visuospatial abilities (Repeatable Battery for the Assessment of Neuropsychological Status, RBANS; P = .005) improved signifi cantly more in the CACR group compared to the CG group. Furthermore, other cognitive functions (RBANS), psychotic symptoms (Positive and Negative Symptom Scale) and psychosocial functioning (Social and Occupational Functioning Assessment Scale) improved signifi cantly, but at similar rates, in the two groups. At long term (n = 22), cognitive abilities did not demonstrated any amelioration in the control group while, in the CACR group, signifi cant long-term improvements in inhibition (Stroop; P = .040) and reasoning (Block Design Test; P = .005) were observed. In addition, symptom severity (Clinical Global Improvement) decreased signifi cantly in the control group (P = .046) and marginally in the CACR group (P = .088). To sum up, CACR can be successfully administered in this population. CACR proved to be effective over and above CG for the most intensively trained cognitive ability. Finally, on the long-term, enhanced reasoning and inhibition abilities, which are necessary to execute higher-order goals or to adapt behavior to the ever-changing environment, were observed in adolescents benefi ting from a CACR.

Adaptations des recommandations pour la pratique clinique: l'exemple du Programme cantonal Diabète de Vaud [Adaptation of clinical practice guidelines--the example of cantonal Diabetes Program].

With the growing number of scientific publications, practitioners can use scientific knowledge synthesis, including Clinical Practice Guidelines (CPG). The practical use of a CPG implies considering the context, that is the local healthcare system and the patient. Thus, the CPG can never replace the expertise of the practitioner! Diabetes is a wide public health issue and the canton of Vaud established the cantonal Diabetes Program (cDP), to optimize the care of diabetic patients. The cDP has many projects including the adaptation of reliable CPG to local needs. We present the pros and cons of the CPG in the cDP and the methods to adapt it to the regional healthcare context, and also at an individual level.