Applied evolution: An integrated approach to studying life history traits in response to drug selection

The use of chemical control measures to reduce the impact of parasite and pest species has frequently resulted in the development of resistance. Thus, resistance management has become a key concern in human and veterinary medicine, and in agricultural production. Although it is known that factors such as gene flow between susceptible and resistant populations, drug type, application methods, and costs of resistance can affect the rate of resistance evolution, less is known about the impacts of density-dependent eco-evolutionary processes that could be altered by drug-induced mortality. The overall aim of this thesis was to take an experimental evolution approach to assess how life history traits respond to drug selection, using a free-living dioecious worm (Caenorhabditis remanei) as a model. In Chapter 2, I defined the relationship between C. remanei survival and Ivermectin dose over a range of concentrations, in order to control the intensity of selection used in the selection experiment described in Chapter 4. The dose-response data were also used to appraise curve-fitting methods, using Akaike Information Criterion (AIC) model selection to compare a series of nonlinear models. The type of model fitted to the dose response data had a significant effect on the estimates of LD50 and LD99, suggesting that failure to fit an appropriate model could give misleading estimates of resistance status. In addition, simulated data were used to establish that a potential cost of resistance could be predicted by comparing survival at the upper asymptote of dose-response curves for resistant and susceptible populations, even when differences were as low as 4%. This approach to dose-response modeling ensures that the maximum amount of useful information relating to resistance is gathered in one study. In Chapter 3, I asked how simulations could be used to inform important design choices used in selection experiments. Specifically, I focused on the effects of both within- and between-line variation on estimated power, when detecting small, medium and large effect sizes. Using mixed-effect models on simulated data, I demonstrated that commonly used designs with realistic levels of variation could be underpowered for substantial effect sizes. Thus, use of simulation-based power analysis provides an effective way to avoid under or overpowering a study designs incorporating variation due to random effects. In Chapter 4, I 3 investigated how Ivermectin dosage and changes in population density affect the rate of resistance evolution. I exposed replicate lines of C. remanei to two doses of Ivermectin (high and low) to assess relative survival of lines selected in drug-treated environments compared to untreated controls over 10 generations. Additionally, I maintained lines where mortality was imposed randomly to control for differences in density between drug treatments and to distinguish between the evolutionary consequences of drug treatment versus ecological processes affected by changes in density-dependent feedback. Intriguingly, both drug-selected and random-mortality lines showed an increase in survivorship when challenged with Ivermectin; the magnitude of this increase varied with the intensity of selection and life-history stage. The results suggest that interactions between density-dependent processes and life history may mediate evolved changes in susceptibility to control measures, which could result in misleading conclusions about the evolution of heritable resistance following drug treatment. In Chapter 5, I investigated whether the apparent changes in drug susceptibility found in Chapter 4 were related to evolved changes in life-history of C. remanei populations after selection in drug-treated and random-mortality environments. Rapid passage of lines in the drug-free environment had no effect on the measured life-history traits. In the drug-free environment, adult size and fecundity of drug-selected lines increased compared to the controls but drug selection did not affect lifespan. In the treated environment, drug-selected lines showed increased lifespan and fecundity relative to controls. Adult size of randomly culled lines responded in a similar way to drug-selected lines in the drug-free environment, but no change in fecundity or lifespan was observed in either environment. The results suggest that life histories of nematodes can respond to selection as a result of the application of control measures. Failure to take these responses into account when applying control measures could result in adverse outcomes, such as larger and more fecund parasites, as well as over-estimation of the development of genetically controlled resistance. In conclusion, my thesis shows that there may be a complex relationship between drug selection, density-dependent regulatory processes and life history of populations challenged with control measures. This relationship could have implications for how resistance is monitored and managed if life histories of parasitic species show such eco-evolutionary responses to drug application.

Mining and Energy Boom, Dutch Disease and Informality in Colombia: a DSGE Approach

The paper develops a Dynamic Stochastic General Equilibrium (DSGE) model, which assesses the macroeconomic and labor market effects derived from simulating a positive shock to the stochastic component of the mining-energy sector productivity. Calibrating the model for the Colombian economy, this shock generates a whole increase in formal wages and a raise in tax revenues, expanding total consumption of the household members. These facts increase non-tradable goods prices relative to tradable goods prices, then real exchange rate decreases (appreciation) and occurs a displacement of productive resources from the tradable (manufacturing) sector to the non-tradable sector, followed by an increase in formal GDP and formal job gains. This situation makes the formal sector to absorb workers from the informal sector through the non-tradable formal subsector, which causes informal GDP to go down. As a consequence, in the net consumption falls for informal workers, which leads some members of the household not to offer their labor force in the informal sector but instead they prefer to keep unemployed. Therefore, the final result on the labor market is a decrease in the number of informal workers, of which a part are in the formal sector and the rest are unemployed.

Bethe graphs attached to the vertices of a connected graph: a spectral approach

A weighted Bethe graph $B$ is obtained from a weighted generalized Bethe tree by identifying each set of children with the vertices of a graph belonging to a family $F$ of graphs. The operation of identifying the root vertex of each of $r$ weighted Bethe graphs to the vertices of a connected graph $\mathcal{R}$ of order $r$ is introduced as the $\mathcal{R}$-concatenation of a family of $r$ weighted Bethe graphs. It is shown that the Laplacian eigenvalues (when $F$ has arbitrary graphs) as well as the signless Laplacian and adjacency eigenvalues (when the graphs in $F$ are all regular) of the $\mathcal{R}$-concatenation of a family of weighted Bethe graphs can be computed (in a unified way) using the stable and low computational cost methods available for the determination of the eigenvalues of symmetric tridiagonal matrices. Unlike the previous results already obtained on this topic, the more general context of families of distinct weighted Bethe graphs is herein considered.

All one-loop scalar vertices in the effective potential approach

Using the one-loop Coleman-Weinberg effective potential, we derive a general analytic expression for all the derivatives of the effective potential with respect to any number of classical scalar fields. The result is valid for a renormalisable theory in four dimensions with any number of scalars, fermions or gauge bosons. This result corresponds to the zero-external momentum contribution to a general one-loop diagram with N scalar external legs. We illustrate the use of the general result in two simple scalar singlet extensions of the Standard Model, to obtain the dominant contributions to the triple couplings of light scalar particles under the zero external momentum approximation.

An introduction to mathematical models of coagulation-fragmentation processes: a discrete deterministic mean-field approach

We summarise the properties and the fundamental mathematical results associated with basic models which describe coagulation and fragmentation processes in a deterministic manner and in which cluster size is a discrete quantity (an integer multiple of some basic unit size). In particular, we discuss Smoluchowski's equation for aggregation, the Becker-Döring model of simultaneous aggregation and fragmentation, and more general models involving coagulation and fragmentation.

A Visual Analytics Approach to Comparing Cohorts of Event Sequences

Sequences of timestamped events are currently being generated across nearly every domain of data analytics, from e-commerce web logging to electronic health records used by doctors and medical researchers. Every day, this data type is reviewed by humans who apply statistical tests, hoping to learn everything they can about how these processes work, why they break, and how they can be improved upon. To further uncover how these processes work the way they do, researchers often compare two groups, or cohorts, of event sequences to find the differences and similarities between outcomes and processes. With temporal event sequence data, this task is complex because of the variety of ways single events and sequences of events can differ between the two cohorts of records: the structure of the event sequences (e.g., event order, co-occurring events, or frequencies of events), the attributes about the events and records (e.g., gender of a patient), or metrics about the timestamps themselves (e.g., duration of an event). Running statistical tests to cover all these cases and determining which results are significant becomes cumbersome. Current visual analytics tools for comparing groups of event sequences emphasize a purely statistical or purely visual approach for comparison. Visual analytics tools leverage humans' ability to easily see patterns and anomalies that they were not expecting, but is limited by uncertainty in findings. Statistical tools emphasize finding significant differences in the data, but often requires researchers have a concrete question and doesn't facilitate more general exploration of the data. Combining visual analytics tools with statistical methods leverages the benefits of both approaches for quicker and easier insight discovery. Integrating statistics into a visualization tool presents many challenges on the frontend (e.g., displaying the results of many different metrics concisely) and in the backend (e.g., scalability challenges with running various metrics on multi-dimensional data at once). I begin by exploring the problem of comparing cohorts of event sequences and understanding the questions that analysts commonly ask in this task. From there, I demonstrate that combining automated statistics with an interactive user interface amplifies the benefits of both types of tools, thereby enabling analysts to conduct quicker and easier data exploration, hypothesis generation, and insight discovery. The direct contributions of this dissertation are: (1) a taxonomy of metrics for comparing cohorts of temporal event sequences, (2) a statistical framework for exploratory data analysis with a method I refer to as high-volume hypothesis testing (HVHT), (3) a family of visualizations and guidelines for interaction techniques that are useful for understanding and parsing the results, and (4) a user study, five long-term case studies, and five short-term case studies which demonstrate the utility and impact of these methods in various domains: four in the medical domain, one in web log analysis, two in education, and one each in social networks, sports analytics, and security. My dissertation contributes an understanding of how cohorts of temporal event sequences are commonly compared and the difficulties associated with applying and parsing the results of these metrics. It also contributes a set of visualizations, algorithms, and design guidelines for balancing automated statistics with user-driven analysis to guide users to significant, distinguishing features between cohorts. This work opens avenues for future research in comparing two or more groups of temporal event sequences, opening traditional machine learning and data mining techniques to user interaction, and extending the principles found in this dissertation to data types beyond temporal event sequences.

Assessing the Role of General Chemistry Learning in Higher Education

The inclusion of General Chemistry (GC) in the curricula of higher education courses in science and technology aims, on the one hand, to develop students' skills necessary for further studies and, on the other hand, to respond to the need of endowing future professionals of knowledge to analyze and solve multidisciplinary problems in a sustainable way. The participation of students in the evaluation of the role played by the GC in their training is crucial, and the analysis of the results can be an essential tool to increase success in the education of students and improving practices in various professions. Undeniably, this work will be focused on the development of an intelligent system to assess the role of GC. The computational framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a problem solving methodology moored on Artificial Neural Networks. The results so far obtained show that the proposed model stands for a good start, being its overall accuracy higher than 95%.

A new, fast and flexible radiative transfer method for Venus general circulation models

We present a new radiation scheme for the Oxford Planetary Unified Model System for Venus, suitable for the solar and thermal bands. This new and fast radiative parameterization uses a different approach in the two main radiative wavelength bands: solar radiation (0.1-5.5 mu m) and thermal radiation (1.7-260 mu m). The solar radiation calculation is based on the delta-Eddington approximation (two-stream-type) with an adding layer method. For the thermal radiation case, a code based on an absorptivity/emissivity formulation is used. The new radiative transfer formulation implemented is intended to be computationally light, to allow its incorporation in 3D global circulation models, but still allowing for the calculation of the effect of atmospheric conditions on radiative fluxes. This will allow us to investigate the dynamical-radiative-microphysical feedbacks. The model flexibility can be also used to explore the uncertainties in the Venus atmosphere such as the optical properties in the deep atmosphere or cloud amount. The results of radiative cooling and heating rates and the global-mean radiative-convective equilibrium temperature profiles for different atmospheric conditions are presented and discussed. This new scheme works in an atmospheric column and can be easily implemented in 3D Venus global circulation models. (C) 2014 Elsevier Ltd. All rights reserved.

Parcellation of fMRI datasets with ICA and PLS: a data driven approach

Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM) and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of Hemodynamic Response Function (HRF) and task-related signal changes, or about the subject behaviour during the task. In this paper, we introduce a data-driven version of the spectral clustering parcellation, based on Independent Component Analysis (ICA) and Partial Least Squares (PLS) instead of the GLM. First, a number of independent components are automatically selected. Seed voxels are then obtained from the associated ICA maps and we compute the PLS latent variables between the fMRI signal of the seed voxels (which covers regional variations of the HRF) and the principal components of the signal across all voxels. Finally, we parcellate all subjects data with a spectral clustering of the PLS latent variables. We present results of the application of the proposed method on both single-subject and multi-subject fMRI datasets. Preliminary experimental results, evaluated with intra-parcel variance of GLM t-values and PLS derived t-values, indicate that this data-driven approach offers improvement in terms of parcellation accuracy over GLM based techniques.

Optimized probing states for qubit phase estimation with general quantum noise

International audience

A New Multi-Objective Approach for Molecular Docking Based on RMSD and Binding Energy

Ligand-protein docking is an optimization problem based on predicting the position of a ligand with the lowest binding energy in the active site of the receptor. Molecular docking problems are traditionally tackled with single-objective, as well as with multi-objective approaches, to minimize the binding energy. In this paper, we propose a novel multi-objective formulation that considers: the Root Mean Square Deviation (RMSD) difference in the coordinates of ligands and the binding (intermolecular) energy, as two objectives to evaluate the quality of the ligand-protein interactions. To determine the kind of Pareto front approximations that can be obtained, we have selected a set of representative multi-objective algorithms such as NSGA-II, SMPSO, GDE3, and MOEA/D. Their performances have been assessed by applying two main quality indicators intended to measure convergence and diversity of the fronts. In addition, a comparison with LGA, a reference single-objective evolutionary algorithm for molecular docking (AutoDock) is carried out. In general, SMPSO shows the best overall results in terms of energy and RMSD (value lower than 2A for successful docking results). This new multi-objective approach shows an improvement over the ligand-protein docking predictions that could be promising in in silico docking studies to select new anticancer compounds for therapeutic targets that are multidrug resistant.

Medications, youth therapeutic cultures and performance consumptions: a sociological approach

"This article analyses performance consumptions among young people. The theme is explored along two main axes. The first concerns the social heterogeneity in this field, considered on two levels: the different purposes for those investments – cognitive/mental and physical performance; and the different social contexts – university and work – where performance practices and dispositions may be fostered. The second axis explores the roles of pharmacological and natural consumptions, and their interrelationship, in the dissemination of these practices. The empirical data for this analysis were drawn from an ongoing research project on performance consumptions among young people (aged 18−29 years) in Portugal, including both university students and young workers without university education. The results correspond to the stage of extensive research, for which a questionnaire was organised at a national level, using non-proportional quota sampling. On the one hand, they show that (a) there is a hierarchy of acceptance of consumptions according to their purposes, with cognitive/mental performance showing higher acceptance and (b) both pharmaceuticals and natural products are consumed for every type of performance investment. On the other, the comparison between students and workers introduces a certain heterogeneity in this general backdrop, both in terms of the purposes for their consumptions and their opting for natural or pharmacological resources. These threads of heterogeneity will prompt a discussion of the dynamics of pharmaceuticalisation within the field of performance, in particular how therapeutic cultures may be changing in terms of the way individuals relate to medications, expanding their uses in social life."

The Effect of Stress Management Program Using Cognitive Behavior Approach on Mental Health of the Mothers of the Children With Attention Deficit Hyperactivity Disorder

Background: Attention deficit hyperactivity disorder is one of the most common psychiatric disorders in children. Objectives: The study aimed to evaluate the effectiveness of stress management program using cognitive behavior approach on mental health of the mothers of the children with attention deficit hyperactivity disorder. Patients and Methods: In this interventional study, 90 mothers of the children with attention deficit hyperactivity disorder were randomly allocated into three intervention, placebo, and control groups. The general health questionnaire was used to measure mental health. Besides, stress was assessed through the depression-anxiety-stress scale. The two instruments were completed at baseline, immediately after, and one month after the intervention by the mothers. Afterwards, within group comparisons were made using one-sample repeated measurement ANOVA. One-way ANOVA was used for inter group comparisons. Mothers in the placebo group only participated in meetings to talk and express feelings without receiving any interventions. Results: At the baseline, no significant difference was found among the three groups regarding the means of stress, anxiety, depression, and mental health. However, a significant difference was observed in the mean score of stress immediately after the intervention (P = 0.033). The results also showed a significant difference among the three groups regarding the mean score of mental health (P < 0.001). One month after the intervention, the mean difference of mental health score remained significant only in the intervention group (P < 0.001). Conclusions: The study findings confirmed the effectiveness of stress management program utilizing cognitive behavior approach in mental health of the mothers of the children with attention deficit hyperactivity disorder.

A Brief View of the ESP Approach

El artículo trata sobre el enfoque de inglés para fines específicos. Está dirigido a profesores de inglés general, aunque intenta también que la comunidad universitaria reconozca la importancia de evaluar la inversión de recursos en la enseñanza del inglés en función de sus resultados concretados. Se ofrece una descripción de las condiciones que se requieren para diseñar y efectuar estos cursos, acompañada de comentarios surgidos a partir de la experiencia del autor.This article provides information about the English for Specific Purposes (ESP) Approach. Although it is intended for teachers of General English, it also aims for the university community as a whole to evaluate how resources are currently invested in English teaching, with regard to the results obtained. A description of the conditions required to design and implement those courses is presented, along with the author's comments based on his own experience.

Enseñanza de la multiplicación desde un enfoque constructivista en tercero y cuarto año de Educación General Básica

La presente investigación tiene como objetivo demostrar teóricamente la importancia de la enseñanza de la multiplicación a partir de un enfoque constructivista en el tercero y cuarto año de Educación General Básica, años en los que esta enseñanza se profundiza. En efecto, este trabajo monográfico busca responder a las siguientes interrogantes: ¿En qué consiste la multiplicación y su proceso? ¿Cuál es la diferencia de enseñar la multiplicación desde un enfoque tradicional y un enfoque constructivo? Según la Actualización y Fortalecimiento Curricular (2010): ¿Cómo se debe desarrollar su proceso de enseñanza? ¿Qué estrategias se pueden utilizar para trabajar en la comprensión de la multiplicación en el tercero y cuarto año de Educación General Básica? Para responder estas preguntas se recurre a la revisión de información bibliográfica procedente de revistas, libros y artículos de diferentes autores, que facilitan cumplir con los objetivos planteados. Finalmente, se concluye que la enseñanza - aprendizaje basada en los lineamientos del enfoque pedagógico constructivista tiene como resultado la comprensión que los estudiantes necesitan tener hacia la multiplicación para poder utilizarla en su vida académica y cotidiana. Por tal razón se afirma que, la importancia de enseñar la multiplicación desde un enfoque constructivista se fundamenta en que este lineamiento pedagógico propende el uso de dicha operación matemática en la resolución de problemas, desarrollando así su pensamiento lógico – matemático y el razonamiento, a diferencia de lo que ocurre con el tradicionalismo en el que se memoriza por corto plazo.