Analyzing the effect of homogeneous frustration in protein folding

The energy landscape theory has been an invaluable theoretical framework in the understanding of biological processes such as protein folding, oligomerization, and functional transitions. According to the theory, the energy landscape of protein folding is funneled toward the native state, a conformational state that is consistent with the principle of minimal frustration. It has been accepted that real proteins are selected through natural evolution, satisfying the minimum frustration criterion. However, there is evidence that a low degree of frustration accelerates folding. We examined the interplay between topological and energetic protein frustration. We employed a Cα structure-based model for simulations with a controlled nonspecific energetic frustration added to the potential energy function. Thermodynamics and kinetics of a group of 19 proteins are completely characterized as a function of increasing level of energetic frustration. We observed two well-separated groups of proteins: one group where a little frustration enhances folding rates to an optimal value and another where any energetic frustration slows down folding. Protein energetic frustration regimes and their mechanisms are explained by the role of non-native contact interactions in different folding scenarios. These findings strongly correlate with the protein free-energy folding barrier and the absolute contact order parameters. These computational results are corroborated by principal component analysis and partial least square techniques. One simple theoretical model is proposed as a useful tool for experimentalists to predict the limits of improvements in real proteins. © 2013 Wiley Periodicals, Inc.

The behavior of brazilian senators: analyzing the exchange of votes inside the fixed committees during the 52nd legislature

Using the method of Social Networks Analysis, we’ll try to see if politicians swap votes between them seeking support for their projects, to this end, we’ll first map the behavior, activities and contacts of the Senators of the Brazilian Federative Republic within all the fixed committees which had some vote during the 52nd Legislature, then we can see the most popular and central Senators to each committee. After this analysis we wish to answer the following question: did logrolling exist in the Brazilian Senate? Previously the empirical analysis and response to the problems posed, we’ll present the necessary theoretical introduction understood by reviewing the literature on relevant subjects, whether they are purely theoretical with respect to the exchange of support, or analytical about the Brazilian political system.

Drug addictions and sexual violence in childhood and adolescence: analyzing life stories

The sexual abuse suffered in childhood and adolescence, in addition to damage to physical and psychological health of the victim, is considered as an important risk factor for alcohol and drugs addiction, development of psychopathology and psychosocial damage in adulthood. In addition to the pain and humiliation that are submitted by the abuse, children and adolescents also experience shame and guilt which require them to adopt coping strategies to endure those feelings. The use of psychoactive substances is a recognized way of dealing with the pains of living. This work, which is of narrative style, analyses and discusses, through five case reports, chemical dependency as a result of sexual abuse suffered in childhood and/or adolescence. The eight subjects in this study are male and have suffered sexual violence in this age period of life. Their ages range from 23 years to 39 years, and all are admitted to a therapeutic community in a city in the interior of Sao Paulo state, in Brazil, for treatment of chemical dependency, being met by the Department of Psychology. The reasons for the choice of the participants for treatment modality for patients are: difficult to stop using drugs, even unwilling to take it, they have easy access to it; the feeling of losing control over their lives; by successive losses as a result of drug use, and for fear that their lives had a tragic ending. With the exception of two participants, the others do not classify that as a child suffered sexual violence. However, all attribute that facilitated their entry into the world of drugs. Seven participants experienced such violence in childhood (between 7 years and 9 years) and adolescence (age 14). The attackers were people closed to the victims—in the case of two victims, their families, with the exception of one participant who was raped by a stranger. Six participants declared themselves as homosexual. Another participant does not claim to be homosexual, but presents difficulties in terms of sexuality. Two participants are HIV positive. The start of psychoactive substances use occurred during adolescence (12 years to 17 years). The participants see drugs as an anesthetic to the pain of the soul, a way to get pleasure, but they get charged expensively, as it increases the feeling of emptiness, guilt, helplessness, worthlessness and hopelessness. Although participants have sought help to deal with addiction, it is noted that throughout the life course the issue of sexual violence was not treated. It was noted that the patients have a double stigma in society: the issue of drugs addiction and the orientation of sexual desire, because the majority of participants are homosexual. The results reinforce the need for effective action geared to accommodate the victims of sexual violence and effective preventive measures to prevent children and adolescents from being abused.

Development of a comprehensive method for analyzing clerodane-type diterpenes and phenolic compounds from Casearia sylvestris Swartz (Salicaceae) based on ultra high performance liquid chromatography combined with chemometric tools

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

School inclusion: analyzing the establishment and organization of a special needs education service in a brazilian municipality

The present research integrates a network of studies called National Monitoring Center for Special Education (NMCSE) which studies the Multi-purpose Feature Rooms (MFRs) in regular schools. We aim to investigate whether the service offered by such rooms, maintained by the Department of Education of the Municipality of Araraquara, in São Paulo State, Brazil, is being successful at supporting the education of children and youth with special needs, pervasive developmental disorders and high skilled/gifted individuals. We have also investigated the limits and possibilities of such rooms concerning the set of services offered to their participants. In order to conduct the present research, we have performed: an interview with the Special Education Program manager from the abovementioned Department of Education; and the analysis of a Training Program that MFRs teachers must take. The training program consists of ten morning and afternoon shift meetings. The analyzed data leads us to conclude that the policy of implementation of MFRs, even in this relatively restricted universe is seen from different perspectives. Some interpretations are still permeated by the clinical model, considering individual action. The challenges observed in the classrooms show that the cooperation among teachers still occur randomly and, among other difficulties raised by them, is the selection of the right placement methods to identify eligible students who will benefit from the Specialized Educational Service (SES). In addition, teaching evaluation was considered fragile, as well as the training and the general requirements demanded in order to achieve the expected results.

Analyzing the ACRE Program

The new farm bill enacted by Congress in June 2008 includes a new revenue-based safety-net, the Average Crop Revenue Election (ACRE) Program, that will be available to producers beginning with the 2009 crop year. This analysis of the mechanics of ACRE and the relevant yields and prices to include in ACRE can help producers assess whether ACRE will be a good choice for this crop year and beyond.

Analyzing ACRE: Results for 2009 and Decisions for 2010

In 2009, agricultural producers participating in federal farm programs had to decide between staying in the existing Direct and Counter-Cyclical Program (DCP), and the new Average Crop Revenue Election Program (ACRE). If producers chose to keep the DCP, their farm income safety net is strictly tied to crop prices, with a combination of marketing loans, counter-cyclical payments and direct payments. If producers chose the new ACRE program, they changed their farm income safety net to a combination of price and revenue. The new ACRE component is based on revenue and replaces the counter-cyclical payment. The other parts of the safety net for ACRE participants remain tied to price, albeit at lower levels (direct payments reduced 20 percent, marketing loan rates reduced 30 percent).

Analyzing the ACRE Program

The new farm bill enacted by Congress in June 2008 includes a new revenue-based safety net, the Average Crop Revenue Election (ACRE) Program, that is available to producers beginning with the 2009 crop year. While final details and implementation of the program is yet to be announced by the USDA Farm Service Agency (FSA), an analysis of the mechanics of ACRE and the relevant yields and prices to include in ACRE can help producers assess whether ACRE will be a good choice for this crop year and beyond.

Analyzing the Complexity and Reliability of Switch-Frequency-Reconfigurable Antennas Using Graph Models

This paper addresses the functional reliability and the complexity of reconfigurable antennas using graph models. The correlation between complexity and reliability for any given reconfigurable antenna is defined. Two methods are proposed to reduce failures and improve the reliability of reconfigurable antennas. The failures are caused by the reconfiguration technique or by the surrounding environment. These failure reduction methods proposed are tested and examples are given which verify these methods.

Discriminating Different Classes of Biological Networks by Analyzing the Graphs Spectra Distribution

The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e. g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed.

Conceptual and Experimental Directions for Analyzing Superstition in the Behavioral Analysis of Culture

This paper examines the notions of illusions and beliefs, discussing some advantages offered by the study of these phenomena based on the concepts of superstitious behavior, superstition and superstitious rules. Among these advantages, the study highlights the possibility of researching these relationships in different levels of analysis, not only at the individual level, focusing on cultural level, this paper presents Cultural Materialism as an anthropological proposal for the consideration of these phenomena on the cultural level and based on adaptive principles, besides it discusses the experimental analysis of cultural practices and points Out how they can help to understand how people in groups behave such as they are being effective in the control of the surrounding environment (when, sometimes, in fact, they are not). The paper offers an integrative proposal which makes easier behavior analysts' dialogue with social psychologists and offers some routes from cultural analysis of illusions and beliefs.

Analyzing the dependence structure of microarray data: a copula–based approach

The main aim of this Ph.D. dissertation is the study of clustering dependent data by means of copula functions with particular emphasis on microarray data. Copula functions are a popular multivariate modeling tool in each field where the multivariate dependence is of great interest and their use in clustering has not been still investigated. The first part of this work contains the review of the literature of clustering methods, copula functions and microarray experiments. The attention focuses on the K–means (Hartigan, 1975; Hartigan and Wong, 1979), the hierarchical (Everitt, 1974) and the model–based (Fraley and Raftery, 1998, 1999, 2000, 2007) clustering techniques because their performance is compared. Then, the probabilistic interpretation of the Sklar’s theorem (Sklar’s, 1959), the estimation methods for copulas like the Inference for Margins (Joe and Xu, 1996) and the Archimedean and Elliptical copula families are presented. In the end, applications of clustering methods and copulas to the genetic and microarray experiments are highlighted. The second part contains the original contribution proposed. A simulation study is performed in order to evaluate the performance of the K–means and the hierarchical bottom–up clustering methods in identifying clusters according to the dependence structure of the data generating process. Different simulations are performed by varying different conditions (e.g., the kind of margins (distinct, overlapping and nested) and the value of the dependence parameter ) and the results are evaluated by means of different measures of performance. In light of the simulation results and of the limits of the two investigated clustering methods, a new clustering algorithm based on copula functions (‘CoClust’ in brief) is proposed. The basic idea, the iterative procedure of the CoClust and the description of the written R functions with their output are given. The CoClust algorithm is tested on simulated data (by varying the number of clusters, the copula models, the dependence parameter value and the degree of overlap of margins) and is compared with the performance of model–based clustering by using different measures of performance, like the percentage of well–identified number of clusters and the not rejection percentage of H0 on . It is shown that the CoClust algorithm allows to overcome all observed limits of the other investigated clustering techniques and is able to identify clusters according to the dependence structure of the data independently of the degree of overlap of margins and the strength of the dependence. The CoClust uses a criterion based on the maximized log–likelihood function of the copula and can virtually account for any possible dependence relationship between observations. Many peculiar characteristics are shown for the CoClust, e.g. its capability of identifying the true number of clusters and the fact that it does not require a starting classification. Finally, the CoClust algorithm is applied to the real microarray data of Hedenfalk et al. (2001) both to the gene expressions observed in three different cancer samples and to the columns (tumor samples) of the whole data matrix.