Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Clinical trial design in non-invasive brain stimulation psychiatric research

Major depressive disorder (MDD) trials - investigating either non-pharmacological or pharmacological interventions - have shown mixed results. Many reasons explain this heterogeneity, but one that stands out is the trial design due to specific challenges in the field. We aimed therefore to review the methodology of non-invasive brain stimulation (NIBS) trials and provide a framework to improve clinical trial design. We performed a systematic review for randomized, controlled MDD trials whose intervention was transcranial magnetic stimulation (rTMS) or transcranial direct current stimulation (tDCS) in MEDLINE and other databases from April 2002 to April 2008. We created an unstructured checklist based on CONSORT guidelines to extract items such as power analysis, sham method, blinding assessment, allocation concealment, operational criteria used for MDD, definition of refractory depression and primary study hypotheses. Thirty-one studies were included. We found that the main methodological issues can be divided in to three groups: (1) issues related to phase II/small trials, (2) issues related to MDD trials and, (3) specific issues of NIBS studies. Taken together, they can threaten study validity and lead to inconclusive results. Feasible solutions include: estimating the sample size a priori; measuring the degree of refractoriness of the subjects; specifying the primary hypothesis and statistical tests; controlling predictor variables through stratification randomization methods or using strict eligibility criteria; adjusting the study design to the target population; using adaptive designs and exploring NIBS efficacy employing biological markers. In conclusion, our study summarizes the main methodological issues of NIBS trials and proposes a number of alternatives to manage them. Copyright (C) 2011 John Wiley & Sons, Ltd.

AcMus: an Open, Integrated Platform for Room Acoustics Research

This article describes the design, implementation, and experiences with AcMus, an open and integrated software platform for room acoustics research, which comprises tools for measurement, analysis, and simulation of rooms for music listening and production. Through use of affordable hardware, such as laptops, consumer audio interfaces and microphones, the software allows evaluation of relevant acoustical parameters with stable and consistent results, thus providing valuable information in the diagnosis of acoustical problems, as well as the possibility of simulating modifications in the room through analytical models. The system is open-source and based on a flexible and extensible Java plug-in framework, allowing for cross-platform portability, accessibility and experimentation, thus fostering collaboration of users, developers and researchers in the field of room acoustics.

A Comparative Wet Collapse Buckling Study for the Carcass Layer of Flexible Pipes

When there is a failure on the external sheath of a flexible pipe, a high value of hydrostatic pressure is transferred to its internal plastic layer and consequently to its interlocked carcass, leading to the possibility of collapse. The design of a flexible pipe must predict the maximum value of external pressure the carcass layer can be subjected to without collapse. This value depends on the initial ovalization due to manufacturing tolerances. To study that problem, two numerical finite element models were developed to simulate the behavior of the carcass subjected to external pressure, including the plastic behavior of the materials. The first one is a full 3D model and the second one is a 3D ring model, both composed by solid elements. An interesting conclusion is that both the models provide the same results. An analytical model using an equivalent thickness approach for the carcass layer was also constructed. A good correlation between analytical and numerical models was achieved for pre-collapse behavior but the collapse pressure value and post-collapse behavior were not well predicted by the analytical model. [DOI: 10.1115/1.4005185]

Interactive quadrangulation with reeb atlases and connectivity textures

Creating high-quality quad meshes from triangulated surfaces is a highly nontrivial task that necessitates consideration of various application specific metrics of quality. In our work, we follow the premise that automatic reconstruction techniques may not generate outputs meeting all the subjective quality expectations of the user. Instead, we put the user at the center of the process by providing a flexible, interactive approach to quadrangulation design. By combining scalar field topology and combinatorial connectivity techniques, we present a new framework, following a coarse to fine design philosophy, which allows for explicit control of the subjective quality criteria on the output quad mesh, at interactive rates. Our quadrangulation framework uses the new notion of Reeb atlas editing, to define with a small amount of interactions a coarse quadrangulation of the model, capturing the main features of the shape, with user prescribed extraordinary vertices and alignment. Fine grain tuning is easily achieved with the notion of connectivity texturing, which allows for additional extraordinary vertices specification and explicit feature alignment, to capture the high-frequency geometries. Experiments demonstrate the interactivity and flexibility of our approach, as well as its ability to generate quad meshes of arbitrary resolution with high-quality statistics, while meeting the user's own subjective requirements.

Linear parameter varying control design for rotating systems supported by journal bearings

Linear parameter varying (LPV) control is a model-based control technique that takes into account time-varying parameters of the plant. In the case of rotating systems supported by lubricated bearings, the dynamic characteristics of the bearings change in time as a function of the rotating speed. Hence, LPV control can tackle the problem of run-up and run-down operational conditions when dynamic characteristics of the rotating system change significantly in time due to the bearings and high vibration levels occur. In this work, the LPV control design for a flexible shaft supported by plain journal bearings is presented. The model used in the LPV control design is updated from unbalance response experimental results and dynamic coefficients for the entire range of rotating speeds are obtained by numerical optimization. Experimental implementation of the designed LPV control resulted in strong reduction of vibration amplitudes when crossing the critical speed, without affecting system behavior in sub- or supercritical speeds. (C) 2012 Elsevier Ltd. All rights reserved.

The Everyday Life in Public Health Research: a theoretical and methodological framework

The aim of this paper is to present some reflections on possibilities to investigate everyday life by examining ways of life, so as to broaden perspectives to the field of research in public health, in light of the fact that the study of daily ways of life involves the analysis of trajectories that contextualize routines, interactions and meanings of life. This allows the social researcher in the health field to have, based on a theoretical framework, a flexible methodology that offers mobility in the choice of the technique that best favors the understanding of the issue to be investigated. We have here, as a conceptual reference, the idea of everyday life investigated from interactive processes and contexts, as opposed to a categorial objectification between subject and object. In this context, from the theoretical reflection, we take, as the research's empirical reference, the waiting room of the outpatient clinic of the Osteoarticular Metabolism Department of a Health Care Unit in the city of Fortaleza/, Northeastern Brazil, in order to foster an interpretive understanding of the daily routine that involves the life and health situations of women with osteoporosis.

Computational framework to support integration of biomolecular and clinical data within a translational approach

Background The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. Results We have implemented an extension of Chado – the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Conclusions Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, existing genomic data models do not represent clinical patient data. A framework was developed to support translational research by integrating biomolecular information coming from different “omics” technologies with patient’s clinical and socio-demographic data. This framework should present some features: flexibility, compression and robustness. The experiments accomplished from a use case demonstrated that the proposed system meets requirements of flexibility and robustness, leading to the desired integration. The Clinical Module can be accessed in http://dcm.ffclrp.usp.br/caib/pg=iptrans webcite.