Structure-based assignment of the biochemical function of a hypothetical protein: A test case of structural genomics

Many small bacterial, archaebacterial, and eukaryotic genomes have been sequenced, and the larger eukaryotic genomes are predicted to be completely sequenced within the next decade. In all genomes sequenced to date, a large portion of these organisms’ predicted protein coding regions encode polypeptides of unknown biochemical, biophysical, and/or cellular functions. Three-dimensional structures of these proteins may suggest biochemical or biophysical functions. Here we report the crystal structure of one such protein, MJ0577, from a hyperthermophile, Methanococcus jannaschii, at 1.7-Å resolution. The structure contains a bound ATP, suggesting MJ0577 is an ATPase or an ATP-mediated molecular switch, which we confirm by biochemical experiments. Furthermore, the structure reveals different ATP binding motifs that are shared among many homologous hypothetical proteins in this family. This result indicates that structure-based assignment of molecular function is a viable approach for the large-scale biochemical assignment of proteins and for discovering new motifs, a basic premise of structural genomics.

Cyprus ... A Test Case for Future European Banking Policy. CEPS Commentary, 21 March 2013

In this CEPS Commentary, the former Irish Prime Minister calls the precedents being set in the Cypriot banking case “troubling” and reflective of a lack of clarity and consistency of thought by both the eurozone Finance Ministers and the European Commission. He welcomes the rejection of the deal by the Cypriot Parliament as it now gives eurozone policy-makers a chance to think again about the underlying philosophy of their approach to the financial crisis.

Tambora 1815 as a test case for high impact volcanic eruptions: Earth system effects

The eruption of Tambora (Indonesia) in April 1815 had substantial effects on global climate and led to the ‘Year Without a Summer’ of 1816 in Europe and North America. Although a tragic event — tens of thousands of people lost their lives — the eruption also was an ‘experiment of nature’ from which science has learned until today. The aim of this study is to summarize our current understanding of the Tambora eruption and its effects on climate as expressed in early instrumental observations, climate proxies and geological evidence, climate reconstructions, and model simulations. Progress has been made with respect to our understanding of the eruption process and estimated amount of SO2 injected into the atmosphere, although large uncertainties still exist with respect to altitude and hemispheric distribution of Tambora aerosols. With respect to climate effects, the global and Northern Hemispheric cooling are well constrained by proxies whereas there is no strong signal in Southern Hemisphere proxies. Newly recovered early instrumental information for Western Europe and parts of North America, regions with particularly strong climate effects, allow Tambora’s effect on the weather systems to be addressed. Climate models respond to prescribed Tambora-like forcing with a strengthening of the wintertime stratospheric polar vortex, global cooling and a slowdown of the water cycle, weakening of the summer monsoon circulations, a strengthening of the Atlantic Meridional Overturning Circulation, and a decrease of atmospheric CO₂. Combining observations, climate proxies, and model simulations for the case of Tambora, a better understanding of climate processes has emerged.

The functions of societies and the evolution of group living: Spider societies as a test case

Many models have been advanced to suggest how different expressions of sociality have evolved and are maintained. However these models ignore the function of groups for the particular species in question. Here we present a new perspective on sociality where the function of the group takes a central role. We argue that sociality may have primarily a reproductive, protective, or foraging function, depending on whether it enhances the reproductive, protective or foraging aspect of the animal's life (sociality may serve a mixture of these functions). Different functions can potentially cause the development of the same social behaviour. By identifying which function influences a particular social behaviour we can determine how that social behaviour will change with changing conditions, and which models are most pertinent. To test our approach we examined spider sociality, which has often been seen as the poor cousin to insect sociality. By using our approach we found that the group characteristics of eusocial insects is largely governed by the reproductive function of their groups, while the group characteristics of social spiders is largely governed by the foraging function of the group. This means that models relevant to insects may not be relevant to spiders. It also explains why eusocial insects have developed a strict caste system while spider societies are more egalitarian. We also used our approach to explain the differences between different types of spider groups. For example, differences in the characteristics of colonial and kleptoparasitic groups can be explained by differences in foraging methods, while differences between colonial and cooperative spiders can be explained by the role of the reproductive function in the formation of cooperative spider groups. Although the interactions within cooperative spider colonies are largely those of a foraging society, demographic traits and colony dynamics are strongly influenced by the reproductive function. We argue that functional explanations help to understand the social structure of spider groups and therefore the evolutionary potential for speciation in social spiders.

A Binary Classifier for Test Case Feasibility Applied to Automatically Generated Tests of Event-Driven Software

Modern software application testing, such as the testing of software driven by graphical user interfaces (GUIs) or leveraging event-driven architectures in general, requires paying careful attention to context. Model-based testing (MBT) approaches first acquire a model of an application, then use the model to construct test cases covering relevant contexts. A major shortcoming of state-of-the-art automated model-based testing is that many test cases proposed by the model are not actually executable. These \textit{infeasible} test cases threaten the integrity of the entire model-based suite, and any coverage of contexts the suite aims to provide. In this research, I develop and evaluate a novel approach for classifying the feasibility of test cases. I identify a set of pertinent features for the classifier, and develop novel methods for extracting these features from the outputs of MBT tools. I use a supervised logistic regression approach to obtain a model of test case feasibility from a randomly selected training suite of test cases. I evaluate this approach with a set of experiments. The outcomes of this investigation are as follows: I confirm that infeasibility is prevalent in MBT, even for test suites designed to cover a relatively small number of unique contexts. I confirm that the frequency of infeasibility varies widely across applications. I develop and train a binary classifier for feasibility with average overall error, false positive, and false negative rates under 5\%. I find that unique event IDs are key features of the feasibility classifier, while model-specific event types are not. I construct three types of features from the event IDs associated with test cases, and evaluate the relative effectiveness of each within the classifier. To support this study, I also develop a number of tools and infrastructure components for scalable execution of automated jobs, which use state-of-the-art container and continuous integration technologies to enable parallel test execution and the persistence of all experimental artifacts.

Structure optimization combining soft-core interaction functions, the diffusion equation method, and molecular dynamics

Smoothing the potential energy surface for structure optimization is a general and commonly applied strategy. We propose a combination of soft-core potential energy functions and a variation of the diffusion equation method to smooth potential energy surfaces, which is applicable to complex systems such as protein structures; The performance of the method was demonstrated by comparison with simulated annealing using the refinement of the undecapeptide Cyclosporin A as a test case. Simulations were repeated many times using different initial conditions and structures since the methods are heuristic and results are only meaningful in a statistical sense.

Modified particle swarm optimization for day-ahead distributed energy resources scheduling including vehicle-to-grid

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.

Terbinafine: optimization of a LC method for quantitative analysis in pharmaceutical formulations and its application for a tablet dissolution test

A simple liquid chromatographic method was optimized for the quantitative determination of terbinafine in pharmaceutical hydroalcoholic solutions and tablets, and was also employed for a tablet dissolution test. The analysis was carried out using a RP-C18 (250 mm × 4.6 mm, 5 μm) Vertical® column, UV-Vis detection at 254 nm, and a methanol-water (95:5, v/v) mobile phase at a flow-rate of 1.2 mL min-1. Method validation investigated parameters such as linearity, precision, accuracy, robustness and specificity, which gave results within the acceptable range. The tablets dissolution was quite fast: 80% of the drug was dissolved within 15 min.

A Functional Verification Methodology Based on Parameter Domains for Efficient Input Stimuli Generation and Coverage Modeling

Modern Integrated Circuit (IC) design is characterized by a strong trend of Intellectual Property (IP) core integration into complex system-on-chip (SOC) architectures. These cores require thorough verification of their functionality to avoid erroneous behavior in the final device. Formal verification methods are capable of detecting any design bug. However, due to state explosion, their use remains limited to small circuits. Alternatively, simulation-based verification can explore hardware descriptions of any size, although the corresponding stimulus generation, as well as functional coverage definition, must be carefully planned to guarantee its efficacy. In general, static input space optimization methodologies have shown better efficiency and results than, for instance, Coverage Directed Verification (CDV) techniques, although they act on different facets of the monitored system and are not exclusive. This work presents a constrained-random simulation-based functional verification methodology where, on the basis of the Parameter Domains (PD) formalism, irrelevant and invalid test case scenarios are removed from the input space. To this purpose, a tool to automatically generate PD-based stimuli sources was developed. Additionally, we have developed a second tool to generate functional coverage models that fit exactly to the PD-based input space. Both the input stimuli and coverage model enhancements, resulted in a notable testbench efficiency increase, if compared to testbenches with traditional stimulation and coverage scenarios: 22% simulation time reduction when generating stimuli with our PD-based stimuli sources (still with a conventional coverage model), and 56% simulation time reduction when combining our stimuli sources with their corresponding, automatically generated, coverage models.

LC-MS/MS quantitation of plasma progesterone in cattle

Quantitation of progesterone (P(4)) in biological fluids is often performed by radioimmunoassay (RIA), whereas liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) has been used much less often. Due to its autoconfirmatory nature, LC-MS/MS greatly minimizes false positives and interference. Herein we report and compare with RIA an optimized LC-MS/MS method for rapid, efficient, and cost-effective quantitation of P(4) in plasma of cattle with no sample derivatization. The quantitation of plasma P(4) released from three nonbiodegradable, commercial, intravaginal P(4)-releasing devices (IPRD) over 192 h in six ovariectomized cows was compared in a pairwise study as a test case. Both techniques showed similar P(4) kinetics (P > 0.05) whereas results of P(4) quantitation by RIA were consistently higher compared with LC-MS/MS (P < 0.05) due to interference and matrix effects. The LC-MS/MS method was validated according to the recommended analytical standards and displayed P(4) limits of detection (LOD) and quantitation (LOQ) of 0.08 and a 0.25 ng/mL, respectively. The high selective LC-MS/MS method proposed herein for P(4) quantitation eliminates the risks associated with radioactive handling; it also requires no sample derivatization, which is a common requirement for LC-MS/MS quantitation of steroid hormones. Its application to multisteroid assays is also viable, and it is envisaged that it may provide a gold standard technique for hormone quantitation in animal reproductive science studies. (C) 2011 Elsevier Inc. All rights reserved.

Optimal dispatch with reactive power compensation by Genetic Algorithm

This paper presents a Unit Commitment model with reactive power compensation that has been solved by Genetic Algorithm (GA) optimization techniques. The GA has been developed a computational tools programmed/coded in MATLAB. The main objective is to find the best generations scheduling whose active power losses are minimal and the reactive power to be compensated, subjected to the power system technical constraints. Those are: full AC power flow equations, active and reactive power generation constraints. All constraints that have been represented in the objective function are weighted with a penalty factors. The IEEE 14-bus system has been used as test case to demonstrate the effectiveness of the proposed algorithm. Results and conclusions are dully drawn.