Data quality in biofilm high-throughput routine analysis: intralaboratory protocol adaptation and experiment reproducibility

Biofilm research is growing more diverse and dependent on high-throughput technologies and the large-scale production of results aggravates data substantiation. In particular, it is often the case that experimental protocols are adapted to meet the needs of a particular laboratory and no statistical validation of the modified method is provided. This paper discusses the impact of intra-laboratory adaptation and non-rigorous documentation of experimental protocols on biofilm data interchange and validation. The case study is a non-standard, but widely used, workflow for Pseudomonas aeruginosa biofilm development, considering three analysis assays: the crystal violet (CV) assay for biomass quantification, the XTT assay for respiratory activity assessment, and the colony forming units (CFU) assay for determination of cell viability. The ruggedness of the protocol was assessed by introducing small changes in the biofilm growth conditions, which simulate minor protocol adaptations and non-rigorous protocol documentation. Results show that even minor variations in the biofilm growth conditions may affect the results considerably, and that the biofilm analysis assays lack repeatability. Intra-laboratory validation of non-standard protocols is found critical to ensure data quality and enable the comparison of results within and among laboratories.

Local non-negative initial data scalar characterization of the Kerr solution

For any vacuum initial data set, we define a local, non-negative scalar quantity which vanishes at every point of the data hypersurface if and only if the data are Kerr initial data. Our scalar quantity only depends on the quantities used to construct the vacuum initial data set which are the Riemannian metric defined on the initial data hypersurface and a symmetric tensor which plays the role of the second fundamental form of the embedded initial data hypersurface. The dependency is algorithmic in the sense that given the initial data one can compute the scalar quantity by algebraic and differential manipulations, being thus suitable for an implementation in a numerical code. The scalar could also be useful in studies of the non-linear stability of the Kerr solution because it serves to measure the deviation of a vacuum initial data set from the Kerr initial data in a local and algorithmic way.

Discussing Chevalier’s data on the efficiency of tariffs for american and french canals in the 1830s

This article revisits Michel Chevalier’s work and discussions of tariffs. Chevalier shifted from Saint-Simonism to economic liberalism during his life in the 19th century. His influence was soon perceived in the political world and economic debates, mainly because of his discussion of tariffs as instruments of efficient transport policies. This work discusses Chevalier’s thoughts on tariffs by revisiting his masterpiece, Le Cours d’Économie Politique. Data Envelopment Analysis (DEA) was conducted to test Chevalier’s hypothesis on the inefficiency of French tariffs. This work showed that Chevalier’s claims on French tariffs are not validated by DEA.

A breakthrough on Amanita phalloides poisoning: an effective antidotal effect by polymyxin B

Amanita phalloides is responsible for more than 90 % of mushroom-related fatalities, and no effective antidote is available. a-Amanitin, the main toxin of A. phalloides, inhibits RNA polymerase II (RNAP II), causing hepatic and kidney failure. In silico studies included docking and molecular dynamics simulation coupled to molecular mechanics with generalized Born and surface area method energy decomposition on RNAP II. They were performed with a clinical drug that shares chemical similarities to a-amanitin, polymyxin B. The results show that polymyxin B potentially binds to RNAP II in the same interface of a-amanitin, preventing the toxin from binding to RNAP II. In vivo, the inhibition of the mRNA transcripts elicited by a-amanitin was efficiently reverted by polymyxin B in the kidneys. Moreover, polymyxin B significantly decreased the hepatic and renal a-amanitin-induced injury as seen by the histology and hepatic aminotransferases plasma data. In the survival assay, all animals exposed to a-amanitin died within 5 days, whereas 50 % survived up to 30 days when polymyxin B was administered 4, 8, and 12 h post-a-amanitin. Moreover, a single dose of polymyxin B administered concomitantly with a-amanitin was able to guarantee 100 % survival. Polymyxin B protects RNAP II from inactivation leading to an effective prevention of organ damage and increasing survival in a-amanitin-treated animals. The present use of clinically relevant concentrations of an already human-use-approved drug prompts the use of polymyxin B as an antidote for A. phalloides poisoning in humans.

Using balanced scorecards to evaluate the data warehouse system utility

Dissertação de mestrado em Systems Engineering

Evaluating balance, stability and gait symmetry of stroke patients using kinematic and dynamic gait lab data

Dissertação de mestrado integrado em Engenharia Biomédica

Poker learner: modelação de jogadores através de data mining

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Data supporting the role of enzymes and polysaccharides during cassava postharvest physiological deterioration

This data article is referred to the research article entitled The role of ascorbate peroxidase, guaiacol peroxidase, and polysaccharides in cassava (Manihot esculenta Crantz) roots under postharvest physiological deterioration by Uarrota et al. (2015). Food Chemistry 197, Part A, 737746. The stress duo to PPD of cassava roots leads to the formation of ROS which are extremely harmful and accelerates cassava spoiling. To prevent or alleviate injuries from ROS, plants have evolved antioxidant systems that include non-enzymatic and enzymatic defence systems such as ascorbate peroxidase, guaiacol peroxidase and polysaccharides. In this data article can be found a dataset called newdata, in RData format, with 60 observations and 06 variables. The first 02 variables (Samples and Cultivars) and the last 04, spectrophotometric data of ascorbate peroxidase, guaiacol peroxidase, tocopherol, total proteins and arcsined data of cassava PPD scoring. For further interpretation and analysis in R software, a report is also provided. Means of all variables and standard deviations are also provided in the Supplementary tables (data.long3.RData, data.long4.RData and meansEnzymes.RData), raw data of PPD scoring without transformation (PPDmeans.RData) and days of storage (days.RData) are also provided for data analysis reproducibility in R software.

The Data Mining applied for the prediction of highway roughness due to overloaded trucks

Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks

Erratum to: Measurement of the inclusive jet cross-section in proton-proton collisions at s√=7 TeV using 4.5 fb−1 of data with the ATLAS detector

It was found that the non-perturbative corrections calculated using Pythia with the Perugia 2011 tune did not include the effect of the underlying event. The affected correction factors were recomputed using the Pythia 6.427 generator. These corrections are applied as baseline to the NLO pQCD calculations and thus the central values of the theoretical predictions have changed by a few percent with the new corrections. This has a minor impact on the agreement between the data and the theoretical predictions. Figures 2 and 6 to 13, and all the tables have been updated with the new values. A few sentences in the discussion in sections 5.2 and 9 were altered or removed.

Modelling Z→ττ processes in ATLAS with τ-embedded Z→μμ data

This paper describes the concept, technical realisation and validation of a largely data-driven method to model events with Z→ττ decays. In Z→μμ events selected from proton-proton collision data recorded at s√=8 TeV with the ATLAS experiment at the LHC in 2012, the Z decay muons are replaced by τ leptons from simulated Z→ττ decays at the level of reconstructed tracks and calorimeter cells. The τ lepton kinematics are derived from the kinematics of the original muons. Thus, only the well-understood decays of the Z boson and τ leptons as well as the detector response to the τ decay products are obtained from simulation. All other aspects of the event, such as the Z boson and jet kinematics as well as effects from multiple interactions, are given by the actual data. This so-called τ-embedding method is particularly relevant for Higgs boson searches and analyses in ττ final states, where Z→ττ decays constitute a large irreducible background that cannot be obtained directly from data control samples.

Text mining na análise de sentimentos em contextos de big data

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Big data e data analysis: visualização de informação

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Integração da área de negócio de retalho do grupo Riopele no Data Warehouse corporativo

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Enquadramento para a compreensão dos impactos do Open Government Data

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação