Bayesian Dependence Tests for Continuous, Binary and Mixed Continuous-Binary Variables

Tests for dependence of continuous, discrete and mixed continuous-discrete variables are ubiquitous in science. The goal of this paper is to derive Bayesian alternatives to frequentist null hypothesis significance tests for dependence. In particular, we will present three Bayesian tests for dependence of binary, continuous and mixed variables. These tests are nonparametric and based on the Dirichlet Process, which allows us to use the same prior model for all of them. Therefore, the tests are “consistent” among each other, in the sense that the probabilities that variables are dependent computed with these tests are commensurable across the different types of variables being tested. By means of simulations with artificial data, we show the effectiveness of the new tests.

Investigation of explosion characteristics of multiphase fuel mixtures with air

Otto-von-Guericke-Universität Magdeburg, Fakultät für Verfahrens- und Systemtechnik, Dissertation, 2016

Complex organochlorine pesticide mixtures as determinant factor for breast cancer risk: a population-based case–control study in the Canary Islands (Spain)

[EN]All the relevant risk factors contributing to breast cancer etiology are not fully known. Exposure to organochlorine pesticides has been linked to an increased incidence of the disease, although not all data have been consistent. Most published studies evaluated the exposure to organochlorines individually, ignoring the potential effects exerted by the mixtures of chemicals.

Multiclass Adaboost Based on an Ensemble of Binary Adaboosts

This paper presents a multi-class AdaBoost based on incorporating an ensemble of binary AdaBoosts which is organized as Binary Decision Tree (BDT). It is proved that binary AdaBoost is extremely successful in producing accurate classification but it does not perform very well for multi-class problems. To avoid this performance degradation, the multi-class problem is divided into a number of binary problems and binary AdaBoost classifiers are invoked to solve these classification problems. This approach is tested with a dataset consisting of 6500 binary images of traffic signs. Haar-like features of these images are computed and the multi-class AdaBoost classifier is invoked to classify them. A classification rate of 96.7% and 95.7% is achieved for the traffic sign boarders and pictograms, respectively. The proposed approach is also evaluated using a number of standard datasets such as Iris, Wine, Yeast, etc. The performance of the proposed BDT classifier is quite high as compared with the state of the art and it converges very fast to a solution which indicates it as a reliable classifier.

Evaluation of fly ash in water reduced paving mixtures, 1984

Fly ash was used to replace 15% of the cement in C3WR and C6WR concrete paving mixes containing ASTM C494 Type A water reducin9 admixtures. Two Class C ashes and one Class F ash from Iowa approved sources were examined in each mix. When Class C ashes were used they were substituted on the basis of 1 pound of ash added for each pound of cement deleted. When Class F was used it was substituted on the basis of 1.25 pounds of ash added for each pound of cement deleted. Compressive strengths of the water reduced mixes, with and without fly ash, were determined at 7, 28, and 56 days of age. In every case except one the mixes containing the fly ash exhibited higher strengths than the same concrete mix without the fly ash. An excellent correlation existed between the C3WR and C6WR mixes both with and without fly ash substitutions. The freeze-thaw durability of the concrete studied was not affected by presence or absence of fly ash. The data gathered suggests that the present Class C water reduced concrete paving mixes can be modified to allow the substitution of 15% of the cement with an approved fly ash.

Durability performance of self-compacting concrete (SCC) with binary and ternary mixes of fly ash and limestone filler

The basic objective of this work is to evaluate the durability of self-compacting concrete (SCC) produced in binary and ternary mixes using fly ash (FA) and limestone filler (LF) as partial replacement of cement. The main characteristics that set SCC apart from conventional concrete (fundamentally its fresh state behaviour) essentially depend on the greater or lesser content of various constituents, namely: greater mortar volume (more ultrafine material in the form of cement and mineral additions); proper control of the maximum size of the coarse aggregate; use of admixtures such as superplasticizers. Significant amounts of mineral additions are thus incorporated to partially replace cement, in order to improve the workability of the concrete. These mineral additions necessarily affect the concrete's microstructure and its durability. Therefore, notwithstanding the many well-documented and acknowledged advantages of SCC, a better understanding its behaviour is still required, in particular when its composition includes significant amounts of mineral additions. An ambitious working plan was devised: first, the SCC's microstructure was studied and characterized and afterwards the main transport and degradation mechanisms of the SCC produced were studied and characterized by means of SEM image analysis, chloride migration, electrical resistivity, and carbonation tests. It was then possible to draw conclusions about the SCC's durability. The properties studied are strongly affected by the type and content of the additions. Also, the use of ternary mixes proved to be extremely favourable, confirming the expected beneficial effect of the synergy between LF and FA.

How to deal with uncertainties regarding the occupational exposure to antineoplastic mixtures: additive effect should always be considered?

Risk assessment considerations - The concept that “safe levels of exposure” for humans can be identified for individual chemicals is central to the risk assessment of compounds with known toxicological profiles. Selection of agents for combination chemotherapy regimens involves minimize overlapping of mechanisms of action, antitumor activity and toxicity profile. Although the toxicological profile and mechanism of action of each individual drug is well characterized, the toxicological interactions between drugs are likely, but poorly established at occupational exposure context. The synergistic nature of interactions may help in understanding the adverse health effects observed in healthcare workers, where exposure situations are characterized by complex mixtures of chemical agents, and the levels of individual exposing agents are often not sufficiently high to explain the health complaints. However, if a substance is a genotoxic carcinogen, this would be the “lead effect”; normally, no OEL based on a NOEL would be derived and the level would be set so low that it would be unlikely that other effects would be expected. Aim of the study - Recently research project developed in Portuguese Hospitals characterize the occupational exposure to antineoplastic agents and the health effects related. The project aimed to assess exposure of the different risk groups that handle antineoplastic agents in the hospital setting, namely during preparation and administration of these drugs. Here it is presented and discussed the results in a study developed in two hospitals from Lisbon.

Endocrine disruptors mixtures: the real scenario of human exposure

Endocrine disrupting chemicals (EDCs) are exogenous agents that have the ability to interfere with/or mimic estrogenic hormones and, therefore can simultaneously and differentially trigger specific signaling pathways responsible for the nature and magnitude of biological responses in diverse cell types. Human exposure to EDCs, particularly at low-doses, is ubiquitous, persistent and occurs in complex mixtures. These compounds can bioaccumulate in lipid compartments of tissues forming a mixed “body burden” of contaminants of different origins. Although the independent action of chemicals has been considered the main principle in EDCs mixture toxicity, several effects cannot be predicted when analyzing single compounds individually. Based in a revision of the literature, focused in studies that evaluated EDCs mixtures, we hypothesize the scenario of a pregnant woman environmentally exposed to three different EDCs as a potential real scenario of human exposure supported by data describing where exposure to these compounds occur.

On the reduction theory of binary forms

Cremona developed a reduction theory for binary forms of degree 3 and 4 with integer coefficients, the motivation in the case of quartics being to improve 2-descent algorithms for elliptic curves over Q. In this paper we extend some of these results to forms of higher degree. One application of this is to the study of hyperelliptic curves.

Degenerate mixtures of rubidium and ytterbium for engineering open quantum systems

In the last two decades, experimental progress in controlling cold atoms and ions now allows us to manipulate fragile quantum systems with an unprecedented degree of precision. This has been made possible by the ability to isolate small ensembles of atoms and ions from noisy environments, creating truly closed quantum systems which decouple from dissipative channels. However in recent years, several proposals have considered the possibility of harnessing dissipation in open systems, not only to cool degenerate gases to currently unattainable temperatures, but also to engineer a variety of interesting many-body states. This thesis will describe progress made towards building a degenerate gas apparatus that will soon be capable of realizing these proposals. An ultracold gas of ytterbium atoms, trapped by a species-selective lattice will be immersed into a Bose-Einstein condensate (BEC) of rubidium atoms which will act as a bath. Here we describe the challenges encountered in making a degenerate mixture of rubidium and ytterbium atoms and present two experiments performed on the path to creating a controllable open quantum system. The first experiment will describe the measurement of a tune-out wavelength where the light shift of $\Rb{87}$ vanishes. This wavelength was used to create a species-selective trap for ytterbium atoms. Furthermore, the measurement of this wavelength allowed us to extract the dipole matrix element of the $5s \rightarrow 6p$ transition in $\Rb{87}$ with an extraordinary degree of precision. Our method to extract matrix elements has found use in atomic clocks where precise knowledge of transition strengths is necessary to account for minute blackbody radiation shifts. The second experiment will present the first realization of a degenerate Bose-Fermi mixture of rubidium and ytterbium atoms. Using a three-color optical dipole trap (ODT), we were able to create a highly-tunable, species-selective potential for rubidium and ytterbium atoms which allowed us to use $\Rb{87}$ to sympathetically cool $\Yb{171}$ to degeneracy with minimal loss. This mixture is the first milestone creating the lattice-bath system and will soon be used to implement novel cooling schemes and explore the rich physics of dissipation.

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.

Segregation predictions for a binary mixture of granular material under flow conditions in a continuum mechanics framework

Abstract not available