98 resultados para Hypothesis testing
Resumo:
This paper explores analytically the contemporary pottery-making community of Pereruela (north-west Spain) that produces cooking pots from a mixture of red clay and kaolin. Analyses by different techniques (XRF, NAA, XRD, SEM and petrography) showed an extremely high variability for cooking ware pottery produced in a single production centre, by the same technology and using local clays. The main source of chemical variation is related to the use of different red clays and the presence of non-normally distributed inclusions of monazite. These two factors induce a high chemical variability, not only in the output of a single production centre, but even in the paste of a single pot, to an extent to which chemical compositions from one"workshop", or even one"pot", could be classified as having different provenances. The implications for the chemical characterization and for provenance studies of archaeological ceramics are addressed.
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In this paper we report on the growth of thick films of magnetoresistive La2/3Sr1/3MnO3 by using spray and screen printing techniques on various substrates (Al2O3 and ZrO2). The growth conditions are explored in order to optimize the microstructure of the films. The films display a room-temperature magnetoresistance of 0.0012%/Oe in the 1 kOe field region. A magnetic sensor is described and tested.
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The present work focuses the attention on the skew-symmetry index as a measure of social reciprocity. This index is based on the correspondence between the amount of behaviour that each individual addresses to its partners and what it receives from them in return. Although the skew-symmetry index enables researchers to describe social groups, statistical inferential tests are required. The main aim of the present study is to propose an overall statistical technique for testing symmetry in experimental conditions, calculating the skew-symmetry statistic (Φ) at group level. Sampling distributions for the skew- symmetry statistic have been estimated by means of a Monte Carlo simulation in order to allow researchers to make statistical decisions. Furthermore, this study will allow researchers to choose the optimal experimental conditions for carrying out their research, as the power of the statistical test has been estimated. This statistical test could be used in experimental social psychology studies in which researchers may control the group size and the number of interactions within dyads.
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This paper examines statistical analysis of social reciprocity, that is, the balance between addressing and receiving behaviour in social interactions. Specifically, it focuses on the measurement of social reciprocity by means of directionality and skew-symmetry statistics at different levels. Two statistics have been used as overall measures of social reciprocity at group level: the directional consistency and the skew-symmetry statistics. Furthermore, the skew-symmetry statistic allows social researchers to obtain complementary information at dyadic and individual levels. However, having computed these measures, social researchers may be interested in testing statistical hypotheses regarding social reciprocity. For this reason, it has been developed a statistical procedure, based on Monte Carlo sampling, in order to allow social researchers to describe groups and make statistical decisions.
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This paper develops an approach to rank testing that nests all existing rank tests andsimplifies their asymptotics. The approach is based on the fact that implicit in every ranktest there are estimators of the null spaces of the matrix in question. The approach yieldsmany new insights about the behavior of rank testing statistics under the null as well as localand global alternatives in both the standard and the cointegration setting. The approach alsosuggests many new rank tests based on alternative estimates of the null spaces as well as thenew fixed-b theory. A brief Monte Carlo study illustrates the results.
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Motivation: The comparative analysis of gene gain and loss rates is critical for understanding the role of natural selection and adaptation in shaping gene family sizes. Studying complete genome data from closely related species allows accurate estimation of gene family turnover rates. Current methods and software tools, however, are not well designed for dealing with certain kinds of functional elements, such as microRNAs or transcription factor binding sites. Results: Here, we describe BadiRate, a new software tool to estimate family turnover rates, as well as the number of elements in internal phylogenetic nodes, by likelihood-based methods and parsimony. It implements two stochastic population models, which provide the appropriate statistical framework for testing hypothesis, such as lineage-specific gene family expansions or contractions. We have assessed the accuracy of BadiRate by computer simulations, and have also illustrated its functionality by analyzing a representative empirical dataset.
Resumo:
Motivation: The comparative analysis of gene gain and loss rates is critical for understanding the role of natural selection and adaptation in shaping gene family sizes. Studying complete genome data from closely related species allows accurate estimation of gene family turnover rates. Current methods and software tools, however, are not well designed for dealing with certain kinds of functional elements, such as microRNAs or transcription factor binding sites. Results: Here, we describe BadiRate, a new software tool to estimate family turnover rates, as well as the number of elements in internal phylogenetic nodes, by likelihood-based methods and parsimony. It implements two stochastic population models, which provide the appropriate statistical framework for testing hypothesis, such as lineage-specific gene family expansions or contractions. We have assessed the accuracy of BadiRate by computer simulations, and have also illustrated its functionality by analyzing a representative empirical dataset.
Resumo:
Invasive candidiasis is the most commonly reported invasive fungal infection worldwide. Although Candida albicans remains the main cause, the incidence of emerging Candida species, such as C. parapsilosis is increasing. It has been postulated that C. parapsilosis clinical isolates result from a recent global expansion of a virulent clone. However, the availability of a single genome for this species has so far prevented testing this hypothesis at genomic scales. We present here the sequence of three additional strains from clinical and environmental samples. Our analyses reveal unexpected patterns of genomic variation, shared among distant strains, that argue against the clonal expansion hypothesis. All strains carry independent expansions involving an arsenite transporter homolog, pointing to the existence of directional selection in the environment, and independent origins of the two clinical isolates. Furthermore, we report the first evidence for the existence of recombination in this species. Altogether, our results shed new light onto the dynamics of genome evolution in C. parapsilosis.
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A change in paradigm is needed in the prevention of toxic effects on the nervous system, moving from its present reliance solely on data from animal testing to a prediction model mostly based on in vitro toxicity testing and in silico modeling. According to the report published by the National Research Council (NRC) of the US National Academies of Science, high-throughput in vitro tests will provide evidence for alterations in"toxicity pathways" as the best possible method of large scale toxicity prediction. The challenges to implement this proposal are enormous, and provide much room for debate. While many efforts address the technical aspects of implementing the vision, many questions around it need also to be addressed. Is the overall strategy the only one to be pursued? How can we move from current to future paradigms? Will we ever be able to reliably model for chronic and developmental neurotoxicity in vitro? This paper summarizes four presentations from a symposium held at the International Neurotoxicology Conference held in Xi"an, China, in June 2011. A. Li reviewed the current guidelines for neurotoxicity and developmental neurotoxicity testing, and discussed the major challenges existing to realize the NCR vision for toxicity testing. J. Llorens reviewed the biology of mammalian toxic avoidance in view of present knowledge on the physiology and molecular biology of the chemical senses, taste and smell. This background information supports the hypothesis that relating in vivo toxicity to chemical epitope descriptors that mimic the chemical encoding performed by the olfactory system may provide a way to the long term future of complete in silico toxicity prediction. S. Ceccatelli reviewed the implementation of rodent and human neural stem cells (NSCs) as models for in vitro toxicity testing that measures parameters such as cell proliferation, differentiation and migration. These appear to be sensitive endpoints that can identify substances with developmental neurotoxic potential. C. Sun ol reviewed the use of primary neuronal cultures in testing for neurotoxicity of environmental pollutants, including the study of the effects of persistent exposures and/or in differentiating cells, which allow recording of effects that can be extrapolated to human developmental neurotoxicity.
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Differences amongst wheat cultivars in the rate of reproductive development are largely dependent on differences in their sensitivity to photoperiod and vernalization. However, when these responses are accounted for, by growing vernalized seedlings under long photoperiods, cultivars can still differ markedly in time to ear emergence. Control of rate of development by this ‘third factor’ has been poorly understood and is variously referred to as intrinsic earliness, earliness in the narrow sense, basic vegetative period, earliness per se, and basic development rate. Certain assumptions are made in the concept of intrinsic earliness. They are that differences in intrinsic earliness (i) are independent of the responses of the cultivars to photoperiod and vernalization, (ii) apply only to the length of the vegetative period up to floral initiation (as suggested by several authors), (iii) are maintained under different temperatures, measured either in days or degree days. As a consequence of this, the ranking of cultivars (from intrinsically early to intrinsically late) must be maintained at different temperatures. This paper, by the re-analysis of published data, examines the extent to which these assumptions can be supported. Although it is shown that intrinsic earliness operates independently of photoperiod and vernalization responses, the other assumptions were not supported. The differences amongst genotypes in time to ear emergence, grown under above-optimum vernalization and photoperiod (that is when the response to these factors is saturated), were not exclusively due to parallel differences in the length of the vegetative phase, and the length of the reproductive phase was independent of that of the vegetative phase. Thus, it would be possible to change the relative allocation of time to vegetative and reproductive periods with no change in the full period to ear emergence. The differences in intrinsic earliness between cultivars were modified by the temperature regime under which they were grown, i.e. the difference between cultivars (both considering the full phase to ear emergence or some sub-phases) was not a constant amount of time or thermal time at different temperatures. In addition, in some instances genotypes changed their ranking for ‘intrinsic earliness’ depending on the temperature regime. This was interpreted to mean that while all genotypes are sensitive to temperature they differ amongst themselves in the extent of that sensitivity. Therefore, ‘intrinsic earliness’ should not be considered as a static genotypic characteristic, but the result of the interaction between the genotype and temperature. Intrinsic earliness is therefore likely to be related to temperature sensitivity. Some implications of these conclusions for plant breeding and crop simulation modelling are discussed.
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Although usability evaluations have been focused on assessing different contexts of use, no proper specifications have been addressed towards the particular environment of academic websites in the Spanish-speaking context of use. Considering that this context involves hundreds of millions of potential users, the AIPO Association is running the UsabAIPO Project. The ultimate goal is to promote an adequate translation of international standards, methods and ideal values related to usability in order to adapt them to diverse Spanish-related contexts of use. This article presents the main statistical results coming from the Second and Third Stages of the UsabAIPO Project, where the UsabAIPO Heuristic method (based on Heuristic Evaluation techniques) and seven Cognitive Walkthroughs were performed over 69 university websites. The planning and execution of the UsabAIPO Heuristic method and the Cognitive Walkthroughs, the definition of two usability metrics, as well as the outline of the UsabAIPO Heuristic Management System prototype are also sketched.
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Many studies have shown that IQs have been increasing over the last half century. These increases have come to be known as «the Flynn effect». The «Flynn effect» represents a difference on ability-level between groups of the same age but different cohort. The ability-level differentiation hypothesis represents a difference on the relevance of cognitive factors between groups of high and low ability. Hence, it should be possible to imitate the ability-level differentiation effect by comparing groups of the same age but different cohort. The indifferentiation hypothesis represents no differences on the relevance of cognitive abilities in all age groups within the same cohort. The aim of the present study is to test the relationships between these phenomena. For this purpose we analyzed the American standardisation samples of the WISC, WISC-R and WISC-III. Results support the link between the Flynn effect and the differentiation hypothesis. Also, reported evidence replicate previous findings supporting the indifferentiation hypothesis. Implications for the assessment of the intelligence are discussed.
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In the present research we have set forth a new, simple, Trade-Off model that would allow us to calculate how much debt and, by default, how much equity a company should have, using easily available information and calculating the cost of debt dynamically on the basis of the effect that the capital structure of the company has on the risk of bankruptcy; in an attempt to answer this question. The proposed model has been applied to the companies that make up the Dow Jones Industrial Average (DJIA) in 2007. We have used consolidated financial data from 1996 to 2006, published by Bloomberg. We have used simplex optimization method to find the debt level that maximizes firm value. Then, we compare the estimated debt with real debt of companies using statistical nonparametric Mann-Whitney. The results indicate that 63% of companies do not show a statistically significant difference between the real and the estimated debt.
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In this paper we describe a taxonomy of task demands which distinguishes between Task Complexity, Task Condition and Task Difficulty. We then describe three theoretical claims and predictions of the Cognition Hypothesis (Robinson 2001, 2003b, 2005a) concerning the effects of task complexity on: (a) language production; (b) interaction and uptake of information available in the input to tasks; and (c) individual differences-task interactions. Finally we summarize the findings of the empirical studies in this special issue which all address one or more of these predictions and point to some directions for continuing, future research into the effects of task complexity on learning and performance.
Resumo:
A new, quantitative, inference model for environmental reconstruction (transfer function), based for the first time on the simultaneous analysis of multigroup species, has been developed. Quantitative reconstructions based on palaeoecological transfer functions provide a powerful tool for addressing questions of environmental change in a wide range of environments, from oceans to mountain lakes, and over a range of timescales, from decades to millions of years. Much progress has been made in the development of inferences based on multiple proxies but usually these have been considered separately, and the different numeric reconstructions compared and reconciled post-hoc. This paper presents a new method to combine information from multiple biological groups at the reconstruction stage. The aim of the multigroup work was to test the potential of the new approach to making improved inferences of past environmental change by improving upon current reconstruction methodologies. The taxonomic groups analysed include diatoms, chironomids and chrysophyte cysts. We test the new methodology using two cold-environment training-sets, namely mountain lakes from the Pyrenees and the Alps. The use of multiple groups, as opposed to single groupings, was only found to increase the reconstruction skill slightly, as measured by the root mean square error of prediction (leave-one-out cross-validation), in the case of alkalinity, dissolved inorganic carbon and altitude (a surrogate for air-temperature), but not for pH or dissolved CO2. Reasons why the improvement was less than might have been anticipated are discussed. These can include the different life-forms, environmental responses and reaction times of the groups under study.