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"EXPERIMENTAL DATA"
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Collecting experiments : making Big Data biology
Databases have revolutionized nearly every aspect of our lives. Information of all sorts is being collected on a massive scale, from Google to Facebook and well beyond. But as the amount of information in databases explodes, we are forced to reassess our ideas about what knowledge is, how it is produced, to whom it belongs, and who can be credited for producing it. Every scientist working today draws on databases to produce scientific knowledge. Databases have become more common than microscopes, voltmeters, and test tubes, and the increasing amount of data has led to major changes in research practices and profound reflections on the proper professional roles of data producers, collectors, curators, and analysts. Collecting Experiments traces the development and use of data collections, especially in the experimental life sciences, from the early twentieth century to the present. It shows that the current revolution is best understood as the coming together of two older ways of knowing--collecting and experimenting, the museum and the laboratory. Ultimately, Bruno J. Strasser argues that by serving as knowledge repositories, as well as indispensable tools for producing new knowledge, these databases function as digital museums for the twenty-first century.
Book
Ecological impacts of invading seaweeds: a meta-analysis of their effects at different trophic levels
Aim Biological invasions are among the main threats to biodiversity. To promote a mechanistic understanding of the ecological impacts of non-native seaweeds, we assessed how effects on resident organisms vary according to their trophic level. Location Global. Methods We performed meta-analytical comparisons of the effects of non-native seaweeds on both individual species and communities. We compared the results of analyses performed on the whole dataset with those obtained from experimental data only and, when possible, between rocky and soft bottoms. Results Meta-analyses of data from 100 papers revealed consistent negative effects of non-native seaweeds across variables describing resident primary producer communities. In contrast, negative effects of seaweeds on consumers emerged only on their biomass and, limited to rocky bottoms, diversity. At the species level, negative effects were consistent across primary producers' response variables, while only the survival of consumers other than herbivores or predators (e.g. deposit/suspension feeders or detritivores) decreased due to invasion. Excluding mensurative data, negative effects of seaweeds persisted only on resident macroalgal communities and consumer species survival, while switched to positive on the diversity of rocky-bottom consumers. However, negative effects emerged for biomass and, in rocky habitats, density of consumers other than herbivores or predators. Main conclusions Our results support the hypothesis that seaweeds' effects on resident biodiversity are generally more negative within the same trophic level than on higher trophic guilds. Finer trophic grouping of resident organisms revealed more complex impacts than previously detected. High heterogeneity in the responses of some consumer guilds suggests that impacts of non-native seaweeds at higher trophic levels may be more invader- and species-specific than competitive effects at the same trophic level. Features of invaded habitats may further increase variability in seaweeds' impacts. More experimental data on consumers' response to invasion are needed to disentangle the effects of non-native seaweeds from those of other environmental stressors.
Journal Article
Distance-based affective states in cellular automata pedestrian simulation
Cellular Automata have successfully been successfully applied to the modeling and simulation of pedestrian and crowd dynamics. In particular, the investigated scenarios have often been focused on the evaluation of medium–high population density situations, in which the motivation of pedestrians to reach a certain location overcomes their tendency to naturally respect proxemic distances. The global COVID-19 outbreak, though, has shown that sometimes it is crucial to contemplate how proxemic tendencies are emphasized and amplified by the affective state of the individuals involved in the scenario, representing an important factor to take into consideration when investigating the behaviour of a crowd. In this paper we present a research effort aimed at integrating results of quantitative analyses regarding the effects of affective states on the perception of distances maintained by different types of pedestrians with the modeling of pedestrian movement choices in a cellular automata framework.
Journal Article
Partition of Trace Elements between Minerals and Melt: Parameterization of Experimental Data on Olivine, Pyroxene, and Feldspars
The partition of trace elements between minerals (olivine, orthopyroxene, clinopyroxene, and feldspars) and silicate melts is analyzed based on experimental data within broad
P
–
T
ranges (from 1 atm to 10 GPa and ∼1000–2000°C) and the compositions of melts (from ultramafic to ultrasilicic) and minerals. The dependences of the logarithmic partition coefficients (ln
D
i
) on
P
–
T
parameters and compositions are approximated by linear functions of 1/
T
,
P
/
T
(where
P
is pressure and
T
is temperature in K) and compositional parameters of the minerals and melts. The
D
i
/
D
j
ratios of a large number of pairs of elements are found out to be independent of experimental parameters and vary within narrow ranges. The parameters of the dependences of
D
i
on
P
–
T
and compositions are estimated by minimizing the squared deviations of model
D
i
and
D
i
/
D
j
values from experimental ones. The dependences thus derived make it possible to calculate
D
i
for numerous elements accurate to a factor of 1.2–2.0. As an illustrative example, a model is discussed for the derivation of mafic basaltic melts in mid-oceanic ridges at the melting of a peridotite source and crystallization of primary magmas under crustal parameters.
Journal Article
Collecting Experiments
Databases have revolutionized nearly every aspect of our lives. Information of all sorts is being collected on a massive scale, from Google to Facebook and well beyond. But as the amount of information in databases explodes, we are forced to reassess our ideas about what knowledge is, how it is produced, to whom it belongs, and who can be credited for producing it.
Every scientist working today draws on databases to produce scientific knowledge. Databases have become more common than microscopes, voltmeters, and test tubes, and the increasing amount of data has led to major changes in research practices and profound reflections on the proper professional roles of data producers, collectors, curators, and analysts.
Collecting Experiments traces the development and use of data collections, especially in the experimental life sciences, from the early twentieth century to the present. It shows that the current revolution is best understood as the coming together of two older ways of knowing—collecting and experimenting, the museum and the laboratory. Ultimately, Bruno J. Strasser argues that by serving as knowledge repositories, as well as indispensable tools for producing new knowledge, these databases function as digital museums for the twenty-first century.
eBook
Robust Semiparametric and Semi-Nonparametric Estimates of Inhomogeneous Experimental Data
A weighted maximum likelihood method (WMLM) of robust estimation of experimental data with outliers is proposed in this work. The method allows effective robust asymptotically unbiased estimates to be obtained under conditions of aprioristic uncertainty. Based on the WMLM, adaptive robust algorithms have been synthesized for solving semiparametric and semi-nonparametric problems of heterogeneous data processing. It is shown that for heterogeneous data samples, these estimates converge to the maximum likelihood estimates for each distribution from the Tukey supermodel not only in the presence of major, but also minor asymmetric and symmetric outliers.
Journal Article
Robust Parametric Estimates of Heterogeneous Experimental Data
In the present work, a weighted maximum likelihood method (WMLM) is proposed to obtain robust estimates of experimental data containing outliers. The method allows asymptotically effective robust unbiased estimates to be obtained in the presence of not only external, but also internal asymmetric and symmetric outliers. Algorithms for obtaining robust WMLM estimates are considered at the parametric level of aprioristic uncertainty. It is demonstrated that these estimates converge to the maximum likelihood estimates of a heterogeneous data sample for each distribution within the Tukey supermodel.
Journal Article
PET Granule Replacement for Fine Aggregate in Concrete and FRP-Wrapping Effect: Overview of Experimental Data and Model Development
In this study, polyethylene terephthalate (PET) was substituted for 10%, 20%, and 30% of the sand volume in concrete. Compressive, splitting tensile, and flexural strength tests were applied to the concrete samples and stress–strain graphs were obtained. It was observed that PET substitution caused a decrease in the mechanical properties of the concrete. For this reason, the concrete with the best PET substitution rate (10%) was reinforced by wrapping it with carbon fiber-reinforced polymer (CFRP) and glass fiber-reinforced polymer (GFRP), and the same experiments were repeated. It was observed that a 10% PET substitution reduced the strength of the reference concrete by about 6%. However, wrapping the PET-substituted concrete with CFRP and GFRP increased the strength by about 1.9 and 1.5 times, respectively, surpassing that of the reference sample. In addition, this study provides a comprehensive database by bringing together experimental data from studies in which PET was used as a substitute by volume or weight instead of fine aggregate in concrete. The models proposed in this study, along with previous models, were tested for applicability. Similarly, the model suggestions in the literature for fiber-reinforced polymer (FRP)-confined concrete were tested with the experimental data in this study, and their suitability for PET-substituted concrete was discussed.
Journal Article
A Geostatistical Simulation of a Mineral Deposit using Uncertain Experimental Data
In the geostatistical modeling and characterization of natural resources, the traditional approach for determining the spatial distribution of a given deposit using stochastic sequential simulation is to use the existing experimental data (i.e., direct measurements) of the property of interest as if there is no uncertainty involved in the data. However, any measurement is prone to error from different sources, for example from the equipment, the sampling method, or the human factor. It is also common to have distinct measurements for the same property with different levels of resolution and uncertainty. There is a need to assess the uncertainty associated with the experimental data and integrate it during the modeling procedure. This process is not straightforward and is often overlooked. For the reliable modeling and characterization of a given ore deposit, measurement uncertainties should be included as an intrinsic part of the geo-modeling procedure. This work proposes the use of a geostatistical simulation algorithm to integrate uncertain experimental data through the use of stochastic sequential simulations with local probability functions. The methodology is applied to the stochastic modeling of a benchmark mineral deposit, where certain and uncertain experimental data co-exist. The uncertain data is modeled by assigning individual probability distribution functions to each sample location. Different strategies are proposed to build these local probability distributions. Each scenario represents variable degrees of uncertainty. The impacts of the different modeling approaches on the final deposit model are discussed. The resulting models of these proposed scenarios are also compared against those retrieved from previous studies that use conventional geostatistical simulation. The results from the proposed approaches showed that using stochastic sequential simulation with local probability functions to represent local uncertainties decreased the estimation error of the resulting model, producing fewer misclassified ore blocks.
Journal Article
Methods for Calculating the Resistance of Grounding Devices with Backfilling Special Compositions
Traditional analytical methods for calculating and designing of grounding devices (GDs) in heterogeneous soils can lead to results that do not correspond to those obtained in practice. The empirical coefficients used in calculations of grounding systems given in various literature sources do not always give an explicable and significant discrepancy with the same initial data. In this paper, some well-known methods for calculating the spreading resistance of GDs are considered and the obtained results are compared with experimental data. It is shown that the recommendations and algorithms for calculating the resistance of GDs, presented in the well-known reference literature and regulatory documentation, do not give full and correct description for grounding devices installed in heterogeneous soil. In particular, it is shown that such a factor as the proportional ratio of soils with different resistivity practically does not affect the final result. This fact may mislead specialists, since the results obtained may differ significantly from what is observed in practice after the installation of GDs. The study proposes a calculation method and shows a fairly good convergence of the results with experimental data, and defines a further direction in optimizing calculation methods GDs.
Journal Article