Big Data Mining and Complexity

This book offers a much needed critical introduction to data mining and ‘big data’. Supported by multiple case studies and examples, the authors provide: Digestible overviews of key terms and concepts relevant to using social media data in quantitative research. A critical review of data mining and ‘big data’ from a complexity science perspective, including its future potential and limitations A practical exploration of the challenges of putting together and managing a ‘big data’ database An evaluation of the core mathematical and conceptual frameworks, grounded in a case-based computational modeling perspective, which form the foundations of all data mining techniques Part of The SAGE Quantitative Research Kit, this book will give you the know-how and confidence needed to succeed on your quantitative research journey

Advancing Shannon entropy for measuring diversity in systems

From economic inequality and species diversity to power laws and the analysis of multiple trends and trajectories, diversity within systems is a major issue for science. Part of the challenge is measuring it. Shannon entropy H has been used to re-think diversity within probability distributions, based on the notion of information. However, there are two major limitations to Shannon's approach. First, it cannot be used to compare diversity distributions that have different levels of scale. Second, it cannot be used to compare parts of diversity distributions to the whole. To address these limitations, we introduce a re-normalization of probability distributions based on the notion of case-based entropy Cc as a function of the cumulative probability c. Given a probability density p(x), Cc measures the diversity of the distribution up to a cumulative probability of c, by computing the length or support of an equivalent uniform distribution that has the same Shannon information as the conditional distribution of ^pc(x) up to cumulative probability c. We illustrate the utility of our approach by re-normalizing and comparing three well-known energy distributions in physics, namely, the Maxwell-Boltzmann, Bose-Einstein and Fermi-Dirac distributions for energy of sub-atomic particles. The comparison shows that Cc is a vast improvement over H as it provides a scale-free comparison of these diversity distributions and also allows for a comparison between parts of these diversity distributions

COMPLEX-IT: A Case-Based Modelling and Scenario Simulation Platform for Social Inquiry

COMPLEX-IT is a case-based, mixed-methods platform for applied social inquiry into complex data/systems, designed to increase non-expert access to the tools of computational social science (i.e., cluster analysis, artificial intelligence, data visualization, data forecasting, and scenario simulation). In particular, COMPLEX-IT aids applied social inquiry though a heavy emphasis on learning about the complex data/system under study, which it does by (a) identifying and forecasting major and minor clusters/trends; (b) visualizing their complex causality; and (c) simulating scenarios for potential interventions. COMPLEX-IT is accessible through the web or can be run locally and is powered by R and the Shiny web framework

On the comparison of diversity of parts of a distribution

The literature on diversity measures, regardless of the metric used (e.g.,Gini-Simpson index, Shannon entropy) has a notable gap: not much has been done to connect these measures back to the shape of the original distribution, or to use them to compare the diversity of parts of a given distribution and their relationship to the diversity of the whole distribution. As such, the precise quantification of the relationship between the probability of each type pi and the diversity Din non-uniform distributions, both among partsof a distribution as well as the whole, remains unresolved. This is particularly true for Hill numbers, despite their usefulness as‘effective numbers’. This gap is problematic as most real-world systems(e.g., income distributions, economic complexity indices, rankings, ecological systems) have unequal distributions, varying frequencies, and comprise multiple diversity types with unknown frequencies that can change. To address this issue, we connect case-based entropy, an approach to diversity we developed, to the shape of aprobability distribution; allowing us to show that the original probability distribution g1, the case-based entropy curve g2 and the c{1,k} versus the c{1,k} *ln A {1,k} curve g3, which we call the slope of diversity, are one-to-one (or injective), i.e., a different probability distribution g1 gives a different curvefor g2 and g3. Hence, a different permutation of the original probability distribution g1(that leads to a different shape) will uniquely determine the graphs g2 and g3. By proving the injective nature of our approach, we will haveestablished a unique way to measure the degree of uniformity of parts as measured byDP/cP for a given part P of the original probability distribution, and also have shown a unique way to compute theDP/cP for various shapes of the original distribution and (in terms of comparison)for different curves

Synthesis and X-ray Crystal Structure of [(C5Ph5)CrCl(μ-Cl)2Tl]2: An Example of the Rare M-X-TlI Linkage (X = Halide)

Reaction of solid TlCl with [(C5Ph5)CrCl(m-Cl)]2 in CH2Cl2 solvent yields the monomeric complex (C5Ph5)CrCl(m-Cl)2Tl in 80% isolated yield. The C5H5 and C5Me5 analogues do not react with TlCl suggesting a steric basis for the reaction of the C5Ph5 material. An X-ray crystal structure of [(C5Ph5)CrCl(m-Cl)2Tl]2•2CH2Cl2 was obtained

Mitigating the impact of air pollution on brain health and dementia: Policy and practice brief

Emerging research suggests exposure to high levels of air pollution at critical points in the life course is detrimental to brain health, including cognitive decline and dementia. Social determinants such as socio-economic deprivation, environmental factors, and heightened health and social inequalities also play a significant role and make the problem more complicated. While policy and practice strategies have been proposed to address air pollution’s impact on public health more generally, their benefits for brain health, including dementia, remain undeveloped [1, 2]. This policy brief suggests necessary advances across policy and practice to mitigate air pollution and its impact on brain health and dementia

Theoretical Uncertainties in Red Giant Branch Evolution: The Red Giant Branch Bump

A Monte Carlo simulation exploring uncertainties in standard stellar evolution theory on the red giant branch of metal-poor globular clusters has been conducted. Confidence limits are derived on the absolute V-band magnitude of the bump in the red giant branch luminosity function (M_v,b) and the excess number of stars in thebump, R_b. The analysis takes into account uncertainties in the primordial helium abundance, abundance of alpha-capture elements, radiative and conductive opacities, nuclear reaction rates, neutrino energy losses, the treatments of diffusion and convection, the surface boundary conditions, and color transformations. The uncertainty in theoretical values for the red giant bump magnitude varies with metallicity between +0.13/-0.12 mag at [Fe/H] = -2.4 and +0.23/-0.21 mag at [Fe/H] = -1.0$. The dominant sources of uncertainty are the abundance of the alpha-capture elements, the mixing length, and the low-temperature opacities. The theoretical values of M_v,b are in good agreement with observations. The uncertainty in the theoretical value of R_b is +/-0.01 at all metallicities studied. The dominant sources of uncertainty are the abundance of the alpha-capture elements, the mixing length, and the high-temperature opacities. The median value of R_b varies from 0.44 at [Fe/H] = -2.4$ to 0.50 at [Fe/H] = -1.0. These theoretical values for R_b are in agreement with observations.Comment: 30 pages, 6 figures. To appear in Ap

Synthesis, Molecular Structure, and 1H NMR Analysis of Bis(tetraphenylcyclopentadienyl)ruthenium(II)

Reaction of [Ru(p-cymene)Cl2]2 with K(η5-C5HPh4) in refluxing diglyme yields (η5-C5Ph4)2Ru in ca 50% yield. The complex was not susceptible to oxidation or reduction. (C5HPH4)2Ru crystallizes in the triclinic P1 space group with a = 8.549(4), b = 10.793(4), c = 12.842(5) Å, α = 65.98(3), β = 73.10(3), γ = 83.49(3)° and Z = 1. The least-squares data refined to R(F) = 3.53% and R(wF = 3.82% for the 3952 independent observed reflections with Fo ≥ 5σ(Fo). The metal-centroid distance is 1.832(2) Å and all other bond lengths and angles are similar to other octaphenylmetallocenes. 1H NMR analysis employing 2D J-resolved, COSY and low temperature techniques allowed assignment of all protons in the molecule. The motional processes of the phenyl groups are discussed

Sea-ice habitat minimizes grazing impact and predation risk for larval Antarctic krill

Survival of larval Antarctic krill (Euphausia superba) during winter is largely dependent upon the presence of sea ice as it provides an important source of food and shelter. We hypothesized that sea ice provides additional benefits because it hosts fewer competitors and provides reduced predation risk for krill larvae than the water column. To test our hypothesis, zooplankton were sampled in the Weddell-Scotia Confluence Zone at the ice-water interface (0–2 m) and in the water column (0–500 m) during August–October 2013. Grazing by mesozooplankton, expressed as a percentage of the phytoplankton standing stock, was higher in the water column (1.97 ± 1.84%) than at the ice-water interface (0.08 ± 0.09%), due to a high abundance of pelagic copepods. Predation risk by carnivorous macrozooplankton, expressed as a percentage of the mesozooplankton standing stock, was significantly lower at the ice-water interface (0.83 ± 0.57%; main predators amphipods, siphonophores and ctenophores) than in the water column (4.72 ± 5.85%; main predators chaetognaths and medusae). These results emphasize the important role of sea ice as a suitable winter habitat for larval krill with fewer competitors and lower predation risk. These benefits should be taken into account when considering the response of Antarctic krill to projected declines in sea ice. Whether reduced sea-ice algal production may be compensated for by increased water column production remains unclear, but the shelter provided by sea ice would be significantly reduced or disappear, thus increasing the predation risk on krill larvae