Identifying structural changes with unsupervised machine learning methods

Unsupervised machine learning methods are used to identify structural changes using the melting point transition in classical molecular dynamics simulations as an example application of the approach. Dimensionality reduction and clustering methods are applied to instantaneous radial distributions of atomic configurations from classical molecular dynamics simulations of metallic systems over a large temperature range. Principal component analysis is used to dramatically reduce the dimensionality of the feature space across the samples using an orthogonal linear transformation that preserves the statistical variance of the data under the condition that the new feature space is linearly independent. From there, k-means clustering is used to partition the samples into solid and liquid phases through a criterion motivated by the geometry of the reduced feature space of the samples, allowing for an estimation of the melting point transition. This pattern criterion is conceptually similar to how humans interpret the data but with far greater throughput, as the shapes of the radial distributions are different for each phase and easily distinguishable by humans. The transition temperature estimates derived from this machine learning approach produce comparable results to other methods on similarly small system sizes. These results show that machine learning approaches can be applied to structural changes in physical systems

Point-of-care diagnostics for niche applications

Point-of-care or point-of-use diagnostics are analytical devices that provide clinically relevant information without the need for a core clinical laboratory. In this review we define point-of-care diagnostics as portable versions of assays performed in a traditional clinical chemistry laboratory. This review discusses five areas relevant to human and animal health where increased attention could produce significant impact: veterinary medicine, space travel, sports medicine, emergency medicine, and operating room efficiency. For each of these areas, clinical need, available commercial products, and ongoing research into new devices are highlighted

Nearshore marine ecology at Hutchinson Island, Florida: 1971-1974. VI. plankton dynamics, 1971-1973, VII. phytoplankton 1971-1973, VIII. zooplankton, 1971-1973, IX. diel plankton, 1973-1974, X. benthic algae species list

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Trust in Private and Common Property Experiments

We report the results from a series of experiments designed to investigate behavior in two settings that are frequently posited in the policy literature as generating different outcomes: private property and common property. The experimental settings closely parallel earlier experimental studies of the investment or trust game. The primary research question relates to the effect of the initial allocation of property rights on the level of trust that subjects will extend to others with whom they are linked. We find that assigning the initial endowments as common property of each of N pairs of a first mover and second mover leads to marginally greater cooperation or trust than when the initial endowments are fully owned by the two individual movers as their, respective, private property. Subjectsâ?? decisions are also shown to be correlated with attitudes toward trust and fairness that are measured in post-experiment questionnaires.

Spin Waves in Detwinned BaFe2_2As2_2

Understanding magnetic interactions in the parent compounds of high-temperature superconductors forms the basis for determining their role for the mechanism of superconductivity. For parent compounds of iron pnictide superconductors such as $A$Fe$_2$As$_2$ ($A=$ Ba, Ca, Sr), although spin excitations have been mapped out throughout the entire Brillouin zone (BZ), measurements were carried out on twinned samples and did not allow for a conclusive determination of the spin dynamics. Here we use inelastic neutron scattering to completely map out spin excitations of $\sim$100\% detwinned BaFe$_2$As$_2$. By comparing observed spectra with theoretical calculations, we conclude that the spin excitations can be well described by an itinerant model with important contributions from electronic correlations.Comment: 6 pages, 4 figures, with supplemental materia

Enhancing the social issues components in our computing curriculum: Computing for the social good

The acceptance and integration of social issues into computing curricula is still a work in progress twenty years after it was first incorporated into the ACM Computing Curricula. Through an international survey of computing instructors, this paper corroborates prior work showing that most institutions include the societal impact of ICT in their programs. However, topics often concentrate on computer history, codes of ethics and intellectual property, while neglecting broader issues of societal impact. This paper explores how these neglected topics can be better developed through a subtle change of focus to the significant role that ICT plays in addressing the needs of the community. Drawing on the survey and a set of implementation cases, the paper provides guidance by means of examples and resources to empower teaching teams to engage students in the application of ICT to bring about positive social outcomes – computing for the social good