A multistage mathematical approach to automated clustering of high-dimensional noisy data

A critical problem faced in many scientific fields is the adequate separation of data derived from individual sources. Often, such datasets require analysis of multiple features in a highly multidimensional space, with overlap of features and sources. The datasets generated by simultaneous recording from hundreds of neurons emitting phasic action potentials have produced the challenge of separating the recorded signals into independent data subsets (clusters) corresponding to individual signal-generating neurons. Mathematical methods have been developed over the past three decades to achieve such spike clustering, but a complete solution with fully automated cluster identification has not been achieved. We propose here a fully automated mathematical approach that identifies clusters in multidimensional space through recursion, which combats the multidimensionality of the data. Recursion is paired with an approach to dimensional evaluation, in which each dimension of a dataset is examined for its informational importance for clustering. The dimensions offering greater informational importance are given added weight during recursive clustering. To combat strong background activity, our algorithm takes an iterative approach of data filtering according to a signal-to-noise ratio metric. The algorithm finds cluster cores, which are thereafter expanded to include complete clusters. This mathematical approach can be extended from its prototype context of spike sorting to other datasets that suffer from high dimensionality and background activity.National Institutes of Health (U.S.) (Grant R01 MH060379)United States. Defense Advanced Research Projects AgencyUnited States. Army Research Office (Grant W911NF-10-1-0059)Cure Huntington’s Disease Initiative, Inc. (Grant A-5552

High-fidelity state detection and tomography of a single ion Zeeman qubit

We demonstrate high-fidelity Zeeman qubit state detection in a single trapped 88 Sr+ ion. Qubit readout is performed by shelving one of the qubit states to a metastable level using a narrow linewidth diode laser at 674 nm followed by state-selective fluorescence detection. The average fidelity reached for the readout of the qubit state is 0.9989(1). We then measure the fidelity of state tomography, averaged over all possible single-qubit states, which is 0.9979(2). We also fully characterize the detection process using quantum process tomography. This readout fidelity is compatible with recent estimates of the detection error-threshold required for fault-tolerant computation, whereas high-fidelity state tomography opens the way for high-precision quantum process tomography

A Novel, Robust Quantum Detection Scheme

Protocols used in quantum information and precision spectroscopy rely on efficient internal quantum state discrimination. With a single ion in a linear Paul trap, we implement a novel detection method which utilizes correlations between two detection events with an intermediate spin-flip. The technique is experimentally characterized as more robust against fluctuations in detection laser power compared to conventionally implemented methods. Furthermore, systematic detection errors which limit the Rabi oscillation contrast in conventional methods are overcome

Statistical practices of educational researchers: An analysis of their ANOVA, MANOVA, and ANCOVA analyses

Articles published in several prominent educational journals were examined to investigate the use of data-analysis tools by researchers in four research paradigms: between-subjects univariate designs, between-subjects multivariate designs, repeated measures designs, and covariance designs. In addition to examining specific details pertaining to the research design (e.g., sample size, group size equality/inequality) and methods employed for data analysis, we also catalogued whether: (a) validity assumptions were examined, (b) effect size indices were reported, (c) sample sizes were selected based on power considerations, and (d) appropriate textbooks and/or articles were cited to communicate the nature of the analyses that were performed. Our analyses imply that researchers rarely verify that validity assumptions are satisfied and accordingly typically use analyses that are nonrobust to assumption violations. In addition, researchers rarely report effect size statistics, nor do they routinely perform power analyses to determine sample size requirements. We offer many recommendations to rectify these shortcomings.Social Sciences and Humanities Research Counci

Conserved and Differential Effects of Dietary Energy Intake on the Hippocampal Transcriptomes of Females and Males

The level of dietary energy intake influences metabolism, reproductive function, the development of age-related diseases, and even cognitive behavior. Because males and females typically play different roles in the acquisition and allocation of energy resources, we reasoned that dietary energy intake might differentially affect the brains of males and females at the molecular level. To test this hypothesis, we performed a gene array analysis of the hippocampus in male and female rats that had been maintained for 6 months on either ad libitum (control), 20% caloric restriction (CR), 40% CR, intermittent fasting (IF) or high fat/high glucose (HFG) diets. These diets resulted in expected changes in body weight, and circulating levels of glucose, insulin and leptin. However, the CR diets significantly increased the size of the hippocampus of females, but not males. Multiple genes were regulated coherently in response to energy restriction diets in females, but not in males. Functional physiological pathway analyses showed that the 20% CR diet down-regulated genes involved in glycolysis and mitochondrial ATP production in males, whereas these metabolic pathways were up-regulated in females. The 40% CR diet up-regulated genes involved in glycolysis, protein deacetylation, PGC-1α and mTor pathways in both sexes. IF down-regulated many genes in males including those involved in protein degradation and apoptosis, but up-regulated many genes in females including those involved in cellular energy metabolism, cell cycle regulation and protein deacetylation. Genes involved in energy metabolism, oxidative stress responses and cell death were affected by the HFG diet in both males and females. The gender-specific molecular genetic responses of hippocampal cells to variations in dietary energy intake identified in this study may mediate differential behavioral responses of males and females to differences in energy availability

Academic performance of undergraduate dental students with learning disabilities

© 2017 British Dental Association. All rights reserved.Aims To compare the academic performance of undergraduate dental students with known learning disabilities (LDs) to their peers.Methods This study analysed the results of students in applied dental knowledge (ADK) progress tests across four cohorts of dental students. A mixed model analysis of variance (ANOVA) was conducted to compare the performance of students with known disability to their peers. ADK test sitting was treated as a repeated measures variable, and the outcome variable of interest was percentage score on the ADK.Results Students' performance data on five ADK test sittings (ADK15, ADK16, ADK17, ADK18, and ADK19) by disability showed a significant main effect of test but no significant effect of disability or any interaction between disability and test.Conclusions This is the first study that explores the academic performance of dental students with a diagnosis of disability. The findings give reassurance to all stakeholders that, within the study population, students with LDs are not disadvantaged in knowledge-based assessments, demonstrating compliance with the legal obligations. Further research is required to explore how generalisable these findings are, as well as assess academic, clinical, and behavioural attributes of students with learning disabilities

Age, extent and carbon storage of the central Congo Basin peatland complex

Peatlands are carbon-rich ecosystems that cover just three per cent of Earth's land surface, but store one-third of soil carbon. Peat soils are formed by the build-up of partially decomposed organic matter under waterlogged anoxic conditions. Most peat is found in cool climatic regions where unimpeded decomposition is slower, but deposits are also found under some tropical swamp forests. Here we present field measurements from one of the world's most extensive regions of swamp forest, the Cuvette Centrale depression in the central Congo Basin. We find extensive peat deposits beneath the swamp forest vegetation (peat defined as material with an organic matter content of at least 65 per cent to a depth of at least 0.3 metres). Radiocarbon dates indicate that peat began accumulating from about 10,600 years ago, coincident with the onset of more humid conditions in central Africa at the beginning of the Holocene. The peatlands occupy large interfluvial basins, and seem to be largely rain-fed and ombrotrophic-like (of low nutrient status) systems. Although the peat layer is relatively shallow (with a maximum depth of 5.9 metres and a median depth of 2.0 metres), by combining in situ and remotely sensed data, we estimate the area of peat to be approximately 145,500 square kilometres (95 per cent confidence interval of 131,900-156,400 square kilometres), making the Cuvette Centrale the most extensive peatland complex in the tropics. This area is more than five times the maximum possible area reported for the Congo Basin in a recent synthesis of pantropical peat extent. We estimate that the peatlands store approximately 30.6 petagrams (30.6 × 10(15) grams) of carbon belowground (95 per cent confidence interval of 6.3-46.8 petagrams of carbon)-a quantity that is similar to the above-ground carbon stocks of the tropical forests of the entire Congo Basin. Our result for the Cuvette Centrale increases the best estimate of global tropical peatland carbon stocks by 36 per cent, to 104.7 petagrams of carbon (minimum estimate of 69.6 petagrams of carbon; maximum estimate of 129.8 petagrams of carbon). This stored carbon is vulnerable to land-use change and any future reduction in precipitation

Galaxy bulges and their massive black holes: a review

With references to both key and oft-forgotten pioneering works, this article starts by presenting a review into how we came to believe in the existence of massive black holes at the centres of galaxies. It then presents the historical development of the near-linear (black hole)-(host spheroid) mass relation, before explaining why this has recently been dramatically revised. Past disagreement over the slope of the (black hole)-(velocity dispersion) relation is also explained, and the discovery of sub-structure within the (black hole)-(velocity dispersion) diagram is discussed. As the search for the fundamental connection between massive black holes and their host galaxies continues, the competing array of additional black hole mass scaling relations for samples of predominantly inactive galaxies are presented.Comment: Invited (15 Feb. 2014) review article (submitted 16 Nov. 2014). 590 references, 9 figures, 25 pages in emulateApJ format. To appear in "Galactic Bulges", E. Laurikainen, R.F. Peletier, and D.A. Gadotti (eds.), Springer Publishin