Application of mean-shift clustering to Blood oxygen level dependent functional MRI activation detection

BACKGROUND: Functional magnetic resonance imaging (fMRI) analysis is commonly done with cross-correlation analysis (CCA) and the General Linear Model (GLM). Both CCA and GLM techniques, however, typically perform calculations on a per-voxel basis and do not consider relationships neighboring voxels may have. Clustered voxel analyses have then been developed to improve fMRI signal detections by taking advantages of relationships of neighboring voxels. Mean-shift clustering (MSC) is another technique which takes into account properties of neighboring voxels and can be considered for enhancing fMRI activation detection. METHODS: This study examines the adoption of MSC to fMRI analysis. MSC was applied to a Statistical Parameter Image generated with the CCA technique on both simulated and real fMRI data. The MSC technique was then compared with CCA and CCA plus cluster analysis. A range of kernel sizes were used to examine how the technique behaves. RESULTS: Receiver Operating Characteristic curves shows an improvement over CCA and Cluster analysis. False positive rates are lower with the proposed technique. MSC allows the use of a low intensity threshold and also does not require the use of a cluster size threshold, which improves detection of weak activations and highly focused activations. CONCLUSION: The proposed technique shows improved activation detection for both simulated and real Blood Oxygen Level Dependent fMRI data. More detailed studies are required to further develop the proposed technique

The Gas Consumption History to z ~ 4

Using the observations of the star formation rate and HI densities to z ~ 4, with measurements of the Molecular Gas Depletion Rate (MGDR) and local density of H_2 at z = 0, we derive the history of the gas consumption by star formation to z ~ 4. We find that closed-box models in which H_2 is not replenished by HI require improbably large increases in rho(H_2) and a decrease in the MGDR with lookback time that is inconsistent with observations. Allowing the H_2 used in star formation to be replenished by HI does not alleviate the problem because observations show that there is very little evolution of rho(HI) from z = 0 to z = 4. We show that to be consistent with observational constraints, star formation on cosmic timescales must be fueled by intergalactic ionized gas, which may come from either accretion of gas through cold (but ionized) flows or from ionized gas associated with accretion of dark matter halos. We constrain the rate at which the extraglactic ionized gas must be converted into HI and ultimately into H_2. The ionized gas inflow rate roughly traces the SFRD: about 1 - 2 x 10^8 M_sun Gyr^-1 Mpc^-3 from z ~ 1 - 4, decreasing by about an order of magnitude from z=1 to z=0 with details depending largely on MGDR(t). All models considered require the volume averaged density of rho(H_2) to increase by a factor of 1.5 - 10 to z ~ 1.5 over the currently measured value. Because the molecular gas must reside in galaxies, it implies that galaxies at high z must, on average, be more molecule rich than they are at the present epoch, which is consistent with observations. These quantitative results, derived solely from observations, agree well with cosmological simulations.Comment: 11 pages, 6 figures. Accepted for publication in the Astrophysical Journal

Performance of the Two Aerogel Cherenkov Detectors of the JLab Hall A Hadron Spectrometer

We report on the design and commissioning of two silica aerogel Cherenkov detectors with different refractive indices. In particular, extraordinary performance in terms of the number of detected photoelectrons was achieved through an appropriate choice of PMT type and reflector, along with some design considerations. After four years of operation, the number of detected photoelectrons was found to be noticeably reduced in both detectors as a result of contamination, yellowing, of the aerogel material. Along with the details of the set-up, we illustrate the characteristics of the detectors during different time periods and the probable causes of the contamination. In particular we show that the replacement of the contaminated aerogel and parts of the reflecting material has almost restored the initial performance of the detectors.Comment: 18 pages, 9 Figures, 4 Tables, 44 Reference

Purely-long-range bound states of He(2s3S)+(2s ^3S)+He(2p3P)(2p ^3P)

We predict the presence and positions of purely-long-range bound states of $^4$He$(2s ^3S)+{}^4$He$(2p ^3P)$ near the $2s ^3S_1+2p ^3P_{0,1}$ atomic limits. The results of the full multichannel and approximate models are compared, and we assess the sensitivity of the bound states to atomic parameters characterizing the potentials. Photoassociation to these purely-long-range molecular bound states may improve the knowledge of the scattering length associated with the collisions of two ultracold spin-polarized $^4$He$(2s ^3S)$ atoms, which is important for studies of Bose-Einstein condensates.Comment: 16 pages, 5 figure

Talbot Effect for Exciton Polaritons

e demonstrate, experimentally and theoretically, a Talbot effect for hybrid light-matter waves—an exciton-polariton condensate formed in a semiconductor microcavity with embedded quantum wells. The characteristic “Talbot carpet” is produced by loading the exciton-polariton condensate into a microstructured one-dimensional periodic array of mesa traps, which creates an array of phase-locked sources for coherent polariton flow in the plane of the quantum wells. The spatial distribution of the Talbot fringes outside the mesas mimics the near-field diffraction of a monochromatic wave on a periodic amplitude and phase grating with the grating period comparable to the wavelength. Despite the lossy nature of the polariton system, the Talbot pattern persists for distances exceeding the size of the mesas by an order of magnitude. Thus, our experiment demonstrates efficient shaping of the two-dimensional flow of coherent exciton polaritons by a one-dimensional “flat lens.

Linear approaches to intramolecular Förster Resonance Energy Transfer probe measurements for quantitative modeling

Numerous unimolecular, genetically-encoded Forster Resonance Energy Transfer (FRET) probes for monitoring biochemical activities in live cells have been developed over the past decade. As these probes allow for collection of high frequency, spatially resolved data on signaling events in live cells and tissues, they are an attractive technology for obtaining data to develop quantitative, mathematical models of spatiotemporal signaling dynamics. However, to be useful for such purposes the observed FRET from such probes should be related to a biological quantity of interest through a defined mathematical relationship, which is straightforward when this relationship is linear, and can be difficult otherwise. First, we show that only in rare circumstances is the observed FRET linearly proportional to a biochemical activity. Therefore in most cases FRET measurements should only be compared either to explicitly modeled probes or to concentrations of products of the biochemical activity, but not to activities themselves. Importantly, we find that FRET measured by standard intensity-based, ratiometric methods is inherently non-linear with respect to the fraction of probes undergoing FRET. Alternatively, we find that quantifying FRET either via (1) fluorescence lifetime imaging (FLIM) or (2) ratiometric methods where the donor emission intensity is divided by the directly-excited acceptor emission intensity (denoted R<sub>alt</sub>) is linear with respect to the fraction of probes undergoing FRET. This linearity property allows one to calculate the fraction of active probes based on the FRET measurement. Thus, our results suggest that either FLIM or ratiometric methods based on R<sub>alt</sub> are the preferred techniques for obtaining quantitative data from FRET probe experiments for mathematical modeling purpose

Ocean biogeochemistry in the Norwegian Earth System Model version 2 (NorESM2)

The ocean carbon cycle is a key player in the climate system through its role in regulating the atmospheric carbon dioxide concentration and other processes that alter the Earth's radiative balance. In the second version of the Norwegian Earth System Model (NorESM2), the oceanic carbon cycle component has gone through numerous updates that include, amongst others, improved process representations, increased interactions with the atmosphere, and additional new tracers. Oceanic dimethyl sulfide (DMS) is now prognostically simulated and its fluxes are directly coupled with the atmospheric component, leading to a direct feedback to the climate. Atmospheric nitrogen deposition and additional riverine inputs of other biogeochemical tracers have recently been included in the model. The implementation of new tracers such as “preformed” and “natural” tracers enables a separation of physical from biogeochemical drivers as well as of internal from external forcings and hence a better diagnostic of the simulated biogeochemical variability. Carbon isotope tracers have been implemented and will be relevant for studying long-term past climate changes. Here, we describe these new model implementations and present an evaluation of the model's performance in simulating the observed climatological states of water-column biogeochemistry and in simulating transient evolution over the historical period. Compared to its predecessor NorESM1, the new model's performance has improved considerably in many aspects. In the interior, the observed spatial patterns of nutrients, oxygen, and carbon chemistry are better reproduced, reducing the overall model biases. A new set of ecosystem parameters and improved mixed layer dynamics improve the representation of upper-ocean processes (biological production and air–sea CO2 fluxes) at seasonal timescale. Transient warming and air–sea CO2 fluxes over the historical period are also in good agreement with observation-based estimates. NorESM2 participates in the Coupled Model Intercomparison Project phase 6 (CMIP6) through DECK (Diagnostic, Evaluation and Characterization of Klima) and several endorsed MIP simulations.publishedVersio