Delay-rate tradeoff for ergodic interference alignment in the Gaussian case

In interference alignment, users sharing a wireless channel are each able to achieve data rates of up to half of the non-interfering channel capacity, no matter the number of users. In an ergodic setting, this is achieved by pairing complementary channel realizations in order to amplify signals and cancel interference. However, this scheme has the possibility for large delays in decoding message symbols. We show that delay can be mitigated by using outputs from potentially more than two channel realizations, although data rate may be reduced. We further demonstrate the tradeoff between rate and delay via a time-sharing strategy. Our analysis considers Gaussian channels; an extension to finite field channels is also possible.Comment: 7 pages, 2 figures, presented at 48th Allerton Conference on Communication Control and Computing, 2010. Includes appendix detailing Markov chain analysi

The Type Ic Supernova 1994I in M51: Detection of Helium and Spectral Evolution

We present a series of spectra of SN 1994I in M51, starting 1 week prior to maximum brightness. The nebular phase began about 2 months after the explosion; together with the rapid decline of the optical light, this suggests that the ejected mass was small. Although lines of He I in the optical region are weak or absent, consistent with the Type Ic classification, we detect strong He I λ10830 absorption during the first month past maximum. Thus, if SN 1994I is a typical Type Ic supernova, the atmospheres of these objects cannot be completely devoid of helium. The emission-line widths are smaller than predicted by the model of Nomoto and coworkers, in which the iron core of a low-mass carbon-oxygen star collapses. They are, however, larger than in Type Ib supernovae

How Cosmic Web Environment Affects Galaxy Quenching Across Cosmic Time

We investigate how cosmic web structures affect galaxy quenching in the IllustrisTNG (TNG-100) cosmological simulations by reconstructing the cosmic web in each snapshot using the DisPerSE framework. We measure the distance from each galaxy with stellar mass log(M*/Msun)>=8 to the nearest node (dnode) and the nearest filament spine (dfil) and study the dependence of both median specific star formation rate () and median gas fraction () on these distances. We find that of galaxies is only dependent on cosmic web environment at z<2, with the dependence increasing with time. At z<=0.5, 8<=log(M*/Msun)<9 galaxies are quenched at dnode<1 Mpc, and significantly star formation-suppressed at dfil<1 Mpc, trends which are driven mostly by satellite galaxies. At z of log(M*/Msun)=10 galaxies actually experience an upturn in at dnode<0.2 Mpc (this is caused by both satellites and centrals). Much of this cosmic web-dependence of star formation activity can be explained by the evolution in . Our results suggest that in the past ~10 Gyr, low-mass satellites are quenched by rapid gas stripping in dense environments near nodes and gradual gas starvation in intermediate-density environments near filaments, while at earlier times cosmic web structures efficiently channeled cold gas into most galaxies. State-of-the-art ongoing spectroscopic surveys such as SDSS and DESI, as well as those planned with JWST and Roman are required to test our predictions against observations.Comment: 5 Figures, 15 pages, submitted to ApJ Letter

Filaments of The Slime Mold Cosmic Web And How They Affect Galaxy Evolution

We present a novel method for identifying cosmic web filaments using the IllustrisTNG (TNG100) cosmological simulations and investigate the impact of filaments on galaxies. We compare the use of cosmic density field estimates from the Delaunay Tessellation Field Estimator (DTFE) and the Monte Carlo Physarum Machine (MCPM), which is inspired by the slime mold organism, in the DisPerSE structure identification framework. The MCPM-based reconstruction identifies filaments with higher fidelity, finding more low-prominence/diffuse filaments and better tracing the true underlying matter distribution than the DTFE-based reconstruction. Using our new filament catalogs, we find that most galaxies are located within 1.5-2.5 Mpc of a filamentary spine, with little change in the median specific star formation rate and the median galactic gas fraction with distance to the nearest filament. Instead, we introduce the filament line density, {\Sigma}fil(MCPM), as the total MCPM overdensity per unit length of a local filament segment, and find that this parameter is a superior predictor of galactic gas supply and quenching. Our results indicate that most galaxies are quenched and gas-poor near high-line density filaments at z10.5 galaxies is mainly driven by mass, while lower-mass galaxies are significantly affected by the filament line density. In high-line density filaments, satellites are strongly quenched, whereas centrals have reduced star formation, but not gas fraction, at z<=0.5. We discuss the prospect of applying our new filament identification method to galaxy surveys with SDSS, DESI, Subaru PFS, etc. to elucidate the effect of large-scale structure on galaxy formation.Comment: Submitted to ApJ, comments welcome. Data available at https://github.com/farhantasy/CosmicWeb-Galaxies

Machine learning classifies predictive kinematic features in a mouse model of neurodegeneration

Motor deficits are observed in Alzheimer’s disease (AD) prior to the appearance of cognitive symptoms. To investigate the role of amyloid proteins in gait disturbances, we characterized locomotion in APP-overexpressing transgenic J20 mice. We used three-dimensional motion capture to characterize quadrupedal locomotion on a treadmill in J20 and wild-type mice. Sixteen J20 mice and fifteen wild-type mice were studied at two ages (4- and 13-month). A random forest (RF) classification algorithm discriminated between the genotypes within each age group using a leave-one-out cross-validation. The balanced accuracy of the RF classification was 92.3 ± 5.2% and 93.3 ± 4.5% as well as False Negative Rate (FNR) of 0.0 ± 0.0% and 0.0 ± 0.0% for the 4-month and 13-month groups, respectively. Feature ranking algorithms identified kinematic features that when considered simultaneously, achieved high genotype classification accuracy. The identified features demonstrated an age-specific kinematic profile of the impact of APP-overexpression. Trunk tilt and unstable hip movement patterns were important in classifying the 4-month J20 mice, whereas patterns of shoulder and iliac crest movement were critical for classifying 13-month J20 mice. Examining multiple kinematic features of gait simultaneously could also be developed to classify motor disorders in humans

Multicentre pilot randomised clinical trial of early in-bed cycle ergometry with ventilated patients.

Introduction: Acute rehabilitation in critically ill patients can improve post-intensive care unit (post-ICU) physical function. In-bed cycling early in a patient\u27s ICU stay is a promising intervention. The objective of this study was to determine the feasibility of recruitment, intervention delivery and retention in a multi centre randomised clinical trial (RCT) of early in-bed cycling with mechanically ventilated (MV) patients. Methods: We conducted a pilot RCT conducted in seven Canadian medical-surgical ICUs. We enrolled adults who could ambulate independently before ICU admission, within the first 4 days of invasive MV and first 7 days of ICU admission. Following informed consent, patients underwent concealed randomisation to either 30 min/day of in-bed cycling and routine physiotherapy (Cycling) or routine physiotherapy alone (Routine) for 5 days/week, until ICU discharge. Our feasibility outcome targets included: accrual of 1-2 patients/month/site; \u3e80% cycling protocol delivery; \u3e80% outcomes measured and \u3e80% blinded outcome measures at hospital discharge. We report ascertainment rates for our primary outcome for the main trial (Physical Function ICU Test-scored (PFIT-s) at hospital discharge). Results: Between 3/2015 and 6/2016, we randomised 66 patients (36 Cycling, 30 Routine). Our consent rate was 84.6 % (66/78). Patient accrual was (mean (SD)) 1.1 (0.3) patients/month/site. Cycling occurred in 79.3% (146/184) of eligible sessions, with a median (IQR) session duration of 30.5 (30.0, 30.7) min. We recorded 43 (97.7%) PFIT-s scores at hospital discharge and 37 (86.0%) of these assessments were blinded. Discussion: Our pilot RCT suggests that a future multicentre RCT of early in-bed cycling for MV patients in the ICU is feasible. Trial registration number: NCT02377830