Model reconstruction from temporal data for coupled oscillator networks

In a complex system, the interactions between individual agents often lead to emergent collective behavior like spontaneous synchronization, swarming, and pattern formation. The topology of the network of interactions can have a dramatic influence over those dynamics. In many studies, researchers start with a specific model for both the intrinsic dynamics of each agent and the interaction network, and attempt to learn about the dynamics that can be observed in the model. Here we consider the inverse problem: given the dynamics of a system, can one learn about the underlying network? We investigate arbitrary networks of coupled phase-oscillators whose dynamics are characterized by synchronization. We demonstrate that, given sufficient observational data on the transient evolution of each oscillator, one can use machine learning methods to reconstruct the interaction network and simultaneously identify the parameters of a model for the intrinsic dynamics of the oscillators and their coupling.Comment: 27 pages, 7 figures, 16 table

Epi-illumination SPIM for volumetric imaging with high spatial-temporal resolution.

We designed an epi-illumination SPIM system that uses a single objective and has a sample interface identical to that of an inverted fluorescence microscope with no additional reflection elements. It achieves subcellular resolution and single-molecule sensitivity, and is compatible with common biological sample holders, including multi-well plates. We demonstrated multicolor fast volumetric imaging, single-molecule localization microscopy, parallel imaging of 16 cell lines and parallel recording of cellular responses to perturbations

Robust methods for inferring sparse network structures

This is the post-print version of the final paper published in Computational Statistics & Data Analysis. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Networks appear in many fields, from finance to medicine, engineering, biology and social science. They often comprise of a very large number of entities, the nodes, and the interest lies in inferring the interactions between these entities, the edges, from relatively limited data. If the underlying network of interactions is sparse, two main statistical approaches are used to retrieve such a structure: covariance modeling approaches with a penalty constraint that encourages sparsity of the network, and nodewise regression approaches with sparse regression methods applied at each node. In the presence of outliers or departures from normality, robust approaches have been developed which relax the assumption of normality. Robust covariance modeling approaches are reviewed and compared with novel nodewise approaches where robust methods are used at each node. For low-dimensional problems, classical deviance tests are also included and compared with penalized likelihood approaches. Overall, copula approaches are found to perform best: they are comparable to the other methods under an assumption of normality or mild departures from this, but they are superior to the other methods when the assumption of normality is strongly violated

Model reconstruction from temporal data for coupled oscillator networks

© 2019 Author(s). In a complex system, the interactions between individual agents often lead to emergent collective behavior such as spontaneous synchronization, swarming, and pattern formation. Beyond the intrinsic properties of the agents, the topology of the network of interactions can have a dramatic influence over the dynamics. In many studies, researchers start with a specific model for both the intrinsic dynamics of each agent and the interaction network and attempt to learn about the dynamics of the model. Here, we consider the inverse problem: given data from a system, can one learn about the model and the underlying network? We investigate arbitrary networks of coupled phase oscillators that can exhibit both synchronous and asynchronous dynamics. We demonstrate that, given sufficient observational data on the transient evolution of each oscillator, machine learning can reconstruct the interaction network and identify the intrinsic dynamics

Impact of Transitory ROSC Events on Neurological Outcome in Patients with Out-of-Hospital Cardiac Arrest

In out-of-hospital cardiac arrest (OHCA), the occurrence of temporary periods of return to spontaneous circulation (t-ROSC) has been found to be predictive of survival to hospital discharge. The relationship between the duration of t-ROSCs and OHCA outcome has not been explored yet. The aim of this prospective observational study was to analyze the duration of t-ROSCs during OHCA and its impact on outcome. Defibrillator-recorded OHCA events were analyzed via dedicated software. The number of t-ROSC episodes and their overall durations were recorded. The study endpoint was the good neurologic outcome at hospital discharge. Among 285 patients included in the study, 45 (15.8%) had one or more t-ROSCs. The likelihood of t-ROSC occurrence was higher in patients with a shockable rhythm (p = 0.009). The cumulative length of t-ROSC episodes was significantly higher for patients who achieved sustained ROSC (p < 0.001). The adjusted cumulative t-ROSC length was an independent predictor for good neurological outcome at hospital discharge (OR 1.588, 95% CI 1.017 to 2.481; p = 0.042). According to our findings and data from previous studies, t-ROSC episodes during OHCA should be considered as a favorable prognostic factor, encouraging continuing resuscitative efforts

Interdisciplinary applications of human time use with generalized lexicons

Time use studies quantify what people do, over particular time intervals. The results of these studies have illuminated diverse and important aspects of societies and economies, from populations around the world. Yet, these efforts have advanced in a fragmented manner, using non-standardized descriptions (lexicons) of time use that often require researchers to make arbitrary designations among non-exclusive categories, and are not easily translated between disciplines. Here we propose a new approach, assembling multiple dimensions of time use to construct what we call the human chronome, as a means to provide novel interdisciplinary perspectives on fundamental aspects of human behaviour and experience. The approach is enabled by parallel lexicons, each of which aims for low ambiguity by focusing on a single coherent categorical dimension, and which can then be combined to provide a multi-dimensional characterization. Each lexicon should follow a single, consistent theoretical orientation, ensure exhaustiveness and exclusivity, and minimize ambiguity arising from temporal and social aggregation. As a pragmatic first step towards this goal, we describe the development of the Motivating- Outcome- Oriented General Activity Lexicon (MOOGAL). The MOOGAL is theoretically oriented towards the outcomes of activities, is applicable to any human from hunter-gatherers to modern urbanites, and deliberately focuses on the physical outcomes which motivate the undertaking of activities to reduce ambiguity from social aggregation. We illustrate the utility of the MOOGAL by comparing it with existing economic, sociological and anthropological lexicons, showing that it exhaustively covers the previously-defined activities with low ambiguity, and apply it to time use and economic data from two countries. Our results support the feasibility of using generalized lexicons to incorporate diverse observational constraints on time use, thereby providing a rich interdisciplinary perspective on the human system that is particularly relevantto the current period of rapid social, technological and environmental change

The Impact of Dual Enrollment on College Application Choice and Admission Success

Dual enrollment is one of the fastest growing programs that support the high school-to-college transition. Yet, there is limited empirical evidence about its impact on either students’ college application choices or admission outcomes. Using a fuzzy regression discontinuity approach and data from two cohorts of ninth-grade students in one anonymous state, the authors of this paper found that taking dual enrollment credits increased the total number of colleges students applied to and the likelihood of applying to any moderately or highly selective in-state four-year institution. Attempting dual enrollment credits also increased the total number of in-state four-year colleges a student got admitted to and the probability of being admitted to a highly selective in-state four-year college. Heterogeneous analysis further indicates that the gains were primarily driven by Black students

Accelerated structural evolution of galaxies in a starbursting cluster at z=2.51

Structural properties of cluster galaxies during their peak formation epoch, $z \sim 2-4$ provide key information on whether and how environment affects galaxy formation and evolution. Based on deep HST/WFC3 imaging towards the z=2.51 cluster, J1001, we explore environmental effects on the structure, color gradients, and stellar populations of a statistical sample of cluster SFGs. We find that the cluster SFGs are on average smaller than their field counterparts. This difference is most pronounced at the high-mass end ($M_{\star} > 10^{10.5} M_{\odot}$) with nearly all of them lying below the mass-size relation of field galaxies. The high-mass cluster SFGs are also generally old with a steep negative color gradient, indicating an early formation time likely associated with strong dissipative collapse. For low-mass cluster SFGs, we unveil a population of compact galaxies with steep positive color gradients that are not seen in the field. This suggests that the low-mass compact cluster SFGs may have already experienced strong environmental effects, e.g., tidal/ram pressure stripping, in this young cluster. These results provide evidence on the environmental effects at work in the earliest formed clusters with different roles in the formation of low and high-mass galaxies.Comment: 13 pages, 10 figures, 1 tabl

Influence of sulfur oxidation state and substituents on sulfur-bridged luminescent copper(I) complexes showing thermally activated delayed fluorescence

C.M.B. thanks Dr. Maria B. Ezhova for helpful discussions regarding NMR spectra, and Dr. Saeid Kamal for assistance with the TCSPC data. C.M.B. and M.O.W. acknowledge the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Peter Wall Institute for Advanced Studies for financial support and the Laboratory for Advanced Spectroscopy for Imaging Research (LASIR) for facilities access. Z.X. thanks Compute Canada for computing resources for DFT calculations. C.L. thanks the Prof. & Mrs. Purdie Bequests Scholarship and AstraZeneca PhD Studentship. E.Z.-C. and I.D.W.S thank EPSRC (grants EP/R035164/1 and EP/L017008/1) for financial support.Copper(I) complexes are seen as more sustainable alternatives to those containing metal ions such as iridium and platinum for emitting devices. Copper(I) complexes have the ability to radiatively decay via a thermally activated delayed fluorescence (TADF) pathway, leading to higher photoluminescent quantum yields. In this work we discuss six new heteroleptic Cu(I) complexes of the diphosphine–diimine motif. The diphosphine ligands employed are (oxydi- 2,1-phenylene)bis(diphenylphosphine) (DPEPhos) and the diimine fragments are sulfur- bridged dipyridyl ligands (DPS) which are functionalized at the 6,6′-positions of the pyridyl rings (R = H, Me, Ph), and have varying oxidation states at the bridging sulfur atom (S, SO2). The proton ( Cu-DPS, Cu-DPSO2 ) and phenyl ( Cu-Ph-DPS, Cu-Ph-DPSO2 ) substituted species are found to form monometallic complexes, while those with methyl substitution ( Cu-Me-DPS, Cu-Me-DPSO2 ) are found to have a “Goldilocks” degree of steric bulk leading to bimetallic species. All six Cu(I) complexes show emission in the solid state, with the photophysical properties characterized by low temperature steady-state and time-resolved spectroscopies and variable temperature time-correlated single photon counting (TCSPC). Cu- DPS , Cu-DPSO2 , Cu-Me-DPS , Cu-Me-DPSO2 and Cu-Ph-DPSO2 were shown to emit via a TADF mechanism, while Cu-Ph-DPS showed photoluminescence properties consistent with triplet ligand-centered (3LC) emission.PostprintPeer reviewe

High School Dual Enrollment in Florida: Effects on College Outcomes by Race/Ethnicity and Course Modality

This report presents findings on the relationship between taking community college dual enrollment courses—in which high school students earn high school and college credits simultaneously—and college outcomes among Florida public high school students. It analyses dual enrollment course-taking by racial/ethnic group (Black, Hispanic, White) and course modality (face-to-face on-college-campus, face-to-face off-campus, and online). The report includes (1) a descriptive analysis of the demographic characteristics and outcomes of dual enrollment participants and (2) multivariate regression analyses of the associations between dual enrollment participation and college outcomes, controlling for a rich set of student and school characteristics. The analyses use transcript-level unit record data on two cohorts of Florida students who started public high school in 2007 and 2012 and were tracked through high school and into Florida state colleges (community colleges) and universities. The authors find that Florida high school students who took dual enrollment courses were more likely to be White, female, and from more affluent backgrounds than those who did not take dual enrollment courses. They also find that taking dual enrollment courses is associated with better college outcomes for all racial/ethnic groups considered, and that the effects of dual enrollment are mediated by course modality, such that taking courses online is associated with slightly smaller benefits than taking courses face-to-face