Browsing by Author "Zhang, Y"

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    A highly sensitive Raman method for selective cyanide detection based on evaporated cuprous iodide substrate
    (Analytical Methods, 2010-05-01) Gopal Reddy, CV; Yan, F; Zhang, Y; Vo-Dinh, T
    A strong interaction between cyanide anion and copper(i) cation in combination with non-resonant Raman fingerprinting allows the selective sensing of aqueous free cynanide with high sensitivity to parts per billion (ppb)-level. © The Royal Society of Chemistry 2010.
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    Adaptability index: quantifying CT tube current modulation performance from dose and quality informatics
    (2017-03-17) Ria, F; Wilson, JM; Zhang, Y; Samei, E
    The balance between risk and benefit in modern CT scanners is governed by the automatic adaptation mechanisms that adjust x-ray flux for accommodating patient size to achieve certain image noise values. The effectiveness of this adaptation is an important aspect of CT performance and should ideally be characterized in the context of real patient cases. Objective of this study was to characterize CT performance with an index that includes image-noise and radiation dose across a clinical patient population. The study included 1526 examinations performed by three scanners, from two vendors, used for two clinical protocols (abdominopelvic and chest). The dose-patient size and noise-patient size dependencies were linearized, and a 3D-fit was performed for each protocol and each scanner with a planar function. In the fit residual plots the Root Mean Square Error (RMSE) values were estimated as a metric of CT adaptability across the patient population. The RMSE values were between 0.0344 HU1/2 and 0.0215 HU1/2: different scanners offer varying degrees of reproducibility of noise and dose across the population. This analysis could be performed with phantoms, but phantom data would only provide information concerning specific exposure parameters for a scan: instead, a general population comparison is a way to obtain new information related to the relevant clinical adaptability of scanner models. A theoretical relationship between image noise, CTDIvol and patient size was determined based on real patient data. This relationship may provide a new index related to the scanners' adaptability concerning image quality and radiation dose across a patient population. © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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    An Estimation-Based Solution to Weak-Grid-Induced Small-Signal Stability Problems of Power Converters
    (IEEE Journal of Emerging and Selected Topics in Power Electronics, 2020) Fang, J; Yu, J; Zhang, Y; Goetz, SM
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    Association of metabolic syndrome and change in Unified Parkinson Disease Rating Scale scores
    (Neurology, 2017) Leehey, M; Luo, S; Sharma, S; Wills, AM; Bainbridge, JL; Wong, PS; Simon, DK; Schneider, J; Zhang, Y; Perez, A; Dhall, R; Christine, CW; Singer, C; Cambi, F; Boyd, JT
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    Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances and Weak Lensing
    Abbott, TMC; Aguena, M; Alarcon, A; Allam, S; Allen, S; Annis, J; Avila, S; Bacon, D; Bechtol, K; Bermeo, A; Bernstein, GM; Bertin, E; Bhargava, S; Bocquet, S; Brooks, D; Brout, D; Buckley-Geer, E; Burke, DL; Carnero Rosell, A; Carrasco Kind, M; Carretero, J; Castander, FJ; Cawthon, R; Chang, C; Chen, X; Choi, A; Costanzi, M; Crocce, M; da Costa, LN; Davis, TM; De Vicente, J; DeRose, J; Desai, S; Diehl, HT; Dietrich, JP; Dodelson, S; Doel, P; Drlica-Wagner, A; Eckert, K; Eifler, TF; Elvin-Poole, J; Estrada, J; Everett, S; Evrard, AE; Farahi, A; Ferrero, I; Flaugher, B; Fosalba, P; Frieman, J; García-Bellido, J; Gatti, M; Gaztanaga, E; Gerdes, DW; Giannantonio, T; Giles, P; Grandis, S; Gruen, D; Gruendl, RA; Gschwend, J; Gutierrez, G; Hartley, WG; Hinton, SR; Hollowood, DL; Honscheid, K; Hoyle, B; Huterer, D; James, DJ; Jarvis, M; Jeltema, T; Johnson, MWG; Johnson, MD; Kent, S; Krause, E; Kron, R; Kuehn, K; Kuropatkin, N; Lahav, O; Li, TS; Lidman, C; Lima, M; Lin, H; MacCrann, N; Maia, MAG; Mantz, A; Marshall, JL; Martini, P; Mayers, J; Melchior, P; Mena-Fernández, J; Menanteau, F; Miquel, R; Mohr, JJ; Nichol, RC; Nord, B; Ogando, RLC; Palmese, A; Paz-Chinchón, F; Plazas, AA; Prat, J; Rau, MM; Romer, AK; Roodman, A; Rooney, P; Rozo, E; Rykoff, ES; Sako, M; Samuroff, S; Sánchez, C; Sanchez, E; Saro, A; Scarpine, V; Schubnell, M; Scolnic, D; Serrano, S; Sevilla-Noarbe, I; Sheldon, E; Smith, J Allyn; Smith, M; Suchyta, E; Swanson, MEC; Tarle, G; Thomas, D; To, C; Troxel, MA; Tucker, DL; Varga, TN; von der Linden, A; Walker, AR; Wechsler, RH; Weller, J; Wilkinson, RD; Wu, H; Yanny, B; Zhang, Y; Zhang, Z; Zuntz, J; Collaboration, DES
    We perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset. Our analysis uses the same shear and source photometric redshifts estimates as were used in the DES combined probes analysis. Our analysis results in surprisingly low values for $S_8 =\sigma_8(\Omega_{\rm m}/0.3)^{0.5}= 0.65\pm 0.04$, driven by a low matter density parameter, $\Omega_{\rm m}=0.179^{+0.031}_{-0.038}$, with $\sigma_8-\Omega_{\rm m}$ posteriors in $2.4\sigma$ tension with the DES Y1 3x2pt results, and in $5.6\sigma$ with the Planck CMB analysis. These results include the impact of post-unblinding changes to the analysis, which did not improve the level of consistency with other data sets compared to the results obtained at the unblinding. The fact that multiple cosmological probes (supernovae, baryon acoustic oscillations, cosmic shear, galaxy clustering and CMB anisotropies), and other galaxy cluster analyses all favor significantly higher matter densities suggests the presence of systematic errors in the data or an incomplete modeling of the relevant physics. Cross checks with X-ray and microwave data, as well as independent constraints on the observable--mass relation from SZ selected clusters, suggest that the discrepancy resides in our modeling of the weak lensing signal rather than the cluster abundance. Repeating our analysis using a higher richness threshold ($\lambda \ge 30$) significantly reduces the tension with other probes, and points to one or more richness-dependent effects not captured by our model.
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    Dark Energy Survey Year 3 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing
    (arXiv e-prints, 2021-05) Collaboration, DES; Abbott, TMC; Aguena, M; Alarcon, A; Allam, S; Alves, O; Amon, A; Andrade-Oliveira, F; Annis, J; Avila, S; Bacon, D; Baxter, E; Bechtol, K; Becker, MR; Bernstein, GM; Bhargava, S; Birrer, S; Blazek, J; Brandao-Souza, A; Bridle, SL; Brooks, D; Buckley-Geer, E; Burke, DL; Camacho, H; Campos, A; Carnero Rosell, A; Carrasco Kind, M; Carretero, J; Castander, FJ; Cawthon, R; Chang, C; Chen, A; Chen, R; Choi, A; Conselice, C; Cordero, J; Costanzi, M; Crocce, M; da Costa, LN; da Silva Pereira, ME; Davis, C; Davis, TM; De Vicente, J; DeRose, J; Desai, S; Di Valentino, E; Diehl, HT; Dietrich, JP; Dodelson, S; Doel, P; Doux, C; Drlica-Wagner, A; Eckert, K; Eifler, TF; Elsner, F; Elvin-Poole, J; Everett, S; Evrard, AE; Fang, X; Farahi, A; Fernandez, E; Ferrero, I; Ferté, A; Fosalba, P; Friedrich, O; Frieman, J; García-Bellido, J; Gatti, M; Gaztanaga, E; Gerdes, DW; Giannantonio, T; Giannini, G; Gruen, D; Gruendl, RA; Gschwend, J; Gutierrez, G; Harrison, I; Hartley, WG; Herner, K; Hinton, SR; Hollowood, DL; Honscheid, K; Hoyle, B; Huff, EM; Huterer, D; Jain, B; James, DJ; Jarvis, M; Jeffrey, N; Jeltema, T; Kovacs, A; Krause, E; Kron, R; Kuehn, K; Kuropatkin, N; Lahav, O; Leget, P-F; Lemos, P; Liddle, AR; Lidman, C; Lima, M; Lin, H; MacCrann, N; Maia, MAG; Marshall, JL; Martini, P; McCullough, J; Melchior, P; Mena-Fernández, J; Menanteau, F; Miquel, R; Mohr, JJ; Morgan, R; Muir, J; Myles, J; Nadathur, S; Navarro-Alsina, A; Nichol, RC; Ogando, RLC; Omori, Y; Palmese, A; Pandey, S; Park, Y; Paz-Chinchón, F; Petravick, D; Pieres, A; Plazas Malagón, AA; Porredon, A; Prat, J; Raveri, M; Rodriguez-Monroy, M; Rollins, RP; Romer, AK; Roodman, A; Rosenfeld, R; Ross, AJ; Rykoff, ES; Samuroff, S; Sánchez, C; Sanchez, E; Sanchez, J; Sanchez Cid, D; Scarpine, V; Schubnell, M; Scolnic, D; Secco, LF; Serrano, S; Sevilla-Noarbe, I; Sheldon, E; Shin, T; Smith, M; Soares-Santos, M; Suchyta, E; Swanson, MEC; Tabbutt, M; Tarle, G; Thomas, D; To, C; Troja, A; Troxel, MA; Tucker, DL; Tutusaus, I; Varga, TN; Walker, AR; Weaverdyck, N; Weller, J; Yanny, B; Yin, B; Zhang, Y; Zuntz, J
    We present the first cosmology results from large-scale structure in the Dark Energy Survey (DES) spanning 5000 deg$^2$. We perform an analysis combining three two-point correlation functions (3$\times$2pt): (i) cosmic shear using 100 million source galaxies, (ii) galaxy clustering, and (iii) the cross-correlation of source galaxy shear with lens galaxy positions. The analysis was designed to mitigate confirmation or observer bias; we describe specific changes made to the lens galaxy sample following unblinding of the results. We model the data within the flat $\Lambda$CDM and $w$CDM cosmological models. We find consistent cosmological results between the three two-point correlation functions; their combination yields clustering amplitude $S_8=0.776^{+0.017}_{-0.017}$ and matter density $\Omega_{\mathrm{m}} = 0.339^{+0.032}_{-0.031}$ in $\Lambda$CDM, mean with 68% confidence limits; $S_8=0.775^{+0.026}_{-0.024}$, $\Omega_{\mathrm{m}} = 0.352^{+0.035}_{-0.041}$, and dark energy equation-of-state parameter $w=-0.98^{+0.32}_{-0.20}$ in $w$CDM. This combination of DES data is consistent with the prediction of the model favored by the Planck 2018 cosmic microwave background (CMB) primary anisotropy data, which is quantified with a probability-to-exceed $p=0.13$ to $0.48$. When combining DES 3$\times$2pt data with available baryon acoustic oscillation, redshift-space distortion, and type Ia supernovae data, we find $p=0.34$. Combining all of these data sets with Planck CMB lensing yields joint parameter constraints of $S_8 = 0.812^{+0.008}_{-0.008}$, $\Omega_{\mathrm{m}} = 0.306^{+0.004}_{-0.005}$, $h=0.680^{+0.004}_{-0.003}$, and $\sum m_{\nu}<0.13 \;\mathrm{eV\; (95\% \;CL)}$ in $\Lambda$CDM; $S_8 = 0.812^{+0.008}_{-0.008}$, $\Omega_{\mathrm{m}} = 0.302^{+0.006}_{-0.006}$, $h=0.687^{+0.006}_{-0.007}$, and $w=-1.031^{+0.030}_{-0.027}$ in $w$CDM. (abridged)
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    Extremal Quantile Regressions for Selection Models and the Black-White Wage Gap
    (Economic Research Initiatives at Duke (ERID), 2014-06-01) D'Haultfœuille, X; Maurel, AP; Zhang, Y
    We consider the estimation of a semiparametric location-scale model subject to endogenous selection, in the absence of an instrument or a large support regressor. Identification relies on the independence between the covariates and selection, for arbitrarily large values of the outcome. In this context, we propose a simple estimator, which combines extremal quantile regressions with minimum distance. We establish the asymptotic normality of this estimator by extending previous results on extremal quantile regressions to allow for selection. Finally, we apply our method to estimate the black-white wage gap among males from the NLSY79 and NLSY97. We find that premarket factors such as AFQT and family background characteristics play a key role in explaining the level and evolution of the black-white wage gap.
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    Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning
    (Proceedings of the ACM on Measurement and Analysis of Computing Systems, 2023-02-28) Zhang, Y; Qu, G; Xu, P; Lin, Y; Chen, Z; Wierman, A
    We study a multi-agent reinforcement learning (MARL) problem where the agents interact over a given network. The goal of the agents is to cooperatively maximize the average of their entropy-regularized long-term rewards. To overcome the curse of dimensionality and to reduce communication, we propose a Localized Policy Iteration (LPI) algorithm that provably learns a near-globally-optimal policy using only local information. In particular, we show that, despite restricting each agent's attention to only its κ-hop neighborhood, the agents are able to learn a policy with an optimality gap that decays polynomially in κ. In addition, we show the finite-sample convergence of LPI to the global optimal policy, which explicitly captures the trade-off between optimality and computational complexity in choosing κ. Numerical simulations demonstrate the effectiveness of LPI.
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    Learning a hybrid architecture for sequence regression and annotation
    (30th AAAI Conference on Artificial Intelligence, AAAI 2016, 2016-01-01) Zhang, Y; Henao, R; Carin, L; Zhong, J; Hartemink, AJ
    © Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.When learning a hidden Markov model (HMM), sequential observations can often be complemented by real-valued summary response variables generated from the path of hidden states. Such settings arise in numerous domains, including many applications in biology, like motif discovery and genome annotation. In this paper, we present a flexible framework for jointly modeling both latent sequence features and the functional mapping that relates the summary response variables to the hidden state sequence. The algorithm is compatible with a rich set of mapping functions. Results show that the availability of additional continuous response variables can simultaneously improve the annotation of the sequential observations and yield good prediction performance in both synthetic data and real-world datasets.
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    MALT1 promotes melanoma progression through JNK/c-Jun signaling
    (Oncogensis, 2017-08-02) Zhang, Y
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    Optical follow-up of gravitational wave triggers with DECam during the first two LIGO/VIRGO observing runs
    Herner, K; Annis, J; Brout, D; Soares-Santos, M; Kessler, R; Sako, M; Butler, R; Doctor, Z; Palmese, A; Allam, S; Tucker, DL; Sobreira, F; Yanny, B; Diehl, HT; Frieman, J; Glaeser, N; Garcia, A; Sherman, NF; Bechtol, K; Berger, E; Chen, HY; Conselice, CJ; Cook, E; Cowperthwaite, PS; Davis, TM; Drlica-Wagner, A; Farr, B; Finley, D; Foley, RJ; Garcia-Bellido, J; Gill, MSS; Gruendl, RA; Holz, DE; Kuropatkin, N; Lin, H; Marriner, J; Marshall, JL; Matheson, T; Neilsen, E; Paz-Chinchón, F; Sauseda, M; Scolnic, D; Williams, PKG; Avila, S; Bertin, E; Buckley-Geer, E; Burke, DL; Rosell, AC; Carrasco-Kind, M; Carretero, J; da Costa, LN; De Vicente, J; Desai, S; Doel, P; Eifler, TF; Everett, S; Fosalba, P; Gaztanaga, E; Gerdes, DW; Gschwend, J; Gutierrez, G; Hartley, WG; Hollowood, DL; Honscheid, K; James, DJ; Krause, E; Kuehn, K; Lahav, O; Li, TS; Lima, M; Maia, MAG; March, M; Menanteau, F; Miquel, R; Plazas, AA; Sanchez, E; Scarpine, V; Schubnell, M; Serrano, S; Sevilla-Noarbe, I; Smith, M; Suchyta, E; Tarle, G; Wester, W; Zhang, Y
    Gravitational wave (GW) events detectable by LIGO and Virgo have several possible progenitors, including black hole mergers, neutron star mergers, black hole--neutron star mergers, supernovae, and cosmic string cusps. A subset of GW events are expected to produce electromagnetic (EM) emission that, once detected, will provide complementary information about their astrophysical context. To that end, the LIGO--Virgo Collaboration (LVC) sends GW candidate alerts to the astronomical community so that searches for their EM counterparts can be pursued. The DESGW group, consisting of members of the Dark Energy Survey (DES), the LVC, and other members of the astronomical community, uses the Dark Energy Camera (DECam) to perform a search and discovery program for optical signatures of LVC GW events. DESGW aims to use a sample of GW events as standard sirens for cosmology. Due to the short decay timescale of the expected EM counterparts and the need to quickly eliminate survey areas with no counterpart candidates, it is critical to complete the initial analysis of each night's images as quickly as possible. We discuss our search area determination, imaging pipeline, and candidate selection processes. We review results from the DESGW program during the first two LIGO--Virgo observing campaigns and introduce other science applications that our pipeline enables.
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    Partially monotone tensor spline estimation of the joint distribution function with bivariate current status data
    (Annals of Statistics, 2012-06-01) Wu, Y; Zhang, Y
    The analysis of the joint cumulative distribution function (CDF) with bivariate event time data is a challenging problem both theoretically and numerically. This paper develops a tensor spline-based sieve maximum likelihood estimation method to estimate the joint CDF with bivariate current status data. The I -splines are used to approximate the joint CDF in order to simplify the numerical computation of a constrained maximum likelihood estimation problem. The generalized gradient projection algorithm is used to compute the constrained optimization problem. Based on the properties of B-spline basis functions it is shown that the proposed tensor spline-based nonparametric sieve maximum likelihood estimator is consistent with a rate of convergence potentially better than n1/3 under some mild regularity conditions. The simulation studies with moderate sample sizes are carried out to demonstrate that the finite sample performance of the proposed estimator is generally satisfactory. © Institute of Mathematical Statistics, 2012.
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    Proceeding of SPIE Medical Imaging
    (2017-03-17) Ria, Francesco; Samei, Ehsan; Wilson, JM; Zhang, Y
    The balance between risk and benefit in modern CT scanners is governed by the automatic adaptation mechanisms that adjust x-ray flux for accommodating patient size to achieve certain image noise values. The effectiveness of this adaptation is an important aspect of CT performance and should ideally be characterized in the context of real patient cases. Objective of this study was to characterize CT performance with an index that includes image-noise and radiation dose across a clinical patient population. The study included 1526 examinations performed by three scanners, from two vendors, used for two clinical protocols (abdominopelvic and chest). The dose-patient size and noise-patient size dependencies were linearized, and a 3D-fit was performed for each protocol and each scanner with a planar function. In the fit residual plots the Root Mean Square Error (RMSE) values were estimated as a metric of CT adaptability across the patient population. The RMSE values were between 0.0344 HU1/2 and 0.0215 HU1/2: different scanners offer varying degrees of reproducibility of noise and dose across the population. This analysis could be performed with phantoms, but phantom data would only provide information concerning specific exposure parameters for a scan: instead, a general population comparison is a way to obtain new information related to the relevant clinical adaptability of scanner models. A theoretical relationship between image noise, CTDIvol and patient size was determined based on real patient data. This relationship may provide a new index related to the scanners' adaptability concerning image quality and radiation dose across a patient population. © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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    The environmental effect of trade liberalization: Evidence from China's manufacturing firms
    (World Economy, 2020-01-01) Cui, J; Tam, OK; Wang, B; Zhang, Y
    © 2020 John Wiley & Sons Ltd While prior literature on trade liberalisation and the environment has mostly focused on the macroeconomic ramifications, this study explores at the firm level whether and how changes of trade barriers brought about by China's accession to the WTO may impact on its manufacturing firms’ environmental performance. Adopting a difference-in-differences (DID) methodology, we document the effects of tariff reductions on improving firm-level SO2 emission intensity, and the key corporate strategic decisions responsible for delivering the observed results, with robustness tests covering other major pollutants. In response to trade liberalisation, firms are found to increase labour resources for environmental protection and to improve their production processes to reduce emission intensity. This study contributes to the literature by investigating at the level of the operating firm how output and input tariff reductions may impact on environmental performance and uncovering for the first time the specific actions responsible for the results.