scispace - formally typeset
Search or ask a question
Institution

York University

EducationToronto, Ontario, Canada
About: York University is a education organization based out in Toronto, Ontario, Canada. It is known for research contribution in the topics: Population & Politics. The organization has 18899 authors who have published 43357 publications receiving 1568560 citations.


Papers
More filters
Journal ArticleDOI
TL;DR: In this paper, a rolling window analysis is used to construct out-of-sample one-step-ahead forecasts of dynamic conditional correlations and optimal hedge ratios for emerging market stock prices.

350 citations

Journal ArticleDOI
Joseph W. H. Liu1
TL;DR: Experimental results indicate that the modified version of the minimum-degree algorithm retains the fill-reducing property of (and is often better than) the original ordering algorithm and yet requires less computer time.
Abstract: The most widely used ordering scheme to reduce fills and operations in sparse matrix computation is the minimum-degree algorithm. The notion of multiple elimination is introduced here as a modification to the conventional scheme. The motivation is discussed using the k-by-k grid model problem. Experimental results indicate that the modified version retains the fill-reducing property of (and is often better than) the original ordering algorithm and yet requires less computer time. The reduction in ordering time is problem dependent, and for some problems the modified algorithm can run a few times faster than existing implementations of the minimum-degree algorithm. The use of external degree in the algorithm is also introduced.

348 citations

Journal ArticleDOI
Abstract: This article investigates factors that affect rejection rates in applications for outside finance among different types of investors (banks, venture capital funds, leasing firms, factoring firms, trade customers and suppliers, partners and working shareholders, private individuals and other sources), taking into account the non-randomness in a firm’s decision to seek outside finance. The data support the traditional pecking order theory. Further, the data indicate that firms seeking capital are typically able to secure their requisite financing from at least one of the different available sources. However, external finance is often not available in the form that a firm would like. This article engages with four interrelated empirical questions. First, what are the characteristics of privately held entrepreneurial firms that seek external (outside) finance, and what drives the request for capital from the different potential sources of external finance: banks, venture capitalists, private individuals, leasing, factoring, suppliers/customers, partners/working shareholders, among other sources? Second, what are the factors that lead to rejection or acceptance of requests for external finance, given this non-randomness in the types of firms that seek external finance ‐ in the spirit of Heckman (1976; 1979)? Third, as various forms of financing are far from being perfect substitutes, are there differences in the ability of firms to obtain capital from the different available sources? Fourth, can firms obtain all of their desired capital from the different available sources, even if it is not in the form they would like? It is widely recognised that the decision to seek external finance and the type of financing sought is related to information asymmetries faced by investors regarding the entrepreneurial firm’s quality; see for example, Jensen and Meckling (1976). 1 Where

348 citations

Journal ArticleDOI
Richard J. Abbott1, T. D. Abbott2, Sheelu Abraham3, Fausto Acernese4  +1329 moreInstitutions (150)
TL;DR: The GW190521 signal is consistent with a binary black hole (BBH) merger source at redshift 0.13-0.30 Gpc-3 yr-1.8 as discussed by the authors.
Abstract: The gravitational-wave signal GW190521 is consistent with a binary black hole (BBH) merger source at redshift 0.8 with unusually high component masses, 85-14+21 M o˙ and 66-18+17 M o˙, compared to previously reported events, and shows mild evidence for spin-induced orbital precession. The primary falls in the mass gap predicted by (pulsational) pair-instability supernova theory, in the approximate range 65-120 M o˙. The probability that at least one of the black holes in GW190521 is in that range is 99.0%. The final mass of the merger (142-16+28 M o˙) classifies it as an intermediate-mass black hole. Under the assumption of a quasi-circular BBH coalescence, we detail the physical properties of GW190521's source binary and its post-merger remnant, including component masses and spin vectors. Three different waveform models, as well as direct comparison to numerical solutions of general relativity, yield consistent estimates of these properties. Tests of strong-field general relativity targeting the merger-ringdown stages of the coalescence indicate consistency of the observed signal with theoretical predictions. We estimate the merger rate of similar systems to be 0.13-0.11+0.30 Gpc-3 yr-1. We discuss the astrophysical implications of GW190521 for stellar collapse and for the possible formation of black holes in the pair-instability mass gap through various channels: via (multiple) stellar coalescences, or via hierarchical mergers of lower-mass black holes in star clusters or in active galactic nuclei. We find it to be unlikely that GW190521 is a strongly lensed signal of a lower-mass black hole binary merger. We also discuss more exotic possible sources for GW190521, including a highly eccentric black hole binary, or a primordial black hole binary.

347 citations

Journal ArticleDOI
TL;DR: Among patients receiving prescription opioids, concomitant treatment with gabapentin was associated with a substantial increase in the risk of accidental opioid-related mortality, and doctors should consider carefully whether to adjust opioid dose accordingly.
Abstract: Background Prescription opioid use is highly associated with risk of opioid-related death, with 1 of every 550 chronic opioid users dying within approximately 2.5 years of their first opioid prescription. Although gabapentin is widely perceived as safe, drug-induced respiratory depression has been described when gabapentin is used alone or in combination with other medications. Because gabapentin and opioids are both commonly prescribed for pain, the likelihood of co-prescription is high. However, no published studies have examined whether concomitant gabapentin therapy is associated with an increased risk of accidental opioid-related death in patients receiving opioids. The objective of this study was to investigate whether co-prescription of opioids and gabapentin is associated with an increased risk of accidental opioid-related mortality. Methods and findings We conducted a population-based nested case–control study among opioid users who were residents of Ontario, Canada, between August 1, 1997, and December 31, 2013, using administrative databases. Cases, defined as opioid users who died of an opioid-related cause, were matched with up to 4 controls who also used opioids on age, sex, year of index date, history of chronic kidney disease, and a disease risk index. After matching, we included 1,256 cases and 4,619 controls. The primary exposure was concomitant gabapentin use in the 120 days preceding the index date. A secondary analysis characterized gabapentin dose as low (<900 mg daily), moderate (900 to 1,799 mg daily), or high (≥1,800 mg daily). A sensitivity analysis examined the effect of concomitant nonsteroidal anti-inflammatory drug (NSAID) use in the preceding 120 days. Overall, 12.3% of cases (155 of 1,256) and 6.8% of controls (313 of 4,619) were prescribed gabapentin in the prior 120 days. After multivariable adjustment, co-prescription of opioids and gabapentin was associated with a significantly increased odds of opioid-related death (odds ratio [OR] 1.99, 95% CI 1.61 to 2.47, p < 0.001; adjusted OR [aOR] 1.49, 95% CI 1.18 to 1.88, p < 0.001) compared to opioid prescription alone. In the dose–response analysis, moderate-dose (OR 2.05, 95% CI 1.46 to 2.87, p < 0.001; aOR 1.56, 95% CI 1.06 to 2.28, p = 0.024) and high-dose (OR 2.20, 95% CI 1.58 to 3.08, p < 0.001; aOR 1.58, 95% CI 1.09 to 2.27, p = 0.015) gabapentin use was associated with a nearly 60% increase in the odds of opioid-related death relative to no concomitant gabapentin use. As expected, we found no significant association between co-prescription of opioids and NSAIDs and opioid-related death (OR 1.11, 95% CI 0.98 to 1.27, p = 0.113; aOR 1.14, 95% CI 0.98 to 1.32, p = 0.083). In an exploratory analysis of patients at risk of combined opioid and gabapentin use, we found that 46.0% (45,173 of 98,288) of gabapentin users in calendar year 2013 received at least 1 concomitant prescription for an opioid. This study was limited to individuals eligible for public drug coverage in Ontario, we were only able to identify prescriptions reimbursed by the government and dispensed from retail pharmacies, and information on indication for gabapentin use was not available. Furthermore, as with all observational studies, confounding due to unmeasured variables is a potential source of bias. Conclusions In this study we found that among patients receiving prescription opioids, concomitant treatment with gabapentin was associated with a substantial increase in the risk of opioid-related death. Clinicians should consider carefully whether to continue prescribing this combination of products and, when the combination is deemed necessary, should closely monitor their patients and adjust opioid dose accordingly. Future research should investigate whether a similar interaction exists between pregabalin and opioids.

347 citations


Authors

Showing all 19301 results

NameH-indexPapersCitations
Dan R. Littman157426107164
Martin J. Blaser147820104104
Aaron Dominguez1471968113224
Gregory R Snow1471704115677
Joseph E. LeDoux13947891500
Kenneth Bloom1381958110129
Osamu Jinnouchi13588586104
Steven A. Narod13497084638
David H. Barlow13378672730
Elliott Cheu133121991305
Roger Moore132167798402
Wendy Taylor131125289457
Stephen P. Jackson13137276148
Flera Rizatdinova130124289525
Sudhir Malik130166998522
Network Information
Related Institutions (5)
University of Toronto
294.9K papers, 13.5M citations

95% related

University of British Columbia
209.6K papers, 9.2M citations

95% related

McGill University
162.5K papers, 6.9M citations

94% related

Boston University
119.6K papers, 6.2M citations

93% related

University of Colorado Boulder
115.1K papers, 5.3M citations

93% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023180
2022528
20212,676
20202,857
20192,426
20182,137