Recent work on econometric detection mechanisms has shown the e¤ectiveness of recursive procedures in identifying and dating …nancial bubbles. These procedures are useful as warning alerts in surveillance strategies conducted by central banks and …scal regulators with real time data. Use of these methods over long historical periods presents a more serious econometric challenge due to the complexity of the nonlinear structure and break mechanisms that are inherent in multiple bubble phenomena within the same sample period. To meet this challenge the present paper develops a new recursive ‡exible window method that is better suited for practical implementation with long historical time series. The method is a generalized version of the sup ADF test of Phillips, Wu and Yu (2011, PWY) and delivers a consistent date-stamping strategy for the origination and termination of multiple bubbles. Simulations show that the test signi…cantly improves discriminatory power and leads to distinct power gains when multiple bubbles occur. An empirical application of the methodology is conducted on S&P 500 stock market data over a long historical period from January 1871 to December 2010. The new approach successfully identi…es the well-known historical episodes of exuberance and collapse over this period, whereas the strategy of PWY and a related CUSUM dating procedure locate far fewer episodes in the same sample range.

The pathogenesis of diabetic nephropathy remains far from clear, partly due to the lack of a suitable animal model that mimics human renal disease in type 2 diabetes. In this study, the natural history of renal manifestations in ZSF 1 rats, a recently developed rodent model of type 2 diabetes, is described. Male ZSF 1 rats developed obesity and hyperglycemia by 20 weeks of age on a highcarbohydrate diet. They also developed systolic and diastolic hypertension, hypercholesterolemia, profound hypertriglyceridemia, proteinuria, and renal failure. Renal histology demonstrated changes consistent with early diabetic nephropathy, including arteriolar thickening, tubular dilation and atrophy, glomerular basement membrane thickening, and mesangial expansion. Furthermore, renal nitric oxide production was decreased, and homogenates from renal cortices demonstrated reduced expression of renal endothelial and inducible nitric oxide synthases. These changes were associated with increased urinary levels and renal expression of 8-hydroxydeoxyguanosine, an indicator of mitochondrial oxidative stress, as well as with increased renal peroxynitrite formation. Administration of either insulin or the antioxidant alpha-lipoic acid decreased proteinuria and oxidative stress, but only the former slowed progression of renal failure. We conclude that ZSF 1 rats represent the best available rat model to study nephropathy from type 2 diabetes and that the renal lesions are associated with increased oxidative stress and decreased renal nitric oxide availability. 18: 294518: -295218: , 200718: . doi: 10.1681 Despite several recent advances, the pathogenesis of diabetic nephropathy (DN) remains far from clear. 1 The lack of suitable diabetic animal models that develop nephropathy akin to human disease is a major barrier for progress in this field. Notwithstanding the contribution to mechanistic pathways, the in vitro models to study DN have compounded the problem, necessitating more dependable in vivo animal models. Furthermore, the growing epidemic of metabolic syndrome warrants need for animal models that develop hyperlipidemia and obesity in addition to maturity-onset diabetes to mimic complications of human diabetes and metabolic syndrome. We report here a genetically engineered rat that developed features of DN as well as full-blown metabolic syndrome. Furthermore, decreased renal nitric oxide (NO) production was noted in these rats, consistent with our previous observations in mesangial cell cultures in vitro that were exposed to high ambient glucose concentrations. These changes were associated with increased oxidative stress, which partly accounted for decreased NO levels. J Am Soc Nephrol

This paper provides the limit theory of real time dating algorithms for bubble detection that were suggested in Phillips, Wu and Yu (2011, PWY) and Phillips, Shi and Yu (2013b, PSY). Bubbles are modeled using mildly explosive bubble episodes that are embedded within longer periods where the data evolves as a stochastic trend, thereby capturing normal market behavior as well as exuberance and collapse. Both the PWY and PSY estimates rely on recursive right tailed unit root tests (each with a di¤erent recursive algorithm) that may be used in real time to locate the origination and collapse dates of bubbles. Under certain explicit conditions, the moving window detector of PSY is shown to be a consistent dating algorithm even in the presence of multiple bubbles. The other algorithms are consistent detectors for bubbles early in the sample and, under stronger conditions, for subsequent bubbles in some cases. These asymptotic results and accompanying simulations guide the practical implementation of the procedures. They indicate that the PSY moving window detector is more reliable than the PWY strategy, sequential application of the PWY procedure and the CUSUM procedure.

Identifying and dating explosive bubbles when there is periodically collapsing behavior over time has been a major concern in the economics literature and is of great importance for practitioners. The complexity of the nonlinear structure inherent in multiple bubble phenomena within the same sample period makes econometric analysis particularly difficult. The present paper develops new recursive procedures for practical implementation and surveillance strategies that may be employed by central banks and fiscal regulators. We show how the testing procedure and dating algorithm of Phillips, Wu and Yu (2011, PWY) are affected by multiple bubbles and may fail to be consistent. The present paper proposes a generalized version of the sup ADF test of PWY to address this difficulty, derives its asymptotic distribution, introduces a new date-stamping strategy for the origination and termination of multiple bubbles, and proves consistency of this dating procedure. Simulations show that the test significantly improves discriminatory power and leads to distinct power gains when multiple bubbles occur. Empirical applications are conducted to S&P 500 stock market data over a long historical period from January 1871 to December 2010. The new approach identifies many key historical episodes of exuberance and collapse over this period, whereas the strategy of PWY and the CUSUM procedure locate far fewer episodes in the same sample range.

The high-temperature rate of reaction of the homogeneous, reverse water-gas shift reaction (rWGSR)

Recently, Yoo and Zhou [ACS Nano 5, 3020–3026 (2011)] reported that graphene can be directly used as electrode for Li-air batteries, suggesting that graphene itself can be served as catalyst for O2 dissociation reaction. In this work, we show from density functional theory calculations that the O2 dissociation reaction energy barrier is substantially decreased on the graphene surface comparing to that of in vacuum. Furthermore, N-doping can further decrease the energy barrier from 2.39 eV (undoped case) to 1.20 eV. The O2 molecule physical adsorption, O atom chemical adsorption at the graphene, and N-doped graphene surfaces are also simulated.

This paper reexamines changes in the causal link between money and income in the United States for over the past half century (1959-2014). Three methods for the datadriven discovery of change points in causal relationships are proposed, all of which can be implemented without prior detrending of the data. These methods are a forward recursive algorithm, a recursive rolling algorithm and the rolling window algorithm all of which utilize subsample tests of Granger causality within a lag-augmented vector autoregressive framework. The limit distributions for these subsample Wald tests are provided. The results from a suite of simulation experiments suggest that the rolling window algorithm provides the most reliable results, followed by the recursive rolling method. The forward expanding window procedure is shown to have worst performance. All three approaches find evidence of money-income causality during the Volcker period in the 1980s. The rolling and recursive rolling algorithms detect two additional causality episodes: the turbulent period of late 1960s and the starting period of the subprime mortgage crisis in 2007.

Identifying and dating explosive bubbles when there is periodically collapsing behavior over time has been a major concern in the economics literature and is of great importance for practitioners. The complexity of the nonlinear structure inherent in multiple bubble phenomena within the same sample period makes econometric analysis particularly difficult. The present paper develops new recursive procedures for practical implementation and surveillance strategies that may be employed by central banks and fiscal regulators. We show how the testing procedure and dating algorithm of Phillips, Wu and Yu (2011, PWY) are affected by multiple bubbles and may fail to be consistent. The present paper proposes a generalized version of the sup ADF test of PWY to address this difficulty, derives its asymptotic distribution, introduces a new date-stamping strategy for the origination and termination of multiple bubbles, and proves consistency of this dating procedure. Simulations show that the test significantly improves discriminatory power and leads to distinct power gains when multiple bubbles occur. Empirical applications are conducted to S&P 500 stock market data over a long historical period from January 1871 to December 2010. The new approach identifies many key historical episodes of exuberance and collapse over this period, whereas the strategy of PWY and the CUSUM procedure locate far fewer episodes in the same sample range.