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Готові списки джерел за темами / Structural breaks

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Добірка наукової літератури з теми "Structural breaks"

Автор: Grafiati

Опубліковано: 4 червня 2021

Оновлено: 25 травня 2024

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Статті в журналах з теми "Structural breaks"

1

Czech, Katarzyna. "Structural Changes in Wheat Market." Zeszyty Naukowe SGGW w Warszawie - Problemy Rolnictwa Światowego 16, no. 4 (December 31, 2016): 92–98. http://dx.doi.org/10.22630/prs.2016.16.4.102.

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Time series analysis is based on the assumption of stationarity. Stationarity implies the parameters are constant over time. Structural break occurs when at least one of the parameters changes at some date. Structural breaks can lead to huge forecasting errors and unreliability of the model. Modelling structure breaks is very popular in the literature of macroeconomics and finance. However, there are still too few publications about structural breaks in agricultural market. The goal of research is to identify structural breaks in wheat prices time series. A few structural break tests are applied. It has been shown that there is at least one significant structural break in the analysed time series. Both Quandt-Andrews and Bai-Perron tests show that there is a significant breakpoint in 12.09.2007. The estimated break date is associated with the beginning of global financial crisis. It may imply that wheat prices have become more prone to changes in global financial market.

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2

Ngene, Geoffrey, Ann Nduati Mungai, and Allen K. Lynch. "Long-Term Dependency Structure and Structural Breaks: Evidence from the U.S. Sector Returns and Volatility." Review of Pacific Basin Financial Markets and Policies 21, no. 02 (May 27, 2018): 1850008. http://dx.doi.org/10.1142/s021909151850008x.

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The study investigates the impact of structural breaks on the long memory of daily returns and variance of 11 sectors. Using multiple sequential structural breaks tests, we uncover numerous and roughly shared structural breaks. Results from two non-parametric, three semi-parametric, and three parametric fractional differencing models using break-adjusted and break-unadjusted returns reveal incidence of short memory and anti-persistence in sector returns. Regarding variance, we find that the removal of breaks from the sector series dampens the fractional differencing parameter estimates. Therefore, the observed long memory in variance may be attributable to the occurrence of structural breaks in the sector series.

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3

Groothuis, Peter A., Kurt W. Rotthoff, and Mark C. Strazicich. "Structural Breaks in the Game." Journal of Sports Economics 18, no. 6 (July 6, 2015): 622–37. http://dx.doi.org/10.1177/1527002515593113.

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To search for eras in a sports league, we utilize time-series tests with structural breaks in Major League Baseball performance. Using data from 1871-2010, the mean and standard deviation of four different performance measures are examined. Throughout, rather than assume that a break point is known a priori, we identify breaks endogenously from the data. Perhaps most notable among our findings, we identify a deterministic trend in mean slugging percentage with breaks in 1921 and 1992. Interestingly, these years closely coincide with the early years of the free-swinging (Babe Ruth) era and the modern steroid era, respectively.

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4

Galadima, Mukhtar Danladi, and Abubakar Wambai Aminu. "STRUCTURAL BREAKS IN NATURAL GAS CONSUMPTION AND ECONOMIC GROWTH IN NIGERIA: EVIDENCE FROM NEW TIME SERIES TESTS THAT ALLOW FOR STRUCTURAL BREAKS." International Journal of New Economics and Social Sciences 9, no. 1 (June 28, 2019): 275–92. http://dx.doi.org/10.5604/01.3001.0013.3049.

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This paper analyzed the issue of structural breaks in natural gas consumption and economic growth in Nigeria. The newly residual augmented least squares (RALS-LM) unit root test with breaks also known as “RALS-LM test with trend breaks and non-normal errors” proposed by Meng-Lee-Payne (2017) and the new structural breaks testing proposed by Kejriwal–Perron (2010) are among the tools used for the investi-gation. Our empirical findings provide significant evidence that the series of natural gas consumption and economic growth are stationary with one or two trend breaks. Furthermore, the investigation identified significant incidences of structural breaks in the relationship between natural gas consumption and economic growth in 1990, 2004, 2009 and all the break dates were found to be significant. The evaluation of the sub-sample periods based on the break dates revealed that the first and second breaks are potential while the last is destructive. Moreover, the estimate of the long-run elasticity is significant where a 1% increase in natural gas consumption induces the growth of Nigerian economy by 0.15% and all the dummies that represent the breakpoints are also significant where the 2004 break had a bigger effect among other breaks. The implication of the results is that shocks in the series of natural gas consumption and economic growth in Nigeria have transitory effect, modeling the relationship between natural gas consumption and economic growth in Nigeria without taking structural breaks into consideration could produce biased and unreliable statistical results, and there is economically significant dependence of the Nigerian economy on natural gas consumption.

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5

Raifu, Isiaka Akande. "Is Tourism-Led-Growth Hypothesis Valid in the Presence of Structural Breaks?" Tourism 72, no. 2 (April 3, 2024): 270–74. http://dx.doi.org/10.37741/t.72.2.11.

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This study revisited the tourism-led growth hypothesis (TLGH) in the presence of structural breaks using the structural break technique of Ditzen et al. (2021). To estimate the impact of tourism on economic growth along the identified structural breaks, we employed Fixed Effects and Feasible Generalised Least Squares methods. Findings showed four structural break dates (1999, 2004, 2009 and 2014), two of which coincided with the Global Financial Crisis (2008-2009) and the Ebola outbreak (2014). Despite the presence of structural breaks, the TLGH remains valid.

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6

Smith, Simon C., George Bulkley, and David S. Leslie. "Equity Premium Forecasts with an Unknown Number of Structural Breaks." Journal of Financial Econometrics 18, no. 1 (January 12, 2019): 59–94. http://dx.doi.org/10.1093/jjfinec/nby034.

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Abstract Estimation of models with structural breaks usually assumes a pre-specified number of breaks. Previous models which do allow an endogenously determined number of breaks require a simple structural model, and rarely allow for information transfer across the break. We introduce a methodology that allows the number of breaks to be determined endogenously and including an economically motivated model of transition regimes between each break. We demonstrate the usefulness of our approach for forecasts of the equity premium. We find the demonstrated success of the historical average can be improved upon by an economic model with theory informed priors estimated using our methodology.

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7

Huang, Yirong, Liang Ding, Yan Lin, and Yi Luo. "A new approach to detect long memory by fractional integration or short memory by structural break." AIMS Mathematics 9, no. 6 (2024): 16468–85. http://dx.doi.org/10.3934/math.2024798.

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<abstract> <p>Long memory in test statistics can either originate from fractional integration or be spuriously induced by a short memory process with a structural break. This research estimated and detected long memory from the two causes by simulations and empirical analysis. The simulation results showed that fractional integration and structural break processes could demonstrate long memory properties. The 2ELW estimator was stable for fractional integration but not stable for time series with structural breaks. The modified W statistic based on 2ELW was efficient in discriminating fractional integration and structural breaks. Moreover, we found that six volatility time series of stock indexes and individual stocks in the Chinese market experience significant long memory and structural breaks, and the fractional differencing parameter is overestimated without controlling structural breaks.</p> </abstract>

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8

Tsuji, Chikashi. "Structural Breaks and Volatility Spillovers: The Case of the US and Canadian Stock Markets." Journal of Management Research 11, no. 2 (April 3, 2019): 30. http://dx.doi.org/10.5296/jmr.v11i2.14513.

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This paper investigates the relations of structural breaks and volatility spillovers by using the US and Canadian stock return data. Specifically, applying spillover MGARCH models without and with structural break dummy variables to the two stock returns, this study derives the following interesting evidence. (1) First, we reveal that for both the US and Canadian stock returns, the volatility persistence parameter values in our spillover MGARCH models decline when structural break dummy variables are incorporated. (2) Second, we further clarify that when we do not take structural breaks into account, the spillover effect was unidirectional from Canada to the US. However, when we take structural breaks into consideration, the results from our spillover MGARCH model with structural break dummies demonstrate that the volatility spillover effects between the US and Canada become bidirectional. (3) Third, we furthermore reveal that around the Lehman Brothers bankruptcy in 2008, the time-varying volatilities derived from our spillover MGARCH model with structural break dummy variables show slightly higher values than those volatilities from our spillover MGARCH model with no structural break dummy variable.

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9

Skrobotov, Anton. "Structural breaks in cointegration models: Multivariate case." Applied Econometrics 64, no. 4 (2021): 83–106. http://dx.doi.org/10.22394/1993-7601-2021-64-83-106.

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This review discusses methods of testing for a cointegration rank in a multivariate time series in the presence of structural breaks. The review covers both the methods with known and unknown break date. Multiple breaks are also considered. The issues of testing for cointegration with a possible change in the cointegration rank over time are discussed separately.

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10

Jiang, Zhuhua, Walid Mensi, and Seong-Min Yoon. "Risks in Major Cryptocurrency Markets: Modeling the Dual Long Memory Property and Structural Breaks." Sustainability 15, no. 3 (January 24, 2023): 2193. http://dx.doi.org/10.3390/su15032193.

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This study estimates the effects of the dual long memory property and structural breaks on the persistence level of six major cryptocurrency markets. We apply the Bai and Perron structural break test, Inclán and Tiao’s iterated cumulative sum of squares (ICSS) algorithm, and the fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH) model, with different distributions. The results show that long memory and structural breaks characterize the conditional volatility of cryptocurrency markets, confirming our hypothesis that ignoring structural breaks leads to an underestimation of the persistence of volatility modeling. The ARFIMA-FIGARCH model, with structural breaks and a skewed Student–t distribution, fits the cryptocurrency market’s price dynamics well.

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Дисертації з теми "Structural breaks"

1

Karlsson, Olov. "Volatility forecasting under structural breaks." Thesis, Uppsala universitet, Statistiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-302398.

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2

Sobreira, Nuno. "Three essays on structural breaks." Doctoral thesis, NSBE - UNL, 2012. http://hdl.handle.net/10362/11853.

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3

Zhang, Dayong. "Structural breaks in empirical modelling of stock markets." Thesis, University of Birmingham, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433631.

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4

Nazare, Ronaldo. "Essays in applied factor analysis with structural breaks." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/360375/.

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5

Malki, Issam. "A structural breaks approach to modelling United States inflation." Thesis, University of Dundee, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.505641.

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6

Banerjee, Abhisek. "Essays on semiparametric estimation of models with structural breaks." Thesis, London School of Economics and Political Science (University of London), 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.538732.

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7

Kartsaklas, Aris. "Long memory, structural breaks and the volatility-volume relationship." Thesis, University of York, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.495883.

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8

Lazarova, Stepana. "Long memory and structural breaks in time series models." Thesis, London School of Economics and Political Science (University of London), 2006. http://etheses.lse.ac.uk/1927/.

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This thesis examines structural breaks in time series regressions where both regressors and errors may exhibit long range dependence. Statistical properties of methods for detecting and estimating structural breaks are analysed and asymptotic distribution of estimators and test statistics are obtained. Valid bootstrap methods of approximating the limiting distribution of the relevant statistics are also developed to improve on the asymptotic approximation in finite samples or to deal with the problem of unknown asymptotic distribution. The performance of the asymptotic and bootstrap methods are compared through Monte Carlo experiments. A background of the concepts of structural breaks, long memory and bootstrap is offered in Introduction where the main contribution of the thesis is also outlined. Chapter 1 proposes a fluctuation-type test procedure for detecting instability of slope coefficients. A first-order bootstrap approximation of the distribution of the test statistic is proposed. Chapter 2 considers estimation and testing of the time of the structural break. Statistical properties of the estimator are examined under a range of assumptions on the size of the break. Under the assumption of shrinking break, a bootstrap approximation of the asymptotic test procedure is proposed. Chapter 3 addresses a drawback of the assumption of fixed size of break. Under this assumption, the asymptotic distribution of the estimator of the breakpoint depends on the unknown underlying distribution of data and thus it is not available for inference purposes. The proposed solution is a bootstrap procedure based on a specific type of deconvolution.

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9

Mendonça, Francisco António Teixeira. "Double unit tests in the presence of structural breaks." Master's thesis, Instituto Superior de Economia e Gestão, 2017. http://hdl.handle.net/10400.5/14894.

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Mestrado em Econometria Aplicada e Previsão
Apresentam-se dois testes estatísticos que permitem averiguar a existência de duas raízes unitárias numa série temporal univariada que contenha um quebra estrutural na função determinística. Os testes foram aplicados a várias séries económicas, e encontrou-se evidência estatística que suporta a hipótese nula.
We present two statistical tests that to verify the existence of two unit roots in a univariate time series that contains a structural break in the deterministic function. The tests were applied to several economic series, and statistical evidence supporting the null hypothesis was found.
info:eu-repo/semantics/publishedVersion

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10

Wang, Bruce Chang-Ming. "Structural breaks and regime switching models : theoretical extensions and applications /." Thesis, Connect to this title online; UW restricted, 2007. http://hdl.handle.net/1773/7476.

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Книги з теми "Structural breaks"

1

Smith, Jeremy. Structural breaks and seasonal integration. Coventry: University of Warwick, Dept. of Economics, 1995.

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2

Smith, Jeremy. Structural breaks and seasonal integration. Coventry: University of Warwick Department of Economics, 1995.

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3

Pástor, Lubos̆. The equity premium and structural breaks. Cambridge, MA: National Bureau of Economic Research, 2000.

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4

Gregory, Allan W. Testing for structural breaks in cointegrated relationships. Kingston, Ont: Institute for Economic Research, Queen's University, 1991.

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5

Timmermann, Allan. Structural breaks, incomplete information and stock prices. London: London School of Economics, Financial Markets Group, 1998.

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6

Hashem, Pesaran M. Forecasting time series subject to multiple structural breaks. Bonn, Germany: IZA, 2004.

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7

León, Javier. Structural breaks and long-run trends in commodity prices. Washington, DC: World Bank, 1995.

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8

Busetti, Fabio. Testing for stochastic trends in series with structural breaks. Roma: Banca d'Italia, 2000.

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9

1964-, Piehl Anne Morrison, and National Bureau of Economic Research., eds. Testing for structural breaks in the evaluation of programs. Cambridge, MA: National Bureau of Economic Research, 1999.

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10

Clark, Todd E. Forecast-based model selection in the presence of structural breaks. Kansas City [Mo.]: Research Division, Federal Reserve Bank of Kansas City, 2002.

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Частини книг з теми "Structural breaks"

1

Levendis, John D. "Structural Breaks." In Springer Texts in Business and Economics, 171–96. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98282-3_8.

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2

Levendis, John D. "Structural Breaks." In Springer Texts in Business and Economics, 175–99. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-37310-7_8.

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3

Hall, Stephen G., and Martin Sola. "Structural Breaks and Garch Modelling." In Advances in Computational Economics, 217–27. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-015-8743-3_11.

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4

Ghosh, Madhusudan. "Structural Breaks and Performance in Agriculture." In Liberalization, Growth and Regional Disparities in India, 83–107. India: Springer India, 2012. http://dx.doi.org/10.1007/978-81-322-0981-2_6.

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5

Andreou, Elena, and Eric Ghysels. "Structural Breaks in Financial Time Series." In Handbook of Financial Time Series, 839–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-71297-8_37.

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6

Karavias, Yiannis. "Structural Breaks in Financial Panel Data." In Encyclopedia of Finance, 2213–28. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-91231-4_95.

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7

Karavias, Yiannis. "Structural Breaks in Financial Panel Data." In Encyclopedia of Finance, 1–17. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73443-5_95-1.

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8

Mills, Terence C. "Trends, Cycles, and Structural Breaks in Cliometrics." In Handbook of Cliometrics, 509–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-40406-1_21.

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Mills, Terence C. "Trends, Cycles, and Structural Breaks in Cliometrics." In Handbook of Cliometrics, 1–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-40458-0_21-1.

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10

Mills, Terence C. "Trends, Cycles, and Structural Breaks in Cliometrics." In Handbook of Cliometrics, 1557–82. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-00181-0_21.

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Тези доповідей конференцій з теми "Structural breaks"

1

LANGE, ALEXANDER, MAX KÄDING, ROGHUA XU, STEFFEN MARX, and JÖRN OSTERMANN. "SEMI-SUPERVISED LEARNING FOR ACOUSTIC VISION MONITORING OF TENDONS IN PRE-STRESSED CONCRETE BRIDGES." In Structural Health Monitoring 2023. Destech Publications, Inc., 2023. http://dx.doi.org/10.12783/shm2023/36855.

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Aging bridge infrastructure appears to become a major challenge in many industrialized countries. Numerous bridges are in bad condition and the current pace of repair and replacement as well as the available financial resources hence demand for a reliable bridge monitoring to facilitate an extended operation period of existing bridges. Nowadays, prestressed concrete bridges are prevalent among other construction types but may suffer from stress corrosion cracking of steel tendons. To detect wire breaks in bridge tendons, recent research suggests the use of acoustic emission analysis. In this work, we propose the use of semi-supervised learning techniques for anomaly detection to detect wire breaks in tendons of prestressed concrete bridges. Particularly, we utilize only acoustic emissions due to traffic and other environmental influences, recorded on a real bridge in operation, to initialize the local outlier factor algorithm. We then apply the initialized local outlier factor algorithm to two separate datasets with more than 500 wire break signals recorded on two different types of bridge girders. It is shown that the anomaly-based approach outperforms a supervised k-nearest neighbors classifier trained using wire breaks from only one girder. An evaluation on the wire break signals from the second bridge girder, not seen during the training phase, shows an improvement of the average recall score from 38 % to more than 99 % for the anomaly-based approach compared to the supervised k-nearest neighbors classifier. Considering the diversity of bridge constructions and the fact that availability of acoustic emission signals due to wire breaks is limited, semi-supervised learning seems to be a suitable approach for wire break detection. Furthermore, acoustic emissions due to normal environmental and operational conditions could be easily and cost-effectively recorded during an initialization phase of any monitoring system and thus be utilized to initialize an anomaly detector for each specific infrastructure.

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2

Molnar, Peter, and Sven Thies. "Structural breaks in emission allowance prices." In 2017 14th International Conference on the European Energy Market (EEM). IEEE, 2017. http://dx.doi.org/10.1109/eem.2017.7981981.

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3

RIJAL, MANOJ, TRAVIS OBIE-ROLLE, and MANNUR SUNDARESAN. "MONITORING DAMAGE EVOLUTION IN CARBON/ EPOXY AND CARBON/THERMOPLASTIC COMPOSITES USING ACOUSTIC EMISSION TECHNIQUE." In Structural Health Monitoring 2023. Destech Publications, Inc., 2023. http://dx.doi.org/10.12783/shm2023/36851.

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Detecting, monitoring, and quantifying the growth of damage in structural components in real time is important for assuring safety of aerospace structures. Acoustic emission (AE) technique is one of the tools that can facilitate such monitoring and quantification of damage growth and provide meaningful insight into damage evolution. Damage growth in composite materials has long been studied under laboratory setting and documented in the literature, but there is a need to track such failure modes in real structures under operational conditions. In this study the progression of damage in pristine carbon/epoxy composites under static loading were examined. Bonded wide band sensors capable of detecting frequency components up to 2 MHz were used to differentiate signals from the three primary AE sources, namely, matrix cracks, delaminations, and fiber breaks. Traditional acoustic emission parameters as well as the waveform characteristics were used to classify the acoustic emission signals related to the three failure modes. Individual clusters of fiber breaks, progressive growth of individual matrix cracks as well as delamination growths were also traced using these techniques. The correspondence between the failure mode and the respective waveforms characteristics were validated to a limited extent using both experimental techniques as well as numerical simulations. Based on these classifications, the rate of growth of individual failure modes was also quantified using their respective cumulative energy. The appearance of greater number of AE clusters related to fiber breaks and the increase in their sizes along with cumulative energy are found to be a clear indication of impending failure.

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4

Li Song and Pascal Bondon. "Structural breaks estimation for long memory signals." In 2009 IEEE/SP 15th Workshop on Statistical Signal Processing (SSP). IEEE, 2009. http://dx.doi.org/10.1109/ssp.2009.5278596.

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5

Miglani, Jitish, Chirag Sachdeva, and Srikant S. Padhee. "Automation of Composite Failure Analysis for Fiber Breaks." In 58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2017. http://dx.doi.org/10.2514/6.2017-0429.

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6

O'Hare, C., and Y. Li. "Structural Breaks in Mortality Models and their Consequences." In Second International Conference on Vulnerability and Risk Analysis and Management (ICVRAM) and the Sixth International Symposium on Uncertainty, Modeling, and Analysis (ISUMA). Reston, VA: American Society of Civil Engineers, 2014. http://dx.doi.org/10.1061/9780784413609.120.

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7

"Testing for structural breaks in discrete choice models." In 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2011. http://dx.doi.org/10.36334/modsim.2011.d10.wongsosaputro.

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8

Al-maadid, Alanoud, Nicola Spagnolo, Fabio Spagnolo, and Guglielmo Maria Caporale. "Spillovers between Food and Energy Prices and Structural Breaks." In Qatar Foundation Annual Research Conference Proceedings. Hamad bin Khalifa University Press (HBKU Press), 2016. http://dx.doi.org/10.5339/qfarc.2016.sshapp2320.

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9

Davis, R. A., T. C. M. Lee, and G. A. Rodriguez-Yam. "Structural breaks estimation for non-stationary time series signals." In 2005 Microwave Electronics: Measurements, Identification, Applications. IEEE, 2005. http://dx.doi.org/10.1109/ssp.2005.1628598.

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10

CAM, VINCENT LE, LAURENT LEMARCHAND, ARTHUR BOUCHE, DAVID PALLIER, and FRANÇOIS ILLIEN. "AN ORIGINAL SMART DATA SAMPLING FOR WIRELESS SENSOR: APPLICATION TO BRIDGE CABLE MONITORING." In Structural Health Monitoring 2023. Destech Publications, Inc., 2023. http://dx.doi.org/10.12783/shm2023/36843.

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Structural health monitoring (SHM) systems often ask for a robust, flexible and costeffective solution. In that domain, since years, the technological development of Wireless Sensor Network try to be an answer. Between many other questions, one of the keypoint in wireless sensing resides in the time synchronization (e.g. how to ensure the same time base between electronic systems that doesn’t know each others ?). At Gustave Eiffel University, robust and deterministic solutions based on GNSS modules have already been demonstrated [1], the goal of the work presented in this paper is to go deeper into turn-key solutions by implementing and coupling this GNSS-synchronization principle into a low-power FPGA to an Analog-To-Digital converter. This hardware and software association represents a generic solution for signal sampling in a wireless manner. This work is illustrated and demonstrated by an application on the acoustic monitoring of wire-breaks in bridges cables.

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Звіти організацій з теми "Structural breaks"

1

Pastor, Lubos, and Robert Stambaugh. The Equity Premium and Structural Breaks. Cambridge, MA: National Bureau of Economic Research, July 2000. http://dx.doi.org/10.3386/w7778.

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2

Cogley, Timothy, and Boyan Jovanovic. Structural Breaks in an Endogenous Growth Model. Cambridge, MA: National Bureau of Economic Research, October 2020. http://dx.doi.org/10.3386/w28026.

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3

Piehl, Anne Morrison, Suzanne Cooper, Anthony Braga, and David Kennedy. Testing for Structural Breaks in the Evaluation of Programs. Cambridge, MA: National Bureau of Economic Research, July 1999. http://dx.doi.org/10.3386/w7226.

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4

Owyang, Michael T., and Howard J. Wall. Structural Breaks and Regional Disparities in the Transmission of Monetary Policy. Federal Reserve Bank of St. Louis, 2003. http://dx.doi.org/10.20955/wp.2003.008.

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5

Ben-David, Dan, Robin Lumsdaine, and David Papell. Unit Roots, Postwar Slowdowns and Long-Run Growth: Evidence from Two Structural Breaks. Cambridge, MA: National Bureau of Economic Research, February 1998. http://dx.doi.org/10.3386/w6397.

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6

Akber, Nusrat, Anjani Kumar, and Seema Bathla. Public expenditure and growth dynamics in Indian agriculture: Trends, structural breaks, and linkages. Washington, DC: International Food Policy Research Institute, 2023. http://dx.doi.org/10.2499/p15738coll2.137019.

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7

Gonzáles-Castillo, Alberto, and Rolando Ossowski. Manna from Heaven: The Impact of Nonrenewable Resource Revenues on Other Revenues of Resource Exporters in Latin America and the Caribbean. Inter-American Development Bank, August 2012. http://dx.doi.org/10.18235/0011400.

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This paper examines the impact of the availability of fiscal revenues from nonrenewable resources on other revenues of Latin American and Caribbean resource-exporting countries. It compares the performance of nonresource revenues in these countries to that in other countries in the region. The effect of resource revenue on nonresource revenue is found to be negative and statistically significant, with structural breaks both over time and across countries. Nonresource revenues have risen considerably, but they are still lower on average than in comparator countries, and the wedge between both groups of countries has widened over time. They also tend to be more volatile. The paper also analyzes the composition of nonresource revenues. It finds that the performance of VAT and nonresource income taxes of resource exporters has been similar to that of other countries, but revenues from other taxes (including excises) have been lower. The paper's findings have important policy implications. Especially for resource exporters with fiscal vulnerabilities to shocks and sustainability issues, strengthening nonresource revenues would be important to create adequate fiscal space to meet expenditure needs. Oil exporters should also consider phasing out their costly, inefficient, and poorly targeted petroleum subsidies, with compensating measures to protect vulnerable groups.

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8

Romero-Chamorro, José Vicente, and Sara Naranjo-Saldarriaga. Weather Shocks and Inflation Expectations in Semi-Structural Models. Banco de la República Colombia, November 2022. http://dx.doi.org/10.32468/be.1218.

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Colombia is particularly affected by the El Niño Southern Oscillation (ENSO) weather fluctuations. In this context, this study explores how the adverse weather events linked to ENSO affect the inflation expectations in Colombia and how to incorporate these second-round effects into a small open economy New Keynesian model. Using BVARx models we provide evidence that the inflation expectations obtained from surveys and break-even inflation measures are affected by weather supply shocks. Later, using this stylised fact, we modify one of the core forecasting models of the Banco de la República by incorporating the mechanisms in which weather-related shocks affect marginal costs and inflation expectations. We find that ENSO shocks had an important role in both inflation and the dynamics of inflation expectations, and that policymakers should consider this fact.

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Pawlowski, Wojtek P., and Avraham A. Levy. What shapes the crossover landscape in maize and wheat and how can we modify it. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600025.bard.

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Meiotic recombination is a process in which homologous chromosomes engage in the exchange of DNA segments, creating gametes with new genetic makeup and progeny with new traits. The genetic diversity generated in this way is the main engine of crop improvement in sexually reproducing plants. Understanding regulation of this process, particularly the regulation of the rate and location of recombination events, and devising ways of modifying them, was the major motivation of this project. The project was carried out in maize and wheat, two leading crops, in which any advance in the breeder’s toolbox can have a huge impact on food production. Preliminary work done in the USA and Israeli labs had established a strong basis to address these questions. The USA lab pioneered the ability to map sites where recombination is initiated via the induction of double-strand breaks in chromosomal DNA. It has a long experience in cytological analysis of meiosis. The Israeli lab has expertise in high resolution mapping of crossover sites and has done pioneering work on the importance of epigenetic modifications for crossover distribution. It has identified genes that limit the rates of recombination. Our working hypothesis was that an integrative analysis of double-strand breaks, crossovers, and epigenetic data will increase our understanding of how meiotic recombination is regulated and will enhance our ability to manipulate it. The specific objectives of the project were: To analyze the connection between double-strand breaks, crossover, and epigenetic marks in maize and wheat. Protocols developed for double-strand breaks mapping in maize were applied to wheat. A detailed analysis of existing and new data in maize was conducted to map crossovers at high resolution and search for DNA sequence motifs underlying crossover hotspots. Epigenetic modifications along maize chromosomes were analyzed as well. Finally, a computational analysis tested various hypotheses on the importance of chromatin structure and specific epigenetic modifications in determining the locations of double-strand breaks and crossovers along chromosomes. Transient knockdowns of meiotic genes that suppress homologous recombination were carried out in wheat using Virus-Induced Gene Silencing. The target genes were orthologs of FANCM, DDM1, MET1, RECQ4, and XRCC2.

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Ladias, John A. Structural Basis for BRCA1 Function in Breast Cancer. Fort Belvoir, VA: Defense Technical Information Center, April 2005. http://dx.doi.org/10.21236/ada436887.

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