At the beginning of the Yuan dynasty a national script was invented. After the Yuan dynasty, this script was called the ḥP’ags-pa script, named for its inventor. Its spelling system is well preserved in the Ménggǔ Zìyùn 蒙古字韻 ‘Mongol Script (arranged according to) Rhymes.’ The Ménggǔ Zìyùn was an effort of the Yuan court to promote the new script and to provide an orthographic standard for transcribing Chinese. For modern Chinese historical phonologists, the obvious significance of this material is that, for the first time, Chinese was systematically transcribed into an alphabetic system. An entire phonology was transcribed into an alphabetical system and there was no need to reconstruct the phonetic values from categories that the characters belonged to. Individual sounds and syllables are spelled out clearly in a systematic way. Since both phonological categories and phonetic values of the standard phonology are given, no reconstruction, in the traditional sense, is required. The phonetic values of many crucial categories, such as the contrast between Division-III and Division-IV syllables, as well as the contrast of the chóngniǔ syllables and the palatalization of Division-II syllables can all be studied directly.

Die Rezeption der Inszenierungen des deutschen Regisseurs Peter Konwitschny (geb. 1945) im Bereich der japanischen Opernregie lässt sich in Bezug auf die Entwicklungsgeschichte der Opernkultur in Fernost unter verschiedenen Gesichtspunkten untersuchen. Sie ist mit der Frage verknüpft, warum die europäische Oper—d.h. die europäischen Musiktheaterstücke, welche vom siebzehnten Jahrhundert bis Anfang des zwanzigsten Jahrhunderts von den europäischen Komponisten und Librettisten geschaffen wurden und bis heute als sogenannte Repertoirestücke weltweit aufgeführt werden—und überhaupt die europäische klassische Musik sich in Ostasien seit dem zwanzigsten Jahrhundert so rasch verbreitet haben und so beliebt wurden. Dieser Beitrag beschränkt sich aber speziell auf Japan und insbesondere die Regiearbeiten der japanischen Schüler von Konwitschny. Die Oper ist in den drei ostasiatischen Ländern (China, Korea und Japan) je nach dem politischen Kontext (z.B. in China durch die kommunistische Zeit und in Korea unter dem starken amerikanischen Einfluss) unterschiedlich rezipiert worden—für eine ausführlichere Rezeptionsgeschichte der Oper in Fernost ist hier aber nicht der Ort.

Zur Vorbereitung dieses Beitrags habe ich die Proben und Premieren zweier Operninszenierungen von Konwitschny in Tokio (Verdis Macbeth 2013 und von Webers Der Freischütz 2018) besucht und als Zuhörerin an seinem Workshop in der Sommerakademie in Biwako Hall in Otsu 2014 teilgenommen. Darüber hinaus gab es zahlreiche Gespräche und Interviews zwischen dem Regisseur, den japanischen Mitwirkenden und mir vor Ort. Außerdem überließen mir einige der japanischen Regieschüler von Konwitschny Mitschnitte ihrer eigenen Regieprojekte. Des Weiteren unternahm ich im Dezember 2018 eine Forschungsreise nach Tokio mit freundlicher Unterstützung von Prof. Dr. Günther Heeg (Direktor des CCT Leipzig) und Prof. Dr. Eiichiro Hirata (Keio Universität Tokio). Dabei hielt ich zwei Vorträge über das vorliegende Thema an der Keio Universität Tokio und führte anschließend vertiefte Diskussionen mit japanischen Theaterwissenschaftlern und -praktikern.

I. Aufnahme und Verbreitung der Oper in Japan

Nach Ostasien gelangte die europäische Oper Anfang des zwanzigsten Jahrhunderts. Es gab zwar bereits gegen Ende des neunzehnten Jahrhunderts ein paar Aufführungen von ausgewählten Opernszenen in Form einer Präsentation, die durch europäische Diplomaten und Missionare in Japan organisiert wurde, und einige Opernaufführungen durch unbekannte europäische Operntruppen in China. Die erste nachgewiesene komplette Opernvorstellung in Japan durch einheimisches Personal war Glucks Orfeo ed Euridice 1903 am Tokyo Music College.

This chapter introduces the Conway–Maxwell–Poisson regression model, along with adaptations of the model to account for zero-inflation, censoring, and data clustering. Section 5.1 motivates the consideration and development of the various COM–Poisson regressions. Section 5.2 introduces the regression model and discusses related issues including parameter estimation, hypothesis testing, and statistical computing in R. Section 5.3 advances that work to address excess zeroes, while Section 5.4 describes COM–Poisson models that incorporate repeated measures and longitudinal studies. Section 5.5 focuses attention on the R statistical packages and functionality associated with regression analysis that accommodates excess zeros and/or clustered data as described in the two previous sections. Section 5.6 considers a general additive model based on COM–Poisson. Finally, Section 5.7 informs readers of other statistical computing softwares that are also available to conduct COM–Poisson regression, discussing their associated functionality. The chapter concludes with discussion.

The sharp and rigid dichotory between public and private corporations is a hallmark of securities regulation, but it has become outdated. The recent emergence, and dominance, of large private companies—once called “unicorns” for their rarity but now numbering in the hundreds—undermines essential assumptions behind securities regulations. This Chapter explores how the rise of these gargantuan private companies was brought on by the public’s eroding confidence in public companies and exacerbated by an ill-equipped government producing ineffective, reactionary legislation. Specifically, the Penny Stock Reform Act of 1990 and the Sarbanes-Oxley Act of 2002 resulted in a muddied pool of legitimate and fraudulent investment opportunities. Ordinary investors were left clambering for new investment opportunities and have shifted their gaze to the wilderness of the unregulated cryptocurrency market.

Chapter 9 examines the bubble in internet and other technology stocks that occurred at the end of the 1990s. This bubble witnessed the coming to market of many young firms which had never generated a profit. The excitement resulted in the NASDAQ index trebling in value in the 18 months prior to its peak in March 2000. By the end of 2000, however, it had lost more than half of its value. This bubble in tech stocks was not confined to the United States – it was a global phenomenon. The chapter then uses the bubble triangle can explain the causes of the dot-com bubble. The spark was provided by the new internet technology. Marketability increased as a result of new technology and many more companies floating on stock exchanges. Monetary conditions were loose in the runup of the bubble and there was a sharp rise in margin lending. Speculation was rampant in the runup, thanks to the rise of the day trader. The chapter concludes by arguing that the modest levels of economic damage associated with the bursting of the dot-com bubble suggest it could have been useful. However, its minor economic impact might also have made the authorities and investors complacent about the housing bubble which followed on its heels.

While the Poisson model motivated much of the classical control chart theory for count data, several works note the constraining equi-dispersion assumption. Dispersion must be addressed because over-dispersed data can produce false out-of-control detections when using Poisson limits, while under-dispersed data will produce Poisson limits that are too broad, resulting in potential false negatives and out-of-control states requiring a longer study period for detection. Section 6.1 introduces the Shewhart COM–Poisson control chart, demonstrating its flexibility in assessing in- or out-of-control status, along with advancements made to this chart. These initial works lead to a wellspring of flexible control chart development motivated by the COM–Poisson distribution. Section 6.2 describes a generalized exponentially weighted moving average control chart, and Section 6.3 describes the cumulative sum charts for monitoring COM–Poisson processes. Meanwhile, Section 6.4 introduces generally weighted moving average charts based on the COM-Poisson, and Section 6.5 presents the Conway–Maxwell–Poisson chart via the progressive mean statistic. Finally, the chapter concludes with discussion.

In 1995, the OMG published a COM/CORBA Interworking Request for Propsals (RFP). The RFP was composed of two parts. Part A dealt with interworking between CORBA and the commercially available implementation of COM. Part B dealt with interworking between CORBA and DCOM, which was still in development at that time. The OMG ratified Part A of the COM/CORBA Interworking Specification in 1996 and Part B in 1998. There are currently commercial implementations of Part A.

Our goal in this appendix is take a look at the concepts and considerations put forth in the specification. To begin, we will consider motivations for COM/CORBA integration. Then, we will give a very brief overview of COM. Moving into the meat of our topic, we will discuss a conceptual model for bridging, examine features common to COM and CORBA, and investigate mapping issues. We will look at locating and managing distributed objects from the perspectives of both COM and CORBA. We will conclude by examining COM/CORBA distribution issues.

From Whence We COM

COM evolved from OLE, Object Linking and Embedding, a technology which was developed for the single-user, single-machine environment of Windows 3.1. OLE enabled users to create and manage compound documents, thereby maximizing code reuse within and across applications on the Windows platform. OLE2 was designed to extend the paradigm to the component level. OLE2 interfaces and protocols mediate dynamic component interaction on a desk top.

Survival analysis studies the time-to-event for various subjects. In the biological and medical sciences, interest can focus on patient time to death due to various (competing) causes. In engineering reliability, one may study the time to component failure due to analogous factors or stimuli. Cure rate models serve a particular interest because, with advancements in associated disciplines, subjects can be viewed as “cured meaning that they do not show any recurrence of a disease (in biomedical studies) or subsequent manufacturing error (in engineering) following a treatment. This chapter generalizes two classical cure-rate models via the development of a COM–Poisson cure rate model. The chapter first describes the COM–Poisson cure rate model framework and general notation, and then details the model framework assuming right and interval censoring, respectively. The chapter then describes the broader destructive COM–Poisson cure rate model which allows for the number of competing risks to diminish via damage or eradication. Finally, the chapter details the various lifetime distributions considered in the literature to date for COM–Poisson-based cure rate modeling.

A multivariate Poisson distribution is a natural choice for modeling count data stemming from correlated random variables; however, it is limited by the underlying univariate model assumption that the data are equi-dispersed. Alternative models include a multivariate negative binomial and a multivariate generalized Poisson distribution, which themselves suffer from analogous limitations as described in Chapter 1. While the aforementioned distributions motivate the need to instead consider a multivariate analog of the univariate COM–Poisson, such model development varies in order to take into account (or results in) certain distributional qualities. This chapter summarizes such efforts where, for each approach, readers will first learn about any bivariate COM–Poisson distribution formulations, followed by any multivariate analogs. Accordingly, because these models are multidimensional generalizations of the univariate COM–Poisson, they each contain their analogous forms of the Poisson, Bernoulli, and geometric distributions as special cases. The methods discussed in this chapter are the trivariate reduction, compounding, Sarmanov family of distributions, and copulas.