Current status of models of Jupiter's magnetosphere in the light of Pioneer data

The salient features of the various models of Jupiter's magnetosphere are compared with each other and with the major findings of Pioneer 10 and 11. No single model explains all the major phenomena detected by the Pioneers. A unified model of Jupiter's magnetosphere is proposed

Theoretical loss and gambling intensity: a simulation study

Many recent studies of internet gambling—particularly those that have analysed behavioural tracking data—have used variables such as ‘bet size’ and ‘number of games played’ as proxy measures for ‘gambling intensity.’ In this paper, it is argued that the best and most stable measure for Gambling Intensity is the ‘Theoretical Loss’ (a product of total bet size and house advantage). In the long run, Theoretical Loss corresponds with the Gross Gaming Revenue generated by commercial gaming operators. For shorter periods of time, Theoretical Loss is the most stable measure of gambling intensity as it is not distorted by gamblers’ occasional wins. Even for single bets, the Theoretical Loss reflects the amount a player is willing to risk. Using a simulation study, with up to 300,000 players playing as many as 13 different games, this paper demonstrates that the bet size and the number of games do not explain the theoretical loss entirely. In fact, there is a large proportion of variance which remains unexplained by measures of ‘bet size’ and ‘number of games’ played. Bet size and the number of games played do not equate to or explain theoretical loss, as neither of these two measures takes into account the house advantage

Revisiting the Core Ontology and Problem in Requirements Engineering

In their seminal paper in the ACM Transactions on Software Engineering and Methodology, Zave and Jackson established a core ontology for Requirements Engineering (RE) and used it to formulate the "requirements problem", thereby defining what it means to successfully complete RE. Given that stakeholders of the system-to-be communicate the information needed to perform RE, we show that Zave and Jackson's ontology is incomplete. It does not cover all types of basic concerns that the stakeholders communicate. These include beliefs, desires, intentions, and attitudes. In response, we propose a core ontology that covers these concerns and is grounded in sound conceptual foundations resting on a foundational ontology. The new core ontology for RE leads to a new formulation of the requirements problem that extends Zave and Jackson's formulation. We thereby establish new standards for what minimum information should be represented in RE languages and new criteria for determining whether RE has been successfully completed.Comment: Appears in the proceedings of the 16th IEEE International Requirements Engineering Conference, 2008 (RE'08). Best paper awar

Exchange rate pass-through, domestic competition, and inflation: Evidence from the 2005/08 revaluation of the Renminbi

This paper quantifies the effect of the government-controlled appreciation of the Chinese renminbi (RMB) vis-à-vis the USD from 2005 to 2008 on the prices charged by US producers. As the RMB during that time was pegged to a basket of currencies, the empirical strategy must account for the fact that the currencies included in the basket may have directly affected US prices. Thus, the pre-2005 period is used to filter out the effects of other exchange rates on import and producer prices. Additionally, utilizing the remainder of the sample, the pure effect of an RMB appreciation on US import prices and, in turn, the effect of RMB-induced US import price fluctuations on US producer prices is established. In a panel spanning the period from 1994 to 2010 and including 417 manufacturing sectors, the main finding emerging from this empirical strategy is that import prices pass into producer prices at an average rate of 0.7. This finding supports the view that the markets for domestic and imported manufactured goods are well integrated. Consequently, even if the exchange rate affects import prices only to a small extent, it may have a substantial impact on inflation, as it exerts a sizeable impact on the competitive environment of domestic producers and the prices that they charge

Product Heterogeneity, Cross-Country Taste Differences, and the Consumption Home Bias

This paper starts by showing that in the European car industry, there exist cross-country taste differences along the product attribute dimension that significantly drive net trade patterns and reduce the volume of trade. Further it is shown that, after the creation of the European common market, these cross-country taste differences caused a sluggish response of trade volume to liberalization as it took time for each country's industry structure to adapt to the demand structure of the common market. To rationalize such trade patterns, a structural model of demand featuring consumers with homothetic preferences and heterogeneous tastes over attributes is developed. Allowing for international trade, the model predicts that consumption is home-biased in the immediate aftermath of trade liberalization since each country's industry structure is optimized for the preferences of domestic consumers and domestic output thus does not match well with preferences abroad. Along the transition to the open economy steady state, each country's industry specializes into market segments with comparatively large domestic demand, implying that domestic firms leave the market segments the foreign industry specializes in. This increasing specialization that underlies the "home market" effect increases the average demand for foreign goods, the volume of trade, and the average gains from liberalization

Advanced MR techniques in glioblastoma imaging—upcoming challenges and how to face them

The management of gliomas has changed dramatically since the presentation of the revised WHO Classification of Tumors of the Central Nervous System in 2016 emphasizing the tumor heterogeneity based on their molecular profile. The need for a more noninvasive characterization of glioblastomas (GBM) by establishing reliable imaging biomarkers to predict patient outcome and improve therapy monitoring is bigger than ever. Multiparametric MRI, including promising newer techniques like electrical property tomography and mapping, may have the potential to provide enough information for intelligent imaging postprocessing algorithms to face the challenge by decoding GBM heterogeneity noninvasively