Building a Model of Aggregate Demand and Aggregate Supply

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A model of aesthetic appreciation and aesthetic judgments Helmut Leder 1,2 *, Benno Belke 1 , Andries Oeberst 1 and Dorothee Augustin 1 1 Freie Universita ¨ t Berlin, Institute of Psychology, Germany 2 Universita ¨ t Wien, Austria Although aesthetic experiences are frequent in modern life, there is as of yet no scientifically comprehensive theory that explains what psychologically constitutes such experiences. These experiences are particularly interesting because of their hedonic properties and the possibility to provide self-rewarding cognitive operations. We shall explain why modern art’s large number of individualized styles, innovativeness and conceptuality offer positive aesthetic experiences. Moreover, the challenge of art is mainly driven by a need for understanding. Cognitive challenges of both abstract art and other conceptual, complex and multidimensional stimuli require an extension of previous approaches to empirical aesthetics. We present an information-processing stage model of aesthetic processing. According to the model, aesthetic experiences involve five stages: perception, explicit classification, implicit classification, cognitive mastering and evaluation. The model differentiates between aesthetic emotion and aesthetic judgments as two types of output. Psychology of aesthetic appreciation Our aim in this article is to explain why people are attracted by art. We give an answer from a psychological perspective with special interest paid to psychologically relevant features of art, especially modern art. We discuss how cognitive processing of art produces affective, often positive and self-rewarding aesthetic experiences. We propose a model that represents different processing stages as well as important variables that are involved in aesthetic experiences. We aim to understand the art-specific cognitive experiences that give art such a prominent position in human culture and thus go beyond perceiving art solely as an interesting perceptual stimulus. Moreover, we show that the often-controversial modern or contemporary art is particularly interesting from such a psychological perspective. Although we mainly focus on visual arts, the * Correspondence should be addressed to Helmut Leder, Freie Universita¨t Berlin, Institute of Psychology, Habelschwerdter Allee 45, 14195 Berlin, Germany (e-mail: leder@experimental-psychology.de). 489 British Journal of Psychology (2004), 95, 489–508 q 2004 The British Psychological Society www.bps.org.uk mechanisms we describe should also be transferable to aesthetic experiences with other forms of art and aesthetic experiences. There is no doubt that art is the prototypical domain for questions of aesthetic research but other objects may also be treated as aesthetically relevant. There is, for example, considerable progress in understanding which faces are found aesthetically pleasing (Etcoff, 1999) or what design in everyday objects such as cars is aesthetically appreciated (Hekkert, Snelders, & van Wieringen, 2003; Leder & Carbon, in press). Every year thousands attend blockbuster art exhibitions. The ‘Matisse–Picasso’ exhibition in the Tate Modern in London sold just under half a million tickets, and the 2002 Documenta in Kassel, a controversial exhibition of contemporary art, even had more than 650,000 visitors. People are exposed to art in magazines and TV programmes. Art even has the power to transform a town and put it back on the tourist track. Witness, for example, the huge Building a Model of Aggregate Demand and Aggregate Supply Building a Model of Aggregate Demand and Aggregate Supply By: OpenStaxCollege To build a useful macroeconomic model, we need a model that shows what determines total supply or total demand for the economy, and how total demand and total supply interact at the macroeconomic level This model is called the aggregate demand/ aggregate supply model This module will explain aggregate supply, aggregate demand, and the equilibrium between them The following modules will discuss the causes of shifts in aggregate supply and aggregate demand The Aggregate Supply Curve and Potential GDP Firms make decisions about what quantity to supply based on the profits they expect to earn Profits, in turn, are also determined by the price of the outputs the firm sells and by the price of the inputs, like labor or raw materials, the firm needs to buy Aggregate supply (AS) is the relationship between real GDP and the price level for output, holding the price of inputs fixed The aggregate supply (AS) curve shows the total quantity of output that firms choose to produce and sell (i.e., real GDP) at each different price level [link] shows an aggregate supply curve In the following paragraphs, we will walk through the elements of the diagram one at a time: the horizontal and vertical axes, the aggregate supply curve itself, and the meaning of the potential GDP vertical line 1/12 Building a Model of Aggregate Demand and Aggregate Supply The Aggregate Supply Curve Aggregate supply (AS) slopes up, because as the price level for outputs rises, with the price of inputs remaining fixed, firms have an incentive to produce more and to earn higher profits The potential GDP line shows the maximum that the economy can produce with full employment of workers and physical capital The horizontal axis of the diagram shows real GDP—that is, the level of GDP adjusted for inflation The vertical axis shows the price level Remember that the price level is different from the inflation rate Visualize the price level as an index number, like the GDP deflator, while the inflation rate is the percentage change between price levels over time As the price level (the average price of all goods and services produced in the economy) rises, the aggregate quantity of goods and services supplied rises as well Why? The price level shown on the vertical axis represents prices for final goods or outputs bought in the economy—like the GDP deflator—not the price level for intermediate goods and services that are inputs to production Thus, the AS curve describes how suppliers will react to a higher price level for final outputs of goods and services, while holding the prices of inputs like labor and energy constant If firms across the economy face a situation where the price level of what they produce and sell is rising, but their costs of production are not rising, then the lure of higher profits will induce them to expand production The slope of an AS curve changes from nearly flat at its far left to nearly vertical at its far right At the far left of the aggregate supply curve, the level of output in the economy is far below potential GDP, which is defined as the quantity that an economy can produce by fully employing its existing levels of labor, physical capital, and technology, in the 2/12 Building a Model of Aggregate Demand and Aggregate Supply context of its existing market and legal institutions At these relatively low levels of output, levels of unemployment are high, and many factories are running only part-time, or have closed their doors In this situation, a relatively small increase in the prices of the outputs that businesses sell—while making the assumption of no rise in input prices—can encourage a considerable surge in the quantity of aggregate supply because so many workers and factories are ready to swing into production As the quantity produced increases, however, certain firms and industries will start running into limits: perhaps nearly all of the expert workers in a certain industry will have jobs or factories in certain geographic areas or industries will be running at full speed In the intermediate area of the AS curve, a higher price level for outputs continues to encourage a greater quantity of output—but as the increasingly steep upward slope of the aggregate supply curve shows, the increase in quantity in response to a given rise in the price level will not be quite as large (Read the following Clear It Up feature to learn why the AS curve crosses potential GDP.) Why does AS cross potential GDP? The aggregate supply curve is typically drawn to cross the potential GDP line This shape may seem puzzling: How can an economy produce at an output level which is higher than its “potential” or “full employment” GDP? The economic intuition here is that if prices for outputs were high enough, producers would make fanatical efforts to produce: all workers would be on double-overtime, all machines ...A Model of Lexical Attraction and Repulsion* Doug Beeferman Adam Berger John Lafferty School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 USA <dougb, aberger, lafferty>@cs, cmu. edu Abstract This paper introduces new methods based on exponential families for modeling the correlations between words in text and speech. While previous work assumed the effects of word co-occurrence statistics to be constant over a window of several hun- dred words, we show that their influence is nonstationary on a much smaller time scale. Empirical data drawn from En- glish and Japanese text, as well as conver- sational speech, reveals that the "attrac- tion" between words decays exponentially, while stylistic and syntactic contraints cre- ate a "repulsion" between words that dis- courages close co-occurrence. We show that these characteristics are well described by simple mixture models based on two- stage exponential distributions which can be trained using the EM algorithm. The resulting distance distributions can then be incorporated as penalizing features in an exponential language model. 1 Introduction One of the fundamental characteristics of language, viewed as a stochastic process, is that it is highly nonstationary. Throughout a written document and during the course of spoken conversation, the topic evolves, effecting local statistics on word oc- currences. The standard trigram model disregards this nonstationarity, as does any stochastic grammar whichassigns probabilities to sentences in a context- independent fashion. *Research supported in part by NSF grant IRI- 9314969, DARPA AASERT award DAAH04-95-1-0475, and the ATR Interpreting Telecommunications Research Laboratories. Stationary models are used to describe such a dy- namic source for at least two reasons. The first is convenience: stationary models require a relatively small amount of computation to train and to apply. The second is ignorance: we know so little about how to model effectively the nonstationary charac- teristics of language that we have for the most part completely neglected the problem. From a theoreti- cal standpoint, we appeal to the Shannon-McMillan- Breiman theorem (Cover and Thomas, 1991) when- ever computing perplexities on test data; yet this result only rigorously applies to stationary and er- godic sources. To allow a language model to adapt to its recent context, some researchers have used techniques to update trigram statistics in a dynamic fashion by creating a cache of the most recently seen n-grams which is smoothed together (typically by linear in- terpolation) with the static model; see for example (Jelinek et al., 1991; Kuhn and de Mori, 1990). An- other approach, using maximum entropy methods similar to those that we present here, introduces a parameter for trigger pairs of mutually informative words, so that the occurrence of certain words in re- cent context boosts the probability of the words that they trigger (Rosenfeld, 1996). Triggers have also been incorporated through different methods (Kuhn and de Mori, 1990; Ney, Essen, and Kneser, 1994). All of these techniques treat the recent context as a "bag of words," so that a word that appears, say, five positions back makes the same contribution to pre- diction as words at distances of 50 or 500 positions back in the history. In this paper we introduce new modeling tech- niques based on exponential families for captur- ing the long-range correlations between occurrences of words in text and speech. We UPTEC STS11 017 Examensarbete 30 hp Mars 2011 Modeling in MathWorks Simscape by building a model of an automatic gearbox Staffan Enocksson Teknisk- naturvetenskaplig fakultet UTH-enheten Besöksadress: Ångströmlaboratoriet Lägerhyddsvägen 1 Hus 4, Plan 0 Postadress: Box 536 751 21 Uppsala Telefon: 018 – 471 30 03 Telefax: 018 – 471 30 00 Hemsida: http://www.teknat.uu.se/student Abstract Modeling in MathWorks Simscape by building a model of an automatic gearbox Staffan Enocksson The purpose of this thesis work has been to analyze the usability and the feasibility for modeling with MathWorks simulation tool Simscape by building a simplified model of the automatic gearbox ZF-ECOMAT 4 (HP 504 C / HP 594 C / HP 604 C). It has been shown throughout the thesis how this model is build. First has system knowledge been acquired by studying relevant literature and speaking with the persons concerned. The second step was to get acquainted with Simscape and the physical network approach. The physical network approach that is accessible through the Simscape language makes is easy to build custom made components with means of physical and mathematical relationships. With this background a stepwise approach been conducted which has led to the final model of the gearbox and the validation concept. The results from this thesis work indicates that Simscape is a powerful tool for modeling physical systems and the results of the model validation gives a good sign that it is possible to build and simulate physical models with the Simscape software. However, during the modeling of the ZF-ECOMAT 4 some things have been discovered which could improve the usability of the tool and make the learning curve for an inexperienced user of physical modeling tools less steep. In particular, a larger model library should be included from the beginning, more examples of simple and more complex models, the object-oriented related parts such as own MATLAB functions should be expanded, and a better troubleshooting guidance. ISSN: 1650-8319, UPTEC STS11 017 Examinator: Elisabet Andrésdóttir Ämnesgranskare: Bengt Carlsson Handledare: Afram Kourie Populärvetenskaplig beskrivning Syftet med den här uppsatsen har varit att analysera användbarheten och möjligheten att modellera med MathWorks simuleringsverktyg Simscape genom att bygga en förenklad modell av den automatiska växellådan ZF-ECOMAT 4 (HP 504 C / HP 594 C / HP 604 C). Genom uppsatsen har det visats hur denna modell är uppbyggd. Först har en systemkunskap inhämtats genom att studera relevant litteratur och genom att tala med berörda personer. Det andra steget var att bekanta sig med Simscape och den fysiska modelleringsapproachen. Den fysiska modelleringsapproachen som är tillgänglig via Simscape-språket gör det enkelt att bygga egentillverkade komponenter med hjälp av fysiska och matematiska samband. Med den här bakgrunden har en stegvis tillvägagångssätt genomförts vilket har mynnat ut i den slutgiltiga modellen av växellådan och valideringkonceptet. Simscape har visat sig vara ett kraftfullt verktyg för att modellera fysikaliska system och resultatet från modellvalideringen ger en god indikation att det är möjligt att bygga och simulera fysikaliska modeller med Simscape-mjukvaran. Dock ska det nämnas, att under modelleringen av ZF-ECOMAT 4 så dök det upp saker som skulle kunna öka användbarheten av verktyget och minska inlärningskurvan för en ovan användare av fysikaliska modelleringsverktyg. Framförallt att ett större modellbibliotek borde finnas med från början, mer exempel av enkla och mer komplicerade modeller, de objektorienterade delarna som t.ex. egna MATLAB-funktioner borde byggas ut, samt en bättre felsökningsguide. A model of light interception and carbon balance for a sweet chestnut coppice (Castanea sativa Mill.) L. Mordacq B. Saugier Laboratoire d’Ecologie V6g6tale (CNRS URA121), Bit 362, Université Paris-Sud, 91405 Orsay Cedex, France Introduction Data have been collected on leaf photo- synthesis, young tree photosynthesis, wood respiration and aerial growth in a sweet chestnut (Castanea sativa Mill.) coppice for several years after a cut. We designed a model to predict photosynthe- sis of heterogeneous canopies and wood respiration. The output of the model to- gether with measurements of aerial growth enabled calculation of the amount of carbon allocated to roots. Materials and Methods Leaf photosynthesis has been measured in situ on attached leaves using a laboratory- made assimilation chamber with control of leaf temperature by Peltier elements. The chamber was working as an open system and the leaf temperature was fixed at 24°C. Measurements were made throughout the growing season. Tree photosynthesis was measured in situ on a 1 yr old chestnut tree using a large assimila- tion chamber (0.9 m x 0.9 m x 1.8 m high) built in the laboratory and working as an open sys- tem. A high flow of air through the cham- ber (maximum 0.08 m3!s-!) kept the increase in air temperature within 4°C with respect to the outside (Mordacq and Saugier, 1989). Measure- ments were performed at the end of the grow- ing season during August and September. The assimilation model took into account the heterogeneous structure of the canopy, which is necessary during the first years after the cut. Each tree was first considered as being iso- lated; there was no intersection between the foliage of different trees until the end of the first year. The leaves in the model were distributed homogeneously within ellipsoids or fractions of ellipsoids around each stump. The dimensions of the ellipsoids were measured in situ and the trees were distributed randomly on the soil sur- face, except that there could be no intersection between the ellipsoids at the end of the first year. The light penetration was calculated at randomly distributed points P by calculating the extinction coefficient from the leaf angle distri- bution (de Wit, 1965), and the pathlength (Fig. 1) of light rays R through the ellipsoids (Norman and Welles, 1983). Diffuse light was treated as direct light and integrated over the whole sky. Thus the model enabled calculation of sha- dowing between trees. As the trees grew, the ellipsoids grew to the point where the soil was completely covered by the canopy (Fig. 1 ). Photosynthesis was calculated on an hourly basis. Results . tion level was 600 pE. M-2-S-1; the maxi- mum photosynthesis level was 13 pmol C0 2 -m- 2 -s-B Fig. 3 shows the tree photosyn- thesis-light curve (by unit leaf area of the tree) compared with the outputs of the model for a single tree and for two light conditions. The light saturation was at 600 pE-m 2 -s-1 and the maximum tree photosynthesis level was 6 pmol COz’m- 2’ s- 1, about half of the maximum leaf photosynthesis. Agreement between measurements and model outputs is good. However, at low light levels, the model underestimated photosynthesis for overcast sky conditions and overestimated it for clear BioMed Central Page 1 of 24 (page number not for citation purposes) Theoretical Biology and Medical Modelling Open Access Research A model of gene-gene and gene-environment interactions and its implications for targeting environmental interventions by genotype Helen M Wallace* Address: GeneWatch UK, The Mill House, Tideswell, Buxton, Derbyshire, SK17 8LN, UK Email: Helen M Wallace* - helen.wallace@genewatch.org * Corresponding author Abstract Background: The potential public health benefits of targeting environmental interventions by genotype depend on the environmental and genetic contributions to the variance of common diseases, and the magnitude of any gene-environment interaction. In the absence of prior knowledge of all risk factors, twin, family and environmental data may help to define the potential limits of these benefits in a given population. However, a general methodology to analyze twin data is required because of the potential importance of gene-gene interactions (epistasis), gene- environment interactions, and conditions that break the 'equal environments' assumption for monozygotic and dizygotic twins. Method: A new model for gene-gene and gene-environment interactions is developed that abandons the assumptions of the classical twin study, including Fisher's (1918) assumption that genes act as risk factors for common traits in a manner necessarily dominated by an additive polygenic term. Provided there are no confounders, the model can be used to implement a top- down approach to quantifying the potential utility of genetic prediction and prevention, using twin, family and environmental data. The results describe a solution space for each disease or trait, which may or may not include the classical twin study result. Each point in the solution space corresponds to a different model of genotypic risk and gene-environment interaction. Conclusion: The results show that the potential for reducing the incidence of common diseases using environmental interventions targeted by genotype may be limited, except in special cases. The model also confirms that the importance of an individual's genotype in determining their risk of complex diseases tends to be exaggerated by the classical twin studies method, owing to the 'equal environments' assumption and the assumption of no gene-environment interaction. In addition, if phenotypes are genetically robust, because of epistasis, a largely environmental explanation for shared sibling risk is plausible, even if the classical heritability is high. The results therefore highlight the possibility – previously rejected on the basis of twin study results – that inherited genetic variants are important in determining risk only for the relatively rare familial forms of diseases such as breast cancer. If so, genetic models of familial aggregation may be incorrect and the hunt for additional susceptibility genes could be largely fruitless. Published: 09 October 2006 Theoretical Biology and Medical Modelling 2006, 3:35 doi:10.1186/1742-4682-3-35 Received: 13 April 2006 Accepted: 09 October 2006 This article is available from: http://www.tbiomed.com/content/3/1/35 © 2006 Wallace; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Theoretical Biology and Medical Modelling 2006, 3:35 http://www.tbiomed.com/content/3/1/35 Page 2 of 24 (page number not for citation purposes) Background Some geneticists have predicted a genetic revolution in healthcare: involving a future in which individuals take a battery of genetic tests, at birth or later in life, to determine their individual 'genetic susceptibility' to disease [1,2]. In theory, once the risk of particular combinations of geno- type and ... Building a Model of Aggregate Demand and Aggregate Supply Are AS and AD macro or micro? These aggregate supply and aggregate demand model and the microeconomic analysis of demand and supply in particular... Building a Model of Aggregate Demand and Aggregate Supply Plot the AD/AS diagram from the data shown Identify the equilibrium Imagine that, as a result of a government tax cut, aggregate demand. .. leftward shift) in aggregate supply could be another reason 9/12 Building a Model of Aggregate Demand and Aggregate Supply Review Questions What is on the horizontal axis of the AD/AS diagram? What