Causes of the 2000s food price surge: Insights from structural VAR

In 2001 began a rise in the prices of food commodities not seen since the 1970s. The prices of grains - the major staple foods - increased fivefold between 2003 and 2008, leading to the additional malnutrition of millions around the world. Many observers attribute the strong increase in part to speculation in derivatives markets. We examine this hypothesis by comparing the impact of speculation to that of fundamental supply and demand forces. We estimate the share of the price increase attributable to the respective market forces using a sign identified structural vector autoregressive model. Speculation is identifid using storage data, though a residual price shock is allowed to ensure the robustness of the findings

The potential of the contradictory in digital media:The example of the political art game PoliShot

When we created PoliShot, a political Dada game and interactive installation, we were confronted quite unexpectedly with the question of what is morally or ethically tolerable in digital games. When it was exhibited, it provoked shocked and concerned reactions from curators and visitors alike. The stumbling block was the use of violence, or more specifically, asking the players to act violently in the game. We take our experiences as an occasion to enquire into and discuss the contradictions of the actual and the virtual, of concept and content. We attempt to draw historical and contemporary parallels and reflect on how art production is not limited to the work, but includes the artists and the audience as essential players in a dynamic system of meanings, motives, and interpretations, full of (un)intended and (un)anticipated conflicts, provocations, breakdowns and shifts, creating exciting and challenging opportunities for play

Skewness-Adjusted Bootstrap Confidence Intervals and Confidence Bands for Impulse Response Functions

This Article Investigates The Construction Of Skewness-Adjusted Confidence Intervals And Joint Confidence Bands For Impulse Response Functions From Vector Autoregressive Models. Three Different Implementations Of The Skewness Adjustment Are Investigated. The Methods Are Based On A Bootstrap Algorithm That Adjusts Mean And Skewness Of The Bootstrap Distribution Of The Autoregressive Coefficients Before The Impulse Response Functions Are Computed. Using Extensive Monte Carlo Simulations, The Methods Are Shown To Improve The Coverage Accuracy In Small And Medium Sized Samples And For Unit Root Processes For Both Known And Unknown Lag Orders

Empirical comparison of diffusion kurtosis imaging and diffusion basis spectrum imaging using the same acquisition in healthy young adults

As diffusion tensor imaging gains widespread use, many researchers have been motivated to go beyond the tensor model and fit more complex diffusion models, to gain a more complete description of white matter microstructure and associated pathology. Two such models are diffusion kurtosis imaging (DKI) and diffusion basis spectrum imaging (DBSI). It is not clear which DKI parameters are most closely related to DBSI parameters, so in the interest of enabling comparisons between DKI and DBSI studies, we conducted an empirical survey of the interrelation of these models in 12 healthy volunteers using the same diffusion acquisition. We found that mean kurtosis is positively associated with the DBSI fiber ratio and negatively associated with the hindered ratio. This was primarily driven by the radial component of kurtosis. The axial component of kurtosis was strongly and specifically correlated with the restricted ratio. The joint spatial distributions of DBSI and DKI parameters are tissue-dependent and stable across healthy individuals. Our contribution is a better understanding of the biological interpretability of the parameters generated by the two models in healthy individuals

Time Constrained Verification of Analog Circuits using Model-Checking Algorithms

In this contribution we present algorithms for model checking of analog circuits enabling the specification of time constraints. Furthermore, a methodology for defining time-based specifications is introduced. An already known method for model checking of integrated analog circuits has been extended to take into account time constraints. The method will be presented using three industrial circuits. The results of model checking will be compared to verification by simulation

Skewness-Adjusted Bootstrap Confidence Intervals and Confidence Bands for Impulse Response Functions

This article investigates the construction of skewness-adjusted con�dence intervals and joint confidence bands for impulse response functions from vector autoregressive models. Three different implementations of the skewness adjustment are investigated. The methods are based on a bootstrap algorithm that adjusts mean and skewness of the bootstrap distribution of the autoregressive coeffcients before the impulse response functions are computed. Using extensive Monte Carlo simulations, the methods are shown to improve the coverage accuracy in small and medium sized samples and for unit root processes for both known and unknown lag orders

Premise Selection for Mathematics by Corpus Analysis and Kernel Methods

Smart premise selection is essential when using automated reasoning as a tool for large-theory formal proof development. A good method for premise selection in complex mathematical libraries is the application of machine learning to large corpora of proofs. This work develops learning-based premise selection in two ways. First, a newly available minimal dependency analysis of existing high-level formal mathematical proofs is used to build a large knowledge base of proof dependencies, providing precise data for ATP-based re-verification and for training premise selection algorithms. Second, a new machine learning algorithm for premise selection based on kernel methods is proposed and implemented. To evaluate the impact of both techniques, a benchmark consisting of 2078 large-theory mathematical problems is constructed,extending the older MPTP Challenge benchmark. The combined effect of the techniques results in a 50% improvement on the benchmark over the Vampire/SInE state-of-the-art system for automated reasoning in large theories.Comment: 26 page

Causes of the 2000s Food Price Surge: New Evidence fromStructural VAR

In 2001 began a rise in the prices of food commodities not seen since the 1970s. Some observers attribute the increase in part to food commodity spec- ulation. This hypothesis is examined by disentangling the impact of specu- lation on grain prices from that of fundamental supply and demand forces. Even though results point to a generally stabilising in uence of speculation on prices, speculation is shown to have pushed prices further up during crisis years. The analysis is based on a structural vector autoregressive model identified by sign and zero restrictions. The model is estimated for global corn, wheat and rice markets

Drag reduction in pipe flows with polymer additives

Polyethylene Oxides (PEO) with molecular weights of 4 and 6 million and a Polyacrylamide (PAM) with a molecular weight of 15 million, were added to a turbulent pipe flow (15000 \u3c Re \u3c 50000) for drag reduction. The polymer was injected directly into the test section in one scenario, premixed in a tank and then pumped through the test section in the second. The injection addition method was found to be optimal because it subjected the polymer to lower amounts of shear stresses than the premixed addition method. A maximum of 75% reduction in drag was obtained. Even trace concentrations, as low as 2.5 WPPM (weight parts per million) , resulted in as high as 37% reduction in drag. Long thin high molecular weight polymers (PEO) were more effective than coiled high molecular weight polymer (PAM) . For the same molecular structure it was found that the polymer with heavier molecules had better drag reducing characteristics. The polymer with coiled molecules, however, is more resistant to shear stresses which break down the polymer into smaller less effective molecules. It was found that there is a critical concentration for the greatest drag reduction. This concentration is approximately 375 WPPM (.0375% byweight) of PEO for the injection method, and 500 WPPM of PEO for the premixed method. At greater concentrations, the viscosity of the solution increases such that the drag reduction characteristics of the polymer can no longer compensate

Wavelet-Based Linear-Response Time-Dependent Density-Functional Theory

Linear-response time-dependent (TD) density-functional theory (DFT) has been implemented in the pseudopotential wavelet-based electronic structure program BigDFT and results are compared against those obtained with the all-electron Gaussian-type orbital program deMon2k for the calculation of electronic absorption spectra of N2 using the TD local density approximation (LDA). The two programs give comparable excitation energies and absorption spectra once suitably extensive basis sets are used. Convergence of LDA density orbitals and orbital energies to the basis-set limit is significantly faster for BigDFT than for deMon2k. However the number of virtual orbitals used in TD-DFT calculations is a parameter in BigDFT, while all virtual orbitals are included in TD-DFT calculations in deMon2k. As a reality check, we report the x-ray crystal structure and the measured and calculated absorption spectrum (excitation energies and oscillator strengths) of the small organic molecule N-cyclohexyl-2-(4-methoxyphenyl)imidazo[1,2-a]pyridin-3-amine