Social preferences in the public goods game-An Agent-Based simulation with EconSim.

Using a reinforcement-learning algorithm, we model an agent-based simulation of a public goods game with endogenous punishment institutions. We propose an outcome-based model of social preferences that determines the agent's utility, contribution, and voting behavior during the learning procedure. Comparing our simulation to experimental evidence, we find that the model can replicate human behavior and we can explain the underlying motives of this behavior. We argue that our approach can be generalized to more complex simulations of human behavior.

Human hair in the identification of cocaine abuse with cantilever-enhanced photoacoustic spectroscopy and principal component analysis.

In this study, a novel approach combining different techniques, including Fourier transform infrared (FT-IR) spectroscopy, photoacoustic spectroscopy (PAS) with an interferometric cantilever microphone, and principal component analysis (PCA) along with a proper data preprocessing procedure, have been used in the investigation of hair samples for cocaine abuse. Hair fibers from cocaine-overdose patients have been measured using a simple procedure involving cantilever-enhanced photoacoustic Fourier transform infrared spectroscopy. In addition, a reference group of hair samples from subjects with no cocaine abuse has been measured. We present a first approach to discriminate the cocaine users from the reference group with the photoacoustic method and PCA. With proper data preprocessing methods, the two groups were successfully separated according to their spectra. The results were confirmed with two different classification methods independent of the principal component data analysis.

FT-IR-cPAS--new photoacoustic measurement technique for analysis of hot gases: a case study on VOCs.

This article describes a new photoacoustic FT-IR system capable of operating at elevated temperatures. The key hardware component is an optical-readout cantilever microphone that can work up to 200 °C. All parts in contact with the sample gas were put into a heated oven, incl. the photoacoustic cell. The sensitivity of the built photoacoustic system was tested by measuring 18 different VOCs. At 100 ppm gas concentration, the univariate signal to noise ratios (1σ, measurement time 25.5 min, at highest peak, optical resolution 8 cm(-1)) of the spectra varied from minimally 19 for o-xylene up to 329 for butyl acetate. The sensitivity can be improved by multivariate analyses over broad wavelength ranges, which effectively co-adds the univariate sensitivities achievable at individual wavelengths. The multivariate limit of detection (3σ, 8.5 min, full useful wavelength range), i.e., the best possible inverse analytical sensitivity achievable at optimum calibration, was calculated using the SBC method and varied from 2.60 ppm for dichloromethane to 0.33 ppm for butyl acetate. Depending on the shape of the spectra, which often only contain a few sharp peaks, the multivariate analysis improved the analytical sensitivity by 2.2 to 9.2 times compared to the univariate case. Selectivity and multi component ability were tested by a SBC calibration including 5 VOCs and water. The average cross selectivities turned out to be less than 2% and the resulting inverse analytical sensitivities of the 5 interfering VOCs was increased by maximum factor of 2.2 compared to the single component sensitivities. Water subtraction using SBC gave the true analyte concentration with a variation coefficient of 3%, although the sample spectra (methyl ethyl ketone, 200 ppm) contained water from 1,400 to 100k ppm and for subtraction only one water spectra (10k ppm) was used. The developed device shows significant improvement to the current state-of-the-art measurement methods used in industrial VOC measurements.

Fourier transform infrared photoacoustic multicomponent gas spectroscopy with optical cantilever detection.

The sensitivity of photoacoustic spectroscopy was improved with the invention of optical cantilever detection (PAS-OCD). However, the ability of present PAS-OCD devices to carry out multicomponent detection is poor. To overcome this, a Fourier transform infrared photoacoustic spectrometer with optical cantilever detection (FT-IR-PAS-OCD) prototype was assembled. In this article, the first evaluation and performance tests of the prototype are described. Selectivity, sensitivity, and the linearity of the signal response are evaluated. The linear response was studied for methane and carbon dioxide and confirmed in the whole analyzed concentration range from 500 to 3500 ppm and from 2500 to 17500 ppm, respectively. The calculated signal-to-noise ratio (SNR) and limit of detection were 2027 and 0.5 ppm for methane and 1362 and 4 ppm for carbon dioxide, with a measurement time of 100 seconds. Selectivity was studied with a multicomponent gas mixture of propene, methane, carbon dioxide, and methylmercaptane. The results indicate that a quantitative analysis of all components in the mixture is possible using the FT-IR-PAS-OCD.