Time discounting (delta) and pain anticipation: Experimental evidence

To be published in: Revista Internacional de Sociología (2011), Special Issue on Experimental and Behavioral Economics.

Do experimental subjects favor their friends?

Ideally we would like subjects of experiments to be perfect strangers so that the situation they face at the lab is not just part of a long run interaction. Unfortunately, it is not easy to reach those conditions and experimenters try to mitigate any effects from those out-of-the-lab relationships by, for instance, randomly matching subjects. However, even if this type of procedure is used, there is a positive probability that a subject may face a friend or an acquaintance. We find evidence that social proximity between subjects is irrelevant to experiment results in dictator games. Thus, although ideal conditions are not met, relations between subjects do not contaminate the results of experiments.

Moral cleansing and moral licenses: experimental evidence

Research on moral cleansing and moral self-licensing has introduced dynamic considerations in the theory of moral behavior. Past bad actions trigger negative feelings that make people more likely to engage in future moral behavior to offset them. Symmetrically, past good deeds favor a positive self-perception that creates licensing effects, leading people to engage in behavior that is less likely to be moral. In short, a deviation from a “normal state of being” is balanced with a subsequent action that compensates the prior behavior. We model the decision of an individual trying to reach the optimal level of moral self-worth over time and show that under certain conditions the optimal sequence of actions follows a regular pattern which combines good and bad actions. We conduct an economic experiment where subjects play a sequence of giving decisions (dictator games) to explore this phenomenon. We find that donation in the previous period affects present decisions and the sign is negative: participants’ behavior in every round is negatively correlated to what they did in the past. Hence donations over time seem to be the result of a regular pattern of self-regulation: moral licensing (being selfish after altruist) and cleansing (altruistic after selfish).

Wave Propagation Analysis in a Pressure-Wave-Refrigerator

Pressure wave refrigerators (PWR) refrigerate the gas through periodical expansion waves. Due to its simple structure and robustness, PWR may have many potential applications if the efficiency becomes competitive with existing alternative devices. In order to improve the efficiency, the characteristics of wave propagation in a PWR are studied by experiment, numerical simulation and theoretical analysis. Based on the experimental results and numerical simulation, a simplified model is suggested, which includes the assumptions of flux-equilibrium and conservation of the free energy. This allows the independent analysis of the operation parameters and design specifics. Furthermore, the optimum operation condition can be deduced. Some considerations to improve the PWR efficiency are also given.

Experimental Study on Subcooled Pool Boiling in Microgravity Utilizing

A Breakdown Criterion of Free Molecular Flows and an Optimum Analysis of EBPVD

Two important issues in electron beam physical vapor deposition (EBPVD) are addressed. The first issue is a validity condition of the classical cosine law widely used in the engineering context. This requires a breakdown criterion of the free molecular assumption on which the cosine law is established. Using the analytical solution of free molecular effusion flow, the number of collisions (N-c) for a particle moving from an evaporative source to a substrate is estimated that is proven inversely proportional to the local Knudsen number at the evaporation surface. N-c = 1 is adopted as a breakdown criterion of the free molecular assumption, and it is verified by experimental data and DSMC results. The second issue is how to realize the uniform distributions of thickness and component over a large-area thin film. Our analysis shows that at relatively low evaporation rates the goal is easy achieved through arranging the evaporative source positions properly and rotating the substrate.

Failure process analysis of cement under explosive loading with a generalized driven nonlinear threshold model

The microstructural heterogeneity and stress fluctuation play important roles in the failure process of brittle materials. In this paper, a generalized driven nonlinear threshold model with stress fluctuation is presented to study the effects of microstructural heterogeneity on continuum damage evolution. As an illustration, the failure process of cement material under explosive loading is analyzed using the model. The result agrees well with the experimental one, which proves the efficiency of the model.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Alkene selenenylation: A comprehensive analysis of relative reactivities, stereochemistry and asymmetric induction, and their comparisons with sulfenylation

A broad perspective of various factors influencing alkene selenenylation has been developed by concurrent detailed analysis of key experimental and theoretical data, such as asymmetric induction, stereochemistry, relative reactivities, and comparison with that of alkene sulfenylation. Alkyl group branching a to the double bond was shown to have the greatest effect on alkene reactivity and the stereochemical outcome of corresponding addition reactions. This is in sharp contrast with other additions to alkenes, which depend more on the degree of substitution on C=C or upon substituent electronic effects. Electronic and steric effects influencing asymmetric induction, stereochemistry, regiochemistry, and relative reactivities in the addition of PhSeOTf to alkenes are compared and contrasted with those of PhSCl.

Experimental Characterization Of Electrical Current Leakage In Poly(Dimethylsiloxane) Microfluidic Devices

Poly(dimethylsiloxane) (PDMS) is usually considered as a dielectric material and the PDMS microchannel wall can be treated as an electrically insulated boundary in an applied electric field. However, in certain layouts of microfluidic networks, electrical leakage through the PDMS microfluidic channel walls may not be negligible, which must be carefully considered in the microfluidic circuit design. In this paper, we report on the experimental characterization of the electrical leakage current through PDMS microfluidic channel walls of different configurations. Our numerical and experimental studies indicate that for tens of microns thick PDMS channel walls, electrical leakage through the PDMS wall could significantly alter the electrical field in the main channel. We further show that we can use the electrical leakage through the PDMS microfluidic channel wall to control the electrolyte flow inside the microfluidic channel and manipulate the particle motion inside the microfluidic channel. More specifically, we can trap individual particles at different locations inside the microfluidic channel by balancing the electroosmotic flow and the electrophoretic migration of the particle.

Design, analysis and implementation of a versatile low level radio frequency system for accelerating cavities

179 p.

Experimental Research On Fatigue Property Of Steel Rubber Vibration Isolator For Offshore Jacket Platform In Cold Environment

Jacket platform is the most widely used offshore platform. Steel rubber vibration isolator and damping isolation system are often used to reduce or isolate the ice-induced and seismic-induced vibrations. The previous experimental and theoretical studies concern mostly with dynamic properties, vibration isolation schemes and vibration-reduction effectiveness analysis. In this paper, the experiments on steel rubber vibration isolator were carried out to investigate the compressive properties and fatigue properties in different low temperature conditions. The results may provide some guidelines for design of steel rubber vibration isolator for offshore platform in a cold environment, and for maintenance and replacement of steel rubber vibration isolator, and also for fatigue life assessment of the steel rubber vibration isolator. (C) 2009 Elsevier Ltd. All rights reserved.

Experimental and finite element studies of a large arch dam

Forced vibration field tests and finite element studies have been conducted on Morrow Point (arch) Dam in order to investigate dynamic dam-water interaction and water compressibility. Design of the data acquisition system incorporates several special features to retrieve both amplitude and phase of the response in a low signal to noise environment. These features contributed to the success of the experimental program which, for the first time, produced field evidence of water compressibility; this effect seems to play a significant role only in the symmetric response of Morrow Point Dam in the frequency range examined. In the accompanying analysis, frequency response curves for measured accelerations and water pressures as well as their resonating shapes are compared to predictions from the current state-of-the-art finite element model for which water compressibility is both included and neglected. Calibration of the numerical model employs the antisymmetric response data since they are only slightly affected by water compressibility, and, after calibration, good agreement to the data is obtained whether or not water compressibility is included. In the effort to reproduce the symmetric response data, on which water compressibility has a significant influence, the calibrated model shows better correlation when water compressibility is included, but the agreement is still inadequate. Similar results occur using data obtained previously by others at a low water level. A successful isolation of the fundamental water resonance from the experimental data shows significantly different features from those of the numerical water model, indicating possible inaccuracy in the assumed geometry and/or boundary conditions for the reservoir. However, the investigation does suggest possible directions in which the numerical model can be improved.

Latent variable models for neural data analysis

The brain is perhaps the most complex system to have ever been subjected to rigorous scientific investigation. The scale is staggering: over 10^11 neurons, each making an average of 10^3 synapses, with computation occurring on scales ranging from a single dendritic spine, to an entire cortical area. Slowly, we are beginning to acquire experimental tools that can gather the massive amounts of data needed to characterize this system. However, to understand and interpret these data will also require substantial strides in inferential and statistical techniques. This dissertation attempts to meet this need, extending and applying the modern tools of latent variable modeling to problems in neural data analysis.

It is divided into two parts. The first begins with an exposition of the general techniques of latent variable modeling. A new, extremely general, optimization algorithm is proposed - called Relaxation Expectation Maximization (REM) - that may be used to learn the optimal parameter values of arbitrary latent variable models. This algorithm appears to alleviate the common problem of convergence to local, sub-optimal, likelihood maxima. REM leads to a natural framework for model size selection; in combination with standard model selection techniques the quality of fits may be further improved, while the appropriate model size is automatically and efficiently determined. Next, a new latent variable model, the mixture of sparse hidden Markov models, is introduced, and approximate inference and learning algorithms are derived for it. This model is applied in the second part of the thesis.

The second part brings the technology of part I to bear on two important problems in experimental neuroscience. The first is known as spike sorting; this is the problem of separating the spikes from different neurons embedded within an extracellular recording. The dissertation offers the first thorough statistical analysis of this problem, which then yields the first powerful probabilistic solution. The second problem addressed is that of characterizing the distribution of spike trains recorded from the same neuron under identical experimental conditions. A latent variable model is proposed. Inference and learning in this model leads to new principled algorithms for smoothing and clustering of spike data.

A dynamical systems analysis of vortex pinch-off

Vortex rings constitute the main structure in the wakes of a wide class of swimming and flying animals, as well as in cardiac flows and in the jets generated by some moss and fungi. However, there is a physical limit, determined by an energy maximization principle called the Kelvin-Benjamin principle, to the size that axisymmetric vortex rings can achieve. The existence of this limit is known to lead to the separation of a growing vortex ring from the shear layer feeding it, a process known as `vortex pinch-off', and characterized by the dimensionless vortex formation number. The goal of this thesis is to improve our understanding of vortex pinch-off as it relates to biological propulsion, and to provide future researchers with tools to assist in identifying and predicting pinch-off in biological flows.

To this end, we introduce a method for identifying pinch-off in starting jets using the Lagrangian coherent structures in the flow, and apply this criterion to an experimentally generated starting jet. Since most naturally occurring vortex rings are not circular, we extend the definition of the vortex formation number to include non-axisymmetric vortex rings, and find that the formation number for moderately non-axisymmetric vortices is similar to that of circular vortex rings. This suggests that naturally occurring vortex rings may be modeled as axisymmetric vortex rings. Therefore, we consider the perturbation response of the Norbury family of axisymmetric vortex rings. This family is chosen to model vortex rings of increasing thickness and circulation, and their response to prolate shape perturbations is simulated using contour dynamics. Finally, the response of more realistic models for vortex rings, constructed from experimental data using nested contours, to perturbations which resemble those encountered by forming vortices more closely, is simulated using contour dynamics. In both families of models, a change in response analogous to pinch-off is found as members of the family with progressively thicker cores are considered. We posit that this analogy may be exploited to understand and predict pinch-off in complex biological flows, where current methods are not applicable in practice, and criteria based on the properties of vortex rings alone are necessary.