The Mnemonic Tuning for Contamination: A Replication and Extension Study Using More Ecologically Valid Stimuli

To face threats posed by pathogens, natural selection designed the Behavioral Immune System, which orchestrates several responses aimed to prevent contact with pathogens. Memory seems to augment this system. Using line drawings of objects, previous studies found that objects described as having been touched by sick people were better remembered than those described as having been touched by healthy people. The current work was designed to replicate and extend these initial studies using more ecologically-valid stimuli—photographs of real objects being held by hands. These photographs were shown along with descriptors (Experiment 1a) or faces (Experiment 1b) denoting the health status of the person whose hands were holding the objects. Experiments 2 and 3 used, as cues of contamination, dirty hands covered with a substance described as being vomit and diarrhea, respectively. Experiment 3 also investigated the need for a fitness-relevant context for the mnemonic effect to occur. In all experiments, stimuli were presented individually on the screen with the “contamination cue.” During encoding participants had to identify whether each object had been touched by a sick or a healthy person. The results of the final surprise free recall tasks replicated those previously reported: performance was enhanced for objects encoded as potential sources of contamination. Furthermore, the results of the last study reinstate the importance of fitness-relevance for the effect to occur. These results establish the generality of the contamination effect previously found, now using more ecologically-valid stimuli.

Addressing the contamination issue in collaborative consumption of fashion: does ownership type of shared goods matter?

PurposeOne of the major concerns in the emerging phenomenon of collaborative consumption (CC) is the issue of contamination (i.e. feeling “grossed out” when sharing items with others). Guided by the law of contagion and the consumer contamination effect theory, this research investigated the ways in which companies can manipulate in order to reduce the negative contamination when renting or purchasing used fashion items from others. Specifically, this research examines this issue of contamination through the ownership type of the shared goods (e.g. corporate-ownership or B2C exchange, and consumer-ownership or C2C exchange) and its effect on consumers' CC intentions in two distinct sharing contexts (i.e. rental and secondhand purchase).Design/methodology/approachA total of 181 American female consumers were assigned to an experimental CC scenario, and their rental/secondhand purchase intentions were compared through ANCOVA analysis.FindingsIn both rental and secondhand purchase contexts, consumers displayed greater intentions to shop in B2C setting (i.e. corporate-ownership) with no direct contact with the previous owner, than in C2C setting (i.e. consumer-ownership) with a greater association with the previous owner and the shared items. Such inclination was more prevalent when purchasing a shirt than a handbag, suggesting that consumers feel more grossed out when there is greater physical contact with the shared item.Originality/valueThe findings of the study suggest a possible solution to alleviate the contamination effect, and the discovery of the degree of contact as a moderator provides new insight into contamination research.

Cross-contamination effect on turbulence spectra from Doppler beam swinging wind lidar

Turbulence velocity spectra are of high importance for the estimation of loads on wind turbines and other built structures, as well as for fitting measured turbulence values to turbulence models. Spectra generated from reconstructed wind vectors of Doppler beam swinging (DBS) wind lidars differ from spectra based on one-point measurements. Profiling wind lidars have several characteristics that cause these deviations, namely cross-contamination between the three velocity components, averaging along the lines of sight and the limited sampling frequency. This study focuses on analyzing the cross-contamination effect. We sample wind data in a computer-generated turbulence box to predict lidar-derived turbulence spectra for three wind directions and four measurement heights. The data are then processed with the conventional method and with the method of squeezing that reduces the longitudinal separation distances between the measurement locations of the different lidar beams by introducing a time lag into the data processing. The results are analyzed and compared to turbulence velocity spectra from field measurements with a Windcube V2 wind lidar and ultrasonic anemometers as reference. We successfully predict lidar-derived spectra for all test cases and found that their shape is dependent on the angle between the wind direction and the lidar beams. With conventional processing, cross-contamination affects all spectra of the horizontal wind velocity components. The method of squeezing improves the spectra to an acceptable level only for the case of the longitudinal wind velocity component and when the wind blows parallel to one of the lines of sight. The analysis of the simulated spectra described here improves our understanding of the limitations of turbulence measurements with DBS profiling wind lidar.

Forward modeling of galaxy kinematics in slitless spectroscopy

Context. Slitless spectroscopy has long been considered a complicated and confused technique. Nonetheless, with the advent of Hubble Space Telescope (HST) instruments, characterized by a low sky background level and a high spatial resolution (most notably WFC3), slitless spectroscopy has become an adopted survey tool to study galaxy evolution from space. Aims. We aim to investigate its application to single-object studies to measure not only redshift and integrated spectral features, but also spatially-resolved quantities such as galaxy kinematics. Methods. We built a complete forward model to quantitatively compare actual slitless observations. This model depends on a simplified thin cold disk galaxy description – including flux-distribution, intrinsic-spectrum, and kinematic parameters – and on the instrumental signature. It is used to improve redshifts and constrain basic rotation curve parameters, meaning the plateau velocity v0 (in km s−1) and the central velocity gradient w0 (in km s−1 arcsec−1). Results. The model is tested on selected observations from 3D-HST and GLASS surveys to estimate redshift and kinematic parameters on several galaxies measured with one or more roll angles. Conclusions. Our forward approach makes it possible to mitigate the self-contamination effect, a primary drawback of slitless spectroscopy, and therefore has the potential to increase precision on redshifts. In a limited sample of well-resolved spiral galaxies from HST surveys, it is possible to significantly constrain galaxy rotation curve parameters. This proof-of-concept work is promising for future large slitless spectroscopic surveys, such as Euclid and WFIRST.

The Investigation of Oven Contamination and Corresponding Methodology

Contamination and particle reduction are critical to semiconductor process control. Lots of failure analysis had been focused on finding the root cause of the particle and contamination. The particle and contamination effect were also easily found in circuit probing (CP) process, and therefore induced yield loss and wafer scrap. In the first part of this paper, an oven contamination case was studied. The second part of this paper focus on oven contamination monitoring. In the beginning, a die flying failure was papered at the stage of blue tape and die sawing. This event clearly indicated bad adhesion between die and plastic tape. This bad adhesion was suspected to be a particle/contamination layer formed on bad die surface. Three failure analysis (FA) approaches were performed to find out the root cause. The SEM/EDS result identified the main elements of big particle, but that is insufficient to identify the root cause. The OM/FTIR, however, showed the contamination may be related to polydimethylsiloxane (PDMS). The last failure analysis was the time of fly Secondary Ion Mass Spectrometer (TOF-SIMS), the result confirmed that there was a thin PDMS layer formed on the contaminated bad die surface. The high temperature CP process induced PDMS is believed to be the contamination root cause. In order to prevent the oven contamination event, a methodology based on contact angle and wettability of Si matrix sample was set up for regular monitor in oven operation. The details of contact angle test (CAT) sample preparation, measurement and analysis results were also discussed in this paper.