Memory distrust is related to memory errors, self-esteem, and personality

Research on memory distrust and nonbelieved memory (NBM) both stress the importance of belief in memory but no previous research has brought these fields together. In the present study, we examined how trait memory distrust is associated with false memory and NBM, self-esteem as well as personality traits. Through two studies (N-1 = 280, N-2 = 77, we found that higher memory distrust was associated with higher false memory as well as NBM frequency, and lower self-esteem. As for personality traits, people who were high on agreeableness, openness, or conscientiousness had lower memory distrust. Explorative mediation analyses showed significant indirect effects of self-esteem on false memory (Study 1a and Study 2) and NBM (Study 2) through memory distrust. We conclude that memory distrust could be conducive to the formation of false memory and NBM under social conditions where one's memory is challenged

On-Line Validation of the Measurement Uncertainty of a Sensor using Wavelet Transforms

The measurement uncertainty of a sensor as a measure of its accuracy is normally derived through static analysis. Conventionally, uncertainty analysis is conducted during the design and development stage of a sensor to select appropriate components and measurement techniques, as well as interpreting its experimental data. The demand for quality assurance by measurement is now increasing. It is therefore desirable to develop a means of assessing the measurement uncertainty of a sensor during its operation on a process plant. A new method using wavelet transforms for the validation of the measurement uncertainty is proposed. Analytical results show that the process variable being measured by the sensor can be separated from a noisy raw sensor signal using its wavelet transforms, provided that the process variable is represented in terms of a limited-degree polynomial function. Unlike the conventional approach to uncertainty calculation, which requires 'average' or 'typical' values substituted for parameters which may vary, the proposed method uses only the latest output of the sensor regardless of the variations of the parameters, and thus can be applied on an online continuous basis. Experimental results obtained from a differential-pressure flow sensor on a water flow test rig confirm the effectiveness of the proposed method

Examining the Associations Between Nonbelieved Memories and Memory Distrust, Self-Esteem, and Rumination

When beliefs in autobiographical memories are reduced while recollections remain relatively intact, a phenomenon termed nonbelieved memories (NBMs) unfolds. The current preregistered study (N = 104) used a 3-week longitudinal design to investigate the relationships between the frequency of recalled NBMs, memory distrust, rumination over autobiographical events, and self-esteem. Our analyses showed that memory distrust was a positive predictor for the initial recall of NBMs during the past 2 months at Time 1, but not for the follow-up recalls of NBMs during the past week at Times 2-4. Exploratory analyses showed that, at Time 1, self-esteem was negatively associated with the total number of NBMs. Furthermore, the tendency to report involuntary memories and rumination over memories was positively associated with the total number of NBMs. In addition, (in)voluntary autobiographical memory recall tendency was also a significant positive predictor for the total number of NBMs at Times 2-4. Our study is one of the first to show that NBMs might be uniquely tied to specific individual markers

PM source apportionment and health effects. 3. Investigation of inter-method variations in associations between estimated source contributions of PM2.5 and daily mortality in Phoenix, AZ.

As part of an EPA-sponsored workshop to investigate the use of source apportionment in health effects analyses, the associations between the participant's estimated source contributions of PM2.5 for Phoenix, AZ for the period from 1995-1997 and cardiovascular and total nonaccidental mortality were analyzed using Poisson generalized linear models (GLM). The base model controlled for extreme temperatures, relative humidity, day of week, and time trends using natural spline smoothers. The same mortality model was applied to all of the apportionment results to provide a consistent comparison across source components and investigators/methods. Of the apportioned anthropogenic PM2.5 source categories, secondary sulfate, traffic, and copper smelter-derived particles were most consistently associated with cardiovascular mortality. The sources with the largest cardiovascular mortality effect size were secondary sulfate (median estimate=16.0% per 5th-to-95th percentile increment at lag 0 day among eight investigators/methods) and traffic (median estimate=13.2% per 5th-to-95th percentile increment at lag 1 day among nine investigators/methods). For total mortality, the associations were weaker. Sea salt was also found to be associated with both total and cardiovascular mortality, but at 5 days lag. Fine particle soil and biomass burning factors were not associated with increased risks. Variations in the maximum effect lag varied by source category suggesting that past analyses considering only single lags of PM2.5 may have underestimated health impact contributions at different lags. Further research is needed on the possibility that different PM2.5 source components may have different effect lag structure. There was considerable consistency in the health effects results across source apportionments in their effect estimates and their lag structures. Variations in results across investigators/methods were small compared to the variations across source categories. These results indicate reproducibility of source apportionment results across investigative groups and support applicability of these methods to effects studies. However, future research will also need to investigate a number of other important issues including accuracy of results. © 2006 Nature Publishing Group All rights reserved