The Emotional Integration of Childhood Experience: Physiological, Facial Expressive, and Self-Reported Emotional Response During the Adult Attachment Interview.

Attachment researchers claim that individual differences in how adults talk about their early memories reflect qualitatively distinct organizations of emotion regarding childhood experiences with caregivers. Testing this assumption, the present study examined the relationship between attachment dimensions and physiological, facial expressive, as well as self-reported emotional responses during the Adult Attachment Interview (AAI). Consistent with theoretical predictions, more prototypically secure adults behaviorally expressed and reported experiencing emotion consistent with the valence of the childhood events they described. Insecure adults also showed distinctive and theoretically anticipated forms of emotional response: Dismissing participants evidenced increased electrodermal activity during the interview, a sign of emotional suppression, whereas preoccupied adults showed reliable discrepancies between the valence of their inferred childhood experiences and their facial expressive as well as reported emotion during the AAI. Results substantiate a case that the AAI reflects individual differences in emotion regulation that conceptually parallel observations of attachment relationships in infancy. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Control of Variation by Reward Probability.

Two bar-press experiments with rats tested the rule that reducing expectation of reward increases the variation from which reward selects. Experiment 1 used a discrete-trial random-interval schedule, with trials signaled by light or sound. One signal always ended with reward; the other signal ended with reward less often. The 2 signals were randomly mixed. Bar-press duration (how long the bar was held down) varied more during the signal with the lower probability of reward. Experiment 2 closely resembled Experiment 1 but used a random-ratio schedule rather than a random-interval schedule. Again, bar-press duration varied more during the signal with the lower probability of reward. The results support the rule--the first well-controlled comparisons to do so. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A new second-order method for blind signal separation from dynamic mixtures

This paper presents a new approach to separate colored stationary signals mixed by convolutive channels. A cost function is proposed by employing linear constraint to the demixing vectors. The linear constraint is shown to be sufficient for avoiding trivial solution. The minimization of the cost function is performed using the Lagrangian method. Simulation results demonstrate the performance of the algorithm.     

Cryptography during the French and American Wars in Vietnam

After Vietnam’s Declaration of Independence on 2 September 1945, the country had to suffer through two long, brutal wars, first against the French and then against the Americans, before finally becoming a unified country free of colonial domination in 1975. The authors’ purpose is to examine the role of cryptography in those two wars. Despite the far greater technological resources of their opponents, the communications intelligence specialists of the Vi?t Minh, the National Liberation Front, and the Democratic Republic of Vietnam had considerable success in both protecting Vietnamese communications and acquiring tactical and strategic secrets from the enemy. Perhaps surprisingly, in both wars there was a balance between the sides. Generally speaking, cryptographic knowledge and protocol design were at a high level at the central commands, but deployment for tactical communications in the field was difficult, and there were many failures on all sides.     

On the problem of optimal estimation of balanced and symmetric three-phase signals

This paper revisits the fundamental problem of optimal estimation of the magnitude and phase of balanced and symmetric three-phase voltage or current signals. We analyze and compare various setups for the corresponding optimal Kalman filter, including the direct use of three-phase measurements, as well as measurements subjected to the Clarke transform in real or complex form. One contribution is to show that the standard practice of disregarding the transformed zero-component of the Clarke transformed three-phase signal almost always leads to a sub-optimal performance of the Kalman estimator. Our analysis extends to show that the closely related complex Kalman estimator is also sub-optimal and that optimal performance can be recovered if the zero-component is made available to the filter provided that the noises are properly characterized. These results are illustrated by means of simple numerical examples, which also highlight the importance of correctly modeling the noise characteristics if a real or complex form of the Clarke transformation is to be used. We conclude the paper with a unified set of guidelines or best practices regarding the use of optimal Kalman estimators for balanced and symmetric three-phase signals.     

Age‐Related Physiological Responses to Working in Deep Cold

Professional order‐picking in deep cold‐storage depots (i.e., storing, picking, and dispatching of frozen groceries) requires employees to remain working at temperatures of approximately ?24°C for a whole workday. Actually, a well‐regulated organization of working times and breaks has not been established, and no competent knowledge exists as to whether an additional age‐differentiated organization is necessary. To assess the physiological effects while working in deep cold, 30 male subjects (Ss) were classified into two age groups (20‐ to 35‐year‐olds and 40‐ to 65‐year‐olds). In whole workday tests, possible age‐dependent effects on the strain were measured to guarantee the preservation of the subjects' ability to work in the long run. For the objectification of the physiological strain, heart rate and skin surface temperature were registered continuously, and blood pressure and body core temperature were measured and recorded discretely during cold exposures of 80, 100, and 120 min, separated by 20‐min warming‐up breaks. Systematic differences of blood pressure could not be found. The heart rate values indicated a high physiological strain for both younger and older Ss, with work‐related increases above the resting level of 30 bpm and more. Due to increases over time, endurance level sometimes was exceeded. Age‐related differences in skin temperature could not be recorded, but the ability to generate heat deteriorated with advancing age, which is shown by more substantial decreases of body core temperature in the group of 40‐ to 65‐year‐olds taken at the tympanum. Regarding physiological strain brought about by maximum heart rate decreasing with age and declined heat generation, correspondingly adapted workday break regimes have to be provided for older employees to ensure their ability to work in the long run. © 2011 Wiley Periodicals, Inc.     

An integrated alcoholic index using tunable-Q wavelet transform based features extracted from EEG signals for diagnosis of alcoholism

Alcoholism affects the structure and functioning of brain. Electroencephalogram (EEG) signals can depict the state of brain. The EEG signals are ensemble of various neuronal activity recorded from different scalp regions having different characteristics and very low magnitude in microvolts. These factors make human interpretation difficult and time consuming to analyze these signals. Moreover, these highly varying EEG signals are susceptible to inter/intra variability errors. So, a Computer-Aided Diagnosis (CAD) can be used to identify the alcoholic and normal subjects accurately. However, these EEG signals exhibit nonlinear and non-stationary properties. Therefore, it needs much effort in deciphering the diagnostic evidence from them using linear time and frequency-domain methods. The nonlinear parameters together with time-frequency/scale domain methods can help to detect tiny changes in these signals. The correntropy is nonlinear indicator which characterizes the dynamic behavior of EEG signals in time-scale domain. In this paper, we present a new way for diagnosis of alcoholism using Tunable-Q Wavelet Transform (TQWT) based features derived from EEG signals. The feature extraction is performed using TQWT based decomposition and extracted Centered Correntropy (CC) from the forth decomposed detail sub-band. The Principal Component Analysis (PCA) is used for feature reduction followed by Least Squares-Support Vector Machine (LS-SVM) for classifying normal and alcoholic EEG signals. In order to make sure reliable classification performance, 10-fold cross-validation scheme is adopted. Our proposed system is able to diagnose the alcoholic and normal EEG signals, with an average accuracy of 97.02%, sensitivity of 96.53%, specificity of 97.50% and Matthews correlation coefficient of 0.9494 for Q-factor (Q) varying between 3 and 8 using Radial Basis Function (RBF) kernel function. Also, we have established a novel Alcoholism Risk Index (ARI) using three clinically significant features to discriminate the given classes by means of a single number. This system can be used for automated diagnosis and monitoring of alcoholic subjects to evaluate the effect of treatment.     

Human interaction with robotic systems: performance and workload evaluations

Abstract

We first tested the effect of differing tactile informational forms (i.e. directional cues vs. static cues vs. dynamic cues) on objective performance and perceived workload in a collaborative human–robot task. A second experiment evaluated the influence of task load and informational message type (i.e. single words vs. grouped phrases) on that same collaborative task. In both experiments, the relationship of personal characteristics (attentional control and spatial ability) to performance and workload was also measured. In addition to objective performance and self-report of cognitive load, we evaluated different physiological responses in each experiment. Results showed a performance–workload association for directional cues, message type and task load. EEG measures however, proved generally insensitive to such task load manipulations. Where significant EEG effects were observed, right hemisphere amplitude differences predominated, although unexpectedly these latter relationships were negative. Although EEG measures were partially associated with performance, they appear to possess limited utility as measures of workload in association with tactile displays.

Practitioner Summary: As practitioners look to take advantage of innovative tactile displays in complex operational realms like human–robotic interaction, associated performance effects are mediated by cognitive workload. Despite some patterns of association, reliable reflections of operator state can be difficult to discern and employ as the number, complexity and sophistication of these respective measures themselves increase.     

Discriminant analysis of multivariate time series: Application to diagnosis based on ECG signals

In analysing ECG data, the main aim is to differentiate between the signal patterns of healthy subjects and those of individuals with specific heart conditions. We propose an approach for classifying multivariate ECG signals based on discriminant and wavelet analyses. For this purpose we use multiple-scale wavelet variances and wavelet correlations to distinguish between the patterns of multivariate ECG signals based on the variability of the individual components of each ECG signal and on the relationships between every pair of these components. Using the results of other ECG classification studies in the literature as references, we demonstrate that our approach applied to 12-lead ECG signals from a particular database compares favourably. We also demonstrate with real and synthetic ECG data that our approach to classifying multivariate time series out-performs other well-known approaches for classifying multivariate time series.