Understanding the role of impulsivity and externalizing psychopathology in alcohol abuse: Application of the UPPS Impulsive Behavior Scale.

The present study explores the relation among 4 personality traits associated with impulsive behavior and alcohol abuse. Personality traits were measured using the 4 subscales of the UPPS Impulsive Behavior Scale (UPPS: S. P. Whiteside & D. R. Lynam. 2001). The UPPS and measures of psychopathology were administered to clinical samples of alcohol abusers high in antisocial personality traits (AAPD), alcohol abusers low in antisocial personality traits (AA), and a control group (total N = 60). Separate analyses of variance indicated that AAPDs had significant elevations on all 4 UPPS scales, whereas the AAs and controls differed only on the Urgency subscale. However, when controlling for psychopathology, group differences on the UPPS scales disappeared. The results suggest that personality traits related to impulsive behavior are not directly related to alcohol abuse but rather are associated with the elevated levels of psychopathology found in a subtype of alcohol abusers. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Position synchronization of multiple motion axes with adaptive coupling control

A new control approach to position synchronization of multiple motion axes is developed, by incorporating cross-coupling technology into adaptive control architecture. The control strategy is to stabilize position tracking of each axis while synchronizing its motion with other axes’ motions so that differential position errors amongst axes converge to zero. The proposed adaptive controller and parameter estimator employ coupling control by feeding back position errors and differential position errors, and have been realized to guarantee asymptotic convergence to zero of both position and synchronization errors. Simulations conducted on a multi-axis motion control system demonstrate the effectiveness of the method.     

Youth gambling behaviors: An examination of the role of resilience.

The study of resilient children has overturned many deficit-focused models concerning the ontogenesis of children raised in adversity. This study explored the relationship between risk and protective factors, resilience, and youth gambling behavior. More specifically, this study examined the relative contribution of various risk and protective domains in relation to problem gambling behavior and examined whether youth identified as resilient (high risk exposure- high internalized protection) were as likely as those identified as vulnerable (high risk exposure-low internalized protection) to engage in excessive gambling behavior. The sample consisted of 1,273 students ages 12 to 19. The findings demonstrated that risk and protective factors each provide a unique contribution to the prediction model of gambling problems. Resilient and vulnerable youth differed significantly in their self-reported gambling severity. As well, resilient youth were not statistically distinguishable from low-risk exposure groups in terms of their gambling severity. Findings are interpreted with respect to resilience and prevention research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Grand theories of personality cannot be integrated.

Comments on the original article "A New Big Five: Fundamental Principles for an Integrative Science of Personality," by Dan P. McAdams and Jennifer L. Pals (see record 2006-03947-002). McAdams and Pals (April 2006) presented a new model to integrate the field of personality psychology. Cultural and evolutionary factors interact with an individual's basic traits, characteristic adaptations, and life narratives, which in turn are linked to roles, demands, and behaviors. The current authors welcome McAdams and Pals's (2006) model for providing a way to integrate much of the previously disparate empirical findings in personality psychology. However, the current authors also think that McAdams and Pals (2006) overstated the inclusiveness of the model, and more generally, the current authors dispute their assertion that the grand theories of personality can be integrated within a single model. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Patterns of discrimination in hiring job applicants with disabilities: The role of disability type, job complexity, and public contact.

Objective: To evaluate the effects of disability type, job complexity, and public contact on hiring decisions. Design and Participants: An Americans With Disabilities Act (ADA; 1990) fact sheet and matched resumes with vocational and medical histories including chronic mental illness, developmental disability, closed head injury, and back injury were provided to 295 undergraduate business-related majors, who rated the applicants' suitability for 2 job positions and work shifts. Results: Findings indicated disparities in ratings of employability as a function of disability type. Paired comparisons yielded complementary findings, with effects of disability type and Disability Type × Job Complexity, but no effects of public contact. Conclusions: Stereotyping and discrimination in employment decisions apparently persist, more than 10 years after the ADA. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Nonlinear model predictive control with polytopic invariant sets

Ellipsoidal invariant sets have been widely used as target sets in model predictive control (MPC). These sets can be computed by constructing appropriate linear difference inclusions together with additional constraints to ensure that the ellipsoid lies within a given inclusion polytope. The choice of inclusion polytope has a significant effect on the size of the target ellipsoid, but the optimal inclusion polytope cannot in general be computed systematically. This paper shows that use of polytopic invariant sets overcomes this difficulty, allowing larger stabilizable sets without loss of performance. In the interests of online efficiency, consideration is focused on interpolation-based MPC.     

Frequency domain solution to delay-type Nehari problem

This paper generalizes the frequency-domain results on the delay-type Nehari problem in the stable case to the unstable case. The solvability condition of the delay-type Nehari problem is formulated in terms of the nonsingularity of three matrices. The optimal value γ_opt is the maximal γ∈(0,∞) such that one of the three matrices becomes singular. All sub-optimal compensators are parameterized in a transparent structure incorporating a modified Smith predictor.     

EM procedures using mean field-like approximations for Markov model-based image segmentation

Image segmentation using Markov random fields involves parameter estimation in hidden Markov models for which the EM algorithm is widely used. In practice, difficulties arise due to the dependence structure in the models and approximations are required. Using ideas from the mean field approximation principle, we propose a class of EM-like algorithms in which the computation reduces to dealing with systems of independent variables. Within this class, the simulated field algorithm is a new stochastic algorithm which appears to be the most promising for its good performance and speed, on synthetic and real image experiments.     

Determination of vitality from a non-invasive biomedical measurement for use in fingerprint scanners

Fingerprints are the oldest and most widely used biometrics for personal identification. Unfortunately, it is usually possible to deceive automatic fingerprint identification systems by presenting a well-duplicated synthetic or dismembered finger. This paper introduces one method to provide fingerprint vitality authentication in order to solve this problem. Detection of a perspiration pattern over the fingertip skin identifies the vitality of a fingerprint. Mapping the two-dimensional fingerprint images into one-dimensional signals, two ensembles of measures, namely static and dynamic measures, are derived for classification. Static patterns as well as temporal changes in dielectric mosaic structure of the skin, caused by perspiration, demonstrate themselves in these signals. Using these measures, this algorithm quantifies the sweating pattern and makes a final decision about vitality of the fingerprint by a neural network trained by examples.