Mixed anaclitic-introjective psychopathology in treatment-resistant inpatients undergoing psychoanalytic psychotherapy.

Utilizing data from the Riggs-Yale Project, 45 male and 45 female 18-29-year-old treatment-resistant inpatients undergoing intensive psychoanalytically oriented treatment were studied. Twenty-seven mixed-type anaclitic-introjective inpatients were compared with 29 "pure" anaclitic and 34 "pure" introjective inpatients. At intake, mixed-type inpatients were more clinically impaired (i.e., were more symptomatic, cognitively impaired, and thought disordered) and more vulnerable (i.e., less accurate object representations and more frequently used maladaptive defense mechanisms) in comparison with clearly defined anaclitic and introjective patients. Mixed-type patients, however, improved significantly more in the course of psychoanalytically oriented treatment, in terms of clinical functioning (i.e., symptoms, cognitive functioning) and psychological vulnerability (i.e., utilization of more adaptive defense mechanisms). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Depressive symptoms erode self-esteem in severe mental illness: A three-wave, cross-lagged study.

Vulnerability, scar, and reciprocal-relations models of depressive symptoms and self-esteem were compared among people with severe mental illness (SMI; N=260) participating in a partnership-based intervention study. Assessments were conducted at baseline, midway through the intervention (after 4 months), and at termination (after 9 months). Cross-lagged, structural equation modeling analyses revealed that participants' baseline depressive symptoms predicted a decrease in self-esteem in the first 4 months but not in the subsequent 5 months of participation. Exploratory regression analyses indicated that improved social functioning buffered this deleterious effect of depressive symptoms. These findings, which are consistent with the scar model, highlight the fragile nature of the self and the importance of social functioning in recovery from SMI. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Role of perfectionism and personality disorder features in response to brief treatment for depression.

Using data from the Treatment of Depression Collaborative Research Program (TDCRP), the authors compared the role of patients' perfectionism and features of personality disorder (PD) in the outcome of brief treatment for depression. Data were extracted as to patients' intake levels of symptoms; perfectionism; and PD features, measured as continuous variables, as well as their symptoms at termination; their contribution to the therapeutic alliance; and their satisfaction with social relations. Poorer therapeutic outcome was demonstrated for patients with elevated levels of perfectionism and odd-eccentric and depressive PD features. Patients' contribution to therapeutic alliance and satisfaction with social relations were predicted by perfectionism but not by PD features. Results highlight the central role played by patients' personality in the course of brief treatment for depression. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

EON: a component-based approach to automation of protocol-directed therapy

Provision of automated support for planning protocol-directed therapy requires a computer program to take as input clinical data stored in an electronic patient-record system and to generate as output recommendations for therapeutic interventions and laboratory testing that are defined by applicable protocols. This paper presents a synthesis of research carried out at Stanford University to model the therapy-planning task and to demonstrate a component-based architecture for building protocol-based decision-support systems. We have constructed general-purpose software components that (1) interpret abstract protocol specifications to construct appropriate patient-specific treatment plans; (2) infer from time-stamped patient data higher-level, interval-based, abstract concepts; (3) perform time-oriented queries on a time-oriented patient database; and (4) allow acquisition and maintenance of protocol knowledge in a manner that facilitates efficient processing both by humans and by computers. We have implemented these components in a computer system known as EON. Each of the components has been developed, evaluated, and reported independently. We have evaluated the integration of the components as a composite architecture by implementing T-HELPER, a computer-based patient-record system that uses EON to offer advice regarding the management of patients who are following clinical trial protocols for AIDS or HIV infection. A test of the reuse of the software components in a different clinical domain demonstrated rapid development of a prototype application to support protocol-based care of patients who have breast cancer.     

Towards identifying the roll motion parameters of a motorcycle simulator

This study aimed at identifying the roll motion parameters of a motorcycle simulator prototype. Experienced motorcyclists tuned the angular physical movement of the mock-up and that of the visual scene to achieve an optimal riding experience during curves. The participants exceeded the rolling angles that would be required in real-world riding, while avoiding leaning the mock-up beyond 10°. In addition, they were more influenced by the speed of the virtual motorcycle than by road curvature, especially in a wide field of view. Heterogeneity was found in the roll applied to the visual scene. The overall patterns suggest that at least when washout is not applied to remove the side forces that in real-world riding are compensated by a centrifugal force, greater roll of the visual at the expense of the mock-up is mandatory to avoid performance biases that might be enhanced due to fear of falling off the simulator. Future roll motion models must take into consideration factors such as riding postures, which might not only influence the forces operating on the rider-motorcycle system, but also how motorcyclists perceive the visual world.     

Using aspects for testing of embedded software: experiences from two industrial case studies

Aspect-oriented software testing is emerging as an important alternative to conventional procedural and object-oriented testing techniques. This paper reports experiences from two case studies where aspects were used for the testing of embedded software in the context of an industrial application. In the first study, we used code-level aspects for testing non-functional properties. The methodology we used for deriving test aspect code was based on translating high-level requirements into test objectives, which were then implemented using test aspects in AspectC++. In the second study, we used high-level visual scenario-based models for the test specification, test generation, and aspect-based test execution. To specify scenario-based tests, we used a UML2-compliant variant of live sequence charts. To automatically generate test code from the models, a modified version of the S2A Compiler, outputting AspectC++ code, was used. Finally, to examine the results of the tests, we used the Tracer, a prototype tool for model-based trace visualization and exploration. The results of the two case studies show that aspects offer benefits over conventional techniques in the context of testing embedded software; these benefits are discussed in detail. Finally, towards the end of the paper, we also discuss the lessons learned, including the technological and other barriers to the future successful use of aspects in the testing of embedded software in industry.     

Incremental application of knowledge to continuously arriving time-oriented data

In our previous work, we introduced a computational architecture that effectively supports the tasks of continuous monitoring and of aggregation querying of complex domain meaningful time-oriented concepts and patterns (temporal abstractions), in environments featuring large volumes of continuously arriving and accumulating time-oriented raw data. Examples include provision of decision support in clinical medicine, making financial decisions, detecting anomalies and potential threats in communication networks, integrating intelligence information from multiple sources, etc. In this paper, we describe the general, domain-independent but task-specific problem-solving method underling our computational architecture, which we refer to as incremental knowledge-based temporal abstraction (IKBTA). The IKBTA method incrementally computes temporal abstractions by maintaining persistence and validity of continuously computed temporal abstractions from arriving time-stamped data. We focus on the computational framework underlying our reasoning method, provide well-defined semantic and knowledge requirements for incremental inference, which utilizes a logical model of time, data, and high-level abstract concepts, and provide a detailed analysis of the computational complexity of our approach.     

Modifying continuous-time random walks to model finite-size particle diffusion in granular porous media

The continuous-time random walk (CTRW) model is useful for alleviating the computational burden of simulating diffusion in actual media. In principle, isotropic CTRW only requires knowledge of the step-size, \(P_l\), and waiting-time, \(P_t\), distributions of the random walk in the medium and it then generates presumably equivalent walks in free space, which are much faster. Here we test the usefulness of CTRW to modelling diffusion of finite-size particles in porous medium generated by loose granular packs. This is done by first simulating the diffusion process in a model porous medium of mean coordination number, which corresponds to marginal rigidity (the loosest possible structure), computing the resulting distributions \(P_l\) and \(P_t\) as functions of the particle size, and then using these as input for a free space CTRW. The CTRW walks are then compared to the ones simulated in the actual media. In particular, we study the normal-to-anomalous transition of the diffusion as a function of increasing particle size. We find that, given the same \(P_l\) and \(P_t\) for the simulation and the CTRW, the latter predicts incorrectly the size at which the transition occurs. We show that the discrepancy is related to the dependence of the effective connectivity of the porous media on the diffusing particle size, which is not captured simply by these distributions. We propose a correcting modification to the CTRW model—adding anisotropy—and show that it yields good agreement with the simulated diffusion process. We also present a method to obtain \(P_l\) and \(P_t\) directly from the porous sample, without having to simulate an actual diffusion process. This extends the use of CTRW, with all its advantages, to modelling diffusion processes of finite-size particles in such confined geometries.