Relationship of psychosocial and background variables to older adults' end-of-life decisions.

Aims were to determine acceptability of a full range of end-of-life decision options and identify related variables; 388 Black and White older adults ages 60–100 responded to 17 decision situations depicting terminal and nonterminal conditions with a very low quality of life, rating the acceptability of 7 end-of-life options per decision situation, and completed demographic, health, and psychosocial measures. Despite low quality of life, maintaining life (striving to live and seeking treatment) was the most acceptable option, but a significant minority of participants wished to end life (suicide, assisted suicide, or euthanasia) and a moderate number wished to defer the decision to others. In hierarchical regressions, psychosocial variables (religiosity, values, fear of death, etc.) contributed significantly (p?     

Locus of control and patient role adjustment of the elderly in acute-care hospitals.

Felton and Kahana's (1974) conclusion that patients with external locus of control beliefs were better adjusted in institutions was reexamined in a high-constraint acute-care hospital. Subjects were 105 patients aged 60–93. The Multidimensional Health Locus of Control (MHLC) scales were used to measure locus of control, and eight staff-rating items measured hospital adjustment. Also, the Loss of Independence subscale of the Hospital Stress Rating Scale was used to indicate perceived institutional constraint. The three MHLC scales correlated weakly with adjustment, and each contributed significantly in multiple regression. Those patients who perceived greater constraint were more poorly adjusted. Those with stronger beliefs that powerful others control health outcomes perceived less constraint in the hospital situation, whereas those with stronger internal control beliefs perceived greater constraint. Beliefs in chance were unrelated. Findings are related to concepts of primary and secondary control. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A service-based architecture for dynamically reconfigurable workflows

In the last few years, business process management systems have been employed for handling information systems of ever increasing complexity. As a consequence, the adoption of modelling languages enabling smooth and seamless transitions among the various phases of the process lifecycle, the ability of exploiting coordination schema over distributed execution contexts and the support for dynamic evolution and reconfiguration have become software engineering issues of great importance. This paper proposes the use of PN-Engine, a decentralized Petri nets execution engine, as a business process enactment engine. PN-Engine, which is based on the Jini service architecture, supports the decentralized execution of process models specified as Petri nets (PNs) enhanced with modular constructs and offers suitable mechanisms for dealing with the aforementioned design issues. PN-Engine allows to deploy and enact a new version of an existing process model without requiring the stopping/removal of older instances that are still running. The paper presents a novel approach enabling a decentralized migration procedure where concurrent portions of older instances migrate asynchronously to the new process model. Advantages of the proposed approach are demonstrated by means of an example concerning a workflow for a wine-production process.     

Q-Learning: computation of optimal Q-values for evaluating the learning level in robotic tasks

A problem related to the use of reinforcement learning (RL) algorithms on real robot applications is the difficulty of measuring the learning level reached after some experience. Among the different RL algorithms, the Q-learning is the most widely used in accomplishing robotic tasks. The aim of this work is to a priori evaluate the optimal Q-values for problems where it is possible to compute the distance between the current state and the goal state of the system. Starting from the Q-learning updating formula the equations for the maximum Q-weights, for optimal and non-optimal actions, have been computed considering delayed and immediate rewards. Deterministic and non deterministic grid-world environments have been also considered to test in simulations the obtained equations. Besides the convergence rates of the Q-learning algorithm have been compared using different learning rate parameters.     

Distributed simulation of modular time Petri nets: An approach and a case study exploiting temporal uncertainty

This paper proposes an approach to modular modelling and simulation of complex time-critical systems. The modelling language is represented by Merlin and Farber’s Time Petri Nets (TPNs) augmented with inhibitor arcs and modular constructs borrowed from the Petri Net Markup Language (PNML) interchange format. Analysis techniques depend on Temporal Uncertainty Time Warp (TUTW), a time warp algorithm capable of exploiting temporal uncertainty in general optimistic simulations over a networked context. A key feature of the approach is the fact that TPN models naturally exhibit a certain degree of temporal uncertainty which the TUTW control engine can exploit to achieve good speedup without a loss in the accuracy of the simulation results. The developed TUTW/TPN kernel is demonstrated by modelling and simulation of a real-time system example.A preliminary version of this paper was presented at 38th SCS Annual Simulation Symposium, April 4–6, 2005, San Diego (CA), IEEE Computer Society, pp. 233–240. Franco Cicirelli achieved a PhD in computer science from the University of Calabria (Unical), DEIS—department of electronics informatics and systems science. As a postdoc, he is making research on agent and service paradigms for the development of distributed systems, parallel simulation, Petri nets, distributed measurement systems. He holds a membership with ACM. Angelo Furfaro, PhD, is a computer science assistant professor at Unical, DEIS, teaching object-oriented programming. His research interests are centred on: multi-agent systems, modeling and analysis of time-dependent systems, Petri nets, parallel simulation, verification of real-time systems, distributed measurement systems. He is a member of ACM. Libero Nigro is a full professor of computer science at Unical, DEIS, where he teaches object-oriented programming, software engineering and real-time systems courses. He directs the Software Engineering Laboratory (www.lis.deis.unical.it). His current research interests include: software engineering of time-dependent and distributed systems, real-time systems, Petri nets, modeling and parallel simulation of complex systems, distributed measurement systems. Prof. Nigro is a member of ACM and IEEE.     

Effect of sibling presence on mother–child interaction.

Interactions were observed as 80 mothers helped their 1st-grade child on an object-sorting task in the presence and absence of a 3rd-grade sibling. Mothers verbalized more to boys than to girls. For opposite-sex siblings, mothers gave less explanation and total verbalization with sibling present than absent. Other findings are presented. (6 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Attachment and obligation as daughters' motives for caregiving behavior and subsequent effect on subjective burden.

Existing studies have failed to adequately determine the combined effects of attachment and filial obligation as motives for adult children's caregiving behavior. This study's aim was to clarify the effects of these motives on caregiving and subsequent feelings of burden. In a path analysis of data from 78 daughters caring for elderly mothers, both attachment and obligation were related to amount of help provided. Stronger attachment was related to less subjective burden, whereas stronger obligation was related to greater burden. Contextual variables also contributed to the explanation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The misinterpretation of the Westinghouse study: A reply to Zigler and Berman.

Replies to the criticism of E. Zigler and W. Berman (see record 1984-07983-001) in their examination of the recent history of early childhood intervention of the Westinghouse study conducted under the direction of the present author (1969). It is asserted that the Westinghouse study did not conclude that Head Start was a success or a failure. Findings of the study resulted in recommendations for expanding and enriching the program and a fuller test of the concept of intervention. (4 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Effects of mother and older sibling on the problem-solving behavior of the younger child.

Determined the effects of aid from mother or older sibling on the child's problem-solving behavior in relation to the sex of the 2 siblings and family size. Ss were 120 1st-grade children with a 3rd- or 4th-grade sibling, half from 2-child families and half from larger families; the 4 possible sex combinations were equally represented. Ss worked on practice problems alone or were aided by sibling or mother prior to testing. Ss with older brothers performed as well alone as after aid by sibling or mother, whereas Ss with older sisters showed more advanced problem solving after aid by sibling or mother. Ss with same-sex siblings solved the problems more rapidly; family size had no effect. Results are interpreted in terms of family interaction patterns. (39 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Target recognition by components for mobile robot navigation

This paper presents a vision-based technique for detecting targets of the environment which have to be reached by an autonomous mobile robot during its navigational tasks. The targets the robot has to reach are the doors of the authors' office building. The detection of the door has been performed by detecting its most significant components in the image and it is based on data classification. Two neural classifiers have been trained for recognizing single components of the door. Then a combining algorithm, based on heuristic considerations, checks that they are in the proper geometric configuration of the structure of the door. The novelty of this work is to use together colour and shape information for identifying features and for detecting the components of the target. The approach, based on learning by components, is able to cleverly solve the problems of scale changes, perspective variations and partial occlusions. The obtained detecting system has been tested on a large test set of real images showing a high reliability and robustness: doors of different rooms, under different illumination conditions and by different viewpoints have been successfully recognized. Results in terms of door detection rate and false positive rate are presented throughout the paper.