Cost and Effectiveness of Training Oral Reading Skills in Preschool Children at Three Levels of Mastery

35 leaves. Advisor: Mary Ann PowersThe problem. Little empirical research has been done to enable behavioral engineers to set mastery criteria at other than arbitrary levels. This study attempted to determine the cost and effectiveness of low (60%), moderate (100%) and high (overtraining) criterion levels, by comparing the number of trials required to train and retrain words with the retention generated at the different levels of mastery. Procedure. Seven preschool children were trained to identify fourteen English words. Words were presented with a modified slide viewer apparatus; initially, both the word and its corresponding picture background were presented. Gradually, the background was faded so that responding was under the control of the word itself. Following training to three criterion levels, retention was measured at three and nine week follow-ups. Words were then retrained to their original level of mastery. Findings. A moderate (100%) level of mastery proved to be optimal. The cost of overtraining was prohibitive due to the large number of training trials required. Retention was inferior for words trained to the low criterion (60%), but equal for the moderate and high criterion word groups after a nine week period. Recommendations. More research is needed to determine whether more extensive overtraining would prove superior in terms of retention, despite its higher cost. Questions of cost and effectiveness of different mastery criteria might be investigated with other populations, different skill areas, and might use techniques other than fading

Using Constraint Programming to Verify DOPLER Variability Models

Software product lines are typically developed using model-based approaches. Models are used to guide and automate key activities such as the derivation of products. The verification of product line models is thus essential to ensure the consistency of the derived products. While many authors have proposed approaches for verifying feature models there is so far no such approach for decision models. We discuss challenges of analyzing and verifying decision-oriented DOPLER variability models. The manual verification of these models is an error-prone, tedious, and sometimes infeasible task. We present a preliminary approach that converts DOPLER variability models into constraint programs to support their verification. We assess the feasibility of our approach by identifying defects in two existing variability models

Initial Development of Tools to Identify Child Abuse and Neglect in Pediatric Primary Care

BACKGROUND: Child abuse and neglect (CAN) is prevalent, associated with long-term adversities, and often undetected. Primary care settings offer a unique opportunity to identify CAN and facilitate referrals, when warranted. Electronic health records (EHR) contain extensive information to support healthcare decisions, yet time constraints preclude most providers from thorough EHR reviews that could indicate CAN. Strategies that summarize EHR data to identify CAN and convey this to providers has potential to mitigate CAN-related sequelae. This study used expert review/consensus and Natural Language Processing (NLP) to develop and test a lexicon to characterize children who have experienced or are at risk for CAN and compared machine learning methods to the lexicon + NLP approach to determine the algorithm\u27s performance for identifying CAN. METHODS: Study investigators identified 90 CAN terms and invited an interdisciplinary group of child abuse experts for review and validation. We then used NLP to develop pipelines to finalize the CAN lexicon. Data for pipeline development and refinement were drawn from a randomly selected sample of EHR from patients seen at pediatric primary care clinics within a U.S. academic health center. To explore a machine learning approach for CAN identification, we used Support Vector Machine algorithms. RESULTS: The investigator-generated list of 90 CAN terms were reviewed and validated by 25 invited experts, resulting in a final pool of 133 terms. NLP utilized a randomly selected sample of 14,393 clinical notes from 153 patients to test the lexicon, and .03% of notes were identified as CAN positive. CAN identification varied by clinical note type, with few differences found by provider type (physicians versus nurses, social workers, etc.). An evaluation of the final NLP pipelines indicated 93.8% positive CAN rate for the training set and 71.4% for the test set, with decreased precision attributed primarily to false positives. For the machine learning approach, SVM pipeline performance was 92% for CAN + and 100% for non-CAN, indicating higher sensitivity than specificity. CONCLUSIONS: The NLP algorithm\u27s development and refinement suggest that innovative tools can identify youth at risk for CAN. The next key step is to refine the NLP algorithm to eventually funnel this information to care providers to guide clinical decision making

Free Radical Chemistry of Phosphasilenes

Understanding the characteristics of radicals formed from silicon-containing heavy analogues of alkenes is of great importance for their application in radical polymerization. Bulky and electronic substituent effects in such compounds as phosphasilenes not only stabilize the Si=P double bond, but also influence the structure and species of the formed radicals. Herein we report our first investigations of radicals derived from phosphasilenes with Mes (2,4,6-trimethylphenyl), Tip (2,4,6-triisopropylphenyl), Dur (2,3,5,6-tetramethylphenyl) and NMe2 (dimethylamino) substituents on the P atom, using muon spin spectroscopy and DFT calculations. Adding muonium (a light isotope of hydrogen) to phosphasilenes reveals that: a) the electron-donor NMe2 and the bulkiest Tip-substituted phosphasilenes form several muoniated radicals with different rotamer conformations; b) bulky Dur-substituted phosphasilene forms two radicals (Si- and P-centred); and c) Mes-substituted phosphasilene mainly forms one species of radical, at the P centre. These significant differences result from intramolecular substituent effects

Für Entmilitarisierung der Sicherheit: 20 Jahre Dresdener Studiengemeinschaft Sicherheitspolitik e. V. (DSS)

Die Autorenbeiträge geben ein Gesamtbild über das Selbstverständnis der Dresdener Studiengemeinschaft Sicherheitspolitik (DSS) e. V. und ihr zwanzigjähriges Wirken. Eine Chronik zur Entstehungsgeschichte und Tätigkeit der DSS e. V. sowie elf Anlagen ergänzen das Bild.:Redaktion, Vorwort. Autorenbeiträge: - Rolf Lehmann, Wissenschaftler in Uniform vor neuen Herausforderungen. - Hermann Hagena, Zwanzig Jahre Dresdener Studiengemeinschaft - Veteranenverein oder Avantgarde im Denken über Krieg, Sicherheit und Frieden? Oder auch: Was bleibt?' - Wolfgang Scheler, Theoretische Grundpositionen zur Sicherheitspolitik. Konstanz und Modifikation. - Ernst Woit, Globalstrategische Ambitionen der gewinner des Kalten krieges. - Egbert Lemcke, Russlands Sicherheits- und Verteidigungspolitik - einige Tendenzen des vergangenen Jahrzehnts. - Siegfried Schönherr, Ökonomie und Sicherheitspolitik. - Paul Heider, Demokratiasche Mitgestaltung - ein grundprinzip der Militärreform 1989/90 in der DDR. - Eberhard Haueis, Rückblicke und Selbstreflexion. - Joachim Klopfer, 20 Jahre Dresdener Studiengemeinschaft Sicherheitspolitik. . Kurzcharakteristik. . Die Mitglieder der Studiengemeinschaft. . Die hauptsächlichen Studien- und Tätigkeitsbereiche. . Veranstaltungen und Publikationen (Übersichten).' Joachim Klopfer, unter Mitarbeit von Eberhard Haueis, Rolf Lehmann, Wolfgang Scheler, Siegfried Schönherr: Chronik ausgewählter Ereignisse zur Entstehungsgeschichte und zur Tätigkeit der Dresdener Studiengemeinschaft Sicherheitspolitik e. V. (DSS), Zeitraum: August 1975 bis September 2010. 11 Anlagen zu den Beiträgen: Dokumente, Listen, Verzeichnisse. Verzeichnis der Abkürzungen

Understanding the buckling behaviour of steered tows in automated dry fibre placement (ADFP)

Technologies for automated fibre lay-up have proven their usefulness in composites manufacturing. Further development of the technologies, such as Automated Dry Fibre Placement (ADFP), allow further reduction of waste and increase of the design space through tow steering which enables creation of composites with tailored properties. Tow steering is, however, limited by possible defects such as wrinkles which result from mismatch of fibre length and steering path. This paper addresses wrinkle formation at different steering radii and provides a closed-form solution for the problem. Experimental results are used for estimation of the model parameters and validation of the model. An analytical framework is used to explore effects of processing parameters on defect formation. It was found that the tack stiffness has the greatest influence on defect formation. Parametric studies showed that increase of the temperature within the admissible temperature window can improve the tack properties and hence improve the lay-up

Averaging level control to reduce off-spec material in a continuous pharmaceutical pilot plant

The judicious use of buffering capacity is important in the development of future continuous pharmaceutical manufacturing processes. The potential benefits are investigated of using optimal-averaging level control for tanks that have buffering capacity for a section of a continuous pharmaceutical pilot plant involving two crystallizers, a combined filtration and washing stage and a buffer tank. A closed-loop dynamic model is utilized to represent the experimental operation, with the relevant model parameters and initial conditions estimated from experimental data that contained a significant disturbance and a change in setpoint of a concentration control loop. The performance of conventional proportional-integral (PI) level controllers is compared with optimal-averaging level controllers. The aim is to reduce the production of off-spec material in a tubular reactor by minimizing the variations in the outlet flow rate of its upstream buffer tank. The results show a distinct difference in behavior, with the optimal-averaging level controllers strongly outperforming the PI controllers. In general, the results stress the importance of dynamic process modeling for the design of future continuous pharmaceutical processes

When forgiving enhances psychological well-being: The role of interpersonal commitment

Contains fulltext : 63487.pdf (publisher's version ) (Closed access)The present research addresses the question of when and why forgiving might enhance psychological well-being. The authors predict that forgiving is associated with enhanced well-being but that this association should he more pronounced in relationships of strong rather than weak commitment. This hypothesis received good support in Studies 1-3. Studies 2 and 3 addressed the issue of why forgiving might be associated with psychological well-being, revealing that this association was reduced after controlling for psychological tension (i.e., a psychological state of discomfort due to conflicting cognitions and feelings). Study 4 revealed that in the context of marital relationships, tendencies toward forgiving one's spouse exhibited a more pronounced association with psychological well-being than did tendencies to forgive others in general.16 p