Training and Application of Correct Information Unit Analysis to Structured and Unstructured Discourse

Correct Information Units (CIU) analysis is one of the few measures of discourse that attempts to quantify discourse as a function of communicating information efficiently. Though this analysis is used reliably as a research tool, most studies\u27 apply CIUs to structured discourse tasks and do not specifically describe how raters are trained. If certified clinical speech-language pathologists can likewise reliably apply CIU analysis within clinical settings to unstructured discourse, such as the discourse of people with aphasia (PWA), it may allow clinicians to quantify the information communicated efficiently in clinical populations with discourse deficits. Purpose: The purpose of this study is to determine if using the outlined training module, clinicians are able to score CIUs with similar inter-rater reliability across both structured and unstructured discourse samples as researchers. Method: Four certified SLPs will undergo a two-hour training session in CIU analysis similar to that of a university research staffs\u27 CIU training protocol. Each SLP will score CIUs in structured and unstructured language samples collected from individuals diagnosed with aphasia. The SLP\u27 scores within the structured and unstructured discourse samples will be compared to those of a university research lab staffs\u27. This will determine (1) whether SLPs can reliably code CIUs when compared with research raters in a lab setting when both using the same two-hour CIU training and resources allotted; (2) whether there is a significant difference in reliability when structured and unstructured discourse is analyzed

Appointments timed in proximity to annual milestones and compliance with screening: randomised controlled trial

Objective To investigate whether appointments for screening timed in proximity to annual milestones (birthdays, Christmas and New Year) may be used as a strategy to improve attendance for screening for colorectal cancer

Dashcams: Wenn die ZPO erlaubt, was das Datenschutzrecht verbietet

Mit Dashcams den Verkehr aufzuzeichnen, kann nach einem Unfall in einem zivilrechtlichen Haftpflichtprozess sehr nützlich sein - obwohl man das datenschutzrechtlich eigentlich nicht darf. Der BGH hat in dieser Woche zwei rechtliche Problemlagen geklärt, die deutsche Gerichte seit geraumer Zeit beschäftigt haben: Zum einen betrifft dies die datenschutzrechtliche Zulässigkeit des Einsatzes von Dashcams im öffentlichen Verkehrsraum. Zum anderen deren zivilprozessuale Verwertbarkeit, insbesondere wenn die Aufnahmen rechtswidrig erfolgten

Entwurf und Implementierung effizienter Objektsysteme für funktionale und imperative Programmiersprachen am Beispiel von Lisp

Bisherige Objektsysteme funktionaler und imperativer Programmiersprachen weisen eine Lücke auf. Aus der funktionalen Tradition wurde das ausdrucksstärkste Objektsystem CLOS entwickelt, das insbesondere durch sein Metaobjektprotokoll hervorsticht, dessen Performanz aber zu wünschen übrig läßt. Auf der anderen Seite zeichnet sich C++ als besonders effizient aus, unterstützt aber zentrale Konzepte objektorientierter Programmierung wie Spezialisieren und Generalisieren von Objektklassen nur unzureichend, was abgeschwächt auch für Java gilt. In dieser Arbeit wird am Beispiel von Lisp gezeigt, wie man effiziente Objektsysteme unter Berücksichtigung des Verursacherprinzips so entwirft und implementiert, daß einfache Konstrukte keinen Overhead durch die Präsenz aufwendiger Konzepte, wie des Metaobjektprotokolls oder des Redefinierens von Klassen, mittragen müssen. Entgegen bisherigen Annahmen wird hier erstmals nachgewiesen, daß diese Konzepte auch ohne Quellcodeinterpretation bzw. -kompilation zur Laufzeit realisiert und somit auch in traditionellen, compiler-orientierten Programmiersprachen, wie Ada, Pascal, Eiffel, C++ und natürlich Java, unterstützt werden können.Up to now a gap is evident in object systems of functional and procedural programming languages. The most expressive object system developed in the family of functional languages is CLOS with its outstanding metaobject protocol. Its performance, however, does not meet the users' needs. In the family of procedural languages the most efficient object system developed is C++. But its support of central concepts of object-oriented programming, such as specialization and generalization of object classes, is not sufficient. This also applies in some degree for Java. Using Lisp as an example this thesis shows how efficient object systems can be designed and implemented so that simple constructs have no overhead because of the presence of complex concepts such as the metaobject protocol or the redefinition of classes. In contrast to former assumptions, this thesis proofs for the first time that the above mentioned concepts can be realized without embedding an interpreter or an incremental compiler in the run-time environment. Therefore, they can also be supported in traditional compileroriented programming languages such as Ada, Pascal, Eiffel, C++, and Java

Prognosis in Women with Interval Breast Cancer: Population Based Observational Cohort Study

Objective: To compare the prognosis in women with interval breast cancer (cancer detected after a normal screening mammogram and before the next scheduled mammogram) with breast cancer detected among women not yet invited to mammography screening (non-screened). Design: Population based observational study. Setting: Norwegian breast cancer screening programme, implemented in different counties from 1996 to 2005. Participants: 7116 women with a diagnosis of breast cancer at age 50 to 72 years; 1816 had interval breast cancer and 5300 had a diagnosis of breast cancer but had not yet been invited to screening. Main outcome measures: Characteristics of the breast tumours, and survival of the women using Kaplan Meier curves and multivariable Cox proportional hazard models. Results: Although interval cancers on average were slightly larger than the cancers in women not invited to screening, the histological type or status of axilliary lymph nodes did not differ noticeably between the two groups. Among interval cancers, there were no appreciable trends in size, nodal status, grade, or hormone receptor positivity associated with time since the last normal mammogram as a marker of growth rate. After 10 years of follow-up, the survival rates were 79.1% (95% confidence interval 75.4% to 82.3%) among women with interval cancers and 76.8% (75.3% to 78.2%) among women in the non-screened cancer group (hazard ratio 0.98, 95% confidence interval 0.84 to 1.15; P=0.53). Analyses stratified by time since last normal mammogram, age at diagnosis, or screening round showed similar results. Conclusion: The prognosis of women with interval breast cancers was the same as that of women with breast cancers diagnosed without mammography screening

Packing While Traveling: Mixed Integer Programming for a Class of Nonlinear Knapsack Problems

Packing and vehicle routing problems play an important role in the area of supply chain management. In this paper, we introduce a non-linear knapsack problem that occurs when packing items along a fixed route and taking into account travel time. We investigate constrained and unconstrained versions of the problem and show that both are NP-hard. In order to solve the problems, we provide a pre-processing scheme as well as exact and approximate mixed integer programming (MIP) solutions. Our experimental results show the effectiveness of the MIP solutions and in particular point out that the approximate MIP approach often leads to near optimal results within far less computation time than the exact approach

Production and inventory management under multiple resource constraints

In this paper we present a model and solution methodology for production and inventory management problems that involve multiple resource constraints. The model formulation is quite general, allowing organizations to handle a variety of multi-item decisions such as determining order quantities, production batch sizes, number of production runs, or cycle times. Resource constraints become necessary to handle interaction among the multiple items. Common types of resource constraints include limits on raw materials, machine capacity, workforce capacity, inventory investment, storage space, or the total number of orders placed. For example, in a production environment, there may be limited workforce capacity and limits on machine capacities for manufacturing various product families. In a purchasing environment where a firm has multiple suppliers, there are often constraints for each supplier, such as the total order from each supplier cannot exceed the volume of the truck. We present efficient algorithms for solving both continuous and integer variable versions of the resource constrained production and inventory management model. The algorithms require the solution of a series of two types of subproblems: one is a nonlinear knapsack problem and the other is a nonlinear problem where the only constraints are lower and upper bounds on the variables. Computational testing of the algorithms is reported and indicates that they are effective for solving large-scale problems