Clinical evaluation of 3 overdenture concepts with tooth roots and implants: 2-year results

PURPOSE: In the present cohort study, overdentures with a combined root and implant support were evaluated and compared with either exclusively root- or implant-supported overdentures. Results of a 2-year follow-up period are reported, namely survival of implants, root copings, and prostheses, plus prosthetic complications, maintenance service, and patient satisfaction. MATERIALS AND METHODS: Fourteen patients were selected for the combined overdenture therapy and were compared with 2 patient groups in which either roots or implants provided overdenture support. Altogether, 14, 17, and 15 patients (in groups 1, 2, and 3, respectively) were matched with regard to age, sex, treatment time, and observation period. The mean age was around 67 years. Periodontal parameters were recorded, radiographs were taken, and all complications and failures were registered during the entire observation time. The patients answered a 9-item questionnaire by means of a visual analogue scale (VAS). RESULTS: One implant failed and 1 tooth root was removed following longitudinal root fracture. Periodontal/peri-implant parameters gave evidence of good oral hygiene for roots and implants, and slight crestal bone resorption was measured for both. Technical complications and service performed were significantly higher in the first year (P < .04) in all 3 groups and significantly higher in the tooth root group (P < .03). The results of the VAS indicated significantly lower scores for satisfaction, speaking ability, wearing comfort, and denture stability with combined or exclusive root support (P < .05 and .02, respectively). Initial costs of overdentures with combined or root support were 10% lower than for implant overdentures. CONCLUSION: The concept of combined root and implant support can be integrated into treatment planning and overdenture design for patients with a highly reduced dentition.

An Instrument Design for Space-Based Optical Observation of Space Debris

Currently, observations of space debris are primarily performed with ground-based sensors. These sensors have a detection limit at some centimetres diameter for objects in Low Earth Orbit (LEO) and at about two decimetres diameter for objects in Geostationary Orbit (GEO). The few space-based debris observations stem mainly from in-situ measurements and from the analysis of returned spacecraft surfaces. Both provide information about mostly sub-millimetre-sized debris particles. As a consequence the population of centimetre- and millimetre-sized debris objects remains poorly understood. The development, validation and improvement of debris reference models drive the need for measurements covering the whole diameter range. In 2003 the European Space Agency (ESA) initiated a study entitled “Space-Based Optical Observation of Space Debris”. The first tasks of the study were to define user requirements and to develop an observation strategy for a space-based instrument capable of observing uncatalogued millimetre-sized debris objects. Only passive optical observations were considered, focussing on mission concepts for the LEO, and GEO regions respectively. Starting from the requirements and the observation strategy, an instrument system architecture and an associated operations concept have been elaborated. The instrument system architecture covers the telescope, camera and onboard processing electronics. The proposed telescope is a folded Schmidt design, characterised by a 20 cm aperture and a large field of view of 6°. The camera design is based on the use of either a frame-transfer charge coupled device (CCD), or on a cooled hybrid sensor with fast read-out. A four megapixel sensor is foreseen. For the onboard processing, a scalable architecture has been selected. Performance simulations have been executed for the system as designed, focussing on the orbit determination of observed debris particles, and on the analysis of the object detection algorithms. In this paper we present some of the main results of the study. A short overview of the user requirements and observation strategy is given. The architectural design of the instrument is discussed, and the main tradeoffs are outlined. An insight into the results of the performance simulations is provided.

Verbalization of Dependencies Between Concepts Built Through Fuzzy Cognitive Maps

The new computing paradigm known as cognitive computing attempts to imitate the human capabilities of learning, problem solving, and considering things in context. To do so, an application (a cognitive system) must learn from its environment (e.g., by interacting with various interfaces). These interfaces can run the gamut from sensors to humans to databases. Accessing data through such interfaces allows the system to conduct cognitive tasks that can support humans in decision-making or problem-solving processes. Cognitive systems can be integrated into various domains (e.g., medicine or insurance). For example, a cognitive system in cities can collect data, can learn from various data sources and can then attempt to connect these sources to provide real time optimizations of subsystems within the city (e.g., the transportation system). In this study, we provide a methodology for integrating a cognitive system that allows data to be verbalized, making the causalities and hypotheses generated from the cognitive system more understandable to humans. We abstract a city subsystem—passenger flow for a taxi company—by applying fuzzy cognitive maps (FCMs). FCMs can be used as a mathematical tool for modeling complex systems built by directed graphs with concepts (e.g., policies, events, and/or domains) as nodes and causalities as edges. As a verbalization technique we introduce the restriction-centered theory of reasoning (RCT). RCT addresses the imprecision inherent in language by introducing restrictions. Using this underlying combinatorial design, our approach can handle large data sets from complex systems and make the output understandable to humans.