835 resultados para Advanced Driving Simulator


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Because driving is a complex task, drivers need to be sure they have the mental and physical capacity for driving safely as they experience changes with aging. Most drivers who are aware of their changing capacity to drive can adjust their driving plans and improve their driving habits to drive safer and longer.

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The value of driving We as Americans - and especially as Iowans - value the independence of getting around in our own vehicles and staying connected with our families and communities. The majority of older Iowans enjoy a more active, healthy and longer life than previous generations. Freedom of mobility shapes our quality of life. With aging, driving becomes an increasing concern for older Iowans and their families. How we deal with changes in our driving ability and, eventually, choose when and how to retire from driving, will affect our safety and our quality of life.

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We study the driving-rate and temperature dependence of the power-law exponents that characterize the avalanche distribution in first-order phase transitions. Measurements of acoustic emission in structural transitions in Cu-Zn-Al and Cu-Al-Ni are presented. We show how the observed behavior emerges within a general framework of competing time scales of avalanche relaxation, driving rate, and thermal fluctuations. We confirm our findings by numerical simulations of a prototype model.

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PURPOSE Updated results are presented after a median follow-up of 7.3 years from the phase III First-Line Indolent Trial of yttrium-90 ((90)Y) -ibritumomab tiuxetan in advanced-stage follicular lymphoma (FL) in first remission. PATIENTS AND METHODS Patients with CD20(+) stage III or IV FL with complete response (CR), unconfirmed CR (CRu), or partial response (PR) after first-line induction treatment were randomly assigned to (90)Y-ibritumomab consolidation therapy (rituximab 250 mg/m(2) days -7 and 0, then (90)Y-ibritumomab 14.8 MBq/kg day 0; maximum 1,184 MBq) or no further treatment (control). Primary end point was progression-free survival (PFS) from date of random assignment. Results For 409 patients available for analysis ((90)Y-ibritumomab, n = 207; control, n = 202), estimated 8-year overall PFS was 41% with (90)Y-ibritumomab versus 22% for control (hazard ratio [HR], 0.47; P < .001). For patients in CR/CRu after induction, 8-year PFS with (90)Y-ibritumomab was 48% versus 32% for control (HR, 0.61; P = .008), and for PR patients, it was 33% versus 10% (HR, 0.38; P < .001). For (90)Y-ibritumomab consolidation, median PFS was 4.1 years (v 1.1 years for control; P < .001). Median time to next treatment (TTNT) was 8.1 years for (90)Y-ibritumomab versus 3.0 years for control (P < .001) with approximately 80% response rates to second-line therapy in either arm, including autologous stem-cell transplantation. No unexpected toxicities emerged during long-term follow-up. Estimated between-group 8-year overall survival rates were similar. Annualized incidence rate of myelodysplastic syndrome/acute myeloblastic leukemia was 0.50% versus 0.07% in (90)Y-ibritumomab and control groups, respectively (P = .042). CONCLUSION (90)Y-ibritumomab consolidation after achieving PR or CR/CRu to induction confers 3-year benefit in median PFS with durable 19% PFS advantage at 8 years and improves TTNT by 5.1 years for patients with advanced FL.

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This brochure explains Iowa's laws concerning the use of cell phones and other electronic communication devices while driving.

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Introduction: Non-operative management (NOM) of blunt splenic injuries in hemodynamically stable patients is nowadays considered the standard treatment. Material and Methods: The aim was to clarify the criteria used for primary operative management (OM) and planned NOM. Furthermore, the study aimed to identify risk factors for failure of NOM. All adult patients with blunt splenic injuries treated from 2000-2008 were reviewed and a logistic regression analysis employed. Results: There were 206 patients (146 men, 70.9%). Mean age was 38.2 ± 19.1 years. The mean Injury Severity Score (ISS) was 30.9 ± 11.6. The American Association for the Surgery of Trauma (AAST) classification of the splenic injury was: grade I, n = 43 (20.9%); grade II, n = 52 (25.2%); grade III, n = 60 (29.1%), grade IV, n = 42 (20.4%) and grade V, n = 9 (4.4%). 47 patients (22.8%) required immediate surgery (OM). More than 5 units of red cell transfusions (odds ratio [OR] 13.72, P < 0.001), a Glasgow Coma Scale < 11 (OR 9.88, P = 0.009) and age ? 55 years (OR 3.29, P = 0.038) were associated with primary OM. 159 patients (77.2%) qualified for a non-surgical approach (NOM), which was successful in 89.9% (143/159). The overall splenic salvage rate amounted to 69.4% (143/206). Multiple logistic regression analysis found age ? 40 years to be the only factor significantly and independently related to the failure of NOM (OR 13.58, P = 0.001). Conclusion: Advanced age is associated with an increased failure rate of NOM in patients with blunt splenic injuries.

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BACKGROUND: Gefitinib is active in patients with pretreated non-small-cell lung cancer (NSCLC). We evaluated the activity and toxicity of gefitinib first-line treatment in advanced NSCLC followed by chemotherapy at disease progression. PATIENTS AND METHODS: In all, 63 patients with chemotherapy-naive stage IIIB/IV NSCLC received gefitinib 250 mg/day. At disease progression, gefitinib was replaced by cisplatin 80 mg/m(2) on day 1 and gemcitabine 1250 mg/m(2) on days 1, 8 for up to six 3-week cycles. Primary end point was the disease stabilization rate (DSR) after 12 weeks of gefitinib. RESULTS: After 12 weeks of gefitinib, the DSR was 24% and the response rate (RR) was 8%. Median time to progression (TtP) was 2.5 months and median overall survival (OS) 11.5 months. Never smokers (n = 9) had a DSR of 56% and a median OS of 20.2 months; patients with epidermal growth factor receptor (EGFR) mutation (n = 4) had a DSR of 75% and the median OS was not reached after the follow-up of 21.6 months. In all, 41 patients received chemotherapy with an overall RR of 34%, DSR of 71% and median TtP of 6.7 months. CONCLUSIONS: First-line gefitinib monotherapy led to a DSR of 24% at 12 weeks in an unselected patients population. Never smokers and patients with EGFR mutations tend to have a better outcome; hence, further trials in selected patients are warranted.

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Squamous cell carcinoma of the head and neck (SCCHN) is a common disease that develops in the upper aerodigestive epithelium. The most important risk factors are tobacco and alcohol consumption. There is also increasing evidence that human papillomavirus plays an important role in the cause of SCCHN. The complex anatomy, the vital functions of the upper aerodigestive tract and the close proximity to vital structures, explain that the goal of treatment is not only to improve survival outcomes, but also to preserve organ function. Radiotherapy and surgery are the standard modalities of treatment, reflecting the locoregional predominance of SCCHN. Chemotherapy plays an important role in the treatment of patients with locoregionally advanced disease, in conjunction with radiotherapy and surgery. Indeed, standard therapy for resectable locoregionally advanced (stage III or IV) SCCHN cancers consists either of surgery and adjuvant chemoradiotherapy or definitive concomitant chemoradiotherapy, depending upon disease site, stage and resectability of the tumour, or institutional experience. Concomitant chemoradiotherapy has been shown in several randomised trials to improve disease-free and overall survival in the postoperative setting for resected disease with poor prognostic factors. Furthermore, multiple randomised studies and meta-analyses have shown that definitive chemoradiotherapy, as well anti-epidermal growth factor receptor treatment in one randomised study, improved disease-free and overall survival when compared with radiotherapy alone. This overview reviews the most relevant published studies on the multidisciplinary management of SCCHN and discusses future strategies to reduce locoregional failures.

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Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

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This report documents Phase IV of the Highway Maintenance Concept Vehicle (HMCV) project, a pooled fund study sponsored by the Departments of Transportation of Iowa, Pennsylvania, and Wisconsin. This report provides the background, including a brief history of the earlier phases of the project, a systems overview, and descriptions of the research conducted in Phase IV. Finally, the report provides conclusions and recommendations for future research. Background The goal of the Highway Maintenance Concept Vehicle Pooled Fund Study is to provide travelers with the level of service defined by policy during the winter season at the least cost to taxpayers. This goal is to be accomplished by using information regarding actual road conditions to facilitate and adjust snow and ice control activities. The approach used in this study was to bring technology applications from other industries to the highway maintenance vehicle. This approach is evolutionary in that as emerging technologies and applications are found to be acceptable to the pooled fund states and as they appear that to have potential for supporting the study goals they become candidates for our research. The objective of Phase IV is to: Conduct limited deployment of selected technologies from Phase III by equipping a vehicle with proven advanced technologies and creating a mobile test laboratory for collecting road weather data. The research quickly pointed out that investments in winter storm maintenance assets must be based on benefit/cost analysis and related to improving level of service. For example, Iowa has estimated the average cost of fighting a winter storm to be about $60,000 to $70,000 per hour typically. The maintenance concept vehicle will have advanced technology equipment capable of applying precisely the correct amount of material, accurately tailored to the existing and predicted pavement conditions. Hence, a state using advanced technology could expect to have a noticeable impact on the average time taken to establish the winter driving service level. If the concept vehicle and data produced by the vehicle are used to support decision-making leading to reducing material usage and the average time by one hour, a reasonable benefit/cost will result. Data from the friction meter can be used to monitor and adjust snow and ice control activities and inform travelers of pavement surface conditions. Therefore, final selection of successfully performing technologies will be based on the foundation statements and criteria developed by the study team.

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Following elective orthopaedic surgery or the treatment of a fracture, patients are temporarily unable to drive. This loss of independence may have serious social and economic consequences for the patient. It is therefore essential to know when it is safe to permit such patients to return to driving. This article, based upon a review of the current literature, proposes recommendations of the time period after which patients may safely return to driving. Practical decisions are made based upon the type of surgical intervention or fracture. Swiss legislation is equally approached so as to better define the decision.

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Delta(9)-Tetrahydrocannabinol (THC) is frequently found in the blood of drivers suspected of driving under the influence of cannabis or involved in traffic crashes. The present study used a double-blind crossover design to compare the effects of medium (16.5 mg THC) and high doses (45.7 mg THC) of hemp milk decoctions or of a medium dose of dronabinol (20 mg synthetic THC, Marinol on several skills required for safe driving. Forensic interpretation of cannabinoids blood concentrations were attempted using the models proposed by Daldrup (cannabis influencing factor or CIF) and Huestis and coworkers. First, the time concentration-profiles of THC, 11-hydroxy-Delta(9)-tetrahydrocannabinol (11-OH-THC) (active metabolite of THC), and 11-nor-9-carboxy-Delta(9)-tetrahydrocannabinol (THCCOOH) in whole blood were determined by gas chromatography-mass spectrometry-negative ion chemical ionization. Compared to smoking studies, relatively low concentrations were measured in blood. The highest mean THC concentration (8.4 ng/mL) was achieved 1 h after ingestion of the strongest decoction. Mean maximum 11-OH-THC level (12.3 ng/mL) slightly exceeded that of THC. THCCOOH reached its highest mean concentration (66.2 ng/mL) 2.5-5.5 h after intake. Individual blood levels showed considerable intersubject variability. The willingness to drive was influenced by the importance of the requested task. Under significant cannabinoids influence, the participants refused to drive when they were asked whether they would agree to accomplish several unimportant tasks, (e.g., driving a friend to a party). Most of the participants reported a significant feeling of intoxication and did not appreciate the effects, notably those felt after drinking the strongest decoction. Road sign and tracking testing revealed obvious and statistically significant differences between placebo and treatments. A marked impairment was detected after ingestion of the strongest decoction. A CIF value, which relies on the molar ratio of main active to inactive cannabinoids, greater than 10 was found to correlate with a strong feeling of intoxication. It also matched with a significant decrease in the willingness to drive, and it matched also with a significant impairment in tracking performances. The mathematic model II proposed by Huestis et al. (1992) provided at best a rough estimate of the time of oral administration with 27% of actual values being out of range of the 95% confidence interval. The sum of THC and 11-OH-THC blood concentrations provided a better estimate of impairment than THC alone. This controlled clinical study points out the negative influence on fitness to drive after medium or high dose oral THC or dronabinol.