Mesurer l'amplitude articulaire du genou: goniométre universel ou smartphone [Measurement of the knee range of motion: standard goniometer or smartphone?].

Universal standard goniometer is an essential tool to measure articulations' range of motion (ROM). In this time of technological advances and increasing use of smartphones, new measurement's tools appear as specific smartphone applications. This article compares the iOS application "Knee Goniometer" with universal standard goniometer to assess knee ROM. To our knowledge, this is the first study that uses a goniometer application in a clinical context. The purpose of this study is to determine if this application could be used in clinical practice.

Time standards of nursing in Primary Health Care: an observational study

Abstract OBJECTIVE To determine time standards for interventions and activities conducted by nursing professionals in Family Health Units (FHU) in Brazil to substantiate the calculation of work force. METHOD This was an observational study carried out in 27 FHU, in 12 municipalities in 10 states, in 2013. In each unit, nursing professionals were observed every 10 minutes, for eight work hours, on five consecutive days via the work sampling technique. RESULTS A total of 32,613 observations were made, involving 47 nurses and 93 nursing technicians/assistants. Appointments were the main intervention carried out by nurses, with a mean time of 25.3 minutes, followed by record-keeping, which corresponded to 9.7%. On average, nursing technicians/assistants spent 6.3% of their time keeping records and 30.6 intervention minutes on immunization/vaccination control. CONCLUSION The study resulted in standard times of interventions carried out by the FHU nursing team, which can underpin the determination of nursing staff size and human resource policies. Furthermore, the study showed the panorama of interventions currently employed, allowing for the work process to be reviewed and optimized.

A polynomial algorithm for special case of the one-machine scheduling problem with time-lags

The standard one-machine scheduling problem consists in schedulinga set of jobs in one machine which can handle only one job at atime, minimizing the maximum lateness. Each job is available forprocessing at its release date, requires a known processing timeand after finishing the processing, it is delivery after a certaintime. There also can exists precedence constraints between pairsof jobs, requiring that the first jobs must be completed beforethe second job can start. An extension of this problem consistsin assigning a time interval between the processing of the jobsassociated with the precedence constrains, known by finish-starttime-lags. In presence of this constraints, the problem is NP-hardeven if preemption is allowed. In this work, we consider a specialcase of the one-machine preemption scheduling problem with time-lags, where the time-lags have a chain form, and propose apolynomial algorithm to solve it. The algorithm consist in apolynomial number of calls of the preemption version of the LongestTail Heuristic. One of the applicability of the method is to obtainlower bounds for NP-hard one-machine and job-shop schedulingproblems. We present some computational results of thisapplication, followed by some conclusions.

Estimating overidentified, nonrecursive, time-varying coefficients structural VARs

This paper provides a method to estimate time varying coefficients structuralVARs which are non-recursive and potentially overidentified. The procedureallows for linear and non-linear restrictions on the parameters, maintainsthe multi-move structure of standard algorithms and can be used toestimate structural models with different identification restrictions. We studythe transmission of monetary policy shocks and compare the results with thoseobtained with traditional methods.

Probabilistic maximal covering location-allocation models with constrained waiting time or queue length for congested systems

When dealing with the design of service networks, such as healthand EMS services, banking or distributed ticket selling services, thelocation of service centers has a strong influence on the congestion ateach of them, and consequently, on the quality of service. In this paper,several models are presented to consider service congestion. The firstmodel addresses the issue of the location of the least number of single--servercenters such that all the population is served within a standard distance,and nobody stands in line for a time longer than a given time--limit, or withmore than a predetermined number of other clients. We then formulateseveral maximal coverage models, with one or more servers per service center.A new heuristic is developed to solve the models and tested in a 30--nodesnetwork.

A consistency test of the time trade-off

This paper tests the internal consistency of time trade-off utilities.We find significant violations of consistency in the direction predictedby loss aversion. The violations disappear for higher gauge durations.We show that loss aversion can also explain that for short gaugedurations time trade-off utilities exceed standard gamble utilities. Ourresults suggest that time trade-off measurements that use relativelyshort gauge durations, like the widely used EuroQol algorithm(Dolan 1997), are affected by loss aversion and lead to utilities thatare too high.

Incorporating waiting time in competitive location models: Formulations and heuristics

In this paper we propose a metaheuristic to solve a new version of the Maximum CaptureProblem. In the original MCP, market capture is obtained by lower traveling distances or lowertraveling time, in this new version not only the traveling time but also the waiting time willaffect the market share. This problem is hard to solve using standard optimization techniques.Metaheuristics are shown to offer accurate results within acceptable computing times.

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

Evaluation of an intravitreal fluocinolone acetonide implant versus standard systemic therapy in noninfectious posterior uveitis.

PURPOSE: To evaluate the safety and efficacy of an intravitreal fluocinolone acetonide (FA) implant compared with standard therapy in subjects with noninfectious posterior uveitis (NIPU). DESIGN: Randomized, controlled, phase 2b/3, open-label, multicenter superiority trial. PARTICIPANTS: Subjects with unilateral or bilateral NIPU. METHODS: One hundred forty subjects received either a 0.59-mg FA intravitreal implant (n = 66) or standard of care (SOC; n = 74) with either systemic prednisolone or equivalent corticosteroid as monotherapy (> or =0.2 mg/kg daily) or, if judged necessary by the investigator, combination therapy with an immunosuppressive agent plus a lower dose of prednisolone or equivalent corticosteroid (> or =0.1 mg/kg daily). MAIN OUTCOME MEASURES: Time to first recurrence of uveitis. RESULTS: Eyes that received the FA intravitreal implant experienced delayed onset of observed recurrence of uveitis (P<0.01) and a lower rate of recurrence of uveitis (18.2% vs. 63.5%; P< or =0.01) compared with SOC study eyes. Adverse events frequently observed in implanted eyes included elevated intraocular pressure (IOP) requiring IOP-lowering surgery (occurring in 21.2% of implanted eyes) and cataracts requiring extraction (occurring in 87.8% of phakic implanted eyes). No treatment-related nonocular adverse events were observed in the implant group, whereas such events occurred in 25.7% of subjects in the SOC group. CONCLUSIONS: The FA intravitreal implant provided better control of inflammation in patients with uveitis compared with systemic therapy. Intraocular pressure and lens clarity of implanted eyes need close monitoring in patients receiving the FA intravitreal implant.

Biofilm formation on bone grafts and bone graft substitutes: comparison of different materials by a standard in vitro test and microcalorimetry.

We analyzed the initial adhesion and biofilm formation of Staphylococcus aureus (ATCC 29213) and S. epidermidis RP62A (ATCC 35984) on various bone grafts and bone graft substitutes under standardized in vitro conditions. In parallel, microcalorimetry was evaluated as a real-time microbiological assay in the investigation of biofilm formation and material science research. The materials beta-tricalcium phosphate (beta-TCP), processed human spongiosa (Tutoplast) and poly(methyl methacrylate) (PMMA) were investigated and compared with polyethylene (PE). Bacterial counts (log(10) cfu per sample) were highest on beta-TCP (S. aureus 7.67 +/- 0.17; S. epidermidis 8.14 +/- 0.05) while bacterial density (log(10) cfu per surface) was highest on PMMA (S. aureus 6.12 +/- 0.2, S. epidermidis 7.65 +/- 0.13). Detection time for S. aureus biofilms was shorter for the porous materials (beta-TCP and processed human spongiosa, p < 0.001) compared to the smooth materials (PMMA and PE), with no differences between beta-TCP and processed human spongiosa (p > 0.05) or PMMA and PE (p > 0.05). In contrast, for S. epidermidis biofilms the detection time was different (p < 0.001) between all materials except between processed human spongiosa and PE (p > 0.05). The quantitative analysis by quantitative culture after washing and sonication of the material demonstrated the importance of monitoring factors like specific surface or porosity of the test materials. Isothermal microcalorimetry proved to be a suitable tool for an accurate, non-invasive and real-time microbiological assay, allowing the detection of bacterial biomass without removing the biofilm from the surface.

On the many-time formulation of classical particle dynamics

Starting from the standard one-time dynamics of n nonrelativistic particles, the n-time equations of motion are inferred, and a variational principle is formulated. A suitable generalization of the classical LieKnig theorem is demonstrated, which allows the determination of all the associated presymplectic structures. The conditions under which the action of an invariance group is canonical are studied, and a corresponding Noether theorem is deduced. A formulation of the theory in terms of n first-class constraints is recovered by means of coisotropic imbeddings. The proposed approach also provides for a better understanding of the relativistic particle dynamics, since it shows that the different roles of the physical positions and the canonical variables is not peculiar to special relativity, but rather to any n-time approach: indeed a nonrelativistic no-interaction theorem is deduced.

Delay in diagnosis of eosinophilic esophagitis increases risk for stricture formation in a time-dependent manner.

BACKGROUND & AIMS: Development of strictures is a major concern for patients with eosinophilic esophagitis (EoE). At diagnosis, EoE can present with an inflammatory phenotype (characterized by whitish exudates, furrows, and edema), a stricturing phenotype (characterized by rings and stenosis), or a combination of these. Little is known about progression of stricture formation; we evaluated stricture development over time in the absence of treatment and investigated risk factors for stricture formation. METHODS: We performed a retrospective study using the Swiss EoE Database, collecting data on 200 patients with symptomatic EoE (153 men; mean age at diagnosis, 39 ± 15 years old). Stricture severity was graded based on the degree of difficulty associated with passing of the standard adult endoscope. RESULTS: The median delay in diagnosis of EoE was 6 years (interquartile range, 2-12 years). With increasing duration of delay in diagnosis, the prevalence of fibrotic features of EoE, based on endoscopy, increased from 46.5% (diagnostic delay, 0-2 years) to 87.5% (diagnostic delay, >20 years; P = .020). Similarly, the prevalence of esophageal strictures increased with duration of diagnostic delay, from 17.2% (diagnostic delay, 0-2 years) to 70.8% (diagnostic delay, >20 years; P < .001). Diagnostic delay was the only risk factor for strictures at the time of EoE diagnosis (odds ratio = 1.08; 95% confidence interval: 1.040-1.122; P < .001). CONCLUSIONS: The prevalence of esophageal strictures correlates with the duration of untreated disease. These findings indicate the need to minimize delay in diagnosis of EoE.

Trends and determinants of time in bed in Geneva, Switzerland

STUDY OBJECTIVES: There is limited information regarding sleep duration and determinants in Switzerland. We aimed to assess the trends and determinants of time in bed as a proxy for sleep duration in the Swiss canton of Geneva. METHODS: Data from repeated, independent cross-sectional representative samples of adults (≥ 18 years) of the Geneva population were collected between 2005 and 2011. Self-reported time in bed, education, monthly income, and nationality were assessed by questionnaire. RESULTS: Data from 3,853 participants (50% women, 51.7 ± 10.9 years) were analyzed. No significant trend was observed between 2005 and 2011 regarding time in bed or the prevalence of short (≤ 6 h/day) and long (> 9 h/day) time in bed. Elderly participants reported a longer time in bed (year-adjusted mean ± standard error: 7.67 ± 0.02, 7.82 ± 0.03, and 8.41 ± 0.04 h/day for 35-50, 50-65, and 65+ years, respectively, p < 0.001), while shorter time in bed was reported by non-Swiss participants (7.77 ± 0.03 vs. 7.92 ± 0.03 h/day for Swiss nationals, p < 0.001), participants with higher education (7.92 ± 0.02 for non-university vs. 7.74 ± 0.03 h/day for university, p < 0.001) or higher income (8.10 ± 0.04, 7.84 ± 0.03, and 7.70 ± 0.03 h/day for < 5,000 SFr; 5,000-9,500 SFr, and > 9,500 SFr, respectively, p < 0.001). Multivariable-adjusted polytomous logistic regression showed short and long time in bed to be positively associated with obesity and negatively associated with income. CONCLUSION: In a Swiss adult population, sleep duration as assessed by time in bed did not change significantly between 2005 and 2011. Both clinical and socioeconomic factors influence time in bed.

Time invested in the global respiratory care of cystic fibrosis paediatrics patients.

INTRODUCTION: Respiratory therapy is a keystone of the treatment for cystic fibrosis (CF) lung disease, but it is time consuming. OBJECTIVES: We aimed to assess the total time spent on respiratory therapy, including chest physiotherapy (CPT) and physical activity (PA), as well as inhalation therapy (IT) and maintenance of materials (MM) to rationalise and optimise treatment. METHODS: A cross-sectional prospective study in a paediatric CF cohort. A questionnaire was developed to look at the time spent on respiratory care over 3 months. Enrolled in this study are all CF patients aged from 6 to 16 years (the exclusion criterion was lung transplantation). RESULTS: Of the 40 enrolled patients, 22 participated (13 boys and 9 girls), with a mean age of 11 years. The patients spent approximately 19.46 h per week (standard deviation ± 7.53, 8.00-35.25 h) on therapy: CPT (30.58%), IT (15.11%), PA (50%) and MM (4.32%), without statistical significance between sexes. CONCLUSION: In our cohort, CF patients spent an average of nearly 20 h a week in respiratory therapy, within a wide range of between 8 h to almost 36 h a week. PA consumes almost half of the time. Physicians have to take into consideration the burden of the treatment, to optimise the therapy.

An Investigation of Concrete Setting Time, R-265 (MLR-75-4), 1975

A water reducing and retarding type admixture in concrete is commonly used on continuous bridge deck pours in Iowa. The concrete placed in the negative moment areas must remain plastic until all the dead load deflection due to the new deck's weight occurs. If the concrete does not remain plastic until the total deflection has occurred, structural cracks will develop in these areas. Retarding type admixtures will delay the setting time of concrete and prevent structural cracks if added in the proper amounts. In Section 2412.02 of the Standard Specifications, 1972, Iowa State Highway Commission, it states, "The admixture shall be used in amounts recommended by the manufacturer for conditions which prevail on the project and as approved by the engineer." The conditions which prevail on the project depend on temperature, humidity, wind conditions, etc. Each of these factors will affect the setting rate of the plastic concrete. The purpose of this project is to provide data that will be useful to field personnel concerning the retardation of concrete setting times, and how the of sets will vary with different addition rates and curing temperatures holding all other atmospheric variables constant.