Anesthetic considerations in the child with Gaucher disease

Alpidem, an imidazopyridine that acts at the gamma-aminobutyric acid/benzodiazepine receptor complex, has been reported to be an effective anxiolytic with a more favorable side effect profile than benzodiazepines. The effect of alpidem was investigated in an 8-week, open, clinical trial in 13 patients with panic disorder, with or without agoraphobia. Three patients were responders (much improved or very much improved), five patients were nonresponders, and five patients dropped out after less than 6 weeks of treatment. Significant improvement was seen in the sample as a whole for spontaneous panic attacks, phobic avoidance, and anticipatory anxiety. Most improvement occurred during the first 4 weeks of treatment, and responders had milder panic disorder at baseline. Adverse effects were generally mild. After 8 weeks of treatment, taper of medication over 2 weeks occurred without significant worsening of panic disorder symptoms. The efficacy of alpidem in the treatment of panic disorder remains uncertain and requires assessment in a controlled trial.     

Performance-Analyse und -Optimierung in der Softwareentwicklung

Nicht-funktionale Anforderungen an ein Softwaresystem beschreiben Aspekte, die nicht direkt die Funktionalit?t, wie sie der Benutzer sieht, betreffen.     

Self‐regulation during e‐learning: using behavioural evidence from navigation log files

The current paper examined the relationship between perceived characteristics of the learning environment in an e‐module in relation to test performance among a group of e‐learners. Using structural equation modelling, the relationship between these variables is further explored in terms of the proposed double mediation as outlined by Ning and Downing. These authors initially proposed that motivation and self‐regulation strategies are mediators between the perception of the learning environment and performance. In our replication and extension study, we substituted self‐reported self‐regulation with behavioural indicators of self‐regulation using navigation log files and focused on test‐taking rather than general motivation. We proposed that navigational patterns captured using log files can also help deduce self‐regulation in e‐modules and provide information in the absence of self‐reports. Path analyses provide partial support for our navigational hypotheses and the model. Implications of our results for the use of e‐module data and conclusions based on navigation are discussed.     

Spectral Ray Differentials

Light refracted by a dispersive interface leads to beautifully colored patterns that can be rendered faithfully with spectral Monte‐Carlo methods. Regrettably, results often suffer from chromatic noise or banding, requiring high sampling rates and large amounts of memory compared to renderers operating in some trichromatic color space. Addressing this issue, we introduce spectral ray differentials, which describe the change of light direction with respect to changes in the spectrum. In analogy with the classic ray and photon differentials, this information can be used for filtering in the spectral domain. Effectiveness of our approach is demonstrated by filtering for offline spectral light and path tracing as well as for an interactive GPU photon mapper based on splatting. Our results show considerably less chromatic noise and spatial aliasing while retaining good visual similarity to reference solutions with negligible overhead in the order of milliseconds.     

Spatio‐temporal geometry fusion for multiple hybrid cameras using moving least squares surfaces

Multi‐view reconstruction aims at computing the geometry of a scene observed by a set of cameras. Accurate 3D reconstruction of dynamic scenes is a key component for a large variety of applications, ranging from special effects to telepresence and medical imaging. In this paper we propose a method based on Moving Least Squares surfaces which robustly and efficiently reconstructs dynamic scenes captured by a calibrated set of hybrid color+depth cameras. Our reconstruction provides spatio‐temporal consistency and seamlessly fuses color and geometric information. We illustrate our approach on a variety of real sequences and demonstrate that it favorably compares to state‐of‐the‐art methods.     

Approximate Symmetry Detection in Partial 3D Meshes

Symmetry is a common characteristic in natural and man‐made objects. Its ubiquitous nature can be exploited to facilitate the analysis and processing of computational representations of real objects. In particular, in computer graphics, the detection of symmetries in 3D geometry has enabled a number of applications in modeling and reconstruction. However, the problem of symmetry detection in incomplete geometry remains a challenging task. In this paper, we propose a vote‐based approach to detect symmetry in 3D shapes, with special interest in models with large missing parts. Our algorithm generates a set of candidate symmetries by matching local maxima of a surface function based on the heat diffusion in local domains, which guarantee robustness to missing data. In order to deal with local perturbations, we propose a multi‐scale surface function that is useful to select a set of distinctive points over which the approximate symmetries are defined. In addition, we introduce a vote‐based scheme that is aware of the partiality, and therefore reduces the number of false positive votes for the candidate symmetries. We show the effectiveness of our method in a varied set of 3D shapes and different levels of partiality. Furthermore, we show the applicability of our algorithm in the repair and completion of challenging reassembled objects in the context of cultural heritage.     

A method for predicting the probability of business network profitability

In the design phase of business collaboration, it is desirable to be able to predict the profitability of the business-to-be. Therefore, techniques to assess qualities such as costs, revenues, risks, and profitability have been previously proposed. However, they do not allow the modeler to properly manage uncertainty with respect to the design of the considered business collaboration. In many real collaboration projects today, uncertainty regarding the business’ present or future characteristics is so significant that ignoring it becomes problematic. In this paper, we propose an approach based on the predictive, probabilistic architecture modeling framework (P²AMF), capable of advanced and probabilistically sound reasoning about profitability risks. The P²AMF-based approach for profitability risk prediction is also based on the e³-value modeling language and on the object constraint language. The paper introduces the prediction and modeling approach, and a supporting software tool. The use of the approach is illustrated by means of a case study originated from the Stockholm Royal Seaport smart city project.     

Exploring the relationship between impulsivity and decision-making on mobile devices

Mobile devices offer a common platform for both leisure and work-related tasks, but this has resulted in a blurred boundary between home and work. In this paper, we explore the security implications of this blurred boundary, both for the worker and the employer. Mobile workers may not always make optimal security-related choices when “on the go” and more impulsive individuals may be particularly affected as they are considered more vulnerable to distraction. In this study, we used a task scenario, in which 104 users were asked to choose a wireless network when responding to work demands while out of the office. Eye-tracking data was obtained from a subsample of 40 of these participants in order to explore the effects of impulsivity on attention. Our results suggest that impulsive people are more frequent users of public devices and networks in their day-to-day interactions and are more likely to access their social networks on a regular basis. However, they are also likely to make risky decisions when working on-the-go, processing fewer features before making those decisions. These results suggest that those with high impulsivity may make more use of the mobile Internet options for both work and private purposes, but they also show attentional behavior patterns that suggest they make less considered security-sensitive decisions. The findings are discussed in terms of designs that might support enhanced deliberation, both in the moment and also in relation to longer term behaviors that would contribute to a better work–life balance.     

Spatial inverse query processing

Traditional spatial queries return, for a given query object q, all database objects that satisfy a given predicate, such as epsilon range and k-nearest neighbors. This paper defines and studies inverse spatial queries, which, given a subset of database objects Q and a query predicate, return all objects which, if used as query objects with the predicate, contain Q in their result. We first show a straightforward solution for answering inverse spatial queries for any query predicate. Then, we propose a filter-and-refinement framework that can be used to improve efficiency. We show how to apply this framework on a variety of inverse queries, using appropriate space pruning strategies. In particular, we propose solutions for inverse epsilon range queries, inverse k-nearest neighbor queries, and inverse skyline queries. Furthermore, we show how to relax the definition of inverse queries in order to ensure non-empty result sets. Our experiments show that our framework is significantly more efficient than naive approaches.     

Development of a coupled land-atmosphere satellite data assimilation system for improved local atmospheric simulations

This study developed a coupled land-atmosphere satellite data assimilation system as a new physical downscaling approach, by coupling a mesoscale atmospheric model with a land data assimilation system (LDAS). The LDAS consists of a land surface scheme as the model operator, a radiative transfer model as the observation operator, and the simulated annealing method for minimizing the difference between the observed and simulated microwave brightness temperature. The atmospheric model produces forcing data for the LDAS, and the LDAS produces better initial surface conditions for the modelling system. This coupled system can take into account land surface heterogeneities through assimilating satellite data for a better precipitation prediction. To assess the effectiveness of the new system, 3-dimensional numerical experiments were carried out in a mesoscale area of the Tibetan Plateau during the wet monsoon season. The results show significant improvement compared with a no assimilation regional atmospheric model simply nested from the global model. The surface soil moisture content and its distribution from the assimilation system were more consistent to in situ observations. These better surface conditions affect the land-atmosphere interactions through convection systems and lead to better atmospheric predictability as confirmed by satellite-based cloud observations and in situ sounding observations. Through the use of satellite brightness temperature, the developed coupled land-atmosphere assimilation system has shown potential ability to provide better initial surface conditions and its inputs to the atmosphere and to improve physical downscaling through regional models.