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With the advent of 5G and the evolution of Internet protocols, industrial applications are moving from vertical solutions to general purpose IP-based infrastructures that need to meet deterministic Quality of Service (QoS) requirements. The IETF DetNet working group aims at providing an answer to this need with support for (i) deterministic worst-case latency and jitter, and (ii) zero packet loss for time-sensitive traffic. In this paper we focus on the joint routing and scheduling problem in large scale deterministic networks using Cycle Specified Queuing and Forwarding (CSQF), an extension of Cyclic Queuing and Forwarding (CQF) with multiple transmission queues and support of segment routing. In this context, we present two centralized algorithms to maximize traffic acceptance for network planning and online flow admission. We propose an effective solution based on column generation and dynamic programming. Thanks to the reinforcement of the model with valid inequalities, we improve the upper bound and the solution. We demonstrate on realistic instances that we reach an optimality gap smaller than 10% in a few seconds. Finally, we also derive an ultra-fast adaptive greedy algorithm to solve the problem at the cost of a small extra gap., Comment: To appear in Elsevier Computer Communications

This paper provides comprehensive cross-country evidence on the relationship between earnings inequality and intra-generational mobility by simulating individual earnings and employment trajectories in the long-term using short panel data for 24 OECD countries. On average across countries, about 25% of earnings inequality in a given year evens out over the life cycle as a result of mobility. Moreover, mobility is not systematically higher in countries with more earnings inequality in general. However, a positive and statistically significant relationship is found only in the bottom of the distribution. This reflects the role of mobility between employment and unemployment and not that of mobility up and down the earnings ladder.

The Laser MegaJoule (LMJ) is a high-power laser dedicated to laser-plasma experiments. At the beginning of the project in the mid-1990s, an optical metrology laboratory was created at CEA to help accomplish all the steps in the construction of this laser. This paper proposes an overview of the capabilities of this metrology laboratory in four main fields: surface imperfections, photometry, laser damage measurement, and wavefront measurement. The specificities for high-power laser optics in each domain are highlighted as well as the specific features that make our instruments unique.

Background A better understanding of the influenza epidemiology among primary care workers could guide future recommendations to prevent transmission in primary care practices. Therefore, we designed a pilot study to assess the feasibility of using a work-based online influenza surveillance system among primary care workers. Such an approach is of particular relevance in the context of the coronavirus disease (COVID-19) pandemic, as its findings could apply to other infectious diseases with similar mechanisms of transmission. Objective This study aims to determine the feasibility of using a work-based online influenza surveillance system for primary care workers in Switzerland. Methods Physicians and staff of one walk-in clinic and two selected primary care practices were enrolled in this observational prospective pilot study during the 2017-2018 influenza season. They were invited to record symptoms of influenza-like illness in a weekly online survey sent by email and to self-collect a nasopharyngeal swab in case any symptoms were recorded. Samples were tested by real-time polymerase chain reaction for influenza A, influenza B, and a panel of respiratory pathogens. Results Among 67 eligible staff members, 58% (n=39) consented to the study and 53% (n=36) provided data. From the time all participants were included, the weekly survey response rate stayed close to 100% until the end of the study. Of 79 symptomatic episodes (mean 2.2 episodes per participant), 10 episodes in 7 participants fitted the definition of an influenza-like illness case (attack rate: 7/36, 19%). One swab tested positive for influenza A H1N1 (attack rate: 3%, 95% CI 0%-18%). Swabbing was considered relatively easy. Conclusions A work-based online influenza surveillance system is feasible for use among primary care workers. This promising methodology could be broadly used in future studies to improve the understanding of influenza epidemiology and other diseases such as COVID-19. This could prove to be highly useful in primary care settings and guide future recommendations to prevent transmission. A larger study will also help to assess asymptomatic infections.

A growing shortage of general practitioners (GPs), in Switzerland and around the world, has forced countries to find new ways to attract young physicians to the specialty. In 2017, Switzerland began to fund hundreds of new study places for medical students. This wave of young physicians will soon finish University and be ready for postgraduate training. We hypothesized that an attractive postgraduate training program would encourage interested young physicians to pursue a GP career. This is a cross-sectional survey of young physicians from the Swiss Young General Practitioners Association (JHaS), members of Cursus Romand de médecine de famille (CRMF), and all current medical students (5 th or 6 th years) (n = 554) in Switzerland, excluding students indicating definitely not to become GPs. We asked all if they were likely to become a GP (Likert: 1-10), and then asked them to score general features of a GP training curriculum, and likely effects of the curriculum on their career choice (Likert scale). They then rated our model curriculum (GO-GP) for attractiveness and effect (Likert Scales, open questions). Most participants thought they would become GPs (Likert: 8 of 10). Over 90% identified the same features as an important part of a curriculum ("yes" or "likely yes"): Our respondents thought the GO-GP curriculum was attractive (7.3 of 10). It was most attractive to those highly motivated to become GPs. After reviewing the curriculum, most respondents (58%) felt GO-GP would make them more likely to become a GP. Almost 80% of respondents thought an attractive postgraduate training program like GO-GP could motivate more young physicians to become GPs. Overall, medical students and young physicians found similar features attractive in the general and GO-GP curriculum, regardless of region or gender, and thought an attractive curriculum would attract more young doctors to the GP specialty. Key points An attractive postgraduate training program in general practice can attract more young physicians to become GPs. In this study cross-sectional survey including medical students (n = 242) and young physicians (n = 312) we presented general features for a curriculum and a model curriculum for general practice training, for evaluation of attractiveness to our study population. General practice training curriculum provides flexibility in choice of rotations, access to short rotations in a wide variety of medical specialties, training in specialty practices as well, mentoring and career guidance by GPs and guidance in choosing courses/certificate programs necessary for general practice. These findings help building attractive postgraduate training programs in general practice and fight GP shortage.

Value creation from open data faces several challenges, among them the risk to be too supply-driven, or the lack of incentives for the re-use. This paper reports an ongoing research program on the stimulation role in an open data ecosystem to mitigate these concerns. First, we present the empirical roots of this role that can be drawn from several initiatives undertaken in different countries and trying to bypass the obstacles faced by potential open data reusers. We discuss the importance of a legal framework inductive to foster innovation and transnationality of the re-use. Then, we introduce the BE-GOOD program which aims to develop new methods to build an open data ecosystem.

This paper provides comprehensive cross-country evidence on the relationship between earnings inequality and intra-generational mobility by simulating individual earnings and employment trajectories in the long-term using short panel data for 24 OECD countries. On average across countries, about 25% of earnings inequality in a given year evens out over the life cycle as a result of mobility. Moreover, mobility is not systematically higher in countries with more earnings inequality in general. However, a positive and statistically significant relationship is found only in the bottom of the distribution. This reflects the role of mobility between employment and unemployment and not that of mobility up and down the earnings ladder.

Glioblastoma (GBM) is the most malignant type of primary brain tumor with a very poor prognosis. The actual standard protocol of treatment for GBM patients consists of radiotherapy and concomitant temozolomide (TMZ). However, the therapeutic efficacy of this treatment is limited due to tumor recurrence and TMZ resistance. Recently isolated, glioma stem-like cells (GSCs) are thought to represent the population of tumorigenic cells responsible for GBM resistance and recurrence following surgery and chemotherapy. In addition, MGMT (O6-methylguanine-methyltransferase) methylation is considered as one of the principal mechanisms contributing to TMZ sensitivity of GBM. In this study we have isolated GSCs from 10 adult GBM patients and investigated the relationship between MGMT methylation status and Temozolomide (TMZ) sensitivity of these lines grown either in stem-like or differentiation promoting conditions. Sensitivity to TMZ was significantly associated with MGMT methylation status in cells committed to differentiation but not in stem-like cells. In addition, patients harboring highly methylated MGMT promoters had a longer overall survival. These results reveal the importance of the differentiation process when considering the predictive value of MGMT status in GSCs for clinical response to TMZ.

Purpose: We present a fully automatic algorithm for the segmentation of the prostate in three-dimensional magnetic resonance (MR) images. Method: Our approach requires the use of an anatomical atlas which is built by computing transformation fields mapping a set of manually segmented images to a common reference. These transformation fields are then applied to the manually segmented structures of the training set in order to get a probabilistic map on the atlas. The segmentation is then realized through a two stage procedure. In the first stage, the processed image is registered to the probabilistic atlas. Subsequently, a \textit{probabilistic segmentation} is obtained by mapping the probabilistic map of the atlas to the patient's anatomy. In the second stage, a deformable surface evolves towards the prostate boundaries by merging information coming from the \textit{probabilistic segmentation}, an \textit{image feature model} and a \textit{statistical shape model}. During the evolution of the surface, the \textit{probabilistic segmentation} allows the introduction of a \textit{spatial constraint} that prevents the deformable surface from leaking in an unlikely configuration. Results: The proposed method is evaluated on 36 exams, that were manually segmented by a single expert. A median Dice similarity coefficient of 0.86 and an average surface error of 2.41 mm are achieved. Conclusion: By merging prior knowledge, the presented method achieves a robust and completely automatic segmentation of the prostate in MR images. Results show that the use of a \textit{spatial constraint} is useful to increase the robustness of the deformable model comparatively to a deformable surface that is only driven by an image appearance model.

Purpose: This paper presents the preliminary results of a semi-automatic method for prostate segmentation of Magnetic Resonance Images (MRI) which aims to be incorporated in a navigation system for prostate brachytherapy. Methods: The method is based on the registration of an anatomical atlas computed from a population of 18 MRI exams onto a patient image. An hybrid registration framework which couples an intensity-based registration with a robust point-matching algorithm is used for both atlas building and atlas registration. Results: The method has been validated on the same dataset that the one used to construct the atlas using the "leave-one-out method". Results gives a mean error of 3.39 mm and a standard deviation of 1.95 mm with respect to expert segmentations. Conclusions: We think that this segmentation tool may be a very valuable help to the clinician for routine quantitative image exploitation., Comment: International Journal of Computer Assisted Radiology and Surgery (2008) 000-999

Efficient job scheduling algorithms needed to improve the resource utilization in cloud computing, the role of a good scheduling algorithm on cloud computing is to minimize the total completion time for last job on the system. In this paper, we present a genetic-based task scheduling algorithms in order to minimize Maximum Completion Time Makespan. These algorithms combines different techniques such as list scheduling and earliest completion time (ECT) with genetic algorithm. We reviewed, evaluated and compared the proposed algorithms against one of the well-known Genetic Algorithms available in the literature, which has been proposed for task scheduling problem on heterogeneous computing systems. After an exhaustive computational analysis we identify that the proposed Genetic algorithms show a good performance overcoming the evaluated method in different problem sizes and complexity for a large benchmark set of instances.

In this paper, we present all the successive steps for realizing dual-band infrared detectors operating in the mid-wavelength infrared (MWIR) band. High crystalline quality HgCdTe multilayer stacks have been grown by molecular beam epitaxy (MBE) on CdZnTe and CdTe/Ge substrates. Material characterization in the light of high-resolution x-ray diffraction (HRXRD) results and dislocation density measurements are exposed in detail. These characterizations show some striking differences between structures grown on the two kinds of substrates. Device processing and readout circuit for 128×128 focal-plane array (FPA) fabrication are described. The electro-optical characteristics of the devices show that devices grown on Ge match those grown on CdZnTe substrates in terms of responsivity, noise measurements, and operability.

Brachytherapy for localized prostate cancer consists in destroying cancer by introducing iodine radioactive seeds into the gland through hollow needles. The planning of the position of the seeds and their introduction into the prostate is based on intraoperative ultrasound (US) imaging. We propose to optimize the global quality of the procedure by: i) using 3D US; ii) enhancing US data with MRI registration; iii) using a specially designed needle-insertion robot, connected to the imaging data. The imaging methods have been successfully tested on patient data while the robot accuracy has been evaluated on a realistic deformable phantom.

Improving school-to-work transitions and ensuring better career opportunities for youth after labour market entrance are common goals in emerging and advanced economies as they can contribute to raising the productive potential of the economy and to increasing social cohesion. However, the challenges faced in achieving these objectives and the policies required vary between emerging and advanced economies. This paper analyses youth labour market outcomes in 16 countries: eight emerging countries and eight advanced economies. In light of this analysis, it also discusses differences and similarities in the policy measures countries have at their disposal to tackle the key emerging challenges.

The Open Data movement has mainly been a data provision movement. The release of Open Data is usually motivated by (i) government transparency (citizen access to government data), (ii) the development of services by third parties for the benefit for citizens and companies (typically smart city approach), or (iii) the development of new services that stimulate the economy. The success of the Open Data movement and its return on investment should therefore be assessed among other criteria by the number and impact of the services created based on those data. In this paper, we study the development of services based on open data and means to make the data opening process more effective.

Hybrid InGaAs focal plane arrays are very interesting for night vision because they can benefit from the nightglow emission in the Short Wave Infrared band. Through a collaboration between III-V Lab and CEA-Leti, a 640x512 InGaAs image sensor with 15μm pixel pitch has been developed. The good crystalline quality of the InGaAs detectors opens the door to low dark current (around 20nA/cm2 at room temperature and -0.1V bias) as required for low light level imaging. In addition, the InP substrate can be removed to extend the detection range towards the visible spectrum. A custom readout IC (ROIC) has been designed in a standard CMOS 0.18μm technology. The pixel circuit is based on a capacitive transimpedance amplifier (CTIA) with two selectable charge-to-voltage conversion gains. Relying on a thorough noise analysis, this input stage has been optimized to deliver low-noise performance in high-gain mode with a reasonable concession on dynamic range. The exposure time can be maximized up to the frame period thanks to a rolling shutter approach. The frame rate can be up to 120fps or 60fps if the Correlated Double Sampling (CDS) capability of the circuit is enabled. The first results show that the CDS is effective at removing the very low frequency noise present on the reference voltage in our test setup. In this way, the measured total dark noise is around 90 electrons in high-gain mode for 8.3ms exposure time. It is mainly dominated by the dark shot noise for a detector temperature settling around 30°C when not cooled. The readout noise measured with shorter exposure time is around 30 electrons for a dynamic range of 71dB in high-gain mode and 108 electrons for 79dB in low-gain mode.

International audience; The poor signal-to-noise ratio in transrectal ultrasound (TRUS) images makes the fully automatic segmentation of the prostate challenging and most approaches proposed in the literature still lack robustness and accuracy. However, it is relatively straightforward to obtain high quality segmentations in magnetic resonance (MR) images. In the context of MR to TRUS data fusion the information gathered in the MR images can hence provide a strong prior for US segmentation. In this paper, we describe a method to non-linearly register a patient specific mesh of the prostate build from MR images to TRUS volume. The MR prior provides shape and volume constraints that are used to guide the MR-to-TRUS surface deformation, in collaboration with a US image contour appearance model. The anatomical point correspondences between the MR and TRUS surfaces are obtained implicitly. The method was validated on 30 pairs of MR/TRUS patient exams and achieves a mean Dice value 0.85 and a mean surface error of 2.0 mm.

The InfraRed staring arrays developed by SOFRADIR are more and more compact and offer system solutions for wide range of IR wavebands. IR detectors have been taken to an even more advanced level of sophistication to achieve staring arrays high performances. Latest developments have also been focused on the silicon readout circuit. Digital conversion on chip is one of the recent progresses in this field of activity. In order to match each system requirements, on chip high performance ultra low power ADCs have been developed. Beyond the performance aspects, digital focal plane arrays can be considered as the first step towards low cost Dewar family, since they allow for a more simple electrical interface on Dewar designs and on chip image processing. Recent results concerning these new readout circuit architectures are presented in this paper.

This paper presents recent studies on the mechanical support system of Laser MegaJoule large dimension optical components. The dimensions of these optical components and their orientation resulted in considerable distortions due to gravity. An original and very simple method based on an isostatic mounting together with industrial springs located on the edges of the component is presented. Springs are used to compensate for gravity distortion. This system provides improved support performance at very low cost (for example, PV less than 0.5μm for a 610mm * 430mm * 80mm silicate optic at 45° from the vertical). The support systems are optimized with IDEAS finite element analysis software and validated with experimental measurements.

International audience; This paper presents a semi-automatic method for tracking the mitral valve leaflet in transesophageal echocardiography. The algorithm requires a manual initialization and then segments an image sequence. The use of two constrained active contours and curve fitting techniques results in a fast segmentation algorithm. The active contours successfully track the inner cardiac muscle and the mitral valve leaflet axis. Three sequences have been processed and the generated muscle outline and leaflet axis have been visually assessed by an expert. This work is a part of a more general project which aims at providing real-time detection of the mitral valve leaflet in transesophageal echocardiography images.

The purpose of this paper is to present the electro-optical performances of dual-band detector working in a fully spatially coherent mode, with small pixel pitch. The successive steps of device fabrication are first exposed including molecular beam epitaxy, technological processing and readout circuit design. It is shown that very high quality multiple layer heterostructures of HgCdTe can be grown and processed into 256x256 arrays of 25μm pitch mesas, each mesa including two photodiodes with different cut-off wavelength ranging in the midwave infrared (MWIR). Characterization of these focal plane arrays (FPAs) shows very good homogeneity, low defect density and operabilities usually above 99% for both responsivity and noise equivalent thermal difference (NETD).

To reach most industrial applications and then complex geometries, research efforts are headed in recent years to develop high order methods on CFD and CAA, which need in most cases unstructured grids. Among others, the finite volume method seems to be a good candidate because of its ease of implementation and its adaptation for complex geometries, but unfortunately it is difficult to achieve space flux derivation schemes with very high order of accuracy for unsteady cases. In this paper, we present three strategies to preserve higher order of accuracy for unsteady cases using the new finite volume method based on Moving Least Squares approximations to solve Linearized Euler Equations on unstructured grids. The adopted strategies are: (1) a zero-mean variables reconstruction using explicit time scheme, (2) a full mass matrix formulation to preserve the residuals order using an implicit BDF preconditioned Newton/Krylov time solver, and finally (3) a lumped mass matrix formulation based on a residual ratio and using an explicit time solver. A comparison between the accuracy of the three formulations is made, and several benchmark problem tests are performed.