pinecone/core-2020-05-10-deduplication huggingface dataset:
A real-time active routing approach via a database for airport surface movement

Airports face challenges due to the increasing volume of air traffic and tighter environmental restrictions which result in a need to actively integrate speed profiles into conventional routing and scheduling procedure. However, only until very recently, the research on airport ground movement has started to take into account such a speed profile optimisation problem actively so that not only time efficiency but also fuel saving and decrease in airport emissions can be achieved at the same time. It is envisioned that the realism of planning could also be improved through speed profiles. However, due to the multi-objective nature of the problem and complexity of the investigated models (objective functions), the existing speed profile optimisation approach features high computational demand and is not suitable for an on-line application. In order to make this approach more competitive for real-world application and to meet limits imposed by International Civil Aviation Organization for on-line decision time, \ud
this paper introduces a pre-computed database acting as a middleware to effectively separate the planning (routing and scheduling) module and the speed profile generation module. Employing a database not only circumvents duplicative optimisation for the same taxiway segments, but also completely avoids the computation of speed profiles during the on-line decision support owing a great deal to newly proposed database initialization procedures. Moreover, the added layer of database facilitates, in the future, more complex and realistic models to be considered in the speed profile generation module, without sacrificing on-line decision time. The experimental results carried out using data from a major European hub show that the proposed approach is promising in speeding up the search process
Noise and dissipation on coadjoint orbits

We derive and study stochastic dissipative dynamics on coadjoint orbits by
incorporating noise and dissipation into mechanical systems arising from the
theory of reduction by symmetry, including a semidirect-product extension.
Random attractors are found for this general class of systems when the Lie
algebra is semi- simple, provided the top Lyapunov exponent is positive. We
study two canonical examples, the free rigid body and the heavy top, whose
stochastic integrable reductions are found and numerical simulations of their
random attractors are shown
A strategic decision support system framework for energy-efficient technology investments

Energy systems optimization under uncertainty is increasing in its importance due to on-going global de-regulation of the energy sector and the setting of environmental and efficiency targets which generate new multi-agent risks requiring a model-based stakeholders dialogue and new systemic regulations. This paper develops an integrated framework for decision support systems (DSS) for the optimal planning and operation of a building infrastructure under appearing systemic de-regulations and risks. The DSS relies on a new two-stage, dynamic stochastic optimization model with moving random time horizons bounded by stopping time moments. This allows to model impacts of potential extreme events and structural changes emerging from a stakeholders dialogue, which may occur at any moment of the decision making process. The stopping time moments induce endogenous risk aversion in strategic decisions in a form of dynamic VaR-type systemic risk measures dependent on the system’s structure. The DSS implementation via an algebraic modeling language (AML) provides an environment that enforces the necessary stakeholders dialogue for robust planning and operation of a building infrastructure. Such a framework allows the representation and solution of building infrastructure systems optimization problems, to be implemented at the building level to confront rising systemic economic and environmental global changes
Thermal coupling in layered convection: evidence for an interface viscosity control from mechanical experiments and marginal stability analysis

Convection in a two-layer system (silicone oil over glycerol, in particular) is studied. Two types of studies have been performed. (1) In the laboratory, we analyse the dynamical role of the interface, by inducing roll-like motions in one of the liquid layers, using a system of two inversely rotating cylinders. Streamlines and velocities on both sides of the interface are measured, by observing suspended aluminum particles. The results strongly depend upon the sense of rotation of the cylinders (convergence or divergence), and upon the amplitude of the imposed velocity. This implies an interface strength, which is of the same order as the volume viscous strength, and that can be associated to a large interface viscosity. (2) A numerical study of convective marginal stability in a two-layer system has been performed. The physical properties of the silicone oil/glycerol system are used, and special attention is given to the influence of interface viscosity. The role of varying the depth ratio, the deformation of the interface, the temperature-dependence of interface tension, and the density ratio is reviewed. It is shown that none of these effects, when realistic values are taken, is able to modify the preferred type of coupling at the threshold: it remains “mechanical” coupling (downwellings in the upper layer remain above uprisings in the lower layer). However, the type of coupling is changed when the interface viscosity is introduced, with values compatible with the experimental observations: “thermal” coupling (uprisings above uprisings) becomes the preferred convective mode. This result removes the contradiction there was until now between the observation of “thermal” coupling in laboratory convection experiments, and the prediction of “mechanical” coupling obtained from marginal stability analysis and numerical experiments
Could occupation duration be related to the diversity of faunal remains in Mesolithic shell middens along the European Atlantic seaboard?

International audienceIn order to define the Mesolithic populations that came to settle on the European Atlantic seaboard, it is essential to assess the duration and continuity of human occupation. Although our knowledge of the geographical distribution of these populations is largely truncated by archaeological bias, the presence of more than 240 Mesolithic shell middens along the European Atlantic coast enables us to establish an overview of the published data on the dwelling patterns (seasonal, permanent, recurrent or limited in time) of these groups of maritime hunter-gatherers. A review of the literature shows that information on human occupations is lacking for many known Mesolithic shell middens. Moreover, the data leading to the identification of settlement patterns prove to be very heterogeneous from one site to another. Marine molluscs play a special role among the artefacts used to define the attraction of human populations for the coast, and help us to understand settlement. Although molluscs represent a major component of Mesolithic shell middens, it has taken several decades for the analysis of these faunal remains to be considered from the outset in excavations. One of the questions addressed here is whether the diversity of faunal remains in these shell middens can be related to the duration of human occupations on the coast. This question is based on the idea that people staying in the same settlement for several seasons can explore the surrounding area in greater detail. In this paper we observe that the diversity of faunal remains, including seashells, is not only dependent on the way of life of coastal people and settlement duration. It also affects other factors, such as the accessibility of more or less diversified environments and their resources in the vicinity of settlements and the degree of adaptability of humans exploiting similar resources
The potential for CO2 emissions trading in transport: the case of personal vehicles and freight

From the issue entitled "Special Issue: Transport, energy and greenhouse gases: perspectives on demand limitation Guest Editors: Charles Raux & Martin E.H. Lee-Gosselin"International audienceTransport currently accounts for around 25-30% of global CO2 emissions and this contribution is growing rapidly. Moreover, road transport holds by far the major part in these emissions. Because of the social and political reluctance to increase fuel taxation, it is of some interest to explore the inclusion of road transport in emission trading schemes. Starting from the theory about tradable permits, their relevance in transport emissions, their appropriate targets and their potential for practical implementation are analysed. Two proposals of "tradable rights for fuel consumption" are presented, the one for drivers of private vehicles, the other for freight transportation. Finally, potential pitfalls and implementation issues are also discussed. It is concluded that the cost of operating markets of fuel rights would be the price to be paid for an effective involvement of the transport sector in the effort to reduce emissions
LARGE PLAYERS IN THE NANOGAME: DEDICATED NANOTECH SUBSIDIARIES OR DISTRIBUTED NANOTECH CAPABILITIES?

Working Paper Serie RMT (WPS 10-09) , 26 pInternational audienceNanotechnologies are reshaping the boundaries between industries, combining two aspects of innovation - both enhancing competences based on cumulative knowledge and experience and destroying competences by forcing the renewal of the firm's knowledge base. To analyze how worldwide R&D leaders adapt to this new technology, we conduct an econometric analysis of about 3,000 subsidiaries of the largest R&D spenders. We find that large groups are creating medium size subsidiary companies to explore nanotechnologies. Knowledge circulates mostly amongst subsidiaries within the same group and scientific clusters do not affect their involvement in nanotechnologies. Nanotechnologies remain marginal within these subsidiaries' knowledge bases and are distributed within corporate groups, stimulating recombination between nanotechnology and other technologie
Method validation for the analysis of estrogens (including conjugated compounds) in aqueous matrices

Estrogens act as endocrine disruptors and are known to be discharged into the aquatic environment via effluents from wastewater- treatment plants (WWTPs). Efficient analytical protocols are needed to identify and to quantify estrogens in wastewaters and aquatic environments in order to study their sources, levels of exposure and modes of transfer. We developed and validated a new analytical method for estrogens in water. It quantifies five estrogenic hormones and their conjugated forms at the ng/L level in rivers, WWTP influents and effluents, with satisfactory precision (relative standard deviation of within-day analytical recoveries is usually <22%). The method is statistically specific, thanks to using perdeuterated hormones as internal surrogates, which proved to be an efficient means of correcting for matrix effects
Characterizing groundwater flow and heat transport in fractured rock using fiber-optic distributed temperature sensing

International audienceWe show how fully distributed space-time measurements with Fiber-Optic Distributed Temperature Sensing (FO-DTS) can be used to investigate groundwater flow and heat transport in fractured media. Heat injection experiments are combined with temperature measurements along fiber-optic cables installed in boreholes. Thermal dilution tests are shown to enable detection of cross-flowing fractures and quantification of the cross flow rate. A cross borehole thermal tracer test is then analyzed to identify fracture zones that are in hydraulic connection between boreholes and to estimate spatially distributed temperature breakthrough in each fracture zone. This provides a significant improvement compared to classical tracer tests, for which concentration data are usually integrated over the whole abstraction borehole. However, despite providing some complementary results, we find that the main contributive fracture for heat transport is different to that for a solute tracer
Rare earth elements complexation with humic acid

The binding of rare earth elements (REE) to humic acid (HA) was studied by combining ultrafiltration and Inductively Coupled Plasma Mass Spectrometry techniques. REE­HA complexation experiments were performed at various pH conditions (ranging from 2 to 10.5) using a standard batch equilibration method. Results show that the amount of REE bound to HA strongly increases with increasing pH. Moreover, a Middle-REE (MREE) downward concavity is evidenced by REE distribution patterns at acidic pH. Modelling of the experimental data using Humic Ion Binding Model VI provided a set of log KMA values (i.e., the REE­HA complexation constants specific to Model VI) for the entire REE series. The log KMA pattern obtained displays a MREE downward concavity. Log KMA values range from 2.42 to 2.79. These binding constants are in good agreement with the few existing datasets quantifying the binding of REE with humic substances but quite different from a recently published study which evidence a lanthanide contraction effect (i.e., continuous increase of the constant from La to Lu). The MREE downward concavity displayed by REE­HA complexation pattern determined in this study compares well with results from REE­fulvic acid (FA) and REE­acetic acid complexation studies. This similarity in the REE complexation pattern suggests that carboxylic groups are the main binding sites of REE in HA. This conclusion is further illustrated by a detailed review of published studies for natural, organic-rich, river- and ground-waters which show no evidence of a lanthanide contraction effect in REE pattern. Finally, application of Model VI using the new, experimentally determined log KMA values to World Average River Water confirms earlier suggestions that REE occur predominantly as organic complexes (= 60%) in the pH range between 5­5.5 and 7­8.5 (i.e., in circumneutral pH waters). The only significant difference as compared to earlier model predictions made using estimated log KMA values is that the experimentally determined log KMA values predict a significantly higher amount of Light-REE bound to organic matter under alkaline pH conditions
Interleukin-6 promoter polymorphism interacts with pain and life stress influencing depression phenotypes

Interleukin-6 (IL-6) has emerged as a potent biomarker for depression as its elevated plasma levels in patients with clinical depression have been confirmed by meta-analyses. Increased plasma IL-6 concentration was associated with various psychological stress factors and physical disorders accompanied by pain. Another  modulator of the IL-6 level is rs1800795, a promoter polymorphism in the IL-6 gene which is able to influence its expression rate. Therefore, we examined in a  Hungarian population sample of 1053 volunteers with European origins if rs1800795 polymorphism can affect depression symptoms measured by Zung Self-rating Depression Scale (ZSDS), and Brief Symptom Inventory (BSI). We also investigated  the interactions of the polymorphism with reported painful physical conditions and Recent Negative Life Events (RLE) measured by the List of Life Threatening Experiences. Rs1800795 significantly interacted with both RLE and painful condition on depressive symptoms measured by ZSDS and BSI using different heritability models, while no main effects of the polymorphism were identified. After correction for multiple testing only the rs1800795 x RLE interaction effect (recessive model) remained significant on the BSI score, while both RLE and painful conditions significantly interacted on the ZSDS. In conclusion, the functional IL-6 rs1800795 polymorphism in interaction with various stress factors increases the risk of depression and has a greater impact on symptoms measured by the ZSDS. Thus, IL-6 and other cytokines may be more relevant in the development  of somatic symptoms compared to affective signs of depression, delineating a specific genotype-phenotype relationship in this heterogeneous disorder
Lightweight String Reasoning in Model Finding

International audienceModels play a key role in assuring software quality in the model-driven approach. Precise models usually require the definition of well-formedness rules to specify constraints that cannot be expressed graphically. The Object Constraint Language (OCL) is a de-facto standard to define such rules. Techniques that check the satisfiability of such models and find corresponding instances of them are important in various activities, such as model-based testing and validation. Several tools for these activities have been developed, but to our knowledge, none of them supports OCL string operations on scale that is sufficient for, e.g., model-based testing. As, in contrast, many industrial models do contain such operations, there is evidently a gap. We present a lightweight solver that is specifically tailored to generate large solutions for tractable string constraints in model finding, and that is suitable for directly express the main operations of the OCL datatype String. It is based on constraint logic programming (CLP) and constraint handling rules (CHR), and can be seamlessly combined with other constraint solvers in CLP. We have integrated our solver into the EMFtoCSP model finder, and we show that our implementation efficiently solves several common string constraints on a large instances
Non-Obviousness and Complementary Innovations

I am grateful to the publisher, Elsevier, for letting the manuscript being archived in this Open Access repository.International audienceThis paper explores which patent policy should be applied to complementary innovations that are aggregated into broader technologies. I compare a setting in which complementary innovations must be bundled prior to patenting, with a second setting in which they can be patented separately. The first setting can improve static efficiency by avoiding the costs resulting from the scattering of complementary patents. But it also limits the disclosure of small innovations, which may lead to inefficient R&D cost duplications. A model capturing these effects shows that patenting complementary innovations separately is not efficient when innovations can be developed rapidly. This result justifies the enforcement of a severe “inventive step” or “non-obviousness” requirement in sectors where complementary innovations are frequent
Can Culture Account for Investment Expectations?

International audienceUntil recently, risk-taking in investment decisions has been explained bycognitive biases and emotional urges. I would like to propose an alternativeexplanation, based on the work of Pierre Bourdieu, who links cultural capital torisk-taking. His concept of cultural capital has a very broad meaning, as itencompasses technical skills, aesthetic preferences, verbal facility, general culturalawareness, educational credentials, and artistic competencies. On theoreticalgrounds, one can assume that a high level of cultural capital enables the taming ofuncertainty and allows for temporal horizons that cover longer terms. I test thishypothesis by conducting and analyzing a survey of 307 entrepreneurs. I define risktakingin two ways: (i) in a somewhat mainstream way, on the basis of expectedutility, and (ii) in a heterodox way, in a qualitative, context-dependent setting. Ifind that, in both cases, there seems to be a link between cultural capital and risktaking.Furthermore, it seems to make financing issues more salient. I conclude byopening a discussion about the heterogeneity of entrepreneurs and their animalspirits
Current Use and Developments Needed for Optimal Design in Pharmacometrics: A Study Performed Among DDMoRe's European Federation of Pharmaceutical Industries and Associations Members

International audienceMethods and software tools for optimal design in nonlinear mixed effect models, based on the Fisher information matrix, have been developed for a decade. Academic groups regularly proposed new versions. Present tools do not incorporate adaptive designs for these models although prior information is needed and adaptive designs are increasingly used in drug development. We conducted a study among drug companies of the Drug and Disease Model Resources consortium to identify current practices and expectations
Mixtures of stochastic differential equations with random effects: Application to data clustering

International audienceWe consider N independent stochastic processes (Xi(t), t ∈ [0, Ti]), i = 1,. .. , N , defined by a stochastic differential equation with drift term depending on a random variable φi. The distribution of the random effect φi is a Gaussian mixture distribution, depending on unknown parameters which are to be estimated from the continuous observation of the processes Xi. The likelihood of the observation is explicit. When the number of components is known, we prove the consistency of the exact maximum likelihood estimators and use the EM algorithm to compute it. When the number of components is unknown, BIC (Bayesian Information Criterion) is applied to select it. To assign each individual to a class, we define a classification rule based on estimated posterior probabilities. A simulation study illustrates our estimation and classification method on various models. A real data analysis is performed on growth curves with convincing results
Monitoring stimulated emission at the single-photon level in one-dimensional atoms

International audienceWe theoretically investigate signatures of stimulated emission at the single-photon level for a two-level atom interacting with a one-dimensional light field. We consider the transient regime where the atom is initially excited, and the steady-state regime where the atom is continuously driven with an external pump. The influence of pure dephasing is studied, clearly showing that these effects can be evidenced with state-of-the-art solid-state devices. We finally propose a scheme to demonstrate the stimulation of one optical transition by monitoring another one, in three-level one-dimensional atoms
An experiment with reactive data-flow tasking in active robot vision

International audienceWe present an experiment of the synchronous approach to reactive systems programming, and particularly the SIGNAL language, ap- plied to a significant problem in robot vision: active visual recon- struction. This application consists of the specification of a system dealing with various domains such as robot control, computer vi- sion and transitions between different modes of control. It illustrates the adequacy in such domains of SIGNAL, a data flow programming language and environment. The SIGNAL programming environment features tools for formal specification, analysis, consistency check- ing and code generation. SIGNAL and its language-level extension for task preemption SIGNALGTι ̇ are used at the different levels of the application: data-flow function for the camera motion control (vi- sual servoing), reconstruction method (in parallel to visual servoing, involving the dynamical processes), and reconstruction of complex scenes (with transitions between several robotics tasks). The com- bination of these levels constitutes a hybrid behavior with (sampled) continuous and discrete transitions. These techniques are validated experimentally by an implementation on a robotic cell