In this paper, we address the Bounded Cardinality Hub Location Routing with Route Capacity wherein each hub acts as a transshipment node for one directed route. The number of hubs lies between a minimum and a maximum and the hub-level network is a complete subgraph. The transshipment operations take place at the hub nodes and flow transfer time from a hub-level transporter to a spoke-level vehicle influences spoke- to-hub allocations. We propose a mathematical model and a branch-and-cut algorithm based on Benders decomposition to solve the problem. To accelerate convergence, our solution framework embeds an efficient heuristic producing high-quality solutions in short computation times. In addition, we show how symmetry can be exploited to accelerate and improve the performance of our method.

In this paper, we address the Bounded Cardinality Hub Location Routing with Route Capacity wherein each hub acts as a transshipment node for one directed route. The number of hubs lies between a minimum and a maximum and the hub-level network is a complete subgraph. The transshipment operations take place at the hub nodes and flow transfer time from a hub-level transporter to a spoke-level vehicle influences spoke- to-hub allocations. We propose a mathematical model and a branch-and-cut algorithm based on Benders decomposition to solve the problem. To accelerate convergence, our solution framework embeds an efficient heuristic producing high-quality solutions in short computation times. In addition, we show how symmetry can be exploited to accelerate and improve the performance of our method.

In this paper we present a mathematical model of the train dynamics in a linear metro line system with demand-dependent run and dwell times. On every segment of the line, we consider two main constraints. The first constraint is on the travel time, which is the sum of run and dwell time. The second one is on the safe separation time, modeling the signaling system, so that only one train can occupy a segment at a time. The dwell and the run times are modeled dynamically, with two control laws. The one on the dwell time makes sure that all the passengers can debark from and embark into the train. The one on the run time ensures train time-headway regularity in the case where perturbations do not exceed a run time margin. We use a Max-plus algebra approach which allows to derive analytic formulas for the train time-headway and frequency depending on the number of trains and on the passenger demand. The analytic formulas, illustrated by 3D figures, permit to understand the phases of the train dynamics of a linear metro line being operated as a transport on demand system.

The martensitic transformation is a fundamental physical phenomenon at the origin of important industrial applications. However, the underlying microscopic mechanism, which is of critical importance to explain the outstanding mechanical properties of martensitic materials, is still not fully understood. This is because for most martensitic materials the transformation is a fast process that makes in situ studies extremely challenging. Noble solids krypton and xenon undergo a progressive pressure induced fcc to hcp martensitic transition with a very wide coexistence domain. Here, we took advantage of this unique feature to study the detailed mechanism of the transformation by employing in situ X-ray diffraction and absorption. We evidenced a four stages mechanism where the lattice mismatch between the fcc and hcp forms plays a key role in the generation of strain. We also determined precisely the effect of the transformation on the compression behavior of these materials.

The ROC curve and the corresponding AUC are popular tools for the evaluation of diagnostic tests. They have been recently extended to assess prognostic markers and predictive models. However, due to the many particularities of time-to-event outcomes, various definitions and estimators have been proposed in the literature. This review article aims at presenting the ones that accommodate to right-censoring, which is common when evaluating such prognostic markers.

SiC/SiC composite tubes are studied as materials for nuclear fuel cladding. A thorough understanding on the mechanisms of damage to this material requires both an experimental and a numerical study. In situ tensile tests were performed under X-ray tomography at the SOLEIL synchrotron. Post processing methods have been developed to analyze the microstructure, measure the deformation and characterize qualitatively and quantitatively the damage mechanisms inside the material. The tomographic images provide 3D descriptions on the microstructure, which are direct input data for the numerical simulation based on FFT. The use of real microstructures makes it possible to combine the simulation results directly with the experimental observations.

This paper introduces a novel model-based clustering approach for clustering time series which present changes in regime. It consists of a mixture of polynomial regressions governed by hidden Markov chains. The underlying hidden process for each cluster activates successively several polynomial regimes during time. The parameter estimation is performed by the maximum likelihood method through a dedicated Expectation-Maximization (EM) algorithm. The proposed approach is evaluated using simulated time series and real-world time series issued from a railway diagnosis application. Comparisons with existing approaches for time series clustering, including the stand EM for Gaussian mixtures, $K$-means clustering, the standard mixture of regression models and mixture of Hidden Markov Models, demonstrate the effectiveness of the proposed approach.

We present in this article traffic flow and control models for the train dynamics in metro lines. The first model, written in the max-plus algebra, takes into account minimum running, dwell and safety time constraints, without any control of the train dwell times at platforms, and without consideration of the passenger travel demand. We show that the dynamics are stable and converge to stationary regimes with a unique asymptotic average growth rate. Moreover, the asymptotic average train time-headway, dwell time, as well as close-in time, are derived analytically, as functions of the number of running trains on the metro line. We then introduce, in a second model, the effect of the passenger demand on the train dwell times at platforms. We review that, if this effect is not well controlled, then the traffic is unstable. Finally, we propose a traffic control model which deals with this instability, by well controlling the effect of passenger arrivals on the train dwell times at platforms. We show that the dynamics are stable and converge to stationary regimes with a unique asymptotic average growth rate. We then calculate by numerical simulations the asymptotic average time-headway as a function of the number of running trains, compare the results with those of the max-plus algebra model, and derive the effect of the passenger travel demand on the frequency of the metro line, under the proposed control model.

Given a sound field generated by a sparse distribution of impulse image sources, can the continuous 3D positions and amplitudes of these sources be recovered from discrete, bandlimited measurements of the field at a finite set of locations, e.g., a multichannel room impulse response? Borrowing from recent advances in super-resolution imaging, it is shown that this nonlinear, non-convex inverse problem can be efficiently relaxed into a convex linear inverse problem over the space of Radon measures in R3. The linear operator introduced here stems from the fundamental solution of the free-field inhomogenous wave equation combined with the receivers' responses. An adaptation of the Sliding Frank-Wolfe algorithm is proposed to numerically solve the problem off-the-grid, i.e., in continuous 3D space. Simulated experiments show that the approach achieves near-exact recovery of hundreds of image sources using an arbitrarily placed compact 32-channel spherical microphone array in random rectangular rooms. The impact of noise, sampling rate and array diameter on these results is also examined.

The stochastic block model (SBM) is a mixture model used for the clustering of nodes in networks. It has now been employed for more than a decade to analyze very different types of networks in many scientific fields such as Biology and social sciences. Because of conditional dependency, there is no analytical expression for the posterior distribution over the latent variables, given the data and model parameters. Therefore, approximation strategies, based on variational techniques or sampling, have been proposed for clustering. Moreover, two SBM model selection criteria exist for the estimation of the number K of clusters in networks but, again, both of them rely on some approximations. In this paper, we show how an analytical expression can be derived for the integrated complete data log likelihood. We then propose an inference algorithm to maximize this exact quantity. This strategy enables the clustering of nodes as well as the estimation of the number clusters to be performed at the same time and no model selection criterion has to be computed for various values of K. The algorithm we propose has a better computational cost than existing inference techniques for SBM and can be employed to analyze large networks with ten thousand nodes. Using toy and true data sets, we compare our work with other approaches.

Smartphones are widespread objects that have been used as physics sensors for the general public thanks to their availability, high connectivity and built-in sensors. Here, we present the use of a fleet of smartphones to create a distributed network of time-synchronized sensors. We first evaluate the sensors quality in the laboratory and then describe the network configuration that allows the remote control of an entire fleet. Finally, we present two test cases that use the smartphone fleet for physical field measurements. By this study, we show that this approach paves the way for large-scale field scientific studies.

This paper investigates whether in frictional granular packings, like in Hamiltonian amorphous elastic solids, the stress autocorrelation matrix presents long range anisotropic contributions just as elastic Green's functions. We find that in a standard model of frictional granular packing this is not the case. We prove quite generally that mechanical balance and material isotropy constrain the stress auto-correlation matrix to be fully determined by two spatially isotropic functions: the pressure and torque auto-correlations. The pressure and torque fluctuations being respectively normal and hyperuniform force the stress autocorrelation to decay as the elastic Green's function. Since we find the torque fluctuations to be hyper-uniform, the culprit is the pressure whose fluctuations decay slower than normally as a function of the system's size. Investigating the reason for these abnormal pressure fluctuations we discover that anomalous correlations build up already during the compression of the dilute system before jamming. Once jammed these correlations remain frozen. Whether this is true for frictional matter in general or is it the consequence of the model properties is a question that must await experimental scrutiny and possible alternative models.

Energy noise indicators are generally used to characterize the exposure of populations to transportation noise in relation to their long-term annoyance, but they do not adequately reflect the repetitive nature of noise peaks generated by railway traffic. The GENIFER project aims to test a study protocol designed to rank railway noise events according to the instantaneous annoyance they cause to residents. This study will be carried out in a sector exposed to railway noise in the {Î}le-de-France region and will require the recruitment of 60 volunteer local residents. It will propose the use of innovative tools for collecting information, including an electronic remote-control allowing participants to rate the annoyance they feel when trains pass by, and noise sensor instrumentation allowing the simultaneous collection of the acoustic characteristics of railway noise peaks. It also includes semi-directive interviews and a questionnaire to identify co-determinants of annoyance. The instantaneous annoyance scores collected will also be compared with those obtained from commented listening to sound samples of passing trains. In addition to assessing the acceptability of the protocol by the participants, this study aims to validate the feasibility of ranking railway noise events according to their acoustic characteristics in terms of the annoyance expressed.

We prepare and study cement foam samples with well-controlled structure, i.e. containing monodisperse bubbles. We observe that the foam structure often changes before cement setting and identify ripening as the major destabilization mechanism at stake. Drainage plays only a minor role in cement foam destabilization except when bubble size is large. Then we show that a single stability criterion can be defined, for a large range of cement foams with different formulations. This criterion involves the bubble radius and the yield stress of the cement paste such as confined by and between the bubbles, at a given characteristic time after sample preparation.

Production of morphology-controlled cement foams remains challenging, mainly due to bubble stability issues during cement setting. The use of cement paste with high yield stress is expected to promote stability by damping intrinsic bubble kinetics. Here we show however that for given W/C ratio, fresh foam stability can be achieved instead by decreasing the yield stress of the cement paste. Indeed, in this low apparent yield stress regime, van der Waals attraction between cement grains is reduced and grains are allowed to be efficiently packed by bubbles, providing enhanced mechanical properties. This result is obtained for two distinct additives used at controlled concentrations and without resorting to set accelerators, which highlights the general significance of the underlying stability mechanism. It offers a promising solution to produce stable cement foams at high air content.

Yield stress of aerated cement paste is studied. Samples are prepared by mixing aqueous foam with cement paste, which allows controlling bubble size, gas volume fraction and yield stress of the cement paste. Two distinct behaviors are observed depending on the surfactant used to prepare the precursor aqueous foam: (i) For a surfactant with low adsorption ability with respect to cement grains, bubbles tend to decrease the yield stress of the paste with magnitude governed by the Bingham capillary number, which accounts for bubble deformability. (ii) For a surfactant with high adsorption ability, bubbles increase significantly the yield stress. This behavior is shown to result from the surfactant-induced hydrophobization of the cement grains, which adsorb at the surface of the bubbles and tend to rigidify them. Within this regime, the effect of air incorporation is comparable to the effect of added solid particles.

The characterization and monitoring of buildings is an issue that has attracted the interest of many sectors over the last two decades. With the increasing use of permanent, continuous and real-time networks, ambient vibrations can provide a simple tool for the identification of dynamic building parameters. This study is focused on the long-term variation of frequency and damping in several buildings, using the Random Decrement Technique (RDT). RDT provides a fast, robust and accurate long-term analysis and improves the reliability of frequency and damping measurements for structural health monitoring. This reveals particularly useful information in finding out precisely how far changes in modal parameters can be related to changes in physical properties. This paper highlights the reversible changes of the structure's dynamic parameters, correlated with external forces, such as temperature and exposure to the sun. Contrasting behaviors are observed, including correlation and anti-correlation with temperature variations.

Multi-objective evaluation is a necessary aspect when managing complex systems, as the intrinsic complexity of a system is generally closely linked to the potential number of optimization objectives. However, an evaluation makes no sense without its robustness being given (in the sense of its reliability). Statistical robustness computation methods are highly dependent of underlying statistical models. We propose a formulation of a model-independent framework in the case of integrated aggregated indicators (multi-attribute evaluation), that allows to define a relative measure of robustness taking into account data structure and indicator values. We implement and apply it to a synthetic case of urban systems based on Paris districts geography, and to real data for evaluation of income segregation for Greater Paris metropolitan area. First numerical results show the potentialities of this new method. Furthermore, its relative independence to system type and model may position it as an alternative to classical statistical robustness methods.

Complex systems having metastable elements often demonstrate nearly log-time relaxations and a kind of aging: repeated stimuli weaken the system's relaxational response. Granular matter is known to exhibit a wealth of such behaviors, for which the role of thermal fluctuations is usually ignored. However, we demonstrate that the latter can pronouncedly affect contacting mesoscopic-scale asperities and be macroscopically observed via appropriate acoustic effects. We also propose a mechanism comprising slow relaxations and aging as intrinsic properties of a wide class of systems with metastable states.

Three-dimensional discrete numerical simulation is used to investigate the properties of close-packed frictionless granular assemblies as a function of particle polydispersity and shape. Unlike some experimental results, simulations show that disordered packings of pinacoids (eight-face convex polyhedron) achieve higher solid fraction values than amorphous packings of spherical or rounded particles, thus fulfilling the analogue of Ulam's conjecture stated by Jiao and co-workers for random packings [Y. Jiao and S. Torquato, Phys. Rev. E $\textbf{84}$, $041309$ ($2011$)]. This seeming discrepancy between experimental and numerical results is believed to lie with difficulties in overcoming interparticle friction through experimental densification processes. Moreover, solid fraction is shown to increase further with bidispersity and peak when the volume proportion of small particles reaches $30\%$. Contrarywise, substituting up to $50\%$ of flat pinacoids for isometric ones yields solid fraction decrease, especially when flat particles are also elongated. Nevertheless, particle shape seems to play a minor role on packing solid fraction compared to polydispersity. Additional investigations focused on the packing microstructure confirm that pinacoid packings fulfill the isostatic conjecture and that they are free of order except beyond $30$ to $50\%$ of flat or flat \& elongated polyhedra in the packing. This order increase progressively takes the form of a nematic phase caused by the reorientation of flat or flat \& elongated particles to minimize the packing potential energy. Simultaneously, this reorientation seems to increase the solid fraction value slightly above the maximum achieved by monodisperse isometric pinacoids, as well as the coordination number. Finally, partial substitution of elongated pinacoids for isometric ones has limited effect on packing solid fraction or order.