École Normale Supérieure de Rennes

The deployment of distributed energy resources, combined with a more proactive demand side management, is inducing a new paradigm in power system operation and electricity markets. Within a consumer-centric market framework, peer-to-peer (P2P) approaches have gained substantial interest. P2P markets rely on multibilateral negotiation among all agents to match supply and demand. These markets can yield a complete mapping of exchanges onto the grid; hence, allowing to rethink the sharing of costs related to the use of common infrastructure and services. We propose here to attribute such costs through exogenous network charges in several alternative ways, i.e., uniformly, based on the electrical distance between agents and by zones. This variety covers the main grid physical and regulatory configurations. Since attribution mechanisms are defined in an exogenous manner to affect each P2P trade, they eventually shift the market issue to cover the grid exploitation costs. It can even be used to release the stress on the grid when necessary. The interest of our approach is illustrated on a test case using the IEEE 39 bus test system, underlying the impact of attribution mechanisms on trades and grid usage.

Evaluating potential musculoskeletal disorders risks in real workstations is challenging as the environment is cluttered, which makes it difficult to accurately assess workers' postures. Being marker-free and calibration-free, Microsoft Kinect is a promising device although it may be sensitive to occlusions. We propose and evaluate a RULA ergonomic assessment in real work conditions using recently published occlusion-resistant Kinect skeleton data correction. First, we compared postures estimated with this method to ground-truth data, in standardized laboratory conditions. Second, we compared RULA scores to those provided by two professional experts, in a non-laboratory cluttered workplace condition. The results show that the corrected Kinect data can provide more accurate RULA grand scores, even under sub-optimal conditions induced by the workplace environment. This study opens new perspectives in musculoskeletal risk assessment as it provides the ergonomists with 30 Hz continuous information that could be analyzed offline and in a real-time framework.

Gut microbiota is involved in the development of several chronic diseases, including diabetes, obesity, and cancer, through its interactions with the host organs. It has been suggested that the cross talk between gut microbiota and skeletal muscle plays a role in different pathological conditions, such as intestinal chronic inflammation and cachexia. However, it remains unclear whether gut microbiota directly influences skeletal muscle function. In this work, we studied the impact of gut microbiota modulation on mice skeletal muscle function and investigated the underlying mechanisms. We determined the consequences of gut microbiota depletion after treatment with a mixture of a broad spectrum of antibiotics for 21 days and after 10 days of natural reseeding. We found that, in gut microbiota-depleted mice, running endurance was decreased, as well as the extensor digitorum longus muscle fatigue index in an ex vivo contractile test. Importantly, the muscle endurance capacity was efficiently normalized by natural reseeding. These endurance changes were not related to variation in muscle mass, fiber typology, or mitochondrial function. However, several pertinent glucose metabolism markers, such as ileum gene expression of short fatty acid chain and glucose transporters G protein-coupled receptor 41 and sodium-glucose cotransporter 1 and muscle glycogen level, paralleled the muscle endurance changes observed after treatment with antibiotics for 21 days and reseeding. Because glycogen is a key energetic substrate for prolonged exercise, modulating its muscle availability via gut microbiota represents one potent mechanism that can contribute to the gut microbiota-skeletal muscle axis. Taken together, our results strongly support the hypothesis that gut bacteria are required for host optimal skeletal muscle function.

The additive laser manufacturing (ALM) technique is an additive manufacturing process which enables the rapid manufacturing of complex metallic parts and the creation of thin parts so as, for example, to decrease parts weight for biomechanical or aeronautic applications. Furthermore, compared with selective laser sintering technology, the ALM process allows creating more huge parts and material gradient. However, for aesthetic or tribological functions, the ALM surfaces need an additional finishing operation, such as the polishing operation. Polishing processes are usually based on abrasive or chemical techniques. These conventional processes are composed by many drawbacks such as accessibility of complex shape, environmental impact, high time consumption and cost, and health risks for operators. In order to solve these problems and to improve surface quality, the laser polishing (LP) process is investigated. Based on melting material by laser, laser polishing process enables the smoothing of initial topography. However, the ALM process and the laser polishing processes are based on laser technology. In this context, the laser ALM process is used directly on the same machine for the polishing operation. Moreover, an alternation between both processes can be established during the manufacturing operation in order to treat nonaccessible surfaces. Currently, few studies focus on laser polishing of additive laser manufacturing surfaces, and it tends to limit the industrial use of additive manufacturing technology. The proposed study describes an experimental investigation of laser polishing surfaces obtained by additive laser manufacturing process. The investigation results in the improvement of complete final surface quality, according to laser polishing parameters. This experimental study introduces the laser polishing of thin section parts, in order to develop laser polishing applications. According to a manufacturing chain context, the final objective is to create a multiprocess mastery in order to optimize the final topography and productivity time.

The large doses of vitamins C and E and β-carotene used to reduce reactive oxygen species (ROS) production and oxidative damages in cancerous tissue have produced disappointing and contradictory results. This therapeutic conundrum was attributed to the double-faced role of ROS, notably, their ability to induce either proliferation or apoptosis of cancer cells. However, for a ROS-inhibitory approach to be effective, it must target ROS when they induce proliferation rather than apoptosis. On the basis of recent advances in redox biology, this review underlined a differential regulation of prooxidant and antioxidant system, respective to the stage of cancer. At early precancerous and neoplastic stages, antioxidant activity decreases and ROS appear to promote cancer initiation via inducing oxidative damage and base pair substitution mutations in prooncogenes and tumor suppressor genes, such as RAS and TP53, respectively. Whereas in late stages of cancer progression, tumor cells escape apoptosis by producing high levels of intracellular antioxidants, like NADPH and GSH, via the pentose phosphate pathway to buffer the excessive production of ROS and related intratumor oxidative injuries. Therefore, antioxidants should be prohibited in patients with advanced stages of cancer and/or undergoing anticancer therapies. Interestingly, the biochemical and biophysical properties of some polyphenols allow them to selectively recognize tumor cells. This characteristic was exploited to design and deliver nanoparticles coated with low doses of polyphenols and containing chemotherapeutic drugs into tumor-bearing animals. First results are encouraging, which may revolutionize the conventional use of antioxidants in cancer.

Brain-Computer Interfaces (BCIs) enable users to interact with computers without any dedicated movement, bringing new hands-free interaction paradigms. In this paper we study the combination of BCI and Augmented Reality (AR). We first tested the feasibility of using BCI in AR settings based on Optical See-Through Head-Mounted Displays (OST-HMDs). Experimental results showed that a BCI and an OST-HMD equipment (EEG headset and Hololens in our case) are well compatible and that small movements of the head can be tolerated when using the BCI. Second, we introduced a design space for command display strategies based on BCI in AR, when exploiting a famous brain pattern called Steady-State Visually Evoked Potential (SSVEP). Our design space relies on five dimensions concerning the visual layout of the BCI menu; namely: orientation, frame-of-reference, anchorage, size and explicitness. We implemented various BCI-based display strategies and tested them within the context of mobile robot control in AR. Our findings were finally integrated within an operational prototype based on a real mobile robot that is controlled in AR using a BCI and a HoloLens headset. Taken together our results (4 user studies) and our methodology could pave the way to future interaction schemes in Augmented Reality exploiting 3D User Interfaces based on brain activity and BCIs.

Although coordinated patterns of body movement can be used to communicate action intention, they can also be used to deceive. Often known as deceptive movements, these unpredictable patterns of body movement can give a competitive advantage to an attacker when trying to outwit a defender. In this particular study, we immersed novice and expert rugby players in an interactive virtual rugby environment to understand how the dynamics of deceptive body movement influence a defending player's decisions about how and when to act. When asked to judge final running direction, expert players who were found to tune into prospective tau-based information specified in the dynamics of 'honest' movement signals (Centre of Mass), performed significantly better than novices who tuned into the dynamics of 'deceptive' movement signals (upper trunk yaw and out-foot placement) (p<.001). These findings were further corroborated in a second experiment where players were able to move as if to intercept or 'tackle' the virtual attacker. An analysis of action responses showed that experts waited significantly longer before initiating movement (p<.001). By waiting longer and picking up more information that would inform about future running direction these experts made significantly fewer errors (p<.05). In this paper we not only present a mathematical model that describes how deception in body-based movement is detected, but we also show how perceptual expertise is manifested in action expertise. We conclude that being able to tune into the 'honest' information specifying true running action intention gives a strong competitive advantage.

This paper reports on the design and soundness proof, using the Coq proof assistant, of Verasco, a static analyzer based on abstract interpretation for most of the ISO C 1999 language (excluding recursion and dynamic allocation). Verasco establishes the absence of run-time errors in the analyzed programs. It enjoys a modular architecture that supports the extensible combination of multiple abstract domains, both relational and non-relational. Verasco integrates with the CompCert formally-verified C compiler so that not only the soundness of the analysis results is guaranteed with mathematical certitude, but also the fact that these guarantees carry over to the compiled code.

International audience

Stream computing is becoming a more and more popular paradigm as it enables the real-time promise of data analytics. Apache Kafka is currently the most popular framework used to ingest the data streams into the processing platforms. However, how to tune Kafka and how much resources to allocate for it remains a challenge for most users, who now rely mainly on empirical approaches to determine the best parameter settings for their deployments. In this poster, we make a through evaluation of several configurations and performance metrics of Kafka in order to allow users avoid bottlenecks, reach its full potential and avoid bottlenecks and eventually leverage some good practice for efficient stream processing.

Analyzing human poses with a Kinect is a promising method to evaluate potentials risks of musculoskeletal disorders at workstations. In ecological situations, complex 3D poses and constraints imposed by the environment make it difficult to obtain reliable kinematic information. Thus, being able to predict the potential accuracy of the measurement for such complex 3D poses and sensor placements is challenging in classical experimental setups. To tackle this problem, we propose a new evaluation method based on a virtual mannequin. In this study, we apply this method to the evaluation of joint positions (shoulder, elbow, and wrist), joint angles (shoulder and elbow), and the corresponding RULA (a popular ergonomics assessment grid) upper-limb score for a large set of poses and sensor placements. Thanks to this evaluation method, more than 500,000 configurations have been automatically tested, which would be almost impossible to evaluate with classical protocols. The results show that the kinematic information obtained by the Kinect software is generally accurate enough to fill in ergonomic assessment grids. However inaccuracy strongly increases for some specific poses and sensor positions. Using this evaluation method enabled us to report configurations that could lead to these high inaccuracies. As a supplementary material, we provide a software tool to help designers to evaluate the expected accuracy of this sensor for a set of upper-limb configurations. Results obtained with the virtual mannequin are in accordance with those obtained from a real subject for a limited set of poses and sensor placements.

This paper introduces DREGON, a novel publicly-available dataset that aims at pushing research in sound source localization using a microphone array embedded in an unmanned aerial vehicle (UAV). The dataset contains both clean and noisy in-flight audio recordings continuously annotated with the 3D position of the target sound source using an accurate motion capture system. In addition, various signals of interests are available such as the rotational speed of individual rotors and inertial measurements at all time. Besides introducing the dataset, this paper sheds light on the specific properties, challenges and opportunities brought by the emerging task of UAV-embedded sound source localization. Several baseline methods are evaluated and compared on the dataset, with real-time applicability in mind. Very promising results are obtained for the localization of a broad-band source in loud noise conditions, while speech localization remains a challenge under extreme noise levels.

Cachexia is a wasting syndrome observed in many patients suffering from several chronic diseases including cancer. In addition to the progressive loss of skeletal muscle mass, cancer cachexia results in cardiac function impairment. During the severe stage of the disease, patients as well as animals bearing cancer cells display cardiac atrophy. Cardiac energy metabolism is also impeded with disruption of mitochondrial homeostasis and reduced oxidative capacity, although the available data remain equivocal. The release of inflammatory cytokines by tumor is a key mechanism in the initiation of heart failure. Oxidative stress, which results from the combination of chemotherapy, inadequate antioxidant consumption and chronic inflammation, will further foster heart failure. Protein catabolism is due to the concomitant activation of proteolytic systems and inhibition of protein synthesis, both processes being triggered by the deactivation of the Akt/mammalian target of rapamycin pathway. The reduction in oxidative capacity involves AMP-activated protein kinase and peroxisome proliferator-activated receptor gamma coactivator 1α dysregulation. The nuclear factor-κB transcription factor plays a prominent role in the coordination of these alterations. Physical exercise appears as an interesting non-pharmaceutical way to counteract cancer cachexia-induced-heart failure. Indeed, aerobic training has anti-inflammatory effects, increases anti-oxidant defenses, prevents atrophy and promotes oxidative metabolism. The present review points out the importance of better understanding the concurrent structural and metabolic changes within the myocardium during cancer and the protective effects of exercise against cardiac cachexia.

Let k be an algebraically closed field. We show that the Cremona group of all birational transformations of the projective plane $ \mathbb{P}_{\mathbf{k}}^2 $ is not a simple group. The strategy makes use of hyperbolic geometry, geometric group theory and algebraic geometry to produce elements in the Cremona group that generate non-trivial normal subgroups.

In chronic kidney disease (CKD), oxidative stress (OS) plays a central role in the development of cardiovascular diseases. This pilot program aimed to determine whether an intradialytic aerobic cycling training protocol, by increasing physical fitness, could reduce OS and improve other CKD-related disorders such as altered body composition and lipid profile. Eighteen hemodialysis patients were randomly assigned to either an intradialytic training (cycling: 30 min, 55%-60% peak power, 3 days/week) group (EX; n = 8) or a control group (CON; n = 10) for 3 months. Body composition (from dual-energy X-ray absorptiometry), physical fitness (peak oxygen uptake and the 6-minute walk test (6MWT)), lipid profile (triglycerides (TG), total cholesterol, high-density lipoprotein, and low-density lipoprotein (LDL)), and pro/antioxidant status (15-F2α-isoprostanes (F2-IsoP) and oxidized LDL in plasma; superoxide dismutase, glutathione peroxidase, and reduced/oxidized glutathione in erythrocytes) were determined at baseline and 3 months later. The intradialytic training protocol did not modify body composition but had significant effects on physical fitness, lipid profile, and pro/antioxidant status. Indeed, at 3 months: (i) performance on the 6MWT was increased in EX (+23.4%, p < 0.001) but did not change in CON, (ii) plasma TG were reduced in EX (-23%, p < 0.03) but were not modified in CON, and (iii) plasma F2-IsoP concentrations were lower in EX than in CON (-35.7%, p = 0.02). In conclusion, our results show that 30 min of intradialytic training, 3 times per week for 3 months, are enough to exert beneficial effects on the most sensitive and reliable marker of lipid peroxidation (IsoP) while improving CKD-associated disorders (lipid profile and physical fitness). Intradialytic aerobic cycling training represents a useful and easy strategy to reduce CKD-associated disorders. These results need to be confirmed with a larger randomized study.

We describe the development of the Intelligent Towing Tank, an automated experimental facility guided by active learning to conduct a sequence of vortex-induced vibration (VIV) experiments, wherein the parameters of each next experiment are selected by minimizing suitable acquisition functions of quantified uncertainties. This constitutes a potential paradigm shift in conducting experimental research, where robots, computers, and humans collaborate to accelerate discovery and to search expeditiously and effectively large parametric spaces that are impracticable with the traditional approach of sequential hypothesis testing and subsequent train-and-error execution. We describe how our research parallels efforts in other fields, providing an orders-of-magnitude reduction in the number of experiments required to explore and map the complex hydrodynamic mechanisms governing the fluid-elastic instabilities and resulting nonlinear VIV responses. We show the effectiveness of the methodology of "explore-and-exploit" in parametric spaces of high dimensions, which are intractable with traditional approaches of systematic parametric variation in experimentation. We envision that this active learning approach to experimental research can be used across disciplines and potentially lead to physical insights and a new generation of models in multi-input/multi-output nonlinear systems.

Building on the concepts of trans active energy and consumer-centric electricity markets, the interest in community-based and peer-to-peer structures to energy transactions and management has substantially increased over the last few years. However, several computational challenges are to be tackled in order for these approaches to be deployed in real-world applications. Our aim here is to identify and analyze these challenges, by comparing distributed community-based market approaches to decentralized and distributed versions of peer-to-peer electricity markets. We show convergence trends of the investigated algorithms as well as how they respond to larger number of participants and presence of asynchronicities. Our findings highlight the practical challenges to face with these setups, in particular with peer-to-peer markets, justifying the further proposal of hybrid approaches and of sparsification of negotiation processes.

This paper proposes an original model for supercapacitors that takes into account both calendar aging and cycling aging. A state variable is used to quantify the state of aging. This model is based on a series of recent experiments conducted in various research laboratories on the same technology (Maxwell Technology) and serves to represent the degradation of equivalent series resistance and capacitance. This model is particularly useful in an aging-aware life-cycle cost analysis. We show that an accurate aging model is critical to the design of an energy storage system that optimizes the economic life-cycle cost. Such an optimization is particularly applicable for smoothing in offshore systems such as direct wave energy converters, which require both cost reduction and high reliability. The influence of an aging model in the sizing process is investigated toward the end of this paper.

Purpose The purpose of this paper is to analyze the current state of the art manufacturing techniques using sand molds for the casting industry by the means of additive manufacturing (AM). In particular, this review will cover two families of 3D printing in regards to sand mold fabrication. Design/methodology/approach This paper will discuss the sand casting manufacturing processes of AM by binder jetting (3D printing) and selective laser sintering. Scientific articles, patents and case studies are analyzed. Topics ranging from the technology types to the economic implications are covered. Findings The review investigates new factors and methods for mold design, looking at mechanical properties and cost analysis as influenced by material selection, thermal characteristics, topological optimization and manufacturing procedure. Findings in this study suggest that this topic lacks vigorous scientific research and that the case studies by manufacturers thus far are not useful. Research limitations/implications As demonstrated by the limited data from previous published studies, a more comprehensive and conclusive analysis is needed due to the lack of interest and resources regarding the AM of sand molds. Practical implications This study is a useful tool for any researchers with an interest in the field of AM of sand molds. Social implications Key perspectives are proposed. Originality/value This review highlights current gaps in this field. The review goes beyond the scientific articles by curating patents and professional case studies.

This paper presents a 3-D analytical model of an axial flux permanent-magnet synchronous machine, based on formal resolution of Maxwell equations. This method requires much less computation time than conventional 3-D finite elements, and is therefore suitable for optimization purposes. In a first part, the mathematical procedure used to compute the machine no-load flux is described in detail. This method is 3-D, and then takes into account the radial edge effects of the machine, as well as the curvature effects by a resolution in cylindrical coordinates. Moreover, the originality of this method lies in the fact that it is totally analytical. The obtained results are verified using 3-D finite elements, and compared with simpler analytical models of axial flux machines, taken from the literature. This work puts in evidence the advantages of the proposed model. In particular, it is shown that the radial edge effects are important for a correct estimation of the no-load flux. On the contrary, the curvature effects are a second-order phenomenon.