Synchronized switch harvesting applied to self-powered smart systems: Piezoactive microgenerators for autonomous wireless receivers

This paper introduces the conceptual architecture of a fully integrated, truly self-powered structural health monitoring (SHM) scheme. The challenge here is to power an array of numerous distributed actuators and sensors as well as wireless data transmission modules without recurring to heavy and costly wiring. Based on microgenerators which directly convert ambient mechanical energy into electrical energy, using the synchronized switch harvesting (SSH) method, the proposed solution allows avoiding the periodic replacement or reloading of batteries. This addresses environmental and economic issues at the same time, knowing that such elements are heavy, polluting and might be installed in rather inaccessible locations. Indeed, especially in airborne structures saving weight and maintenance cost is of priority importance.Previous work showed that such microgenerators provide a stand-alone power source, whose performances meet the requirements of autonomous wireless transmitters (AWTs) that comprise an acoustic Lamb wave's actuator and a radio frequency (RF) emitter (D. Guyomar, Y. Jayet, L. Petit, E. Lefeuvre, T. Monnier, C. Richard, M. Lallart, Synchronized switch harvesting applied to self-powered smart systems: Piezoactive microgenerators for autonomous wireless transmitters, Sens Actuators A: Phys. 138 (1) (2007) 151–160, doi:10.1016/j.sna.2007.04.009). Following this work, the present contribution presents a further step towards the integration of the SHM technique. It shows the ability of our microgenerators to provide enough energy to give logical autonomy to each self-powered sensing node, named autonomous wireless receiver (AWR), and thus to provide some local (decentralized) pre-processing ability to the SHM system.A preliminary design of the device using off-the-shelf electronics and surface mounted piezoelectric patches will be presented. Since the existence of a positive energy balance between the harvesting capabilities of the SSH technique and the energy requirements of the proposed device will be proved, the system formed by the combination of the AWR with the previously developed AWT, is a proof of concept of truly self-powered smart systems for damage detection in simple structures, setting apart application-specific optimization or miniaturization concerns that will be addressed in future works.     

Mixtures of robust probabilistic principal component analyzers

Mixtures of probabilistic principal component analyzers model high-dimensional nonlinear data by combining local linear models. Each mixture component is specifically designed to extract the local principal orientations in the data. An important issue with this generative model is its sensitivity to data lying off the low-dimensional manifold. In order to address this problem, the mixtures of robust probabilistic principal component analyzers are introduced. They take care of atypical points by means of a long tail distribution, the Student-t. It is shown that the resulting mixture model is an extension of the mixture of Gaussians, suitable for both robust clustering and dimensionality reduction. Finally, we briefly discuss how to construct a robust version of the closely related mixture of factor analyzers.     

Crossing textual and visual content in different application scenarios

This paper deals with multimedia information access. We propose two new approaches for hybrid text-image information processing that can be straightforwardly generalized to the more general multimodal scenario. Both approaches fall in the trans-media pseudo-relevance feedback category. Our first method proposes using a mixture model of the aggregate components, considering them as a single relevance concept. In our second approach, we define trans-media similarities as an aggregation of monomodal similarities between the elements of the aggregate and the new multimodal object. We also introduce the monomodal similarity measures for text and images that serve as basic components for both proposed trans-media similarities. We show how one can frame a large variety of problem in order to address them with the proposed techniques: image annotation or captioning, text illustration and multimedia retrieval and clustering. Finally, we present how these methods can be integrated in two applications: a travel blog assistant system and a tool for browsing the Wikipedia taking into account the multimedia nature of its content.

Self-adaptive utility-based web session management

In the Internet, where millions of users are a click away from your site, being able to dynamically classify the workload in real time, and predict its short term behavior, is crucial for proper self-management and business efficiency. As workloads vary significantly according to current time of day, season, promotions and linking, it becomes impractical for some ecommerce sites to keep over-dimensioned infrastructures to accommodate the whole load. When server resources are exceeded, session-based admission control systems allow maintaining a high throughput in terms of properly finished sessions and QoS for a limited number of sessions; however, by denying access to excess users, the website looses potential customers.In the present study we describe the architecture of AUGURES, a system that learns to predict Web user’s intentions for visiting the site as well its resource usage. Predictions are made from information known at the time of their first request and later from navigational clicks. For this purpose we use machine learning techniques and Markov-chain models. The system uses these predictions to automatically shape QoS for the most profitable sessions, predict short-term resource needs, and dynamically provision servers according to the expected revenue and the cost to serve it. We test the AUGURES prototype on access logs from a high-traffic, online travel agency, obtaining promising results.     

On the Black-Box Complexity of Sperner’s Lemma

We present several results on the complexity of various forms of Sperner’s Lemma in the black-box model of computing. We give a deterministic algorithm for Sperner problems over pseudo-manifolds of arbitrary dimension. The query complexity of our algorithm is linear in the separation number of the skeleton graph of the manifold and the size of its boundary. As a corollary we get an deterministic query algorithm for the black-box version of the problem 2D-SPERNER, a well studied member of Papadimitriou’s complexity class PPAD. This upper bound matches the deterministic lower bound of Crescenzi and Silvestri. The tightness of this bound was not known before. In another result we prove for the same problem an lower bound for its probabilistic, and an lower bound for its quantum query complexity, showing that all these measures are polynomially related. Research supported by the European Commission IST Integrated Project Qubit Application (QAP) 015848, the OTKA grants T42559 and T46234, and by the ANR Blanc AlgoQP grant of the French Research Ministry.     

A wireless embedded tongue tactile biofeedback system for balance control

We describe the architecture of an original biofeedback system for balance improvement for fall prevention and present results of a feasibility study. The underlying principle of this biofeedback consists of providing supplementary information related to foot sole pressure distribution through a wireless embedded tongue-placed tactile output device.Twelve young healthy adults voluntarily participated in this experiment. They were asked to stand as immobile as possible with their eyes closed in two conditions of no-biofeedback and biofeedback. Centre of foot pressure (CoP) displacements were recorded using a force platform. Results showed reduced CoP displacements in the biofeedback relative to the no-biofeedback condition.On the whole, the present findings evidence the effectiveness of this system in improving postural control on young healthy adults. Further investigations are needed to strengthen the potential clinical value of this device.     

Hierarchical learning from human preferences and curiosity

Applied Intelligence - Recent success in scaling deep reinforcement algorithms (DRL) to complex problems has been driven by well-designed extrinsic rewards, which limits their applicability to many...     

Ferritin Protein Regulates the Degradation of Iron Oxide Nanoparticles

Proteins implicated in iron homeostasis are assumed to be also involved in the cellular processing of iron oxide nanoparticles. In this work, the role of an endogenous iron storage protein—namely the ferritin—is examined in the remediation and biodegradation of magnetic iron oxide nanoparticles. Previous in vivo studies suggest the intracellular transfer of the iron ions released during the degradation of nanoparticles to endogenous protein cages within lysosomal compartments. Here, the capacity of ferritin cages to accommodate and store the degradation products of nanoparticles is investigated in vitro in the physiological acidic environment of the lysosomes. Moreover, it is questioned whether ferritin proteins can play an active role in the degradation of the nanoparticles. The magnetic, colloidal, and structural follow‐up of iron oxide nanoparticles and proteins in lysosome‐like medium confirms the efficient remediation of potentially harmful iron ions generated by nanoparticles within ferritins. The presence of ferritins, however, delays the degradation of particles due to a complex colloidal behavior of the mixture in acidic medium. This study exemplifies the important implications of intracellular proteins in processes of degradation and metabolization of iron oxide nanoparticles.     

Dual‐Action Cancer Therapy with Targeted Porous Silicon Nanovectors

There is a pressing need to develop more effective therapeutics to fight cancer. An idyllic chemotherapeutic is expected to overcome drug resistance of tumors and minimize harmful side effects to healthy tissues. Antibody‐functionalized porous silicon nanoparticles loaded with a combination of chemotherapy drug and gold nanoclusters (AuNCs) are developed. These nanocarriers are observed to selectively deliver both payloads, the chemotherapy drug and AuNCs, to human B cells. The accumulation of AuNCs to target cells and subsequent exposure to an external electromagnetic field in the microwave region render them more susceptible to the codelivered drug. This approach represents a targeted two‐stage delivery nanocarrier that benefits from a dual therapeutic action that results in enhanced cytotoxicity.