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.     

Anticipating Cutoff Diameters in Deterministic Lateral Displacement (DLD) Microfluidic Devices for an Optimized Particle Separation

Deterministic lateral displacement (DLD) devices enable to separate nanometer to micrometer‐sized particles around a cutoff diameter, during their transport through a microfluidic channel with slanted rows of pillars. In order to design appropriate DLD geometries for specific separation sizes, robust models are required to anticipate the value of the cutoff diameter. So far, the proposed models result in a single cutoff diameter for a given DLD geometry. This paper shows that the cutoff diameter actually varies along the DLD channel, especially in narrow pillar arrays. Experimental and numerical results reveal that the variation of the cutoff diameter is induced by boundary effects at the channel side walls, called the wall effect. The wall effect generates unexpected particle trajectories that may compromise the separation efficiency. In order to anticipate the wall effect when designing DLD devices, a predictive model is proposed in this work and has been validated experimentally. In addition to the usual geometrical parameters, a new parameter, the number of pillars in the channel cross dimension, is considered in this model to investigate its influence on the particle trajectories.     

Tunable Diode Laser Absorption Spectroscopy of Carbon Monoxide Around 2.35 microm

Novel GaInSbAs/GaSb multiple-quantum-well lasers operating near room temperature have been successfully used for tunable diode laser absorption spectroscopy in the vicinity of 2.35 mum. Continuous current tuning over a more than 150-GHz frequency range has been realized. Direct absorption measurements have been carried out on the R, R, R, and R lines of carbon monoxide. Traces of carbon monoxide at the level of 0.3 part in 10(6) in volume at 100 Torr could be detected by the low-frequency wavelength-modulation technique and an astigmatic multipass cell. These results show a potential use of these diode lasers in portable low-cost trace-pollutant sensors.     

Indexing and querying segmented web pages: the BlockWeb Model

We present in this paper a model for indexing and querying web pages, based on the hierarchical decomposition of pages into blocks. Splitting up a page into blocks has several advantages in terms of page design, indexing and querying such as (i) blocks of a page most similar to a query may be returned instead of the page as a whole (ii) the importance of a block can be taken into account, as well as (iii) the permeability of the blocks to neighbor blocks: a block b is said to be permeable to a block b?? in the same page if b?? content (text, image, etc.) can be (partially) inherited by b upon indexing. An engine implementing this model is described including: the transformation of web pages into blocks hierarchies, the definition of a dedicated language to express indexing rules and the storage of indexed blocks into an XML repository. The model is assessed on a dataset of electronic news, and a dataset drawn from web pages of the ImagEval campaign where it improves by 16% the mean average precision of the baseline.     

Learning a generic 3D face model from 2D image databases using incremental Structure-from-Motion

Over the last decade 3D face models have been extensively used in many applications such as face recognition, facial animation and facial expression analysis. 3D Morphable Models (MMs) have become a popular tool to build and fit 3D face models to images. Critical to the success of MMs is the ability to build a generic 3D face model. Major limitations in the MMs building process are: (1) collecting 3D data usually involves the use of expensive laser scans and complex capture setups, (2) the number of available 3D databases is limited, and typically there is a lack of expression variability and (3) finding correspondences and registering the 3D model is a labor intensive and error prone process.     

A tabu search with an oscillation strategy for the discriminant analysis problem

This article proposes a tabu search approach to solve a mathematical programming formulation of the linear classification problem, which consists of determining an hyperplane that separates two groups of points as well as possible in ?^m. The tabu search approach proposed is based on a non-standard formulation using linear system infeasibility. The search space is the set of bases defined on the matrix that describes the linear system. The moves are performed by pivoting on a specified row and column. On real machine learning databases, our approach compares favorably with implementations based on parametric programming and irreducible infeasible constraint sets. Additional computational results for randomly generated instances confirm that our method provides a suitable alternative to the mixed integer programming formulation that is solved by a commercial code when the number of attributes m increases.