Fast differential scanning calorimetry: new solutions in data treatment and applications to molecular glass-formers

Fast scanning calorimetry is an experimental technique very appreciated for its capability of suppressing reorganization processes, thanks to its wide interval of scanning rates, several orders higher than that of conventional calorimeters; nevertheless, drawbacks still exist. In this paper we propose a novel way to estimate the dynamical thermal lag by using the temperatures of maximum slope of the heat flow through the glass transition when we are not in the optimal conditions to apply the existing methods based on a reference material added on both cells of the chip or on the fictive temperature. Moreover, a novel interpretation of the heat flow losses due to the sample depending on the scanning rate sign is provided, in order to rescale the measured specific heat capacity to that from conventional calorimetry. Finally, the use of the glass to liquid transition measured on heating is shown as a new manner to reveal static thermal gradients

Going Further with Point Pair Features

Point Pair Features is a widely used method to detect 3D objects in point clouds, however they are prone to fail in presence of sensor noise and background clutter. We introduce novel sampling and voting schemes that significantly reduces the influence of clutter and sensor noise. Our experiments show that with our improvements, PPFs become competitive against state-of-the-art methods as it outperforms them on several objects from challenging benchmarks, at a low computational cost.Comment: Corrected post-print of manuscript accepted to the European Conference on Computer Vision (ECCV) 2016; https://link.springer.com/chapter/10.1007/978-3-319-46487-9_5

Unfreezing of molecular motions in protein-polymer conjugates: a calorimetric study

Protein-polymer conjugates are a promising class of biohybrids. In this work, the dynamics of a set of biodegradable conjugates myoglobin-poly(ethyl ethylene phosphate) (My-PEEP) with variations in the number of attached polymers and their molar mass in the dry-state, have been investigated to understand the role of polymer on protein dynamics. We performed Differential Scanning Calorimetry measurements between 190 and 300 K, observing the large-scale dynamics arising from reorganization of conformational states, i.e. within the 100 s timescale. The application of an annealing time during the cooling scans was used to investigate the non-equilibrium glassy-state of the samples, observing the relaxation enthalpy at different annealing temperatures. This procedure permitted to extensively describe the transition broadness and the system relaxation kinetics in the glassy state. The samples show an experimental behaviour different from the theoretical predictions, suggesting the establishment of interactions among the protein and the polymer chains. The different behaviour of the conjugates and the physical mixture (composed of the protein and the polymer physically mixed) highlighted the importance of the covalent bond in defining the system dynamics

Shrec'16 Track: Retrieval of Human Subjects from Depth Sensor Data

International audienceIn this paper we report the results of the SHREC 2016 contest on "Retrieval of human subjects from depth sensor data". The proposed task was created in order to verify the possibility of retrieving models of query human subjects from single shots of depth sensors, using shape information only. Depth acquisition of different subjects were realized under different illumination conditions, using different clothes and in three different poses. The resulting point clouds of the partial body shape acquisitions were segmented and coupled with the skeleton provided by the OpenNI software and provided to the participants together with derived triangulated meshes. No color information was provided. Retrieval scores of the different methods proposed were estimated on the submitted dissimilarity matrices and the influence of the different acquisition conditions on the algorithms were also analyzed. Results obtained by the participants and by the baseline methods demonstrated that the proposed task is, as expected, quite difficult, especially due the partiality of the shape information and the poor accuracy of the estimated skeleton, but give useful insights on potential strategies that can be applied in similar retrieval procedures and derived practical applications. Categories and Subject Descriptors (according to ACM CCS): I.4.8 [IMAGE PROCESSING AND COMPUTER VISION]: Scene Analysis—Shap

Boosting Object Recognition in Point Clouds by Saliency Detection

Object recognition in 3D point clouds is a challenging task, mainly when time is an important factor to deal with, such as in industrial applications. Local descriptors are an amenable choice whenever the 6 DoF pose of recognized objects should also be estimated. However, the pipeline for this kind of descriptors is highly time-consuming. In this work, we propose an update to the traditional pipeline, by adding a preliminary filtering stage referred to as saliency boost. We perform tests on a standard object recognition benchmark by considering four keypoint detectors and four local descriptors, in order to compare time and recognition performance between the traditional pipeline and the boosted one. Results on time show that the boosted pipeline could turn out up to 5 times faster, with the recognition rate improving in most of the cases and exhibiting only a slight decrease in the others. These results suggest that the boosted pipeline can speed-up processing time substantially with limited impacts or even benefits in recognition accuracy.Comment: International Conference on Image Analysis and Processing (ICIAP) 201

トクシュウ トクシマケン ノ キュウキュウ イリョウ ト チイキ イリョウ : ゲンジョウ ト テンボウ : カントウゲン

We introduce GFrames, a novel local reference frame (LRF) construction for 3D meshes and point clouds. GFrames are based on the computation of the intrinsic gradient of a scalar field defined on top of the input shape. The resulting tangent vector field defines a repeatable tangent direction of the local frame at each point; importantly, it directly inherits the properties and invariance classes of the underlying scalar function, making it remarkably robust under strong sampling artifacts, vertex noise, as well as non-rigid deformations. Existing local descriptors can directly benefit from our repeatable frames, as we showcase in a selection of 3D vision and shape analysis applications where we demonstrate state-of-the-art performance in a variety of challenging settings

Object Registration in Semi-cluttered and Partial-occluded Scenes for Augmented Reality

This paper proposes a stable and accurate object registration pipeline for markerless augmented reality applications. We present two novel algorithms for object recognition and matching to improve the registration accuracy from model to scene transformation via point cloud fusion. Whilst the first algorithm effectively deals with simple scenes with few object occlusions, the second algorithm handles cluttered scenes with partial occlusions for robust real-time object recognition and matching. The computational framework includes a locally supported Gaussian weight function to enable repeatable detection of 3D descriptors. We apply a bilateral filtering and outlier removal to preserve edges of point cloud and remove some interference points in order to increase matching accuracy. Extensive experiments have been carried to compare the proposed algorithms with four most used methods. Results show improved performance of the algorithms in terms of computational speed, camera tracking and object matching errors in semi-cluttered and partial-occluded scenes

The Italian Consensus Conference on FAI Syndrome in Athletes (Cotignola Agreement)

Background. Femoro-acetabular impingement (FAI) is an important topic in literature because of its strong relationship with sport populations. Methods. Sixty-five experts participated in "this Consensus Conference (CC)". They discussed, voted and approved a consensus document on the FAI syndrome in athletes. Results. The CC experts approved document provided suggestions concerning: 1) Epidemiology of FAI; 2) Clinical evaluation; 3) Radiological evaluation; 4) Conserva-tive treatment; 5) Surgical criteria; 6) Surgical techniques; 7) Post-surgical rehabilita-tion; 8) Outcome evaluation; 9) FAI-associated clinical frameworks. Conclusions. The CC offers a multidisciplinary approach to the diagnosis and treat-ment of FAI syndrome in athletes taking into account all the different steps needed to approach this pathology in sport populations

Entropy-driven liquid-liquid separation in supercooled water

Twenty years ago Poole et al. (Nature 360, 324, 1992) suggested that the anomalous properties of supercooled water may be caused by a critical point that terminates a line of liquid-liquid separation of lower-density and higher-density water. Here we present an explicit thermodynamic model based on this hypothesis, which describes all available experimental data for supercooled water with better quality and with fewer adjustable parameters than any other model suggested so far. Liquid water at low temperatures is viewed as an 'athermal solution' of two molecular structures with different entropies and densities. Alternatively to popular models for water, in which the liquid-liquid separation is driven by energy, the phase separation in the athermal two-state water is driven by entropy upon increasing the pressure, while the critical temperature is defined by the 'reaction' equilibrium constant. In particular, the model predicts the location of density maxima at the locus of a near-constant fraction (about 0.12) of the lower-density structure.Comment: 7 pages, 6 figures. Version 2 contains an additional supplement with tables for the mean-field equatio