An epistemological and bio-physical point of view on complex systems

In this article, after a historical introduction, we give an epistemological point of view of the physics of complex systems. Complex systems are epistemologically interesting because of the fundamental interaction experiment/observer and physicists in their everyday life can experience the paradoxes given by this interaction. Here we describe some of these paradoxes, we make a parallel with quantum mechanics and give a possible philosophical solution, based on notorious physicists/philosopher from the past, transposing and reinterpreting their ideas to modern times. In particular, we analyse the interaction with a complex system such as the living cell, and therefore we also analyse some biophysical implications of complexity

Power-law and log-normal avalanche size statistics in random growth processes

ACKNOWLEDGMENTS We thank J.P. Bouchaud for constructive comments. We acknowledge financial support from the Agence Nationale de la Recherche (ANR grant number ANR-18- CE45-0012-01) and from the French Research Ministry (MESR) (contract No. 2017-SG-D-09) and from ENS Lyon for SP PhD funding. FJPR acknowledges financial support from the Carnegie Trust.Peer reviewedPostprin

Characterization of nanoporous lanthanide-doped gadolinium gallium garnet powders obtained by propellant synthesis

In the present work we study the nanocrystalline powders of lanthanide-doped Gd3Ga5O12 (GGG, gadolinium gallium garnet) prepared using propellant synthesis. A series of GGG samples containing a number of different trivalent lanthanide ions (Tm, Er, Ho, Eu, Sm, Nd, and Pr) in different quantities (1%, 5%, 10%) were produced. Samples were characterized by X-ray diffraction (pre- and post calcination) for phase identification and line-broadening analysis, and by electron microscopy (SEM and TEM) for morphological and nanostructural investigation. Thermal behavior of the powder was investigated by thermal gravimetric analysis (TGA) and differential thermal analysis (DTA). The samples have a polycrystalline porous structure. Elemental microanalysis made by energy dispersive X-ray spectroscopy (EDX) detector attached to TEM and XRD unit-cell determinations confirmed that the lanthanides ions entered the structure of GGG. Crystallites have a high degree of disorder

Routes to the preparation of mixed monolayers of fluorinated and hydrogenated alkanethiolates grafted on the surface of gold nanoparticles

The use of binary blends of hydrogenated and fluorinated alkanethiolates represents an interesting approach to the construction of anisotropic hybrid organic-inorganic nanoparticles since the fluorinated and hydrogenated components are expected to self-sort on the nanoparticle surface because of their reciprocal phobicity. These mixed monolayers are therefore strongly non-ideal binary systems. The synthetic routes we explored to achieve mixed monolayer gold nanoparticles displaying hydrogenated and fluorinated ligands clearly show that the final monolayer composition is a non-linear function of the initial reaction mixture. Our data suggest that, under certain geometrical constraints, nucleation and growth of fluorinated domains could be the initial event in the formation of these mixed monolayers. The onset of domain formation depends on the structure of the fluorinated and hydrogenated species. The solubility of the mixed monolayer nanoparticles displayed a marked discontinuity as a function of the monolayer composition. When the fluorinated component content is small, the nanoparticle systems are fully soluble in chloroform, at intermediate content the nanoparticles become soluble in hexane and eventually they become soluble in fluorinated solvents only. The ranges of monolayer compositions in which the solubility transitions are observed depend on the nature of the thiols composing the monolayer

Patchy and Janus Nanoparticles by Self-Organization of Mixtures of Fluorinated and Hydrogenated Alkanethiolates on the Surface of a Gold Core

The spontaneous self-organization of dissimilar ligands on the surface of metal nanoparticles is a very appealing approach to obtain anisotropic "spherical". systems. In addition to differences in ligand length and end groups, a further thermodynamic driving force to control the self-assembled monolayer organization may become available if the ligands are inherently immiscible, as is the case of hydrogenated (H-) and fluorinated (F-) species. Here, we validate the viability of this approach by combining F-19 NMR experiments and multiscale molecular simulations on large sets of mixed-monolayer-protected gold nanoparticles (NPs). The phase segregation of blends of F- and H-thiolates grafted on the surface of gold NPs allows a straightforward approach to patterned mixed monolayers, with the shapes of the monolayer domains being encoded in the structure of the F/H-thiolate ligands. The results obtained from this comprehensive study offer molecular design rules to achieve a precise control of inorganic nanoparticles protected by specifically patterned monolayers

Characterization of Pupillary Light Response Features for the Classification of Patients with Optic Neuritis

Pupillometry is a promising technique for the potential diagnosis of several neurological pathologies. However, its potential is not fully explored yet, especially for prediction purposes and results interpretation. In this work, we analyzed 100 pupillometric curves obtained by 12 subjects, applying both advanced signal processing techniques and physics methods to extract typically collected features and newly proposed ones. We used machine learning techniques for the classification of Optic Neuritis (ON) vs. Healthy subjects, controlling for overfitting and ranking the features by random permutation, following their importance in prediction. All the extracted features, except one, turned out to have significant importance for prediction, with an average accuracy of 76%, showing the complexity of the processes involved in the pupillary light response. Furthermore, we provided a possible neurological interpretation of this new set of pupillometry features in relation to ON vs. Healthy classification

Development and validation of a semi-automated and unsupervised method for femur segmentation from CT

: Quantitative computed tomography (QCT)-based in silico models have demonstrated improved accuracy in predicting hip fractures with respect to the current gold standard, the areal bone mineral density. These models require that the femur bone is segmented as a first step. This task can be challenging, and in fact, it is often almost fully manual, which is time-consuming, operator-dependent, and hard to reproduce. This work proposes a semi-automated procedure for femur bone segmentation from CT images. The proposed procedure is based on the bone and joint enhancement filter and graph-cut algorithms. The semi-automated procedure performances were assessed on 10 subjects through comparison with the standard manual segmentation. Metrics based on the femur geometries and the risk of fracture assessed in silico resulting from the two segmentation procedures were considered. The average Hausdorff distance (0.03 ± 0.01 mm) and the difference union ratio (0.06 ± 0.02) metrics computed between the manual and semi-automated segmentations were significantly higher than those computed within the manual segmentations (0.01 ± 0.01 mm and 0.03 ± 0.02). Besides, a blind qualitative evaluation revealed that the semi-automated procedure was significantly superior (p < 0.001) to the manual one in terms of fidelity to the CT. As for the hip fracture risk assessed in silico starting from both segmentations, no significant difference emerged between the two (R2 = 0.99). The proposed semi-automated segmentation procedure overcomes the manual one, shortening the segmentation time and providing a better segmentation. The method could be employed within CT-based in silico methodologies and to segment large volumes of images to train and test fully automated and supervised segmentation methods