Efficient computation of high-order Meixner moments for large-size signals and images analysis

In this paper, we present an in-depth study on the computational aspects of high-order discrete orthogonal Meixner polynomials (MPs) and Meixner moments (MMs). This study highlights two major problems related to the computation of MPs. The first problem is the overflow and the underflow of MPs values (“Nan” and “infinity”). To overcome this problem, we propose two new recursive Algorithms for MPs computation with respect to the polynomial order n and with respect to the variable x. These Algorithms are independent of all functions that are the origin the numerical overflow and underflow problem. The second problem is the propagation of rounding errors that lead to the loss of the orthogonality property of high-order MPs. To fix this problem, we implement MPs based on the following orthogonalization methods: modified Gram-Schmidt process (MGS), Householder method, and Givens rotation method. The proposed Algorithms for the stable computation of MPs are efficiently applied for the reconstruction and localization of the region of interest (ROI) of large-sized 1D signals and 2D/3D images. We also propose a new fast method for the reconstruction of large-size 1D signal. This method involves the conversion of 1D signal into 2D matrix, then the reconstruction is performed in the 2D domain, and a 2D to 1D conversion is performed to recover the reconstructed 1D signal. The results of the performed simulations and comparisons clearly justify the efficiency of the proposed Algorithms for the stable analysis of large-size signals and 2D/3D images.

     

Voice assessments for detecting patients with Parkinson’s diseases using PCA and NPCA

In this study, we wanted to discriminate between two groups of people. The database used in this study contains 20 patients with Parkinson’s disease and 20 healthy people. Three types of sustained vowels (/a/, /o/ and /u/) were recorded from each participant and then the analyses were done on these voice samples. Firstly, an initial feature vector extracted from time, frequency and cepstral domains. Then we used linear and nonlinear feature extraction techniques, principal component analysis (PCA), and nonlinear PCA. These techniques reduce the number of parameters and choose the most effective acoustic features used for classification. Support vector machine with its different kernel was used for classification. We obtained an accuracy up to 87.50 % for discrimination between PD patients and healthy people.     

Application of the Resources Model to the Supervision of an Automated Process

The present study was designed to ascertain how far flagging up potential errors can improve the automatic interpretation of technical documents. We used the resources model to analyze the supervised retro-conversion of architectural floor plans from the perspective of distributed cognition. Results showed that automated assistance helps users to correct errors spotted by the system and saves time. Surprisingly, they also showed that flagging up possible errors may make users less effective in identifying and correcting errors that go unnoticed by the system. Responses to a questionnaire probing the participants’ confidence in the system suggested that they were so trusting that they lowered their vigilance in those areas that had not been signaled by the system, leading to the identification of fewer errors there. Thus, although the participants’ confidence in the automated assistance system led to improved performances in those areas it highlighted, it also meant that areas to which the system did not draw attention were less thoroughly checked.     

A comparative study of the removal of trivalent chromium from aqueous solutions by bentonite and expanded perlite

Local bentonite and expanded perlite (Morocco) have been characterised and used for the removal of trivalent chromium from aqueous solutions. The kinetic study had showed that the uptake of Cr(III) by bentonite is very rapid compared to expanded perlite. To calculate the sorption capacities of the two sorbents, at different pH, the experimental data points have been fitted to the Freundlich and Langmuir models, respectively, for bentonite and expanded perlite. For both sorbents the sorption capacity increases with increasing the pH of the suspensions. The removal efficiency has been calculated for both sorbents resulting that bentonite (96% of Cr(III) was removed) is more effective in removing trivalent chromium from aqueous solution than expanded perlite (40% of Cr(III) was removed). In the absence of Cr(III) ions, both bentonite and expanded perlite samples yield negative zeta potential in the pH range of 2-11. The changes of expanded perlite charge, from negative to positive, observed after contact with trivalent chromium(III) solutions was related to Cr(III) sorption on the surface of the solid. Thus, it was concluded that surface complexation plays an important role in the sorption of Cr(III) species on expanded perlite. In the case of bentonite, cation-exchange is the predominate mechanism for sorption of trivalent chromium ions, wherefore no net changes of zeta potential was observed after Cr(III) sorption. X-ray photoelectron spectroscopy measurements, at different pH values, were also made to corroborate the zeta potential results.     

Molecular weight influence on shape memory effect of shape memory polymer blend (poly(caprolactone)/styrene-butadiene-styrene)

The shape memory effect (SME) does not only concern the macroscopic structure. It concerns also the polymer structure at morphological, macromolecular, and molecular scales. This effect may depend on different physicochemical properties like morphology heterogeneity, chain rigidity, steric hindrance, chain polarity, free volume, cross-linking or entanglement density, molecular shape and weight, and so on. Hence, finding the relationship between the SME and these properties is very important. This can help to obtain the knowledge about the phenomenon origin and mechanism. One of the basic polymer properties, which can have direct SME, may be the molecular weight (M_w ). The question here is: If the M_w of a shape memory polymer (SMP) changes, for different reasons like degradation, what will be the effect of this change on its SME. In order to answer to this question, the investigation is focused on an SMP blend of 40% poly(ɛ-caprolactone) (PCL) and 60% styrene-butadiene-styrene (SBS). Then, enzymatic hydrolysis is performed on this blend to change its M_w . It is shown that this change is only related to the variation in the M_w of PCL. After that, different samples with a distinct average M_w are prepared and characterized by various experimental methods. Shape memory tests are performed on these blends, and the recovery rate (R_r ) for each of them is determined. It is found that when M_w of PCL decreases, its degree of crystallinity, its glass transition, and its melting temperatures, corresponding to the PCL phase, increase. However, the elongation at break of the blend declines with the reduction in M_w . The tests show that the alteration in the blend's M_w influences its SME. Indeed, R_r of the (PCL/SBS) mixture drops with the decrease in M_w of PCL.     

SupraCells: Living Mammalian Cells Protected within Functional Modular Nanoparticle‐Based Exoskeletons

Creating a synthetic exoskeleton from abiotic materials to protect delicate mammalian cells and impart them with new functionalities could revolutionize fields like cell‐based sensing and create diverse new cellular phenotypes. Herein, the concept of “SupraCells,” which are living mammalian cells encapsulated and protected within functional modular nanoparticle‐based exoskeletons, is introduced. Exoskeletons are generated within seconds through immediate interparticle and cell/particle complexation that abolishes the macropinocytotic and endocytotic nanoparticle internalization pathways that occur without complexation. SupraCell formation is shown to be generalizable to wide classes of nanoparticles and various types of cells. It induces a spore‐like state, wherein cells do not replicate or spread on surfaces but are endowed with extremophile properties, for example, resistance to osmotic stress, reactive oxygen species, pH, and UV exposure, along with abiotic properties like magnetism, conductivity, and multifluorescence. Upon decomplexation cells return to their normal replicative states. SupraCells represent a new class of living hybrid materials with a broad range of functionalities.     

Modular Assembly of Red Blood Cell Superstructures from Metal–Organic Framework Nanoparticle-Based Building Blocks

Bio/artificial hybrid nanosystems based on biological matter and synthetic nanoparticles (NPs) remain a holy grail of materials science. Herein, inspired by the well-defined metal–organic framework (MOF) with diverse chemical diversities, the concept of “armored red blood cells” (armored RBCs) is introduced, which are native RBCs assembled within and protected by a functional exoskeleton of interlinked MOF NPs. Exoskeletons are generated within seconds through MOF NP interlocking based on metal-phenolic coordination and RBC membrane/NP complexation via hydrogen-bonding interactions at the cellular interface. Armored RBC formation is shown to be generalizable to many classes of MOF NPs or any NPs that can be coated by MOF. Moreover, it is found that armored RBCs preserve the original properties of RBCs (such as oxygen carrier capability and good ex ovo/in vivo circulation property) and show enhanced resistance against external stressors (like osmotic pressure, detergent, toxic NPs, and freezing conditions). By modifying the physicochemical properties of MOF NPs, armored RBCs provide the capability for blood nitric oxide sensing or multimodal imaging. The synthesis of armored RBCs is straightforward, reliable, and reversible and hence, represent a new class of hybrid biomaterials with a broad range of functionalities.     

Flexible calibration of structured-light systems projecting point patterns

Structured-light systems (SLSs) are widely used in active stereo vision to perform 3D modelling of a surface of interest. We propose a flexible method to calibrate SLSs projecting point patterns. The method is flexible in two respects. First, the calibration is independent of the number of points and their spatial distribution inside the pattern. Second, no positioning device is required since the projector geometry is determined in the camera coordinate system based on unknown positions of the calibration board. The projector optical center is estimated together with the 3D rays originating from the projector using a numerical optimization procedure. We study the 3D point reconstruction accuracy for two SLSs involving a laser based projector and a pico-projector, respectively, and for three point patterns. We finally illustrate the potential of our active vision system for a medical endoscopy application where a 3D cartography of the inspected organ (a large field of view surface also including image textures) can be reconstructed from a video acquisition using the laser based SLS.     

Cu-Promoted Cobalt Oxide Film Catalyst for Efficient Gas Emissions Abatement

Thin film catalysts have been recently reported as promising catalysts owing to their good catalytic activity and reduced material amount, leading to low-cost efficient catalysts for gaseous emissions control. Here, we report the slight loading of Cu in cobalt spinel using a one-step pulsed-spray evaporation chemical vapor deposition(PSE-CVD) synthesis technique for efficient short-chain volatile organic compounds(VOCs) emissions treatment. Crystalline structure and morphology analyses revealed nano-crystallite sizes and open-like morphology. The catalytic performance was evaluated through the complete oxidation of C_3H_6, as a short-chain representative model of VOCs, at a high gas hourly space velocity(GHSV). Very good activity was obtained towards the complete abatement of C_3H_6 at low temperature and no carbon monoxide(CO) was formed during the oxidation process. Slightly-promoted Co_3O_4 catalyst with Cu introduction resulted in high catalytic activity comparing to the performance of the catalysts in the literature, due to the high dispersion of Cu and high active surface oxygen amount. Moreover, to evaluate the capability of the used catalysts under near realistic reaction conditions, CO_2 effect on the catalytic activity was performed and the catalyst exhibited very good results. Thus, the adopted slightly-doping strategy to tailor a high active catalyst at low temperature could establish a very promising route to strongly enhance the activity of such other catalysts towards gas emissions abatement at low temperature.