Synthesis of poly(N‐isopropylacrylamide) by distillation precipitation polymerization and quantitative grafting on mesoporous silica

In this work, syntheses of thermoresponsive poly(N‐isopropylacrylamide) (PNIPAM) with different molecular weights were carried out in ethanol by distillation precipitation polymerization (DPP) technique. The synthesized polymers were fully characterized by attenuated total reflection Fourier‐transform infrared (ATR‐FTIR) spectroscopy, nuclear magnetic resonance spectroscopy, and size exclusion chromatography techniques. The lower critical solution temperatures of the polymers were determined with differential scanning calorimetry. A simple and versatile method for the in situ synthesis and grafting of PNIPAM on mesoporus silica nanoparticles (MSNs) with improved control over quantitative grafting is devised. The PNIPAM grafted MSNs were characterized with ATR‐FTIR, thermogravimetric analysis, transmission electron microscopy, and dynamic light scattering analyses. From the results obtained it is showed that quantitative grafting of PNIPAM on MSNs from 1 to 20% by weight can be tuned by manipulating the in situ DPP reaction conditions. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 44181.     

Group contribution model for determination of molecular diffusivity of non-electrolyte organic compounds in air at ambient conditions

Determination of diffusion coefficients of pure compounds in air is of great interest for modeling of air pollution control processes. In this communication, a Group Contribution (GC) method is applied to represent/predict the molecular diffusivity of chemical compounds in air at 298.15 K and atmospheric pressure. 4661 compounds from various chemical families have been investigated to propose a comprehensive and predictive model. The final model is resulted from coupling the Artificial Neural Network (ANN) with group contributions. Using this dedicated model, we obtain satisfactory results quantified by the following statistical results: Squared Correlation Coefficient=0.995, Standard Deviation Error=0.02, and Average Absolute Deviation=1.4% for the calculated/predicted properties from existing experimental values.     

Skeletons for parallel image processing: an overview of the SKIPPER project

This paper is a general overview of the S project, run at Blaise Pascal University between 1996 and 2002. The main goal of the S project was to demonstrate the applicability of skeleton-based parallel programming techniques to the fast prototyping of reactive vision applications. This project has produced several versions of a full-fledged integrated parallel programming environment (PPE). These PPEs have been used to implement realistic vision applications, such as road following or vehicle tracking for assisted driving, on embedded parallel platforms embarked on semi-autonomous vehicles. All versions of S share a common front-end and repertoire of skeletons––presented in previous papers––but differ in the techniques used for implementing skeletons. This paper focuses on these implementation issues, by making a comparative survey, according to a set of four criteria (efficiency, expressivity, portability, predictability), of these implementation techniques. It also gives an account of the lessons we have learned, both when dealing with these implementation issues and when using the resulting tools for prototyping vision applications.     

Straightforward modeling of dynamic I–V characteristics for microwave FETs

This work presents a straightforward approach aimed at modeling the dynamic I–V characteristics of microwave active solid‐state devices. The drain‐source current generator represents the most significant source of nonlinearity in a transistor and, therefore, its correct modeling is fundamental to predict accurately the current and voltage waveforms under large‐signal operation. The proposed approach relies on using a small set of low‐frequency time‐domain waveform measurements combined with numerical optimization‐based estimation of the nonlinear model parameters. The procedure is applied to a gallium nitride HEMT and silicon FinFET. The effectiveness of the modeling procedure in terms of prediction accuracy and generalization capability is demonstrated by validation of the extracted models under operating conditions different than the ones used for the parameters estimation. Good agreement between measurements and model simulations is achieved for both technologies and in both low‐ and high‐frequency range. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:109–116, 2014.     

A general procedure for the design of bulk acoustic wave filters

This article presents a procedure for the design of bulk acoustic wave (BAW) filters. The procedure consists of optimizing the modified Butterworth‐Van Dyke model of each resonator, considering appropriate technological parameters. The approach is demonstrated first to design a classical aluminum nitride‐based BAW filter but remains valid for other piezoelectric layers, considering either longitudinal or transverse acoustic wave coupling. The approach is finally applied to the design of a lithium niobate (LiNbO₃) BAW filter for wide‐band filtering applications. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2011.     

Constraint based approach for the steady-state simulation of complex systems: Application to ship control

When the steady states are largely predominant with respect to transitional phases, steady-state simulation seems sufficient to predict the behavior of a complex system. Over the past 20 years, different modeling languages and dedicated tools have been developed to improve steady state simulation.In this paper, focus is made on steady-state simulation for system control and design. A model combining an emission sub-model with a ship propulsion sub-model was implemented in a constraint programming (CP) approach. It will help to determine the efficiency (i.e. the ability to model and solve the problem) and complexity of implementation (i.e. difficulties encountered during the implementation) of this approach.First, requirements for the steady-state simulation of complex systems are defined. Then, CP approach is shown to be able to answer these issues through experiments. This approach is then compared to one of the main simulation languages: Modelica.Although the two approaches (i.e Modelica and CP) are able to reverse models, the study shows that the use of Modelica principles for steady-state simulation involves some crippling limitations, such as the non-management of under/over-constrained systems, or inequalities.This study also shows that the constraint programming approach permits to meet some needs for steady-state simulation not yet covered by current approaches.     

Experience with a Hybrid Processor: K-Means Clustering

We discuss hardware/software co-processing on a hybrid processor for a compute- and data-intensive multispectral imaging algorithm, k-means clustering. The experiments are performed on two models of the Altera Excalibur board, the first using the soft IP core 32-bit NIOS 1.1 RISC processor, and the second with the hard IP core ARM processor. In our experiments, we compare performance of the sequential k-means algorithm with three different accelerated versions. We consider granularity and synchronization issues when mapping an algorithm to a hybrid processor. Our results show that speedup of 11.8X is achieved by migrating computation to the Excalibur ARM hardware/software as compared to software only on a Gigahertz Pentium III. Speedup on the Excalibur NIOS is limited by the communication cost of transferring data from external memory through the processor to the customized circuits. This limitation is overcome on the Excalibur ARM, in which dual-port memories, accessible to both the processor and configurable logic, have the biggest performance impact of all the techniques studied.     

Proteomics of plaques and novel sources of potential biomarkers for atherosclerosis

Cardiovascular disease (CVD) is the leading cause of death and loss of productive life years in the world. The underlying syndrome of CVD, atherosclerosis, is a complex disease process, which involves lipid metabolism, inflammation, innate and adaptive immunity, and many other pathophysiological aspects. Furthermore, CVD is influenced by genetic as well as environmental factors. Early detection of CVD and identification of patients at risk are crucial to reduce the burden of disease and to allow personalized treatment. As established risk factors fail to accurately predict which part of the population is likely to suffer from the disease, novel biomarkers are urgently needed. Proteomics can play a significant role in identifying these biomarkers. In this review, we describe the progress made in proteome profiling of the atherosclerotic plaque and several novel sources of potential biomarkers, including circulating cells and plasma extracellular vesicles. The importance of longitudinal biobanking in biomarker discovery is highlighted and exemplified by several plaque proteins identified in the biobank study Athero-Express. Finally, we discuss the PTMs of proteins that are involved in atherosclerosis, which may become one of the foci in the ongoing quest for biomarkers through proteomics of plaque and other matrices relevant to the progression of atherosclerosis.     

Social Exclusion in Later Life: A Systematic Review of the Literature

In the last decade, there has been a growing awareness regarding social exclusion. Considering the ageing population and the likelihood of older people being socially excluded, the aims of this article are to: (1) review existing studies concerning social exclusion in later life; and (2) identify how environmental and life-course perspectives are presented in studies focusing on social exclusion in later life. A systematic review in seven scientific databases was conducted to explore the peer-reviewed evidence. In total, 26 articles were included and analysed. Findings describe the variety of methods, conceptualisation, dimensions and measures used in this recent area of research. Determinants of social exclusion in later life are discussed and life-course and environmental perspectives are examined. The discussion highlights the complex character of the concept and measurement of social exclusion, and the presence of general and age-specific dimensions of social exclusion in later life. The time and context relativity and the need for life-course and environmental perspectives on social exclusion in later life are discussed. Finally, future directions of research are discussed.