Life cycle cost and energy analysis of a Net Zero Energy House with solar combisystem

The Net Zero Energy House (NZEH) presented in this paper is an energy efficient house that uses available solar technologies to generate at least as much primary energy as the house uses over the course of the year. The computer simulation results show that it is technically feasible to reach the goal of NZEH in the cold climate of Montreal. In terms of the life cycle energy use, which considers the operating and embodied energy of the house, the energy payback time is 8.4–8.7 years, when the NZEH is compared with an average house that complies with the provincial code. The energy payback ratio of the combisystem is 3.5–3.8 compared with the heating system of conventional house. By converting solar energy, the combisystem supplies at least 3.5 times more energy than the energy invested for manufacturing and shipping the system. The life cycle cost analysis of the NZEH shows, however, that due to the high cost of the solar technologies and the low cost of electricity in Montreal, financial payback is never achieved.     

Critical Review of the Evolution of Extracellular Vesicles’ Knowledge: From 1946 to Today

Extracellular vesicles (EVs) are a family of particles/vesicles present in blood and body fluids, composed of phospholipid bilayers that carry a variety of molecules that can mediate cell communication, modulating crucial cell processes such as homeostasis, induction/dampening of inflammation, and promotion of repair. Their existence, initially suspected in 1946 and confirmed in 1967, spurred a sharp increase in the number of scientific publications. Paradoxically, the increasing interest for EV content and function progressively reduced the relevance for a precise nomenclature in classifying EVs, therefore leading to a confusing scientific production. The aim of this review was to analyze the evolution of the progress in the knowledge and definition of EVs over the years, with an overview of the methodologies used for the identification of the vesicles, their cell of origin, and the detection of their cargo. The MISEV 2018 guidelines for the proper recognition nomenclature and ways to study EVs are summarized. The review finishes with a “more questions than answers” chapter, in which some of the problems we still face to fully understand the EV function and potential as a diagnostic and therapeutic tool are analyzed.     

Sounds Stimulation on In Vitro HL1 Cells: A Pilot Study and a Theoretical Physical Model

Mechanical vibrations seem to affect the behaviour of different cell types and the functions of different organs. Pressure waves, including acoustic waves (sounds), could affect cytoskeletal molecules via coherent changes in their spatial organization and mechano-transduction signalling. We analyzed the sounds spectra and their fractal features. Cardiac muscle HL1 cells were exposed to different sounds, were stained for cytoskeletal markers (phalloidin, beta-actin, alpha-tubulin, alpha-actinin-1), and studied with multifractal analysis (using FracLac for ImageJ). A single cell was live-imaged and its dynamic contractility changes in response to each different sound were analysed (using Musclemotion for ImageJ). Different sound stimuli seem to influence the contractility and the spatial organization of HL1 cells, resulting in a different localization and fluorescence emission of cytoskeletal proteins. Since the cellular behaviour seems to correlate with the fractal structure of the sound used, we speculate that it can influence the cells by virtue of the different sound waves’ geometric properties that we have photographed and filmed. A theoretical physical model is proposed to explain our results, based on the coherent molecular dynamics. We stress the role of the systemic view in the understanding of the biological activity.     

Interfacial and Bulk Magnetic Properties of Stoichiometric Cerium Doped Terbium Iron Garnet Polycrystalline Thin Films

One of the best magneto‐optical claddings for optical isolators in photonic integrated circuits is sputter deposited cerium‐doped terbium iron garnet (Ce:TbIG) which has a large Faraday rotation (≈?3500° cm^?1 at 1550 nm). Near‐ideal stoichiometry $\left(\frac{\text{Ce}+\text{Tb}}{\text{Fe}}=0.57\right)$ of Ce_0.5Tb_2.5Fe_4.75O₁₂ is found to have a 44 nm magnetic dead layer that can impede the interaction of propagating modes with garnet claddings. The effective anisotropy of Ce:TbIG on Si is also important, but calculations using bulk thermal mismatch overestimate the effective anisotropy. Here, X‐ray diffraction measurements yield highly accurate measurements of strain that show anisotropy favors an in‐plane magnetization in agreement with the positive magnetostriction of Ce:TbIG. Upon doping TbIG with Ce, a slight decrease in compensation temperature occurs which points to preferential rare‐earth occupation in dodecahedral sites and an absence of cation redistribution between different lattice sites. The high Faraday rotation, large remanent ratio, large coercivity, and preferential in‐plane magnetization enable Ce:TbIG to be an in‐plane latched garnet, immune to stray fields with magnetization collinear to direction of light propagation.     

Polyhedral object recognition by indexing

In computer vision, the indexing problem is the problem of recognizing a few objects in a large database of objects while avoiding the help of the classical image-feature-to-object-feature matching paradigm. In this paper we address the problem of recognizing three-dimensional (3-D) polyhedral objects from 2-D images by indexing. Both the objects to be recognized and the images are represented by weighted graphs. The indexing problem is therefore the problem of determining whether a graph extracted from the image is present or absent in a database of model graphs. We introduce a novel method for performing this graph indexing process which is based both on polynomial characterization of binary and weighted graphs and on hashing. We describe in detail this polynomial characterization and then we show how it can be used in the context of polyhedral object recognition. Next we describe a practical recognition-by-indexing system that includes the organization of the database, the representation of polyhedral objects in terms of 2-D characteristic views, the representation of this views in terms of weighted graphs and the associated image processing. Finally, some experimental results allow the evaluation of the system performance.     

Prevalence of Salmonella in broilers at retail outlets, processing plants and farms in Malaysia

A study was conducted to estimate the prevalence of Salmonella among broilers retailed at wet-markets and processing plants. Litter and feed samples obtained from both broiler and breeder farms were also examined for Salmonella. A total of 158 out of 445 (35.5%) and 52 out of 104 (50.0%) broiler carcasses obtained from wet-markets and processing plants were contaminated with Salmonella, respectively. Salmonella was isolated from 14 out of 98 (14.3%) samples of intestinal content. Litter samples from broiler and breeder farms were positive for Salmonella, 8/40 (20%) and 2/10 (20%), respectively. Salmonella isolates (230) belonging to 15 different serovars were isolated. Predominant serovars were S. enteritidis, S. muenchen, S. kentucky and S. blockley.     

Smooth curve extraction by mean field annealing

In this paper, we attack the figure — ground discrimination problem from a combinatorial optimization perspective. In general, the solutions proposed in the past solved this problem only partially: either the mathematical model encoding the figure — ground problem was too simple or the optimization methods that were used were not efficient enough or they could not guarantee to find the global minimum of the cost function describing the figure — ground model. The method that we devised and which is described in this paper is tailored around the following contributions. First, we suggest a mathematical model encoding the figure — ground discrimination problem that makes explicit a definition of shape (or figure) based on cocircularity, smoothness, proximity, and contrast. This model consists of building a cost function on the basis of image element interactions. Moreover, this cost function fits the constraints of aninteracting spin system, which in turn is a well suited physical model to solve hard combinatorial optimization problems. Second, we suggest a combinatorial optimization method for solving the figure — ground problem, namely mean field annealing which combines the mean field approximation and annealing. Mean field annealing may well be viewed as a deterministic approximation of stochastic methods such as simulated annealing. We describe in detail the theoretical bases of this method, derive a computational model, and provide a practical algorithm. Finally, some experimental results are shown for both synthetic and real images.This research has been sponsored in part by Commissariat à l'Energie Atomique, and in part by the ORASIS project (PRC Communications Homme/Machine).     

Anderson accelerated fixed-stress splitting schemes for consolidation of unsaturated porous media

In this paper, we study the robust linearization of nonlinear poromechanics of unsaturated materials. The model of interest couples the Richards equation with linear elasticity equations, generalizing the classical Biot equations. In practice a monolithic solver is not always available, defining the requirement for a linearization scheme to allow the use of separate simulators. It is not met by the classical Newton method. We propose three different linearization schemes incorporating the fixed-stress splitting scheme, coupled with an L-scheme, Modified Picard and Newton linearization of the flow equations. All schemes allow the efficient and robust decoupling of mechanics and flow equations. In particular, the simplest scheme, the Fixed-Stress-L-scheme, employs solely constant diagonal stabilization, has low cost per iteration, and is very robust. Under mild, physical assumptions, it is theoretically shown to be a contraction. Due to possible break-down or slow convergence of all considered splitting schemes, Anderson acceleration is applied as post-processing. Based on a special case, we justify theoretically the general ability of the Anderson acceleration to effectively accelerate convergence and stabilize the underlying scheme, allowing even non-contractive fixed-point iterations to converge. To our knowledge, this is the first theoretical indication of this kind. Theoretical findings are confirmed by numerical results. In particular, Anderson acceleration has been demonstrated to be very effective for the considered Picard-type methods. Finally, the Fixed-Stress-Newton scheme combined with Anderson acceleration shows the best performance among the splitting schemes.     

Inducing strong convergence into the asymptotic behaviour of proximal splitting algorithms in Hilbert spaces

Proximal splitting algorithms for monotone inclusions (and convex optimization problems) in Hilbert spaces share the common feature to guarantee for the generated sequences in general weak convergence to a solution. In order to achieve strong convergence, one usually needs to impose more restrictive properties for the involved operators, like strong monotonicity (respectively, strong convexity for optimization problems). In this paper, we propose a modified Krasnosel'ski?–Mann algorithm in connection with the determination of a fixed point of a nonexpansive mapping and show strong convergence of the iteratively generated sequence to the minimal norm solution of the problem. Relying on this, we derive a forward–backward and a Douglas–Rachford algorithm, both endowed with Tikhonov regularization terms, which generate iterates that strongly converge to the minimal norm solution of the set of zeros of the sum of two maximally monotone operators. Furthermore, we formulate strong convergent primal–dual algorithms of forward–backward and Douglas–Rachford-type for highly structured monotone inclusion problems involving parallel-sums and compositions with linear operators. The resulting iterative schemes are particularized to the solving of convex minimization problems. The theoretical results are illustrated by numerical experiments on the split feasibility problem in infinite dimensional spaces.     

Formal modelling and verification of GALS systems using GRL and CADP

A GALS (Globally Asynchronous, Locally Synchronous) system consists of several synchronous components that evolve concurrently and interact with each other asynchronously. The design of GALS systems is tedious and error-prone due to the high degree of synchronous and asynchronous concurrency present in complex architectures. In this paper, we present GRL (GALS Representation Language), a formal language designed to model GALS systems, for the purpose of formal verification of the asynchronous aspects. GRL combines the synchronous reactive model underlying dataflow languages and the asynchronous concurrent model underlying process algebras. We propose a translation from GRL to LNT, a value-passing concurrent language with classical process algebra flavour. This makes possible the analysis of GRL specifications using all the state-of-the-art simulation and verification functionalities provided by the CADP toolbox.