Pilot-scale crossflow-microfiltration and pasteurization to remove spores of Bacillus anthracis (Sterne) from milk

High-temperature, short-time pasteurization of milk is ineffective against spore-forming bacteria such as Bacillus anthracis (BA), but is lethal to its vegetative cells. Crossflow microfiltration (MF) using ceramic membranes with a pore size of 1.4 μm has been shown to reject most microorganisms from skim milk; and, in combination with pasteurization, has been shown to extend its shelf life. The objectives of this study were to evaluate MF for its efficiency in removing spores of the attenuated Sterne strain of BA from milk; to evaluate the combined efficiency of MF using a 0.8-μm ceramic membrane, followed by pasteurization (72°C, 18.6 s); and to monitor any residual BA in the permeates when stored at temperatures of 4, 10, and 25°C for up to 28 d. In each trial, 95 L of raw skim milk was inoculated with about 6.5 log10 BA spores/mL of milk. It was then microfiltered in total recycle mode at 50°C using ceramic membranes with pore sizes of either 0.8 μm or 1.4 μm, at crossflow velocity of 6.2 m/s and transmembrane pressure of 127.6 kPa, conditions selected to exploit the selectivity of the membrane. Microfiltration using the 0.8-μm membrane removed 5.91 ± 0.05 log10 BA spores/mL of milk and the 1.4- μm membrane removed 4.50 ± 0.35 log10 BA spores/ mL of milk. The 0.8-μm membrane showed efficient removal of the native microflora and both membranes showed near complete transmission of the casein proteins. Spore germination was evident in the permeates obtained at 10, 30, and 120 min of MF time (0.8-μm membrane) but when stored at 4 or 10°C, spore levels were decreased to below detection levels (≤0.3 log10 spores/mL) by d 7 or 3 of storage, respectively. Permeates stored at 25°C showed coagulation and were not evaluated further. Pasteurization of the permeate samples immediately after MF resulted in additional spore germination that was related to the length of MF time. Pasteurized permeates obtained at 10 min of MF and stored at 4 or 10°C showed no growth of BA by d 7 and 3, respectively. Pasteurization of permeates obtained at 30 and 120 min of MF resulted in spore germination of up to 2.42 log10 BA spores/mL. Spore levels decreased over the length of the storage period at 4 or 10°C for the samples obtained at 30 min of MF but not for the samples obtained at 120 min of MF. This study confirms that MF using a 0.8-μm membrane before high-temperature, short-time pasteurization may improve the safety and quality of the fluid milk supply; however, the duration of MF should be limited to prevent spore germination following pasteurization

Game Interactive Learning: A New Paradigm towards Intelligent Decision-Making

Decision-making plays an essential role in various real-world systems like automatic driving, traffic dispatching, information system management, and emergency command and control. Recent breakthroughs in computer game scenarios using deep reinforcement learning for intelligent decision-making have paved decision-making intelligence as a burgeoning research direction. In complex practical systems, however, factors like coupled distracting features, long-term interact links, and adversarial environments and opponents, make decision-making in practical applications challenging in modeling, computing, and explaining. This work proposes game interactive learning, a novel paradigm as a new approach towards intelligent decision-making in complex and adversarial environments. This novel paradigm highlights the function and role of a human in the process of intelligent decision-making in complex systems. It formalizes a new learning paradigm for exchanging information and knowledge between humans and the machine system. The proposed paradigm first inherits methods in game theory to model the agents and their preferences in the complex decision-making process. It then optimizes the learning objectives from equilibrium analysis using reformed machine learning algorithms to compute and pursue promising decision results for practice. Human interactions are involved when the learning process needs guidance from additional knowledge and instructions, or the human wants to understand the learning machine better. We perform preliminary experimental verification of the proposed paradigm on two challenging decision-making tasks in tactical-level War-game scenarios. Experimental results demonstrate the effectiveness of the proposed learning paradigm

Méthodes éléments finis avancées appliquées à la modélisation de tissus biologiques en biomécanique

This thesis has focused on the construction of strain energy densities for describing the non-linear behavior of anisotropic materials such as biological soft tissues (ligaments, tendons, arterial walls, etc.) or fiber-reinforced rubbers. The densities we have proposed have been developed with the mathematical theory of invariant polynomials, particularly the Noether theorem and the Reynolds operator. Our work involved two types of anisotropic materials, the first with a single fiber family and the second with a four-fiber family. The concept of polyconvexity has also been studied because it is well known that it plays an important role for ensuring the existence of solutions. In the case of a single fiber family, we have demonstrated that it is impossible for a polynomial density of any degree to predict shear tests with a loading parallel and then perpendicular to the direction of the fibers. A linear polynomial density combined with a power-law function allowed to overcome this problem. In the case of a material made of a four-fiber family, a polynomial density allowed to correctly predict bi-axial tensile test data extracted from the literature. The two proposed densities were implemented in C++ language in the university finite element software FER by adopting a total Lagrangian formulation. This implementation has been validated by comparisons with reference analytical solutions exhibited in the case of simple loads leading to homogeneous deformations. More complex three-dimensional examples, involving non-homogeneous deformations, have also been studied.Cette thèse a porté sur la construction de densités d'énergie de déformation permettant de décrire le comportement non linéaire de matériaux anisotropes tels que les tissus biologiques souples (ligaments, tendons, parois artérielles etc.) ou les caoutchoucs renforcés par des fibres. Les densités que nous avons proposées ont été élaborées en se basant sur la théorie mathématique des polynômes invariants et notamment sur le théorème de Noether et l'opérateur de Reynolds. Notre travail a concerné deux types de matériaux anisotropes, le premier avec une seule famille de fibre et le second avec quatre familles. Le concept de polyconvexité a également été étudié car il est notoire qu'il joue un rôle important pour s'assurer de l'existence de solutions. Dans le cas d'un matériau comportant une seule famille de fibre, nous avons démontré qu'il était impossible qu'une densité polynomiale de degré quelconque puisse prédire des essais de cisaillement avec un chargement parallèle puis perpendiculaire à la direction des fibres. Une densité polynomiale linéaire combinée avec une fonction puissance a permis de contourner cet obstacle. Dans le cas d'un matériau comportant quatre familles de fibre, une densité polynomiale a permis de prédire correctement des résultats d'essai en traction bi-axiale extraits de la littérature. Les deux densités proposées ont été implémentées avec la méthode des éléments finis et en langage C++ dans le code de calcul universitaire FER. Pour se faire, une formulation lagrangienne totale a été adoptée. L'implémentation a été validée par des comparaisons avec des solutions analytiques de référence que nous avons exhibée dans le cas de chargements simples conduisant à des déformations homogènes. Des exemples tridimensionnels plus complexes, impliquant des déformations non-homogènes, ont également été étudiés

Identification of Lactobacillus Strains Capable of Fermenting Fructo-Oligosaccharides and Inulin

Novel probiotic strains that can ferment prebiotics are important for functional foods. The utilization of prebiotics is strain specific, so we screened 86 Lactobacillus strains and compared them to Bifidobacterium breve 2141 for the ability to grow and produce SCFA when 1% inulin or fructo-oligosaccharides (FOS) were provided as the carbon source in batch fermentations. When grown anaerobically at 32 °C, ten Lactobacillus strains grew on both prebiotic substrates (OD600 ≥ 1.2); while Lactobacillus coryniformis subsp. torquens B4390 grew only in the presence of inulin. When the growth temperature was increased to 37 °C to simulate the human body temperature, four of these strains were no longer able to grow on either prebiotic. Additionally, L. casei strains 4646 and B441, and L. helveticus strains B1842 and B1929 did not require anaerobic conditions for growth on both prebiotics. Short-chain fatty acid analysis was performed on cell-free supernatants. The concentration of lactic acid produced by the ten Lactobacillus strains in the presence of prebiotics ranged from 73–205 mM. L. helveticus B1929 produced the highest concentration of acetic acid ~19 mM, while L. paraplantarum B23115 and L. paracasei ssp. paracasei B4564 produced the highest concentrations of propionic (1.8–4.0 mM) and butyric (0.9 and 1.1 mM) acids from prebiotic fermentation. L. mali B4563, L. paraplantarum B23115 and L. paracasei ssp. paracasei B4564 were identified as butyrate producers for the first time. These strains hold potential as synbiotics with FOS or inulin in the development of functional foods, including infant formula

A new hyperelastic strain energy function and integrity basis of invariants for modelling transversely isotropic materials

International audienceThe present paper proposes a new Strain Energy Function (SEF) for incompressible transversely isotropic hyperelastic materials, i.e. materials with a single fiber family. This SEF combines polyconvex invariants forming an integrity basis (Ta et al., 2014) in a polynomial and exponential form. Compared to a previous attempt for building a SEF based on the same invariants (Cai et al., 2016), we have reduced the number of material parameters from 23 to 10, without losing any accuracy on the numerical results. The 10 material parameters are identified by comparing the closed form solutions deriving from our model with experimental and numerical data extracted from the literature. These data concern uniaxial tension and shear tests, both parallel and transverse to the fiber direction (Ciarletta et al., 2011; Davis and De Vita, 2014) [3, 4], as well as shear calculations with 9 different fiber angles (Horgan and Murphy, 2017) [5]. Due to the variety of the considered situations, we have developed specific identification strategies based on: 1) the linear or nonlinear nature of the material parameters of the model; 2) the modeling of the free boundary conditions by a spectral approach

A simple polyconvex strain energy density with new invariants for modeling four-fiber family biomaterials

International audienceWe introduce in this paper a new hyperelastic model for the prediction of nonlinear mechanical properties of anisotropic hyperelastic materials under biaxial stretching. The proposed strain energy function (SEF) can be applied for understanding the nature of behavior laws for materials with four-fiber family structures, which has a large potential of applications, particularly in biomechanics, surgical and interventional therapies for peripheral artery disease (PAD). This SEF is built with a recent and new invariant system based on the mathematical theory of invariant polynomials. By recombining them in an appropriate manner, we demonstrate that it is possible to build a polyconvex integrity basis of invariants. Accuracy and reliability of the corresponding numerical model were validated by a comparison with experimental and numerical results extracted from Kamenskiy et al. (2014). 1 1We warmly thank Assistant Professor Kamenskiy to have kindly provided us the numerical data corresponding to the measurements included in These results concerned diseased superficial femoral (SFA), popliteal (PA) and tibial arteries (TA) from one patient under planar biaxial extension. For each kind of arteries tested with 5 combinations of different biaxial stretches, the predicted results of the proposed model and the experimental data are consistent. Our model includes 7 material parameters and their identification result in a single solution because of the linear form we have chosen for the SEF with respect to the material parameters

Deep Learning for Finger Vein Recognition: A Brief Survey of Recent Trend

Finger vein image recognition technology plays an important role in biometric recognition and has been successfully applied in many fields. Because veins are buried beneath the skin tissue, finger vein image recognition has an unparalleled advantage, which is not easily disturbed by external factors. This review summarizes 46 papers about deep learning for finger vein image recognition from 2017 to 2021. These papers are summarized according to the tasks of deep neural networks. Besides, we present the challenges and potential development directions of finger vein image recognition

Convexity, polyconvexity and finite element implementation of a four-fiber anisotropic hyperelastic strain energy density—Application to the modeling of femoral, popliteal and tibial arteries

International audienceComputational analysis of the nonlinear mechanical properties of anisotropic hyperelastic materials aims at a better understanding of its physiology and pathophysiology under different loading conditions. This has an important role in biomechanics, surgical, clinical diagnostic and design of medical devices. This study investigates the modeling of arterial tissues made of a four-fiber family by using an anisotropic hyperelastic model. This model is based on the theory of polynomial invariant and was implemented in the university finite element code FER. The convex property of the strain energy function is investigated as well as the positive definite nature of the tangent stiffness matrix used within the framework of a finite element analysis. This allows us to guarantee the invertibility of the linearized problem and the uniqueness of the solution computed at each step of the Newton–Raphson scheme used to solve nonlinear problems