Design of an antibacterial gelatin based on a covalent protein–protein coupling

An antibacterial peptide (AMP), i.e., nisin, was covalently bound to gelatin through a protein–protein coupling. Various reaction conditions were tested to study and optimize parameters of grafting e.g., orientation and density of AMP, which could impact the final antibacterial activity of the modified biopolymer. Modification was investigated by Fourier transform infrared (FT‐IR) spectroscopy and zeta potential. The antibacterial activity of the nisin‐enriched gelatin was evaluated against two staphylococci bacterial strains, i.e., Staphylococus epidermidis and Staphylococcus aureus. A higher activity was found for gelatin modified at pH = 7.4 revealing an influence of the nisin orientation on the protein antibacterial property. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41825.     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

Radiometric sensor for temperature control of food processing

This paper describes a novel planar antenna sensor created for the purpose of noninvasive temperature measurements using microwave radiometry. In order to improve radiometric measurements in industrial applications, a new generation of sensors is introduced, composed of a metallic sheet. Simulations based upon the method of moments is used both to design and to determine their electromagnetic performances. This paper also describes a radiometric device using these sensors to measure and control the temperature of food products during deep freezing processes. The results and discussions are presented.     

Fuzzy sets-a convenient fiction for modeling vagueness andpossibility

This paper is a reply to Laviolette and Seaman's critical discussion of fuzzy set theory. Rather than questioning the interest of the Bayesian approach to uncertainty, some reasons why Bayesian find the idea of a fuzzy set not palatable are laid bare. Some links between fuzzy sets and probability that Laviolette and Seaman seem not to be aware of are pointed out. These links suggest that, contrary to the claim sometimes found in the literature, probability theory is not a special case of fuzzy set theory. The major objection to Laviolette and Seaman is that they found their critique on as very limited view of fuzzy sets, including debatable papers, while they fail to account for significant works pertaining to axiomatic derivation of fuzzy set connectives, possibility theory, fuzzy random variables, among others     

Engagement of T cell receptor triggers its recruitment to low-density detergent-insoluble membrane domains

T-cell receptors (TCRs) upon binding to peptide-MHC ligands transduce signals in T lymphocytes. Tyrosine phosphorylations in the cytoplasmic domains of the CD3 (gammadeltaepsilon) and zeta subunits of the TCR complex by Src family kinases initiate the signaling cascades via docking and activation of ZAP-70 kinase and other signaling components. We examined the role of the low-density detergent-insoluble membranes (DIMs) in TCR signaling. Using mouse thymocytes as a model, we characterized the structural organization of DIMs in detail. We then demonstrated that TCR engagement triggered an immediate increase in the amount of TCR/CD3 present in DIMs, which directly involves the engaged receptor complexes. TCR/CD3 recruitment is accompanied by the accumulation of a series of prominent tyrosine-phosphorylated substrates and by an increase of the Lck activity in DIMs. Upon TCR stimulation, the DIM-associated receptor complexes are highly enriched in the hyperphosphorylated p23 zeta chains, contain most of the TCR/CD3-associated, phosphorylation-activated ZAP-70 kinases and seem to integrate into higher order, multiple tyrosine-phosphorylated substrate-containing protein complexes. The TCR/CD3 recruitment was found to depend on the activity of Src family kinases. We thus provide the first demonstration of recuitment of TCR/CD3 to DIMs upon receptor stimulation and propose it as a mechanism whereby TCR engagement is coupled to downstream signaling cascades.     

A Sketch-Based Interface for Clothing Virtual Characters

This interactive system for garment creation determines a garment's shape and how the character wears it based on a user-drawn sketch. The system then uses distances between the 2D garment silhouette and the character model to infer remaining distance variations in 3D     

Hybrid Approach for Addressing Uncertainty in Risk Assessments

Parameter uncertainty is a major aspect of the model-based estimation of the risk of human exposure to pollutants. The Monte Carlo method, which applies probability theory to address model parameter uncertainty, relies on a statistical representation of available information. In recent years, other uncertainty theories have been proposed as alternative approaches to address model parameter uncertainty in situations where available information is insufficient to identify statistically representative probability distributions, due in particular to data scarcity. The simplest such theory is possibility theory, which uses so-called fuzzy numbers to represent model parameter uncertainty. In practice, it may occur that certain model parameters can be reasonably represented by probability distributions, because there are sufficient data available to substantiate such distributions by statistical analysis, while others are better represented by fuzzy numbers (due to data scarcity). The question then arises as to how these two modes of representation of model parameter uncertainty can be combined for the purpose of estimating the risk of exposure. This paper proposes an approach (termed a hybrid approach) which combines Monte Carlo random sampling of probability distribution functions with fuzzy calculus. The approach is applied to a real case of estimation of human exposure, via vegetable consumption, to cadmium present in the surficial soils of an industrial site located in the north of France. The application illustrates the potential of the proposed approach, which allows the uncertainty affecting model parameters to be represented in a way that is consistent with the information at hand. Also, because the hybrid approach takes advantage of the “rich” information provided by probability distributions, while retaining the conservative character of fuzzy calculus, it is believed to hold value in terms of a “reasonable” application of the precautionary principle.     

Complete oxidation of methane at low temperature over Pt and Pd catalysts for the abatement of lean-burn natural gas fuelled vehicles emissions: influence of water and sulphur containing compounds

The catalytic activity of fresh Pd and Pt catalysts supported on γ-alumina in the complete oxidation of CH₄ traces under lean-burn conditions was studied in the presence or the absence of water or H₂S. Steam-aged catalysts were also studied in order to simulate long-term ageing in real lean-burn natural gas fuelled vehicles (NGVs) exhaust conditions. Without water or H₂S added to the feed, Pd catalysts exhibit a superior catalytic activity in methane oxidation compared to Pt ones, whatever the catalysts were fresh or aged. The addition of 10 vol.% water vapour to the feed strongly affects the activity of the fresh Pd catalyst, thus being only slightly more efficient than the fresh Pt one. H₂S has a strong poisoning effect on the catalytic activity of Pd catalysts, while Pt catalysts are more resistant. The fresh H₂S-poisoned Pd/Al₂O₃ catalyst was studied by TPD in O₂/He. Poisoning species decompose above 873 K as SO₂ and O₂ in relative concentrations consistent with the decomposition of surface sulphate species. However, a treatment in O₂/He at temperatures as high as 923 K does not allow the complete regeneration of the catalytic activity of H₂S-poisoned Pd/Al₂O₃. A mechanism involving the poisoning of PdO by sulphate species is proposed. Different diffusion processes by which these sulphate species can migrate back and forth between PdO and the support, depending on the experimental conditions, are suggested.     

Golden interfaces: The Surface of Self-Assembled Monolayers

Self-assembled monolayers (SAMs) of alkanethiols and disulfides on gold form organic interfaces with properties largely controlled by the end groups of the molecules composing the film. SAMs provide a unique link between the science of organic surfaces and technologies that seek to exploit their adaptable character. Many techniques are useful for probing the structure of SAMs although only scanning tunneling microscopy (STM) at picoamperes reveals the details of the packing of their end groups at the sub-angstrom level. This review demonstrates that STM effectively tests new types of control over the microscopic structure–property relationships characteristic of SAMs on gold that should prove useful to their application.