Individual cell lag time distributions of Cronobacter (Enterobacter sakazakii) and impact of pooling samples on its detection in powdered infant formula

Cells of six strains of Cronobacter were subjected to dry stress and stored for 2.5 months at ambient temperature. The individual cell lag time distributions of recovered cells were characterized at 25 °C and 37 °C in non-selective broth. The individual cell lag times were deduced from the times taken by cultures from individual cells to reach an optical density threshold. In parallel, growth curves for each strain at high contamination levels were determined in the same growth conditions. In general, the extreme value type II distribution with a shape parameter fixed to 5 (EVIIb) was the most effective at describing the 12 observed distributions of individual cell lag times. Recently, a model for characterizing individual cell lag time distribution from population growth parameters was developed for other food-borne pathogenic bacteria such as Listeria monocytogenes. We confirmed this model’s applicability to Cronobacter by comparing the mean and the standard deviation of individual cell lag times to populational lag times observed with high initial concentration experiments. We also validated the model in realistic conditions by studying growth in powdered infant formula decimally diluted in Buffered Peptone Water, which represents the first enrichment step of the standard detection method for Cronobacter. Individual lag times and the pooling of samples significantly affect detection performances.     

Hybrid verification integrating HOL theorem proving with MDG model checking

In this paper, we describe a hybrid tool for hardware formal verification that links the HOL (higher-order logic) theorem prover and the MDG (multiway decision graphs) model checker. Our tool supports abstract datatypes and uninterpreted function symbols available in MDG, allowing the verification of high-level specifications. The hybrid tool, HOL-MDG, is based on an embedding in HOL of the grammar of the hardware modeling language, MDG-HDL, as well as an embedding of the first-order temporal logic L_mdg used to express properties for the MDG model checker. Verification with the hybrid tool is faster and more tractable than using either tools separately. We hence obtain the advantages of both verification paradigms.     

Thymoquinone effects on DMH-induced erythrocyte oxidative stress and haematological alterations during colon cancer promotion in rats

The effect of thymoquinone (TQ), the abundant component of black cumin seed (Nigella sativa) oil extract, was evaluated on 1,2-dimethylhydrazine (DMH)-induced erythrocyte oxidative stress and haematological perturbations during colon cancer promotion in rats. Two TQ approaches, the pre- and post-treatment, were used. DMH promoted erythrocyte oxidative damage in rats by enhancing lipid peroxidation (30%) and decreasing antioxidant enzymes activities (20–35%). This was associated with the decline of erythrocyte count, haemoglobin concentration and haematocrit (20%) and the count increase of white blood cell (60%) and platelet (180%). TQ pre-treatment repaired DMH-induced erythrocyte oxidative stress, anaemia, leukocytosis, and thrombocytosis and allowed a 60% of tumour incidence decline. TQ post-treatment exerted a slight effect on erythrocyte oxidative stress and reduced colon cancer incidence by 30% only. Thus, TQ efficacy in preventing DMH-induced colon cancer promotion was related to its virtue antioxidant effect on erythrocyte oxidative stress.     

An end-to-end neural network for detecting hidden people in images based on multiple attention network

Camouflaged people like soldiers on the battlefield or even camouflaged objects in the natural environments are hard to be detected because of the strong resemblances between the hidden target and the background. That’s why seeing these hidden objects is a challenging task. Due to the nature of hidden objects, identifying them require a significant level of visual perception. To overcome this problem, we present a new end-to-end framework via a multi-level attention network in this paper. We design a novel inception module to extract multi-scale receptive fields features aiming at enhancing feature representation. Furthermore, we use a dense feature pyramid taking advantage of multi-scale semantic features. At last, to locate and distinguish the camouflaged target better from the background, we develop a multi-attention module that generates more discriminative feature representation and combines semantic information with spatial information from different levels. Experiments on the camouflaged people dataset show that our approach outperformed all state-of-the-art methods.

     

Electrochemical treatment of the pollutants generated in an ink-manufacturing process

The effluents of ink-manufacturing processes contain a large variety of pollutants such as dyes, surfactants, biocides, water soluble solvents, etc. In this work, the electrochemical oxidation of several dyes (methylene blue and rhodamine B), solvents (monoethylene glycol, diethylene glycol and glycerol) and surfactants (sodium dodecylbenzenesulfonate) has been studied. To carry out the electrolyses, a bench-scale plant with a single-compartment electrochemical flow-cell was used. Boron doped diamond (BDD) was used as anode and stainless steel (AISI 304) as cathode. For all the compounds tested, the conductive diamond electrooxidation allows achieving the almost complete removal of COD of the waste with a very high current efficiency. The efficiencies of the electrochemical processes seem to depend on the current density and on the nature of the anions contained in the waste (chlorine, sulphate, phosphate). Thus, it has been observed that the use of chloride media favours the treatment of dyes. On the contrary, the use of sulphate- or phosphate-containing solutions improves the removal of the aliphatic compounds studied (solvents). These results suggest an important role of the mediated electrochemical processes on the overall performance of the reaction system.     

Reflexive transitive invariant relations: A basis for computing loop functions

Invariant assertions play an important role in the analysis and verification of iterative programs. In this paper, we introduce a related but distinct concept, namely that of invariant relation. While invariant assertions are useful to prove the correctness of a loop with respect to a specification (represented by a precondition/ postcondition pair) in Hoare’s logic, invariant relations are useful to derive the function of the loop in Mills’ logic.     

Electrochemical degradation of an anionic surfactant on boron-doped diamond anodes

In this work, the electrochemical oxidation on boron-doped diamond of synthetic wastes polluted with surfactant sodium dodecylbenzenesulfonate (SDBS) has been studied. Results show that SDBS can be successfully removed with this technology inside different current densities and concentration ranges. The oxidation of the SDBS seems to occur in two main sequential steps: the first is the rapid degradation of SDBS, and the final is the less efficient oxidation of aliphatic intermediates to carbon dioxide. The nature of supporting electrolyte (NaCl, Na(2)SO(4) and K(3)PO(4)) influences on the efficiency of the electrochemical oxidation process. The treatment of the NaCl solution seems to be more efficient in the chemical oxygen demand (COD) removal, while the sulphate and specially the phosphate media improve the TOC removal. However, in spite of this observation, chemical oxidation of SDBS by different types of oxidants cannot explain alone the results of the electrochemical oxidation with diamond anodes. This suggests that the synergistic effect of the different oxidation mechanisms that occurs into the electrochemical cell (direct oxidation and mediated oxidation by hydroxyl radicals and by oxidants formed from the electrolyte) is the responsible of the great efficiencies obtained with this technology in the treatment of organics.