Multi‐Scale Bionic Structure Constructs Biomass Flame‐Retardant Thermal Insulation Foam Material
Inspired by mussel adhesion and hierarchical brick‐and‐mortar architectures, a cellulose‐based biomimetic foam is constructed by anchoring bentonite nanosheets onto a polydopamine‐decorated cellulose nanofiber network. The resulting foam combines low thermal conductivity with intrinsic flame retardancy and full biodegradability, presenting a ...
Jianming Liao +10 more
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Long-term control of <i>Legionella pneumophila</i> and <i>Pseudomonas aeruginosa</i> in dental unit waterlines following optimization of a hypochlorous acid-based water safety program. [PDF]
Wolf A +3 more
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Gut Microbiome Diversity, Functional Potential, and Ecological Relevance of Hottentotta tamulus. [PDF]
Khan KU +8 more
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Integrated GC-HRAM-MS and UHPLC-QTOF-MS metabolomics reveal mineral-induced metabolic adaptation of <i>Lactiplantibacillus pentosus</i> 9D3 during milk fermentation. [PDF]
Tunsagool P +8 more
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Integrated Assessment of Shelf Life Evolution in Small Marine Fish from the Northwestern Spanish Coast: Microbial, Chemical, and Sensory Changes During Chilled Storage. [PDF]
Aubourg SP +4 more
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Microbial Survival, Sublethal Injury, and Recovery in Frozen Food Systems: Implications for Safety, Quality Deterioration, and Cold-Chain Control. [PDF]
Chen A, Qu T, Li J, Du G, Chen J.
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On Modeling the Irregular Fluctuations in Microbial Counts
Critical Reviews in Food Science and Nutrition, 1999Daily or other periodic microbial counts in many foods, particularly ground meats, poultry, and raw milk, show an irregular fluctuating pattern. The cause of the fluctuations is the interplay of many random factors that tend to promote or inhibit microbial growth.
Micha Peleg, J Horowitz
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Fitting a distribution to microbial counts: Making sense of zeroes
International Journal of Food Microbiology, 2015The accurate estimation of true prevalence and concentration of microorganisms in foods is an important element of quantitative microbiological risk assessment (QMRA). This estimation is often based on microbial detection and enumeration data. Among such data are artificial zero counts, that originated by chance from contaminated food products.
Maarten Nauta, Anders Stockmarr
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