Interest in applications of natural dye applications has increased because of their antibacterial properties and the possibility of extracting them from nature and residues. Using nanoclays as hosts to reinforce natural dye properties has been successfully demonstrated. However, no one has attempted to optimize the polymer matrix and hybrid pigment properties at the same time to ensure the best final properties for bio-composite applications. Using a statistical design for experiments, we propose the best combination of modifiers with the best nanoclay as the host of three natural dyes: chlorophyll, β-carotene, and betanine. Using the L9 Taguchi designs, we learned both the influence of the nanoclay structure, and the addition moment of surfactant, mordant salt, and silane modifiers. FTIR, XRD, DTG, integration sphere spectrophotometer, and UV-aging tests were used to characterize the hybrid pigments and epoxy bioresin composites. The degradation temperatures of the three natural dyes rose and the reinforcement of the stability of three natural dyes to UV–Vis radiation exposure was demonstrated, which avoided the migration of these dyes from bioresin to wet ribbing. Optimal results were obtained with hydrotalcite clay (calcined or not) by using surfactant and mordant before the natural dye, and before or after silane.

Many entropy-related methods for signal classification have been proposed and exploited successfully in the last several decades. However, it is sometimes difficult to find the optimal measure and the optimal parameter configuration for a specific purpose or context. Suboptimal settings may therefore produce subpar results and not even reach the desired level of significance. In order to increase the signal classification accuracy in these suboptimal situations, this paper proposes statistical models created with uncorrelated measures that exploit the possible synergies between them. The methods employed are permutation entropy (PE), approximate entropy (ApEn), and sample entropy (SampEn). Since PE is based on subpattern ordinal differences, whereas ApEn and SampEn are based on subpattern amplitude differences, we hypothesized that a combination of PE with another method would enhance the individual performance of any of them. The dataset was composed of body temperature records, for which we did not obtain a classification accuracy above 80% with a single measure, in this study or even in previous studies. The results confirmed that the classification accuracy rose up to 90% when combining PE and ApEn with a logistic model.

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Highlights• First time Permutation Entropy is applied to glucose time series.• Test of different customizations for Permutation Entropy in order to address equal values and amplitude variations.• Prediction of evolution to diabetes based on a Permutation Entropy analysis of the glucose time series.

Our purpose was to improve the thermal, mechanical, and optimal properties of an epoxy bioresin using optimum hybrid natural pigments previously synthetized in our lab. Then, we searched the best combinations of factors in the synthesis of natural hybrid nanopigments, and then incorporated them into the bioresin. We combined three structural modifiers in the nanopigment synthesis, surfactant, coupling agent (silane) and a mordant salt (alum), selected to replicate mordant textile dyeing with natural dyes.We used Taguchi's design L8 to seek final performance optimisation. We selected three natural dyes, chlorophyll, beta-carotene and beetroot extract, and used two laminar nanoclay types, montmorillonite, and hydrotalcite. The thermal, mechanical and colorimetric characterisation of the composite obtained by mixing natural hybrid nanopigments (bionanocomposite) was made. The natural dye interactions with both nanoclays improved the natural dyes and bioresin's thermal stabilities, colour performance and UV-VIS light exposure stability. The best bionanocomposite materials were found by using an acidic pH [3][4] environment, and modifying nanoclays with mordant and surfactant during the nanopigment synthesis process.

Wastewater recovery is one of the most pressing contaminant-related subjects in the textile industry. Many cleaning and recovery techniques have been applied in recent decades, from physical separation to chemical separation. This work reviews textile wastewater recovery by focusing on natural or synthetic nanoclays in order to compare their capabilities. Presently, a wide variety of nanoclays are available that can adsorb substances dissolved in water. This review summarizes and describes nanoclay modifications for different structures (laminar, tubular, etc.) to compare adsorption performance under the best conditions. This adsorbent capacity can be used in contaminant industries to recover water that can be used and be recontaminated during a second use to close the production circle. It explores and proposes future perspectives for the nanoclay hybrid compounds generated after certain cleaning steps. This is a critical review of works that have studied adsorption or desorption procedures for different nanoclay structures. Finally, it makes a future application proposal by taking into account the summarized pros and cons of each nanoclay. This work addresses contaminant reuse, where part of the employed dyes can be reused in printing or even dyeing processes, depending on the fixing capacity of the dye in the nanoclay, which is herein discussed.