RESUMO

Permutation entropy and its associated frameworks are remarkable examples of physics-inspired techniques adept at processing complex and extensive datasets. Despite substantial progress in developing and applying these tools, their use has been predominantly limited to structured datasets such as time series or images. Here, we introduce the k-nearest neighbor permutation entropy, an innovative extension of the permutation entropy tailored for unstructured data, irrespective of their spatial or temporal configuration and dimensionality. Our approach builds upon nearest neighbor graphs to establish neighborhood relations and uses random walks to extract ordinal patterns and their distribution, thereby defining the k-nearest neighbor permutation entropy. This tool not only adeptly identifies variations in patterns of unstructured data but also does so with a precision that significantly surpasses conventional measures such as spatial autocorrelation. Additionally, it provides a natural approach for incorporating amplitude information and time gaps when analyzing time series or images, thus significantly enhancing its noise resilience and predictive capabilities compared to the usual permutation entropy. Our research substantially expands the applicability of ordinal methods to more general data types, opening promising research avenues for extending the permutation entropy toolkit for unstructured data.

RESUMO

The interplay of diffusion with phenomena like stochastic adsorption-desorption, absorption, and reaction-diffusion is essential for life and manifests in diverse natural contexts. Many factors must be considered, including geometry, dimensionality, and the interplay of diffusion across bulk and surfaces. To address this complexity, we investigate the diffusion process in heterogeneous media, focusing on non-Markovian diffusion. This process is limited by a surface interaction with the bulk, described by a specific boundary condition relevant to systems such as living cells and biomaterials. The surface can adsorb and desorb particles, and the adsorbed particles may undergo lateral diffusion before returning to the bulk. Different behaviors of the system are identified through analytical and numerical approaches.

RESUMO

We study the entropy production in a fractal system composed of two subsystems, each of which is subjected to an external force. This is achieved by using the H-theorem on the nonlinear Fokker-Planck equations (NFEs) characterizing the diffusing dynamics of each subsystem. In particular, we write a general NFE in terms of Hausdorff derivatives to take into account the metric of each system. We have also investigated some solutions from the analytical and numerical point of view. We demonstrate that each subsystem affects the total entropy and how the diffusive process is anomalous when the fractal nature of the system is considered.

RESUMO

In this study, we investigate a nonlinear diffusion process in which particles stochastically reset to their initial positions at a constant rate. The nonlinear diffusion process is modeled using the porous media equation and its extensions, which are nonlinear diffusion equations. We use analytical and numerical calculations to obtain and interpret the probability distribution of the position of the particles and the mean square displacement. These results are further compared and shown to agree with the results of numerical simulations. Our findings show that a system of this kind exhibits non-Gaussian distributions, transient anomalous diffusion (subdiffusion and superdiffusion), and stationary states that simultaneously depend on the nonlinearity and resetting rate.

RESUMO

Given the environmental issues caused by the extensive use of conventional petroleum-based packaging, this work proposes functional films based on commercial κ-carrageenan (κc), poly(vinyl alcohol) (PVA), and gallic acid (GA) prepared by the "casting" method. Metallic ions in the κc composition stabilized the films, supporting processability and suitable mechanical properties. However, the incorporated GA amount (6.25 and 10 wt%) in the films created from an aqueous κc solution at 3.0 % wt/v (κc3) prevented crystalline domains in the resulting materials. The κc3/GA6.25 and κc3/GA10 films had less tensile strength (8.50 ± 0.61 and 10.28 ± 0.65 MPa) and high elongation at break (2.36 ± 0.16 and 1.19 ± 0.17 %) compared to the other samples, respectively. Low κc contents (κc2.5/GA6.25 and κc2.5/GA10) promoted stiff films and less permeability to water vapor (5.36 ± 0.51 and 3.76 ± 0.02 [×10-12 g(Pa × m × s)-1], respectively. The κc/GA weight ratio also influenced the film wettability, indicating water contact angles (WCAs) between 55 and 74°. The surface wettability implies a low oil permeability and high water swelling capacity of up to 1600 %. The κc/GA also played an essential role in the film's antimicrobial action against Staphylococcus aureus and Escherichia coli. Thus, the κc3/GA10 film showed suitable physical, chemical, and biological properties, having the potential to be applied as food coatings.

Assuntos

Ácido Gálico , Álcool de Polivinil , Carragenina/química , Álcool de Polivinil/química , Resistência à Tração , Permeabilidade , Escherichia coli , Embalagem de Alimentos/métodos

RESUMO

Machine learning algorithms have been available since the 1990s, but it is much more recently that they have come into use also in the physical sciences. While these algorithms have already proven to be useful in uncovering new properties of materials and in simplifying experimental protocols, their usage in liquid crystals research is still limited. This is surprising because optical imaging techniques are often applied in this line of research, and it is precisely with images that machine learning algorithms have achieved major breakthroughs in recent years. Here we use convolutional neural networks to probe several properties of liquid crystals directly from their optical images and without using manual feature engineering. By optimizing simple architectures, we find that convolutional neural networks can predict physical properties of liquid crystals with exceptional accuracy. We show that these deep neural networks identify liquid crystal phases and predict the order parameter of simulated nematic liquid crystals almost perfectly. We also show that convolutional neural networks identify the pitch length of simulated samples of cholesteric liquid crystals and the sample temperature of an experimental liquid crystal with very high precision.

RESUMO

This study reports the synthesis, characterization and biological properties of films based on poly(vinyl alcohol) (PVA) and a cationic tannin polymer derivative (TN). Films are obtained from polymeric blends by tuning the PVA/TN weight ratios. The materials are characterized through infrared spectroscopy, X-ray photoelectron spectroscopy, contact angle measurements, mechanical analyses, and scanning electron microscopy. More hydrophilic surfaces are created by modulating the PVA and TN concentrations in the blends. Disintegration tests showed that the films present durability in phosphate buffer (pH 7.4) and low stability in simulated gastric fluid (pH 1.2). The film created at 90/10 PVA/TN weight ratio and crosslinked at 109 PVA/glutaraldehyde molar ratio (sample PVA10/TN10) supports the attachment and proliferation of bone marrow mesenchymal stem cells after 7 days of culture. The scaffolding capacity of the PVA10/TN10 surface is compared with titanium, one of the most important biomedical materials used in bone replacements. Also, the PVA/TN films exhibited cytocompatibility, antioxidant and antimicrobial activity against Staphylococcus aureus and Pseudomonas aeruginosa. These properties make PVA/TN films are candidates for biomedical applications in the tissue engineering field.

Assuntos

Antibacterianos/farmacologia , Antioxidantes/química , Antioxidantes/farmacologia , Materiais Biocompatíveis/química , Taninos/farmacocinética , Animais , Antibacterianos/química , Antioxidantes/farmacocinética , Materiais Biocompatíveis/farmacologia , Adesão Celular/efeitos dos fármacos , Reagentes de Ligações Cruzadas/química , Glutaral/química , Hidrogéis/síntese química , Hidrogéis/farmacologia , Interações Hidrofóbicas e Hidrofílicas , Masculino , Teste de Materiais , Células-Tronco Mesenquimais/efeitos dos fármacos , Microscopia Eletrônica de Varredura , Espectroscopia Fotoeletrônica , Álcool de Polivinil/química , Pseudomonas aeruginosa/efeitos dos fármacos , Ratos Wistar , Staphylococcus aureus/efeitos dos fármacos , Taninos/química

RESUMO

Here, we have demonstrated the production and characterization of hydrogel scaffolds based on chitosan/gellan gum (CS/GG) assemblies, without any covalent and metallic crosslinking agents, conventionally used to yield non-soluble polysaccharide-based materials. The polyelectrolyte complexes (physical hydrogels called as PECs) are characterized by Fourier-transform infrared spectroscopy, wide-angle X-ray scattering, and scanning electron microscopy. Hydrogels containing chitosan (CS) excesses (ranging from 60 to 80 wt%) were created. Durable polysaccharide-based scaffolds with structural homogeneity and interconnecting pore networks are developed by modulating the CS/GG weight ratio. The CS/GG hydrogel prepared at 80/20 CS/GG weight ratio (sample CS/GG80-20) is cytocompatible, supporting the attachment, growth, and spreading of bone marrow mesenchymal stem cells (BMSCs) after nine days of cell culture. The cytocompatibility is correlated to the swelling capacity of the PEC in PBS buffer (pH 7.4). By controlling the CS content, we can tune the water uptake of the material, enhancing the capacity to serve as a three-dimensional cell scaffold for BMSCs. This work presents for the first time that CS/GG hydrogels can be applied as scaffolds for tissue engineering purposes.

Assuntos

Materiais Biocompatíveis/química , Quitosana/química , Hidrogéis/química , Células-Tronco Mesenquimais/citologia , Polissacarídeos Bacterianos/química , Animais , Materiais Biocompatíveis/farmacologia , Humanos , Masculino , Células-Tronco Mesenquimais/efeitos dos fármacos , Microscopia Eletrônica de Varredura , Ratos , Ratos Wistar , Espectroscopia de Infravermelho com Transformada de Fourier , Engenharia Tecidual/métodos

RESUMO

A confined liquid with dispersed neutral particles is theoretically studied when the limiting surfaces present different dynamics for the adsorption-desorption phenomena. The investigation considers different non-singular kernels in the kinetic equations at the walls, where the suitable choice of the kernel can account for the relative importance of physisorption or chemisorption. We find that even a small difference in the adsorption-desorption rate of one surface (relative to the other) can drastically affect the behavior of the whole system. The surface and bulk densities and the dispersion are calculated when several scenarios are considered and anomalous-like behaviors are found. The approach described here is closely related to experimental situations, and can be applied in several contexts such as dielectric relaxation, diffusion-controlled relaxation in liquids, liquid crystals, and amorphous polymers.