Highlights • We look for an approach to massive risk factor discovery for early childhood caries. • Association rule mining with adequate rule pruning and ranking performs well. • Literature supports ...most risk factors identified in associative analysis. • When coupled with other risk factors frequent breastfeeding confirmed as a risk. • Parent health awareness significant only for boys.
The aim of this work was to develop a simple and easy-to-apply model to predict the pH values of deep eutectic solvents (DESs) over a wide range of pH values that can be used in daily work. For this ...purpose, the pH values of 38 different DESs were measured (ranging from 0.36 to 9.31) and mathematically interpreted. To develop mathematical models, DESs were first numerically described using σ profiles generated with the COSMOtherm software. After the DESs’ description, the following models were used: (i) multiple linear regression (MLR), (ii) piecewise linear regression (PLR), and (iii) artificial neural networks (ANNs) to link the experimental values with the descriptors. Both PLR and ANN were found to be applicable to predict the pH values of DESs with a very high goodness of fit (R2independent validation > 0.8600). Due to the good mathematical correlation of the experimental and predicted values, the σ profile generated with COSMOtherm could be used as a DES molecular descriptor for the prediction of their pH values.
The most important and commonly used process for biodiesel synthesis is transesterification. The main by-product of biodiesel synthesis by transesterification is glycerol, which must be removed from ...the final product. Recently, deep eutectic solvent (DES) assisted extraction has been shown to be an effective and sustainable method for biodiesel purification. In this study, biodiesel was produced by lipase-catalysed transesterification from sunflower oil and methanol. A total of 12 different eutectic solvents were prepared and their physical properties were determined. Mathematical models were used to define which physical and chemical properties of DES and to what extent affect the efficiency of extraction of glycerol from the biodiesel. After initial screening, cholinium-based DES with ethylene glycol as hydrogen bond donor was selected and used for optimization of extraction process conditions performed in a microsystem. To determine the optimal process conditions (temperature, biodiesel:DES volume ratio, residence time), the experimental three-level-three-factor Box-Behnken experimental design was used. In the end, a combination of a mathematical model and experimental results was used to estimate how many micro-extractors are necessary for the complete removal of glycerol.
•Finite strain finite element shell formulations for shape memory alloys are developed.•The developed shell formulations use 3D SMA material models.•The analyses with shell elements are much faster ...than those with 3D solid elements.
Many shape memory alloy (SMA) applications, such as biomedical devices, electromechanical actuators, and elastocaloric cooling devices, are based on thin-walled flat or shell-like structures. An advanced design of such structures requires the development of an efficient and accurate numerical tool for simulations of very thin and curved SMA structures that may experience large deformations and even buckling upon thermo-mechanical loading. So far, finite element models for finite strain deformations of SMA structures have been based on 3D solid formulations, which are relatively inefficient for solving (thin) shell problems. In this paper, we present a finite element model for the analysis of shape memory alloy shells. Our model is based on a 7-parameter, large-rotation, one-director shell formulation, which takes into account a fully three-dimensional form of the constitutive equations for the isothermal transformations of isotropic superelasticity, as well as the shape-memory effect in a simplified way. In fact, we present three 4-node shell finite elements for SMAs. Two of them use the assumed natural strain concepts for the transverse shear strains, through-the-thickness normal strain, and membrane strains. The third element is a combination of the assumed natural strain and the enhanced assumed strain concepts, applied to satisfy the zero through-the-thickness-normal-stress condition for thin geometries to a high degree of accuracy. After a detailed description of the SMA finite element models for shells in the first part of the paper, numerical examples in the second part illustrate the approach. Compared to 3D solid SMA formulations, our results show excellent accuracy, even with a significantly reduced number of degrees of freedom, which consequently translates into a reduction in the computational time.
The extraction of xylanase was performed using an aqueous two-phase system (ATPS) based on polyethylene glycol (PEG1540) and various salts. Preliminary studies in a batch extractor showed that the ...highest extraction efficiency, E = 79.63 ± 5.21%, and purification factor, PF = 1.26 ± 0.25, were obtained with sodium citrate dihydrate-H2O-PEG1540-based ATPS for an extraction time of 10 min. The process was optimized using the experimental Box-Behnken design at three levels with three factors: extraction time (t), xylanase concentration (γ), and mass fraction of PEG in the ATPS (wPEG). Under optimal process conditions (γ = 0.3 mg/mL, wPEG = 0.21 w/w, and t = 15 min), E = 99.13 ± 1.20% and PF = 6.49 ± 0.05 were achieved. In order to intensify the process, the extraction was performed continuously in microextractors at optimal process conditions. The influence of residence time, different feeding strategies, and channel diameter on extraction efficiency and purification factor was further examined. Similar results were obtained in the microextractor for a residence time of τ = 1.03 min (E = 99.59 ± 1.22% and PF = 6.61 ± 0.07) as in the experiment carried out under optimal conditions in the batch extractor. In addition, a batch extractor and a continuous microextractor were used for the extraction of raw xylanase produced by Thermomyces lanuginosus on solid supports.
Ethylene has impact on several physiological plant processes, including abscission, during which plants shed both their vegetative and reproductive organs. Cell separation and programmed cell death ...are involved in abscission, and these have also been correlated with ethylene action. However, the detailed spatiotemporal pattern of the molecular events during abscission remains unknown. We examined the expression of two tomato
genes,
, and
that encode the last enzyme in ethylene biosynthesis, 1-aminocyclopropane-1-carboxylate oxidase (ACO), together with the expression of other abscission-associated genes involved in cell separation and programmed cell death, during a period of 0-12 h after abscission induction in the tomato flower pedicel abscission zone and nearby tissues. In addition, we determined their localization in specific cell layers of the flower pedicel abscission zone and nearby tissues obtained by laser microdissection before and 8 h after abscission induction. The expression of both
genes was localized to the vascular tissues in the pedicel. While
was more uniformly expressed in all examined cell layers, the main expression site of
was in cell layers just outside the abscission zone in its proximal and distal part. We showed that after abscission induction, ACO1 protein was synthesized in phloem companion cells, in which it was localized mainly in the cytoplasm. Samples were additionally treated with 1-methylcyclopropene (1-MCP), a competitive inhibitor of ethylene actions, and analyzed 8 h after abscission induction. Cell-layer-specific changes in gene expression were observed together with the specific localization and ethylene sensitivity of the hallmarks of cell separation and programmed cell death. While treatment with 1-MCP prevented separation of cells through inhibition of the expression of polygalacturonases, which are the key enzymes involved in degradation of the middle lamella, this had less impact on the occurrence of different kinds of membrane vesicles and abscission-related programmed cell death. In the flower pedicel abscission zone, the physical progressions of cell separation and programmed cell death are perpendicular to each other and start in the vascular tissues.
The growing threat of antibiotic resistance necessitates accurate differentiation between bacterial and viral infections for proper antibiotic administration. In this study, a Virus vs. Bacteria ...machine learning model was developed to distinguish between these infection types using 16 routine blood test results, C-reactive protein concentration (CRP), biological sex, and age. With a dataset of 44,120 cases from a single medical center, the model achieved an accuracy of 82.2 %, a sensitivity of 79.7 %, a specificity of 84.5 %, a Brier score of 0.129, and an area under the ROC curve (AUC) of 0.905, outperforming a CRP-based decision rule. Notably, the machine learning model enhanced accuracy within the CRP range of 10–40 mg/L, a range where CRP alone is less informative. These results highlight the advantage of integrating multiple blood parameters in diagnostics. The "Virus vs. Bacteria" model paves the way for advanced diagnostic tools, leveraging machine learning to optimize infection management.
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