A Quantitative Index Representing Crack Shapes and Corresponding Techniques

In order to quantificationally describe the soil cracks due to dry-wet cycles, the concept of gray level entropy is applied according to the physical significance of the information entropy to represent various shapes of cracks. Then a piece of simple and easy-to-use equipment for taking photos is used to monitor and record the crack propagation. A grayscale image and the corresponding gray level entropy are obtained automatically by a program. Test results showed that gray level entropy can quantificationally describe the shape of cracks reasonably well and evaluate the degree of crack development effectively.

Processing technology and electrical decontamination of bedding manure and litter in ground trenches and bioreactors

The paper presents data on the effect of electric current on the quantitative index of Mucor and Bacillus fungal colonies in bedding litter. It was found that with an increase in direct current to 3A, the quantitative index (%) of Mucor fungal colonies sharply decreases from 45 to 3 (by 42%), and the quantitative index (%) of Bacillus fungal colonies decreases from 70 to 50 (by 20%). Fresh litter has high acidity, and it cannot be used without preliminary processing and electrical decontamination in ground trenches and bioreactors.

Study on Establish a Brittle Fracture Prediction Considering Different Crack Opening Modes Using Mixed-Mode Ratio

In this study, we propose a method for predicting the occurrence of brittle fractures in the beam-to-column joints of steel structures, considering different crack opening modes. We conducted experiments on beam-to-diaphragm joint specimens with varying plastically constrained cracks to reproduce brittle fractures. The experiments’ results demonstrated the effectiveness of the toughness scale model and the Weibull stress approach. In addition, we propose the mixed-mode ratio, which is a quantitative index of the mode difference, and we applied it to the finite element models of the specimens. In this study, we evaluate the validity of the mixed-mode ratio and explore the differences in crack opening modes, as they pertain to the occurrence of brittle fractures.

Machine learning for lung texture analysis on thin-section CT: Capability for assessments of disease severity and therapeutic effect for connective tissue disease patients in comparison with expert panel evaluations

Background The need for quantitative assessment of interstitial lung involvement on thin-section computed tomography (CT) has arisen in interstitial lung diseases including connective tissue disease (CTD). Purpose To evaluate the capability of machine learning (ML)-based CT texture analysis for disease severity and treatment response assessments in comparison with qualitatively assessed thin-section CT for patients with CTD. Material and Methods A total of 149 patients with CTD-related ILD (CTD-ILD) underwent initial and follow-up CT scans (total 364 paired serial CT examinations), pulmonary function tests, and serum KL-6 level tests. Based on all follow-up examination results, all paired serial CT examinations were assessed as “Stable” (n = 188), “Worse” (n = 98) and “Improved” (n = 78). Next, quantitative index changes were determined by software, and qualitative disease severity scores were assessed by consensus of two radiologists. To evaluate differences in each quantitative index as well as in disease severity score between paired serial CT examinations, Tukey's honestly significant difference (HSD) test was performed among the three statuses. Stepwise regression analyses were performed to determine changes in each pulmonary functional parameter and all quantitative indexes between paired serial CT scans. Results Δ% normal lung, Δ% consolidation, Δ% ground glass opacity, Δ% reticulation, and Δdisease severity score showed significant differences among the three statuses ( P < 0.05). All differences in pulmonary functional parameters were significantly affected by Δ% normal lung, Δ% reticulation, and Δ% honeycomb (0.16 ≤r2 ≤0.42; P < 0.05). Conclusion ML-based CT texture analysis has better potential than qualitatively assessed thin-section CT for disease severity assessment and treatment response evaluation for CTD-ILD.

Pulse sharpness as a quantitative index of vascular aging

The aim of this study was to develop a robust algorithm to quantify pulse sharpness that can complement the limitations of radial augmentation index (rAIx) and explore the role of this quantitative sharpness index in reflecting vascular aging or arterial stiffness. The pulse sharpness index (PSI) was developed by combining the end point angle and virtual height, and 528 radial pulses were analyzed. The PSI could be uniformly applied to various waveform morphologies, even those with no or vague tidal waves, unlike the rAIx. Significant sex differences were identified in the rAIx and PSI (P < 0.01 for both), and significant age-dependent decreases in the PSI were observed (P < 0.01). In addition, the PSI and age were correlated (r = − 0.550) at least as strong as the rAIx and age (r = 0.532), and the PSI had a significant negative correlation with arterial stiffness (r = − 0.700). Furthermore, the multiple linear regression model for arterial stiffness using the PSI, age, sex and heart rate showed the excellent performance (cross-validated R2 = 0.701), and the PSI was found to have the greatest influence on arterial stiffness. This study confirmed that the PSI could be a quantitative index of vascular aging and has potential for use in inferring arterial stiffness with an advantage over the rAIx.

CDX2 Protein as a Surrogate Marker of Gastric Mucosal Atrophy

The aim of the study is to develop an approach to assess the severity of the gastric mucosa (GM) atrophy based on the immunohistochemical (IHC) technique to improve diagnostic quality of the stage of chronic gastritis (CG) and to implement predictive assessment of risk factors of gastric cancer development.Material and methods. The study included 155 cases of CG selected in accordance with Operational Link for Gastritis Assessment (OLGA)-system (2 samples of antral gastric mucosa (GM), 1 sample of angular GM and 2 samples of corpus GM). All biopsy samples were examined using histological and IHC (CDX2) techniques. An expression semi-quantitative index was developed to characterize CDX2. The results obtained were statistically processed using the Mann-Whitney and Kruskal-Wallis tests, the Spearman correlation coefficient, and the construction of logistic regression models.Results. It was found that the value of the CDX2 index assessed within the GM biopsy samples positively correlates with the gradation of atrophy (r=0.665 (p<0.001)). A positive correlation remains between the CDX2sum index, calculated by summing the CDX2 index values at each of the GM points, and the stage of chronic gastritis according to the OLGA classification (r=0.70 (p<0.01)). When assessing the contribution of changes at each point of biopsy sampling and retrospective correlation of the CDX2 index at two points of the GM and the stage of chronic gastritis, the greatest correlation was found for points 3 (stomach angle) and 5 (greater curvature of the gastric body), at three points – for points 1 (greater curvature antrum), 3 and 5 (r=0.592 (p<0.01)). Logistic regression models were built to predict the stage of chronic gastritis based on the CDX2 index in the specified combinations of points. The following model was chosen as the optimal one: to take biopsies at three points (1, 3, 5) and assess their CDX2 index, with sensitivity equal 80.4%, specificity equal 82.8% and diagnostic accuracy equal 83.9%.Conclusion. The CDX2 semi-quantitative index can be used to evaluate GM atrophy. The performed regression analysis demonstrates its predictive role. The constructed regression model based on the CDX2 semi-quantitative index calculation at two/three points of GM allows increasing predictive value of biopsy investigations and accuracy of stratified assessment of the gastric adenocarcinoma risk development in patients with CG.

A Quantitative Index Based on Leaf Heteroblasty for Predicting Root Biomass in a Frequently Burned Savanna Species: Cussonia arborea Hochst. Ex A. Rich. (Araliaceae)

Background: Biotic and abiotic disturbances such as frequent wildfires and herbivory contribute to maintain trees and grasses coexistence in savanna ecosystems. In comparison to stems and leaves, exposed to fire and herbivory, the roots, protected by being belowground, are less affected by these disturbances. Therefore, indirect estimation of belowground biomass (BGB) of savanna trees from simple allometric relations based on stem measurements can lead to major biases. Aims: In this study we explored how the Leaf ontogenetic change index (LOCI), a quantitative index based on leaf heteroblastic development, can provide an accurate estimate of BGB in Cussonia arborea, a widespread species in West African humid savannas. Methodology: We examined leaf morphometrics on post-fire resprouts of 40 individuals to assess whether LOCI can inform on plant age. We then analyzed by log-level regressions the variation of LOCI in relation to plant stem volume. Subsequently, we studied the variation of BGB according to stem volume, and as a function of both stem volume and LOCI, which allowed us to evaluate the contribution of LOCI to BGB estimation. BGB was obtained destructively by digging up roots and weighing total dry mass of 25 individuals including small and large trees. Statistical analyses were done with the R software. Place and Duration of Study: Study was performed in the Lamto Scientific Reserve, Côte d’Ivoire, between May 2020 and June 2021. Results: Using the stem volume as single explanatory variable of BGB, the regression model provided an adjusted R2 of 0.71. Association of the stem volume with LOCI increased the adjusted R2 from 0.71 to 0.90. Conclusion: Combining LOCI with a measure of stem size provides better estimate of BGB in C. arborea compared to estimate based on stem size only. Since a large proportion of woody species in frequently disturbed environments exhibit an overall strategies promoting persistence, future works should evaluate how these strategies are modulated during ontogeny and can explain biomass variation over time.