Estimation of rice seedling growth traits with an end-to-end multi-objective deep learning framework

In recent years, rice seedling raising factories have gradually been promoted in China. The seedlings bred in the factory need to be selected manually and then transplanted to the field. Growth-related traits such as height and biomass are important indicators for quantifying the growth of rice seedlings. Nowadays, the development of image-based plant phenotyping has received increasing attention, however, there is still room for improvement in plant phenotyping methods to meet the demand for rapid, robust and low-cost extraction of phenotypic measurements from images in environmentally-controlled plant factories. In this study, a method based on convolutional neural networks (CNNs) and digital images was applied to estimate the growth of rice seedlings in a controlled environment. Specifically, an end-to-end framework consisting of hybrid CNNs took color images, scaling factor and image acquisition distance as input and directly predicted the shoot height (SH) and shoot fresh weight (SFW) after image segmentation. The results on the rice seedlings dataset collected by different optical sensors demonstrated that the proposed model outperformed compared random forest (RF) and regression CNN models (RCNN). The model achieved R2 values of 0.980 and 0.717, and normalized root mean square error (NRMSE) values of 2.64% and 17.23%, respectively. The hybrid CNNs method can learn the relationship between digital images and seedling growth traits, promising to provide a convenient and flexible estimation tool for the non-destructive monitoring of seedling growth in controlled environments

A seismic prediction method of reservoir brittleness based on mineral composition and pore structure

The Lucaogou Formation, a typical fine-grained mixed formation in the Jimusaer Sag of the Junggar Basin, exhibits considerable potential for hydrocarbon exploration. Accurate brittle prediction is a crucial factor in determining hydraulic fracturing effectiveness. However, the area features complex lithological characteristics, including carbonate rocks, clastic rocks, volcanic rocks, and gypsum interbeds, along with thin layering and sporadic sweet spots. Traditional prediction methods offer limited resolution and there is an urgent need for a seismic brittle prediction method tailored to this complex geological environment. This paper presents a multi-mineral composition equivalent model for complex lithologies that enables the accurate calculation of Vp and Vs These ratios serve as the foundation for pre-stack elastic parameter predictions, which include Poisson’s ratio and Young’s modulus. By comparing the predicted parameters with well-logging measurements, the prediction accuracy is improved to 82%, with particularly high conformity in intervals characterized by high organic matter and clay content. Additionally, a three-dimensional brittle modeling approach reveals that the brittleness of the reservoir exceeds that of the surrounding rock, showing a gradual improvement in brittleness with increasing burial depth from southeast to northwest. The central area exhibits relatively good brittleness, with a stable, blocky distribution pattern

Efficacy and Safety of Tripterygium Wilfordii Glycoside Tablets Combined with Acitretin Capsules in the Treatment of Moderate to Severe Plaque Psoriasis: A Randomized Controlled Trial

Objective. To probe into the clinical efficacy of tripterygium wilfordii glycoside (TWGs) tablets combined with acitretin capsules in the treatment of patients with moderate to severe plaque psoriasis (MSPP). Methods. Thirty-six patients with MSPP were collected and divided into three groups, namely, group A (n=12, TWG tablets + acitretin capsules), group B (n=12, compound glycyrrhizin capsules + acitretin capsules), and group C (n=12, acitretin capsules). The general data of the patients was recorded. In addition, a comparison was made before treatment, 4 weeks and 8 weeks after treatment in terms of the clinical efficacy, liver function indicators (alanine aminotransferase (ALT), aspartate transaminase (AST), and creatinine), psoriasis area, and severity index (PASI) scores. The incidence of adverse reactions after treatment and the recurrence rate during two months of follow-up was statistically analyzed. Results. The therapeutic effect of group A was superior to the other two groups, with obviously more satisfactory results of serum parameters, clinical efficacy and PASI score, and incidence of adverse reactions. Conclusions. TWGs combined with acitretin had better therapeutic effects and higher safety in the treatment of MSPP

Catalytic ozonation of ketoprofen by defective boron nitride

This study focuses on the feasibility of boron nitride as a catalyst for ozonation of ketoprofen. The defective boron nitride was prepared by calcination of boric acid and melamine and characterized by XRD, SEM, FT-IR, XPS, temperature programmed desorption, Raman and UV–Vis diffuse reflectance spectra. The apparent rate constant and removal efficiency of chemical oxygen demand in the boron nitride catalyzed system were 2.7 times and 1.6 times higher than those of the ozonation alone at the pH of 7, respectively. The catalytic active sites were found to be acidic BOH and could be generated by manufacturing defects during preparation

Raman spectroscopy analysis of the biochemical characteristics of molecules associated with the malignant transformation of gastric mucosa.

OBJECTIVE: The purpose of this study was to comparatively analyze the signature Raman spectra of genomic DNA, nuclei, and tissue of normal gastric mucosa and gastric cancer and to investigate the biochemical transformation of molecules associated with gastric mucosa malignancy. METHOD: Genomic DNA, nuclei, and tissue from normal gastric mucosa and gastric cancer were analyzed by Raman spectroscopy. RESULTS: 1) The Raman spectrum of gastric cancer genomic DNA showed that two peaks appeared, one at approximately 1090 cm-1 with a higher intensity than the peak at 1050 cm-1 in the spectrum. Characteristic peaks appeared at 950 cm-1, 1010 cm-1, and 1100-1600 cm-1. 2) Using a hematoxylin and eosin (H&E)-stained section, the intensity of the characteristic peak of nucleic acids at 1085 cm-1 was increased and shifted to 1088 cm-1 in cancer cells. The relative intensity of the characteristic peaks of nucleoproteins at 755 cm-1 and 1607 cm-1 was significantly increased in cancer cells compared with normal cells. 3) Compared with normal tissues, the peak representing PO2- symmetric stretching vibration shifted from 1088 cm-1 to 1083 cm-1 in cancer tissue, and the characteristic peak for collagen at 938 cm-1 shifted to 944 cm-1. In addition, an extra characteristic peak indicating C = C stretching vibration appeared at 1379 cm-1 in the lipid spectrum in cancer tissue. CONCLUSIONS: The position, intensity, and shape of peaks in the Raman spectra of DNA, nuclei, and tissue from gastric cancer were significantly different compared with those of normal cells. These results indicate that the DNA phosphate backbone becomes unstable in cancer cells and might be broken; the relative content of histones is increased and stable; the relative collagen content is reduced, facilitating cancer cell metastasis; and the relative content of unsaturated fatty acids is increased, increasing the mobility of the plasma membrane of cancer cells

Image of tissue obtained by confocal Raman spectrometry (100x).

<p>Image of tissue obtained by confocal Raman spectrometry (100x).</p

The distribution of signature peaks in the Raman spectra of nuclei from H&E-stained sections.

<p>The distribution of signature peaks in the Raman spectra of nuclei from H&E-stained sections.</p

Raman spectra of 15 normal mucosal tissues.

<p>Raman spectra of 15 normal mucosal tissues.</p

Gastric cancer tissue (H&E 200x).

<p>Figure 5-2 Confocal Raman microscopy image of a gastric cancer tissue section.</p