Autumn Crop Yield Prediction using Data-Driven Approaches:- Support Vector Machines, Random Forest, and Deep Neural Network Methods

Accurate prediction of crop yield before harvest is critical to food security and importation. The calculated ten explanatory factors and autumn crop yield data were used as data sources in this research. Firstly, a Redundancy Analysis (RDA) was employed to carry out explanatory factors and feature selection. The simple effects of RDA were used to evaluate the interpretation rates of the explanatory factors. The conditional effects of RDA were adopted to select the features of the explanatory factors. Then, the autumn crop yield was divided into the training set and testing set with an 80/20 ratio, using Support Vector Regression (SVR), Random Forest Regression (RFR), and deep neural network (DNN) for the model, respectively. Finally, the coefficient of determination (R2), the root mean square error (RMSE), the mean absolute error (MAE), and the mean absolute percentage error (MAPE) were used to evaluate the performance of the model comprehensively. The results showed that the interpretation rates of the explanatory factors ranged from 54.3% to 85.0% (p = 0.002), which could reflect the autumn crop yields well. When a small number of sample training data (e.g., 80 samples) was used, the DNN model performed better than both SVR and RF models

Histomorphological Characteristics and Pathological Types of Hyperproliferation of Gastric Surface Epithelial Cells

Objective. To investigate the histomorphological characteristics and pathological types of hyperproliferation of gastric surface epithelial cells. Methods. Hematoxylin and Eosin, Periodic acid–Schiff, and immunohistochemical staining were performed on biopsy specimens obtained from 723 patients with hyperproliferation of gastric surface epithelial cells and/or hyperplasia of gastric pits. Follow-up gastroscopic reexaminations were performed on 475 patients included. Improvement probability was analyzed using Kaplan-Meyer as well as Cox proportional hazards models. Results. Seven different histomorphologies and clinicopathologies of hyperproliferation of gastric surface epithelial cells were identified: (1) common hyperplasia of gastric epithelial cells, which was characterized by focal glandular epithelial hyperplasia of gastric pits with chronic inflammation; (2) drug-induced hyperplasia of gastric epithelial cells, which was characterized by increased hyperplasia of gastric pits and cells arranged in a monolayer; (3) Helicobacter pylori (Hp) infection-induced hyperplasia of gastric epithelial cells, which was characterized by the disappearance of oval, spherical, and bounded membrane-enclosed mucus-containing granules in the cytoplasm and on the nucleus together with cytoplasmic swelling and vacuolation; (4) metaplastic hyperplasia of gastric epithelial cells, which was characterized by the coexistence of intestinal metaplastic cells with hyperplastic gastric epithelial cells; (5) atrophic hyperplasia of gastric epithelial cells, which was characterized by the mucosal atrophy accompanied with hyperplasia of gastric pits; (6) low-grade neoplasia of epithelial cells, which was characterized by the mild to moderate dysplasia of gastric epithelial cells; and (7) high-grade neoplasia of epithelial cells, which was characterized by the evident dysplasia of hyperplastic epithelial cells and losses of cell polarity. The different pathological types are associated with different improvement probabilities. Conclusions. This study demonstrated the histomorphological characteristics and pathological types, which might guide clinicians to track malignant cell transformation, perform precise treatment, predict the clinical prognosis, and control the development of gastric cancer

Chemical Composition and Antioxidant Characteristic of Traditional and Industrial Zhenjiang Aromatic Vinegars during the Aging Process

Zhenjiang aromatic vinegar (ZAV) is one of the well-known fermented condiments in China, which is produced by solid-state fermentation. It can be classified into traditional Zhenjiang aromatic vinegar (TZAV) and industrial Zhenjiang aromatic vinegar (IZAV) because of different production methods. The purpose of the study was to evaluate the variations and differences on chemical compositions and antioxidant activities of TZAV and IZAV during the aging process. The proximate composition, organic acids content, total phenolic content (TPC), total flavonoid content (TFC), total antioxidant activity (TAA) and phenolic compounds composition of TZAV and IZAV were detected during the aging process. Organic acids contents, TPC, TFC, TAA and phenolic compounds contents in ZAV were increased during the aging process. Acetic acid, lactic acid and pyroglutamic acid in ZAV were major organic acids. With the extension of aging time, TZAV and IZAV had similar proximate compositions and organic acids content. The values of TPC, TFC and TAA were higher in TZAV than in IZAV when aging is more than 3 years. Rutin and p-coumaric acid were detected in TZAV but not in IZAV. In principal component analysis (PCA), TZAV and IZAV can be divided into two groups according to their phenolic compounds composition. These findings provide references for evaluating TZAV and IZAV on the basis of their characterizations