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Predicting the key plume evolution features of groundwater contamination are crucial for assessing uncertainty in contamination control and remediation, while implementing detailed complex numerical models for a large number of scenario simulations is time-consuming and sometimes even impossible. This work develops surrogate models with an effective and practicable pathway for predicting the key plume evolution features, such as the distance of maximum plume spreading, of groundwater contamination with natural attenuation. The representative various scenarios of the input parameter combinations were effectively generated by the orthogonal experiment method and the corresponding numerical simulations were performed by the reliable Groundwater Modeling System. The PSO-SVM surrogate models were first developed, and the accuracy was gradually enhanced from 0.5 to 0.9 under a multi-objective condition by effectively increasing the sample data size from 54 sets to 78 sets and decreasing the input variables from 25 of all the considered parameters to a smaller number of the key controlling factors. The statistical surrogate models were also constructed with the fitting degree all above 0.85. The achieved findings provide effective generic surrogate models along with a scientific basis and investigation approach reference for the environmental risk management and remediation of groundwater contamination, particularly with limited data. [ABSTRACT FROM AUTHOR]

The acquisition of vegetation coverage information is crucial for crop field management, and utilizing visible light spectrum vegetation indices to extract vegetation coverage information is a commonly used method. However, most visible light spectrum vegetation indices do not fully consider the relationships between the red, green, and blue bands during their construction, making it difficult to ensure the accurate extraction of coverage information throughout the crop's entire growth cycle. To rapidly and accurately obtain potato vegetation coverage information, drones were used in this study to obtain high-resolution digital orthoimages of potato growth stages. Based on the differences in the grayscale values of potato plants, soil, shadows, and drip irrigation belts, this study presents a combination index of blue and green bands (BGCI) and a combination index of red and green bands (RGCI). The vegetation index intersection method was used with 10 vegetation information indices to extract vegetation coverage, and the differences in extraction accuracy were compared with those of the maximum entropy method and bimodal histogram method. Based on the high-precision fraction vegetation coverage (FVC) extraction results, the Pearson correlation coefficient method and random forest feature selection were used to screen 10 vegetation and 24 texture features, and the top six vegetation indices most strongly correlated with the FVC were selected for potato growth stage FVC estimation and accuracy verification. A high-precision potato vegetation coverage estimation model was successfully established. This study revealed that during the potato tuber formation and expansion stages, the BGCI combined with the vegetation index intersection method achieved the highest vegetation coverage extraction accuracy, with overall accuracies of 99.61% and 98.84%, respectively. The RGCI combined with the vegetation index intersection method achieved the highest accuracy, 98.63%, during the maturation stage. For the potato vegetation coverage estimation models, the model based on the BGCI achieved the highest estimation accuracy (R2 = 0.9116, RMSE = 5.7903), and the RGCI also achieved good accuracy in terms of vegetation coverage estimation (R2 = 0.8987, RMSE = 5.8633). In the generality verification of the models, the R2 values of the FVC estimation models based on the BGCI and RGCI were both greater than 0.94. A potato vegetation coverage estimation model was constructed based on two new vegetation information indices, demonstrating good accuracy and universality. [ABSTRACT FROM AUTHOR]

The mechanization of red jujube industry is a high-potential agricultural research field in China. In this study, a vibration harvesting device has been developed for jujube trees that features adjustable vibration frequency and amplitude. The device is designed to make jujube trees vibrate with varying diameters by utilizing different vibration frequencies and amplitudes according to the tree's size such that jujubes can be harvested efficiently. The study completed the structural design of excitation and fruit collection mechanisms based on the working principle of vibration harvesting. The red jujube excitation mechanism was dynamically simulated using ADAMS, and it was found that the acceleration at the end of the vibration rod of the mechanism had a tendency to sharply increase and decrease, which was conducive to the vibration shedding of red jujube. A collision model between the red jujubes and the fruit collection umbrella was constructed, and the fruit collection mechanism was structurally simulated using ANSYS. The tests showed that the device effectively harvested red jujubes from nine types of jujube trees with diameter ranges of 29.15–31.26 mm, 49.56–52.34 mm, and 65.23–73.25 mm. The average net harvesting rates were 93.98%, 94.71%, and 94.33%, and the average fruit collection efficiencies were 95.78%, 89.43%, and 85.04%, respectively. These results demonstrate the effectiveness of the excitation and collection mechanisms and provide a theoretical basis for the development of vibratory harvesting devices for red jujubes. [ABSTRACT FROM AUTHOR]

Spermatogenesis carries the task of precise intergenerational transmission of genetic information from the paternal genome and involves complex developmental processes regulated by the testicular microenvironment. Studies performed mainly in mouse models have established the theoretical basis for spermatogenesis, yet the wide interspecies differences preclude direct translation of the findings, and farm animal studies are progressing slowly. More than 32,000 cells from prepubertal (3-month-old) and pubertal (24-month-old) buffalo testes were analyzed by using single-cell RNA sequencing (scRNA-seq), and dynamic gene expression roadmaps of germ and somatic cell development were generated. In addition to identifying the dynamic processes of sequential cell fate transitions, the global cell-cell communication essential to maintain regular spermatogenesis in the buffalo testicular microenvironment was uncovered. The findings provide the theoretical basis for establishing buffalo germline stem cells in vitro or culturing organoids and facilitating the expansion of superior livestock breeding., Competing Interests: The authors declare no competing interests., (© 2022 The Author(s).)