The effect of biogas slurry application on biomass production and the silage quality of corn.

OBJECTIVE: The objective of this study was to evaluate the effect of biogas slurry application on biomass production and the silage quality of corn. METHODS: A field experiment was conducted in which corn was grown using different biogas slurry application rates. The effect of 25% to 500% biogas slurry nitrogen replacement (T1 to T14) on the yield and quality indices of corn were studied by field plot experiments. RESULTS: The results revealed that biogas slurry application improved the stem diameter and relative feed value of corn silage in treatments T13 and T11. Moreover, the fermentation quality of corn silage was improved due to an increase in lactic acid content; in comparison with the chemical synthetic fertilizer (CF) group. The crude protein contents of corn silage had no obvious change with increasing biogas slurry application. However, the forage quality index of acid detergent fiber was decreased (p<0.05) in the T11 group compared with the CF group. In addition, higher (p<0.05) 30 h in vitro dry matter digestibility and 30 h in vitro neutral detergent fiber digestibility were observed in the T11 and T13 groups than in the CF group. CONCLUSION: Based on these results, it was concluded that the optimum biogas slurry application rate for corn was approximately 350% to 450% biogas slurry nitrogen replacement under the present experimental conditions.

Application of Table Tennis Ball Trajectory and Rotation-Oriented Prediction Algorithm Using Artificial Intelligence.

The present work aims to accelerate sports development in China and promote technological innovation in the artificial intelligence (AI) field. After analyzing the application and development of AI, it is introduced into sports and applied to table tennis competitions and training. The principle of the trajectory prediction of the table tennis ball (TTB) based on AI is briefly introduced. It is found that the difficulty of predicting TTB trajectories lies in rotation measurement. Accordingly, the rotation and trajectory of TTB are predicted using some AI algorithms. Specifically, a TTB detection algorithm is designed based on the Feature Fusion Network (FFN). For feature exaction, the cross-layer connection network is used to strengthen the learning ability of convolutional neural networks (CNNs) and streamline network parameters to improve the network detection response. The experimental results demonstrate that the trained CNN can reach a detection accuracy of over 98%, with a detection response within 5.3 ms, meeting the requirements of the robot vision system of the table tennis robot. By comparison, the traditional Color Segmentation Algorithm has advantages in detection response, with unsatisfactory detection accuracy, especially against TTB's color changes. Thus, the algorithm reported here can immediately hit the ball with high accuracy. The research content provides a reference for applying AI to TTB trajectory and rotation prediction and has significant value in popularizing table tennis.

The Energy Difference between the Triply-Bridged and All-Terminal Structures of Co4(CO)12, Rh4(CO)12, and Ir4(CO)12: A Difficult Test for Conventional Density Functional Methods.

The M4(CO)12 molecules Co4(CO)12, Rh4(CO)12, and Ir4(CO)12 have two low-lying structures, the all-terminal structure with Td symmetry and the triply bridged structure with C3v symmetry. A total of 45 density functional theory (DFT) methods have been used to predict structures and vibrational frequencies for Co4(CO)12, Rh4(CO)12, and Ir4(CO)12. The different DFT methods show a broad range of energy differences ΔE = E(Td) - E(C3v). For Rh4(CO)12, none of the 45 DFT predictions is within 11 kcal/mol of the 2005 experimental value of 5.1 ± 0.6 kcal/mol reported by Allian and Garland (Dalton Trans. 2005, 1957 - 1965). For the challenging Ir4(CO)12 molecule, 21 DFT methods predict the correct Td structure, while 24 DFT methods predict the C3v structure to lie lower in energy. This research reveals many peculiar problems in the computation of the vibrational frequencies for the all-terminal structure.

The acidity/basicity of metal-containing ionic liquids: insights from surface analysis and the Fukui function.

Metal-containing ionic liquids (ILs) have been recognized as potential solvents, catalysts, catalyst precursors and reagents for many organic processes. In this work, several quantum-chemical parameters, including the surface electrostatic potential (Vs,max and Vs,min), the lowest surface average local ionization energy (I̅s,min), and the electrostatic potential at the position of an atom (EPnuc), were adopted to understand the acidity/basicity of metal-containing ILs. Chlorometallate-based ILs show stronger acidity than conventional ILs, because of the increased electron-deficiency of the imidazole ring upon the incorporation of metal chloride. For the ILs with the Ag-coordinated cations, the acidity tends to attenuate while the basicity becomes stronger, as compared to traditional ILs. In addition, the regional Fukui function was also used to assess the molecular distribution of the Lewis acidity/basicity of the ILs under study. Overall, the introduction of metals into either the cations or the anions influences the acidity/basicity of ILs to a large degree, which would be beneficial for their certain applications, such as catalysis and extraction. We hope that the results presented here will assist in the development of novel metal-containing ILs with desirable properties.

Experimental Mycobacterium tuberculosis infection in the Chinese tree shrew.

In recent years, the Chinese tree shrew has been considered to be a promising experimental animal for numerous diseases. Yet the susceptibility of Mycobacterium tuberculosis (MTB) in Chinese tree shrew is still unknown. We infected Chinese tree shrews with a high dose (2.5 × 10(6) CFU) or a low dose (2.5 × 10(3) CFU) of the H37Rv strain via the femoral vein to cause severe or mild disease. Disease severity was determined by clinical signs, pathologic changes and bacteria distribution in organs. Furthermore, among lung samples of the uninfected, mildly and seriously ill Chinese tree shrews, differentially expressed protein profiles were analyzed through iTRAQ and validated by qPCR. Tuberculous nodules, skin ulceration, pleural effusion and cerebellum necrosis could be observed in seriously ill animals. Regulation of the actin cytoskeleton was newly defined as a possible MTB-related pathway correlated with disease progression. This comprehensive analysis of the experimental infection and the depiction of the proteomics profiles in the Chinese tree shrew provide a foundation for the establishment of a new animal model of tuberculosis and provide a better understanding of the mechanism of tuberculosis.