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With the continuous increase of the spraying area, the problem of droplet drift risk in the spraying process of UAV is becoming increasingly prominent, especially the herbicide drift. In order to clarify the effect of the herbicide solution on the droplet size and the deposition and drift distribution characteristics sprayed by UAVs, the droplet sizes of 15 herbicide solutions sprayed by the centrifugal rotary atomizer nozzle installed in the plant protection UAV were measured in the laboratory, and the distribution of droplet deposition and drift in the spraying area and drift area were measured by adding a fluorescent tracer (60 g/hm2) to the tank in the field. The results showed that the herbicide solution had a significant effect on the droplet size distribution. The DV50 of all the other solutions was reduced after sprayed by the centrifugal atomizer except the Carfentrazone-ethyl water dispersible granule, and the maximum decrease ratio was 22.0%. The proportion of small droplets (V

The measurement of chemical oxygen demand (COD) is very important in the process of sewage treatment. The value of COD reflects the effectiveness and trend of sewage treatment to a certain extent, but obtaining accurate data requires high cost and labor intensity. To1 solve this problem, this paper proposes an online soft measurement method for COD based on Convolutional Neural Network-Bidirectional Long Short-Term Memory Network-Attention Mechanism (CNN-BiLSTM-Attention) algorithm. Firstly, by analyzing the mechanism of the aerobic tank stage in the Anaerobic-Anoxic-Oxic (A2O) wastewater treatment process, the selection range of input variables was preliminarily determined, and the collected sample dataset was subjected to correlation analysis. Finally, pH, dissolved oxygen (DO), electrical conductivity (EC), and water temperature (T) were determined as input variables for soft measurement prediction of COD.Then, based on the feature extraction ability of CNN and the advantage that BiLSTM is able to capture the backward and forward dependencies in time series data, combined with the attention mechanism that can assign higher weights to the key data, a CNN-BiLSTM-Attention algorithm model was established to soft measure COD in the effluent from the aerobic zone of the A2O wastewater treatment process. At the same time, root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and coefficient of determination (R2) were utilized Three indicators were used to evaluate the model, and the results showed that the model can accurately predict the value of COD and has a high accuracy. At the same time, compared with models such as CNN-LSTM-Attention, CNN-BiLSTM, CNN-LSTM, LSTM, RNN, BP, SVM, XGBoost, and RF etc., the results showed that the CNN-BiLSTM Attention model performed the best, proving the superiority of the algorithm model.The Wilcoxon signed-rank test indicates significant differences between the CNN-BiLSTM-Attention model and other models. [ABSTRACT FROM AUTHOR]

The method of acoustic radiation signal detection not only enables contactless measurement but also provides comprehensive state information during equipment operation. This paper proposes an enhanced feature extraction network (EFEN) for fault diagnosis of rolling bearings based on acoustic signal feature learning. The EFEN network comprises four main components: the data preprocessing module, the information feature selection module (IFSM), the channel attention mechanism module (CAMM), and the convolutional neural network module (CNNM). Firstly, the one-dimensional acoustic signal is transformed into a two-dimensional grayscale image. Then, IFSM utilizes three different-sized convolution filters to process input image data and fuse and assign weights to feature information that can attenuate noise while highlighting effective fault information. Next, a channel attention mechanism module is introduced to assign weights to each channel. Finally, the convolutional neural network (CNN) fault diagnosis module is employed for accurate classification of rolling bearing faults. Experimental results demonstrate that the EFEN network achieves high accuracy in fault diagnosis and effectively detects rolling bearing faults based on acoustic signals. The proposed method achieves an accuracy of 98.52%, surpassing other methods in terms of performance. In comparative analysis of antinoise experiments, the average accuracy remains remarkably high at 96.62%, accompanied by a significantly reduced average iteration time of only 0.25 s. Furthermore, comparative analysis confirms that the proposed algorithm exhibits excellent accuracy and resistance against noise. [ABSTRACT FROM AUTHOR]

Sewage treatment plants face significant problems as a result of the annual growth in urban sewage discharge. Substandard sewage discharge can also be caused by rising sewage treatment expenses and unpredictable procedures. The most widely used sewage treatment process in urban areas is the Anaerobic–Anoxic–Oxic (A2O) sewage treatment process. Therefore, modeling the sewage treatment process and predicting the effluent quality are of great significance. A process modeling method based on Kernel Principal Component Analysis–Particle Swarm Optimization–Stochastic Configuration Network (KPCA-PSO-SCN) is proposed for the A2O aerobic wastewater treatment process. Firstly, eight auxiliary variables were determined through mechanism analysis, including Chemical Oxygen Demand (COD) and ammonia nitrogen (NH4+) and nitrate nitrogen (NO3−) of influent water, pH, temperature (T), Mixed Liquor Suspended Solid (MLSS), Dissolved Oxygen (DO) and hydraulic residence time (HRT) in the aerobic zone. Dimensionality reduction was carried out using the kernel principal component analysis method based on the Gaussian function, and the eight-dimensional data were changed to five-dimensional data, which improved the running speed and efficiency of subsequent models. Then, according to the advantages of the particle swarm optimization algorithm, such as low calculation cost and fast convergence, combined with the advantages of stochastic configuration network general approximation performance, the PSO-SCN model was established to predict the three water quality indexes of effluent COD, NH4+, and NO3− for the aerobic zone. The experimental results proved the effectiveness of the model. Compared with classic water quality prediction algorithm models such as SCN, PSO-BP, RBF, PSO-RBF, etc., the superiority of the PSO-SCN algorithm model was demonstrated. [ABSTRACT FROM AUTHOR]

Abstract The origin of elemental chromium for the archaeological weapons from the pits of Qin terracotta warriors in China has been highly controversial. Although previous studies have highlighted that the chromium on the surface of weapon originated from the contamination of surrounding lacquer, the exact origin of chromium in the lacquer remains unclear. In this work, the measurement by inductively coupled plasma-mass spectrometer (ICP-MS) firstly confirmed that the elemental chromium was indeed contained in the archaeological Qin original lacquer. Nevertheless, the amount of elemental chromium in the Qin lacquer was as low as 0.0759 μg/mg, disclosing that it was impossible to artificially add extra refined chromium-containing substance to the lacquer in the preparation of the terracotta warriors. The soil from the archaeological site of Qin lacquer was found to have a chromium amount of 0.0660 μg/mg by ICP-MS. After the hygrothermal and soil-buried aging cycles for the lab-prepared lacquer, the surface and depth elemental analyses by time of flight-secondary ion mass spectrometer (TOF–SIMS) showed a gradient distribution of elemental chromium from the surface to interior of aged lacquer, indicating the migration and enrichment behavior of elemental chromium from the burial soil towards the lacquer. To explore the migration mechanism of elemental chromium, fluorescence imaging technique was employed in combination with Fourier transform infrared spectrometry (FT-IR) and X-ray photoelectron spectroscopy (XPS) characterizations. The results revealed that catechol-containing fragments were formed during hygrothermal and soil-buried aging of lacquer and consequently coordinated with chromium ions, inducing the migration of elemental chromium towards the lacquer.

Bipolar disorder, as a major mental illness, has a high lifetime suicide attempt rate in patients, and suicidal behavior is most likely to occur during depressive episodes. Therefore, in-depth study of its mechanism is essential for prevention, early detection and intervention of suicide. With the development of magnetic resonance imaging (MRI) technology, it has been found that there are abnormalities in the brain structure and function in suicidal patients with bipolar disorder. This article reviews the studies on suicide in bipolar disorder patients by MRI from four aspects: structure, function, structure-function, and central metabolism and cerebral blood flow perfusion, and summarizes the suicide-related changes. This review focuses on distinguishing the brain MRI changes under different mood states and diverse definitions of suicide, aiming to provide reference for further exploration of the pathophysiological mechanism of suicide in bipolar disorder.

Objective: 15-Deoxy-Δ12,14-prostaglandin J2 (15d-PGJ2) induces reactive oxygen species (ROS)-mediated apoptosis in many malignant cells, which has not been studied in hepatoma cells. In this study, we investigated whether 15d-PGJ2 induced apoptosis in hepatocellular carcinoma (HCC) associated with ROS., Materials and Methods: The LM3, SMMC-7721, and Huh-7 HCC cell lines were treated with 15d-PGJ2 (5-40 μM) for 24, 48, and 72 hours. Cholecystokinin 8 was used to detect the cytotoxicity of 15d-PGJ2. Flow cytometry, Hoechst staining, and Western blotting were used to analyze apoptosis. ROS were combined with the fluorescent probe dihydroethidium and then observed by fluorescence microscopy and flow cytometry. Activation of JNK and expression of Akt were detected by Western blotting., Results: 15d-PGJ2 inhibited HCC cell proliferation and induced apoptosis in a dose- and time-dependent manner. Apoptosis was mainly induced via an intrinsic pathway and was ROS-dependent, and was alleviated by ROS scavengers. ROS induced JNK activation and Akt downregulation in HCC cells., Conclusion: 15d-PGJ2 induced ROS in HCC cell lines, and inhibition of cell growth and apoptosis were partly ROS-dependent.

Background and Aim: Ursodeoxycholic acid (UDCA) is the standard treatment for primary biliary cirrhosis (PBC), but not all cases respond well. Evidence has shown that combination therapy of UDCA with bezafibrate significantly improved liver function. A meta-analysis was performed to assess the efficacy and safety of UDCA and bezafibrate combination therapy in the treatment of PBC., Results: Nine trials, with a total of 269 patients, were included in the analysis. The bias risk of these trials was high. Compared with UDCA alone, the combination with bezafibrate improved the Mayo risk score (mean difference [MD], 0.60; 95% confidence interval [CI], 0.25-0.95; P=0.0008) and liver biochemistry: alkaline phosphatase (MD, -238.21 IU/L; 95% CI, -280.83 to -195.60; P<0.00001); gamma-glutamyltransferase (MD, -38.23 IU/L; 95% CI, -50.16 to -25.85; P<0.00001); immunoglobulin M (MD, -128.63 IU/L; 95% CI, -151.55 to -105.71; P<0.00001); bilirubin (MD, -0.20 mg/dL; 95% CI, -0.33 to -0.07; P=0.002); triglycerides (MD, -26.84 mg/dL; 95% CI, -36.51 to -17.17; P<0.0001); total cholesterol (MD, -21.58 mg/dL; 95% CI, -30.81 to -12.34; P<0.0001), and serum alanine aminotransferase (MD, -10.24 IU/L; 95% CI, -12.65 to -78.5; P<0.00001). However, combination therapy showed no significant differences in the incidence of all-cause mortality or pruritus, and may have resulted in more adverse events (risk ratio [RR], 0.22; 95% CI, 0.07-0.67; P=0.008)., Conclusion: Combination therapy improved liver biochemistry and the prognosis of PBC, but did not improve clinical symptoms or incidence of death. Attention should be paid to adverse events when using bezafibrate.

Background: Although the effectiveness of treatment with ursodeoxycholic acid (UDCA) and fenofibrate for primary biliary cirrhosis (PBC) has been suggested by small trials, a systematic review to summarize the evidence has not yet been carried out., Methods: A meta-analysis of all long-term randomized controlled trials comparing the combination of UDCA and fenofibrate with UDCA monotherapy was performed via electronic searches., Results: Six trials, which included 84 patients, were assessed. Combination therapy with UDCA and fenofibrate was more effective than UDCA monotherapy in improving alkaline phosphatase (mean difference [MD]: -90.44 IU/L; 95% confidence interval [CI]: -119.95 to -60.92; P<0.00001), gamma-glutamyl transferase (MD: -61.58 IU/L; 95% CI: -122.80 to -0.35; P=0.05), immunoglobulin M (MD: -38.45 mg/dL; 95% CI: -64.38 to -12.51; P=0.004), and triglycerides (MD: -0.41 mg/dL; 95% CI: -0.82 to -0.01; P=0.05). However, their effects on pruritus (odds ratio [OR]: 0.39; 95% CI: 0.09-1.78; P=0.23), total bilirubin (MD: -0.05 mg/dL; 95% CI: -0.21 to 0.12; P=0.58), and alanine aminotransferase (MD: -3.31 IU/L; 95% CI: -14.60 to 7.97; P=0.56) did not differ significantly. This meta-analysis revealed no significant differences in the incidence of adverse events (OR: 0.21; 95% CI: 0.03-1.25; P=0.09) between patients treated with combination therapy and those treated with monotherapy., Conclusion: In this meta-analysis, combination therapy with UDCA and fenofibrate was more effective in reducing alkaline phosphatase than UDCA monotherapy, but it did not improve clinical symptoms. There did not appear to be an increase in adverse events with combination therapy.

In this study, a meta-analysis of randomized controlled trials comparing ursodeoxycholic acid (UDCA) monotherapy with combination therapies utilizing UDCA and budesonide was performed. We found that combination therapy with UDCA and budesonide was more effective than UDCA monotherapy for primary biliary cirrhosis-autoimmune hepatitis overlap syndrome. Moreover, compared to prednisone, budesonide has fewer side effects.

In this study, a meta-analysis of randomised controlled trials that compared ursodeoxycholic acid (UDCA) monotherapy with therapies combining UDCA and corticosteroids was performed. We found that combination therapy with UDCA and corticosteroids was more effective than UDCA monotherapy for primary biliary cirrhosis-autoimmune hepatitis-overlap syndrome.