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Summary: During horizontal drilling operations, real‐time prediction of drilling pressure during the drilling process can help the drilling team cope with the complex and changing working environment downhole, adjust the parameters of the drilling rig promptly, make correct decisions, reduce the probability of drilling accidents, and avoid affecting the duration and cost of the project. This study provides a method for real‐time prediction of the drilling pressure of horizontal drilling rigs. A deep learning model based on a convolutional Transformer is trained for accurate real‐time prediction by extracting real‐time operating data of the horizontal drilling rig from the data acquisition system. The method proposed in this study can be a useful tool to improve the performance of horizontal drilling rigs and can assist the drilling team in operating horizontal drilling rigs. The results of the case study show that: (1) the proposed convolutional Transformer model provides reliable real‐time prediction with an MAE of 0.304 MPa and an RMSE of 0.508 MPa; (2) the proposed method can quickly and accurately predict the trend of drilling pressure change in the next period based on the current change of drilling pressure, and grasp the dynamics of drilling pressure of horizontal drilling rigs in advance. Further research could focus on assisted decision‐making and intelligent optimization to provide solutions for preventing drilling accidents and improving horizontal rig performance based on the prediction. [ABSTRACT FROM AUTHOR]

Blonanserin is a novel oral antischizophrenic drug. Under fasting (n = 50) and fed (n = 60) conditions, this study compared the bioequivalence of the generic blonanserin tablet with the reference blonanserin tablet. In this single‐center, randomized, open‐label, 2‐period, 2‐sequence, crossover study, 110 patients were randomly given a 4‐mg dose of either the test or reference blonanserin tablet with a 14‐day washout period. Blood samples were taken before performing and up to 72 hours following. A validated high‐performance liquid chromatography‐tandem mass spectrometry technique was used to measure the levels of blonanserin in plasma. Safety was evaluated throughout the study. The study found no significant differences in the maximum observed drug concentration in the plasma (Cmax), the area under the plasma concentration‐time curve from time 0 to the last sampling time (AUC0‐t), and the area under the plasma concentration‐time curve from time 0 to infinity (AUC0‐∞) between the 2 blonanserin formulations. The 90% confidence intervals of the geometric mean ratio of the test/reference formulations for Cmax, AUC0‐t, and AUC0‐∞ were within the 80%‐125% limit. Food dramatically raised blonanserin exposure, and also significantly prolonged the lag time of absorption. No serious adverse events occurred. These results indicate that the 2 blonanserin formulations were bioequivalent and well tolerated in healthy Chinese subjects. In clinical treatment, it is necessary to consider the food effect of blonanserin. [ABSTRACT FROM AUTHOR]

Aims: Status epilepticus (SE) is the most common neurological emergency in pediatric patients. This study aimed to screen for prognostic biomarkers of SE in the cerebrospinal fluid (CSF) using metabolomics. Methods: Ultra‐performance liquid chromatography quadrupole time‐of‐flight tandem mass spectrometry (UPLC‐QTOF‐MS) was conducted to identify prognostic biomarkers in CSF metabolomics by comparing the poor outcome group (N = 13) with the good outcome group (N = 15) of children with SE. Differentially expressed metabolites were identified using Mann–Whitney U test corrected by Benjamini‐Hochberg and partial least squares discriminant analysis (PLS‐DA). Results: The PLS‐DA model identified and validated significant metabolic differences between the poor and good outcome groups of children with SE (PLS‐DA with R2Y = 0.992 and Q2 = 0.798). A total of 49 prognosis‐related metabolites were identified. Of these metabolites, 20 including glutamyl‐glutamine, 3‐iodothyronamine, and L‐fucose had an area under the curve (AUC) ≥ 80% in prognostic prediction of SE. The logistic regression model combining glutamyl‐glutamine and 3‐iodothyronamine produced an AUC value of 0.976, with a sensitivity of 0.863 and specificity of 0.956. Pathway analysis revealed that dysregulation of the citrate cycle (TCA) and arginine biosynthesis may contribute to poor SE prognosis. Conclusions: This study highlighted the prognosis‐related metabolomic disturbances in the CSF of children with SE and identified potential prognostic biomarkers. A prognostic prediction model combining glutamyl‐glutamine and 3‐iodothyronamine with high predictive value was established. [ABSTRACT FROM AUTHOR]

Summary: Aiming at current serious problems that the bolt looseness can cause heavy damages and the manual bolt looseness detection is ineffective, this study presents a bolt looseness detection method based on Canny edge detector. First, HSV (hue, saturation, value) color space is used to extract the area of mark bar. Then, after expanding, eroding and median filtering the image, Canny edge detector is used to segment the marker area to extract its edge. Last, the fitted slope of edge is used to judge whether the bolt is loose. The experimental results show that the proposed method has F1 score of 88.37%, contributing to the automated detection of bolt looseness. [ABSTRACT FROM AUTHOR]

Owing to unique alkyne‐rich structure, graphdiyne (GDY) has been proven to be a superb support for anchoring metal catalysts. Herein we demonstrate a new role of GDY as the wettability modifier for enhanced hydrogenation catalysis. After loading a certain amount GDY nanospheres, the silica mesoporous channels become superaerophilic, which allows gaseous H2 to be directly stored inside, thus significantly increasing the H2 concentration around the palladium nanoparticles (NPs). At the same time, GDY nanospheres also alter the electronic structure of the Pd NPs via a strong d‐π interaction. Combining these two roles of GDY, allows the hydrogenation of benzaldehyde to proceed under ambient H2 pressure in water, with an impressive 4.3‐fold enhancement compared to the unmodified Pd/mSiO2 catalyst. This study demonstrates a new role of GDY in constructing wettability matched catalysts for gas‐liquid‐solid tri‐phase reactions. [ABSTRACT FROM AUTHOR]