Tetrastigma (Vitaceae) comprises about 95 species widely distributed throughout subtropical and tropical Asia, and extending to Australia. The genus is best known for being the host plants of Rafflesia, with the largest flower in the world, and other members of Rafflesiaceae. The phylogeny of Tetrastigma, however, remains poorly known. Four plastid markers (atpB‐ rbcL, psbA‐trnH, trnL‐trnF intergenic spacers, rps16 intron) were employed to infer the first phylogeny of Tetrastigma. Our sampling included eleven reported host species of Rafflesiaceae, being scattered in seven major clades throughout the Tetrastigma tree. A Templeton test rejected the hypothesis of a single origin of the parasite‐host relationship between Rafflesiaceae and Tetrastigma. Analysis of 114 accessions representing 53 species and four varieties throughout the distributional range of the genus provided robust support for the monophyly of Tetrastigma, yet Tetrastigma was found to be nested within Cayratia. Tetrastigma subg. Palmicirrata from the Sino‐Himalayan region was nested within the large and widely distributed T. subg. Tetrastigma. Two major clades (clades A and F) in our phylogeny correspond to T. sect. Tetrastigma and T. sect. Carinata of subgenus Tetrastigma, respectively.

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OBJECTIVE The hemodynamics of a brain arteriovenous malformation (AVM) nidus may be closely related to clinical presentation. The authors of this study aimed to explore the hemorrhagic quantitative hemodynamic indicators of the nidus through quantitative digital subtraction angiography (QDSA). METHODS The quantitative hemodynamic parameters were generated from QDSA. Three data sets were used to explore independent quantitative hemodynamic indicators associated with AVM rupture. The training data set was exploited to discover independent quantitative hemodynamic indicators of AVM rupture by performing univariate and multivariate logistic regression analyses. The authors plotted receiver operating characteristic curves to validate the diagnostic performance of the hemorrhagic hemodynamic indicators using the training and two external validation data sets. Kaplan-Meier survival analysis was adopted to verify the predictive power of these risk indicators of future hemorrhage in the external prospective validation data set. RESULTS A total of 151 patients were included in this study, 91 in the training set and 30 in each of the two validation sets. A higher stasis index and slower transnidal relative velocity (TRV) of the nidus were significantly correlated with AVM rupture. The areas under the curve (AUCs) of the stasis index (nidus) were 0.765 and 0.815 and those of the TRV (nidus) were 0.735 and 0.796, respectively, in the training and retrospective external validation sets. Kaplan-Meier survival analysis confirmed the validity of the stasis index and TRV in predicting future rupture risk in the prospective validation data set (p = 0.008 and 0.041, respectively, log-rank test). CONCLUSIONS A higher stasis index (nidus) and slower TRV (nidus) in QDSA were associated with AVM rupture and were effective indicators of future hemorrhage, suggesting that the core mechanisms underlying AVM rupture could be intravascular blood stasis and occlusive hyperemia of the nidus.

The film cooling holes in the blade of modern gas turbines have commonly been manufactured by laser drilling, Electric Discharge Machining (EDM), and Additive Manufacturing (AM) in recent years. These manufacturing processes often result in small geometric deviations, such as conical angles, filleted edges, and diameter deviations of the hole, which can lead to deviations on the distribution of adiabatic cooling effectiveness (η) values, the value of the discharge coefficient (Cd), and the characteristic of the in-hole flow field. The current study employed flat plate fan-shaped film cooling holes with length-to-diameter values (L/D) equal to 3.5 and six to investigate the effects of these manufacturing deviations on the distribution of η values, the value of Cd, and the characteristic of in-hole flow field. An Uncertainty Quantification (UQ) analysis using the Polynomial Chaos Expansion (PCE) model was carried out to quantify the uncertainty in the values of η and Cd. The statistical characteristics (mean values, standard deviation (Std) values, and Probability Density Function (PDF) values) of η and Cd were also calculated. The results show that conical angle deviations exert no visible changes on the value of η. However, the Cd value decreases by 6.2% when the conical angle changes from 0–0.5°. The area averaged adiabatic cooling effectiveness ( η = ) decreases by 3.4%, while the Cd increases by 15.2% with the filleted edge deviation existing alone. However, the deviation value of η = is 7.6%, and that of Cd is 25.7% with the filleted edge deviation and the diameter deviation existing.