2,2′-{[4,6-Bis(octyl­amino)-1,3,5-triazin-2-yl]aza­nedi­yl}diethanol

In the title compound, C23H46N6O2, the two hy­droxy groups are located on opposite sides of the triazine ring. One of the hy­droxy groups links with the triazine N atom via an intra­molecular O—H⋯N hydrogen bond. Inter­molecular O—H⋯N and N—H⋯O hydrogen bonding is observed in the crystal structure. π–π stacking is also observed between parallel triazine rings of adjacent mol­ecules, the centroid–centroid distance being 3.5944 (14) Å

Case report: Cardiac arrest during carotid body tumor resection indicating carotid sinus hypersensitivity

BackgroundCarotid body tumor surgery is associated with various complications. However, intraoperative cardiac arrest is very rare and no more than 10 cases have been reported.Case descriptionA 58-year-old woman diagnosed with bilateral carotid body tumors underwent right carotid body tumor surgery. Sudden cardiac arrest occurred during the resection and was attributed to carotid sinus hypersensitivity. The patient recovered after prompt treatment and the tumor was removed completely with no complications.ConclusionCardiac arrest attributed to carotid sinus hypersensitivity during carotid body tumor resection is very rare. Proper treatments can reverse intraoperative cardiac arrest. If carotid sinus hypersensitivity is detected preoperatively, prophylactic temporary pacemaker implantation may be appropriate

The Application Research of Inverse Finite Element Method for Frame Deformation Estimation

A frame deformation estimation algorithm is investigated for the purpose of real-time control and health monitoring of flexible lightweight aerospace structures. The inverse finite element method (iFEM) for beam deformation estimation was recently proposed by Gherlone and his collaborators. The methodology uses a least squares principle involving section strains of Timoshenko theory for stretching, torsion, bending, and transverse shearing. The proposed methodology is based on stain-displacement relations only, without invoking force equilibrium. Thus, the displacement fields can be reconstructed without the knowledge of structural mode shapes, material properties, and applied loading. In this paper, the number of the locations where the section strains are evaluated in the iFEM is discussed firstly, and the algorithm is subsequently investigated through a simple supplied beam and an experimental aluminum wing-like frame model in the loading case of end-node force. The estimation results from the iFEM are compared with reference displacements from optical measurement and computational analysis, and the accuracy of the algorithm estimation is quantified by the root-mean-square error and percentage difference error

An improved game-theoretic approach to uncover overlapping communities

How can we uncover overlapping communities from complex networks to understand the inherent structures and functions? Chen et al. firstly proposed a community game (Game) to study this problem, and the overlapping communities have been discovered when the game is convergent. It is based on the assumption that each vertex of the underlying network is a rational game player to maximize its utility. In this paper, we investigate how similar vertices affect the formation of community game. The Adamic–Adar Index (AA Index) has been employed to define the new utility function. This novel method has been evaluated on both synthetic and real-world networks. Experimental study shows that it has significant improvement of accuracy (from 4.8% to 37.6%) compared with the Game on 10 real networks. It is more efficient on Facebook networks (FN) and Amazon co-purchasing networks than on other networks. This result implicates that “friend circles of friends” of Facebook are valuable to understand the overlapping community division

Geostatistical mapping and quantitative source apportionment of potentially toxic elements in top- and sub-soils: A case of suburban area in Beijing, China

Abstract The risk assessment and source identification for potentially toxic elements (PTEs) in soils, particularly agricultural soils from megacities, are significant for environmental protection and pollution control. In this study, an intensive sampling (4127 topsoil samples and 994 subsoil samples) was conducted in the Shunyi District, Beijing, which is a suburban area with extensive cropland cover and has been impacted by the megacity over several decades. Concentrations and distributions of 8 PTEs, including V, Cr, Ni, As, Cd, Zn, Pb and Hg, were determined, and their possible sources were quantitatively assessed by principal component analysis (PCA), redundancy analysis (RDA), positive matrix factorization (PMF) analysis, and anthropogenic contribution ratio method. Among 8 PTEs, Zn, V and Cr exhibited significantly high concentrations in soils, with means of 68.29, 68.19 and 52.13 mg/kg, respectively, followed by Pb (23.84 mg/kg), Ni (22.91 mg/kg), As (8.30 mg/kg), Cd (0.15 mg/kg) and Hg (0.05 mg/kg). RDA and PCA demonstrated that the rock weathering was a significant source of V, Cr, Ni and As, and the local emissions and atmospheric deposition respectively contributed most of Cd, Zn and Pb, and of Hg in soils. This source category was confirmed the spatial variations of anthropogenic contribution ratios to individual PTEs. PMF results showed that the local emissions contributed 96.3% of Cd, 44.4% of Zn and 32.0% of Pb in soils, and the atmospheric source carrying urban pollutants amounted to 78.7–80.2% of Hg. In this case, several effective analysis methods have been successfully applied to quantify the impact of a megacity to PTEs in suburban soils. These results improve understanding of the contamination status of PTEs in suburban soils from Beijing megacity, and provide basis for policymaker regarding environmental protection and pollution control

Efficient hybrid density functional calculation by deep learning

Hybrid density functional calculation is indispensable to accurate description of electronic structure, whereas the formidable computational cost restricts its broad application. Here we develop a deep equivariant neural network method (named DeepH-hybrid) to learn the hybrid-functional Hamiltonian from self-consistent field calculations of small structures, and apply the trained neural networks for efficient electronic-structure calculation by passing the self-consistent iterations. The method is systematically checked to show high efficiency and accuracy, making the study of large-scale materials with hybrid-functional accuracy feasible. As an important application, the DeepH-hybrid method is applied to study large-supercell Moir\'{e} twisted materials, offering the first case study on how the inclusion of exact exchange affects flat bands in the magic-angle twisted bilayer graphene

6,6′-Dihydr­oxy-2,2′-[(pentane-1,5-diyl­dioxy)bis­(nitrilo­methyl­idyne)]diphenol

The mol­ecule of the title compound, C19H22N2O6, assumes a W-shaped configuration with the dihedral angle between the two halves of the mol­ecule being 82.48 (5)°. There is one half-mol­ecule in the asymmetric unit with a crystallographic twofold rotation axis passing through the central C atom of the five methylene groups in the [—CH=N—O—(CH2)5—O—N=CH—] bridge. The dihedral angle formed by the two benzene rings in each mol­ecule of the title compound is 84.18 (4)°. There are strong intra­molecular O—H⋯N and O—H⋯O hydrogen bonds and weak inter­molecular π–π stacking inter­actions between neighbouring benzene rings, and the inter­molecular plane-to-plane distances are 3.488 (2) and 3.841 (3) Å along the b and c axes, respectively. In the crystal structure, inter­molecular O—H⋯O hydrogen bonds link each mol­ecule to two others, forming an infinite three-dimensional supra­molecular structure

A fast community detection method in bipartite networks by distance dynamics

Many real bipartite networks are found to be divided into two-mode communities. In this paper, we formulate a new two-mode community detection algorithm BiAttractor. It is based on distance dynamics model Attractor proposed by Shao et al. with extension from unipartite to bipartite networks. Since Jaccard coefficient of distance dynamics model is incapable to measure distances of different types of vertices in bipartite networks, our main contribution is to extend distance dynamics model from unipartite to bipartite networks using a novel measure Local Jaccard Distance (LJD). Furthermore, distances between different types of vertices are not affected by common neighbors in the original method. This new idea makes clear assumptions and yields interpretable results in linear time complexity O(jEj) in sparse networks, where jEj is the number of edges. Experiments on synthetic networks demonstrate it is capable to overcome resolution limit compared with existing other methods. Further research on real networks shows that this model can accurately detect interpretable community structures in a short time

ROR-γ drives androgen receptor expression and represents a therapeutic target in castration-resistant prostate cancer.

The androgen receptor (AR) is overexpressed and hyperactivated in human castration-resistant prostate cancer (CRPC). However, the determinants of AR overexpression in CRPC are poorly defined. Here we show that retinoic acid receptor-related orphan receptor γ (ROR-γ) is overexpressed and amplified in metastatic CRPC tumors, and that ROR-γ drives AR expression in the tumors. ROR-γ recruits nuclear receptor coactivator 1 and 3 (NCOA1 and NCOA3, also known as SRC-1 and SRC-3) to an AR-ROR response element (RORE) to stimulate AR gene transcription. ROR-γ antagonists suppress the expression of both AR and its variant AR-V7 in prostate cancer (PCa) cell lines and tumors. ROR-γ antagonists also markedly diminish genome-wide AR binding, H3K27ac abundance and expression of the AR target gene network. Finally, ROR-γ antagonists suppressed tumor growth in multiple AR-expressing, but not AR-negative, xenograft PCa models, and they effectively sensitized CRPC tumors to enzalutamide, without overt toxicity, in mice. Taken together, these results establish ROR-γ as a key player in CRPC by acting upstream of AR and as a potential therapeutic target for advanced PCa