Energy Loss Signals in the ALICE TRD

We present the energy loss measurements with the ALICE TRD in the $\beta\gamma$ range 1--10$^{4}$, where $\beta=v/c$ and $\gamma=1/\sqrt{1-\beta^2}$. The measurements are conducted in three different scenarios: 1) with pions and electrons from testbeams; 2) with protons, pions and electrons in proton-proton collisions at center-of-mass energy 7 TeV; 3) with muons detected in ALICE cosmic runs. In the testbeam and cosmic ray measurements, ionization energy loss (dE/dx) signal as well as ionization energy loss plus transition radiation (dE/dx+TR) signal are measured. With cosmic muons the onset of TR is observed. Signals from TeV cosmic muons are consistent with those from GeV electrons in the other measurements. Numerical descriptions of the signal spectra and the $\beta\gamma$-dependence of the most probable signals are also presented.Comment: Proceedings for the 4th Workshop on Advanced Transition Radiation Detectors for Accelerator and Space Applications, 14-16 September 2011, Bari, Ital

Mercury, Cadmium and Lead Biogeochemistry in the Soil–Plant–Insect System in Huludao City

Mercury, cadmium, and lead concentrations of ashed plants and insects samples were investigated and compared with those of soil to reveal their biogeochemical processes along food chains in Huludao City, Liaoning Province, China. Concentration factors of each fragments of the soil–plant–the herbivorous insect–the carnivorous insect food chain were 0.18, 6.57, and 7.88 for mercury; 6.82, 2.01, and 0.48 for cadmium; 1.47, 2.24, and 0.57 for lead, respectively. On the whole, mercury was the most largely biomagnified, but cadmium and lead were not greatly accumulated in the carnivorous insects as expected when the food chain extended to the secondary consumers. Results indicated that concentration factors depended on metals and insects species of food chains

Semantic Segmentation for Point Cloud Scenes via Dilated Graph Feature Aggregation and Pyramid Decoders

Semantic segmentation of point clouds generates comprehensive understanding of scenes through densely predicting the category for each point. Due to the unicity of receptive field, semantic segmentation of point clouds remains challenging for the expression of multi-receptive field features, which brings about the misclassification of instances with similar spatial structures. In this paper, we propose a graph convolutional network DGFA-Net rooted in dilated graph feature aggregation (DGFA), guided by multi-basis aggregation loss (MALoss) calculated through Pyramid Decoders. To configure multi-receptive field features, DGFA which takes the proposed dilated graph convolution (DGConv) as its basic building block, is designed to aggregate multi-scale feature representation by capturing dilated graphs with various receptive regions. By simultaneously considering penalizing the receptive field information with point sets of different resolutions as calculation bases, we introduce Pyramid Decoders driven by MALoss for the diversity of receptive field bases. Combining these two aspects, DGFA-Net significantly improves the segmentation performance of instances with similar spatial structures. Experiments on S3DIS, ShapeNetPart and Toronto-3D show that DGFA-Net outperforms the baseline approach, achieving a new state-of-the-art segmentation performance.Comment: accepted to AAAI Workshop 202

Tris[2-meth­oxy-6-(4-methyl­phenyl­iminio­meth­yl)phenolato-κ2 O,O′]tris­(thio­cyanato-κN)neodymium(III)

In the title compound, [Nd(NCS)3(C15H15NO2)3], the NdIII ion is coordinated by three thio­cyanate anions [Nd—N = 2.489 (8)–2.530 (7) Å] and six O atoms [Nd—O = 2.375 (4)–2.843 (5) Å] from three zwitterionic 2-meth­oxy-6-(4-methyl­phenyl­iminiometh­yl)phenolate ligands in a tricapped trigonal-prismatic geometry. Intra­molecular N—H⋯O hydrogen bonds occur. The crystal packing exhibits weak inter­molecular C—H⋯S hydrogen bonds, π–π inter­actions with a distance of 3.904 (7) Å between the centroids of the aromatic rings, and voids of 101 Å3

(Methanol-κO)bis­{2-meth­oxy-6-[(4-methyl­phen­yl)iminiometh­yl]phenolato-κ2 O,O′}tris­(nitrato-κ2 O,O′)lanthanum(III)

The asymmetric unit of title compound, [La(NO3)3(C15H15NO2)2(CH3OH)], consists of two Schiff base 2-meth­oxy-6-[(4-methyl­phen­yl)iminiometh­yl]phenolato (HL) ligands, three independent nitrate anions and one methanol mol­ecule coordinated to LaIII. The coordination environment of the LaIII ion is formed by eleven O atoms. Three bidentate nitrate anions coordinate to the LaIII ion, while two HL ligands chelate the metal center with O atoms from the phenolate and meth­oxy groups. The HL ligands are zwitterionic, with protonated imine N atoms. The coordination sphere is completed by one methanol mol­ecule. The protonated imine N atoms are involved in intra­molecular N—H⋯O hydrogen bonds with the phen­oxy groups and nitrate ligands. One O atom of one nitrate group is disordered over two sites of equal occupancy

Anatomy-Aware Lymph Node Detection in Chest CT using Implicit Station Stratification

Finding abnormal lymph nodes in radiological images is highly important for various medical tasks such as cancer metastasis staging and radiotherapy planning. Lymph nodes (LNs) are small glands scattered throughout the body. They are grouped or defined to various LN stations according to their anatomical locations. The CT imaging appearance and context of LNs in different stations vary significantly, posing challenges for automated detection, especially for pathological LNs. Motivated by this observation, we propose a novel end-to-end framework to improve LN detection performance by leveraging their station information. We design a multi-head detector and make each head focus on differentiating the LN and non-LN structures of certain stations. Pseudo station labels are generated by an LN station classifier as a form of multi-task learning during training, so we do not need another explicit LN station prediction model during inference. Our algorithm is evaluated on 82 patients with lung cancer and 91 patients with esophageal cancer. The proposed implicit station stratification method improves the detection sensitivity of thoracic lymph nodes from 65.1% to 71.4% and from 80.3% to 85.5% at 2 false positives per patient on the two datasets, respectively, which significantly outperforms various existing state-of-the-art baseline techniques such as nnUNet, nnDetection and LENS

Analytical Strategies Involved in the Detailed Componential Characterization of Biooil Produced from Lignocellulosic Biomass

Elucidation of chemical composition of biooil is essentially important to evaluate the process of lignocellulosic biomass (LCBM) conversion and its upgrading and suggest proper value-added utilization like producing fuel and feedstock for fine chemicals. Although the main components of LCBM are cellulose, hemicelluloses, and lignin, the chemicals derived from LCBM differ significantly due to the various feedstock and methods used for the decomposition. Biooil, produced from pyrolysis of LCBM, contains hundreds of organic chemicals with various classes. This review covers the methodologies used for the componential analysis of biooil, including pretreatments and instrumental analysis techniques. The use of chromatographic and spectrometric methods was highlighted, covering the conventional techniques such as gas chromatography, high performance liquid chromatography, Fourier transform infrared spectroscopy, nuclear magnetic resonance, and mass spectrometry. The combination of preseparation methods and instrumental technologies is a robust pathway for the detailed componential characterization of biooil. The organic species in biooils can be classified into alkanes, alkenes, alkynes, benzene-ring containing hydrocarbons, ethers, alcohols, phenols, aldehydes, ketones, esters, carboxylic acids, and other heteroatomic organic compounds. The recent development of high resolution mass spectrometry and multidimensional hyphenated chromatographic and spectrometric techniques has considerably elucidated the composition of biooils

Prevention of Paclitaxel-induced allodynia by Minocycline: Effect on loss of peripheral nerve fibers and infiltration of macrophages in rats

<p>Abstract</p> <p>Background</p> <p>Although paclitaxel is a frontline antineoplastic agent for treatment of solid tumors, the paclitaxel-evoked pain syndrome is a serious problem for patients. There is currently no valid drug to prevent or treat the paclitaxel-induced allodynia, partly due to lack of understanding regarding the cellular mechanism. Studies have shown that minocycline, an inhibitor of microglia/macrophage, prevented neuropathic pain and promoted neuronal survival in animal models of neurodegenerative disease. Recently, Cata <it>et al </it>also reported that minocycline inhibited allodynia induced by low-dose paclitaxel (2 mg/kg) in rats, but the mechanism is still unclear.</p> <p>Results</p> <p>Here, we investigate by immunohistochemistry the change of intraepidermal nerve fiber (IENF) in the hind paw glabrous skin, expression of macrophage and activating transcription factor 3 (ATF3) in DRG at different time points after moderate-dose paclitaxel treatment (cumulative dose 24 mg/kg; 3 × 8 mg/kg) in rats. Moreover, we observe the effect of minocycline on the IENF, macrophages and ATF3. The results showed that moderate-dose paclitaxel induced a persisted, gradual mechanical allodynia, which was accompanied by the loss of IENF in the hind paw glabrous skin and up-regulation of macrophages and ATF3 in DRG in rats. The expressions of ATF3 mainly focus on the NF200-positive cells. More importantly, we observed that pretreatment of minocycline at dose of 30 mg/kg or 50 mg/kg, but not 5 mg/kg, prevented paclitaxel-evoked allodynia. The evidence from immunohistochemistry showed that 30 mg/kg minocycline rescued the degeneration of IENF, attenuated infiltration of macrophages and up-regulation of ATF3 induced by paclitaxel treatment in rats.</p> <p>Conclusions</p> <p>Minocycline prevents paclitaxel-evoked allodynia, likely due to its inhibition on loss of IENF, infiltration of macrophages and up-regulation of ATF3 in rats. The finding might provide potential target for preventing paclitaxel-induced neuropathic pain.</p