Contextual Modeling for 3D Dense Captioning on Point Clouds

3D dense captioning, as an emerging vision-language task, aims to identify and locate each object from a set of point clouds and generate a distinctive natural language sentence for describing each located object. However, the existing methods mainly focus on mining inter-object relationship, while ignoring contextual information, especially the non-object details and background environment within the point clouds, thus leading to low-quality descriptions, such as inaccurate relative position information. In this paper, we make the first attempt to utilize the point clouds clustering features as the contextual information to supply the non-object details and background environment of the point clouds and incorporate them into the 3D dense captioning task. We propose two separate modules, namely the Global Context Modeling (GCM) and Local Context Modeling (LCM), in a coarse-to-fine manner to perform the contextual modeling of the point clouds. Specifically, the GCM module captures the inter-object relationship among all objects with global contextual information to obtain more complete scene information of the whole point clouds. The LCM module exploits the influence of the neighboring objects of the target object and local contextual information to enrich the object representations. With such global and local contextual modeling strategies, our proposed model can effectively characterize the object representations and contextual information and thereby generate comprehensive and detailed descriptions of the located objects. Extensive experiments on the ScanRefer and Nr3D datasets demonstrate that our proposed method sets a new record on the 3D dense captioning task, and verify the effectiveness of our raised contextual modeling of point clouds

Effects of oxycodone hydrochloride and dezocine on hemodynamics and levels of inflammatory factors in patients receiving gynecological laparoscopic surgery under general anesthesia

We aimed to compare the effects of oxycodone hydrochloride and dezocine on hemodynamics and inflammatory factors in patients receiving gynecological laparoscopic surgery under general anesthesia. A total of 246 patients were divided into group A and B (n=123). Hemorheology indices were recorded 5 min after anesthesia (T0), 1 min after pneumoperitoneum (T1), when position was changed 5 min after pneumoperitoneum (T2), 15 min after pneumoperitoneum (T3), 1 min (T4) and 5 min (T5) after position was restored. Visual analogue scale scores 1, 2, 6, 12, 24 and 48 h after operation were recorded. Postoperative adverse reactions and visceral pain were observed. The expression levels of inflammatory factors were detected by enzyme-linked immunosorbent assay 12 h after operation. Compared with group A, group B had higher heart rate and mean arterial pressure at T2, lower central venous pressure and cardiac output at T1-T3, and higher systemic vascular resistance at T1-T5 (P<0.05). The incidence rate of pain syndrome in group A was lower (P<0.05). Group A had lower tumor necrosis factor-alpha and interleukin-6 expression levels and higher interleukin-10 level than those of group B (P<0.05). For gynecological laparoscopic surgery, oxycodone preemptive analgesia has superior outcomes to those of dezocine

Review on the Synthesis and Applications of Fe

Recently, Fe3O4 nanomaterials have attracted tremendous attention because of their favorable electric and magnetic properties. Fe3O4 nanostructures with various morphologies have been successfully synthesized and have been used in many fields such as lithium-ion batteries (LIBs), wastewater treatment, and magnetic resonance imaging (MRI) contrast agents. In this paper, we provide an in-depth discussion of recent development of Fe3O4 nanomaterials, including their effective synthetic methods and potential applications

COAL GASIFICATION CHARACTERISTICS IN A 2MWth SECOND-GENERATION PFB GASIFIER

ABSTRACT Coal gasification process and equipment feasibility research w ere carried out in a 2 MW thermal input pressurized spout-fluid bed pilot-scale gasifier and a long-time-run test was performed to study the effects of operating parameters on coal partial gasification behaviors. The test results have demonstrated the feasibility of the gasifier to provide suitable fuel gas and residual char for downstream system of 2G PFBC-CC. The concentration of methane decreased at higher gasification temperature due to the secondary cracking of methane while the carbon conversion increased, and the concentration of hydrogen increased with an increase of steam flow rate. The main experimental results were compared with those of pilot-scale facilities in the world

Experimental study of characteristics of bimetallic Pt-Fe nano-particle fuel cell electrocatalyst

© 2015 Elsevier Ltd. The characteristics of 1.5wt% Platinum (Pt) loading on Fe incorporated Y zeolite (Pt-Fe/Y zeolite) nano-electrocatalysts have been experimentally studied by the extended X-ray adsorption fine structure (EXAFS) and cyclic voltammetry (CV) techniques using Nafionat bound electrode to determine Pt electrocatalytic performance in direct methanol fuel cell. The Pt particle size was found to be small in electrochemical environment (0.7nm with 55 atoms). Study implies that the Pt electrocatalytic performance can be affected by the Pt cluster electron deficiency, due to the change of Pt particle size associated with the lattice strain energy. The CV measurement in the hydride region indicated higher Pt dispersion for Pt-Fe/Y zeolite electrocatalyst chemically reduced in H2 at 400°C (15PtFeancr4), compared to that of Pt/Y zeolite reduced at 400°C (15Ptancr4) and Pt-Fe/Y zeolite electrocatalysts reduced at 300°C (15PtFeancr3), respectively. This provided further implication that the chemical reduction temperature would be important for achieving a higher Pt dispersion. The present study has revealed two possible electron transfer pathways that might contribute to the Pt electronic conduction: (1) the surface mobility of adsorbed species; (2) the hydrogen atoms/H+ ion spillover through the zeolite framework and on the electrode surface, despite the DC insulator nature of zeolite

Fluorescence sensing of chromium (VI) and ascorbic acid using graphitic carbon nitride nanosheets as a fluorescent "switch"

通讯作者地址: Chen, XUsing graphitic carbon nitride (g-C3N4) nanosheets, an effective and facile fluorescence sensing approach for the label-free and selective determination of chromium (VI) (Cr(VI)) was developed. The fluorescence of the solution of g-C3N4 nanosheets was quenched effectively by Cr(VI) via the inner filter effect. Under optimal conditions, a wide detection linear range for Cr(VI) was found to be from 0.6 mu M to 300 mu M with a limit of detection (LOD) of 0.15 mu M. In addition, the fluorescence of the solution of g-C3N4 nanosheets-Cr(VI) could be sensitively turned on in the presence of a reductant such as ascorbic acid (AA) via an "on-off-on" fluorescence response through the oxidation-reduction between Cr(VI) and AA. And a wide detection linear range for AA was found to be from 0.5 mu M to 200 mu M with an LOD of 0.13 mu M. Furthermore, the proposed method has the potential application for detection of Cr(VI) in lake waters and AA in biological fluids.National Nature Scientific Foundation of China 21175112 21375112 National Basic Research Program of China 2010CB732402 program of Science and Technology of Xiamen for University Innovation 3502Z2014302

Canvass: a crowd-sourced, natural-product screening library for exploring biological space

NCATS thanks Dingyin Tao for assistance with compound characterization. This research was supported by the Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health (NIH). R.B.A. acknowledges support from NSF (CHE-1665145) and NIH (GM126221). M.K.B. acknowledges support from NIH (5R01GM110131). N.Z.B. thanks support from NIGMS, NIH (R01GM114061). J.K.C. acknowledges support from NSF (CHE-1665331). J.C. acknowledges support from the Fogarty International Center, NIH (TW009872). P.A.C. acknowledges support from the National Cancer Institute (NCI), NIH (R01 CA158275), and the NIH/National Institute of Aging (P01 AG012411). N.K.G. acknowledges support from NSF (CHE-1464898). B.C.G. thanks the support of NSF (RUI: 213569), the Camille and Henry Dreyfus Foundation, and the Arnold and Mabel Beckman Foundation. C.C.H. thanks the start-up funds from the Scripps Institution of Oceanography for support. J.N.J. acknowledges support from NIH (GM 063557, GM 084333). A.D.K. thanks the support from NCI, NIH (P01CA125066). D.G.I.K. acknowledges support from the National Center for Complementary and Integrative Health (1 R01 AT008088) and the Fogarty International Center, NIH (U01 TW00313), and gratefully acknowledges courtesies extended by the Government of Madagascar (Ministere des Eaux et Forets). O.K. thanks NIH (R01GM071779) for financial support. T.J.M. acknowledges support from NIH (GM116952). S.M. acknowledges support from NIH (DA045884-01, DA046487-01, AA026949-01), the Office of the Assistant Secretary of Defense for Health Affairs through the Peer Reviewed Medical Research Program (W81XWH-17-1-0256), and NCI, NIH, through a Cancer Center Support Grant (P30 CA008748). K.N.M. thanks the California Department of Food and Agriculture Pierce's Disease and Glassy Winged Sharpshooter Board for support. B.T.M. thanks Michael Mullowney for his contribution in the isolation, elucidation, and submission of the compounds in this work. P.N. acknowledges support from NIH (R01 GM111476). L.E.O. acknowledges support from NIH (R01-HL25854, R01-GM30859, R0-1-NS-12389). L.E.B., J.K.S., and J.A.P. thank the NIH (R35 GM-118173, R24 GM-111625) for research support. F.R. thanks the American Lebanese Syrian Associated Charities (ALSAC) for financial support. I.S. thanks the University of Oklahoma Startup funds for support. J.T.S. acknowledges support from ACS PRF (53767-ND1) and NSF (CHE-1414298), and thanks Drs. Kellan N. Lamb and Michael J. Di Maso for their synthetic contribution. B.S. acknowledges support from NIH (CA78747, CA106150, GM114353, GM115575). W.S. acknowledges support from NIGMS, NIH (R15GM116032, P30 GM103450), and thanks the University of Arkansas for startup funds and the Arkansas Biosciences Institute (ABI) for seed money. C.R.J.S. acknowledges support from NIH (R01GM121656). D.S.T. thanks the support of NIH (T32 CA062948-Gudas) and PhRMA Foundation to A.L.V., NIH (P41 GM076267) to D.S.T., and CCSG NIH (P30 CA008748) to C.B. Thompson. R.E.T. acknowledges support from NIGMS, NIH (GM129465). R.J.T. thanks the American Cancer Society (RSG-12-253-01-CDD) and NSF (CHE1361173) for support. D.A.V. thanks the Camille and Henry Dreyfus Foundation, the National Science Foundation (CHE-0353662, CHE-1005253, and CHE-1725142), the Beckman Foundation, the Sherman Fairchild Foundation, the John Stauffer Charitable Trust, and the Christian Scholars Foundation for support. J.W. acknowledges support from the American Cancer Society through the Research Scholar Grant (RSG-13-011-01-CDD). W.M.W.acknowledges support from NIGMS, NIH (GM119426), and NSF (CHE1755698). A.Z. acknowledges support from NSF (CHE-1463819). (Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health (NIH); CHE-1665145 - NSF; CHE-1665331 - NSF; CHE-1464898 - NSF; RUI: 213569 - NSF; CHE-1414298 - NSF; CHE1361173 - NSF; CHE1755698 - NSF; CHE-1463819 - NSF; GM126221 - NIH; 5R01GM110131 - NIH; GM 063557 - NIH; GM 084333 - NIH; R01GM071779 - NIH; GM116952 - NIH; DA045884-01 - NIH; DA046487-01 - NIH; AA026949-01 - NIH; R01 GM111476 - NIH; R01-HL25854 - NIH; R01-GM30859 - NIH; R0-1-NS-12389 - NIH; R35 GM-118173 - NIH; R24 GM-111625 - NIH; CA78747 - NIH; CA106150 - NIH; GM114353 - NIH; GM115575 - NIH; R01GM121656 - NIH; T32 CA062948-Gudas - NIH; P41 GM076267 - NIH; R01GM114061 - NIGMS, NIH; R15GM116032 - NIGMS, NIH; P30 GM103450 - NIGMS, NIH; GM129465 - NIGMS, NIH; GM119426 - NIGMS, NIH; TW009872 - Fogarty International Center, NIH; U01 TW00313 - Fogarty International Center, NIH; R01 CA158275 - National Cancer Institute (NCI), NIH; P01 AG012411 - NIH/National Institute of Aging; Camille and Henry Dreyfus Foundation; Arnold and Mabel Beckman Foundation; Scripps Institution of Oceanography; P01CA125066 - NCI, NIH; 1 R01 AT008088 - National Center for Complementary and Integrative Health; W81XWH-17-1-0256 - Office of the Assistant Secretary of Defense for Health Affairs through the Peer Reviewed Medical Research Program; P30 CA008748 - NCI, NIH, through a Cancer Center Support Grant; California Department of Food and Agriculture Pierce's Disease and Glassy Winged Sharpshooter Board; American Lebanese Syrian Associated Charities (ALSAC); University of Oklahoma Startup funds; 53767-ND1 - ACS PRF; PhRMA Foundation; P30 CA008748 - CCSG NIH; RSG-12-253-01-CDD - American Cancer Society; RSG-13-011-01-CDD - American Cancer Society; CHE-0353662 - National Science Foundation; CHE-1005253 - National Science Foundation; CHE-1725142 - National Science Foundation; Beckman Foundation; Sherman Fairchild Foundation; John Stauffer Charitable Trust; Christian Scholars Foundation)Published versionSupporting documentatio

COVID−19 hospitalization increases the risk of developing glioblastoma: a bidirectional Mendelian-randomization study

BackgroundAs a result of the COVID-19 pandemic, patients with glioblastoma (GBM) are considered a highly vulnerable population. Despite this, the extent of the causative relationship between GBM and COVID-19 infection is uncertain.MethodsGenetic instruments for SARS-CoV-2 infection (38,984 cases and 1,644,784 control individuals), COVID-19 hospitalization (8,316 cases and 1,549,095 control individuals), and COVID-19 severity (4,792 cases and 1,054,664 control individuals) were obtained from a genome-wide association study (GWAS) from European populations. A total of 6,183 GBM cases and 18,169 controls from GWAS were enrolled in our study. Their associations were evaluated by applying Mendelian randomization (MR) including IVW meta-analysis, MR-Egger regression, and weighted-median analysis. To make the conclusions more robust and reliable, sensitivity analyses were performed.ResultsOur results showed that genetically predicted COVID−19 hospitalization increases the risk of GBM (OR = 1.202, 95% CI = 1.035–1.395, p = 0.016). In addition, no increased risk of SARS-CoV-2 infection, COVID-19 hospitalization and severity were observed in patients with any type of genetically predicted GBM.ConclusionOur MR study indicated for the first time that genetically predicted COVID−19 hospitalization was demonstrated as a risk factor for the development of GBM