A novel method for the highly efficient and reversible capture of CO in carbanion‐functionalized ionic liquids (ILs) by a C‐site interaction is reported. Because of its supernucleophilicity, the ...carbanion in ILs could absorb CO efficiently. As a result, a relatively high absorption capacity for CO (up to 0.046 mol mol−1) was achieved under ambient conditions, compared with CO solubility in a commonly used IL BmimTf2N (2×10−3 mol mol−1). The results of quantum mechanical calculations and spectroscopic investigation confirmed that the chemical interaction between the C‐site in the carbanion and CO resulted in the superior CO absorption capacities. Furthermore, the subsequent conversion of captured CO into valuable chemicals with good reactivity was also realized through the alkoxycarbonylation reaction under mild conditions. Highly efficient CO absorption by carbanion‐functionalized ILs provides a new way of separating and converting CO.
Carbanions licensed to IL: A highly efficient and reversible capture of CO in carbanion‐functionalized ionic liquids was achieved (up to 0.046 mol mol−1 under ambient conditions). The C‐site chemical interaction between the carbanion and CO is responsible for the superior CO absorption capacities.
Structural Relational Reasoning of Point Clouds Duan, Yueqi; Zheng, Yu; Lu, Jiwen ...
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),
06/2019
Conference Proceeding
The symmetry for the corners of a box, the continuity for the surfaces of a monitor, the linkage between the torso and other body parts - it suggests that 3D objects may have common and underlying ...inner relations between local structures, and it is a fundamental ability for intelligent species to reason for them. In this paper, we propose an effective plug-and-play module called the structural relation network (SRN) to reason about the structural dependencies of local regions in 3D point clouds. Existing network architectures on point sets such as PointNet++ capture local structures individually, without considering their inner interactions. Instead, our SRN simultaneously exploits local information by modeling their geometrical and locational relations, which play critical roles for our humans to understand 3D objects. The proposed SRN module is simple, interpretable, and does not require any additional supervision signals, which can be easily equipped with the existing networks. Experimental results on benchmark datasets indicate promising boosts on the tasks of 3D point cloud classification and segmentation by capturing structural relations with the SRN module.
One-pot oxidative cascade catalysis plays a central role in the synthesis of key pharmaceutical and industrial molecules. Although ionic liquids are one of the most promising solvents and reaction ...media, the breakthrough of their catalysis in aerobic oxidation is very challenging due to the difficulty in the direct activation of molecular oxygen. Herein, a family of novel thermally regulated molybdate-based ionic liquids (Mo-ILs) has been designed and developed for the first time toward molecular oxygen activation for highly efficient tandem oxidative catalysis. Three diverse one-pot oxidative cascade processes for the syntheses of various flavones, imines, and benzyl benzoates were achieved with good to excellent yields using the Mo-IL Bmim
2
MoO
4
as a catalyst under air conditions. The results of spectroscopic investigations and quantum-chemical calculations further demonstrated that a thermally regulated proton migration between the cation Bmim and anion MoO
4
was the key to forming N-heterocyclic carbene and thereby to effortlessly promoting the generation of &z.rad;O
2
−
active species from molecular oxygen, which results in excellent catalytic performance in these three aerobic tandem oxidations. Our work extends the application area of ILs as the sole catalyst to one-pot aerobic oxidative cascade catalysis, which could have pronounced implications in future work.
A family of thermally regulated molybdate-based ionic liquids has been developed for highly efficient synthesis of various flavones, imines, and benzyl benzoates through one-pot oxidative cascade catalysis.
The extensive amount of multimedia information available necessitates content-based video indexing and retrieval methods. Since humans tend to use high-level semantic concepts when querying and ...browsing multimedia databases, there is an increasing need for semantic video indexing and analysis. For this purpose, we present a unified framework for semantic shot classification in sports video, which has been widely studied due to tremendous commercial potentials. Unlike most existing approaches, which focus on clustering by aggregating shots or key-frames with similar low-level features, the proposed scheme employs supervised learning to perform a top-down video shot classification. Moreover, the supervised learning procedure is constructed on the basis of effective mid-level representations instead of exhaustive low-level features. This framework consists of three main steps: 1) identify video shot classes for each sport; 2) develop a common set of motion, color, shot length-related mid-level representations; and 3) supervised learning of the given sports video shots. It is observed that for each sport we can predefine a small number of semantic shot classes, about 5-10, which covers 90%-95% of broadcast sports video. We employ nonparametric feature space analysis to map low-level features to mid-level semantic video shot attributes such as dominant object (a player) motion, camera motion patterns, and court shape, etc. Based on the fusion of those mid-level shot attributes, we classify video shots into the predefined shot classes, each of which has clear semantic meanings. With this framework we have achieved good classification accuracy of 85%-95% on the game videos of five typical ball type sports (i.e., tennis, basketball, volleyball, soccer, and table tennis) with over 5500 shots of about 8 h. With correctly classified sports video shots, further structural and temporal analysis, such as event detection, highlight extraction, video skimming, and table of content, will be greatly facilitated.
AST‐001 is a chemically synthesized inactive nitrogen mustard prodrug that is selectively cleaved to a cytotoxic aziridine (AST‐2660) via aldo‐keto reductase family 1 member C3 (AKR1C3). The purpose ...of this study was to investigate the pharmacokinetics and tissue distribution of the prodrug, AST‐001, and its active metabolite, AST‐2660, in mice, rats, and monkeys. After single and once daily intravenous bolus doses of 1.5, 4.5, and 13.5 mg/kg AST‐001 to Sprague‐Dawley rats and once daily 1 h intravenous infusions of 0.5, 1.5, and 4.5 mg/kg AST‐001 to cynomolgus monkeys, AST‐001 exhibited dose‐dependent pharmacokinetics and reached peak plasma levels at the end of the infusion. No significant accumulation and gender differences were observed after 7 days of repeated dosing. In rats, the half‐life of AST‐001 was dose independent and ranged from 4.89 to 5.75 h. In cynomolgus monkeys, the half‐life of AST‐001 was from 1.66 to 5.56 h and increased with dose. In tissue distribution studies conducted in Sprague‐Dawley rats and in liver cancer PDX models in female athymic nude mice implanted with LI6643 or LI6280 HepG2‐GFP tumor fragments, AST‐001 was extensively distributed to selected tissues. Following a single intravenous dose, AST‐001 was not excreted primarily as the prodrug, AST‐001 or the metabolite AST‐2660 in the urine, feces, and bile. A comprehensive analysis of the preclinical data and inter‐species allometric scaling were used to estimate the pharmacokinetic parameters of AST‐001 in humans and led to the recommendation of a starting dose of 5 mg/m2 in the first‐in‐human dose escalation study.
AST‐001 is a chemically synthesized inactive nitrogen mustard prodrug that is selectively cleaved to a cytotoxic aziridine (AST‐2660) via aldo‐keto reductase family 1 member C3 (AKR1C3). The purpose of this study was to investigate the pharmacokinetics and tissue distribution of the prodrug, AST‐001, and its active metabolite, AST‐2660, in mice, rats and monkeys. AST‐001 has an acceptable pharmacokinetic profile, desirable efficacy and safety profile, as well as potential clinical efficacy, and is therefore currently well underway in clinical studies.
We aimed to assess whether disease-free survival (DFS) could serve as a reliable surrogate endpoint for overall survival (OS) in adjuvant trials of pancreatic cancer.
We systematically reviewed ...adjuvant randomized trials for non-metastatic pancreatic cancer after curative resection that reported a hazard ratio (HR) for DFS and OS. We assessed the correlation between treatment effect (HR) on DFS and OS, weighted by sample size or precision of hazard ratio estimate, assuming fixed and random effects, and calculated the surrogate threshold effect (STE). We also performed sensitivity analyses and a leave-one-out cross validation approach to evaluate the robustness of our findings.
After screening 450 relevant articles, we identified a total of 20 qualifying trails comprising 5170 patients for quantitative analysis. We noted a strong correlation between the treatment effects for DFS and OS, with coefficient of determination of 0.82 in the random effect model, 0.82 in the fixed effect model, and 0.80 in the sample size weighting; the robustness of this finding was further verified by the leave-one-out cross-validation approach. Sensitivity analyses with restriction to phase 3 trials, large trials, trials with mature follow-up periods, and trials with adjuvant therapy versus adjuvant therapy strengthened the correlation (0.75 to 0.88) between DFS and OS. The STE was 0.96 for DFS.
Therefore, DFS could be regarded as a surrogate endpoint for OS in adjuvant trials of pancreatic cancer. In future similar adjuvant trials, a hazard ratio for DFS of 0.96 or less would predict a treatment impact on OS.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Methane is a greenhouse gas that contributes to global warming. Hence, effectively removing the low concentration (<1000 ppm) of methane in the environment is an issue that deserves research in the ...field of catalysis. In this study, oxygen–magnesium bivacancies are simultaneously imbedded into MgO by designing an in situ reduction combustion atmosphere for oxygen release and substituting magnesium with carbon to induce the formation of magnesium vacancies. The DFT calculations reveal that the surface electron density of MgO is improved by the oxygen vacancy structure and the substitution of Mg by C in bulk; this accelerates migration of the charge from the material surface to the adsorbed oxygen species, which leads to abundant surface peroxide species that enable activation and oxidation of methane at a low temperature (below 200 °C). This work could provide a concept for developing non-noble or transition metal oxides for low-temperature activation and conversion of alkanes in the thermocatalytic field through reactive oxygen species.
We have reported an efficient synthetic protocol to build different hollow hybrid nanocomposites with tunable compositions, such as Au/TiO2, Pt/ZrO2, and Au/CexTi1-xO2. The noble metal nanoparticles ...were well encapsulated in a wall composed of the designated transition metal oxides, showing promising potential as stable catalysts as demonstrated by Pt/ZrO2 for methane combustion.
The openEHR approach can improve the interoperability of electronic health record (EHR) through two-level modeling. Developing archetypes for the complete EHR dataset is essential for implementing a ...large-scale interoperable EHR system with the openEHR approach. Although the openEHR approach has been applied in different domains, the feasibility of archetyping a complete EHR dataset in a hospital has not been reported in academic literature, especially in a country where using openEHR is still in its infancy stage, like China. This paper presents a case study of modeling an EHR in China aiming to investigate the feasibility and challenges of archetyping a complete EHR dataset with the openEHR approach.
We proposed an archetype modeling method including an iterative process of collecting requirements, normalizing data elements, organizing concepts, searching corresponding archetypes, editing archetypes and reviewing archetypes. Two representative EHR systems from Chinese vendors and the existing Chinese EHR standards have been used as resources to identify the requirements of EHR in China, and a case study of modeling EHR in China has been conducted. Based on the models developed in this case study, we have implemented a clinical data repository (CDR) to verify the feasibility of modeling EHR with archetypes.
Sixty four archetypes were developed to represent all requirements of a complete EHR dataset. 59 (91%) archetypes could be found in Clinical Knowledge Manager (CKM), of which 35 could be reused directly without change, and 23 required further development including two revisions, two new versions, 18 extensions and one specialization. Meanwhile, 6 (9%) archetypes were newly developed. The legacy data of the EHR system in hospitals could be integrated into the CDR developed with these archetypes successfully.
The existing archetypes in CKM can faithfully represent most of the EHR requirements in China except customizations for local hospital management. This case study verified the feasibility of modeling EHR with the openEHR approach and identified the fact that the challenges such as localization, tool support, and an agile publishing process still exist for a broader application of the openEHR approach.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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