•Copper species of Cu/SiO2 catalysts were tuned by hydrolysis precipitation method.•Higher dispersion of copper species and large ratio of Cu+/(Cu++Cu0) were obtained.•Superior catalytic performance ...was achieved for the hydrogenation of DMO to EG.•Cu+ plays key role in DMO hydrogenation on the as-prepared copper-based catalyst.
The chemoselective synthesis of ethylene glycol (EG) from the hydrogenation of dimethyl oxalate (DMO) derived from syngas is an attractive technology in the modern chemical industry. This work reported a novel hydrolysis precipitation (HP) method to efficiently tune the active copper species of Cu/SiO2 catalysts for DMO hydrogenation. Characterization techniques such as N2 physical adsorption, X-ray diffraction, H2 temperature programmed reduction, N2O titration, Fourier-transform infrared spectra, transmission electron microscopy, and X-ray photoelectron spectroscopy were employed to reveal the origin of the catalytic performances. Compared to the ammonia evaporation (AE) method, the HP method presented remarkable higher dispersion of copper species and large ratio of Cu+/(Cu++Cu0) on the catalyst surface, resulting in a superior catalytic performance in the hydrogenation of DMO to EG. Moreover, the amount of Cu0 and Cu+ sites on catalyst surface is dramatically affected by copper loading, and the catalyst with 30% copper showed the highest catalytic activity with a space time yield of 1.74gEG/(gcat·h) at 463K. Meanwhile, the positive correlation between Cu+ surface area and space time yield of EG suggests that the amount Cu+ is the key factor for hydrogenation of DMO to EG on the as-prepared Cu/SiO2 catalyst. The formation of more Cu+ species in the catalyst would enhance the activation of CO group in DMO and significantly improve the catalytic performances in DMO hydrogenation.
Adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) are the pre- and minimally invasive forms of lung adenocarcinoma. We aimed to investigate safety results and survival outcomes ...following different types of surgical resection in a large sample of patients with AIS/MIA.
Medical records of patients with lung AIS/MIA who underwent surgery between 2012 and 2017 were retrospectively reviewed. Clinical characteristics, surgical types and complications, recurrence-free survival, and overall survival were investigated.
A total of 1644 patients (422 AIS and 1222 MIA) were included. The overall surgical complication rate was significantly lower in patients receiving wedge resection (1.0%), and was comparable between patients undergoing segmentectomy (3.3%) or lobectomy (5.6%). Grade ≥ 3 complications occurred in 0.1% of patients in the wedge resection group, and in a comparable proportion of patients in the segmentectomy group (1.5%) and the lobectomy group (1.5%). There was no lymph node metastasis. The 5-year recurrence-free survival rate was 100%. The 5-year overall survival rate in the entire cohort was 98.8%, and was comparable among the wedge resection group (98.8%), the segmentectomy group (98.2%), and the lobectomy group (99.4%).
Sublobar resection, especially wedge resection without lymph node dissection, may be the preferred surgical procedure for patients with AIS/MIA. If there are no risk factors, postoperative follow-up intervals may be extended. These implications should be validated in further studies.
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An efficient homotype Ag3PO4/BiVO4 heterojunction photocatalyst is described. Ag3PO4 nanoparticles preferentially deposit on the highly active BiVO4(040) facets by means of heterojunction ...construction together with morphology engineering. The Ag3PO4/BiVO4 photocatalyst shows high charge separation efficiency as well as enhanced visible‐light response ability and thus possesses superior visible light photocatalytic activity.
During the process of seabed terrain exploration using a multi-beam echo system, it is inevitable to obtain a sounding set containing anomalous points. Conventional methods for eliminating outliers ...are unable to reduce the disruption caused by outliers over the whole dataset. Furthermore, incomplete consideration is given to the terrain complexity, error magnitude, and outlier distribution. In order to achieve both a high-precision terrain quality estimate and quick detection of depth anomalies, this study suggests a dual robust technique. Firstly, a robust polyhedral function is utilized to solve anomaly detection for large errors. Secondly, the robust kriging algorithm is used for refined outlier removal. Ultimately, the process of dual detection and anomaly removal is achieved. The experimental results demonstrate that DRS technology has the most favorable mean square error and error fluctuation range in the test set, with values of 0.8321 and -2.0582, 1.9209, respectively, when compared to RPF, WT, GF, and WLS-SVM schemes. Furthermore, DRS is able to adjust to various terrain complexities, discrete distribution features, and cluster outlier detection, as shown by objective indicators and visual outcome maps, guaranteeing a high-quality seabed terrain estimate.
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•High efficient copper-based catalyst was prepared with ordered mesoporous silica as support precursor.•Appropriate pH value of the solution can ensure the high dispersion of copper ...species.•The presence of mesoporous structure enhanced the formation of copper phyllosilicate.•20Cu/OMS presented excellent catalytic performance in dimethyl oxalate hydrogenation.
A modified ammonia evaporation method with an ordered mesoporous silica as the precursor of the support was applied to prepare the well dispersed copper-based catalysts. Appropriate amount of ammonia was used during the aging stage to prevent the destruction of the ordered mesoporous structure, which can ensure the homogeneous pre-distribution of the copper precursor (Cu(NH3)42+) in the mesopores. Then the formation of copper phyllosilicate or surface Cu–O–Si species can be prompted during the ammonia evaporation stage, resulting in large surface areas of both Cu0 and Cu+ species in the final catalysts. It was also revealed that the formation of copper phyllosilicate led to the destruction of mesoporous silica structure in the ammonia evaporation stage especially at the higher copper loading. The catalysts with various copper loading were systematically characterized and applied in the hydrogenation of dimethyl oxalate to ethylene glycol (EG). An excellent low-temperature catalytic performance and stability were achieved on 20Cu/OMS with EG selectivity of 98.2% at 453K, due to the superior surface areas of both Cu0 and Cu+, as well as the highest ratio of Cu+/(Cu0+Cu+).
Objective
To develop a deep learning–based artificial intelligence (AI) scheme for predicting the likelihood of the ground-glass nodule (GGN) detected on CT images being invasive adenocarcinoma (IA) ...and also compare the accuracy of this AI scheme with that of two radiologists.
Methods
First, we retrospectively collected 828 histopathologically confirmed GGNs of 644 patients from two centers. Among them, 209 GGNs are confirmed IA and 619 are non-IA, including 409 adenocarcinomas in situ and 210 minimally invasive adenocarcinomas. Second, we applied a series of pre-preprocessing techniques, such as image resampling, rescaling and cropping, and data augmentation, to process original CT images and generate new training and testing images. Third, we built an AI scheme based on a deep convolutional neural network by using a residual learning architecture and batch normalization technique. Finally, we conducted an observer study and compared the prediction performance of the AI scheme with that of two radiologists using an independent dataset with 102 GGNs.
Results
The new AI scheme yielded an area under the receiver operating characteristic curve (AUC) of 0.92 ± 0.03 in classifying between IA and non-IA GGNs, which is equivalent to the senior radiologist’s performance (AUC 0.92 ± 0.03) and higher than the score of the junior radiologist (AUC 0.90 ± 0.03). The Kappa value of two sets of subjective prediction scores generated by two radiologists is 0.6.
Conclusions
The study result demonstrates using an AI scheme to improve the performance in predicting IA, which can help improve the development of a more effective personalized cancer treatment paradigm.
Key Points
• The feasibility of using a deep learning method to predict the likelihood of the ground-glass nodule being invasive adenocarcinoma.
• Residual learning–based CNN model improves the performance in classifying between IA and non-IA nodules.
• Artificial intelligence (AI) scheme yields higher performance than radiologists in predicting invasive adenocarcinoma.
•Three approaches were used to isolate hydrological impacts of LUC and CC.•Various source of errors and uncertainties occurred in the different approaches.•The decadal hydrological impacts of LUC and ...CC varied with time.•It is necessary to employ adaptive watershed management.
Assessing the respective impacts of land use change and climate change on decadal streamflow variation is important for water resources management. By using: (i) a simple eco-hydrological approach, (ii) an elasticity differential analysis, and (iii) a calibrated physically-based MIKESHE model, we have qualitatively and quantitatively isolated the relative contributions that land use change and climate change made to decadal streamflow changes in Chaohe watershed (4854km2) located in northern China. This is an important watershed of Miyun Reservoir that supplies 70% of drinking water for Greater Beijing Area (Population over 19M). The results suggested that streamflow of the watershed, compared with the reference period from 1963-1979, greatly decreased during 1980–1989 and 2000–2008, whilst it slightly changed during 1990–1999. The insignificant streamflow change for 1990–1999 was due to the effects of less soil water storage capacity on hydrological impact of land use change. However, the change impacts (i.e., land use change impacts dQ_Landuse and climate change impacts dQ_Climate) for 1980–1989 and 2000–2008 seem different between the approaches: dQ_Climate were almost similar to dQ_Landuse for these two periods according to eco-hydrological approach, whilst dQ_Climate from the differential elasticity-based analysis only 33% and 45% and from MIKESHE modeling 51% and 78% for 1980–1989 and 2000–2008, respectively. We found that the different results were mainly caused by errors associated with each approach. By taking into account the errors of each approach, a general consistent results could be arrived from the three approaches, i.e., streamflow reduction of 1980–1989 and 2000–2008 was accounted for by land use change and climate change with almost similar magnitude contribution. We emphasized that various source of errors and uncertainties may occurre in the different approaches. This required a careful interpretation of the results on isolating hydrological impacts of land use change and climate change. As hydrological impacts of land use change and climate change may be temporally varied, it is requisite to manage water resources adaptively to address future climate change and water resources shortage.
Objectives
To identify the radiomics signature allowing preoperative discrimination of lung invasive adenocarcinomas from non-invasive lesions manifesting as ground-glass nodules.
Methods
This ...retrospective primary cohort study included 160 pathologically confirmed lung adenocarcinomas. Radiomics features were extracted from preoperative non-contrast CT images to build a radiomics signature. The predictive performance and calibration of the radiomics signature were evaluated using intra-cross (n=76), external non-contrast-enhanced CT (n=75) and contrast-enhanced CT (n=84) validation cohorts. The performance of radiomics signature and CT morphological and quantitative indices were compared.
Results
355 three-dimensional radiomics features were extracted, and two features were identified as the best discriminators to build a radiomics signature. The radiomics signature showed a good ability to discriminate between invasive adenocarcinomas and non-invasive lesions with an accuracy of 86.3%, 90.8%, 84.0% and 88.1%, respectively, in the primary and validation cohorts. It remained an independent predictor after adjusting for traditional preoperative factors (odds ratio 1.87,
p
< 0.001) and demonstrated good calibration in all cohorts. It was a better independent predictor than CT morphology or mean CT value.
Conclusions
The radiomics signature showed good predictive performance in discriminating between invasive adenocarcinomas and non-invasive lesions. Being a non-invasive biomarker, it could assist in determining therapeutic strategies for lung adenocarcinoma.
Key Points
• The radiomics signature was a non-invasive biomarker of lung invasive adenocarcinoma.
• The radiomics signature outweighed CT morphological and quantitative indices.
• A three-centre study showed that radiomics signature had good predictive performance.
A series of novel metal–organic framework-anchored RuCl3 catalysts for the CO2 hydrogenation to formic acid have been developed. RuCl3@MIL-101(Cr)-DPPB catalyst exhibited the higher catalytic ...performance for hydrogenation of CO2 to formic acid due to the phosphorus atom of DPPBde as a stronger electron-donor substituent to promote the insertion of CO2 into RuH bond.
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A series of efficient ruthenium chloride (RuCl3)-anchored MOF catalysts, such as RuCl3@MIL-101(Cr)-Sal, and RuCl3@MIL-101(Cr)-DPPB, have been successfully synthesized by post-synthetic modification (PSM) of the terminal amino of MIL-101(Cr)-NH2 with salicylaldehyde, 2-diphenylphosphinobenzaldehyde (DPPBde) and anchoring of Ru(III) ions. The stronger coordination electron donor interaction between Ru(III) ions and chelating groups in the RuCl3@MIL-101(Cr)-DPPB enhances its catalytic performance for CO2 hydrogenation to formic acid. The turnover number (TON) of formic acid was up to 831 in reaction time of 2h with dimethyl sulfoxide (DMSO) and water (H2O) as mixed solvent, trimethylamine (Et3N) as organic base, and PPh3 as electronic additive.
