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[Display omitted] • Machine learning analysis identifies catalyst's key role in Me 2 SiCl 2 selectivity. • MeSiCl 2 -SiCl 2 Me and MeSiCl 2 -SiClMe 2 are main compositions of industrial HBRs. • MeSiCl 2 -SiClMe 2 prefers to produce MeSiCl 3 and Me 2 SiHCl based upon DFT insights. • Challenges & suggestions for upgrading HBRs to Me 2 SiHCl has been analyzed. Recently, the growing capacity of silicone monomers directly lead to a large accumulation of associated high-boiling residues (HBRs), which has become an urgent issue for limiting the sustainably development in industry. Dimethyldichlorosilane (M2) is an essential intermediate in silicone industry, which have been extensively applied in kinds of fields like architecture, electronics, new energy, medicine, transportation and plastic rubber. Consequently, the catalytic cracking of HBRs to produce value-added M2 is considered a promising strategy. However, most cracking catalysts exhibit low M2 selectivity in batch reactors. In this perspective, we initially provide an overview of the HBRs current cracking system. Moreover, the influence factors of M2 selectivity during HBRs-catalytic cracking system through machine learning (ML) methods are systematically calculated and analyzed. The latest findings regarding the actual components of HBRs feeding and their effluxes of HBRs-tri-n-butylamine cracking system are presented, as well as their distribution of final products. Finally, the existing challenges and suggestions for HBRs to M2, are given with the aim of providing novel research ideas and stimulating inspiration to drive toward a sustainable development for minimizing pollution and enhancing cost-effectiveness. [ABSTRACT FROM AUTHOR]

Morphine is usually preferred to treat moderate or severe pain for late-stage cancer patients. However, medically unindicated or excessive morphine use may result in respiratory depression and death. This essay contends that a clear distinction between relieving pain and performing active euthanasia in the use of morphine should be made in practice. By drawing on Confucian virtue resources, we construct a Confucian conception of human dignity, including both intrinsic and acquired dignity, to analyze the circumstances of morphine use in current China. We argue that not only the Confucian view of intrinsic dignity but also that of acquired dignity would not support morphine euthanasia. [ABSTRACT FROM AUTHOR]

Reconstructing the history of tree cover and exploring the relationship between forest growth and environmental factors are of great significance for predicting future vegetation changes and guiding ecosystem restoration and protection. On the basis of pollen data of two lake cores and three peat profiles in the central–northern parts of the Daxing'an Mountains and using multiple methods, we quantitatively reconstructed the tree cover of the past 2000 years. We found that the reconstruction results of the different methods are quite similar. Among all these methods, random forest had the highest prediction accuracy for modern pollen samples. Therefore, the random forest reconstruction results can better reflect changes in regional tree cover, which was approximately 38%–42% during 2000–200 Cal yr BP. It then obviously increased from a low value of approximately 40% to a modern level of approximately 45%. The precipitation and carbon dioxide (CO 2) concentration were the main drivers for the tree cover before and after 200 Cal yr BP, respectively. This indicates that environments with elevated CO 2 level in the near future will benefit the growth of vegetation in the central–northern parts of the Daxing'an Mountains. • Tree cover over the past 2000 years was reconstructed using multiple methods. • CO 2 concentration and precipitation were found to influence tree cover change. • Rapid increase in tree cover after 200 Cal yr BP was linked to CO 2 concentration. [ABSTRACT FROM AUTHOR]

Advanced oxidation processes (AOPs) are widely used as efficient technologies to treat highly toxic and harmful substances in wastewater. Taking the most representative aromatic compounds (monosubstituted benzenes, substituted phenols and heterocyclic compounds) as examples, this paper firstly introduces their structures and the structural descriptors studied in AOPs before, and the influence of structural differences in AOPs with different reactive oxygen species (ROS) on the degradation rate was discussed in detail. The structure-activity relationship of pollutants has been previously analyzed through quantitative structure-activity relationship (QSAR) model, in which ROS is a very important influencing factor. When electrophilic oxidative species attacks pollutants, aromatic compounds with electron donating groups are more favorable for degradation than aromatic compounds with electron donating groups. While nucleophilic oxidative species comes to the opposite conclusion. The choice of advanced oxidation processes, the synergistic effect of various active oxygen species and the used catalysts will also change the degradation mechanism. This makes the structure-dependent activity relationship uncertain, and different conclusions are obtained under the influence of various experimental factors. [Display omitted] • The structure of pollutants is a key factor affecting reactivity. • Typical structure descriptors and reactive oxidizing species are introduced. • The substrate-dependent reaction activity is affected by various factors. • Machine learning can be a new tool for this issue. [ABSTRACT FROM AUTHOR]

Leveraging multi‐platform laser scanning systems offers a complete solution for 3D modelling of large‐scale urban scenes. However, the spatial inconsistency of point clouds collected by heterogeneous platforms with different viewpoints presents challenges in achieving seamless fusion. To tackle this challenge, this paper proposes a coarse‐to‐fine adjustment for multi‐platform point cloud fusion. First, in the preprocessing stage, the bounding box of each point cloud block is employed to identify potential constraint association. Second, the proposed local optimisation facilitates preliminary pairwise alignment with these potential constraint relationships, and obtaining initial guess for a comprehensive global optimisation. At last, the proposed global optimisation incorporates all the local constraints for tightly coupled optimisation with raw point correspondences. We choose two study areas to conduct experiments. Study area 1 represents a fast road scene with a significant amount of vegetation, while study area 2 represents an urban scene with many buildings. Extensive experimental evaluations indicate the proposed method has increased the accuracy of study area 1 by 50.6% and the accuracy of study area 2 by 44.7%. [ABSTRACT FROM AUTHOR]

In this work, we propose combining a low work function anode metal and junction barrier Schottky structure to simultaneously achieve low turn-on voltage (Von) and high breakdown voltage (BV), which alleviates the dilemma that high BV requires high Schottky barrier height (SBH) and high Von. Molybdenum (Mo) is used to serve as the anode metal to reduce the SBH and facilitate fast turn-on to achieve a low Von. To resolve the low SBH related low BV issue, a p-NiO/n-Ga2O3-based heterojunction structure is used to enhance β-Ga2O3 sidewall depletion during the reverse state to improve the BV. With such a design, a low Von = 0.64 V(@1A/cm2) and a high BV = 2.34 kV as well as a specific on-resistance (Ron,sp) of 5.3 mΩ cm2 are demonstrated on a 10 μm-drift layer with a doping concentration of 1.5 × 1016 cm−3. β-Ga2O3 JBS diodes with low Von = 0.64 V and a power figure of merit of 1.03 GW/cm2 show great potential for future high-voltage and high-efficiency power electronics. [ABSTRACT FROM AUTHOR]

The position consistency of mobile laser scanning (MLS) point clouds is crucial for large-scale applications, and is normally guaranteed by the global navigation satellite system (GNSS) and high-precision inertial measurement unit (IMU) in the data acquisition. However, GNSS-denied environments such as city valleys result in significant position inconsistency for overlapping areas, and it is difficult to automatically locate these inconsistent areas. In this paper, to overcome these problems, we present MuCoGraph , which introduces mu lti-scale co nstraints to establish the correct correspondences for revisited areas, and formulates an enhanced pose graph for position inconsistency correction. The georeferenced MLS point cloud is first sliced into segments adaptively, and these segments are then abstracted as graph vertices, which satisfy local geometric consistency and rigid transformation hypotheses. Accurate revisited graph edges are then constructed hierarchically under multi-scale scenery consistency constraints. These revisited edges are initialized based on feature-based correspondence estimation and further unreliable edge pruning. Finally, through combination with virtual co-observations, correspondence-enhanced pose-graph optimization is introduced to globally redistribute the errors and obtain a high-precision point cloud. The proposed method was used to correct the MLS point cloud position inconsistency in three datasets. The average three-dimensional distance of the checkpoints was reduced from 0.362 m, 0.108 m, and 1.027 m to 0.057 m, 0.033 m, and 0.051 m for datasets I, II, and III respectively. In addition, the root-mean-square error of all three datasets was less than 0.04 m after correction. The experiments confirmed that the proposed method can automatically locate and correct the position inconsistency of MLS point clouds, showing good robustness and effectiveness. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ultra-small PtSn clusters were controlled through argon calcination atmosphere. • More than 8 g[C 3 H 6 ]·g[Pt]−1·h−1 of propylene formation rates were achieved. • Ultra-low deactivation constant of 0.0001 h−1 was evaluated for PtSn8@S-1-Ar-50. • The anticipating C 3 H 6 selectivity was owing to PtSn@S-1 confined-catalysis. It's a great challenge for enhancing the stability over Pt-based catalysts with low Pt loading during propane dehydrogenation based upon the manipulation of ultra-small PtSn clusters and their compositions. Here, we developed a novel strategy to produce and stabilize sub-nanometer PtSn clusters even atomical dispersion within Silicalite-1 crystals via tailoring calcination atmosphere from air to argon, which could achieve a stable performance of propane dehydrogenation with only 0.15 wt% Pt loading. Argon calcination atmosphere of PtSn@Silicalite-1 significantly decreased the size of PtSn clusters, which further presented a strikingly catalytic performance with the high formation of propylene over 8.0 mol[C 3 H 6 ]·g[Pt]−1·h−1 even after 3840 min at 600 °C (WHSV=760 g[C 3 H 8 ]·g[Pt]−1·h−1). Hardly any deactivation was obtained over PtSn8@S-1-Ar-50 after long-term runs for 3840 min with an extremely low deactivation constant of 0.0001 h−1 so far, which was mainly derived from the outstanding stability of PtSn sub-nanometers within S-1 crystals through appropriate flow rate of argon calcination atmosphere. [ABSTRACT FROM AUTHOR]

• Amino acids functionalized GO nanosheets were mixed with Pebax to fabricate MMMs. • Amine and carboxyl groups intensified facilitated mechanism and solution mechanism. • DFT calculation revealed the interaction between gases molecules and amino acids. • Arg@GO/Pebax (0.4) membrane exhibited high CO 2 /N 2 separation performance. Graphene oxide (GO) nanosheets, as versatile nanofillers, can create two-dimensional passageways in mixed matrixed membranes (MMMs), yet the flexible manipulation of GO nanosheets is hampered by the lack of appropriate chemical functional groups. In this study, we chose amino acids（arginine, histidine and cysteine）to modify GO nanosheets by direct crosslinking and the loading content of amino acids on GO nanosheets was more than 20%. The modified GO nanosheets were then filled into the Pebax matrix to prepare MMMs. The CO 2 separation performance of MMMs with different nanofillers was compared and different amino acids modified GO nanosheets could fortify the solution mechanism for CO 2 in the order of arginine@GO ＞ histidine@GO ＞ cysteine@GO. Density functional theory (DFT) calculations were conducted to further elucidate the interaction mechanism between gases molecules and amino acids. Under dry state, the complexation energy (Ec) between CO 2 and amine groups was similar to the Ec between CO 2 and carboxylic groups in amino acids. In particular, 0.4 wt% arg@GO nanosheets rendered the membranes with promising CO 2 permeance of 169 Barrer and CO 2 /N 2 selectivity of 70, and surpassed the 2008 upper bound. The amino acids modified GO nanosheets may enlighten an alternative way to explore CO 2 transfer mechanism within MMMs and fabricate high separation performance membranes. [ABSTRACT FROM AUTHOR]