Preparation of single atom catalysts (SACs) is of broad interest to materials scientists and chemists but remains a formidable challenge. Herein, we develop an efficient approach to synthesize SACs ...via a precursor-dilution strategy, in which metalloporphyrin (MTPP) with target metals are co-polymerized with diluents (tetraphenylporphyrin, TPP), followed by pyrolysis to N-doped porous carbon supported SACs (M
/N-C). Twenty-four different SACs, including noble metals and non-noble metals, are successfully prepared. In addition, the synthesis of a series of catalysts with different surface atom densities, bi-metallic sites, and metal aggregation states are achieved. This approach shows remarkable adjustability and generality, providing sufficient freedom to design catalysts at atomic-scale and explore the unique catalytic properties of SACs. As an example, we show that the prepared Pt
/N-C exhibits superior chemoselectivity and regioselectivity in hydrogenation. It only converts terminal alkynes to alkenes while keeping other reducible functional groups such as alkenyl, nitro group, and even internal alkyne intact.
Display omitted
•Successful synthesis of kilogram-scale Au1/CeO2 SACs with ball milling approach.•Au1/CeO2 SACs are highly active, selective, and extremely stable for PROX reaction.•The Au1/CeO2 SACs ...with different preparation scales show essentially identical catalyst structure and catalytic performance.•The results show wide applicability of ball milling method to fabricate a family of oxide-supported noble metal SACs.
Although CeO2-supported Au single atoms (Au1/CeO2) have great potential in preferential oxidation of CO (PROX) reaction, the large-scale synthesis of such single-atom catalysts (SACs) is still greatly challenging. Herein, we develop a dry ball milling method for the mass production of Au1/CeO2 SACs in large quantities (>1 kg). The as-prepared Au1/CeO2 SACs were demonstrated as highly active, selective, and stable catalysts for PROX at 120 °C with 100% CO conversion. The TOFs of Au1/CeO2 SACs for H2 oxidation at 120 °C (<0.01 s−1) were about two orders of magnitude lower than that for CO oxidation. Moreover, the four Au1/CeO2 SACs with different preparation scales showed essentially identical catalyst structure as well as catalytic performance. This approach can also be extended to prepare a family of oxide-supported noble metal SACs, which may pave a facile path for the mass production of oxide-supported SACs to meet industrialization production requirements.
Point of interest (POI) recommendation is a popular personalized location-based service. This paper proposes a Geographic Personal Matrix Factorization (GPMF) model that makes effective use of ...geographic information from the perspective of the relationship between POIs and users. This model considers the role of geographic information from multiple perspectives based on the locational relationship among users, the distributional relationship between users and POIs, and the proximity and clustering relationship among POIs. The GPMF mines the influence of geographic information on different objects and carries out unique modeling through cosine similarity, non-linear function, and k nearest neighbor (KNN). This study explored the influence of geographic information on POI recommendation through extensive experiments with data from Foursquare. The result shows that GPMF performs better than the commonly used POI recommendation algorithm in terms of both precision and recall. Geographic information through proximity relations effectively improves the recommendation algorithm.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
•Long time series multi-spectral images are utilized for large-area crop yield mapping.•3D Convolutional Neural Network was used as an automated spatial-spectral feature extractor.•Long-Short Term ...Memory network identified complex temporal feature during crop growth.•Best yield estimation performance is obtained near the harvest.•Improved accuracy compared to state-of-art deep learning and machine learning methods.
Crop yield prediction has played a vital role in maintaining food security and has been extensively investigated in recent decades. Most research has focused on excavating fixed spectral information from remote sensing images. However, the growth of crops is a highly complex trait determined by diverse features. To maximally explore these heterogeneous features, we aim to simultaneously exploit spatial, spectral, and temporal information from multi-spectral and multi-temporal remotely sensed imagery. Therefore, in this paper, we propose a novel deep learning architecture for crop yield prediction, namely, SSTNN (Spatial-Spectral-Temporal Neural Network), which combines 3D convolutional and recurrent neural networks to exploit their complementarity. Specifically, the SSTNN incorporates a spatial-spectral learning module and a temporal dependency capturing module into a unified convolutional network to recognize the joint spatial-spectral-temporal representation. The novel spatial-spectral feature learning module first exploits sufficient spatial-spectral features from the multi-spectral images. Then, the temporal dependency capturing module is concatenated on top of the spatial-spectral feature learning module to mine the temporal relationship from the long time-series images. Furthermore, we introduce a new loss function that eliminates the influence of an imbalanced distribution of crop yield labels. Finally, the proposed SSTNN is validated on winter wheat and corn yield predictions from China. The results are compared with widely used machine learning methods as well as state-of-art deep learning methods. The experimental results demonstrate that the proposed method can provide better prediction performance than the competitive methods.
In this study, atomically dispersed metal catalysts supported on metal oxides are prepared through a ball milling method. The Ru1/NiO catalyst shows superior performance for the selective oxidation ...of 5-hydroxymethylfurfural (HMF) to 2,5-diformylfuran (DFF), with 91.1% HMF conversion and 81.3% selectivity to DFF under 110 °C for 2.0 h. It also displays promising recyclability with no aggregation after three catalytic runs. Moreover, the ball milling method shows greatly favorable applicability in preparing a family of oxide-supported atomically dispersed noble-metal catalysts. Our approach not only provides a facile, low-cost, and green method to atomically dispersed catalysts but also benefits the development of highly efficient catalysts for biomass conversion reactions.
SUMMARY
Ambient noise tomography (ANT) is a widely used method to obtain shear wave velocity structure in the crust and upper mantle. Usually, the topography is assumed to have negligible effect on ...the resulting models. This, however, might not be proper in regions with large topographic variation, such as plateau edges, submarine slopes and volcanic islands. In this study, we use synthetics from waveform-based numerical simulation to quantify the topography effect on ANT in the Longmen Shan area, eastern Tibetan Plateau margin. Three kinds of models are used in forward simulation to obtain theoretical waveforms, including Case1: the layered model, Case2: the layered model with topographic variation and Case3: the flattened model of Case2. The final inversion results show that the bias of ANT is negligible in the blocks with relatively flat topography, such as the interior regions of the Tibetan Plateau and the Sichuan Basin. However, for the Longmen Shan boundary zone with significant topographic variation (∼4 km), the shear wave velocity image has an obvious negative bias that can reach up to −4 per cent. The maximum depth of bias is ∼5 km, which is mirrored with the maximum topographic elevation difference of the region, and the average bias disappears as the depth decreases to the surface (0 km) or increases to three times of the maximum influence depth (∼15 km). The horizontal distribution of the tomographic bias is almost linearly related to the topographic elevation difference with a slope of −1.04 and a correlation coefficient of 0.90 at maximum influence depth. According to this first-order correction formula and the decreasing trend of average bias with depth, the topography effect on ANT can be suppressed to a certain extent.
The Pawnee M5.8 earthquake is the largest event in Oklahoma instrument recorded history. It occurred near the edge of active seismic zones, similar to other M5+ earthquakes since 2011. It ruptured a ...previously unmapped fault and triggered aftershocks along a complex conjugate fault system. With a high-resolution earthquake catalog, we observe propagating foreshocks leading to the mainshock within 0.5 km distance, suggesting existence of precursory aseismic slip. At approximately 100 days before the mainshock, two M ≥ 3.5 earthquakes occurred along a mapped fault that is conjugate to the mainshock fault. At about 40 days before, two earthquakes clusters started, with one M3 earthquake occurred two days before the mainshock. The three M ≥ 3 foreshocks all produced positive Coulomb stress at the mainshock hypocenter. These foreshock activities within the conjugate fault system are near-instantaneously responding to variations in injection rates at 95% confidence. The short time delay between injection and seismicity differs from both the hypothetical expected time scale of diffusion process and the long time delay observed in this region prior to 2016, suggesting a possible role of elastic stress transfer and critical stress state of the fault. Our results suggest that the Pawnee earthquake is a result of interplay among injection, tectonic faults, and foreshocks.
Accurate and fast path calculation is essential for applications such as vehicle navigation systems and transportation network routing. Although many shortest path algorithms for restricted search ...areas have been developed in the past ten years to speed up the efficiency of path query, the performance including the practicability still needs to be improved. To settle this problem, this paper proposes a new method of calculating statistical parameters based on a unidirectional road network model that is more in line with the real world and a path planning algorithm for dynamically restricted search areas that constructs virtual boundaries at a lower confidence level. We conducted a detailed experiment on the proposed algorithm with the real road network in Zhengzhou. As the experiment shows, compared with the existing algorithms, the proposed algorithm improves the search performance significantly in the condition of optimal path under the premise of ensuring the optimal path solution.
In this present study, we assembled and analyzed the mitogenomes of two asymbiotic and six ectomycorrhizal
species based on next-generation sequencing data. The size of the eight
mitogenomes ranged ...from 37,341 to 137,428 bp, and we considered introns to be one of the main factors contributing to the size variation of
. The introns of the
gene experienced frequent gain/loss events in
; and the intron position class cox1P386 was lost in the six ectomycorrhizal
species. In addition, ectomycorrhizal
species had more repetitive sequences and fewer intergenic sequences than asymbiotic
species in their mitogenomes. Large-scale gene rearrangements were detected in the
species we tested, including gene displacements and inversions. On the basis of the combined mitochondrial gene set, we reconstructed the phylogenetic relationships of 66
. The six ectomycorrhizal
species were of single origin, and the two saprophytic
species formed two distinct clades. This study is the first to elucidate the functions of the mitogenome in the evolution and ecological adaptation of
species.
PDF
