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Airborne light detection and ranging (LiDAR) point clouds have become growingly popular as a reliable data source for 3-D digital building model reconstruction. Therefore, we develop a label-constraint approach for automatically detecting building roofs using airborne LiDAR point clouds and multispectral images, where the label information is introduced in both the discriminative feature space generation and the detection procedure. To obtain a robust and highly discriminative descriptor, a supervised sparse coding-enhanced bag of visual word (SC-BOVW) model based on a learned discriminative dictionary is used to encode local geometric and spectral information within each super-voxel into high-level semantic representation, which is then fed into a support vector machine (SVM) classifier for distinguishing buildings from others. Additionally, a graph cut-based procedure is used as a postprocessing step to guarantee the spatial consistency in detection results. Experiments were conducted on the International Society for Photogrammetry and Remote Sensing (ISPRS) benchmark data sets. Results indicate that the proposed method is accurate and efficient in terms of building roof region detection. Moreover, the proposed method is superior to other existing methods with average differences in recall of 2.23%, precision of 0.28% and quality of 1.99%.

Global geo-reference Lunar Reconnaissance Orbiter Camera-wide angle camera (LROC-WAC) mosaic imagery provides the precise geographic information for the mapping of mineral elements based on Chang’E-1 interferometric imaging spectrometer (IIM) imagery. However, the traditional image registration methods fail to achieve the accurate registration in between due to heterogeneous characteristics. Therefore, this letter proposes a semiautomatic registration method for Chang’E-1 IIM imagery based on global geo-reference LROC-WAC mosaic imagery. Due to the lack of ground control points, the method implemented a random sample consensus (RANSAC)-guided affine transformation (AT) model to help predict the potential coarse correspondence. Afterward, a multiwindow image matching approach is performed for the fine correspondence. To verify the performance of the proposed method, experiments were performed using Chang’E-1 IIM imagery and geo-reference LROC-WAC mosaic imagery. Experimental results indicate that the proposed method can obtain a massive number of homologous points while minimizing manual intervention, which is comparable to manual results and has high image registration accuracy.

The increasing availability of both indoor positioning services and sensors for 3D data capture, such as RGB-D sensors, allows the provision of indoor spatial information services for indoor localization-based applications. To efficiently realize these services, the indoor information and the relationships between indoor spaces are required. The recently released Indoor Geography Markup Language (IndoorGML) attempts to represent and exchange geo-information for modeling topology and semantics of indoor spaces. However, it is still challenging to map indoor space features to the IndoorGML-encoded navigation network model directly from colorized 3D points. Therefore, we propose a semantics-guided method for indoor navigation element reconstruction from RGB-D sensor data. First, a hierarchical indoor scene interpretation framework is used for robustly recognizing the architecture structures and doors, respectively. In the developed hierarchical structure, a graph convolutional network-based architectural structure recognition method is adopted to deduce the long-range interactions among primitives for describing the rich physical relationships in the real world. Its output is the produced initial annotated results, from which doors as the common openings are further detected using a U-Net-based door recognition method. This enables to effectively provide the semantic guidance for the cellular representation of the indoor space and its topological reconstruction. Second, an adaptive architectural structure-guided room segmentation method is developed by combining distance transform and watershed segmentation to determine cellular spaces according to the definition in IndoorGML. Third, taking the different states of doors into consideration, a door-guided topological relationship reconstruction method is proposed to achieve the network graph representation of indoor environments. In this context, a simulated door model is designed to correct and update the true position of a door leaf, and a virtual door is defined to optimize the topological analysis. As a consequence, an IndoorGML-encoded navigation network model is generated, which can be used as the base for indoor navigation applications independent of the platform. Experiments are performed on the public Stanford large-scale 3D Indoor Spaces Dataset to verify the robustness and effectiveness of the proposed method both qualitatively and quantitatively. Results indicate the capability of the proposed method in automatically reconstructing indoor navigation elements of Manhattan-world indoor environments from RGB-D sensor data.

Point cloud feature extraction as a classification task is crucial in maximizing the efficient downstream applicability of raw point clouds. With the goal of learning optimum features for efficient classification of a multi-class point cloud for downstream applications, this letter presents a supervoxel-Fisher vector (FV)-based approach for airborne light detection and ranging (LiDAR) data classification. In our approach, FV encoding is implemented to deduce compact global descriptors from aggregated supervoxels to establish a more descriptive and discriminative representation, transforming the low-level visual features into high-level semantic features. As a result, the proposed approach combines local and global feature properties through the quantization and aggregation of higher order statistics to harnesses their combined advantages for producing good classification results. Experiments were conducted on the international society for photogrammetry and remote sensing 3-D semantic labeling benchmark data set. Results indicate that the proposed approach is robust and efficient, attained the third best position with an overall accuracy of 81.79%, and ranked first with an $\text{F}_{{1}}$ -score of 72.31%.

Accurate individual tree segmentation is an important basis for the subsequent calculation and analysis of forestry parameters. However, rasterized canopy height model based methods often suffer from 3-D information loss due to the interpolation operation. Therefore, this article proposes an individual tree segmentation method based on the marker-controlled watershed algorithm and 3-D spatial distribution analysis from airborne LiDAR point clouds. First, based on the potential tree apices derived from the local maxima filtering, the marker-controlled watershed segmentation algorithm is conducted to obtain the coarse point clusters. Then, within the principal component analysis defined local coordinate reference framework, a multidirectional 3-D spatial profile analysis is performed on each point cluster to refine the potential tree apex positions. Finally, the refined potential tree apex positions are used as a prior of K-means clustering to achieve the coarse-to-fine individual tree segmentation. Comparative experiments were conducted on the public NEWFOR dataset to evaluate the proposed method. Results indicate that the proposed method is efficient and robust for segmenting individual trees.

Recently, extensive research has been done to explore the potential thermoelectric performance of p-Type Zintl compounds AB2Sb2 (A = Ca, Yb, Eu, Sr, Mg; B = Zn, Mn, Cd, Mg), mainly focus on A-site substitution and/or B-site substitution effect. Herein, we report that both power factors and thermal conductivities are simultaneously optimized to increase ZT values via substitution of Sb atoms with the isoelectronic Bi atoms in YbZn2Sb2−xBix compounds. We found that the power factor could be enhanced by 27%, as a result of improved electrical conductivities and the maintained Seebeck coefficients. The former is obtained from an increase of carrier density through a shift of Fermi level via Bi doping, which is supported by XPS analysis. The Seebeck coefficients are maintained due to the increased effective mass. Moreover, the lowest lattice thermal conductivity (0.47 Wm−1 K−1 at 723K) is below the lattice thermal conductivity limit due to enhanced phonon scattering via Bi-doping, which is analyzed by the Callaway model. Benefiting from the synergistic effect, the ZT of Bi-doping samples are significantly enhanced compared with that of the pristine one. These results probably offer a synergistic strategy to enhance ZT for p-Type Zintl compounds AB2Sb2 and other high-efficiency thermoelectric materials.

The chemical-coupled three-dimensional (3D) γ-MnOOH with CoOOH particles (γ-MnOOH/CoOOH) was fabricated through a two-step strategy involving a hydrothermal and reduction–oxidation process. The str...

The pole-like object detection is of significance for robot navigation, autonomous driving, road infrastructure inventory, and detailed 3-D map generation. In this letter, we develop a skeleton-based hierarchical method for automatic detection of pole-like objects from mobile LiDAR point clouds. First, coarse extraction of building facades is adopted for the occlusion analysis. Second, slice-based Euclidean clustering algorithm is implemented to derive a set of pole-like object candidates. Third, skeleton-based principal component analysis shape recognition is presented to robustly locate all possible positions of pole-like objects. Finally, a Voronoi-constrained vertical region growing algorithm is proposed to adaptively producing the individual pole-like objects. Experiments were conducted on the public Paris–Lille-3-D data set. Experimental results demonstrate that the proposed method is robust and efficient for extracting the pole-like objects, with average quality of 90.43%. Furthermore, the proposed method outperforms other existing methods, especially for detecting pole-like objects with a large radius.

The development of designing and searching inexpensive electrocatalysts with high activity for both hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is significant to enable water splitting as a future renewable energy source. Herein, we synthesize a new CoP(MoP)-CoMoO3 heterostructure coated by a N-doped carbon shell [CoP(MoP)-CoMoO3@CN] via thermal decomposition and phosphatizing of the CoMoO4·0.9H2O nanowires encapsulated in N-doped carbon. At 10 mA·cm–2, this CoP(MoP)-CoMoO3@CN nanocomposite exhibits superior electrocatalytic activity at low overpotentials of 296 mV for OER and 198 mV for HER in alkaline media. More importantly, we achieve a current density of 10 mA·cm–2 at 1.55 V by using this CoP(MoP)-CoMoO3@CN as both cathode and anode for overall water splitting. This promising performance could be due to the high activity of CoP(MoP)-CoMoO3 and the good conductivity of the external mesoporous N-carbon shell, which makes the CoP(MoP)-CoMoO3@CN nanowires a competitive alternati...

The higher electrocatalytic activity of hydrogen evolution in basic media for Pt-based catalysts is largely dependent on the intrinsic microscopic surface chemical environment. Given the fundamental mechanism of the interfacial interaction between Pt and oxophilic components, engineering a moderate oxygen-friendly surface environment of Pt-based catalysts is beneficial for endowing Pt with high catalytic activity for the hydrogen evolution reaction (HER). Herein, we fabricated ultralong jagged Pt85Mo15–S nanowires with rich interfacial active sites by using S as the “active auxiliary” to demonstrate an enhanced catalytic HER performance. Strikingly, the Pt85Mo15–S nanowires exhibited exceptional activity with 3.62 times the specific current density and 4.03 times the mass current density of commercial Pt/C as well as excellent stability towards alkaline HER. X-ray photoelectron spectroscopy revealed that the S element could prevent the further oxidization of Mo and then lead to enough electron transfer from Mo to Pt. In addition, the theoretical calculations demonstrated that the water dissociation energy barrier could be significantly reduced under the interfacial synergy of the intimate contact between Pt and MoSx. This work illustrates a new strategy to advance the fundamental exploration on electrocatalytic materials, which makes a systematic approach to build an interfacial model catalyst for fundamental electrocatalytic studies of alkaline HER.

Morphology-controlled synthesis of PtNi concave nanocubes (CNCs) with high-index facets (HIFs) supported on porous graphene (PG) was first achieved via changing the amount of PG. Impressively, the optimal PtNi/10PG CNCs exhibited superior activity for the hydrogen evolution reaction (HER), outperforming the pristine PtNi CNCs and commercial 20 wt% Pt/C.

Rapid responses in the early stage of a new epidemic are crucial in outbreak control. Public holidays for outbreak control could provide a critical time window for a rapid rollout of social distancing and other control measures at a large population scale. The objective of our study was to explore the impact of the timing and duration of outbreak-control holidays on the coronavirus disease 2019 (COVID-19) epidemic spread during the early stage in China. We developed a compartment model to simulate the dynamic transmission of COVID-19 in China starting from January 2020. We projected and compared epidemic trajectories with and without an outbreak-control holiday that started during the Chinese Lunar New Year. We considered multiple scenarios of the outbreak-control holiday with different durations and starting times, and under different assumptions about viral transmission rates. We estimated the delays in days to reach certain thresholds of infections under different scenarios. Our results show that the outbreak-control holiday in China likely stalled the spread of COVID-19 for several days. The base case outbreak-control holiday (21 d for Hubei province and 10 days for all other provinces) delayed the time to reach 100 000 confirmed infections by 7.54 d. A longer outbreak-control holiday would have had stronger effects. A nationwide outbreak-control holiday of 21 d would have delayed the time to 100 000 confirmed infections by nearly 10 d. Furthermore, we find that outbreak-control holidays that start earlier in the course of a new epidemic are more effective in stalling epidemic spread than later holidays and that additional control measures during the holidays can boost the holiday effect. In conclusion, an outbreak-control holiday can likely effectively delay the transmission of epidemics that spread through social contacts. The temporary delay in the epidemic trajectory buys time, which scientists can use to discover transmission routes and identify effective public health interventions and which governments can use to build physical infrastructure, organize medical supplies, and deploy human resources for long-term epidemic mitigation and control efforts.

Indoor environment model reconstruction has emerged as a significant and challenging task in terms of the provision of a semantically rich and geometrically accurate indoor model. Recently, there has been an increasing amount of research related to indoor environment reconstruction. Therefore, this paper reviews the state-of-the-art techniques for the three-dimensional (3D) reconstruction of indoor environments. First, some of the available benchmark datasets for 3D reconstruction of indoor environments are described and discussed. Then, data collection of 3D indoor spaces is briefly summarized. Furthermore, an overview of the geometric, semantic, and topological reconstruction of the indoor environment is presented, where the existing methodologies, advantages, and disadvantages of these three reconstruction types are analyzed and summarized. Finally, future research directions, including technique challenges and trends, are discussed for the purpose of promoting future research interest. It can be concluded that most of the existing indoor environment reconstruction methods are based on the strong Manhattan assumption, which may not be true in a real indoor environment, hence limiting the effectiveness and robustness of existing indoor environment reconstruction methods. Moreover, based on the hierarchical pyramid structures and the learnable parameters of deep-learning architectures, multi-task collaborative schemes to share parameters and to jointly optimize each other using redundant and complementary information from different perspectives show their potential for the 3D reconstruction of indoor environments. Furthermore, indoor–outdoor space seamless integration to achieve a full representation of both interior and exterior buildings is also heavily in demand.

The velocity of an ice shelf is an important characteristic to understand its dynamics and interaction with the internal ice sheet. Therefore, we develop an improved multi-scale image matching method for producing a complete and accurate Amery ice shelf velocity field from Landsat 8 images. First, we investigate the relationship between the template size and the image entropy and propose an image entropy-based preliminary operation for distinguishing the high-contrast regions from the low-contrast regions prior to iteratively determining the optimum template size. Second, a Gaussian pyramid image-based hierarchical data structure is designed to support a coarse-to-fine image matching strategy.The image entropy-based matching method is applied on the top layer of the image pyramid to guarantee the matching results have optimal completeness and high accuracy. Finally, a postprocess procedure is performed to derive a complete and accurate Amery ice shelf velocity field. Experimental results demonstrate that the proposed method can significantly improve computational efficiency. Moreover, the proposed method provides more accurate and robust matching results than other existing methods, particularly over the low-contrast surfaces. Additionally, the derived velocity field also shows good consistency with the one acquired from MEaSUREs Annual Antarctic Ice Velocity Maps 2016–2017.

The digital mapping of road environment is an important task for road infrastructure inventory and urban planning. Automatic extraction and classification of pole-like objects can remarkably reduce mapping cost and enhance work efficiency. Therefore, this paper proposes a voxel-based method that automatically extracts and classifies three-dimensional (3-D) pole-like objects by analyzing the spatial characteristics of objects. First, a voxel-based shape recognition is conducted to generate a set of pole-like object candidates. Second, according to their isolation and vertical continuity, the pole-like objects are detected and individualized using the proposed circular model with an adaptive radius and the vertical region growing algorithm. Finally, several semantic rules, consisting of shape features and spatial topological relationships, are derived for further classifying the extracted pole-like objects into four categories (i.e., lamp posts, utility poles, tree trunks, and others). The proposed method was evaluated using three datasets from mobile LiDAR point cloud data. The experimental results demonstrate that the proposed method efficiently extracted the pole-like objects from the three datasets, with extraction rates of 85.3%, 94.1%, and 92.3%. Moreover, the proposed method can achieve robust classification results, especially for classifying tree trunks.

The safety of the electricity infrastructure significantly affects both our daily life and industrial activities. Timely and accurate monitoring of the safety of electricity network can prevent dangerous situations effectively. Thus, we, in this paper, develop a voxel-based method for automatically extracting the transmission lines from airborne LiDAR point cloud data. The method proposed in this paper uses three-dimensional (3-D) voxels as primitives and consist of the following steps: First, skeleton structure extraction using Laplacian smoothing; second, feature construction of a 3-D voxel using Latent Dirichlet allocation topic model; and third Markov random field model-based extraction for generating locally continuous and globally optimal results. To evaluate the effectiveness and robustness of the proposed method, experiments were conducted on four different types of power line scenes with flat and complex terrains from helicopter-borne LiDAR point cloud data. Experimental results demonstrate that our proposed method is efficient and robust for automatically detecting both the single conductor and the bundled conductors, with precision, recall, and quality of over 96.78%, 98.67%, and 96.66%, respectively. Moreover, compared with other existing methods, our proposed method provides higher detection correctness rate.

The Yandong porphyry copper deposit is located in the southern part of the Dananhu-Tousuquan Island Arc belt in Eastern Tianshan (Xinjiang, NW China). The Dananhu-Tousuquan belt contains a number of large and medium Cu deposits, among which the Yandong deposit (∼2.0 Mt Cu @ 0.67%) is the largest. The Yandong Cu deposit is hosted by plagiogranite porphyry and the Carboniferous Qi’eshan Group mafic to intermediate calc-alkaline volcanic and pyroclastic rocks. According to the crosscutting relationships and mineral assemblages, the alteration and mineralization processes at Yandong comprise three episodes: the porphyry mineralization episode (including potassic, propylitic, early phyllic and late phyllic stages), the overprinting mineralization episode (including main- and post-mineralization stages) and lastly supergene alteration episode. Fluid inclusions (FIs) in quartz from the potassic, early/late phyllic and post-mineralization stages, and anhydrite from the main-/post-mineralization stages include four types: 1) vapor-liquid two phases (W-type), 2) daughter mineral-bearing (S-type), 3) pure liquid (PW-type), and 4) pure vapor (PV-type). The potassic stage contains W-, S- and PV-type FIs, which yielded homogenization temperatures of 304–445 °C (mainly 340–400 °C) and salinities of 3.1–16.4 (mainly 4.0–10.0) wt% NaCl eqv. At the early phyllic stage, three types of FIs are identified, i.e., the W-, S-, and PV-type. The S-type and W-type FIs homogenized at 213–441 °C (mainly 280–300 °C) and 241–352 °C (mainly 300–320 °C), respectively, with corresponding salinities of 33.1–52.0 (mainly 34.0–40.0) wt% NaCl eqv. and 0.9–15.9 (mainly 0.9–4.0) wt% NaCl eqv., respectively. The late phyllic stage contains W-, S- and PW-type FIs, which homogenized at 146–248 °C (mainly 160–180 °C), with salinities ranging from 3.9 to 18.2 (mainly 4.0–8.0) wt% NaCl eqv. Mineralization depths calculated from FIs are: 0.8–1.2 km (Stage I), 0.6–1.8 km (Stage IIIA) and 0.4–0.7 km (Stage IIIB). Fluid boiling and mixing likely occurred during the porphyry mineralization period, leading to the precipitation of pyrite and chalcopyrite. During the overprinting mineralization, the W- and PV-type FIs occur in the main-mineralization anhydrite, with homogenization temperatures and salinities being 248–421 °C (mainly 300–340 °C) and 5.3–13.8 (mainly 8.0–10.0) wt% NaCl eqv., respectively. The post-mineralization quartz and anhydrite homogenized at 105–195 °C (mainly 120–140 °C), with salinities of 0.5–13.6 (mainly 8.0–10.0) wt% NaCl eqv. The ore-forming fluids may have predominantly been entrapped at 0.8–1.6 km (Stage IV) and 0.3–0.6 km (Stage V). The decreasing temperature may have led to the sulfides and sulfate precipitation and enrichment. Sericite 40 Ar/ 39 Ar dating of the altered plagiogranite porphyry yielded a plateau age of 332.8 ± 3.8 Ma, consistent with the age of the early ore-forming plagiogranite porphyry (339–332 Ma). Re–Os dating of molybdenite, coexisting with chalcopyrite-anhydrite-chlorite-calcite assemblage, yielded an age of 324.3 ± 2.7 Ma (weighted mean), consistent with the late quartz albite porphyry age (zircon U-Pb: 323.6 ± 2.5 Ma). Consequently, we propose that at least two mineralization episodes may have occurred at Yandong, with the second episode contributing to the majority of the Cu-Mo resources. Such overprinting mineralization style at Yandong may represent a good example of the Paleozoic Cu deposits in the Central Asian Orogenic Belt.

The Yandong porphyry Cu deposit in the Eastern Tianshan terrane is the largest in Xinjiang, NW China (metal reserve: 2.3 Mt Cu @ 0.67%). Three periods and six alteration and mineralization stages were identified in this study, i.e., Porphyry period (including Stage I: propylitic alteration; II: quartz-magnetite alteration; III: phyllic alteration and early mineralization); overprinting period (including Stage IV: overprinting mineralization and Stage V: late vein) and supergene period (Stage VI: supergene mineralization). Stage IV was the main Cu mineralization stage at the Yandong Cu deposit, which is characterized by the mineral assemblage of chalcopyrite + chlorite + anhydrite + calcite. Electron microprobe analysis (EMPA) data indicate that Stage IV chlorite contains lower SiO2 and MgO, but higher FeO, Al2O3 and Fe/(Fe + Mg) than Stage I chlorite. LA-ICP-MS analyses indicate that Stage IV chlorite contains lower Cr, Ni, Co, B, Ca and Sr, but higher Sc, Ga, Sn, Ti, Zn and Mn than Stage I chlorite. Stage IV epidote contains lower B, Zr, Ba and Ti, but higher Sn, Y, Ga, Ag, U, Y, Cu and Sr than Stage I epidote. Concentrations of Ti, Zn, As, V, Sc and Cu are highest near the orebody for both Stage I and IV chlorite, and Au and Sn in Stage IV chlorite are highest near the orebody. Titanium content of Stage I epidote is highest near the orebody, but V, Sc and Zr are lowest there. Stage I chlorite at Yandong is geochemically similar to the giant Batu Hijau porphyry Cu-Au deposit (Indonesia), but Stage IV chlorite contains higher Fe, Al and As, lower Mg and Sn than the latter. Stage I epidote at Yandong is geochemically similar to the porphyry and skarn deposits in the central Baguio district (Philippines), but Stage IV epidote has higher Sn, Ga and U, but lower Zr, Ti and Ba than the latter. Ore deposit geology and alteration mineral chemistry indicate that the Yandong Cu deposit is an atypical porphyry deposit. The adakitic tonalite porphyry and quartz albite porphyry (granitic) may have formed the early and overprinting Cu mineralization, respectively. Chlorite Ti and V, and epidote Sb show similar spatial variation patterns in Cenozoic and Paleozoic porphyry deposits, which may be used for exploration targeting for ancient porphyry deposits, such as the Yandong Cu deposit.

The Duotoushan Fe-Cu deposit is located in the western segment of the Aqishan-Yamansu metallogenic belt in Eastern Tianshan, Xinjiang (China). Magnetite orebodies are mainly developed in the Upper Carboniferous volcano-sedimentary rocks and are mostly stratabound. Pyrite Re-Os dating has yielded an isochron age of 312 ± 24 Ma (MSWD = 1.5). Five hydrothermal and one supergene alteration/mineralization stages have been recognized from the spatial distribution of alteration zoning, mineral assemblages and textural relationships. The earliest alteration of albite (Ab84-98Or2-16) ± amphibole was related to the nearby albitization granite porphyry. Prograde alteration was developed on the footwall of the intermediate-mafic volcanic rocks, and formed a garnet (Ad60-95Gr5-40)-clinopyroxene (Hd0Di93Jo7 to Hd10Di83Jo7) assemblage. Alteration associated with magnetite can be further divided into three sub-stages, consisting of magnetite-amphibole ± titanite (stage III-A), magnetite-amphibole-epidote (stage III-B) and epidote-magnetite-quartz ± amphibole ± titanite ± pyrite (stage III-C) mineral assemblages. The secondary amphibole is dominantly actinolite. Pyrite, with minor chlorite-chalcopyrite veins, cut the magnetite ore, followed by later quartz/calcite/hematite veinlets. Based on fluid inclusions (FIs) and stable isotopes studies, the pre-ore stage (stage II) was formed at high temperature (>500 °C) and originated from magmatic-hydrothermal fluids ( δ 18 O H 2 O = +7.1‰, δ D H 2 O = −85‰). Two garnet samples have similar δ 18 O H 2 O values (+5.6‰ and +6.4‰) but considerably lower δ D H 2 O values (−134‰ and −139‰), indicating the overprinting by late meteoric water. Iron ore and hydrous minerals assemblages and the associated fluids had overprinted the early anhydrous minerals. Early magnetite mineralization stage (stage III-A) shows clear magmatic water input, as constrained from the δ 18 O H 2 O (+6.9‰ to +7.8‰) and δ D H 2 O (−85‰ to −72‰) values. Later magnetite stage was magmatic-hydrothermal fluid-dominated, but with mixing of heavy δ D H 2 O , as indicated by stable isotope compositions ( δ 18 O H 2 O = +6.1‰ to +7.8‰, δ D H 2 O = −47‰ to −32‰). Sulfur isotope values of the stage IV pyrite give a δ34S interval of +8.8‰ to +12.1‰, suggesting significant addition of external basin fluid/seawater or evaporite sulfur source to magmatic fluid. The low temperatures (83‒213 °C, average = 135 °C), generally medium-high but variable salinities (9.9‒27.2 wt.% NaCl equiv., average = 21.3 wt.%) and Ca-Mg-rich components of stage V fluids show clear features of involvement of basinal brines/seawater and minor meteoric water in the late hydrothermal stages. We infer that the temperature drop of the hydrothermal fluids may have been the main cause of massive magnetite precipitation at the Duotoushan deposit, whereas increasing pH values, decreasing temperature and fluid mixing maybe responsible for Cu precipitation. Ore deposit geology, mineral geochemistry and fluid evolution confirm that the Duotoushan Fe-Cu deposit is different from typical skarns and may represent a distinct group of Fe (-Cu) deposits formed during the Aqishan-Yamansu back (intra-) arc basin inversion, which show many similarities with the Central Andean IOCG deposits.

Mobile Light Detection And Ranging (LiDAR) point clouds have the characteristics of complex and incomplete scenes, uneven point density and noises, which raises great challenges for automatically interpreting 3D scene. Aiming at the problem of 3D point cloud classification, we propose a probabilistic graphical model for automatic classification of mobile LiDAR point clouds in this paper. First, the super-voxels are generated as primitives based on the similar geometric and radiometric properties. Second, we construct point-based multi-scale visual features that are used to describe the texture information at various scales. Third, the topic model is used to analyze the semantic correlations among points within super-voxels to establish the semantic representation, which is finally fed into the proposed probabilistic graphical model. The proposed model combines Bayesian network and Markov random fields to obtain locally continuous and globally optimal classification results. To evaluate the effectiveness and the robustness of the proposed method, experiments were conducted using mobile LiDAR point clouds for three types of street scenes. Experimental results demonstrate that our proposed model is efficient and robust for extracting vehicles, buildings, street trees and pole-like objects, with overall accuracies of 98.17%, 97.41% and 96.81% respectively. Moreover, compared with other existing methods, our proposed model can provide higher classification correctness, specifically for small objects such as cars and pole-like objects.

The Heijianshan Fe–Cu (− Au) deposit is located in the Aqishan–Yamansu belt in Eastern Tianshan, NW China. As a typical Fe–Cu deposit in the region, Heijianshan is hosted in the Upper Carboniferous Matoutan Formation submarine volcanic/volcaniclastic rocks. Alteration styles, mineral assemblages and vein crosscutting relationships divide the hydrothermal alteration and mineralization processes into seven stages, namely the chromite (Stage I), epidote (Stage II), magnetite (Stage III), pyrite (Stage IV), Cu (–Au) (Stage V), late veins (Stage VI) and supergene (Stage VII) alteration/mineralization stages. Magnetite mineralization comprises the hematite (Stage III–A) and main magnetite (Stage III–B) mineralization sub-stages. The Heijianshan magnetite ores consist of massive (with mushketovite (MOM) or sulfides (MOS)), disseminated (DO) and magnetite clasts (with chromite (MWC) or without chromite (MNC)) ores. Magnetite in massive- and disseminated ores is featured by (1) depletion in Zr, Nb and Ta; (2) low Ti ( f O 2 increased, which may represent the major controls on the formation of the various magnetite ore types. Compositions of the ore fluids and host rocks, formation of coexisting minerals and other physicochemical parameters (such as T and f O 2 ) may have variably influenced the magnetite geochemistry in the different Heijianshan ore types, with fluid compositions probably playing the most important role. Discrimination diagrams, for instance, Cr vs. Co/Ni, Cr vs. Ti, V vs. Cr and Ni vs. Cr, may be useful for magnetite mineralization type differentiation in other submarine volcanic-hosted Fe/Fe–Cu deposits in the Aqishan–Yamansu belt. Geochemical discrimination diagrams, alteration and mineralization paragenesis indicate that the Heijianshan Fe–Cu (–Au) deposit is best classified as an IOCG-like deposit, which offers a new insight for classifying and characterizing ore genetic types for similar Fe and Fe–Cu deposits in Eastern Tianshan.

The Aqishan-Yamansu belt in the Eastern Tianshan (Xinjiang, NW China) is an important mineralization belt. The belt mainly comprises Carboniferous volcanic, volcaniclastic and clastic rocks, and hosts many intermediate–felsic intrusions and Fe (–Cu) deposits. The biotite diorite, felsic brecciated tuff, granodiorite and syenite from the western Aqishan-Yamansu belt are newly zircon U–Pb dated to be 316.7 ± 1.4 Ma, 315.6 ± 2.6 Ma, 305.8 ± 1.9 Ma and 252.5 ± 1.4 Ma, respectively. The mafic rocks (mafic brecciated tuff and diabase porphyry) are tholeiitic to calc-alkaline series, LILE-rich (e.g., Rb, Ba and Pb), HFSE-depleted (e.g., Nb and Ta), and have high Mg#(44–60), Nb/Ta (15.0–20.0), Ba/La (>30) and Ba/Nb (>57) values/ratios, and low Th/Yb ratios ( 2.10) and positive eNd(t) (>5.7), combined with variable Nb/Ta ratios (9.52–21.4), Y/Nb ratios (1.47–39.7) and Pb isotopes (206Pb/204Pb = 16.225–17.640, 207Pb/204Pb = 15.454–15.520, 208Pb/204Pb = 37.097–38.025) suggest that these rocks were magma mixing products between juvenile crustal-derived magmas and minor mantle-derived magmas. Combined published works with our new ages, geochemical and isotopic data, we propose that the Aqishan-Yamansu belt was an Early Carboniferous fore-arc basin during the southward subduction of the Kangguer oceanic slab beneath the Yili-Central Tianshan block. With the continuing southward subduction, the Aqishan-Yamansu fore-arc basin initiated to close, which generated the mafic and intensive intermediate–felsic magmatism associated with regional Fe (–Cu) mineralization.

Point cloud classification is of great importance to applications of airborne Light Detection And Ranging (LiDAR) data. In recent years, airborne LiDAR has been integrated with various other sensors, e.g., optical imaging sensors, and thus, the fusion of multiple data types for scene classification has become a hot topic. Therefore, this paper proposes a Bayesian network (BN) model that is suitable for airborne point cloud classification fusing multiple data types. Based on an analysis of the characteristics of LiDAR point clouds and aerial images, we first extract the geometric features from the point clouds and the spectral features from the optical images. The optimal BN structure is then trained using an improved mutual-information-based K2 algorithm to obtain the optimal BN classifier for point cloud classification. Experiments demonstrate that the BN classifier can effectively distinguish four types of basic ground objects, including ground, vegetation, trees, and buildings, with a high accuracy of over 90%. Moreover, compared with other classifiers, the proposed BN classifier can achieve the highest overall accuracies, and in particular, the classifier demonstrates its advantage in the classification of ground and low vegetation points.

The late Paleozoic Bailingshan intrusions and volcanic rocks are located in the Aqishan–Yamansu arc belt in the southern part of the eastern Tianshan and are associated with an important group of iron skarn deposits. The exposed intrusive rocks are mainly granodiorite, monzonitic granite, and granite. Zircon U–Pb dating of the Tugutublak Formation tuffaceous dacitic lava yields an age of 324 Ma, whereas dates of the Bailingshan granodiorite, monzonitic granite, and granite yields ages of 317 Ma, 313 Ma, and 307 Ma, respectively. The results indicate that the Bailingshan granitoids were emplaced soon after the eruption of the Tugutublak dacite. All these rocks studied show calc-alkaline to high-K calc-alkaline and metaluminous affinities, with A/CNK values ranging 0.83–1.10. They are enriched in Rb, K, and Pb, depleted in Nb, Ta, Ti, and P, and contain low Sr/Y (4.16–23.7) and Sr (109.0–347.0 ppm) values, displaying typical arc geochemical affinities. The tuffaceous dacitic lava has low Nb/Ta (10.3–14.1) values, a wide range of Mg# (6–64), positive zircon eHf(t) (3.2–7.5) values, and elevated whole-rock eNd(t) (2.03–4.41), but low ISr values (0.70427–0.70530), indicating that the source magma may have been derived from the juvenile lower crust with minor mantle input. The Bailingshan I-type intrusions also exhibit a mixed source signal, as constrained by Nb/Ta ratios, Mg#, and isotopes characteristics. Because the granodiorite, monzonitic granite, and granite intrusions have higher zircon eHf(t) (3.3–7.5, 11.8–13.5, and 10.2–14.4, respectively) and eNd(t) (3.90, 5.78, and 5.94, respectively) values than those of the tuffaceous dacitic lava, it is suggested that mantle-derived materials may have played a more prominent role with their petrogenetic evolution. Integrating our new geological, age, geochemical and isotopic data we propose that the Aqishan–Yamansu iron skarn belt may have formed in a back-arc position or within an intra-arc basin generated by the southward subduction of the Kanggur oceanic plate beneath the Yili–Central Tianshan block during the late Paleozoic, with felsic-intermediate magmatism occurring during the basin inversion.

Considering the practical use of electrochemical water splitting, it is important to construct a highly efficient and stable hydrogen evolution reaction (HER) electrocatalyst over a wide pH range. Herein, we develop an efficient strategy to enhance the electrochemical activity of few-layer MoS2 and Pt nanoparticles (NPs) anchored on multi-wall carbon nanotube (MWCNTs). The as-prepared Pt-MoS2/MWCNTs provides an excellent HER electrocatalytic activity with low overpotentials at −10 mA cm−2 over a wide pH range, namely, 20 mV in 0.5 M H2SO4, 92 mV in 1.0 M phosphate buffer solution (PBS), and 75 mV in 1.0 M KOH, respectively. In addition, Pt-MoS2/MWCNTs deliver the highest mass activity at the overpotential of 0.05 V, which is 8.1, 2.3, and 26.5 times higher than that of commercial 20 wt% Pt/C in acidic, neutral and alkaline media, respectively. Density functional theory (DFT) calculations revealed that the co-existence of MoS2 and Pt NPs facilitated the water dissociation reaction and hydrogen generation, thereby enhancing the activity of HER. This work provides a potential strategy to construct high-performance electrocatalysts for HER over the entire pH range.

Before the natural gas pipeline was put into operation, nitrogen is usually used to replace the air in the natural gas pipeline. In order to prevent air and natural gas from forming explosive mixtures, it is necessary to study the mixing law in the displacement process. In this article, based on computational fluid dynamics basic theory and turbulence model theory, the mathematical model and boundary conditions of nitrogen replacement were determined. The nitrogen replacement process was simulated by Fluent software. The following conclusions are drawn from the analysis: (1) when the flow is laminar, the mixing length is longer than that of the turbulent state, so try to keep the gas in the turbulent state; (2) with an increase in the flow velocity, pipeline diameter, and pipeline length, mixing length increases; (3) with an increase in the back pressure, gas mixing length increases gradually, so try to avoid the presence of back pressure venting; (4) with an increase in the temperature, the mixing length increases gradually; (5) the formula for calculating the mixing length obtained by fitting is L m / D = ( 1 . 95 ~ 2 . 55 ) v 0 . 39 ( L / D ) 0 . 53 .

In recent years, two-dimensional (2D) Ni-based bimetallic sulfides have been widely studied for oxygen evolution reaction (OER). However, traditional 2D nanomaterials are easily re-stacked into dense structures or films when manufactured into practical electrodes. Herein, we report an efficient approach to construct amorphous holey NiMS nanosheets (M = Co, Fe, Mn) to overcome this difficulty. Taking amorphous holey NiCoS nanosheets (denoted as holey NiCoS-NS) as a model material, we illustrate the feasibility of this method to control the hole size and pore density in the nanosheets by altering the time of sulfidation process. Benefiting from porous 2D architecture, S-doped species, synergistic effects of Ni and Co, as well as amorphous nature, the holey NiCoS-NS exhibit a low overpotential of 280 mV at current density of 10 mA cm−2 and excellent stability in 1.0 M KOH. By the X-ray photoelectron spectrum (XPS) analysis, this enhanced performance is ascribe to the in-situ generated Ni/Co oxy(hydroxide) active phase during oxygen evolution reaction. Besides, when further employed as a two-electrode electrolyzer assembly, the holey NiCoS-NS exhibits a low potential of 1.58 V at 20 mA cm−2, serving as one of the best water-splitting electrocatalysts to date. This work not only provides a feasible strategy to develop efficient and durable OER catalysts but also represents a general strategy for the structure-performance relationship of 2D transition metal sulfide electrocatalysts.

In-flight cargo fires are fatal threats to freighter aircraft, and depressurization is one of the main measures for fire suppression. To explore the effects of low pressure on in-flight fire and accurately assess the fire hazard during this emergency situation, liquid pool and cardboard box fire tests were conducted. Depressurization could suppress the cargo fire by reducing the mass burning rate and radiant heat flux but could not put out the fire. For liquid fires, depressurization increases the flame height and elevates the high-temperature region of the flame, resulting in cargo liner burn-through more easily. Depressurization could weaken the burning of the solid fire and eliminate the visible flame but could not eliminate smoldering. Smoldering causes the accumulation of smoke containing high carbon particles and flammable gas and increases the possibility of flashover. For solid fires, the greatest danger exists in the flashover caused by pressure recovery during the landing. Combustion characteristic of the loads and other synergetic fire control measures should be considered simultaneously with the depressurization fire suppression.