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This paper proposes a path-planning method for 3D information collection on the space station surface via the hyper-redundant space robot (HSR). Firstly, to efficiently acquire information on the space station surface, the space station is reduced to a cylindrical model for modelling, and the initial mapping of the temperature field is carried out by a popular Gaussian process. Based on the active information collection method, the collision-free viewpoint trajectory of the space station surface can be planned to improve the efficiency of surface information collection. Then, the path planning of the space station surface information collection can be realized by importing the space station model and temperature field data and performing weight initialization, stochastic search, and continuous optimization. Finally, simulation experiments show that the root-mean-square errors in the surface information collection process are lower than 1 mm relative to the true value. It proves the effectiveness of the online information collection path-planning (IP) method.

Since RF breakdown is one of the primary limitations to improving the performances of RF accelerators, extensive efforts have been dedicated to locating the breakdowns. However, most existing methods rely on specialized techniques, resulting in high financial burdens. Although the method based on transient response of transmission line (TL) is suitable for facilities with sporadic recoverable breakdowns, practical operations are susceptible to notable errors. This study revisits the fundamental theories of lossless TL and investigates the wave process to understand the characteristics of the reversed pulse induced by the breakdowns. By utilizing steady-state response of the TL and employing phasor method, we derive analytical formulas to determine the exact location of breakdowns within the faulty cell for constant-gradient TW accelerator. Furthermore, the derived formulas demonstrate their independence from RF phase, thereby distinguishing them from traditional phase-based methods. Additionally, experimental validations are conducted at the HUST injector, and the results confirm the consistency of the analysis. Thus, the proposed method represents a promising improvement over the TL-based approaches and serves as a valuable complement to current techniques. Importantly, this method demonstrates particular advantages for constructed TW accelerators seeking to achieve a balance among high performance, low costs, and compact layouts.

Collapse is one of the most destructive natural disaster, being sudden, frequent, and highly concealed, causing large-scale damage. On August 10, 2023, the slope of 108 national highway in Weinan, Shaanxi Province collapsed. The lower edge of the collapse slope body is the Luohe river, and the collapse body rushes into the river to form a barrier lake. Remote sensing technique can provide multiple dimensional information for disaster emergency and management. Lutan-1 SAR satellites are the first group L-band SAR constellation for multiple applications in China. Owing to the precise orbit control ability and high revisit characteristics for Lutan-1 SAR satellites, surface deformation monitoring with centimeter even millimeter accuracy may be achieved. Based on the multi-temporal pre-disaster and post-disaster Lutan-1 SAR data and high resolution optical data, the collapse information including the pre-disaster and post-disaster were extracted and analysed. From July 11 to 27, 2023, the pre-collapse deformation was obtained with the maximum value of 6 cm, and obvious deformation occurred before the collapse. Lutan-1 monitored results pre-collapse can provide certain information for disaster early identification. From July 27 to August 24, 2023, due to the serious incoherence caused by large deformation and ground changes, effective deformation information cannot be obtained based on the InSAR technique. In addition, the collapse information was clearly extracted by the high resolution optical data acquired pre-collapse and post collapse. After the collapse, significant deformation was extracted from August 24 to September 21 with the maximum value of 6 cm, indicating that obvious deformation still occurred over the collapse area. Through the analysis for the series results obtained by SAR and optical data, it is favourable for disaster emergency and management.

Intermetallic formation in sludge during magnesium (Mg) melting, holding and high pressure die casting practices is a very important issue. But, very often it is overlooked by academia, original equipment manufacturers (OEM), metal ingot producers and even die casters. The aim of this study was to minimize the intermetallic formation in Mg sludge via the optimization of the chemistry and process parameters. The Al8Mn5 intermetallic particles were identified by the microstructure analysis based on the Al and Mn ratio. The design of experiment (DOE) technique, Taguchi method, was employed to minimize the intermetallic formation in the sludge of Mg alloys with various chemical compositions of Al, Mn, Fe, and different process parameters, holding temperature and holding time. The sludge yield (SY) and intermetallic size (IS) was selected as two responses. The optimum combination of the levels in terms of minimizing the intermetallic formation were 9 wt.% Al, 0.15 wt.%Mn, 0.001 wt.% (10 ppm) Fe, 690 °C for the holding temperature and holding at 30 mins for the holding time, respectively. The best combination for smallest intermetallic size were 9 wt.% Al, 0.15 wt.%Mn, 0.001 wt.% (10 ppm) Fe, 630 °C for the holding temperature and holding at 60 mins for the holding time, respectively. Three groups of sludge factors, Chemical Sludge (CSF), Physical Sludge (PSF) and Comprehensive Sludge Factors (and CPSF) were established for prediction of sludge yields and intermetallic sizes in Al-containing Mg alloys. The CPSF with five independent variables including both chemical elements and process parameters gave high accuracy in prediction, as the prediction of the PSF with only the two processing parameters of the melt holding temperature and time showed a relatively large deviation from the experimental data. The Chemical Sludge Factor was primarily designed for small ingot producers and die casters with a limited melting and holding capacity, of which process parameters could be fixed easily. The Physical Sludge Factor could be used for mass production with a single type of Mg alloy, in which the chemistry fluctuation might be negligible. In large Mg casting suppliers with multiple melting and holding furnaces and a number of Mg alloys in production, the Comprehensive Sludge Factor should be implemented to diminish the sludge formation.

The MIXv2 Asian emission inventory is developed under the framework of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase IV and produced from a mosaic of up-to-date regional emission inventories. We estimated the emissions for anthropogenic and biomass burning sources covering 23 countries and regions in East, Southeast and South Asia and aggregated emissions to a uniform spatial and temporal resolution for seven sectors: power, industry, residential, transportation, agriculture, open biomass burning and shipping. Compared to MIXv1, we extended the dataset to 2010–2017, included emissions of open biomass burning and shipping, and provided model-ready emissions of SAPRC99, SAPRC07, and CB05. A series of unit-based point source information was incorporated covering power plants in China and India. A consistent speciation framework for non-methane volatile organic compounds (NMVOCs) was applied to develop emissions by three chemical mechanisms. The total Asian emissions for anthropogenic/open biomass sectors in 2017 are estimated as follows: 41.6/1.1 Tg NOx, 33.2/0.1 Tg SO2, 258.2/20.6 Tg CO, 61.8/8.2 Tg NMVOC, 28.3/0.3 Tg NH3, 24.0/2.6 Tg PM10, 16.7/2.0 Tg PM2.5, 2.7/0.1 Tg BC (black carbon), 5.3/0.9 Tg OC (organic carbon), and 18.0/0.4 Pg CO2. The contributions of India and Southeast Asia were emerging in Asia during 2010–2017, especially for SO2, NH3 and particulate matter. Gridded emissions at a spatial resolution of 0.1° with monthly variations are now publicly available. This updated long-term emission mosaic inventory is ready to facilitate air quality and climate model simulations, as well as policymaking and associated analyses.

Abstract Geometrically frustrated kagome lattices are raising as novel platforms to engineer correlated topological electron flat bands that are prominent to electronic instabilities. Here, we demonstrate a phonon softening at the k z = π plane in ScV6Sn6. The low energy longitudinal phonon collapses at ~98 K and q = $$\frac{1}{3}\frac{1}{3}\frac{1}{2}$$ 1 3 1 3 1 2 due to the electron-phonon interaction, without the emergence of long-range charge order which sets in at a different propagation vector q CDW = $$\frac{1}{3}\frac{1}{3}\frac{1}{3}$$ 1 3 1 3 1 3 . Theoretical calculations corroborate the experimental finding to indicate that the leading instability is located at $$\frac{1}{3}\frac{1}{3}\frac{1}{2}$$ 1 3 1 3 1 2 of a rather flat mode. We relate the phonon renormalization to the orbital-resolved susceptibility of the trigonal Sn atoms and explain the approximately flat phonon dispersion. Our data report the first example of the collapse of a kagome bosonic mode and promote the 166 compounds of kagomes as primary candidates to explore correlated flat phonon-topological flat electron physics.

This study enhances an existing global hydrological model (GHM), Xanthos, by adding a new water management module that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We remapped reservoirs in the Global Reservoir and Dam (GRanD) database to the 0.5∘ spatial resolution in Xanthos so that a single lumped reservoir exists per grid cell, which yielded 3790 large reservoirs. We implemented unique operation rules for each reservoir type, based on their primary purposes. In particular, hydropower reservoirs have been treated as flood control reservoirs in previous GHM studies, while here, we determined the operation rules for hydropower reservoirs via optimization that maximizes long-term hydropower production. We conducted global simulations using the enhanced Xanthos and validated monthly streamflow for 91 large river basins, where high-quality observed streamflow data were available. A total of 1878 (296 hydropower, 486 irrigation, and 1096 flood control and others) out of the 3790 reservoirs are located in the 91 basins and are part of our reported results. The Kling–Gupta efficiency (KGE) value (after adding the new water management) is ≥ 0.5 and ≥ 0.0 in 39 and 81 basins, respectively. After adding the new water management module, model performance improved for 75 out of 91 basins and worsened for only 7. To measure the relative difference between explicitly representing hydropower reservoirs and representing hydropower reservoirs as flood control reservoirs (as is commonly done in other GHMs), we use the normalized root mean square error (NRMSE) and the coefficient of determination (R2). Out of the 296 hydropower reservoirs, the NRMSE is > 0.25 (i.e., considering 0.25 to represent a moderate difference) for over 44 % of the 296 reservoirs when comparing both the simulated reservoir releases and storage time series between the two simulations. We suggest that correctly representing hydropower reservoirs in GHMs could have important implications for our understanding and management of freshwater resource challenges at regional-to-global scales. This enhanced global water management modeling framework will allow the analysis of future global reservoir development and management from a coupled human–earth system perspective.

The electrical conductivity of gabbroic melt with four different water contents (i.e., 0 %, 2.59 wt %, 5.92 wt %, and 8.32 wt %) was measured at temperatures of 873–1373 K and pressures of 1.0–3.0 GPa using a YJ-3000t multi-anvil high-pressure apparatus and Solartron-1260 impedance spectroscopy analyzer. At a fixed water content of 2.59 wt %, the electrical conductivity of the sample slightly decreased with increasing pressure in the temperature range of 873–1373 K, and its corresponding activation energy and activation volume were determined as 0.87 ± 0.04 eV and −1.98 ± 0.02 cm3 molec.−1, respectively. Under the certain conditions of 873–1373 K and 1.0 GPa, the electrical conductivity of the gabbroic melts tends to gradually increase with a rise in water content from 0 wt % to 8.32 wt %, and the activation enthalpy decreases from 0.93 to 0.63 eV accordingly. Furthermore, functional relation models for the electrical conductivity of gabbroic melts with variations of temperature, pressure, and water content were constructed at high-temperature and high-pressure conditions. In addition, the dependence relation of the electrical conductivity of melts with the degree of depolymerization was explored under conditions of four different water contents at 1373 K and 1.0 GPa, and three previously available reported results on those of representative calc-alkaline igneous rock melts (i.e., dacitic melt, basaltic melt, and andesitic melt) were compared in detail. In combination with our presently acquired electrical conductivity data on gabbroic melt with four different water contents and the available data on polycrystalline olivine, the electrical conductivity of a gabbroic melt–olivine system with variation of the volume percentage of anhydrous and hydrous melts was successfully constructed by using the typical Hashin–Shtrikman upper-bound model. In light of the electrical conductivity of the gabbroic melt–olivine system with previous magnetotelluric (MT) results, we find that anhydrous and hydrous gabbroic melts can be employed to reasonably interpret the high-conductivity anomalies in the Mohns Ridge of the Arctic Ocean.

Nitrate radical (NO3) is an important nocturnal atmospheric oxidant in the troposphere that significantly affects the lifetime of pollutants emitted by anthropogenic and biogenic activities, especially volatile organic compounds (VOCs). Here, we used 1 year of VOC observation data obtained in urban Beijing in 2019 to look into the level, composition, and seasonal variation in NO3 reactivity (kNO3). We show that hourly kNO3 towards measured VOC varied widely from < 10−4 to 0.083 s−1 with a campaign-average value (± standard deviation) of 0.0032 ± 0.0042 s−1. There was large seasonal difference in NO3 reactivity towards VOC with averaged values (± standard deviation) of 0.0024±0.0026 s−1 (spring), 0.0067±0.0066 s−1 (summer), 0.0042±0.0037 s−1 (autumn), and 0.0027±0.0028 s−1 (winter). Alkenes such as isoprene and styrene accounted for the majority. Isoprene was the dominant species in spring, summer, and autumn, accounting for 40.0 %, 77.2 %, and 43.2 %, respectively. Styrene only played a leading role in winter, with a percentage of 39.8 %. A sensitivity study shows monoterpenes, the species we did not measure, may account for a large fraction of kNO3. Based on the correlation between the calculated kNO3 and VOC concentrations in 2019, we established localized parameterization schemes for predicting the reactivity by only using a part of VOC species. The historically published VOC data were collected using the parameterization method to reconstruct the long-term kNO3 in Beijing. The lower kNO3 during 2014–2021 compared with that during 2005–2013 may be attributed to anthropogenic VOC emission reduction. Finally, we revealed that NO3 dominated the nocturnal VOC oxidation, with 83 % of the annual average in Beijing in 2019, which varied seasonally and was strongly regulated by the level of kNO3, nitrogen oxide, and ozone. Our results improve the understanding of nocturnal atmospheric oxidation in urban regions and contribute to our knowledge of nocturnal VOC oxidation and secondary organic pollution.

High-frequency observations of the ice–ocean interaction and high-precision estimation of the ice–ocean heat exchange are critical to understanding the thermodynamics of the landfast ice mass balance in Antarctica. To investigate the oceanic contribution to the evolution of the landfast ice, an integrated ocean observation system, including an acoustic Doppler velocimeter (ADV), conductivity–temperature–depth (CTD) sensors, and a sea ice mass balance array (SIMBA), was deployed on the landfast ice near the Chinese Zhongshan Station in Prydz Bay, East Antarctica, from April to November 2021. The CTD sensors recorded the ocean temperature and salinity. The ocean temperature experienced a rapid increase in late April, from −1.62 to the maximum of −1.30 ∘C, and then it gradually decreased to −1.75 ∘C in May and remained at this temperature until November. The seawater salinity and density exhibited similar increasing trends during April and May, with mean rates of 0.04 psu d−1 and 0.03 kg m−3 d−1, respectively, which was related to the strong salt rejection caused by freezing of the landfast ice. The ocean current observed by the ADV had mean horizontal and vertical velocities of 9.5 ± 3.9 and 0.2 ± 0.8 cm s−1, respectively. The domain current direction was ESE (120∘)–WSW (240∘), and the domain velocity (79 %) was 5–15 cm s−1. The oceanic heat flux (Fw) estimated using the residual method reached a peak of 41.3 ± 9.8 W m−2 in April, and then it gradually decreased to a stable level of 7.8 ± 2.9 W m−2 from June to October. The Fw values calculated using three different bulk parameterizations exhibited similar trends with different magnitudes due to the uncertainties of the empirical friction velocity. The spectral analysis results suggest that all of the observed ocean variables exhibited a typical half-day period, indicating the strong diurnal influence of the local tidal oscillations. The large-scale sea ice distribution and ocean circulation contributed to the seasonal variations in the ocean variables, revealing the important relationship between the large-scale and local phenomena. The high-frequency and cross-seasonal observations of oceanic variables obtained in this study allow us to deeply investigate their diurnal and seasonal variations and to evaluate their influences on the landfast ice evolution.

Dicarboxylic acids are ubiquitous in atmospheric aerosol particles, but their roles as surfactants in cloud condensation nuclei (CCN) activity remain unclear. In this study, we investigated CCN activity of inorganic salt (sodium chloride and ammonium sulfate) and dicarboxylic acid (including malonic acid (MA), phenylmalonic acid (PhMA), succinic acid (SA), phenylsuccinic acid (PhSA), adipic acid (AA), pimelic acid (PA), and octanedioic acid (OA)), mixed particles with varied organic volume fractions (OVFs), and then directly determined their surface tension and phase state at high relative humidity (over 99.5 %) via atomic force microscopy (AFM). Our results show that CCN-derived κCCN of studied dicarboxylic acids ranged from 0.003 to 0.240. A linearly positive correlation between κCCN and solubility was obtained for slightly dissolved species, while negative correlation was found between κCCN and molecular volume for highly soluble species. For most inorganic salts and dicarboxylic acids (MA, PhMA, SA, PhSA and PA), a good closure within 30 % relative bias between κCCN and chemistry-derived κChem was obtained. However, κCCN values of inorganic salt–AA and inorganic salt–OA systems were surprisingly 0.3–3.0 times higher than κChem, which was attributed to surface tension reduction, as AFM results showed that their surface tensions were 20 %–42 % lower than that of water (72 mN m−1). Meanwhile, semisolid phase states were obtained for inorganic salt–AA and inorganic salt–OA and also affected hygroscopicity closure results. Our study highlights that surface tension reduction should be considered when investigating aerosol–cloud interactions.

ABSTRACT: The small intestine is the primary site of nutrient digestion and absorption, which plays a key role in the survival of neonatal calves. A comprehensive assessment of the phosphoproteomic changes in the small intestine of neonatal calves is unavailable; therefore, we used phosphopeptide enrichment coupled with liquid chromatography-tandem mass spectrometry to investigate the changes in the phosphoproteome profile in the bovine small intestine during the first 36 h of life. Twelve neonatal male calves were assigned to one of the following groups: (1) calves not fed colostrum and slaughtered approximately 2 h postpartum (n = 3), (2) calves fed colostrum at 1 to 2 h and slaughtered 8 h postpartum (n = 3), (3) calves fed 2 colostrum meals (at 1–2 and 10–12 h) and slaughtered 24 h postpartum (n = 3), (4) calves fed 3 colostrum meals (at 1–2, 10–12, and 22–24 h) and slaughtered 36 h postpartum (n = 3). Mid-duodenal, jejunal, and ileal samples of the calves were collected after slaughter. We identified 1,678 phosphoproteins with approximately 3,080 phosphosites, which were mainly Ser (89.9%), Thr (9.8%), and Tyr (0.3%) residues; they belonged to the prodirected (52.9%), basic (20.4%), acidic (16.6%), and Tyr-directed (1.7%) motif categories. The regional differentially expressed phosphoproteins included zonula occludens 2, sorting nexin 12, and protein kinase C, which are mainly associated with developmental processes, intracellular transport, vesicle-mediated transport, and immune system process. They are enriched in the endocytosis, tight junction, insulin signaling, and focal adhesion pathways. The temporal differentially expressed phosphoproteins included occludin, epsin 1, and bridging integrator 1, which were mainly associated with macromolecule metabolic process, cell adhesion, and growth. They were enriched in the spliceosomes, adherens junctions, and tight junctions. The observed changes in the phosphoproteins in the tissues of small intestine suggest the protein phosphorylation plays an important role in nutrient transport and immune response of calves during early life, which needs to be confirmed in a larger study.

ABSTRACT: The purposes of this study were (1) to explore the relationship between 3 milk mid-infrared predicted features including nitrogen intake (NINT), milk true protein N (MTPN), and milk urea-N yield (MUNY); (2) to integrate these 3 features into an N efficiency index (NEI) and analyses approximate genetic correlations between the NEI and 37 traits (indices) of interest; and (3) to assess the potential effect of including the NEI into breeding programs of bulls. The edited data were 1,043,171 test-day records on 342,847 cows in 1,931 herds and 143,595 test-day records on 53,660 cows in 766 herds used for estimating breeding values (EBV) and variance components, respectively. The used records were within 5 to 50 d in milk. The records were grouped into primiparous and multiparous. The genetic parameters for the included mid-infrared features and EBV of the animals included in the pedigree were estimated using a multiple-trait repeatability animal model. Then, the EBV of the NINT, MTPN, MUNY were integrated into the NEI using a selection index assuming weights based on the N partitioning. The approximate genetic correlations between the NEI and 37 traits of interest were estimated using the EBV of the selected bulls. The bulls born from 2011 to 2014 with NEI were selected and the NEI distribution of these bulls having EBV for the 8 selected traits (indices) was checked. The heritability and repeatability estimates for NINT, MTPN, and MUNY ranged from 0.09 to 0.13, and 0.37 to 0.65, respectively. The genetic and phenotypic correlations between NINT, MTPN, and MUNY ranged from −0.31 to 0.87, and −0.02 to 0.42, respectively. The NEI ranged from −13.13 to 12.55 kg/d. In total, 736 bulls with reliability ≥0.50 for all included traits (NEI and 37 traits) and at least 10 daughters distributed in at least 10 herds were selected to investigate genetic aspects of the NEI. The NEI had positive genetic correlations with production yield traits (0.08–0.46), and negative genetic correlations with the investigated functional traits and indices (−0.71 to −0.07), except for the production economic index and functional type economic index. The daughters of bulls with higher NEI had lower NINT and MUNY, and higher MTPN. Furthermore, 26% of the bulls (n = 50) with NEI born between 2011 to 2014 had higher NEI and global economic index than the average in the selected bulls. Finally, the developed NEI has the advantage of large-scale prediction and therefore has the potential for routine application in dairy cattle breeding in the future.

Development of lightweight Al alloys with high electrical conductivities, tensile properties and low cost are highly needed for market expansion of battery-powered electric vehicles (BEVs) in the automotive industry and durable transmission lines in the electric power industry (EPI). As an alloying element, Mn has a low maximum solubility of 1.25 wt% in Al under equilibrium solidification and forms Al6Mn dispersoid as a strengthening phase. Manganese (Mn) is usually introduced into wrought Al alloys such as AA3xxx series, because of its capability of improving uniform deformation and strengths of pure aluminum. In this article, the influence of Mn on the electrical and mechanical properties of Al alloys is discussed. The microstructure features and relevant electrical conductivities of Mn-containing Al alloys are reviewed. The strengthening mechanisms of Al alloys are overviewed. The cooling rate-dependent mechanical properties of Al-Mn alloys are presented.

The Australian, Chinese, European, Indian, and North American pulsar timing array (PTA) collaborations recently reported, at varying levels, evidence for the presence of a nanohertz gravitational-wave background (GWB). Given that each PTA made different choices in modeling their data, we perform a comparison of the GWB and individual pulsar noise parameters across the results reported from the PTAs that constitute the International Pulsar Timing Array (IPTA). We show that despite making different modeling choices, there is no significant difference in the GWB parameters that are measured by the different PTAs, agreeing within 1 σ . The pulsar noise parameters are also consistent between different PTAs for the majority of the pulsars included in these analyses. We bridge the differences in modeling choices by adopting a standardized noise model for all pulsars and PTAs, finding that under this model there is a reduction in the tension in the pulsar noise parameters. As part of this reanalysis, we “extended” each PTA’s data set by adding extra pulsars that were not timed by that PTA. Under these extensions, we find better constraints on the GWB amplitude and a higher signal-to-noise ratio for the Hellings–Downs correlations. These extensions serve as a prelude to the benefits offered by a full combination of data across all pulsars in the IPTA, i.e., the IPTA’s Data Release 3, which will involve not just adding in additional pulsars but also including data from all three PTAs where any given pulsar is timed by more than a single PTA.

The currently available long-term snow depth data sets are either from point-scale ground measurements or from gridded satellite/modeled/reanalysis data with coarse spatial resolution, which limits the applications in climate models, hydrological models, and regional snow disaster monitoring. Benefitting from its unique advantages of cost-effective and high spatiotemporal resolution (∼ 1000 m2, hourly in theory), snow depth retrieval using the Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technique has become a popular topic in recent years. However, due to complex environmental and observation conditions, developing robust and operational technology to produce long-term snow depth data sets using observations from various GNSS station networks is still challenging. The two objectives of this study are (1) to propose a comprehensive framework using raw data of the complex GNSS station networks to retrieve snow depth and control its quality automatically; and (2) to produce a long-term snow depth data set over northern China (i.e., GSnow-CHINA v1.0, 12 h or 24 h, 2013–2022) using the proposed framework and historical data from 80 stations. The data set has high internal consistency with regards to different GNSS constellations (mean r=0.98, RMSD = 0.99 cm, and nRMSD (snow depth > 5 cm) = 0.11), different frequency bands (mean r = 0.97, RMSD = 1.46 cm, and nRMSD (snow depth > 5 cm) = 0.16), and different GNSS receivers (mean r = 0.62). The data set also has high external consistency with the in situ measurements and the passive microwave (PMW) product, with a consistent illustration of the interannual snow depth variability. Additionally, the result show the potential of GNSS to derive hourly snow depth observations for better monitoring of snow disasters. The proposed framework to develop the data set provides comprehensive and supportive information for users to process raw data of ground GNSS stations with complex environmental conditions and various observation conditions. The resulting GSnow-CHINA v1.0 data set is distinguished from the current point-scale in situ data or coarse-gridded data, which can be used as an independent data source for validation purposes. The data set is also useful for regional climate research and other meteorological and hydrological applications. The algorithm and data files will be maintained and updated as more data become available in the future. The GSnow-CHINA v1.0 data set is available at the National Tibetan Plateau/Third Pole Environment Data Center via https://doi.org/10.11888/Cryos.tpdc.271839 (Wan et al., 2021).

Introduction: Complex soft tissues, such as knee meniscus, play a crucial role in mobility and joint health but are incredibly difficult to repair and replace when damaged. This difficulty is due to the highly hierarchical and porous nature of the tissues, which, in turn, leads to their unique mechanical properties that provide joint stability, load redistribution, and friction reduction. To design tissue substitutes, the internal architecture of the native tissue needs to be understood and replicated.Methods: We explore a combined audiovisual approach, a so-called transperceptual approach, to generate artificial architectures mimicking the native architectures. The proposed methodology uses both traditional imagery and sound generated from each image to rapidly compare and contrast the porosity and pore size within the samples. We have trained and tested a generative adversarial network (GAN) on 2D image stacks of a knee meniscus. To understand how the resolution of the set of training images impacts the similarity of the artificial dataset to the original, we have trained the GAN with two datasets. The first consists of 478 pairs of audio and image files for which the images were downsampled to 64 × 64 pixels. The second dataset contains 7,640 pairs of audio and image files for which the full resolution of 256 × 256 pixels is retained, but each image is divided into 16 square sections to maintain the limit of 64 × 64 pixels required by the GAN.Results: We reconstructed the 2D stacks of artificially generated datasets into 3D objects and ran image analysis algorithms to characterize the architectural parameters statistically (pore size, tortuosity, and pore connectivity). Comparison with the original dataset showed that the artificially generated dataset based on the downsampled images performs best in terms of parameter matching, achieving between 4% and 8% of the mean of grayscale values of the pixels, mean porosity, and pore size of the native dataset.Discussion: Our audiovisual approach has the potential to be extended to larger datasets to explore how similarities and differences can be audibly recognized across multiple samples.

The roles of microorganisms in enhancing crop production have been demonstrated for a range of cropping systems. Most studies to date, however, have been confined to a limited number of locations, making it difficult to identify general soil biotic and abiotic characteristics underpinning the yield-promotion across various locations. This knowledge gap limits our capacity to harness soil microbiome to improve crop production. Here we used high-throughput amplicon sequencing to investigate the common features of bacterial community composition, ecological networks and physicochemical properties in six yield-invigorating and adjacent yield-debilitating orchards. We found that yield-invigorating soils exhibited higher contents of organic matter than yield-debilitating soils and harbored unique bacterial communities. Greater alpha diversity and higher relative abundances of Planctomycetota and Chloroflexota were observed in yield-debilitating soils. Co-occurrence network analysis revealed that yield-invigorating soils displayed a greater number of functionally interrelated modules (meta-modules) and a higher proportion of negative links to positive links. Chloroflexota was recognized as a keystone taxon in manipulating the interaction of bacterial communities in yield-invigorating soils. Altogether, we provide evidence that yield-invigorating soils across a range of locations appear to share common features, including accumulation of soil organic matter, higher microbial diversity, enrichment of key taxa like Chloroflexota and maintaining a competitive network. These findings have implications for science-based guidance for sustainable food production.

Sludge consisting of heavy element phases and oxides is often generated during the casting operation of aluminum (Al) and magnesium (Mg) alloys. With the help of the well-established Sludge Factor (SF) formula, it is relatively easy to control the sludge generation in aluminum alloys. But formation mechanisms and characteristics of sludge in die casting magnesium alloys are still unclear. To ensure the production of high quality die cast components at a low cost, a full understanding of sludge in die casting Mg alloys and its proper control measures need to be developed, since excessive sludge formation affects deleteriously material and operation cost, and casting performance. In the present report, the formation, characteristics and control of Mg die-casting sludge, based on the established knowledge of sludge formation and sludge factor in Al die casting alloys, are reviewed. Previous work on characterization and assessment of sludge in die cast Mg alloys are reviewed. Metallurgical principles for control of sludge in ingot production in association with die casting of Mg alloys are discussed. Rapid assessment of Mg oxide and intermetallics relevant to sludge formation in Mg alloys are highlighted.

Large-scale Digital Surface Model (DSM) generated with high-resolution satellite images (HRSI) are comparable, cheaper, and more accessible when comparing to Light Detection and Ranging (LiDAR) data and aerial remotely sensed images. Several photogrammetric commercial/open-source software packages are being developed for satellite image-based 3D reconstruction, in which, most of them adopt a modified version of Semi-Global Matching (SGM) algorithm for dense image matching. With the continuous development of matching cost computation methods, the existing methods can be divided into classical (low-level) and learning-based algorithms (non-end-to-end learning and end-to-end learning methods). On Middlebury and KITTI datasets, learning-based algorithms has shown their superiority compared to SGM derived methods. In this context, we assume that matching cost is the key factor of DIM. This paper reviews and evaluates Census Transform, and MC-CNN on a WorldView-3 typical city scene satellite stereo images on the premise that the overall SGM framework remains unchanged, providing a preliminary comparison for academic and industrial. We first compute the cost valume of these two methods, obtains the final DSM after semi-global optimization, and compares their gemetric accuracy with the corresponding LiDAR derived ground truth. We presented our comparison and findings in the experimental section.

The purpose of this work is to investigate transient aerodynamic characteristics of the coach under the crosswind in straight-line situations with different uniform speeds and uniform accelerations. The transient aerodynamics caused by different speed changes are analyzed using the real-time interaction between aerodynamic simulation and dynamic simulation. The target model is a simplified coach on a full scale. The SST (Menter) K-Omega Improved Delayed Detached Eddy Simulation and overset mesh technique are used to predict the transient aerodynamic loads. The accuracy of the turbulence model is verified by a wind tunnel experiment of the 1/7th scaled coach model. The present results show that the transient aerodynamic loads have different locations of maximum side force and the holding duration of yaw moment for different constant speeds. The speed becomes larger, and the position where the side force is maximum becomes farther away. The holding duration of the top yaw moment is larger simultaneously. Moreover, proper acceleration for low initial driving speed and crosswind of small influence range could build up stability. High speed driving in gust wind is not suggested for unskilled drivers.

The paper describes the modelling and the subsequent implementation of an integrated system that consists of a composite material microstructure and its Material Twin (MT). The developed MT is based on statistical continuum theory and probability functions. The MT is used to reproduce/reconstruct 3D porous composite material microstructures, to simulate the multi-physical behaviour of this composite material system and to design desired anisotropic 3D microstructures. To correlate the effective physical properties of a composite material system to its microstructure, we use probability functions in conjunction with the strong-contrast formulation. A practical use case dealing with porous materials demonstrates the versatile advantages of the implemented approach with respect to its prediction and design capabilities.

Terrestrial Laser scanner has been widely used in the field of forestry. Wood-leaf separation is the fundamental step to most applications of forestry. This paper presented a robust supervised learning method for wood and leaf classification by developing four new feature vectors. Fractal dimension is first calculated to indicate the difference of regularity or roughness between wood and leaf. Zenith angle and variation are presented to distinguish trunks or branches from leaves. The adaptive axis direction of cylinder is adopted to calculate the local point density precisely. Experimental results show that the supervised learning method using the four feature vectors presented in this paper can achieve a good classification performance. Both accuracy and F1 score are higher than the ones of the method using eigen value based feature vectors.

Regularized arrangement of primitives on building façades to aligned locations and consistent sizes is important towards structured reconstruction of urban environment. Mixed integer linear programing was used to solve the problem, however, it is extremely time consuming even for state-of-the-art commercial solvers. Aiming to alleviate this issue, we cast the problem into binary integer programming, which omits the requirements for real value parameters and is more efficient to be solved. Firstly, the bounding boxes of the primitives are detected using the YOLOv3 architecture in real-time. Secondly, the coordinates of the upper left corners and the sizes of the bounding boxes are automatically clustered in a binary integer programming optimization, which jointly considers the geometric fitness, regularity and additional constraints; this step does not require a priori knowledge, such as the number of clusters or pre-defined grammars. Finally, the regularized bounding boxes can be directly used to guide the façade reconstruction in an interactive environment. Experimental evaluations have revealed that the accuracies for the extraction of primitives are above 0.82, which is sufficient for the following 3D reconstruction. The proposed approach only takes about 10% to 20% of the runtime than previous approach and reduces the diversity of the bounding boxes to about 20% to 50%.

Abstract Background Health-care professionals need to collect wound samples to identify potential pathogens that contribute to wound infection. Obtaining appropriate samples from diabetic foot ulcers (DFUs) where there is a suspicion of infection is of high importance. Paired swabs and tissue biopsies were collected from DFUs and both sampling techniques were compared using 16S rRNA gene sequencing. Results Mean bacterial abundance determined using quantitative polymerase chain reaction (qPCR) was significantly lower in tissue biopsies (p = 0.03). The mean number of reads across all samples was significantly higher in wound swabs ( X ¯ $$ \Big(\overline{X} $$ = 32,014) compared to tissue ( X ¯ $$ \overline{X} $$ = 15,256, p = 0.001). Tissue biopsies exhibited greater overall diversity of bacteria relative to swabs (Shannon’s H diversity p = 0.009). However, based on a presence/absence analysis of all paired samples, the frequency of occurrence of bacteria from genera of known and potential pathogens was generally higher in wound swabs than tissue biopsies. Multivariate analysis identified significantly different bacterial communities in swabs compared to tissue (p = 0.001). There was minimal correlation between paired wound swabs and tissue biopsies in the number and types of microorganisms. RELATE analysis revealed low concordance between paired DFU swab and tissue biopsy samples (Rho = 0.043, p = 0.34). Conclusions Using 16S rRNA gene sequencing this study identifies the potential for using less invasive swabs to recover high relative abundances of known and potential pathogen genera from DFUs when compared to the gold standard collection method of tissue biopsy.

Microbial stoichiometry and its potential driving factors play crucial roles in understanding the balance of chemical elements in ecological interactions and nutrient limitations along the aridity gradient. However, little is known about the variation in these features along the aridity gradient due to the lack of comprehensive field investigations. Additionally, previous studies focused on the topsoil (0–10 or 0–20 cm); however, the minimum sampling depth for topsoil could impact the results of the vertical distribution of microbial stoichiometry. In the present study, we measured the variation in microbial stoichiometry, examined the major influential factors (climatic, edaphic, and biotic factors) along an aridity gradient, and determined whether the sampling depth affected microbial C : N : P stoichiometry. From the topsoil to the subsoil, the microbial C : N, C : P, and N : P ratios varied from 6.59 to 6.83, from 60.2 to 60.5, and from 9.29 to 8.91, respectively. Only the microbial C : N ratio significantly increased with soil depth. The microbial C : N ratio significantly increased with increasing aridity in both topsoil and subsoil, while the microbial N : P ratio decreased along the aridity gradient only for the topsoil. This result implied that drought-stimulated microbes tend to be more N conservative, especially those in topsoil. Among all the factors, the soil organic carbon (SOC) content and the fungi-to-bacteria ratio exerted the largest influence on the microbial C : N, C : P, and N : P ratios at both soil depths, implying that the substrate supply and microbial structure together controlled the microbial stoichiometry. The results also revealed that the aridity index (AI) and plant aboveground biomass (AGB) exerted negative impacts on the microbial C : N ratio at both soil depths, and the effects of AI decreased in the subsoil. The results of this study suggested that the flexibility of the microbial N : P ratio should be considered when establishing the sampling depth for microbial stoichiometry study.

Abstract Accurate glacial isostatic adjustment (GIA) models are required for correcting measurements of mass change in Antarctica and for improving knowledge of the sub‐surface, especially in areas of large current ice loss such as the Amundsen Sea Embayment (ASE). Regionally, seismic and gravity data suggests lateral differences in viscosity (3D). Furthermore, mantle flow laws allow for a stress‐dependent effective viscosity which changes over time (3D‐s). In this study we investigate whether models with 3D/3D‐s have significant effects on the uplift in the region. We use a finite element model with composite rheology consisting of diffusion and dislocation creep, forced by an ice deglaciation model starting in 1900. We use its uplift predictions as synthetic observations to test the performance of 1D model inversion in the presence of viscosity variations. Stress‐dependent rheology results in lower viscosity beneath the load and a more localized uplift pattern. We demonstrate that the background stress from earlier ice load changes can both increase or decrease the influence of stress‐induced effective viscosity changes. For the ASE, fitting 1D models to 3D model uplift results in a best fitting model with viscosity that represents the average of a large area, while for 3D‐s rheology, local viscosity is more influential. 1D models are statistically indistinguishable from 3D/3D‐s viscosity with current GPS stations. However, 3D and 3D‐s models should be taken into account when accurate uplift and gravity rate patterns are needed, as uplift can differ up to 45% compared to 1D models in between existing GPS stations.

Venom peptides are potent and selective modulators of voltage-gated ion channels that regulate neuronal function both in health and in disease. We previously identified the spider venom peptide Tap1a from the Venezuelan tarantula Theraphosa apophysis that targeted multiple voltage-gated sodium and calcium channels in visceral pain pathways and inhibited visceral mechano-sensing neurons contributing to irritable bowel syndrome. In this work, alanine scanning and domain activity analysis revealed Tap1a inhibited sodium channels by binding with nanomolar affinity to the voltage-sensor domain II utilising conserved structure-function features characteristic of spider peptides belonging to family NaSpTx1. In order to speed up the development of optimized NaV-targeting peptides with greater inhibitory potency and enhanced in vivo activity, we tested the hypothesis that incorporating residues identified from other optimized NaSpTx1 peptides into Tap1a could also optimize its potency for NaVs. Applying this approach, we designed the peptides Tap1a-OPT1 and Tap1a-OPT2 exhibiting significant increased potency for NaV1.1, NaV1.2, NaV1.3, NaV1.6 and NaV1.7 involved in several neurological disorders including acute and chronic pain, motor neuron disease and epilepsy. Tap1a-OPT1 showed increased potency for the off-target NaV1.4, while this off-target activity was absent in Tap1a-OPT2. This enhanced potency arose through a slowed off-rate mechanism. Optimized inhibition of NaV channels observed in vitro translated in vivo, with reversal of nocifensive behaviours in a murine model of NaV-mediated pain also enhanced by Tap1a-OPT. Molecular docking studies suggested that improved interactions within loops 3 and 4, and C-terminal of Tap1a-OPT and the NaV channel voltage-sensor domain II were the main drivers of potency optimization. Overall, the rationally designed peptide Tap1a-OPT displayed new and refined structure-function features which are likely the major contributors to its enhanced bioactive properties observed in vivo. This work contributes to the rapid engineering and optimization of potent spider peptides multi-targeting NaV channels, and the research into novel drugs to treat neurological diseases.

Passive remote sensing of atmospheric carbon dioxide uses spectroscopic measurements of sunlight backscattered by the Earth's surface and atmosphere. The current state-of-the-art retrieval methods use three different spectral bands, the oxygen A band at 0.76 µm and the weak and strong CO2 absorption bands at 1.61 and 2.06 µm, respectively, to infer information on light scattering and the carbon dioxide column-averaged dry-air mole fraction XCO2. In this study, we propose a one-band XCO2 retrieval technique which uses only the 2.06 µm band measurements from the Orbiting Carbon Observatory-2 (OCO-2) satellite. We examine the data quality by comparing the OCO-2 XCO2 with collocated ground-based measurements from the Total Carbon Column Observing Network (TCCON). Over land and ocean the OCO-2 one-band retrieval shows differences from TCCON observations with a standard deviation of ∼1.30 ppm and a station-to-station variability of ∼0.50 ppm. Moreover, we compare one-band and three-band retrievals over Europe, the Middle East, and Africa and see high correlation between the two retrievals with a SD of 0.93 ppm. Compared to the three-band retrievals, XCO2 retrievals using only the 2.06 µm band have similar retrieval accuracy, precision, and data yield.

Retrievals of methane isotopologues have the potential to differentiate between natural and anthropogenic methane sources types, which can provide much needed information about the current global methane budget. We investigate the feasibility of retrieving the second most abundant isotopologue of atmospheric methane (13CH4, roughly 1.1 % of total atmospheric methane) from the shortwave infrared (SWIR) channels of the future Sentinel-5/ultra-violet, visible, near-infrared, shortwave infrared (UVNS) and current Copernicus Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI) instruments. With the intended goal of calculating the δ13C value, we assume that a δ13C uncertainty of better than 1 ‰ is sufficient to differentiate between source types, which corresponds to a 13CH4 uncertainty of  ppb. Using the well-established information content analysis techniques and assuming clear-sky, non-scattering conditions, we find that the SWIR3 (2305–2385 nm) channel on the TROPOMI instrument can achieve a mean uncertainty of  ppb, while the SWIR1 channel (1590–1675 nm) on the Sentinel-5 UVNS instrument can achieve  ppb or  ppb in high signal-to-noise ratio (SNR) cases. These uncertainties combined with significant spatial and/or temporal averaging techniques can reduce δ13C uncertainty to the target magnitude or better. However, we find that 13CH4 retrievals are highly sensitive to errors in a priori knowledge of temperature and pressure, and accurate knowledge of these profiles is required before 13CH4 retrievals can be performed on TROPOMI and future Sentinel-5/UVNS data. In addition, we assess the assumption that scattering-induced light path errors are cancelled out by comparing the δ13C values calculated for non-scattering and scattering scenarios. We find that there is a minor bias in δ13C values from scattering and non-scattering retrievals, but this is unrelated to scattering-induced errors.

Base on January and July 4-times daily ECMWF Interim data from 2009 to 2018 over the Northeast Sphere (0–180E,0–90N), the condensed moisture profile of experiential methods and that of ECMWF analysis are compared. The result shows that, the meridional-height distribution of mean cloud condensed moisture has a maximum slab spreading near ground in the Arctic region in July, and the maximum takes a circular shape at 700 hPa above 30N latitude in January. The distribution feature unlike the universal profile, it distributes in a single or double peak function manner, instead of a constant value. The quick decreasing level height and thickness varies with latitude, especially in January. The second experiential profile concerning warm cloud assumes air parcel lifting adiabatically, the liquid water path (LWP) is compared for general information. The result shows that the experiential LWP is much larger than that of the reanalysis by 1 to 2 order, decreasing with latitudes. The possible reason of LWP difference is from the critic water content value of cloud boundary identification. If the value is small, the thickness of warm cloud will be large, temperature and pressure at the cloud base are both large too, results in a larger LWP. These results will enrich the knowledge of the condensed moisture characteristics of ECMWF reanalysis and the experiential moisture profile methods.

Mineralization potential is a key property for assessing carbon substrate's degradability and mineralization in biogeochemical models and studies. While mineralization potential is widely examined under controlled conditions, whether and how it is influenced by the past aridity of sample's origins remain poorly constrained, which is important for an accurate assessment and prediction of future CO2 emissions. Here we collect topsoils and subsoils from different aridity regimes along a 2100 km grassland transect of northern China and conduct a 91 d decomposition experiment with and without the addition of 13C-labeled leaf litter under controlled temperature and moisture. CO2 release from both soil organic carbon (SOC) and fresh litter is measured, along with microbial biomass, extracellular enzyme activities, and soil and mineral properties. We find that neither microbial carbon use efficiency nor biomass-normalized metabolic quotient (qCO2) is related to the aridity of sampling sites. However, both fresh litter and SOC display the highest mineralization potentials in soils originating from the driest site. Using pathway analysis, we demonstrate that past aridity's effect is mediated by differential mechanisms for substrates of varied complexity. While microbial biomass plays a more important role in the decomposition of fresh litter, enzyme-catalyzed extracellular reactions predominantly govern the mineralization of SOC. Our findings provide novel evidence on the mechanisms underlying past aridity's effect on the mineralization potentials of organic matter with different qualities, which has significant implications for assessing and modeling decomposition in different aridity regimes.

Denoising is a key pre-processing step for many airborne LiDAR point cloud applications. However, the previous algorithms have a number of problems, which affect the quality of point cloud post-processing, such as DTM generation. In this paper, a novel automated denoising algorithm is proposed based on empirical mode decomposition to remove outliers from airborne LiDAR point cloud. Comparing with traditional point cloud denoising algorithms, the proposed method can detect outliers from a signal processing perspective. Firstly, airborne LiDAR point clouds are decomposed into a series of intrinsic mode functions with the help of morphological operations, which would significantly decrease the computational complexity. By applying OTSU algorithm to these intrinsic mode functions, noise-dominant components can be detected and filtered. Finally, outliers are detected automatically by comparing observed elevations and reconstructed elevations. Three datasets located at three different cities in China were used to verify the validity and robustness of the proposed method. The experimental results demonstrate that the proposed method removes both high and low outliers effectively with various terrain features while preserving useful ground details.

Planetary remote sensing images are the primary datasets for high-resolution topographic mapping and modeling of the planetary surfaces. However, unlike the mapping satellites for Earth observations, cameras onboard the planetary satellites generally present special imaging geometries and configurations, which makes the stereo photogrammetric process difficult and requires a large number of manual interactions. At the Hong Kong Polytechnic University, we developed a unified photogrammetric software system, namely Planetary3D, for 3D topographic mapping modeling of various planetary bodies using images collected by various sensors. Planetary3D consists of three modules, including: (1) the pre-processing module to deliver standardized image products, (2) the bundle adjustment module to alleviate the inconsistencies between the images and possibly the reference frame, and (3) the dense image matching module to create pixel-wise image matches and produce high quality topographic models. Examples of using three changeling datasets, including the MRO CTX, MRO HiRISE and Chang’E-2 images, have revealed that the automatic pipeline of Planetary3D can produce high-quality digital elevation models (DEMs) with favorable performances. Notably, the notorious jitter effects visible on HiRISE images can be effectively removed and good consistencies with the reference DEMs are found for the test datasets by the Planetary3D pipeline.

In this study, medium-carbon steel was subjected to warm deformation experiments on a Gleeble 3500 thermosimulator machine at temperatures of 550°C and 650°C and strain rates of 0.001 s–1 to 1 s–1. The warm deformation behavior of martensite and the effects of strain rate on the microstructure of ultrafine grained medium-carbon steel were investigated. The precipitation behavior of Fe3C during deformation was analyzed and the results showed that recrystallization occurred at a low strain rate. The average ultrafine ferrite grains of 500 ± 58 nm were fabricated at 550°C and a strain rate of 0.001 s–1. In addition, the size of Fe3C particles in the ferrite grains did not show any apparent change, while that of the Fe3C particles at the grain boundaries was mainly affected by the deformation temperature. The size of Fe3C particles increased with the increasing deformation temperature, while the strain rate had no significant effect on Fe3C particles. Moreover, the grain size of recrystallized ferrite decreased with an increase in the strain rate. The effects of the strain rate on the grain size of recrystallized ferrite depended on the deformation temperature and the strain rate had a prominent effect on the grain size at 550°C deformation temperature. Finally, the deformation resistance apparently decreased at 550°C and strain rate of 1 s–1 due to the maximum adiabatic heating in the material.

We detail a method to produce a GeV-photon source with polarisation degree exceeding 91% and 78% (corresponding to a 96% and 89% fraction of the photons) for linear and circular polarised photons respectively and with a brilliance of the order of 1021photons/(smm2mrad20.1%BW). Using currently available multi-GeV electron bunches and laser pulses of moderately relativistic intensities, we show how the weakly nonlinear regime can produce photons polarised mainly parallel to the laser field. We demonstrate the robustness of this scheme by considering electron bunches of various emissivities colliding with linearly and circularly-polarised laser pulses at a range of angles.

Current treatments have limited effectiveness in treating tumors. The combination of multiple drugs or treatment strategies is widely studied to improve therapeutic effect and reduce adverse effects of cancer therapy. The codelivery system is the key to realize combined therapies. It is necessary to design and construct different codelivery systems in accordance with the variable structures and properties of cargoes and vectors. This review presented the typical design considerations about codelivery vectors for cancer therapy and described the current state of codelivery systems from two aspects: different types of vectors and collaborative treatment strategies. The commonly used loading methods of cargoes into the vectors, including physical and chemical processes, are discussed in detail. Finally, we outline the challenges and perspectives about the improvement of codelivery systems.

On 13 October 2017, the European Space Agency (ESA) successfully launched the Sentinel-5 Precursor satellite with the Tropospheric Monitoring Instrument (TROPOMI) as its single payload. TROPOMI is the first of ESA's atmospheric composition Sentinel missions, which will provide complete long-term records of atmospheric trace gases for the coming 30 years as a contribution to the European Union's Earth Observing program Copernicus. One of TROPOMI's primary products is atmospheric carbon monoxide (CO). It is observed with daily global coverage and a high spatial resolution of 7×7 km2. The moderate atmospheric resistance time and the low background concentration leads to localized pollution hotspots of CO and allows the tracking of the atmospheric transport of pollution on regional to global scales. In this contribution, we demonstrate the groundbreaking performance of the TROPOMI CO product, sensing CO enhancements above cities and industrial areas and tracking, with daily coverage, the atmospheric transport of pollution from biomass burning regions. The CO data product is validated with two months of Fourier-transform spectroscopy (FTS) measurements at nine ground-based stations operated by the Total Carbon Column Observing Network (TCCON). We found a good agreement between both datasets with a mean bias of 6 ppb (average of individual station biases) for both clear-sky and cloudy TROPOMI CO retrievals. Together with the corresponding standard deviation of the individual station biases of 3.8 ppb for clear-sky and 4.0 ppb for cloudy sky, it indicates that the CO data product is already well within the mission requirement.

A new data set of vertical column densities of the water vapour isotopologues H2O and HDO from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument for the whole of the mission period from January 2003 to April 2012 is presented. The data are retrieved from reflectance measurements in the spectral range 2339 to 2383 nm with the Shortwave Infrared CO Retrieval (SICOR) algorithm, ignoring atmospheric light scattering in the measurement simulation. The retrievals are validated with ground-based Fourier transform infrared measurements obtained within the Multi-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) project. A good agreement for low-altitude stations is found with an average bias of −3.6×1021 for H2O and −1.0×1018 molec cm−2 for HDO. The a posteriori computed δD shows an average bias of −8 ‰, even though polar stations have a larger negative bias. The latter is due to the large amount of sensor noise in SCIAMACHY in combination with low albedo and high solar zenith angles. To demonstrate the benefit of accounting for light scattering in the retrieval, the quality of the data product fitting effective cloud parameters simultaneously with trace gas columns is evaluated in a dedicated case study for measurements round high-altitude stations. Due to a large altitude difference between the satellite ground pixel and the mountain station, clear-sky scenes yield a large bias, resulting in a δD bias of 125 ‰. When selecting scenes with optically thick clouds within 1000 m above or below the station altitude, the bias in a posteriori δD is reduced from 125 to 44 ‰. The insights from the present study will also benefit the analysis of the data from the new Sentinel-5 Precursor mission.

In the perspective of the upcoming TROPOMI Sentinel-5 Precursor carbon monoxide data product, we discuss the benefit of using CO total column retrievals from cloud-contaminated SCIAMACHY 2.3 µm shortwave infrared spectra to detect atmospheric CO enhancements on regional and urban scales due to emissions from cities and wildfires. The study uses the operational Sentinel-5 Precursor algorithm SICOR, which infers the vertically integrated CO column together with effective cloud parameters. We investigate its capability to detect localized CO enhancements distinguishing between clear-sky observations and observations with low (

In this study we present the retrieval of the column-averaged dry air mole fraction of carbon dioxide (XCO2) from the Orbiting Carbon Observatory-2 (OCO-2) satellite observations using the RemoTeC algorithm, previously successfully applied to retrieval of greenhouse gas concentration from the Greenhouse Gases Observing Satellite (GOSAT). The XCO2 product has been validated with collocated ground-based measurements from the Total Carbon Column Observing Network (TCCON) for almost 2 years of OCO-2 data from September 2014 to July 2016. We found that fitting an additive radiometric offset in all three spectral bands of OCO-2 significantly improved the retrieval. Based on a small correlation of the XCO2 error over land with goodness of fit, we applied an a posteriori bias correction to our OCO-2 retrievals. In overpass averaged results, XCO2 retrievals have an SD of ∼ 1.30 ppm and a station-to-station variability of ∼ 0.40 ppm among collocated TCCON sites. The seasonal relative accuracy (SRA) has a value of 0.52 ppm. The validation shows relatively larger difference with TCCON over high-latitude areas and some specific regions like Japan.

Plastic film mulching (PFM) has widely been used around the world to save water and improve crop yield. However, the effect of PFM on soil respiration (Rs) remains unclear and could be further confounded by irrigation and precipitation. To address these topics, controlled experiments were conducted in mulched and non-mulched fields under drip irrigation from 2014 to 2016 in an arid area of the Xinjiang Uygur Autonomous Region, northwest China. The spatio-temporal pattern of soil surface CO2 flux as an index of soil respiration under drip irrigation with PFM was investigated, and the confounded effects of PFM and irrigation/precipitation on soil respiration were explored. The main findings were as follows. (1) Furrows, planting holes, and plastic mulch are three important pathways of soil CO2 emissions in mulched fields, of which the planting hole efflux outweighs that from the furrow, with the largest values of 8.0 and 6.6 µmol m−2 s−1, respectively, and the plastic mulch itself can emit up to 3.6 µmol m−2 s−1 of CO2. (2) The frequent application of water (i.e. through irrigation and precipitation) elevates soil moisture and soil respiration and enhances their variation. The resultant higher variation of soil moisture further alleviates the sensitivity of soil respiration to soil temperature, leading to a weak correlation and lower Q10 values. (3) Soil CO2 effluxes from furrows and ridges in mulched fields outweigh the corresponding values in non-mulched fields in arid areas. However, this outweighing relation attenuates with increasing precipitation. Furthermore, by combining our results with those from the literature, we show that the difference in soil CO2 effluxes between non-mulched and mulched fields presents a linear relation with the amount of precipitation, which results in negative values in arid areas and positive values in humid areas. Therefore, whether PFM increases soil respiration or not depends on the amount of precipitation during the crop-growing season.

The electrical conductivity of gneiss samples with different chemical compositions (WA = Na2O + K2O + CaO = 7.12, 7.27 and 7.64 % weight percent) was measured using a complex impedance spectroscopic technique at 623–1073 K and 1.5 GPa and a frequency range of 10−1 to 106 Hz. Simultaneously, a pressure effect on the electrical conductivity was also determined for the WA = 7.12 % gneiss. The results indicated that the gneiss conductivities markedly increase with total alkali and calcium ion content. The sample conductivity and temperature conform to an Arrhenius relationship within a certain temperature range. The influence of pressure on gneiss conductivity is weaker than temperature, although conductivity still increases with pressure. According to various ranges of activation enthalpy (0.35–0.52 and 0.76–0.87 eV) at 1.5 GPa, two main conduction mechanisms are suggested that dominate the electrical conductivity of gneiss: impurity conduction in the lower-temperature region and ionic conduction (charge carriers are K+, Na+ and Ca2+) in the higher-temperature region. The electrical conductivity of gneiss with various chemical compositions cannot be used to interpret the high conductivity anomalies in the Dabie–Sulu ultrahigh-pressure metamorphic belt. However, the conductivity–depth profiles for gneiss may provide an important constraint on the interpretation of field magnetotelluric conductivity results in the regional metamorphic belt.

Atmospheric rivers (ARs) account for more than 75 % of heavy precipitation events and nearly all of the extreme flooding events along the Olympic Mountains and western Cascade Mountains of western Washington state. In a warmer climate, ARs in this region are projected to become more frequent and intense, primarily due to increases in atmospheric water vapor. However, it is unclear how the changes in water vapor transport will affect regional flooding and associated economic impacts. In this work we present an integrated modeling system to quantify the atmospheric–hydrologic–hydraulic and economic impacts of the December 2007 AR event that impacted the Chehalis River basin in western Washington. We use the modeling system to project impacts under a hypothetical scenario in which the same December 2007 event occurs in a warmer climate. This method allows us to incorporate different types of uncertainty, including (a) alternative future radiative forcings, (b) different responses of the climate system to future radiative forcings and (c) different responses of the surface hydrologic system. In the warming scenario, AR integrated vapor transport increases; however, these changes do not translate into generalized increases in precipitation throughout the basin. The changes in precipitation translate into spatially heterogeneous changes in sub-basin runoff and increased streamflow along the entire Chehalis main stem. Economic losses due to stock damages increase moderately, but losses in terms of business interruption are significant. Our integrated modeling tool provides communities in the Chehalis region with a range of possible future physical and economic impacts associated with AR flooding.

A new 3-D tracer tool is coupled to the WRF model to analyze the origin of the moisture in two extreme atmospheric river (AR) events: the so-called Great Coastal Gale of 2007 in the Pacific Ocean and the Great Storm of 1987 in the North Atlantic. Results show that between 80 and 90 % of moisture advected by the ARs, and a high percentage of the total precipitation produced by the systems have a tropical origin. The tropical contribution to precipitation is in general above 50 % and largely exceeds this value in the most affected areas. Local convergence transport is responsible for the remaining moisture and precipitation. The ratio of tropical moisture to total moisture is maximized as the cold front arrives on land. Vertical cross sections of the moisture content suggest that the maximum in tropical humidity does not necessarily coincide with the low-level jet (LLJ) of the extratropical cyclone. Instead, the amount of tropical humidity is maximized in the lowest atmospheric level in southern latitudes and can be located above, below or ahead of the LLJ in northern latitudes in both analyzed cases.

The Narrow-Angle Camera (NAC) on board the Lunar Reconnaissance Orbiter (LRO) comprises of a pair of closely attached high-resolution push-broom sensors, in order to improve the swath coverage. However, the two image sensors do not share the same lenses and cannot be modelled geometrically using a single physical model. Thus, previous works on dense matching of stereo pairs of NAC images would generally create two to four stereo models, each with an irregular and overlapping region of varying size. Semi-Global Matching (SGM) is a well-known dense matching method and has been widely used for image-based 3D surface reconstruction. SGM is a global matching algorithm relying on global inference in a larger context rather than individual pixels to establish stable correspondences. The stereo configuration of LRO NAC images causes severe problem for image matching methods such as SGM, which emphasizes global matching strategy. Aiming at using SGM for image matching of LRO NAC stereo pairs for precision 3D surface reconstruction, this paper presents a coupled epipolar rectification methods for LRO NAC stereo images, which merges the image pair in the disparity space and in this way, only one stereo model will be estimated. For a stereo pair (four) of NAC images, the method starts with the boresight calibration by finding correspondence in the small overlapping stripe between each pair of NAC images and bundle adjustment of the stereo pair, in order to clean the vertical disparities. Then, the dominate direction of the images are estimated by project the center of the coverage area to the reference image and back-projected to the bounding box plane determined by the image orientation parameters iteratively. The dominate direction will determine an affine model, by which the pair of NAC images are warped onto the object space with a given ground resolution and in the meantime, a mask is produced indicating the owner of each pixel. SGM is then used to generate a disparity map for the stereo pair and each correspondence is transformed back to the owner and 3D points are derived through photogrammetric space intersection. Experimental results reveal that the proposed method is able to reduce gaps and inconsistencies caused by the inaccurate boresight offsets between the two NAC cameras and the irregular overlapping regions, and finally generate precise and consistent 3D surface models from the NAC stereo images automatically.

We used next generation DNA sequencing to profile the microbiome of infected Diabetic Foot Ulcers (DFUs). The microbiota was correlated to clinical parameters and treatment outcomes to determine if directed antimicrobial therapy based on conventional microbiological cultures are relevant based on genomic analysis. Patients ≥ 18 years presenting with a new Diabetic Foot Infection (DFI) who had not received topical or oral antimicrobials in the two weeks prior to presentation, were eligible for enrolment. Tissue punch biopsies were obtained from infected DFUs for analysis. Demographics, clinical and laboratory data were collected and correlated against microbiota data. Thirty-nine patients with infected DFUs were recruited over twelve-months. Shorter duration DFUs (