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Abstract Pathological complete response (pCR) serves as a critical measure of the success of neoadjuvant chemotherapy (NAC) in breast cancer, directly influencing subsequent therapeutic decisions. With the continuous advancement of artificial intelligence, methods for early and accurate prediction of pCR are being extensively explored. In this study, we propose a cross-modal multi-pathway automated prediction model that integrates temporal and spatial information. This model fuses digital pathology images from biopsy specimens and multi-temporal ultrasound (US) images to predict pCR status early in NAC. The model demonstrates exceptional predictive efficacy. Our findings lay the foundation for developing personalized treatment paradigms based on individual responses. This approach has the potential to become a critical auxiliary tool for the early prediction of NAC response in breast cancer patients.

Abstract Background Perihematomal edema (PHE) after post-intracerebral hemorrhage (ICH) has complex pathophysiological mechanisms that are poorly understood. The complicated immune response in the post-ICH brain constitutes a crucial component of PHE pathophysiology. In this study, we aimed to characterize the transcriptional profiles of immune cell populations in human PHE tissue and explore the microscopic differences between different types of immune cells. Methods 9 patients with basal ganglia intracerebral hemorrhage (hematoma volume 50-100 ml) were enrolled in this study. A multi-stage profile was developed, comprising Group1 (n = 3, 0–6 h post-ICH, G1), Group2 (n = 3, 6–24 h post-ICH, G2), and Group3 (n = 3, 24–48 h post-ICH, G3). A minimal quantity of edematous tissue surrounding the hematoma was preserved during hematoma evacuation. Single cell RNA sequencing (scRNA-seq) was used to map immune cell populations within comprehensively resected PHE samples collected from patients at different stages after ICH. Results We established, for the first time, a comprehensive landscape of diverse immune cell populations in human PHE tissue at a single-cell level. Our study identified 12 microglia subsets and 5 neutrophil subsets in human PHE tissue. What’s more, we discovered that the secreted phosphoprotein-1 (SPP1) pathway served as the basis for self-communication between microglia subclusters during the progression of PHE. Additionally, we traced the trajectory branches of different neutrophil subtypes. Finally, we also demonstrated that microglia-produced osteopontin (OPN) could regulate the immune environment in PHE tissue by interacting with CD44-positive cells. Conclusions As a result of our research, we have gained valuable insight into the immune-microenvironment within PHE tissue, which could potentially be used to develop novel treatment modalities for ICH.

This study was conducted to investigate the effects of dietary supplementation of active dry yeast (Saccharomyces cerevisiae) on growth performance, circulating ghrelin, fatty acid concentrations in the gastrointestinal tract, and trace mineral elements utilisation of finishing bulls. Twenty Yanbian cattle (bulls) [body weight (BW) 485 ± 38 kg] were randomly divided into two groups (control and treatment groups) and participated in a 100-day finishing trial. The control group (CON) was fed a basal diet (total mixed ration, TMR). The treatment group (active dry yeast, ADY) was fed a basal diet supplemented with ADY (Levucell SC, Saccharomyces cerevisiae CNCM I-1077, viable count ≥8.0 × 109 CFU/g, 1.0 g/bull/day). ADY supplementation significantly increased the dry matter intake (DMI) of bulls (p

Abstract We present data and analysis of a set of balloon‐borne sounding profiles, which includes co‐located O3, CO, CH4, and particles, over the northern Tibetan Plateau during an Asian summer monsoon (ASM) season. These novel measurements shed light on the ASM transport behavior near the northern edge of the anticyclone. Joint analyses of these species with the temperature and wind profiles and supported by back trajectory modeling identify three distinct transport processes that dominate the vertical chemical structure in the middle troposphere, upper troposphere (UT), and the tropopause region. The correlated changes in profile structures in the middle troposphere highlight the influence of the strong westerly jet. Elevated constituent concentrations in the UT identify the main level of convective transport at the upstream source regions. Observed higher altitude maxima for CH4 characterize the airmasses' continued ascent following convection. These data complement constituent observations from other parts of the ASM anticyclone.

The objective of this work is to characterize the anticancer mechanism of platinum nanoparticles coated with polyethylene glycol and conjugated with Rutin (Rutin-PEG-PtNPs) in a breast cancer cell line. PtNPs were synthesized using Dendrobium officinale extract, coated with PEG, conjugated with Rutin, and characterized by the FT-IR, XRD, DLS, and TEM. The viability of the breast cancer cells (MCF-7) and normal breast cells (MCF-10A) after treatment with PEG-PtNPs and Rutin-PEG-PtNPs was studied by the MTT assay. Superoxide dismutase (SOD) and catalase (CAT) activity, MDA level, and LDH leakage in the PEG-PtNPs and Rutin-PEG-PtNPs were measured. The expression of the p53, Bax, Bcl-2, and caspase −8, and −9 genes, as well as the NF-κB and IL-6 levels in the Rutin-PEG-PtNPs treated cells, were investigated by qPCR and ELISA assays. Results demonstrated that the NPs were in a size range of 30 to 60 nm. The Rutin-PEG-PtNPs showed greater cytotoxic effects on breast cancer cells (IC50: 45.5 µg/mL) than normal breast cells (IC50: 69.4 µg/mL). The expression of the p53, Bax, caspase-8, and −9 was upregulated by 1.96, 1.84, 1.31, and 2.79 folds, while the expression of the Bcl-2 was reduced in Rutin-PEG-PtNP-treated cells. The activity of the SOD and CAT decreased, while the LDH leakage and MDA levels increased after treating the cells with Rutin-PEG-PtNPs. Also, the NF-κB and IL-6 levels in the cell cultures treated with Rutin-PEG-PtNPs were reduced by 22.6 and 17.0 %, respectively. Rutin-PEG-Pt indicated promising inhibitory potential against MCF-7 cells.

Pectobacterium brasiliense is a worldwide distributed bacterial pathogen causing soft rot and blackleg of a wide range of economically important crops. Here, we present the complete, high-quality genome of P. brasiliense strain TS20HJ1, which was isolated from a ginger (Zingiber officinale) rhizome showing soft rot symptoms. The genome assembly consists of a circular 4,766,353-bp chromosome with 52.1% GC content. The genome harbors 4,128 protein-coding genes, 22 rRNA genes, and 77 tRNA genes. We believe that the complete genome sequence of P. brasiliense TS20HJ1 will provide a valuable resource for understanding the molecular basis of host adaptation and evolution of pathogenesis. [Figure: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

We have integrated a compact and lightweight PET with an existing CT image-guided small animal irradiator to enable practical onboard PET/CT image-guided preclinical radiation therapy (RT) research. The PET with a stationary and full-ring detectors has ~1.1 mm uniform spatial resolution over its imaging field-of-view of 8.0 cm diameter and 3.5 cm axial length and was mechanically installed inside the irradiator in a tandem configuration with CT and radiation unit. A common animal bed was used for acquiring sequential dual functional and anatomical images with independent PET and CT control and acquisition systems. The reconstructed dual images were co-registered based on standard multi-modality image calibration and registration processes. Phantom studies were conducted to evaluate the integrated system and dual imaging performance. The measured mean PET/CT image registration error was ~0.3 mm. With one-bed and three-bed acquisitions, initial tumor focused and whole-body [18F]FDG animal images were acquired to test the capability of onboard PET/CT image guidance for preclinical RT research. Overall, the results have shown that integrated PET/CT/RT can provide advantageous and practical onboard PET/CT image to significantly enhance the accuracy of tumor delineation and radiation targeting that should enhance the existing and enable new and potentially breakthrough preclinical RT research and applications.

Abstract Histone modifications play critical roles in regulating gene expression and present dynamic changes during early embryo development. However, how they are reprogrammed during human prenatal germline development has not yet been elucidated. Here, we map the genome-wide profiles of three key histone modifications in human primordial germ cells (hPGCs) from weeks 8 to 23 of gestation for the first time by performing ULI-NChIP-seq. Notably, H3K4me3 exhibits a canonical promoter-enriched pattern, though with relatively lower enrichment, and is positively correlated with gene expression in globally hypomethylated hPGCs. In addition, H3K27me3 presents very low enrichment but plays an important role in not only dynamically governing specific bivalent promoters but also impeding complete X chromosome reactivation in female hPGCs. Given the activation effects of both global DNA demethylation and H3K4me3 signals, repressive H3K9me3 and H3K27me3 marks are jointly responsible for the paradoxical regulation of demethylation-resistant regions in hPGCs. Collectively, our results provide a unique roadmap of three core histone modifications during hPGC development, which helps to elucidate the architecture of germ cell reprogramming in an extremely hypomethylated DNA environment.

IntroductionAgrobacterium-mediated genetic transformation has been widely used for the identification of functional genes and regulatory and developmental mechanisms in plants. However, there are still some problems of low genetic transformation efficiency and high genotype dependence in cruciferous crops.MethodsIn this study, broccoli, a worldwide Brassica crop, was used to investigate the effects of genotype, explant type, concentration of hygromycin B used during seedling selection, overexpression vector type, RNAi and CRISPR/cas9 on the genetic transformation efficiency. At the same time, two vectors, PHG-031350 and PHG-CRa, were used for subcellular localization of the glucoraphanin synthesis-related gene FMOGS-OX5 and clubroot resistance gene by a PEG-Ca2+-mediated transient transformation system for broccoli protoplasts. Finally, the Agrobacterium-mediated genetic transformation system of broccoli was optimized and improved.Results and DiscussionThis study showed that hypocotyl explants are more suitable for Agrobacterium-mediated transgene and CRISPR/Cas9 gene editing of broccoli. In contrast to previous studies, we found that 5 mg/L hygromycin B was more advantageous for the selection of resistant broccoli sprouts, and genotype 19B42 reached the highest transformation rate of 26.96%, which is higher than that in Brassica oleracea crops. In addition, the inbred line 19B42 successfully achieved high genetic transformation of overexpression, RNAi and CRISPR/Cas9 vectors; thus, it is powerful recipient material for the genetic transformation of broccoli. Subcellular localization proved that the glucoraphanin metabolism-related gene Bol031350 and clubroot resistance gene CRa were both expressed in the cytoplasm and nucleus, which provided a scientific basis for studying the regulation of glucosinolate metabolism and clubroot resistance in cruciferous crops. Therefore, these findings will provide new insight into the improvement of the genetic transformation and molecular breeding of Brassica oleracea crops.

TanSat-2, the next-generation Chinese greenhouse gas monitoring satellite for measuring carbon dioxide (CO2), has a new city-scale observing mode. We assess the theoretical capability of TanSat-2 to quantify integrated urban CO2 emissions over the cities of Beijing, Jinan, Los Angeles, and Paris. A high-resolution emission inventory and a column-averaged CO2 (XCO2) transport model are used to build an urban CO2 inversion system. We design a series of numerical experiments describing this observing system to evaluate the impacts of sampling patterns and XCO2 measurement errors on inferring urban CO2 emissions. We find that the correction in systematic and random flux errors is correlated with the signal-to-noise ratio of satellite measurements. The reduction in systematic flux errors for the four cities are sizable, but are subject to unbiased satellite sampling and favorable meteorological conditions (i.e., less cloud cover and lower wind speed). The corresponding correction to the random flux error is 19–28%. Even though clear-sky satellite data from TanSat-2 have the potential to reduce flux errors for cities with high CO2 emissions, quantifying urban emissions by satellite-based measurements is subject to additional limitations and uncertainties.

Transient transformation of plant protoplasts is an important method for studying gene function, subcellular localization and plant morphological development. In this study, an efficient transient transformation system was established by optimizing the plasmid concentration, PEG4000 mass concentration and genotype selection, key factors that affect transformation efficiency. Meanwhile, an efficient and universal broccoli protoplast isolation system was established. Using 0.5% (w/v) cellulase R-10 and 0.1% (w/v) pectolyase Y-23 to hydrolyze broccoli cotyledons of three different genotypes for 3 h, the yield was more than 5×106/mL/g, and the viability was more than 95%, sufficient to meet the high standards for protoplasts to be used in various experiments. The average transformation efficiency of the two plasmid vectors PHG-eGFP and CP507-YFP in broccoli B1 protoplasts were 61.4% and 41.7%, respectively. Using this system, we successfully performed subcellular localization of the products of three target genes (the clubroot resistance gene CRa and two key genes regulated by glucosinolates, Bol029100 and Bol031350).The results showed that the products of all three genes were localized in the nucleus. The high-efficiency transient transformation system for broccoli protoplasts constructed in this study makes it possible to reliably acquire high-viability protoplasts in high yield. This research provides important technical support for international frontier research fields such as single-cell sequencing, spatial transcriptomics, plant somatic hybridization, gene function analysis and subcellular localization.

Landslides pose huge challenges to the economic activities in mountainous areas at present, while large numbers of landslide disasters have developed in the Hengduan Mountains area in the eastern part of the Tibetan Plateau. Accurate landslide susceptibility mapping (LSM) serves as a critical measure to predict the serious risks that may be encountered in engineering activities. However, previous landslide susceptibility assessment can only play a limited role in the real-time analysis of current activities of slopes. In this study, the deformation rates of the slopes along the Lancang River were determined using the SBAS-InSAR technique. Meanwhile, the landslide susceptibility along the north Lancang River was assessed using the frequency ratio (FR), random forest and FR-RF models, and the precision of the assessment results was verified according to receiver operating characteristic curves (ROCs). Finally, a refined landslide susceptibility map was developed by integrating the deformation rates and landslide susceptibility indexes (LSIs) using a contingency matrix. As indicated by the deformation rates calculated using the SBAS-InSAR technique according to ascending and descending data show that the RADARSAT-2 descending data yielded more precise deformation results. The area-under-the-curve (AUC) values of the three assessment models were 0.866, 0.897, and 0.916, respectively, indicating that the assessment results obtained with the FR-RF model are the most precise. In the upgraded landslide susceptibility map, the areas with high and very high landslide susceptibility increased by 2.97%. Meanwhile, a total of 563,430 grid cells showed an increase in landslide susceptibility, accounting for 11.15% of all the grid cells. Most especially, the Xueru and Ritong areas exhibited a significant increase in landslide susceptibility, and it has been verified by remote sensing images and field surveys that both areas are subject to landslide risks. Therefore, the upgraded landslide susceptibility map has a better prediction performance and can provide valuable support for the decision making in the construction of major engineering facilities and the prevention and remediation of landslides.

The recent outbreak of epidemic disease (COVID-19) has dramatically changed the socio-economic and environmental dynamics of the world. In particular, it affects human movement, travel intentions, and ambient air pollution amid rising stringency measures. Therefore, this study examines the influence of tourism knowledge, environmental vulnerability, and risk knowledge on travelers’ intentions in China’s tourism industry during COVID-19. To address the study objectives, an online survey questionnaire was created, through which a valid sample of 402 respondents was achieved. The direct and indirect relationship between variables was tested through structural equation modeling, the outcomes confirm that both tourism knowledge and risk knowledge in terms of COVID-19 significantly and negatively define the travelers’ intention toward tourism. Moreover, environmental vulnerability moderately affected tourism behavior and augmented with COVID-19 stringency disclosures. The mediating effect of risk perception and attitude towards the relationship between exogenous and endogenous constructs was tested. It shows a significant mediating impact of risk perception, environmental hazards and attitude towards risk on the nexus between tourism knowledge and travelers’ intention. The study offers valuable recommendations for policymakers to understand tourist intentions and climate vulnerability.

Image fusion is the process of combining multiple input images from single or multiple imaging modalities into a fused image, which is expected to be more informative for human or machine perception as compared to any of the input images. In this paper, we propose a novel method based on deep learning for fusing infrared images and visible images, named the local binary pattern (LBP)-based proportional input generative adversarial network (LPGAN). In the image fusion task, the preservation of structural similarity and image gradient information is contradictory, and it is difficult for both to achieve good performance at the same time. To solve this problem, we innovatively introduce LBP into GANs, enabling the network to have stronger texture feature extraction and utilization capabilities, as well as anti-interference capabilities. In the feature extraction stage, we introduce a pseudo-Siamese network for the generator to extract the detailed features and the contrast features. At the same time, considering the characteristic distribution of different modal images, we propose a 1:4 scale input mode. Extensive experiments on the publicly available TNO dataset and CVC14 dataset show that the proposed method achieves the state-of-the-art performance. We also test the universality of LPGAN by fusing RGB and infrared images on the RoadScene dataset and medical images. In addition, LPGAN is applied to multi-spectral remote sensing image fusion. Both qualitative and quantitative experiments demonstrate that our LPGAN can not only achieve good structural similarity, but also retain richly detailed information.

Understanding the damage mechanism of glacial debris flow mitigation systems is crucial for the risk prevention and assessment of the 200 km traffic corridor in the Southeast of the Tibetan Plateau, where the Sichuan-Tibet railway and expressway have been planned. Based on the phenomena, position and residual efficiency of damaged engineering, our analysis of satellite imagery and field investigation in multitype spatial reveals the damage types and influencing factors of glacial debris flow mitigation engineering. An evaluation model which can be used to estimate the engineering damage grade is established by using the relationship between mono engineering works and mitigation systems. In the new model, the engineering damage is divided into five grades: undamaged, slightly damaged, relatively damaged, seriously damaged, and totally damaged. For glacial debris flow in the Parlung river basin, the five grades of damage of mitigation works account for 8.70%, 34.78%, 21.74%, 13.04% and 21.74%, respectively. Furthermore, the soil source type and channel profile gradient are the key factors in engineering damage. Design defect of profile gradient is the controlling factor of damage in drainage channel engineering. Based on those results, an engineering damage model is established, which can provide an important reference for risk reduction and prevention of hazards due to the increasing development of traffic engineering.

Kinetic resolution allows to obtain enantioenriched compounds from racemic mixtures. Here, the authors report a synergistic magnesium catalyst promoting kinetic resolution of an intramolecular vinylogous Michael reaction to access [6.6.5]-tricyclic chiral skeletons.

TanSat is China’s first greenhouse gases observing satellite. In recent years, substantial progresses have been achieved on retrieving column-averaged CO2 dry air mole fraction (XCO2). However, relatively few attempts have been made to estimate terrestrial net ecosystem exchange (NEE) using TanSat XCO2 retrievals. In this study, based on the GEOS-Chem 4D-Var data assimilation system, we infer the global NEE from April 2017 to March 2018 using TanSat XCO2. The inversion estimates global NEE at −3.46 PgC yr-1, evidently higher than prior estimate and giving rise to an improved estimate of global atmospheric CO2 growth rate. Regionally, our inversion greatly increases the carbon uptakes in northern mid-to-high latitudes and significantly enhances the carbon releases in tropical and southern lands, especially in Africa and India peninsula. The increase of posterior sinks in northern lands is mainly attributed to the decreased carbon release during the nongrowing season, and the decrease of carbon uptakes in tropical and southern lands basically occurs throughout the year. Evaluations against independent CO2 observations and comparison with previous estimates indicate that although the land sinks in the northern middle latitudes and southern temperate regions are improved to a certain extent, they are obviously overestimated in northern high latitudes and underestimated in tropical lands (mainly northern Africa), respectively. These results suggest that TanSat XCO2 retrievals may have systematic negative biases in northern high latitudes and large positive biases over northern Africa, and further efforts are required to remove bias in these regions for better estimates of global and regional NEE.

Background Histone H1.5 has been considered as a novel cancer marker as its expression is associated with various human cancers. The objective of this study was to explore the effects of H1.5 phosphorylation in Ras-driven growth and migration of glioma cells.Methods The plasmids for expression of wide-type of Ras or RasG12V/Y40C were transfected into A172 cells. The expression levels of phosphorylated AKT and H1.5T10ph were tested by Western blot. The effects of H1.5T10ph on A172 cells growth and migration were determined by MTT, soft-agar colony formation, and transwell assay. qRT-PCR and ChIP assay were utilized to assess the role of H1.5T10ph in the transcription of Ras downstream genes. Besides, qRT-PCR and Western blot analysis were carried out to reveal the enzymes which were responsible for phosphorylating H1.5.Results H1.5T10ph was down-regulated by Ras mutation, which accompanied by the activation of AKT signaling. Ras-driven A172 cells growth and migration were inhibited when H1.5T10ph was overexpressed. Additionally, H1.5T10ph was able to regulate the transcription of Ras downstream genes, including CYR61, IGFBP3, WNT16B, NT5E, GDF15, and CARD16. Further experiments revealed that Ras-AKT signaling repressed H1.5T10ph expression through degradation of GSK3, and the degradation was dependent on MDM2 mediation.Conclusion Ras-AKT signaling driven the growth and migration of glioma cells possibly through repressing the phosphorylation of H1.5 at threonine 10. Ras-AKT activation repressed H1.5T10ph through MDM2-dependent degradation of GSK3. The findings provide a better understanding of Ras’s oncogenic functions which further suggest Ras as a therapeutic target for glioma.

Conventional mortar cemented anchors cannot meet the needs for landslide emergency management, as they can withstand loads only after mortar curing for 14–28 days. This study developed a multi-segment expanded anchor (MSEA) that expands using a sliding mechanism and rapidly bears loads using multiple load-bearing bodies by the frictional drag along the perforated wall, and the reaction force of the underreams’ platforms. Field tensile tests without grouting and the secondary tensile tests of six MSEAs, each with a length of 23 m, were carried out. The field tests show that the installed load-bearing bodies expanded steadily when the MSEAs were tensioned without grouting. In hard sandstones, the initial tensile force of each load-bearing body exceeded its design value of 150 kN, and the initial bearing capacity of each MSEA was greater than 300 kN, which exceeded the bearing capacity of the existing anchors regardless of grouting. The secondary tensile tests of the MSEAs were conducted after they were grouted for three days, and their lock-off load was greater than their design value of 600 kN. Based on the elastic mechanics and the stress process of the MSEAs, this study derived the theoretical equations of the ultimate bearing capacity of the MSEAs without grouting. The results calculated using the theoretical equations were roughly consistent with the field test results of the ultimate bearing capacity.

A series of carbon dioxide (CO2) emission inventories with high spatial resolutions covering China have been developed in the last decade, making it possible to assess not only the anthropogenic emissions of large administrational units (countries; provinces) but also those of small administrational units (cities; counties). In this study, we investigate three open-source gridded CO2 emission inventories (EDGAR; MEIC; PKU-CO2) and two statistical data-based inventories (CHRED; CEADs) covering the period of 2000–2020 for 16 prefecture-level cities in Shandong province in order to quantify the cross-inventory uncertainty and to discuss potential reasons for it. Despite ±20% differences in aggregated provincial emissions, all inventories agree that the emissions from Shandong increased by ~10% per year before 2012 and that the increasing trend slowed down after 2012, with a quasi-stationary industrial emission proportion being observed during 2008–2014. The cross-inventory discrepancies increased remarkably when downscaled to the city level. The relative differences between two individual inventories for half of the cities exceeded 100%. Despite close estimations of aggregated provincial emissions, the MEIC provides relatively high estimates for cities with complex and dynamic industrial systems, while the CHRED tends to provide high estimates for heavily industrial cities. The CHRED and MEIC show reasonable agreement regarding the evolution of city-level emissions and the city-level industrial emission ratios over 2005–2020. The PKU-CO2 and EDGAR failed to capture the emissions and their structural changes at the city level, which is related to their point-source database stopping updates after 2012. Our results suggest that cross-inventory differences for city-level emissions exist not only in their aggregated emissions but also in their changes over time.

Accurate measurements of the vertical distribution of carbon dioxide (CO2) in the atmosphere are critical to validate the vertical columns recorded by satellite and ground-based spectrometers and to estimate sources and sinks of CO2. This work describes an in-situ air-sampler system (Aircore). Profiles of CO2 and carbon monoxide (CO) were retrieved from two soundings of this system in Xilin Hot on 13 and 14 June 2018, and compared with observations from the Tropospheric Monitoring Instrument (TROPOMI), Orbiting Carbon Observatory-2 (OCO-2), and Copernicus Atmosphere Monitoring Service (CAMS). The column-averaged mixing ratio of CO (XCO) monitored by TROPOMI agreed well with that calculated from the in-situ CO profile, with a small mean difference of 5 ± 1.89 ppb. The column-averaged mixing ratio of CO2 (XCO2) monitored by OCO-2 also agreed well with that calculated from the in-situ CO2 profile, with a slight bias of 0.4 ± 0.6 ppm. The OCO-2 a posteriori profile had an obvious bias compared with the in-situ CO2 profile on 13 June, with an underestimation between 600 hPa and 250 hPa and an overestimation below 600 hPa. CAMS also had the same bias compared with the in-situ CO profile; however, CAMS agreed well with the in-situ CO profile on 14 June in the troposphere because a weak cold vortex passed Xilin Hot on 13 June and disappeared on 14 June. In the stratosphere, there were significant biases in the vertical degradation. The striking agreement between the column-averaged mixing ratios and the differences in the vertical distribution suggests new exciting applications for the profile product.

Monitoring the atmospheric CO2 columns inside and around a city is of great importance to understand the temporal–spatial variation of XCO2 near strong anthropogenic emissions. In this study, we use two FTIR CO2 column measurements in Beijing (Bruker EM27/SUN) and Xianghe (Bruker IFS 125HR) between 2019 and 2021 to investigate the differences of XCO2 between Beijing (urban) and Xianghe (suburb) in North China and to validate the OCO-2 and OCO-3 satellite XCO2 retrievals. The mean and standard deviation (std) of the ΔXCO2 between Beijing and Xianghe (Beijing–Xianghe) observed by two FTIR instruments are 0.206 ± 1.736 ppm, which has a seasonal variation and varies with meteorological conditions (wind speed and wind direction). The mean and std of the XCO2 differences between co-located satellite and FTIR measurements are −0.216 ± 1.578 ppm in Beijing and −0.343 ± 1.438 ppm in Xianghe for OCO-2 and 0.637 ± 1.594 ppm in Beijing and 1.206 ± 1.420 ppm in Xianghe for OCO-3. It is found that the OCO-3 snapshot area mode (SAM) measurements can capture the spatial gradient of XCO2 between urban and suburbs well. However, the FTIR measurements indicate that the OCO-3 SAM measurements are about 0.9–1.4 ppm overestimated in Beijing and Xianghe.

The Chinese carbon dioxide measurement satellite (TanSat) has collected a large number of measurements in the solar calibration mode. To improve the accuracy of XCO2 retrieval, the Instrument Line Shape (ILS, also known as the slit function) must be accurately determined. In this study, we characterized the on-orbit ILS of TanSat by fitting measured solar irradiance from 2017 to 2018 with a well-calibrated high-spectral-resolution solar reference spectrum. We used various advanced analytical functions and the stretch/sharpen of the tabulated preflight ILS to represent the ILS for each wavelength window, footprint, and band. Using super Gaussian+P7 and the stretch/sharpen functions substantially reduced the fitting residual in O2 A-band and weak CO2 band compared with using the preflight ILS. We found that the difference between the derived ILS width and on-ground preflight ILS was up to −3.5% in the weak CO2 band, depending on footprint and wavelength. The large amplitude of the ILS wings, depending on the wavelength, footprint, and bands, indicated possible uncorrected stray light. Broadening ILS wings will cause additive offset (filling-in) on the deep absorption lines of the spectra, which we confirmed using offline bias correction of the solar-induced fluorescence retrieval. We estimated errors due to the imperfect ILS using simulated TanSat spectra. The results of the simulations showed that XCO2 retrieval is sensitive to errors in the ILS, and 4% uncertainty in the full width of half maximum (FWHM) or 20% uncertainty in the ILS wings can induce an error of up to 1 ppm in the XCO2 retrieval.

Records and projections of increasing global average temperature call for improvements of global stocktake inputs, which are vital to achieving targets of intergovernmental agreements on climate change. Unmanned Aerial Vehicle (UAV)-based atmospheric observation of greenhouse gas (GHG) concentrations is an upcoming addition to the top-down measurement methods due to its advantageous spatial-temporal resolutions, greater coverage area and lower costs. Hence, we developed and tested a lightweight UAV payload enclosure integrating a non-dispersive diffusion infrared (NDIR) spectrometer and two electrochemical sensors for measurements of carbon dioxide (CO2), carbon monoxide (CO) and nitrogen dioxide (NO2). To achieve higher response times and maintain measurement qualities, we designed a custom air inlet on the rotor-facing side of the enclosure to reduce measurement fluctuations caused by rotor downwash airflow. To validate the payload design, we conducted a controlled test for comparing chambered and chamber-less NDIR spectrometer measurements. From the test we observed a reduction of 0.48 hPa in terms of standard deviation of pressure measurements and minimised downwash-flow-induced anomalous biases (+0.49 ppm and +0.08 hpa for chambered compared to −1.33 ppm and −1.05 hpa for chamber-less). We also conducted an outdoor in-situ measurement test with multiple flights reaching 500 m above ground level (ABGL). The test yielded high resolution results representing vertical distributions of mole fraction concentrations of three types of gases via two types of flight trajectory planning methods. Therefore, we provide an alternative UAV payload integration method for NDIR spectrometer CO2 measurements that complement existing airborne GHG observation methodologies. Additionally, we also introduced an aerodynamic approach in reducing measurement noises and biases for a low response time sensor configuration.

We estimated CO _2 emissions from the Beijing region of China using differential ground-based observations of the column-averaged dry air mole fractions of CO _2 ( $\Delta X{\text{C}}{{\text{O}}_{2,{\text{ obs}}}}$ ; urban minus upwind background column observations) in winter (1 November 2020–1 March 2021). Beijing is one of the most world’s populated cities and the CO _2 emissions from this region contain large uncertainties in different bottom-up anthropogenic inventories. Differential measurements are potentially able to capture urban signals over Beijing (3.46 ± 2.35 ppm). The simulated X CO _2 enhancements were calculated ( $\Delta X{\text{C}}{{\text{O}}_{2,{\text{ sim}}}}$ ) based on three emission inventories (the Open-source Data Inventory for Anthropogenic CO _2 (ODIAC), Multiresolution Emission Inventory for China (MEIC) and Emissions Database for Global Atmospheric Research (EDGAR) datasets) for Beijing. The $\Delta X{\text{C}}{{\text{O}}_{2,{\text{ sim}}}}$ values based on the ODIAC dataset were much higher than the observations, whereas the values from the EDGAR dataset were much lower and the MEIC dataset was more consistent. We performed a Lagrangian inversion framework based on Bayesian theory. The average and uncertainty of a priori estimates (12.18 ± 8.0, 7.09 ± 7.5 and 3.53 ± 11.4 μ mol (m ^2 s) ^−1 ) were optimized to the posterior emissions (9.44 ± 5.7, 7.13 ± 4.9 and 7.15 ± 5.7 μ mol (m ^2 s) ^−1 ), suggesting that the three posterior estimates tended to converge to become more consistent, transport errors (especially the horizontal transport errors) and the spatially uneven corrections in Beijing were the main reason for the differences between the posterior estimates. Sensitivity tests suggested that the prescribed spatial and temporal structures affected up to about 12.9%, 4.9% and 20.8%, respectively, of the three inventories.

Following a brief historical summary of the way in which electron beam lithography developed out of the scanning electron microscope, three state-of-the-art charged-particle beam nanopatterning technologies are considered. All three have been the subject of a recently completed European Union Project entitled “Single Nanometre Manufacturing: Beyond CMOS”. Scanning helium ion beam lithography has the advantages of virtually zero proximity effect, nanoscale patterning capability and high sensitivity in combination with a novel fullerene resist based on the sub-nanometre C60 molecule. The shot noise-limited minimum linewidth achieved to date is 6 nm. The second technology, focused electron induced processing (FEBIP), uses a nozzle-dispensed precursor gas either to etch or to deposit patterns on the nanometre scale without the need for resist. The process has potential for high throughput enhancement using multiple electron beams and a system employing up to 196 beams is under development based on a commercial SEM platform. Among its potential applications is the manufacture of templates for nanoimprint lithography, NIL. This is also a target application for the third and final charged particle technology, viz. field emission electron scanning probe lithography, FE-eSPL. This has been developed out of scanning tunneling microscopy using lower-energy electrons (tens of electronvolts rather than the tens of kiloelectronvolts of the other techniques). It has the considerable advantage of being employed without the need for a vacuum system, in ambient air and is capable of sub-10 nm patterning using either developable resists or a self-developing mode applicable for many polymeric resists, which is preferred. Like FEBIP it is potentially capable of massive parallelization for applications requiring high throughput.

The increase in atmospheric greenhouse gas concentrations of CO2 and CH4, due to human activities, is the main driver of the observed increase in surface temperature by more than 1 °C since the pre-industrial era. At the 2015 United Nations Climate Change Conference held in Paris, most nations agreed to reduce greenhouse gas emissions to limit the increase in global surface temperature to 1.5 °C. Satellite remote sensing of CO2 and CH4 is now well established thanks to missions such as NASA’s OCO-2 and the Japanese GOSAT missions, which have allowed us to build a long-term record of atmospheric GHG concentrations from space. They also give us a first glimpse into CO2 and CH4 enhancements related to anthropogenic emission, which helps to pave the way towards the future missions aimed at a Monitoring & Verification Support (MVS) capacity for the global stock take of the Paris agreement. China plays an important role for the global carbon budget as the largest source of anthropogenic carbon emissions but also as a region of increased carbon sequestration as a result of several reforestation projects. Over the last 10 years, a series of projects on mitigation of carbon emission has been started in China, including the development of the first Chinese greenhouse gas monitoring satellite mission, TanSat, which was successfully launched on 22 December 2016. Here, we summarise the results of a collaborative project between European and Chinese teams under the framework of the Dragon-4 programme of ESA and the Ministry of Science and Technology (MOST) to characterize and evaluate the datasets from the TanSat mission by retrieval intercomparisons and ground-based validation and to apply model comparisons and surface flux inversion methods to TanSat and other CO2 missions, with a focus on China.

The COVID-19 pandemic has led to ongoing reductions in economic activity and anthropogenic emissions. Beijing was particular badly affected by lockdown measures during the early months of the COVID-19 pandemic. It has significantly reduced the CO2 emission and toxic air pollution (CO and NO2). We use column-averaged dry-air mole fractions of CO2 and CO (XCO2 and XCO) observed by a ground-based EM27/SUN Fourier transform spectrometer (FTS), the tropospheric NO2 column observed by MAX-DOAS and satellite remote sensing data (GOSAT and TROPOMI) to investigate the variations in anthropogenic CO2 emission related to COVID-19 lockdown in Beijing. The anomalies describe the spatio-temporal enhancement of gas concentration, which relates to the emission. Anomalies in XCO2 and XCO, and XNO2 (ΔXCO2, ΔXCO, and ΔXNO2) for ground-based measurements were calculated from the diurnal variability. Highly correlated daily XCO and XCO2 anomalies derived from FTS time series data provide the ΔXCO to ΔXCO2 ratio (the correlation slope). The ΔXCO to ΔXCO2 ratio in Beijing was lower in 2020 (8.2 ppb/ppm) than in 2019 (9.6 ppb/ppm). The ΔXCO to ΔXCO2 ratio originating from a polluted area was significantly lower in 2020. The reduction in anthropogenic CO2 emission was estimated to be 14.2% using FTS data. A comparable value reflecting the slowdown in growth of atmospheric CO2 over the same time period was estimated to be 15% in Beijing from the XCO2 anomaly from GOSAT, which was derived from the difference between the target area and the background area. The XCO anomaly from TROPOMI is reduced by 8.7% in 2020 compared with 2019, which is much smaller than the reduction in surface air pollution data (17%). Ground-based NO2 observation provides a 21.6% decline in NO2. The NO2 to CO2 correlation indicates a 38.2% decline in the CO2 traffic emission sector. Overall, the reduction in anthropogenic CO2 emission relating to COVID-19 lockdown in Beijing can be detected by the Bruker EM27/SUN Fourier transform spectrometer (FTS) and MAX-DOAS in urban Beijing.

The steam oxidation behavior of three heterogeneous HR3C alloys was investigated at 650 °C comparatively. After a long-term oxidation process for 1000 h, the results demonstrated that the commercial HR3C alloy already exhibited a high oxidation resistance. However, the spallation resistance of the oxide scale was low during the initial oxidation period. The addition of a moderate amount of Nb into the alloy (1#HR3C) increased the oxidation resistance of the alloy. In addition, the improvement of the microstructural stability was substantially influenced by solid solution strengthening and fine grain strengthening. However, the addition of excessive Nb could significantly affect the growth model of the oxide scale and negatively affect the oxidation performance and microstructural evolution of the alloy (2#HR3C).

The main objective of this paper is to use deep neural networks to decode the electroencephalography (EEG) signals evoked when individuals perceive four types of motion stimuli (contraction, expansion, rotation, and translation). Methods for single-trial and multi-trial EEG classification are both investigated in this study. Attention mechanisms and a variant of recurrent neural networks (RNNs) are incorporated as the decoding model. Attention mechanisms emphasize task-related responses and reduce redundant information of EEG, whereas RNN learns feature representations for classification from the processed EEG data. To promote generalization of the decoding model, a novel online data augmentation method that randomly averages EEG sequences to generate artificial signals is proposed for single-trial EEG. For our dataset, the data augmentation method improves the accuracy of our model (based on RNN) and two benchmark models (based on convolutional neural networks) by 5.60%, 3.92%, and 3.02%, respectively. The attention-based RNN reaches mean accuracies of 67.18% for single-trial EEG decoding with data augmentation. When performing multi-trial EEG classification, the amount of training data decreases linearly after averaging, which may result in poor generalization. To address this deficiency, we devised three schemes to randomly combine data for network training. Accordingly, the results indicate that the proposed strategies effectively prevent overfitting and improve the correct classification rate compared with averaging EEG fixedly (by up to 19.20%). The highest accuracy of the three strategies for multi-trial EEG classification achieves 82.92%. The decoding performance for the methods proposed in this work indicates they have application potential in the brain–computer interface (BCI) system based on visual motion perception.

Debris flow gullies have high potential energy and geomorphic characteristics including a steep longitudinal slope and abundant loose material sources. They often experience debris flow with a strong impact force and a large instantaneous flow. Drainage engineering measures are most commonly used for mitigation in these gullies. However, the abrasion of drainage channels with large gradients (DCLG) is complex and strong because of the high-speed flushing of debris. In this study, the abrasion behavior of debris flow in DCLG is analyzed based on the kinematic characteristics and the theory of composite abrasive wear. Energy dissipation and anti-wear measures are suggested, and their effects are summarized with reference to a case study and in situ observation. The results show that there are four main types of wear morphology in drainage channels. The abrasion system of drainage channels shows the characteristics of system dependency, time dependency and multidisciplinary coupling. Energy dissipation and anti-wear measures include prefabricated reinforced concrete boxes as substrate, transverse roughening belts, adding a wear-resistant admixture, etc. The flow velocity of the debris flow is reduced by 5.7–37.1% after passing through the energy dissipation section. The distribution of abrasion and the mud depth show that the variation trend of the flow velocity in the channel is ”acceleration → deceleration → reacceleration“. According to tracking observations during two flood seasons, the energy dissipation and anti-wear measures are the most effective.

Aerosols significantly affect carbon dioxide (CO2) retrieval accuracy and precision by modifying the light path. Hyperspectral measurements in the near infrared and shortwave infrared (NIR/SWIR) bands from the generation of new greenhouse gas satellites (e.g., the Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite, TanSat) contain aerosol information for correction of scattering effects in the retrieval. Herein, a new approach is proposed for optimizing the aerosol model used in the TanSat CO2 retrieval algorithm to reduce CO2 uncertainties associated with aerosols. The weighting functions of hyperspectral observations with respect to elements in the state vector are simulated by a forward radiative transfer model. Using the optimal estimation method (OEM), the information content and each component of the CO2 column-averaged dry-air mole fraction (XCO2) retrieval errors from the TanSat simulations are calculated for typical aerosols which are described by Aerosol Robotic Network (AERONET) inversion products at selected sites based on the a priori and measurement assumptions. The results indicate that the size distribution parameters (reff, veff), real refractive index coefficient of fine mode (arf) and fine mode fraction (fmf) dominate the interference errors, with each causing 0.2−0.8 ppm of XCO2 errors. Given that only 4−7 degrees of freedom for signal (DFS) of aerosols can be obtained simultaneously and CO2 information decreases as more aerosol parameters are retrieved, four to seven aerosol parameters are suggested as the most appropriate for inclusion in CO2 retrieval. Focusing on only aerosol-induced XCO2 errors, forward model parameter errors, rather than interference errors, are dominant. A comparison of these errors across different aerosol parameter combination groups reveals that fewer aerosol-induced XCO2 errors are found when retrieving seven aerosol parameters. Therefore, the model selected as the optimal aerosol model includes aerosol optical depth (AOD), peak height of aerosol profile (Hp), width of aerosol profile (Hw), effective variance of fine mode aerosol (vefff), effective radius of coarse mode aerosol (reffc), coefficient a of the real part of the refractive index for the fine mode and coarse mode (arf and arc), with the lowest error of less than 1.7 ppm for all aerosol and surface types. For marine aerosols, only five parameters (AOD, Hp, Hw, reffc and arc) are recommended for the low aerosol information. This optimal aerosol model therefore offers a theoretical foundation for improving CO2 retrieval precision from real TanSat observations in the future.

Aerosol scattering is an important source of error in CO2 retrievals from satellite. This paper presents an analysis of aerosol information content from the Cloud and Aerosol Polarimetric Imager (CAPI) onboard the Chinese Carbon Dioxide Observation Satellite (TanSat) to be launched in 2016. Based on optimal estimation theory, aerosol information content is quantified from radiance and polarization observed by CAPI in terms of the degrees of freedom for the signal (DFS). A linearized vector radiative transfer model is used with a linearized Mie code to simulate observation and sensitivity (or Jacobians) with respect to aerosol parameters. In satellite nadir mode, the DFS for aerosol optical depth is the largest, but for mode radius, it is only 0.55. Observation geometry is found to affect aerosol DFS based on the aerosol scattering phase function from the comparison between different viewing zenith angles or solar zenith angles. When TanSat is operated in target mode, we note that multi-angle retrieval represented by three along-track measurements provides additional 0.31 DFS on average, mainly from mode radius. When adding another two measurements, the a posteriori error decreases by another 2%–6%. The correlation coefficients between retrieved parameters show that aerosol is strongly correlated with surface reflectance, but multi-angle retrieval can weaken this correlation.