Search

Since 2008, the Yellow Sea has experienced the world's largest-scale marine disaster, the green tide, marked by the rapid proliferation and accumulation of large floating algae. Leveraging advanced artificial intelligence (AI) models, namely AlgaeNet and GANet, this study comprehensively extracted and analyzed green tide occurrences using optical Moderate Resolution Imaging Spectroradiometer (MODIS) images and microwave Sentinel-1 synthetic aperture radar (SAR) images. However, due to cloud and rain interference and the varying observation frequencies of the two types of satellites, the daily green tide coverage time series throughout the entire life cycle often contain large gaps and missing frames, resulting in discontinuity and limiting their use. Therefore, this study presents a continuous and seamless weekly average green tide coverage dataset with a resolution of 500 m, by integrating highly precise daily optical and SAR data for each week during the green tide breakout. The uncertainty assessment shows that this weekly product conforms to the life pattern of green tide outbreaks and exhibits parabolic-curve-like characteristics, with a low uncertainty (R2=0.89 and RMSE=275 km2). This weekly dataset offers reliable long-term data spanning 15 years, facilitating research in forecasting, climate change analysis, numerical simulation, and disaster prevention planning in the Yellow Sea. The dataset is accessible through the Oceanographic Data Center, Chinese Academy of Sciences (CASODC), along with comprehensive reuse instructions provided at https://doi.org/10.12157/IOCAS.20240410.002 (Gao et al., 2024).

The composition, sources and chemical transformation of volatile organic compounds (VOCs) and organic aerosol (OA) particles were investigated during July–August 2021 at a rural forested site in southwest Germany, 10 km north of the city of Karlsruhe. VOCs and semi-volatile OA particles were measured with a proton-transfer-reaction mass spectrometer coupled to the CHemical Analysis of aeRosols ONline particle inlet (CHARON–PTR-MS). The CHARON-measured OA mass accounted for 62 ± 18 % on average of the total OA mass (4.2 ± 2.8 µg m−3) measured concurrently with an aerosol mass spectrometer (AMS). The total concentrations of measured VOCs ranged from 7.6 to 88.9 ppb with an average of 31.2 ± 13.4 ppb. Positive matrix factorization (PMF) was used to identify major source factors of VOCs and OA particles. Three types of oxygenated VOC (OVOC), namely aromatic OVOCs, biogenic OVOCs and aged OVOCs, contributed on average 11 % ± 9 %, 37 % ± 29 % and 29 % ± 21 % of total VOC concentrations, respectively. The results of AMS–PMF indicated substantial contributions of oxygenated organic compounds to OA particle mass. Three secondary OA (SOA) factors determined by CHARON–PMF analysis, namely aromatic SOA (5 % ± 7 %), daytime biogenic SOA (17 % ± 17 %) and nighttime biogenic SOA (28 % ± 21 %), consistently showed high contributions to the total CHARON-measured OA mass. Nighttime particle growth was observed regularly in this area, which was mainly attributed to the semi-volatile organic compounds and organic nitrates formed from the oxidation of monoterpenes and sesquiterpenes. This study presents the major sources, real-time transformations of VOCs and OA particles, and nighttime particle formation characteristics for central European forested areas.

Satellite-based detection of methane (CH4) point sources is crucial in identifying and mitigating anthropogenic emissions of CH4, a potent greenhouse gas. Previous studies have indicated the presence of CH4 point source emissions from coal mines in Shanxi, China, which is an important source region with large CH4 emissions, but a comprehensive survey has remained elusive. This study aims to conduct a survey of CH4 point sources over Shanxi's coal mines based on observations of the Advanced Hyperspectral Imager (AHSI) on board the Gaofen-5B satellite (GF-5B/AHSI) between 2021 and 2023. The spectral shift in centre wavelength and change in full width at half-maximum (FWHM) from the nominal design values are estimated for all spectral channels, which are used as inputs for retrieving the enhancement of the column-averaged dry-air mole fraction of CH4 (ΔXCH4) using a matched-filter-based algorithm. Our results show that the spectral calibration on GF-5B/AHSI reduced estimation biases of the emission flux rate by up to 5.0 %. We applied the flood-fill algorithm to automatically extract emission plumes from ΔXCH4 maps. We adopted the integrated mass enhancement (IME) model to estimate the emission flux rate values from each CH4 point source. Consequently, we detected CH4 point sources in 32 coal mines with 93 plume events in Shanxi province. The estimated emission flux rate ranges from 761.78 ± 185.00 to 12 729.12 ± 4658.13 kg h−1. Our results show that wind speed is the dominant source of uncertainty contributing about 84.84 % to the total uncertainty in emission flux rate estimation. Interestingly, we found a number of false positive detections due to solar panels that are widely spread in Shanxi. This study also evaluates the accuracy of wind fields in ECMWF ERA5 reanalysis by comparing them with a ground-based meteorological station. We found a large discrepancy, especially in wind direction, suggesting that incorporating local meteorological measurements into the study CH4 point source are important to achieve high accuracy. The study demonstrates that GF-5B/AHSI possesses capabilities for monitoring large CH4 point sources over complex surface characteristics in Shanxi.

The aqueous-phase chemistry of glyoxal (GL) with reduced nitrogen compounds (RNCs) is a significant source for secondary brown carbon (SBrC), which is one of the largest uncertainties in climate predictions. However, a few studies have revealed that SBrC formation is affected by multifunctional RNCs, which have a non-negligible atmospheric abundance. Hence, we assessed theoretical and experimental approaches to investigate the reaction mechanisms and kinetics of the mixtures for ammonium sulfate (AS), multifunctional amine monoethanolamine (MEA), and GL. Our experiments indicate that light absorption and growth rate are enhanced more efficiently in the MEA–GL mixture relative to AS–GL and MEA–AS–GL mixtures and MEA reactions of the chromophores than in the analogous AS reactions. Quantum chemical calculations show that the formation and propagation of oligomers proceed via four-step nucleophilic addition reactions in three reaction systems. The presence of MEA provides the two extra branched chains that affect the natural charges and steric hindrance of intermediates, facilitating the formation of chromophores. Molecule dynamics simulations reveal that the interfacial and interior attraction on the aqueous aerosols with MEA is more pronounced for small α-dicarbonyls to facilitate further engagement in the aqueous-phase reactions. Our results show a possible missing source for SBrC formation on urban, regional, and global scales.

Cloud condensation nuclei (CCN) are mediators of aerosol–cloud interactions (ACIs), contributing to the largest uncertainties in the understandings of global climate change. We present a novel remote-sensing-based algorithm that quantifies the vertically resolved CCN number concentrations (NCCN) using aerosol optical properties measured by a multiwavelength lidar. The algorithm considers five distinct aerosol subtypes with bimodal size distributions. The inversion used the lookup tables developed in this study, based on the observations from the Aerosol Robotic Network, to efficiently retrieve optimal particle size distributions from lidar measurements. The method derives dry aerosol optical properties by implementing hygroscopic enhancement factors in lidar measurements. The retrieved optically equivalent particle size distributions and aerosol-type-dependent particle composition are utilized to calculate critical diameters using κ-Köhler theory and NCCN at six supersaturations ranging from 0.07 % to 1.0 %. Sensitivity analyses indicate that uncertainties in extinction coefficients and relative humidity greatly influence the retrieval error in NCCN. The potential of this algorithm is further evaluated by retrieving NCCN using airborne lidar from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign and is validated against simultaneous measurements from the CCN counter. The independent validation with robust correlation demonstrates promising results. Furthermore, the NCCN has been retrieved for the first time using a proposed algorithm from spaceborne lidar – Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) – measurements. The application of this new capability demonstrates the potential for constructing a 3D CCN climatology at a global scale, which helps to better quantify ACI effects and thus reduce the uncertainty in aerosol climate forcing.

The apparent volatility of atmospheric organic aerosol (OA) particles is determined by their chemical composition and environmental conditions (e.g., ambient temperature). A quantitative, experimental assessment of volatility and the respective importance of these two factors remains challenging, especially in ambient measurements. We present molecular composition and volatility of oxygenated OA (OOA) particles in different rural, urban, and mountain environments (including Chacaltaya, Bolivia; Alabama, US; Hyytiälä, Finland; Stuttgart and Karlsruhe, Germany; and Delhi, India) based on deployments of a filter inlet for gases and aerosols coupled to a high-resolution time-of-flight chemical ionization mass spectrometer (FIGAERO-CIMS). We find on average larger carbon numbers (nC​​​​​​​) and lower oxygen-to-carbon (O : C) ratios at the urban sites (nC: 9.8 ± 0.7; O : C: 0.76 ± 0.03; average ±1 standard deviation) compared to the rural (nC: 8.8 ± 0.6; O : C: 0.80 ± 0.05) and mountain stations (nC: 8.1 ± 0.8; O : C: 0.91 ± 0.07), indicative of different emission sources and chemistry. Compounds containing only carbon, hydrogen, and oxygen atoms (CHO) contribute the most to the total OOA mass at the rural sites (79.9 ± 5.2 %), in accordance with their proximity to forested areas (66.2 ± 5.5 % at the mountain sites and 72.6 ± 4.3 % at the urban sites). The largest contribution of nitrogen-containing compounds (CHON) is found at the urban stations (27.1 ± 4.3 %), consistent with their higher NOx levels. Moreover, we parametrize OOA volatility (saturation mass concentrations, Csat) using molecular composition information and compare it with the bulk apparent volatility derived from thermal desorption of the OOA particles within the FIGAERO. We find differences in Csat values of up to ∼ 3 orders of magnitude and variation in thermal desorption profiles (thermograms) across different locations and systems. From our study, we draw the general conclusion that environmental conditions (e.g., ambient temperature) do not directly affect OOA apparent volatility but rather indirectly by influencing the sources and chemistry of the environment and thus the chemical composition. The comprehensive dataset provides results that show the complex thermodynamics and chemistry of OOA and their changes during its lifetime in the atmosphere. We conclude that generally the chemical description of OOA suffices to predict its apparent volatility, at least qualitatively. Our study thus provides new insights that will help guide choices of, e.g., descriptions of OOA volatility in different model frameworks such as air quality models and cloud parcel models.

To improve the aerodynamic characteristics of compressor blades, a novel asymmetric leading edge (ASYLE) has been introduced and shown to offer superior performance. However, the aerodynamic robustness of such specially designed leading edge (LE) remains unclear due to the considerable uncertainty problems it presents. This paper investigates the robustness of ASYLE blade under both geometric and operational uncertainties. Profile deviations within ±0.05mm were introduced to investigate the influence of manufacturing errors. In addition, the perturbated inflow angles between ±0.375° were considered for uncertain inflow conditions. The statistic aerodynamic performance as well as operating dispersibilities at Ma=0.7 were obtained by the non-intrusive polynomial chaos (NIPC) method. The results show that considering uncertain profile errors, the operating range of ASYLE blade is 2.3° wider than original leading edge (ORILE) blade and the dispersion of total pressure loss can be reduced by 53.1% at β1=45.8°. Regarding uncertain inflow angle variations, the total pressure loss dispersion of ASYLE blade can be reduced by 93.8% at β1=50.8°. The ASYLE shows better overall aerodynamic robustness than ORILE upon considering uncertainty limits. The influence propagations in the flow fields of both uncertainties were further analysed, which revealed that the variations of separation bubble structure near LE are the direct cause to the aerodynamic uncertainties. The ASYLE design effectively controls the size and variation of LE separation bubble and thus demonstrates better aerodynamic robustness.

Abstract Large laser facilities have recently enabled material characterization at the pressures of Earth and Super-Earth cores. However, the temperature of the compressed materials has been largely unknown, or solely relied on models and simulations, due to lack of diagnostics under these challenging conditions. Here, we report on temperature, density, pressure, and local structure of copper determined from extended x-ray absorption fine structure and velocimetry up to 1 Terapascal. These results nearly double the highest pressure at which extended x-ray absorption fine structure has been reported in any material. In this work, the copper temperature is unexpectedly found to be much higher than predicted when adjacent to diamond layer(s), demonstrating the important influence of the sample environment on the thermal state of materials; this effect may introduce additional temperature uncertainties in some previous experiments using diamond and provides new guidance for future experimental design.

Brown carbon (BrC) aerosol could impact atmospheric radiative forcing and play a crucial role in atmospheric photochemistry. In this study, fine particulate matter (PM2.5) filter samples were collected synchronously in four major cities in northwestern China during the winter season (December 2019–January 2020): Lanzhou (LZ), Xining (XN), Yinchuan (YC), and Ürümqi (UR), which are represented as energy-producing and heavy manufacturing cities in China. The primary aim of the study is to explore the optical properties, sources, and chemical processes of water-soluble BrC (WS-BrC). The average mass absorption efficiency at 365 nm (MAE365) of WS-BrC at these four cities was 1.24 ± 0.19 m2 g−1 (XN), 1.19 ± 0.12 m2 g−1 (LZ), 1.07 ± 0.23 m2 g−1 (YC), and 0.78 ± 0.16 m2 g−1 (UR). The properties of WS-BrC were further investigated by an acid–base titration experiment. The results showed that the MAE365 values in all cities increased with higher pH values (2–11), while the fluorescence intensities of water extracts fluctuated with pH values, being stronger under both highly acidic and basic conditions. The sensitivity to pH variation was most pronounced in the WS-BrC samples from YC and LZ, indicating the important contribution of acid or base functional group compounds in these locations. Additionally, the study revealed significant photo-enhancement (LZ) or photo-bleaching (YC and UR) phenomena of WS-BrC in different cities. These results suggest that the sources and/or chemical processes of WS-BrC varied among the cities. The sources and chemical processes of WS-BrC were further explored by a combination of parallel factor analysis (PARAFAC) on excitation–emission matrix (EEM) spectra of WS-BrC and positive matrix factorization analysis (PMF) on high-resolution mass spectra of water-soluble organic aerosol (WSOA). Six PARAFAC components were identified, including three humic-like substances (HULIS; two less oxygenated (LO) HULIS and one highly oxygenated (HO) HULIS), two protein-like or phenol-like substances (PLS), and one undefined substance. Four PMF factors were identified, including a water-soluble primary OA (WS-POA), a less oxidized oxygenated OA associated with coal combustion-induced WSOA (LO-OOA), and two highly oxidized oxygenated OAs resulting from photochemical oxidation and aqueous-phase oxidation transformations (HO-OOA1 and HO-OOA2). WS-POA was determined to be the most significant source of light absorption, accounting for 30 %–60 % based on multiple linear regression models, and it showed a significant correlation with PLS and LO-HULIS components. The loss of light absorption of WS-POA was found to occur through its conversion to LO-OOA and HO-OOAs through photochemical or aqueous reactions, with HO-OOAs being significantly correlated with the HO-HULIS component. These processes can be clearly illustrated by integrating optical properties and chemical composition using a Van Krevelen diagram and an EEM plot.

Accurately capturing cloud condensation nuclei (CCN) concentrations is key to understanding the aerosol–cloud interactions that continue to feature the highest uncertainty amongst numerous climate forcings. In situ CCN observations are sparse, and most non-polarimetric passive remote sensing techniques are limited to providing column-effective CCN proxies such as total aerosol optical depth (AOD). Lidar measurements, on the other hand, resolve profiles of aerosol extinction and/or backscatter coefficients that are better suited for constraining vertically resolved aerosol optical and microphysical properties. Here we present relationships between aerosol backscatter and extinction coefficients measured by the airborne High Spectral Resolution Lidar 2 (HSRL-2) and in situ measurements of CCN concentrations. The data were obtained during three deployments in the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) project, which took place over the southeast Atlantic (SEA) during September 2016, August 2017, and September–October 2018. Our analysis of spatiotemporally collocated in situ CCN concentrations and HSRL-2 measurements indicates strong linear relationships between both data sets. The correlation is strongest for supersaturations (S) greater than 0.25 % and dry ambient conditions above the stratocumulus deck, where relative humidity (RH) is less than 50 %. We find CCN–HSRL-2 Pearson correlation coefficients between 0.95–0.97 for different parts of the seasonal burning cycle that suggest fundamental similarities in biomass burning aerosol (BBA) microphysical properties. We find that ORACLES campaign-average values of in situ CCN and in situ extinction coefficients are qualitatively similar to those from other regions and aerosol types, demonstrating overall representativeness of our data set. We compute CCN–backscatter and CCN–extinction regressions that can be used to resolve vertical CCN concentrations across entire above-cloud lidar curtains. These lidar-derived CCN concentrations can be used to evaluate model performance, which we illustrate using an example CCN concentration curtain from the Weather Research and Forecasting Model coupled with physics packages from the Community Atmosphere Model version 5 (WRF-CAM5). These results demonstrate the utility of deriving vertically resolved CCN concentrations from lidar observations to expand the spatiotemporal coverage of limited or unavailable in situ observations.

The southeastern Atlantic is home to an expansive smoke aerosol plume overlying a large cloud deck for approximately a third of the year. The aerosol plume is mainly attributed to the extensive biomass burning activities that occur in southern Africa. Current Earth system models (ESMs) reveal significant differences in their estimates of regional aerosol radiative effects over this region. Such large differences partially stem from uncertainties in the vertical distribution of aerosols in the troposphere. These uncertainties translate into different aerosol optical depths (AODs) in the planetary boundary layer (PBL) and the free troposphere (FT). This study examines differences of AOD fraction in the FT and AOD differences among ESMs (WRF-CAM5, WRF-FINN, GEOS-Chem, EAM-E3SM, ALADIN, GEOS-FP, and MERRA-2) and aircraft-based measurements from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign. Models frequently define the PBL as the well-mixed surface-based layer, but this definition misses the upper parts of decoupled PBLs, in which most low-level clouds occur. To account for the presence of decoupled boundary layers in the models, the height of maximum vertical gradient of specific humidity profiles from each model is used to define PBL heights. Results indicate that the monthly mean contribution of AOD in the FT to the total-column AOD ranges from 44 % to 74 % in September 2016 and from 54 % to 71 % in August 2017 within the region bounded by 25∘ S–0∘ N–S and 15∘ W–15∘ E (excluding land) among the ESMs. ALADIN and GEOS-Chem show similar aerosol plume patterns to a derived above-cloud aerosol product from the Moderate Resolution Imaging Spectroradiometer (MODIS) during September 2016, but none of the models show a similar above-cloud plume pattern to MODIS in August 2017. Using the second-generation High Spectral Resolution Lidar (HSRL-2) to derive an aircraft-based constraint on the AOD and the fractional AOD, we found that WRF-CAM5 produces 40 % less AOD than those from the HSRL-2 measurements, but it performs well at separating AOD fraction between the FT and the PBL. AOD fractions in the FT for GEOS-Chem and EAM-E3SM are, respectively, 10 % and 15 % lower than the AOD fractions from the HSRL-2. Their similar mean AODs reflect a cancellation of high and low AOD biases. Compared with aircraft-based observations, GEOS-FP, MERRA-2, and ALADIN produce 24 %–36 % less AOD and tend to misplace more aerosols in the PBL. The models generally underestimate AODs for measured AODs that are above 0.8, indicating their limitations at reproducing high AODs. The differences in the absolute AOD, FT AOD, and the vertical apportioning of AOD in different models highlight the need to continue improving the accuracy of modeled AOD distributions. These differences affect the sign and magnitude of the net aerosol radiative forcing, especially when aerosols are in contact with clouds.

The optical properties, chemical composition, and potential chromophores of brown carbon (BrC) aerosol particles were studied during typical summertime and wintertime at a kerbside in downtown Karlsruhe, a city in central Europe. The average absorption coefficient and mass absorption efficiency at 365 nm (Abs365 and MAE365) of methanol-soluble BrC (MS-BrC) were lower in the summer period (1.6 ± 0.5 Mm−1, 0.5 ± 0.2 m2 g−1) than in the winter period (2.8 ± 1.9 Mm−1, 1.1 ± 0.3 m2 g−1). Using a parallel factor (PARAFAC) analysis to identify chromophores, two different groups of highly oxygenated humic-like substances (HO-HULIS) dominated in summer and contributed 96 ± 6 % of the total fluorescence intensity. In contrast, less-oxygenated HULIS (LO-HULIS) dominated the total fluorescence intensity in winter with 57 ± 12 %, followed by HO-HULIS with 31 ± 18 %. Positive matrix factorization (PMF) analysis of organic compounds detected in real time by an online aerosol mass spectrometer (AMS) led to five characteristic organic compound classes. The statistical analysis of PARAFAC components and PMF factors showed that LO-HULIS chromophores were most likely emitted from biomass burning in winter. HO-HULIS chromophores could be low-volatility oxygenated organic aerosol from regional transport and oxidation of biogenic volatile organic compounds (VOCs) in summer. Five nitro-aromatic compounds (NACs) were identified by a chemical ionization mass spectrometer (C7H7O3N, C7H7O4N, C6H5O5N, C6H5O4N, and C6H5O3N), which contributed 0.03 ± 0.01 % to the total organic mass but can explain 0.3 ± 0.1 % of the total absorption of MS-BrC at 365 nm in winter. Furthermore, we identified 316 potential brown carbon molecules which accounted for 2.5 ± 0.6 % of the organic aerosol mass. Using an average mass absorption efficiency (MAE365) of 9.5 m2g−1 for these compounds, we can estimate their mean light absorption to be 1.2 ± 0.2 Mm−1, accounting for 32 ± 15 % of the total absorption of MS-BrC at 365 nm. This indicates that a small fraction of brown carbon molecules dominates the overall absorption. The potential BrC molecules assigned to the LO-HULIS component had a higher average molecular weight (265 ± 2 Da) and more nitrogen-containing molecules (62 ± 1 %) than the molecules assigned to the HO-HULIS components. Our analysis shows that the LO-HULIS, with a high contribution of nitrogen-containing molecules originating from biomass burning, dominates aerosol fluorescence in winter, and HO-HULIS, with fewer nitrogen-containing molecules as low-volatility oxygenated organic aerosol from regional transport and oxidation of biogenic volatile organic compounds (VOC), dominates in summer.

In situ cloud probe data from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign were used to estimate the effective radius (Re), cloud optical thickness (τ), and cloud droplet concentration (Nc) for marine stratocumulus over the southeast Atlantic Ocean. The in situ Re, τ, and Nc were compared with co-located Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of Re and τ and MODIS-derived Nc. For 145 cloud profiles, a MODIS retrieval was co-located with in situ data with a time gap of less than 1 h. On average, the MODIS Re and τ (11.3 µm and 11.7) were 1.6 µm and 2.3 higher than the in situ Re and τ with Pearson's correlation coefficients (R) of 0.77 and 0.73, respectively. The average MODIS Nc (151.5 cm−3) was within 1 cm−3 of the average in situ Nc with an R of 0.90. The 145 cloud profiles were classified into 67 contact profiles where an aerosol concentration (Na) greater than 500 cm−3 was sampled within 100 m above cloud tops and 78 separated profiles where Na less than 500 cm−3 was sampled up to 100 m above cloud tops. Contact profiles had a higher in situ Nc (by 88 cm−3), higher τ (by 2.5), and lower in situ Re (by 2.2 µm) compared to separated profiles. These differences were associated with aerosol–cloud interactions (ACI), and MODIS estimates of the differences were within 5 cm−3, 0.5, and 0.2 µm of the in situ estimates when profiles with MODIS Re>15 µm or MODIS τ>25 were removed. The agreement between MODIS and in situ estimates of changes in Re, τ, and Nc associated with ACI was driven by small biases in MODIS retrievals of cloud properties relative to in situ measurements across different aerosol regimes. Thus, when combined with estimates of aerosol location and concentration, MODIS retrievals of marine stratocumulus cloud properties over the southeast Atlantic can be used to study ACI over larger domains and longer timescales than possible using in situ data.

Abstract This study focuses on unraveling the microphysical origins of the nonlinear elastic effects, which are pervasive in the Earth's crust. Here, we examine the influence of grain shape on the elastic nonlinearity of granular assemblies. We find that the elastic nonlinearity of angular sand particles is of the same order of magnitude as that previously measured in spherical glass beads. However, while the elastic nonlinearity of glass beads increases by an order of magnitude with RH that of sand particles is rather RH independent. We attribute this difference to the angularity of sand particles: absorbed water on the spherical grains weakens the junctions making them more nonlinear, while no such effect occurs in sand due to grain interlocking. Additionally, for one of the nonlinear parameters that likely arises from shearing/partial slip of the grain junctions, we observe a sharp amplitude threshold in sand which is not observed in glass beads.

Summary: Background: Integrase inhibitor (INSTI) with boosted darunavir (DRV/r), a regimen with a high-resistance barrier, avoiding NRTI toxicities, might be a switching option in children living with HIV (CLWHIV). Methods: SMILE is a randomised non-inferiority trial evaluating safety and antiviral efficacy of once-daily INSTI + DRV/r vs. continuing on current standard-of-care (SOC) triple ART (2NRTI + boosted PI/NNRTI) in virologically-suppressed CLWHIV aged 6–18 years. The primary outcome is the proportion with confirmed HIV-RNA ≥50 copies/mL by week 48, estimated by Kaplan–Meier method. Non-inferiority margin was 10%. Registration number for SMILE are: ISRCTN11193709, NCT #: NCT02383108. Findings: Between 10th June 2016 and 30th August 2019, 318 participants were enrolled from Africa 53%, Europe 24%, Thailand 15% and Latin America 8%, 158 INSTI + DRV/r [153 Dolutegravir (DTG); 5 Elvitegravir (EVG)], 160 SOC. Median (range) age was 14.7 years (7.6–18.0); CD4 count 782 cells/mm3 (227–1647); 61% female. Median follow-up was 64.3 weeks with no loss to follow-up. By 48 weeks, 8 INSTI + DRV/r vs. 12 SOC had confirmed HIV-RNA ≥50 copies/mL; difference (INSTI + DRV/r-SOC) −2.5% (95% CI: −7.6, 2.5%), showing non-inferiority. No major PI or INSTI resistance mutations were observed. There were no differences in safety between arms. By week 48, difference (INSTI + DRV/r-SOC) in mean CD4 count change from baseline was −48.3 cells/mm3 (95% CI: −93.4, −3.2; p = 0.036). Difference (INSTI + DRV/r-SOC) in mean HDL change from baseline was −4.1 mg/dL (95% CI: −6.7, −1.4; p = 0.003). Weight and Body Mass Index (BMI) increased more in INSTI + DRV/r than SOC [difference: 1.97 kg (95% CI: 1.1, 2.9; p

Laser surface micro-treatment refers to the use of appropriate laser energy to induce the surrounding gas and stainless steel reaction to produce a film or the use of large laser energy to manufacture micrometer grating. Using the principle of thin film interference or grating diffraction, the surface of stainless steel is marked with color, which can be used for information storage of metallurgical products. The relationship between laser line scanning and laser power is studied experimentally, the range of laser power density with color variation is obtained, and the optimal process parameters of uniform color are obtained.

High automation, high speed and high efficiency are the advantages of laser welding metallurgical products. It is a great significance to study the quality of laser welding. In the paper, the input current and pulse width of laser are used as variables to improve the tensile strength of welding samples. Firstly, the effect of current and pulse width on tensile strength is obtained through experiments. Then the fitting formula and cureve of experimental data are obtained by orthogonal regression method. Finally, the prediction and optimization of tensile strength are carried out, and the error of the results is less than 12,5 %, indicating that they have a certain guiding role.

Small α-dicarbonyls represent the major precursors of secondary organic aerosol (SOA) and brown carbon (BrC) in the atmosphere, but the chemical mechanisms leading to their formation remain unclear. Here we elucidate the fundamental kinetics and mechanisms for aqueous-phase oligomerization of glyoxal (GL) using quantum chemical and kinetic rate calculations. Our results identify several essential isomeric processes for GL, including protonation to yield diol / tetrol and carbenium ions, nucleophilic addition of carbenium ions to diol / tetrol as well as to free methylamine / ammonia (MA / AM), and deprotonation to propagate oligomers and N-heterocycles. Both protonation and nucleophilic addition occur without activation barriers and are dominantly driven by electrostatic attraction. Deprotonation proceeds readily via water molecules in the absence of MA / AM but corresponds to the rate-limiting step for N-containing cationic intermediates to yield N-heterocycles. On the other hand, the latter occurs readily via a catalytic process by acidic anions (e.g., SO42-). A carbenium ion-mediated reaction rate of GL is 4.62 × 10−3 s−1 under atmospheric conditions, in good agreement with the experimental data. Our results provide essential mechanistic and kinetic data for accurate assessment of the role of small α-dicarbonyls in SOA and BrC formation.

β-caryophyllene (BCP) is one of the most important sesquiterpenes (SQTs) in the atmosphere, with a large potential contribution to secondary organic aerosol (SOA) formation mainly from reactions with ozone (O3) and nitrate radicals (NO3). In this work, we study the temperature dependence of the kinetics of BCP ozonolysis, SOA yields, and SOA chemical composition in the dark and in the absence and presence of nitrogen oxides including nitrate radicals (NO3). We cover a temperature range of 213–313 K, representative of tropospheric conditions. The oxidized components in both gas and particle phases were characterized on a molecular level by a chemical ionization mass spectrometer equipped with a filter inlet for gases and aerosols using iodide as the reagent ion (FIGAERO-iodide-CIMS). The batch mode experiments were conducted in the 84.5 m3 aluminium simulation chamber AIDA at the Karlsruhe Institute of Technology (KIT). In the absence of nitrogen oxides, the temperature-dependent rate coefficient of the endocyclic double bond in BCP reacting with ozone between 243–313 K is negatively correlated with temperature, corresponding to the following Arrhenius equation: k= (1.6 ± 0.4) × 10−15 × exp((559 ± 97)/T). The SOA yields increase from 16 ± 5 % to 37 ± 11 %, with temperatures decreasing from 313 to 243 K at a total organic particle mass of 10 µg m−3. The variation in the ozonolysis temperature leads to a substantial impact on the abundance of individual organic molecules. In the absence of nitrogen oxides, monomers C14−15H22−24O3−7 (37.4 %), dimers C28−30H44−48O5−9 (53.7 %), and trimers C41−44H62−66O9−11 (8.6 %) are abundant in the particle phase at 213 K. At 313 K, we observed more oxidized monomers (mainly C14−15H22−24O6−9, 67.5 %) and dimers (mainly C27−29H42−44O9−11, 27.6 %), including highly oxidized molecules (HOMs; C14H22O7,9, C15H22O7,9C15H24O7,9), which can be formed via hydrogen shift mechanisms, but no significant trimers. In the presence of nitrogen oxides, the organonitrate fraction increased from 3 % at 213 K to 12 % and 49 % at 243 and 313 K, respectively. Most of the organonitrates were monomers with C15 skeletons and only one nitrate group. More highly oxygenated organonitrates were observed at higher temperatures, with their signal-weighted O:C atomic ratio increasing from 0.41 to 0.51 from 213 to 313 K. New dimeric and trimeric organic species without nitrogen atoms (C20, C35) were formed in the presence of nitrogen oxides at 298–313 K, indicating potential new reaction pathways. Overall, our results show that increasing temperatures lead to a relatively small decrease in the rate coefficient of the endocyclic double bond in BCP reacting with ozone but to a strong decrease in SOA yields. In contrast, the formation of HOMs and organonitrates increases significantly with temperature.

A light source has been built at the AIDA (Aerosol Interactions and Dynamics in the Atmosphere) simulation chamber at the Karlsruhe Institute of Technology, simulating solar radiation at ground level. Instead of full spectra light sources, it uses a combination of LEDs with a narrow emission spectrum, resulting in a combined spectrum similar to the solar spectrum between 300 and 530 nm. The use of LEDs leads to an energy-efficient, robust and versatile illumination concept. The light source can be used over a wide temperature range down to −90 ∘C and is adjustable in intensity and spectral width as well as easily adjustable to new technological developments or scientific needs. Characterization of the illumination conditions shows a vertical intensity gradient in the chamber. The integral intensity corresponds to a NO2 photolysis frequency j(NO2) of (1.58±0.21(1σ))×10-3 s−1 for temperatures between 213 and 295 K. At constant temperature, the light intensity is stable within ±1 %. While the emissions of the different LEDs change with temperature, they can be adjusted, and thus it is possible to adapt the spectrum for different temperatures. Although the illumination of the simulation chamber leads to an increase of 0.7 K h−1 of the mean gas temperature, it is possible to perform experiments with aqueous droplets at relative humidities up to ≤95 % and also above water or ice saturation with corresponding clouds. Additionally, temperature- and wavelength-dependent photolysis experiments with 2,3-pentanedione have been conducted. The photolysis of 2,3-pentanedione occurs mainly between 400 and 460 nm, resulting in a mean photolysis frequency of (1.03±0.15)×10-4 s−1 independent of temperature in the range 213–298 K with a quantum yield of 0.36±0.04. In contrast, the yield of the two main photolysis products, acetaldehyde and formaldehyde, decreases with temperature. Furthermore, the light source was applied to study the photochemistry of aerosol particles. For the atmospheric brown carbon proxy compound 3,5-diacetyl-2,4,6-trimethyl-1,4-dihydropyridine, photochemical reaction products were identified. In aerosol particles containing iron oxalate as a photosensitizer, the photosensitized degradation of organic acids (pinic and pinonic acid) was studied. Although the light source only generates about one-third of the maximum solar irradiation at ground level at Karlsruhe (49.007∘ N, 8.404∘ E; 12:00 UTC+2) on a clear summer day with a substantial intensity gradient throughout the simulation chamber, it could be shown that this type of light source allows reproducible experiments over a wide range of simulated atmospheric conditions and with a large flexibility and control of the irradiation spectrum.

Biomass burning smoke is advected over the southeastern Atlantic Ocean between July and October of each year. This smoke plume overlies and mixes into a region of persistent low marine clouds. Model calculations of climate forcing by this plume vary significantly in both magnitude and sign. NASA EVS-2 (Earth Venture Suborbital-2) ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) had deployments for field campaigns off the west coast of Africa in 3 consecutive years (September 2016, August 2017, and October 2018) with the goal of better characterizing this plume as a function of the monthly evolution by measuring the parameters necessary to calculate the direct aerosol radiative effect. Here, this dataset and satellite retrievals of cloud properties are used to test the representation of the smoke plume and the underlying cloud layer in two regional models (WRF-CAM5 and CNRM-ALADIN) and two global models (GEOS and UM-UKCA). The focus is on the comparisons of those aerosol and cloud properties that are the primary determinants of the direct aerosol radiative effect and on the vertical distribution of the plume and its properties. The representativeness of the observations to monthly averages are tested for each field campaign, with the sampled mean aerosol light extinction generally found to be within 20 % of the monthly mean at plume altitudes. When compared to the observations, in all models, the simulated plume is too vertically diffuse and has smaller vertical gradients, and in two of the models (GEOS and UM-UKCA), the plume core is displaced lower than in the observations. Plume carbon monoxide, black carbon, and organic aerosol masses indicate underestimates in modeled plume concentrations, leading, in general, to underestimates in mid-visible aerosol extinction and optical depth. Biases in mid-visible single scatter albedo are both positive and negative across the models. Observed vertical gradients in single scatter albedo are not captured by the models, but the models do capture the coarse temporal evolution, correctly simulating higher values in October (2018) than in August (2017) and September (2016). Uncertainties in the measured absorption Ångstrom exponent were large but propagate into a negligible (<4 %) uncertainty in integrated solar absorption by the aerosol and, therefore, in the aerosol direct radiative effect. Model biases in cloud fraction, and, therefore, the scene albedo below the plume, vary significantly across the four models. The optical thickness of clouds is, on average, well simulated in the WRF-CAM5 and ALADIN models in the stratocumulus region and is underestimated in the GEOS model; UM-UKCA simulates cloud optical thickness that is significantly too high. Overall, the study demonstrates the utility of repeated, semi-random sampling across multiple years that can give insights into model biases and how these biases affect modeled climate forcing. The combined impact of these aerosol and cloud biases on the direct aerosol radiative effect (DARE) is estimated using a first-order approximation for a subset of five comparison grid boxes. A significant finding is that the observed grid box average aerosol and cloud properties yield a positive (warming) aerosol direct radiative effect for all five grid boxes, whereas DARE using the grid-box-averaged modeled properties ranges from much larger positive values to small, negative values. It is shown quantitatively how model biases can offset each other, so that model improvements that reduce biases in only one property (e.g., single scatter albedo but not cloud fraction) would lead to even greater biases in DARE. Across the models, biases in aerosol extinction and in cloud fraction and optical depth contribute the largest biases in DARE, with aerosol single scatter albedo also making a significant contribution.

The phenomenon in which the warming rate of air temperature is amplified with elevation is termed elevation-dependent warming (EDW). It has been clarified that EDW can accelerate the retreat of glaciers and melting of snow, which can have significant impacts on the regional ecological environment. Owing to the lack of high-density ground observations in high mountains, there is widespread controversy regarding the existence of EDW. Current evidence is mainly derived from typical high-mountain regions such as the Swiss Alps, the Colorado Rocky Mountains, the tropical Andes and the Tibetan Plateau–Himalayas. Rare evidence in other mountain ranges has been reported, especially in arid regions. In this study, EDW features (regional warming amplification and altitude warming amplification) in the Chinese Tian Shan (CTM) were detected using a unique high-resolution (1 km, 6-hourly) air temperature dataset (CTMD) from 1979 to 2016. The results showed that there were significant EDW signals at different altitudes on different timescales. The CTM showed significant regional warming amplification in spring, especially in March, and the warming trends were greater than those of continental China with respect to three temperatures (minimum temperature, mean temperature and maximum temperature). The significance values of EDW above different altitude thresholds are distinct for three temperatures in 12 months. The warming rate of the minimum temperature in winter showed a significant elevation dependence (p), especially above 3000 m. The greatest altitudinal gradient in the warming rate of the maximum temperature was found above 4000 m in April. For the mean temperature, the warming rates in June and August showed prominent altitude warming amplification but with different significance above 4500 m. Within the CTM, the Tolm Mountains, the eastern part of the Borokoonu Mountains, the Bogda Mountains and the Balikun Mountains are representative regions that showed significant altitude warming amplification on different timescales. This new evidence could partly explain the accelerated melting of snow in the CTM, although the mechanisms remain to be explored.

Observations of rapid ongoing grounding line retreat, ice shelf thinning and accelerated ice flow from the West Antarctic Ice Sheet (WAIS) may forebode a possible collapse if global temperatures continue to increase. Understanding and reconstructing West Antarctic Ice Sheet dynamics in past warmer-than-present times will inform about its behavior as an analogue for future climate scenarios. International Ocean Discovery Program (IODP) Expedition 379 visited the Amundsen Sea sector of Antarctica to obtain geological records suitable for this purpose. During the expedition, cores from two drill sites at the Resolution Drift on the continental rise returned sediments whose deposition was possibly influenced by West Antarctic Ice Sheet dynamics from late Miocene to Holocene times. To examine the West Antarctic Ice Sheet dynamics, shipboard physical properties and sedimentological data are correlated with seismic data and extrapolated across the Resolution Drift via core-log-seismic integration. An interval with strongly variable physical properties, high diatom abundance and ice-rafted debris occurrence, correlating with partially high amplitude seismic reflection characteristics was identified between 4.2 and 3.2 Ma. Sedimentation during this interval is interpreted as having occurred during an extended warm period with a dynamic West Antarctic Ice Sheet in the Amundsen Sea sector. These records compare to those of other drill sites in the Ross Sea and the Bellingshausen Sea, and thus suggest an almost simultaneous occurrence of extended warm periods in all three locations.

Boulder bars are a common form of riverbed morphology that could be affected by landslide dams. However, few studies have focused on the formation and geometry characteristics of boulder bars due to outburst floods triggered by landslide dam failure. In such a way, eight group landslide dam failure experiments with a movable bed length of 4 to 7 times the dam length with 25 boulder bars were carried out. In addition, 38 boulder bars formed in the field triggered by four landslide dam failures were investigated. The aim of this paper is to study the formation and geometry characteristics of boulder bars along the riverbeds. The results show that boulder bars are formed after peak discharge of outburst flow. The number of boulder bars is 0.4 to 1.0 times the ratio of riverbed length to dam bottom length. Besides, boulder bars have the characteristic of lengthening upstream during the failure process. A boulder bar's upstream edge has a more extensive development than a boulder bar's downstream edge. The length of a boulder bar along the channel changes faster than the boulder bar's width and height. After the dam failure, the boulder bar's length is about 8 to 14 times its width. The relationship between the ratio of boulder bar length to width and the boulder bar's dimensionless length could be described with a hyperbolic equation. The dimensionless area of the boulder bar increases linearly with the dimensionless area of the river section, and the linear ratio is about 0.5. With the field data, this demonstrates that the formation and geometry characteristics of boulder bars in tests are consistent with the field boulder bars. Therefore, the results in this paper are credible and can be applied to the riverbed's geomorphological characteristics analysis triggered by overtopped landslide dam failure. The plentiful experimental and field data could contribute to the community boulder bar research.

Fire is an important source of ozone (O3) precursors. The formation of surface O3 can cause damage to vegetation and reduce stomatal conductance. Such processes can feed back to inhibit dry deposition and indirectly enhance surface O3. Here, we apply a fully coupled chemistry–vegetation model to estimate the indirect contributions of global fires to surface O3 through O3–vegetation feedback during 2005–2012. Fire emissions directly increase the global annual mean O3 by 1.2 ppbv (5.0 %) with a maximum of 5.9 ppbv (24.4 %) averaged over central Africa by emitting a substantial number of precursors. Considering O3–vegetation feedback, fires additionally increase surface O3 by 0.5 ppbv averaged over the Amazon in October, 0.3 ppbv averaged over southern Asia in April, and 0.2 ppbv averaged over central Africa in April. During extreme O3–vegetation interactions, such a feedback can rise to >0.6 ppbv in these fire-prone areas. Moreover, large ratios of indirect-to-direct fire O3 are found in eastern China (3.7 %) and the eastern US (2.0 %), where the high ambient O3 causes strong O3–vegetation interactions. With the likelihood of increasing fire risks in a warming climate, fires may promote surface O3 through both direct emissions and indirect chemistry–vegetation feedbacks. Such indirect enhancement will cause additional threats to public health and ecosystem productivity.

Background: Patients scheduled for coronary angiography may feel insufficiently informed about the planned procedure. We aimed to evaluate the patient-rated quality of the Informed Consent (IC) process and to investigate the efficacy of medical graphics to assist and improve the IC procedure. Methods: A graphic-based information broschure illustrating central steps of the procedure was created in collaboration with scientific illustrators. In a randomized, controlled, prospective trial, 121 patients undergoing coronary angiography/PCI were randomized to a group obtaining the usual IC (Control group) or to a group that additionally obtained a graphic-based IC (Comic group). The perceived quality of the IC was compared between groups using single items of the Client Satisfaction Questionnaire-8 and self-designed single items. Results: Only 67.8% of patients stated to have completely read the standard written IC sheet. The quality of the IC was perceived to be very good in 45.0% of patients in the Comic group compared to 24.6% in the Control group (p =.023). 57.4% of the Control group compared to 76.7% of the Comic group stated that all of their questions were satisfactorily adressed (p =.015). 43.3% of the Comic group, in contrast to only 18.0% of the Control group, declared to feel „very satisfied“ with the obtained IC procedure (p =.002). The acceptance of this new IC approach was very high: no patient expressed feelings of not being taken seriously when reading medical graphics. Conclusions: Our data confirm pronounced limitations of the usual IC practice. The use of medical graphics positively impacts on patient-evaluated endpoints and may significantly improve the IC procedure.

This study introduces an efficient deep-learning model based on convolutional neural networks with joint autoencoder and adversarial structures for 3D subsurface mapping from 2D surface observations. The method was applied to delineate paleovalleys in an Australian desert landscape. The neural network was trained on a 6400 km2 domain by using a land surface topography as 2D input and an airborne electromagnetic (AEM)-derived probability map of paleovalley presence as 3D output. The trained neural network has a squared error across 99 % of the training domain and produces a squared error across 93 % of the validation domain, demonstrating that it is reliable in reconstructing 3D paleovalley patterns beyond the training area. Due to its generic structure, the neural network structure designed in this study and the training algorithm have broad application potential to construct 3D geological features (e.g., ore bodies, aquifer) from 2D land surface observations.

Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA EVS-2 (Earth Venture Suborbital-2) investigation with three intensive observation periods designed to study key atmospheric processes that determine the climate impacts of these aerosols. During the Southern Hemisphere winter and spring (June–October), aerosol particles reaching 3–5 km in altitude are transported westward over the southeast Atlantic, where they interact with one of the largest subtropical stratocumulus (Sc) cloud decks in the world. The representation of these interactions in climate models remains highly uncertain in part due to a scarcity of observational constraints on aerosol and cloud properties, as well as due to the parameterized treatment of physical processes. Three ORACLES deployments by the NASA P-3 aircraft in September 2016, August 2017, and October 2018 (totaling ∼350 science flight hours), augmented by the deployment of the NASA ER-2 aircraft for remote sensing in September 2016 (totaling ∼100 science flight hours), were intended to help fill this observational gap. ORACLES focuses on three fundamental science themes centered on the climate effects of African BB aerosols: (a) direct aerosol radiative effects, (b) effects of aerosol absorption on atmospheric circulation and clouds, and (c) aerosol–cloud microphysical interactions. This paper summarizes the ORACLES science objectives, describes the project implementation, provides an overview of the flights and measurements in each deployment, and highlights the integrative modeling efforts from cloud to global scales to address science objectives. Significant new findings on the vertical structure of BB aerosol physical and chemical properties, chemical aging, cloud condensation nuclei, rain and precipitation statistics, and aerosol indirect effects are emphasized, but their detailed descriptions are the subject of separate publications. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project and the dataset it produced.

The changes of hardening depth and surface hardness of C45 steel after laser surface quenching were studied. Firstly, the Nd: YAG laser and CO2 laser were used to realize the surface quenching. High power CO2 laser quenching C45 steel, variable process parameters include power, scanning speed and defocusing distance. Then, the Nd:YAG laser was used to quench the samples through orthogonal experiments, and the optimized process parameters were obtained, and the surface hardness was obviously improved. Finally, by comparing the quenching C45 steel of CO2 laser, the influence curve of process parameters on surface hardness was found, and the optimal process parameters were obtained.

Ferredoxin-thioredoxin reductase (FTR) is an iron-sulfur protein that supplies electrons from photochemically reduced ferredoxin (Fd) to thioredoxin (Trx) in the ferredoxin/thioredoxin system in chloroplasts. The FTR is a heterodimer with a variable subunit (FTRv) and a catalytic subunit (FTRc). The function of FTRv is not well known. In petunia (Petunia hybrida), FTRv is a single-copy gene, which is named PhFTRv. In this study, the spatio-temporal expression of PhFTRv in petunia was analyzed, and PhFTRv transcription was found to be high in leaves and stems. A tobacco rattle virus gene silencing was used in this study. Virus induced gene silencing-mediated PhFTRv silencing resulted in large yellow-green leaves, delayed flowering, and reduced cold tolerance in petunia plants.

ABSTRACTThe coronavirus disease 2019 (COVID-19) pandemic has resulted in millions of patients infected worldwide and indirectly affecting even more individuals through disruption of daily living. Long-term adverse outcomes have been reported with similar diseases from other coronaviruses, namely Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Emerging evidence suggests that COVID-19 adversely affects different systems in the human body. This review summarizes the current evidence on the short-term adverse health outcomes and assesses the risk of potential long-term adverse outcomes of COVID-19. Major adverse outcomes were found to affect different body systems: immune system (including but not limited to Guillain-Barré syndrome and paediatric inflammatory multisystem syndrome), respiratory system (lung fibrosis and pulmonary thromboembolism), cardiovascular system (cardiomyopathy and coagulopathy), neurological system (sensory dysfunction and stroke), as well as cutaneous and gastrointestinal manifestations, impaired hepatic and renal function. Mental health in patients with COVID-19 was also found to be adversely affected. The burden of caring for COVID-19 survivors is likely to be huge. Therefore, it is important for policy makers to develop comprehensive strategies in providing resources and capacity in the healthcare system. Future epidemiological studies are needed to further investigate the long-term impact on COVID-19 survivors.

Disruption prediction has made rapid progress in recent years, especially in machine learning (ML)-based methods. If a disruption prediction model can be interpreted, it can tell why certain samples are classified as disruption precursors. This allows us to tell the types of incoming disruption for disruption avoidance and gives us insight into the mechanism of disruption. This paper presents a disruption predictor called interpretable disruption predictor based on physics-guided feature extraction (IDP-PGFE) and its results on J-TEXT experiment data. The prediction performance of IDP-PGFE with physics-guided features is effectively improved (true positive rate = 97.27%, false positive rate = 5.45%, area under the ROC curve = 0.98) compared to the models with raw signal input. The validity of the interpretation results is ensured by the high performance of the model. The interpretability study using an attribution technique provides an understanding of J-TEXT disruption and conforms to our prior comprehension of disruption. Furthermore, IDP-PGFE gives a possible mean on inferring the underlying cause of the disruption and how interventions affect the disruption process in J-TEXT. The interpretation results and the experimental phenomenon have a high degree of conformity. The interpretation results also gives a possible experimental analysis direction that the resonant magnetic perturbations delays the density limit disruption by affecting both the MHD instabilities and the radiation profile. PGFE could also reduce the data requirement of IDP-PGFE to 10% of the training data required to train a model on raw signals. This made it possible to be transferred to the next-generation tokamaks, which cannot provide large amounts of data. Therefore, IDP-PGFE is an effective approach to exploring disruption mechanisms and transferring disruption prediction models to future tokamaks.

In this paper, Neodymium-doped Yttrium Aluminum Garnet crystal laser welding machine is used to study the laser welding process of dual phase steel. The electric current, pulse width and frequency are selected as variables for welding, and the maximum force of weldment under different parameters is detected by tensile testing machine. Through the analysis of the experimental results, find out the influence of different parameters on the welding quality, select the best welding parameters. The analysis shows that the current has the most significant effect on the welding quality, followed by the frequency, and the pulse width has almost no effect.

Summary Background Neuroimaging studies have identified obesity‐related differences in the brain's resting state activity. An imbalance between homeostatic and reward aspects of ingestive behaviour may contribute to obesity and food addiction. The interactions between early life adversity (ELA), the reward network and food addiction were investigated to identify obesity and sex‐related differences, which may drive obesity and food addiction. Methods Functional resting state magnetic resonance imaging was acquired in 186 participants (high body mass index [BMI]: ≥25: 53 women and 54 men; normal BMI: 18.50–24.99: 49 women and 30 men). Participants completed questionnaires to assess ELA (Early Traumatic Inventory) and food addiction (Yale Food Addiction Scale). A tripartite network analysis based on graph theory was used to investigate the interaction between ELA, brain connectivity and food addiction. Interactions were determined by computing Spearman rank correlations, thresholded at q

Millions of tons of bottom sediments are dredged annually all over the world. Ports and bays need to extract the sediments to guarantee the navigation levels or remediate the aquatic ecosystem. The removed material is commonly disposed of in open oceans or landfills. These disposal methods are not in line with circular-economy goals and additionally are unsuitable due to their legal and environmental compatibility. Recovery of valuables represents a way to eliminate dumping and contributes towards the sustainable extraction of secondary raw materials. Nevertheless, the recovery varies on a case-by-case basis and depends on the sediment components. Therefore, the first step is to analyse and identify the sediment composition and properties. Malmfjärden is a shallow semi-enclosed bay located in Kalmar, Sweden. Dredging of sediments is required to recuperate the water level. This study focuses on characterizing the sediments, pore water and surface water from the bay to uncover possible sediment recovery paths and define the baseline of contamination in the water body. The results showed that the bay had high amounts of nitrogen (170–450 µg L−1), leading to eutrophication problems. The sediments mainly comprised small size particle material (silt, clay and sand proportions of 62 %–79 %, 14 %–20 %, 7 %–17 %, respectively) and had a medium–high level of nitrogen (7400–11 000 mg kg−1). Additionally, the sediments had little presence of organic pollutants and low–medium concentration of metals or metalloids. The characterization of the sediments displays a potential use in less sensitive lands such as in industrial and commercial areas where the sediments can be employed as construction material or as plant-growing substrate (for ornamental gardens or vegetation beside roads).

Paleovalleys are buried ancient river valleys that often form productive aquifers, especially in the semiarid and arid areas of Australia. Delineating their extent and hydrostratigraphy is however a challenging task in groundwater system characterization. This study developed a methodology based on the deep learning super-resolution convolutional neural network (SRCNN) approach, to convert electrical conductivity (EC) estimates from an airborne electromagnetic (AEM) survey in South Australia to a high-resolution binary paleovalley map. The SRCNN was trained and tested with a synthetic training dataset, where valleys were generated from readily available digital elevation model (DEM) data from the AEM survey area. Electrical conductivities typical of valley sediments were generated by Archie's law, and subsequently blurred by down-sampling and bicubic interpolation to represent noise from the AEM survey, inversion and interpolation. After a model training step, the SRCNN successfully removed such noise, and reclassified the low-resolution, converted unimodal but skewed EC values into a high-resolution paleovalley index following a bimodal distribution. The latter allows us to distinguish valley from non-valley pixels. Furthermore, a realistic spatial connectivity structure of the paleovalley was predicted when compared with borehole lithology logs and a valley bottom flatness indicator. Overall the methodology permitted us to better constrain the three-dimensional paleovalley geometry from AEM images that are becoming more widely available for groundwater prospecting.