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Brassica napus is a globally important vegetable and oil crop. The research is meaningful for the yield and plant architecture of B. napus. In this study, one natural mutant line with determinate and capitulum-like inflorescence was chosen for further study. Genetic analysis indicated that the segregation patterns of inflorescences in the F2 populations supported a digenic inheritance model, which was further approved via the BSA-Seq technique. The BSA-Seq method detected two QTL regions on C02 (14.27–18.41 Mb) and C06 (32.98–33.68 Mb) for the genetic control of determinate inflorescences in MT plants. In addition, the expression profile in MT compared with WT was analyzed, and a total of 133 candidate genes for regulating the flower development (75 genes, 56.4%), shoot meristem development (29 genes, 21.8%), and inflorescence meristem development (13 genes, 9.8%) were identified. Then one joint analysis combing BSA-Seq and RNA-Seq identified two candidate genes of BnaTFL1 and BnaAP1 for regulating the MT phenotype. Furthermore, the potential utilization of the MT plants was also discussed. [ABSTRACT FROM AUTHOR]

Epsilon toxin (ETX) is an exotoxin produced by type B and D Clostridium perfringens that causes enterotoxemia or necrotic enteritis in animals such as goats, sheep, and cattle. Vaccination is a key method in preventing such diseases. In this study, we developed a new type of dissolving microneedle patch (dMN) with a nanoparticle adjuvant for enhanced immune response to deliver the rETXY196E-C protein vaccine. We chose FDA-approved poly(lactic-co-glycolic acid) (PLGA) to prepare nanospheres as the vaccine adjuvant and introduced dimethyldioctadecylammonium bromide (DDAB) to make the surface of PLGA nanoparticles (PLGA NPs) positively charged for antigen adsorption. PLGA NPs with a diameter of 100~200 nm, a surface ZETA potential of approximately +40 mV, and good safety were successfully prepared and could effectively adsorb rETXY196E-C protein. Using non-toxic and antibacterial fish gelatin as the microneedle (MN) matrix, we prepared a PLGA-DDAB dMN vaccine with good mechanical properties that successfully penetrated the skin. After immunization of subcutaneous (SC) and dMN, antibody titers of the PLGA and Al adjuvant groups were similar in both two immune ways. However, in vivo neutralization experiments showed that the dMN vaccines had a better protective effect. When challenged with 100 × LD50 GST-ETX, the survival rate of the MN group was 100%, while that of the SC Al group was 80%. However, a 100% protective effect was achieved in both immunization methods using PLGA NPs. In vitro neutralization experiments showed that the serum antibodies from the dMN and SC PLGA NPs groups both protect naive mice from 10 × LD50 GST-ETX attack after being diluted 20 times and could also protect MDCK cells from 20 × CT50 GST-ETX attack. In conclusion, the PLGA-DDAB dMN vaccine we prepared has good mechanical properties, immunogenicity, and protection, and can effectively prevent ETX poisoning. This provides a better way of delivering protein vaccines. [ABSTRACT FROM AUTHOR]

Our understanding of molecules has stagnated at a single quantum system, with atoms as Newtonian particles and electrons as quantum particles. Here, however, we reveal that both atoms and electrons in a molecule are quantum particles, and their quantum–quantum interactions create a previously unknown, newfangled molecular property—supracence. Molecular supracence is a phenomenon in which the molecule transfers its potential energy from quantum atoms to photo-excited electrons so that the emitted photon has more energy than that of the absorbed one. Importantly, experiments reveal such quantum energy exchanges are independent of temperature. When quantum fluctuation results in absorbing low-energy photons, yet still emitting high-energy photons, supracence occurs. This report, therefore, reveals novel principles governing molecular supracence via experiments that were rationalized by full quantum (FQ) theory. This advancement in understanding predicts the super-spectral resolution of supracence, and molecular imaging confirms such innovative forecasts using closely emitting rhodamine 123 and rhodamine B in living cell imaging of mitochondria and endosomes. [ABSTRACT FROM AUTHOR]

Strain rate is a critical parameter in the mechanical application of nano-devices. A comparative atomistic study on both perfect monocrystalline silicon crystal and silicon nanowire was performed to investigate how the strain rate affects the mechanical response of these silicon structures. Using a rate response model, the strain rate sensitivity and the critical strain rate of two structures were given. The rate-dependent dislocation activities in the fracture process were also discussed, from which the dislocation nucleation and motion were found to play an important role in the low strain rate deformations. Finally, through the comparison of five equivalent stresses, the von Mises stress was verified as a robust yield criterion of the two silicon structures under the strain rate effects. [ABSTRACT FROM AUTHOR]

In order to increase the loading of rare earth- and molybdenum-rich high-level waste in the waste forms, zirconolite- and powellite-based multi-phase borosilicate glass-ceramics were synthesized via an in-situ heat treatment method. The effects of the CTZ (CaO, TiO2 and ZrO2) content on the crystallization, microstructure and aqueous durability of the multi-phase borosilicate glass-ceramics were studied. The results indicate that the increase of CTZ content can promote crystallization. The glass-ceramics presented even structures when the CTZ content was ≥ 40 wt%. For the glass-ceramic with 40 wt% CTZ, only zirconolite and powellite crystals were detected and powellite crystals were mainly distributed around zirconolite, whereas for the glass-ceramics with 50 wt% CTZ, perovskite was detected. Furthermore, the leaching rates of Na, Ca, Mo and Nd were in the ×10−3, ×10−4, ×10−3 and ×10−5 g·m−2·d·−1 orders of magnitude on the 28th leaching day, respectively. [ABSTRACT FROM AUTHOR]

The number of distinct components of a high-order material/physical tensor might be remarkably reduced if it has certain symmetry types due to the crystal structure of materials. An nth-order tensor could be decomposed into a direct sum of deviators where the order is not higher than n, then the symmetry classification of even-type deviators is the basis of the symmetry problem for arbitrary even-order physical tensors. Clearly, an nth-order deviator can be expressed as the traceless symmetric part of tensor product of n unit vectors multiplied by a positive scalar from Maxwell's multipole representation. The set of these unit vectors shows the multipole structure of the deviator. Based on two steps of exclusion, the symmetry classifications of all even-type deviators are obtained by analyzing the geometric symmetry of the unit vector sets, and the general results are provided. Moreover, corresponding to each symmetry type of the even-type deviators up to sixth-order, the specific multipole structure of the unit vector set is given. This could help to identify the symmetry types of an unknown physical tensor and possible back-calculation of the involved physical coefficients. [ABSTRACT FROM AUTHOR]

Mechanical anisotropy and point defects would greatly affect the product quality while producing silicon wafers via diamond-wire cutting. For three major orientations concerned in wafer production, their mechanical performances under the nanoscale effects of a point defect were systematically investigated through molecular dynamics methods. The results indicated anisotropic mechanical performance with fracture phenomena in the uniaxial deformation process of monocrystalline silicon. Exponential reduction caused by the point defect has been demonstrated for some properties like yield strength and elastic strain energy release. Dislocation analysis suggested that the slip of dislocations appeared and created hexagonal diamond structures with stacking faults in the [100] orientation. Meanwhile, no dislocation was observed in [110] and [111] orientations. Visualization of atomic stress proved that the extreme stress regions of the simulation models exhibited different geometric and numerical characteristics due to the mechanical anisotropy. Moreover, the regional evolution of stress concentration and crystal fracture were interrelated and mutually promoted. This article contributes to the research towards the mechanical and fracture anisotropy of monocrystalline silicon. [ABSTRACT FROM AUTHOR]

The molecular dynamics method was used to simulate the fracture process of monocrystalline silicon with different sizes of point defect under a constant strain rate. The mechanism of the defect size on the mechanical properties of monocrystalline silicon was also investigated. The results suggested that the point defect significantly reduces the yield strength of monocrystalline silicon. The relationships between the yield strength variation and the size of point defect fitted an exponential function. By statistically analyzing the internal stress in monocrystalline silicon, it was found that the stress concentration induced by the point defect led to the decrease in the yield strength. A comparison between the theoretical strength given by the four theories of strength and actual strength proved that the Mises theory was the best theory of strength to describe the yield strength of monocrystalline silicon. The dynamic evolution process of Mises stress and dislocation showed that the fracture was caused by the concentration effect of Mises stress and dislocation slip. Finally, the fractured microstructures were similar to a kind of two-dimensional grid which distributed along the cleavage planes while visualizing the specimens. The results of this article provide a reference for evaluating the size effects of point defects on the mechanical properties of monocrystalline silicon. [ABSTRACT FROM AUTHOR]

Spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) provides a new opportunity for land observation. This study is the first to compare and evaluate the performance of the only two spaceborne GNSS-R satellite missions whose data are publicly available, i.e., the UK's TechdemoSat-1 (TDS-1) and the US's Cyclone Global Navigation Satellite System (CYGNSS), for sensitivity analysis with SMAP SM on a daily basis and soil moisture (SM) estimates on a monthly basis over Mainland China. For daily sensitivity analysis, the two data were matched up and compared for the period (i.e., May 2017 through April 2018) when they coexisted (R = 0.561 vs. R = 0.613). For monthly SM estimates, a back-propagation artificial neural network (BP-ANN) was used to construct a model using data from more than two years. The model was subsequently used to derive long-term and continuous SM maps over Mainland China. The results showed that TDS-1 and CYGNSS agree and correlate very well with the SMAP SM in Mainland China (R = 0.676, MAE = 0.052 m3m−3, and ubRMSE = 0.060 m3m−3 for TDS-1; R = 0.798, MAE = 0.040 m3m−3, and ubRMSE = 0.062 m3m−3 for CYGNSS). The retrieved results were further validated using monthly in situ SM data from dense sites across Mainland China. It was found that the SM derived from the TDS-1/CYGNSS also correlated well with in situ SM (R = 0.687, MAE = 0.066 m3m−3, and ubRMSE = 0.056 m3m−3 for TDS-1; R = 0.724, MAE = 0.052 m3m−3, and ubRMSE = 0.053 m3m−3 for CYGNSS). The results in this study suggested that TDS-1/CYGNSS and the upcoming spaceborne GNSS-R mission could be new and powerful data sources to produce SM data set at a large scale and with relatively high precision. [ABSTRACT FROM AUTHOR]

Spaceborne global navigation satellite system reflectometry (GNSS-R) data collected by the UK TechDemoSat-1 (TDS-1) satellite is applied to retrieve global lake levels for the first time. Lake levels of 351 global lakes (area greater than 500 km2 and elevation lower than 3000 m each) are estimated using TDS-1 Level 1b data over 2015–2017. Strong correlations (overall R2 greater than 0.95) are observed among lake levels derived from TDS-1 and other altimetry satellites such as CryoSat-2, Jason, and Envisat (the latter two are collected by Hydroweb), although with large root-mean-square error (RMSE) (tens of meters) mainly due to the fact that TDS-1 is not dedicated for altimetry measuring purpose. Examples of the Caspian Sea and the Poyang Lake show consistent spatial and temporal variations between TDS-1 and other data sources. The results in this paper provide supportive information for further application of GNSS-R constellations to measure altimetry of inland water bodies. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented which includes articles on topics including application of Synthetic Aperture Radar (SAR) Backscatter and InSAR coherence to monitor the wetland extent across Amazon lowland, and precipitation estimates, using remote sensing data.

NASA's Cyclone Global Navigation Satellite System (CYGNSS) mission, launched in 2016, is a small satellite constellation designed to measure the ocean surface wind speed in hurricanes and tropical cyclones. To explore its additional capabilities for applications on the land surface, this study investigated the advantages and limitations of using CYGNSS data to monitor flood inundation during typhoon and extreme precipitation events in southeast China in 2017. The results showed that despite the lack of quantitative evaluation, the CYGNSS-derived surface reflectivity (SR) and flood inundation area was qualitatively consistent with the Global Precipitation Measurement (GPM)-derived precipitation and Soil Moisture Active Passive (SMAP)/Soil Moisture and Ocean Salinity (SMOS)-derived total brightness temperature at circular polarization ( T b C ). The results provide supporting evidence for further designation of Global Navigation Satellite System (GNSS) reflectometry (GNSS-R) constellations to monitor land surface hydrology. [ABSTRACT FROM AUTHOR]

Synaptic plasticity enhances or reduces connections between neurons, affecting learning and memory. Postsynaptic AMPARs mediate greater than 90% of the rapid excitatory synaptic transmission in glutamatergic neurons. The number and subunit composition of AMPARs are fundamental to synaptic plasticity and the formation of entire neural networks. Accordingly, the insertion and functionalization of AMPARs at the postsynaptic membrane have become a core issue related to neural circuit formation and information processing in the central nervous system. In this review, we summarize current knowledge regarding the related mechanisms of AMPAR expression and trafficking. The proteins related to AMPAR trafficking are discussed in detail, including vesicle-related proteins, cytoskeletal proteins, synaptic proteins, and protein kinases. Furthermore, significant emphasis was placed on the pivotal role of the actin cytoskeleton, which spans throughout the entire transport process in AMPAR transport, indicating that the actin cytoskeleton may serve as a fundamental basis for AMPAR trafficking. Additionally, we summarize the proteases involved in AMPAR post-translational modifications. Moreover, we provide an overview of AMPAR transport and localization to the postsynaptic membrane. Understanding the assembly, trafficking, and dynamic synaptic expression mechanisms of AMPAR may provide valuable insights into the cognitive decline associated with neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite System Reflectometry (GNSS-R) is an emerging earth observation method for remote sensing of feature parameters using reflected signals from navigation satellites, and is a purely specular bistatic forward scattering observation means with special right-handed circular polarization incident wave. In this paper, the small-slope approximation model of non-Gaussian sea surface is used as the basis to construct the scattering model for the observation geometry of GNSS-R as well as the L-band characteristics, and the fully-polarization normalized bistatic radar scattering cross section (NBRCS) are simulated by the method of polarization synthesis to analyze the scattering characteristics under different wind speeds and directions on the ocean surface, which highlights the variation of NBRCS with wind direction, and the scattering modeling accuracy is improved by comparing with the data of CYGNSS. In addition, we adopt the observation geometry deviating from purely specular geometry, discuss the scattering azimuth angle, scattering influence, and the relative relationship between different polarizations of the scattering angle under the non-specular geometry. [ABSTRACT FROM AUTHOR]

Background: Primary pelvis and spine osteosarcoma (PSOS) is a specific type of osteosarcoma that is difficult to treat and has a poor prognosis. In recent years, the research on osteosarcoma has been increasing, but there have been few studies on PSOS; in particular, there have been a lack of analyses with a large sample size. This study aimed to construct and validate a model to predict the overall survival (OS) of PSOS patients, as currently there are no tools available for assessing their prognosis. Methods: Data including demographic information, clinical characteristics, and follow-up information on patients with PSOS were collected from the Surveillance, Epidemiology, and End Results (SEER) database, as well as from the Spine Tumor Center of Changzheng Hospital. Variable selection was achieved through a backward procedure based on the Akaike Information Criterion (AIC). Prognostic factors were identified by univariate and multivariate Cox analysis. A nomogram was further constructed for the estimation of 1-, 3-, and 5-year OS. Calibration plots, the concordance index (C-index), and the receiver operating characteristic (ROC) were used to evaluate the prediction model. Results: In total, 83 PSOS patients and 90 PSOS patients were separately collected from the SEER database and Changzheng Hospital. In the SEER cohort, liver metastasis, lung metastasis, and chemotherapy were recognized as independent prognostic factors for OS (p < 0.05) and were incorporated to construct the initial nomogram. However, the initial nomogram showed poor predictive accuracy in internal and external validation. Then, we shifted our focus to the Changzheng data. Lung metastasis involving segments, Eastern Cooperative Oncology Group (ECOG) performance score, alkaline phosphatase (ALP) level, and en bloc resection were ultimately identified as independent prognostic factors for OS (p < 0.05) and were further incorporated to construct the current nomogram, of which the bias-corrected C-index was 0.834 (0.824–0.856). The areas under the ROC curves (AUCs) of the current nomogram regarding 1-, 3-, and 5-year OS probabilities were 0.93, 0.96, and 0.92, respectively. Conclusion: We have developed a predictive model with satisfactory performance and clinical practicability, enabling effective prediction of the OS of PSOS patients and aiding clinicians in decision-making. [ABSTRACT FROM AUTHOR]

Background: As a Class A bioterrorism agent, botulinum neurotoxin serotype A (BoNT/A) carries the risk of being used by terrorists to cause mass poisoning. The microneedle (MN) patch has a great potential for application as a novel vaccine delivery method. The aim of this study is to develop a thermally stable, dissolving microneedle patch for the delivery of a recombinant protein vaccine using a recombinant C-terminal heavy chain of BoNT/A (Hc of BoNT/A, AHc) to prevent botulism. Methods: Fish gelatin, a natural non-toxic and bacteriostatic material, was selected as the microneedle matrix for the preparation of the dissolving microneedle vaccine. Subsequently, the mechanical performance, bacteriostatic properties, vaccination effect, and stability of the microneedle patches were evaluated using instruments such as the displacement-force test station and optical coherence tomography (OCT) scanner. Results: Fish gelatin matrix at high concentrations has good bacteriostatic properties, and excellent mechanical performance and vaccination effect, meeting the necessities of a vaccine. In both in vivo and in vitro neutralization experiments, MN vaccines containing different antigen doses achieved the same protective efficacy as subcutaneous vaccinations, protecting mice against 106 LD50 of BoNT/A injected intraperitoneally. Thermal stability analysis of the MN vaccines revealed that the fish gelatin matrix protected the AHc vaccine from protein denaturation even after 7 days of storage at 37 °C and enabled the vaccine patches to maintain good immunogenicity and protective efficacy even after 6 months of storage at room temperature. Conclusion: In this study, we successfully prepared a bacteriostatic MN patch using a fish gelatin matrix that not only has a good vaccination effect, but also obviates the need for a cold chain for the AHc vaccine, providing the possibility of rapid, painless, and large-scale vaccination. [ABSTRACT FROM AUTHOR]

Snow depth is an essential meteorological indicator for monitoring snow disasters. The Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technique has been proven to be a practical approach to retrieving snow depth. This study presents a case study to explore utilizing the GNSS-IR-derived snow depth to monitor the 2022 early February snowstorm over southern China. A snow depth retrieval framework considering data quality control and specific ground surface substances was developed using 8-day data from 13 operational GNSS/Meteorology stations. The daily snow depths retrieved from different ground surfaces, i.e., dry grass, wet grass, and concrete, agreed well with the measured snow depth, with Mean Absolute Error (MAE) of 2.79 cm, 3.36 cm, and 2.53 cm, respectively. The percentage MAE when snow depths > 5 cm for the three ground surface substances was 26.8%, 53.7%, and 35.0%, respectively. The 6 h snow depth results also showed a swift and significant response to the snowfall event. This study proves the potential of GNSS-IR, used as a new operational tool in the automatic meteorological system, to monitor snow disasters over southern China, particularly as an efficient and cost-effective framework for real-time and accurate monitoring. [ABSTRACT FROM AUTHOR]

Ricin and abrin are phytotoxins that can be easily used as biowarfare and bioterrorism agents. Therefore, developing a rapid detection method for both toxins is of great significance in the field of biosecurity. In this study, a novel nanoforest silicon microstructure was prepared by the micro-electro-mechanical systems (MEMS) technique; particularly, a novel microfluidic sensor chip with a capillary self-driven function and large surface area was designed. Through binding with the double antibodies sandwich immunoassay, the proposed sensor chip is confirmed to be a candidate for sensing the aforementioned toxins. Compared with conventional immunochromatographic test strips, the proposed sensor demonstrates significantly enhanced sensitivity (≤10 pg/mL for both toxins) and high specificity against the interference derived from juice or milk, while maintaining good linearity in the range of 10–6250 pg/mL. Owing to the silicon nanoforest microstructure and improved homogeneity of the color signal, short detection time (within 15 min) is evidenced for the sensor chip, which would be helpful for the rapid tracking of ricin and abrin for the field of biosecurity. [ABSTRACT FROM AUTHOR]

DDoS (Distributed Denial of Service) has emerged as a serious and challenging threat to computer networks and information systems' security and integrity. Before any remedial measures can be implemented, DDoS assaults must first be detected. DDoS attacks can be identified and characterized with satisfactory achievement employing ML (Machine Learning) and DL (Deep Learning). However, new varieties of aggression arise as the technology for DDoS attacks keep evolving. This research explores the impact of a new incarnation of DDoS attack–adversarial DDoS attack. There are established works on ML-based DDoS detection and GAN (Generative Adversarial Network) based adversarial DDoS synthesis. We confirm these findings in our experiments. Experiments in this study involve the extension and application of the GAN, a machine learning framework with symmetric form having two contending neural networks. We synthesize adversarial DDoS attacks utilizing Wasserstein Generative Adversarial Networks featuring Gradient Penalty (GP-WGAN). Experiment results indicate that the synthesized traffic can traverse the detection systems such as k-Nearest Neighbor (KNN), Multi-Layer Perceptron (MLP) and Random Forest (RF) without being identified. This observation is a sobering and pessimistic wake-up call, implying that countermeasures to adversarial DDoS attacks are urgently needed. To this problem, we propose a novel DDoS detection framework featuring GAN with Dual Discriminators (GANDD). The additional discriminator is designed to identify adversary DDoS traffic. The proposed GANDD can be an effective solution to adversarial DDoS attacks, as evidenced by the experimental results. We use adversarial DDoS traffic synthesized by GP-WGAN to train GANDD and validate it alongside three other DL technologies: DNN (Deep Neural Network), LSTM (Long Short-Term Memory) and GAN. GANDD outperformed the other DL models, demonstrating its protection with a TPR of 84.3%. A more sophisticated test was also conducted to examine GANDD's ability to handle unseen adversarial attacks. GANDD was evaluated with adversarial traffic not generated from its training data. GANDD still proved effective with a TPR around 71.3% compared to 7.4% of LSTM. [ABSTRACT FROM AUTHOR]

Trans-epithelial electrical resistance (TEER) is a good indicator of the barrier integrity of epithelial tissues and is often employed in biomedical research as an effective tool to assess ion transport and permeability of tight junctions. The Ussing chamber is the gold standard for measuring TEER of tissue specimens, but it has major drawbacks: it is a macroscopic method that requires a careful and labor intensive sample mounting protocol, allows a very limited viability for the mounted sample, has large parasitic components and low throughput as it cannot perform multiple simultaneous measurements, and this sophisticated and delicate apparatus has a relatively high cost. This paper demonstrates a low-cost home-made "sandwich ring" method which was used to measure the TEER of tissue specimens effectively. This method inspired the subsequent design of a biochip fabricated using standard soft lithography and laser engraving technologies, with which the TEER of pig epithelial tissues was measured. Moreover, it was possible to temporarily preserve the tissue specimens for days in the biochip and monitor the TEER continuously. Tissue responses after exposure tests to media of various pH values were also successfully recorded using the biochip. All these demonstrate that this biochip could be an effective, cheaper, and easier to use Ussing chamber substitute that may have relevant applications in clinical practice. [ABSTRACT FROM AUTHOR]

Lakes and reservoirs are essential elements of the hydrological and biochemical cycles, considered sentinels of global climate change. However, comprehensive quantifications of their water storage changes (∆V) at a large spatiotemporal scale are still rare. Here, we integrated a global surface water dataset and SRTM digital elevation models, both available from Google Earth Engine platform at a spatial resolution of 30 m, to evaluate ∆V for a total of 760 lakes and reservoirs across China at an annual timescale since 1984. The results indicated that (1) the aggregated water storage went through a slight increase of 41.5 Gt (1.7 Gt/yr) during 1985–2005, a significant decrease of 100 Gt (−20.6 Gt/yr) during 2005–2009, and then increased by 136.3 Gt (21.3 Gt/yr) during 2009–2015. (2) The increasing trend was largely attributed to lakes and reservoirs in the Tibetan Plateau Lake Zone, and the decreasing trend was mainly due to the North and Northwest Lake Zone, with little variations observed for the Northeast and Southwest Lake Zones. (3) Qinghai lake was associated with the largest increase (18.3 Gt) and Poyang lake presented the largest decline (−9.2 Gt). The results can help advance our understanding of the impact of climate change and improve future projection. [ABSTRACT FROM AUTHOR]

Background: Many clinical trials with potential drug treatment options for non-alcoholic fatty liver disease (NAFLD) are focused on patients with non-alcoholic steatohepatitis (NASH) stages 2 and 3 fibrosis. As the histological features differentiating stage 1 (F1) from stage 2 (F2) NASH fibrosis are subtle, some patients may be wrongly staged by the in-house pathologist and miss the opportunity for enrollment into clinical trials. We hypothesized that our refined artificial intelligence (AI)-based algorithm (qFibrosis) can identify these subtle differences and serve as an assistive tool for in-house pathologists. Methods: Liver tissue from 160 adult patients with biopsy-proven NASH from Singapore General Hospital (SGH) and Peking University People's Hospital (PKUH) were used. A consensus read by two expert hepatopathologists was organized. The refined qFibrosis algorithm incorporated the creation of a periportal region that allowed for the increased detection of periportal fibrosis. Consequently, an additional 28 periportal parameters were added, and 28 pre-existing perisinusoidal parameters had altered definitions. Results: Twenty-eight parameters (20 periportal and 8 perisinusoidal) were significantly different between the F1 and F2 cases that prompted a change of stage after a careful consensus read. The discriminatory ability of these parameters was further demonstrated in a comparison between the true F1 and true F2 cases as 26 out of the 28 parameters showed significant differences. These 26 parameters constitute a novel sub-algorithm that could accurately stratify F1 and F2 cases. Conclusion: The refined qFibrosis algorithm incorporated 26 novel parameters that showed a good discriminatory ability for NASH fibrosis stage 1 and 2 cases, representing an invaluable assistive tool for in-house pathologists when screening patients for NASH clinical trials. [ABSTRACT FROM AUTHOR]

Satellite-based quantitative precipitation estimates (QPE) with a fine quality are of great importance to global water cycle and matter and energy exchange research. In this study, we firstly apply various statistical indicators to evaluate and compare the main current satellite-based precipitation products from Chinese Fengyun (FY)-2 and the Global Precipitation Measurement (GPM), respectively, over mainland China in summer, 2018. We find that (1) FY-2G QPE and Integrated Multi-satellitE Retrievals for GPM (IMERG) perform significantly better than FY-2E QPE, using rain gauge data, with correlation coefficients (CC) varying from 0.65 to 0.90, 0.80 to 0.90, and 0.40 to 0.53, respectively; (2) IMERG agrees well with rain gauge data at monthly scale, while it performs worse than FY-2G QPE at hourly and daily scales, which may be caused by its algorithms; (3) FY-2G QPE underestimates the precipitation in summer, while FY-2E QPE and IMERG generally overestimate the precipitation; (4) there is an interesting error phenomenon in that both FY-based and GPM-based precipitation products perform more poorly during the period from 06:00 to 10:00 UTC than other periods at diurnal scale; and (5) FY-2G QPE agrees well with IMERG in terms of spatial patterns and consistency (CC of ~0.81). These findings can provide valuable preliminary references for improving next generation satellite-based QPE retrieval algorithms and instructions for applying these data in various practical fields. [ABSTRACT FROM AUTHOR]

The effect of the design and process parameters of a particle-classification zone on the sizing precision of a plate differential mobility analyzer (PDMA) was investigated by simulation software in this work. The design parameters consisted of the length, width, and height of the classification zone, and the process parameters could lead to height deviation and an uneven classification-zone wall. Prior to investigating the parameters, a comparison between experimental voltages and PDMA simulation results was applied to validate the simulation model. Thanks to velocity-field and particle-trajectory simulations, as well as experimental data from the former version of the PDMA, the dimensions of the classification zone and other key parameters were optimized. Our research shows that the dimensions of the classification zone influence the applied voltages and the measuring range of the PDMA, and range can be extended to 500 nm with low applied voltages after optimization. When the reasonable error range of the height is ±2% for the classification zone, the PDMA could basically achieve a classification role, and when it is ±1%, the PDMA has a better classifying effect. [ABSTRACT FROM AUTHOR]

Sun-induced chlorophyll fluorescence (SIF) provides a new method for monitoring vegetation photosynthesis from space and has been widely used to estimate gross primary productivity (GPP). However, the ability of SIF obtained from the Orbital Carbon Observatory 2 (OCO-2 SIF) and Global Ozone Monitoring Experiment-2 (GOME-2) to estimate GPP in the cold and arid region of Heihe River Basin remains unclear because previous comparisons were insufficient. Here, we choose maize and alpine meadow to evaluate the performance of SIF obtained by OCO-2 and GOME-2 in GPP estimations. The results of this study show that daily SIF757 had stronger correlations with daily tower GPP than daily SIF771, and the correlation between daily SIF757 and daily tower GPP was stronger than the correlation between 16-d averaged SIF740 and 16-d averaged tower GPP. The 16-d averaged absorbed photosynthetically active radiation (APAR) and reconstructed sun-induced fluorescence (RSIF) had the strongest linear correlations with 16-d averaged tower GPP. GPP_VPM and GPP_RSIF exhibited the best performance in GPP estimation, closely followed by GPP_SIF757, then GPP_SIF771 and GPP_ SIF740. We also found that the robustness of the correlation coefficients of OCO-2 SIF with GOME-2 SIF was highly dependent on the size of their spatial footprint overlaps, indicating that the spatial differences between OCO-2 and GOME-2 footprints contribute to the differences in GPP estimates between OCO-2 and GOME-2. In addition, the differences of viewing zenith angle (VZA), cloud contamination, scale effects, and environmental scalars (Tscalar × Wscalar) can result in differences between OCO-2 SIF and GOME-2 SIF. [ABSTRACT FROM AUTHOR]