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Background: Surgical approach in the treatment of thymoma is varied. This retrospective study aimed to evaluate the outcomes of different surgical approaches in the treatment of thymoma. Methods: From January 2020 to December 2023, a total of 208 patients underwent thoracoscopic surgical treatment and were diagnosed with thymoma by postoperative pathological result in our institution. We collected and then analysed potential factors including general conditions, surgical approaches, preoperative clinical symptoms, surgical procedures, postoperative hospital stay, postoperative drainge, postoperative pain score, postoperative complications and postoperative follow-up. Results: Of the 208 patients, 98 patients underwent surgery via subxiphoid approach (47.1%) and 110 patients via lateral intercostal approach (52.8%). The duration of the surgical procedure (P = 0.02), intraoperative blood loss (P = 0.045), total postoperative drainage (P = 0.021), postoperative drainage per day (P = 0.004) and Postoperative pain score (Day1 P = 0.010 and Day2 P = 0.002)showed a significant difference between these two groups. 31 patients (14.9%) received postoperative radiotherapy. One patient died due to postoperative radiotherapy. No recurrence occurred in one-year follow-up. Conclusions: The present study not only showed that subxiphoid approach was a safe and feasible technique for thymoma, with a potentially faster postoperative recovery and less postoperative pain. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate the relationship between food sponsorships and gender stereotypes, focusing on how patriarchal beliefs influence consumers' purchase intentions in sports. Design/methodology/approach: The research comprised two studies. In Study 1, n = 161 participants participated via Amazon's Mechanical Turk platform. Study 2 involved n = 250 participants who completed a cross-sectional and self-administered survey. Findings: Study 1 indicated an apparent gender-based categorization of certain foods and beverages: beer and red meat were predominantly perceived as masculine, while yogurt, salads, and wine were seen as feminine. Further, brands like Budweiser and Red Bull were mainly seen as masculine, while Chobani and Smoothie King were perceived as feminine. Moreover, findings indicate that foods, especially those rich in protein or linked to BBQ and spicy tastes, are considered more masculine by men than women in sports settings. Further, Study 2 findings unveiled a significant relationship between patriarchal beliefs and both attitudes (ß = 0.327, p < 0.01) and subjective norms (ß = 0.525, p < 0.01) towards masculine brands. Originality/value: The two studies' results underscore the profound impact of gender stereotypes shaping sports fans' perceptions of food items and the brands sponsoring them. This inquiry significantly augments the current understanding of the nuanced interrelation between the paradigms of social role theory and the theory of planned behavior, particularly within the ambit of sports-related sponsorship by food and beverage brands and its consequent influence on consumer purchasing inclinations. [ABSTRACT FROM AUTHOR]

As the most commonly used attack strategy by Botnets, the Domain Generation Algorithm (DGA) has strong invisibility and variability. Using deep learning models to detect different families of DGA domain names can improve the network defense ability against hackers. However, this task faces an extremely imbalanced sample size among different DGA categories, which leads to low classification accuracy for small sample categories and even classification failure for some categories. To address this issue, we introduce the long-tailed concept and augment the data of small sample categories by transferring pre-trained knowledge. Firstly, we propose the Data Balanced Review Method (DBRM) to reduce the sample size difference between the categories, thus a relatively balanced dataset for transfer learning is generated. Secondly, we propose the Knowledge Transfer Model (KTM) to enhance the knowledge of the small sample categories. KTM uses a multi-stage transfer to transfer weights from the big sample categories to the small sample categories. Furthermore, we propose the Knowledge Distillation Transfer Model (KDTM) to relieve the catastrophic forgetting problem caused by transfer learning, which adds knowledge distillation loss based on the KTM. The experimental results show that KDTM can significantly improve the classification performance of all categories, especially the small sample categories. It can achieve a state-of-the-art macro average F1 score of 84.5%. The robustness of the KDTM model is verified using three DGA datasets that follow the Pareto distributions. [ABSTRACT FROM AUTHOR]

Training large-scale models needs big data. However, the few-shot problem is difficult to resolve due to inadequate training data. It is valuable to use only a few training samples to perform the task, such as using big data for application scenarios due to cost and resource problems. So, to tackle this problem, we present a simple and efficient method, contrastive label generation with knowledge for few-shot learning (CLG). Specifically, we: (1) Propose contrastive label generation to align the label with data input and enhance feature representations; (2) Propose a label knowledge filter to avoid noise during injection of the explicit knowledge into the data and label; (3) Employ label logits mask to simplify the task; (4) Employ multi-task fusion loss to learn different perspectives from the training set. The experiments demonstrate that CLG achieves an accuracy of 59.237%, which is more than about 3% in comparison with the best baseline. It shows that CLG obtains better features and gives the model more information about the input sentences to improve the classification ability. [ABSTRACT FROM AUTHOR]

Multimodal learning is a promising area in artificial intelligence (AI) that can make the model understand different kinds of data. Existing works are trying to re-train a new model based on pre-trained models that requires much data, computation power, and time. However, it is difficult to achieve in low-resource or small-sample situations. Therefore, we propose VL-Meta, Vision Language Models for Multimodal Meta Learning. It (1) presents the vision-language mapper and multimodal fusion mapper, which are light model structures, to use the existing pre-trained models to make models understand images to language feature space and save training data, computation power, and time; (2) constructs the meta-task pool that can only use a small amount of data to construct enough training data and improve the generalization of the model to learn the data knowledge and task knowledge; (3) proposes the token-level training that can align inputs with the outputs during training to improve the model performance; and (4) adopts the multi-task fusion loss to learn the different abilities for the models. It achieves a good performance on the Visual Question Answering (VQA) task, which shows the feasibility and effectiveness of the model. This solution can help blind or visually impaired individuals obtain visual information. [ABSTRACT FROM AUTHOR]

The fraction of absorbed photosynthetically active radiation (FAPAR) is a critical land surface variable for carbon cycle modeling and ecological monitoring. Several global FAPAR products have been released and have become widely used; however, spatiotemporal inconsistency remains a large issue for the current products, and their spatial resolutions and accuracies can hardly meet the user requirements. An effective solution to improve the spatiotemporal continuity and accuracy of FAPAR products is to take better advantage of the temporal information in the satellite data using deep learning approaches. In this study, the latest version (V6) of the FAPAR product with a 250 m resolution was generated from Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data and other information, as part of the Global LAnd Surface Satellite (GLASS) product suite. In addition, it was aggregated to multiple coarser resolutions (up to 0.25 ∘ and monthly). Three existing global FAPAR products (MODIS Collection 6; GLASS V5; and PRoject for On-Board Autonomy–Vegetation, PROBA-V, V1) were used to generate the time-series training samples, which were used to develop a bidirectional long short-term memory (Bi-LSTM) model. Direct validation using high-resolution FAPAR maps from the Validation of Land European Remote sensing Instrument (VALERI) and ImagineS networks revealed that the GLASS V6 FAPAR product has a higher accuracy than PROBA-V, MODIS, and GLASS V5, with an R2 value of 0.80 and root-mean-square errors (RMSEs) of 0.10–0.11 at the 250 m, 500 m, and 3 km scales, and a higher percentage (72 %) of retrievals for meeting the accuracy requirement of 0.1. Global spatial evaluation and temporal comparison at the AmeriFlux and National Ecological Observatory Network (NEON) sites revealed that the GLASS V6 FAPAR has a greater spatiotemporal continuity and reflects the variations in the vegetation better than the GLASS V5 FAPAR. The higher quality of the GLASS V6 FAPAR is attributed to the ability of the Bi-LSTM model, which involves high-quality training samples and combines the strengths of the existing FAPAR products, as well as the temporal and spectral information from the MODIS surface reflectance data and other information. The 250 m 8 d GLASS V6 FAPAR product for 2020 is freely available at https://doi.org/10.5281/zenodo.6405564 and https://doi.org/10.5281/zenodo.6430925 (Ma, 2022a, b) as well as at the University of Maryland for 2000–2021 (http://glass.umd.edu/FAPAR/MODIS/250m , last access 1 November 2022). [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) serves as a crucial variable in characterizing climatological, agricultural, ecological, and hydrological processes. Thermal infrared (TIR) remote sensing provides high temporal and spatial resolutions for obtaining LST information. Nevertheless, TIR-based satellite LST products frequently exhibit missing values due to cloud interference. Prior research on estimating all-weather instantaneous LST has predominantly concentrated on regional or continental scales. This study involved generating a global all-weather instantaneous and daily mean LST product spanning from 2000 to 2020 using XGBoost. Multisource data, including Moderate-Resolution Imaging Spectroradiometer (MODIS) top-of-atmosphere (TOA) observations, surface radiation products, and reanalysis data, were employed. Validation using an independent dataset of 77 individual stations demonstrated the high accuracy of our products, yielding root mean squared errors (RMSEs) of 2.787 K (instantaneous) and 2.175 K (daily). The RMSE for clear-sky conditions was 2.614 K for the instantaneous product, which is slightly lower than the cloudy-sky RMSE of 2.931 K. Our instantaneous and daily mean LST products exhibit higher accuracy compared to the MODIS official LST product (instantaneous RMSE = 3.583 K; daily 3.105 K) and the land component of the fifth generation of the European ReAnalysis (ERA5-Land) LST product (instantaneous RMSE = 4.048 K; daily 2.988 K). Significant improvements are observed in our LST product, notably at high latitudes, compared to the official MODIS LST product. The LST dataset from 2000 to 2020 at the monthly scale, the daily mean LST on the first day of 2010 can be freely downloaded from 10.5281/zenodo.4292068 (Li et al., 2024), and the complete product will be available at https://glass-product.bnu.edu.cn/ (last access: 22 August 2024). [ABSTRACT FROM AUTHOR]

Bioelectrochemical technologies based on electroactive biofilms (EAB) are promising for petroleum hydrocarbons (PHs) remediation as anode can serve as inexhaustible electron acceptor. However, the toxicity of PHs might inhibit the formation and function of EABs. Quorum sensing (QS) is ideal for boosting the performance of EABs, but its potential effects on reshaping microbial composition of EABs in treating PHs are poorly understood. Herein, two AHL signals, C4-HSL and C12-HSL, were employed to promote EABs for PHs degradation. The start-times of AHL-mediated EABs decreased by 18–26%, and maximum current densities increased by 28–63%. Meanwhile, the removal of total PHs increased to over 90%. AHLs facilitate thicker and more compact biofilm as well as higher viability. AHLs enhanced the electroactivity and direct electron transfer capability. The total abundance of PH-degrading bacteria increased from 52.05% to 75.33% and 72.02%, and the proportion of electroactive bacteria increased from 26.14% to 62.72% and 63.30% for MFC-C4 and MFC-C12. Microbial networks became more complex, aggregated, and stable with addition of AHLs. Furthermore, AHL-stimulated EABs showed higher abundance of genes related to PHs degradation. This work advanced our understanding of AHL-mediated QS in maintaining the stable function of microbial communities in the biodegradation process of petroleum hydrocarbons. [Display omitted] • AHLs boosted the current out and petroleum hydrocarbon (PH) removal of EABs • AHLs facilitate thicker and more compact biofilm as well as higher viability. • AHLs enhanced the direct electron transfer capability (EET) of EABs. • AHLs contributed to more complex, aggregated, and stable co-occurrence network. • AHLs promoted the abundance of genes related to EET and PH degradation in EABs. [ABSTRACT FROM AUTHOR]

The medium-resolution spectral imager (MERSI) onboard China’s new generation of polar-orbiting meteorological satellite series FengYun-3 (FY-3) is providing global observations of the Earth’s environment. One of the important characteristics of the MERSI sensor is that it has four bands at 250-m spatial resolution. However, very few high-level land surface and atmospheric products have been generated from MERSI data. This article presents an effective optimization method to estimate the continuous temporal distribution of multiple land surface and atmospheric variables at a 250-m spatial resolution from time series FY-3B MERSI top-of-atmosphere (TOA) observations. The MODIS cloud detection method was applied to the MERSI TOA reflectance to determine the clear observations. Then, a physics-based BRDF correction was adopt to reduce the topographic effects using the slope angle and aspect angle of the slope. Finally, a coupled land surface-atmosphere radiative transfer (RT) model and the shuffled complex evolution (SCE) optimization algorithm were used to estimate a suit of variables, including the leaf area index (LAI), the aerosol optical depth (AOD), the cloud optical thickness (COT), the cloud effective particle radius (CER), the land surface reflectance, the shortwave and visible albedo, the incident shortwave radiation (ISR), the incident photosynthetically active radiation (PAR), the fraction of absorbed PAR (FAPAR), the surface broadband emissivity (BBE), and the TOA shortwave albedo. The method was applied to the data from the 18 SURFRAD, the America FluxNet (AmeriFlux), and the Images and Beijing Normal University net (BNUnet) sites. All the estimated variables were also compared with Moderate Resolution Imaging Spectroradiometer (MODIS) and Global Land Surface Satellite (GLASS) products. The estimated LAI, PAR, FAPAR, shortwave albedo, and ISR were also validated using ground measurements from the selected sites. The results show that our method can simultaneously estimate multiple temporally continuous variables in both clear-and cloudy-sky conditions, with an accuracy comparable to those of MODIS and GLASS products. The estimated LAI, PAR, FAPAR, shortwave albedo, and ISR are consistent with the field measurements, with coefficients of determination ($R^{2}$) of 0.692, 0.783, 0.788, 0.559, and 0.833, and root mean square errors (RMSEs) of 0.427, 56.681 W/m2, 0.092, 0.084, and 115.305 W/m2, respectively. The proposed algorithm can effectively estimate the instantaneous atmospheric and land surface variables directly from satellite observations without cumbersome atmospheric corrections. Moreover, it can potentially be applied to multiple satellite observations. [ABSTRACT FROM AUTHOR]

Cognitive strategies are preferred among nurses who have limited opportunities in the workplace to use behavioral strategies to cope with negative life events. To explore whether different cognitive emotion regulation profiles could be distinguished in nurses exposed to workplace violence, and to investigate whether such profiles had differential associations with depressive symptoms. An online survey was conducted among nurses exposed to workplace violence (N = 399). Latent profile analysis was performed to identify discrete profiles based on the use of cognitive emotion regulation strategies. The Bolck, Croon, and Hagenaars method was applied to compare the latent profiles on the depressive symptoms. Seven latent profiles were identified: Low Regulators, Medium Regulators, High Regulators, Intensely Adaptive Regulators, Moderately Adaptive Regulators, Intensely Maladaptive Regulators, and Moderately Maladaptive Regulators. High Regulators had the highest level of depressive symptoms. Although using less adaptive strategies, Low Regulators did not report significantly more depressive symptoms than Medium Regulators, Intensely Maladaptive and Moderately Maladaptive Regulators. The adaptability of cognitive emotion regulation strategies depends on the conjunction of different strategies one person has at his disposal. Cognitive emotion regulation skill training should focus on flexible implementation of strategies and decreasing use of maladaptive strategies. [ABSTRACT FROM AUTHOR]

Since a new generation of geostationary satellite data has incredibly high temporal, spatial, and spectral resolutions, new methodologies are now needed to take advantage of both the temporal and spectral signatures of them for accurate estimation of Earth’s environmental variables. This article describes a novel optimization method to estimate a suite of 11 physically consistent land surface and atmospheric variables under all-sky conditions from the geostationary advanced Himawari imager (AHI) top-of-atmosphere (TOA) observations. This method is based on a coupled soil, snow, vegetation, and atmospheric radiative transfer (RT) model from 0.28 to 14 μm. The inversion algorithm consists of three major steps. First, the “clearest” observations at each moment during a temporal window were determined and then the essential variables that characterize surface RT models, such as leaf area index (LAI), leaf chlorophyll concentration, and soil parameters were estimated. Second, the atmospheric variables, including aerosol optical depth (AOD) under clear-sky conditions, and cloud optical thickness (COT) and cloud effective particle radius (CER) under cloudy-sky conditions, were inverted given surface reflectance calculated by the surface RT models. Finally, the inverted atmospheric and land surface variables were fed into the coupled RT model to calculate the remaining set of variables, including spectral directional reflectance, surface broadband albedo, thermal emissivity, incident shortwave radiation (ISR), photosynthetically active radiation (PAR), fraction of absorbed PAR by green vegetation (FAPAR), and TOA shortwave albedo. The retrieved variables were validated using in-situ measurements from Ozflux network sites and compared with the other existing satellite products. Intercomparisons demonstrate that the AHI-retrieved atmospheric variables (AOD, CER, and COT) and surface variables (surface reflectance, LAI, FAPAR, PAR, and surface emissivity) are well correlated with the corresponding JAXA released AHI, NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth’s Radiant Energy System (CERES), and the Global LAnd Surface Satellite (GLASS) products. Direct validation using in-situ measurements indicates that the retrieved ISR achieves higher accuracy than the CERES ISR product (with R2 values of 0.95 and 0.89, and root-mean-square error (RMSE) of 20.3 and 29.6 Wm2 for the AHI-retrieved and CERES daily ISR, respectively). Validation also shows that the estimated daily surface albedo has an accuracy comparable to the MODIS daily albedo product (RMSE = 0.03). Both the direct validation and product comparisons have demonstrated that this proposed inversion framework works very well for the AHI data. Unlike other algorithms that are usually used for estimating an individual parameter and rely heavily on a separate atmospheric correction, this inversion framework can effectively estimate a group of atmospheric and land surface variables and be easily applied to other similar multispectral geostationary satellite data. A comprehensive sensitivity and validation study is still needed to quantify the uncertainties of the retrieval variables. [ABSTRACT FROM AUTHOR]

Autonomous 3-D exploration with unmanned aerial vehicles (UAVs) is increasingly prevalent for environment monitoring without human intervention. In this article, we present a systematic solution toward efficient UAV exploration in 3-D environments. Innovatively, a road map is incrementally built and maintained along with the exploration process, which explicitly exhibits the topological structure of the 3-D environment. By simplifying the environment, the road map can efficiently provide the information gain and the cost-to-go for a candidate region to be explored, which are two quantities for next-best-view (NBV) evaluation, thus prompting the efficiency for NBV determination. In addition, with reference to the global plan queried on the road map, we propose a local planner based on the potential field method that drives the robot to the information-rich area during the navigation process, which further improves the exploration efficiency. The proposed framework and its composed modules are verified in various 3-D environments, which exhibit their distinctive features in NBV selection and better performance in improving the exploration efficiency than other methods. [ABSTRACT FROM AUTHOR]

Graphene has attracted much attention and holds great promise in various applications due to its extraordinary properties. To realize applications of graphene in large scale, developing a facile, green and cost-effective method for mass production of high-quality graphene is highly desired. Relative to expensive and complicated bottom-up approaches, top-down methods for graphene production are promising owing to their low cost and simplicity. Specifically, exfoliation of graphene nanosheets in liquid phase is favorable for their dispersion, functionalization and processing. Instead of highly toxic organic solvents, using water as the liquid medium makes exfoliation process eco-friendly and sustainable. In this review, recent progress on exfoliation of graphene nanosheets in water is discussed, with a particular focus on exfoliation and stabilizing mechanism in various aqueous media. Different water-based exfoliation methods, such as liquid-phase exfoliation and electrochemical exfoliation, are surveyed. [ABSTRACT FROM AUTHOR]

Formononetin‐7‐O‐β‐d‐glucoside has been proved to have significant anti‐inflammatory effect. To evaluate its rat pharmacokinetics, a rapid, sensitive, and specific liquid chromatography–tandem mass spectrometry method has been developed and validated for the quantification of formononetin‐7‐O‐β‐d‐glucoside and its main metabolite formononetin in rat plasma. Samples were pretreated using a simple protein precipitation and the chromatographic separation was performed on a C18 column by a gradient elution using a mobile phase consisting of water and acetonitrile both containing 0.1% formic acid. Both analytes were detected using a tandem mass spectrometer in positive multiple reaction monitoring mode. The assay showed wide linear dynamic ranges of both 0.10–100 ng/mL, with acceptable intra‐ and inter‐batch accuracy and precision. The lower limits of quantification were both 0.10 ng/mL using 50 μL of rat plasma for two analytes. The method has been successfully used to investigate the oral pharmacokinetic profiles of both analytes in rats. After oral administration of formononetin‐7‐O‐β‐d‐glucoside at the dose of 50 mg/kg, it was rapidly absorbed in vivo and metabolized to its metabolite formononetin. The plasma concentration‐time profiles both showed double‐peak phenomena, which would be attributed to the strong enterohepatic circulation of formononetin‐7‐O‐β‐d‐glucoside. [ABSTRACT FROM AUTHOR]

The test chip including transistors and Static Random Access Memory (SRAM) is proposed and fabricated by an advanced 22 nm Ultra-Thin Body and Buried Oxide Fully Depleted Silicon-on-Insulator (UTBB FD-SOI) technology. Experimental results of Co-60 irradiation and heavy ion experiments are presented. Total Ionizing Dose (TID) experiment results show that the threshold voltage shift of the transistor is about 100 mV when the dose is 500 krad(Si) and the SRAM irradiated to a dose of at least 300 krad(Si) can maintain its functionality, which means that 22 nm UTBB FD-SOI devices exhibit significantly improved total dose tolerance performance compared to the previous generation process. TID-induced threshold voltage shift in conventional-well nMOSFET can be mitigated by applying biasing to back-gate, while back-gate biasing is invalid for TID mitigation of the conventional-well pMOSFET. Heavy ion experimental results make known that 22 nm UTBB FD-SOI technology has contributions to Single Event Effect (SEE) hardness and the hardened SRAM has higher single event upset (SEU) tolerance and even SEU immunity. The research indicates that the circuits manufactured by 22 nm UTBB FD-SOI technology have great potential space applications in harsh radiation environments. • Back-gate biasing is valid for TID mitigation in RBB NMOS, which is invalid in RBB PMOS. • The 22 nm SRAM irradiated to a dose of 300 krad(Si) can maintain its functionality. • No error was recorded in DICE SRAM under all heavy ion experimental conditions. • The 22 nm UTBB FD-SOI has great potential applications in radiation environments. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) serves as a crucial variable in characterizing climatological, agricultural, ecological, and hydrological processes. Thermal infrared (TIR) remote sensing provides high temporal and spatial resolution for obtaining LST information. Nevertheless, TIR-based satellite-LST products frequently exhibit missing values due to cloud interference. Prior research on estimating all-weather instantaneous LST has predominantly concentrated on regional or continental scales. This study involved generating a global all-weather instantaneous and daily mean LST product spanning from 2000 to 2020 using XGBOOST. Multisource data, including Moderate-Resolution Imaging Spectroradiometer (MODIS) top-of-atmosphere (TOA) observations, surface radiation products, and reanalysis data, were employed. Validation using an independent dataset of 77 individual stations demonstrated the high accuracy of our products, yielding RMSEs of 2.787 K (instantaneous) and 2.175 K (daily). The RMSE for clear-sky conditions was 2.614 K for the instantaneous product, slightly lower than the cloudy-sky RMSE of 2.931 K. Our instantaneous and daily mean LST products exhibit higher accuracy compared to the MODIS official LST product (RMSE=3.583 K instantaneous, 3.105 K daily) and the land component of the 5th generation of European ReAnalysis (ERA5-Land) LST product (RMSE= 4.048 K instantaneous, 2.988 K daily). Significant improvements are observed in our LST product, notably at high latitudes, compared to the official MODIS LST product. The LST dataset from 2000 to 2020 at the monthly scale, the daily mean LST on the first day of 2010 can be freely downloaded from https://doi.org/10.5281/zenodo.4292068 (Li et al. 2024), and the complete product will be available at https://glass-product.bnu.edu.cn/dload.html. [ABSTRACT FROM AUTHOR]

Background Anastomotic leak after esophagectomy is one of the most challenging complications resulting in a high morbidity and mortality and prolonged hospitalization. The aim of this retrospective study was to access the impact of endoscopy intervention in anastomotic leak. Methods A retrospective review was conducted at our hospital from January 2008 to December 2016. In total, 263 patients who were diagnosed with an anastomotic leak after esophagectomy and underwent endoscopy examination were included in this study. First, all patients were divided into two groups based on a single criteria—whether they received endoscopy intervention or not—and comparisons were conducted between the two groups. Second, we categorized all patients into three groups based on the diameter of the anastomotic leak (group I: <5 mm; group II: 5–15 mm; group III: >15 mm). Detailed analyses were made for each group. Factors we considered included demographic factors, the length of postoperative hospital stay, the amount of medical expenditure, limited days of oral intake, and the incurrence of complications. Data relating to those factors were collected and then analyzed using standard statistic tools. Results In general, the difference between endoscopy intervention and conservative measure was significant. Moreover, the hospital stay (p < 0.001; p = 0.018), medical expenditure (p < 0.001; p = 0.003), limited days of oral intake (p < 0.001; p = 0.019), and postoperative complications such as hemorrhage (p < 0.001; p = 0.036), tracheoesophageal fistula (p = 0.002; p = 0.017), and anastomosis stricture (p = 0.03; p = 0.026) were significantly lower among patients who received endoscopy intervention in groups II and III. However, no significant difference was identified between endoscopy intervention and conservative measure in group I. Conclusions Endoscopy intervention is safe and effective in the diagnosis and treatment of postesophagectomy anastomotic leak. Especially for patients with a diameter of anastomotic leaks greater than 5 mm, the advantages of endoscopy intervention should not be neglected. [ABSTRACT FROM AUTHOR]

A ratiometric fluorescence probe (named ZOC) for the fast detection of HClO/ClO− was constructed by coumarin (donor) and pyridinium (acceptor) based on Forster resonance energy transfer (FRET) and intramolecular charge transfer (ICT) platform. ZOC possessed red emission signal (610 nm), large Stocks shift (190 nm), high energy transfer efficiency (95.3%), high selectivity and sensitivity, low detection limit (25 nM), wider detection range (from 25 nM to 30 μM), rapid response (within 13 S), and good biocompatibility. It was very interesting that the recognition mechanism involved a new organic reaction in which olefin double bond reacted first with HClO/ClO− regioselectively, followed by cyclization. ZOC was successfully used to the real time detection of endogenous HClO/ClO− in RAW 264.7 cells. Image 1 • A ratiometric fluorescence probe for rapidly monitoring (within 13 S) HClO/ClO− was developed. • FRET-based probe displayed larger gap band (130 nm) between two emissions. • A novel recognition mechanism was observed. • The probe was applied to the real time detection of endogenous HClO/ClO− in living RAW264.7 cells. [ABSTRACT FROM AUTHOR]

Background. Irritable bowel syndrome (IBS) is a chronic gastrointestinal disorder characterized by abdominal pain and altered bowel habits in the absence of any detectable organic illnesses. Interest in the effect of dietary opponents to the IBS pathogenesis has been increased in recent years. This study aims to review previous studies to determine the relationship between IBS prevalence in community and dietary energy and macronutrients intakes according to the national nutrition surveys. Methods. A literature search was conducted in PubMed and EMBASE to September, 2018, to identify population-based studies that reported the prevalence of IBS. Daily energy intake, daily carbohydrates, and protein and fat percent contribution to energy intake (%) were obtained from study population-based national nutrition survey. The correlations of prevalence of IBS and dietary intakes were obtained by Spearman coefficient or Pearson coefficient. Results. Global prevalence of IBS was 11.7%. There was no correlation between overall prevalence of IBS of individual countries and national energy intake (P = 0.785), protein proportion (P = 0.063), carbohydrates proportion (P = 0.505), or fat proportion (P = 0.384) according to the years when the studies were conducted. No correlations were detected between dietary intake and male or female IBS prevalence. Interestingly, protein proportion was positively correlated with the prevalence of IBS in Rome III criteria (r = 0.569). Conclusion. Our findings demonstrate that dietary energy and macronutrients intake do not play a direct role in prevalence of IBS. However, IBS diagnostic criteria seem to have a bias on the correlation between prevalence of IBS and dietary intake. Further studies are needed to confirm the correlation between prevalence of IBS and specific dietary intake. [ABSTRACT FROM AUTHOR]

Abstract Lipid droplets were found to be involved in many organism activities. Here, a lipid droplets-targeted near-infrared fluorescence probe (named XHZ) for ratiometric detection of endogenous hypochlorous acid/hypochlorite (HClO/ClO-) in living cells was developed, which was constructed by a coumarin moiety and a malononitrile derivative. XHZ could detect HClO/ClO- with high selectivity and sensitivity in a ratiometric manner based on FRET (Förster Resonance Energy Transfer) mechanism. The two well-resolved emission (470/672 nm) bands could ensure accurate detection of HClO/ClO- in vitro as well as in vivo. XHZ was successfully used for ratiometric fluorescence imaging of exogenous and endogenous HClO/ClO- in RAW264.7 cells. A good linear relationship between the fluorescence intensity ratios of the two emissions and HClO/ClO- concentrations from 0 to 40 μM was obtained. Importantly, XHZ could localize mainly in lipid droplets of RAW264.7 cells. To the best of our knowledge, XHZ is the first lipid droplets-targeted ratiometric fluorescence probe for HClO/ClO-. Graphical abstract FRET-based hypochlorite NIR specific bioprobe (XHZ) for lipid droplets was reported here. fx1 Highlights • A lipid droplets-targeted fluorescence NIR probe (XHZ). • Ratiometric detection of endogenous hypochlorite in the living cells. • Well-resolved emission (from 672 nm to 470 nm). • Ratiometric tracking of endogenous HClO/ClO- in RAW264.7 cells with high selectivity and sensitivity. [ABSTRACT FROM AUTHOR]

Graphical abstract Abstract In this study, we report a potentially scalable method for producing multilayer molybdenum disulfide (MoS 2) nanosheets. The addition of a small amount of ammonia solution can improve the exfoliation of MoS 2 nanosheets in water. The surface charge induced by spontaneous adsorption of hydroxyl ions on MoS 2 surfaces favors the exfoliation process. The edge charge generated by the ionization of edge-attached groups facilities the dispersion of exfoliated nanosheets in water. It is also found that smaller MoS 2 nanosheets show an improved photocatalytic performance, which stems from enhanced edge effects and a reduced flake thickness. This work opens a new vista on preparation and application of multilayer MoS 2 nanosheets. [ABSTRACT FROM AUTHOR]

The International Paralympic Committee has been promoting the development of evidence‐based classification to reduce the subjectivity in current decision‐making systems. The current study aimed to evaluate the validity of the impairment and performance tests for para‐alpine sit skiing classification, and whether cluster analysis of the measures would produce a valid classification structure. Thirty‐eight para‐alpine sit skiers with different disabilities completed seven tests. During these tests, isometric trunk strength, trunk muscle excitation, trunk range of movement (ROM), and simulated skiing performance (board tilt angle) were assessed. Correlations between the measures and the board tilt angle were calculated. To group athletes, K‐means cluster analysis was performed according to how much the impairment measures affected the board tilting. There were significant correlations between all measures and the maximal board tilt angle (r = 0.35–0.81, p < 0.05). The cluster analysis revealed that the introduction of ROM and muscle excitation was an effective supplement to strength measures in improving the classification accuracy (53%–79%). It produced four clusters with strong structures (mean silhouette coefficient = 0.81) and large and significant inter‐cluster differences in most measures and performance between clusters (p < 0.05). The cluster analysis produced classes comprising athletes with similar degrees of activity limitation. All tests reported can help establish a more transparent classification system for para‐alpine sit skiers. This study also provides a reference for evidence‐based classification systems in other Para sports. [ABSTRACT FROM AUTHOR]

Background. Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases. Machine learning techniques were introduced to evaluate the optimal predictive clinical model of NAFLD. Methods. A cross-sectional study was performed with subjects who attended a health examination at the First Affiliated Hospital, Zhejiang University. Questionnaires, laboratory tests, physical examinations, and liver ultrasonography were employed. Machine learning techniques were then implemented using the open source software Weka. The tasks included feature selection and classification. Feature selection techniques built a screening model by removing the redundant features. Classification was used to build a prediction model, which was evaluated by the F-measure. 11 state-of-the-art machine learning techniques were investigated. Results. Among the 10,508 enrolled subjects, 2,522 (24%) met the diagnostic criteria of NAFLD. By leveraging a set of statistical testing techniques, BMI, triglycerides, gamma-glutamyl transpeptidase (γGT), the serum alanine aminotransferase (ALT), and uric acid were the top 5 features contributing to NAFLD. A 10-fold cross-validation was used in the classification. According to the results, the Bayesian network model demonstrated the best performance from among the 11 different techniques. It achieved accuracy, specificity, sensitivity, and F-measure scores of up to 83%, 0.878, 0.675, and 0.655, respectively. Compared with logistic regression, the Bayesian network model improves the F-measure score by 9.17%. Conclusion. Novel machine learning techniques may have screening and predictive value for NAFLD. [ABSTRACT FROM AUTHOR]

A new ratiometric fluorescent probe ( RPM ) was developed based on through-bond energy transfer (TBET) mechanism for detecting hypochlorous acid. The probe was constructed from imidazo[1,5- a ]pyridine as the energy donor and the rhodamine as the energy acceptor. The probe could be used to determine the concentration of HOCl with high selectivity and sensitivity (the detection limit = 2.08 × 10 −6 M). In addition, RPM had a good time resolution for measuring HOCl with the response time of less than 30 s. Upon addition of HOCl, the fluorescence colors of probe RPM solution changed from green to red. Moreover, the probe has been successfully utilized for sensing HOCl in living cells. [ABSTRACT FROM AUTHOR]

To bring graphene closer to its real-world applications, finding a green, low-cost, environment-friendly and less toxic solvent for production of high-quality graphene is highly demanded. However, water, the most widely used green solvent, is generally considered to be a poor solvent for hydrophobic graphene. In this study, we exfoliate graphene nanosheets directly in basic water without surfactants, polymers or organic solvents. The addition of a small amount of ammonia solution achieves the exfoliation of few-layer graphene nanosheets from pristine graphite. Diverse characterization methods are employed to investigate the morphology and quality of as-prepared graphene sheets. The release of gaseous ammonia plays the key role in exfoliation of graphene. The concentration of stable graphene dispersions can reach 0.058 mg/mL. [ABSTRACT FROM AUTHOR]

Leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), and surface broadband albedo are three routinely generated land-surface parameters from satellite observations, which have been widely used in land-surface modeling and environmental monitoring. Currently, most global land products are retrieved separately from individual satellite data. Many issues, such as data gaps, spatial and temporal inconsistencies, and insufficient accuracy under certain conditions resulting from the inadequacies of single-sensor observations, have made the incorporation of multiple sensors a reasonable solution. In this paper, an approach to simultaneous estimation of LAI, broadband albedo, and FAPAR from multiple-satellite sensors is further refined. The method, improved from that proposed in an earlier study using Moderate Resolution Imaging Spectroradiometer (MODIS) data, consists of several steps. First, a coupled dynamic and radiative-transfer model based on MODIS, SPOT/VEGETATION, and Multiangle Imaging SpectroRadiometer data was developed to retrieve LAI values and use them to construct a time-evolving dynamic model. Second, an iteration process with predefined exit criteria was developed to obtain consistent gap-filled LAI estimates. Third, a spectral albedo based on the retrieved LAI values was simulated using a radiative-transfer model and then converted to a broadband albedo using empirical methods. Snow-covered pixels identified by normalized difference snow index thresholds were adjusted to the weighted average of the underlying albedo and the maximum snow albedo. Finally, the FAPAR of green vegetation was calculated as a combination of the albedo at the top of the canopy, the soil albedo, and the transmittance of the PAR down to the background. Validation of retrieved LAI, albedo, and FAPAR values obtained from multiple-satellite data over ten study sites has demonstrated that the proposed method can produce more accurate products than presently distributed global products. [ABSTRACT FROM PUBLISHER]

Magnetron-sputtering deposition of coatings onto a flat surface is well established, but coating metal on the curved surface of nanoparticles (NPs) is still challenging. Herein, by using a magnetron sputtering system in which a vibration generator with variable frequency is applied to the sample stage to maintain NPs' dispersity and movability, we successfully deposit noble metal (Au, Ag, Pt) nanodots onto the surface of TiO 2 NPs. It is found that the metal nanodots are of a size of 1–6 nm and they are firmly bonded to the TiO 2 NPs' surface. The photocatalytic activity of Ag/TiO 2 is demonstrated to be 2.7 times that of pure TiO 2 under simulated sunlight irradiation. This study creates new opportunities for fabricating excellent NP composite catalysts by liquid-free methods. [ABSTRACT FROM AUTHOR]

Land surface parameters from remote sensing observations are critical in monitoring and modeling of global climate change and biogeochemical cycles. Current methods for estimating land surface variables usually focus on individual parameters separately even from the same satellite observations, resulting in inconsistent products. Moreover, no efforts have been made to generate global products from integrated observations from the optical to Thermal InfraRed (TIR) spectrum. Particularly, Middle InfraRed (MIR) observations have received little attention due to the complexity of the radiometric signal, which contains both reflected and emitted radiation. In this paper, we propose a unified algorithm for simultaneously retrieving six land surface parameters – Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), land surface albedo, Land Surface Emissivity (LSE), Land Surface Temperature (LST), and Upwelling Longwave radiation (LWUP) by exploiting MODIS visible-to-TIR observations. We incorporate a unified physical radiative transfer model into a data assimilation framework. The MODIS visible-to-TIR time series datasets include the daily surface reflectance product and MIR-to-TIR surface radiance, which are atmospherically corrected from the MODIS data using the Moderate Resolution Transmittance program (MODTRAN, ver. 5.0). LAI was first estimated using a data assimilation method that combines MODIS daily reflectance data and a LAI phenology model, and then the LAI was input to the unified radiative transfer model to simulate spectral surface reflectance and surface emissivity for calculating surface broadband albedo and emissivity, and FAPAR. LST was estimated from the MIR–TIR surface radiance data and the simulated emissivity, using an iterative optimization procedure. Lastly, LWUP was estimated using the LST and surface emissivity. The retrieved six parameters were extensively validated across six representative sites with different biome types, and compared with MODIS, GLASS, and GlobAlbedo land surface products. The results demonstrate that the unified inversion algorithm can retrieve temporally complete and physically consistent land surface parameters, and provides more accurate estimates of surface albedo, LST, and LWUP than existing products, with R 2 values of 0.93 and 0.62, RMSE of 0.029 and 0.037, and BIAS values of 0.016 and 0.012 for the retrieved and MODIS albedo products, respectively, compared with field albedo measurements; R 2 values of 0.95 and 0.93, RMSE of 2.7 and 4.2 K, and BIAS values of −0.6 and −2.7 K for the retrieved and MODIS LST products, respectively, compared with field LST measurements; and R 2 values of 0.93 and 0.94, RMSE of 18.2 and 22.8 W/m 2 , and BIAS values of −2.7 and −14.6 W/m 2 for the retrieved and MODIS LWUP products, respectively, compared with field LWUP measurements. [ABSTRACT FROM AUTHOR]

A new FRET-based ratiometric fluorescent probe (DSPT) for the detection of bisulfite was developed by the dansyl-piperazine-benzothiazolium conjugate platform, in which C C conjugated with benzothiazolium was recognition unit and benzothiazolium moiety was mitochondria-targeted unit. The C C double bond group would undergo Michael addition reaction with bisulfite, triggering significant fluorescence ratio increasing which was linear to the concentrations of bisulfite. The probe can be used in real sample including dry white wine and tap water. Besides, the test strips for bisulfite were prepared. Moreover, cell imaging results indicate that this probe is cell-membrane permeable and mitochondria-targetable, and can be applied to monitor both exogenous and endogenous bisulfite in ratiometric fluorescence imaging. [ABSTRACT FROM AUTHOR]

Spin-dependent transport via flat-band states in organic-ferromagnetic devices with spin radicals is investigated theoretically. A spin-resolved negative differential resistance phenomenon is observed together with a spin-filtering effect. A new mechanism as bias-induced distinct localization of the spin-split flat-band states is proposed, which originates from the weaker hybridization of the flat-band states rather than the π -conjugated orbitals. The peak-to-valley ratio increases with the interaction strength between the main chain and radicals. This work explores the unique transport property of flat-band states and their intriguing prospect in designing high-performed organic spintronic devices. • Spin-resolved negative differential resistance is observed in organic-ferromagnetic devices with spin radicals. • A new mechanism as bias-induced distinct localization of the spin-split flat-band states is proposed. • The peak-to-valley ratio increases with the interaction strength between the main chain and radicals. [ABSTRACT FROM AUTHOR]

• Reduces the scanning time and data storage space of 3D topographic imaging. • Measuring height is unaffected by the sample reflectivity. • A novel alternative approach with higher lateral resolution level as conventional method. • Applied directly to existing confocal microscopy. Confocal microscopy (CM) is extensively used in many fields due to its unique axial tomographic capabilities and high-resolution three-dimensional imaging properties. However, this requires layer-by-layer scanning on the sample along the axial direction, which restricts the imaging speed. In this study, we have proposed the defocused differential correlation confocal microscopy (DDCCM), which is based on axial sensing imaging and correlation product method. This method can obtain an axial response curve independent of sample reflectivity and fast 3D sensing imaging of the sample by dividing the difference between the two defocused intensity images by their sum, improving the imaging efficiency at least five times higher than that of CM. The proposed method improves the lateral resolution using the correlation product of two defocused intensity images. DDCCM provides a new way for the fast measurement of conventional CM without changing the system conditions. [ABSTRACT FROM AUTHOR]

The gel network structure filled with attractive nanoparticles (NPs) significantly affects the viscoelasticity of the nanocomposites, which is poorly understood and troubles industrial processes. In this work, the nanoparticle gel matrices were prepared with hydrophilic fumed silica (FS), and filled with aluminium sub-microparticles (Al SMPs) loading in the range of 10%− 50%. The effects of particle content and composition on the large amplitude oscillatory shear (LAOS) behaviors are investigated by stress decomposition methods. Meanwhile, the higher harmonics and the Chebyshev harmonics coefficients were obtained. We found that the gels exhibit consistent progressive stiffening with particles filling, companying with plastic transformation and weak strain overshoot (WSO). With aluminum increasing, nonlinear viscoelastic responses gradually weaken in LAOS, severely decreasing the linear viscoelastic (LVE) region, and were validated by strain stiffening index S , T and high-order harmonics. In confocal microscopy (CFM) images, the aluminum particles were fluorescently labeled and found to be adhered together with FS clusters. This article could provide a perspective on understanding the flow mechanism of particulate network structure by combining morphological details and LAOS behaviors. [Display omitted] • The surface of the naked aluminum particles is adhered with the clusters in gel fuels. • Solid-liquid transition was monitored by the FT-rheology analysis under LAOS. • Addition of fumed silica and aluminum particles induces the plastic transformation. • Nonlinear characteristics are reflected by the third harmonics in the particulate gels. [ABSTRACT FROM AUTHOR]

Motivated by the lack of long-term global soil moisture products with both high spatial and temporal resolutions, a global 1 km daily spatiotemporally continuous soil moisture product (GLASS SM) was generated from 2000 to 2020 using an ensemble learning model (eXtreme Gradient Boosting – XGBoost). The model was developed by integrating multiple datasets, including albedo, land surface temperature, and leaf area index products from the Global Land Surface Satellite (GLASS) product suite, as well as the European reanalysis (ERA5-Land) soil moisture product, in situ soil moisture dataset from the International Soil Moisture Network (ISMN), and auxiliary datasets (Multi-Error-Removed Improved-Terrain (MERIT) DEM and Global gridded soil information (SoilGrids)). Given the relatively large-scale differences between point-scale in situ measurements and other datasets, the triple collocation (TC) method was adopted to select the representative soil moisture stations and their measurements for creating the training samples. To fully evaluate the model performance, three validation strategies were explored: random, site independent, and year independent. Results showed that although the XGBoost model achieved the highest accuracy on the random test samples, it was clearly a result of model overfitting. Meanwhile, training the model with representative stations selected by the TC method could considerably improve its performance for site- or year-independent test samples. The overall validation accuracy of the model trained using representative stations on the site-independent test samples, which was least likely to be overfitted, was a correlation coefficient (R) of 0.715 and root mean square error (RMSE) of 0.079 m 3 m -3. Moreover, compared to the model developed without station filtering, the validation accuracies of the model trained with representative stations improved significantly for most stations, with the median R and unbiased RMSE (ubRMSE) of the model for each station increasing from 0.64 to 0.74 and decreasing from 0.055 to 0.052 m 3 m -3 , respectively. Further validation of the GLASS SM product across four independent soil moisture networks revealed its ability to capture the temporal dynamics of measured soil moisture (R=0.69–0.89; ubRMSE = 0.033–0.048 m 3 m -3). Lastly, the intercomparison between the GLASS SM product and two global microwave soil moisture datasets – the 1 km Soil Moisture Active Passive/Sentinel-1 L2 Radiometer/Radar soil moisture product and the European Space Agency Climate Change Initiative combined soil moisture product at 0.25 ∘ – indicated that the derived product maintained a more complete spatial coverage and exhibited high spatiotemporal consistency with those two soil moisture products. The annual average GLASS SM dataset from 2000 to 2020 can be freely downloaded from 10.5281/zenodo.7172664 (Zhang et al., 2022a), and the complete product at daily scale is available at http://glass.umd.edu/soil%5fmoisture/ (last access: 12 May 2023). [ABSTRACT FROM AUTHOR]

Background/Aim. To investigate the association between serum sialic acid (SA) levels and nonalcoholic fatty liver disease (NAFLD) in a nonobese Chinese population. Methods. A cross-sectional study was performed among the 5916 adults who took their annual health examinations at International Health Care Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, from December 2013 to November 2014. Results. A total of 693 (11.71%) subjects fulfilled the diagnostic criteria of NAFLD, and NAFLD patients had significantly higher serum SA levels than controls (P<0.001). The prevalence of NAFLD was positively associated with serum SA levels (P for trend <0.001). Serum sialic acid levels are significantly associated with features of metabolic syndrome (Ps<0.01). Multivariate logistic regression analysis showed that serum SA level was significantly associated with risk for NAFLD (odds ratio: 1.018, 95%; confidence interval: 1.007–1.030; P=0.002). Conclusions. Our results suggest for the first time that NAFLD patients had higher serum SA level than controls, and increased serum SA level is significantly associated with risk for NAFLD in a large nonobese Chinese population. [ABSTRACT FROM AUTHOR]

The Visible Infrared Imaging Radiometer Suite (VIIRS) has observed the Earth since 2011 and will continue for several decades. Unfortunately, few high-level land surface products have been produced and publicly released. The numerical inversion of radiative transfer model (RTM) has long been used for the retrieval of land surface and atmospheric variables from satellite data; however, it is computationally intensive. Some methods (e.g., using look-up tables) are efficient but are most suitable for estimating individual variable. Various machine learning (ML) models have been developed, mostly trained by either ground measurements that may not be adequate to represent different conditions, or RTM simulations that may not be realistic due to model uncertainty and unnecessary combinations of illumination-viewing geometries and variable values. In this study, we replaced the numerical inversion scheme by the ML algorithm that is trained using RTM inversion for estimating multiple variables simultaneously. Our training dataset for the ML models was generated by inverting the land and atmospheric variables from VIIRS top-of-atmosphere (TOA) reflectance data using a coupled land-surface–atmosphere RT model. Two multi-output ML algorithms were explored: backpropagation neural networks and random forest (RF) regression. The best-performing RF model was then applied to estimate seven land and atmospheric variables globally from VIIRS TOA data: the leaf area index (LAI), incident photosynthetically active radiation (PAR), fraction of absorbed photosynthetically active radiation (FAPAR), incident shortwave radiation (ISR), land surface albedo, land surface reflectance, and TOA albedo. The inversion results were validated using ground measurements at 54 sites and showed comparable accuracy to the numerical inversion scheme that is suitable for only small regions. An experiment was also conducted to test this method on a much larger region for detailed evaluation. Finally, seven global estimates in 2013 were experimentally produced. Inter-comparison with the existing satellite products showed that the VIIRS estimates had high consistency with the LAI and FAPAR products of the Global LAnd Surface Satellite (GLASS) products suite. Moreover, the VIIRS officially released the VNP43MA3 albedo and VNP09A1 surface reflectance products, the retrieved estimates also matched them well. It was also shown that simultaneous estimation of all seven variables was more accurate and efficient than estimating individual variable sequentially. • A method to replace the coupled RT model by the machine learning method for estimating multiple variables simultaneously. • The training dataset was generated by reversely simulating using the coupled RT model from TOA reflectance. • Simultaneous estimation of multiple variables is more accurate and efficient than estimating individual variable sequentially • The generated multiple products have high accuracy based on extensive validation. [ABSTRACT FROM AUTHOR]

ABSTRACT Background Aims Patients/Methods Results Conclusions Periorbital hyperpigmentation is a prevalent skin condition that represents a large quantity of cases seen in cosmetic dermatology. Patients tend to be left with pigmentation after Q‐switched ruby laser treatment, especially the perioribital area.The study is conducted to compare the effect of PRP injection combined with laser therapy versus laser alone for periorbital hyperpigmentation treatment.In this single‐center, case–control study, 30 patients with periorbital hyperpigmentation were allocated to receive PRP injection injection after Q‐switched ruby laser or Q‐switched ruby laser only, followed by a 12‐week and 24‐week follow‐up visit. Visual analogue scale, Sadick tear trough rating scale, and patients' self‐evaluation were used to evaluate the therapeutic effect.The combined group achieved a better improvement in long‐term effect and had effect on facial rejuvenation. Patient satisfaction was higher in the combined group. Erythema and mild pain were the most common adverse reactions of both groups.Combining with PRP injection can improve the therapeutic effect of Q‐switched ruby laser in treating periorbital hyperpigmentation and lessen the risk of post‐inflammatory hyperpigmentation, indicating a new option for POH treatment. [ABSTRACT FROM AUTHOR]

Effects of Cr alloying on phase stability, magnetism, and electronic structures in both body‐centered cubic (bcc) and face‐centered cubic (fcc) phases and on the transformation from fcc to bcc are studied by first‐principles calculations. Results show that the doped Cr atoms in fcc and bcc phases choose distinct occupation models. This phenomenon can be understood from the amount of electron density of states close to Fermi energy. For magnetism, Cr tends to be antiferromagnetically coupled with the surrounding Fe in the studied phases. The magnetic moment of Fe is greater than that of Cr in bcc, but the order is reversed in fcc. The moment of Fe is dictated by the distance between it and the doped Cr in bcc, whereas it is dominated by spatial orientation with Cr in fcc. For phase stability, it is found that the alloying of Cr prefers destabilizing bcc while tends to stabilize fcc, leading to a strong inhibition of phase transition from fcc to bcc. Notably, the role in the fcc phase is more prominent than that in bcc, which can be associated with the antiferromagnetism between Fe and Cr in fcc. [ABSTRACT FROM AUTHOR]

BACKGROUND: Soy 11S globulin has high thermal stability, limiting its application in the production of low‐temperature gel foods. In this study, the low‐frequency magnetic field (LF‐MF, 5 mT) treatment (time, 30, 60, 90, and 120 min) was used to improve the solubility, conformation, physicochemical properties, surface characteristics, and gel properties of soy 11S globulin. RESULTS: Compared with the native soy 11S globulin, the sulfhydryl content, emulsifying capacity, gel strength, water‐holding capacity, and absolute zeta potential values significantly increased (P < 0.05) after LF‐MF treatment. The LF‐MF treatment induced the unfolding of the protein structure and the fracture of disulfide bonds. The variations in solubility, foaming properties, viscosity, surface hydrophobicity, and rheological properties were closely related to the conformational changes of soy 11S globulin, with the optimum LF‐MF modification time being 90 min. CONCLUSION: LF‐MF treatment is an effective method to improve various functional properties of native soy 11S globulin, and this study provides a reference for the development of plant‐based proteins in the food industry. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Leaf area index (LAI) is a terrestrial essential climate variable that is required in a variety of ecosystem and climate models. The Global LAnd Surface Satellite (GLASS) LAI product has been widely used, but its current version (V5) from Moderate Resolution Imaging Spectroradiometer (MODIS) data has several limitations, such as frequent temporal fluctuation, large data gaps, high dependence on the quality of surface reflectance, and low computational efficiency. To address these issues, this paper presents a deep learning model to generate a new version of the LAI product (V6) at 250-m resolution from MODIS data from 2000 onward. Unlike most existing algorithms that estimate one LAI value at one time for each pixel, this model estimates LAI for 2 years simultaneously. Three widely used LAI products (MODIS C6, GLASS V5, and PROBA-V V1) are used to generate global representative time-series LAI training samples using K-means clustering analysis and least difference criteria. We explore four machine learning models, the general regression neural network (GRNN), long short-term memory (LSTM), gated recurrent unit (GRU), and Bidirectional LSTM (Bi-LSTM), and identify Bi-LSTM as the best model for product generation. This new product is directly validated using 79 high-resolution LAI reference maps from three in situ observation networks. The results show that GLASS V6 LAI achieves higher accuracy, with a root mean square (RMSE) of 0.92 at 250 m and 0.86 at 500 m, while the RMSE is 0.98 for PROBA-V at 300 m, 1.08 for GLASS V5, and 0.95 for MODIS C6 both at 500 m. Spatial and temporal consistency analyses also demonstrate that the GLASS V6 LAI product is more spatiotemporally continuous and has higher quality in terms of presenting more realistic temporal LAI dynamics when the surface reflectance is absent for a long period owing to persistent cloud/aerosol contaminations. The results indicate that the new Bi-LSTM deep learning model runs significantly faster than the GLASS V5 algorithm, avoids the reconstruction of surface reflectance data, and is resistant to the noises (cloud and snow contamination) or missing values contained in surface reflectance than other methods, as the Bi-LSTM can effectively extract information across the entire time series of surface reflectance rather than a single time point. To our knowledge, this is the first global time-series LAI product at the 250-m spatial resolution that is freely available to the public (www.geodata.cn and www.glass.umd.edu). • Exploring a deep learning model for global LAI estimation based on temporal and spectral signatures of MODIS reflectance. • Generating the first global 21-year LAI product at 250-m spatial resolution. • The retrieved LAI maintains spatio-temporal consistency even when the high-quality reflectance is absent for a long period. • The learning model is very efficient and requires no smoothing and gap-filling of surface reflectance. [ABSTRACT FROM AUTHOR]

Highlights: [•] Forest LAI retrieval was improved by combing LiDAR, MODIS and MISR data. [•] LAI was estimated from canopy height and GOMS model structural parameters. [•] Canopy height was estimated by extrapolating the LiDAR-derived canopy height by using MODIS BRDF model parameters (MCD43A1). [•] The accuracy of the estimated LAI was impressive with R 2 value of 0.73 compared to the in situ measured LAI. [Copyright &y& Elsevier]

Abstract: A series of novel 6-cinnamoyl-2H-benzo[b][1,4]oxazin-3(4H)-one derivatives was synthesized. The structures of compounds were characterized by 1H NMR, IR, and MS. Moreover, representative crystal structure was determined by X-ray diffraction analysis. The preliminary biological evaluation of all these compounds showed that compounds 3a–3d would suppress the growth of A549 lung cells effectively by inducing autophagy and cell cycle arrest. [Copyright &y& Elsevier]

Wavefront fitting is used to analyze the characteristic of the wavefront distortion caused by the aerodynamic flow field, and aero-optical effects in compressible shear layers are discussed. The spatial scales of the wavefront distortion are analyzed by comparing the coefficients of Zernike polynomials, and they are related to the scales of the structure in the shear layer. The results show that wavefront fitting is valid to indicate the scale of the wavefront distortion quantitatively, and the scales and distribution of the vortex structure affect wavefront distortion greatly for the compressible shear layer. [ABSTRACT FROM AUTHOR]

• Mg-8Gd-4Y-1Zn-0.5Al alloy rolled at 793 K exhibits good surface quality. • β' phase precipitates from matrix in the rolled sheet after aging treatment. • Morphology of 18R-LPSO affects the anisotropy of mechanical properties of alloy. The Mg-8Gd-4Y-1Zn-0.5Al (wt%) alloy prepared by metal type casting were homogenized, rolled or extruded-rolled to obtain sheets, and followed by aging treatment. The microstructures were analyzed by OM, SEM, TEM, EBSD and XRD, the hardness and tensile mechanical properties were tested. The results show that the optimal process is rolling at 793 K with the deformation of 70% for the homogenized sheet. The microstructure of the sheet is composed of fully dynamic recrystallized grains with a strong basal texture, and the aggregated 18R-LPSO structures randomly distribute in the matrix. After peak aging treatment, the yield strength (YS), ultimate tensile strength (UTS) and elongation to failure (EL) of the sheet are 343 MPa, 380 MPa and 7.5%, respectively. After the extruded sheets were rolled at 793 K with 50% deformation, the grains grew up. The texture changes from a silk type to the strong basal type. The 18R-LPSO structures reduce the torsion phenomena, but get together. After peak aging treatment, the YS, UTS and EL reach 391 MPa, 462 MPa and 5.5%, respectively. The 18R-LPSO structures with streamlined distribution along rolling direction increase the anisotropy of mechanical properties of the extruded-rolled sheet. [ABSTRACT FROM AUTHOR]

The Hapke bidirectional reflectance model has mainly been used in planetary remote sensing and has given rise to some studies in Earth science. However, it has not yet been comprehensively evaluated using data from different sources, and its ability to model reflectance spectra needs to be further explored. Therefore, the objective of this study was to develop a tangible parametric model of soil hyperspectral bidirectional reflectance via the evaluation and extension of the Hapke model (hereafter named the Hapke-HSR model). Comprehensive directional and spectral soil reflectance datasets, including satellite, field data, two spectral libraries, and simulated reflectance spectra, were used. First, the two widely used versions of the Hapke model, namely, the SOILSPECT and original Hapke models, were compared. Thereafter, the simplified SOILSPECT model was extended to characterize soil hyperspectral reflectance by deriving an approximate relationship between the single-scattering albedo and wavelength. We obtained the following results. (1) Both versions of the Hapke model agreed well in fitting soil bidirectional reflectance data. However, the SOILSPECT model (R2 = 0.983–0.997, RMSE = 0.007–0.014) performed better than the original Hapke model (R2 = 0.800–0.988, RMSE = 0.014–0.057) when both satellite and field data were used. (2) The Hapke-HSR model could effectively capture the characteristics of the soil hyperspectral reflectance (R2 = 0.963–0.983 and RMSE = 0.018–0.028) based on both spectral libraries. The simulated reflectance spectra showed that the Hapke-HSR model can capture the soil moisture content variations (R2 = 0.987, RMSE = 0.011). In addition, the residual prediction deviation (RPD) values of the Hapke-HSR model were greater than 3, indicating a high prediction accuracy. These findings demonstrate that the Hapke-HSR model performs well with respect to the characterization of soil hyperspectral directional reflectance. • The Hapke model performed well with soil reflectance data from different sources. • The SOILSPECT model performed better than the original Hapke model. • The extended Hapke model effectively represented hyperspectral reflectance. • The extended Hapke model accurately captured soil moisture content variations. [ABSTRACT FROM AUTHOR]

Abstract: Mantel cell lymphoma is one of the small B-cell non-Hodgkin's lymphomas and usually involves lymph nodes, bone marrow, spleen, liver, gastrointestinal tract, and Waldeyer's ring, but rarely skin and orbit. A 53-year-old man presented skin nodules and plaques on the head, trunk, and lower extremities for half a month, and the left periorbital region swelled 4 days ago. Serum calcium and lactate dehydrogenase were increased to 3.12mmol/L (normal 2.03–2.65mmol/L) and 853U/L (normal 71–231U/L), respectively. Histopathologic examination of the skin nodule revealed tumor cells infiltrated nodular distribution in the dermis and subcutaneous tissue. Immunophenotyping of the abnormal lymphocytes indicated positive reactions for L26, CD79a, Bcl-2, Cyclin D1, and Ki-67 (>80%), but negative for CD5, CD21, CD23, CD38, CD3, CD10, UCHL-1, TdT, MPO, CD30, ALK, CD117, and CD34. Fluorescence in situ hybridization analysis with the CCND1/IGH probe revealed a fusion signal on the abnormal lymphocytes. The final diagnosis was a rare case of blastoid mantle cell lymphoma involving skin and orbit with hypercalcemia. Following the R-Hyper-CVAD treatment plan, the patient achieved a quick and excellent recovery on the 6th day. Unfortunately, the patient eventually died of pneumonia one month later. [Copyright &y& Elsevier]

Previous studies have revealed large anomalies in vertical ExB drift during the sudden stratospheric warming (SSW), and little attention focused on the behaviors of field‐aligned plasma drift. We report the first simultaneous observations of the equatorial ionospheric vertical ExB and field‐aligned plasma drifts and neutral winds during the 2020–2021 SSW, using the Ionospheric Connections Explorer (ICON) satellite measurements. The downward ExB drift is observed in the afternoon equatorial topside ionosphere in longitudes of ∼180°–270°E, in good agreement with the Jicamarca incoherent scatter radar measurements. What is more, the ICON records the afternoon northward disturbance in field‐aligned plasma drift, which is mainly due to the disturbance meridional wind. The enhanced semidiurnal tides maybe contribute to the disturbances in equatorial topside plasma drifts and neutral winds. This study indicates that the field‐aligned motion is an important factor in the ionosphere‐thermosphere responses to SSW. Plain Language Summary: Previous studies have revealed that the sudden stratospheric warming causes large anomalies in the low‐latitude ionosphere via the vertical ExB plasma drift driven by the E region wind dynamo. However, ionospheric electron density distributions are not only influenced by the vertical ExB drifts, but also by the plasma drifts along geomagnetic field lines driven by the F region neutral wind and plasma pressure gradient and gravity. In the past studies, little attention focused on the behaviors of the F region field‐aligned plasma drifts during the sudden stratospheric warming (SSW). Ionospheric Connections Explorer (ICON) provides the first simultaneous observations of the E and F region neutral winds and topside ionospheric vertical ExB and field‐aligned plasma drift. The results show that the enhanced semidiurnal tides can cause the significant disturbances in both the F region vertical ExB and field‐aligned plasma drift and neutral winds during the 2020–2021 SSW. The observed neutral wind and plasma drift will likely impact Earth's ionospheric plasma environment and imply a substantial impact of the lower atmosphere on ionospheric space weather. Key Points: The Ionospheric Connections Explorer satellite observes the afternoon downward plasma drift during sudden stratospheric warming (SSW)Disturbance in the F region neutral wind and their contribution to the field‐aligned plasma drift during SSW are observed for the first timeThe enhanced semidiurnal tides may contribute to the F region ExB and field‐aligned plasma drifts [ABSTRACT FROM AUTHOR]

An antipodal linearly tapered slot antenna fed by substrate integrated waveguide for Ku band application is presented.To reduce the mutual coupling between elements, several slots are cut both on the radiation arms and between radiation elements to chock the coupling currents. With this approach, the measured mutual coupling levels between antenna elements are reduced to lower than −27 dB within 13-17 GHz. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53:2512-2515, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26368 [ABSTRACT FROM AUTHOR]

Abstract: The hepatitis C virus (HCV) non-structural (NS) 5A protein plays an essential role in the replication of the viral RNA by the membrane-associated replication complex (RC). Recently, a putative NS5A inhibitor, BMS-790052, exhibited the highest potency of any known anti-HCV compound in inhibiting HCV replication in vitro and showed a promising clinical effect in HCV-infected patients. The precise mechanism of action for this new class of potential anti-HCV therapeutics, however, is still unclear. In order to gain further insight into its mode of action, we sought to test the hypothesis that the antiviral effect of BMS-790052 might be mediated by interfering with the functional assembly of the HCV RC. We observed that BMS-790052 indeed altered the subcellular localization and biochemical fractionation of NS5A. Taken together, our data suggest that NS5A inhibitors such as BMS-790052 can suppress viral genome replication by altering the proper localization of NS5A into functional RCs. [Copyright &y& Elsevier]

The hydrophobicity of vertically aligned multiwalled carbon nanotubes (MWCNTs) was improved through the creation of a parallel array of microwalls via a laser pruning technique. Changes to the hydrophobic nature of the patterned MWCNTs due to artificially induced roughness through variations in both the widths of the walls and the distance between adjacent walls, channel width, were investigated. The sample became more hydrophobic whenever water droplets landed on one microwall 7 or 13 μm in width. However, when a droplet bridged two microwalls, the surface became less hydrophobic. The optimal superhydrophobic MWCNT surface corresponded to a parallel array of microwalls with a width of 13 μm and a channel width of ∼50 μm. Such findings could possibly serve as value-add for further developments in the creation of water-repelling CNT surfaces via micropatterning. [ABSTRACT FROM AUTHOR]