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Abstract Accurate prediction of regional terrestrial water storage change (TWSA) is of great significance for water resources planning and management, and early warning of extreme climate disasters. Aiming at the problem that the conventional methods on prediction of TWSA time series are difficult to be accurate, the six typical regions are selected in China as examples, including the upper reaches of the Yangtze River (UYR), the southwest region (SWR), the Liaohe River Basin (LRB), the North China Plain (NCP), the Qinghai-Tibet Plateau (QTP), and the Pearl River Basin (PRB). The mascon product from GRACE/GRACE-FO provided by CSR is used to extract TWSA time series in six typical areas. The improved Back Propagation (BP) neural network, Long Short-Term Memory (LSTM) neural network and the latest Bidirectional LSTM (BiLSTM-attention) neural network model based on attention mechanism are proposed to predict and analyze the regional TWSA. In the experiment, the selection of the optimal model parameters such as the number of hidden layer nodes and the number of hidden units of the neural network model is tested and analyzed in detail. Meanwhile, the model prediction results are compared with the traditional least squares method and random forest (RF) prediction method. The root mean square error (RMSE), determination coefficient (R2), Nash–Sutcliffe efficiency coefficient (NSE) and mean absolute percentage error (MAPE) were used to evaluate the accuracy of the predicted results. The results show that the improved BP, LSTM and Bi-LSTM-attention neural network models all achieve higher prediction accuracy in UYR and SWR areas. RMSE is less than 2.641 cm, R2 is as high as 0.8 or more, NSE is above 0.6, and MAPE is within 0.1. Compared with the least square method, the RMSE of the predicted results from three neural network decreased by 0.998 cm, 0.700 cm and 0.7563 on average, and the R2 increased by 81.75%, 69.89% and 72% on average. Compared with RFML method, the RMSE from three neural network is reduced by 0.601 cm, 0.316 cm and 0.360, and R2 is increased by 38.20%, 24.60% and 27.06% on average. NSE and RMSE are improved to varying degrees in the above regions. It shows that the improved BP, LSTM and BiLSTM-attention model used can effectively predict TWSA. The research methods and results in this paper can provide important reference for the rational utilization of regional water resources and disaster risk assessment.

A novel recrystallization and partial melting process combined radial forging was proposed to prepare long axial 2A50 aluminum alloy semi-solid billets. Microstructure characteristics of the forged and isothermal treated samples were investigated. Results demonstrate that initial elongated grains (fibrous structure) and low angle grain boundaries were substituted by spherical equiaxed grains and high angle grain boundaries when the sample was heated at 585 °C for 10 min. Deformed textures of the forged 2A50 aluminum alloy were remarkably weaken after isothermal treatment. The average grain size and shape factor increased with the increased temperature and holding time. Long holding time resulted in some dendrites. The liquid films at the grain boundaries thickened with the increase in temperature and holding time. Grains growth and spheroidization were determined by coarsening and Ostwald ripening mechanisms. The coarsening rate constant k of grains at 575 °C was 378.5 μm3/s.

Abstract Nanofluidic membranes have demonstrated great potential in harvesting osmotic energy. However, the output power densities are usually hampered by insufficient membrane permselectivity. Herein, we design a polyoxometalates (POMs)-based nanofluidic plasmonic electron sponge membrane (PESM) for highly efficient osmotic energy conversion. Under light irradiation, hot electrons are generated on Au NPs surface and then transferred and stored in POMs electron sponges, while hot holes are consumed by water. The stored hot electrons in POMs increase the charge density and hydrophilicity of PESM, resulting in significantly improved permselectivity for high-performance osmotic energy conversion. In addition, the unique ionic current rectification (ICR) property of the prepared nanofluidic PESM inhibits ion concentration polarization effectively, which could further improve its permselectivity. Under light with 500-fold NaCl gradient, the maximum output power density of the prepared PESM reaches 70.4 W m−2, which is further enhanced even to 102.1 W m−2 by changing the ligand to P5W30. This work highlights the crucial roles of plasmonic electron sponge for tailoring the surface charge, modulating ion transport dynamics, and improving the performance of nanofluidic osmotic energy conversion.

In this work, the blueberry candied syrup was separated and purified by microfiltration combined with macroporous resin technology to recover anthocyanins. Firstly, the macroporous resin was screened through static test. On the basis of single factor and Box-Behnken response surface tests, the flow rate, ethanol concentration and elution flow rate were optimized with anthocyanin recovery rate and total sugar removal rate as indexes in the dynamic test. The result showed that the anthocyanin content and the total sugar content were 6.84 mg/100 mL and 31.76 mg/mL respectively. Among AB-8, D101 and HPD 600 resins, AB-8 was optimized for the purification of anthocyanins from blueberry candied syrup, and the best technological conditions for the purification of anthocyanins by macroporous resin were as follows: The flow rate was 2.0 mL/min, the ethanol concentration was 83%, and the elution flow rate was 2.0 mL/min. Under these conditions, the anthocyanin recovery rate was 86.68%, and the total sugar removal rate was 84.13%. After the anthocyanin desorbing solution was concentrated by rotation evaporation, the concentration of anthocyanin was 5.56 mg/100 mL, and the total sugar concentration was 5.24 mg/mL. The color value of anthocyanins was 31.43, which was about 5 times of the color value of anthocyanins in raw materials. Microfiltration combined with macroporous resin purification of blueberry candied syrup anthocyanin was effective, and this study provides some technical reference for the isolation and purification of blueberry anthocyanin.

High-precision sea surface height is crucial for determining the marine gravity field. The Sentinel-3/6 altimetry missions, equipped with SRAL and Poseidon-4 altimeters, provide this essential data. However, there is a lack of comprehensive assessment of the Sentinel-3/6 altimeters for inverting marine gravity anomalies (MGA). In this study, we employ the inverse Venning-Meinsz method to derive nine sets of 1’×1’ MGAs in the South China Sea (SCS) and the Ross Sea (RS). Specifically, MGAs from Sentinel-3A, Sentinel-3B, Sentinel-6 SARM, Sentinel-6 LRM, HY-2A, ICESat-2, and CryoSat-2 are denoted as S3A, S3B, S6S, S6L, H2A, IS2, and CS2, respectively. MGA from the combined HY-2A, ICESat-2, and CryoSat-2 is referred to as HIC, while 3SHIC denotes the MGA from the combination of Sentinel-3/6 SARM, HY2A, ICESat-2, and CryoSat-2. We assess the performance of these MGAs using the EGM08, DTU17, SIO V32.1, and SDUST2021 gravity field models, as well as shipboard gravity across different ocean regions. Among the Sentinel-3/6 MGAs, S3B exhibits the highest accuracy in the SCS, with a root mean square error (RMSE) of 5.277 mGal, followed closely by S3A. Conversely, S3A demonstrates the highest accuracy with an RMSE of 4.635 mGal, followed by S3B in the RS. The inversion accuracy of MGAs from S6S and S6L are comparable, though S6S outperforms S6L in the open sea. The performance of MGAs from Sentinel-3/6 matches or surpasses that of other altimetry missions during the same period. In the SCS, the best-performing MGA is 3SHIC, with an RMSE of 4.585 mGal, closely matching DTU17. However, 3SHIC exhibits superior performance in the RS with an RMSE of 4.263 mGal compared to DTU17 and SDUST 2021. Furthermore, the performance of 3SHIC, which integrates Sentinel-3/6 data, improves that of HIC by 0.74% and 3.37% in the SCS and RS, respectively. These results underscore the contribution of Sentinel-3/6 altimeters to the MGA, particularly in coastal and high-latitude regions. Integration of Sentinel-3/6 data with other altimetry satellites is expected to enhance the spatial resolution and accuracy of the global marine gravity field, especially with the successful establishment of the network of Sentinel-6 in the future.

Background and objectiveThe rupture risk of intracranial aneurysms (IAs) is related to their arterial origin, but whether the different segments of the artery have different risks and act as independent risk factors is still unknown. Our study aimed to investigate the rupture risk of IAs in different arterial segments in a large Chinese cohort.MethodsImaging and clinical data of consecutive patients with IAs diagnosed by Computed Tomography angiography (CTA) from January 2013 to December 2022 were collected. Two neuroradiologists independently identified ruptured and unruptured IAs based on imaging and medical records. The internal carotid artery (ICA), middle cerebral artery (MCA), anterior cerebral artery (ACA), vertebral artery (VA), and posterior cerebral artery (PCA) were segmented according to the Bouthillier and Fischer segmentation methods. Stenoses of the proximal parent vessel were evaluated and documented. The Institutional Review Board (IRB) at Beijing Tiantan Hospital approved this retrospective study.ResultsA total of 3,837 aneurysms {median size 3.5 mm [interquartile range (IQR) 2.6–5.1 mm]; 532 ruptured} were included in this study from 2,968 patients [mean age: 57 years (IQR 50–64); male patients: 1,153]. Ruptured aneurysms were most commonly located in the posterior inferior cerebellar artery (PICA) (52.9%), anterior communicating artery (ACoA) (33.8%), other locations (33.3%), ACA (22.4%), and basilar artery (BA) (21.4%). The locations with the highest likelihood of rupture were the C7 ICA (21.3%), M2 MCA (24.0%), distal MCA (25.0%), and A2 ACA (28.1%). IAs originating from the C7 (p < 0.001), dM1 (p = 0.022), and dA1 (p = 0.021) segments were independent risk factors for rupture. IAs without stenosis of the proximal parent vessel were associated with a higher risk of rupture (p = 0.023).ConclusionThere are unique associations between the origins of aneurysms from various arterial segments. Aneurysms originating from the anterior communicating artery (ACoA), BA, PICA, A2, dA, C7, and M2 indicate a higher risk of rupture. Aneurysms originating from C4, C5, and C6 indicate a lower risk of rupture. C7 IAs, ACoA IAs, and PICA IAs seem to be independent risk factors.

Abstract Efficient animal detection is essential for biodiversity protection. Unmanned aerial vehicles (UAVs) have been widely used because of their low costs and minimal environmental intrusion. However, using UAVs for practical animal detection poses two challenges: (a) the UAV's fly highly to avoid disturbing animals, resulting in small object detection problems; (b) the limited processing power of UAVs makes large state‐of‐the‐art (SOTA) methods (e.g., You Only Look Once V7, YOLOv7) difficult to deploy. This work proposes the WILD‐YOLO based on YOLOv7 to deal with the two problems. To detect small objects, WILD‐YOLO improves upon YOLOv7 by adding a small object detection head in the head part. To enable real‐time animal detection in field environments with UAVs, the lighten FasterNet and GhostNet have been used to significantly reduce the model size. Compared to YOLOv7, WILD‐YOLO significantly reduces the number of parameters, making it suitable for lightweight deployment on UAVs. Additionally, comparisons with other lightweight models such as YOLOv7‐tiny, YOLOv5‐s, YOLOv4‐s and MobilenetV2 on the datasets are conducted. The experimental results demonstrate that this proposed WILD‐YOLO method outperforms other approaches and has great potential for effective detection of wildlife in complex environments encountered by UAVs.

Abstract Monitoring and predicting the regional groundwater storage (GWS) fluctuation is an essential support for effectively managing water resources. Therefore, taking Shandong Province as an example, the data from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) is used to invert GWS fluctuation from January 2003 to December 2022 together with Watergap Global Hydrological Model (WGHM), in-situ groundwater volume and level data. The spatio-temporal characteristics are decomposed using Independent Components Analysis (ICA), and the impact factors, such as precipitation and human activities, which are also analyzed. To predict the short-time changes of GWS, the Support Vector Machines (SVM) is adopted together with three commonly used methods Long Short-Term Memory (LSTM), Singular Spectrum Analysis (SSA), Auto-Regressive Moving Average Model (ARMA), as the comparison. The results show that: (1) The loss intensity of western GWS is significantly greater than those in coastal areas. From 2003 to 2006, GWS increased sharply; during 2007 to 2014, there exists a loss rate − 5.80 ± 2.28 mm/a of GWS; the linear trend of GWS change is − 5.39 ± 3.65 mm/a from 2015 to 2022, may be mainly due to the effect of South-to-North Water Diversion Project. The correlation coefficient between GRACE and WGHM is 0.67, which is consistent with in-situ groundwater volume and level. (2) The GWS has higher positive correlation with monthly Global Precipitation Climatology Project (GPCP) considering time delay after moving average, which has the similar energy spectrum depending on Continuous Wavelet Transform (CWT) method. In addition, the influencing facotrs on annual GWS fluctuation are analyzed, the correlation coefficient between GWS and in-situ data including the consumption of groundwater mining, farmland irrigation is 0.80, 0.71, respectively. (3) For the GWS prediction, SVM method is adopted to analyze, three training samples with 180, 204 and 228 months are established with the goodness-of-fit all higher than 0.97. The correlation coefficients are 0.56, 0.75, 0.68; RMSE is 5.26, 4.42, 5.65 mm; NSE is 0.28, 0.43, 0.36, respectively. The performance of SVM model is better than the other methods for the short-term prediction.

ABSTRACTStaphylococcus pseudintermedius (S. pseudintermedius) is a common pathogen that causes canine corneal ulcers. However, the pathogenesis remained unclear. In this study, it has been demonstrated that S. pseudintermedius invaded canine corneal epithelial cells (CCECs) intracellularly, mediating oxidative damage and pyroptosis by promoting the accumulation of intracellular reactive oxygen species (ROS) and activating the NLRP3 inflammasome. The canine corneal stroma was infected with S. pseudintermedius to establish the canine corneal ulcer model in vivo. The intracellular infectious model in CCECs was established in vitro to explore the mechanism of the ROS – NLRP3 signalling pathway during the S. pseudintermedius infection by adding NAC or MCC950. Results showed that the expression of NLRP3 and gasdermin D (GSDMD) proteins increased significantly in the infected corneas (p < 0.01). The intracellular infection of S. pseudintermedius was confirmed by transmission electron microscopy and immunofluorescent 3D imaging. Flow cytometry analysis revealed that ROS and pyroptosis rates increased in the experimental group in contrast to the control group (p

Objective With mechanical thrombectomy (MT), we investigated the prognostic importance of aortic arch calcification (AoAC) and carotid sinus calcification (CaSC) for symptomatic intracerebral hemorrhage (sICH) and poor outcome in acute large artery occlusion (LAO). Methods In this retrospective observational study, we calculated pre-cranial artery calcification burden (PACB) scores (burden score of AoAC and CaSC) using the AoAC grading scale score plus Woodcock visual score. The outcome measure was sICH per the European Cooperative Acute Stroke Study III definition. A 3-month modified Rankin scale score 3–6 was designated as poor outcome. Results Compared with patients who had PACB

After long-term development, the global economic level has improved significantly, but environmental issues generated by early extensive development seriously threaten the survival of human beings. China, in particular, urgently needs to promote sustainable development through green finance policies. For this reason, this paper regards the 2017 eight pilot zones in five provinces for green finance reform and innovations (GFRIs) as a quasi-natural experiment, and explores whether it can encourage investment in environmental protection in heavily polluting enterprises by using difference-in-differences-in-differences (DDD) model. The paper finds that: First, GFRIs can bolster investment in environmental protection in heavy polluting enterprises. The results remain consistent after several robustness checks, covering the placebo test, PSM-DID test and so on. Second, mechanism tests find that the policy promotes environmental protection investment by alleviating financing constraints and cutting financing costs. Third, heterogeneity analysis shows that the promotion effect of GFRIs on environmental protection investment is more pronounced for provinces with higher percentages of secondary industry GDP, large-scale enterprises, and enterprises with better ESG management. This paper demonstrates the beneficial influence of GFRIs on promoting the transformation of heavy polluting enterprises and provides suggestions for the improvement of such policies.

Massive online open courses (MOOCs) have been extensively researched in reducing user learning blindness and improving user experience, especially personalized course resource recommendation based on graph neural networks. However, these efforts focus primarily on fixed or homogeneous graphs, vulnerable to data sparsity problems, and difficult to scale. This paper uses graph convolution on local subgraphs combined with an extended matrix factorization (MF) model to overcome this limitation. Firstly, the proposed method decomposes the heterogeneous graph into multiple meta-path-based subgraphs and combines random wandering sampling methods to capture complex semantic relationships between entities while sampling nodes’ influential neighborhoods, and performs graph convolution on local neighborhoods to smooth the representation of each node and achieve high scalability. Next, the attention mechanism adaptively fuses the contextual information of different subgraphs for a more comprehensive construction of user preferences. Finally, the model parameters are optimized by expanding MF to obtain recommendation list. To validate the performance of the proposed model, comparative experiments are conducted on publicly available MOOCs datasets, with a 2% performance improvement and a nearly 500% reduction in memory computation requirements compared with the optimal baseline, providing strong scalability while alleviating the data sparsity problem.

Background: and purpose: Acupuncture and moxibustion, as a complementary and alternative therapy, has been widely used in the treatment of acute gouty arthritis (AGA). However, there are various forms of acupuncture and moxibustion, and the curative effect of different forms is different. This study evaluated the clinical efficacy of different acupuncture therapies in treating AGA by network meta-analysis. Methods: Computer searches of English databases (including PubMed, The Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, Embase) and Chinese databases (including China National Knowledge Infrastructure (CNKI), VIP Database, Wanfang Database and China Biomedical Literature Database) were conducted for randomized controlled trials (RCTs) of acupuncture therapies in treating AGA. We set the search time from the database establishment to May 2022. Data analysis was performed using Stata14.2 software. Results: Thirty-two RCTs involving 2434 patients with AGA were screened out. The results showed that in terms of the improvement of pain visual analogue scale (VAS) scores, the top ones were acupoint application (100%), electroacupuncture + Western medicine (73.5%) and acupuncture + Western medicine (69.2%); In terms of total effective rate, acupoint application (85.2%), acupuncture (75.2%) and acupuncture + Western medicine (63%) ranked the top; In terms of reducing serum uric acid (SUA) levels, the top ones were acupoint application (95%), acupuncture + Western medicine (87.5%) and acupuncture (66.2%); In terms of the reduction of erythrocyte sedimentation rate (ESR), acupuncture (95%), acupoint application (84.7%), and electroacupuncture + Western medicine (52.8%) were the most prominent. Conclusion: The existing evidence shows that acupoint application has more advantages in improving the total effective rate, improving pain and reduce SUA levels, and acupuncture has an advantage in reducing ESR levels and adverse events. However, due to the low qualities of the original studies, the quality of this evidence is poor. Therefore, it is recommended that more scientific research be performed to confirm the efficacy of acupuncture.

Abstract Background Ralstonia solanacearum (Rs) is a soilborne phytopathogen that causes bacterial wilt and substantial yield losses in many plants, such as tomatoes. A resistant tomato cultivar can recruit a beneficial microbiome from soil to resist Rs. However, whether this recruitment is inheritable from resistant parent to progeny has not been determined. Results In the present study, we investigated the rhizosphere microbiomes of tomatoes with clear kinship and different resistance against Rs. Resistant tomatoes grown with the additions of natural soil or its extract showed lower disease indexes than those grown in the sterile soil, demonstrating the importance of soil microbiome in resisting Rs. The results of 16S ribosomal RNA gene amplicon sequencing revealed that the resistant cultivars had more robust rhizosphere microbiomes than the susceptible ones. Besides, the resistant progeny HF12 resembled its resistant parent HG64 in the rhizosphere microbiome. The rhizosphere microbiome had functional consistency between HF12 and HG64 as revealed by metagenomics. Based on multi-omics analysis and experimental validation, two rhizobacteria (Sphingomonas sp. Cra20 and Pseudomonas putida KT2440) were enriched in HF12 and HG64 with the ability to offer susceptible tomatoes considerable protection against Rs. Multiple aspects were involved in the protection, including reducing the virulence-related genes of Rs and reshaping the transcriptomes of the susceptible tomatoes. Conclusions We found promising bacteria to suppress the tomato bacterial wilt in sustainable agriculture. And our research provides insights into the heritability of Rs-resistant tomato rhizobacteria, echoing the inheritance of tomato genetic material. Video Abstract

The concentrated blueberry candied syrup and the whole milk sterilized pure milk were used as raw material to prepare set yoghurt. The influence of addition amount for blueberry candied syrup, sugar content, starter inoculation quantity and fermentation time on the yogurt sensory quality, whey exhalation rate and acidity were investigated. Furthermore, the response surface experiment was carried out on the basis of single factor experiment to optimize the set yoghurt preparation technological parameters. Then the texture parameters of yoghurt were compared with those of commercial yoghurt. The results showed that the optimal preparation technology of blueberry set yoghurt was as follows: The addition amount of concentrate blueberry candied syrup (concentration ratio 2 with the total sugar content 0.679 mg/mL) in the yoghurt 7%, custer sugar 4%, starter inoculation amount 0.6%, whey protein powder 2%, and fermentation control time 11 h. Under these conditions, the whey release rate was 12.43%, the acidity was 83.66°T and the sensory score reached the highest score 88.13. The blueberry set yoghurt was purple with strong frankincense and blueberry flavor. The hardness, cohesiveness and adhesiveness of this product were lower than those of commercially available fermented milk, but the water holding capacity was stronger. It was more delicate and refreshing, which tasted better than the commercially available products with thickening agent addition. In this study, the basic preparation conditions of set yoghurt of blueberry preserved fruit syrup were determined, which provided useful reference for improving the comprehensive utilization value of blueberry preserved fruit syrup and developing new fruity set yoghurt.

Abstract Background As a noninvasive tool, myocardial deformation imaging may facilitate the early detection of cardiac dysfunction. However, normal reference ranges of myocardial strain and strain rate (SR) based on large-scale East Asian populations are still lacking. This study aimed to provide reference values of left ventricular (LV) and right ventricular (RV) strain and SR based on a large cohort of healthy Chinese adults using cardiovascular magnetic resonance (CMR) feature tracking (FT). Methods Five hundred and sixty-six healthy Chinese adults (55.1% men) free of hypertension, diabetes, and obesity were included. On cine CMR, biventricular global radial, circumferential, and longitudinal strain (GRS, GCS, and GLS), and the peak radial, circumferential, and longitudinal systolic, and diastolic SRs (PSSRR, PSSRC, PSSRL, PDSRR, PDSRC, and PDSRL), and regional radial and circumferential strain at the basal, mid-cavity, and apical levels were measured. Associations of global and regional biventricular deformation indices with age and sex were investigated. Results Women demonstrated greater magnitudes of LV GRS (37.6 ± 6.1% vs. 32.1 ± 5.3%), GCS (− 20.7 ± 1.9% vs. − 18.8 ± 1.9%), GLS (− 17.8 ± 1.8% vs. − 15.6 ± 1.8%), RV GRS (25.1 ± 7.8% vs. 22.1 ± 6.7%), GCS (− 14.4 ± 3.6% vs. − 13.2 ± 3.2%), GLS (− 22.4 ± 5.2% vs. − 20.2 ± 4.6%), and biventricular peak systolic and diastolic SR in all three coordinate directions (all P

To better understand the elevated temperature flow behaviors of 30Si2MnCrMoVE low-alloy ultra-high strength steel, hot compressive deformation tests were performed at a wide range of forming temperatures (1123–1423 K) and strain rates (0.01–1s−1). The constitutive equations of the material were established through the physical-based modified Zerilli-Armstrong (ZA) and phenomenological Arrhenius-type models, along with the optimized ZA model of strain compensation constructed based on the modified ZA model. Suitability of these models were evaluated by comparing the correlation coefficient and absolute average error between the prediction and experimental data, its ability to predict the deformation behavior, and the amount of calculation required for the material constants. Results show that the modified ZA model cannot accurately describe the flow behavior of the 30Si2MnCrMoVE steel in the abovementioned hot working zone. The optimized ZA model and Arrhenius-Type model based on strain compensation require similar computational effort, and both can effectively predict the high temperature flow behavior of 30Si2MnCrMoVE steel. Relatively, the Arrhenius type model has the highest prediction accuracy.

In order to study the attenuation regularity of membrane flux in the process of forward osmosis (FO) concentration, the fouling rule of FO membrane affected by different parameters including ionic strength, BSA concentration in the feed and membrane orientation was studied with Bovine serum albumin (BSA) as the primary typical pollutants. In order to improve the membrane flux and rejection rate, the type and concentration of draw solution and the flow rate of feed solution were optimized and the appropriate membrane cleaning scheme was optimized. The results showed that the initial flux of FO membrane decreased with the increasing of ionic strength in feed solution, but the flux of FO membrane with BSA solution containing salt ions was higher than that of pure BSA solution as the running time went on. The lower the concentration of BSA, the lighter the membrane fouling was, and the water flux in FO mode (13.82±3.2 L/m2·h) was higher than that in PRO mode (5.08±2.1 L/m2·h), which indicated that FO mode should be adopted for concentration. Under the optimal operating conditions, the 1.5 mol/L NaCl as the draw solution and the flow rate of both feed and draw solution controlled at 2.89 m/s, FO flux was 11.23±2.13 L/m2·h, BSA retention rate was 97.83%, and reverse solute flux Js was 0.14 mol/m2·h. After the fouled membrane was immersed in 0.05% NaOH for 4 min, the flux recovery rate reached 98.39% and the flux recovery rate was still exceed 98% after reusing and cleaning many times, which indicated that the membrane had good cleaning resistance. This study would provide a certain technical reference for protein recovery from food materials.

With the development trend of an aging society, Alzheimer’s disease (AD) has become an urgent problem in the field of medicine worldwide. Cognitive impairment in AD patients leads to a decline in the ability to perform daily living and abnormalities in behavior and personality, causing abnormal psychiatric symptoms, which seriously affect the daily life of patients. Currently, mainly drug therapy is used for AD patients in the clinic, but a large proportion of patients will experience drug efficacy not working, and even some drugs bring severe sleep disorders. Acupuncture, with its unique concept and treatment method, has been validated through a large number of experiments and proved its reliability of acupuncture in the treatment of AD. Many advances have been made in the study of the neurobiological mechanisms of acupuncture in the treatment of AD, further demonstrating the good efficacy and unique advantages of acupuncture in the treatment of AD. This review first summarizes the pathogenesis of AD and then illustrates the research progress of acupuncture in the treatment of AD, which includes the effect of acupuncture on the changes of biochemical indicators in AD in vivo and the specific mechanism of action to exert the therapeutic effect. Changes in relevant indicators of AD similarly further validate the effectiveness of acupuncture treatment. The clinical and mechanistic studies of acupuncture in the treatment of AD are intensified to fit the need for social development. It is believed that acupuncture will achieve new achievements in the treatment of AD as research progresses.

In recent years, ultra-high-field magnetic resonance imaging (MRI) applications have been rapidly increasing in both clinical research and practice. Indeed, 7-Tesla (7T) MRI allows improved depiction of smaller structures with high signal-to-noise ratio, and, therefore, may improve lesion visualization, diagnostic capabilities, and thus potentially affect treatment decision-making. Incremental evidence emerging from research over the past two decades has provided a promising prospect of 7T magnetic resonance angiography (MRA) in the evaluation of intracranial vasculature. The ultra-high resolution and excellent image quality of 7T MRA allow us to explore detailed morphological and hemodynamic information, detect subtle pathological changes in early stages, and provide new insights allowing for deeper understanding of pathological mechanisms of various cerebrovascular diseases. However, along with the benefits of ultra-high field strength, some challenges and concerns exist. Despite these, ongoing technical developments and clinical oriented research will facilitate the widespread clinical application of 7T MRA in the near future. In this review article, we summarize technical aspects, clinical applications, and recent advances of 7T MRA in the evaluation of intracranial vascular disease. The aim of this review is to provide a clinical perspective for the potential application of 7T MRA for the assessment of intracranial vascular disease, and to explore possible future research directions implementing this technique. [ABSTRACT FROM AUTHOR]

Drones are widely used for wildlife monitoring. Deep learning algorithms are key to the success of monitoring wildlife with drones, although they face the problem of detecting small targets. To solve this problem, we have introduced the SE-YOLO model, which incorporates a channel self-attention mechanism into the advanced real-time object detection algorithm YOLOv7, enabling the model to perform effectively on small targets. However, there is another barrier; the lack of publicly available UAV wildlife aerial datasets hampers research on UAV wildlife monitoring algorithms. To fill this gap, we present a large-scale, multi-class, high-quality dataset called WAID (Wildlife Aerial Images from Drone), which contains 14,375 UAV aerial images from different environmental conditions, covering six wildlife species and multiple habitat types. We conducted a statistical analysis experiment, an algorithm detection comparison experiment, and a dataset generalization experiment. The statistical analysis experiment demonstrated the dataset characteristics both quantitatively and intuitively. The comparison and generalization experiments compared different types of advanced algorithms as well as the SE-YOLO method from the perspective of the practical application of UAVs for wildlife monitoring. The experimental results show that WAID is suitable for the study of wildlife monitoring algorithms for UAVs, and SE-YOLO is the most effective in this scenario, with a mAP of up to 0.983. This study brings new methods, data, and inspiration to the field of wildlife monitoring by UAVs.

The propagation of ultrasonic wave in solids can cause a softening effect during metal deformation, and this concept has been widely exploited in micro-forming. Low-frequency vibration with micro-amplitudes was recently found to have a similar effect on metal deformation. In this study, the effects of low-frequency vibration on the mechanical behavior and microstructure of low-carbon steel DC04 during upsetting deformation was investigated. Vibration-assisted compression test results showed low-frequency vibration had a softening effect, that was proportional to vibration amplitude. Residual softening occurred in all cases during re-yield period after vibration removal. A sectional view of the deformed sample showed that vibration with larger amplitude could exacerbate the deformation of the contact area between the sample and the mold. The internal misorientation of grains in the deformation zone of the compressed sample increased significantly after large vibration treatment, indicating that low-frequency vibration promoted the occurrence of plastic deformation. A softening model considering transfer efficiency was proposed to explain the different performances under the action of small amplitude and large amplitude vibration. The residual softening effect that occurred in this study was an illusion produced by the uneven sample deformation caused by low-frequency vibration.

Background and purposeNon-invasive and accurate assessment of intracranial arterial stenosis (ICAS) is important for the evaluation of intracranial atherosclerotic disease. This study aimed to evaluate the performance of 3D pointwise encoding time reduction magnetic resonance angiography (PETRA-MRA) and compare its performance with that of 3D time-of-flight (TOF) MRA and computed tomography angiography (CTA), using digital subtraction angiography (DSA) as the reference standard in measuring the degree of stenosis and lesion length.Materials and methodsThis single-center, prospective study included a total of 52 patients (mean age 57 ± 11 years, 27 men, 25 women) with 90 intracranial arterial stenoses who underwent PETRA-MRA, TOF-MRA, CTA, and DSA within 1 month. The degree of stenosis and lesion length were measured independently by two radiologists on these four datasets. The degree of stenosis was classified according to DSA measurement. Severe stenosis was defined as a single lesion with >70% diameter stenosis. The smaller artery stenosis referred to the stenosis, which occurred at the anterior cerebral artery, middle cerebral artery, and posterior cerebral artery, except for the first segment of them. The continuous variables were compared using paired t-test or Wilcoxon signed rank test. The intraclass correlation coefficients (ICCs) were used to assess the agreement between MRAs/CTA and DSA as well as inter-reader variabilities. The ICC value >0.80 indicated excellent agreement. The agreement of data was assessed further by Bland–Altman analysis and Spearman's correlation coefficients. When the difference between MRAs/CTA and DSA was statistically significant in the degree of stenosis, the measurement of MRAs/CTA was larger than that of DSA, which referred to the overestimation of MRAs/CTA for the degree of stenosis.ResultsThe four imaging methods exhibited excellent inter-reader agreement [intraclass correlation coefficients (ICCs) > 0.80]. PETRA-MRA was more consistent with DSA than with TOF-MRA and CTA in measuring the degree of stenosis (ICC = 0.94 vs. 0.79 and 0.89) and lesion length (ICC = 0.99 vs. 0.97 and 0.73). PETRA-MRA obtained the highest specificity and positive predictive value (PPV) than TOF-MRA and CTA for detecting stenosis of >50% and stenosis of >75%. TOF-MRA and CTA overestimated considerably the degree of stenosis compared with DSA (63.0% ± 15.8% and 61.0% ± 18.6% vs. 54.0% ± 18.6%, P < 0.01, respectively), whereas PETRA-MRA did not overestimate (P = 0.13). The degree of stenosis acquired on PETRA-MRA was also more consistent with that on DSA than with that on TOF-MRA and CTA in severe stenosis (ICC = 0.78 vs. 0.30 and 0.57) and smaller artery stenosis (ICC = 0.95 vs. 0.70 and 0.80). In anterior artery circulation stenosis, PETRA-MRA also achieved a little bigger ICC than TOF-MRA and CTA in measuring the degree of stenosis (0.93 vs. 0.78 and 0.88). In posterior artery circulation stenosis, PETRA-MRA had a bigger ICC than TOF-MRA (0.94 vs. 0.71) and a comparable ICC to CTA (0.94 vs. 0.91) in measuring the degree of stenosis.ConclusionPETRA-MRA is more accurate than TOF-MRA and CTA for the evaluation of intracranial stenosis and lesion length when using DSA as a reference standard. PETRA-MRA is a promising non-invasive tool for ICAS assessment.

Abstract Background The prevalence of myopia is increasing worldwide and is presently recognized as a major public health issue. Researchers and clinicians have been devoted in exploring appropriate clinical interventions to slow its progression in children. Mounting publications have proven that both orthokeratology (OK lens) and 0.01% atropine eyedrop can retard eye growth and myopia progression. However, it remains unclear whether the combination of OK lens and 0.01% atropine has the potential to magnify the effectiveness of myopia control. The present study aims to compare the myopia control efficiency of the combination of OK lens and 0.01% atropine with the monotherapy of OK lens in children. Methods The present study is a randomized, controlled, double-blind and multicenter clinical trial. A total of 96 children within 8–12 years old were recruited. These participants are treated with the combination of OK lens and 0.01% atropine eyedrop or the combination of OK lens and placebo eyedrop. Each group includes 48 participants. The inclusion criteria are as follows: myopia between − 1.00 and − 4.00 D in either eye and astigmatism of no more than 1.50 D. The follow-up time points will be 1, 6, 12, 18, and 24 months from randomization. The primary outcome is determined by the difference in axial length of the two groups, between the baseline and 24 months from randomization. Discussion The present randomized, controlled clinical trial would indicate the additive effects of the combination of OK lens and 0.01% atropine, and the extent of these effects, in retarding myopia progression and axial elongation in children. Trial registration Chinese Clinical Trial Registry (ChiCTR), ChiCTR1800018419 . Registered on 17 September 2018. http://www.chictr.org.cn/showproj.aspx?proj=29216

Alzheimer's disease (AD) as an advanced brain disorder may cause damage to the memory and tissue loss in the brain. Since AD is a mostly costly disease, various deep learning-based models have been presented to achieve a high accuracy classifier to Alzheimer's diagnosis. While a model with high discriminative features is required to obtain a high performance classifier, the lack of image samples in the datasets causes over-fitting and deteriorates the performance of deep learning models. To overcome this problem, few-shot learning such as deep metric learning was introduced. In this paper we employ a novel deep triplet network as a metric learning approach to brain MRI analysis and Alzheimer's detection. The proposed deep triplet network uses a conditional loss function to overcome the lack of limited samples and improve the accuracy of the model. The basic network of this model inspired by VGG16 and experiments are conducted on open access series of imaging studies (OASIS). The experiments show that the proposed model outperforms the state-of-the-art models in term of accuracy.

ObjectiveTo describe the surgical techniques and short-term outcomes for 50 cases of modified sacrospinous ligament fixation via the anterior vaginal wall path for pelvic organ prolapseMethods100 patients with pelvic organ prolapse (stage III or stage IV based on POP-Q staging) from January 2018 to January 2020 were retrospectively analyzed. Among them, 50 patients received modified sacrospinous ligament fixation via the anterior vaginal wall path for pelvic organ prolapse (mSSLF group), while the other 50 patients received pelvic reconstruction using T4 mesh (T4 group). Operative time, blood loss, postoperative POP-Q score, length of the hospital stay, complications, and postoperative pain were compared between the two groups.ResultsThe duration of the operation in mSSLF group was (50 ± 15.2 min), which was shorter than that of the T4 group (60 ± 14.8 min) (p = 0.02). No intraoperative complications were reported from the mSSLF group, whereas one vascular injury occurred in the T4 group. In both groups, postoperative pain and painful intercourse was significantly lower in the mSSLF group than in the SSLF group (p

Altimeter data processing is very important to improve the quality of sea surface height (SSH) measurements. Sea state bias (SSB) correction is a relatively uncertain error correction due to the lack of a clear theoretical model. At present, the commonly used methods for SSB correction are polynomial models (parametric models) and non-parametric models. The non-parametric model usually was constructed by collinear data. However, the amount of collinear data was enormous, and it contained redundant information. In this study, the non-parametric regression estimation model was optimized by using the parameter replacement method of ascending and descending tracks based on the crossover data. In this method, significant wave heights from the Jason-2 altimeter data during cycles 200–301 and wind speed from the ERA5 reanalysis data were used. The non-parametric regression estimation model of Jason-2 was constructed by combining it with local linear regression, Epanechnikov kernel function and local window width. At the same time, based on the significant wave height and wind speed at the crossover points, the SSB polynomial model containing six parameters was constructed by using the Taylor series expansion, and the model was optimized. By comparing polynomial model construction with different parameters, the optimized model was obtained. The SSH of the crossover points and the tide gauge records were used to validate these results derived from two models and GDR. Compared with the crossover discrepancies of SSH corrected by the polynomial model, the RMS of the crossover discrepancies of SSH corrected by the non-parametric regression estimation model was reduced by 7.9%. Compared with the crossover discrepancies of SSH corrected by the conventional non-parametric model from GDR, the RMS of the crossover discrepancies of SSH corrected by the non-parametric regression estimation model was reduced by 4.1%. This shows that the precision of the SSHs derived by after the SSB correction, as calculated by the non-parametric regression estimation model, was better than that of the polynomial model and the SSB correction from GDR. Using the Jason-2 altimeter data, the along-track geoid gradient and the sea level change rate of the global ocean were determined by using two models to correct the SSB. By comparing the results of the two models, the accuracy of the geoid gradient along the orbit that was obtained by the non-parametric regression estimation model was better than that of the polynomial model and GDR. The global average sea level change rate after the non-parametric regression estimation model correction was 3.47 ± 0.09 mm/y, which was the closest to the average sea level change rate that has been published in the international literature within this field.