Search

Liposarcoma (LPS) is one of the most common subtypes of sarcoma with a high recurrence rate. CENPF is a regulator of cell cycle, differential expression of which has been shown to be related with various cancers. However, the prognostic value of CENPF in LPS has not been deciphered yet. Using data from TCGA and GEO datasets, the expression difference of CENPF and its effects on the prognosis or immune infiltration of LPS patients were analyzed. As results show, CENPF was significantly upregulated in LPS compared to normal tissues. Survival curves illustrated that high CENPF expression was significantly associated with adverse prognosis. Univariate and multivariate analysis suggested that CENPF expression could be an independent risk factor for LPS. CENPF was closely related to chromosome segregation, microtubule binding and cell cycle. Immune infiltration analysis elucidated a negative correlation between CENPF expression and immune score. In conclusion, CENPF not only could be considered as a potential prognostic biomarker but also a potential malignant indicator of immune infiltration-related survival for LPS. The elevated expression of CENPF reveals an unfavorable prognostic outcome and worse immune score. Thus, therapeutically targeting CENPF combined with immunotherapy might be an attractive strategy for the treatment of LPS.

Shared energy storage systems (SESS) have been gradually developed and applied to distribution networks (DN). There are electrical connections between SESSs and multiple DN nodes; SESSs could significantly improve the power restoration potential and reduce the power interruption cost during fault periods. Currently, a major challenge exists in terms of how to consider both the efficiency of the operation and the reliability cost when formulating the SESS scheduling scheme. A SESS optimal scheduling method that considers the DN operation risk is proposed in this paper. First, a multi-objective day-ahead scheduling model for SESS is developed, where the user’s interruption cost is regarded as the reliability cost and it is the product of the occurrence probability of the expected accident and the loss of power outage. Then, an island partition model with SESS was established in order to accurately calculate the reliability cost. Via the maximum island partition and island optimal rectification, the SESS was carefully integrated into the power restoration system. Furthermore, in order to minimize the comprehensive operation cost, an improved genetic algorithm for the island partition was designed to solve the complex SESS optimal scheduling model. Finally, a case study on the improved PG&E 69 bus system was analyzed. Moreover, we found that the DN’s comprehensive operation cost decreased by 6.6% using the proposed method.

High-performance grinding has been converted from traditional manual grinding to robotic grinding over recent years. Accurate material removal is challenging for workpieces with complex profiles. Over recent years, digital processing of grinding has shown its great potential in the optimization of manufacturing processes and operational efficiency. Thus, quantification of the material removal process is an inevitable trend. This research establishes a three-dimensional model of the grinding workstation and designs the blade back arc grinding trajectory. A prediction model of the blade material removal depth (MRD) is established, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS). Experiments were carried out using the Taguchi method to investigate how certain elements might affect the outcomes. An Analysis of Variance (ANOVA) was used to study the effect of abrasive belt grinding characteristics on blade material removal. The mean absolute percent error (MAPE) of the established ANFIS model, after training and testing, was 3.976%, demonstrating superior performance to the reported findings, which range from 4.373% to 7.960%. ANFIS exhibited superior outcomes, when compared to other prediction models, such as random forest (RF), artificial neural network (ANN), and support vector regression (SVR). This work can provide some sound guidance for high-precision prediction of material removal amounts from surface grinding of steam turbine blades.

ScAlMgO4 (SAM) is a promising substrate material for group III-nitride semiconductors. SAM has a lower lattice mismatch with III-nitride materials compared to conventionally used sapphire (Al2O3) and silicon substrates. Bulk SAM substrate has the issues of high cost and lack of large area substrates. Utilizing solid-phase epitaxy to transform an amorphous SAM on a sapphire substrate into a crystalline form is a cost-efficient and scalable approach. Amorphous SAM layers were deposited on 0001-oriented Al2O3 by sputtering and crystallized by annealing at a temperature greater than 850 °C. Annealing under suboptimal annealing conditions results in a larger volume fraction of a competing spinel phase (MgAl2O4) exhibiting themselves as crystal facets on the subsequently grown InGaN layers during MOCVD growth. InGaN on SAM layers demonstrated both a higher intensity and emission redshift compared to the co-loaded InGaN on GaN on sapphire samples, providing a promising prospect for achieving efficient longer-wavelength emitters.

Background: Hemorrhagic transformation (HT) is a severe complication in patients with acute ischemic stroke (AIS). This study was performed to explore and validate the relation between bilirubin levels and spontaneous HT (sHT) and HT after mechanical thrombectomy (tHT). Methods: The study population consisted of 408 consecutive AIS patients with HT and age- and sex-matched patients without HT. All patients were divided into quartiles according to total bilirubin (TBIL) level. HT was classified as hemorrhagic infarction (HI) and parenchymal hematoma (PH) based on radiographic data. Results: In this study, the baseline TBIL levels were significantly higher in the HT than non-HT patients in both cohorts (p < 0.001). Furthermore, the severity of HT increased with increasing TBIL levels (p < 0.001) in sHT and tHT cohorts. The highest quartile of TBIL was associated with HT in sHT and tHT cohorts (sHT cohort: OR = 3.924 (2.051–7.505), p < 0.001; tHT cohort: OR = 3.557 (1.662–7.611), p = 0.006). Conclusions: Our results suggest that an increased TBIL is associated with a high risk of patients with sHT and tHT, and that TBIL is more suitable as a predictor for sHT than tHT. These findings may help to identify patients susceptible to different types and severity of HT.

UAV localization in denial environments is a hot research topic in the field of cross-view geo-localization. The previous methods tried to find the corresponding position directly in the satellite image through the UAV image, but they lacked the consideration of spatial information and multi-scale information. Based on the method of finding points with an image, we propose a novel architecture—a Weight-Adaptive Multi-Feature fusion network for UAV localization (WAMF-FPI). We treat this positioning as a low-level task and achieve more accurate localization by restoring the feature map to the resolution of the original satellite image. Then, in order to enhance the ability of the model to solve multi-scale problems, we propose a Weight-Adaptive Multi-Feature fusion module (WAMF), which introduces a weighting mechanism to fuse different features. Finally, since all positive samples are treated in the same way in the existing methods, which is very disadvantageous for accurate localization tasks, we introduce Hanning loss to allow the model to pay more attention to the central area of the target. Our model achieves competitive results on the UL14 dataset. When using RDS as the evaluation metric, the performance of the model improves from 57.22 to 65.33 compared to Finding Point with Image (FPI). In addition, we calculate the actual distance errors (meters) to evaluate the model performance, and the localization accuracy at the 20 m level improves from 57.67% to 69.73%, showing the powerful performance of the model. Although the model shows better performance, much remains to be done before it can be applied.

Abstract Optimal treatment of acute myeloid leukemia (AML) arising in elderly patients remains a challenge. FDA approval of Ivosidenib and Enasidenib, small molecule inhibitors of isocitrate dehydrogenase enzymes (IDH1 and 2) have opened new avenues of treatment. We present a 60-year-old woman with refractory AML, achieving complete response to the combination therapy of hypomethylating agent, Azacytidine with the IDH2 inhibitor, Enasidenib, and BCL2 inhibitor, Venetoclax. To our knowledge, this is the first case report of a patient with IDH2 mutated refractory AML achieving complete response to combination therapy with azacytidine, enasidenib and venetoclax.

Numerous studies have shown that plant shading can promote the quality of green tea. However, the association of shading with metabolic regulation in tea leaves and roots remains unelucidated. Here, the metabolic profiling of two tea cultivars (“Xiangfeicui” and “Jinxuan”) in response to shading and relighting periods during the summer season was performed using non-targeted metabolomics methods. The metabolic pathway analyses revealed that long-term shading remarkably inhibit the sugar metabolism such as glycolysis, galactose metabolism, and pentose phosphate pathway in the leaves and roots of “Xiangfeicui,” and “Jinxuan” were more sensitive to light recovery changes. The lipid metabolism in the leaves and roots of “Xiangfeicui” was promoted by short-term shading, while it was inhibited by long-term shading. In addition, the intensity of the flavonoid metabolites in the leaves and roots of “Jinxuan” were upregulated with a trend of rising first and then decreasing under shading, and five flavonoid synthesis genes showed the same trend (F3H, F3′5′H, DFR, ANS, and ANR). Simultaneously, the amino acids of the nitrogen metabolism in the leaves and roots of the two cultivars were significantly promoted by long-term shading, while the purine and caffeine metabolism was inhibited in the leaves of “Xiangfeicui.” Interestingly, CsGS1.1 and CsTSI, amino acid synthase genes was upregulated in the leaves and roots of two cultivars. These results indicated that shading could participate in carbon and nitrogen metabolic regulation of both leaf and root, and root metabolism could have a positive association with leaf metabolism to promote the shaded tea quality.

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic is having a dramatic impact on acute stroke care. Its effects may accompany stroke care for a long time. We compared the treatment, short-term and long-term functional outcomes of patients with AIS from 2019 to 2020. Our objective was to evaluate the effect of COVID-19 epidemic on mechanical thrombectomy (MT) in patients in our hospital.MethodsWe collected information on subjects treated with MT in 2019–2020, including age, sex, time from the onset to arterial sheath insertion, time from the onset to recanalization, the rate of lung infection and hemorrhagic transformation, modified Rankin scale (mRS), NHISS, and ASPECTS.ResultsThe number of patients with MT decreased significantly by 26.6% in 2020 (p = 0.025). The pretreatment ASPECTS score for 2020 was significantly higher than 2019 (p = 0.004). Besides, the patients were more likely to develop lung infection (65 vs. 54.1%, p = 0.042) and had a higher risk of hemorrhagic transformation (47.4% vs. 30.4%, p = 0.005) in 2019. The discharged mRS reflected the worse short-term functional prognosis of patients with MT in 2019 (66 vs. 44.9%, p = 0.046). In the subgroup analysis of bridging thrombolysis (BT), more patients with BT are expected to have a poor short-term functional prognosis in 2020, according to the discharged mRS (62.5 vs. 37.5%, p = 0.024). However, there was no difference in mRS at 180 days between the two groups (p = 0.094).ConclusionFor patients with MT, both short- and long-term functional outcomes were not significantly affected due to the mild condition of patients admitted to hospital in 2020. For patients with BT, the COVID-19 pandemic has prolonged the green channel time of stroke, leading to a poor short-term functional prognosis of patients with stroke in the pandemic period. There was no difference in the effectiveness of direct MT and BT during the COVID-19 pandemic.

Abstract Background Current evidence on the association of dietary ω-3 and ω-6 fatty acids intake with cognitive performance is inconsistent. Therefore, the aim is to explore the association of dietary ω-3 and ω-6 fatty acids intake with cognitive performance in the U.S. noninstitutionalized population of older adults. Methods We used data from the National Health and Nutrition Examination Survey (NHANES) 2011–2014. Intakes of ω-3 and ω-6 fatty acids were obtained through two 24-h dietary recalls and were adjusted by energy. Cognitive performance was evaluated by the Consortium to Establish a Registry for Alzheimer’s disease (CERAD) Word Learning sub-test, Animal Fluency test and Digit Symbol Substitution Test (DSST). For each cognitive test, people who scored lower than the lowest quartile in each age group were defined as having low cognitive performance. Binary logistic regression and restricted cubic spline models were applied to evaluate the association of dietary ω-3 and ω-6 fatty acids intake with cognitive performance. Results A total of 2496 participants aged 60 years or older were included. In the full-adjusted model, the odds ratios (ORs) with 95% confidence interval (CI) of CERAD test score, Animal Fluency test score and DSST test score were 0.58 (0.38–0.88), 0.68 (0.47–0.99) and 0.59 (0.37–0.92) for the highest versus lowest tertile of dietary ω-3 fatty acids intake, respectively; the ORs with 95% CI of CERAD test score, Animal Fluency test score and DSST test score were 0.48 (0.31–0.75), 0.60 (0.40–0.92) and 0.50 (0.34–0.75) for the highest versus lowest tertile of dietary ω-6 fatty acids intake, respectively. The association between ω-6: ω-3 ratio and cognitive performance was not statistically significant in three tests. In dose-response relationship analysis, L-shaped associations were apparent for ω-3 and ω-6 fatty acids intake with CERAD test score, Animal Fluency test score and DSST test score. Conclusions Dietary ω-3 and ω-6 fatty acids intake might be inversely associated with low cognitive performance.

Models based on deep learning are prone to misjudging the results when faced with adversarial examples. In this paper, we propose an MCTS-T algorithm for generating adversarial examples of cross-site scripting (XSS) attacks based on Monte Carlo tree search (MCTS) algorithm. The MCTS algorithm enables the generation model to provide a reward value that reflects the probability of generative examples bypassing the detector. To guarantee the antagonism and feasibility of the generative adversarial examples, the bypassing rules are restricted. The experimental results indicate that the missed detection rate of adversarial examples is significantly improved after the MCTS-T generation algorithm. Additionally, we construct a generative adversarial network (GAN) to optimize the detector and improve the detection rate when dealing with adversarial examples. After several epochs of adversarial training, the accuracy of detecting adversarial examples is significantly improved.

Composited nighttime light (NTL) data are widely used to evaluate the intensity of human activities and estimate urban dynamics. However, due to the effects of stray light, Visible Infrared Imaging Radiometer Suite (VIIRS) monthly composited data are vastly missing in middle-high latitude areas in summer, resulting in obvious application limitations. Interpolation methods for missing values based on the temporal continuity characteristics of pixels in monthly composite images could be a potential solution to address the limitations. In this paper, we employed least-squares line fitting (LSLF), least-squares quadratic polynomial fitting (LSQPF), least-squares cubic polynomial fitting (LSCPF), cubic spline interpolation (Spline), cubic Hermite interpolation (Hermite), cubic Bezier curve interpolation (Bezier), gray forecast model (GFM) and cubic exponential smoothing (Exponent) to simulate the missing values in VIIRS/DNB data. The rationality and accuracy of the simulation results was quantitatively evaluated. Then, we modeled and decomposed the time series to estimate the missing values of multiple months in NTL data. The results showed that 1)in comparison with the vcm data, the simulation results for LSLF were the closest to the vcm data. In the fitting experiment between the simulation results of these algorithms and vcm data, the correlation coefficient of LSLF was the highest in 4 of the 6 low-latitude cities, ranging from 0.896 to 0.976. 2) In comparison with the socioeconomic data regression, the simulation results of the LSLF, Bezier and Exponent methods showed greater correlation coefficients than vcmsl data. 3) The correlation coefficients between the six months image estimated by the time series decomposition method and the vcm data were all greater than 0.8. It can be inferred from the results that data interpolation methods based on temporal continuity characteristics between pixels in the same location could be potential practical approaches for the simulation of missing values in the vcm monthly composited data.

Co-delivery nanoparticles with characteristics of intracellular precision release drug have been generally accepted as an effective therapeutic strategy for eye diseases. In this study, we designed a new co-delivery system (miRNA/NP-BRZ) as a lasting therapeutic approach to prevent the neuro-destructive after the long-term treatment of glaucoma. Neuroprotective and intraocular pressure (IOP) response were assessed in in vivo and in vitro models of glaucoma. At the meaning time, we describe the preparation of miRNA/NP-BRZ, drug release characteristics, intraocular tracing, pharmacokinetic and pharmacodynamics study and toxicity test. We found that miRNA/NP-BRZ could remarkably decrease IOP and significantly prevent retinal ganglion cell (RGC) damages. The new formula of miRNA-124 encapsulated in PEG-PSA-BRZ nanoparticles exhibits high encapsulation efficiency (EE), drug-loading capacity (DC), and stable controlled-release efficacy (EC). Moreover, we also verified that the miRNA/NP-BRZ system is significantly neuroprotective and nontoxic as well as lowering IOP. This study shows our co-delivery drug system would have a wide potential on social and economic benefits for glaucoma.

Background. Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality and most ARDS patients require ventilatory support. Applying appropriate ventilation strategies based on patients’ individual situations has a direct impact upon patients’ outcome. The neutrophil-to-lymphocyte ratio (NLR) has been shown to predict the early requirement of invasive mechanical ventilation (IMV) in patients with coronavirus disease 2019 (COVID-19). Our study aimed to investigate the relationship between baseline NLR and IMV in ARDS. Methods. A retrospective study was performed on patients who were diagnosed with ARDS using the Berlin definition and admitted to the First Affiliated Hospital of Soochow University from 2017 to 2022. Clinical data within 24 h after the ARDS diagnosis were collected from the medical record system. Based on the ventilation strategies during hospitalization, patients were divided into three groups and their clinical characteristics were compared. Furthermore, logistic regression analysis was used to screen the independent risk factors for IMV. STROBE checklist was used for this manuscript. Results. 520 ARDS patients were included and the median NLR value in IMV group was significantly higher than that of other groups (P

A biomaterial-mediated immune response is a critical factor to determine the cell fate as well as the tissue-regenerative outcome. Although piezoelectric-membranes have attracted considerable interest in the field of guided bone regeneration thanks to their biomimetic electroactivity, the influence of their different surface-charge polarities on the immune-osteogenic microenvironment remains obscure. The present study aimed at investigating the interaction between piezoelectric poly (vinylidene fluoridetrifluoroethylene) [P (VDF-TrFE)] membranes with different surface polarities (negative or positive) and macrophage response, as well as their subsequent influence on osteogenesis from an immunomodulating perspective. Specifically, the morphology, wettability, crystal phase, piezoelectric performance, and surface potential of the synthetic P (VDF-TrFE) samples were systematically characterized. In addition, RAW 264.7 macrophages were seeded onto differently charged P (VDF-TrFE) surfaces, and the culture supernatants were used to supplement cultures of rat bone marrow mesenchymal stem cells (rBMSCs) on the corresponding P (VDF-TrFE) surfaces. Our results revealed that oppositely charged surfaces had different abilities in modulating the macrophage-immune-osteogenic microenvironment. Negatively charged P (VDF-TrFE), characterized by the highest macrophage elongation effect, induced a switch in the phenotype of macrophages from M0 (inactivated) to M2 (anti-inflammatory), thus promoting the osteogenic differentiation of rBMSCs by releasing anti-inflammatory cytokine IL-10. Interestingly, positively charged P (VDF-TrFE) possessed pro-inflammatory properties to induce an M1 (pro-inflammatory) macrophage-dominated reaction, without compromising the subsequent osteogenesis as expected. In conclusion, these findings highlighted the distinct modulatory effect of piezoelectric-P (VDF-TrFE) membranes on the macrophage phenotype, inflammatory reaction, and consequent immune-osteogenic microenvironment depending on their surface-charge polarity. This study provides significant insight into the design of effective immunoregulatory materials for the guided bone regeneration application.

Oral microecosystem is a very complicated ecosystem that is located in the mouth and comprises oral microbiome, diverse anatomic structures of oral cavity, saliva and interactions between oral microbiota and between oral microbiota and the host. More and more evidence from studies of epidemiology, microbiology and molecular biology is establishing a significant link between oral microecosystem and respiratory diseases. Microbiota settling down in oral microecosystem is known as the main source of lung microbiome and has been associated with the occurrence and development of respiratory diseases like pneumonia, chronic obstructive pulmonary disease, lung cancer, cystic fibrosis lung disease and asthma. In fact, it is not only indigenous oral microbes promote or directly cause respiratory infection and inflammation when inhaled into the lower respiratory tract, but also internal environment of oral microecosystem serves as a reservoir for opportunistic respiratory pathogens. Moreover, poor oral health and oral diseases caused by oral microecological dysbiosis (especially periodontal disease) are related with risk of multiple respiratory diseases. Here, we review the research status on the respiratory diseases related with oral microecosystem. Potential mechanisms on how respiratory pathogens colonize oral microecosystem and the role of indigenous oral microbes in pathogenesis of respiratory diseases are also summarized and analyzed. Given the importance of oral plaque control and oral health interventions in controlling or preventing respiratory infection and diseases, we also summarize the oral health management measures and attentions, not only for populations susceptible to respiratory infection like the elderly and hospitalized patients, but also for dentist or oral hygienists who undertake oral health care. In conclusion, the relationship between respiratory diseases and oral microecosystem has been established and supported by growing body of literature. However, etiological evidence on the role of oral microecosystem in the development of respiratory diseases is still insufficient. Further detailed studies focusing on specific mechanisms on how oral microecosystem participate in the pathogenesis of respiratory diseases could be helpful to prevent and treat respiratory diseases.

Hepatitis B virus-related acute liver failure (HBV-ALF) is a common type of liver failure, associated with high short-term mortality and morbidity rates. However, the immune landscape of HBV-ALF and its correlation with cell death are currently unknown. Based on 3 Gene Expression Omnibus data sets, infiltrated immune cells were quantified by single-sample gene set enrichment analysis method. The expression levels of immune genes and the abundance of immune cells in liver failure were compared with those in normal liver. The enrichment scores of cell death gene sets from Kyoto Encyclopedia of Genes and Genomes (KEGG) were calculated by gene set variation analysis method, and a protein-protein interaction (PPI) network was constructed using Cytoscape. Besides 21 differentially expressed immune genes, we identified 11 types of differentially infiltrated immune cells in HBV-ALF compared with normal liver. Enriched pathways of these immune genes mainly consisted of chemokine receptors, chemokine binding, interleukin-10 signaling, and TNFs bind their physiological receptors by Reactome pathway analysis. In addition, the enrichment scores of apoptosis and necroptosis pathway instead of autophagy and ferroptosis were increased in liver failure compared with normal liver. PPI network and gene cluster analysis of immune genes and apoptosis and necroptosis genes suggested that hub genes were mainly related to immune response and apoptosis. In summary, our study offers a conceptual framework to understand the immune landscape of HBV-ALF, which might help to improve prognosis.

A simplified calculation method is proposed for determining the peak dynamic windage yaw angle φ^ of electricity transmission line (TL) tower suspension insulator strings (SISs). According to the rigid-body rule, the geometric stiffness matrix in the calculation of the windage yaw angle φ of SISs is dominated by the average wind loads, while the fluctuating wind loads are the dominant factor in the elastic stiffness. With the average wind state of conductors as the initial calculation condition, the load-response-correlation (LRC) method can be used to determine the fluctuating windage yaw angle φd and the corresponding equivalent static wind loads (ESWLs). Then, the improved rigid straight rod model, which uses the actual length of conductors rather than the projected length, was used to determine the average windage yaw angle φ¯. Through the linear superposition of the horizontal increments of φ¯ and φ^d (the peak value of φd), the formulae to calculate the φ^ of SISs were derived. Additionally, the formulae for the dynamic wind load factor, βc, which is a key factor in designing wind loads for φ, were derived according to the principle of ESWLs, rather than being empirically determined by the Chinese code. Thus, the calculation model regarding the loads and response for the φ of SISs was established, and an actual TL was used to verify the established calculation model. Afterward, the influence of the different engineering design parameters on φ and its βc were analyzed. The parameter analyses show that the wind speed, span, and ground roughness influence the magnitudes of φ^ and βc, however, the height difference between the two suspension points of the conductors, the nominal height, and the sag-to-span ratio may be neglected in the approximate calculation. Our method offers a new solution to TL design when there are large deformations and small strains.

Seismic, core, drilling, logging, and thin-section data are considered to analyze the reservoir diversity in the east, middle, and west fan of the Liushagang Formation in the steep-slope zone of the Weixinan Sag, Beibuwan Basin. Three factors primarily affect the reservoir differences for steep-slope systems: (1) Sedimentary factors mostly control reservoir scales and characteristics and the drainage system and microfacies. Massive high-quality reservoirs have shallow burial depths. Channel development and sediment supply favor the formation of these reservoirs. The sedimentary microfacies suggest fan delta plain distributary channels. (2) Lithofacies factors primarily control reservoir types and evolution. The diagenesis of high-quality reservoirs is weak, and a weak compaction–cementation diagenetic facies and medium compaction–dissolution diagenetic facies were developed. (3) Sandstone thickness factors primarily control the oil-bearing properties of reservoirs. The average porosity and permeability of high-quality reservoirs are large, the critical sandstone thickness is small, the average sandstone thickness is large, and the oil-bearing capacity is high. Furthermore, the reservoir prediction models are summarized as fan delta and nearshore subaqueous fan models. The high-quality reservoir of the fan delta model is in the fan delta plain, and the lithology is medium–coarse sandstone. The organic acid + meteoric freshwater two-stage dissolution is developed, various dissolved pores are formed, and a Type I reservoir is developed. The high-quality reservoir of the nearshore subaqueous fan model is in the middle fan, and the lithology is primarily medium–fine sandstone. Only organic acid dissolution, dissolution pores, and Type I–II reservoirs are developed. Regarding reservoir differences and models, the high-quality reservoir of the steep-slope system is shallow and large-scale, and the reservoir is a fan delta plain distributary channel microfacies. Weak diagenetic evolution, good physical properties, thick sandstone, and good oil-bearing properties developed a Type I reservoir. The study of reservoir control factors of the northern steep-slope zone was undertaken in order to guide high-quality reservoir predictions. Further, it provides a reference for high-quality reservoir distribution and a prediction model for the steep-slope system.

Abstract: Therapy-related acute myeloid leukemia and myelodysplastic syndromes (t-AML/t-MDS) are secondary hematologic malignancies associated with poor prognosis, warranting insights into their predisposing conditions and cells of origin. We identified patients with myeloma who developed t-AML/t-MDS and analyzed their stem and progenitor cells collected years before the onset of secondary disease. We demonstrate that aberrant stem cells with high CD123 expression can be detected long before the onset of overt leukemia. Rigorous sorting, followed by targeted sequencing, resulted in ultradeep functional depth of sequencing and revealed preexisting mutant hematopoietic stem cell (HSC) clones, mainly harboring TP53 mutations, that became the dominant population at the time of leukemic presentation. Taken together, these data show that HSCs can act as reservoirs for leukemia-initiating cells many years before the onset of myeloid leukemia.

Summary: Phase separation of proteins regulates transcription. Here, we present a protocol to manipulate phase separation capacity of a protein. We use this protocol to disrupt phase separation by mutating residues at intrinsically disordered regions (IDRs). Further, we rescue the disabled phase separation by fusing an IDR known to drive phase separation. Phase separation promotes cell fate transitions, whereas disruption of phase attenuates the transitions. The major challenge is how to effectively predict mutation residues.For complete details on the use and execution of this protocol, please refer to Wang et al. (2021).

Abstract Background Blood pressure (BP) is an independent and important factor for chronic diseases such as cardiovascular diseases and diabetes. Methods We firstly conducted twin modeling analyses to explore the heritability of BP, including systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure (PP) and mean arterial pressure (MAP), and then performed genome‐wide association studies to explore the associated genomic loci, genes, and pathways. Results A total of 380 Chinese twin pairs were included. The AE model containing additive genetic parameter (A) and unique/non‐shared environmental parameter (E) was the best fit model, with A accounting for 53.7%, 50.1%, 48.1%, and 53.3% for SBP, DBP, PP and MAP, respectively. No SNP was found to reach the genome‐wide significance level (p

This paper presents a novel algorithm about the industrial robot contouring control based on the NURBS (non-uniform rational B-spline) curve. First, aiming at the error between the industrial robot’s actual trajectory and the desired trajectory, the contour error is proposed as the trajectory evaluation index, and the estimation algorithm of contour error based on the tangent approximation is proposed. Based on the tangent approximation algorithm, the estimation algorithm of contour error in the local task coordinate frame is proposed to realize the transformation from the Cartesian coordinate frame to the local task coordinate frame. Second, according to the configuration of the industrial robot, a modified cross-coupling control scheme based on the local task coordinate frame is designed. Finally, the Bernoulli’s lemniscate curves are constructed by NURBS curve and five-order polynomial curve, respectively, and they are symmetrical. The contrast experiment is designed using the two types of constructed Bernoulli’s lemniscate curves as the incentive trajectory. Through the analysis and comparison between the obtained uniaxial tracking error and the contour error curve of the two incentive trajectories, it is concluded that the incentive trajectory constructed by the NURBS curve has better contour control performance than that constructed by the five-order polynomial curve. The results drawn from this paper lay a certain foundation for the future high-precision contouring control of industrial robots.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by intra-tumoral heterogeneity, and patients are always diagnosed after metastasis. Thus, finding out how to effectively estimate metastatic risk underlying PDAC is necessary. In this study, we proposed scMetR to evaluate the metastatic risk of tumor cells based on single-cell RNA sequencing (scRNA-seq) data. First, we identified diverse cell types, including tumor cells and other cell types. Next, we grouped tumor cells into three sub-populations according to scMetR score, including metastasis-featuring tumor cells (MFTC), transitional metastatic tumor cells (TransMTC), and conventional tumor cells (ConvTC). We identified metastatic signature genes (MSGs) through comparing MFTC and ConvTC. Functional enrichment analysis showed that up-regulated MSGs were enriched in multiple metastasis-associated pathways. We also found that patients with high expression of up-regulated MSGs had worse prognosis. Spatial mapping of MFTC showed that they are preferentially located in the cancer and duct epithelium region, which was enriched with the ductal cells’ associated inflammation. Further, we inferred cell–cell interactions, and observed that interactions of the ADGRE5 signaling pathway, which is associated with metastasis, were increased in MFTC compared to other tumor sub-populations. Finally, we predicted 12 candidate drugs that had the potential to reverse expression of MSGs. Taken together, we have proposed scMetR to estimate metastatic risk in PDAC patients at single-cell resolution which might facilitate the dissection of tumor heterogeneity.

Salicylic acid (SA) is a natural inducer of disease resistance in fruit, but its application in the food industry is limited due to low water solubility. Here, SA was encapsulated in β-cyclodextrin (β-CD) via the host–guest inclusion complexation method, and the efficacy of SA microcapsules (SAM) against blue mold caused by Penicillium expansum in postharvest apple fruit was elucidated. It was observed that SAM was the most effective in inhibiting the mycelial growth of P. expansum in vitro. SAM was also superior to SA for control of blue mold under in vivo conditions. Enzyme activity analysis revealed that both SA and SAM enhanced the activities of superoxide dismutase (SOD) and phenylalanine ammonia lyase (PAL) in apple fruit, whereas SAM led to higher SOD activities than SA. Total phenolic contents in the SAM group were higher than those in the SA group at the early stage of storage. SAM also improved fruit quality by retarding firmness loss and maintaining higher total soluble solids (TSS) contents. These findings indicate that microcapsules can serve as a promising formulation to load SA for increasing P. expansum inhibition activity and improving quality attributes in apple fruit.

Robotic systems have emerged in dental implant surgery due to their accuracy. Autonomous robotic surgery may offer unprecedented advantages over conventional alternatives. This clinical protocol was used to show the feasibility of autonomous robotic surgery for immediately loaded implant-supported full-arch prostheses in the maxilla. This case report demonstrated the surgical protocol and outcomes in detail, highlighting the pros and cons of the autonomous robotic system. Within the limitations of this study, autonomous robotic surgery could be a feasible alternative to computer-assisted guided implant surgery.

Camellia sinensis cv. ‘Yanlingyinbiancha’ is a leaf-variegated mutant with stable genetic traits. The current study aimed to reveal the differences between its albino and green tissues, and the molecular mechanism underlying the variegation. Anatomic analysis showed the chloroplasts of albino tissues to have no intact lamellar structure. Photosynthetic pigment in albino tissues was significantly lower than that in green tissues, whereas all catechin components were more abundant in the former. Transcriptome analysis revealed most differentially expressed genes involved in the biosynthesis of photosynthetic pigment, photosynthesis, and energy metabolism to be downregulated in albino tissues while most of those participating in flavonoid metabolism were upregulated. In addition, it was found cryptochrome 1 (CRY1) and phytochrome B (PHYB) genes that encode blue and red light photoreceptors to be downregulated. These photoreceptors mediate chloroplast protein gene expression, chloroplast protein import and photosynthetic pigment biosynthesis. Simultaneously, SUS gene, which was upregulated in albino tissues, encodes sucrose synthase considered a biochemical marker for sink strength. Collectively, we arrived to the following conclusions: (1) repression of the biosynthesis of photosynthetic pigment causes albinism; (2) destruction of photoreceptors in albino tissues suppresses photomorphogenesis, leading to abnormal chloroplast development; (3) albino tissues receive sucrose from the green tissues and decompose their own storage substances to obtain the energy needed for survival; and (4) UV-B signal and brassinosteroids promote flavonoid biosynthesis.

OBJECTIVES:. The aim was to evaluate the effect of dihydropyridine calcium channel blocker on the prognosis for moderate-severe pulmonary acute respiratory distress syndrome in hypertension patients. DESIGN:. A retrospective, observational, multicenter cohort study. SETTING:. A total of 307 patients without propensity score matching and 186 adult inpatients with propensity score matching diagnosed with hypertension and moderate-severe pulmonary acute respiratory distress syndrome in five teaching hospitals in Jiangsu province, China, from December 2015 to December 2020 were enrolled. PATIENTS:. A total of 307 patients without propensity score matching and 186 patients with propensity score matching diagnosed with hypertension and moderate-severe pulmonary acute respiratory distress syndrome were included in the final analysis. INTERVENTIONS:. None. MEASUREMENTS AND MAIN RESULTS:. Demographic characteristics and clinical characteristics were recorded. The propensity score matching method was used to eliminate the difference between group with dihydropyridine calcium channel blocker and group without dihydropyridine calcium channel blocker. The primary outcome was in-hospital mortality. We used univariate and multivariate regression analyses for both patients with or without propensity score matching to assess the effect of these variables on mortality. In the subset of 186 patients with propensity score matching, in-hospital mortality was 53.2%. Inpatient mortality was significantly higher in patients treated with dihydropyridine calcium channel blocker than in those not treated with dihydropyridine calcium channel blocker of patients without propensity score matching (65.4% vs 40.4%; p < 0.01). Multivariate analysis for patients without propensity score matching showed that dihydropyridine calcium channel blocker (hazard ratio, 1.954; 95% CI, 1.415–2.699), lactate dehydrogenase greater than or equal to 600 U/L (hazard ratio, 3.809; 95% CI, 2.106–4.531), and lactate greater than or equal to 2 mmol/L (hazard ratio, 1.454; 95% CI, 1.041–2.029) were independently associated with in-hospital mortality. Based on univariate analysis for patients with propensity score matching, dihydropyridine calcium channel blocker (hazard ratio, 2.021; 95% CI, 1.333–3.064), lactate dehydrogenase greater than or equal to 600 U/L (hazard ratio, 4.379; 95% CI, 2.642–7.257), and lactate greater than or equal to 2 mmol/L (hazard ratio, 2.461; 95% CI, 1.534–3.951) were independently associated with in-hospital mortality. In contrast, patients not treated with dihydropyridine calcium channel blocker had a significant survival advantage over those treated with dihydropyridine calcium channel blocker in both patients without or with propensity score matching (p < 0.001; p = 0.001 by Kaplan-Meier analysis). CONCLUSIONS:. Dihydropyridine calcium channel blocker, lactate dehydrogenase greater than or equal to 600 U/L, and lactate greater than or equal to 2 mmol/L at admission were independent risk factors for patients with hypertension and moderate-severe pulmonary acute respiratory distress syndrome.

Mulberry leaf polysaccharide (MLP) possess many biological characteristics, such as immunomodulatory and antioxidant properties, but whether MLP can impact the distribution and characteristics of the gut microbiota is not yet clear. In this study, the effects of MLP on diversity- and immune-related factors and short-chain fatty acids (SCFAs) of the gut microbiota in mice were investigated. The results showed that MLP could restore the indexes of the thymus and spleen, the damaged intestinal barrier and levels of inflammatory cytokines in cyclophosphamide (CTX)-treated mice, and alleviate oxidative damage to the liver. Additionally, MLP were associated with a relatively higher abundance of Bacteroidetes but lower levels of Firmicutes, Butyricimonas and Eubacterium in CTX-treated mice. Moreover, MLP restored the levels of acetic acid, propionic acid, and n-butyric acid reduced by CTX. These results indicated that MLP, as a special ingredient, might regulate the immune response by altering the spatial structure of the gut microbiota and the production of SCFAs.

In this study, we evaluated the protective effects and potential mechanisms of acidifiers on intestinal epithelial cells exposure to oxidative stress (OS). IPEC-J2 cells were first pretreated with 5 × 10−5 acidifiers for 4 h before being exposed to the optimal dose of diquat to induce oxidative stress. The results showed that acidifiers attenuated diquat-induced oxidative stress, which manifests as the improvement of antioxidant capacity and the reduction in reactive oxygen species (ROS) accumulation. The acidifier treatment decreased cell permeability and enhanced intestinal epithelial barrier function through enhancing the expression of claudin-1 and occludin in diquat-induced cells. Moreover, acidifier treatment attenuated diquat-induced inflammatory responses, which was confirmed by the decreased secretion and gene expression of pro-inflammatory (TNF-α, IL-8) and upregulated anti-inflammatory factors (IL-10). In addition, acidifiers significantly reduced the diquat-induced gene and protein expression levels of COX-2, NF-κB, I-κB-β, ERK1/2, and JNK2, while they increased I-κB-α expression in IPEC-J2 cells. Furthermore, we discovered that acidifiers promoted epithelial cell proliferation (increased expression of PCNA and CCND1) and inhibited apoptosis (decreased expression of BAX, increased expression of BCL-2). Taken together, these results suggest that acidifiers are potent antioxidants that attenuate diquat-induced inflammation, apoptosis, and maintain cellular barrier integrity by regulating the NF-κB/MAPK/COX-2 signaling pathways.

The linear curve distribution of the beam and the asymmetrical layout of the stay cables may have beneficial or adverse influences on cable-stayed bridges. Sectional model wind tunnel tests and numerical simulations were used to analyze the influence of these two factors on the wind-induced vibration characteristics of a curved beam unilateral stayed bridges (CBUSB) and the interaction between its stay cables and curved beams. According to the basic similarity law, the sectional models of a CBUSB example were designed and manufactured. The aerodynamic force and wind-induced vibration of the models were measured in an atmospheric boundary wind tunnel laboratory to obtain the aerodynamic coefficient and displacement, respectively. Based on the wind tunnel test results, the verified finite element model was used to determine the displacement, acceleration, and cable tension of the CBUSB excited by the buffeting force under 5 curvature cases and 4 cable layout cases. Then, band-pass filter technology and fast Fourier transform technology were used to analyze the influence of these two parameters on the wind-induced vibration characteristics of the CBUSB. Results show that the CBUSB had good aerodynamic stability in the wind tunnel at low and high wind speeds. With increasing curvature, the high-order modal vibration and modal coupling vibration of the CBUSB may be generated. The frequency, the proportion of wind-induced vibration response components, and the distribution characteristics of spectrum energy of CBUSB will be affected by 4 cable layout schemes. Cables arranged on both sides of the bridge and near the center of curvature can improve pedestrian comfort and reduce wind-induced vibration, respectively. Affected by the interaction between cable and bridge, the cable and bridge transmit their own vibration to each other, both of which contain the response components of each other.

Water area and waterweed coverage are the key environmental factors for ecological breeding of Eriocheir sinensis in ponds. In order to explore the effects of above two factors on the growth of E. sinensis, three groups of experiments were set up: low coverage small area (C1S1), high coverage small area (C2S1), and high coverage large area (C2S2), and water environmental factors and the growth of E. sinensis were monitored. The results showed that the dissolved oxygen of ponds with different waterweed coverage was significantly different (p < 0.05), and the phosphate in ponds changed significantly from July to October (p < 0.05). The correlation analysis showed that NH3-N and pH were significantly positively correlated (p < 0.05). At the same time, there was a significant negative correlation between NH3-N and DO, H3PO4 and pH (p < 0.05). Further analysis of the relationship between surface area, waterweed coverage and environmental factors revealed that the surface area and waterweed coverage were closely related to NH3-N, H3PO4 and DO. From July to October, the differences in morphology and weight of E. sinensis in different ponds became more and more significant. In terms of growth rate, C1S1 with a small area and low coverage had a downward trend, while C2S1 and C2S2 were the opposite. In the final stage of the experiment, C2S2 had the highest yield (0.1311 kg/m2), and C1S1 had the lowest yield (0.0600 kg/m2). Then, the ponds with high waterweed coverage and large area can bring better benefits.

Background and Purpose: The results regarding the independent association between homocysteine (Hcy) levels and post-stroke cognitive impairment (PSCI) were inconsistent. The effect of age on this association has yet to be explored. This study aims to determine the relationship between Hcy levels, age, and cognitive impairment in a post-stroke population.Methods: A total of 592 patients with acute ischemic stroke (AIS) completed follow-up. Serum Hcy levels were measured enzymatically by spectrophotometry within 24 h of admission. Cognitive function was evaluated by the Mini-Mental State Examination (MMSE) 1 month after stroke, and the scores ≤ 24 were considered as cognitive impairment. Our study was dichotomized into two groups by a cut-off of 65 years. Multivariate logistic regression models were used to determine the association between baseline Hcy levels and cognitive impairment.Results: According to the MMSE score, 317 (53.5%) patients had cognitive impairment. Patients with higher levels of Hcy were more prone to have cognitive impairment 1 month after stroke than patients with lower levels of Hcy (p < 0.001). The optimal cut-off points of Hcy level (μmol/L) were (T1) ≤ 8, (T2) 8–12, and (T3) ≥ 12. After adjusting for confounding factors, the multivariate regression analysis showed that the third Hcy tertile was independently associated with cognitive impairment [odds ratio (OR) = 2.057, 95% confidence interval (CI) = 1.133–3.735, p = 0.018). A stronger association [T2 (OR = 2.266, 95% CI = 1.042–4.926, p = 0.039); T3 (OR =3.583, 95% CI = 1.456–8.818, p = 0.005)] was found in the younger group. However, the independent association was not confirmed in the older group.Conclusions: Elevated Hcy levels in the acute phase of ischemic stroke were independently associated with cognitive impairment in a post-stroke population. Furthermore, the association was age-dependent and more meaningful in a younger population aged below 65. So, Hcy levels in patients with stroke should be well-monitored, especially in younger patients.

Finite-element analysis (FEA) is one of the most significant tools in the designing and analyzing of electrical machines, which mainly includes the transient-magnetic (TM), magnet-static (MS) and time-harmonic (TH) solutions. The transient-magnetic (TM) solution in FEA is capable of considering both the harmonic effects and eddy-current effects accurately, which makes it suitable for the induction machine (IM) simulation. However, the drawback of the TM FEA for the IM modelling is that it takes some time before reaching the steady state because of the longer numerical transient, which is affected by the inherent electromagnetic time constants of the IM directly. In this paper, a new approach is proposed to reduce the duration of the numerical transient of the IM in the time-stepping FEA so that the steady state can be achieved in a short time. The proposed approach is capable of creating an initial condition close to the final steady state for the simulation by eliminating or reducing the stator and rotor electromagnetic time constants separately. The stator electromagnetic time constant is eliminated by an initial current excitation (obtained by the TH solution or the analytical method) and the rotor electromagnetic time constant is reduced by a locked rotor model at the beginning of the simulation. Then the initial current excitation is switched to a voltage excitation and the locked rotor is turned to the rotating state at proper time. Finally, the proposed approach is tested and proved efficient to reduce the transients by two typical cases (a solid-rotor IM and a squirrel-cage IM) with 2D FEA.

Accurate detection of network-based attacks is crucial to prevent security breaches of information systems. The recent application of deep learning approaches for network intrusion detection has shown promising. However, the challenges remain on how to deal with imbalance data and small samples as well as reducing false alarm rate (FAR). To address these issues, this work has proposed a multiple-layer representation learning model for accurate end-to-end network intrusion detection by combining deep convolutional neural networks (CNN) with gcForest. The contributions of this work lie in 1) a new data encoding scheme based on P-Zigzag to encode network traffic data into two-dimensional gray-scale images for representation learning without loss of original information; 2) The combination of gcForest and CNN allows accurate detection on imbalanced data and small scale data with fewer hyperparamters comparing to most existing deep learning models, which increase computational efficiency. The proposed approach is based on a multiple-layer approach consisting of a coarse layer and a fine layer, in which the coarse layer with the improved CNN model (GoogLeNetNP) focuses on identification of N abnormal classes and a normal class. While in the fine layer, an improved model based on gcForest (caXGBoost) further classifies the abnormal classes into N-1 subclasses. This ensures fine-grained detection of various attacks. The proposed framework has been compared with the existing deep learning models using three real datasets (a new dataset NBC, a combination of UNSW-NB15 and CICIDS2017 consisting of 101 classes). The experimental results show that our proposed method outperforms other single deep learning methods (i.e., AlexNet, VGG19, GoogleNet, InceptionV3, ResNet18) in terms of accuracy, detection rate, and FAR, which demonstrates its effectiveness in detecting fine-grained attacks and handling imbalanced datasets with high-precision and low FAR.

The energy consumption of a vehicle is closely related to the resistance it receives, and it is of great significance to study the drag reduction of a vehicle to promote energy conservation and emissions reductions. Boundary layer control drag reduction is mainly achieved by controlling the coherent structure in turbulence and reducing its burst intensity and frequency. It can be divided into an active control drag reduction and passive control drag reduction. In passive drag reduction, the advantages of the surface groove drag reduction are relatively obvious. In this paper, the large eddy simulation method is used to study the boundary layer flow with triangular groove and rectangular groove plates along the flow direction under subsonic flow, and to explore the influence of a surface micro-groove structure on the boundary layer flow. The simulation results show that the fluid inside the groove can be blocked by the triangular groove which can keep the low-velocity fluid at the bottom of the groove, and that it can increase the thickness of the viscous bottom layer as well as reduce the velocity gradient at the wall. The spanwise stress component of the Reynolds stress in the triangular groove boundary layer and the burst of turbulence on the wall are inhibited, and the spanwise flow in the boundary layer is blocked. In the subsonic range, about 10% shear force can be reduced because there are secondary vortices induced by the upper flow vortices at the top of the groove wall, and these secondary vortices can restrain the rising of the low-speed strip in the groove and reduce the burst of turbulence. The rectangular groove creates a weak blocking effect on the fluid inside the groove, which can only inhibit spanwise pulsation under subsonic speed. The wall shear stress cannot be reduced when the flow velocity is low, and it even increases.

In the last few years, autonomous ships have attracted increasing attention in the maritime industry. Autonomous ships with an autonomous collision avoidance capability are the development trend for future ships. In this study, a ship manoeuvring process deduction-based dynamic adaptive autonomous collision avoidance decision support method for autonomous ships is presented. Firstly, the dynamic motion parameters of the own ship relative to the target ship are calculated by using the dynamic mathematical model. Then the fuzzy set theory is adopted to construct collision risk models, which combine the spatial collision risk index (SCRI) and time collision risk index (TCRI) in different encountered situations. After that, the ship movement model and fuzzy adaptive PID method are used to derive the ships’ manoeuvre motion process. On this basis, the feasible avoidance range and the optimal steering angle for ship collision avoidance are calculated by deducting the manoeuvring process and the modified velocity obstacle (VO) method. Moreover, to address the issue of resuming sailing after the ship collision avoidance is completed, the Line of Sight (LOS) guidance system is adopted to resume normal navigation for the own ship in this study. Finally, the dynamic adaptive autonomous collision avoidance model is developed by combining the ship movement model, the fuzzy adaptive PID control model, the modified VO method and the resume-sailing model. The results of the simulation show that the proposed methodology can effectively avoid collisions between the own ship and the moving TSs for situations involving two or multiple ships, and the own ship can resume its original route after collision avoidance is completed. Additionally, it is also proved that this method can be applied to complex situations with various encountered ships, and it exhibits excellent adaptability and effectiveness when encountering multiple objects and complex situations.

High-purity magnesium (Mg) is a promising biodegradable metal for oral and maxillofacial implants. Appropriate surface roughness plays a critical role in the degradation behavior and the related cellular processes of biodegradable Mg-based metals. Nevertheless, the most optimized surface roughness has been questionable, especially for Mg-based oral and maxillofacial implants. Three representative scales of surface roughness were investigated in this study, including smooth (Sa < 0.5 µm), moderately rough (Sa between 1.0–2.0 µm), and rough (Sa > 2.0 µm). The results indicated that the degradation rate of the Mg specimen in the cell culture medium was significantly accelerated with increased surface roughness. Furthermore, an extract test revealed that Mg with different roughness did not induce an evident cytotoxic effect. Nonetheless, the smooth Mg surface had an adversely affected cell attachment. Therefore, the high-purity Mg with a moderately rough surface exhibited the most optimized balance between biodegradability and overall cytocompatibility.

The quality of the veneer directly affects the quality and grade of a blockboard made of veneer. To improve the quality and utilization of a defective veneer, a novel deep generative model-based method is proposed, which can generate higher-quality inpainting results. A two-phase network is proposed to stabilize the network training process. Then, region normalization is introduced to solve the inconsistency problem between the mean and standard deviation, improve the convergence speed of the model, and prevent the model gradient from exploding. Finally, a hybrid dilated convolution module is proposed to reconstruct the missing areas of the panels, which alleviates the gridding problem by changing the dilation rate. Experiments on our dataset prove the effectiveness of the improved approach in image inpainting tasks. The results show that the PSNR of the improved method reaches 33.11 and the SSIM reaches 0.93, which are superior to other methods.

Floating offshore wind turbines (FOWTs) still face many challenges on how to better predict the dynamic responses. Artificial intelligence (AI) brings a new solution to overcome these challenges with intelligent strategies. A new AI technology-based method, named SADA, is proposed in this paper for the prediction of dynamic responses of FOWTs. Firstly, the methodology of SADA is introduced with the selection of Key Disciplinary Parameters (KDPs). The AI module in SADA was built in a coupled aero-hydro-servo-elastic in-house program DARwind and the policy decision is provided by the machine learning algorithms deep deterministic policy gradient (DDPG). Secondly, a set of basin experimental results of a Hywind Spar-type FOWT were employed to train the AI module. SADA weights KDPs by DDPG algorithms' actor network and changes their values according to the training feedback of 6DOF motions of Hywind platform through comparing the DARwind simulation results and that of experimental data. Many other dynamic responses that cannot be measured in basin experiment could be predicted in higher accuracy with this intelligent DARwind. Finally, the case study of SADA method was conducted and the results demonstrated that the mean values of the platform's motions can be predicted by AI-based DARwind with higher accuracy, for example the maximum error of surge motion is reduced by 21%. This proposed SADA method takes advantage of numerical-experimental method and the machine learning method, which brings a new and promising solution for overcoming the handicap impeding direct use of traditional basin experimental technology in FOWTs design.

Aconitine (AC) is the primary bioactive and secondary metabolite alkaloidin of Aconitum species which is accounted for more than 60% of the total diester-diterpenoid alkaloids in Aconite. To evaluate the analgesic effects of AC, 4 different pain models including hot plate assay, acetic acid writhing assay, formalin and CFA induced pain models were adopted in this study. In hot plate experiment, AC treatment at concentration of 0.3 mg/kg and 0.9 mg/kg improved the pain thresholds of mice similar to the positive drug aspirin at the concentration of 200 mg/kg (17.12% and 20.27% VS 19.21%). In acetic acid writhing experiment, AC significantly reduced the number of mice writhing events caused by acetic acid, and the inhibition rates were 68% and 76%. These results demonstrated that AC treatment revealed significant analgesic effects in both acute thermal stimulus pain model and chemically-induced visceral pain model. The biphasic nociceptive responses induced by formalin were significantly inhibited after AC treatment for 1h or 2h. The inhibition rates were 33.23% and 20.25% of AC treatment for 1h at 0.3 mg/kg and 0.9 mg/kg in phase I. In phase II, the inhibition rates of AC and aspirin were 36.08%, 32.48% and 48.82% respectively, which means AC showed similar analgesic effect to non-steroidal anti-inflammatory compounds. In the chronic CFA-induced nociception model, AC treatment also improved mice pain threshold to 131.33% at 0.3 mg/kg, which was similar to aspirin group (152.03%). Above all, our results verified that AC had obviously analgesic effects in different mice pain models.

Proper postharvest storage preserves horticultural products, including tea, until they can be processed. However, few studies have focused on the physiology of ripening and senescence during postharvest storage, which affects the flavor and quality of tea. In this study, physiological and biochemical indexes of the leaves of tea cultivar ‘Yinghong 9′ preserved at a low temperature and high relative humidity (15–18 °C and 85–95%, PTL) were compared to those of leaves stored at ambient conditions (24 ± 2 °C and relative humidity of 65% ± 5%, UTL). Water content, chromatism, chlorophyll fluorescence, and key metabolites (caffeine, theanine, and catechins) were analyzed over a period of 24 h, and volatilized compounds were determined after 24 h. In addition, the expression of key biosynthesis genes for catechin, caffeine, theanine, and terpene were quantified. The results showed that water content, chromatism, and chlorophyll fluorescence of preserved leaves were more similar to fresh tea leaves than unpreserved tea leaves. After 24 h, the content of aroma volatiles and caffeine significantly increased, while theanine decreased in both groups. Multiple catechin monomers showed distinct changes within 24 h, and EGCG was significantly higher in preserved tea. The expression levels of CsFAS and CsTSI were consistent with the content of farnesene and theanine, respectively, but TCS1 and TCS2 expression did not correlate with caffeine content. Principal component analysis considered results from multiple indexes and suggested that the freshness of PTL was superior to that of UTL. Taken together, preservation conditions in postharvest storage caused a series of physiological and metabolic variations of tea leaves, which were different from those of unpreserved tea leaves. Comprehensive evaluation showed that the preservation conditions used in this study were effective at maintaining the freshness of tea leaves for 2–6 h. This study illustrates the metabolic changes that occur in postharvest tea leaves, which will provide a foundation for improvements to postharvest practices for tea leaves.

The impact of drought on terrestrial ecosystem Gross Primary Productivity (GPP) is strong and widespread; therefore, it is important to study the response of terrestrial ecosystem GPP to drought. In this paper, we compared the correlations of Sun-induced Chlorophyll fluorescence (SIF), Enhanced Vegetation Index (EVI), and Normalized Differential Vegetation Index (NDVI) with the drought index sc_PDSI, estimated GPP in Yunnan Province, China, based on SIFTOTAL data (SIF data with canopy effects eliminated), and analyzed the response characteristics of GPP to drought for one mega-drought event (2009–2011) in combination with the sc_PDSI drought index. The results show that SIF is more sensitive to drought than the NDVI and EVI; the correlation between the GPP estimated based on SIF data (GPPSIF) and the actual observed flux values (R2 = 0.83) is better than GPPGLASS and GPPLUE, and the RMSE is also lower than those two products. This drought has a serious impact on GPP, and the monthly average values of the effect of drought on GPP (GPPd) in Yunnan Province in 2009, 2010, and 2011 are −11.37 gC·m−2·month−1, −23.48 gC·m−2·month−1 and −17.92 gC·m−2·month−1, which are 8.6%, 17.48% and 13.85% of the monthly average in a normal year, respectively. The spatial variability of GPP response to drought is significant, which is mainly determined by the degree, and duration of the drought, the vegetation type, the topography, and anthropogenic factors. In conclusion, GPPSIF quickly and accurately reflects the process of this drought, and this study helps to elucidate the response of GPP to drought conditions and provides more scientific information for drought prediction and ecosystem management.

As one of the most promising fast energy storage devices, supercapacitor has been attracting intense attention for many emerging applications. However, how to enhance the electrochemical performance of electrode materials is still the main issue among various researches. In this paper, hierarchical porous carbons derived from Eleocharis dulcis has been prepared by chemical activation process with the aid of KOH at elevated temperature. Results show that the N, P co-doped porous carbon exhibits excellent electrochemical performance, it owns a specific capacitance of 340.2 F/g at 1 A/g, and obtains outstanding cycling stability of 96.9% of capacitance retention at 10 A/g after 5,000 cycles in a three-electrode system. Moreover, in the two-electrode system, the product still maintains a high specific capacitance of 227.2 F/g at 1 A/g, and achieves good electrochemical cycle stability (94.2% of capacitance retention at 10 A/g after 10,000 cycles); besides, its power/energy density are 3694.084 and 26.289 Wh/kg, respectively. Therefore, the combination of facile synthesis strategy and excellent electrochemical performance makes Eleocharis dulcis-based porous carbon as a promising electrode material for supercapacitor.

BackgroundCoronavirus disease 2019 (COVID-19) has spread to the world. Whether there is an association between lifestyle behaviors and the acquisition of COVID-19 remains unclear.MethodsIn this case-control study, we recruited 105 patients with SARS-CoV-2 infection as a case group from the Wuhan Tongji Hospital (Wuhan, China). For each case two control subjects were recruited. Participants were randomly selected from communities in Wuhan and matched for sex, age (± 2yrs), and pre-existing comorbidities (hypertension and diabetes).ResultsA total of 105 patients diagnosed with COVID-19 and 210 controls were included. Compared with control group, the case group had higher proportions of lack of sleep (30.5% vs. 14.8%, P = 0.001) and increased physical activities (56.2% vs. 32.9%, P < 0.001). And patients in the case group were more likely to have alopecia (28.6% vs. 10.0%, P < 0.001) than people from the control group. Overall, we found that lack of sleep [adjusted odds ratio (OR) 1.56, 95% confidence interval (CI) 1.03-2.39)], physical activities (≥ 5 times a week) (adjusted OR 2.05, 95%CI 1.39-3.02) and alopecia (adjusted OR 1.73, 95%CI 1.13-2.66) were independent risk factors for COVID-19 infection. Conversely, low-dose alcohol intake (ConclusionsIndividual lifestyle behaviors and health status can affect the occurrence of COVID-19.

Scaffold materials, neurotrophic factors, and seed cells are three elements of neural tissue engineering. As well-known self-assembling peptide-based hydrogels, RADA16-I and modified peptides are attractive matrices for neural tissue engineering. In addition to its neuroprotective effects, cerebral dopamine neurotrophic factor (CDNF) has been reported to promote the proliferation, migration, and differentiation of neural stem cells (NSCs). However, the role of RADA16-I combined with CDNF on NSCs remains unknown. First, the effect of RADA16-I hydrogel and CDNF on the proliferation and differentiation of cultured NSCs was investigated. Next, RADA16-I hydrogel and CDNF were microinjected into the lateral ventricle (LV) of middle cerebral artery occlusion (MCAO) rats to activate endogenous NSCs. CDNF promoted the proliferation of NSCs, while RADA16-I induced the neural differentiation of NSCs in vitro. Importantly, both RADA16-I and CDNF promoted the proliferation, migration, and differentiation of endogenous NSCs by activating the ERK1/2 and STAT3 pathways, and CDNF exerted an obvious neuroprotective effect on brain ischemia-reperfusion injury. These findings provide new information regarding the application of the scaffold material RADA16-I hydrogel and the neurotrophic factor CDNF in neural tissue engineering and suggest that RADA16-I hydrogel and CDNF microinjection may represent a novel therapeutic strategy for the treatment of stroke.

Zinc (Zn) and its alloys have been regarded as promising biodegradable metals. The standardized cytotoxicity evaluation is a mandatory step to screen the biocompatibility of novel Zn and its alloys. Nevertheless, the suitability of the tetrazolium-based assay in the direct contact test for some metallic biomaterials (i.e., magnesium and manganese) is questionable. In this study, our results demonstrate an obvious inconsistency between qualitative observation via fluorescence staining and quantitative assessment using water-soluble tetrazolium salt (CCK-8). Subsequent experiments revealed that Zn and pre-treated Zn can directly convert tetrazolium salts to formazan, falsifying the cytotoxicity results. Therefore, we conclude that the CCK-8 assay is not suitable for evaluating the cytotoxicity of biodegradable Zn-based metals in the direct contact test.

As a natural extension of the fuzzy variable, a bifuzzy variable is defined as a mapping from a credibility space to the collection of fuzzy variables, which is an appropriate tool to model the two-fold fuzzy phenomena. In order to enrich its theoretical foundation, this paper explores some important measures for regular bifuzzy variables, the most commonly used type of bifuzzy variables. Firstly, we introduce the regular bifuzzy variables’ mean chance measure and some properties, including self-duality and its calculation formulas. Furthermore, we also investigate the mean chance distribution for strictly monotone functions of regular bifuzzy variables based on the proposed operational law. Finally, we present the expected value operator as well as equivalent analytical formulas of the expected value of regular bifuzzy variables and their strictly monotone functions.