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Social network is the mainstream medium of current information dissemination, and it is particularly important to accurately predict its propagation law. In this paper, we introduce a social network propagation model integrating multiple linear regression and infectious disease model. Firstly, we proposed the features that affect social network communication from three dimensions. Then, we predicted the node influence via multiple linear regression. Lastly, we used the node influence as the state transition of the infectious disease model to predict the trend of information dissemination in social networks. The experimental results on a real social network dataset showed that the prediction results of the model are consistent with the actual information dissemination trends.

LZTFL1 is a tumor suppressor located in chromosomal region 3p21.3 that is deleted frequently and early in various cancer types including the kidney cancer. However, its role in kidney tumorigenesis remains unknown. Here we hypothesized a tumor suppressive function of LZTFL1 in clear cell renal cell carcinoma (ccRCC) and its mechanism of action based on extensive bioinformatics analysis of patients’ tumor data and validated it using both gain- and loss-functional studies in kidney tumor cell lines and patient-derive xenograft (PDX) model systems. Our studies indicated that LZTFL1 inhibits kidney tumor cell proliferation by destabilizing AKT through ZNRF1-mediated ubiquitin proteosome pathway and inducing cell cycle arrest at G1. Clinically, we found that LZTFL1 is frequently deleted in ccRCC. Downregulation of LZTFL1 is associated with a poor ccRCC outcome and may be used as prognostic maker. Furthermore, we show that overexpression of LZTFL1 in PDX via lentiviral delivery suppressed PDX growth, suggesting that re-expression of LZTFL1 may be a therapeutic strategy against ccRCC.

Gastrointestinal (GI) tumor is a serious disease with high mortality rates and morbidity rates worldwide. Chemotherapy is a key treatment for GI, however, systematic side effects and inevitable drug resistance complicate the situation. In the process of therapy, P-glycoprotein (P-gp) could remove chemotherapy drugs from cells, thus causing multi-drug resistance. Chemodynamic therapy (CDT) utilizing Fenton chemistry has been used for cancer therapy, along with various combination therapies. The reactive oxygen species produced by CDT could inhibit P-gp’s efflux pump function, which reduce chemoagents excretion and reverse drug resistance. In the present study, we developed novel nanocrystals (Cu2O@Pt NCs) to overcome drug resistance by reducing mitochondria-derived ATP through chemo/CDT in GI cancer. Furthermore, in vivo results in tumor-bearing mice demonstrated that treatment with Cu2O@Pt NCs with CDT and chemotherapy could achieve the most effective antitumor therapeutic effect with the least amounts of adverse effects. As a result, Cu2O@Pt NCs could provide a promising strategy for chemo/CDT-synergistic therapy.

Electric vehicles will contribute to emissions reductions in the United States, but their charging may challenge electricity grid operations. We present a data-driven, realistic model of charging demand that captures the diverse charging behaviours of future adopters in the US Western Interconnection. We study charging control and infrastructure build-out as critical factors shaping charging load and evaluate grid impact under rapid electric vehicle adoption with a detailed economic dispatch model of 2035 generation. We find that peak net electricity demand increases by up to 25% with forecast adoption and by 50% in a stress test with full electrification. Locally optimized controls and high home charging can strain the grid. Shifting instead to uncontrolled, daytime charging can reduce storage requirements, excess non-fossil fuel generation, ramping and emissions. Our results urge policymakers to reflect generation-level impacts in utility rates and deploy charging infrastructure that promotes a shift from home to daytime charging., Nature Energy, 7 (10), ISSN:2058-7546

It is an effective means for merchants to carry out precision marketing and improve ROI by using historical user behavior data obtained from promotional activities in order to build a model to predict the repeat purchase behavior of users after promotional activities. Most of the existing prediction models are supervised learning, which does not work well with a small amount of labeled data. This paper proposes a BERT-MLP prediction model that uses “large-scale data unsupervised pre-training + small amount of labeled data fine-tuning.” The experimental results on Alibaba real dataset show that the accuracy of the BERT-MLP model is better than the baseline model.

Clear cell renal cell carcinoma (ccRCC) is the most common histological and devastating subtype of renal cell carcinoma. Necroptosis is a form of programmed cell death that causes prominent inflammatory responses. miRNAs play a significant role in cancer progression through necroptosis. However, the prognostic value of necroptosis-related miRNAs remains ambiguous. In this study, 39 necroptosis-related miRNAs (NRMs) were extracted and 17 differentially expressed NRMs between normal and tumor samples were identified using data form The Cancer Genome Atlas (TCGA). After applying univariate Cox proportional hazard regression analysis and LASSO Cox regression model, six necroptosis-related miRNA signatures were identified in the training cohort and their expression levels were verified by qRT-PCR. Using the expression levels of these miRNAs, all patients were divided into the high- and low-risk groups. Patients in the high-risk group showed poor overall survival ( P < 0.0001 ). Time-dependent ROC curves confirmed the good performance of our signature. The results were verified in the testing cohort and the entire TCGA cohort. Univariate and multivariate Cox regression models demonstrated that the risk score was an independent prognostic factor. Additionally, a predictive nomogram with good performance was constructed to enhance the implementation of the constructed signature in a clinical setting. We then employed miRBD, miRTarBase, and TargetScan to predict the target genes of six necroptosis-related miRNAs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses indicated that 392 potential target genes were enriched in cell proliferation-related biological processes. Six miRNAs and 59 differentially expressed target genes were used to construct an miRNA–mRNA interaction network, and 11 hub genes were selected for survival and tumor infiltration analysis. Drug sensitivity analysis revealed potential drugs that may contribute to cancer management. Hence, necroptosis-related genes play an important role in cancer biology. We developed, for the first time, a necroptosis-related miRNA signature to predict ccRCC prognosis.

BackgroundEsophagogastroduodenoscopy (EGD) screening is vital for the early diagnosis of esophageal squamous cell cancer (ESCC). However, improvement in the detection rate of precancerous lesions and early ESCC with anesthesia assistance (AA) has not yet been investigated. This retrospective study aimed to evaluate the effect of AA on the detection rate of precancerous lesions and early ESCC in patients undergoing EGD screening and identify risk factors affecting the detection rate.MethodsWe reviewed patients’ electronic medical records who underwent EGD screening between May 2019 and August 2020. Patients were divided into two groups based on whether they received AA: those in Group A underwent EGD screening with AA, and patients in Group O underwent EGD screening without AA. Propensity score matching (PSM) was used to account for differences in baseline characteristics. Detection rates of precancerous lesions and early ESCC were compared between the two groups following PSM. Binary logistic regression was used to identify risk factors affecting the detection rate.ResultsThe final analysis included 21,835 patients (Group A = 13,319, Group O = 8,516) from 28,985 patients who underwent EGD screening during the study period. Following PSM, 6009 patients remained in each group for analysis. There was no significant difference in the detection rate of precancerous lesions and early ESCC between Groups A and O (1.1% vs. 0.8%, p > 0.05). Binary logistic regression showed that age (50–59 years, 60–69 years and 70–79 years), higher endoscopist seniority, high-definition (HD) endoscopy, narrow-band imaging (NBI), and number of endoscopic images were all independent risk factors that affected the detection rate of precancerous lesions and early ESCC.ConclusionThere was no statistically significant difference in the detection rate of precancerous lesions and early ESCC between patients who underwent EGD screening with and without AA. All independent risk factors that affected the detection rate of precancerous lesions and early ESCC included the following: age (50–59 years, 60–69 years and 70–79 years), higher endoscopist seniority, HD endoscopy, NBI, and number of endoscopic images. Endoscopists should consider all these factors as much as possible when performing EGD screening.

Additional file 1: Methods. Supplementary figures and legends. Table S1: Basic information of enrolled patients. Table S2: Brief summary of all participants. Table S13: Performance of single mutation site in the diagnosis of HCC.

This article investigates the voltage monitoring and control feature for smart meters and identifies the impact of this feature on both power distribution and communication systems. Regarding the voltage monitoring, a cosimulation platform is developed using GridLAB-D and ns-3 to analyze the impact of adding voltage measurements to smart meter readings and assess the mitigation strategies for reducing timeout errors and packet drops of smart meter data. Regarding the voltage control, a new voltage stability control scheme is developed, which applies the voltage stability margin as the control objective, instead of the traditional voltage magnitude. The proposed control scheme makes use of existing advanced metering infrastructure and distributed energy resources (DERs), requiring small marginal costs. It is indicated that integrating the voltage monitoring and control feature, smart meters could enable the voltage stability issues being solved at end-user sides, i.e., the “last-mile” segment. It is also implied that the new feature could support the coordination of the local and system-level voltage controls using both customer-owned and utility-scale DERs.

Aims Patients with heart failure (HF) have a poor prognosis and are categorized by ejection fraction. We performed a meta‐analysis to compare baseline characteristics and long‐term outcomes of patients with heart failure with reduced (HFrEF), mid‐range (HFmrEF), and preserved ejection fraction (HFpEF). Methods and Results A total of 27 prospective studies were included. Patients with HFpEF were older and had a higher proportion of females, hypertension, diabetes, and insufficient neuroendocrine antagonist treatments, while patients with HFrEF and HFmrEF had a higher prevalence of coronary heart disease and chronic kidney disease. After more than 1‐year of follow‐up, all‐cause mortality was significantly lower in patients with HFmrEF 9388/25 042 (37.49%) than those with HFrEF 39 333/90 023 (43.69%) and HFpEF 24 828/52 492 (47.30%) (p

Existing multi-orientation scene text detection methods generally contain two crucial components: regression prediction for text bounding boxes and classification prediction for text/non-text. However, these methods always regard classification prediction and regression prediction as two independent procedures, neglecting fully exploring their mutual relations. Based on this key observation, we propose an innovative Scale-Guided Regression Module (SRM), specially for multi-orientation scene text detection. Equipped with width-guided kernels and height-guided kernels of different sizes, our SRM can generate a series of scale feature maps of candidate texts by capturing their shape information in classification prediction. The scale feature maps are used to predict the width and height of candidate texts, which can serve as guides for regressing bounding boxes. In this way, the procedures of classification and regression can be coherently integrated. In addition, we adopt IoU loss to train our network and then integrate IoU loss and l 1 -smooth loss for fine-tuning. Extensive experiments on publicly available datasets demonstrate the state-of-the-art performance of our method. Notably, our method achieves significant improvement of performance on long texts, e.g., on MSRA-TD500, our method outperforms Basemodel with a great margin (4.86 % in terms of Recall).

Taraxerol (TRX) is one of triterpenoid extracts from traditional Chinese medicine (TCM) Taraxacum, and its anti-tumor effect has been extensively proved. However, the effects and molecular mechanisms of TRX in Triple Negative Breast Cancer (TNBC) have not been illustrated completely. In this study, we found that TRX inhibited the migration and invasion of the TNBC cell line MDA-MB-231, and further identified 20 targets both closely related to TNBC and TRX through network pharmacology. Subsequently, analyzing these targets by GO and KEGG enrichment, and MAPK3 was the most potential candidate target. It was found by molecular docking that could combine stably with TRX, as well it was illustrated by experiments in vitro that could inhibit the migration and invasion of MDA-MB-231 cells by acting on Slug. Meanwhile, ERK activator (tert-Butylhydroquinone, tBHQ) could significantly reverse the suppression of TRX on the migration and invasion of MDA-MB-231 cells. In conclusion, TRX could inhibit the migration and invasion of MDA-MB-231 cells via ERK/Slug axis.

Long noncoding RNAs (lncRNAs) have been reported to exert important roles in tumors, including clear cell renal cell carcinoma (ccRCC). PVT1 is an important oncogenic lncRNA which has critical effects on onset and development of various cancers, however, the underlying mechanism of PVT1 functioning in ccRCC remains largely unknown. VHL deficiency-induced HIF2α accumulation is one of the major factors for ccRCC. Here, we identified the potential molecular mechanism of PVT1 in promoting ccRCC development by stabilizing HIF2α. PVT1 was significantly upregulated in ccRCC tissues and high PVT1 expression was associated with poor prognosis of ccRCC patients. Both gain-of-function and loss-of function experiments revealed that PVT1 enhanced ccRCC cells proliferation, migration, and invasion and induced tumor angiogenesis in vitro and in vivo. Mechanistically, PVT1 interacted with HIF2α protein and enhanced its stability by protecting it from ubiquitination-dependent degradation, thereby exerting its biological significance. Meanwhile, HIF2α bound to the enhancer of PVT1 to transactivate its expression. Furthermore, HIF2α specific inhibitor could repress PVT1 expression and its oncogenic functions. Therefore, our study demonstrates that the PVT1/ HIF2α positive feedback loop involves in tumorigenesis and progression of ccRCC, which may be exploited for anticancer therapy.

Background The aim of this study was to identify the ferroptosis induced tumor microenvironment (FeME) landscape in bladder cancer (BCa) for mRNA vaccine development and selecting suitable patients for precision treatment. Methods Gene expression profiles and clinical information of 1216 BCa patients were extracted from TCGA-BLCA, three GEO databases and IMvigor210 cohort. We comprehensively established the FeME landscape of 1216 BCa samples based on 290 ferroptosis related genes (FRGs), and systematically correlated these regulation patterns with TME cell-infiltrating characteristics. Besides, we identified the patients’ ferroptosis risk index (FRI) to predict the prognosis of BCa for precise treatment. Results Six over-expressed and mutated tumor antigens associated with poor prognosis and infiltration of antigen presenting cells were identified in BCa. Furthermore, we demonstrated the evaluation of FeME within individual tumors could predict stages of tumor inflammation, subtypes, genetic variation, and patient prognosis. Then, 5-lncRNA signature was mined to produce the FRI. Low FRI was also linked to increased mutation load, better prognosis and enhanced response to anti-PD-L1 immunotherapy. Besides, an immunotherapy cohort confirmed patients with lower FRI demonstrated significant therapeutic advantages and clinical benefits. Conclusions TFRC, SCD, G6PD, FADS2, SQLE, and SLC3A2 are potent antigens for developing anti-BCa mRNA vaccine. Establishment of FRI will contribute to enhancing our cognition of TME infiltration characterization and guiding more effective immunotherapy strategies and selecting appropriate patients for tumor vaccine therapy.

With the method of ultraviolet-visible absorption spectroscopy (UV-vis) and excitation-emission matrix spectroscopy combined with parallel factor analysis (EEMs-PARAFAC), this study analyzed the change in dissolved organic matter (DOM) content and composition in spring and summer of two non-point source urban rivers which had different input intensities. The results indicated that the level of humification and molecular weight of DOM in summer was significantly higher than that in spring in these two rivers (

Objective: The aim of this study was to investigate and compare the diagnostic performance of dynamic contrast-enhanced (DCE)-MRI, multiparametric MRI (mpMRI), and multimodality imaging (MMI) combining mpMRI and mammography (MG) for discriminating breast non-mass-like enhancement (NME) lesions. Methods: This retrospective study enrolled 193 patients with 199 lesions who underwent 3.0 T MRI and MG from January 2017 to December 2019. The features of DCE-MRI, turbo inversion recovery magnitude (TIRM), and diffusion-weighted imaging (DWI) were assessed by two breast radiologists. Then, all lesions were divided into microcalcification and non-microcalcification groups to assess the features of MG. Comparisons were performed between groups using univariate analyses. Then, multivariate analyses were performed to construct diagnostic models for distinguishing NME lesions. Diagnostic performance was evaluated by using the area under the curve (AUC) and the differences between AUCs were evaluated by using the DeLong test. Results: Overall (n = 199), mpMRI outperformed DCE-MRI alone (AUCmpMRI = 0.924 vs. AUCDCE-MRI = 0.884; p = 0.007). Furthermore, MMI outperformed both mpMRI and MG (the microcalcification group [n = 140]: AUCMMI = 0.997 vs. AUCmpMRI = 0.978, p = 0.018 and AUCMMI = 0.997 vs. AUCMG = 0.912, p < 0.001; the non-microcalcification group [n = 59]: AUCMMI = 0.857 vs. AUCmpMRI = 0.768, p = 0.044 and AUCMMI = 0.857 vs. AUCMG = 0.759, p = 0.039). Conclusion & advances in knowledge: DCE-MRI combined with DWI and TIRM information could improve the diagnostic performance for discriminating NME lesions compared with DCE-MRI alone. Furthermore, MMI combining mpMRI and MG showed better discrimination than both mpMRI and MG.

(1) Background: Circulating tumor DNA (ctDNA) has emerged as a promising biomarker for many kinds of tumors. However, whether ctDNA could be an accurate diagnostic biomarker in colorectal cancer (CRC) remains to be clarified. The aim of this study was to evaluate the diagnostic accuracy of ctDNA in CRC. (2) Methods: PubMed, Web of Science, and Cochrane databases were searched to identify studies reporting the use of ctDNA to screen and diagnose CRC, and all relevant studies published until October 2022 were enrolled for our analysis. These studies were divided into three primer subgroups: the subgroup of quantitative or qualitative analysis of ctDNA and the subgroup of septin9 (SEPT9) methylation assay. (3) Results: A total of 79 qualified articles with 25,240 subjects were incorporated into our meta-analysis. For quantitative studies, the combined sensitivity (SEN), specificity (SPE), and diagnostic odds ratio (DOR) were 0.723 (95% CI: 0.623–0.803), 0.920 (95% CI: 0.827–0.966), and 23.305 (95% CI: 9.378–57.906), respectively, yielding an AUC of 0.860. The corresponding values for qualitative studies were 0.610 (95% CI: 0.566–0.651), 0.891 (95% CI: 0.878–0.909), 12.569 (95% CI: 9.969–15.848), and 0.823, respectively. Detection of SEPT9 methylation depicted an AUC of 0.879, with an SEN of 0.679 (95% CI: 0.622–0.732), an SPE of 0.903 (95% CI: 0.878–0.923), and a DOR of 20.121 (95% CI:14.404–28.106), respectively. (4) Conclusion: Blood-based ctDNA assay would be a potential novel biomarker for CRC screening and diagnosis. Specifically, quantitative analysis of ctDNA or qualitative analysis of SEPT9 methylation exhibited satisfying diagnostic efficiency. Larger sample studies are needed to further confirm our conclusions and to make the ctDNA approach more sensitive and specific.

Methamphetamine (METH) has been shown to alter learning and memory by affecting the neuroplasticity of the dorsal hippocampus, a key structure that undergoes extensive remodeling during adolescence. In this study, we investigated whether mid-to-late adolescent exposure to METH leads to long-lasting memory impairment. To do this, adolescents (35–48 postnatal days) were exposed to different doses of METH for 14 days and then evaluated by the Morris water maze (MWM), new object recognition test (NORT), and the Y-maze, to investigate the learning and memory abilities of mice in their adolescence and adulthood, respectively. We also detected the mRNA levels of genes associated with neuroplasticity in the dorsal hippocampus. The synaptic ultrastructure and the number of neurons and astrocytes in the dorsal hippocampus were also determined by transmission electron microscopy (TEM) and immunofluorescence (IF). Exposure to METH in mid-to-late adolescence impaired spatial memory retrieval ability and the long-term recognition memory of mice in their adulthood, but not in their adolescence. Of note, the impairment of memory capacity in adulthood was accompanied by molecular and structural changes in synapses in the dorsal hippocampus. Our results indicate that mice exposed to METH in mid-to-late adolescence have impaired memory ability in their adulthood; this may be the result of abnormal changes in the structural plasticity of the dorsal hippocampus; the causal relationship between changes in synaptic structural plasticity and memory impairment needs to be further confirmed. In summary, our study provides evidence for the detrimental consequences of adolescent addiction and the prevention of adolescent drug abuse.

Additional file 1: Figure S1. Total ion flow diagram of 1,3-butadiene thermal reaction products measured by GC-MS. Figure S2. Total ion flow diagram of 1,3-butadiene photolysis reaction products measured by GC-MS.

This study aimed to explore the anti-tumor effect of icaritin loading poly (lactic-co-glycolic acid) nanoparticles (refer to PLGA@Icaritin NPs) on gastric cancer (GC) cells. Transmission Electron Microscope (TEM), size distribution, zeta potential, drug-loading capability, and other physicochemical characteristics of PLGA@Icaritin NPs were carried out. Furthermore, flow cytometry, confocal laser scanning microscope (CLSM), Cell Counting Kit-8 (CCK-8), Transwell, Elisa assay and Balb/c mice were applied to explore the cellular uptake, anti-proliferation, anti-metastasis, immune response activation effects, and related anti-tumor mechanism of PLGA@Icaritin NPs in vitro and in vivo. PLGA@Icaritin NPs showed spherical shape, with appropriate particle sizes and well drug loading and releasing capacities. Flow cytometry and CLSM results indicated that PLGA@Icaritin could efficiently enter into GC cells. CCK-8 proved that PLGA@Icaritin NPs dramatically suppressed cell growth, induced Lactic dehydrogenase (LDH) leakage, arrested more GC cells at G2 phase, and inhibited the invasion and metastasis of GC cells, compared to free icaritin. In addition, PLGA@Icaritin could help generate dozens of reactive oxygen species (ROS) within GC cells, following by significant mitochondrial membrane potentials (MMPs) loss and excessive production of oxidative-mitochondrial DNA (Ox-mitoDNA). Since that, Ox-mitoDNA further activated the releasing of damage associated molecular pattern molecules (DAMPs), and finally led to immunogenic cell death (ICD). Our in vivo data also elaborated that PLGA@Icaritin exerted a powerful inhibitory effect (∼80%), compared to free icaritin (∼60%). Most importantly, our results demonstrated that PLGA@Icaritin could activate the anti-tumor immunity via recruitment of infiltrating CD4+ cells, CD8+ T cells and increased secretion of cytokine immune factors, including interferon-γ (IFN-γ) tumor necrosis factor-α (TNF-α) and interleukin-1 (IL-1).++ Our findings validate that the successful design of PLGA@Icaritin, which can effectively active ICD and facilitate tumor recruitment in GC through inducing mitoDNA oxidative damage.

The continuous liquid interface production (CLIP) process has dramatically improved the fabrication speed of 3D printing technology, which makes it possible for Stereolithography to be used for direct manufacturing of functional parts. The effect of the CLIP process is significant owing to the skillful application of the photopolymerization inhibition effect of oxygen; therefore, the mass transfer behavior of the oxygen across the substrate is the key factor affecting the thickness and stability of the inhibition zone. In this paper, a low-cost scheme for a constrained substrate with good oxygen permeability that is made of PDMS membrane has been proposed, and the paper focuses on the effect of PDMS membrane and microscopic pore characteristics on the oxygen mass transfer behavior in the substrate. Based on the calculation result of the oxygen-diffusion coefficient in the PDMS membrane through molecular dynamics simulation, the influencing factors and laws of oxygen permeability of substrate are numerically studied using COMSOL software. The substrates with oxygen permeability that was measured based on the constructed experiment device were fabricated. The results show that the PDMS membrane possesses good oxygen content and the diffusion coefficient of the content in the PDMS film is 4.018 ×10−5 cm2/s. The thickness of the PDMS film and the area ratio and diameter of the micro-pores in the supporting glass substrate affect the oxygen permeability. Reducing the thickness of the PDMS film, increasing the pore-area ratio, and reducing the micro-pore diameter facilitate the oxygen permeability improvement under the premise of meeting the strength requirements. The research results can provide process improvement direction and theoretical basis for the preparation of constrained substrates.

In this work, we develop a polynomial-chaos-expa- nsion (PCE)-based approach for decentralized dynamic parameter estimation through Bayesian inference. Using this approach, the non-Gaussian distribution of the inverted parameters is obtained. More specifically, we first represent the decentralized generator model with the PCE-based surrogate. This surrogate allows us to efficiently evaluate the time-consuming dynamic solver at parameter values through Metropolis-Hastings (M-H)-based Markov chain Monte Carlo (MCMC). Then, we propose a two-stage hybrid Markov chain Monte Carlo (MCMC) to recover a posteriori distribution of the decentralized generator model parameters. In the first stage, we use the gradient-enhanced Langevin MCMC algorithm to characterize an intermediate posterior parameter distribution. This algorithm is computationally scalable to the high-dimensional parameter space. Based on the intermediate posterior distribution, during the second stage, we use the adaptive MCMC algorithm to fine-tune the strong correlations between the parameters. Finally, the fully recovered a posterior distribution is obtained in the end. The simulation results show that the proposed PCE-based hybrid MCMC algorithm can accurately and efficiently estimate the high-dimensional generator dynamic model parameters with full probabilistic distribution provided.

The risks associated with rare events threatening the security of power system operation are of paramount importance to power system planners and operators. To analyze the risks caused by high-impact, low-frequency rare events, an immensely large number of samples are typically required for the Monte-Carlo (MC) method on the high-fidelity power system model to achieve a sufficient accuracy, thereby rendering this approach computationally prohibitive. To handle this problem efficiently, it is desirable to construct a surrogate model for the power system response. However, the straightforward MC sampling of the low-fidelity surrogate can lead to biased results in the low-probability tail regions that are vital to risk assessment. Moreover, a single surrogate is unable to handle the topology uncertainties caused by random branch outages. To overcome these issues, we propose a hybrid multi-surrogate (HMS) method based on the polynomial chaos expansion (PCE) with low-probability tail events reevaluated by the high-fidelity model through a probabilistic analysis. This method improves the computational efficiency of the MC method for rare-event risk assessment by leveraging multi-fidelity models while retaining the desired accuracy. Simulations conducted in three test systems verify the excellent performances of the HMS method.

The emerging distribution-level phasor measurement unit (D-PMU) is expected to play an important role in enhancing distribution system observability and situational-awareness. It is a demanding yet challenging task to develop advanced D-PMU data management and analytics tools to improve D-PMU data usability and further promote D-PMU projects deployment. This paper focuses on D-PMU data processing and storage. It presents a brief review of existing D-PMU data storage systems and points out their limitations on high-performance, flexibility, and scalability. To overcome the limitations, a unified PMU-data storage system (UPS) is proposed. Specifically, a unified I/O interface between storage servers and computing jobs is developed to effectively reduce the overhead of managing various computing jobs and data analytics over multiple storage infrastructures; and PMUCache with PMUCache partitioning and PMUCache replacement algorithms are designed to support in-situ data processing and shared distributed data storage and further serve the computing jobs/queries with different quality of service (QoS) requirements. Through a series of experiments, it is demonstrated that UPS achieves high performance on fast and big data processing and storage, and efficiently increases the flexibility and scalability of PMU data management systems.

This paper develops a new response-surface-based Bayesian inference approach for power system dynamic parameter estimation of a decentralized generator using phasor-measurement-unit measurement. The response surface for the decentralized generator model is formulated through a polynomial-chaos-based surrogate. This surrogate allows us to efficiently evaluate the time-consuming dynamic solver at parameter values through a polynomial-based reduced-order representation. In addition, a polynomial-chaos-based analysis of variance is performed to screen out model parameters while ensuring system observability. In dealing with sampling the non-Gaussian posterior distribution for the parameters, the Metropolis-Hastings sampler is adopted. The simulations conducted in the New England system under different system events show that the proposed method can achieve a speedup factor of two orders or magnitude compared with the traditional method while providing full probabilistic distribution of model parameters and achieving the same level of accuracy.

Aim: The purpose of the present research was to investigate the effect and mechanism of Astragaloside IV (AS-IV) on liver cancer progression in vivo and in vitro. Since M1 macrophages play an essential role in suppressing tumors, while M2 macrophages can accelerate the incidence and progression of tumors by promoting angiogenesis, increasing tumor cell invasion and inhibiting tumor immune response, the effect and mechanism of AS-IV on macrophage polarization and their role in the development of HCC was explored. Methods: The effects of different concentrations of AS-IV (0, 50, 80, 100, 120, and 150 μM) on the capacity of hepatocellular carcinoma (HCC) cells to proliferate, migrate, and invade were detected. THP-1 cells were subjected to incubation in PMA for the purpose of stimulating differentiation into M0 macrophages. These macrophages were treated using LPS, IFN-γ, and PMA to produce M1 macrophages or treated using PMA, IL-13, and IL-4 to produce M2 macrophages. HCC cells and M1 or M2 macrophages were co-cultured for 48 hours, then the cell proliferation and migration were measured. The MTT assay was employed to determine cell viability. The capability of the cells to migrate and invade was investigated utilizing the Transwell assay and the wound healing assay. The expression of the M2 macrophage CD206 in macrophages treated with AS-IV was evaluated by flow cytometry. The expression of p-signal transducer and activator of transcription 3 (STAT3), phosphorylated (p)-NF-κB, and toll-like receptor 4 (TLR4) in macrophages was measured after treatment with AS-IV and M2 induction. To verify the function of the TLR4/NF-κB/STAT3 signaling pathway, TLR4 expression was knocked down in M2 macrophages, then the proliferation and migration and the M2 macrophage markers of HCC cells were measured. The effect of AS-IV on HCC in vivo was confirmed by a subcutaneous tumor mouse model. AS-IV was 2 was administered by gavage (0, 40, 80, and 100 mg/kg) for every 3 days. The tumor volume and weight were recorded. Results: AS-IV suppressed the capacities of HCC cells to proliferate, migrate, and invade in a dose-dependent way. M2 macrophages could promote the proliferative, migratory, and invasive ability of Huh-7 cells, which were suppressed by AS-IV. AS-IV directly attenuated the expression of M2 macrophage markers, indicating that AS-IV can inhibit macrophage M2 polarization. M2 macrophages stimulated the expression of p-STAT3, p-NF-κB, and TLR4, while AS-IV decreased the expression compared to the M2 group, indicating that AS-IV can regulate the TLR4/NF-κB/STAT3 signaling pathway. TLR4 small interfering RNA (siRNA/si) inhibited the proliferation of Huh-7 cells. The tumor volume, as well as weight of mice, was significantly reduced by AS-IV, indicating the antitumor impact of AS-IV in vivo. Conclusion: AS-IV can inhibit the proliferative, invasive, and migratory ability of liver cancer through the suppression of the M2 polarization of macrophages, and the mechanism may involve the TLR4/NF-κB/STAT3 signaling pathway. The present study indicates that AS-IV could be an alternative drug to treat liver cancer, and the polarization of macrophages may be a novel treatment target for HCC.

To verify the superiority of motor imagery acupuncture in improving muscle tension for patients with upper limb hemiplegia in early stroke.A total of 64 patients of stroke hemiplegia with upper limb flaccid paralysis were randomly divided into an observation group (32 cases, 1 case dropped off ) and a control group (32 cases, 4 cases dropped off ). The observation group was treated with motor imagery acupuncture (both acupuncture and motor imagery therapy at affected upper limb were performed).The control group was treated with acupuncture plus motor imagery therapy at affected lower limb, 2 h later after acupuncture, motor imagery therapy was applied to upper limb. Baihui (GV 20) to Taiyang (EX-HN 5) of healthy side, Fengchi (GB 20) and Jianyu (LI 15), Jianjing (GB 21), Quchi (LI 11), Waiguan (TE 5) on the affected side, ect. were selected in both groups, once a day, 5 times a week for 4 weeks. Before and after treatment, 4, 8 weeks after treatment, the modified Ashworth scale (MAS) grade and Brunnstrom stage were compared in the two groups.Compared before treatment, the muscle tension of shoulder, elbow and wrist each time point after treatment was increased in the two groups (Motor imagery acupuncture could promote hemiplegia upper limb muscle tension recovery in patients of stroke hemiplegia with upper limb flaccid paralysis, make the patients gradually shift to the separate fine movement mode, inhibit and relieve the appearance and development of spasm.

This paper understands the personality traits and cluster types of physical education (PE) teachers in elementary schools. A total of 393 elementary PE teachers volunteered to participate in this study. The Personality Trait Questionnaire for PE teachers in elementary school was summarized and compiled on the basis of the theory of the Big Five personality traits. The researchers used the discriminant analysis method to analyze and obtain the data. The results show that the Big Five personality traits of PE teachers in elementary schools was agreeableness. Classification of the Big Five personality traits through discriminant analysis revealed a Wilk’s λ value of .199, an eigenvalue of 3.254, and 94.7% of the variance explained. Use of Ward’s minimum variance method indicated that the participants’ personalities were characterized by steady and pioneering type, sensitive and cautious type, and moderate and peaceful type. There were more males than females in the steady and pioneering type, more steady and pioneering type under the age of 30 years old, and more moderate and peaceful type with more than 16 years of work experience. In conclusion, most the personality traits of PE teachers in elementary school were agreeableness, moderate and peaceful type, which shows that most PE teachers have calm emotions, appropriate expressions of emotions, regularity, optimism, and enjoy interacting and collaborating with others.

With the development and popularization of big data, artificial intelligence, and cloud computing, the digital and information development of campuses and education has become a common phenomenon. Smart campus is the development of traditional digital campus. At present, many colleges and universities are constructing and exploring smart campus. The lightweight “smart campus” based on LAPP is a unique campus system that combines manpower, equipment, environment, resources, and social factors on the basis of informatization to form a unique campus system. All information resources related to life services are fully integrated, interconnected and integrated, based on in-depth data mining and analysis, to provide comprehensive, effective and intelligent management and service process support for school work. Based on in-depth data mining and analysis, this paper analyzes and studies the lightweight “smart campus” system of LAPP from the perspective of construction and technology.

The production of platform chemicals from lignocellulosic biomass is scientifically valuable but technologically challenging. With the aim to establish a green reaction system for the production of furfural from lignocellulosic biomass, in the current work, H-SAPO-34 was investigated for catalysis of the conversion of Eucalyptus sawdust to furfural in γ-valerolactone (GVL). H-SAPO-34 was prepared and characterized by XRD, SEM, FTIR, BET, TGA and ammonia adsorbed FTIR. H-SAPO-34 possesses Bronsted and Lewis acid sites and a large specific surface area. The average pore diameter of H-SAPO-34 was 0.86 nm, which is beneficial for the spread of xylose and furfural and the inhibition of humin production. In this work, a peak furfural yield of 99.28% from Eucalyptus was achieved at 210 °C in 120 min with 30 g/L H-SAPO-34. The Bronsted/Lewis acid bifunctionality and the solvent effect of γ-valerolactone possibly contributed to the high furfural yield from real biomass. The kinetics of the conversion of Eucalyptus sawdust to furfural was also studied, and the activation energy for furfural production was calculated. Additionally, the catalytic activity and stability of the regenerated catalyst were estimated.