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Abstract Background Sphingosine-1-phosphate receptor 1 (S1PR1) is considered to be closely related to a variety of malignant tumors, but the role and mechanism of S1PR1 in lung adenocarcinoma are not fully understood. In this study, we aim to explore the role and downstream signaling pathways of S1PR1 in the malignant biological functions of lung adenocarcinoma (LUAD). Methods Bioinformatics analysis, RT-qPCR, western blot and immunohistochemistry (IHC) were was used to investigate the expression of S1PR1 in LUAD. The prognosis of S1PR1 was also analyzed. CCK-8 assay, colony formation assay, scratch assay, transwell migration and invasion assay, cell adhesion assay were performed to examine the effect of S1PR1 on LUAD. RNA sequencing was employed to analyze the DEGs in LUAD cells overexpressing S1PR1. Enrichment pathway analysis using KEGG, GO, and GSEA was conducted to predict potential signaling pathways and downstream targets. chromatin immunoprecipitation (ChIP) and dual luciferase reporter assay were performed to verify the direct regulation between FOXA1 and the target genes. Then FOXA1 overexpression were performed to functional rescue experiments. miRNA-30c-5p was identified as a microRNA regulating FOXA1 by dual luciferase reporter assay. The downstream signaling pathways of S1PR1 was detected to clarify the specific pathways to regulates miR-30c-5p. Results S1PR1 is significantly decreased in LUAD and is positively correlated with the prognosis. Overexpression of S1PR1 inhibits the proliferation, migration, invasion and adhesion function of LUAD cells by suppressing the expression of COL5A1, MMP1, and SERPINE1. FOXA1 is a key transcription factor regulating the expression of MMP1, COL5A1 and SERPINE1. S1PR1 inhibits the expression of FOXA1 through p-STAT1/miR-30c-5p, thereby suppressing the malignant function of LUAD cells. Conclusions The expression of S1PR1 is downregulated in LUAD, which is positively correlated with prognosis. S1PR1 regulates the malignant function of LUAD cells by inhibiting the expression of COL5A1, MMP1 and SERPINE1 through the p-STAT1/miR-30c-5p/FOXA1 signaling pathway.

Periodic pattern mining is of great significance for understanding passenger travel behavior, but the previous works mainly focused on the trajectory data and the dimension of the spot/point. Besides, many uncertain factors (severe weather, traffic accident, etc.) may interfere with discovering original and accurate periodic travel patterns. This paper proposes a novel type of travel pattern called motif periodic frequent pattern (MPFP), which captures the periodicity of network temporal motifs of individual metro passengers with higher-order spatio-temporal characteristics, considering, uncertain disturbances. We also propose a new complete mining algorithm MPFP-growth to extract MPFP from smart card data (SCD), and apply the real long-time-span experimental data from a large-scale metro system is applied. Results show that frequent-travel metro passengers usually have some typical MPFPs with the temporal periodic characteristic of “week”. Only the top 10 types of all 4 624 types account for about 95% of all motifs and the top 5 types constitute about 90%, and the MPFP of the top 3 types of motifs account for nearly 80% of all periodic patterns, in which Mono-MPFP and 2-MPFP are the main ones. The relatively stable time range of MPFP is three months, and the threshold for the optimal uncertain disturbance factor should be set at 5%. Additionally, several interesting typical MPFPs of individual metro commuting passengers and their proportions are introduced to further understand the multifarious variants of MPFP.

Periodic frequent pattern discovery is a non-trivial task to discover frequent patterns based on user interests using a periodicity measure. Although conventional algorithms for periodic frequent pattern detection have numerous applications, there is still little research on periodic frequent pattern detection of individual passengers in the metro. The travel behavior of individual passengers has complex spatio-temporal characteristics in the metro network, which may pose new challenges in discovering periodic frequent patterns of individual metro passengers and developing mining algorithms based on real-world smart card data. This study addresses these issues by proposing a novel pattern for metro passenger travel pattern called periodic frequent passenger traffic patterns with time granularities and station attributes (PFPTS). This discovered pattern can automatically capture the features of the temporal dimension (morning and evening peak hours, week) and the spatial dimension (entering and leaving stations). The corresponding complete mining algorithm with the PFPTS-tree structure has been developed. To evaluate the performance of PFPTS-tree, several experiments are conducted on one-year real-world smart card data collected by an automatic fare collection system in a certain large metro network. The results show that PFPTS-Tree is efficient and can discover numerous interesting periodic frequent patterns of metro passengers in the real-world dataset.

[Objective] Holding train is a train operation scheme often used in urban rail transit under the condition of long initial delay. In order to evaluate the rationality of the scheme, it is necessary to build an evaluation model and evaluate the train holding scheme based on passenger service level and safety. [Method] Based on the complexity and specialty of passenger travel law, a train holding scheme in urban rail transit is formulated. The train holding evaluation model is built on the basis of maximum departure interval, total train delay time, train evenness, the number of delayed trains at the terminal, the number of detained passengers and passengers′ total travel time. Four sections of one urban rail transit line in Shanghai are selected to calculate the actual OD (origin and destination) passenger flow in morning peak hours. [Result & Conclusion] The calculation shows that scheme 6 is the optimal train holding adjustment scheme as it has the smallest comprehensive evaluation index. This scheme can effectively improve the evenness of the train operation diagram, and reduce the number of detained passengers, and lower safety risks at the station.

Increasing research has shown that the abnormal expression of microRNA (miRNA) is associated with many complex diseases. However, biological experiments have many limitations in identifying the potential disease-miRNA associations. Therefore, we developed a computational model of Three-Layer Heterogeneous Network based on the Integration of CircRNA information for MiRNA-Disease Association prediction (TLHNICMDA). In the model, a disease-miRNA-circRNA heterogeneous network is built by known disease-miRNA associations, known miRNA-circRNA interactions, disease similarity, miRNA similarity, and circRNA similarity. Then, the potential disease-miRNA associations are identified by an update algorithm based on the global network. Finally, based on global and local leave-one-out cross validation (LOOCV), the values of AUCs in TLHNICMDA are 0.8795 and 0.7774. Moreover, the mean and standard deviation of AUC in 5-fold cross-validations is 0.8777+/−0.0010. Especially, the two types of case studies illustrated the usefulness of TLHNICMDA in predicting disease-miRNA interactions.

Many studies have examined the influence of digital technologies, such as robots and artificial intelligence, on enterprise labor, but few have investigated the underlying mechanisms and impact paths of digital empowerment on labor employment. Therefore, this study uses data on manufacturing enterprises listed on China's Shanghai and Shenzhen A-share markets from 2011 to 2020, and applies a panel fixed effect model to test the relationship between digital empowerment and labor employment, and the mechanisms underlying this relationship. We find that digital empowerment increases labor employment. However, the effects are heterogeneous: firms with better corporate governance, more competitive industry, and less favorable regional business environments are more motivated to optimize the structure of their labor resources. Through robustness test and mediation effect model test, we find that digital empowerment can improve enterprise human capital by increasing economies scale and managerial efficiency, especially the employment of R&D and innovation personnel and management personnel; it can also affect the amount of human capital by improving total factor productivity.

IntroductionWith the increasingly serious problem of antiviral drug resistance, drug repurposing offers a time-efficient and cost-effective way to find potential therapeutic agents for disease. Computational models have the ability to quickly predict potential reusable drug candidates to treat diseases.MethodsIn this study, two matrix decomposition-based methods, i.e., Matrix Decomposition with Heterogeneous Graph Inference (MDHGI) and Bounded Nuclear Norm Regularization (BNNR), were integrated to predict anti-viral drugs. Moreover, global leave-one-out cross-validation (LOOCV), local LOOCV, and 5-fold cross-validation were implemented to evaluate the performance of the proposed model based on datasets of DrugVirus that consist of 933 known associations between 175 drugs and 95 viruses.ResultsThe results showed that the area under the receiver operating characteristics curve (AUC) of global LOOCV and local LOOCV are 0.9035 and 0.8786, respectively. The average AUC and the standard deviation of the 5-fold cross-validation for DrugVirus datasets are 0.8856 ± 0.0032. We further implemented cross-validation based on MDAD and aBiofilm, respectively, to evaluate the performance of the model. In particle, MDAD (aBiofilm) dataset contains 2,470 (2,884) known associations between 1,373 (1,470) drugs and 173 (140) microbes. In addition, two types of case studies were carried out further to verify the effectiveness of the model based on the DrugVirus and MDAD datasets. The results of the case studies supported the effectiveness of MHBVDA in identifying potential virus-drug associations as well as predicting potential drugs for new microbes.

Background A growing number of experiments have shown that microRNAs (miRNAs) can be used as target of small molecules (SMs) to regulate gene expression for treating diseases. Therefore, identifying SM-related miRNAs is helpful for the treatment of diseases in the domain of medical investigation. Methods This article presents a new computational model, called NIRBMSMMA (neighborhood-based inference (NI) and restricted Boltzmann machine (RBM)), which we developed to identify potential small molecule-miRNA associations (NIRBMSMMA). First, grounded on known SM-miRNAs associations, SM similarity and miRNA similarity, NI was used to predict score of an unknown SM-miRNA pair by reckoning the sum of known associations between neighbors of the SM (miRNA) and the miRNA (SM). Second, utilizing a two-layered generative stochastic artificial neural network, RBM was used to predict SM-miRNA association by learning potential probability distribution from known SM-miRNA associations. At last, an ensemble learning model was conducted to combine NI and RBM for identifying potential SM-miRNA associations. Results Furthermore, we conducted global leave one out cross validation (LOOCV), miRNA-fixed LOOCV, SM-fixed LOOCV and five-fold cross validation to assess performance of NIRBMSMMA based on three datasets. Results showed that NIRBMSMMA obtained areas under the curve (AUC) of 0.9912, 0.9875, 0.8376 and 0.9898 ± 0.0009 under global LOOCV, miRNA-fixed LOOCV, SM-fixed LOOCV and five-fold cross validation based on dataset 1, respectively. For dataset 2, the AUCs are 0.8645, 0.8720, 0.7066 and 0.8547 ± 0.0046 in turn. For dataset 3, the AUCs are 0.9884, 0.9802, 0.8239 and 0.9870 ± 0.0015 in turn. Also, we conducted case studies to further assess the predictive performance of NIRBMSMMA. These results illustrated the proposed model is a useful tool in predicting potential SM-miRNA associations.

Abstract Previous literatures have suggested the importance of inflammatory response during lung adenocarcinoma (LUAD) development. This study aimed at exploring the inflammation-related genes and developing a prognostic signature for predicting the prognosis of LUAD. Survival‑associated inflammation-related genes were identified by univariate Cox regression analysis in the dataset of The Cancer Genome Atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) penalized Cox regression model was used to derive a risk signature which is significantly negatively correlated with OS and divide samples into high-, medium- and low-risk group. Univariate and multivariate Cox analyses suggested that the level of risk group was an independent prognostic factor of the overall survival (OS). Time-dependent receiver operating characteristic (ROC) curve indicated the AUC of 1-, 3- and 5-years of the risk signature was 0.715, 0.719, 0.699 respectively. A prognostic nomogram was constructed by integrating risk group and clinical features. The independent dataset GSE30219 of Gene Expression Omnibus (GEO) was used for verification. We further explored the differences among risk groups in Gene set enrichment analysis (GSEA), tumor mutation and tumor microenvironment. Furthermore, Single Sample Gene Set Enrichment Analysis (ssGSEA) and the results of Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) suggested the status of immune cell infiltration was highly associated with risk groups. We demonstrated the prediction effect of CTLA-4 and PD-1/PD-L1 inhibitors in the low-risk group was better than that in the high-risk group using two methods of immune score include immunophenoscore from The Cancer Immunome Atlas (TCIA) and TIDE score from Tumor Immune Dysfunction and Exclusion (TIDE). In addition, partial targeted drugs and chemotherapy drugs for lung cancer had higher drug sensitivity in the high-risk group. Our findings provide a foundation for future research targeting inflammation-related genes to predictive prognosis and some reference significance for the selection of immunotherapy and drug regimen for lung adenocarcinoma.

Objective: To explore the mechanism of Guizhou Rosa roxburghii Radix in the treatment of ulcerative colitis in rats based on TLR4/NF-κB signaling pathway. Methods: The ulcerative colitis model was established by gavage with 2,4,6-trinitrobenzenesulfonic acid (TNBS)/ethanol solution, gavage with Rosa roxburghii Radix aqueous decoction high, medium and low dose groups (8, 4 and 2 g/kg) and salazosulfanil group (0.3 g/kg). Observation of the appearance, motor behaviour and blood stool of the rats. Serum and colon of rats were collected, and hematoxylin-eosin (HE) staining was used to observe the pathological changes in the colon of each group of rats. Enzyme-linked immunosorbent assay (ELISA) for the detection of serum interleukin (IL)-1β, IL-6, TNF-α levels in rats. Reverse transcription-polymerase chain reaction (RT-PCR) for the detection of rat colon Myd88, NF-κB p50, NF-κB p65, TLR4 mRNA expression. Protein immunoblotting (Western blot) was performed to detect Myd88, NF-κB p50, NF-κB p65, TLR4 protein expression in rat colon. Results: Rosa roxburghii Radix aqueous decoction significantly improved colonic inflammatory injury in rats with ulcerative colitis, especially in the high dose group of Rosa roxburghii Radix aqueous decoction. Compared with the model group, the Rosa roxburghii Radix aqueous decoction high-dose group showed significant improvement in colon pathological damage. Serum IL-1β, IL-6 and TNF-α levels were significantly decreased in the Rosa roxburghii Radix aqueous decoction high-dose group (P

In this work, the numerical simulation study of the hydrothermal flow and heat transfer process in the porous rock under 30 MPa pressure was developed. The flow and heat transfer characteristics of hydrothermal in rocks with different porosities are studied by changing the porosity of the rock. The simulation results show that the average flow velocity decreases and the average temperature increases when the porosity decreases. The velocity field and temperature field are coupled due to the nonlinear thermophysical properties of hydrothermal. The velocity field and temperature field have strongly interacted in the range of 400–450 ℃ and the effect of temperature on velocity is gradually diminishing outside the range. Most of the fluid will be "squeezed" into the crevice and the average velocity is almost three times the no-creviced case when a crevice is present. The existence of the crevice makes the total heat flux decrease from an overall perspective, and the crevice makes a large temperature gradient at the entrance and export of the crevice from a local perspective. These results provide theoretical support for the utilization of submarine hydrothermal fluid shallow circulation heat energy.

Graphene-based photodetectors have many advantages for applications. Here, the authors demonstrate a high-speed optical coherent receiver for optical communications based on graphene-on-plasmonic slot waveguide photodetectors.

The Covid pandemic had turned the world upside down, but not much is known about how people’s empathy toward others in difficult situations might be affected by the pandemic. Based on a nationally representative sample ( N = 943) from China, this study first let participants read three real scenarios and then measured: (1) how empathy toward others might be influenced by the perceived social support people obtained by using social media (i.e., WeChat); and (2) how different demographics such as age and gender as well as lockdown situations may affect preserving empathetic during the Covid outbreak. Results show that perceived social support via WeChat not only positively impacted empathy but also interacted with anxiety in influencing the degree to which participants could maintain empathy toward others. Those living in cities or towns with higher incomes were more empathetic to others. While anxiety does not necessarily decrease empathy, those who reported gaining more social support on social media showed more empathy toward others despite their elevated levels of anxiety. Age negatively predicted empathy, but gender and lockdown conditions did not impact empathy. This study contributes to the literature by identifying the critical role empathy plays in people’s affective response to others during a public health crisis.

The lower Wuerhe formation reservoir of the 8th district is a blocky, ultra-low-permeability gravel reservoir with poor waterflooding development, and it is urgent to attack the gas injection gravity flooding. The barrier property of seepage barriers such as interlayers developed inside the reservoir is very important for the study of gas injection gravity flooding. The mineral composition, pore throat structure, and physical characteristics of the interlayer rocks were studied by X-ray diffraction (XRD) whole-rock analysis and nuclear magnetic resonance (NMR). The gas injection breakthrough pressure of the interlayer was studied by core breakthrough experiment and digital core simulation. Based on the determination of the interlayer criteria, logging was used to interpret and characterize the interlayer. The effects of different types of interlayer combinations on gas injection were studied by combining the physical model and numerical simulation methods. The results showed that the lithology of the interlayer in the lower Wuerhe formation of the 8th district was mainly mud-bearing fine gravel with microporosity, average porosity of 6.1% and permeability of 0.0043 mD. The interlayer gas injection breakthrough pressure and permeability were in a logarithmic linear relationship, and the lower limit of gas injection breakthrough under reservoir conditions was 0.003 mD. Initially, it is difficult to flood the upper remaining oil of the gas injection due to the blockage of the interlayer, while in the middle and late stage, the gas-liquid interface gradually reached stability with the increase in injected gas, which has little impact on the final recovery. These results indicate that it is feasible to carry out gas injection gravity flooding in this reservoir.

Colorectal cancer (CRC) is a common malignant tumor, and its incidence ranks third and mortality rate ranks second in the world. Cisplatin cannot target CRC cells and has notable toxicity, which significantly limits its clinical application. The emerging PEGylated nanodrug delivery system can improve circulation time and enhance tumor targeting. In this study, the HA-mPEG-Cis NPs were synthesized by self-assembly, which can target CD44-positive CRC cells and dissolve the PEG hydration layer responsive to the weakly acidic tumor environment. The average hydrodynamic diameter of HA-mPEG-Cis NPs was 48 nm with the polydispersity index of 0.13. The in vitro cisplatin release was in a pH-responsive manner. The HA-mPEG-Cis NPs group showed the highest apoptosis rate (25.1%). The HA-mPEG-Cis NPs exhibited antitumor efficacy via the PI3K/AKT/mTOR signaling pathway. The HA-mPEG-Cis NPs showed the lowest tumor volume and weight among all the groups in CT26 cell-bearing mouse model. The HA-mPEG-Cis nanodrug delivery system not only increases the stability and circulation time but also reduces the side effects of loaded cisplatin. Overall, the in vitro and in vivo experiments confirmed the satisfied antitumor efficacy of HA-mPEG-Cis NPs. Therefore, this study provides a rational design for application of pH-responsive HA-mPEG-Cis nanodrug delivery system in the future.

ObjectiveTo systematically evaluate the efficacy and safety of alectinib versus crizotinib in the treatment of anaplastic lymphoma kinase (ALK) positive non-small-cell lung cancer.MethodsStudies about the efficacy of alectinib versus crizotinib in the treatment of ALK-positive non-small cell lung cancer were searched in PubMed, Scopus, Embase and the Cocharane Library from inception to February 15, 2020. Two reviewers independently screened these studies, extracted the data, assessed the risk of bias in the included studies by using the Cochrane risk assessment tool, and then used review manager 5.3 software for meta-analysis.ResultsThree studies comprising a total of 697 patients with ALK-positive non-small cell lung cancer were included, 380 in the alectinib group and 317 in the crizotinib group. The dose of alectinib (300 mg) in J-ALEX were lower than the approved dose (600 mg), however the crizotinib group in all three studies received the recommended dose (250 mg). Performance bias was high in all three studies whereas, and the attrition bias was high in two studies (Toyoaki Hida 2017 and Solange peters 2017). The results of meta-analysis showed that: the overall response rate [OR = 2.07, 95% CI (1.41, 3.06), P = 0.0002], the progression free survival [HR = 0.34, 95% CI (0.21, 0.55), P

Photo-mixing with its advantages of ultra-large bandwidth and precise tunability has emerged as an important technique for terahertz (THz) wave generation. Recently, graphene photodetectors exhibiting a large bandwidth are expected to further boost the development of integrated THz emitters. Here, we fabricate a sub-THz emitter based on a large-bandwidth silicon–plasmonic graphene (SPG) photodetector integrated with a broadband rounded bow-tie THz antenna. The SPG sub-THz emitter is experimentally demonstrated to emit sub-THz waves with a radiation spectrum from 50 to 300 GHz. A maximum sub-THz emission power of 5.4 nW is obtained at 145 GHz with only 3 mW input light power. The SPG sub-THz emitter can be fabricated by a CMOS-compatible process, which offers enormous opportunities for its use in a variety of THz applications.

BackgroundLung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. At present, most patients with LUAD are diagnosed at an advanced stage, and the prognosis of advanced LUAD is poor. Hence, we aimed to identify novel biomarkers for the diagnosis and treatment of early stage LUAD and to explore their predictive value.MethodsThe microarray datasets GSE63459, GSE27262, and GSE33532 were searched, and the differentially expressed genes (DEGs) were obtained using GEO2R. The DEGs were subjected to gene ontology (GO) and pathway enrichment analyses using METASCAPE. A protein–protein interaction (PPI) network was plotted with STRING and visualized by Cytoscape. Module analysis of the PPI network was performed using MCODE. Overall survival (OS) analysis and analysis of the mRNA expression levels of genes identified by MCODE were performed with UALCAN. Western blot analysis of hub genes in LUAD patients, MTS assays, and clonogenic assays were performed to test the effects of the hub genes on cell proliferation in vitro.ResultsA total of 341 DEGs were obtained, which were mainly enriched in terms related to blood vessel development, growth factor binding, and extracellular matrix organization. A PPI network consisting of 300 nodes and 1140 edges was constructed, and a significant module including 15 genes was identified. Elevated expression of ASPM, CCNB2, CDCA5, PRC1, KIAA0101, and UBE2T was associated with poor OS in LUAD patients. In the protein level, the hub gene was overexpressed in LUAD patients. In vitro experiments showed that knockdown of the hub genes in the LUAD cell lines could promote cell proliferation.ConclusionsDEGs are potential biomarkers for early stage lung adenocarcinoma and could have utility for the diagnosis and predicting treatment efficacy.

The Mobei reservoir is a low-permeability-sandstone reservoir, due to differences in pore geometry, it can be divided into two independent reservoirs: A1 reservoir and A2 reservoir. For better understanding the water flooding development effects of Mobei reservoir, the mercury intrusion porosimetry, water flooding CT scanning and micro-CT scanning experiments are used in this study. The result shows that the reservoir has the strong heterogeneity which is weaken gradually from A1 reservoir to A2 reservoir. Reservoir pore radius is mainly distributed in the 100–200 microns, the throat radius is mainly distributed in the 1–3 micron. The water flooding core experiment in each reservoir shows a short water-free oil production period and rapid water cut after breakthrough. The A2 reservoir core flooding process is similar to piston displacement, the A1 reservoir core flooding process refers to the phenomenon (The fingering phenomenon in the process of core flooding in the A1 reservoir is obvious). The calculated water drive efficiency of the A2 reservoir is 61.2%, which is higher than 49.1% of the A1 reservoir. According to the CT scanning process, the Mobei oilfield has low micro displacement efficiency and the A1 reservoir has a smaller spread (sweep area) and higher residual oil saturation. Keywords: Low permeability reservoir, Oil displacement efficiency, CT scanning, Micro-CT, Mobei oilfield

Lithium-sulfur (Li-S) batteries can provide far higher energy density than currently commercialized lithium ion batteries, but challenges remain before it they are used in practice. One of the challenges is the shuttle effect that originates from soluble intermediates, like lithium polysulfides. To address this issue, we report a novel laminar composite, N,O-carboxymethyl chitosan-reduced graphene oxide (CC-rGO), which is manufactured via the self-assembly of CC onto GO and subsequent reduction of GO under an extreme condition of 1 Pa and −50 °C. The synthesized laminar CC-rGO composite is mixed with acetylene black (AB) and coated on a commercial polypropylene (PP) membrane, resulting in a separator (CC-rGO/AB/PP) that can not only completely suppress the polysulfides penetration, but also can accelerate the lithium ion transportation, providing a Li-S battery with excellent cyclic stability and rate capability. As confirmed by theoretic simulations, this unique feature of CC-rGO is attributed to its strong repulsive interaction to polysulfide anions and its benefit for fast lithium ion transportation through the paths paved by the heteroatoms in CC.

This paper investigates the station-keeping control of autonomous and remotely-operated vehicles (ARVs) for free-floating manipulation under model uncertainties and external disturbances. A modified adaptive generalized super-twisting algorithm (AGSTA) enhanced by adaptive tracking differentiator (ATD) and reduced-order extended state observer (RESO) is proposed. The ATD is used to obtain the smooth reference signal and its derivative. The RESO is used to estimate and compensate for the model uncertainties and external disturbances in real-time, which enhances the robustness of the controller. The modified AGSTA ensures the fast convergence of the system states and maintains them in a predefined neighborhood of origin without overestimating control gains. Besides, the proposed new variable gain strategy completely avoids the control gains vibrating near the set minimum value. Thanks to the RESO, the proposed controller is model-free and can be easily implemented in practice. The stability of the closed-loop system is analyzed based on Lyapunov’s direct method in the time domain. Finally, the proposed control scheme is applied to the station-keeping control of Haidou-1 ARV, and the simulation results confirm the superiority of the proposed control scheme over the original AGSTA.

Precise and reasonable evaluation of the multi-attribute value of medical system is the basis for hospitals to implement total quality management. Excellent medical system is necessary as a part of modern urban governance. However, most of medical value evaluation work relies on scale and artificial scoring at present, lacking in objectivity. Therefore, a scientific and comprehensive medical value evaluation system is needed urgently to give full play to the guiding role of value evaluation and promote the improvement of the medical service system. In this study, DEMATEL and information entropy are used to quantify the degree of mutual influence between system indicators and the differences in medical market performance respectively, so as to obtain the objective index weight. Hypertension has the highest incidence in the whole chronic disease system, which seriously affects people's daily life. Based on the existing hypertension diagnosis and treatment index system, a comprehensive and objective evaluation model is established to evaluate the hypertension diagnosis and treatment behaviors of different medical institutions, which achieves good result. This method has effectively improved the relative deficiency of one-sided subjective evaluation and has a great guiding significance for the comparison of treatment in departments and the economical use of medical resources.

The penetration and displacement behavior of N2 molecules in porous interlayer structures containing a water/salt component with porosities of 4.29%, 4.73%, 5.17%, 7.22%, and 11.38% were explored using molecular dynamics simulations. The results demonstrated that the large porosity of the interlayer structures effectively enhanced the permeation and diffusion characteristics of N2. The water and salt in the interlayer structures were displaced during the injection of N2 in the porosity sequence of 4.29% < 4.73% < 5.17% < 7.22% < 11.38%. The high permeance of 7.12 × 10−6 indicated that the interlayer structures with a porosity of 11.38% have better movability. The strong interaction of approximately 15 kcal/mol between N2 and H2O had a positive effect on the diffusion of N2 and the displacement of H2O before it reached a stable equilibrium state. The distribution of N2 in porous interlayer structures and the relationship between the logarithm of permeability and breakthrough pressure were presented. This work highlighted the effects of porosity on the permeability and diffusion of N2/H2O in the interlayer, thus providing theoretical guidance for the development of petroleum resources.

The purpose of this study was to discuss shape, scale and superimposed types of sandy gravel bodies in sandy-gravel braided distributary channel. Lithofacies analysis, hierarchy bounding surface analysis and subsurface dense well pattern combining with outcrops method were used to examine reservoir architecture patterns of sandy gravel braided distributary channel based on cores, well logging, and outcrops data, and the reservoir architecture patterns of sandy gravel braided distributary channels in different grades have been established. The study shows: (1) The main reservoir architecture elements for sandy gravel braided channel delta are distributary channel and overbank sand, while reservoir flow barrier elements are interchannel and lacustrine mudstone. (2) The compound sand bodies in the sandy gravel braided delta distributary channel take on three shapes: sheet-like distributary channel sand body, interweave strip distributary channel sand body, single strip distributary channel sand body. (3) Identification marks of single distributary channel include: elevation of sand body top, lateral overlaying, “thick-thin-thick” feature of sand bodies, interchannel mudstone and overbank sand between distributary channels and the differences in well log curve shape of sand bodies. (4) Nine lithofacies types were distinguished in distributary channel unit interior, different channel units have different lithofacies association sequence.

Understanding the nature of rail transit dwell time has potential benefits for both the users and the operators. Crowded passenger trains cause longer dwell times and may prevent some passengers from boarding the first available train that arrives. Actual dwell time and the process of passenger alighting and boarding are interdependent through the sequence of train stops and propagated delays. A comprehensive and feasible dwell time simulation model was developed and optimized to address the problems associated with scheduled timetables. The paper introduces the factors that affect dwell time in urban rail transit systems, including train headway, the process and number of passengers alighting and boarding the train, and the inability of train doors to properly close the first time because of overcrowded vehicles. Finally, based on a time-driven micro-simulation system, Shanghai rail transit Line 8 is used as an example to quantify the feasibility of scheduled dwell times for different stations, directions of travel and time periods, and a proposed dwell time during peak hours in several crowded stations is presented according to the simulation results.

Postoperative myocardial infarction (PMI) is one of the most serious complications of cardiac surgeries. No preoperative biomarker is currently available for predicting PMI after cardiac surgeries. In the present study, we used a phage display peptide library to screen potential preoperative peptide biomarkers for predicting PMI after coronary artery bypass grafting (CABG) surgery. Twenty patients who developed PMI after CABG and 20 age-, sex-, and body mass index-matched patients without PMI after CABG were enrolled as a discovery cohort. Another 50 patients who developed PMI after CABG and 50 randomly selected patients without PMI after CABG were enrolled as a validation cohort to validate the potential peptide biomarkers identified in the discovery cohort. Fifty randomly selected healthy volunteers were also enrolled in the validation phase as a healthy control group. In the discovery/screening phase, 17 out of 20 randomly selected phage clones exhibited specific reaction with purified sera IgG from the PMI group, among which 11 came from the same phage clone with inserted peptide sequence GVIMVIAVSCVF (named PMI-1). In the validation phase, phage ELISA showed that serum IgG from 90% of patients in the PMI group had a positive reaction with PMI-1; in contrast, only 14% and 6% of patients in the non-PMI group and the healthy control group had a positive reaction with PMI-1, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of the PMI-1 phage clone to preoperatively identify patients who would develop PMI after CABG were 90.0%, 86.0%, 86.5, 89.5% and 88.0%, respectively. The absorbance value of the PMI-1 phage clone showed statistically significant correlation with the peak postoperative serum cardiac troponin I level (r = 0.349, p = 0.012) in the PMI group. In conclusion, we for the first time identified a mimic peptide (PMI-1) with high validity in preoperative prediction of PMI after CABG.