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With the development of deep learning and machine learning, more new methods have been produced in the economic and financial fields. When talking about machines, one thing that comes to people’s minds is what they can do with machines to solve problems that need machines. The people in the stock market always want to find ways to forecast the stock trend, the pattern of stock, and the stock value. Before the development of machine learning algorithms, stock market predictions could be made in limited ways, and those methods usually did not produce accurate predictions. However, machine learning algorithms changed the phenomenon and offered people novel ways to analyze the stock market. This paper will discuss three research in which authors have implemented machine learning algorithms into stock market analyses. From analyzing the research, this paper tries to investigate the extent of applying machine learning algorithms in the stock market and how the algorithms have helped investors make improvements in stock market analysis.

Radio frequency interference (RFI) is a significant challenge faced by today's radio astronomers. While most past efforts were devoted to cleaning the RFI from the data, we develop a novel method for categorizing and cataloguing RFI for forensic purpose. We present a classifier that categorizes RFI into different types based on features extracted using Principal Component Analysis (PCA) and Fourier analysis. The classifier can identify narrowband non-periodic RFI above 2 sigma, narrowband periodic RFI above 3 sigma, and wideband impulsive RFI above 5 sigma with F1 scores between 0.87 and 0.91 in simulation. This classifier could be used to identify the sources of RFI as well as to clean RFI contamination (particularly in pulsar search). In the long-term analysis of the categorized RFI, we found a special type of drifting periodic RFI that is detrimental to pulsar search. We also found evidences of an increased rate of impulsive RFI when the telescope is pointing toward the cities. These results demonstrate this classifier's potential as a forensic tool for RFI environment monitoring of radio telescopes., Comment: 15 pages, 19 figures

Online multi-object tracking is a process of extending multi-object trajectories with only past information. In this process, tracking drift, missing detection, and occlusion among objects are common problems. To address the problem of tracking drift, in this paper, a detector–tracker integration framework is proposed and the framework includes the linear regression model (LRM) that can detect and track objects simultaneously. The two kinds of results are combined using LRM to suppress tracking drift. Moreover, to overcoming missing detection and the occlusion, a structural similarity calculation based on the attention mechanism is proposed. The attention mechanism is utilized to learn the discriminative features of each object, and a structural similarity calculation are used to improve the ability to extend the objects’ trajectories. Based on these, we design a multi-object tracking strategy, enabling the trajectory’s initialization, extension, and termination. Finally, experiments and analysis are executed on MOT16 and MOT17 benchmarks datasets, and the proposed method obtains multi-object tracking accuracy of 60%.

Space-time prism is a fundamental concept in time geography that can model an individual's accessibility to resources under space-time constraints. A prism anchor is often defined by work, school, or home activity with a fixed location and schedule. Trips and other activities are relatively flexible and scheduled between prism anchors. This fixity-flexibility dichotomy may not capture the increasing complexity of human mobility behaviors or variations among individuals. Recent developments in location-aware technologies allow us to collect person-level mobility data with detailed space-time paths and contextual information. This article develops methods to extract prism anchors from these GPS-based survey data and examines whether home, work, and school activities can always be used to define prism anchors for everyone. To illustrate our methods, we use data collected in Minnesota and Beijing as two study cases. Results in both study cases suggest that not everyone has home, work, or school anchors, and people with the same socio-demographic background tend to have similar anchor types. By deriving home, work, and school anchors, we can better understand how a person's everyday schedules are governed by home, work, and school and refine person-based accessibility measures.

Carbapenem-resistant Enterobacter cloacae complex (CRECC) has increasingly emerged as a major cause of healthcare-associated infections, with colistin being one of the last-resort antibiotics of treatment. Mobile colistin resistance (mcr)-9 is a member of a growing family of mcr genes and has been reported to be an inducible gene encoding an acquired phosphoethanolamine transferase. Here, we collected 24 ECC strains from Chongqing, China from 2018 to 2021. Subsequently, antibiotic resistance genes and the transmission dynamics of the strains were determined by PCR, whole-genome sequencing, and bioinformatic analysis. The mcr-9 was identified in IncHI2/2A or IncHI2/2A + IncN plasmids from six CRECC strains and was co-located with blaNDM-1 or blaIMP-4 in 2/6 plasmids. The genetic environment of mcr-9.1 was composed of IS903B-mcr-9.1-wbuC-IS26 in the five mcr-9.1-harboring-plasmid, but IS1B was located downstream of mcr-9.2 in the pECL414-1 sequence. We also found that the pNDM-068001 plasmid carrying mcr-9.1 could be a hybrid plasmid, formed by a Tn6360-like blaNDM-1 region inserted into an mcr-9.1-positive IncHI2/2A plasmid. A conjugation assay showed that plasmids mediated the co-dissemination of mcr-9 and metallo-β-lactamase (MBL) genes. In addition, we performed induction assays with sub-inhibitory concentrations of colistin and found an increase in the relative expression levels of the mcr-9.2, qseC, and qseB genes, as well as an increase in the minimum inhibitory concentration values of colistin in the CRECC414 strain. These findings provide a basis for studying the regulatory mechanisms of mcr-9 expression and highlight the importance of effective monitoring to assess the prevalence of MBL and mcr-9 co-existing plasmids.

Carbapenem-resistant

Coronavirus disease 2019 (COVID-19) caused by coronavirus-2 (SARS-CoV-2) infection has rapidly spread throughout the world and become a major threat to human beings. Cytokine storm is a major cause of death in severe patients. Abatacept can suppress cytokines used as antirheumatic drugs in clinical applications. This study analyzed the molecular mechanisms of abatacept treatment for COVID-19. Differentially expressed genes (DEGs) were identified by analyzing expression profiling of abatacept treatment for rheumatoid arthritis (RA) patients and SARS-CoV-2 infection patients. We found that 59 DEGs were upregulated in COVID-19 patients and downregulated following abatacept treatment. Gene set enrichment analysis (GSEA) and Gene Ontology (GO) analysis showed that immune and inflammatory responses were potential regulatory mechanisms. Moreover, we verified 8 targeting genes and identified 15 potential drug candidates for the treatment of COVID-19. Our study illustrated that abatacept could be a promising property for preventing severe COVID-19, and we predicted alternative potential drugs for the treatment of SARS-CoV-2 infection.

Background: Previous studies have partly explored the role of B-cell CLL/lymphoma 7 protein family member B (BCL7B) in tumorigenesis and development. However, the prognosis and immunoregulatory value of BCL7B in pan-cancer patients remains unclear.Methods: Through The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, the distinct expression of BCL7B gene in 33 tumors and adjacent normal tissues was analyzed. The Kaplan–Meier method (univariate Cox regression analysis and Kaplan–Meier curve) was used to identify the cancer types whose BCL7B gene expression was related to prognosis. The receiver operating characteristic (ROC) curve was used to elucidate the diagnosis value of BCL7B gene. Spearman’s rank correlation coefficient was used to explore the relationship between BCL7B gene expression and immune cell infiltration, immune checkpoints, DNA methylation, DNA repair genes, immune-activating genes, immune-suppressing genes, immune subtypes, tumor mutation burden (TMB), and microsatellite instability (MSI). The Wilcoxon rank sum test and Kruskal–Wallis test were used to compare the expression of BCL7B gene in tumor tissues with different clinicopathological features. Gene set enrichment analysis (GSEA) was conducted to identify the tumor-related pathways in pan-cancer. The Human Protein Atlas (HPA) database was used to verify the BCL7B gene expression at the protein level.Results: High expression of BCL7B was associated with an inferior prognosis in glioblastoma multiforme (GBM), glioma (GBMLGG), kidney chromophobe (KICH), brain lower grade glioma (LGG), oral squamous cell carcinoma (OSCC), rectum adenocarcinoma (READ), and uveal melanoma (UVM). Low expression of BCL7B was associated with a poor prognosis in kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), skin cutaneous melanoma (SKCM), thyroid carcinoma (THCA), and sarcoma (SARC). The BCL7B gene expression had varying degrees of correlation with 24 immune cell subsets in 37 tumor environments such as adrenocortical carcinoma (ACC) and bladder urothelial carcinoma (BCLA). Spearman’s rank correlation coefficient showed that BCL7B gene expression had different degrees of correlation with 47 immune checkpoints, 46 immune-activating genes, 24 immune-suppressing genes, 5 DNA repair genes, and DNA methylation, TMB, and MSI in 39 tumors. GSEA suggested that BCL7B was notably associated with cancer-related and immune-related pathways.Conclusion: In summary, BCL7B gene has a high diagnostic and prognostic value in pan-cancer and is related to the infiltration of 24 immune cell subsets in pan-cancer.

Improper sludge treatment will cause serious environmental problems, and sludge drying is the key to effective treatment. Almost all the existing sludge drying technologies use heating to overcome the great latent heat of moisture vaporization, which leads to high drying energy consumption. In this study, based on the particle high-speed self-rotation in the cyclone and micro-interface oscillations, the cyclone self-rotation drying (CSRD) technology was developed. It can realize drying of the dewatered landfill sludge (DLS) and the urban sewage dewatered sludge (UDSS) with mainly non-phase change. The obtained results reveal that at low carrier gas temperatures (100 °C) and very short residence time (15 s), the moisture content of the DLS decreased from 53% to 6.85%, and that of the UDSS decreased from 67% to 18.92%. Through calculation, the proportions of moisture non-phase change removal during the CSRD process touched 68.94% and 63.39%, respectively. Based on the experimental studies, we proposed an enlarged industrial application program (50 t/d) for the UDSS drying by employing the CSRD technology. The operating cost was 159.69 CNY/t H

Delineating life circles is an essential prerequisite for urban community life circle planning. Recent studies combined the environmental contexts with residents’ global positioning system (GPS) data to delineate the life circles. This method, however, is constrained by GPS data, and it can only be applied in the GPS surveyed communities. To address this limitation, this study developed a generalizable delineation method without the constraint of behavioral data. According to previous research, the community life circle consists of the walking-accessible range and internal structure. The core task to develop the generalizable method was to estimate the spatiotemporal behavioral demand for each plot of land to acquire the internal structure of the life circle, as the range can be delineated primarily based on environmental data. Therefore, behavioral demand estimation models were established through logistic regression and machine learning techniques, including decision trees and ensemble learning. The model with the lowest error rate was chosen as the final estimation model for each type of land. Finally, we used a community without GPS data as an example to demonstrate the effectiveness of the estimation models and delineation method. This article extends the existing literature by introducing spatiotemporal behavioral demand estimation models, which learn the relationships between environmental contexts, population composition and the existing delineated results based on GPS data to delineate the internal structure of the community life circle without employing behavioral data. Furthermore, the proposed method and delineation results also contributes to facilities adjustments and location selections in life circle planning, people-oriented transformation in urban planning, and activity space estimation of the population in evaluating and improving the urban policies.

The ice thermal parameters are the key to reasonably simulating ice phenology, distribution, and thickness, but they have always been a “vulnerable group” in ice research. Technically, it may seem simple to obtain accurate ice thermal property parameters, but in reality, there are numerous impact factors, requiring a rigorous research process. In the 1980s, the thermal conductivity of ice was explored in the field and laboratory, after which there has been no significant progress in China. In this century, mathematics is introduced, after which the inversion identification and analysis with the time-series data of the vertical temperature profiles of ice layers by in situ testing are carried out. The in situ thermal diffusivities of different natural ices were obtained and cross-validated with the inversion identification results. Both natural freshwater ice and sea ice exhibited differences in the thermal diffusivity of the pure ice chosen for the current simulations due to impurities within the unfrozen water among the ice crystals, but the trends are consistent with the results of a small number of laboratory tests on different types of saltwater frozen ice. In this paper, the inversion identification results of the thermal diffusivity of typical ice were selected, and the factors constraining the thermal diffusivities were analyzed. The importance of parameterizing the thermal diffusivity in the phase transition zone of ice under the trend of global warming was illustrated. Future research ideas on the physical mechanism, application value, and parameterization scheme of the thermal diffusivity of natural ice were envisaged.

Unfrozen free and non-free water between ice crystals in flat and hummock ice in the Yellow River exists as water films with varying contents based on ice temperature. These contents can affect the radar wave velocity of the ice despite its theoretical dependence on the crystal structure and ice body components. The unfrozen water content in ice depends on the ice temperature, which is controlled by the air temperature, solar radiation, and ice thickness. Winter air temperature and radar-detected ice thickness data observed at the Shisifenzi bend in the Yellow River from 2020 to 2021 were analyzed. The unfrozen water content in the ice was the primary factor influencing the accuracy of flat ice thickness detection. The heat flux at the ice–water interface in the Yellow River was determined. The evolution of ice thickness and temperature were simulated using a one-dimensional (1D) ice thermodynamic model forced by the local weather station data (i.e., air temperature, solar radiation, wind speed, and cloud cover). On this basis, the measured ice thickness data of 13 drill holes were combined to calculate 1251 thermodynamically simulated ice thicknesses consistent with the ice thickness detection time of the radar; therefore, statistical relationships regarding the influence of air temperature and the combined action of air temperature and ice thickness on the radar wave velocity in granular and columnar ice during air temperature increases and decreases were determined. Finally, the statistical relationship between the combined influence of air temperature and ice thickness on radar wave velocity was selected as a parameterization scheme to dynamically correct the radar wave velocity of flat ice. To enhance the radar detection accuracy for flat ice thickness, the radar wave velocity of ice was parameterized as a function. Given the presence of unfrozen frazil ice and accumulated broken ice blocks in the Yellow River, radar is suggested to detect the thickness of different types of ice in future research.

Background To compare the gait patterns between posterior cruciate retention and substitution in total knee arthroplasty (TKA). Methods Electronic databases including the PubMed, Embase, CINAHL, Web of Science, and Cochrane databases were searched to identify clinical trials investigating posterior cruciate retention versus substitution in TKA. The outcome measurements were the kinematic gait parameters (flexion at heel strike, maximum flexion during loading response, flexion range during loading, minimal flexion at terminal stance, maximal flexion at the swing, and total flexion during the gait cycle), Knee Society Score (KSS), knee flexion, knee extension, and walking speed. Statistical software Review Manager 5.4 and Stata 14.0 were used for data analysis. Results There were finally 9 studies included in this meta-analysis. The results did not reveal differences between posterior cruciate retention (CR) and posterior cruciate substitution (PS) groups in TKA, in terms of kinematic gait parameters, knee extension, walking speed, and KSS. However, the PS group had a significantly larger knee flexion angle than that in the CR group [weighted mean difference = − 3.20, 95% CI − 6.13 to − 0.28, P = 0.03]. Conclusion Both the posterior cruciate retention and posterior cruciate substitution lead to obvious improvements in patient function and have their advantages in getting a good cup position. The PS design is significantly better on the knee flexion, while there are no statistical differences in kinematic gait parameters and outcome scores between them. This might indicate that surgeons do not necessarily need a PS design to substitute the posterior cruciate ligament during TKA.

Background: The aim of this study was to investigate the characteristics of carbapenem-resistant Klebsiella pneumoniae (CRKP) ST76 isolates collected during an outbreak in a hospital's intensive ca...

SKINNY is a tweakable lightweight block cipher algorithm. In order to test its security, this paper performs optimal differential trail search analysis on all SKINNY-64 versions under single-key setting based on the MILP (Mixed Integer Linear Programming) algorithm. Firstly, SKINNY round function is abstracted equivalently by precise constraints, and the objective function is set as the minimum number of active S-box number to optimize SKINNY-64 MILP model. Experiments show the differential trail searched by this method is not necessarily optimal. In order to directly search for the optimal differential trail, the S-box differential probability coding information is added to the optimized SKINNY-64 MILP model, the S-box differential characteristic is reconstructed, and the objective function is set to the minimum value of the probability coding information, which improves the SKINNY-64 MILP model. The results of experimental show that the improved MILP model can directly search for the optimal differential trail, and the complexity is slightly increased, but the search efficiency is significantly improved. Under single-key setting, this method has obvious advantage in searching the optimal differential trails of SKINNY-64 with low round number.

This study aimed to investigate the efficacy of colistin both alone and in combination with either meropenem or levofloxacin against CRAB clinical isolates. The OXA carbapenemase genes and multiloc...

Apple latent spherical virus (ALSV) is a latent virus with wide host range of plant species. In the present study, we prepared ALSV vectors expressing RNA silencing suppressors (RSSs) from eight plant viruses: P19 of carnation Italian ring spot virus (tombusvirus), 2b of peanut stunt virus (cucumovirus), NSs of tomato spotted wilt virus (tospovirus), HC-Pro of bean yellow mosaic virus (potyvirus), γb of barley stripe mosaic virus (hordeivirus), P15 of peanut clump virus (pecluvirus), P1 of rice yellow mottle virus (sobemovirus), or P21 of beet yellows virus (closterovirus). These vectors were inoculated to Nicotiana benthamiana to investigate the effects of RSSs on the virulence and accumulation of ALSV. Among the vectors, ALSV expressing NSs (ALSV-NSs) developed severe mosaic symptoms in newly developed leaves followed by plant death. Infection of ALSV-γb induced characteristic concentric ringspot symptoms on leaves, and plants infected with ALSV-HC-Pro showed mosaic and dwarf symptoms. Infection of the other five ALSV vectors did not show symptoms. ELISA and immunoblot assay indicated that virus titer increased in leaves infected with ALSV-NSs, γb, HC-Pro, or P19. RT-qPCR indicated that the amount of ALSV in plants infected with ALSV-NSs was increased by approximately 45 times compared with that of wtALSV without expression of any RSS. When ALSV-P19, NSs, or HC-Pro was inoculated to Cucumis sativus plants, none of these ALSV vectors induced symptoms, but accumulation of ALSV in plants infected with ALSV-NSs was increased, suggesting that functions of RSSs on virulence and accumulation of ALSV depend on host species.

The simplified governing equations of applied mechanics play a pivotal role and were derived based on ingenious assumptions or hypotheses regarding the displacement fields for specific problems. In this paper, we introduce a data-driven method by the name AI-Timoshenko in honor of Timoshenko, father of applied solid mechanics, to automatically discover simplified governing equations for applied mechanics problems directly from discrete data simulated by the three-dimensional (3D) finite element method. The simplified governing equations are in variational form, which is compact and advantageous for data-driven discovery. AI-Timoshenko liberates applied mechanicians from burdensome labor, including assumptions, derivation, and trial and error. The simplified governing equations for Euler–Bernoulli and Timoshenko beam theories are successfully rediscovered using the present AI-Timoshenko method, which shows that this method is capable of discovering simplified governing equations for applied mechanics problems.

The decision tree is a common machine learning algorithm. Decision tree model theory is often used for classification and prediction. It focuses on inferring classification rules represented by a decision tree from a group of irregular cases. In this paper, the decision tree model was used to analyze the common surgical movements. Firstly, the surgical process and the common basic movements were observed and analyzed. Secondly, each movement was decomposed, and the data set was obtained by analyzing and sorting the finger posture and force form respectively. Finally, the corresponding decision tree model was obtained by machine learning, to obtain the classification of surgical hand movements.

An algorithm of laser curve segmentation for a train wheelset based on an encoder- decoder network is proposed. Aiming at the rich local features and simple semantic features of the train wheelset laser curve image, a neural network with shallow depth, high resolution, and good detail performance was designed. The proposed neural network makes full use of the dense connection mechanism and the upsampling module to enhance feature reuse and feature propagation. It can extract context semantic information at multiple scales with fewer parameters. Experimental results show that the encoder-decoder network has better performance than other neural networks in laser curve extraction of train wheelset. Based on the encoder-decoder neural network, mIOU, Recall, Accuracy, and F1_score of the laser curve dataset of the train wheelset, the score index reached 86.5%, 89.2%, 99.9%, and 85.0%, which can accurately extract the laser stripe of the train wheelset. Additionally, the encoder-decoder network can diminish the influence of noise on the extraction of laser fringes of a train wheelset to a certain extent. Therefore, it has good application in railway safety.

Background: Sodium acetate is one of the important nutrients that regulate milk fat synthesis in bovine mammary epithelial cells (BMECs), and it regulates milk fat synthesis mainly through the SREBP1 pathway. Our previous study has showed that TATA element modulatory factor 1 (TMF1) may be interacts with SREBP1 and regulates the sodium acetate-dependent milk synthesis in BMECs, but the underlying mechanism is unclear. In the current study, the effect of TMF1 on sodium acetate activated milk fat synthesis in BMECs was assessed. Results: Overexpressing or inhibiting TMF1 demonstrated that TMF1 negatively regulated sodium acetate activated sterol regulatory element-binding protein 1 (SREBP1) pathway and milk fat synthesis; Overexpressing or inhibiting SREBP1 showed that TMF1 inhibited sodium acetate activated milk fat synthesis through SREBP1 pathway; Co-immunoprecipitation analysis showed that TMF1 interacted with SREBP1; Nuclear localization of SREBP1 analysis showed that sodium acetate activated nuclear localization of SREBP1 was inhibited by TMF1; Depletion or supply sodium acetate demonstrated that sodium acetate negatively regulated expression of TMF1 and the interaction between TMF1 and SREBP1. Conclusions: Together, these results indicate that TMF1 is a negative regulatory factor for sodium acetate activated milk fat synthesis, it induced expression by sodium acetate depletion, and interacts with SREBP1 in cytoplasmic, prevents the nuclear localization of SREBP1 and then suppresses the expression of SREBP1 target gene and subsequent milk fat synthesis in BMECs.

To solve the problems of time consuming, labor consuming and low efficiency in traditional geometric measurement methods, a real-time online measurement system for the electrical parameters of DBD (Dielectric Barrier Discharge) type ozone generator is designed in this paper. With this system, the accuracy and efficiency of electrical parameter measurement are greatly improved. First, the design idea of the proposed measurement system is introduced in detail from hardware circuit systems such as the controller unit circuit, signal detection circuit as well as software systems like data processing unit and result output. Second, the key points of voltage and current of DBD ozone generator at different moments are collected in real time by setting up the experiment platform of real-time online measurement system, and dielectric barrier capacitance, air gap capacitance and discharge power of DBD ozone generator are rapidly calculated. Then, based on the comparison method, the efficiency and accuracy of the main characteristic discharge parameters are verified experimentally. The experimental data show that the realtime online measurement system designed in this paper is more stable than the traditional manual calculation method, and the efficiency is improved by at least two orders magnitude. Finally, the online measurement system is briefly summarized.

BCL7B plays a potential role in the progression of various cancers, while its role in sarcomas is unknown. We aimed to evaluate BCL7B's diagnostic and prognostic value, and potential BCL7B-related mechanisms in sarcomas based on The Cancer Genome Atlas (TCGA) database. We collected patients with sarcoma from TCGA. Wilcoxon rank sum test was used to compare the expression of BCL7B in sarcoma samples with different clinical-pathologic features. Univariate Cox regression analysis and multivariate Cox regression analysis were used to evaluate prognosis factors for sarcoma. Gene set enrichment analysis (GSEA) was conducted to elucidate the significant functions and pathways associated with BCL7B. BCL7B was a potential biomarker for distinguishing normal and tumor tissues with the analysis of ROC curve (AUC = 0.588). Low BCL7B expression was significantly correlated with tumor multifocal (OR = 0.39 for yes vs no), larger residual tumor (OR = 0.40 for R1,R2 vs RO), male gender (OR = 0.48 for male vs female) and White race (OR = 0.29 for White vs Asian, Black or African American). High BCL7B expression was correlated with leiomyosarcoma histological type (OR = 6.08 for leiomyosarcoma vs dedifferentiated liposarcoma, pleomorphic sarcoma). Univariate and multivariate Cox regression analysis showed that low BCL7B expression was independently associated with poor overall survival (P = .008). GSEA showed that GPCR (G protein-coupled receptors) ligand binding, secreted factors, class A1 rhodopsin-like receptors, extracellular matrix organization, core matrisome, Fc epsilon receptor I mediated NF-κB activation, and WNT signaling pathway were differentially enriched in BCL7B low expression phenotype (|NES| > 1, adjusted P value

The micro-arc oxidation coating was prepared on the surface of the amorphous zirconium sheet, and the influence of frequency on the micro-arc oxidation coating of the Zr-based amorphous alloy was studied. The results show that the change of the frequency of the electrical parameters of the micro-arc oxidation in the silicate micro-arc oxidation bath will promote the transformation of the t-ZrO2 phase to the m-ZrO2 phase in the coating; the frequency affects the gap, uniformity and thickness of the coating. When the frequency is 400 Hz, the coating surface has small voids and no cracks, and the thickness reaches a maximum of 15 μm. With the increase of frequency, the weight loss of the amorphous zirconium micro-arc oxidation coating first decreases and then increases. The wear resistance can be improved.

Poyang Lake is the largest freshwater lake in China and one of the most important wetlands in the world. Wetland biomass is a key index to weigh the healthiness of wetland ecosystem. Polarimetric information can significantly improve wetland vegetation biomass inversion. In this study, 4 scenes of RADARSAT-2 PolSAR data in year 2011, 2013, 2015 and 2016 were used to estimate the above-ground-biomass (AGB) for the Poyang Lake Wetland. For this purpose, polarimetric decomposition components and a simplified Water-Cloud Model (WCM) were used. The parameters of the simplified WCM were retrieved using the field measurements and the polarimetric decomposition components. Finally, the relationship between the estimated AGB and measured AGB was assessed and the vegetation biomass distribution in year 2011, 2013, 2015 and 2016 were also mapped.

Silicon (Si), germanium (Ge), and gallium arsenide (GaAs) are familiar semiconductors that always act in the role of optical dielectrics. However, these semiconductors also have plasmonic behaviors in ultraviolet (UV) ranges due to the strong interband transitions or valence electrons. And few studies are aimed at investigating plasmonic properties in the semiconductor at the nanoscale. In this work, we discuss UV plasmonics and sensing properties in single and dimer Si, Ge, and GaAs triangular prism meta-antenna systems. The results show that obvious local surface plasmon resonances (LSPRs) can be realized in the proposed triangular prism meta-antennas, and the resonant wavelength, electromagnetic field distribution, surface charge distribution, and surface current density can be effectively tuned by structural and material parameters. In addition, we also find that the Si triangular prism meta-antenna shows more intense plasmonic responses in UV ranges than that in the Ge or GaAs triangular prism nanostructures. Especially, the phase difference between the triangular prism nanostructure and light source can effectively regulate the symbol and value of the surface charge. Moreover, the great enhancement of electric field can be seen in the dimer triangular prism meta-antennas when the distance of the gap is gnm, especially g=1 nm. The most interesting result is that the maximum of refractive index sensitivity s and figure of merit (FoM) are greatly enlarged in dimer triangular prism meta-antennas. Particularly, the sensitivity can reach up to 215 nm/RIU in the dimer GaAs triangular prism meta-antennas, which is improved more than one order of magnitude. These research results may play important roles in applications of the photo detecting, plasmonic sensing and disinfecting in UV ranges.

This study aimed to investigate the efficacy of colistin both alone and in combination with either meropenem or levofloxacin against CRAB clinical isolates. The OXA carbapenemase genes and multilocus sequence typing were detected after 35 CRAB isolates biochemical identification. Then, the minimum inhibitory concentrations, minimum bactericidal concentrations, antibiotic interactions of the test antibiotics, and synergistic effects were determined by the checkerboard method and time-kill assays. The chromosomal gene

Background Enterobacter cloacae is an emerging opportunistic pathogen. We retrospectively conducted a study to assess antimicrobial susceptibility and investigated the Molecular characteristics of carbapenem-resistant Enterobacter cloacae (CREL) isolates. Methods Three hundred forty-two isolates of Enterobacter cloacae were collected from January 2014 to December 2018. Ten strains of CREL were collected for further research. The species identifications and minimum inhibitory concentrations (MICs) of all antibiotics tested were analyzed using the Vitek 2 Compact system (BioMerieux, France) and supplemented by the disk diffusion method. Polymerase chain reaction (PCR) was performed to detect extended-spectrum β-lactamase (ESBL) and carbapenemase resistance genes. Results The results showed that most of the isolates remained susceptible to tested antibiotics; however, the resistance rate of Cefepime has been increasing in recent years. One strain co-producing New Delhi Metallo-β-lactamase NDM-1 and Imipenem hydrolase IMP-4. NDM-1 and IMP-4-producing isolates highlight that active surveillance is necessary to prevent the further spread of the bacteria. Multilocus sequence typing (MLST) showed that two KPC-producing isolates assigned to ST93, two isolates carrying NDM-1 assigned to ST1120. Moreover, the MEGA analysis showed that ST93, ST256, and ST1120 have homology, showing that CREL in our area has a potential spread risk. Conclusions These findings indicating that CREL clonal dissemination may occurred in this region and should be taken seriously concern. Our study highlights an urgent need to monitor these isolates to prevent their further spread.

We study dual-Fano resonances and its sensing properties in a crossed ring-shaped metasurface by use of the finite-different time-domain (FDTD) simulation. The results show that the dual-Fano resonances in the proposed crossed ring-shaped metasurface are caused by the interaction among three local surface plasmon resonances (LSPRs), and the spectra of dual-Fano resonances can be tuned by the radius of the circular ring (CR) nanostructure, the distance between the center of the two CRs in x direction, and the polarization of the incident light. Interestingly, single Fano resonance splits into dual-Fano resonances in the case of asymmetric ring structure arrangement or non-y-axis polarized incident or the distance d

Background There is increasing resistance to carbapenems among Klebsiella pneumoniae,and fluoroquinolones (FQ) are increasingly used to treat infections from extended-spectrum β- lactamase(ESBLs) and carbapenemase-producing Klebsiella pneumoniae. However, the acquisition of plasmid-mediated quinolone resistance (PMQR) or the spontaneous mutation of the quinolone resistance-determining regions (QRDR) of the gyrA and parC genes can severely affect the therapeutic effect of quinolones. The goal of this study was to investigate the molecular determinants of FQ resistance(FQ-R) in carbapenem-resistant Klebsiella pneumoniae (CRKP) isolates from Heilongjiang Province,China. Materials and methods We isolated 40 strains of CRKP from a treatment center in the eastern part of Heilongjiang Province from January 2016 to December 2018. The VITEK2 Compact analyzer was used to identify and detect drug sensitivity. Different types of drug resistance genes were detected by polymerase chain reaction (PCR). PCR and DNA sequencing were used to assess the presence of qnrA, qnrB, qnrS,qepA and acc(6′) Ib-cr genes,which are plasmid-encode genes that can contribute to resistance. The sequences of gyrA and parC genes were sequenced and compared with the sequences of standard strains to determine if mutations were present.Multi-site sequence typing (MLST) and pulsed-field gel electrophoresis (PFGE) were performed on the strains to assess homology. Results The isolated CRKP strains showed rates of resistance to fluoroquinolones of 22.5% to 42.5%. The resistance rate of ciprofloxacin was significantly higher than that of levofloxacin.Nine CRKP strains (22.5%) showed co-resistance to ciprofloxacin and levofloxacin.The quinolone resistant strains were screened for plasmid-encoded genes that can contribute to resistance (PMQR genes).Among the 17 quinolone resistant strains,one strain contained no PMQR genes,twelve strains contained two PMQR genes,and four strains contained four PMQR genes.Acc (6′) Ib-cr was the most frequently detected PMQR gene, detected in 95% of strains tested (38 of 40) and in 94.1% of the quinolone-resistant strains (16 of 17). The qepA gene encoding an efflux pump was not detected in any strains.No isolate carried five different PMQRs simultaneously.Changes of S83I and D87G changes in gyrA, and the S80I change in parC,which were mediated by QRDR,were identified in two isolates,which showed resistance to both ciprofloxacin and levofloxacin.Most of the FQ-R strains(58.8%,10/17) belong to ST(sequence type) 76, which is dominant in the local area, while all the mutant strains (100%,2/2),that differ in at least one site from standard bacteria, belong to the ST11 group. The strains were isolated from a hospital where there had been a recent outbreak of ST76 type CRKP in the neurosurgery ward and intensive care unit. Conclusion CRKP strains were identified that were insensitive or even resistant to quinolones,and this resistance is common in Heilongjiang Province of eastern China;fluoroquinolone-resistance in these clinical CRKP strains is a complex interplay between PMQR determinants and mutations in gyrA and parC.The resistance level caused by QRDR mutation is higher than that caused by PMQR, however, the high frequency of PMQR genes in the isolated CRKP strains suggests the potential for impact of these genes.PMQR determinants are often found in carbapenemase-producing or ESBLs-producing Klebsiella pneumoniae,and some resistance genes,such as:SHV,TEM, CTX-M-15,and OXA-1 are closely associated with FQ-R. Finally, geographical factors can affect the emergence and spread of PMQR and QRDR.Some genetic lineages have higher potential risks, and continuous close monitoring is required.

Additional file 1. The plasmid sequence with NDM

With the rapid development of e-commerce platforms, how to quickly sort out and summarize a large number of product reviews on e-commerce websites has become an urgent problem. Product attribute extraction is one of the methods to solve this problem. Automatic extraction of product attributes is one of the important research contents in the field of natural language processing. A product attribute extraction method based on affinity propagation clustering algorithm and pointwise mutual information pruning is proposed to extract product attributes comprehensively and rapidly. Firstly, candidate product attribute sets are obtained from the corpus according to predefined syntactic rules. Then, the candidate product attribute sets are represented by word vectors and calculating the similarity of attribute words to cluster the candidate attribute sets. Thus the candidate attribute clusters are obtained. At last, the effectiveness of the method is proved in a Chinese product review.

Extensive literature has investigated the impacts of different influencing factors on home-work separation in urban China. However, most studies have adopted a cross-sectional design, which provides little direct evidence on changing trends in these effects in the context of rapid urban transformation. This study examined the 10-year changes in the factors influencing home-work separation in Beijing. By drawing on community surveys conducted in 2007 and 2017, we constructed two regression models under the same framework, considering the implications of sociodemographic, built environment and institutional factors on home-work separation in the respective year. A t-test was employed to compare the effects of the same factors on home-work separation between the 2007 and 2017 models. We found that the relationships between the influencing factors and residential home-work separation changed substantially from 2007 to 2017, indicating dramatic urban transformations in Chinese cities. Specifically, the effects of the built environment measured by population density and jobs-to-housing ratio became stronger, reflecting the rapid urban expansion and suburbanization of Chinese cities. The effect of danwei system became weaker due to the removal of the housing provision responsibility of danwei as well as the dissolution of existing danwei. The direction of the effect of hukou changed from negative to positive because of the relaxation of the hukou system. In addition, the effects of sociodemographic attributes changed. The effects of socioeconomic attributes reflecting the market force such as income and education level became stronger, while the effects of demographic attributes related to social role such as gender and age became weaker. We further discuss the debate on institutional constraints and the legacy of danwei, the transformations in Chinese cities, and the implications for policymaking aiming to reduce home-work separation.