An Aging Giant At The Center of Global Warming: Population Dynamics and Its Effect on CO2 Emissions in China

Managing the aging crisis and mitigating CO2 emissions are currently two great challenges faced by China. Revealing the complex correlation between aging and CO2, and projecting their future dynamics are fundamentally necessary to inform effective strategies and policies toward a low-carbon and sustainable development in China. In this paper, we quantitatively investigated the impacts of population aging, economy, and energy intensity on CO2 emissions through a STIRPAT model based on balanced provincial panel data from 1995-2019, and employed a cohort model and scenario analysis to project the demographic change and CO2 emissions till 2050. It is found that CO2 emissions in China has witnessed a significant growth during 1995-2019, and will exhibit an inverted U-shaped growth till 2050 with its peak appears between 2030-2040. Every 1% increase of aging will exert a 0.69% emission of CO2 in China. However, a big regional difference was also detected as aging contributed to CO2 reduction in the eastern region, but stimulated CO2 emissions in the central and western regions. Policy implications for achieving a low-carbon and aging-oriented sustainable development include the integration of aging into the decision-making of industrial structure upgrading and CO2 emission reduction in both national and region levels, the promotion of the further transition to low-carbon consumption and green products in the eastern region, and strengthening the deep fusion of aging-oriented industries with local resource and environmental endowment in the central and western regions such as the development of eco-agriculture and green pension industries.

Correlation Research Between Gondola Car Body Structure And Weld Stress Based On Asymmetry Coefficient

In order to find out the root cause of cross bearer welds’ cracks on the general purpose gondola cars, the relationship between asymmetric structure and stress distribution is studied in this paper. Firstly, the concept of asymmetry coefficient is proposed, and the asymmetric coefficients’ calculation methods of independent and dependent variables are given respectively in two-dimensional space. Secondly, according to the different positions of side column 1 and side column 2, 30 local models are established, the cross bearer weld stresses are extracted after finite element simulation, and the stress distribution clusters are formed. Finally, the asymmetry coefficients of the side columns are calculated, and the correlation between the positions of the side columns and the weld stresses is studied by the methods of Pearson correlation coefficient and complex correlation coefficient. The results show that the correlation between the stress of cross bearer weld 2 and the positions of the side columns is much higher. This research can not only provide an important basis for the structural optimization of 80t gondola car body, and it also provides reference for the structural design of the gondola car body.

Simulation Investigation of Bulk and Surface Properties of Liquid Benzonitrile: Ring Stacking  Assessment and Deconvolution

This manuscript is devoted to classical molecular dynamics (MD) simulation studies of the bulk and surface properties of liquid benzonitrile (BZN) in the temperature range of 293-323K. The content and the simulation-analysis are inspired by our recent ab initio calculation on benzonitrile, whereas present results are to expand and develop macroscopic documentation involving data verification. We investigate the molecular stacking that involves phenyl ring, which is notably absent in the counterpart acetonitrile solvent. MD simulations of the bulk liquid unravel the hydrogen bond (C≡N⋯H) formation and strength, in the order of ortho-H >> meta-H ~>para-H. The possibility for ortho-H’s to get involved in the formation of two bonds simultaneously confirms each having - and -bonding features. The singularity centered at about 313 K found in the trend of the simulated temperature-dependent viscosity and diffusion coefficient of liquid BZN goes alongside the reported experiment, and the phenomenon may root from a change in the internal frictional motion of the molecular cluster in stacking modes. Accordingly, we used vast efforts for analysis particularly based on the deconvolution of the corresponding complex correlation functions. Specific angle-dependent correlation functions led to the recognition of the stacking molecules and their strict orientational character by utilizing relative molecular twist angles. Recognition of the strict orientational character of the stacking molecules, as a clue to the singularity in the viscosity trend, will be discussed based on specific angle-dependent correlation functions.

Elastic Correlation Adjusted Regression (ECAR) scores for high dimensional variable importance measuring

Investigation of the genetic basis of traits or clinical outcomes heavily relies on identifying relevant variables in molecular data. However, characteristics such as high dimensionality and complex correlation structures of these data hinder the development of related methods, resulting in the inclusion of false positives and negatives. We developed a variable importance measure method, termed the ECAR scores, that evaluates the importance of variables in the dataset. Based on this score, ranking and selection of variables can be achieved simultaneously. Unlike most current approaches, the ECAR scores aim to rank the influential variables as high as possible while maintaining the grouping property, instead of selecting the ones that are merely predictive. The ECAR scores’ performance is tested and compared to other methods on simulated, semi-synthetic, and real datasets. Results showed that the ECAR scores improve the CAR scores in terms of accuracy of variable selection and high-rank variables’ predictive power. It also outperforms other classic methods such as lasso and stability selection when there is a high degree of correlation among influential variables. As an application, we used the ECAR scores to analyze genes associated with forced expiratory volume in the first second in patients with lung cancer and reported six associated genes.

Biological Network Inference With GRASP: A Bayesian Network Structure Learning Method Using Adaptive Sequential Monte Carlo

Bayesian networks (BNs) provide a probabilistic, graphical framework for modeling high-dimensional joint distributions with complex correlation structures. BNs have wide applications in many disciplines, including biology, social science, finance and biomedical science. Despite extensive studies in the past, network structure learning from data is still a challenging open question in BN research. In this study, we present a sequential Monte Carlo (SMC)-based three-stage approach, GRowth-based Approach with Staged Pruning (GRASP). A double filtering strategy was first used for discovering the overall skeleton of the target BN. To search for the optimal network structures we designed an adaptive SMC (adSMC) algorithm to increase the quality and diversity of sampled networks which were further improved by a third stage to reclaim edges missed in the skeleton discovery step. GRASP gave very satisfactory results when tested on benchmark networks. Finally, BN structure learning using multiple types of genomics data illustrates GRASP’s potential in discovering novel biological relationships in integrative genomic studies.

Research on the Operational Modal Prediction of Dry Gas Seal System Based on Response Surface Method

The cross power spectrum function is used to realize the operational modal analysis and identification of the dry gas seal device system through the multi-reference point least squares complex frequency domain method. The steady state diagram and mathematical indicators MAC, MPD, MPC, MOV and MIF are used to verify the modal results. At the same time, based on the response surface method, with two different operating conditions of medium pressure and rotating speed, modal direction and modal order as the response surface variables, a time-varying modal recognition model is established. Through the Full Factorial experiment design, Box-Behnken experiment design and Central Composite experiment design, the suitable variable sample points are formed. A complete quadratic polynomial response surface model of the system operational modal parameters is established. The complex correlation coefficient, the modified complex correlation coefficient and the root mean square error are used to verify the effectiveness of the response surface model. It provides new method and technical support for realizing time-varying modal identification in this paper.

Az interleukin-6-expresszió vizsgálata colorectalis adenocarcinomában szenvedő betegeken

Összefoglaló. Bevezetés: A gyulladásos folyamatok és a tumorok kialakulása, illetve progressziója közötti összetett kapcsolat ismert. Az interleukin-6 (IL6) egy pleiotrop gyulladásos citokin, melynek tumorstimuláló és -gátló tulajdonsága is van. Célkitűzés: Kutatásunk célja az IL6-expresszió vizsgálata volt colorectalis adenocarcinoma miatt reszekción átesett betegek szövettani metszetein. Módszer: Az Uzsoki Utcai Kórházban 2004 és 2011 között reszekált 64, colorectalis tumoros beteg demográfiai, sebészeti és patológiai adatait gyűjtöttük össze. A betegek szövettani metszeteit IL6-antitesttel festettük. A digitalizált metszeteket kvantitatív színelemzéssel kiértékeltük, majd az eredményeket a betegek klinikai paramétereinek függvényében elemeztük. Eredmények: Előrehaladott stádiumú betegekben a tumorsejtek IL6-expressziója szignifikánsan magasabbnak bizonyult lineáris regresszióval. A tumorsejtek IL6-expressziója azonban nem korrelált a nemmel, az életkorral vagy a tumor differenciáltságával. Megbeszélés: Különbségek mutatkoztak a tumorsejtek és a stromasejtek IL6-kifejeződése között. Következtetés: Az IL6 hasznos marker és potenciális terápiás cél lehet az előrehaladottabb stádiumú colorectalis tumoros betegeknél. Orv Hetil. 2021; 162(37): 1502–1507. Summary. Introduction: It is well known that there is a complex correlation between inflammation and tumor development and tumor progression. Interleukin-6 (IL6) is a pleiotropic inflammatory cytokine with both tumor stimulating and inhibiting effect. Objective: The goal of our study was to evaluate the IL6 expression of histological slides from patients after resection of colorectal adenocarcinoma. Method: Demographical, surgical, and pathological findings of 64 patients with colorectal cancer operated between 2004 and 2011 in Uzsoki Teaching Hospital were evaluated. Histopathological slides were stained with IL6 antibody. The digitalized slides were assessed with quantitative color analysis, and the results were evaluated according to patients’ clinical parameters. Results: Linear regression showed significantly higher IL6 expression in the tumor cells in patients with advanced stages. However, the IL6 expression of the tumor cells did not correlate with sex, age, or tumor grade. Discussion: There were differences between the IL6 expression in tumor cells and stromal cells. Conclusion: IL6 may be a useful marker and potential therapeutic target in patients with advanced colorectal cancer. Orv Hetil. 2021; 162(37): 1502–1507.

A Time-Domain Simulation System of MICAP L-Band Radiometer for Pre-Launch RFI Processing Study

Microwave Imager Combined Active and Passive (MICAP), which is a package of active and passive microwave instruments including L/C/K-band radiometers and L-band scatterometer, has been approved to be taken onbord the Chinese Ocean Salinity Mission. The L-band one-dimensional synthetic aperture radiometer (L-Rad) is the key part of MICAP to measure sea surface salinity (SSS). Since radio frequency interference (RFI) is reported as a serious threat to L-band radiometry, the RFI detection and mitigation techniques must be carefully designed before launch. However, these techniques need to be developed based on the knowledge of how RFI affects complex correlation, visibility function, and reconstructed brightness temperature. This paper presents a time-domain signal modeling method for the simulation of interferometric measurement under RFI’s presences, and a simulation system for L-Rad is established accordingly. Several RFI cases are simulated with different RFI types, parameters, and positions; and the RFI characteristics upon L-Rad’s measurement are discussed. The proposed simulation system will be further dedicated to the design of RFI processing strategy onboard MICAP.

Structural characterization and magnetic response of poly(p-xylylene)–MnSb and MnSb films deposited at cryogenic temperature

In this study, we employed several experimental techniques to investigate structure and magnetic properties of poly(p-xylylene)–MnSb composites synthesized by low-temperature vapor deposition polymerization technique and MnSb films deposited at various temperatures. The presence of MnSb nanocrystallites in the studied films was verified by the results of X-ray diffraction, electron microscopy and Raman spectroscopy studies. The obtained data revealed the formation of Sb-rich sublayer with well-oriented Sb grains near the susbtrate, which seems to act as a buffer for the consequent poly(p-xylylene)–MnSb or MnSb layer growth. Increasing the polymer content results in qualitative change of surface morphology of studied films. At high polymer content the hybrid nanocomposite with MnSb nanoparticles embedded into poly(p-xylylene) matrix is formed. All investigated samples demonstrated detectable ferromagnetic response at room temperature, while the parameters of this response revealed a complex correlation with nominal composition, presented crystal phases and surface morphology of studied films. Estimated values of the Curie temperature of the samples are close to that of bulk MnSb.