Mechanical Properties and Stress Strain Relationship Models for Bamboo Scrimber

In order to investigate the basic mechanical properties and stress strain relationship model for bamboo scrimber manufactured based on a new technique,a large quantities of experiments have been carried out.Based on the analysis of the test results,the following conclusions can be drawn.Two main typical failure modes were classified for bamboo scrimber specimens both under tension parallel to grain and tension perpendicular to grain.Brittle failure happened for all tensile tests.The slope values for the elastic stages have bigger discreteness compared with those for the specimens under tensile parallel to grain.The failure modes for bamboo scrimber specimens under compression parallel to grain could be divided into four.Only one main failure mode happened both for the bending specimens and the shear specimens.With the COV values of 28.64 and 25.72 respectively,the values for the strength and elastic modulus under tensile perpendicular to grain have the largest discreteness for bamboo scrimber.From the point of CHV values,the relationship among the mechanical parameters for bamboo scrimber were proposed based on the test results.Compared with other green building materials,bamboo scrimber manufactured based on a new technique has better mechanical performance and could be used in construction area.Three stress strain relationship models which are four-linear model,quadratic function model,and cubic function model were proposed for bamboo scrimber specimens manufactured based on a new technique.The latter two models gives better prediction for stress strain relationship in elastic plastic stage.

Relationship between rock uniaxial compressive strength and digital core drilling parameters and its forecast method

The rock uniaxial compressive strength(UCS)is the basic parameter for support designs in underground engineering.In particular,the rock UCS should be obtained rapidly for underground engineering with complex geological conditions,such as soft rock,fracture areas,and high stress,to adjust the excavation and support plan and ensure construction safety.To solve the problem of obtaining real-time rock UCS at engineering sites,a rock UCS forecast idea is proposed using digital core drilling.The digital core drilling tests and uniaxial compression tests are performed based on the developed rock mass digital drilling system.The results indicate that the drilling parameters are highly responsive to the rock UCS.Based on the cutting and fracture characteristics of the rock digital core drilling,the mechanical analysis of rock cutting provides the digital core drilling strength,and a quantitative relationship model(CDP-UCS model)for the digital core drilling parameters and rock UCS is established.Thus,the digital core drilling-based rock UCS forecast method is proposed to provide a theoretical basis for continuous and quick testing of the surrounding rock UCS.

Temporal variability of temperature-nitrate relationship in a coastal region

The inverse relationship between nitrate and temperature(N-T relationship) has been used to estimate new production from remotely sensed sea surface temperature at the regional or global scale of oceans. This study aimed to develop a time-series model of the N-T relationship from automated, continuous hourly observations over two years on the coast of Halifax, Canada. The model demonstrated time-series variability of the N-T relationship at a coastal station on the Nova Scotia Shelf, with adjusted R 2 =0.999 4 and RMSE=0.025 7. The maximum residual value was 0.077. The annual temperature variations described a sine curve, and daily, weekly, and monthly variations fluctuated within the normal ranges, controlled by the local climate. The annual variation of nitrate concentration formed nearly a sine curve. Heavy or longlasting rainfall increased nitrate concentration by 4 to 30-fold in 24 h, and then the increased nitrogen was quickly depleted by phytoplankton growth in 10 to 48 h. In general, biological activity was a key factor in causing nitrate concentration change, dependent mainly on seawater temperature. The power function of the N-T relationship observed in our study area could be used to quickly estimate sea surface nitrate concentration, in combination with temperature data obtained by remote sensing.

Compression Behaviors of Parallel Bamboo Strand Lumber Under Static Loading

In order to investigate the influence of length and compression directions upon behaviour of parallel bamboo strand lumber(PBSL)specimens,240 axial compression tests have been performed.With three similar one different typical failure modes,the mechanical performance for PBSL specimens under compression parallel to grain and perpendicular to grain are different as a whole.From the point of the characteristic values,the compression strength parallel to grain is 2.1 times of the compression strength perpendicular to grain.The elastic modulus for compression parallel to grain is 3.64 times of the compression strength perpendicular to grain.While the compression ratios along two compression directions are equal to each other.The bigger Poisson ratios for one typical side surface is 3.93 times of that for another typical side surface for PBSL specimens under compression perpendicular to grain,and the bigger value is equal to that for PBSL specimens under compression parallel to grain.Length can influence the mechanical properties of the PBSL specimens.The size 50 mm×50 mm×100 mm should be good choice for the standard or code to measure the compression strength.PBSL materials have better ductility under compression parallel to grain than that under compression perpendicular to grain.Stress-strain relationship models were proposed for PBSL specimens under compression parallel to grain and perpendicular to grain,respectively.These proposed models gave a good agreement with the test results.

An LCOR model for suppressing cascading failure in weighted complex networks

Based on the relationship between capacity and load, cascading failure on weighted complex networks is investigated, and a load-capacity optimal relationship （LCOR） model is proposed in this paper. Compared with three other kinds of load- capacity linear or non-linear relationship models in model networks as well as a number of real-world weighted networks including the railway network, the airports network and the metro network, the LCOR model is shown to have the best robustness against cascading failure with less cost. Furthermore, theoretical analysis and computational method of its cost threshold are provided to validate the effectiveness of the LCOR model. The results show that the LCOR model is effective for designing real-world networks with high robustness and less cost against cascading failure.

Microstructural evolution and its effect on mechanical properties in different regions of 2219-C10S aluminum alloy TIG-welded joint

Microstructural evolution and its effect on mechanical properties in different regions of 2219-C10S aluminum alloy tungsten inert gas(TIG)welded joint were analyzed in detail.In weld zone(WZ),α+θeutectic structure formed at grain boundaries with no precipitates inside the grains.In partially melted zone(PMZ),symbiotic eutectic or divorced eutectic formed at grain boundaries and needle-likeθ′phases appeared in the secondary heated zone.In over aged zone(OAZ),the coarsening and dissolution ofθ′phases occurred and mostθ′phases transformed intoθphases.In general heat affected zone(HAZ),θ′phases coarsened.Factors such as the strengthening phases,the grain size,the Cu content in matrix and the dislocation density can affect the mechanical properties in different regions of the joint.Moreover,a model describing the relationship between mechanical properties of the material and the volume fraction of precipitates,the average diameter of precipitates and the concentration of soluble elements was proposed.

Proposal and evaluation of a new norm index-based QSAR model to predict pEC50 and pCC50 activities of HEPT derivatives

The search and development of anti-HIV drugs is currently one of the most urgent tasks of pharmacological studies. In this work, a quantitative structure-activity relationship （QSAR） model based on some new norm indexes, was obtained to a series of more than 150 HEPT derivatives （1-[（2-hydroxyethoxy）methyl]-6-（phenylthio）thymine） to find their pEC50 （the required effective concentration to achieve 50% protection of MT-4 cells against the cytopathic effect of virus） and pCC50 （the required cytotoxic concentration to reduce visibility of 50% mock infected cell） activities. The model efficiencies were then validated using the leave-one-out cross validation （LOO-CV） and y- randomization test. Results indicated that this new model was efficient and could provide satisfactory results for prediction of pECso and pCC50 with the higher R2 train and the higher Rt2est. By using the leverage approach, the applicability domain of this model was further investigated and no response outlier was detected for HEFT derivatives involved in this work. Comparison results with reference methods demonstrated that this new method could result in significant improvements for predicting pEC50 and pCC50 of anti-HIV HEPT derivatives. Moreover, results shown in this present study suggested that these two absolutely different activities pECso and pCC50 of anti-HIV HEPT derivatives could be predicted well with a totally similar QSAR model, which indicated that this model mizht have the potential to be further utilized for other biological activities of HEFT derivatives.

Parameter Fitting of Seismic Intensity Attenuation Model in Xinjiang

By using the existing historical earthquake investigation data in Xinjiang,this paper obtained the envelope curves of isoseismal maps of 103 destructive earthquakes occurring from 1716 to 2010 after digitization of the data. The author summarized the seismic intensity attenuation laws in the Xinjiang region with the multiple regression fitting method. The intensity attenuation function of the elliptical model was provided and the fitting results in different periods and areas were compared. Finally, the intensity attenuation relationship in the Xinjiang region was obtained by the method of constraining the start and end of the attenuation curves.

Machine Learning-Based Quantitative Structure-Activity Relationship and ADMET Prediction Models for ERα Activity of Anti-Breast Cancer Drug Candidates

Breast cancer is presently one of the most common malignancies worldwide,with a higher fatality rate.In this study,a quantitative structure-activity relationship(QSAR)model of compound biological activity and ADMET(Absorption,Distribution,Metabolism,Excretion,Toxicity)properties prediction model were performed using estrogen receptor alpha(ERα)antagonist information collected from compound samples.We first utilized grey relation analysis(GRA)in conjunction with the random forest(RF)algorithm to identify the top 20 molecular descriptor variables that have the greatest influence on biological activity,and then we used Spearman correlation analysis to identify 16 independent variables.Second,a QSAR model of the compound were developed based on BP neural network(BPNN),genetic algorithm optimized BP neural network(GA-BPNN),and support vector regression(SVR).The BPNN,the SVR,and the logistic regression(LR)models were then used to identify and predict the ADMET properties of substances,with the prediction impacts of each model compared and assessed.The results reveal that a SVR model was used in QSAR quantitative prediction,and in the classification prediction of ADMET properties:the SVR model predicts the Caco-2 and hERG(human Ether-a-go-go Related Gene)properties,the LR model predicts the cytochrome P450 enzyme 3A4 subtype(CYP3A4)and Micronucleus(MN)properties,and the BPNN model predicts the Human Oral Bioavailability(HOB)properties.Finally,information entropy theory is used to validate the rationality of variable screening,and sensitivity analysis of the model demonstrates that the constructed model has high accuracy and stability,which can be used as a reference for screening probable active compounds and drug discovery.

A Study on Heterogeneous Cellular Automaton Simulation of the Influencing Factors on Seismicity

For the purpose of investigating conditions of earthquake pregnancies,a heterogeneous 2-D single fault model with 81 × 81 cells is set up. By using cellular automata models and changing the model heterogeneity and correlation parameters, we compute and get different synthetic event catalogues for analyzing general seismic activity and intensity distribution properties. The results show that different heterogeneous structures produce different seismic sequence types and G-R relationship,so the heterogeneity is an important influencing factor on seismicity. Nevertheless,both the coefficients of stress redistribution and local friction loss can also influence seismicity to some extent. This is possibly useful for further understanding of the complexity of earthquake processes.

Research on FDI and China＇s Economic Growth

In this paper, the relationship between FDI and China＇s economic growth is analyzed by Granger causality test and multiple regression model. It is found that relationship is bi-directional causal. It is suggested that the utilization of FDI should be focused on not only the quantity, but also the quality of FDI with its rapid development.

Antitumor Compound Identification from Zanthoxylum bungeanum Essential Oil Based on Composition-activity Relationship

The chemical composition of Zanthoxylum bungeanum（Z bungeanum） essential oi1（39 batches） was analyzed by gas chromatography-mass spectrometry（GC-MS） analysis（23 ingredients）, and the antitumor activity against HeLa cells was detected via the MTT[3-（4,5-dimethylthiazol-2-yl）-2,5-diphenyltetrazolium bromide] assay. Two composition-activity relationship（CAR） models, generalized regression neural network（GRNN） and support vector regression（SVR） were respectively used to calculate the mean impact value（MIV） so as to identify bioactive com- pounds. Among them 9 ingredients（peaks 4, 15, 7, 8, 13, 3, 16, 9 and 11） were selected due to their high absolute MIVs. All of them have been confirmed with potential antitumor activity by previous researches. The CAR model combined with MIV was expected to be a credible tool for the active compound identification from herbs.

Key Parameters Analysis and Regulation of Singlet Oxygen Quenching Rate of Carotenoids

28 kinds of carotenoids are studied to reveal the key parameters and regulation on the singlet oxygen quenching rate.First,the quantum chemistry parameters of carotenoids calculated by Gaussian software combined with substitution parameters were used to construct the quantitative structure-activity relationship model(QSAR)of the singlet oxygen quenching rate of carotenoids.The key parameters affecting the antioxidant activity of carotenoids are revealed,and the data predicted via the QSAR model were provided for subsequent research.Then,a three-dimensional(3D)pharmacophore model was used to regulate and modify the antioxidant activity of carotenoids.The correlation coefficients of the modeling group(R2)and verification group(Rpre2)of the established QSAR model were 0.945 and 0.916,respectively,which can be used for the analysis of antioxidant activity of carotenoids;the antioxidant activity of carotenoids can be significantly regulated by the number of conjugated C=C bonds,the energy difference between frontier molecular orbitals and the partial Mulliken charge in C1 and theπ···π*excitation energy E(s);the antioxidant activity of carotenoids can be effectively regulated by the hydrogen bond acceptor pharmacophores on both sides of the conjugated C=C bonds and the hydrophobic groups on the conjugated C=C bond;the hydrophobic substituents attached to conjugated C=C bonds can effectively improve the singlet oxygen quenching rate of carotenoids.

Prediction of CO_(2) solubility in deep eutectic solvents using random forest model based on COSMO-RS-derived descriptors

This work presents the development of molecular-based mathematical model for the prediction of CO_(2) solubility in deep eutectic solvents(DESs).First,a comprehensive database containing 1011 CO_(2) solubility data in various DESs at different temperatures and pressures is established,and the COSMO-RS-derived descriptors of involved hydrogen bond acceptors and hydrogen bond donors of DESs are calculated.Afterwards,the efficiency of the input variables,i.e.,temperature,pressure,COSMO-RS-derived descriptors of HBA and HBD as well as their molar ratio,is explored by a qualitative analysis of CO_(2) solubility in DESs using a simple multiple linear regression model.A machine learning method namely random forest is then employed to develop more accurate nonlinear quantitative structure-property relationship(QSPR)model.Combining the QSPR validation and comparisons with literature-reported models(i.e.,COSMO-RS model,traditional thermodynamic models and equations of state methods),the developed QSPR model with COSMO-RS-derived parameters as molecular descriptors is suggested to be able to give reliable predictions of CO_(2) solubility in DESs and could be used as a useful tool in selecting DESs for CO_(2) capture processes.

A linear varying coefficient ARCH-M model with a latent variable

Motivated by the psychological factor of time-varying risk-return relationship, this paper studies a linear varying coefficient ARCH-M model with a latent variable. Due to the unobservable property of the latent variable, a corrected likelihood method is employed for parametric estimation. Estimators are proved to be consistent and asymptotically normal under certain regularity conditions. A simple test statistic is also proposed for testing latent variable effect. Simulation results confirm that the proposed estimators and test perform well.The model is further applied to examine whether the risk-return relationship depends on investor's sentiment in American Market and some explainable results are obtained.

Predictive models on photolysis and photoinduced toxicity o persistent organic chemicals

Photodegradation is a major abiotic transfor- mation pathway of toxic chemicals in the environment, which in some cases might lead to photoinduced toxicities. The data on photodegradation kinetics and photoinduced toxicities of organic chemicals are essential for their risk assessment. However, the relevant data are only available for a limited number of chemicals, due to the difficulty and high cost of experimental determination. Quantitative structure-activity relationship （QSAR） models that relate photodegradation kinetics or photoinduced toxicity of organic chemicals with their physicochemical properties or molecular structural descriptors may enable simple and fast estimation of their photochemical behaviors. This paper reviews the QSAR models on photodegradation quantum yields and rate constants for toxic organic chemicals in different media including liquid phase, gaseous phase, surfaces of plant leaves, and QSAR models on photo- induced toxicity of organic chemicals to plants, bacteria, and aquatic invertebrates. Further prospects for QSAR model development on photodegradation kinetics and photoinduced toxicity of refractory organic chemicals are proposed.

Studies on QSAR of metalloporphyrin catalysts in the oxidation of cyclohexane to adipic acid

The catalysis of chloridized metalloporphyrins in the oxidation of cyclohexane to adipic acid was systemati-cally investigated.The turnover numbers(TON)data of 19 catalysts were obtained experimentally under optimal reac-tion conditions,and 2.4x106 TON for T(o-Cl)PP-MnIIICl catalyst at 2.0x10–6 mol/L of dosage was reached under the conditions of dioxygen pressure of 2.5 MPa at 150°C for 4 h.This was the best result reported for this reaction up to now.The QSAR models for each concerned metallopor-phyrin were established,where the catalytic activity was significantly correlated with the ELUMO(the energy level of the lowest unoccupied molecule orbit)and LM-N(the bond length between metal-nitrogen atoms).Using the QSAR models,four new metalloporphyrins with substituted nitro group were designed,and their catalytic activities were predicted.The experimental TON data of newly designed porphyrins were in good agreement with the predicted ones,and the square of their correlation coefficient was more than 0.958.The above results demonstrated that the proposed structure-activity relationship model could be applied to design some new metalloporphyrin catalysts,and to predict their catalytic activity in cyclohexane oxidation.