Ytterbia and erbia dual-doped zirconia (ZrO₂: Yb³⁺, Er³⁺) nanophosphors were successfully synthesized by high-temperature fuel combustion at 1000 °C for 2 h. The effects of dopant concentration on the structure and upconversion properties were investigated by X-ray diffraction, transmission electron microscopy and photoluminescence, respectively. XRD patterns indicate that the main phase of products belongs to cubic ZrO₂ fluorite-type structure. TEM results show that different fuels have great influence on the morphologies of dual-doped ZrO₂ samples. Under 980 nm excitation, the glycine-calcined nanophosphors show high stimulated luminescence and doped-ion concentration-depended intensities. The intensely red upconversion emissions are attributed to the fact that the dual-doped Yb³⁺ and Er³⁺ ions result in the non-radiative relaxation, energy migration, and cross relaxation.

Effect of Ti addition on the microstructure and strengthening behavior in press hardening steels (PHS) was analyzed by optical metallography (OM), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-ray diffraction (XRD). The results show that the microstructure of PHS is martensite, and two sizes of particles disperse in the martensite matrix during the forming and quenching process. The size of the bigger particles is between 100 and 200 nm, and the small particles are nanometer-sized. The quantity of the particles has a positive relation with the Ti content. More importantly, the microstructure and strengthening mechanism are affected by the precipitating behavior of the particles. Besides the prior austenite grain, martensite packet, block and lath are refined by Ti addition. The steels are strengthened by the fine grains, martensite substructure and precipitates. The uniformly distributed dislocation in the martensite lath, the density of which is between 3.0×10¹⁴ cm^–2 and 5.0×10¹⁴ cm^–2, strengthens the steels through associating with fine carbide particles.

The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor (DSP) is proposed. First, the combination of genetic algorithm (GA) and simulated annealing algorithm (SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.

Al–5.0Cu–0.4Mn alloys with different Zr additions have been prepared by direct squeeze casting. The effects of Zr on microstructures and mechanical properties of the as-cast and T6 heat-treated alloys were investigated by tensile test, optical microscope (OM), scanning electron microscope (SEM) and transmission electron microscope (TEM). The results show that the optimal tensile property of the as-cast alloy occurs at the Zr content of 0.15% (mass fraction) due to the “Zr poisoning” action and the appearance of bulky primary Al₃Zr, which decreases the grain refinement strengthening effect of the as-cast alloy. The peak values of ultimate tensile strength and yield strength of the T6 alloy occur at the Zr content of 0.25%, and that of the elongation occurs at Zr content of 0.05%. This is mainly attributed to the strengthening effect of dispersed precipitation of Al₃Zr and θ’ phases. The optimal mechanical properties of T6 heat-treated alloy are the tensile strength of 429 MPa, the yield strength of 327 MPa and the elongation of 18%, respectively when the squeeze pressure is 100 MPa and Zr content is 0.25%.

Nanocomposite multilayer TiBN coatings were prepared on Si (100) and 9Cr18Mo substrates using TiBN composite cathode plasma immersion ion implantation and deposition technique (PIIID). Synthesis of TiBN composite cathodes was conducted by powder metallurgy technology and the content of hexagonal boron nitride (h-BN) was changed from 8% to 40% (mass fraction). The as-deposited coatings were characterized by energy dispersive spectrometer (EDS), grazing incidence X-ray diffraction (GIXRD), Fourier Transform Infrared Spectroscopy (FTIR) and high resolution transmission electron microcopy (HRTEM). EDS results show that the B content of the coatings was varied from 3.71% to 13.84% (molar fraction) when the composition of the h-BN in the composited cathodes was changed from 8 % to 40% (mass fraction). GIXRD results reveal that the TiBN coatings with a B content of 8% has the main diffraction peak of TiN (200), (220) and (311), and these peaks disappear when the B content is increased. FTIR analysis of the multilayer coatings showed the presence of h-BN in all coatings. TEM images reveal that all coatings have the characteristics of self-forming nanocomposite multilayers, where the nanocomposites are composed of face-centered cubic TiN or h-BN nanocrystalline embedded in amorphous matrix. The tribological tests reveal that the TiBN coatings exhibit a marked decrease of coefficient at room temperature (~0.25). The improved properties were found to be derived from the comprehensiveness of the self-forming multilayers structure and the h-BN solid lubrication effects in the coatings.

The effect of ultraviolet mutagenesis on a heterotrophic strain (Providencia JAT-1) mutation was studied and bioleaching of low grade copper ore with mutant bacteria was investigated. The results show that the activity of bacteria was improved after ultraviolet mutagenesis; the best irradiation time was 120 s. Compared to the original bacteria, the cells density of mutant bacteria at stationary phase increased by 26% and ammonia produced by mutant bacteria increased by 12%. Higher activity of bacteria leads to a higher copper extraction rate. The bioleaching performance of Providencia JAT-1 was improved after UV mutagenesis. The copper extraction rate with mutant bacteria increased by 10.6% compared to the original bacteria. The ore surface was corroded and the fine particles were absent after bioleaching. Free copper oxide and copper silicates could be leached out easily by using JAT-1; a small part of the copper sulfide can also be leached out. Bioleaching using JAT-1 is more effective than ammonia leaching and copper extraction rate with mutant bacteria was 21.1% higher than that by ammonia leaching under the same condition.

Synergistic extraction has been proven to enhance extractability and selectivity for the separation of cadmium and zinc from magnesium and calcium in the sulfuric acid medium with Mextral V10 and Mextral 622H (aromatic hydroxamic) mixtures diluted in DT100. Mixtures of Mextral V10 and 622H are highly selective for Zn and Cd over Mg and Ca compared with the single Mextral V10, resulting in larger synergistic shifts for zinc and cadmium with the ΔpH_{50 (Zn–Ca)} values increasing substantially from 0.83 to 1.73 pH units and ΔpH_{50 (Cd–Ca)} values increasing from 0.63 to 2.13 pH units. The aqueous to organic ratio (A/O ratio), the saponification ratio of Mextral V10 and extracting agent concentration were studied on the effect of metal ions extraction, which helped to increase the organic capacity of metal extraction. The McCabe-Thiele plot for Cd and Zn extraction with 5% (volume fraction) Mextral V10 and 5% Mextral 622H extractants mixture indicate the necessity of only one theoretical stages at an A/O ratio of 1.5:1. One stage extraction simulation test conducted at pH 6.50 shows that Cd and Zn reach the extraction of 99.6% and 97.9%, respectively, and only low levels of magnesium and calcium are extracted in the organic phase. The extracted Zn²⁺ or Cd²⁺-organic species are Zn(A₁)(A₂) or Cd(A₁)(A₂) with the mixture system by slope analysis.

The granulability and absorbtivity of sawdust and coke breeze were investigated. These properties are important within the preparation of agglomeration charge. They have a significant impact on plynodynamic batch conditions. Ability of materials to wet is a fundamental condition of granulability of materials. Wettability and water absorption of wood with liquids is generally significantly affected by their chemical structure. The important factors affecting the wetting process are undoubtedly the wood moisture content, the value of the surface tension of liquid media and their chemical composition. With increasing moisture content of wood, the time to equilibrium rises. Determination of water absorption and granulability of sawdust was conducted to seek their possible use as a partial replacement of coke dust in the production of the agglomerate. Experiments have been realized with alder, oak and pine sawdust and reference material−coke breeze. These materials were divided to four classes of granularity: supplied material, 1−2 mm, 0.5−1 mm and less than 0.5 mm. And different liquid media were used: water 16 °C, water 60 °C, soapy water, lime milk and surfactant.

The orthogonal test was used to optimize the reaction conditions of roasting zinc oxide ore with NaOH aiming to comprehensively utilize zinc oxide ore. The optimized reaction conditions were molar ratio of NaOH to zinc oxide ore 6:1, roasting temperature 450 °C, holding time 150 min. The molar ratio of NaOH to zinc oxide ore was the most predominant factor affecting the extraction ratios of zinc oxide and silica. The mineral phase transformations were investigated by testing the phases of specimens obtained at different temperatures. The process was that silica reacted with molten NaOH to form Na₂SiO₃ at first, then transformed into Na₄SiO₄ with temperature rising. ZnCO₃ and its decomposing product ZnO reacted with NaOH to form Na₂ZnO₂. Na₂ZnSiO₄ was also obtained. The reaction rate was investigated using unreacted shrinking core model. Two models used were chemical reaction at the particle surface and diffusion through the product layer. The results indicated that the reaction rate was combine-controlled by two models. The activation energy and frequency factor were obtained as 24.12 kJ/mol and 0.0682, respectively.

Electrospinning is a useful and efficient technique to produce polymeric nanofibers. Nanofibers of polymers are electrospun by creating an electrically charged jet of polymer solution. Numerical study on non-Newtonian and viscoelastic jets of polymer nanofibers in electrospinning process is presented in this work. In particular, the effect of non-Newtonian rheology on the jet profile during the electrospinning process is examined. The governing equations of the problem are solved numerically using the Keller-Box method. The effects of yield stress and power-law index on the elongation, velocity, stress and total force are presented and discussed in detail. The results show that by increasing the values of yield stress, the fluid elongation is reduced significantly.

In the present work, the gas flow pressure drop and gas–solid heat transfer characteristics in sinter bed layer of vertical tank were studied experimentally on the basis of the homemade experimental setup. The gas flow pressure drop through the sinter bed layer was measured with different gas velocity and particle diameters, as well as the sinter and air temperatures. The influences of gas superficial velocity and particle diameter on the gas flow pressure drop and gas solid heat transfer in sinter bed layer were analyzed in detail. The revised Ergun’s correlation and gas solid heat transfer correlation were obtained according to the regression analysis of experimental data. It is found that, the pressure drop of unit bed layer height gradually increases as a quadratic relationship with increasing the gas superficial velocity, and decreases as an exponential relationship with the increase of sinter particle diameter. For a given sinter temperature, the heat transfer coefficient in sinter bed layer increases with increasing the gas superficial velocity, and increases with decreasing the sinter particle diameter. In addition, the heat transfer coefficient also gradually increases with increasing the sinter temperature at the same gas superficial velocity and sinter particle diameter. The mean deviations between the experimental data obtained from this work and the values calculated by the revised Ergun’s correlation and the experimental heat transfer correlation are 7.22% and 4.22% respectively, showing good prediction.

Various incorporation of Au in pyrite and its effects on the geometrical structure, electronic structure and flotability of pyrite were theoretically investigated and fully discussed by performing density functional theory (DFT). The calculated incorporation energy shows that gold would most likely exist in pyrite via incorporating into interstitial lattice sites in the absence of As impurity. As a result of incorporated Au, the covalence levels of the S—Fe and S—S bonds are changed, and the tonicity of Au—S bonds and antibonding of Au—Fe bonds are found to form in the pyrite, which would change the natural flotability of pyrite. The Au impurity energy levels are introduced into the energy band and result in the transformation of pyrite semiconductivity type. The calculated band-gap value suggests that the incorporated Au significantly decreases pyrite semiconductivity level, which enhances the formation and the adsorption stability of dixanthogen during pyrite flotation. The DOS results reveal that the stability and depression difficulty level of pyrites increases in the following order: Fe₃₂S₆₃As < Fe₃₂S₆₄ < Fe₃₂S₆₃AsAu < Fe₃₂S₆₄Au.

The displacement feedback with time delay considered is introduced in order to enhance the vibration isolation performance of a high-static-low-dynamic stiffness (HSLDS) vibration isolator. Such feedback is detailedly analyzed from the viewpoint of equivalent damping. Firstly, the primary resonance of the controlled HSLDS vibration isolator subjected to a harmonic force excitation is obtained based on the multiple scales method and further verified by numerical integration. The stability of the primary resonance is subsequently investigated. Then, the equivalent damping is defined to study the effects of feedback gain and time delay on primary resonance. The condition of jump avoidance is obtained with the purpose of eliminating the adverse effects induced by jumps. Finally, the force transmissibility of the controlled HSLDS vibration isolator is defined to evaluate its isolation performance. It is shown that an appropriate choice of feedback parameters can effectively suppress the force transmissibility in resonant region and reduce the resonance frequency. Furthermore, a wider vibration isolation frequency bandwidth can be achieved compared to the passive HSLDS vibration isolator.

The disc cutters of tunnel boring machine (TBM) are installed with different polar angles. This causes the cutting depth difference between adjacent disc cutters on the tunnel face. A rock-cutting model was established to study the rock fragmentation law between adjacent disc cutters with different polar angles based on particle flow code (PFC). The influence of polar angle of adjacent disc cutters on rock cracks and stresses under different cutter spacing and penetration was studied. Research shows that polar angle difference leads to the discontinuity of rock-fragmentation process by adjacent cutters. The effect of rock-fragmentation is influenced by the cutting depth difference between adjacent cutters. The effect of rock-fragmentation performed best, meanwhile large rock blocks were flaked when the difference of cutting depth is half of the penetration. Too large or small difference of the cutting depth will cause high specific energy consumption of rock fragmentation. The specific energy consumption is relatively small when the difference of cutting depth is half of the penetration.

Many studies have been done in cognitive radios to maximize the network efficiency. There is always a trade-off between sensing and transmission time which has been addressed fully in the literature. There is also some missed idle times during the waiting phase when secondary user finds the channel busy. Therefore, the longer the transmission time is, the higher the successfully delivered bits would be and the higher the missed idle times in the waiting stage would be expected. In this work, we formulate these missed idle times to addressed this trade-off. Furthermore, interference due to PU re-occupancy is modelled in successful transmitted time and in collision probability. Moreover, we derive secondary user’s packet delay distribution using phase type model at which retransmission due to collision results from both sensing error and PU re-occupancy is considered. Thanks to derived delay distribution, any statistical moments of delay could be found as a closed form mathematical expression. These moments can be used as constraints for applications with delay sensitive packets. Numerical results are given to clarify the network metrics. Finally, the optimized values for sensing and transmission time are computed using genetic algorithm in order to maximize access efficiency.

With the rising and spreading of micro-blog, the sentiment classification of short texts has become a research hotspot. Some methods have been developed in the past decade. However, since the Chinese and English are different in language syntax, semantics and pragmatics, sentiment classification methods that are effective for English twitter may fail on Chinese micro-blog. In addition, the colloquialism and conciseness of short Chinese texts introduces additional challenges to sentiment classification. In this work, a novel hybrid learning model was proposed for sentiment classification of Chinese micro-blogs, which included two stages. In the first stage, emotional scores were calculated over the whole dataset by utilizing an improved Chinese-oriented sentiment dictionary classification method. Data with extremely high or low scores were directly labeled. In the second stage, the remaining data were labeled by using an integrated classification method based on sentiment dictionary, support vector machine (SVM) and k-nearest neighbor (KNN). An improved feature selection method was adopted to enhance the discriminative power of the selected features. The two-stage hybrid framework made the proposed method effective for sentiment classification of Chinese micro-blogs. Experiments on the COAE2014 (Chinese Opinion Analysis Evaluation 2014) dataset show that the proposed method outperforms other schemes.

Cloud data centers consume a multitude of power leading to the problem of high energy consumption. In order to solve this problem, an energy-efficient virtual machine (VM) consolidation algorithm named PVDE (prediction-based VM deployment algorithm for energy efficiency) is presented. The proposed algorithm uses linear weighted method to predict the load of a host and classifies the hosts in the data center, based on the predicted host load, into four classes for the purpose of VMs migration. We also propose four types of VM selection algorithms for the purpose of determining potential VMs to be migrated. We performed extensive performance analysis of the proposed algorithms. Experimental results show that, in contrast to other energy-saving algorithms, the algorithm proposed in this work significantly reduces the energy consumption and maintains low service level agreement (SLA) violations.

This work proposes constrained constant modulus unscented Kalman filter (CCM-UKF) algorithm and its low-complexity version called reduced-rank constrained constant modulus unscented Kalman filter (RR-CCM-UKF) algorithm for blind adaptive beamforming. In the generalized sidelobe canceller (GSC) structure, the proposed algorithms are devised according to the CCM criterion. Firstly, the cost function of the constrained optimization problem is transformed to suit the Kalman filter-style state space model. Then, the optimum weight vector of the beamformer can be estimated by using the recursive formulas of UKF. In addition, the a priori parameters of UKF (system and measurement noises) are processed adaptively in the implementation. Simulation results demonstrate that the proposed algorithms outperform the existing methods in terms of convergence speeds, output signal-tointerference- plus-noise ratios (SINRs), mean-square deviations (MSDs) and robustness against steering mismatch.

Motion of a vertically falling nano droplet in incompressible Newtonian media with initial velocity is investigated. The instantaneous velocity and acceleration are carried out by using the variational iteration method (VIM) and homotopy perturbation method (HPM), which are analytical solution techniques. The obtained results are compared with Runge–Kutta method in order to verify the accuracy of the proposed methods. The results show that, the analytical solutions are in good agreement with each other and with the numerical solution. Also, the effects of sphericity (φ) on the velocity and acceleration profiles of the nano droplet are explained. Moreover, the results demonstrate that the VIM-Padé and HPM-Padé are very effective in generating analytical solutions for even highly nonlinear problems.

Nowadays, the vein based recognition system becomes an emerging and facilitating biometric technology in the recognition system. Vein recognition exploits the different modalities such as finger, palm and hand image for the person identification. In this work, the fuzzy least brain storm optimization and Euclidean distance (EED) are proposed for the vein based recognition system. Initially, the input image is fed into the region of interest (ROI) extraction which obtains the appropriate image for the subsequent step. Then, features or vein pattern is extracted by the image enlightening, circular averaging filter and holoentropy based thresholding. After the features are obtained, the entropy based Euclidean distance is proposed to fuse the features by the score level fusion with the weight score value. Finally, the optimal matching score is computed iteratively by the newly developed fuzzy least brain storm optimization (FLBSO) algorithm. The novel algorithm is developed by the least mean square (LMS) algorithm and fuzzy brain storm optimization (FBSO). Thus, the experimental results are evaluated and the performance is compared with the existing systems using false acceptance rate (FAR), false rejection rate (FRR) and accuracy. The performance outcome of the proposed algorithm attains the higher accuracy of 89.9% which ensures the better recognition rate.

Force analysis using a compact tension model, as recommended by ASTM, was carried out on a crack stop hole. The stress before, and after, drilling the hole was compared in terms of stress concentration and stress gradient. The optimum drilling location and diameter were studied through analysis of different locations and diameters. By analyzing the effects of flank holes and an additional hole, drilling advice was proposed and fatigue testing of the cracks in a steel bridge deck with a crack stop hole was conducted. The results show that the stress at the crack tip with a crack stop hole decreased, and the major principal stress around the hole was distributed accordingly. The optimum position of the crack stop hole centre was where the centre of the crack stop hole was situated behind the crack and the hole edge coincided with the crack tip. Therefore, hole diameters larger than 8 mm, or those weakening the section by 10%, were suggested as the best diameters. In terms of multi-hole crack stopping, a flank hole was not recommended. The optimum horizontal position of flank holes was at a distance of 1/4 of a single hole diameter from, and in front of, the single hole. Besides, the experiment showed that crack stop hole could only prevent cracks from growing and had no influence on crack growth rate.

The present work is aimed at studying the mechanic properties of the extra-wide concrete self-anchored suspension bridge under static and dynamic vehicle loads. Based on the field test using 12 heavy trucks and finite element simulations, the static deformations of different components, stress increments and distributions of the girder, as well as the vibration characteristics and damping ratio of the Hunan Road Bridge were analyzed, which is the widest self-anchored suspension bridge in China at present. The dynamic responses were calculated using the Newmark-β integration method assisted by the simulation models of bridge and vehicles, the influences on the dynamic impact coefficient (DIC) brought by the vehicle parameters, girder width, eccentricity travel and deck flatness were also researched. The spatial effect of the girder is obvious due to the extra width, which performs as the stress increments distribute unevenly along the transverse direction, and the girder deflections and stress increments of the upper plate change as a “V” and “M” shape respectively under the symmetrical vehicle loads affected by the shear lag effect, cross slope and local effect of the wheels, the maximum of stress increments are located in the junctions with the inner webs. The obvious girder torsional deformation and the apparent unevenness of the hanger forces between the two cable planes under the eccentric vehicle loads, together with the mode shapes such as the girder transverse bending and torsion which appear relatively earlier, all reflect the weakened torsional rigidity of the extra-wide girder. The transverse displacements of towers are more obvious than the longitudinal ones. As for the influences on the DIC, the static effect of the heavier vehicles plays a major role when pass through with a higher speed and the changes of vehicle suspension stiffness generate greater impacts than the suspension damp. The values of DIC in the vehicle-running side during the eccentric travel, affected by the restricts from the static effects of the eccentric moving trucks, are significantly smaller than the vehicle-free side, the increase in the road roughness is the most sensitive one among the above influential factors. The results could provide references for the design, static and dynamic response analysis of the similar extra-wide suspension bridges.

The seepage property of low-permeability rock is of significant importance for the design and safety analysis of underground cavities. By using a self-developed test system, both permeability and porosity of granite from an underground oil storage depot were measured. In order to study the influence of rock types on permeability, a tight sandstone was selected as a contrast. The experimental results suggested that the porosity of this granite is less than 5% and permeability is low to 10^–20 m² within the range of effective stress. During the loading process, both exponential relationship and power law can be utilized to describe the relationship between effective stress and permeability. However, power law matches the experimental data better during the unloading condition. The stress dependent porosity of granite during loading process can be described via an exponential relationship while the match between the model and experimental data can be improved by a power law in unloading paths. The correlation of permeability and porosity can be described in a power law form. Besides, granite shows great different evolution rules in permeability and porosity from sandstone. It is inferred that this difference can be attributed to the preparing of samples and different movements of microstructures subjected to effective stress.

The stability of underground excavations is influenced by discontinuities interspaced in surrounding rock masses as well as the stress condition. In this work, a numerical study was undertaken on the failure behavior around a circular opening in a rock mass having non-persistent open joints using PFC software package. A parallel-bond stress corrosion (PSC) approach was incorporated to drive the failure of rock mass around the circular opening, such that the whole progressive failure process after excavation was reproduced. Based on the determined micro parameters for intact material and joint segments, the failure process around the circular opening agrees very well with that obtained through laboratory experiment. A subsequent parametric study was then carried out to look into the influence of lateral pressure coefficient, joint dip angle and joint persistency on the failure pattern and crack evolution of the rock mass around the circular opening. Three failure patterns identified are step path failure, planar failure and rotation failure depending on the lateral pressure coefficient. Moreover, the increment of joint dip angle and joint persistency aggravates the rock mass failure around the opening. This study offers guideline on stability estimation of underground excavations.

Wind data were collected during the 2011 typhoon Meari at heights of 10, 20, 30, and 40 m above the ground using a 40 m high anemometer tower in the coastal area near Shanghai Pudong International Airport. Wind speeds and directions, turbulence intensities, gust factors, and peaks were analyzed using the time records of wind speed. The results show that turbulence intensity components in longitudinal, lateral, and vertical directions decrease with mean wind speed, regardless of elevations, and the turbulence intensities are in a linear relationship with mean wind speeds. The ratios of three turbulence intensity components (i.e. I_u, I_v, I_w) at heights of 10, 20 and 40 m were calculated and equal to be 1:0.88:0.50, 1:0.84:0.57, and 1:0.9:0.49, respectively. In addition, the gust factors in three directions exhibit a reduction with increasing mean wind speed. The peak factors at different heights show a similar trend and slightly decrease with mean wind speed; average peak factors for all 10-min data from Typhoon Meari are 2.43, 2.48, and 2.47, respectively.

To explore a new evaluation method for spontaneous combustion tendency of different areas in sulfide ore heap, ore samples from a pyrite mine in China were taken as experimental materials, and the temperature variations of the measuring points of simulated ore heap were measured. Combined with wavelet transform and nonlinear parameters extraction, a new method for spontaneous combustion tendency of different areas in sulfide ore heap based on nonlinear parameters was proposed and its reliability was verified by field test. The results indicate that temperature field evolution of the simulated ore heap presents significant spatial difference during self-heating process. Area with the maximum increasing extent of temperature in sulfide ore heap changes notably with the proceeding of self-heating reaction. Self-heating of sulfide ore heap is a chaotic evolution process, which means that it is feasible to evaluate spontaneous combustion tendency of different areas by nonlinear analysis method. There is a relatively strong correlation between the maximum Lyapunov exponent and spontaneous combustion tendency with the correlation coefficient of 0.9792. Furthermore, the sort of the maximum Lyapunov exponent is consistent with that of spontaneous combustion tendency. Therefore, spontaneous combustion tendency of different areas in sulfide ore heap can be evaluated by means of the maximum Lyapunov exponent method.

Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.

To reduce the longitudinal coupler forces of heavy haul trains and improve the running safety, the velocity method and New-mark method were used for the coupler simulation and numerical integration, and a numerical model on the longitudinal dynamics of heavy haul trains was established. Validation was performed against the experimental data. Using this model, the emergency braking process for a combined marshalling heavy haul train was investigated to obtain the distributions of the longitudinal compressive forces and strokes of coupler devices. Then, the influences of the initial braking velocity, the synchronization time of master and slave locomotives, the coupler stiffness and the vibrator mass on the longitudinal forces and strokes were analyzed. The results show that it should be avoided that the emergency braking starts at a low initial speed. Keeping synchronism between master locomotive and slave locomotives effectively helps to reduce the longitudinal forces. Reducing the coupler stiffness appropriately and adding rigid arm connections, the longitudinal vibration frequency can be brought down and the longitudinal forces will be decreased, which improves the running safety of heavy haul trains. All of these research results can provide a reference for the operation and development of heavy haul trains.

The 3D clearance of a high-speed train (HST) is critical to ensure the safety of railway transportation. Many studies have been conducted on the inspection of the clearance profile in railway operation based on the vision system, but few researchers have focused on the computation of the 3D clearance in the design phase of an HST. This paper summarizes the virtual 3D clearance computation of an HST based on model integration and the convex hull method. First, both the aerodynamic and kinetic analysis models of the HST are constructed. The two models are then integrated according to the corresponding relationship map, and an array of transformation matrixes of the HST is created to drive the designed model simulating the physical railway motion. Furthermore, the convex hull method is adopted to compute the 3D envelope of the moving train. Finally, the Hausdorff metric is involved in the measurement of the minimum clearance model and the 3D envelope model. In addition, the color map of the Hausdorff distance is established to verify that the designed shape of the HST meets the national standards. This paper provides an effective method to accurately calculate the 3D clearance for the shape design of an HST, which greatly reduces the development cost by minimizing the physical prototype that must be built.

This study aims to determine the differences in leaf functional traits and phenotypic plasticity of leaf functional traits between exotic and native Compositae plant species. Leaf width of exotic plants was significantly lower than that of native species. Leaf length, specific leaf area (SLA), single-leaf wet and dry weights, leaf moisture, and leaf thickness of exotic plants were also lower than those of native species but not significantly. The leaf shape index of exotic plants was higher than that of native species but not significantly. This implies that the relatively low leaf construction cost for exotic plants may play an important role in the success of their invasions. The higher leaf shape index and lower leaf width of exotic plants can enhance the efficiency of resource capture (especially sunlight capture) via adjustments to leaf shape and size, thereby increasing the survival of exotic plants. The plasticity indices of single-leaf wet weight and leaf thickness of exotic plants were significantly lower than those of native species. The lower phenotypic plasticity of single-leaf wet weight and leaf thickness of exotic plants may be the result of a cost to plasticity. That is, if the plasticity is too high, the fitness of plant species might be reduced sharply under unfavorable environments. Thus, lower plasticity of leaf functional traits may compensate for the negative impact of adverse environments and stabilize leaf construction costs for exotic plants. Moreover, reduced phenotypic plasticity might be one of the key competitive strategies by which exotic plants successfully invade new habitats. Overall, exotic plants did not always exhibit higher values of leaf functional traits or increased phenotypic plasticity of leaf functional traits compared with native species.

Squeezing ground in tunneling is associated with large deformation of the tunnel face. In this study, squeezing characteristics of the ground and rock conditions in Golab water conveyance tunnel, Iran, are discussed and the classification of squeezing behavior around zones where the problems occurred is presented. The squeezing conditions were investigated using empirical and semi empirical methods. In the next step, creep convergence of the tunnel with Burger’s model was simulated by the numerical method. Numerical analysis showed that wall displacement (64.1 mm) of the Golab tunnel was more than allowable strain (1% of the tunnel diameter), therefore, it was found that squeezing phenomenon could exist, leading to the failure of the support system. Numerical analysis at the phyllite-slate zone also showed squeezing conditions due to the weakness of rock mass and high overburden that this situation cause failure in the segmental lining. In this research, failure in segmental lining in phyllite-slate zone verified the results of the numerical modeling.

Authors’ first and last names were interchanged in the original version of the article and they should be replaced as follows: Majid Siavashi, Mohammad Jamali.