RULED SURFACE MACHINING BY 4-AXES SIMULTANEOUS CONTROL WIRE-EDM

On the tasis of study in the mathematical model of 3-dimensional ruled surface (RS),this paper introduces a new concept of distance paramcter (DP) and also puts forward that themethod of modeling a RS depends on not only two boundary curves but also DP. According toabove theory, the formulas to calculate corresponding point coordinates to any kind of top and bot-tom profile of a workpiece and formulas to calcuate the maximum inclination angle of ruling linehave been obtained. Then a different top and bottom RS mathining method including profile withline-are combination as well as parametric curves has been achieved by 4-axes simultancous con-trol programming proposed.

Cutting Path Planning for Ruled Surface Impellers

At present, most commercial computer-aided manufacturing （CAM） systems are deficient in efficiency and performances on generating tool path during machining impellers. To solve the problem, this article develops a special software to plan cutting path for ruled surface impellers. An approximation algorithm to generate cutting path for machining integral ruled surface impellers is proposed. By fitting sampling data points of an impeller blade into a curve, a model of ruled surface blade of an impeller is built up. Furthermore, by calculating the points where the cutter axis vector intersects the free-form hub surface of an impeller, problems about, for instance, the ambiguity in calculation and machining the wide blade surface with a short flute cutter are solved. Finally, an integral impeller cutting path is planned by way of an integrated cutter location control algorithm. Simulation and machining tests with an impeller are performed on a 5-axis computer numerically controlled （CNC） mill machine, which shows the feasibility of the proposed algorithm.

论“rule by law”和“rule of law”的区别

"Rule of law"和"Rule by law"两个词是当代中国对"法治"一词的两种翻译,其内涵有着本质的不同。正确地区分两者关系,不仅对于当今法制与法治的建设有着重要的借鉴价值,更有助于处理好当今政府与人民之间的权限问题,对构建现代民主基础之上的法治社会以及对依法治国的发展有着重要意义。

Collective coordination of multi-agent systems guided by multiple leaders

A neighbour-based coordination scheme is proposed for a multi-agent system with multiple leaders. Under assumptions of the connectivity of the interconnection topology and a simple first-order dynamics model for each mobile agent, the results show that all the agents will flock to the polytope region formed by the leaders.

A general metrology of stress on crystalline silicon with random crystal plane by using micro-Raman spectroscopy

The requirement of stress analysis and measurement is increasing with the great development of heterogeneous structures and strain engineering in the field of semiconductors.Micro-Raman spectroscopy is an effective method for the measurement of intrinsic stress in semiconductor structures.However,most existing applications of Raman-stress measurement use the classical model established on the (001) crystal plane.A non-negligible error may be introduced when the Raman data are detected on surfaces/cross-sections of different crystal planes.Owing to crystal symmetry,the mechanical,physical and optical parameters of different crystal planes show obvious anisotropy,leading to the Raman-mechanical relationship dissimilarity on the different crystal planes.In this work,a general model of stress measurement on crystalline silicon with an arbitrary crystal plane was presented based on the elastic mechanics,the lattice dynamics and the Raman selection rule.The wavenumberstress factor that is determined by the proposed method is suitable for the measured crystal plane.Detailed examples for some specific crystal planes were provided and the theoretical results were verified by experiments.

Combined influence of nonlinearity and dilation on slope stability evaluated by upper-bound limit analysis

The combined influence of nonlinearity and dilation on slope stability was evaluated using the upper-bound limit analysis theorem.The mechanism of slope collapse was analyzed by dividing it into arbitrary discrete soil blocks with the nonlinear Mohr–Coulomb failure criterion and nonassociated flow rule.The multipoint tangent(multi-tangent) technique was used to analyze the slope stability by linearizing the nonlinear failure criterion.A general expression for the slope safety factor was derived based on the virtual work principle and the strength reduction technique,and the global slope safety factor can be obtained by the optimization method of nonlinear sequential quadratic programming.The results show better agreement with previous research result when the nonlinear failure criterion reduces to a linear failure criterion or the non-associated flow rule reduces to an associated flow rule,which demonstrates the rationality of the presented method.Slope safety factors calculated by the multi-tangent inclined-slices technique were smaller than those obtained by the traditional single-tangent inclined-slices technique.The results show that the multi-tangent inclined-slices technique is a safe and effective method of slope stability limit analysis.The combined effect of nonlinearity and dilation on slope stability was analyzed,and the parameter analysis indicates that nonlinearity and dilation have significant influence on the result of slope stability analysis.

Influences of nonassociated flow rules on seismic bearing capacity factors of strip footing on soil slope by energy dissipation method

Seismic bearing capacity factors of a strip footing placed on soil slope were determined with both associated and nonassociated flow rules. Quasi-static representation of earthquake effects using a seismic coefficient concept was adopted for seismic bearing capacity calculations. A multi-wedge translational failure mechanism was used to obtain the seismic bearing capacity factors for different seismic coefficients and various inclined angles. Employing the associated flow rule, numerical results were compared with the published solutions. For bearing capacity factors related to cohesion and equivalent surcharge load, the maximum difference approximates 0.1%. However, the difference of bearing capacity factor related to unit weight is larger. With the two flow rules, the seismic bearing capacity factors were presented in the form of design charts for practical use. The results show that seismic bearing capacity factors related to the cohesion, the equivalent surcharge load and the unit weight increase greatly as the dilatancy angle increases, and that the nonassociated flow rule has important influences on the seismic bearing capacity.

Use Chou’s 5-Steps Rule to Predict Remote Homology Proteins by Merging Grey Incidence Analysis and Domain Similarity Analysis

Detecting remote homology proteins is a challenging problem for both basic research and drug development. Although there are a couple of methods to deal with this problem, the benchmark datasets based on which the existing methods were trained and tested contain many high homologous samples as reflected by the fact that the cutoff threshold was set at 95%. In this study, we reconstructed the benchmark dataset by setting the threshold at 40%, meaning none of the proteins included in the benchmark dataset has more than 40% pairwise sequence identity with any other in the same subset. Using the new benchmark dataset, we proposed a new predictor called “dRHP-GreyFun” based on the grey modeling and functional domain approach. Rigorous cross-validations have indicated that the new predictor is superior to its counterparts in both enhancing success rates and reducing computational cost. The predictor can be downloaded from https://github.com/jcilwz/dRHP-GreyFun.

A Study on Damage Rules on Insulators by Conducting Sols

Insulating parts are easily subjected to pollution which may cause damage to the electric system. A typical disc insulator is chosen as the target to test its flashover voltage by using an artificial pollution system. This test system aims at obtaining characteristic parameters of damage for chosen conducting sola to the selected insulator. Experimental results show that thickness and electric conductivity of pollutant layer over insulators are the main parameters in damage evaluation. The flashover voltage decreases with increase of thickness and/or conductivity. These results provide a better basis on further revealing the damaging nature of conducting sol materials.

Calculation of the Phase Equilibrium of CO2–Hydrocarbon Binary Mixtures by PR-BM EOS and PR EOS

The phase equilibrium data of CO2 hydrocarbon binary mixtures are important for the design and operation of CO 2 ood- ing, coal liquefaction, and supercritical extraction processes. Numerous pieces of binary phase equilibrium data have been obtained. Thus, models for the accurate calculation of binary and multicomponent mixtures must be developed on the basis of existing data. In this work, 3578 vapor liquid phase equilibrium data points for 10 CO 2 hydrocarbon binary mixtures, including CO2 butane, CO 2 pentane, CO 2 isopentane, C O 2 hexane, CO 2 benzene, CO 2 heptane, CO 2 octane, C O 2 non- ane, CO 2 decane, and C O 2 undecane, were collected. The PR and PR-BM equations of state (EOS) in combination with relevant mixing rules were used to calculate the phase equilibrium data of the CO 2 hydrocarbon binary mixtures. The binary interaction parameter k ij in the PR EOS was temperature independent, whereas parameters in the PR-BM EOS were functions of temperature. Thus, the phase equilibrium data and other thermodynamic properties of the binary and multicomponent mixtures at di erent temperatures and pressures can be calculated by using the parameters obtained in this work. The PR-BM EOS performed better than the PR EOS, and the average absolute deviations over the temperature range of 255.98 408.15 K calculated by the PR EOS and PR-BM EOS were less than 5.74% and 3.36%, respectively. The results calculated by the two EOS were compared with those calculated by other models, such as PPR78, PR + LCVM + UNIFAC, KIE + PR EOS + HV, and PSRK. The phase equilibrium data of CO 2 butane decane, CO 2 hexane decane, and C O 2 octane decane ternary mixtures were calculated by the two EOS. The average overall deviations for the CO 2 mole fractions calculated by the two EOS were less than 7.66%.

How the Even-Odd Rule, by Defining Electrons Pairs and Charge Positions, Can Be Used as a Substitute to the Langmuir-Octet Rule in Understanding Interconnections between Atoms in Ions and Molecules

In the course of time, numerous rules were proposed to predict how atoms connect through covalent bonds. Based on the classification of elements in the periodic table, the rule of eight was first proposed to draw formulas of organic compounds. The later named octet rule exhibited shortcomings when applied to inorganic compounds. Another rule, the rule of two, using covalent bonds between atoms, was proposed as an attempt to unify description of organic and inorganic molecules. This rule unfortunately never managed to expand the field of application of the octet rule to inorganic compounds. In order to conciliate organic and inorganic compounds, the recently put forward even-odd and the isoelectronicity rules suggest the creation of one group of compounds with pairs of electrons. These rules compass the rule of two for covalent bonds as well as the octet rule for organic compounds and suggest transforming bonds of multi-bonded compounds in order to unify representations of both groups of compounds. The aim of the present paper is fourfold: to extend the rule of two to every atom shells;to replace the well-known octet rule by the even-odd rule;to apply the isoelectronicity rule to each atom and to reduce the influence range of the charge of an atom in a compound. According to both rules, the drawing of one atom with its single-covalent bonds is described with electron pairs and charge positions. To illustrate the rules, they are applied to 3D configurations of clusters.

Non-invasive prediction of non-alcoholic steatohepatitis in Japanese patients with morbid obesity by artificial intelligence using rule extraction technology

AIM To construct a non-invasive prediction algorithm for predicting non-alcoholic steatohepatitis(NASH), we investigated Japanese morbidly obese patients using artificial intelligence with rule extraction technology.METHODS Consecutive patients who required bariatric surgery underwent a liver biopsy during the operation. Standard clinical, anthropometric, biochemical measurements were used as parameters to predict NASH and were analyzed using rule extraction technology. One hundred and two patients, including 79 NASH and 23 non-NASH patients were analyzed in order to create the predictionmodel, another cohort with 77 patients including 65 NASH and 12 non-NASH patients were analyzed to validate the algorithm.RESULTS Alanine aminotransferase, C-reactive protein, homeostasis model assessment insulin resistance, albumin were extracted as predictors of NASH using a recursive-rule extraction algorithm. When we adopted the extracted rules for the validation cohort using a highly accurate rule extraction algorithm, the predictive accuracy was 79.2%. The positive predictive value, negative predictive value,sensitivity and specificity were 88.9%, 35.7%, 86.2% and 41.7%, respectively.CONCLUSION We successfully generated a useful model for predicting NASH in Japanese morbidly obese patients based on their biochemical profile using a rule extraction algorithm.

Chebyshev spectral variational integrator and applications

The Chebyshev spectral variational integrator(CSVI) is presented in this paper. Spectral methods have aroused great interest in approximating numerically a smooth problem for their attractive geometric convergence rates. The geometric numerical methods are praised for their excellent long-time geometric structure-preserving properties.According to the generalized Galerkin framework, we combine two methods together to construct a variational integrator, which captures the merits of both methods. Since the interpolating points of the variational integrator are chosen as the Chebyshev points,the integration of Lagrangian can be approximated by the Clenshaw-Curtis quadrature rule, and the barycentric Lagrange interpolation is presented to substitute for the classic Lagrange interpolation in the approximation of configuration variables and the corresponding derivatives. The numerical float errors of the first-order spectral differentiation matrix can be alleviated by using a trigonometric identity especially when the number of Chebyshev points is large. Furthermore, the spectral variational integrator(SVI) constructed by the Gauss-Legendre quadrature rule and the multi-interval spectral method are carried out to compare with the CSVI, and the interesting kink phenomena for the Clenshaw-Curtis quadrature rule are discovered. The numerical results reveal that the CSVI has an advantage on the computing time over the whole progress and a higher accuracy than the SVI before the kink position. The effectiveness of the proposed method is demonstrated and verified perfectly through the numerical simulations for several classical mechanics examples and the orbital propagation for the planet systems and the Solar system.

pLoc_Deep-mEuk: Predict Subcellular Localization of Eukaryotic Proteins by Deep Learning

Recently, the life of worldwide human beings has been endangering by the spreading of pneu- monia-causing virus, such as Coronavirus, COVID-19, and H1N1. To develop effective drugs against Coronavirus, knowledge of protein subcellular localization is prerequisite. In 2019, a predictor called “pLoc_bal-mEuk” was developed for identifying the subcellular localization of eukaryotic proteins. Its predicted results are significantly better than its counterparts, particularly for those proteins that may simultaneously occur or move between two or more subcellular location sites. However, more efforts are definitely needed to further improve its power since pLoc_bal-mEuk was still not trained by a “deep learning”, a very powerful technique developed recently. The present study was devoted to incorporating the “deep- learning” technique and developed a new predictor called “pLoc_Deep-mEuk”. The global absolute true rate achieved by the new predictor is over 81% and its local accuracy is over 90%. Both are overwhelmingly superior to its counterparts. Moreover, a user-friendly web- server for the new predictor has been well established at http://www.jci-bioinfo.cn/pLoc_Deep-mEuk/, by which the majority of experimental scientists can easily get their desired data.

pLoc_Deep-mHum: Predict Subcellular Localization of Human Proteins by Deep Learning

Recently, the life of human beings around the entire world has been endangering by the spreading of pneumonia-causing virus, such as Coronavirus, COVID-19, and H1N1. To develop effective drugs against Coronavirus, knowledge of protein subcellular localization is indispensable. In 2019, a predictor called “pLoc_bal-mHum” was developed for identifying the subcellular localization of human proteins. Its predicted results are significantly better than its counterparts, particularly for those proteins that may simultaneously occur or move between two or more subcellular location sites. However, more efforts are definitely needed to further improve its power since pLoc_bal-mHum was still not trained by a “deep learning”, a very powerful technique developed recently. The present study was devoted to incorporate the “deep-learning” technique and develop a new predictor called “pLoc_Deep-mHum”. The global absolute true rate achieved by the new predictor is over 81% and its local accuracy is over 90%. Both are overwhelmingly superior to its counterparts. Moreover, a user-friendly web-server for the new predictor has been well established at http://www.jci-bioinfo.cn/pLoc_Deep-mHum/, which will become a very useful tool for fighting pandemic coronavirus and save the mankind of this planet.

pLoc_Deep-mVirus: A CNN Model for Predicting Subcellular Localization of Virus Proteins by Deep Learning

The recent worldwide spreading of pneumonia-causing virus, such as Coronavirus, COVID-19, and H1N1, has been endangering the life of human beings all around the world. In order to really understand the biological process within a cell level and provide useful clues to develop antiviral drugs, information of virus protein subcellular localization is vitally important. In view of this, a CNN based virus protein subcellular localization predictor called “pLoc_Deep-mVirus” was developed. The predictor is particularly useful in dealing with the multi-sites systems in which some proteins may simultaneously occur in two or more different organelles that are the current focus of pharmaceutical industry. The global absolute true rate achieved by the new predictor is over 97% and its local accuracy is over 98%. Both are transcending other existing state-of-the-art predictors significantly. It has not escaped our notice that the deep-learning treatment can be used to deal with many other biological systems as well. To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_Deep-mVirus/.

Detection of invisible phonon modes in individual defect-free carbon nanotubes by gradient-field Raman scattering

We provide an effective method to investigate the field gradient effect in nanoconfined plasmon-matter interaction.Aligned ultralong SWNTs without defects were grown on marked substrates, followed by assembling gold nanoparticle clusters around individual nanotubes. The Raman scattering behavior of a nanotube placed in an atomic scale nanogap between adjacent nanoparticles was studied. In addition to the expected plasmon-induced Raman enhancement up to 103,the defect-free D-mode of an individual SWNT induced by gradient field is found for the first time. When the light is confined at atomic scale, gradient field Raman scattering becomes significant and dipole-forbidden phonon modes can be activated by quadrupole Raman tensor variation, indicating breakdown of the Raman selection rules.

A new experimental way for the monitoring of the real/equivalent inservice- time of double base rocket propellant by coupling VST and PCA

The assessment of the real in-service-time(RIST)and the equivalent in-service-time(EIST)of double base rocket propellants(DBRPs)is of utmost importance for the safe storage and use of weapon systems as well as the efficiency of the accelerated aging plans.In this work,four DBRPs with similar chemical composition and different natural aging have been artificially aged at T?338.65 K for 4 months with sampling every 30 days.The unaged and artificially aged samples have been investigated by vacuum stability test(VST)at five isothermal temperatures(T?333.15 K,343.15 K,353.15 K,363.15 K,and 373.15 K).The volume of the evolved gases in VST was found to decrease with natural/artificial aging.Furthermore,the VST data were treated and subjected to principal component analysis(PCA).The results showed excellent discrimination of the DBRP samples according to their stability thermal properties.Most of the variance was described by the first principal component(PC1)whose scores were linearly correlated with the natural aging durations when PCA is applied on VST data obtained at T?363.15 K.In light of the obtained results,a new experimental way for the estimation of the real/equivalent IST was proposed,which takes into account the impact of the natural aging of the sample.The approach predicts successfully the RIST of two similar DBRPs with a relative deviation of less than 2%.At the specific heating temperature T?338.65 K,the developed model provides more conceivable EIST values,with asymptotic behavior against artificial aging duration evolution,thus overcoming some shortcomings of the common generalized van’t Hoff formula(GvH).

Improved slope safety analysis by new Druker-Prager type criterion

Based on Mohr-Coulomb （M-C） criterion, the parameters of Druker-Prager （D-P） criterion for geomaterial were determined under non-associated flow rule, and thus a new D-P type criterion was presented. Two assumptions were employed during the derivation： 1） principal strains by M-C model and D-P model are equal, and 2） the material is under plane strain condition. Based on the analysis of the surface on rt plane, it is found that the proposed D-P type criterion is better than the D-P criterion with M-C circumscribed circle or M-C inscribed circle, and is applicable for stress Lode angle less than zero. By comparing the predicted results with the test data of sand under plane strain condition and other D-P criteria, the proposed criterion is verified and agrees well with the test data, which is further proved to be better than other D--P type criteria in certain range of Lode angle. The criterion was compiled into a finite difference package FLAC3D by user-subroutine, and was used to analyze the stability of a slope by strength reduction method. The predicted slope safety factor from the proposed criterion agrees well with that by Spencer method, and it is more accurate than that from classic D-P criteria.

pLoc_Deep-mPlant: Predict Subcellular Localization of Plant Proteins by Deep Learning

Current coronavirus pandemic has endangered mankind life. The reported cases are increasing exponentially. Information of plant protein subcellular localization can provide useful clues to develop antiviral drugs. To cope with such a catastrophe, a CNN based plant protein subcellular localization predictor called “pLoc_Deep-mPlant” was developed. The predictor is particularly useful in dealing with the multi-sites systems in which some proteins may simultaneously occur in two or more different organelles that are the current focus of pharmaceutical industry. The global absolute true rate achieved by the new predictor is over 95% and its local accuracy is about 90%?-?100%. Both have substantially exceeded the?other existing state-of-the-art predictors. To maximize the convenience for most?experimental scientists, a user-friendly web-server for the new predictor has been established?at?http://www.jci-bioinfo.cn/pLoc_Deep-mPlant/, by which the majority of experimental?scientists can easily obtain their desired data without the need to go through the?mathematical details.