A Multi-Task Motion Generation Model that Fuses a Discriminator and a Generator

The human motion generation model can extract structural features from existing human motion capture data,and the generated data makes animated characters move.The 3D human motion capture sequences contain complex spatial-temporal structures,and the deep learning model can fully describe the potential semantic structure of human motion.To improve the authenticity of the generated human motion sequences,we propose a multi-task motion generation model that consists of a discriminator and a generator.The discriminator classifies motion sequences into different styles according to their similarity to the mean spatial-temporal templates from motion sequences of 17 crucial human joints in three-freedom degrees.And target motion sequences are created with these styles by the generator.Unlike traditional related works,our model can handle multiple tasks,such as identifying styles and generating data.In addition,by extracting 17 crucial joints from 29 human joints,our model avoids data redundancy and improves the accuracy of model recognition.The experimental results show that the discriminator of the model can effectively recognize diversified movements,and the generated data can correctly fit the actual data.The combination of discriminator and generator solves the problem of low reuse rate of motion data,and the generated motion sequences are more suitable for actual movement.

Kinetics and model of gas generation of source rocks in the deepwater area, Qiongdongnan Basin

In order to investigate the hydrocarbon generation process and gas potentials of source rocks in deepwater area of the Qiongdongnan Basin, kinetic parameters of gas generation （activation energy distribution and frequency factor） of the Yacheng Formation source rocks （coal and neritic mudstones） was determined by thermal simulation experiments in the closed system and the specific KINETICS Software. The results show that the activation energy （Ea） distribution of C1–C5 generation ranges from 50 to 74 kcal/mol with a frequency factor of 2.4×1015 s–1 for the neritic mudstone and the Ea distribution of C1–C5 generation ranges from 49 to 73 kcal/mol with a frequency factor of 8.92×1013 s–1 for the coal. On the basis of these kinetic parameters and combined with the data of sedimentary burial and paleothermal histories, the gas generation model of the Yacheng Formation source rocks closer to geological condition was worked out, indicating its main gas generation stage at Ro （vitrinite reflectance） of 1.25%–2.8%. Meanwhile, the gas generation process of the source rocks of different structural locations （central part, southern slope and south low uplift） in the Lingshui Sag was simulated. Among them, the gas generation of the Yacheng Formation source rocks in the central part and the southern slope of the sag entered the main gas window at 10 and 5 Ma respectively and the peak gas generation in the southern slope occurred at 3 Ma. The very late peak gas generation and the relatively large gas potential indices （GPI：20×10^8–60×10^8 m^3/km^2） would provide favorable conditions for the accumulation of large natural gas reserves in the deepwater area.

Study on End Milling Generation Surface Model and Simulation in View of Main Axle's Tolerance

In accordance with the relative movement between end-milling cutter and workpiece surface, a theoretical generation model for milled surface was established with the movement error of principal axle considered. Then the milled surfaces under various cutting condition were simulated, the results of which showed that end milled surfaces were of "vaulted profile", heights of surface irregularty at various points to be different with maximum value in the middle and smaller at both sides, the difference were determined by diameter of milling cutter, feeding speed, ratio between the diameter of milling cutter and teeth point curve radius and width of workpiece. The study results can be applied to quality prediction of milled surfaces for precision and/or super precision milling operation.

Temperature- and voltage-dependent trap generation model in high-k metal gate MOS device with percolation simulation

High-k metal gate stacks are being used to suppress the gate leakage due to tunneling for sub-45 nm technology nodes.The reliability of thin dielectric films becomes a limitation to device manufacturing,especially to the breakdown characteristic.In this work,a breakdown simulator based on a percolation model and the kinetic Monte Carlo method is set up,and the intrinsic relation between time to breakdown and trap generation rate R is studied by TDDB simulation.It is found that all degradation factors,such as trap generation rate time exponent m,Weibull slope β and percolation factor s,each could be expressed as a function of trap density time exponent α.Based on the percolation relation and power law lifetime projection,a temperature related trap generation model is proposed.The validity of this model is confirmed by comparing with experiment results.For other device and material conditions,the percolation relation provides a new way to study the relationship between trap generation and lifetime projection.

Monetary policy rules：Forward-looking and backward-looking in an overlapping generations model

In the framework of an overlapping generations model, forward-looking monetary policy roles and backward-looking monetary policy rules were investigated. It is shown that the monetary steady state is more likely to be indeterminate under an active forwardlooking rule than under the corresponding backward-looking rule. It is also shown that backward-looking roles can render the monetary steady state unstable.

Automated Service Search Model for the Social Internet of Things

The social internet of things(SIoT)is one of the emerging paradigms that was proposed to solve the problems of network service discovery,navigability,and service composition.The SIoT aims to socialize the IoT devices and shape the interconnection between them into social interaction just like human beings.In IoT,an object can offer multiple services and different objects can offer the same services with different parameters and interest factors.The proliferation of offered services led to difficulties during service customization and service filtering.This problem is known as service explosion.The selection of suitable service that fits the requirements of applications and objects is a challenging task.To address these issues,we propose an efficient automated query-based service search model based on the local network navigability concept for the SIoT.In the proposed model,objects can use information from their friends or friends of their friends while searching for the desired services,rather than exploring a global network.We employ a centrality metric that computes the degree of importance for each object in the social IoT that helps in selecting neighboring objects with high centrality scores.The distributed nature of our navigation model results in high scalability and short navigation times.We verified the efficacy of our model on a real-world SIoT-related dataset.The experimental results confirm the validity of our model in terms of scalability,navigability,and the desired objects that provide services are determined quickly via the shortest path,which in return improves the service search process in the SIoT.

Model for Generating Scale-Free Artificial Social Networks Using Small-World Networks

The Internet of Things(IoT)has the potential to be applied to social networks due to innovative characteristics and sophisticated solutions that challenge traditional uses.Social network analysis(SNA)is a good example that has recently gained a lot of scientific attention.It has its roots in social and economic research,as well as the evaluation of network science,such as graph theory.Scientists in this area have subverted predefined theories,offering revolutionary ones regarding interconnected networks,and they have highlighted the mystery of six degrees of separation with confirmation of the small-world phenomenon.The motivation of this study is to understand and capture the clustering properties of large networks and social networks.We present a network growth model in this paper and build a scale-free artificial social network with controllable clustering coefficients.The random walk technique is paired with a triangle generating scheme in our proposed model.As a result,the clustering controlmechanism and preferential attachment(PA)have been realized.This research builds on the present random walk model.We took numerous measurements for validation,including degree behavior and the measure of clustering decay in terms of node degree,among other things.Finally,we conclude that our suggested random walk model is more efficient and accurate than previous state-of-the-art methods,and hence it could be a viable alternative for societal evolution.

REVIEW OF HIGH LEVEL FAULT MODELING APPROACHES FOR MIXED-SIGNAL SYSTEMS

In the modern analogue design, Transistor Level Fault Simulation (TLFS) plays the im-portant part since every fault in the whole circuit has to be simulated at that level. Unfortunately, it is a very CPU intensive task even though it maintains the high accuracy. Therefore, High Level Fault Modeling (HLFM) and High Level Fault Simulation (HLFS) are required in order to alleviate the efforts of simulation. In this paper, different HLFM approaches are reviewed at the device level during last two decades. We clarify their domains of application and evaluate their strengths and current limitations. We also analyze causes of faults and introduce various test approaches.

Wash Waves Generated by High Speed Displacement Ships

It is difficult to compute far-field waves in a relative large area by using one wave generation model when a large calculation domain is needed because of large dimensions of the waterway and long distance of the required computing points. Variation of waterway bathymetry and nonlinearity in the far field cannot be included in a ship fixed process either. A coupled method combining a wave generation model and wave propagation model is then used in this paper to simulate the wash waves generated by the passing ship. A NURBS-based higher order panel method is adopted as the stationary wave generation model; a wave spectrum method and Boussinesq-type equation wave model are used as the wave propagation model for the constant water depth condition and variable water depth condition, respectively. The waves calculated by the NURBS-based higher order panel method in the near field are used as the input for the wave spectrum method and the Boussinesq-type equation wave model to obtain the far-field waves. With this approach it is possible to simulate the ship wash waves including the effects of water depth and waterway bathymetry. Parts of the calculated results are validated experimentally, and the agreement is demonstrated. The effects of ship wash waves on the moored ship are discussed by using a diffraction theory method. The results indicate that the prediction of the ship induced waves by coupling models is feasible.

Low organic matter abundance and highly efficient hydrocarbon generation of saline source rock in the Qaidam Basin,NW China

The geochemical analysis and experimental simulation are comprehensively used to systematically study the hydrocarbon generation material,organic matter enrichment and hydrocarbon generation model of Paleogene source rock in the Western Qaidam Depression,Qaidam Basin,NW China.Three main factors result in low TOC values of saline lacustrine source rock of the Qaidam Basin:relatively poor nutrient supply inhibits the algal bloom,too fast deposition rate causes the dilution of organic matter,and high organic matter conversion efficiency causes the low residual organic carbon.For this type of hydrogen-rich organic matter,due to the reduction of organic carbon during hydrocarbon generation,TOC needs to be restored based on maturity before evaluating organic matter abundance.The hydrocarbon generation of saline lacustrine source rocks of the Qaidam Basin is from two parts:soluble organic matter and insoluble organic matter.The soluble organic matter is inherited from organisms and preserved in saline lacustrine basins.It generates hydrocarbons during low-maturity stage,and the formed hydrocarbons are rich in complex compounds such as NOS,and undergo secondary cracking to form light components in the later stage;the hydrocarbon generation model of insoluble organic matter conforms to the traditional“Tissot”model,with an oil generation peak corresponding to Ro of 1.0%.

Projecting future precipitation change across the semi-arid Borana lowland,southern Ethiopia

Climate change caused by past,current,and future greenhouse gas emissions has become a major concern for scientists in the field in many countries and regions of the world.This study modelled future precipitation change by downscaling a set of large-scale climate predictor variables(predictors)from the second generation Canadian Earth System Model(CanESM2)under two Representative Concentration Pathway(RCP)emission scenarios(RCP4.5 and RCP8.5)in the semi-arid Borana lowland,southern Ethiopia.The Statistical DownScaling Model(SDSM)4.2.9 was employed to downscale and project future precipitation change in the middle(2036-2065;2050s)and far(2066-2095;2080s)future at the local scale.Historical precipitation observations from eight meteorological stations stretching from 1981 to 1995 and 1996 to 2005 were used for the model calibration and validation,respectively,and the time period of 1981-2018 was considered and used as the baseline period to analyze future precipitation change.The results revealed that the surface-specific humidity and the geopotential height at 500 hPa were the preferred large-scale predictors.Compared to the middle future(2050s),precipitation showed a much greater increase in the far future(2080s)under both RCP4.5 and RCP8.5 scenarios at all meteorological stations(except Teletele and Dillo stations).At Teltele station,the projected annual precipitation will decrease by 26.53%(2050s)and 39.45%(2080s)under RCP4.5 scenario,and 34.99%(2050s)and 60.62%(2080s)under RCP8.5 scenario.Seasonally,the main rainy period would shift from spring(March to May)to autumn(September to November)at Dehas,Dire,Moyale,and Teltele stations,but for Arero and Yabelo stations,spring would consistently receive more precipitation than autumn.It can be concluded that future precipitation in the semi-arid Borana lowland is predicted to differ under the two climate scenarios(RCP4.5 and RCP8.5),showing an increasing trend at most meteorological stations.This information could be helpful for policymakers to design adaptation plans in water resources management,and we suggest that the government should give more attention to improve early warning systems in drought-prone areas by providing dependable climate forecast information as early as possible.

Exploration progress of the Paleogene in Jiyang Depression,Bohai Bay Basin

With increased exploration in the faulted basins of eastern China,petroleum exploration in this region has been challenged by unclear remaining petroleum resources distribution,complex reservoir and hydrocarbon enrichment patterns,and lacking of suitable exploration techniques.Aiming at resolving these problems,studies on source rocks,reservoirs,hydrocarbon accumulation and geophysical prospection were carried out by laboratory analysis,reservoir anatomy,and seismic analysis.A highlyefficient hydrocarbon generation/expulsion model of source rocks in saline environment was established,which aided in the discovery of a new set of source rocks in the Jiyang Depression.This study also reveals the formation process of high-quality reservoir by alternating acid and alkaline fluids during deposition and diagenesis,and pattern of secondary pores development in deep clastic rocks.Through the fine anatomy of the oil reservoirs,an orderly distribution pattern of the oil reservoirs is established,and the potential exploration targets in the undrilled area are identified.In addition,single-point highdensity seismic acquisition and high-resolution imaging technologies are developed,enabling fine and efficient exploration in areas with high exploration maturity.The research result plays a leading and demonstrative role in the fine and efficient exploration of faulted basins in eastern China.

Immature Oils in China and Their Genetic Mechanisms

Immature crude oils are a kind of unconventional petroleum resources. They are generated through early low-temperature biochemical/chemical reactions of some specific organic matter. Their geological reserves explored are as high as several hundred million tons in China. Based on a detailed organic geochemical study, five genetic mechanisms of immature oils have been proposed in this paper for early hydrocarbon generation from suberinite, resinite, bacteria-reworked terrestrial organic matter, biolipids and sulphur-rich macromolecules respectively.

Modeling of the nonlinear acoustic field generated from a phased array using Gaussian superposition technique

The nonlinearity has significant effect on the ultrasonic therapy using phased ar- rays. A numerical approach is developed to calculate the nonlinear sound field generated from a phased array based on the Gaussian superposition technique. The parameters of the phased array elements are first estimated from the focal parameters using the inverse matrix algorithm; Then the elements are expressed as a set of Gaussian functions; Finally, the nonlinear sound field can be calculated using the Gaussian superposition technique. In the numerical simulation, a 64~ 1 phased array is used as the transmitter. In the linear case, the difference between the results of the Gaussian superposition technique and the Fresnel integral is less than 0.5%, which verifies the feasibility of the approach. In the nonlinear case, the nonlinear fields of single-focus modes and double-focus modes are calculated. The results reveal that the nonlinear effects can improve the focusing performance, and the nonlinear effects are related with the source pressures and the excitation frequencies.

Improvement and optimization for the first order decay model parameters at typical municipal solid waste landfills in China

Landfill gas(LFG)generation is commonly modeled by using a first-order model.Methane generation potential(L0)and methane generation rate constant(k)are two key parameters in the first-order model.Coal-ash based default values or roughly analyzed values often used in China may not be appropriate for accurately estimating of LFG generation.In this study,seven groups of parameters were evaluated by comparing the theoretical predictions with real measurements from five Chinese landfills.The optimal approach for calculating L0 is the use of site-specific waste composition and the default values of degradable organic carbon(DOC)reported by the Chinese industry standard(CJJ133-2009),and the matching k can be adjusted by fitting and regression.The optimized average values were L0=67 m3 Mg−1,k=0.06 per year for landfills in Beijing and Zhengzhou in cold–dry regions,L0=69 m3 Mg−1,k=0.16 per year for landfill in Shanghai in cold–wet region,and L0=64 m3 Mg−1,k=0.21 per year for landfills in Guangzhou and Shenzhen in hot–wet regions.Monte Carlo analysis showed that the uncertainty of LFG generation at closure year varied in−22.5%to 20.5%,−17.1%to 17.1%and−28.2%to 34.7%for three climatic regions,respectively.The k value is the key influencing factor,with a 95.6%contribution ratio in the hot–wet region landfill.The results provide references for future better waste management.

Hydrocarbon Generation Characteristics of Source Rocks from Different Saline Environments in the Dongpu Depression,Bohai Bay Basin,China

The Dongpu Depression is a secondary salt-bearing tectonic unit in the Bohai Bay Basin,eastern China.The depositional environment of this depression regarding its Paleogene strata is clearly different in plane,including the saltwater environment(SE)in the north,the freshwater environment(FE)in the south and the brackish water environment(BE)in the middle.The result of oil and gas exploration in the Dongpu Depression shows that more than 90%of the proven oil reserves are distributed in the northern saltwater environment.Previous studies indicate that the organic geochemistry characteristics and the hydrocarbon generation capacity of the source rocks are very clearly diverse under different environments,which results in the significant differences in the proved reserves between the north and the south.In order to further explore the differences in the hydrocarbon generation capacity of the source rocks under distinct depositional environments and the mechanism of their occurrence,three samples from different depositional environments(W18-5 for SE,H7-18 for BE,CH9 for FE)were used for confined gold tube pyrolysis experiments.The results show that the CH4 yields of W18-5,H7-18 and CH9 increase with increasing temperature,the maximum yields being 405.62 mg/g TOC,388.56 mg/g TOC and 367.89 mg/g TOC,respectively.The liquid hydrocarbon yields of W18-5,H7-18 and CH9 firstly increase with increasing temperature and then decrease after the critical temperatures.The maximum yields of C6-14 are 149.54 mg/g TOC,140.18 mg/g TOC and 116.94 mg/g TOC,the maximum yields of C14+being 852.4 mg/g TOC,652.6 mg/g TOC and 596.41 mg/g TOC,respectively for W18-5,H7-18 and CH9.To summarize,the order of hydrocarbon potential from high to low is W18-5,H7-18 and CH9.On this basis,through analyzing the influencing factors of hydrocarbon differences,this paper reveals that the saltwater environment is characterized by 4 factors:higher salinity,halophilic algae,high paleo-productivity and a strongly reducing environment,which are beneficial to the enrichment of organic matter and lead to the formation of high levels of sapropelite and exinite.According to the variation of oil and gas components in the pyrolysis experiments,the hydrocarbon generation process is divided into three stages:kerogen cracking,oil cracking and C2-5 cracking.Combined with hydrocarbon generation characteristics and stages,the evolutionary model of hydrocarbon generation for source rocks under different environments is established.

Parity Violation in Weak Nuclear Interactions

The treatment of parity violations in the weak nuclear interactions is discussed within the frameworks of both the Standard Model (SM) and the Generation Model (GM) of particle physics. It will be demonstrated that several important differences between these two models lead to the SM merely describing the parity violations, while the GM provides an understanding of the cause of the parity violations in weak nuclear interactions. The significant differences arising from several dubious assumptions made during the development of the SM, lead to very different conclusions concerning the nature of the parity violations in the two models. While the SM is able to describe the observed parity violations in terms of a “V-A” theory of the weak nuclear interactions, the GM is also able to demonstrate the cause of the observed parity violations: in the GM, the observed parity violations arise as a consequence of the negative intrinsic parity of both the W massive bosons, which mediate these so-called charge-changing (CC) weak nuclear interactions.

Inductive Model Generation for Text Classification Using a Bipartite Heterogeneous Network

Algorithms for numeric data classification have been applied for text classification. Usually the vector space model is used to represent text collections. The characteristics of this representation such as sparsity and high dimensionality sometimes impair the quality of general-purpose classifiers. Networks can be used to represent text collections, avoiding the high sparsity and allowing to model relationships among different objects that compose a text collection. Such network- based representations can improve the quality of the classification results. One of the simplest ways to represent textual collections by a network is through a bipartite heterogeneous network, which is composed of objects that represent the documents connected to objects that represent the terms. Heterogeneous bipartite networks do not require computation of similarities or relations among the objects and can be used to model any type of text collection. Due to the advantages of representing text collections through bipartite heterogeneous networks, in this article we present a text classifier which builds a classification model using the structure of a bipartite heterogeneous network. Such an algorithm, referred to as IMBHN （Inductive Model Based on Bipartite Heterogeneous Network）, induces a classification model assigning weights to objects that represent the terms for each class of the text collection. An empirical evaluation using a large amount of text collections from different domains shows that the proposed IMBHN algorithm produces significantly better results than k-NN, C4.5, SVM, and Naive Bayes algorithms.

Efficient generation of the mouse model with a defined point mutation through haploid cell-mediated gene editing

Generation of mouse models carrying a defined point mutation,especially disease-related point mutations,is of considerable interest for research in biology and medicine.The standard method based on embryonic stem cell（ESC）-mediated homologous recombination（HR）is time-and labor-consuming.

An Improvement of Herbrand's Theorem and Its Application to Model Generation Theorem Proving

This paper presents an improvement of Herbrand＇s theorem. We propose a method for specifying a subuniverse of the Herbrand universe of a clause set S for each argument of predicate symbols and function symbols in S. We prove that a clause set S is unsatisfiable if and only if there is a finite unsatisfiable set of ground instances of clauses of S that are derived by only instantiating each variable, which appears as an argument of predicate symbols or function symbols, in S over its corresponding argument＇s sub-universe of the Herbrand universe of S. Because such sub-universes are usually smaller （sometimes considerably） than the Herbrand universe of S, the number of ground instances may decrease considerably in many cases. We present an algorithm for automatically deriving the sub-universes for arguments in a given clause set, and show the correctness of our improvement. Moreover, we introduce an application of our approach to model generation theorem proving for non-range-restricted problems, show the range-restriction transformation algorithm based on our improvement and provide examples on benchmark problems to demonstrate the power of our approach.