中国古典法学的知识体系

古典法学既见于西方,也见于中国。西方法学的知识体系中,有古罗马的古典法学,资本主义革命时期的古典自然法学,还有19世纪晚期兴起的英美古典法学。相较西方的古典法学,中国的古典法学源远流长,主要包含四种形态的法学知识,它们分别是:以礼为基础的礼法学,以律为基础的律法学,以经为基础的经法学,以政为基础的政法学。把这四种形态的法学知识汇聚起来,可以全面展示中国古典法学的知识体系。这四种形态的中国古典法学虽然是在不同的历史背景下分别兴起的,分别对应法的不同形态,满足不同的需要,但是它们彼此交织、相互关联,堪称中国古典法学知识体系的四大分支。

Assessing dynamic modulus properties for typical asphalt mixtures in Jiangsu

To investigate the validity of two dynamic modulus predictive models（ Witczak 1-37 A viscosity-based model and Witczak 1-40 D shear modulus-based model） in the context of Jiangsu, and evaluate the effect of different mixture design variables（ aggregate gradations, binder type, and volumetric properties） on dynamic modulus E＊, asphalt mixtures commonly used in the local surface layer, including Sup-13 and AC-13, are prepared in the laboratory and their dynamic modulus E＊values are predicted based on the above mentioned models. The corresponding asphalt tests, including viscosity and dynamic shear modulus tests, are also carried out to obtain the prediction model parameters. The test results showthat binder type and asphalt content have a significant impact on dynamic modulus.There is a good correlation between the E＊values based on above two predictive models and the measured E＊, while a relatively lower bias can be expected from Witczak 1-37 A model. The test results can be used for the calibration of dynamic modulus with higher accuracy.

Theoretical Study on Stereodynamics of Reactions of N（^2D）＋H2→NH＋H and N（^2D）＋D2→ND＋D

The vector correlations between products and reagents for the title reactions have been calculated by the quasi-classical trajectory method at a collision energy of 21.32 kJ/mol on an accurate potential energy surface of Ho et al. （J. Chem. Phys. 119, 3063 （2003））. The peaks of the product angular distribution are found to be in both backward and forward directions for the two title reactions. The product rotational angular momentum is not only aligned, but also oriented along the negative direction of y-axis. These theoretical results are in good agreement with recent experimental findings for the two title reactions. The isotopic effect is also revealed and primarily attributed to the difference of the mass factor in the two title reactions.

On Fair Prices of a Contingent Claim with Random Interval Payoff

In order to get the price of a contingent claim with random interval payoff, a concept of fair price was proposed based on weighted expected utility maximization. After setting up a programming model of maximizing the weighted expected utility involving basic securities and contingent claim,and using techniques in optimization analysis,explicit expressions of the fair price interval for a contingent claim were derived. Relations between acceptable price interval and fair price interval were discussed. It is shown that all fair prices fit the demand for acceptability of a market.

Method for Evaluating the Degrees of Land Use Sustainability of Mountainous County and its Application in Yunnan Province,China

The evaluation of sustainable land use is the key issue in the field of studying the sustainable land utilization. In general analysis, the sustainable land use is evaluated respectively from its ecological sustainability, economic sustainability and social sustainability in China and other countries in recent years. Although this evaluation is an important work, it seems insufficient and hard to comprehensively reflect the whole degree of land use sustainability. Thus, to make up this deficiency, this paper brings forward the evaluation indexes, which make it possible to quantitatively reflect the whole degree of land use sustainability, namely, the concept of ＂degrees of overall land use sustainability＂ （Dos）, and research and measurement development of the method of and calculation in Dos. Taking the evaluation of the degree of land use sustainability in county regions of Yunnan Province as the actual example for analysis, results are basically as follows： 1） The degree of land use sustainability （Dos） is the ration index to organically and systematically integrate the degree of ecological friendliness （DeF）, the degree of economic viability （Dev） and the degree of social acceptability （Dsa）, able to comprehensively reflect the whole sustainability degree of regional land use 2） Based on the value of Dos, the grading system and standard for the sustainability of land use may be established and totally divided into five grades, namely, the high-degree sustainability, middle-degree sustainability, low-degree sustainability, conditional sustainability and non-sustainability. Meanwhile, the standard for distinguishing sustainability grades has also been confirmed so as to determine the nature of sustainability degrees in different grades. This makes the possibility for the combination of nature determination with ration in research result and provides with the scientific guideline and decision-making gist for better implementation of sustainable land use strategy. 3） The practice in evaluation of sustainability degree in county regional land use in Yunnan shows that the value of the degree of land use sustainability （Dos） of whole Yunnan Province is only 58.39, belonging to the grade of low-degree sustainability. Two thirds of counties in the whole province represent the grade of ＂conditional sustainability＂ and ＂non-sustainability＂ in the sustainability of land use. Among these counties, 11.11 % shows ＂non- sustainability＇. The lowest degree of land use sustainability appears especially in the middle plateau mountain region of Northeast Yunnan, where the value of Dos in most counties （districts） is below 40 %, belonging to the grade of ＂non-sustainability＂. The sustainability degree in the karst mountainous region in lower-middle plateau mountain region in Southeast Yunnan is generally low and the value of sustainability degree （Dos） in most of the counties （cities and districts） is below 55. The value of sustainability degree （Dos） in most of the counties （cities and districts） in the north, west, northwest and southwest parts of Yunnan is below 55. This article also analyzes the reasons of low degree of sustainability in land use in Yunnan and puts forward the countermeasures to increase the degree of sustainability in land use in the whole province.

Theories and Applications of Mixed Quantum-Classical Non-adiabatic Dynamics

Electronically non-adiabatic processes are essential parts of photochemical process, collisions of excited species, electron transfer processes, and quantum information processing. Various non-adiabatic dynamics methods and their numerical implementation have been developed in the last decades. This review summarizes the most significant development of mixed quantum-classical methods and their applications which mainly include the Liouville equa- tion, Ehrenfest mean-field, trajectory surface hopping, and multiple spawning methods. The recently developed quantum trajectory mean-field method that accounts for the decoherence corrections in a parameter-free fashion is discussed in more detail.

A study of legal attributes of carbon emission rights in carbon trading

Clean Development Mechanism (CDM) has given birth to an international carbon trading market prosperity, which provides developing countries with valuable opportunity to address climate change issues right along with economic development and environmental improvement to achieve sustainable development. However, most studies of CDM focus on economics, and few on its legal problems. CDM involves too many aspects. And the clear legal attribute of trading object is the basis of progress of the transaction and also the start point of legal protection. Therefore, this paper in accordance with the inherent principle of property rights economics, and environmental economics in CDM, only discusses CDM carbon emission right legal interpretation and its attribution. The paper recommends that in order to ensure and promote the carbon emission right trading, carbon emission right should be attributed into the system of real rights to be regulated by Real Right Law. In this way, carbon emission right can gain exclusive power of possession and use, which can achieve a clear right def inition of environmental goods in line with Coase's theory to protect Chinese prof it in carbon trading market and promote the development of the carbon trading market further.

STUDY ON THE METEOROLOGICAL PREDICTION MODEL USING THE LEARNING ALGORITHM OF NEURAL ENSEMBLE BASED ON PSO ALGORITHMS

Because of the difficulty in deciding on the structure of BP neural network in operational meteorological application and the tendency for the network to transform to an issue of local solution, a hybrid Particle Swarm Optimization Algorithm based on Artificial Neural Network (PSO-BP) model is proposed for monthly mean rainfall of the whole area of Guangxi. It combines Particle Swarm Optimization (PSO) with BP, that is, the number of hidden nodes and connection weights are optimized by the implementation of PSO operation. The method produces a better network architecture and initial connection weights, trains the traditional backward propagation again by training samples. The ensemble strategy is carried out for the linear programming to calculate the best weights based on the "east sum of the error absolute value" as the optimal rule. The weighted coefficient of each ensemble individual is obtained. The results show that the method can effectively improve learning and generalization ability of the neural network.

Symmetry Analysis and Exact Solutions of (2+1)-Dimensional Sawada-Kotera Equation

Based on the symbolic computation system Maple, the infinite-dimensional symmetry group of the （2＋1）- dimensional Sawada-Kotera equation is found by the classical Lie group method and the characterization of the group properties is given. The symmetry groups are used to perform the symmetry reduction. Moreover, with Lou＇s direct method that is based on Lax pairs, we obtain the symmetry transformations of the Sawada-Kotera and Konopelchenko Dubrovsky equations, respectively.

Chemotherapy of cerebral gliomas directed by the chemosensitivity test in vitro: a clinical study

Objective： To evaluate correlation between chemosensitivity of tumor cells in vitro and their clinical responsiveness in vivo by comparing the difference of curative effect between chemotherapy of cerebral gliomas directed by chemosensitivity test in vitro and its routine chemotherapy. Methods： Sixty-two patients with cerebral gliomas were recruited as the experiment group, who had received total resection or subtotal resection of the tumor. The resected tumor cells were cultured in vitro, followed by chemosensitivity test using colorimetric MTT assay. Finally, chemotherapeutic protocol was made based on the results of the chemosensitivity test. Fifty patients with cerebral gliomas subjected to the routine chemotherapeutic protocol were simultaneously recruited as the control group, whose age, gender, survival functional status and operational fashion were matched with the experiment group. The two groups were equally followed up for the survival functional status, recurrence and death. All data were analyzed using SPSS 10.0 software. Results： At the time of evaluation, KPS values of 64.52 ± 35.84 were seen in the experiment group, and 33.60 ± 36.24 in the control group, showing statistical difference between the two groups （t = 4.5163, P = 0.000）. During 2-4 years of follow up, a recurrence rate of 32.26% was seen in the experimental group, and 60.00% in the control group, showing a statistical difference between the two groups （X^2 = 8.620, P = 0.003）. The fatality was 22.58% in the experiment group, and 48.00% in the control group, showing a statistical difference between the two groups （X^2 = 7.978, P = 0.005）. The survival rate of the experimental group was higher than that of the control group, showing a statistical differences between the two groups （X^2= 7.29, P = 0.0069）. Conclusion： Chemotherapy of glio- mas under the guidance of chemosensitivity test in vitro contributes to obvious improvement on the current survival functional status, a clear decline of the recurrence rates and fatality rate, and raised survival rates of the patients. A close correlation between the chemosensitivity in vitro and clinical responsiveness in vivo is observed.

Quasi-Classical Trajectory Study on O＋＋DH（v=0,j=0）→OD＋＋H Reaction at Different Collision Energy

The quasi-classical trajectory calculations O＋＋DH（v=0,j=0）→OD＋＋H reactions on the RODRIGO potential energy surface have been carried out to study the isotope effect on stereo-dynamics at the collision energies of 1.0, 1.5, 2.0, and 2.5 eV. The distributions of dihedral angle P（~r） and the distributions of P（Or） are discussed. Furthermore, the angular distributions of the product rotational vectors in the form of polar plot in θr and φr are calculated. The differential cross section shows interesting phenomenon that the reaction is dominated by the direct reaction mechanism. Reaction probability and reaction cross section are also calculated. The calculations indicate that the stereo-dynamics properties of the title reactions are sensitive to the collision energy.

Ship motion extreme short time prediction of ship pitch based on diagonal recurrent neural network

A DRNN (diagonal recurrent neural network) and its RPE (recurrent prediction error) learning algorithm are proposed in this paper .Using of the simple structure of DRNN can reduce the capacity of calculation. The principle of RPE learning algorithm is to adjust weights along the direction of Gauss-Newton. Meanwhile, it is unnecessary to calculate the second local derivative and the inverse matrixes, whose unbiasedness is proved. With application to the extremely short time prediction of large ship pitch, satisfactory results are obtained. Prediction effect of this algorithm is compared with that of auto-regression and periodical diagram method, and comparison results show that the proposed algorithm is feasible.

Research on High Resolution Satellite Image Classification Algorithm based on Convolution Neural Network

Artifi cial neural network is a kind of artificial intelligence method to simulate the function of human brain, and deep learning technology can establish a depth network model with hierarchical structure on the basis of artificial neural network. Deep learning brings new development direction to artificial neural network. Convolution neural network is a new artificial neural network method, which combines artificial neural network and deep learning technology, and this new neural network is widely used in many fields of computer vision. Modern image recognition algorithm requires classifi cation system to adapt to different types of tasks, and deep network and convolution neural network is a hot research topic in neural networks. According to the characteristics of satellite digital image, we use the convolution neural network to classify the image, which combines texture features with spectral features. The experimental results show that the convolution neural network algorithm can effectively classify the image.

Prediction for asphalt pavement water film thickness based on artificial neural network

In order to study the variation o f the asphalt pavement water film thickness influenced by multi-factors,anew method for predicting water film thickness was developed by the combination o f the artificial neural network(ANN)a d two-dimensional shallow water equations based on hydrodynamic theory.Multi-factors included the rainfall intensity,pavement width,cross slope,longitudinal slope a d pavement roughness coefficient.The two-dimensional hydrodynamic method was validated by a natural rainfall event.Based on the design scheme o f Shen-Sha expressway engineering project,the limited training data obtained by the two-dimensional hydrodynamic simulation model was used to predict water film thickness.Furthermore,the distribution of the water film thickness influenced by multi-factors on the pavement was analyzed.The accuracy o f the ANN model was verified by the18sets o f data with a precision o f0.991.The simulation results indicate that the water film thickness increases from the median strip to the edge o f the pavement.The water film thickness variation is obviously influenced by rainfall intensity.Under the condition that the pavement width is20m and t e rainfall intensity is3m m/h,t e water film thickness is below10mm in the fast lane and20mm in t e lateral lane.Athough there is fluctuation due to the amount oftraining data,compared with the calculation on the basis o f the existing criterion and theory,t e ANN model exhibits a better performance for depicting the macroscopic distribution of the asphalt pavement water film.

Adsorption of Rhenium（Ⅶ） with Anion Exchange Resin D318

The adsorption and mechanism of Re(Ⅶ)on resin D318 were studied using chemical methods and IR spectrometry.At pH 5.2,the static and dynamic saturation adsorption capacities were 351.4 and 366.5 mg·g-1,respectively.The adsorption behavior obeyed the Freundlich empirical equation and the adsorption rate constant k298 was 6.37×10-4s-1.The desorption percentage was up to 99.7%when 2.0 mol·L-1KSCN was used for dynamic desorption.

LEARNING ALGORITHM OF STAGE CONTROL NBP NETWORK

This letter analyzes the reasons why the known Neural Back Promulgation (NBP)network learning algorithm has slower speed and greater sample error. Based on the analysis and experiment, the training group descending Enhanced Combination Algorithm (ECA) is proposed.The analysis of the generalized property and sample error shows that the ECA can heighten the study speed and reduce individual error.

Collection Cost Screening Mechanism in a Closedloop Supply Chain

Recently, the product remanufacturing has been a hot topic in the field of operational management, and more manufacturers are beginning to recover the value in their end of life （EOI.） products hy remanufacturing. This paper focuses on the closed loop supply chain where the retailer takes charge of not only retail, but also col- lection. There are two possible types of the retailer＇s collection cost as an assumption, i.e. high cost or low cost, and the retailer knows his type, whereas the manufacturer only has a prior prohability over the two possible cost types. This paper deploys the contracts with which the manufacturer can screen the type of the retailer to improve her profit under incomplete information. As a result, the pooling contract can perfectly coordinate the decentral- ized system under incomplete information, but the manufacturer obtains the lower profit; nevertheless, with the separating contracts the manufacturer obtains the larger profits though the system profit is lower.

New generation of breast cancer clinical trials implementing molecular profiling

The implementation of molecular profiling technologies in oncology deepens our knowledge for the molecular landscapes of cancer diagnoses, identifying aberrations that could be linked with specific therapeutic vulnerabilities. In particular, there is an increasing list of molecularly targeted anticancer agents undergoing clinical development that aim to block specific molecular aberrations. This leads to a paradigm shift, with an increasing list of specific aberrations dictating the treatment of patients with cancer. This paradigm shift impacts the field of clinical trials, since the classical approach of having clinico-pathological disease characteristics dictating the patients' enrolment in oncology trials shifts towards the implementation of molecular profiling as prescreening step. In order to facilitate the successful clinical development of these new anticancer drugs within specific molecular niches of cancer diagnoses, there have been developed new, innovative trial designs that could be classified as follows: i)longitudinal cohort studies that implement(or not) "nested" downstream trials, 2) studies that assess the clinical utility of molecular profiling, 3) "master" protocol trials, iv) "basket" trials, v) trials following an adaptive design. In the present article, we review these innovative study designs, providing representative examples from each category and we discuss the challenges that still need to be addressed in this era of new generation oncology trials implementing molecular profiling. Emphasis is put on the field of breast cancer clinical trials.

Neurotrophic and metabotrophic potential of nerve growth factor and brain-derived neurotrophic factor: Linking cardiometabolic and neuropsychiatric diseases

One of biggest recent achievements of neurobiology is the study on neurotrophic factors. The neurotrophins are exciting examples of these factors. They belong to a family of proteins consisting of nerve growth fac-tor （NGF）, brain-derived neurotrophic factor （BDNF）, neurotrophin-3 （NT-3）, NT-4/5, NT-6, and NT-7. Today, NGF and BDNF are well recognized to mediate a diz-zying number of trophobiological effects, ranging from neurotrophic through immunotrophic and epitheliotro-phic to metabotrophic effects. These are implicated in the pathogenesis of various diseases. In the same vein, recent studies in adipobiology reveal that this tissue is the body’s largest endocrine and paracrine organ producing multiple signaling proteins collectively termed adipokines, with NGF and BDNF being also produced from adipose tissue. Altogether, neurobio-logy and adipobiology contribute to the improvement of our knowledge on diseases beyond obesity such as cardiometabolic （atherosclerosis, type 2 diabetes, and metabolic syndrome） and neuropsychiatric （e.g. , Alzheimer’s disease and depression） diseases. The present review updates evidence for （1） neurotrophic and metabotrophic potentials of NGF and BDNF linking the pathogenesis of these diseases, and （2） NGF- and BDNF-mediated effects in ampakines, NMDA receptor antagonists, antidepressants, selective deacetylase inhibitors, statins, peroxisome proliferator-activated receptor gamma agonists, and purinergic P2X3 recep-tor up-regulation. This may help to construct a novel paradigm in the feld of translational pharmacology of neuro-metabotrophins, particularly NGF and BDNF.

Optimized algorithm in mine production planning, mined material destination, and ultimate pit limit

An integral connection exists among the mine production planning, the mined material destination, and the ultimate pit limit （UPL） in the mining engineering economy. This relation is reinforced by real information and the benefits it engenders in the mining economy. Hence, it is important to create optimizing algorithms to reduce the errors of economic calculations. In this work, a logical mathematical algorithm that considers the important designing parameters and the mining economy is proposed. This algorithm creates an optimizing repetitive process among different designing constituents and directs them into the maximum amount of the mine economical parameters. This process will produce the highest amount of ores and the highest degree of safety. The modeling produces a new relation between the concept of the cutoff grade, mine designing, and mine planning, and it provides the maximum benefit by calculating the destination of the ores. The proposed algorithm is evaluated in a real case study. The results show that the net present value of the mine production is increased by 3% compared to previous methods of production design and UPL.