重新分析的无标化解释

语法化理论和历史句法学某些重要文献对重新分析的动因及单向性的解释仍有进一步完善的余地。本文基于汉语及跨语言资料提出“无标化解释”，认为促使重新分析实际发生并常呈单向性的根本原因是人类语言对无标记状态的追求。表达需求的无限拓展和表达方式的新奇性追求总会诱发语言的有标记现象，主要由现有手段的扩展所致，可称旧瓶装新酒现象。对此，语言会产生回归无标记状态的推力，于是通过重新分析实现无标化，产生新酒塑新瓶的效应。无标化的路向主要有两种，一种是结构简化（包括几种具体情况）。一种是语法形式和语义的自然匹配。两种因素总体上是合力共谋关系，有时主要由一个因素起作用，但一般不会发生二者的矛盾冲突。

Marker_Free: a Novel Tendency of Transgenic Plants

Marker free is a rapidly developed strategy that offers a new approach for the elimination of public concerns caused by the selectable marker genes conferring antibiotic or herbicide resistance and so on. Furthermore, marker_free transgenic plants (MFTPs) have a number of special advantages, such as decreasing the concerns about safety of selectable marker and stacking transgenes progressively into transgenic plants, which significantly owns potential application value. Major approaches developed recently for obtaining MFTPs were reviewed in this paper.

On the Computation of Noether Normalization

This paper considered the Noether normalization of a finitely generated algebra over an algebraically closed field. It gives a necessary and sufficient condition as well as an algorithm for the identification of those algebraically independent variables, then uses these elements to construct the Noether normalization of this algebra.

The Experimental Research on the Frameless Registration of DSA/CT Images

DSA images show vessels with clarity and CT images show bones distinctly. In this paper, we present an experimental research on the frameless registration of DSA/CT images based on localization algorithm. With four external markers, the vessels and bones in human brain can be integrated. The mean accuracy of simulated experiment is about 2.0 mm. The experiment proved that the 3D images composed cerebral anatomy and vasculature could help neurosurgeons perform accurate diagnosis and make right operation planning.

Self-organized Criticality in a Modified Evolution Model on Generalized Barabasi-Albert Scale-Free Networks

A modified evolution model of self-organized criticality on generalized Barabasi-Albert （GBA）.scale-free networks is investigated. In our model, we find that spatial and temporal correlations exhibit critical behaviors. More importantly, these critical behaviors change with the parameter b, which weights the distance in comparison with the degree in the GBA network evolution.

A novel localization and orientation method for an objective embedded with a rectangle magnet

To wirelessly obtain the accurate location and orientation of an objective and exert an appropriate guidance for the objective, a feasible approach is to enclose a small rectangular permanent mag- net in the objective. The magnetic field, produced by the rectangular magnet can be detected by magnetic sensors outside the objective. With these sensor data, the 3D localization and 3D orienta- tion parameters can be computed based on the mathematic model of the rectangular magnet magnetic field. In this 6D localization and orientation system, we first obtain 5D parameters of the objective by dipole model, then based on these parameters we can obtain 6D parameters by the model of rectangular magnet magnetic field using the particle swarm optimization （PSO） algorithm. Simulation experiments show that the proposed approach achieves ~ood performance.

Dynamic reactive power planning method for CSP-PV hybrid power generation system

Aiming at the faults of some weak nodes in the concentrated solar power-photovoltaic(CSP-PV)hybrid power generation system,it is impossible to restore the transient voltage only relying on the reactive power regulation capability of the system itself.We propose a dynamic reactive power planning method suitable for CSP-PV hybrid power generation system.The method determines the installation node of the dynamic reactive power compensation device and its compensation capacity based on the reactive power adjustment capability of the system itself.The critical fault node is determined by the transient voltage stability recovery index,and the weak node of the system is initially determined.Based on this,the sensitivity index is used to determine the installation node of the dynamic reactive power compensation device.Dynamic reactive power planning optimization model is established with the lowest investment cost of dynamic reactive power compensation device and the improvement of system transient voltage stability.Furthermore,the component of the reactive power compensation node is optimized by particle swarm optimization based on differential evolution(DE-PSO).The simulation results of the example system show that compared with the dynamic position compensation device installation location optimization method,the proposed method can improve the transient voltage stability of the system under the same reactive power compensation cost.

Multi-objective optimization sensor node scheduling for target tracking in wireless sensor network

Target tracking in wireless sensor network usually schedules a subset of sensor nodes to constitute a tasking cluster to collaboratively track a target.For the goals of saving energy consumption,prolonging network lifetime and improving tracking accuracy,sensor node scheduling for target tracking is indeed a multi-objective optimization problem.In this paper,a multi-objective optimization sensor node scheduling algorithm is proposed.It employs the unscented Kalman filtering algorithm for target state estimation and establishes tracking accuracy index,predicts the energy consumption of candidate sensor nodes,analyzes the relationship between network lifetime and remaining energy balance so as to construct energy efficiency index.Simulation results show that,compared with the existing sensor node scheduling,our proposed algorithm can achieve superior tracking accuracy and energy efficiency.

Contamination of Water for Domestic Use and Human Consumption by Heavy Metals Derived from Mining Activity in Parral, Chihuahua, Mexico

Research was done with the objective of evaluating the quality of water supplied to the potable water system in Hidalgo Del Parral, which comes from two main supply sources： wells from ＂Valle del Verano＂, which provide water to the east side of the city, and the Water Treatment Plant, which receives water from different mines and supplies the west side of the city. When this plant is overcome on its capacity of treatment, a part of the water from the mines is fed directly to the northwest part of the city. The metals lead （Pb）, chromium （Cr）, cadmium （Cd）, zinc （Zn）, and arsenic （As） were analyzed by atomic absorption （AA） technique, based on the United States Environmental Protection Agency （EPA） Method 7000B （Revision 2, February 2007）. The digestion process was done according to the guidelines established in Method NMX-AA-051-SCFI-2001, Analysis of Water-Determination of Metals by Atomic Absorption, developed by the National Standardization Technical Committee for Environmental Protection （Mexico）. The samples were collected from the following points： 13 wells and 2 re-pumping stations of ＂Valle del Verano＂, the inlet and outlet of the Water Treatment Plant, and domestic faucets. The east side of the city, supplied by the wells of ＂Valle del Verano＂, is metal-pollution free. The water that comes from the mines contains high concentrations of As, Zn, Cd and Pb, with levels that can get to 0.12, 32.6, 0.26 and 3.5 mg/L, respectively. This water pollution generated by mining can be concluded from the high levels found in the domestic samples in which, for several points, the concentrations exceed the parameters set by the current guideline. According to the results, it is vital to set a plan of remediation for the water that comes from the mines, because there is a great risk for health in the consumotion of this water.

Multi-objective pigeon-inspired optimization for brushless direct current motor parameter design

Pigeon-inspired optimization(PIO) is a new swarm intelligence optimization algorithm, which is inspired by the behavior of homing pigeons. A variant of pigeon-inspired optimization named multi-objective pigeon-inspired optimization(MPIO) is proposed in this paper. It is also adopted to solve the multi-objective optimization problems in designing the parameters of brushless direct current motors, which has two objective variables, five design variables, and five constraint variables. Furthermore, comparative experimental results with the modified non-dominated sorting genetic algorithm are given to show the feasibility, validity and superiority of our proposed MIPO algorithm.

Effects of Some Topological Ingredients on the Evolutionary Ultimatum Game

This study aims at figuring out the crucial topological ingredients which affect the outcomes of the ultimatum game located on different networks, encompassing the regular network, the random network, the smallworld network, and the scale-free network. With the aid of random interchanging algorithm, we investigate the relations between the outcomes of the ultimatum game and some topological ingredients, including the average range, the clustering coefficient and the heterogeneity, and so forth. It is found that for the regular, random and small-work networks, the average range and the clustering coefficient have evident impacts on the ultimatum game, while for the scale-free network, the original degree heterogeneity and the underlying rich-club characterizations are the mainly important topological ingredients that influence the outcomes of ultimatum game substantially.

Soft-Control for Collective Opinion of Weighted DeGroot Model

The DeGroot model is a classic model to study consensus of opinion in a group of individuals(agents). Consensus can be achieved under some circumstances. But when the group reach consensus with a convergent opinion value which is not what we expect, how can we intervene the system and change the convergent value? In this paper a mechanism named soft control is first introduced in opinion dynamics to guide the group's opinion when the population are given and evolution rules are not allowed to change. According to the idea of soft control, one or several special agents,called shills, are added and connected to one or several normal agents in the original group. Shills act and are treated as normal agents. The authors prove that the change of convergent opinion value is decided by the initial opinion and influential value of the shill, as well as how the shill connects to normal agents. An interesting and counterintuitive phenomenon is discovered: Adding a shill with an initial opinion value which is smaller(or larger) than the original convergent opinion value dose not necessarily decrease(or increase) the convergent opinion value under some conditions. These conditions are given through mathematical analysis and they are verified by the numerical tests. The authors also find out that the convergence speed of the system varies when a shill is connected to different normal agents. Our simulations show that it is positively related to the degree of the connected normal agent in scale-free networks.

Toward Seamless Indoor-Outdoor Applications:Developing Stakeholder-Oriented Location-Based Services

Location-Based Services (LBS),an emerging new business based on smartphone and mobile networks,are becoming more and more popular.Most of these LBSs,however,only offer non-seamless indoor/outdoor applications and simple applications without giving stakeholders the chance to play an active role.Our specific aim is to solve these issues.This paper presents concepts to solve these issues by expanding the Open Location Services Interface Standard (OpenLS) to allow seamless indoor/outdoor positioning and to extend the content of the services to include information recommended by stakeholders.

Ultrasensitive label-free electrochemiluminescence immunosensor based on N-(4-aminobutyl)-N-ethylisoluminol-functionalized graphene composite

The electrochemiluminescence(ECL) behavior of N-(4-aminobutyl)-N-ethylisoluminol(ABEI)-functionalized graphene composite(ABEI-GC) modified on an indium tin oxide(ITO) electrode was studied. ABEI-GC exhibited excellent ECL activity. On this basis, a label-free ECL immunosensor was developed for the sensitive detection of human immunoglobulin G(h Ig G) by using ABEI-GC as the ECL nano-interface via a layer-by-layer assembly technique. ABEI-GC was first assembled onto an ITO electrode. Positively charged chitosan was then electrostatically adsorbed to the modified electrode. Finally, negatively charged antibody-coated gold nanoparticles were attached to the surface to form the ECL immunosensor. In the presence of h Ig G, h Ig G was captured by its antibody. In addition, an ECL signal was detected in the presence of H2O2 when a double potential was applied. The ECL immunosensor for the determination of h Ig G showed a linear range of 1.0×10-13–1.0×10-8 g/mL with a detection limit of 5.0×10-14 g/m L. This immunosensor has high sensitivity, wide linearity and good reproducibility. The superior sensitivity of the proposed ECL immunoassay mainly derives from the incorporation of ABEI-GC, which not only improves the ECL intensity, response speed, and stability, but also provides a large specific surface for high levels of protein loading. This work reveals that ABEI-GC is good nano-interface for the construction of ECL biosensors. Our strategy is promising for protein detection and may open up a new avenue for ultrasensitive label-free immunoassays.

Functionalized CVD monolayer graphene for label-free impedimetric biosensing

Recent advances in large area graphene growth have led to many applications in different areas. In the present study, chemical vapor deposited （CVD） monolayer graphene supported on glass substrate electrochemical biosensing applications was examined as electrode material for We report a facile strategy for covalent functionalization of CVD monolayer graphene by electrochemical reduction of carboxyphenyl diazonium salt prepared in situ in acidic aqueous solution. The carboxyphenyl-modified graphene is characterized using Raman spectroscopy, X-ray photoelectron spectroscopy （XPS）, and atomic force microscopy （AFM）, as well as electrochemical impedance spectroscopy （hIS）. We also show that the number of grafted carboxyphenyl groups on the graphene surface can be controlled by the number of cyclic voltammetry （CV） scans used for electrografting. We further present the fabrication and characterization of an immunosensor based on immobilization of ovalbumin antibody on the graphene surface after the activation of the grafted carboxylic groups via EDC/NHS chemistry. The binding between the surface-immobilized antibodies and ovalbumin was then monitored using Faradaic EIS in [Fe（CN）6]^3-/4- solution. The percentage change of charge transfer resistance （Rct） after binding exhibited a linear dependence for ovalbumin concentrations ranging from 1.0 pg·mL^-1 to 100 ng·mL^-1, with a detection limit of 0.9 pg·mL^-1. Our results indicate good sensitivity of the developed functionalized CVD graphene platform, paving the way for using CVD monolayer graphene in a variety of electrochemical biosensing devices.

Biological object recognition approach using space variant resolution and pigeon-inspired optimization for UAV

Recognizing the target from a rotated and scaled image is an important and difficult task for computer vision. Visual system of humans has a unique space variant resolution mechanism(SVR) and log-polar transformations(LPT) is a mapping method that is invariant to rotation and scale. Motivated by biological vision, we propose a novel global LPT based template-matching algorithm(GLPT-TM) which is invariant to rotational and scale changes; and with pigeon-inspired optimization(PIO) used to optimize search strategy, a hybrid model of SVR and pigeon-inspired optimization(SVRPIO) is proposed to accomplish object recognition for unmanned aerial vehicles(UAV) with rotational and scale changes of the target. To demonstrate the efficiency, effectiveness and reliability of the proposed method, a series of experiments are carried out. By rotating and scaling the sample image randomly and recognizing the target with the method, the experimental results demonstrate that our proposed method is not only efficient due to the optimization, but effective and accurate in recognizing the target for UAV.