Research on various factors influencing the moisture absorption property of sodium polyacrylate

Sodium polyacrylate was synthesized with acrylic acid as the monomer, and sodium bisulfate and ammonium persulfate as the initiator, by means of aqueous solution polymerization. The factors influencing the properties of moisture absorption, such as monomer concentration, dosage of initiator, and reaction temperature were systematically investigated. The experimental results indicate that the moisture-absorbing property of this polymer was better than other traditional material, such as silica gel, and molecular sieve. The best reaction condition and formula are based on the orthogonal experiment design. The optimum moisture absorbency of sodium polyacrylate reaches 1.01 g/g. The mathematical correlation of this polymer with various factors and moisture absorbency is obtained based on the multiple regression analysis. The moisture content intuitive analysis table shows that neutralization degree has the most significant influence on moisture absorbency, followed by monomer concentration and reaction temperature, while other factors have less influence.

Code for chemical environment and computation of molecular similarity

A new code for chemical environment and an empirical mathematical pattern Sa(m) on computation of molecular similarity were suggested. Seven molecules which referred to as the probe compounds and the nearest neighbors of each probe structure were determined by the methods of Sa(m) and Tanimoto, The results show an intuitive notion of chemical similarity.

Controlling electric field distribution by graded spherical core-shell metamaterials

This paper investigates analytically the electric field distribution of graded spherical core-shell metamaterials, whose permittivity is given by the graded Drude model. Under the illumination of a uniform incident optical field, the obtained results show that the electrical field distribution in the shell region is controllable and the electric field peak's position inside the spherical shell can be confined in a desired position by varying the frequency of the optical field as well as the parameters of the graded dielectric profiles. It has also offered an intuitive explanation for controlling the local electric field by graded metamaterials.

Localization of the electric-field distribution in graded core-shell metamaterials

The local electric-field distribution has been investigated in a core-shell cylindrical metamaterial structure under the illumination of a uniform incident optical field. The structure consists of a homogeneous dielectric core, a shell of graded metal-dielectric metamaterial, embedded in a uniform matrix. In the quasistatic limit, the permittivity of the metamaterial is given by the graded Drude model. The local electric potentials and hence the electric fields have been derived exactly and analytically in terms of hypergeometric functions. Our results showed that the peak of the electric field inside the cylindrical shell can be confined in a desired position by varying the frequency of the optical field and the parameters of the graded profiles. Thus, by fabricating graded metamaterials, it is possible to control electric-field distribution spatially. We offer an intuitive explanation for the gradation-controlled electric-field distribution.

具有力觉与视觉反馈的交互式纳米操作系统

提出了交互式纳米操作的实现方法,搭建了一个具有力觉与视觉反馈的交互式纳米操作系统.操作者通过该系统不仅可以实时感受到作用在原子力显微镜(AFM)探针上的力,而且可以实时观察到纳米环境在AFM操作下的变化过程,使得对微观世界的纳米操作如同在宏观世界搬运物体一样直观、灵活.实验结果证实了本系统的高效性及先进性.

Bézier曲线间最近距离的计算方法

针对Bzier曲线间最近距离计算问题,提出一种简捷、可靠的计算方法.该方法以Bernstein多项式算术运算为工具,建立Bzier曲线间最近距离的计算模型;然后充分利用Bzier曲面的凸包性质和de Casteljau分割算法进行求解.该方法几何意义明确,能有效地避免迭代初始值的选择和非线性方程组的求解,并可进一步推广应用于计算Bzier曲线/曲面间的最近距离.实验结果表明,该方法简捷、可靠且容易实现,与Newton-Raphson方法的融合可进一步提高该方法的运行速度.

5-13岁儿童对惯性运动的认知发展

Research on naïve physics investigates children’s intuitive understanding of physical objects, phenomena and processes. Children, and also many adults, were found to have a misconception of inertia, called impetus theory. In order to investigate the development of this naïve concept and the mechanism underlying it, four age groups (5-year-olds, 2nd graders, 5th graders, and 8th graders) were included in this research. Modified experimental tasks were used to explore the effects of daily experience, perceptual cues and general information-processing ability on children’s understanding of inertia. The results of this research are: 1) Five- to thirteen-year-olds’ understanding of inertia problems which were constituted by two ogjects moving at the same spped undergoes an L-shaped developmental trend; Children’s performance became worse as they got older, and their performance in the experiment did not necessarily ascend with the improvement of their cognitive abilities. 2) The L-shaped developmental curve suggests that children in different ages used different strategies to solve inertia problems: Five- to eight-year-olds only used heuristic strategy, while eleven- to thirteen-year-olds solved problems by analyzing the details of inertia motion. 3) The different performance between familiar and unfamiliar problems showed that older children were not able to spontaneously transfer their knowledge and experience from daily action and observation of inertia to unfamiliar, abstract inertia problems. 4) Five- to eight-year-olds showed straight and fragmented pattern, while more eleven- to thirteen-year-olds showed standard impetus theory and revised impetus theory pattern, which showed that younger children were influenced by perceptual cues and their understanding of inertia was fragmented, while older children had coherent impetus theory. 5) When the perceptual cues were controlled, even 40 percent 5 years olds showed the information-processing ability to analyze the distance, speed and time of two objects traveling in two different directions at the same time, demonstrating that they have achieved a necessary level to theorize their naïve concept of inertia.

团队有效性：协作行为与作业特征作用机制研究

Organizations are increasingly turning to team-based structures to contend with the pressure of the increasing global competition, consolidation, innovation and need for diverse skills, expertise, and experiences. This ongoing transformation in the basic organization of work has captured the attention of researcher. And group and team research has become increasingly centered in the fields of organizational psychology and organizational behavior since the 1990s. A great deal empirical studies were conducted; a number of variables contributing to team effectiveness and several IPO models were summarized. But teamwork behaviors, the dynamic and adaptive interactions among team members during the task completion, were still very vague. So were the team task characteristics, an important input variable of the IPO models. The effects of team task characteristics and teamwork behaviors on team effectiveness were explored according to IPO model on the basis of the reviews on previous studies, the Hierarchical Conceptual Structure of Teamwork Behaviors (Rousseau et al.,2006), and the task characteristic theory(Hackman & Oldman, 1975). The questionnaire data from 479 team members and 110 team managers of 22 organizations were analyzed. The results indicate: A. Teamwork behaviors consist of 13 behavioral dimensions: team mission analysis, goal specification, planning, coordination, cooperation, information exchange, performance monitoring, backing-up behaviors, intra-team coaching, collaborative problem solving, team practice innovation, psychological support and integrative conflict management. The hierarchical conceptual structure was partly supported with five variable identified, i.e., preparation of work accomplishment, task-related collaborative behaviors, work assessment behaviors, team adjustment behaviors and the management of team maintenance. The formal four variables are in a sequential way. B. The task characteristic theory at individual level is applicable to the team level. This means that the team task characteristics consist of task variety, identity, significance, feedback, autonomy, interdependence. C. The correlations among task characteristics, teamwork behaviors and outcomes support the IPO model. The regulation of team performance mediated the effects of task meaningfulness and interdependence on team outcomes, with the direct effects of task meaningfulness on the preparation behaviors and the direct effects of interdependence on the task-related collaborative behaviors. The management of team maintenance mediated the effects of autonomy on team cohesion and satisfaction. The regulation of team performance has a direct effect on the team performance and the management of team maintenance. And the management of team maintenance has a direct effect on the team attitude and the regulation of team performance.

A Robot that Walks: Emergent Behaviors from a Carefully Evolved Network

Most animals have significant behavioral expertise built in without having to explicitly learn it all from scratch. This expertise is a product of evolution of the organism; it can be viewed as a very long term form of learning which provides a structured system within which individuals might learn more specialized skills or abilities. This paper suggests one possible mechanism for analagous robot evolution by describing a carefully designed series of networks, each one being a strict augmentation of the previous one, which control a six legged walking machine capable of walking over rough terrain and following a person passively sensed in the infrared spectrum. As the completely decentralized networks are augmented, the robot's performance and behavior repertoire demonstrably improve. The rationale for such demonstrations is that they may provide a hint as to the requirements for automatically building massive networks to carry out complex sensory-motor tasks. The experiments with an actual robot ensure that an essence of reality is maintained and that no critical problems have been ignored.

Taxonomic Syntax for First-Order Inference

Most knowledge representation languages are based on classes and taxonomic relationships between classes. Taxonomic hierarchies without defaults or exceptions are semantically equivalent to a collection of formulas in first order predicate calculus. Although designers of knowledge representation languages often express an intuitive feeling that there must be some advantage to representing facts as taxonomic relationships rather than first order formulas, there are few, if any, technical results supporting this intuition. We attempt to remedy this situation by presenting a taxonomic syntax for first order predicate calculus and a series of theorems that support the claim that taxonomic syntax is superior to classical syntax.

Qualitative Analysis of MOS Circuits

With the push towards sub-micron technology, transistor models have become increasingly complex. The number of components in integrated circuits has forced designer's efforts and skills towards higher levels of design. This has created a gap between design expertise and the performance demands increasingly imposed by the technology. To alleviate this problem, software tools must be developed that provide the designer with expert advice on circuit performance and design. This requires a theory that links the intuitions of an expert circuit analyst with the corresponding principles of formal theory (i.e. algebra, calculus, feedback analysis, network theory, and electrodynamics), and that makes each underlying assumption explicit.

Dependency Directed Reasoning for Complex Program Understanding

Artificial Intelligence research involves the creation of extremely complex programs which must possess the capability to introspect, learn, and improve their expertise. Any truly intelligent program must be able to create procedures and to modify them as it gathers information from its experience. [Sussman, 1975] produced such a system for a 'mini-world'; but truly intelligent programs must be considerably more complex. A crucial stepping stone in AI research is the development of a system which can understand complex programs well enough to modify them. There is also a complexity barrier in the world of commercial software which is making the cost of software production and maintenance prohibitive. Here too a system which is capable of understanding complex programs is a necessary step. The Programmer's Apprentice Project [Rich and Shrobe, 76] is attempting to develop an interactive programming tool which will help expert programmers deal with the complexity involved in engineering a large software system. This report describes REASON, the deductive component of the programmer's apprentice. REASON is intended to help expert programmers in the process of evolutionary program design. REASON utilizes the engineering techniques of modelling, decomposition, and analysis by inspection to determine how modules interact to achieve the desired overall behavior of a program. REASON coordinates its various sources of knowledge by using a dependency-directed structure which records the justification for each deduction it makes. Once a program has been analyzed these justifications can be summarized into a teleological structure called a plan which helps the system understand the impact of a proposed program modification.

Flexibility and Efficiency in a Computer Program for Designing Circuits

This report is concerned with the problem of achieving flexibility (additivity, modularity) and efficiency (performance, expertise) simultaneously in one AI program. It deals with the domain of elementary electronic circuit design. The proposed solution is to provide a deduction-driven problem solver with built-in-control-structure concepts. This problem solver and its knowledge base in the applicaitn areas of design and electronics are descrbed. The prgram embodying it is being used to explore the solutionof some modest problems in circuit design. It is concluded that shallow reasoning about problem-solver plans is necessary for flexibility, and can be implemented with reasonable efficiency.

The Definition and Implementation of a Computer Programming Language Based on Constraints

The constraint paradigm is a model of computation in which values are deduced whenever possible, under the limitation that deductions be local in a certain sense. One may visualize a constraint 'program' as a network of devices connected by wires. Data values may flow along the wires, and computation is performed by the devices. A device computes using only locally available information (with a few exceptions), and places newly derived values on other, locally attached wires. In this way computed values are propagated. An advantage of the constraint paradigm (not unique to it) is that a single relationship can be used in more than one direction. The connections to a device are not labelled as inputs and outputs; a device will compute with whatever values are available, and produce as many new values as it can. General theorem provers are capable of such behavior, but tend to suffer from combinatorial explosion; it is not usually useful to derive all the possible consequences of a set of hypotheses. The constraint paradigm places a certain kind of limitation on the deduction process. The limitations imposed by the constraint paradigm are not the only one possible. It is argued, however, that they are restrictive enough to forestall combinatorial explosion in many interesting computational situations, yet permissive enough to allow useful computations in practical situations. Moreover, the paradigm is intuitive: It is easy to visualize the computational effects of these particular limitations, and the paradigm is a natural way of expressing programs for certain applications, in particular relationships arising in computer-aided design. A number of implementations of constraint-based programming languages are presented. A progression of ever more powerful languages is described, complete implementations are presented and design difficulties and alternatives are discussed. The goal approached, though not quite reached, is a complete programming system which will implicitly support the constraint paradigm to the same extent that LISP, say, supports automatic storage management.

The use of podcasts to enhance research-teaching linkages in undergraduate nursing students.

An understanding of research is important to enable nurses to provide evidencebasedcare. However, undergraduate nursing students often find research a challenging subject. The purpose of this paper is to present an evaluation of the introduction of podcasts in an undergraduate research module to enhance research teaching linkages between the theoretical content and research in practice and improve the level of student support offered in a blended learning environment. Two cohorts of students (n=228 and n=233) were given access to a series of 5 “guest speaker” podcasts made up of presentations and interviews with research experts within Edinburgh Napier. These staff would not normally have contact with students on this module, but through the podcasts were able to share their research expertise and methods with our learners. The main positive results of the podcasts suggest the increased understanding achieved by students due to the multi-modal delivery approach, a more personal student/tutor relationship leading to greater engagement, and the effective use of materials for revision and consolidation purposes. Negative effects of the podcasts centred around problems with the technology, most often difficulty in downloading and accessing the material. This paper contributes to the emerging knowledge base of podcasting in nurse education by demonstrating how podcasts can be used to enhance research-teaching linkages and raises the question of why students do not exploit the opportunities for mobile learning.