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This paper aims to propose a boundary element analysis of two-dimensional linear elasticity problems by a new expanding element interpolation method.

The expanding element is made up based on a traditional discontinuous element by adding virtual nodes along the perimeter of the element. The internal nodes of the original discontinuous element are referred to as source nodes and its shape function as raw shape function. The shape functions of the expanding element constructed on both source nodes and virtual nodes are referred as fine shape functions. Boundary variables are interpolated by the fine shape functions, while the boundary integral equations are collocated on source nodes.

The expanding element inherits the advantages of both the continuous and discontinuous elements while overcomes their disadvantages. The polynomial order of fine shape functions of the expanding elements increases by two compared with their corresponding raw shape functions, while the expanding elements still keep independence to each other as the original discontinuous elements. This feature makes the expanding elements able to naturally and accurately interpolate both continuous and discontinuous fields.

Numerical examples are presented to verify the proposed method. Results have demonstrated that the accuracy, efficiency and convergence rate of the expanding element method.

The purpose of this study is to investigate the long-term performance of firms that early adopted Statement of Financial Accounting Standard 142 (SFAS 142).

In particular, the paper focuses on a relatively lengthy time frame after the standard became effective in 2002 and examines whether the firms which early adopted SFAS 142 exhibit different characteristics from their non-early adopting counterparts when comparing operating returns, stock returns and earnings quality over the same time period. Profit margin, return on assets and return on equity are used to measure operating returns; buy-and-hold return, Tobin’s Q and price-to-book ratio are used to measure stock returns; and abnormal accruals and accruals quality are used to measure earnings quality.

Based on a sample of 692 firm-year observations over five years between 2002 and 2006, the authors find that early adopters tend to exhibit lower operating performance (most noticeable when measuring profit margin and return on assets) and lower earnings quality following the early adoption of SFAS 142 than non-early adopters. However, little relation is found between post-adoption market returns and the choice to early adopt SFAS 142.

This study helps fill the gap in accounting literature by investigating the long-term performance of firms post adoption of SFAS 142. The empirical results may provide greater understanding of the firms choosing to early adopt SFAS 142, and offer additional insight to guide standard setters on similar accounting issues in the future.

This study’s research questions attempt to identify potential differences in operating and stock performance and earnings quality by comparing early adopters and non-early adopters of SFAS 142 over a five-year period between 2002 and 2006, which extends the research beyond the relatively short window covered by prior research, and also takes into consideration Statement of Financial Accounting Standard 141 (SFAS 141)-R “Business Combination”, issued in 2007, to supersede SFAS 141 of 2001.

Properly planned module installation on an industrial site is a critical factor in delivering a project safely, on time and within budget. Different sizes of heavy-duty mobile cranes are used to pick, swing and place the modules. Crane selection depends on module size and weight, as well as crane availability, location and configuration. Weeks can be spent in trial and error to prepare and improve module installation plans due to the large number of ways to install the modules on site, high crane operating costs and other crane-module constraints. A tool to automatically generate module installation plans is essential.

This paper presents a novel heuristic-based methodology for planning and sequencing module installation on industrial construction sites that takes into account proposed technological constraints.

Case studies are presented to demonstrate the ease and effectiveness of the developed methodology in planning module installations.

On a complex project, the tool can save time in preparing the installation plan, while also reducing the amount of crane supporting tasks (foundation preparation and crane movement).

The fluid flow in a rotating channel is obviously different from that in a stationary channel due to the existence of Coriolis force, which, in turn, enhances the heat transfer on the trailing side and reduces the heat transfer on the leading side. The purpose of this paper is to study various rib configurations combined with channel orientation on heat transfer and frictional loss in a rotating channel.

In the present study, the k-ω SST model was used as the turbulence model. The fluid flow direction in the channel is radially outward. The angle between the rotation axis and leading side is 45°. The channel aspect ratio (W/H) is 2, the blockage ratio (e/D_n ) is 0.1 and the pitch ratio (P/e) is 10. The Reynolds number is fixed at 10,000 and the rotation number varies from 0 to 0.7. Angled ribs, reversed angled ribs, standard V-shaped ribs and outer-leaning V-shaped ribs, are examined.

It is found that the reversed angled rib configuration and the outer-leaning V-shaped rib configuration display better heat transfer performance than the V-shaped ribs in rotating condition, which is in contrast to stationary condition. At the leading side, the reversed angled rib and the outer-leaning V-shaped rib show better performance in recovering the heat transfer recession due to the negative effects of the Coriolis force.

In the present study, the fluid is incompressible with constant thermophysical properties and the flow is steady.

The results of this study will be helpful in design of ribbed channels internal cooling for turbine blade.

The results imply that the rib configuration combined with channel orientation significantly impacts the heat transfer performance in a rotating channel. The reversed angled rib and the outer-leaning V-shaped rib show better heat transfer performance than standard V-shaped ribs, especially at high Rotating numbers, which is in contrast to stationary condition. The outer-leaning V-shaped rib has a relatively good heat transfer uniformity along the widthwise direction.

This paper seeks to explore the design, organisation and application of group discussions in which projective techniques (expressive and associative) are used to unravel health perception of consumers in cognitive and affective terms.

A trained moderator led four group discussions in which 24 Dutch women, divided into two groups of six women aged between 50 and 65, and two groups of women with young children (0‐7 years old) participated. By means of expressive and associative techniques participants discuss health and food based on non‐verbal expressions, namely, drawings and abstract paintings made by themselves. The participants selected and discussed relevant terms related to food and health based on their interpretations and associations of images.

Participants related healthy to feeling free and happy (affective) and implied a balance between being active and passive. “Health” and “food” are associated with terms of nature (e.g. season, water and sun), specific products (vegetables and fruits), ingredients (vitamins, fibres, minerals) and no additives (cognitive).

The expressive and associative group discussions proved to be a promising, fascinating and participant‐friendly approach to gain an insight into the affective and the cognitive aspects that consumers relate to health‐promoting product characteristics.

Incorporating users’ behavior patterns could help in the ranking process. Different click models (CMs) are introduced to model the sophisticated search-time behavior of users among which commonly used the triple of attractiveness, examination and satisfaction. Inspired by this fact and considering the psychological definitions of these concepts, this paper aims to propose a novel learning to rank by redefining these concepts. The attractiveness and examination factors could be calculated using a limited subset of information retrieval (IR) features by the random forest algorithm, and then they are combined with each other to predicate the satisfaction factor which is considered as the relevance level.

The attractiveness and examination factors of a given document are usually considered as its perceived relevance and the fast scan of its snippet, respectively. Here, attractiveness and examination factors are regarded as the click-count and the investigation rate, respectively. Also, the satisfaction of a document is supposed to be the same as its relevance level for a given query. This idea is supported by the strong correlation between attractiveness-satisfaction and the examination-satisfaction. Applying random forest algorithm, the attractiveness and examination factors are calculated using a very limited set of the primitive features of query-document pairs. Then, by using the ordered weighted averaging operator, these factors are aggregated to estimate the satisfaction.

Experimental results on MSLR-WEB10K and WCL2R data sets show the superiority of this algorithm over the state-of-the-art ranking algorithms in terms of P@n and NDCG criteria. The enhancement is more noticeable in top-ranked items which are reviewed more by the users.

This paper proposes a novel learning to rank based on the redefinition of major building blocks of the CMs which are the attractiveness, examination and satisfactory. It proposes a method to use a very limited number of selected IR features to estimate the attractiveness and examination factors and then combines these factors to predicate the satisfactory which is regarded as the relevance level of a document with respect to a given query.

This article aims to describe and discuss four major innovations to improve the quality of teacher education including preparation programs and professional development programs in recent years in China. The four major innovations include establishing the National Curriculum Standards for Teacher Education (NCSTE) and the National Teacher Certification Examination; implementing the “double development plan” to reform clinical practice; launching the “National Training Plan” to develop in‐service teachers; and consolidating the career ladder for teachers.

The paper takes the form of a review of the government documents and current literature.

The author argues that the four major innovations reflect the central trends to reform teacher education both in China and the USA – increased standards and accreditation, more clinical experiences in preparation, increased use of technology in teacher professional development, and more accountability and incentive for teachers.

When the world is faced with the globalized economy, cultural exchange and social equity issues, discussions about the recent innovations of China's teacher education will shed light on our understanding of better approaches to improve teacher quality that no doubt connect tradition and local practices with global convergence.

The purpose of this paper is to research electrochemical testing technology as applied to in field corrosion evaluation of metallic materials and to study the corrosion behaviors of the materials exposed in different marine regions.

The electrode systems for in field electrochemical evaluation of metallic samples are designed and applied to monitor two types of carbon steel samples exposed both in the submerged zone and the tidal zone at a marine corrosion test station. Corrosion potential monitoring, potentiostatic square wave, electrochemical impedance spectroscopy, and electrochemical noise methods are used in the test.

It is confirmed that the electrode systems could be used for electrochemical measurement of metallic samples during exposure in the submerged zone and the tidal zone of a marine corrosion test station for long‐term test durations. The electrochemical measuring results reflect the changes and differences of the samples' corrosion behavior during exposure in different regions and they respond directly to the influence of marine environmental factors on the corrosion behaviors, especially the influence of temperature.

In this paper, lots of consecutive and dynamic corrosion information is obtained from field exposures. The findings provide a foundation upon which to investigate and forecast the corrosion behaviors of materials in marine environments.

User feedback inferred from the user's search-time behavior could improve the learning to rank (L2R) algorithms. Click models (CMs) present probabilistic frameworks for describing and predicting the user's clicks during search sessions. Most of these CMs are based on common assumptions such as Attractiveness, Examination and User Satisfaction. CMs usually consider the Attractiveness and Examination as pre- and post-estimators of the actual relevance. They also assume that User Satisfaction is a function of the actual relevance. This paper extends the authors' previous work by building a reinforcement learning (RL) model to predict the relevance. The Attractiveness, Examination and User Satisfaction are estimated using a limited number of the features of the utilized benchmark data set and then they are incorporated in the construction of an RL agent. The proposed RL model learns to predict the relevance label of documents with respect to a given query more effectively than the baseline RL models for those data sets.

In this paper, User Satisfaction is used as an indication of the relevance level of a query to a document. User Satisfaction itself is estimated through Attractiveness and Examination, and in turn, Attractiveness and Examination are calculated by the random forest algorithm. In this process, only a small subset of top information retrieval (IR) features are used, which are selected based on their mean average precision and normalized discounted cumulative gain values. Based on the authors' observations, the multiplication of the Attractiveness and Examination values of a given query–document pair closely approximates the User Satisfaction and hence the relevance level. Besides, an RL model is designed in such a way that the current state of the RL agent is determined by discretization of the estimated Attractiveness and Examination values. In this way, each query–document pair would be mapped into a specific state based on its Attractiveness and Examination values. Then, based on the reward function, the RL agent would try to choose an action (relevance label) which maximizes the received reward in its current state. Using temporal difference (TD) learning algorithms, such as Q-learning and SARSA, the learning agent gradually learns to identify an appropriate relevance label in each state. The reward that is used in the RL agent is proportional to the difference between the User Satisfaction and the selected action.

Experimental results on MSLR-WEB10K and WCL2R benchmark data sets demonstrate that the proposed algorithm, named as SeaRank, outperforms baseline algorithms. Improvement is more noticeable in top-ranked results, which usually receive more attention from users.

This research provides a mapping from IR features to the CM features and thereafter utilizes these newly generated features to build an RL model. This RL model is proposed with the definition of the states, actions and reward function. By applying TD learning algorithms, such as the Q-learning and SARSA, within several learning episodes, the RL agent would be able to learn how to choose the most appropriate relevance label for a given pair of query–document.

This paper seeks to argue that a new and broader definition of food value should be introduced that includes other factors than the traditional mantra of nutritional value, appearance, and the like. This paper introduces the concept of food consumption value (FCV).

The development of FCV is based upon various research traditions and corresponding bodies of literature. The four constituting parts of FCV origins in different lines of scholarly theorising. These lines of thought are discussed separately. Collectively, they form the breeding ground of the concept of food consumption value.

The consumer-centred framework of FCV consists of four elements. Product value refers to food's features and functionalities like taste or texture. Process value refers to consumers' interest in the practices and processes of food production. Ethical considerations (consumer concerns) are thus taken into account. Furthermore, FCV encompasses location value and emotional value. Location value refers to the setting in which food is purchased or consumed. Emotional value is the most elusive element of FCV, because it refers to “feel goods” such as experience, entertainment, (self) indulgence or identity values with respect to the consumption of food products or brands.

The message of FCV for (marketing) practitioners in the field of food is that value creation should depart from assessing consumer value in narrow senses such as value for money. The feelings that foods can arouse are anything but valueless intangibilities, but crucial assets of value creation and competitiveness. Another practical implication of FCV is that for value creation in the food supply chain it is a sine qua non that downstream (location value) and upstream (process value) are fine-tuned consistently and constructively.

This paper is the first exploratory study on the development of the new concept of FCV that examines consumer value beyond tangible product attributes and price. This broader concept of FCV aims to interpret value in terms that adjust to today's consumer-oriented food market. Though inspired by other interpretations of value in marketing and food studies, FCV differs from these.