Eutectic solidification and its role in casting porosity formation

Understanding and controlling the eutectic solidification process in Al-Si alloys permits prediction of the formation of casting porosity, eventually leading to methods for its control and elimination. In addition, it enables control of eutectic structure, silicon morphology, and eutectic grain size to further improve the alloy properties. This paper presents the current understanding of eutectic solidification in hypoeutectic Al-Si foundry alloys and the relationship between eutectic solidification and porosity formation. New concepts in engineering eutectic solidification are also explored.

The role of technology in the shift towards open innovation: the case of Procter & Gamble

As with all new ideas, the concept of Open Innovation requires extensive empirical investigation, testing and development. This paper analyzes Procter and Gamble's 'Connect and Develop' strategy as a case study of the major organizational and technological changes associated with open innovation. It argues that although some of the organizational changes accompanying open innovation are beginning to be described in the literature, more analysis is warranted into the ways technological changes have facilitated open innovation strategies, particularly related to new product development. Information and communications technologies enable the exchange of distributed sources of information in the open innovation process. The case study shows that furthermore a suite of new technologies for data mining, simulation, prototyping and visual representation, what we call 'innovation technology', help to support open innovation in Procter and Gamble. The paper concludes with a suggested research agenda for furthering understanding of the role played by and consequences of this technology.

Workplace diversity: The moderating role of work context on the relationship between surface and deep level diversity and group functioning

This research examines the relationship between perceived group diversity and group conflict, and the moderating role of team context. Currentiy, diversity research predominantly focuses on surface and job-related dimensions, largely to the neglect of deep-level diversity (in terms of values, attitude and beliefs). First, this research hjfpothesised that all three dimensions of diversity would be positively related to group conflict, with deep-level diversity the strongest predictor of task. conflict. Second, it was hypothesised that team context would moderate the relationship between deep-level diversity and group conflict. Team context refers to the extent to which the work performed (1) has high consequences (in terms of health and well being for team members and others); (2) is relatively isolating, (3) requires a high reliance upon team members; (4) is volatile; and (5) interpersonal attraction and mutual helpfulness is essential. Two studies were conducted. The first study employed 44 part-time employees across a range of occupations, and the second study employed 66 full-time employees from a mining company in Australia. A series of hierarchical multiple regressions and moderated multiple regressions confirmed both hypotheses. Practical implications and future research directions are discussed.

Defining a role for the subthalamic nucleus within operative theoretical models of subcortical participation in language

Objective:To investigate the effects of bilateral, surgically induced functional inhibition of the subthalamic nucleus (STN) on general language, high level linguistic abilities, and semantic processing skills in a group of patients with Parkinson’s disease. Methods:Comprehensive linguistic profiles were obtained up to one month before and three months after bilateral implantation of electrodes in the STN during active deep brain stimulation (DBS) in five subjects with Parkinson’s disease (mean age, 63.2 years). Equivalent linguistic profiles were generated over a three month period for a non-surgical control cohort of 16 subjects with Parkinson’s disease (NSPD) (mean age, 64.4 years). Education and disease duration were similar in the two groups. Initial assessment and three month follow up performance profiles were compared within subjects by paired t tests. Reliability change indices (RCI), representing clinically significant alterations in performance over time, were calculated for each of the assessment scores achieved by the five STN-DBS cases and the 16 NSPD controls, relative to performance variability within a group of 16 non-neurologically impaired adults (mean age, 61.9 years). Proportions of reliable change were then compared between the STN-DBS and NSPD groups. Results:Paired comparisons within the STN-DBS group showed prolonged postoperative semantic processing reaction times for a range of word types coded for meanings and meaning relatedness. Case by case analyses of reliable change across language assessments and groups revealed differences in proportions of change over time within the STN-DBS and NSPD groups in the domains of high level linguistics and semantic processing. Specifically, when compared with the NSPD group, the STN-DBS group showed a proportionally significant (p

Redefining functional models of basal ganglia organisation: Role for the posteroventral pallidum in linguistic processing?

Traditionally the basal ganglia have been implicated in motor behavior, as they are involved in both the execution of automatic actions and the modification of ongoing actions in novel contexts. Corresponding to cognition, the role of the basal ganglia has not been defined as explicitly. Relative to linguistic processes, contemporary theories of subcortical participation in language have endorsed a role for the globus pallidus internus (GPi) in the control of lexical-semantic operations. However, attempts to empirically validate these postulates have been largely limited to neuropsychological investigations of verbal fluency abilities subsequent to pallidotomy. We evaluated the impact of bilateral posteroventral pallidotomy (BPVP) on language function across a range of general and high-level linguistic abilities, and validated/extended working theories of pallidal participation in language. Comprehensive linguistic profiles were compiled up to 1 month before and 3 months after BPVP in 6 subjects with Parkinson's disease (PD). Commensurate linguistic profiles were also gathered over a 3-month period for a nonsurgical control cohort of 16 subjects with PD and a group of 16 non-neurologically impaired controls (NC). Nonparametric between-groups comparisons were conducted and reliable change indices calculated, relative to baseline/3-month follow-up difference scores. Group-wise statistical comparisons between the three groups failed to reveal significant postoperative changes in language performance. Case-by-case data analysis relative to clinically consequential change indices revealed reliable alterations in performance across several language variables as a consequence of BPVP. These findings lend support to models of subcortical participation in language, which promote a role for the GPi in lexical-semantic manipulation mechanisms. Concomitant improvements and decrements in postoperative performance were interpreted within the context of additive and subtractive postlesional effects. Relative to parkinsonian cohorts, clinically reliable versus statistically significant changes on a case by case basis may provide the most accurate method of characterizing the way in which pathophysiologically divergent basal ganglia linguistic circuits respond to BPVP.

An unexpected role for visual feedback in vehicle steering control

Some motor tasks can be completed, quite literally, with our eyes shut. Most people can touch their nose without looking or reach for an object after only a brief glance at its location. This distinction leads to one of the defining questions of movement control: is information gleaned prior to starting the movement sufficient to complete the task (open loop), or is feedback about the progress of the movement required (closed loop)? One task that has commanded considerable interest in the literature over the years is that of steering a vehicle, in particular lane-correction and lane-changing tasks. Recent work has suggested that this type of task can proceed in a fundamentally open loop manner [1 and 2], with feedback mainly serving to correct minor, accumulating errors. This paper reevaluates the conclusions of these studies by conducting a new set of experiments in a driving simulator. We demonstrate that, in fact, drivers rely on regular visual feedback, even during the well-practiced steering task of lane changing. Without feedback, drivers fail to initiate the return phase of the maneuver, resulting in systematic errors in final heading. The results provide new insight into the control of vehicle heading, suggesting that drivers employ a simple policy of “turn and see,” with only limited understanding of the relationship between steering angle and vehicle heading.

Pedagogical work and the 'cult of the body': Considering the role of HPE in the context of the 'new public health'

Physical education, now often explicitly identified with health in contemporary school curricula, continues to be implicated in the (re)production of the 'cult of the body'. We argue that HPE is a form of health promotion that attempts to 'make' healthy citizens of young people in the context of the 'risk society'. In our view there is still work to be done in understanding how and why physical education (as HPE) continues to be implicated in the reproduction of values associated with the cult of body. We are keen to understand why HPE continues to be ineffective in helping young people gain some measure of analytic and embodied 'distance' from the problematic aspects of the cult of the body. This paper offers an analysis of this enduring issue by using some contemporary analytic discourses including 'governmentality', 'risk society' and the 'new public health'.

Investigation of the role of cadmium sulfide in the surface passivation of lead sulfide quantum dots

Surface passivation of PbS nanocrystals (NC), resulting in strong photoluminescence, can be achieved by the introduction of CdS precursors. The role of CdS in the surface passivation of PbS NCs is uncertain, as the crystalline structure of CdS and PbS are different, which should impede effective epitaxial overgrowth. Absorption spectroscopy is used to show that the CdS precursors strongly interact with the PbS NC surface. Electron microscopy reveals that the introduction of CdS precursors results in an increased particle size, consistent with overcoating. However, we also find the process to be highly non-uniform. Nevertheless, evidence for epitaxial growth is found, suggesting that effective surface passivation may be possible.

The role of affect, fairness, and social perception in team member exchange

Accumulating evidence suggests that Team-member exchange (TMX) influences employee work attitudes and behaviours separately from the effects of leader-member exchange (LMX). In particular, little is known of the effect of LMX differentiation (in-group versus out-group) as a process of social exhange that can, in turn, affect TMX quality. To explore this phenomenon, this chapter presents a multi-level model of TMX in organizations, which incorporates LMX differentiation, team identification, team member affect at the individual level, and fairness of LMX differentiation and affective climate at the group-level. We conclude with a discussion of the implications of our model for theory, research, and practice.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

A framework for electricity price spike analysis with advanced data mining methods

There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.