In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head

In vivo measurements of equivalent resistivities of skull (rho(skull)) and brain (rho(brain)) are performed for six subjects using an electric impedance tomography (EIT)-based method and realistic models for the head. The classical boundary element method (BEM) formulation for EIT is very time consuming. However, the application of the Sherman-Morrison formula reduces the computation time by a factor of 5. Using an optimal point distribution in the BEM model to optimize its accuracy, decreasing systematic errors of numerical origin, is important because cost functions are shallow. Results demonstrate that rho(skull)/rho(brain) is more likely to be within 20 and 50 rather than equal to the commonly accepted value of 80. The variation in rho(brain)(average = 301 omega x cm, SD = 13%) and rho(skull)(average = 12230 omega x cm, SD = 18%) is decreased by half, when compared with the results using the sphere model, showing that the correction for geometry errors is essential to obtain realistic estimations. However, a factor of 2.4 may still exist between values of rho(skull)/rho(brain) corresponding to different subjects. Earlier results show the necessity of calibrating rho(brain) and rho(skull) by measuring them in vivo for each subject, in order to decrease errors associated with the electroencephalogram inverse problem. We show that the proposed method is suited to this goal.     

Uncertainties in the fate of nitrogen I: An overview of sources of uncertainty illustrated with a Dutch case study

This study focuses on the uncertainties in the fate of nitrogen (N) in the Netherlands. Nitrogen inputs into the Netherlands in products, by rivers, and by atmospheric deposition, and microbial and industrial fixation of atmospheric N₂ amount to about 4450 Gg N y^–1. About 60% of this N is transported out of the Netherlands in products. The fate of the remaining 40%, however, is less clear. We discuss uncertainties in losses to the atmosphere (as ammonia or through denitrification), by leaching and runoff, and in N accumulation in biomass and soils. These processes may account for the fate of about 40% of the N in the Netherlands, and for the fate of about 60% of the N in Dutch agricultural soils. Reducing uncertainties in the estimates of these fluxes is necessary for reducing the impact of excess N in the environment. In particular, monitoring the environmental effects of ammonia emissions and nitrate leaching to groundwater and aquatic systems requires an increased understanding of the fate of N. Uncertainties arise because (1) some N fluxes cannot be measured directly and are usually quantified indirectly as the balance in N budgets, (2) direct measurements of N fluxes have inevitable inaccuracies, (3) lack of experimental data and other information (e.g. statistics) needed for upscaling, (4) large spatial and temporal variability of fluxes, and (5) poor understanding of the processes involved. These uncertainties can be reduced by additional experimental studies and by further development of process-based models and N budget studies. We prioritize these future research needs according to a range of different criteria.     

Re-purposing existing generic games and simulations for e-learning

There is a growing interest among teachers in using games as a part of their lesson plans. A standardised, interoperable approach to the sharing of such game-based lesson plans would allow teachers and educational technologists to compare and contrast Digital Game Based Learning scenarios, allowing best practices and lessons learned to emerge. Although games can be used as ‘add-ons’ in educational contexts, greater benefits can be attained by integrating games more fully into the educational process, i.e. by repurposing existing games to target the specific learning objectives. In this article we analyse this problem. We developed two possible solutions based on the integration and the interaction of games and learning scenarios. The first solution is based on ‘pedagogical wrappers’, where games are linked to e-learning flows but without interaction and communication. The second solution sees a tighter integration which supports ongoing interaction and communication between game and e-learning flow. We applied both solutions to a generic game. This game was firstly programmed in Action Script and later re-used for learning purposes and represented in IMS Learning Design. We analysed the pros and cons of each solution and identify research topics for further research.     

Robust forecasting of mortality and fertility rates: A functional data approach

A new method is proposed for forecasting age-specific mortality and fertility rates observed over time. This approach allows for smooth functions of age, is robust for outlying years due to wars and epidemics, and provides a modelling framework that is easily adapted to allow for constraints and other information. Ideas from functional data analysis, nonparametric smoothing and robust statistics are combined to form a methodology that is widely applicable to any functional time series data observed discretely and possibly with error. The model is a generalization of the Lee-Carter (LC) model commonly used in mortality and fertility forecasting. The methodology is applied to French mortality data and Australian fertility data, and the forecasts obtained are shown to be superior to those from the LC method and several of its variants.     

Examination of the mediational influences of peer norms, environmental influences, and parent communications on heavy drinking in athletes and nonathletes.

The present study used perspectives from the general literature on college alcohol consumption to examine mediational influences of peer, environmental, and parental variables on heavy drinking for student athlete and nonathlete samples. Eight hundred thirty-five freshmen who differed in organized sports involvement were compared on heavy drinking outcomes, peer norms, environmental influences, and parental communication. College athletes reported significantly more heavy drinking experiences than nonathletes. Peer norms, environmental influences, and parental communication were all significant mediators of the athlete-heavy drinking relationship. Athletes reported a higher perception of peer drinking, peer approval of drinking, higher alcohol availability, and direct drink offers, which, in turn, were related to higher rates of heavy drinking. Parental communication mediated the athlete-heavy drinking relationship differently, depending on the specific topic of conversation. Discussion surrounding the importance of incorporating a variety of interventions aimed at reducing collegiate athlete drinking on the basis of the peer, environmental, and parental influences observed in the present analyses are presented. Limitations and directions for future research are also noted. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

采用高效LDO为亚微米CMOS负载供电

论述数字IC的供电问题.     

焊接的重要性

现在，电子制造行业必须满足无铅标准，并且已经取得了很大的进展，整个行业正在了解可靠的无铅方案。业内正在生产高性能无铅电路板，并且已经制订出无铅处理的新标准。本文重点介绍无铅焊接处理中的回流焊工艺考虑因素。[第一段]     

Lyapunov based predictive control of vehicle drivetrains over CAN

Vehicle drivetrains are characterized by fast dynamics, subject to physical and control constraints, which make controller design for driveline oscillations damping a challenging problem. Furthermore, in current implementations, the connections between the controller and the physical plant are realized using a controller area network (CAN) as the communication medium, which introduces time-varying delays. As such, the goal of this paper is to provide a control design methodology that can cope with all these challenges and limitations and still yield an effective solution. To this end, firstly, a continuous-time model of a vehicle drivetrain is derived. Then, a method for determining a worst case upper bound on the delays that can be introduced by a CAN is presented, which enables the usage of a polytopic approximation technique to obtain a discrete-time model of the closed-loop CAN system. Thirdly, a non-conservative Lyapunov based predictive controller is designed for the resulting model with time-varying delays, polytopic uncertainty and hard constraints. Several tests performed using an industry validated drivetrain model and the Matlab toolbox TrueTime indicate that the proposed design methodology can handle both the performance/physical constraints and the strict limitations on the computational complexity, while effectively coping with time-varying delays. Preliminary real-time results further validate the proposed methodology.