Reliability of the input-output properties of the cortico-spinal pathway obtained from transcranial magnetic and electrical stimulation

The purpose of this experiment was to assess the test-retest reliability of input-output parameters of the cortico-spinal pathway derived from transcranial magnetic (TMS) and electrical (TES) stimulation at rest and during muscle contraction. Motor evoked potentials (MEPs) were recorded from the first dorsal interosseous muscle of eight individuals on three separate days. The intensity of TMS at rest was varied from 5% below threshold to the maximal output of the stimulator. During trials in which the muscle was active, TMS and TES intensities were selected that elicited MEPs of between 150 and 300 X at rest. MEPs were evoked while the participants exerted torques up to 50% of their maximum capacity. The relationship between MEP size and stimulus intensity at rest was sigmoidal (R-2 = 0.97). Intra-class correlation coefficients (ICC) ranged between 0.47 and 0.81 for the parameters of the sigmoid function. For the active trials, the slope and intercept of regression equations of MEP size on level of background contraction were obtained more reliably for TES (ICC = 0.63 and 0.78, respectively) than for TMS (ICC = 0.50 and 0.53, respectively), These results suggest that input-output parameters of the cortico-spinal pathway may be reliably obtained via transcranial stimulation during longitudinal investigations of cortico-spinal plasticity. (C) 2001 Elsevier Science B.V. All rights reserved.

Neural network forecasts of input-output technology

A significant part of the literature on input-output (IO) analysis is dedicated to the development and application of methodologies forecasting and updating technology coefficients and multipliers. Prominent among such techniques is the RAS method, while more information demanding econometric methods, as well as other less promising ones, have been proposed. However, there has been little interest expressed in the use of more modern and often more innovative methods, such as neural networks in IO analysis in general. This study constructs, proposes and applies a Backpropagation Neural Network (BPN) with the purpose of forecasting IO technology coefficients and subsequently multipliers. The RAS method is also applied on the same set of UK IO tables, and the discussion of results of both methods is accompanied by a comparative analysis. The results show that the BPN offers a valid alternative way of IO technology forecasting and many forecasts were more accurate using this method. Overall, however, the RAS method outperformed the BPN but the difference is rather small to be systematic and there are further ways to improve the performance of the BPN.

Investigating the cost Performance of UK Credit Unions using Radial and Non-Radial Efficiency Measures

This paper examines the relative efficiency of UK credit unions. Radial and non-radial measures of input cost efficiency plus associated scale efficiency measures are computed for a selection of input output specifications. Both measures highlighted that UK credit unions have considerable scope for efficiency gains. It was mooted that the documented high levels of inefficiency may be indicative of the fact that credit unions, based on clearly defined and non-overlapping common bonds, are not in competition with each other for market share. Credit unions were also highlighted as suffering from a considerable degree of scale inefficiency with the majority of scale inefficient credit unions subject to decreasing returns to scale. The latter aspect highlights that the UK Government's goal of larger credit unions must be accompanied by greater regulatory freedom if inefficiency is to be avoided. One of the advantages of computing non-radial measures is that an insight into potential over- or under-expenditure on specific inputs can be obtained through a comparison of the non-radial measure of efficiency with the associated radial measure. Two interesting findings emerged, the first that UK credit unions over-spend on dividend payments and the second that they under-spend on labour costs.

Robust fuzzy Gustafson-Kessel clustering for nonlinear system identification

This paper deals with Takagi-Sugeno (TS) fuzzy model identification of nonlinear systems using fuzzy clustering. In particular, an extended fuzzy Gustafson-Kessel (EGK) clustering algorithm, using robust competitive agglomeration (RCA), is developed for automatically constructing a TS fuzzy model from system input-output data. The EGK algorithm can automatically determine the 'optimal' number of clusters from the training data set. It is shown that the EGK approach is relatively insensitive to initialization and is less susceptible to local minima, a benefit derived from its agglomerate property. This issue is often overlooked in the current literature on nonlinear identification using conventional fuzzy clustering. Furthermore, the robust statistical concepts underlying the EGK algorithm help to alleviate the difficulty of cluster identification in the construction of a TS fuzzy model from noisy training data. A new hybrid identification strategy is then formulated, which combines the EGK algorithm with a locally weighted, least-squares method for the estimation of local sub-model parameters. The efficacy of this new approach is demonstrated through function approximation examples and also by application to the identification of an automatic voltage regulation (AVR) loop for a simulated 3 kVA laboratory micro-machine system.

Phosphorus Retention in a Constructed Wetland System used to Treat Dairy Wastewater

The aim of this study was to develop an input/output mass balance to predict phosphorus retention in a five pond constructed wetland system (CWS) at Greenmount Farm, County Antrim, Northern Ireland. The mass balance was created using 14-months of flow data collected at inflow and outflow points on a weekly basis. Balance outputs were correlated with meteorological parameters, such as daily air temperature and hydrological flow, recorded daily onsite. The mass balance showed that phosphorus retention within the system exceeded phosphorus release, illustrating the success of constructed wetland systems to remove nutrients from agricultural effluent from a dairy farm. Pond 5 showed the greatest relative retention of 86%. Comparison of retention and mean air temperature highlighted a striking difference in trends between up-gradient and down-gradient ponds, with Ponds 1 and 2 displaying a positive quadratic relationship and ponds 3 through 5 displaying a negative quadratic relationship.

Molecular Logic Gates and Luminescent Sensors Based on Photoinduced Electron Transfer

The competition between Photoinduced electron transfer (PET) and other de-excitation pathways such as fluorescence and phosphorescence can be controlled within designed molecular structures. Depending on the particular design, the resulting optical output is thus a function of various inputs such as ion concentration and excitation light dose. Once digitized into binary code, these input-output patterns can be interpreted according to Boolean logic. The single-input logic types of YES and NOT cover simple sensors and the double- (or higher-) input logic types represent other gates such as AND and OR. The logic-based arithmetic processors such as half-adders and half-subtractors are also featured. Naturally, a principal application of the more complex gates is in multi-sensing contexts.

Parallel Programming of General-Purpose Programs Using Task-Based Programming Models

The prevalence of multicore processors is bound to drive most kinds of software development towards parallel programming. To limit the difficulty and overhead of parallel software design and maintenance, it is crucial that parallel programming models allow an easy-to-understand, concise and dense representation of parallelism. Parallel programming models such as Cilk++ and Intel TBBs attempt to offer a better, higher-level abstraction for parallel programming than threads and locking synchronization. It is not straightforward, however, to express all patterns of parallelism in these models. Pipelines are an important parallel construct, although difficult to express in Cilk and TBBs in a straightfor- ward way, not without a verbose restructuring of the code. In this paper we demonstrate that pipeline parallelism can be easily and concisely expressed in a Cilk-like language, which we extend with input, output and input/output dependency types on procedure arguments, enforced at runtime by the scheduler. We evaluate our implementation on real applications and show that our Cilk-like scheduler, extended to track and enforce these dependencies has performance comparable to Cilk++.

Discrete cosine transform generator for VLSI synthesis

A generator for the automated design of Discrete Cosine Transform (DCT) cores is presented. This can be used to rapidly create silicon circuits from a high level specification. These compare very favourably with existing designs. The DCT cores produced are scaleable in terms of point size as well as input/output and coefficient wordlengths. This provides a high degree of flexibility. An example, 8-point 1D DCT design, produced occupies less than 0.92 mm when implemented in a 0.35µ double level metal CMOS technology. This can be clocked at a rate of 100MHz.

A molecular photoionic AND gate based on fluorescent signalling

MOLECULES that perform logic operations are prerequisites for molecular information processing and computation. We and others have previously reported receptor molecules that can be considered to perform simple logic operations by coupling ionic bonding or more complex molecular-recognition processes with photonic (fluorescence) signals: in these systems, chemical binding (the 'input') results in a change in fluorescence intensity (the 'output') from the receptor. Here we describe a receptor (molecule (1) in Fig. 1) that operates as a logic device with two input channels: the fluorescence signal depends on whether the molecule binds hydrogen ions, sodium ions or both. The input/output characteristics of this molecular device correspond to those of an AND gate.

Analysis of Dependence Tracking Algorithms for Task Dataflow Execution

Processor architectures has taken a turn towards many-core processors, which integrate multiple processing cores on a single chip to increase overall performance, and there are no signs that this trend will stop in the near future. Many-core processors are harder to program than multi-core and single-core processors due to the need of writing parallel or concurrent programs with high degrees of parallelism. Moreover, many-cores have to operate in a mode of strong scaling because of memory bandwidth constraints. In strong scaling increasingly finer-grain parallelism must be extracted in order to keep all processing cores busy.

Task dataflow programming models have a high potential to simplify parallel program- ming because they alleviate the programmer from identifying precisely all inter-task de- pendences when writing programs. Instead, the task dataflow runtime system detects and enforces inter-task dependences during execution based on the description of memory each task accesses. The runtime constructs a task dataflow graph that captures all tasks and their dependences. Tasks are scheduled to execute in parallel taking into account dependences specified in the task graph.

Several papers report important overheads for task dataflow systems, which severely limits the scalability and usability of such systems. In this paper we study efficient schemes to manage task graphs and analyze their scalability. We assume a programming model that supports input, output and in/out annotations on task arguments, as well as commutative in/out and reductions. We analyze the structure of task graphs and identify versions and generations as key concepts for efficient management of task graphs. Then, we present three schemes to manage task graphs building on graph representations, hypergraphs and lists. We also consider a fourth edge-less scheme that synchronizes tasks using integers. Analysis using micro-benchmarks shows that the graph representation is not always scalable and that the edge-less scheme introduces least overhead in nearly all situations.

Holistic design of 8-way combining transformers in SiGe technology for use in millimetre-wave power amplifiers

This paper presents the design of a novel 8-way power-combining transformer for use in mm-wave power amplifier (PA). The combiner exhibits a record low insertion loss of 1.25 dB at 83.5 GHz. A complete circuit comprised of a power splitter, two-stage cascode PA array, a power combiner and input/output matching elements was designed and realized in SiGe technology. Measured gain of at least 16.8 dB was obtained from 76.4 GHz to 85.3 GHz with a peak 19.5 dB at 83 GHz. The prototype delivered 12.5 dBm OP and 14 dBm saturated output power when operated from a 3.2 V DC supply voltage at 78 GHz. © 2013 IEEE.

Current Developments in Fluorescent PET (Photoinduced Electron Transfer) Sensors and Switches

Following a brief introduction to the principle of fluorescent PET (photoinduced electron transfer) sensors and switches, the outputs of laboratories in various countries from the past year or two are categorized and critically discussed. Emphasis is placed on the molecular design and the experimental outcomes in terms of target-induced fluorescence enhancements and input/output wavelengths. The handling of single targets takes up a major fraction of the review, but the extension to multiple targets is also illustrated. Conceptually new channels of investigation are opened up by the latter approach, e.g. ‘lab-on-a-molecule’ systems and molecular keypad locks. The growing trends of theoretically-fortified design and intracellular application are pointed out.

Measuring the sustainability of a national economy. The application of three measures of sustainability to Ireland

An assessment of the sustainability of the Irish economy has been carried out using three methodologies, enabling comparison and evaluation of the advantages and disadvantages of each, and potential synergies among them. The three measures chosen were economy-wide Material Flow Analysis (MFA), environmentally extended input-output (EE-IO) analysis and the Ecological Footprint (EF). The research aims to assess the sustainability of the Irish economy using these methods and to draw conclusions on their effectiveness in policy making both individually and in combination. A theoretical description discusses the methods and their respective advantages and disadvantages and sets out a rationale for their combined application. The application of the methods in combination has provided insights into measuring the sustainability of a national economy and generated new knowledge on the collective application of these methods. The limitations of the research are acknowledged and opportunities to address these and build on and extend the research are identified. Building on previous research, it is concluded that a complete picture of sustainability cannot be provided by a single method and/or indicator.

Physical model parameter optimisation for calibrated emulation of the Dallas Rangemaster Treble Booster guitar pedal

In this work we explore optimising parameters of a physical circuit model relative to input/output measurements, using the Dallas Rangemaster Treble Booster as a case study. A hybrid metaheuristic/gradient descent algorithm is implemented, where the initial parameter sets for the optimisation are informed by nominal values from schematics and datasheets. Sensitivity analysis is used to screen parameters, which informs a study of the optimisation algorithm against model complexity by fixing parameters. The results of the optimisation show a significant increase in the accuracy of model behaviour, but also highlight several key issues regarding the recovery of parameters.