Neurofuzzy design and model construction of nonlinear dynamical processes from data

A common problem in many data based modelling algorithms such as associative memory networks is the problem of the curse of dimensionality. In this paper, a new two-stage neurofuzzy system design and construction algorithm (NeuDeC) for nonlinear dynamical processes is introduced to effectively tackle this problem. A new simple preprocessing method is initially derived and applied to reduce the rule base, followed by a fine model detection process based on the reduced rule set by using forward orthogonal least squares model structure detection. In both stages, new A-optimality experimental design-based criteria we used. In the preprocessing stage, a lower bound of the A-optimality design criterion is derived and applied as a subset selection metric, but in the later stage, the A-optimality design criterion is incorporated into a new composite cost function that minimises model prediction error as well as penalises the model parameter variance. The utilisation of NeuDeC leads to unbiased model parameters with low parameter variance and the additional benefit of a parsimonious model structure. Numerical examples are included to demonstrate the effectiveness of this new modelling approach for high dimensional inputs.

Coupling and memory in liquid crystal elastomers

The polymer backbone of a side-chain liquid crystal polymer exhibits an anisotropic shape due to the coupling of the liquid crystal orientational order of the mesogenic side-chains to the backbone. The magnitude and sign of this coupling may be controlled by chemical design. The introduction of chemical cross-links in to such a system provides both a memory of the anisotropic organisation and a mechanism by which the microscopic anisotropy can be realised at a macroscopic level. We show how this anisotropic network structure yields new phenomena when electric or mechanical fields are applied.

Digital predistorter design using B-Spline neural network and inverse of De Boor algorithm

This contribution introduces a new digital predistorter to compensate serious distortions caused by memory high power amplifiers (HPAs) which exhibit output saturation characteristics. The proposed design is based on direct learning using a data-driven B-spline Wiener system modeling approach. The nonlinear HPA with memory is first identified based on the B-spline neural network model using the Gauss-Newton algorithm, which incorporates the efficient De Boor algorithm with both B-spline curve and first derivative recursions. The estimated Wiener HPA model is then used to design the Hammerstein predistorter. In particular, the inverse of the amplitude distortion of the HPA's static nonlinearity can be calculated effectively using the Newton-Raphson formula based on the inverse of De Boor algorithm. A major advantage of this approach is that both the Wiener HPA identification and the Hammerstein predistorter inverse can be achieved very efficiently and accurately. Simulation results obtained are presented to demonstrate the effectiveness of this novel digital predistorter design.

Crystal design approaches for the synthesis of paracetamol co-crystals

Crystal engineering principles were used to design three new co-crystals of paracetamol. A variety of potential cocrystal formers were initially identified from a search of the Cambridge Structural Database for molecules with complementary hydrogen-bond forming functionalities. Subsequent screening by powder X-ray diffraction of the products of the reaction of this library of molecules with paracetamol led to the discovery of new binary crystalline phases of paracetamol with trans-1,4- diaminocyclohexane (1); trans-1,4-di(4-pyridyl)ethylene (2); and 1,2-bis(4-pyridyl)ethane (3). The co-crystals were characterized by IR spectroscopy, differential scanning calorimetry, and 1H NMR spectroscopy. Single crystal X-ray structure analysis reveals that in all three co-crystals the co-crystal formers (CCF) are hydrogen bonded to the paracetamol molecules through O−H···N interactions. In co-crystals (1) and (2) the CCFs are interleaved between the chains of paracetamol molecules, while in co-crystal (3) there is an additional N−H···N hydrogen bond between the two components. A hierarchy of hydrogen bond formation is observed in which the best donor in the system, the phenolic O−H group of paracetamol, is preferentially hydrogen bonded to the best acceptor, the basic nitrogen atom of the co-crystal former. The geometric aspects of the hydrogen bonds in co-crystals 1−3 are discussed in terms of their electrostatic and charge-transfer components.

Computerized short-term memory treatment for older adults with aphasia

We report on a software prototype designed to deliver a novel term memory treatment for older adults with aphasia. We conducted a review of the prototype with 14 speech and language therapists, to elicit feedback on the potential usefulness of the ultimate application and, particularly, the prototype in terms of its main design features and use by older adults with aphasia. The clinicians’ feedback highlights a number of design considerations relating to the usability, training methods, and appeal of treatment software, which can help engage patients more fully in computerized treatments and improve treatment outcomes.

The development of time-based prospective memory in childhood: the role of working memory updating

This large-scale study examined the development of time-based prospective memory (PM) across childhood and the roles that working memory updating and time monitoring play in driving age effects in PM performance. One hundred and ninety-seven children aged 5 to 14 years completed a time-based PM task where working memory updating load was manipulated within individuals using a dual task design. Results revealed age-related increases in PM performance across childhood. Working memory updating load had a negative impact on PM performance and monitoring behavior in older children, but this effect was smaller in younger children. Moreover, the frequency as well as the pattern of time monitoring predicted children’s PM performance. Our interpretation of these results is that processes involved in children’s PM may show a qualitative shift over development from simple, nonstrategic monitoring behavior to more strategic monitoring based on internal temporal models that rely specifically on working memory updating resources. We discuss this interpretation with regard to possible trade-off effects in younger children as well as alternative accounts.

A pilot study investigating the effects of a single dose of a flavonoid-rich blueberry drink on memory in 8-10 year old children

Recent evidence from animal and adult human subjects has demonstrated potential benefits to cognition from flavonoid supplementation. This study aimed to investigate whether these cognitive benefits extended to a sample of school-aged children. Using a cross-over design, with a wash out of at least seven days between drinks, fourteen 8-10 year old children consumed either a flavonoid-rich blueberry drink or matched vehicle. Two hours after consumption, subjects completed a battery of five cognitive tests comprising the Go-NoGo, Stroop, Rey’s Auditory Verbal Learning Task, Object Location Task, and a Visual N-back. In comparison to vehicle, the blueberry drink produced significant improvements in the delayed recall of a previously learned list of words, showing for the first time a cognitive benefit for acute flavonoid intervention in children. However, performance on a measure of proactive interference indicated that the blueberry intervention led to a greater negative impact of previously memorised words on the encoding of a set of new words. There was no benefit of our blueberry intervention for measures of attention, response inhibition or visuo-spatial memory. While findings are mixed, the improvements in delayed recall found in this pilot study suggest that, following acute flavonoid-rich blueberry interventions, school aged children encode memory items more effectively.

A randomised controlled trial of positive memory training for the treatment of depression within schizophrenia

Abstract Background: Depression is highly prevalent within individuals diagnosed with schizophrenia, and is associated with an increased risk of suicide. There are no current evidence based treatments for low mood within this group. The specific targeting of co-morbid conditions within complex mental health problems lends itself to the development of short-term structured interventions which are relatively easy to disseminate within health services. A brief cognitive intervention based on a competitive memory theory of depression, is being evaluated in terms of its effectiveness in reducing depression within this group. Methods/Design: This is a single blind, intention-to-treat, multi-site, randomized controlled trial comparing Positive Memory Training plus Treatment as Usual with Treatment as Usual alone. Participants will be recruited from two NHS Trusts in Southern England. In order to be eligible, participants must have a DSM-V diagnosis of schizophrenia or schizo-affective disorder and exhibit at least a mild level of depression. Following baseline assessment eligible participants will be randomly allocated to either the Positive Memory Training plus Treatment as Usual group or the Treatment as Usual group. Outcome will be assessed at the end of treatment (3-months) and at 6-month and 9-month post randomization by assessors blind to group allocation. The primary outcome will be levels of depression and secondary outcomes will be severity of psychotic symptoms and cost-effectiveness. Semi-structured interviews will be conducted with all participants who are allocated to the treatment group so as to explore the acceptability of the intervention. Discussion: Cognitive behaviour therapy is recommended for individuals diagnosed with schizophrenia. However, the number of sessions and length of training required to deliver this intervention has caused a limit in availability. The current trial will evaluate a short-term structured protocol which targets a co-morbid condition often considered of primary importance by service users. If successful the intervention will be an important addition to current initiatives aimed at increasing access to psychological therapies for people diagnosed with severe mental health problems. Trial registration: Current Controlled Trials. ISRCTN99485756. Registered 13 March 2014.

Enhancing prospective memory in mild cognitive impairment: the role of enactment

Prospective memory (PM) is a fundamental requirement for independent living which might be prematurely compromised in the neurodegenerative process, namely in mild cognitive impairment (MCI), a typical prodromal Alzheimer's disease (AD) phase. Most encoding manipulations that typically enhance learning in healthy adults are of minimal benefit to AD patients. However, there is some indication that these can display a recall advantage when encoding is accompanied by the physical enactment of the material. The aim of this study was to explore the potential benefits of enactment at encoding and cue-action relatedness on memory for intentions in MCI patients and healthy controls using a behavioral PM experimental paradigm. Method: We report findings examining the influence of enactment at encoding for PM performance in MCI patients and education-matched controls using a laboratory-based PM task with a factorial independent design. Results: PM performance was consistently superior when physical enactment was used at encoding and when target-action pairs were strongly associated. Importantly, these beneficial effects were cumulative and observable across both a healthy and a cognitively impaired lifespan as well as evident in the perceived subjective difficulty in performing the task. Conclusions: The identified beneficial effects of enacted encoding and semantic relatedness have unveiled the potential contribution of this encoding technique to optimize attentional demands through an adaptive allocation of resources strategies. We discuss our findings with respect to their potential impact on developing strategies to improve PM in AD sufferers.

Design of associative memories using cellular neural networks

Cellular neural networks (CNNs) have locally connected neurons. This characteristic makes CNNs adequate for hardware implementation and, consequently, for their employment on a variety of applications as real-time image processing and construction of efficient associative memories. Adjustments of CNN parameters is a complex problem involved in the configuration of CNN for associative memories. This paper reviews methods of associative memory design based on CNNs, and provides comparative performance analysis of these approaches.

Design of a simplified neuro-fuzzy system based on CMAC Architectures

This work presents the design of a fuzzy controller with simplified architecture that use an artificial neural network working as the aggregation operator for several active fuzzy rules. The simplified architecture of the fuzzy controller is used to minimize the time processing used in the closed loop system operation, the basic procedures of fuzzification are simplified to maximum while all the inference procedures are computed in a private way. As consequence, this simplified architecture allows a fast and easy configuration of the simplified fuzzy controller. The structuring of the fuzzy rules that define the control actions is previously computed using an artificial neural network based on CMAC Cerebellar Model Articulation Controller. The operational limits are standardized and all the control actions are previously calculated and stored in memory. For applications, results and conclusions several configurations of this fuzzy controller are considered.

A hierarchy of adaptive (X)over-bar control charts

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

An accurate low-voltage analog memory-cell with built-in multiplication

A CMOS memory-cell for dynamic storage of analog data and suitable for LVLP applications is proposed. Information is memorized as the gate-voltage of input-transistor of a gain-boosting triode-transconductor. The enhanced output-resistance improves accuracy on reading out the sampled currents. Additionally, a four-quadrant multiplication between the input to regulation-amplifier of the transconductor and the stored voltage is provided. Designing complies with a low-voltage 1.2μm N-well CMOS fabrication process. For a 1.3V-supply, CCELL=3.6pF and sampling interval is 0.25μA≤ ISAMPLE ≤ 0.75μA. The specified retention time is 1.28ms and corresponds to a charge-variation of 1% due to junction leakage @75°C. A range of MR simulations confirm circuit performance. Absolute read-out error is below O.40% while the four-quadrant multiplier nonlinearity, at full-scale is 8.2%. Maximum stand-by consumption is 3.6μW/cell.

Reduction of the memory size in the microprogrammed controllers

In the paper the method of reduction of the memory size in the microprogrammed controllers with sharing codes is discussed. The idea is based on the modification of internal modules and connections of the device. Next, the reduction of the microinstruction length based on the hypergraph theory is performed, thus the total size of the memory is highly reduced. © 2011 IEEE.