Real-time error detection but not error correction drives automatic visuomotor adaptation

We investigated the role of visual feedback of task performance in visuomotor adaptation. Participants produced novel two degrees of freedom movements (elbow flexion-extension, forearm pronation-supination) to move a cursor towards visual targets. Following trials with no rotation, participants were exposed to a 60A degrees visuomotor rotation, before returning to the non-rotated condition. A colour cue on each trial permitted identification of the rotated/non-rotated contexts. Participants could not see their arm but received continuous and concurrent visual feedback (CF) of a cursor representing limb position or post-trial visual feedback (PF) representing the movement trajectory. Separate groups of participants who received CF were instructed that online modifications of their movements either were, or were not, permissible as a means of improving performance. Feedforward-mediated performance improvements occurred for both CF and PF groups in the rotated environment. Furthermore, for CF participants this adaptation occurred regardless of whether feedback modifications of motor commands were permissible. Upon re-exposure to the non-rotated environment participants in the CF, but not PF, groups exhibited post-training aftereffects, manifested as greater angular deviations from a straight initial trajectory, with respect to the pre-rotation trials. Accordingly, the nature of the performance improvements that occurred was dependent upon the timing of the visual feedback of task performance. Continuous visual feedback of task performance during task execution appears critical in realising automatic visuomotor adaptation through a recalibration of the visuomotor mapping that transforms visual inputs into appropriate motor commands.

Heterogeneous error-resilient scheme for spectral analysis in ultra-low power wearable electrocardiogram devices

Wearable devices performing advanced bio-signal analysis algorithms are aimed to foster a revolution in healthcare provision of chronic cardiac diseases. In this context, energy efficiency is of paramount importance, as long-term monitoring must be ensured while relying on a tiny power source. Operating at a scaled supply voltage, just above the threshold voltage, effectively helps in saving substantial energy, but it makes circuits, and especially memories, more prone to errors, threatening the correct execution of algorithms. The use of error detection and correction codes may help to protect the entire memory content, however it incurs in large area and energy overheads which may not be compatible with the tight energy budgets of wearable systems. To cope with this challenge, in this paper we propose to limit the overhead of traditional schemes by selectively detecting and correcting errors only in data highly impacting the end-to-end quality of service of ultra-low power wearable electrocardiogram (ECG) devices. This partition adopts the protection of either significant words or significant bits of each data element, according to the application characteristics (statistical properties of the data in the application buffers), and its impact in determining the output. The proposed heterogeneous error protection scheme in real ECG signals allows substantial energy savings (11% in wearable devices) compared to state-of-the-art approaches, like ECC, in which the whole memory is protected against errors. At the same time, it also results in negligible output quality degradation in the evaluated power spectrum analysis application of ECG signals.

Assistive software tools for secondary-level students with literacy difficulties.

Study conducted to evaluate the effectiveness of four assistive technology (AT) tools on literacy: (1) speech synthesis, (2) spellchecker, (3) homophone tool, and (4) dictionary. All four of these programs are featured in TextHelp’s Read&Write Gold software package. A total of 93 secondary-level students with reading disabilities participated in the study. The participants completed a number of computer-based literacy tests after being assigned to a Read&Write group or a control group that utilized Microsoft Word. The results indicated that improvements in the following areas for the Read&Write group: (1) reading comprehension, (2) homophone error detection, (3) spelling error detection, and (4) word meanings. The Microsoft Word group also improved in the areas of word meanings and error detection, though performed worse on homophone error detection. The authors contend that these results indicate that speech synthesis, spell checkers, homophone tools, and dictionary programs have a positive effect on literacy among students with reading disabilities. This study was conducted by researchers at the Queen’s University in Belfast, Ireland.

Optimizing the balance between false positive and false negative error probabilities of confirmatory methods for the detection of veterinary drug residues

GC-MS data on veterinary drug residues in bovine urine are used for controlling the illegal practice of fattening cattle. According to current detection criteria, peak patterns of preferably four ions should agree within 10 or 20% from a corresponding standard pattern. These criteria are rigid, rather arbitrary and do not match daily practice. A new model, based on multivariate modeling of log peak abundance ratios, provides a theoretical basis for the identification of analytes and optimizes the balance between the avoidance of false positives and false negatives. The performance of the model is demonstrated on data provided by five laboratories, each supplying GC-MS measurements on the detection of clenbuterol, dienestrol and 19 beta-nortestosterone in urine. The proposed model shows a better performance than confirmation by using the current criteria and provides a statistical basis for inspection criteria in terms of error probabilities.

Detection of cathepsin S cysteine protease in human brain tumour microdialysates in vivo.

Microdialysis enables the chemistry of extracellular ?uid in body tissues to be measured. Extracellular proteases such as the cysteine protease, cathepsin S (CatS), are thought to facilitate astrocytoma invasion. Microdialysates obtained from human brain tumoursin vivo were subjected to cathepsin S activity and ELISA assays. Cathepsin S ELISA expression was detected in ?ve out of 10 tumour microdialysates, while activity was detected in ?ve out of 11 tumour microdialysates. Cathepsin S expression was also detected in microdialysate from the normal brain control although no activity was found in the same sample. While some re?nements to the technique are necessary, the authors demonstrate the feasibility and safety of microdialysis in human astrocytomasin vivo. Characterisation of the extracellular environment of brain tumoursin vivo using microdialysis may be a useful tool to identify the protease pro?le of brain tumours.

Cooperative transmission protocol with full diversity and iterative detection

The authors propose a three-node full diversity cooperative protocol, which allows the retransmission of all symbols. By allowing multiple nodes to transmit simultaneously, relaying transmission only consumes limited bandwidth resource. To facilitate the performance analysis of the proposed cooperative protocol, the lower and upper bounds of the outage probability are first developed, and then the high signal-to-noise ratio behaviour is studied. Our analytical results show that the proposed strategy can achieve full diversity. To achieve the performance gain promised by the cooperative diversity, at the relays decode-and-forward strategy is adopted and an iterative soft-interference-cancellation minimum mean-squared error equaliser is developed. The simulation results compare the bit-error-rate performance of the proposed protocol with the non-cooperative scheme and the scheme presented by Azarian et al. ( 2005).

Detection of improper installation from the sensor signal of vortex flowmeters

Effects of inappropriate installation can bias the measurements of flowmeters. For vortex flowmeters, a method is proposed to detect inappropriate installation of the flowmeter from the oscillatory signal of the vortex sensor. The method is based on assuming the process of vortex generation to be a generic, noisy, nonlinear oscillation, describable by a noisy Stuart-Landau equation, with a corresponding sensor signal that also contains higher harmonic excitations. By making use of the scaling properties of the Navier-Stokes Equation, the method was designed to be robust with respect to uncertainties in the fluid properties. The diagnostic functionality is demonstrated on measurement data. In the experiments, installation effects that lead to more than 0.5% error in the output of the flowmeter could clearly be detected. (C) 2003 Elsevier Ltd. All rights reserved.

The application of Reporter Gene Assays for the detection of endocrine disruptors in sport supplements.

The increasing availability and use of sports supplements is of concern as highlighted by a number of studies reporting endocrine disruptor contamination in such products. The health food supplement market, including sport supplements, is growing across the Developed World. Therefore, the need to ensure the quality and safety of sport supplements for the consumer is essential. The development and validation of two reporter gene assays coupled with solid phase sample preparation enabling the detection of estrogenic and androgenic constituents in sport supplements is reported. Both assays were shown to be of high sensitivity with the estrogen and androgen reporter gene assays having an EC50 of 0.01 ng mL-1 and 0.16 ng mL-1 respectively. The developed assays were applied in a survey of 63 sport supplements samples obtained across the Island of Ireland with an additional seven reference samples previously investigated using LC–MS/MS. Androgen and estrogen bio-activity was found in 71% of the investigated samples. Bio-activity profiling was further broken down into agonists, partial agonists and antagonists. Supplements (13) with the strongest estrogenic bio-activity were chosen for further investigation. LC–MS/MS analysis of these samples determined the presence of phytoestrogens in seven of them. Supplements (38) with androgen bio-activity were also selected for further investigation. Androgen agonist bio-activity was detected in 12 supplements, antagonistic bio-activity was detected in 16 and partial antagonistic bio-activity was detected in 10. A further group of supplements (7) did not present androgenic bio-activity when tested alone but enhanced the androgenic agonist bio-activity of dihydrotestosterone when combined. The developed assays offer advantages in detection of known, unknown and low-level mixtures of endocrine disruptors over existing analytical screening techniques. For the detection and identification of constituent hormonally active compounds the combination of biological and physio-chemical techniques is optimal.

An improved immunoassay for detection of saxitoxin by surface plasmon resonance biosensors

Saxitoxin and its analogs, the causative agents of paralytic shellfish poisoning (PSP), are a worldwide threat to seafood safety. Effective monitoring of potentially contaminated fishing areas as well as screening of seafood samples is necessary to adequately protect the public. While many analytical methods exist for detecting paralytic shellfish toxins (PSTs), each technique has challenges associated with routine use. One recently developed method [1] that overcomes ethical or performance-related issues of other techniques is the surface plasmon resonance (SPR) bioassay. Notwithstanding the advantages of this method, much research remains in optimizing the sensor substrate and assay conditions to create a robust technique for rapid and sensitive measurement of PSTs. This manuscript describes a more rigorous and stable SPR inhibition immunoassay through optimization of the surface chemistry as well as determination of optimum mixture ratios and mixing times. The final system provides rapid substrate formation (18 h saxitoxin conjugation with low reagent consumption), contains a reference channel for each assay, and is capable of triplicate measurements in a single run with detection limits well below the regulatory action level. Published by Elsevier B.V.

Detection of hazardous food contaminants by transcriptomics fingerprinting

Unprecedented biotechnological advances in the past decade have delivered powerful transcriptomics methods that provide new opportunities for a risk-based and, hence, more effective control of food quality and safety. The fundamental hypothesis underlying the application of a transcriptomics or other

Mass spectrometry-based metabolomics applied to the chemical safety of food

Mass spectrometry (MS)-based metabolomics is emerging as an important field of research in many scientific areas, including chemical safety of food. A particular strength of this approach is its potential to reveal some physiological effects induced by complex mixtures of chemicals present at trace concentrations. The limitations of other analytical approaches currently employed to detect low-dose and mixture effects of chemicals make detection very problematic. Besides this basic technical challenge, numerous analytical choices have to be made at each step of a metabolomics study, and each step can have a direct impact on the final results obtained and their interpretation (i.e. sample preparation, sample introduction, ionization, signal acquisition, data processing, and data analysis). As the application of metabolomics to chemical analysis of food is still in its infancy, no consensus has yet been reached on defining many of these important parameters. In this context, the aim of the present study is to review all these aspects of MS-based approaches to metabolomics, and to give a comprehensive, critical overview of the current state of the art, possible pitfalls, and future challenges and trends linked to this emerging field. (C) 2010 Elsevier Ltd. All rights reserved.

Tree-Based Adaptive Spatial Detection for Adaptive Modulated MIMO Systems

Adaptive Multiple-Input Multiple-Output (MIMO) systems achieve a much higher information rate than conventional fixed schemes due to their ability to adapt their configurations according to the wireless communications environment. However, current adaptive MIMO detection schemes exhibit either low performance (and hence low spectral efficiency) or huge computational
complexity. In particular, whilst deterministic Sphere Decoder (SD) detection schemes are well established for static MIMO systems, exhibiting deterministic parallel structure, low computational complexity and quasi-ML detection performance, there are no corresponding adaptive schemes. This paper solves
this problem, describing a hybrid tree based adaptive modulation detection scheme. Fixed Complexity Sphere Decoding (FSD) and Real-Values FSD (RFSD) are modified and combined into a hybrid scheme exploited at low and medium SNR to provide the highest possible information rate with quasi-ML Bit Error
Rate (BER) performance, while Reduced Complexity RFSD, BChase and Decision Feedback (DFE) schemes are exploited in the high SNR regions. This algorithm provides the facility to balance the detection complexity with BER performance with compatible information rate in dynamic, adaptive MIMO communications
environments.

Effect-based proteomic detection of growth promoter abuse

Unregulated growth promoter use in food-producing animals is an issue of concern both from food safety and animal welfare perspectives. However, the monitoring of such practices is analytically challenging due to the concerted actions of users to evade detection. Techniques based on the monitoring of biological responses to exogenous administrations have been proposed as more sensitive methods to identify treated animals. This study has, for the first time, profiled plasma proteome responses in bovine animals to treatment with nortestosterone decanoate and 17 beta-oestradiol benzoate, followed by dexamethasone administration. Two-dimensional fluorescence differential in-gel electrophoresis analysis revealed a series of hepatic and acute-phase proteins within plasma whose levels were up- or down-regulated within phases of the treatment regime. Surface plasmon resonance (SPR) immuno-assays were developed to quantify responses of identified protein markers during the experimental treatment study with a view to developing methods which can be used as screening tools for growth promoter abuse detection. SPR analysis demonstrated the potential for plasma proteins to be used as indicative measures of growth promoter administrations and concludes that the sensitivity and robustness of any detection approach based on plasma proteome analysis would benefit from examination of a range of proteins representative of diverse biological processes rather being reliant on specific individual markers.