Dissociating the spatio-temporal characteristics of cortical neuronal activity associated with human volitional swallowing in the healthy adult brain

Human swallowing represents a complex highly coordinated sensorimotor function whose functional neuroanatomy remains incompletely understood. Specifically, previous studies have failed to delineate the temporo-spatial sequence of those cerebral loci active during the differing phases of swallowing. We therefore sought to define the temporal characteristics of cortical activity associated with human swallowing behaviour using a novel application of magnetoencephalography (MEG). In healthy volunteers (n = 8, aged 28-45), 151-channel whole cortex MEG was recorded during the conditions of oral water infusion, volitional wet swallowing (5 ml bolus), tongue thrust or rest. Each condition lasted for 5 s and was repeated 20 times. Synthetic aperture magnetometry (SAM) analysis was performed on each active epoch and compared to rest. Temporal sequencing of brain activations utilised time-frequency wavelet plots of regions selected using virtual electrodes. Following SAM analysis, water infusion preferentially activated the caudolateral sensorimotor cortex, whereas during volitional swallowing and tongue movement, the superior sensorimotor cortex was more strongly active. Time-frequency wavelet analysis indicated that sensory input from the tongue simultaneously activated caudolateral sensorimotor and primary gustatory cortex, which appeared to prime the superior sensory and motor cortical areas, involved in the volitional phase of swallowing. Our data support the existence of a temporal synchrony across the whole cortical swallowing network, with sensory input from the tongue being critical. Thus, the ability to non-invasively image this network, with intra-individual and high temporal resolution, provides new insights into the brain processing of human swallowing. © 2004 Elsevier Inc. All rights reserved.

Three-factor models versus time series models:quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data

Signal integration determines cell fate on the cellular level, affects cognitive processes and affective responses on the behavioural level, and is likely to be involved in psychoneurobiological processes underlying mood disorders. Interactions between stimuli may subjected to time effects. Time-dependencies of interactions between stimuli typically lead to complex cell responses and complex responses on the behavioural level. We show that both three-factor models and time series models can be used to uncover such time-dependencies. However, we argue that for short longitudinal data the three factor modelling approach is more suitable. In order to illustrate both approaches, we re-analysed previously published short longitudinal data sets. We found that in human embryonic kidney 293 cells cells the interaction effect in the regulation of extracellular signal-regulated kinase (ERK) 1 signalling activation by insulin and epidermal growth factor is subjected to a time effect and dramatically decays at peak values of ERK activation. In contrast, we found that the interaction effect induced by hypoxia and tumour necrosis factor-alpha for the transcriptional activity of the human cyclo-oxygenase-2 promoter in HEK293 cells is time invariant at least in the first 12-h time window after stimulation. Furthermore, we applied the three-factor model to previously reported animal studies. In these studies, memory storage was found to be subjected to an interaction effect of the beta-adrenoceptor agonist clenbuterol and certain antagonists acting on the alpha-1-adrenoceptor / glucocorticoid-receptor system. Our model-based analysis suggests that only if the antagonist drug is administer in a critical time window, then the interaction effect is relevant.

Microarray analysis of expression of cell death-associated genes in rat spinal cord cells exposed to cyclic tensile stresses in vitro

The application of mechanical insults to the spinal cord results in profound cellular and molecular changes, including the induction of neuronal cell death and altered gene expression profiles. Previous studies have described alterations in gene expression following spinal cord injury, but the specificity of this response to mechanical stimuli is difficult to investigate in vivo. Therefore, we have investigated the effect of cyclic tensile stresses on cultured spinal cord cells from E15 Sprague-Dawley rats, using the FX3000 Flexercell Strain Unit. We examined cell morphology and viability over a 72 hour time course. Microarray analysis of gene expression was performed using the Affymetrix GeneChip System, where categorization of identified genes was performed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) systems. Changes in expression of 12 genes were validated with quantitative real-time reverse transcription polymerase chain reaction (RT-PCR).

Investigating the functional properties of the somatosensory cortex during experimental visceral pain using magnetoencephalography

Background The somatosensory cortex has been inconsistently activated in pain studies and the functional properties of subregions within this cortical area are poorly understood. To address this we used magnetoencephalography (MEG), a brain imaging technique capable of recording changes in cortical neural activity in real-time, to investigate the functional properties of the somatosensory cortex during different phases of the visceral pain experience. Methods In eight participants (4 male), 151-channel whole cortex MEG was used to detect cortical neural activity during 25 trials lasting 20 seconds each. Each trial comprised four separate periods of 5 seconds in duration. During each of the periods, different visual cues were presented, indicating that period 1=rest, period 2=anticipation, period 3=pain and period 4=post pain. During period 3, participants received painful oesophageal balloon distensions (four at 1 Hz). Regions of cortical activity were identified using Synthetic Aperture Magnetometry (SAM) and by the placement of virtual electrodes in regions of interest within the somatosensory cortex, time-frequency wavelet plots were generated. Results SAM analysis revealed significant activation with the primary (S1) and secondary (S2) somatosensory cortices. The time-frequency wavelet spectrograms showed that activation in S1 increased during the anticipation phase and continued during the presentation of the stimulus. In S2, activation was tightly time and phase-locked to the stimulus within the pain period. Activations in both regions predominantly occurred within the 10–15 Hz and 20–30 Hz frequency bandwidths. Discussion These data are consistent with the role of S1 and S2 in the sensory discriminatory aspects of pain processing. Activation of S1 during anticipation and then pain may be linked to its proposed role in attentional as well as sensory processing. The stimulus-related phasic activity seen in S2 demonstrates that this region predominantly encodes information pertaining to the nature and intensity of the stimulus.

Mathematical modelling and control of agitated extraction columns

Liquid-liquid extraction has long been known as a unit operation that plays an important role in industry. This process is well known for its complexity and sensitivity to operation conditions. This thesis presents an attempt to explore the dynamics and control of this process using a systematic approach and state of the art control system design techniques. The process was studied first experimentally under carefully selected. operation conditions, which resembles the ranges employed practically under stable and efficient conditions. Data were collected at steady state conditions using adequate sampling techniques for the dispersed and continuous phases as well as during the transients of the column with the aid of a computer-based online data logging system and online concentration analysis. A stagewise single stage backflow model was improved to mimic the dynamic operation of the column. The developed model accounts for the variation in hydrodynamics, mass transfer, and physical properties throughout the length of the column. End effects were treated by addition of stages at the column entrances. Two parameters were incorporated in the model namely; mass transfer weight factor to correct for the assumption of no mass transfer in the. settling zones at each stage and the backmixing coefficients to handle the axial dispersion phenomena encountered in the course of column operation. The parameters were estimated by minimizing the differences between the experimental and the model predicted concentration profiles at steady state conditions using non-linear optimisation technique. The estimated values were then correlated as functions of operating parameters and were incorporated in·the model equations. The model equations comprise a stiff differential~algebraic system. This system was solved using the GEAR ODE solver. The calculated concentration profiles were compared to those experimentally measured. A very good agreement of the two profiles was achieved within a percent relative error of ±2.S%. The developed rigorous dynamic model of the extraction column was used to derive linear time-invariant reduced-order models that relate the input variables (agitator speed, solvent feed flowrate and concentration, feed concentration and flowrate) to the output variables (raffinate concentration and extract concentration) using the asymptotic method of system identification. The reduced-order models were shown to be accurate in capturing the dynamic behaviour of the process with a maximum modelling prediction error of I %. The simplicity and accuracy of the derived reduced-order models allow for control system design and analysis of such complicated processes. The extraction column is a typical multivariable process with agitator speed and solvent feed flowrate considered as manipulative variables; raffinate concentration and extract concentration as controlled variables and the feeds concentration and feed flowrate as disturbance variables. The control system design of the extraction process was tackled as multi-loop decentralised SISO (Single Input Single Output) as well as centralised MIMO (Multi-Input Multi-Output) system using both conventional and model-based control techniques such as IMC (Internal Model Control) and MPC (Model Predictive Control). Control performance of each control scheme was. studied in terms of stability, speed of response, sensitivity to modelling errors (robustness), setpoint tracking capabilities and load rejection. For decentralised control, multiple loops were assigned to pair.each manipulated variable with each controlled variable according to the interaction analysis and other pairing criteria such as relative gain array (RGA), singular value analysis (SVD). Loops namely Rotor speed-Raffinate concentration and Solvent flowrate Extract concentration showed weak interaction. Multivariable MPC has shown more effective performance compared to other conventional techniques since it accounts for loops interaction, time delays, and input-output variables constraints.

Classification of oximetry signals using Bayesian neural networks to assist in the detection of obstructive sleep apnoea syndrome

In the present study, multilayer perceptron (MLP) neural networks were applied to help in the diagnosis of obstructive sleep apnoea syndrome (OSAS). Oxygen saturation (SaO2) recordings from nocturnal pulse oximetry were used for this purpose. We performed time and spectral analysis of these signals to extract 14 features related to OSAS. The performance of two different MLP classifiers was compared: maximum likelihood (ML) and Bayesian (BY) MLP networks. A total of 187 subjects suspected of suffering from OSAS took part in the study. Their SaO2 signals were divided into a training set with 74 recordings and a test set with 113 recordings. BY-MLP networks achieved the best performance on the test set with 85.58% accuracy (87.76% sensitivity and 82.39% specificity). These results were substantially better than those provided by ML-MLP networks, which were affected by overfitting and achieved an accuracy of 76.81% (86.42% sensitivity and 62.83% specificity). Our results suggest that the Bayesian framework is preferred to implement our MLP classifiers. The proposed BY-MLP networks could be used for early OSAS detection. They could contribute to overcome the difficulties of nocturnal polysomnography (PSG) and thus reduce the demand for these studies.

Medicines management strategies to improve antibiotic prescribing

A systematic review was conducted to explicitly identify interventions that alone, or in combination, were effective in improving antibiotic prescribing. The citation search strategy used in the present review provided a database of 365077 studies, of which only twenty-five were included in the final review (“review studies”). Analysis of the interventions used within the review studies indicated that a combination of “guidelines” and “pharmacy” interventions have the greatest potential to improve antibiotic prescribing. Two types of qualitative research were conducted, semi-structured interviews and the collection of naturally occurring data. Semi-structured interviews were conducted in order to determine NHS managers? perceptions of current policies used to improve antibiotic prescribing within selected Primary Care Trusts and highlighted the importance of pharmacy intervention, formularies or guidelines and improved prescribing analysis (IT based intervention) on improving antibiotic prescribing. This was supported by the collection of naturally occurring data, which was used to provide further insight into interventions used to improve antibiotic prescribing. The Specialist Antibiotic Pharmacist (HD) produced and implemented an innovative electronic antibiotic prescribing analysis tool (the Antibiotic Database) to analyse and improve antibiotic prescribing in a consistent manner. The key advantage of the Antibiotic Database was the time and money saved on producing visual electronic outputs containing an inaccurate outcome measure or time period for analysis. The results concluded that an IT based intervention, such as the Antibiotic Database should be used, in addition to the use of antibiotic guidelines and pharmacy intervention, within all sectors of the NHS in order to improve antibiotic prescribing and its analysis.

Maternal low-protein diet during mouse pre-implantation development induces vascular dysfunction and altered renin-angiotensin-system homeostasis in the offspring

Environmental perturbations during early mammalian development can affect aspects of offspring growth and cardiovascular health. We have demonstrated previously that maternal gestational dietary protein restriction in mice significantly elevated adult offspring systolic blood pressure. Therefore, the present study investigates the key mechanisms of blood pressure regulation in these mice. Following mating, female MF-1 mice were assigned to either a normal-protein diet (NPD; 18% casein) or an isocaloric low-protein diet throughout gestation (LPD; 9% casein), or fed the LPD exclusively during the pre-implantation period (3.5d) before returning to the NPD for the remainder of gestation (Emb-LPD). All offspring received standard chow. At 22 weeks, isolated mesenteric arteries from LPD and Emb-LPD males displayed significantly attenuated vasodilatation to isoprenaline (P=0.04 and P=0.025, respectively), when compared with NPD arteries. At 28 weeks, stereological analysis of glomerular number in female left kidneys revealed no significant difference between the groups. Real-time RT-PCR analysis of type 1a angiotensin II receptor, Na /K ATPase transporter subunits and glucocorticoid receptor expression in male and female left kidneys revealed no significant differences between the groups. LPD females displayed elevated serum angiotensin-converting enzyme (ACE) activity (P=0.044), whilst Emb-LPD males had elevated lung ACE activity (P=0.001), when compared with NPD offspring. These data demonstrate that elevated offspring systolic blood pressure following maternal gestational protein undernutrition is associated with impaired arterial vasodilatation in male offspring, elevated serum and lung ACE activity in female and male offspring, respectively, but kidney glomerular number in females and kidney gene expression in male and female offspring appear unaffected. © 2010 The Authors.

Optimally-designed single fiber Bragg grating filter scheme for RZ-OOK/DPSK/DQPSK to NRZ-OOK/DPSK/DQPSK format conversion

We investigate return-to-zero (RZ) to non-return-to-zero (NRZ) format conversion by means of the linear time-invariant system theory. It is shown that the problem of converting random RZ stream to NRZ stream can be reduced to constructing an appropriate transfer function for the linear filter. This approach is then used to propose novel optimally-designed single fiber Bragg grating (FBG) filter scheme for RZ-OOK/DPSK/DQPSK to NRZ-OOK/DPSK/DQPSK format conversion. The spectral response of the FBG is designed according to the optical spectra of the algebraic difference between isolated NRZ and RZ pulses, and the filter order is optimized for the maximum Q-factor of the output NRZ signals. Experimental results as well as simulations show that such an optimallydesigned FBG can successfully perform RZ-OOK/DPSK/DQPSK to NRZOOK/ DPSK/DQPSK format conversion.

Investigating the role of capacitive coupling between the operating table and the return electrode of an electrosurgery unit in the modification of the current density distribution within the patients’ body

Background: Electrosurgery units are widely employed in modern surgery. Advances in technology have enhanced the safety of these devices, nevertheless, accidental burns are still regularly reported. This study focuses on possible causes of sacral burns as complication of the use of electrosurgery. Burns are caused by local densifications of the current, but the actual pathway of current within patient's body is unknown. Numerical electromagnetic analysis can help in understanding the issue. Methods: To this aim, an accurate heterogeneous model of human body (including seventy-seven different tissues), electrosurgery electrodes, operating table and mattress was build to resemble a typical surgery condition. The patient lays supine on the mattress with the active electrode placed onto the thorax and the return electrode on his back. Common operating frequencies of electrosurgery units were considered. Finite Difference Time Domain electromagnetic analysis was carried out to compute the spatial distribution of current density within the patient's body. A differential analysis by changing the electrical properties of the operating table from a conductor to an insulator was also performed. Results: Results revealed that distributed capacitive coupling between patient body and the conductive operating table offers an alternative path to the electrosurgery current. The patient's anatomy, the positioning and the different electromagnetic properties of tissues promote a densification of the current at the head and sacral region. In particular, high values of current density were located behind the sacral bone and beneath the skin. This did not occur in the case of non-conductive operating table. Conclusion: Results of the simulation highlight the role played from capacitive couplings between the return electrode and the conductive operating table. The concentration of current density may result in an undesired rise in temperature, originating burns in body region far from the electrodes. This outcome is concordant with the type of surgery-related sacral burns reported in literature. Such burns cannot be immediately detected after surgery, but appear later and can be confused with bedsores. In addition, the dosimetric analysis suggests that reducing the capacity coupling between the return electrode and the operating table can decrease or avoid this problem. © 2013 Bifulco et al.; licensee BioMed Central Ltd.

An efficient, approximate path-following algorithm for elastic net based nonlinear spike enhancement

Unwanted spike noise in a digital signal is a common problem in digital filtering. However, sometimes the spikes are wanted and other, superimposed, signals are unwanted, and linear, time invariant (LTI) filtering is ineffective because the spikes are wideband - overlapping with independent noise in the frequency domain. So, no LTI filter can separate them, necessitating nonlinear filtering. However, there are applications in which the noise includes drift or smooth signals for which LTI filters are ideal. We describe a nonlinear filter formulated as the solution to an elastic net regularization problem, which attenuates band-limited signals and independent noise, while enhancing superimposed spikes. Making use of known analytic solutions a novel, approximate path-following algorithm is given that provides a good, filtered output with reduced computational effort by comparison to standard convex optimization methods. Accurate performance is shown on real, noisy electrophysiological recordings of neural spikes.

Selection, staging and sequencing in the recent Chinese privatization

Selection in privatization is a decision-making process of choosing state-owned enterprises (SOEs), prioritizing and sequencing privatizing events, and determining the extent of private ownership in partial privatization. We investigate this process in an important but rarely studied case of China. Based on the SOE population over 1998-2008, we track 49,456 wholly SOEs and identify 9,359 privatization cases over time. Our econometric analysis concludes: (i) The privatization selection is a complex decision-making process in which local governments balance between various economic, financial and political objectives. (ii) In the recent Chinese privatization, firm performance relates to the selection, staging and sequencing in privatization in an inverted-U fashion. The worse and the best performing SOEs are more likely to remain state-owned, maintain higher state holding when privatized, and are less likely to be privatized later in time. These patterns suggest the privatization reform slowdown and the underlying changes in the privatization policy.

Non-invasive winding fault detection for induction machines based on stray flux magnetic sensors

Non-intrusive monitoring of health state of induction machines within industrial process and harsh environments poses a technical challenge. In the field, winding failures are a major fault accounting for over 45% of total machine failures. In the literature, many condition monitoring techniques based on different failure mechanisms and fault indicators have been developed where the machine current signature analysis (MCSA) is a very popular and effective method at this stage. However, it is extremely difficult to distinguish different types of failures and hard to obtain local information if a non-intrusive method is adopted. Typically, some sensors need to be installed inside the machines for collecting key information, which leads to disruption to the machine operation and additional costs. This paper presents a new non-invasive monitoring method based on GMRs to measure stray flux leaked from the machines. It is focused on the influence of potential winding failures on the stray magnetic flux in induction machines. Finite element analysis and experimental tests on a 1.5-kW machine are presented to validate the proposed method. With time-frequency spectrogram analysis, it is proven to be effective to detect several winding faults by referencing stray flux information. The novelty lies in the implement of GMR sensing and analysis of machine faults.

Project time risk analysis through simulation

An inherent weakness in the management of large scale projects is the failure to achieve the scheduled completion date. When projects are planned with the objective of time achievement, the initial planning plays a vital role in the successful achievement of project deadlines. Cost and quality are additional priorities when such projects are being executed. This article proposes a methodology for achieving time duration of a project through risk analysis with the application of a Monte Carlo simulation technique. The methodology is demonstrated using a case application of a cross-country petroleum pipeline construction project.

Time series analysis in the assessment of ICT impact at the aggregate level – lessons and implications for the new economy

The major role of information and communication technology (ICT) in the new economy is well documented: countries worldwide are pouring resources into their ICT infrastructure despite the widely acknowledged “productivity paradox”. Evaluating the contribution of ICT investments has become an elusive but important goal of IS researchers and economists. But this area of research is fraught with complexity and we have used Solow's Residual together with time-series analysis tools to overcome some methodological inadequacies of previous studies. Using this approach, we conduct a study of 20 countries to determine if there was empirical evidence to support claims that ICT investments are worthwhile. The results show that ICT contributes to economic growth in many developed countries and newly industrialized economies (NIEs), but not in developing countries. We finally suggest ICT-complementary factors, in an attempt to rectify possible flaws in ICT policies as a contribution towards improvement in global productivity.