Experimental investigation of open-ended microwave oven assisted encapsulation process

An open ended microwave oven is presented with improved uniform heating, heating rates and power conversion efficiency. This next generation oven produces more uniform EM fields in the evanescent region forming part of the heating area of the oven. These fields are vital for the rapid and uniform heating of various electromagnetically lossy materials. A fibre optic temperature sensor and an IR pyrometer are used to measure in situ and in real-time the temperature of the curing materials. An automatic computer controlled closed feedback loop measures the temperature in the curing material and drives the microwave components to obtain predetermined curing temperature cycles for efficient curing. Uniform curing of the lossy encapsulants is achieved with this oven with typical cure cycle of 270 seconds with a ramp rate of 1oC/s and a hold period of 2 minutes. Differential scanning calorimeter based measurement for the pulsed microwave based curing of the polymer dielectric indicates a ~ 100% degree of cure

Increased spontaneous MEG signal diversity for psychoactive doses of ketamine, LSD and psilocybin

What is the level of consciousness of the psychedelic state? Empirically, measures of neural signal diversity such as entropy and Lempel-Ziv (LZ) complexity score higher for wakeful rest than for states with lower conscious level like propofol-induced anesthesia. Here we compute these measures for spontaneous magnetoencephalographic (MEG) signals from humans during altered states of consciousness induced by three psychedelic substances: psilocybin, ketamine and LSD. For all three, we find reliably higher spontaneous signal diversity, even when controlling for spectral changes. This increase is most pronounced for the single-channel LZ complexity measure, and hence for temporal, as opposed to spatial, signal diversity. We also uncover selective correlations between changes in signal diversity and phenomenological reports of the intensity of psychedelic experience. This is the first time that these measures have been applied to the psychedelic state and, crucially, that they have yielded values exceeding those of normal waking consciousness. These findings suggest that the sustained occurrence of psychedelic phenomenology constitutes an elevated level of consciousness - as measured by neural signal diversity

Brain function assessment in different conscious states

Background: The study of brain functioning is a major challenge in neuroscience fields as human brain has a dynamic and ever changing information processing. Case is worsened with conditions where brain undergoes major changes in so-called different conscious states. Even though the exact definition of consciousness is a hard one, there are certain conditions where the descriptions have reached a consensus. The sleep and the anesthesia are different conditions which are separable from each other and also from wakefulness. The aim of our group has been to tackle the issue of brain functioning with setting up similar research conditions for these three conscious states.Methods: In order to achieve this goal we have designed an auditory stimulation battery with changing conditions to be recorded during a 40 channel EEG polygraph (Nuamps) session. The stimuli (modified mismatch, auditory evoked etc.) have been administered both in the operation room and the sleep lab via Embedded Interactive Stimulus Unit which was developed in our lab. The overall study has provided some results for three domains of consciousness. In order to be able to monitor the changes we have incorporated Bispectral Index Monitoring to both sleep and anesthesia conditions.Results: The first stage results have provided a basic understanding in these altered states such that auditory stimuli have been successfully processed in both light and deep sleep stages. The anesthesia provides a sudden change in brain responsiveness; therefore a dosage dependent anesthetic administration has proved to be useful. The auditory processing was exemplified targeting N1 wave, with a thorough analysis from spectrogram to sLORETA. The frequency components were observed to be shifting throughout the stages. The propofol administration and the deeper sleep stages both resulted in the decreasing of N1 component. The sLORETA revealed similar activity at BA7 in sleep (BIS 70) and target propofol concentration of 1.2 μg/mL.Conclusions: The current study utilized similar stimulation and recording system and incorporated BIS dependent values to validate a common approach to sleep and anesthesia. Accordingly the brain has a complex behavior pattern, dynamically changing its responsiveness in accordance with stimulations and states. © 2010 Ozgoren et al; licensee BioMed Central Ltd

Entropy and Complexity Analyses in Alzheimer’s Disease: An MEG Study

Alzheimer’s disease (AD) is one of the most frequent disorders among elderly population and it is considered the main cause of dementia in western countries. This irreversible brain disorder is characterized by neural loss and the appearance of neurofibrillary tangles and senile plaques. The aim of the present study was the analysis of the magnetoencephalogram (MEG) background activity from AD patients and elderly control subjects. MEG recordings from 36 AD patients and 26 controls were analyzed by means of six entropy and complexity measures: Shannon spectral entropy (SSE), approximate entropy (ApEn), sample entropy (SampEn), Higuchi’s fractal dimension (HFD), Maragos and Sun’s fractal dimension (MSFD), and Lempel-Ziv complexity (LZC). SSE is an irregularity estimator in terms of the flatness of the spectrum, whereas ApEn and SampEn are embbeding entropies that quantify the signal regularity. The complexity measures HFD and MSFD were applied to MEG signals to estimate their fractal dimension. Finally, LZC measures the number of different substrings and the rate of their recurrence along the original time series. Our results show that MEG recordings are less complex and more regular in AD patients than in control subjects. Significant differences between both groups were found in several brain regions using all these methods, with the exception of MSFD (p-value < 0.05, Welch’s t-test with Bonferroni’s correction). Using receiver operating characteristic curves with a leave-one-out cross-validation procedure, the highest accuracy was achieved with SSE: 77.42%. We conclude that entropy and complexity analyses from MEG background activity could be useful to help in AD diagnosis

Complexity Analysis of Resting-State MEG Activity in Early-Stage Parkinson's Disease Patients

The aim of the present study was to analyze resting-state brain activity in patients with Parkinson's disease (PD), a degenerative disorder of the nervous system. Magnetoencephalography (MEG) signals were recorded with a 151-channel whole-head radial gradiometer MEG system in 18 early-stage untreated PD patients and 20 age-matched control subjects. Artifact-free epochs of 4 s (1250 samples) were analyzed with Lempel-Ziv complexity (LZC), applying two- and three-symbol sequence conversion methods. The results showed that MEG signals from PD patients are less complex than control subjects' recordings. We found significant group differences (p-values <0.01) for the 10 major cortical areas analyzed (e.g., bilateral frontal, central, temporal, parietal, and occipital regions). In addition, using receiver-operating characteristic curves with a leave-one-out cross-validation procedure, a classification accuracy of 81.58% was obtained. In order to investigate the best combination of LZC results for classification purposes, a forward stepwise linear discriminant analysis with leave-one out cross-validation was employed. LZC results (three-symbol sequence conversion) from right parietal and temporal brain regions were automatically selected by the model. With this procedure, an accuracy of 84.21% (77.78% sensitivity, 90.0% specificity) was achieved. Our findings demonstrate the usefulness of LZC to detect an abnormal type of dynamics associated with PD

The Electroencephalogram as a Biomarker Based on Signal Processing Using Nonlinear Techniques to Detect Dementia

Dementia being a syndrome caused by a brain disease of a chronic or progressive nature, in which the irreversible loss of intellectual abilities, learning, expressions arises; including memory, thinking, orientation, understanding and adequate communication, of organizing daily life and of leading a family, work and autonomous social life; leads to a state of total dependence; therefore, its early detection and classification is of vital importance in order to serve as clinical support for physicians in the personalization of treatment programs. The use of the electroencephalogram as a tool for obtaining information on the detection of changes in brain activities. This article reviews the types of cognitive spectrum dementia, biomarkers for the detection of dementia, analysis of mental states based on electromagnetic oscillations, signal processing given by the electroencephalogram, review of processing techniques, results obtained where it is proposed the mathematical model about neural networks, discussion and finally the conclusions

Functional optical fibers: organic and hybrid structures

Constant need for saving space and energy has led to the miniaturization of electronic devices and to the integration of such devices into various unconventional substrates like different kind of fibers. It has been proposed and in some cases already demonstrated that electronic devices such as light emitting diodes, photovoltaic cells, thin film transistors could be deposited straightto the fibers. Traditional textile fibers do not offer sufficiently stable and smooth base forelectronic devices. Plastic optical fibers (POF) that are flexible and of small size are suitable candidates for functional fibers and can be easily incorporated into the textile structure. POF could also enable to use light as an information carrier instead of typical electrical signals and would provide interesting lighting solutions. Such fibrous electronic devices however need new type of materials thats processing techniques would be compatible with cylindrical shape of the substrate and could be processable at temperatures suitable for plastic fibers. Inherently conductive polymers (ICPs) have opened the way to polymeric electronics thats driving force is the manufacturing of electronics at low cost on flexible substrates using solution processing methods such as printing or dip-coating. For some device components one has to still use inorganic materials that have nowadays been developed in a form compatible with plastic substrates and their processing conditions (e.g. indium tin oxide in a form of printing ink). The aim of this thesis is to study possibilities to combine unique properties of POF and ICPs in a form of functional optical fibers. This goal is realized by first studying manufacturing methods of POF as a substrate of functional fibers. In the second step of the research two different ICPs—polypyrrole (PPy) and poly(3,4-ethylene dioxythiophene) (PEDOT)—are studied as components of possible electronic devices. PPy films in a planar and fiber form are studied for transparent electrode application. Film formation is successful, but the results suggest that such PPy films have insufficient electrical conductivity and environmental stability for any real electronic device applications. PEDOT films are studied for ammonia sensor application in electrical and optical regime. It is demonstrated that PEDOT films can be used for detecting gaseous ammonia. Comparative study between the sensitivity of PEDOT: p-toluene sulfonate (PTS) and films made of commercially available aqueous dispersion of PEDOT:poly(styrene sulfonate) indicates that in situ polymerized PEDOT:PTS has better performance in sensor application due to its smaller counter-ion and larger surface area. Finally, a photovoltaic fiber based on a dye sensitized solar cell technology is demonstrated. This type of fiber acts as a fibrous photo-detector, but the obtained results are poor (short circuit current at nA level). Low performance of the photovoltaic fiber originates from the poor quality of a TiO2 layer and from the low intensity of light penetrating into the dye sensitized solar cell structure

Functional optical fibers: organic and hybrid structures

Constant need for saving space and energy has led to the miniaturization of electronic devices and to the integration of such devices into various unconventional substrates like different kind of fibers. It has been proposed and in some cases already demonstrated that electronic devices such as light emitting diodes, photovoltaic cells, thin film transistors could be deposited straightto the fibers. Traditional textile fibers do not offer sufficiently stable and smooth base forelectronic devices. Plastic optical fibers (POF) that are flexible and of small size are suitable candidates for functional fibers and can be easily incorporated into the textile structure. POF could also enable to use light as an information carrier instead of typical electrical signals and would provide interesting lighting solutions. Such fibrous electronic devices however need new type of materials thats processing techniques would be compatible with cylindrical shape of the substrate and could be processable at temperatures suitable for plastic fibers. Inherently conductive polymers (ICPs) have opened the way to polymeric electronics thats driving force is the manufacturing of electronics at low cost on flexible substrates using solution processing methods such as printing or dip-coating. For some device components one has to still use inorganic materials that have nowadays been developed in a form compatible with plastic substrates and their processing conditions (e.g. indium tin oxide in a form of printing ink). The aim of this thesis is to study possibilities to combine unique properties of POF and ICPs in a form of functional optical fibers. This goal is realized by first studying manufacturing methods of POF as a substrate of functional fibers. In the second step of the research two different ICPs—polypyrrole (PPy) and poly(3,4-ethylene dioxythiophene) (PEDOT)—are studied as components of possible electronic devices. PPy films in a planar and fiber form are studied for transparent electrode application. Film formation is successful, but the results suggest that such PPy films have insufficient electrical conductivity and environmental stability for any real electronic device applications. PEDOT films are studied for ammonia sensor application in electrical and optical regime. It is demonstrated that PEDOT films can be used for detecting gaseous ammonia. Comparative study between the sensitivity of PEDOT: p-toluene sulfonate (PTS) and films made of commercially available aqueous dispersion of PEDOT:poly(styrene sulfonate) indicates that in situ polymerized PEDOT:PTS has better performance in sensor application due to its smaller counter-ion and larger surface area. Finally, a photovoltaic fiber based on a dye sensitized solar cell technology is demonstrated. This type of fiber acts as a fibrous photo-detector, but the obtained results are poor (short circuit current at nA level). Low performance of the photovoltaic fiber originates from the poor quality of a TiO2 layer and from the low intensity of light penetrating into the dye sensitized solar cell structure

A critical analysis of polymer cure modeling for microelectronics applications

A review of polymer cure models used in microelectronics packaging applications reveals no clear consensus of the chemical rate constants for the cure reactions, or even of an effective model. The problem lies in the contrast between the actual cure process, which involves a sequence of distinct chemical reactions, and the models, which typically assume only one, (or two with some restrictions on the independence of their characteristic constants.) The standard techniques to determine the model parameters are based on differential scanning calorimetry (DSC), which cannot distinguish between the reactions, and hence yields results useful only under the same conditions, which completely misses the point of modeling. The obvious solution is for manufacturers to provide the modeling parameters, but failing that, an alternative experimental technique is required to determine individual reaction parameters, e.g. Fourier transform infra-red spectroscopy (FTIR)

Assessment of the accuracy of cure kinetics models and fitting approaches utilised in analysis of microelectronics encapsulation materials

The accuracy of four widely used cure kinetics models in predicting the cure rate of a commercially available encapsulant material is assessed. Four nth order phenomenological cure kinetics models and the single step autocatalytic model are outlined. These models are fitted to Differential Scanning Calorimetry data using two differing approaches. The Borchardt-Daniels approach is outlined and utilised in conjunction with a Levenberg Marquardt solver to determine model coefficients correlating the models to the experimental data. A particle swarm optimization approach to model fitting is also outlined and is used to develop an alternate set of model coefficients. The accuracy of each of the models combined with each of the fitting methods is defined using an error metric. Optimal model coefficients and related error metric data are presented. The results obtained indicate that the particle swarm optimization approach is able to fit the models more closely to the experimental data, resulting in lower error values than the Borchardt Daniels fitted data. The single step model is also shown to approximate the cure kinetics of the encapsulant material more closely than the nth order models