Design of a Neuromemristive Echo State Network Architecture

Echo state neural networks (ESNs) provide an efficient classification technique for spatiotemporal signals. The feedback connections in the ESN enable feature extraction in both spatial and temporal components in time series data. This property has been used in several application domains such as image and video analysis, anomaly detection, and speech recognition. The software implementations of the ESN demonstrated efficiency in processing such applications, and have low design cost and flexibility. However, hardware implementation is necessary for power constrained resources applications such as therapeutic and mobile devices. Moreover, software realization consumes an order or more power compared to the hardware realization. In this work, a hardware ESN architecture with neuromemristive system is proposed. A neuromemristive system is a brain inspired computing system that uses memristive devises for synaptic plasticity. The memristive devices in neuromemristive systems have several interesting properties such as small footprint, simple device structure, and most importantly zero static power dissipation. The proposed architecture is reconfigurable for different ESN topologies. 2-D mesh architecture and toroidal networks are exploited in the reservoir layer. The relation between performance of the proposed reservoir architecture and reservoir metrics are analyzed. The proposed architecture is tested on a suite of medical and human computer interaction applications. The benchmark suite includes epileptic seizure detection, speech emotion recognition, and electromyography (EMG) based finger motion recognition. The proposed ESN architecture demonstrated an accuracy of $90\%$, $96\%$, and $84\%$ for epileptic seizure detection, speech emotion recognition and EMG prosthetic fingers control respectively

Methods for Quantifying Power Characteristics and Chronic Patterns of Use Behavior of Electronic Vaping Products

Background: The complexity and variety of inhaled tobacco products have increased significantly with the introduction of Electronic Nicotine Delivery Systems (ENDS). Product characteristics and human behavior are the main factors affecting products\u27 emissions, consumption, and health effects. Combining the understanding of these two factors informs the next generation of regulations of these products. Quantifying use patterns helps health care professionals provide informed treatment of users addicted to nicotine and tobacco products. The literature lacks comprehensive studies to characterize ENDS hardware and operation, such as heating element resistance, battery performance, power, and thermal management. Human behavior is measured as use topography, a temporal signal of the interaction between the user\u27s mouth and the product. Traditional analysis of use topography focused on short-term puff dynamics, and overlooks extended session dynamics. The literature lacks the appropriate parameters and tools to quantify session dynamics over a long duration (i.e. days, weeks, months). Method and validation: This dissertation focuses on two aims: The first aim is to design methods to characterize the hardware and operation of modern ENDS devices and test their effects on ENDS performance. Parts of ENDS devices are repurposed to produce product-specific testing apparatus of effective coil resistance for several ENDS products. The effects of manufacturing variation in coil resistance on coil lifetime and Total Particulate Matter (TPM) are measured for one of the most popular pod-style ENDS. A method for dynamic measurement of electrical signals in modern ENDS is presented and validated for ENDS power management characterization. The second aim is to design and validate algorithms for quantifying chronic use topographies associated with inhaled tobacco products. The quantifying tool is designed based on autocorrelation to quantify chronic topography parameters including session period, and session duration as random distributions. These distributions provide insights into session topography dynamics over a day, a week, a month, and longer. Results: Significant variations in coil resistance were observed within and between brands such as the difference of 0.593 [Ω] (p \u3c 0.001) between JUUL and Vuse ALTO. The mean resistance and standard deviation of the coil assemblies was shown to be μ= 1.031 (σ= 0.067) [Ω] for Vuse ALTO and μ= 1.624 (σ= 0.033)[Ω] for JUUL. The variation in coil resistance between products and within products can have significant impacts on aerosol emissions. Dynamic measurement of power in Vuse ALTO showed that voltage is delivered to the coil as pulses of ~119.5 Hz with duty cycles of 0.3 - 0.6 which found to be correlated with the energy and change in temperature in coil. The mass of the generated aerosol per puff was correlated with the energy per puff. Quantifying session topography method successfully worked with puff period, session period and session duration with mean absolute percentage error of 1.18 [%], 2.92 [%], 12.59 [%] respectively. The method showed resiliency to session dynamic variation with accepted percentage of 99.98 [%], 92.39 [%], and 76.21 [%] for puff period, session period and session duration respectively. The method appears sufficiently valid and robust for analysis of natural environment human subject behavioral studies of tobacco product use. Conclusions: The absence of e-liquid in the pod is an important factor in causing coil failure. Small bits of the degraded coil could be potentially introduced to the aerosol. Energy is an important, if not the most important, contributor to the yield generated form an ENDS. A method was demonstrated to dynamically measure coil temperature based on temperature coefficient of resistance (TCR). It was also shown that coil temperature can be controlled by the ENDS by changing the energy delivered to the coil per pulse which is intern controlled by duty cycle of the pulses using the PWM algorithm. The quantifying session topography method provides high value in investigating the effects of user environment such as a day of week on session dynamics. It also demonstrated an example of using the method for quantifying how product characteristics such as e-liquid flavors and nicotine concentration may moderate use behavior

Design and Analysis of a Neuromemristive Reservoir Computing Architecture for Biosignal Processing

Reservoir computing (RC) is gaining traction in several signal processing domains, owing to its nonlinear stateful computation, spatiotemporal encoding, and reduced training complexity over recurrent neural networks (RNNs). Previous studies have shown the effectiveness of software-based RCs for a wide spectrum of applications. A parallel body of work indicates that realizing RNN architectures using custom integrated circuits and reconfigurable hardware platforms yields significant improvements in power and latency. In this research, we propose a neuromemristive RC architecture, with doubly twisted toroidal structure, that is validated for biosignal processing applications. We exploit the device mismatch to implement the random weight distributions within the reservoir and propose mixed-signal subthreshold circuits for energy efficiency. A comprehensive analysis is performed to compare the efficiency of the neuromemristive RC architecture in both digital(reconfigurable) and subthreshold mixed-signal realizations. Both EEG and EMG biosignal benchmarks are used for validating the RC designs. The proposed RC architecture demonstrated an accuracy of 90% and 84% for epileptic seizure detection and EMG prosthetic finger control respectively

Method for Quantifying Variation in the Resistance of Electronic Cigarette Coils

In electronic nicotine delivery systems (ENDS), coil resistance is an important factor in the generation of heat energy used to change e-liquid into vapor. An accurate and unbiased method for testing coil resistance is vital for understanding its effect on emissions and reporting results that are comparable across different types and brands of ENDS and measured in different laboratories. This study proposes a robust, accurate and unbiased method for measuring coil resistance. An apparatus is used which mimics the geometric configuration and assembly of ENDS reservoirs, coils and power control units. The method is demonstrated on two commonly used ENDS devices—the ALTO by Vuse and JUUL. Analysis shows that the proposed method is stable and reliable. The two-wire configuration introduced a positive measurement bias of 0.086 (Ω), which is a significant error for sub-ohm coil designs. The four-wire configuration is far less prone to bias error and is recommended for universal adoption. We observed a significant difference in the coil resistance of 0.593 (Ω) (p < 0.001) between the two products tested. The mean resistance and standard deviation of the reservoir/coil assemblies was shown to be 1.031 (0.067) (Ω) for ALTO and 1.624 (0.033) (Ω) for JUUL. The variation in coil resistance between products and within products can have significant impacts on aerosol emissions

Genetic profiling of hsp70 gene in local Iraqi goats

Animals display numerous physiological and behavioral responses that reduce the effects of heat stress. Moreover, genetic variance is strongly associated with responses to heat stress, including variants of heat shock proteins (HSPs) that are necessary for thermoregulation and stress resistance. Herein, we performed the molecular profiling of the HSP 70 gene, and its polymorphism was demonstrated as a possible factor in the stress tolerance of local Iraqi goats. A number of different mutations were found owing to seven main polymorphisms. Results indicated the occurrence of silent and missense mutations in sequences obtained for Iraqi local goats. Genetic diversity was observed in the HSP70 gene of Iraqi local goats on the basis of phylogenetic-tree analysis as some mutations occurred once whereas others occurred multiple times. The polymorphisms LC616787, LC616788, and LC616791 were combined with the reference gene in the same branch, whereas polymorphisms (LC616785 and LC616786) and (LC616789 and LC616790) met in different branches, respectively. Moreover, all studied proteins had mismatches in their three-dimensional structures. Therefore, the presence of specific genetic differences within the HSP70 gene in Iraqi goats can increase the possibility of selecting animals more suitable to various levels of stress

Effects of Manufacturing Variation in Electronic Cigarette Coil Resistance and Initial Pod Mass on Coil Lifetime and Aerosol Generation

This work investigated the effects of manufacturing variations, including coil resistance and initial pod mass, on coil lifetime and aerosol generation of Vuse ALTO pods. Random samples of pods were used until failure (where e-liquid was consumed, and coil resistance increased to high value indicating a coil break). Initial coil resistance, initial pod mass, and e-liquid net mass ranged between 0.89 to 1.14 [Ω], 6.48 to 6.61 [g], and 1.88 to 2.00 [g] respectively. Coil lifetime was µ (mean) = 158, σ (standard deviation) = 21.5 puffs. Total mass of e-liquid consumed until coil failure was µ = 1.93, σ = 0.035 [g]. TPM yield per puff of all test pods for the first session (brand new pods) was µ = 0.0123, σ = 0.0003 [g]. Coil lifetime and TPM yield per puff were not correlated with either variation in initial coil resistance or variation in initial pod mass. The absence of e-liquid in the pod is an important factor in causing coil failure. Small bits of the degraded coil could be potentially introduced to the aerosol. This work suggests that further work is required to investigate the effect of e-liquid composition on coil lifetime and TPM yield per puff

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population