78 research outputs found

    Preparation and Properties of Nanoparticle-enhanced Composite Phase Change Material with Ceramic Porous Media

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    Paper presented at 2018 Canadian Society of Mechanical Engineers International Congress, 27-30 May 2018.Nanoparticle-enhanced tailing-paraffin composite phase change material (NCPCM) is fabricated by spontaneous melt infiltration. Industrial waste-iron tailing is used as raw material to prepare ceramic porous carrier with a foam-gel casting method. By adjusting the fabrication parameters, optimal NCPCM properties are obtained with paraffin content of 70%~88% and thermal conductivity of 0.351~0.490 W/(m·K), which is nearly 200% the thermal conductivity of paraffin wax. After 25 melting/solidification cycles, the nanoparticles remain well dispersion with overall stability in the composite phase change material, and the thermal conductivity slightly decreased from 0.349 to 0.317 W/ m·K. With multiple melting and solidification cycles, a low weight loss of 2.3~7.8 wt.% is demonstrated. The strength of ceramic frame is found to have a direct effect on the weight loss. Compared with exisiting nanoparticle-enhanced phase change material, the new NCPCM shows significantly improved thermal conductivity and better nanoparticle stability due to its ability to prevent nanoparticles from disposition

    A Novel Approach for Modeling Neural Responses to Joint Perturbations Using the NARMAX Method and a Hierarchical Neural Network

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    The human nervous system is an ensemble of connected neuronal networks. Modeling and system identification of the human nervous system helps us understand how the brain processes sensory input and controls responses at the systems level. This study aims to propose an advanced approach based on a hierarchical neural network and non-linear system identification method to model neural activity in the nervous system in response to an external somatosensory input. The proposed approach incorporates basic concepts of Non-linear AutoRegressive Moving Average Model with eXogenous input (NARMAX) and neural network to acknowledge non-linear closed-loop neural interactions. Different from the commonly used polynomial NARMAX method, the proposed approach replaced the polynomial non-linear terms with a hierarchical neural network. The hierarchical neural network is built based on known neuroanatomical connections and corresponding transmission delays in neural pathways. The proposed method is applied to an experimental dataset, where cortical activities from ten young able-bodied individuals are extracted from electroencephalographic signals while applying mechanical perturbations to their wrist joint. The results yielded by the proposed method were compared with those obtained by the polynomial NARMAX and Volterra methods, evaluated by the variance accounted for (VAF). Both the proposed and polynomial NARMAX methods yielded much better modeling results than the Volterra model. Furthermore, the proposed method modeled cortical responded with a mean VAF of 69.35% for a three-step ahead prediction, which is significantly better than the VAF from a polynomial NARMAX model (mean VAF 47.09%). This study provides a novel approach for precise modeling of cortical responses to sensory input. The results indicate that the incorporation of knowledge of neuroanatomical connections in building a realistic model greatly improves the performance of system identification of the human nervous system

    Ultra-broadband near-field Josephson microwave microscopy

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    Advanced microwave technologies constitute the foundation of a wide range of modern sciences, including quantum computing, microwave photonics, spintronics, etc. To facilitate the design of chip-based microwave devices, there is an increasing demand for state-of-the-art microscopic techniques capable of characterizing the near-field microwave distribution and performance. In this work, we integrate Josephson junctions onto a nano-sized quartz tip, forming a highly sensitive microwave mixer on-tip. This allows us to conduct spectroscopic imaging of near-field microwave distributions with high spatial resolution. Leveraging its microwave-sensitive characteristics, our Josephson microscope achieves a broad detecting bandwidth of up to 200 GHz with remarkable frequency and intensity sensitivities. Our work emphasizes the benefits of utilizing the Josephson microscope as a real-time, non-destructive technique to advance integrated microwave electronics

    The gut metabolite indole-3-propionic acid activates ERK1 to restore social function and hippocampal inhibitory synaptic transmission in a 16p11.2 microdeletion mouse model

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    Background: Microdeletion of the human chromosomal region 16p11.2 (16p11.2+/−) is a prevalent genetic factor associated with autism spectrum disorder (ASD) and other neurodevelopmental disorders. However its pathogenic mechanism remains unclear, and efective treatments for 16p11.2+/− syndrome are lacking. Emerging evidence suggests that the gut microbiota and its metabolites are inextricably linked to host behavior through the gut-brain axis and are therefore implicated in ASD development. Despite this, the functional roles of microbial metabo‑ lites in the context of 16p11.2+/− are yet to be elucidated. This study aims to investigate the therapeutic potential of indole-3-propionic acid (IPA), a gut microbiota metabolite, in addressing behavioral and neural defcits associated with 16p11.2+/−, as well as the underlying molecular mechanisms. // Results: Mice with the 16p11.2+/− showed dysbiosis of the gut microbiota and a signifcant decrease in IPA levels in feces and blood circulation. Further, these mice exhibited signifcant social and cognitive memory impairments, along with hyperactivation of hippocampal dentate gyrus neurons and reduced inhibitory synaptic transmission in this region. However, oral administration of IPA efectively mitigated the histological and electrophysiological alterations, thereby ameliorating the social and cognitive defcits of the mice. Remarkably, IPA treatment signifcantly increased the phosphorylation level of ERK1, a protein encoded by the Mapk3 gene in the 16p11.2 region, with‑ out afecting the transcription and translation of the Mapk3 gene. // Conclusions: Our study reveals that 16p11.2+/− leads to a decline in gut metabolite IPA levels; however, IPA supple‑ mentation notably reverses the behavioral and neural phenotypes of 16p11.2+/− mice. These fndings provide new insights into the critical role of gut microbial metabolites in ASD pathogenesis and present a promising treatment strategy for social and cognitive memory defcit disorders, such as 16p11.2 microdeletion syndrome

    Dynamic Information Flow Based on EEG and Diffusion MRI in Stroke: A Proof-of-Principle Study

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    In hemiparetic stroke, functional recovery of paretic limb may occur with the reorganization of neural networks in the brain. Neuroimaging techniques, such as magnetic resonance imaging (MRI), have a high spatial resolution which can be used to reveal anatomical changes in the brain following a stroke. However, low temporal resolution of MRI provides less insight of dynamic changes of brain activity. In contrast, electro-neurophysiological techniques, such as electroencephalography (EEG), have an excellent temporal resolution to measure such transient events, however are hindered by its low spatial resolution. This proof-of-principle study assessed a novel multimodal brain imaging technique namely Variational Bayesian Multimodal Encephalography (VBMEG), which aims to improve the spatial resolution of EEG for tracking the information flow inside the brain and its changes following a stroke. The limitations of EEG are complemented by constraints derived from anatomical MRI and diffusion weighted imaging (DWI). EEG data were acquired from individuals suffering from a stroke as well as able-bodied participants while electrical stimuli were delivered sequentially at their index finger in the left and right hand, respectively. The locations of active sources related to this stimulus were precisely identified, resulting in high Variance Accounted For (VAF above 80%). An accurate estimation of dynamic information flow between sources was achieved in this study, showing a high VAF (above 90%) in the cross-validation test. The estimated dynamic information flow was compared between chronic hemiparetic stroke and able-bodied individuals. The results demonstrate the feasibility of VBMEG method in revealing the changes of information flow in the brain after stroke. This study verified the VBMEG method as an advanced computational approach to track the dynamic information flow in the brain following a stroke. This may lead to the development of a quantitative tool for monitoring functional changes of the cortical neural networks after a unilateral brain injury and therefore facilitate the research into, and the practice of stroke rehabilitation

    Multiband orthogonal frequency division multiplexing modulation and demodulation for wireless universal serial bus

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    Wireless Universal Serial Bus (W-USB) has been proposed to offer a mechanism in short range and high speed Wireless Personal Area Networks (WPAN). Wireless USB has now been standardized by utilizing the common WiMedia Ultra Wideband (UWB) radio platform to use the services of Multiband Orthogonal Frequency Division Multiplexing (MB-OFDM) as the transport mechanism. With regards to the high data rate mode using DCM modulation scheme, different DCM demapping methods resulting in different system performance are presented, which include soft bit demapping, Maximum Likelihood (ML) soft bit demapping and I Log Likelihood Ratio (LLR) demapping. The proposed Channel State Information (CSl) aided scheme coupled with the band hopping information is used as the further technique to improve the DCM demapping performance.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Multiband OFDM modulation and demodulation for ultra wideband communications

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    This chapter considers the Multiband Orthogonal Frequency Division Multiplexing (MB- OFDM) modulation and demodulation with the intention to optimize the Ultra-Wideband (UWB) system performance. OFDM is a type of multicarrier modulation and becomes the most important aspect for the MB-OFDM system performance. It is also a low cost digital signal component efficiently using Fast Fourier Transform (FFT) algorithm to implement the multicarrier orthogonality. Within the MB-OFDM approach, the OFDM modulation is employed in each 528 MHz wide band to transmit the data across the different bands while also using the frequency hopping technique across different bands. Each parallel bit stream can be mapped onto one of the OFDM subcarriers. Quadrature Phase Shift Keying (QPSK) and Dual Carrier Modulation (DCM) are currently used as the modulation schemes for MB-OFDM in the ECMA-368 defined UWB radio platform. A dual QPSK soft-demapper is suitable for ECMA-368 that exploits the inherent Time-Domain Spreading (TDS) and guard symbol subcarrier diversity to improve the receiver performance, yet merges decoding operations together to minimize hardware and power requirements. There are several methods to demap the DCM, which are soft bit demapping, Maximum Likelihood (ML) soft bit demapping, and Log Likelihood Ratio (LLR) demapping. The Channel State Information (CSI) aided scheme coupled with the band hopping information is used as a further technique to improve the DCM demapping performance. ECMA-368 offers up to 480 Mb/s instantaneous bit rate to the Medium Access Control (MAC) layer, but depending on radio channel conditions dropped packets unfortunately result in a lower throughput. An alternative high data rate modulation scheme termed Dual Circular 32-QAM that fits within the configuration of the current standard increasing system throughput thus maintaining the high rate throughput even with a moderate level of dropped packets
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