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Extensive deep neural networks for transferring small scale learning to large scale systems
No full textWe present a physically-motivated topology of a deep neural network that can efficiently infer extensive parameters (such as energy, entropy, or number of particles) of arbitrarily large systems, doing so with O(N) scaling. We use a form of domain decomposition for training and inference, where each sub-domain (tile) is comprised of a non-overlapping focus region surrounded by an overlapping context region. The size of these regions is motivated by the physical interaction length scales of the problem. We demonstrate the application of EDNNs to three physical systems: the Ising model and two hexagonal/graphene-like datasets. In the latter, an EDNN was able to make total energy predictions of a 60 atoms system, with comparable accuracy to density functional theory (DFT), in 57 milliseconds. Additionally EDNNs are well suited for massively parallel evaluation, as no communication is necessary during neural network evaluation. We demonstrate that EDNNs can be used to make an energy prediction of a two-dimensional 35.2 million atom system, over 1.0 \u3bcm\ub2 of material, at an accuracy comparable to DFT, in under 25 minutes. Such a system exists on a length scale visible with optical microscopy and larger than some living organisms.Peer reviewed: YesNRC publication: Ye
Electrophoretic deposition of LiFePO4 for Li-ion batteries
No full textAn electrophoretic deposition (EPD) method has been developed for the deposition of LiFePO4-carbon black films for application in Li-ion batteries. The approach is based on the use of poly[1-[4-(3-carboxy-4-hydroxyphenylazo)benzenesulfonamido]-1,2-ethanediyl, sodium salt] (PAZO-Na) and carboxymethyl cellulose sodium salt (CMC-Na), as dispersing, charging and film forming agents. The individual monomers of PAZO-Na and CMC-Na created multiple bonds with metal atoms on the particle surface and allowed for efficient electrosteric dispersion and charging of relatively large commercial LiFePO4 particles. The microstructure, deposition mechanism and electrochemical performance were investigated. The LiFePO4 electrode, prepared by the EPD method, exhibited a capacity of 146.7\u202fmA\u202fh\u202fg 121 at C/10 and enhanced cycling stability.Peer reviewed: YesNRC publication: Ye
Live long and praise TOR: a role for TOR signaling in every stage of plant life
No full textFrom scientific advances in medical research to the plethora of anti-aging products available, our obsession with slowing the aging process and increasing lifespan is indisputable. A large research effort has been levied towards this perpetual search for the fountain of youth, yet the molecular mechanisms governing an organism\u2019s lifespan and the causes of aging are only beginning to emerge in animals and remain largely unanswered in plants. One central pathway in eukaryotes controlling cell growth, development and metabolism, the target of rapamycin (TOR), plays an evolutionarily conserved role in aging and the determination of lifespan. The modulation of TOR pathway components in a wide range of species, including the model plant Arabidopsisthaliana have effects on lifespan. However, the mechanisms enabling some of the longest living species to endure, including trees that can live for millennia, have not been defined. Here, we introduce key TOR research from plant systems and discuss its implications in the plant life cycle and the broader field of lifespan research. TOR pathway functions in plant life cycle progression and lifespan determination are discussed, noting key differences from yeast and animal systems and the importance of \u2018omics\u2019 research for the continued progression of TOR signaling research.yesPeer reviewed: YesNRC publication: Ye
Model-based and data-driven anomaly detection for heating and cooling demands in office buildings
No full textA considerable portion of total energy loss within the built environment originates from operational errors during the actual lifespan of a building. With the rise of fully automated commercial buildings, a large amount of sensory data is becoming available that can be leveraged to detect and predict such errors. However, processing these data on-site requires significant knowledge and effort by building operators. In this work, a combination of model-based and data-driven approaches are employed to facilitate the analysis of historical energy demand data. Using change-point models and symbolic quantisation techniques, a large dataset of heating and cooling demand profiles collected from several office buildings are transformed into a format that is easily interpreted by the building operator and is suitable for actionable anomaly detection. Further quantification of anomalies and calculation of potential savings are drawn from the results.Peer reviewed: YesNRC publication: Ye
A comparison of the immune responses induced by antigens in three different archaeosome-based vaccine formulations
No full textArchaeosomes are liposomes composed of natural or synthetic archaeal lipids that can be used as adjuvants to induce strong long-lasting humoral and cell-mediated immune responses against entrapped antigen. However, the entrapment efficiency of antigen within archaeosomes constituted using standard liposome forming methodology is often only 5\u201340%. In this study, we evaluated different formulation methods using a simple semi-synthetic archaeal lipid (SLA, sulfated lactosyl archaeol) and two different antigens, ovalbumin (OVA) and hepatitis B surface antigen (HBsAg). Antigen was entrapped within archaeosomes using the conventional thin film hydration-rehydration method with or without removal of non-entrapped antigen, or pre-formed empty archaeosomes were simply admixed with an antigen solution. Physicochemical characteristics were determined (size distribution, zeta potential, vesicle morphology and lamellarity), as well as location of antigen relative to bilayer using cryogenic transmission electron microscopy (TEM). We demonstrate that antigen (OVA or HBsAg) formulated with SLA lipid adjuvants using all the different methodologies resulted in a strong antigen-specific immune response. Nevertheless, the advantage of using a drug substance process that comprises of simply admixing antigen with pre-formed empty archaeosomes, represents a simple, efficient and antigenic dose-sparing formulation for adjuvanting and delivering vaccine antigens.Peer reviewed: YesNRC publication: Ye
Reinforcement of ice covers for transportation: material investigation and preliminary laboratory testing
No full textPeer reviewed: NoNRC publication: Ye
Modeling and mapping dynamic vulnerability to better assess WUI evacuation performance
No full textWildland\u2010urban interface (WUI) fire incidents are likely to become more severe and will affect more and more people. Given their scale and complexity, WUI incidents require a multidomain approach to assess their impact and the effectiveness of any mitigation efforts. The authors recently produced a specification for a simulation framework that quantifies evacuation performance during WUI incidents including inputs from three core domains: fire development, pedestrian performance and vehicular traffic [26]. This framework could produce new insights by simulating evolving conditions of WUI incidents based on developments and interactions between the core components. Thus, it aims to overcome known limitations of previous approaches (eg, static assessment, single domain approaches, or lack of projection), as well as to provide explanatory insights into the outcomes produced by the simulation. The proposed framework would also advance geo\u2010spatial mapping of WUI incidents. The concept of dynamic vulnerability, urn:x-wiley:03080501:media:fam2708:fam2708-math-0001, is at the core of the framework and is enabled by the integrated simulation framework and the emergent conditions predicted. This allows users to construct richer incident narratives from the perspective of specific locations or subpopulations, and also makes fewer simplifying assumptions regarding interactions between the three core domains.Peer reviewed: YesNRC publication: Ye
Compact modeling of thin film transistors for flexible hybrid IoT design
No full textFlexible Electronics (FE) is emerging for low-cost, light-weight wearable electronics, artificial skins and IoT nodes, benefiting from its low-cost fabrication and mechanical flexibility. Combining FE with thinned silicon chips, known as flexible hybrid electronics (FHE), can take advantages of both low-cost printed electronics and high performance silicon chips, which brings together flexible form factors and IoT innovations. Thin film transistors (TFTs), as a critical component for FHE applications, have achieved tremendous improvements in charge carrier mobility, device stability and scalability; however, an accurate compact model for TFTs which can capture fundamental behaviors of TFTs and be broadly applicable to multiple flexible technologies is still missing for circuit and system design. Such a model is crucial for designing flexible hybrid IoT (Flex-IoT) in order to enable design explorations and technology evaluations. In this paper, we present a SPICE-compatible unified compact model covering DC, AC and technology scaling of TFTs for Flex-IoT designs. We validated the presented model for three different types of TFT technologies and performed circuits-level investigations based on fabricated Pseudo-CMOS circuits. We demonstrate that the presented TFT model can provide accurate and trustworthy predictions for circuit evaluation and Flex-IoT system design.Peer reviewed: YesNRC publication: Ye