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Integrative sensor networks, informatics, and modeling for precision and preventative medicine

Published in:
IEEE J. Biomed. Health, Vol. 24, No. 7, July 2020, pp. 1858-1859.

Summary

The topics of integrative sensor networks, informatics and modeling bring together the tightly coupled and rapidly developing fields of biomedical and health informatics and body sensor networks. Biomedical and health informatics encompasses methods to extract and communicate information from data in order to impact health, healthcare, life sciences and biomedicine. Body sensor networks provide one means to measure the needed data, through continuous monitoring in both clinical and free-living environments. Developments in these areas were highlighted at two co-located conferences: the 2019 IEEE-EMBS International Conferences on Biomedical and Health Informatics (BHI'19) and Wearable and Implantable Body Sensor Networks (BSN'19). BHI and BSN are long-standing IEEE EMBS conferences that provide a forum for researchers and leaders from academia, government and industry to share technical advances and new initiatives in these important areas. Through an open call for this special issue, eleven papers have been included for publication. The majority were presented in an initial form at the 2018 or 2019 BHI and BSN conferences. Nine of the papers were selected through a rigorous peer review. In addition, two keynote speakers from BHI'19 and BSN'19 have provided short position papers.
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Summary

The topics of integrative sensor networks, informatics and modeling bring together the tightly coupled and rapidly developing fields of biomedical and health informatics and body sensor networks. Biomedical and health informatics encompasses methods to extract and communicate information from data in order to impact health, healthcare, life sciences and biomedicine...

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Adjoint analysis of guidance systems for time-series inputs using Fourier analysis

Author:
Published in:
J. Guid., Control, Dyn., Vol. 43, No. 7, July 2020.

Summary

The adjoint technique is a proven technique for analysis of linear time-varying systems and is widely used in the missile design community. It is a very efficient technique that can solve for both deterministic and stochastic disturbances and can develop a miss distance budget in a single computer solution of the differential equations without use of time-consuming Monte Carlo simulations. The adjoint technique is very valuable in both preliminary and more advanced missile design stages and is based upon the mathematical adjoint of the system dynamics matrix of the homing loop. Zarchan [1,2] describes extensive use of the technique for a variety of disturbances for homing missiles, and this author has developed its use for command guided missiles [3]. For adjoint analysis, the usual method of modeling maneuver disturbances to a missile guidance system starts by modeling the maneuver in the forward-time system as a delta function input into a transfer function with the same second-order statistics as the maneuver, and its output is input into the guidance system; then the system is converted into its adjoint system [1]. Bucco and Weiss [4] show that a set of nonstandard time-varying inputs cannot be treated in the normal fashion [2,5,6], and they present a new technique that enables these nonstandard inputs to be analyzed using adjoint analysis. This paper was inspired by and extends the results of the paper by Bucco and Weiss [4]. This paper shows that the use of the complex digital Fourier amplitude spectrums of both the maneuver and the adjoint impulse response at the maneuver point allows adjoint analysis to address another type of nonstandard input, namely, an arbitrary time-series inputs such as specific target maneuvers that are not representable by an impulse input into a transfer function; heretofore, these time-series inputs have not been treatable with adjoint analysis. Additionally, if there are several sets of arbitrary time series of target maneuvers, each with an associated probability of occurrence, the root-mean-square (rms) value of the set of probabilistic maneuvers can be calculated, another significant new capability introduced in this paper.
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Summary

The adjoint technique is a proven technique for analysis of linear time-varying systems and is widely used in the missile design community. It is a very efficient technique that can solve for both deterministic and stochastic disturbances and can develop a miss distance budget in a single computer solution of...

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Deep implicit coordination graphs for multi-agent reinforcement learning [e-print]

Summary

Multi-agent reinforcement learning (MARL) requires coordination to efficiently solve certain tasks. Fully centralized control is often infeasible in such domains due to the size of joint action spaces. Coordination graph based formalization allows reasoning about the joint action based on the structure of interactions. However, they often require domain expertise in their design. This paper introduces the deep implicit coordination graph (DICG) architecture for such scenarios. DICG consists of a module for inferring the dynamic coordination graph structure which is then used by a graph neural network based module to learn to implicitly reason about the joint actions or values. DICG allows learning the tradeoff between full centralization and decentralization via standard actor-critic methods to significantly improve coordination for domains with large number of agents. We apply DICG to both centralized-training-centralized-execution and centralized-training-decentralized-execution regimes. We demonstrate that DICG solves the relative overgeneralization pathology in predatory-prey tasks as well as outperforms various MARL baselines on the challenging StarCraft II Multi-agent Challenge (SMAC) and traffic junction environments.
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Summary

Multi-agent reinforcement learning (MARL) requires coordination to efficiently solve certain tasks. Fully centralized control is often infeasible in such domains due to the size of joint action spaces. Coordination graph based formalization allows reasoning about the joint action based on the structure of interactions. However, they often require domain expertise...

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Control systems need software security too: cyber-physical systems and safety-critical application domains must adopt widespread effective software defenses

Author:
Published in:
SIGNAL Mag., 1 June 2020.

Summary

Low-level embedded control systems are increasingly being targeted by adversaries, and there is a strong need for stronger software defenses for such systems. The cyber-physical nature of such systems impose real-time performance constraints not seen in enterprise computing systems, and such constraints fundamentally alter how software defenses should be designed and applied. MIT Lincoln Laboratory scientists demonstrated that current randomization-based defenses, which have low average-case overhead, can incur significant worst-case overhead that may be untenable in real-time applications, while some low-overhead enforcement-based defenses have low worst-case performance overheads making them more amenable to real-time applications. Such defenses should be incorporated into a comprehensive resilient architecture with a strategy for failover and timely recovery in the case of a cyber threat.
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Summary

Low-level embedded control systems are increasingly being targeted by adversaries, and there is a strong need for stronger software defenses for such systems. The cyber-physical nature of such systems impose real-time performance constraints not seen in enterprise computing systems, and such constraints fundamentally alter how software defenses should be designed...

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COVID-19: famotidine, histamine, mast cells, and mechanisms [eprint]

Summary

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. Currently, there are no pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain obscure. We explore several plausible avenues of activity including antiviral and host-mediated actions. We propose that the principal famotidine mechanism of action for COVID-19 involves on-target histamine receptor H2 activity, and that development of clinical COVID-19 involves dysfunctional mast cell activation and histamine release.
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Summary

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. Currently, there are no pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain...

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75,000,000,000 streaming inserts/second using hierarchical hypersparse GraphBLAS matrices

Summary

The SuiteSparse GraphBLAS C-library implements high performance hypersparse matrices with bindings to a variety of languages (Python, Julia, and Matlab/Octave). GraphBLAS provides a lightweight in-memory database implementation of hypersparse matrices that are ideal for analyzing many types of network data, while providing rigorous mathematical guarantees, such as linearity. Streaming updates of hypersparse matrices put enormous pressure on the memory hierarchy. This work benchmarks an implementation of hierarchical hypersparse matrices that reduces memory pressure and dramatically increases the update rate into a hypersparse matrices. The parameters of hierarchical hypersparse matrices rely on controlling the number of entries in each level in the hierarchy before an update is cascaded. The parameters are easily tunable to achieve optimal performance for a variety of applications. Hierarchical hypersparse matrices achieve over 1,000,000 updates per second in a single instance. Scaling to 31,000 instances of hierarchical hypersparse matrices arrays on 1,100 server nodes on the MIT SuperCloud achieved a sustained update rate of 75,000,000,000 updates per second. This capability allows the MIT SuperCloud to analyze extremely large streaming network data sets.
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Summary

The SuiteSparse GraphBLAS C-library implements high performance hypersparse matrices with bindings to a variety of languages (Python, Julia, and Matlab/Octave). GraphBLAS provides a lightweight in-memory database implementation of hypersparse matrices that are ideal for analyzing many types of network data, while providing rigorous mathematical guarantees, such as linearity. Streaming updates...

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The 2017 Buffalo Area Icing and Radar Study (BAIRS II)

Published in:
MIT Lincoln Laboratory Report ATC-447

Summary

The second Buffalo Area Icing and Radar Study (BAIRS II) was conducted during the winter of 2017. The BAIRS II partnership between Massachusetts Institute of Technology (MIT) Lincoln Laboratory (LL), the National Research Council of Canada (NRC), and Environment and Climate Change Canada (ECCC) was sponsored by the Federal Aviation Administration (FAA). It is a follow-up to the similarly sponsored partnership of the original BAIRS conducted in the winter of 2013. The original BAIRS provided in situ verification and validation of icing and hydrometeors, respectively, within the radar domain in support of a hydrometeor-classification-based automated icing hazard algorithm. The BAIRS II motivation was to: --Collect additional in situ verification and validation data, --Probe further dual polarimetric radar features associated with icing hazard, --Provide foundations for additions to the icing hazard algorithm beyond hydrometeor classifications, and --Further characterize observable microphysical conditions in terms of S-band dual polarimetric radar data. With BAIRS II, the dual polarimetric capability is provided by multiple Next Generation Weather Radar (NEXRAD) S-band radars in New York State, and the verification of the icing hazard with microphysical and hydrometeor characterizations is provided by NRC's Convair-580 instrumented research plane during five icing missions covering about 21 mission hours. The ability to reliably interpret the NEXRAD dual polarization radar-sensed thermodynamic phase of the hydrometeors (solid, liquid, mix) in the context of cloud microphysics and precipitation physics makes it possible to assess the icing hazard potential to aviation. The challenges faced are the undetectable nature of supercooled cloud droplets (for Sband) and the isotropic nature of Supercooled Large Drops (SLD). The BAIRS II mission strategy pursued was to study and probe radar-identifiable, strongly anisotropic crystal targets (dendrites and needles) with which supercooled water (and water saturated conditions) are physically linked as a means for dual polarimetric detection of icing hazard. BAIRS II employed superior optical array probes along with state and microphysical instrumentation; and, using again NEXRAD-feature-guided flight paths, was able to make advances from the original BAIRS helpful to the icing algorithm development. The key findings that are given thorough treatment in this report are: --Identification of the radar-detectable "crystal sandwich" structure from two anisotropic crystal types stratified by in situ air temperature in association with varying levels of supercooled water --with layer thicknesses observed to 2 km, --over hundred-kilometer scales matched with the mesoscale surveillance of the NEXRAD radars, --Development and application of a multi-sensor cloud phase algorithm to distinguish between liquid phase, mixed phase, and glaciated (no icing) conditions for purposes of a "truth" database and improved analysis in BAIRS II, --Development of concatenated hydrometeor size distributions to examine the in situ growth of both liquid and solid hydrometeors over a broad size spectrum; used, in part, to demonstrate differences between maritime and continental conditions, and --The Icing Hazard Levels (IHL) algorithm’s verification in icing conditions is consistent with previous work and, new, is documented to perform well when indicating "glaciated" (no icing) conditions.
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Summary

The second Buffalo Area Icing and Radar Study (BAIRS II) was conducted during the winter of 2017. The BAIRS II partnership between Massachusetts Institute of Technology (MIT) Lincoln Laboratory (LL), the National Research Council of Canada (NRC), and Environment and Climate Change Canada (ECCC) was sponsored by the Federal Aviation...

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Kawasaki disease, multisystem inflammatory syndrome in children: antibody-induced mast cell activation hypothesis

Published in:
J Pediatrics & Pediatr Med. 2020; 4(2): 1-7

Summary

Multisystem Inflammatory Syndrome in Children (MIS-C) is appearing in infants, children, and young adults in association with COVID-19 (coronavirus disease 2019) infections of SARS-CoV-2. Kawasaki Disease (KD) is one of the most common vasculitides of childhood. KD presents with similar symptoms to MIS-C especially in severe forms such as Kawasaki Disease Shock Syndrome (KDSS). The observed symptoms for MIS-C and KD are consistent with Mast Cell Activation Syndrome (MCAS) characterized by inflammatory molecules released from activated mast cells. Based on the associations of KD with multiple viral and bacterial pathogens, we put forward the hypothesis that KD and MIS-C result from antibody activation of mast cells by Fc receptor-bound pathogen antibodies causing a hyperinflammatory response upon second pathogen exposure. Within this hypothesis, MIS-C may be atypical KD or a KD-like disease associated with SARS-CoV-2. We extend the mast cell hypothesis that increased histamine levels are inducing contraction of effector cells with impeded blood flow through cardiac capillaries. In some patients, pressure from impeded blood flow, within cardiac capillaries, may result in increased coronary artery blood pressure leading to aneurysms, a well-known complication in KD.
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Summary

Multisystem Inflammatory Syndrome in Children (MIS-C) is appearing in infants, children, and young adults in association with COVID-19 (coronavirus disease 2019) infections of SARS-CoV-2. Kawasaki Disease (KD) is one of the most common vasculitides of childhood. KD presents with similar symptoms to MIS-C especially in severe forms such as Kawasaki...

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Bayesian estimation of PLDA with noisy training labels, with applications to speaker verification

Published in:
2020 IEEE Intl. Conf. on Acoustics, Speech and Signal Processing, ICASSP, 4-8 May 2020.

Summary

This paper proposes a method for Bayesian estimation of probabilistic linear discriminant analysis (PLDA) when training labels are noisy. Label errors can be expected during e.g. large or distributed data collections, or for crowd-sourced data labeling. By interpreting true labels as latent random variables, the observed labels are modeled as outputs of a discrete memoryless channel, and the maximum a posteriori (MAP) estimate of the PLDA model is derived via Variational Bayes. The proposed framework can be used for PLDA estimation, PLDA domain adaptation, or to infer the reliability of a PLDA training list. Although presented as a general method, the paper discusses specific applications for speaker verification. When applied to the Speakers in the Wild (SITW) Task, the proposed method achieves graceful performance degradation when label errors are introduced into the training or domain adaptation lists. When applied to the NIST 2018 Speaker Recognition Evaluation (SRE18) Task, which includes adaptation data with noisy speaker labels, the proposed technique provides performance improvements relative to unsupervised domain adaptation.
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Summary

This paper proposes a method for Bayesian estimation of probabilistic linear discriminant analysis (PLDA) when training labels are noisy. Label errors can be expected during e.g. large or distributed data collections, or for crowd-sourced data labeling. By interpreting true labels as latent random variables, the observed labels are modeled as...

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One giant leap for computer security

Summary

Today's computer systems trace their roots to an era of trusted users and highly constrained hardware; thus, their designs fundamentally emphasize performance and discount security. This article presents a vision for how small steps using existing technologies can be combined into one giant leap for computer security.
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Summary

Today's computer systems trace their roots to an era of trusted users and highly constrained hardware; thus, their designs fundamentally emphasize performance and discount security. This article presents a vision for how small steps using existing technologies can be combined into one giant leap for computer security.

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