Claudio L. Flores Martinez Kybernesia BiomimOmics

BiomimOmics of PALS Relevant Organisms

Project Overview

Next-generation sequencing tools for functional and comparative genomics allow the relatively cheap, fast and precise characterization of the gene and protein complement of various model and non-model organisms. This includes a multitude of marine organisms relevant for PALS, from bioluminescent bacteria and unicellular eukaryotes, the octopus equipped with advanced camouflage to electro-perceptive fish and mammals capable of complex echolocation. Generated genomic data, assembled from automated bioinformatic pipelines, can then be used to compare genomes of species to extract information about the exact physiological underpinning of a specific PALS-relevant trait. We developed a novel organizational scheme, the BiomimOmic Traceability Matrix (BTM), which is modeled after the systems engineering tool from space mission design known as Science Traceability Matrix (STM). Our aim is the development of a comprehensive database of PALS organisms and genomes, according to the already established BTM workflow, that map on desired target traits, specifically bioluminescence and any other organismal features relevant to PALS.

TA1: Physiology is the foundation for characterizing any relevant biological signal. Comparative genomics provides the necessary background and starting point for further research into systems design requirements of PALS relevant biosensors. TA2: Understanding the biological signal from a genomic perspective will facilitate the design and implementation of adequate sensor platforms, including unusual solutions such as soft robotics. BTMs cover the complete bio-systems engineering workflow, from identifying relevant traits to genomic analysis and biosensor R&D efforts. In-depth trade-off analysis is part of this process as well.

Teaming Overview and Objectives

PI: Claudio L. Flores Martinez, M. Sc. Molecular Biosciences, PhD Student at University of Hamburg. Relevant experience: space mission design (instrument selection of biosensors via STM) for EnEx (Enceladus Explorer) at DLR and Germany Army University. Expertise in astrobiology, comparative genomics, reverse (bio-systems) engineering, neuroscience and biomimetics. He is founder and CEO of “Kybernesia – Biomimetic Systems Design” specializing in rapid breakthrough innovation in bio-inspired technology with a novel genomics-driven innovation methodology. Publications: Flores Martinez C.L. (2017) Introducing Biomimomics: Combining Biomimetics and Comparative Genomics for Constraining Organismal and Technological Complexity. In: Mangan M., Cutkosky M. et al., Biomimetic and Biohybrid Systems. Living Machines 2017. Lecture Notes in Computer Science, vol 10384. Springer, Cham. Desired collaborators: Computational and marine biologists for PALS genome database construction, experts in advanced UUV design and soft / bio-inspired robotics to connect results of genomic analysis with sensor platform design and integration.

Impact

We aim to introduce a novel genome database-driven workflow that facilitates understanding of relevant biological signals within the systems-level (soft) robotic infrastructure needed for PALS. This enables new capabilities based on the physiology of PALS relevant organisms. Potential applications: novel bioluminescence detection and response in a swarm robotic context, stationary mussel-like sensor platforms and advanced bio-inspired camouflage for man-made detector systems. Our goal is to establish an integrated R&D workflow connecting basic research with rapid prototyping and field testing in a three year period.

Contact Information

Claudio L. Flores Martinez, Kybernesia, Email: claudio@kybernesia.org, Mobile: +49 17682423579

Kevin Devaney SRC, Inc. Team SRC

Project Overview

• Utilize snapping shrimp noise as transmitters of opportunity to provide bistatic sonar detection, tracking and target discrimination.

• Also investigate other noise sources (e.g. fish) for situational awareness and anomaly detection.

• Machine learning techniques can be used to improve detection and classification over conventional methods.

Teaming Overview and Objectives

• SRC has a long history as a leader in bistatic radar technology, including using transmitters of opportunity, and also in mobile platforms.

• SRC also has experience applying machine learning to target detection and classification problems.

• We are looking for collaborators with passive acoustic sensing experience, including experience with field testing, permits, etc.

Impact

• Given the high signal levels provided by snapping shrimp, this approach should provide good standoff range performance.

• Machine learning technology may enable breakthrough performance in classification accuracy, using the multiple sources of information in our approach.

Contact Information

Kevin Devaney

kdevaney@srcinc.com

(315) 452-8115 (O)

(315) 491-0164 (C)

DennisL.Dollens(UScitizen)•UniversitatInternacionaldeCatalunya,Barcelona•MetabolicArchitecturesProjectOverviewResearchisdevelopinginfrastructure,substrates,andarchitecturesusingbiologicaldataandAI/biodigitallife-supportsystemsforhousinglivingorganisms.InadditiontobiologyandcomputationthistypeofprojectisalsoanadvanceddesignrequiringtheinterfacingoflivingorganismswithAIandcommunicationsnetworks.Muchofourresearchisappropriatetounderwaterformsandsystemsconcernedwithsurveillance,sensing,signaling,andmonitoringofmolecularsubstancesbylivingorganisms.WorkingwithteamsofbiologistsandprogrammersweofferspecialskillsetsforsituatingandmaintainingformsthatthemselveslookandbehaveasorganismsandthusfurthergoalsofTA1andTA2bywithdesign-by-researchexperiencethatallows“buildings,”casings,orrelaystoblendintoterrestrialorunderwaterenvironments.Thisisanestablisheduniversityprogramwithongoingtraininginareasofbiodigitalandbiomimeticdesignandcomputationalfabrication.TeamingOverviewTheteamofprimaryresearchesisanaccreditedofficialresearchgroup.Itsmembersareinvolvedinvariousareasofadvancebiological-to-analogdesign.Ph.D.andpost-graduateresearchersaregivenassociatemembership,determinedbyskillsandtherequirementsoftheproject.TeamleaderforthisprojectisDr.DennisDollenswhosemostrecentbookisthetheoreticaltext:MetabolicArchitectures:Turing,Sullivan,Autopoiesis,&AI.https://www.amazon.com/Metabolic-Architectures-Turing-Sullivan-Autopoiesis/dp/1549954474/ref=sr_1_1?s=books&ie=UTF8&qid=1519624328&sr=1-1&keywords=dollens+metabolic+architectures&dpID=51GpNgG0pIL&preST=_SY344_BO1,204,203,200_QL70_&dpSrc=srchThemasterprograminBiodigitalArchitecturesandtheGeneticArchitecturesPh.D.programhasexisted20years.Theyarethecoreinstitutionalorganizationaroundwhichresearchtakesplace.Wearelookingtojoinwithteamsinterestedinadvancedreasoning,logics,andtheorytoenvisionandprototypephysicalinfrastructures,substratesurfaces,forms,linkagesystems,environments,andmarinearchitectureshousingandmaintaininglivingorganismsthatarethemselvesnetworkingdatainwater-borneorair-borneenvironments,thatisembeddedindifficult,wild,orwetnatures.ImpactTheinterfacebetweenorganismsanddigitalsystemsistheunderpinningsofbiologicalnanocommunicationsandwearticulatetypologiesofbiologicalintelligencessuitabletonewconceptionsofsensingincitiesandinwildnature.Theteamhasalonghistoryofapplyingdataanddevelopingformsandinfrastructuresfrombiologicalandbiocomputationaldata,ithaslongexperiencewithsimulationssituatingobjects,forms,materials,andarchitecturesinnature.ContactInformationexodesic@mac.com(505)603-5019

Magdi Essawy UTAS and UOM Mobile Sensor Networks

Project Overview

• Develop undersea mobile sensor network for underwater target detection and tracking. The sensor network will perform passive listening to the undersea environment, mine sensory data, and monitor bio-organisms behavior. The sensors will communicate with each other and with a central floating node (to command & Control) through acoustic and RF links, respectively.

• Sensors will be autonomous and mobile to optimize their location with respect to monitored targets, areas, and organisms. The sensors will be used to collect data and develop algorithms.

• The program will be planned in three phases matching the Technology Readiness Levels (TRL). Phase I will develop the technology to TRL2, phase II to TRL IV and Phase III to TRL6.

Teaming Overview and Objectives

• The UTAS – SIS Technology team have expertise in various sensor technology development and production for applications in the aerospace and defense industries.

• The PI, Magdi Essawy, has a Ph.D. in artificial intelligence and signal processing, more than forty publications and technical presentations, and more than ten patents in sensor technologies. Dr. Marchtto of UOM has strong background in underwater acoustics, more than twenty publications and technical presentations, and six patents. Dr. Sorensen of UOM in addition to his impressive teaching and research accomplishments in Marine Biology, he has managed more than eighty funded research grants and authored more than 150 publications. Dr. Holger Klinck, the Director of Bioacoustics Research Program (BRP) at Cornell, in addition to his impressive published research record, his graduate work focused on the development of the Perennial Acoustic Observatory in the Antarctic Ocean and the study of the leopard seal.

• UTAS-SIS has advanced engineering and sensor technology development and production facilities in addition to 10,000 sq. ft. class-1000 MEMs facility and environmental testing and wind, icing, and supersonic tunnels. The UOM & Cornell marine biology and acoustic sensing teams with years of experience in underwater testing in ocean and rivers, and access to knowledge of bio-organisms and bioacoustics Research, and data of the Perennial Acoustic Observatory in the Antarctic Ocean.

Impact

• Provide effective underwater vehicle detection and tracking system that is easy to install, autonomous and economical to operate and efficient in exploring and tracking moving targets in the undersea environment. The system will use effective natural sensing modalities and use natural undersea acoustic noise and other artifacts from natural organisms to advantage.

• The system will provide in-expensive underwater deployable system to detect, locate, and track submarines, manned, and unmanned under water vehicles and personnel.

• After the technology is developed to TRL6, the UTAS process is capable of transitioning the design to engineering and production in one of its sensor manufacturing facilities.

Contact Information: Magdi.Essawy@utas.utc.com 952-892-4331 (office) – 612-770-9168 (Mobile)

Paul Gader , University of Florida

Machine Learning, Image and Signal Analysis (MALISA)

Project Overview

• I am seeking to provide Machine Learning and Image / Signal Analysis support

• TA1: I can help establish criteria for training datasets , confirm characterizations, build detection algorithms for weak signals, and build robust algorithms for real-world conditions

• TA2: I can build robust detection and discrimination algorithms for real-world implementation

Teaming Overview and Objectives

• Lab has several PhD, MS, and Undergraduate students along with Prof. Hichem Frigui, U. of Louisville is colleague that I have worked on algorithms with extensively. I teach hyperspectral image analysis and machine learning

• Developed & implemented fielded algorithms for IED detection using Ground Penetrating Radar

• Developed handwriting recognition algorithms that tested as well as Deep Network architecture (CNN) and took 1st place in handwritten word recognition contest, both sponsored by NIST

• Numerous high-speed processing capabilities including the HiPerGator, high-speed graphical processing units (GPUs), very experienced in machine and deep learning

• I have 3 decades of experience building algorithms, but I need sensor developers and marine biologists to work with

Impact

• Anticipated outcome: Algorithms that are robust in real-world conditions

• Numerous applications of Machine Learning, Image and Signal Analysis can be affected

• Make algorithms available to system builders.

Contact Information

pgader@ufl.edu

352-262-4267

PI Name Institution Team Name Scott Gallager, Houshuo Jiang, Eugene Terray Woods Hole Oceanographic Institution Plankton Hunters Project Overview Objects moving through the water generate signals of hydrodynamic disturbances of both near-field particle displacement and far-field acoustic pressure waves. As such, sensing anomalies in the ocean has been accomplished by using passive acoustics for short periods of time. However, distributed sensing arrays have high cost, short duration, limited detection range, and require routine maintenance to avert bio-fouling and re-powering. If we consider the ubiquitous distribution of living organisms in the ocean on the scale of microns to millimeters (i.e., micro to mesoplankton), the use of a detection system that monitors and understands changes in plankton behavior may provide high spatial-temporal signal strength relative to ambient noise. Teaming Overview and Objectives Technical strengths: *Fluid mechanics at all scales, DNS modeling, of vehicles and plankton. *Turbulence measurement and modeling. *Biological understanding of hydromechanical, chemical and light signatures in ocean and those produced by plankton. *Open and coastal ocean experience with many AUV vehicles. *Deep Learning AI experience of data integration/classification of behavior, anomaly detection. *Experience in lab and ocean experimentation. *Open ocean imaging, PIV, machine vision, machine learning. *100 collective years in oceanography Impact A man-made vehicle traveling through the water will impart energy to the fluid causing a change in velocity, rotation and deformation. The length scales of this signal will depend on the vehicles form function (drag), speed and density of the fluid its traveling through. Let’s say that a man-made vehicle 1m in diameter moving through seawater at 8 kts emits a hydromechanical signal with a deformation rate of 1000 s-1 at the source typical of a small propeller on an AUV. With a decay rate of 1/r2 the signal would be felt 100 m away with a detection threshold for deformation rate of 1 s-1. This detection distance is easily within the realm for many micro and meso-zooplankton. A similar calculation may be made for light. If Noctiluca can be detected at a distance of 100 m then we just have to have a detector that can count photons and determine if and when an event has taken place. Similarly, a chemical trail in seawater of nM in concentration could in theory be detected using absorption spectroscopy Sensor nodes with these capabilities could be constructed for about $45 each so 300 would cost $13,500, the cable another $1000 and the waverider another $5,000 for a total for the package of $19,500. Fewer sensor nodes might be fine if the vertical resolution did not need to be 1 m. Arrays of these waverider packages could be deployed to cover a certain spatial extent providing passive protection throughout the water column over 100s of km. Contact Information Scott Gallager, sgallager@whoi.edu, 508 289 2783 Houshuo Jiang, hsjiang@whoi.edu, 508 289 3641 Eugene Terray, eterray@whoi.edu, 50 289 2438

David M. Kehoe Indiana University Team CA4

Project Overview

• In the past decade, we developed molecular genetic tools to routinely genetically modify strains of marine Synechococcus from around the world. We are using these tools to reveal how blue-green light regulates transcriptional activity and investigating responses to other environmental signals with these tools. Our goal is to create synthetic biology tools for use in industry and biotechnology.

• We will need more information to determine what light wavelengths are most useful for M/UUV detection, and if intensity or color ratios are most useful. Because we already know our sensory system, we will need to optimize it for maximum sensitivity and responsiveness and connect it to its output, the transcription regulation of gene expression, for additional signal propagation as part of TA1. This information will then have to be linked with a compatible T2 system. Since this is a photosynthetic organism, the energy needs of the system will be met by sunlight.

• Synechococcus sensory systems will be physically constrained and will be most useful anchored in the benthic zone in relatively shallow environments, so that light interference from above can be detected but enough sunlight can penetrate for the cells to be maintained through photosynthesis.

Teaming Overview and Objectives

• Current Members: PI David Kehoe, Co-PI Joel Ybe, Postdoc Bo Chen, PhD Student Allissa Haney

• We have achieved routine genetic manipulation of marine Synechococcus strains from around the world and are the first group to have done so. We have published all our findings in PNAS:

• Shukla, A., et al. 2012. A phycoerythrin-specific bilin lyase-isomerase controls blue-green chromatic acclimation in marine Synechococcus. Proc Natl Acad Sci USA 109: 20136-20141

• Sanfilippo, J.E., et al. 2016. A self-regulating genomic island encoding tandem regulators confers chromatic acclimation to marine Synechococcus. Proc Natl Acad Sci USA 113: 6077–6082

• Grébert, T., et al. 2018. Light color acclimation: a key process in the global ocean distribution of Synechococcus cyanobacteria. Proc Natl Acad Sci USA. Published ahead of print February 12, 2018

• We have all of the facilities necessary to genetically modify Synechococcus cells in order to create appropriate signals for TA2 and conduct small-scale tests of the system.

• We are seeking collaborators for TA2.

Impact

• We will create a new biological light sensing and detection system for use in coastal environments.

• This system will be useful for M/UUV sensing, optogenetic, and synthetic biology applications.

• We will also transform the genetic elements of this system into microbes useful for biotechnology.

Contact Information

Email address: dkehoe@indiana.edu Phone number: (812) 929-9083 (cell) (812) 856-4715 (work)

John Kuhn, Leidos Hydrodynamic / Biology Departments (Subcontractor)

Project Overview • Leidos has broad expertise in hydrodynamics, marine biology, quantitative behavioral analysis,

remote sensors, and signal processing • We offer support in Biological Signal Characterization (TA1) and Signal Interpretation (TA2)

Teaming Overview and Objectives • We are not yet a part of any PALS team, but we wish to participate as a subcontractor • Relevant experience in hydrodynamics and signal processing / remote sensors:

• 40 years Computational Fluid Dynamics (CFD) analysis / code development for US Navy • 30 years Anti-Submarine Warfare (ASW), including extensive signal / image processing • Developed concept for mitigation of bioluminescent signatures (2004/5 DARPA effort),

including novel tools / lab tests for phenomenology (collaboration with Scripps Institute) • Relevant experience in marine biology:

• 20 years of marine microbiological experience, encompassing detection, tracking, imaging, isolation, and functional analyses of marine microbial communities

• Custom marine bio-chamber design with automated growth maintenance • Relevant experience in quantitative behavioral analysis:

• Development of automated, real time group behavioral assays and analysis software (primarily applied to insects but can be easily adapted to any organism)

• System / software development for temporal detection of bioluminescence in bacteria • Institutional assets:

• Biological laboratory outfitted with incubators for growing marine plankton

Examples of Potential Areas of Impact • Development of turbulence sensor module that exploits mechanosensory abilities of plankton • Deployment of interfaced network of turbulence sensors for detection and tracking of AUVs • Synthesis of fluid dynamics, marine biology, and automated group organism behavioral analysis

to develop a bio-based turbulence sensor module

Contact: John Kuhn, Chief Engineer / Naval Architect, john.c.kuhn@leidos.com, 858-826-6929

Group Behavioral Analysis

A population of flies are filmed interacting at a food source, and social interactions are automatically quantified in real time. Orientation (green arrows), proximity (black lines), and relative velocity are used to quantify group-level escape response. This approach can be directly applied to characterize the Planktonic response to disturbances within an integrated behavioral detection system as illustrated to the right.

CFD Simulation

Bioluminescence Study Planktonic Biosensor

PI Name Institution Team Name James C. Liao University of Florida, Whitney Lab for Marine Bioscience Chironex

Project Overview

• Our goal is to monitor the auditory and lateral line system of fishes to look for detection of external sound and flow stimuli.

• We will combine our neurophysiology and behavioral recording expertise with the tag manufacturing expertise of Dr. David Mann (President/founder Loggerhead Instruments, former professor at FSU)

Teaming Overview and Objectives

• Dr. James C. Liao, postdoc Dimitri Skandalis, Ph.D. student Elias Lunsford, collaborator Dr. David Mann.

• Fish biomechanics and neuroscience professor, over 18 years research experience, tenured faculty at UF Biology and affiliate professor in Biomedical Engineering (Ph.D Harvard 2004, postdoc Cornell 2008).

• Specialized holding facilities at the Whitney Lab for Marine Bioscience, Loggerhead instruments

• Developing tags for monitoring the ocation and behavior of freely swimming fishes.

Impact

• The ability to harness the sensory capabilities of fish in the field to detect distinct acoustic and flow signatures.

• High temporal and spatial resolution for aquatic tracking. Data storage and compression technologies. Dead reckoning and machine learning algorithms to determine position and behavior.

Contact Information

Email address: jliao@whitney.ufl.edu

Phone number: 904-461-4011

Freeman, Freeman and Gaudette Naval Undersea Warfare Center NUWC

Contact Information

Email: Simon.freeman@navy.mil, Phone: 401-832-3209

Project PI’s:

Lauren A. Freeman Simon E. Freeman Jason E. Gaudette

Academic Collaborators: Aaron Thode (UCSD) Paul Gendron (UMassD)

Project Overview

We wish to perform detection and classification through analyzing the soniferous behavioral changes of coral reef organisms in the presence of otherwise quiet underwater vehicles

We will characterize ambient biological sound by using simultaneous passive acoustic sensing (using high resolution directional recorders) and simultaneous optical validation of soniferous biology in the field. Parallel to that effort, we will also validate sound sources in controlled laboratory tank environments. We plan to characterize changes in ambient biological sound by performing tests using AUVs that will transit through instrumented areas. In tank experiments, we plan to perform similar tests by exposing specimens to stimulus such as overhead shading or the sudden presence of a large nearby object. We will interpret ambient biological sound by developing a transient-based passive acoustic detector and classifier. The algorithms will be extensions of previous work we have performed in interpreting ambient biological reef sound for environmental evaluation. An ‘acoustic library’ of validated biological responses will be critical to detector success. Our hardware approach is to use directional acoustic sensing devices such as a large-N (>64 element) hydrophone arrays and /or vector sensor arrays, configured for estimating the directionality of broad-band, short-duration biological sounds. The acoustic recording system will be tethered to a surface marker and will communicate the output of on-board acoustic data processing in semi-real-time.

We bring unique experience in coral reef biological soundscape signal processing and expertise in field-based reef acoustic studies. We also bring the institutional assets available at NUWC such as the AUV fleet and permanently employed support staff, and various testing facilities in the U.S. and abroad. NUWC also regularly designs and fabricates custom underwater acoustic sensing equipment.

We seek collaborators who can perform laboratory based acoustic analysis of organisms in controlled conditions, such as inside an anechoic chamber. We also seek collaborators who have access to field sites that are ecologically appropriate for our proposal and are logistically straightforward to access.

We hope to develop a field-capable system that can reliably detect submerged human assets in bio-acoustically rich underwater environments to a tactically useful standoff range. Such a system will enhance situational awareness in regions such as the South China Sea and others where biological contributions to the underwater soundscape are significant. An enhanced ability to understand littoral bio-acoustic sources will also increase our understanding of the associated biological processes, with ramifications for environmental monitoring for resource management purposes.

NUWC is a center dedicated to the development and application of new technology to fleet assets. Direct communication of research outputs with NAVSEA, with the intent of developing transition opportunities, will be pursued as the project matures.

Rolandi UC Santa Cruz Shark Sense

Project Overview

The Ampullae of Lorenzini allow sharks, skates, and rays to detect changes in electric fields generated by muscle contractions and physiology of their potential prey. An individual Ampulla consists of a pore through the skin that opens to the aquatic environment. This pore is connected to a collagen canal enclosing an epithelium that secretes a jelly like substance (AoL jelly). This canal runs sub-dermally to an alveolus that contains electrosensitive cells. Within the alveolus the electrosensitive cells of the Ampullae communicate with neurons. Remarkably, the integration of signals from many Ampullae allows sharks, skates, and rays to detect changes in the electric field as small as 5 nV/cm. We have arranged a multidisciplinary team of electrical engineers (Rolandi, Dowla), developmental biologists (Amemiya), and electrophysiologists (DeCoursey) to tackle this complex problem at the organism level. The understanding spanning from this research will lead to the development of ultrasensitive e-field detectors for marine applications (Task 1)

Teaming Overview and Objectives

• Marco Rolandi, PI, UC Santa Cruz, Electrical Engineering. Expertise in Bioelectronics, ion conductivity, biomaterials.

• Chris Amemiya, co-PI, UC Merced, Molecular Cell Biology, Evolutionary and developmental biology of verterbates.

• Farid Dowla, co-PI, UC Santa Cruz, Electrical Engineering, RF Communications, Radar, Signal, and Image Processing.

• Tom de Coursey, co-PI, Rush Medical Center, Electrophysiology of proton channels.

• E.J. Josberger, P. Hassanzadeh, Y. Deng, J. Sohn, M. J. Rego, C. T. Ammemiya, M. Rolandi, * Proton Conductivity in Ampullae of Lorenzini Jelly, Science Advances, 2, e1600112 (2016).

• Needed Expertise: Translating shark electric field sensing into a measurable signal from outside detector.

Impact

The first level of success will be to precisely understand and model how electric field sensing occurs in the Ampullae and to measure the signal in the shark, or ampullae from shark in response to the weak electric signals from M/UUVs. With this fundamental knowledge Shark Sense will develop a strategy to retrieve the signal from the shark for detection of M/UUV.

Contact Information

mrolandi@ucsc.edu 831 459 9138

Michael Smanski Minnesota Synthetic Speciation

Project Overview

• We have developed a technique to prevent the flow of genes into or out from a GE organism. We want to team with a group submitting to PALS to provide a needed layer of biocontainment.

• We will provide genetic biocontainment for GMOs engineered as part of TA1

Teaming Overview and Objectives

• We have ongoing work (and preliminary data) for yeast, fish, mammals, roundworms, plants, and insects. We have relevant collaborators in each organism and would likely bring some of these collaborators into the team, depending on target organism.

• We have published a proof-of-concept in yeast [link]

• Top-notch facilities at the University of Minnesota for this type of research.

• I am seeking a team. I have experience submitting successful DARPA proposals.

Contact Information

smanski@umn.edu (best route)

612-624-9752 (second best route)

Tyler/Barth/Mellinger Oregon State University Reflected Sound Imaging Project Overview

• The project aims to use reflections from sounds produced by marine animals to detect M/UUVs • TA1: Documentation of sounds produced by marine animals is extensive and ongoing; changes to

production of these sounds in the presence of M/UUVs will be investigated using underwater gliders. • TA2: This presents the principal challenge. Reflected signals must be distinguished from the original

sound, and interpreted into spatial information. We will address this challenge by integrating experimentation, cutting edge machine learning approaches, and existing echolocation technology.

Teaming Overview and Objectives • Existing team members and partners & relevant experience

• Jack Barth (OSU College of Earth, Ocean and Atmospheric Sciences; CEOAS) Project Co-PI Co-PI of the OSU node of the NSF-funded Ocean Observatories Institute (OOI). OOI is a networked infrastructure of science-driven sensor systems to measure the physical, chemical, and biological variables in the ocean and seafloor. The OSU node includes sensors on the seafloor, buoys and underwater gliders.

• David K. Mellinger (OSU/NOAA Cooperative. Institute of Marine Resource Studies; CIMRS) Directs the CIMRS Bioacoustics Lab, investigating marine ecosystems using passive acoustic techniques. Analysis of worldwide long-term bioacoustics data sets; software and hardware for detecting, classifying, and locating animals acoustically. Project Co-PI

• Joe Haxel (OSU CIMRS and NOAA Pacific Marine Environmental Laboratory; PMEL) Expert in ocean ambient noise. Co-PI on project to establish a unique network of hydrophones to collect consistent and comparable long-term acoustic data sets from all major regions of the U.S.

• Mellinger and Haxel collaborate on marine soundscapes and impacts of noise on marine organisms. • Xiaoli Fern (OSU School of Electrical Engineering and Computer Science; EECS)

Expertise in machine learning and data mining, specifically unsupervised learning, clustering, correlation analysis, dimension reduction, and pattern mining, and Bayesian Optimization for active sensing, with applications to bioacoustics.

• Raviv Raich (OSU School of Electrical Engineering and Computer Science; EECS) Expertise in statistical signal processing, machine learning, inverse problem, sparse signal reconstruction, manifold learning, and adaptive sensing.

• Brett M. Tyler (Director, OSU Center for Genome Research & Biocomputing; CGRB) Project Co-PI The CGRB provides high performance computing facilities and research in support of data-intensive research in the life and environmental sciences

• Fern, Raich & Tyler collaborate on the detection and classification of animal vocalizations in the wild • Institutional assets

• Sensor arrays of the Ocean Observatories Institute including collaborating institutions • NOAA and OSU research vessels and their on-board capabilities • CGRB and CEOAS high performance computing clusters, including GPU arrays • OSU artificial intelligence and data science group (16 faculty in EECS and Statistics) • OSU’s College of Earth, Ocean and Atmospheric Sciences and Hatfield Marine Science Center

• For which technical challenge are you seeking collaborators? • Interpretation of reflected sounds into spatial information about M/UUVs (most important) • Changes to marine animal production of sounds in the presence of M/UUVs (useful) • Any independent technology for detecting M/UUVs (opportunity for use of Ensemble methods)

Impact • What is the anticipated impact of the team’s success (in terms of technique AND capability)?

• Improved detection and monitoring of M/UUVs and other objects of interest • Include a list of potential applications enabled by this technology.

• Defense and environmental applications for improved monitoring of moving bodies in water and air • Advancement of algorithms and technologies for detection of complex signals in noisy environments

• Defense, homeland security, cybersecurity, biomedicine, etc • How will the team pursue transition of this technology?

• OSU Office for Commercialization & Corporate Development Contact Information

Brett Tyler (brett.tyler@oregonstate.edu, 541-737-3347), Jack Barth (jack.barth@oregonstate.edu, 541-737-1607) and David Mellinger (David.Mellinger@oregonstate.edu, 541-867-0372)

Jennifer L. Miksis-Olds University of New Hampshire UNH

Project Overview

UNH excels in R&D related to passive acoustic monitoring and environmental DNA (eDNA) analysis. We envision a coupled in-situ system where passive acoustic detections inform fine-scale eDNA sampling to detect, classify, and report the presence of M/UUV or other vessel types in a targeted area. We envision a tiered detection system that continuously monitors background conditions for comparison to detected aberrations indicative of vessel presence.

Passive acoustic technology is used non-invasively to assess environmental sound levels, surface conditions, human activity, and the distribution and biodiversity of vocalizing marine life at regional scales. Advances in directional sensors are providing an enhanced capacity to localize sound sources. Acoustic detection and localization, however, fail when sources are not generating sound. We propose consideration of the amalgamated behavior of marine life contributing to the ocean soundscape as a living sensor that can be analyzed to detect the presence of silent, intrusive sources via increased biological activity or voids in the soundscape indicative of decreased biological activity. Deviations from background conditions then target time periods of fine-scale eDNA sampling for a second level of detection and classification.

Organisms at all levels of the food chain contain or produce genetic material that can be used to detect their presence. This genetic material can be captured directly from sampling the animal itself, animal produced wastes, externally shed cells (e.g. skin, scales), or unconsumed prey remnants. Manned vessels produce detectable genetic signatures that persist for a finite period of time in their environment. Similarly, vessels harbor a “microbiome” on the surface and in bilge waters and that biological material dispersed during travel and can be identified using modern genetic tools.

Tier 1 – Background monitoring of regional soundscape and local eDNA spectrum (TA1) Tier 2 – Detection of soundscape deviations direct targeted eDNA sampling for deviations from background (TA1 and TA2) Tier 3 – Verified detections translated and communicated to end user (TA2)

Challenges: 1) Conclusively relating cause and effect to soundscape deviations, 2) develop and demonstrate the appropriate sampling strategy that can capture genetic material before dispersal and dilution, 3) Capturing the relevant genetic signatures by understanding potential false positives and validating target loci, and 4) translation of lab eDNA analysis techniques to real-time, marine analysis.

Teaming Overview and Objectives

• Personnel: Acoustics (Jennifer Miksis-Olds), UNH Hubbard Genome Center (Kelley Thomas, Director) • Institutional acoustic assets - 60’ x 40’ x 20’ engineering tank, Atlantic Deepwater Ecosystem

Observatory Network (ADEON – Lead PI, Miksis-Olds) https://adeon.unh.edu/ • Institutional genomic assets - In-house next generation sequencing capacity, HPC computing facility

SEEKING COLLABORATION in 1) M/UUV access, 2) transitioning eDNA techniques from lab to field, 3) operational system integration.

Impact

Potential applications enabled by this technology: 1) Targeted monitoring of invasive species and pathogens, 2) Microbial source tracking for vessel identification, and 3) Characterization and Identification of passengers and crew (e.g. human trafficking)

Contact Information Acoustics: Jennifer Miksis-Olds - J.Miksisolds@unh.edu, 603 862-5147 Genomics: Kelley Thomas - Kelley.Thomas@unh.edu, 603 862-2470