Detection, classification, and density estimation of marine mammals: final report

Detection, classification, and localization (DCL) research on marine mammal vocalizations has been in development for decades, and methods for marine mammal population density estimation using acoustic data have been in development since at least 2007. These efforts have been supported by MobySound, an archive of cetacean sounds used for studying call detection and localization that are annotated to facilitate research in DCL. This project was aimed to begin development of high‐performing automatic detection methods for the sounds of beaked whales and other odontocetes. Specifically, this report [1] details the newly collected odontocete recordings that have been added to the MobySound archive; [2] documents continuing development of methods for detection and classification, including improvements to the Energy Ratio Mapping Algorithm (ERMA) method for use on gliders and its extension to new species and populations; [3] reports on application of a newly developed method for population density estimation to field recordings; and [4] also reports on the successful production of datasets focused on odontocete whistles and clicks and baleen whale calls for the Fifth Workshop on Detection, Classification, Localization, and Density Estimation of Marine Mammals using Passive Acoustics.Chief of Naval Operations, Energy and Environmental Readiness Division, Washington DC. The report was prepared by Oregon State University and supported under NPS Grant N00244-10-1-0047.Approved for public release; distribution is unlimited

A comparison of methods for detecting right whale calls,”

ABSTRACT North Atlantic, North Pacific, and southern right whales all produce the up call, a frequency-modulated upsweep in the 50-200 Hz range. This call is one of the most common sounds, and frequently the most common sound, received from right whales, and as such is a useful indicator of the presence of right whales for acoustic surveys. A data set was prepared of 1857 calls and 6359 non-call sounds recorded from North Atlantic right whales (Eubalaena glacialis) near Georgia and Massachusetts. Two methods for the detection of the calls were compared: spectrogram correlation and a neural network. Spectrogram correlation parameters were chosen two ways, by manual choice using a sample of 20 calls, and by an optimization procedure that used all available calls. Neural network weights were trained via backpropagation on 9/10 of the test data set. Performance was measured separately for calls of different signal-to-noise ratio, as SNR heavily influences the performance of any detector. Results showed that the neural network performed best at this task, achieving an error rate of less than 6%, and is thus the preferred detection method here. Spectrogram correlation may be useful in situations in which a large set of training data is not available, as manual training on a small set of examples achieved an error rate (26%) that may be acceptable for many applications. SOMMAIRE Les baleines franches de l'Atlantique Nord, du Pacific Nord et Sud produisent toutes une vocalisation montante, soit un balayage ascendant modulé en fréquence dans la région de 50 à 200 Hz. Cette vocalisation est un des sons les plus communs produit par les baleines franches et, par le fait même, est un indicateur très utile de la présence des baleines lors de sondages acoustiques. Un ensemble de données a été préparé avec 1857 vocalisations et 6359 sons non vocalisés enregistrés auprès de baleines franches de l'Atlantique Nord (Eubalaena glacialis) près de la Georgie et du Massachusetts. Deux méthodes de détection des vocalisations ont été comparées: la corrélation de spectrogramme et le réseau neuronal. Les paramètres de la corrélation de spectrogramme ont été choisis de deux façons: par choix manuel, en utilisant seulement 20 vocalisations, et par une optimisation de la procédure utilisant toutes les vocalisations. Les coefficients de pondération du réseau neuronal ont été établi par rétropropagation sur 9/10 des données de test. Les performances ont été mesurées séparément pour des vocalisations ayant des rapports signal sur bruit différents, le rapport signal sur bruit ayant une grande influence sur tout détecteur. Les résultats démontrent que le réseau neuronal performe mieux dans ce genre de tâche, atteignant un taux d'erreur de moins de 6% et, par conséquent, est défini ici comme la meilleure méthode de détection. La corrélation de spectrogramme peut être utile dans les situations où un grand nombre de données de formation ne sont pas disponibles. Le choix manuel sur de petite tranche d'échantillons a atteint un taux d'erreur (26%) qui pourrait être acceptable dans plusieurs applications

Moving from Binders to Bytes: Processing, Digitizing, and Publishing a Paper-Based Archive to an Institutional Repository

At San Jose State University, a paper-based archive centering on library and information science history is being processed, organized, and uploaded onto ScholarWorks, the campus institutional repository. Prior to its digitization, the presenters grappled with many questions. What platform should be used to house the archive? What entry points would researchers expect in order to access the collection? What research purposes would this collection satisfy? The presenters will discuss their rationale for their decision-making in transferring 300 binders to an open access, digital format. Among the individuals who are involved in making this detail-rich collection openly accessible online and searchable are a scholarly communications librarian, a cataloging and metadata specialist who is serving as the interim institutional repository coordinator, and a library and information science graduate student focusing on archival records and management. These individuals will discuss their varying perspectives and how each of their emphases contributes to the enterprise of making this paper-based archive discoverable, searchable, and digitally accessible in an ever-evolving institutional repository and scholarly communications environment

The energy ratio mapping algorithm: A tool to improve the energy-based detection of odontocete echolocation clicks

The energy ratio mapping algorithm (ERMA) was developed to improve the performance of energy-based detection of odontocete echolocation clicks, especially for application in environments with limited computational power and energy such as acoustic gliders. ERMA systematically evaluates many frequency bands for energy ratio-based detection of echolocation clicks produced by a target species in the presence of the species mix in a given geographic area. To evaluate the performance of ERMA, a Teager-Kaiser energy operator was applied to the series of energy ratios as derived by ERMA. A noise-adaptive threshold was then applied to the Teager-Kaiser function to identify clicks in data sets. The method was tested for detecting clicks of Blainville’s beaked whales while rejecting echolocation clicks of Risso’s dolphins and pilot whales. Results showed that the ERMA-based detector correctly identified 81.6% of the beaked whale clicks in an extended evaluation data set. Average false-positive detection rate was 6.3% (3.4% for Risso’s dolphins and 2.9% for pilot whales). VC 2011 Acoustical Society of America. [DOI: 10.1121/1.3531924

Detections of whale vocalizations by simultaneously deployed bottom-moored and deep-water mobile autonomous hydrophones

Funding for this work was provided by the Living Marine Resources Program (N39430-14-C-1435 and N39430-14-C-1434), the Office of Naval Research (N00014-15-1-2142, N00014-10-1-0534, and N00014-13-1-0682), and NOAA’s Southwest Fisheries Science Center. SF was supported by the National Science and Engineering Graduate Fellowship.Advances in mobile autonomous platforms for oceanographic sensing, including gliders and deep-water profiling floats, have provided new opportunities for passive acoustic monitoring (PAM) of cetaceans. However, there are few direct comparisons of these mobile autonomous systems to more traditional methods, such as stationary bottom moored recorders. Cross-platform comparisons are necessary to enable interpretation of results across historical and contemporary surveys that use different recorder types, and to identify potential biases introduced by the platform. Understanding tradeoffs across recording platforms informs best practices for future cetacean monitoring efforts. This study directly compares the PAM capabilities of a glider (Seaglider) and a deep-water profiling float (QUEphone) to a stationary seafloor system (High-frequency Acoustic Recording Package, or HARP) deployed simultaneously over a 2 week period in the Catalina Basin, California, United States. Two HARPs were deployed 4 km apart while a glider and deep-water float surveyed within 20 km of the HARPs. Acoustic recordings were analyzed for the presence of multiple cetacean species, including beaked whales, delphinids, and minke whales. Variation in acoustic occurrence at 1-min (beaked whales only), hourly, and daily scales were examined. The number of minutes, hours, and days with beaked whale echolocation clicks were variable across recorders, likely due to differences in the noise floor of each recording system, the spatial distribution of the recorders, and the short detection radius of such a high-frequency, directional signal type. Delphinid whistles and clicks were prevalent across all recorders, and at levels that may have masked beaked whale vocalizations. The number and timing of hours and days with minke whale boing sounds were nearly identical across recorder types, as was expected given the relatively long propagation distance of boings. This comparison provides evidence that gliders and deep-water floats record cetaceans at similar detection rates to traditional stationary recorders at a single point. The spatiotemporal scale over which these single hydrophone systems record sounds is highly dependent on acoustic features of the sound source. Additionally, these mobile platforms provide improved spatial coverage which may be critical for species that produce calls that propagate only over short distances such as beaked whales.Publisher PDFPeer reviewe

A Pulsed-air Model of Blue Whale B Call Vocalizations

Blue whale sound production has been thought to occur by Helmholtz resonance via air flowing from the lungs into the upper respiratory spaces. This implies that the frequency of blue whale vocalizations might be directly proportional to the size of their sound-producing organs. Here we present a sound production mechanism where the fundamental and overtone frequencies of blue whale B calls can be well modeled using a series of short-duration (\u3c1 \u3es) wavelets. We propose that the likely source of these wavelets are pneumatic pulses caused by opening and closing of respiratory valves during air recirculation between the lungs and laryngeal sac. This vocal production model is similar to those proposed for humpback whales, where valve open/closure and vocal fold oscillation is passively driven by airflow between the lungs and upper respiratory spaces, and implies call frequencies could be actively changed by the animal to center fundamental tones at different frequency bands during the call series

Repertoire and classification of non-song calls in Southeast Alaskan humpback whales (Megaptera novaeangliae)

On low-latitude breeding grounds, humpback whales produce complex and highly stereotyped songs as well as a range of non-song sounds associated with breeding behaviors. While on their Southeast Alaskan foraging grounds, humpback whales produce a range of previously unclassified non-song vocalizations. This study investigates the vocal repertoire of Southeast Alaskan humpback whales from a sample of 299 non-song vocalizations collected over a 3-month period on foraging grounds in Frederick Sound, Southeast Alaska. Three classification systems were used, including aural spectrogram analysis, statistical cluster analysis, and discriminant function analysis, to describe and classify vocalizations. A hierarchical acoustic structure was identified; vocalizations were classified into 16 individual call types nested within four vocal classes. The combined classification method shows promise for identifying variability in call stereotypy between vocal groupings and is recommended for future classification of broad vocal repertoires

Alzheimer's pathology targets distinct memory networks in the ageing brain

Alzheimer’s disease researchers have been intrigued by the selective regional vulnerability of the brain to amyloid-β plaques and tau neurofibrillary tangles. Post-mortem studies indicate that in ageing and Alzheimer’s disease tau tangles deposit early in the transentorhinal cortex, a region located in the anterior-temporal lobe that is critical for object memory. In contrast, amyloid-β pathology seems to target a posterior-medial network that subserves spatial memory. In the current study, we tested whether anterior-temporal and posterior-medial brain regions are selectively vulnerable to tau and amyloid-β deposition in the progression from ageing to Alzheimer’s disease and whether this is reflected in domain-specific behavioural deficits and neural dysfunction. 11C-PiB PET and 18F-flortaucipir uptake was quantified in a sample of 131 cognitively normal adults (age: 20–93 years; 47 amyloid-β-positive) and 20 amyloid-β-positive patients with mild cognitive impairment or Alzheimer’s disease dementia (65–95 years). Tau burden was relatively higher in anterior-temporal regions in normal ageing and this difference was further pronounced in the presence of amyloid-β and cognitive impairment, indicating exacerbation of ageing-related processes in Alzheimer’s disease. In contrast, amyloid-β deposition dominated in posterior-medial regions. A subsample of 50 cognitively normal older (26 amyloid-β-positive) and 25 young adults performed an object and scene memory task while functional MRI data were acquired. Group comparisons showed that tau-positive (n = 18) compared to tau-negative (n = 32) older adults showed lower mnemonic discrimination of object relative to scene images [t(48) = −3.2, P = 0.002]. In a multiple regression model including regional measures of both pathologies, higher anterior-temporal flortaucipir (tau) was related to relatively worse object performance (P = 0.010, r = −0.376), whereas higher posterior-medial PiB (amyloid-β) was related to worse scene performance (P = 0.037, r = 0.309). The functional MRI data revealed that tau burden (but not amyloid-β) was associated with increased task activation in both systems and a loss of functional specificity, or dedifferentiation, in posterior-medial regions. The loss of functional specificity was related to worse memory. Our study shows a regional dissociation of Alzheimer’s disease pathologies to distinct memory networks. While our data are cross-sectional, they indicate that with ageing, tau deposits mainly in the anterior-temporal system, which results in deficits in mnemonic object discrimination. As Alzheimer’s disease develops, amyloid-β deposits preferentially in posterior-medial regions additionally compromising scene discrimination and anterior-temporal tau deposition worsens further. Finally, our findings propose that the progression of tau pathology is linked to aberrant activation and dedifferentiation of specialized memory networks that is detrimental to memory function

Extracellular Vesicles from Pseudomonas aeruginosa Suppress MHC-Related Molecules in Human Lung Macrophages

Pseudomonas aeruginosa, a Gram-negative bacterium, is one of the most common pathogens colonizing the lungs of cystic fibrosis patients. P. aeruginosa secrete extracellular vesicles (EVs) that contain LPS and other virulence factors that modulate the host\u27s innate immune response, leading to an increased local proinflammatory response and reduced pathogen clearance, resulting in chronic infection and ultimately poor patient outcomes. Lung macrophages are the first line of defense in the airway innate immune response to pathogens. Proper host response to bacterial infection requires communication between APC and T cells, ultimately leading to pathogen clearance. In this study, we investigate whether EVs secreted from P. aeruginosa alter MHC Ag expression in lung macrophages, thereby potentially contributing to decreased pathogen clearance. Primary lung macrophages from human subjects were collected via bronchoalveolar lavage and exposed to EVs isolated from P. aeruginosa in vitro. Gene expression was measured with the NanoString nCounter gene expression assay. DNA methylation was measured with the EPIC array platform to assess changes in methylation. P. aeruginosa EVs suppress the expression of 11 different MHC-associated molecules in lung macrophages. Additionally, we show reduced DNA methylation in a regulatory region of gene complement factor B (CFB) as the possible driving mechanism of widespread MHC gene suppression. Our results demonstrate MHC molecule downregulation by P. aeruginosa-derived EVs in lung macrophages, which is consistent with an immune evasion strategy employed by a prokaryote in a host-pathogen interaction, potentially leading to decreased pulmonary bacterial clearance

Preliminary assessment of candidate immobilization technologies for retrieved single-shell tank wastes

This report describes the initial work that has been performed to select technologies for immobilization of wastes that may be retrieved from Hanford single-shell tanks (SSTs). Two classes of waste will require immobilization. One is the combined high-level waste/transuranic (HLW/TRU) fraction, the other the low-level waste (LLW) fraction. A number of potential immobilization technologies are identified for each class of waste. Immobilization technologies were initially selected based on a number of considerations, including (1) the waste loading that could likely be achieved within the constraint of producing acceptable waste forms, (2) process flexibility (primarily compatibility with anticipated waste variability), (3) process complexity, and (4) state of development. Immobilization technologies selected for further development include the following: for HLW/TRU waste -- borosilicate glass, lead-iron phosphate glass, glass-calcine composites, glass-ceramics, and cement based forms; for non-denitrated LLW -- grout, laxtex-modified concrete, and polyethylene; and for denitrated LLW -- silicate glass, phosphate glass, and clay calcination or tailored ceramic in various matrices