299 research outputs found

    A Pulsed-air Model of Blue Whale B Call Vocalizations

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    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

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

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    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

    Long-term passive acoustic recordings track the changing distribution of North Atlantic right whales (Eubalaena glacialis) from 2004 to 2014

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    © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 7 (2017): 13460, doi:10.1038/s41598-017-13359-3.Given new distribution patterns of the endangered North Atlantic right whale (NARW; Eubalaena glacialis) population in recent years, an improved understanding of spatio-temporal movements are imperative for the conservation of this species. While so far visual data have provided most information on NARW movements, passive acoustic monitoring (PAM) was used in this study in order to better capture year-round NARW presence. This project used PAM data from 2004 to 2014 collected by 19 organizations throughout the western North Atlantic Ocean. Overall, data from 324 recorders (35,600 days) were processed and analyzed using a classification and detection system. Results highlight almost year-round habitat use of the western North Atlantic Ocean, with a decrease in detections in waters off Cape Hatteras, North Carolina in summer and fall. Data collected post 2010 showed an increased NARW presence in the mid-Atlantic region and a simultaneous decrease in the northern Gulf of Maine. In addition, NARWs were widely distributed across most regions throughout winter months. This study demonstrates that a large-scale analysis of PAM data provides significant value to understanding and tracking shifts in large whale movements over long time scales.This research was funded and supported by many organizations, specified by projects as follows: Data recordings from region 1 were provided by K. Stafford and this research effort was funded by the National Science Foundation #NSF-ARC 0532611. Region 2 data were provided by D. K. Mellinger and S. Nieukirk, funded by National Oceanic and Atmospheric Agency (NOAA) and the Office of Naval Research (ONR) #N00014–03–1–0099, NOAA #NA06OAR4600100, US Navy #N00244-08-1-0029, N00244-09-1-0079, and N00244-10-1-0047

    SAGES consensus recommendations on an annotation framework for surgical video

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    Background: The growing interest in analysis of surgical video through machine learning has led to increased research efforts; however, common methods of annotating video data are lacking. There is a need to establish recommendations on the annotation of surgical video data to enable assessment of algorithms and multi-institutional collaboration. Methods: Four working groups were formed from a pool of participants that included clinicians, engineers, and data scientists. The working groups were focused on four themes: (1) temporal models, (2) actions and tasks, (3) tissue characteristics and general anatomy, and (4) software and data structure. A modified Delphi process was utilized to create a consensus survey based on suggested recommendations from each of the working groups. Results: After three Delphi rounds, consensus was reached on recommendations for annotation within each of these domains. A hierarchy for annotation of temporal events in surgery was established. Conclusions: While additional work remains to achieve accepted standards for video annotation in surgery, the consensus recommendations on a general framework for annotation presented here lay the foundation for standardization. This type of framework is critical to enabling diverse datasets, performance benchmarks, and collaboration

    A stage-structured model to predict the effect of temperature and salinity on glass eel Anguilla anguilla pigmentation development

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    The pigmentation development process of glass eels Anguilla anguilla from stage V-B to VIA3 was modelled by gamma cumulative functions. These functions varied with respect to the factors temperature and salinity whose effects were adjusted by beta functions. Temperature was shown to accelerate pigmentation, while salinity acted as a secondary factor slowing down the pigmentation. The model fits the development of 15 samples kept at various temperatures and salinities in the Vilaine River, as well as samples monitored at other dates and places in Europe. It allows the prediction of the duration of estuarine residency for glass eels, in winter and spring, in the Atlantic estuaries

    Exploring movement patterns and changing distributions of baleen whales in the western North Atlantic using a decade of passive acoustic data

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    © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Davis, G. E., Baumgartner, M. F., Corkeron, P. J., Bell, J., Berchok, C., Bonnell, J. M., Thornton, J. B., Brault, S., Buchanan, G. A., Cholewiak, D. M., Clark, C. W., Delarue, J., Hatch, L. T., Klinck, H., Kraus, S. D., Martin, B., Mellinger, D. K., Moors-Murphy, H., Nieukirk, S., Nowacek, D. P., Parks, S. E., Parry, D., Pegg, N., Read, A. J., Rice, A. N., Risch, D., Scott, A., Soldevilla, M. S., Stafford, K. M., Stanistreet, J. E., Summers, E., Todd, S., & Van Parijs, S. M. Exploring movement patterns and changing distributions of baleen whales in the western North Atlantic using a decade of passive acoustic data. Global Change Biology, (2020): 1-30, doi:10.1111/gcb.15191.Six baleen whale species are found in the temperate western North Atlantic Ocean, with limited information existing on the distribution and movement patterns for most. There is mounting evidence of distributional shifts in many species, including marine mammals, likely because of climate‐driven changes in ocean temperature and circulation. Previous acoustic studies examined the occurrence of minke (Balaenoptera acutorostrata ) and North Atlantic right whales (NARW; Eubalaena glacialis ). This study assesses the acoustic presence of humpback (Megaptera novaeangliae ), sei (B. borealis ), fin (B. physalus ), and blue whales (B. musculus ) over a decade, based on daily detections of their vocalizations. Data collected from 2004 to 2014 on 281 bottom‐mounted recorders, totaling 35,033 days, were processed using automated detection software and screened for each species' presence. A published study on NARW acoustics revealed significant changes in occurrence patterns between the periods of 2004–2010 and 2011–2014; therefore, these same time periods were examined here. All four species were present from the Southeast United States to Greenland; humpback whales were also present in the Caribbean. All species occurred throughout all regions in the winter, suggesting that baleen whales are widely distributed during these months. Each of the species showed significant changes in acoustic occurrence after 2010. Similar to NARWs, sei whales had higher acoustic occurrence in mid‐Atlantic regions after 2010. Fin, blue, and sei whales were more frequently detected in the northern latitudes of the study area after 2010. Despite this general northward shift, all four species were detected less on the Scotian Shelf area after 2010, matching documented shifts in prey availability in this region. A decade of acoustic observations have shown important distributional changes over the range of baleen whales, mirroring known climatic shifts and identifying new habitats that will require further protection from anthropogenic threats like fixed fishing gear, shipping, and noise pollution.We thank Chris Pelkie, David Wiley, Michael Thompson, Chris Tessaglia‐Hymes, Eric Matzen, Chris Tremblay, Lance Garrison, Anurag Kumar, John Hildebrand, Lynne Hodge, Russell Charif, Kathleen Dudzinski, and Ann Warde for help with project planning, field work support, and data management. For all the support and advice, thanks to the NEFSC Protected Species Branch, especially the passive acoustics group, Josh Hatch, and Leah Crowe. We thank the field and crew teams on all the ships that helped in the numerous deployments and recoveries. This research was funded and supported by many organizations, specified by projects as follows: data recordings from region 1 were provided by K. Stafford (funding: National Science Foundation #NSF‐ARC 0532611). Region 2 data: D. K. Mellinger and S. Nieukirk, National Oceanic and Atmospheric Administration (NOAA) PMEL contribution #5055 (funding: NOAA and the Office of Naval Research #N00014–03–1–0099, NOAA #NA06OAR4600100, US Navy #N00244‐08‐1‐0029, N00244‐09‐1‐0079, and N00244‐10‐1‐0047). Region 3A data: D. Risch (funding: NOAA and Navy N45 programs). Region 3 data: H. Moors‐Murphy and Fisheries and Oceans Canada (2005–2014 data), and the Whitehead Lab of Dalhousie University (eastern Scotian Shelf data; logistical support by A. Cogswell, J. Bartholette, A. Hartling, and vessel CCGS Hudson crew). Emerald Basin and Roseway Basin Guardbuoy data, deployment, and funding: Akoostix Inc. Region 3 Emerald Bank and Roseway Basin 2004 data: D. K. Mellinger and S. Nieukirk, NOAA PMEL contribution #5055 (funding: NOAA). Region 4 data: S. Parks (funding: NOAA and Cornell University) and E. Summers, S. Todd, J. Bort Thornton, A. N. Rice, and C. W. Clark (funding: Maine Department of Marine Resources, NOAA #NA09NMF4520418, and #NA10NMF4520291). Region 5 data: S. M. Van Parijs, D. Cholewiak, L. Hatch, C. W. Clark, D. Risch, and D. Wiley (funding: National Oceanic Partnership Program (NOPP), NOAA, and Navy N45). Region 6 data: S. M. Van Parijs and D. Cholewiak (funding: Navy N45 and Bureau of Ocean and Energy Management (BOEM) Atlantic Marine Assessment Program for Protected Species [AMAPPS] program). Region 7 data: A. N. Rice, H. Klinck, A. Warde, B. Martin, J. Delarue, and S. Kraus (funding: New York State Department of Environmental Conservation, Massachusetts Clean Energy Center, and BOEM). Region 8 data: G. Buchanan, and K. Dudzinski (funding: New Jersey Department of Environmental Protection and the New Jersey Clean Energy Fund) and A. N. Rice, C. W. Clark, and H. Klinck (funding: Center for Conservation Bioacoustics at Cornell University and BOEM). Region 9 data: J. E. Stanistreet, J. Bell, D. P. Nowacek, A. J. Read, and S. M. Van Parijs (funding: NOAA and US Fleet Forces Command). Region 10 data: L. Garrison, M. Soldevilla, C. W. Clark, R. A. Chariff, A. N. Rice, H. Klinck, J. Bell, D. P. Nowacek, A. J. Read, J. Hildebrand, A. Kumar, L. Hodge, and J. E. Stanistreet (funding: US Fleet Forces Command, BOEM, NOAA, and NOPP). Region 11 data: C. Berchok as part of a collaborative project led by the Fundacion Dominicana de Estudios Marinos, Inc. (Dr. Idelisa Bonnelly de Calventi; funding: The Nature Conservancy [Elianny Dominguez]) and D. Risch (funding: World Wildlife Fund, NOAA, and Dutch Ministry of Economic Affairs)

    Benzodiazepine use among adults residing in the urban settlements of Karachi, Pakistan: A cross sectional study

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    <p>Abstract</p> <p>Background</p> <p>There are hardly any studies carried out in Pakistan on the usage of benzodiazepines at the level of community. This research was aimed to determine the frequency of benzodiazepine use, along with its associations with socio-demographic and clinical characteristics among community dwelling adults, residing in two urban settlements of Karachi, Pakistan.</p> <p>Methods</p> <p>We performed a cross sectional study from August 2008 to December 2009, in 2 areas of Karachi, namely Garden and Sultanabad. We followed the systematic sampling strategy to randomly select the households, with an adult of either sex and of age 18 years or more. Data collection was carried out through interview, using a pre-tested questionnaire, with items on socio-demographic position, medical history and benzodiazepine use. Student's t-test and χ<sup>2 </sup>test was employed to determine the associations between socio-demographic and clinical characteristics, and their relationship with benzodiazepine use was determined using applied logistic regression.</p> <p>Results</p> <p>The overall percentage of benzodiazepine consumption was estimated to be 14%. There were significantly more benzodiazepine users in the peri-urban Sultanabad community to the urban community of Garden (p-value = 0.001). The mean age (± SD) for users was 51.3 (± 15.6) years compared to 37.1 (± 14.4) years among non-users. Bromazepam was the most widely used benzodiazepine (29%); followed by diazepam, with a median duration on primary use being 144 weeks (IQR = 48-240). The adjusted logistic regression model revealed that increasing age, location, female sex, unemployment and psychiatric consultation were associated with increased likelihood of benzodiazepine use.</p> <p>Conclusion</p> <p>We believe the unregulated over-the-counter sales of benzodiazepines and social conditions might be playing a role in this high consumption of benzodiazepines in the community.</p

    High source levels and small active space of high-pitched song in bowhead whales (Balaena mysticetus)

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    © The Author(s), 2012. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Public Library of Science, doi:10.1371/journal.pone.0052072.The low-frequency, powerful vocalizations of blue and fin whales may potentially be detected by conspecifics across entire ocean basins. In contrast, humpback and bowhead whales produce equally powerful, but more complex broadband vocalizations composed of higher frequencies that suffer from higher attenuation. Here we evaluate the active space of high frequency song notes of bowhead whales (Balaena mysticetus) in Western Greenland using measurements of song source levels and ambient noise. Four independent, GPS-synchronized hydrophones were deployed through holes in the ice to localize vocalizing bowhead whales, estimate source levels and measure ambient noise. The song had a mean apparent source level of 185±2 dB rms re 1 µPa @ 1 m and a high mean centroid frequency of 444±48 Hz. Using measured ambient noise levels in the area and Arctic sound spreading models, the estimated active space of these song notes is between 40 and 130 km, an order of magnitude smaller than the estimated active space of low frequency blue and fin whale songs produced at similar source levels and for similar noise conditions. We propose that bowhead whales spatially compensate for their smaller communication range through mating aggregations that co-evolved with broadband song to form a complex and dynamic acoustically mediated sexual display.This work was funded by the Oticon Foundation (grant # 08-3469 to Arctic Station, OT). OT and MC were additionally funded by AP Møller og Hustru Chastine Mc-Kinney Møllers Fond til almene Formaal, MS by a PhD scholarship from the Oticon Foundation, FHJ by a Danish Council for Independent Research, Natural Sciences post-doctoral grant, SEP by a grant from the U.S. Office of Naval Research, and PTM by frame grants from the Danish Natural Science Research Council

    Insomnia and its correlates in a representative sample of the Greek population

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    <p>Abstract</p> <p>Background</p> <p>Insomnia is a major public health concern affecting about 10% of the general population in its chronic form. Furthermore, epidemiological surveys demonstrate that poor sleep and sleep dissatisfaction are even more frequent problems (10-48%) in the community. This is the first report on the prevalence of insomnia in Greece, a southeastern European country which differs in several socio-cultural and climatic aspects from the rest of European Community members. Data obtained from a national household survey (n = 1005) were used to assess the relationship between insomnia symptoms and a variety of sociodemographic variables, life habits, and health-related factors.</p> <p>Methods</p> <p>A self-administered questionnaire with questions pertaining to general health and related issues was given to the participants. The Short Form-36 (Mental Health subscale), the Athens Insomnia Scale (AIS) as a measure of insomnia-related symptoms, and the International Physical Activity Questionnaire (IPAQ) were also used for the assessment.</p> <p>Results</p> <p>The prevalence of insomnia in the total sample was 25.3% (n = 254); insomnia was more frequent in women than men (30.7% vs. 19.5%) and increased with age. Multiple regression analysis revealed a significant association of insomnia with low socio-economical status and educational level, physical inactivity, existence of a chronic physical or mental disease and increased number of hospitalizations in the previous year.</p> <p>Conclusions</p> <p>The present study confirms most findings reported from other developed countries around the world regarding the high prevalence of insomnia problems in the general population and their association with several sociodemographic and health-related predisposing factors. These results further indicate the need for more active interventions on the part of physicians who should suspect and specifically ask about such symptoms.</p
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