Effects of noise and by-catch on a Danish harbour porpoise population

Ships and wind turbines generate noise, which can have a negative impact on marine mammal populations by scaring animals away. Effective modelling of how this affects the populations has to take account of the location and timing of disturbances. Here we construct an individual-based model of harbour porpoises in the Inner Danish Waters. Individuals have their own energy budgets constructed using established principles of physiological ecology. Data are lacking on the spatial distribution of food which is instead inferred from knowledge of time-varying porpoise distributions. The model produces plausible patterns of population dynamics and matches well the age distribution of porpoises caught in by-catch. It estimates the effect of existing wind farms as a 10% reduction in population size when food recovers fast (after two days). Proposed new wind farms and ships do not result in further population declines. The population is however sensitive to variations in mortality resulting from by-catch and to the speed at which food recovers after being depleted. If food recovers slowly the effect of wind turbines becomes negligible, whereas ships are estimated to have a significant negative impact on the population. Annual by-catch rates ≥10% lead to monotonously decreasing populations and to extinction, and even the estimated by-catch rate from the adjacent area (approximately 4.1%) has a strong impact on the population. This suggests that conservation efforts should be more focused on reducing by-catch in commercial gillnet fisheries than on limiting the amount of anthropogenic noise. Individual-based models are unique in their ability to take account of the location and timing of disturbances and to show their likely effects on populations. The models also identify deficiencies in the existing database and can be used to set priorities for future field research.

Acoustic scattering : high frequency boundary element methods and unified transform methods

We describe some recent advances in the numerical solution of acoustic scattering problems. A major focus of the paper is the efficient solution of high frequency scattering problems via hybrid numerical-asymptotic boundary element methods. We also make connections to the unified transform method due to A. S. Fokas and co-authors, analysing particular instances of this method, proposed by J. A. De-Santo and co-authors, for problems of acoustic scattering by diffraction gratings.

Reducing noise associated with the Monte Carlo Independent Column Approximation for weather forecasting models

The Monte Carlo Independent Column Approximation (McICA) is a flexible method for representing subgrid-scale cloud inhomogeneity in radiative transfer schemes. It does, however, introduce conditional random errors but these have been shown to have little effect on climate simulations, where spatial and temporal scales of interest are large enough for effects of noise to be averaged out. This article considers the effect of McICA noise on a numerical weather prediction (NWP) model, where the time and spatial scales of interest are much closer to those at which the errors manifest themselves; this, as we show, means that noise is more significant. We suggest methods for efficiently reducing the magnitude of McICA noise and test these methods in a global NWP version of the UK Met Office Unified Model (MetUM). The resultant errors are put into context by comparison with errors due to the widely used assumption of maximum-random-overlap of plane-parallel homogeneous cloud. For a simple implementation of the McICA scheme, forecasts of near-surface temperature are found to be worse than those obtained using the plane-parallel, maximum-random-overlap representation of clouds. However, by applying the methods suggested in this article, we can reduce noise enough to give forecasts of near-surface temperature that are an improvement on the plane-parallel maximum-random-overlap forecasts. We conclude that the McICA scheme can be used to improve the representation of clouds in NWP models, with the provision that the associated noise is sufficiently small.

Separating heart and brain: on the reduction of physiological noise from multichannel functional near-infrared spectroscopy (fNIRS) signals

Objective. Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the in vivo assessment of functional activity of the cerebral cortex as well as in the field of brain–computer interface (BCI) research. A common challenge for the utilization of fNIRS in these areas is a stable and reliable investigation of the spatio-temporal hemodynamic patterns. However, the recorded patterns may be influenced and superimposed by signals generated from physiological processes, resulting in an inaccurate estimation of the cortical activity. Up to now only a few studies have investigated these influences, and still less has been attempted to remove/reduce these influences. The present study aims to gain insights into the reduction of physiological rhythms in hemodynamic signals (oxygenated hemoglobin (oxy-Hb), deoxygenated hemoglobin (deoxy-Hb)). Approach. We introduce the use of three different signal processing approaches (spatial filtering, a common average reference (CAR) method; independent component analysis (ICA); and transfer function (TF) models) to reduce the influence of respiratory and blood pressure (BP) rhythms on the hemodynamic responses. Main results. All approaches produce large reductions in BP and respiration influences on the oxy-Hb signals and, therefore, improve the contrast-to-noise ratio (CNR). In contrast, for deoxy-Hb signals CAR and ICA did not improve the CNR. However, for the TF approach, a CNR-improvement in deoxy-Hb can also be found. Significance. The present study investigates the application of different signal processing approaches to reduce the influences of physiological rhythms on the hemodynamic responses. In addition to the identification of the best signal processing method, we also show the importance of noise reduction in fNIRS data.

Twice erased: the silencing of feminisms in her noise

A cluster of three texts following a conference panel on the Her Noise research and exhibition project (2005 - present, curated by Lina Dzuverovic and Anne Hilde Neset) in 2013 held at the 'Women in Music' Conference in New York. The articles have been published in Volume 20 of Women and Music: A Journal of Gender and Culture: “Intimate Publics in the Her Noise Archive,” by Holly Ingleton “Twice Erased: The silencing of Feminisms in Her Noise,” by Lina Dzuverovic “Why Not Our Voices? by Cathy Lane

Acceptable noise levels for neonates in the neonatal intensive care unit

The study was a sound survey of naturally occurring noise in a metropolitan hospital NICU. The collected sound level samples were then compared to the noise standard recommended by the American Academy of Pediatrics. It was concluded that sound levels in the NICU exceed the standard and the standard does not have a proper foundation.

The relation between speech recognition in noise and the speech-evoked brainstem response in normal-hearing and hearing-impaired individuals

Little is known about the way speech in noise is processed along the auditory pathway. The purpose of this study was to evaluate the relation between listening in noise using the R-Space system and the neurophysiologic response of the speech-evoked auditory brainstem when recorded in quiet and noise in adult participants with mild to moderate hearing loss and normal hearing.

Characteristics of TMD noise analyzed by electrovibratography

Studying joint noise is an important parameter for diagnosing temporomandibular dysfunction. In this study, eight groups (n=9) were formed according to joint dysfunction classification, provided by employing vibration analysis equipment. Parameters for analyzing joint noise were: total vibration energy, peak amplitude, and peak frequency. Mouth opening range was also analyzed. Statistical analysis results for each parameter were significant at 1 %. Each analyzed group presented different noise characteristics. This allowed for inclusion of the groups within a determined value category. The patient group with normal condyle/disk relationship always presented the lowest values. The type of joint noise was characterized by analyzing total integral noise, peak amplitude, peak frequency, and mouth opening. Analyzing joint noise using electrovibratography suggests the type of joint dysfunction and may help to establish a diagnosis, as well as a treatment plan.

The search of a genetic basis for noise-induced hearing loss (NIHL)

Background and aim: Knowledge about the genetic factors responsible for noise-induced hearing loss (NIHL) is still limited. This study investigated whether genetic factors are associated or not to susceptibility to NIHL. Subjects and methods: The family history and genotypes were studied for candidate genes in 107 individuals with NIHL, 44 with other causes of hearing impairment and 104 controls. Mutations frequently found among deaf individuals were investigated (35delG, 167delT in GJB2, Delta(GJB6- D13S1830), Delta(GJB6- D13S1854) in GJB6 and A1555G in MT-RNR1 genes); allelic and genotypic frequencies were also determined at the SNP rs877098 in DFNB1, of deletions of GSTM1 and GSTT1 and sequence variants in both MTRNR1 and MTTS1 genes, as well as mitochondrial haplogroups. Results: When those with NIHL were compared with the control group, a significant increase was detected in the number of relatives affected by hearing impairment, of the genotype corresponding to the presence of both GSTM1 and GSTT1 enzymes and of cases with mitochondrial haplogroup L1. Conclusion: The findings suggest effects of familial history of hearing loss, of GSTT1 and GSTM1 enzymes and of mitochondrial haplogroup L1 on the risk of NIHL. This study also described novel sequence variants of MTRNR1 and MTTS1 genes.

Malassezia spp. in acoustic meatus of bats (Molossus molossus) of the Amazon region, Brazil

The yeasts of the Malassezia genus are opportunistic microorganisms and can cause human and animal infections. They are commonly isolated from the skin and auricular canal of mammalians, mainly dogs and cats. The present study was aimed to isolate Malassezia spp. from the acoustic meatus of bats (Molossus molossus) in the Montenegro region, `` Rondonia ``, Brazil. From a total of 30 bats studied Malassezia spp. were isolated in 24 (80%) animals, the breakdown by species being as follows (one Malassezia sp. per bat, N=24): 15 (62.5%) M. pachydermatis, 5 (20.8%) M. furfur, 3 (12.5%) M. globosa and 1 (4.2%) M. sympodialis. This study establishes a new host and anatomic place for Malassezia spp., as it presents the first report ever of the isolation of this genus of yeasts in the acoustic meatus of bats.

Low-Frequency Noise in Field-Effect Devices Functionalized With Dendrimer/Carbon-Nanotube Multilayers

Low-frequency noise in an electrolyte-insulator- semiconductor (EIS) structure functionalized with multilayers of polyamidoamine (PAMAM) dendrimer and single-walled carbon nanotubes (SWNT) is studied. The noise spectral density exhibits 1/f(gamma) dependence with the power factor of gamma approximate to 0.8 and gamma = 0.8-1.8 for the bare and functionalized EIS sensor, respectively. The gate-voltage noise spectral density is practically independent of the pH value of the solution and increases with increasing gate voltage or gate-leakage current. It has been revealed that functionalization of an EIS structure with a PAMAM/SWNTs multilayer leads to an essential reduction of the 1/f noise. To interpret the noise behavior in bare and functionalized EIS devices, a gate-current noise model for capacitive EIS structures based on an equivalent flatband-voltage fluctuation concept has been developed.

Shot Noise in a Spin-Diode Geometry

We apply the master equation technique to calculate shot noise in a system composed of single level quantum dot attached to a normal metal lead and to a ferromagnetic lead (NM-QD-FM). It is known that this system operates as a spin-diode, giving unpolarized currents for forward bias and polarized current for reverse bias. This effect is observed when only one electron can tunnel at a time through the dot, due to the strong intradot Coulomb interaction. We find that the shot noise also presents a signature of this spin-diode effect, with a super-Poissonian shot noise for forward and a sub-Poissonian shot noise for reverse bias voltages. The shot noise thus can provide further experimental evidence of the spin-rectification in the NM-QD-FM geometry.

Nonstationary feature extraction techniques for automatic classification of impact acoustic signals

Condition monitoring of wooden railway sleepers applications are generallycarried out by visual inspection and if necessary some impact acoustic examination iscarried out intuitively by skilled personnel. In this work, a pattern recognition solutionhas been proposed to automate the process for the achievement of robust results. Thestudy presents a comparison of several pattern recognition techniques together withvarious nonstationary feature extraction techniques for classification of impactacoustic emissions. Pattern classifiers such as multilayer perceptron, learning cectorquantization and gaussian mixture models, are combined with nonstationary featureextraction techniques such as Short Time Fourier Transform, Continuous WaveletTransform, Discrete Wavelet Transform and Wigner-Ville Distribution. Due to thepresence of several different feature extraction and classification technqies, datafusion has been investigated. Data fusion in the current case has mainly beeninvestigated on two levels, feature level and classifier level respectively. Fusion at thefeature level demonstrated best results with an overall accuracy of 82% whencompared to the human operator.