Combined impacts of elevated CO2 and anthropogenic noise on European sea bass (Dicentrarchus labrax)

Ocean acidification (OA) and anthropogenic noise are both known to cause stress and induce physiological and behavioural changes in fish, with consequences for fitness. OA is also predicted to reduce the ocean's capacity to absorb low-frequency sounds produced by human activity. Consequently, anthropogenic noise could propagate further under an increasingly acidic ocean. For the first time, this study investigated the independent and combined impacts of elevated carbon dioxide (CO2) and anthropogenic noise on the behaviour of a marine fish, the European sea bass (Dicentrarchus labrax). In a fully factorial experiment crossing two CO2 levels (current day and elevated) with two noise conditions (ambient and pile driving), D. labrax were exposed to four CO2/noise treatment combinations: 400 µatm/ambient, 1000 µatm/ambient, 400 µatm/pile-driving, and 1000 µatm/pile driving. Pile-driving noise increased ventilation rate (indicating stress) compared with ambient noise conditions. Elevated CO2 did not alter the ventilation rate response to noise. Furthermore, there was no interaction effect between elevated CO2 and pile-driving noise, suggesting that OA is unlikely to influence startle or ventilatory responses of fish to anthropogenic noise. However, effective management of anthropogenic noise could reduce fish stress, which may improve resilience to future stressors.

Influence of road noise disturbances on black vulture nesting area: Case of "Cabeza de Hierro" state in Spanish Mediterranean Central Mountain

The real and potential road influence on soundscape is considered a relevant management aspect that can assess the negative effects of massive visitants on such sensitive species -that have been living for centuries in the area-. As a first approach to the study of human disturbances sound impact, acoustic engineering tools allow us to model noise pollution caused by the main road that crosses the state ?Cabeza de Hierro? (M-604). For these preliminary results we use the French method XPS 31-133, recommend at EU level. Noise emission levels in black vulture nesting area are analyzed to understand the influence of human activities on rural areas and road management on biodiversity conservation. This approach develops a useful tool to make compatible the public enjoyment of forest services such as recreation or landscape scenary, the conservation of biodiversity as well as a suitable social and economic activity level ?timber and firewood harvesting, industry?- at the region.

Noise Figure Measurement of Differential Amplifiers Using non-Ideal Baluns

This paper analyzes the noise and gain measurement of microwave differential amplifiers using two passive baluns. A general model of the baluns is considered, including potential losses and phase/amplitude unbalances. This analysis allows de-embedding the actual gain and noise performance of the isolated amplifier by using single-ended measurements of the cascaded system and baluns. Finally, measured results from two amplifier prototypes are used to validate the theoretical principles.

Reduction in Calculated Uncertainty of a Noise Map by Improving the Traffic Model Data Through Two Phases

The influence of applying European default traffic values to the making of a noise map was evaluated in a typical environment like Palma de Mallorca. To assess these default traffic values, a first model has been created and compared with measured noise levels. Subsequently a second traffic model, improving the input data used for the first one, has been created and validated according to the deviations. Different methodologies were also examined for collecting model input data that would be of higher quality, by analysing the improvement generated in the reduction in the uncertainty of the noise map introduced by the road traffic noise emission

Energy-Entropy-Momentum integration of discrete thermo-visco-elastic dynamics.

A novel time integration scheme is presented for the numerical solution of the dynamics of discrete systems consisting of point masses and thermo-visco-elastic springs. Even considering fully coupled constitutive laws for the elements, the obtained solutions strictly preserve the two laws of thermo dynamics and the symmetries of the continuum evolution equations. Moreover, the unconditional control over the energy and the entropy growth have the effect of stabilizing the numerical solution, allowing the use of larger time steps than those suitable for comparable implicit algorithms. Proofs for these claims are provided in the article as well as numerical examples that illustrate the performance of the method.

Effectiveness of resilient wheels in reducing noise and vibrations

This study focuses on the effectiveness of resilient wheels in reducing railway noise and vibrations, and compares the effectiveness of three types of wheels. The finite elements method has been used to characterise the vibratory behaviour of these wheels. The model has been excited with a realistic spectrum of vertical track irregularities, and a spectral analysis has been carried out. Results have been post-processed in order to estimate the sound power emitted. These calculations have been used to assess the effectiveness of the resilient wheel designs in reducing noise emitted to the environment and in propagating structural vibrations.

Comparison of vibration and rolling noise emission of resilient and solid monobloc railway wheels in underground lines

Flat or worn wheels rolling on rough or corrugated tracks can provoke airborne noise and ground-borne vibration, which can be a serious concern for nearby neighbours of urban rail transit lines. Among the various treatments used to reduce vibration and noise, resilient wheels play an important role. In conventional resilient wheels, a slightly prestressed V­shaped rubber ring is mounted between the steel wheel centre and tyre. The elastic layer enhances rolling noise and vibration suppression, as well as impact reduction on the track. In this paper the effectiveness of resilient wheels in underground lines, in comparison to monobloc ones, is assessed. The analysed resilient wheel is able to carry greater loads than standard resilient wheels used for light vehicles. It also presents a greater radial resiliency and a higher axial stiffness than conventional V­wheels. The finite element method was used in this study. A quarter car model was defined, in which the wheelset was modelled as an elastic body. Several simulations were performed in order to assess the vibrational behaviour of elastic wheels, including modal, harmonic and random vibration analysis, the latter allowing the introduction of realistic vertical track irregularities, as well as the influence of the running speed. Due to numerical problems some simplifications were needed. Parametric variations were also performed, in which the sensitivity of the whole system to variations of rubber prestress and Poisson’s ratio of the elastic material was assessed.Results are presented in the frequency domain, showing a better performance of the resilient wheels for frequencies over 200 Hz. This result reveals the ability of the analyzed design to mitigate rolling noise, but not structural vibrations, which are primarily found in the lower frequency range.

Quantitative evaluation of artifact removal in real magnetoencephalogram signals with blind source separation

The magnetoencephalogram (MEG) is contaminated with undesired signals, which are called artifacts. Some of the most important ones are the cardiac and the ocular artifacts (CA and OA, respectively), and the power line noise (PLN). Blind source separation (BSS) has been used to reduce the influence of the artifacts in the data. There is a plethora of BSS-based artifact removal approaches, but few comparative analyses. In this study, MEG background activity from 26 subjects was processed with five widespread BSS (AMUSE, SOBI, JADE, extended Infomax, and FastICA) and one constrained BSS (cBSS) techniques. Then, the ability of several combinations of BSS algorithm, epoch length, and artifact detection metric to automatically reduce the CA, OA, and PLN were quantified with objective criteria. The results pinpointed to cBSS as a very suitable approach to remove the CA. Additionally, a combination of AMUSE or SOBI and artifact detection metrics based on entropy or power criteria decreased the OA. Finally, the PLN was reduced by means of a spectral metric. These findings confirm the utility of BSS to help in the artifact removal for MEG background activity.

Contribution of the noise radiated by a single vehicle to the road traffic noise

El ruido del tráfico rodado supone aproximadamente la mitad del ruido global ambiental. Las técnicas de control de ruido habitual en emisión (límites de emisión de vehículos) e inmisión (barreras acústicas, doble acristalamiento) no han sido suficientes para disminuir significativamente las molestias por el tráfico rodado en las últimas tres décadas. El efecto positivo de estas técnicas de control ha sido contrarrestado por el aumento de la densidad del tráfico. Por otra parte, la molestia del ruido del tráfico está altamente correlacionada con los niveles máximos de ruido (MNL), producidos por lo general por conductores agresivos. Sin embargo, los sistemas actuales de medición de ruido de tráfico se basan en una valoración global, por lo que no son capaces de discriminar entre los conductores silenciosos y ruidosos. Por lo tanto, en esta tesis se propone un sistema de medida de ruido en el campo cercano, que es capaz de medir la contribución de cada vehículo individual al ruido del tráfico rodado, permitiendo la detección de los conductores ruidosos. Este trabajo describe también una combinación de investigaciones analíticas y experimentales para la identificación de los conductores responsables de la generación de niveles máximos de ruido. El sistema se basa en dos micrófonos embarcados, uno para el ruido del motor y otro para el ruido de rodadura. Con el fin de relacionar estas mediciones de campo cercano con el ruido de los vehículos radiado al campo lejano, se desarrolla un procedimiento completo para la extrapolación del ruido medido por los micrófonos de campo próximo a las posiciones de campo lejano, usando una combinación de predicción analítica y mediciones experimentales. Las correcciones para los niveles extrapolados se deben a factores atmosféricos, al término de divergencia esférica y a las condiciones de absorción de la superficie de propagación. Para el micrófono situado próximo al motor, es necesario también caracterizar las propiedades acústicas del capó del motor. Ambos niveles de ruido se extrapolan de forma independiente a la posición de campo lejano, donde se realiza una comparación entre la predicción y mediciones para confirmar que la metodología es fiable para estimar el impacto a distancia del ruido de tráfico

Cross-entropy optimization for scaling factors of a fuzzy controller: a see-and-avoid approach for unmanned aerial systems

The Cross-Entropy (CE) is an efficient method for the estimation of rare-event probabilities and combinatorial optimization. This work presents a novel approach of the CE for optimization of a Soft-Computing controller. A Fuzzy controller was designed to command an unmanned aerial system (UAS) for avoiding collision task. The only sensor used to accomplish this task was a forward camera. The CE is used to reach a near-optimal controller by modifying the scaling factors of the controller inputs. The optimization was realized using the ROS-Gazebo simulation system. In order to evaluate the optimization a big amount of tests were carried out with a real quadcopter.

Application of postprocessing techniques methods for noise reduction in cylindrical near field antenna measurements

Three different methods to reduce the noise power in the far-field pattern of an antenna when it is measured in a cylindrical near field system are presented and compared. The first one is based on a modal filtering while the other two are based on spatial filtering, either on an antenna plane or either on a cylinder of smaller radius. Simulated and measured results will be presented.

Signal-to-noise ratio of the MEG signal after preprocessing

Background Magnetoencephalography (MEG) provides a direct measure of brain activity with high combined spatiotemporal resolution. Preprocessing is necessary to reduce contributions from environmental interference and biological noise. New method The effect on the signal-to-noise ratio of different preprocessing techniques is evaluated. The signal-to-noise ratio (SNR) was defined as the ratio between the mean signal amplitude (evoked field) and the standard error of the mean over trials. Results Recordings from 26 subjects obtained during and event-related visual paradigm with an Elekta MEG scanner were employed. Two methods were considered as first-step noise reduction: Signal Space Separation and temporal Signal Space Separation, which decompose the signal into components with origin inside and outside the head. Both algorithm increased the SNR by approximately 100%. Epoch-based methods, aimed at identifying and rejecting epochs containing eye blinks, muscular artifacts and sensor jumps provided an SNR improvement of 5–10%. Decomposition methods evaluated were independent component analysis (ICA) and second-order blind identification (SOBI). The increase in SNR was of about 36% with ICA and 33% with SOBI. Comparison with existing methods No previous systematic evaluation of the effect of the typical preprocessing steps in the SNR of the MEG signal has been performed. Conclusions The application of either SSS or tSSS is mandatory in Elekta systems. No significant differences were found between the two. While epoch-based methods have been routinely applied the less often considered decomposition methods were clearly superior and therefore their use seems advisable.

Evaluation, energy optimization, and spectrum analysis of an artificial noise technique to improve CWSN security

This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number of packets transmitted by the network and the active period of the nodes increase. Security evaluation demonstrates that these techniques are effective against eavesdropper attacks, but also optimization allows for the implementation of these approaches in low-resource networks such as Cognitive Wireless Sensor Networks. In this work, the scenario is formally modeled and the optimization according to the simulation results and the impact analysis over the frequency spectrum are presented.

Using the Cross-Entropy Method for Control Optimization: A Case Study of See-and-Avoid on Unmanned Aerial Vehicles

This paper presents an adaptation of the Cross-Entropy (CE) method to optimize fuzzy logic controllers. The CE is a recently developed optimization method based on a general Monte-Carlo approach to combinatorial and continuous multi-extremal optimization and importance sampling. This work shows the application of this optimization method to optimize the inputs gains, the location and size of the different membership functions' sets of each variable, as well as the weight of each rule from the rule's base of a fuzzy logic controller (FLC). The control system approach presented in this work was designed to command the orientation of an unmanned aerial vehicle (UAV) to modify its trajectory for avoiding collisions. An onboard looking forward camera was used to sense the environment of the UAV. The information extracted by the image processing algorithm is the only input of the fuzzy control approach to avoid the collision with a predefined object. Real tests with a quadrotor have been done to corroborate the improved behavior of the optimized controllers at different stages of the optimization process.