Exposure to loud sound (acoustic overexposure; AOE) induces hearing loss and damages cellular structures at multiple locations in the auditory pathway. Whether AOE can also induce changes in myelin sheaths of the auditory nerve (AN) is an important issue particularly because these changes can be responsible for impaired action potential propagation along the AN. Here we investigate the effects of AOE on morphological and electrophysiological features of the centrally directed part of the rat AN projecting from the cochlear spiral ganglion to brainstem cochlear nuclei. Using electron microscopy and immunocytochemistry, we show that AOE elongates the AN nodes of Ranvier and triggers notable perinodal morphological changes. Compound action potential recordings of the AN coupled to biophysical modeling demonstrated that these nodal and perinodal structural changes were associated with decreased conduction velocity and conduction block. Furthermore, AOE decreased the number of release sites in the cochlear nuclei associated with the reduced amplitudes of EPSCs evoked by AN stimulation. In conclusion, AN dysmyelination may be of fundamental importance in auditory impairment following exposure to loud sound.
The objective of the EU-funded CLEVER Project (Compact Low Emission VEhicle for uRban transport) is the design and development of a novel two-seat vehicle for individual urban transport providing car-like levels of comfort, safety and convenience with the lower emissions, noise levels and road footprints of motorcycles. A narrow three-wheeled tilting vehicle has been identified as the best method of achieving these goals. One problem with vehicles with a narrow track is the unstable roll moment created when cornering. To solve this issue, the vehicle's centre of gravity is moved towards the centre of the corner by tilting the vehicle in a similar manner to that of a motorcycle. An active tilting system using hydraulic actuation has been employed, allowing for car-like controls. A prototype vehicle has been built to test this active tilting system. Initial testing revealed that while basic steady state handling was good, transient response required improvement. The evidence indicating this poor response is examined, and the necessary methods employed within the control system to solve the issue are discussed. Improved results are presented following an increase in the system gain. The effects of different filter cutoff frequencies on the objective and subjective vehicle handling characteristics is also investigated and presented here. It is shown that when designing a three-wheeled tilting vehicle with the arrangement used in CLEVER, safe handling can only be achieved at the expense of fast tilt response. This is a result of fundamental limitations of the vehicle design.
Knowledge spillovers occur when a firm researches a new technology and that technology is adapted or adopted by another firm, resulting in a social value of the technology that is larger than the initially predicted private value. As a result, firms systematically under-invest in research compared with the socially optimal investment strategy. Understanding the level of underinvestment, as well as policies to correct it, is an area of active economic research. In this paper, we develop a new model of spillovers, taking inspiration from the available microeconomic data. We prove existence and uniqueness of solutions to the model, and we conduct some initial simulations to understand how indirect spillovers contribute to the productivity of a sector.
We demonstrate the classification of common motions of held objects using the harmonic micro-Doppler signatures scattered from harmonic radio-frequency tags. Harmonic tags capture incident signals and retransmit at harmonic frequencies, making them easier to distinguish from clutter. We characterize the motion of tagged handheld objects via the time-varying frequency shift of the harmonic signals (harmonic Doppler). With complex micromotions of held objects, the time-frequency response manifests complex micro-Doppler signatures that can be used to classify the motions. We developed narrow-band harmonic tags at 2.4/4.8 GHz that support frequency scalability for multi-tag operation, and a harmonic radar system to transmit a 2.4 GHz continuous-wave signal and receive the scattered 4.8 GHz harmonic signal. Experiments were conducted to mimic four common motions of held objects from 35 subjects in a cluttered indoor environment. A 7-layer convolutional neural network (CNN) multi-label classifier was developed and obtained a real time classification accuracy of 94.24%, with a response time of 2 seconds per sample with a data processing latency of less than 0.5 seconds.
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