987 resultados para occupational noise


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Within Ireland, interest in strategically supporting young people’s participation in the arts has increased. Additionally, awareness of the Internet’s potential for promot- ing engagement with the arts has grown. Addressing national directives and local needs assessments, South Dublin County Council’s Arts Office initiated NOISE South Dublin (http://www.noisesouthdublin.com), an interactive Web site based on Australia Council’s NOISE project (http://www.noise.net), to promote the creative development of young people in the county. This article presents the practical chal- lenges and potential of youth arts Web-based programs for harnessing the creative engagement of youth. It concludes that the Internet is only useful if it expands online engagement offline.

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To obtain cm/s precision, stellar surface magneto-convection must be disentangled from observed radial velocities (RVs). In order to understand and remove the convective signature, we create Sun-as-a-star model observations based on a 3D magnetohydrodynamic solar simulation. From these Sun-as-a-star model observations, we find several line characteristics are correlated with the induced RV shifts. The aim of this campaign is to feed directly into future high precision RV studies, such as the search for habitable, rocky worlds, with forthcoming spectrographs such as ESPRESSO.

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Background

Chronic kidney disease is now regarded as a risk factor for cardiovascular disease. The impact of occupational or non-occupational physical activity (PA) on moderate decreases of renal function is uncertain.

Objectives

We aimed to identify the potential association of PA (occupational and leisure-time) on early decline of estimated glomerular filtration rate (eGFR) and to determine the potential mediating effect of PA on the relationship between eGFR and heart disease.

Methods

From the PRIME study analyses were conducted in 1058 employed men. Energy expended during leisure, work and commuting was calculated. Linear regression analyses were used to determine the link between types of PA and moderate decrements of eGFR determined with the KDIGO guideline at the baseline assessment. Cox proportional hazards analyses were used to explore the potential effect of PA on the relationship between eGFR and heart disease, ascertained during follow-up over 10 years.

Results

For these employed men, and after adjustment for known confounders of GFR change, more time spent sitting at work was associated with increased risk of moderate decline in kidney function, while carrying objects or being active at work was associated with decreased risk. In contrast, no significant link with leisure PA was apparent. No potential mediating effect of occupational PA was found for the relationship between eGFR and coronary heart disease.

Conclusion

Occupational PA (potential modifiable factors) could provide a dual role on early impairment of renal function, without influence on the relationship between early decrease of e-GFR and CHD risk.

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The implementation of a dipole antenna co-designed and monolithically integrated with a low noise amplifier (LNA) on low resistivity Si substrate (20 Omega . cm) manufactured in 0.35 mu m commercial SiGe HBT process with f(T)/f(max) of 170 GHz and 250 GHz is investigated theoretically and experimentally. An air gap is introduced between the chip and a reflective ground plane, leading to substantial improvements in efficiency and gain. Moreover, conjugate matching conditions between the antenna and the LNA are exploited, enhancing power transfer between without any additional matching circuit. A prototype is fabricated and tested to validate the performance. The measured 10-dB gain of the standalone LNA is centered at 58 GHz with a die size of 0.7 mm x 0.6 mm including all pads. The simulated results showed antenna directivity of 5.1 dBi with efficiency higher than 70%. After optimization, the co-designed LNA-Antenna chip with a die size of 3 mm x 2.8 mm was characterized in anechoic chamber environment. A maximum gain of higher than 12 dB was obtained.

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This paper presents a new approach to speech enhancement from single-channel measurements involving both noise and channel distortion (i.e., convolutional noise), and demonstrates its applications for robust speech recognition and for improving noisy speech quality. The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive noise. Second, we present an improved method for modeling noise for speech estimation. Third, we present an iterative algorithm which updates the noise and channel estimates of the corpus data model. In experiments using speech recognition as a test with the Aurora 4 database, the use of our enhancement approach as a preprocessor for feature extraction significantly improved the performance of a baseline recognition system. In another comparison against conventional enhancement algorithms, both the PESQ and the segmental SNR ratings of the LMS algorithm were superior to the other methods for noisy speech enhancement.

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This paper presents a new approach to single-channel speech enhancement involving both noise and channel distortion (i.e., convolutional noise). The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive noise. Second, we present an improved method for modeling noise. Third, we present an iterative algorithm for improved speech estimates. In experiments using speech recognition as a test with the Aurora 4 database, the use of our enhancement approach as a preprocessor for feature extraction significantly improved the performance of a baseline recognition system. In another comparison against conventional enhancement algorithms, both the PESQ and the segmental SNR ratings of the LMS algorithm were superior to the other methods for noisy speech enhancement. Index Terms: corpus-based speech model, longest matching segment, speech enhancement, speech recognition

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Background: Workplace sedentary behaviour is a priority target for health promotion. However, little is known about how to effect change. We aimed to explore desk-based office workers’ perceptions of factors that influenced sedentary behaviour at work and to explore the feasibility of using a novel mobile phone application to track their behaviours.

Methods: We invited office employees (n = 12) and managers (n = 2) in a software engineering company to participate in semi-structured interviews to explore perceived barriers and facilitators affecting workplace sedentary behaviour. We assessed participants’ sedentary behaviours using an accelerometer before and after they used a mobile phone application to record their activities at self-selected time intervals daily for 2 weeks. Interviews were analysed using a thematic framework.

Results: Software engineers (5 employees; 2 managers) were interviewed; 13 tested the mobile phone application; 8 returned feedback. Major barriers to reducing workplace sedentary behaviour included the pressure of ‘getting the job done’, the nature of their work requiring sitting at a computer, personal preferences for the use of time at and after work, and a lack of facilities, such as a canteen, to encourage moving from their desks. Facilitators for reduced sedentariness included having a definite reason to leave their desks, social interaction and relief of physical and mental symptoms of prolonged sitting. The findings were similar for participants with different levels of overall physical activity. Valid accelerometer data were tracked for four participants: all reduced their sedentary behaviour. Participants stated that recording data using the phone application added to their day’s work but the extent to which individuals perceived this as a burden varied and was counter-balanced by its perceived value in increasing awareness of sedentary behaviour. Individuals expressed a wish for flexibility in its configuration.

Conclusions: These findings indicate that employers’ and employees’ perceptions of the cultural context and physical environment of their work, as well as personal factors, must be considered in attempting to effect changes that reduce workplace sedentary behaviour. Further research should investigate appropriate individually tailored approaches to this challenge, using a framework of behaviour change theory which takes account of specific work practices, preferences and settings.

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It is shown that under certain conditions it is possible to obtain a good speech estimate from noise without requiring noise estimation. We study an implementation of the theory, namely wide matching, for speech enhancement. The new approach performs sentence-wide joint speech segment estimation subject to maximum recognizability to gain noise robustness. Experiments have been conducted to evaluate the new approach with variable noises and SNRs from -5 dB to noise free. It is shown that the new approach, without any estimation of the noise, significantly outperformed conventional methods in the low SNR conditions while retaining comparable performance in the high SNR conditions. It is further suggested that the wide matching and deep learning approaches can be combined towards a highly robust and accurate speech estimator.

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Experience continuously imprints on the brain at all stages of life. The traces it leaves behind can produce perceptual learning [1], which drives adaptive behavior to previously encountered stimuli. Recently, it has been shown that even random noise, a type of sound devoid of acoustic structure, can trigger fast and robust perceptual learning after repeated exposure [2]. Here, by combining psychophysics, electroencephalography (EEG), and modeling, we show that the perceptual learning of noise is associated with evoked potentials, without any salient physical discontinuity or obvious acoustic landmark in the sound. Rather, the potentials appeared whenever a memory trace was observed behaviorally. Such memory-evoked potentials were characterized by early latencies and auditory topographies, consistent with a sensory origin. Furthermore, they were generated even on conditions of diverted attention. The EEG waveforms could be modeled as standard evoked responses to auditory events (N1-P2) [3], triggered by idiosyncratic perceptual features acquired through learning. Thus, we argue that the learning of noise is accompanied by the rapid formation of sharp neural selectivity to arbitrary and complex acoustic patterns, within sensory regions. Such a mechanism bridges the gap between the short-term and longer-term plasticity observed in the learning of noise [2, 4-6]. It could also be key to the processing of natural sounds within auditory cortices [7], suggesting that the neural code for sound source identification will be shaped by experience as well as by acoustics.