Complex statistics and diffusion in nonlinear disordered particle chains.

We investigate dynamically and statistically diffusive motion in a Klein-Gordon particle chain in the presence of disorder. In particular, we examine a low energy (subdiffusive) and a higher energy (self-trapping) case and verify that subdiffusive spreading is always observed. We then carry out a statistical analysis of the motion, in both cases, in the sense of the Central Limit Theorem and present evidence of different chaos behaviors, for various groups of particles. Integrating the equations of motion for times as long as 10(9), our probability distribution functions always tend to Gaussians and show that the dynamics does not relax onto a quasi-periodic Kolmogorov-Arnold-Moser torus and that diffusion continues to spread chaotically for arbitrarily long times

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

Enzymatic evaluation of renal damage caused by different therapeutic procedures for kidney stone disease

In an attempt to evaluate renal injury relative to open surgery, percutaneous nephrolithotripsy (PCN) and extracorporeal shock wave lithotripsy (ESWL) were studied in 52 patients with renal calculus disease. Preoperative and postoperative urinary levels of N-acetyl-glycosaminidase (NAG), a sensitive marker of renal tubular damage, were studied. No significant changes were noted in posttreatment urinary NAG values among patients who underwent ESWL or PCN. Although statistically nonsignificant, a constant mild increase of urinary NAG was observed after PCN, that has to be evaluated with long-term follow-up studies. The shock wave number or power in cases treated with ESWL as well as the number of renal punctures in the PCN group did not change the effect on renal tubular function. Diabetics and patients with chronic renal disease treated by ESWL did not show any significant change in posttreatment urinary NAG levels. In contrast to that, all patients treated by open surgery had significant, intense and prolonged increase of the postoperative NAG values, especially those treated by ischaemic nephrolithotomy. Comparing the three different therapeutic modalities, open surgical procedures had the most significant effect on renal function and this difference was statistically significant. We therefore suggest that ESWL does not endanger renal function, while open surgery must be reserved for selected cases. © 1995 Akadémiai Kiadó

Deep neural networks for dynamic range compression in mastering applications

The process of audio mastering often, if not always, includes various audio signal processing techniques such as frequency equalisation and dynamic range compression. With respect to the genre and style of the audio content, the parameters of these techniques are controlled by a mastering engineer, in order to process the original audio material. This operation relies on musical and perceptually pleasing facets of the perceived acoustic characteristics, transmitted from the audio material under the mastering process. Modelling such dynamic operations, which involve adaptation regarding the audio content, becomes vital in automated applications since it significantly affects the overall performance. In this work we present a system capable of modelling such behaviour focusing on the automatic dynamic range compression. It predicts frequency coefficients which allow the dynamic range compression, via a trained deep neural network, and applies them to unmastered audio sign al served as input. Both dynamic range compression and the prediction of the corresponding frequency coefficients take place inside the time-frequency domain, using magnitude spectra acquired from a critical band filter bank, similar to human's peripheral auditory system. Results from conducted listening tests, incorporating professional music producers and audio mastering engineers, demonstrate on average an equivalent performance compared to professionally mastered audio content. Improvements were also observed, when compared to relevant and commercial software

Memory requirement reduction of deep neural networks for field programmable gate arrays using low-bit quantization of parameters

Effective employment of deep neural networks (DNNs) in mobile devices and embedded systems, like field programmable gate arrays, is hampered by requirements for memory and computational power. In this paper we propose a method that employs a non-uniform fixed-point quantization and a virtual bit shift (VBS) to improve the accuracy of the quantization of the DNN weights. We evaluate our method in a speech enhancement application, where a fully connected DNN is used to predict the clean speech spectrum from the input noisy speech spectrum. A DNN is optimized, its memory requirement is calculated, and its performance is evaluated using the short-time objective intelligibility (STOI) metric. The application of the low-bit quantization leads to a 50% reduction of the DNN memory requirement while the STOI performance drops only by 2.7%

Close miking empirical practice verification: A source separation approach

Close miking represents a widely employed practice of placing a microphone very near to the sound source in order to capture more direct sound and minimize any pickup of ambient sound, including other, concurrently active sources. It is used by the audio engineering community for decades for audio recording, based on a number of empirical rules that were evolved during the recording practice itself. But can this empirical knowledge and close miking practice be systematically verified? In this work we aim to address this question based on an analytic methodology that employs techniques and metrics originating from the sound source separation evaluation field. In particular, we apply a quantitative analysis of the source separation capabilities of the close miking technique. The analysis is applied on a recording dataset obtained at multiple positions of a typical musical hall, multiple distances between the microphone and the sound source multiple microphone types and multiple level differences between the sound source and the ambient acoustic component. For all the above cases we calculate the Source to Interference Ratio (SIR) metric. The results obtained clearly demonstrate an optimum close-miking performance that matches the current empirical knowledge of professional audio recording

Consumer Responses to SMS Advertising: Antecedents and Consequences

Mobile phone advertisements, in the form of text messages (SMS, or short message service), have been recognized as an important form of product promotion. The purpose of this paper is to investigate factors that influence the effectiveness of SMS advertising by using a hierarchy of effects approach. We employ a simulated experiment with 736 respondents to examine how consumers react to SMS advertisements and identify factors that influence their attitude toward the ad, their attitude toward the brand, and their purchase intention. Perceived ad credibility, attitude toward mobile advertising, message appeal, argument quality, incentive, product involvement, and interactivity were found to be antecedents of the attitude toward the ad. Moreover, there is a clear link between attitude and behavioral intention. The study is among the first to provide an experimental based assessment and a unified model linking consumer attitudes toward mobile text ads with brand attitudes and purchase intentions