Speech Signal Enhancement in Cocktail Party Scenarios by Deep Learning based Virtual Sensing of Head-Mounted Microphones

The cocktail party effect refers to the human sense of hearing’s ability to pay attention to a single conversation while filtering out all other background noise. To mimic this human hearing ability for people with hearing loss, scientists integrate beamforming algorithms into the signal processing path of hearing aids or implants’ audio processors. Although these algorithms’ performance strongly depends on the number and spatial arrangement of the microphones, most devices are equipped with a small number of microphones mounted close to each other on the audio processor housing. We measured and evaluated the impact of the number and spatial arrangement of hearing aid or head-mounted microphones on the performance of the established Minimum Variance Distortionless Response beamformer in cocktail party scenarios. The measurements revealed that the optimal microphone placement exploits monaural cues (pinna-effect), is close to the target signal, and creates a large distance spread due to its spatial arrangement. However, this microphone placement is impractical for hearing aid or implant users, as it includes microphone positions such as on the forehead. To overcome microphones’ placement at impractical positions, we propose a deep virtual sensing estimation of the corresponding audio signals. The results of objective measures and a subjective listening test with 20 participants showed that the virtually sensed microphone signals significantly improved the speech quality, especially in cocktail party scenarios with low signal-to-noise ratios. Subjective speech quality was assessed using a 3-alternative forced choice procedure to determine which of the presented speech mixtures was most pleasant to understand. Hearing aid and cochlear implant (CI) users might benefit from the presented approach using virtually sensed microphone signals, especially in noisy environments

5,11,17,23-Tetra-tert-butyl-25,26,27,28-tetramethoxycalix[4]arene tetrahydrofuran solvate

The asymmetric unit of the title compound, C44H64O4·C4H8O, comprises two crystallographically independent calixarene mol-ecules, which display a partial cone conformation, and two tetrahydrofuran molecules. The crystal packing is stabilized by C - H⋯π contacts involving the meth-oxy groups, while the solvent mol-ecules are located in voids between the calixarene molecules. Two of the tert-butyl residues of each calixarene mol-ecule are disordered over two positions [0.74/0.26 (ring B), 0.71/0.29 (ring C), 0.77/0.23 (ring C′), 0.67/0.33 (ring D′)], resulting in bond distances that deviate from ideal values

Are Smartwatches a Suitable Tool to Monitor Noise Exposure for Public Health Awareness and Otoprotection?

Introduction and Objectives: Noise-induced hearing loss (NIHL) and tinnitus are common problems that can be prevented with hearing protection measures. Sound level meters and noise dosimeters enable to monitor and identify health-threatening occupational or recreational noise, but are limited in their daily application because they are usually difficult to operate, bulky, and expensive. Smartwatches, which are becoming increasingly available and popular, could be a valuable alternative to professional systems. Therefore, the aim of this study was to evaluate the applicability of smartwatches for accurate environmental noise monitoring. Methods: The A-weighted equivalent continuous sound pressure level (LAeq) was recorded and compared between a professional sound level meter and a popular smartwatch. Noise exposure was assessed in 13 occupational and recreational settings, covering a large range of sound pressure levels between 35 and 110 dBA. To assess measurement agreement, a Bland-Altman plot, linear regression, the intra-class correlation coefficient, and descriptive statistics were used. Results: Overall, the smartwatch underestimated the sound level meter measurements by 0.5 dBA (95% confidence interval [0.2, 0.8]). The intra-class correlation coefficient showed excellent agreement between the two devices (ICC = 0.99), ranging from 0.65 (music club) to 0.99 (concert) across settings. The smartwatch’s sampling rate decreased significantly with lower sound pressure levels, which could have introduced measurement inaccuracies in dynamic acoustic environments. Conclusions: The assessment of ambient noise with the tested smartwatch is sufficiently accurate and reliable to improve awareness of hazardous noise levels in the personal environment and to conduct exploratory clinical research. For professional and legally binding measurements, we recommend specialized sound level meters or noise dosimeters. In the future, smartwatches will play an important role in monitoring personal noise exposure and will provide a widely available and cost-effective measure for otoprotection

Poly–adenosine diphosphate–ribose polymerase inhibition for myocardial protection: Pathophysiologic and physiologic considerations

Plantilles de l’Institut Barcelona Esports, de l’Institut Municipal del Paisatge Urbà i la Qualitat de Vida, de l’Institut Municipal d'Informàtica, de l’Institut Municipal d'Hisenda, de l’Institut Municipal d'Educació, de l’Institut Municipal de Mercats, de l’Institut Municipal de Serveis Socials i de l’Institut Municipal de Persones amb Discapacita

5,11,17,23-Tetra-tert-butyl-25,26,27,28-tetra­methoxy­calix[4]arene dichloro­methane hemisolvate

In the title compound, C48H64O4·0.5CH2Cl2, both crystallographically independent calixarene mol­ecules display a partial cone conformation. Their crystal packing is stabilized by C—H⋯π contacts involving the meth­oxy groups. The solvent mol­ecule is located inter­stitially between two calixarene units with C—H⋯Cl contacts to meth­oxy and tert-butyl groups. One tert-butyl residue of each calixarene mol­ecule is disordered over two positions (occupancies 0.60/0.40 and 0.63/0.37), resulting in bond distances that deviate from ideal values. The tetra­mer calixarene mol­ecules present models with approximate non-crystallographic Cs symmetry

Semi-supervised LC/MS alignment for differential proteomics

Motivation: Mass spectrometry (MS) combined with high-performance liquid chromatography (LC) has received considerable attention for high-throughput analysis of proteomes. Isotopic labeling techniques such as ICAT [5,6] have been successfully applied to derive differential quantitative information for two protein samples, however at the price of significantly increased complexity of the experimental setup. To overcome these limitations, we consider a label-free setting where correspondences between elements of two samples have to be established prior to the comparative analysis. The alignment between samples is achieved by nonlinear robust ridge regression. The correspondence estimates are guided in a semi-supervised fashion by prior information which is derived from sequenced tandem mass spectra. Results: The semi-supervised method for finding correspondences was successfully applied to aligning highly complex protein samples, even if they exhibit large variations due to different biological conditions. A large-scale experiment clearly demonstrates that the proposed method bridges the gap between statistical data analysis and label-free quantitative differential proteomics. Availability: The software will be available on the website Contact: [email protected]