A database and digital signal processing framework for the perceptual analysis of voice quality

Bermúdez de Alvear RM, Corral J, Tardón LJ, Barbancho AM, Fernández Contreras E, Rando Márquez S, Martínez-Arquero AG, Barbancho I. A database and digital signal processing framework for the perceptual analysis of voice quality. Pan European Voice Conferenc: PEVOC 11 Abstract Book. Aug. 31-Sept.2, 2015.Introduction. Clinical assessment of dysphonia relies on perceptual as much as instrumental methods of analysis [1]. The perceptual auditory analysis is potentially subject to several internal and external sources of bias [2]. Furthermore acoustic analyses which have been used to objectively characterize pathological voices are likely to be affected by confusion variables such as the signal processing or the hardware and software specifications [3]. For these reasons the poor correlation between perceptual ratings and acoustic measures remains to be a controversial matter [4]. The availability of annotated databases of voice samples is therefore of main importance for clinical and research purposes. Databases to perform digital processing of the vocal signal are usually built from English speaking subjects’ sustained vowels [5]. However phonemes vary from one language to another and to the best of our knowledge there are no annotated databases with Spanish sustained vowels from healthy or dysphonic voices. This work shows our first steps to fill in this gap. For the aim of aiding clinicians and researchers in the perceptual assessment of voice quality a two-fold objective was attained. On the one hand a database of healthy and disordered Spanish voices was developed; on the other an automatic analysis scheme was accomplished on the basis of signal processing algorithms and supervised learning machine techniques. Material and methods. A preliminary annotated database was created with 119 recordings of the sustained Spanish /a/; they were perceptually labeled by three experienced experts in vocal quality analysis. It is freely available under Links in the ATIC website (www.atic.uma.es). Voice signals were recorded using a headset condenser cardioid microphone (AKG C-544 L) positioned at 5 cm from the speaker’s mouth commissure. Speakers were instructed to sustain the Spanish vowel /a/ for 4 seconds. The microphone was connected to a digital recorder Edirol R-09HR. Voice signals were digitized at 16 bits with 44100 Hz sampling rate. Afterwards the initial and last 0.5 second segments were cut and the 3 sec. mid portion was selected for acoustic analysis. Sennheiser HD219 headphones were used by judges to perceptually evaluate voice samples. To label these recordings raters used the Grade-Roughness-Breathiness (GRB) perceptual scale which is a modified version of the original Hirano’s GRBAS scale, posteriorly modified by Dejonckere et al., [6]. In order to improve intra- and inter-raters’ agreement two types of modifications were introduced in the rating procedure, i.e. the 0-3 points scale resolution was increased by adding subintervals to the standard 0-3 intervals, and judges were provided with a written protocol with explicit definitions about the subintervals boundaries. By this way judges could compensate for the potential instability that might occur in their internal representations due to the perceptual context influence [7]. Raters’ perceptual evaluations were simultaneously performed by means of connecting the Sennheiser HD219 headphones to a multi-channel headphone preamp Behringer HA4700 Powerplay Pro-XL. The Yin algorithm [8] was selected as initial front-end to identify voiced frames and extract their fundamental frequency. For the digital processing of voice signals some conventional acoustic parameters [6] were selected. To complete the analysis the Mel-Frequency Cepstral Coefficients (MFCC) were further calculated because they are based on the auditory model and they are thus closer to the auditory system response than conventional features. Results. In the perceptual evaluation excellent intra-raters agreement and very good inter-raters agreement were achieved. During the supervised machine learning stage some conventional features were found to attain unexpected low performance in the classification scheme selected. Mel Frequency Cepstral Coefficients were promising for assorting samples with normal or quasi-normal voice quality. Discussion and conclusions. Despite it is still small and unbalanced the present annotated data base of voice samples can provide a basis for the development of other databases and automatic classification tools. Other authors [9, 10, 11] also found that modeling the auditory non-linear response during signal processing can help develop objective measures that better correspond with perceptual data. However highly disordered voices classification remains to be a challenge for this set of features since they cannot be correctly assorted by either conventional variables or the auditory model based measures. Current results warrant further research in order to find out the usability of other types of voice samples and features for the automatic classification schemes. Different digital processing steps could be used to improve the classifiers performance. Additionally other types of classifiers could be taken into account in future studies. Acknowledgment. This work was funded by the Spanish Ministerio de Economía y Competitividad, Project No. TIN2013-47276-C6-2-R has been done in the Campus de Excelencia Internacional Andalucía Tech, Universidad de Málaga. References [1] Carding PN, Wilson JA, MacKenzie K, Deary IJ. Measuring voice outcomes: state of the science review. The Journal of Laryngology and Otology 2009;123,8:823-829. [2] Oates J. Auditory-perceptual evaluation of disordered voice quality: pros, cons and future directions. Folia Phoniatrica et Logopaedica 2009;61,1:49-56. [3] Maryn et al. Meta-analysis on acoustic voice quality measures. J Acoust Soc Am 2009; 126, 5: 2619-2634. [4] Vaz Freitas et al. Correlation Between Acoustic and Audio-Perceptual Measures. J Voice 2015;29,3:390.e1 [5] “Multi-Dimensional Voice Program (MDVP) Model 5105. Software Instruction Manual”, Kay PENTAX, A Division of PENTAX Medical Company, 2 Bridgewater Lane, Lincoln Park, NJ 07035-1488 USA, November 2007. [6] Dejonckere PH, Bradley P, Clemente P, Cornut G, Crevier-Buchman L, Friedrich G, Van De Heyning P, Remacle M, Woisard V. A basic protocol for functional assessment of voice pathology, especially for investigating the efficacy of (phonosurgical) treatments and evaluating new assessment techniques. Guideline elaborated by the Comm. on Phoniatrics of the European Laryngological Society (ELS). Eur Arch Otorhinolaryngol 2001;258:77–82. [7] Kreiman et al. Voice Quality Perception. J Speech Hear Res 1993;36:21-4 [8] De Cheveigné A, Kawahara H. YIN, a fundamental frequency estimator for speech and music. J. Acoust. Soc. Amer. 202; 111,4:1917. [9] Shrivastav et al. Measuring breathiness. J Acoust Soc Am 2003;114,4:2217-2224. [10] Saenz-Lechon et al. Automatic Assessment of voice quality according to the GRBAS scale. Eng Med Biol Soc Ann 2006;1:2478-2481. [11] Fredouille et al. Back-and-forth methodology for objective voice quality assessment: from/to expert knowledge to/from automatic classification of dysphonia. EURASIP J Appl Si Pr 2009.Campus de Excelencia Internacional Andalucía Tech, Universidad de Málaga. Ministerio de Economía y Competitividad, Projecto No. TIN2013-47276-C6-2-R

Improving drug discovery using a neural networks based parallel scoring function

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology named BINDSURF that scans the whole protein surface to find new hotspots, where ligands might potentially interact with, and which is implemented in massively parallel Graphics Processing Units, allowing fast processing of large ligand databases. BINDSURF can thus be used in drug discovery, drug design, drug repurposing and therefore helps considerably in clinical research. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to solve this problem, we propose a novel approach where neural networks are trained with databases of known active (drugs) and inactive compounds, and later used to improve VS predictions.This work has been jointly supported by the Fundación Séneca (Agencia Regional de Ciencia y Tecnología de la Región de Murcia) under grant 15290/PI/2010, by the Spanish MINECO and the European Commission FEDER funds under grants TIN2009-14475-C04 and TIN2012-31345, and by the Catholic University of Murcia (UCAM) under grant PMAFI/26/12. This work was partially supported by the computing facilities of Extremadura Research Centre for Advanced Technologies (CETA-CIEMAT), funded by the European Regional Development Fund (ERDF). CETA-CIEMAT belongs to CIEMAT and the Government of Spain

CREB-binding protein (CBP) gene family regulates planarian survival and stem cell differentiation

In developmental biology, the regulation of stem cell plasticity and differentiation remains an open question. CBP(CREB-binding protein)/p300 is a conserved gene family that functions as a transcriptional co-activator and plays important roles in a wide range of cellular processes, including cell death, the DNA damage response, and tumorigenesis. The acetyl transferase activity of CBPs is particularly important, as histone and non-histone acetylation results in changes in chromatin architecture and protein activity that affect gene expression. Many studies have described the conserved functions of CBP/p300 in stem cell proliferation and differentiation. The planarian Schmidtea mediterranea is an excellent model for the in vivo study of the molecular mechanisms underlying stem cell differentiation during regeneration. However, how this process is regulated genetically and epigenetically is not well-understood yet. We identified 5 distinct Smed-cbp genes in S. mediterranea that show different expression patterns. Functional analyses revealed that Smed-cbp-2 appears to be essential for stem cell maintenance. On the other hand, the silencing of Smed-cbp-3 resulted in the growth of blastemas that were apparently normal, but remained largely unpigmented and undifferentiated. Smed-cbp-3 silencing also affected the differentiation of several cell lineages including neural, epidermal, digestive, and excretory cell types. Finally, we analysed the predicted interactomes of CBP-2 and CBP-3 as an initial step to better understand their functions in planarian stem cell biology. Our results indicate that planarian cbp genes play key roles in stem cell maintenance and differentiation

Can activation of NRF2 be a strategy against COVID-19?

Acute respiratory distress syndrome (ARDS) caused by SARS-CoV-2 is largely the result of a dysregulated host response, followed by damage to alveolar cells and lung fibrosis. Exacerbated proinflammatory cytokines release (cytokine storm) and loss of T lymphocytes (leukopenia) characterize the most aggressive presentation. We propose that a multifaceted anti-inflammatory strategy based on pharmacological activation of nuclear factor erythroid 2 p45-related factor 2 (NRF2) can be deployed against the virus. The strategy provides robust cytoprotection by restoring redox and protein homeostasis, promoting resolu-tion of inflammation, and facilitating repair. NRF2 activators such as sulforaph-ane and bardoxolone methyl are already in clinical trials. The safety and efficacy information of these modulators in humans, together with their well -documented cytoprotective and anti-inflammatory effects in preclinical models, highlight the potential of this armamentarium for deployment to the battlefield against COVID-19We are grateful to the Biotechnology and Biological Sciences Research Council (BB/L01923X/1), Tenovus Scotland (T17/14), Cancer Research UK (C20953/A18644), the Autonomous Community of Madrid (grant B2017/BMD-3827), the 'Tatiana de Guzman el Bueno Foundation' (P-024-FTPGB 2018), and the European Regional Development Fund, Competitiveness Operational Program 2014–2020 (P_37_732/2016; REDBRAIN) for funding our researc

Developing models for future real-time platforms: Virtual simulation and design of new components and systems for aircraft and remotely piloted aircraft systems

In the development of electrified and other vehicle systems, the modelling and simulation of the vehicle is very important. With these tools the preliminary design, as well as later detailed studies of the systems developed, allow engineers to spend less time on each phase of their projects or address them with an integrated approach. In addition, this integrated approach provides the possibility of building hardware-in-the loop models with all the components required. This vehicle modelling and simulation has gained more interest with the increasing use of a wide variety of RPAS, ranging from light weight micro aircraft to large vehicles of various tons. For this reason, the previously-described building tools are the final objective of the developing models to be used in real-time platform projects. The first step presented in this paper is to build a simulator that reproduces the behaviour of a selected aircraft and validate it. This paper presents the study of the performances and behaviour of an OPV used to validate the simulator developed later. At the end, some preliminary tests and estimations of the performances for the selected OPV with an electric motor are presented

SARS-CoV-2 viral load analysis at low and high altitude: A case study from Ecuador

SARS-CoV-2 has spread throughout the world, including remote areas such as those located at high altitudes. There is a debate about the role of hypobaric hypoxia on viral transmission and COVID-19 incidence. A descriptive cross-sectional analysis of SARS-CoV-2 infection and viral load among patients living at low (230 m) and high altitude (3800 m) in Ecuador was completed. Within these two communities, the total number of infected people at the time of the study was 108 cases (40.3%). The COVID-19 incidence proportion at low altitude was 64% while at high altitude was 30.3%. The mean viral load from those patients who tested positive was 3,499,184 copies/mL (SD = 23,931,479 copies/mL). At low altitude (Limoncocha), the average viral load was 140,223.8 copies/mL (SD = 990,840.9 copies/mL), while for the high altitude group (Oyacachi), the mean viral load was 6,394,789 copies/mL (SD = 32,493,469 copies/mL). We found no statistically significant differences when both results were compared (p = 0.056). We found no significant differences across people living at low or high altitude; however, men and younger populations had higher viral load than women older populations, respectivel

Conditional BDNF delivery from astrocytes rescues memory deficits, spine density and synaptic properties in the 5xFAD mouse model of Alzheimer disease

It has been well documented that neurotrophins, including brain-derived neurotrophic factor (BDNF), are severely affected in Alzheimer's disease (AD), but their administration faces a myriad of technical challenges. Here we took advantage of the early astrogliosis observed in an amyloid mouse model of AD (5xFAD) and used it as an internal sensor to administer BDNF conditionally and locally. We first demonstrate the relevance of BDNF release from astrocytes by evaluating the effects of coculturing WT neurons and BDNF-deficient astrocytes. Next, we crossed 5xFAD mice with pGFAP:BDNF mice (only males were used) to create 5xFAD mice that overexpress BDNF when and where astrogliosis is initiated (5xF:pGB mice). We evaluated the behavioral phenotype of these mice. We first found that BDNF from astrocytes is crucial for dendrite outgrowth and spine number in cultured WT neurons. Double-mutant 5xF:pGB mice displayed improvements in cognitive tasks compared with 5xFAD littermates. In these mice, there was a rescue of BDNF/TrkB downstream signaling activity associated with an improvement of dendritic spine density and morphology. Clusters of synaptic markers, PSD-95 and synaptophysin, were also recovered in 5xF:pGB compared with 5xFAD mice as well as the number of presynaptic vesicles at excitatory synapses. Additionally, experimentally evoked LTP in vivo was increased in 5xF:pGB mice. The beneficial effects of conditional BDNF production and local delivery at the location of active neuropathology highlight the potential to use endogenous biomarkers with early onset, such as astrogliosis, as regulators of neurotrophic therapy in AD.SIGNIFICANCE STATEMENT Recent evidence places astrocytes as pivotal players during synaptic plasticity and memory processes. In the present work, we first provide evidence that astrocytes are essential for neuronal morphology via BDNF release. We then crossed transgenic mice (5xFAD mice) with the transgenic pGFAP-BDNF mice, which express BDNF under the GFAP promoter. The resultant double-mutant mice 5xF:pGB mice displayed a full rescue of hippocampal BDNF loss and related signaling compared with 5xFAD mice and a significant and specific improvement in all the evaluated cognitive tasks. These improvements did not correlate with amelioration of β amyloid load or hippocampal adult neurogenesis rate but were accompanied by a dramatic recovery of structural and functional synaptic plasticity

Report of the first international liver transplantation society expert panel consensus conference on renal insufficiency in liver transplantation

No abstract.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/64330/1/21877_ftp.pd

Aprendizaje colaborativo usando Microsoft Teams en la asignatura de Odontopediatría II

El aprendizaje colaborativo es una técnica didáctica que promueve desarrollar la colaboración entre individuos con el fin de compartir, conocer y ampliar información que tienen cada uno de ellos sobre un tema. No significa repartirse las tareas sino que cada miembro aporte su información para que así el grupo lo pueda modificar, ampliar y así pasar de un trabajo individual a uno más completo. Este aprendizaje colaborativo se puede hacer de manera presencial o virtual. Para la realización de manera virtual contamos con multitud de plataformas para crear grupos y aprender de forma colaborativa. Nosotros hemos elegido la plataforma Microsoft Teams ya que en la Universidad Complutense de Madrid se está implementado está plataforma para la docencia online. Microsoft Teams (MT) es una plataforma unificada de comunicación y colaboración en la que un grupo puede mantener la comunicación. Dentro de los canales que dispone MT, pueden organizarse reuniones, mantener conversaciones, compartir y almacenar archivos e integrar aplicaciones. En el curso 2021/2022 hemos creado varios Equipo de trabajo en MT con los alumnos matriculados en el asignatura de Odontopeadiatría II. Los profesores hemos subido casos clínicos, preguntas así como temas de debates relacionados con la Odontopediatría, donde se crearon debates entre los alumnos y los profesores de manera on-line. Posteriormente se les pasó a los alumnos encuesta de satisfacción donde valoraron el aprendizaje con este tipo de docencia y esta plataforma. Una vez obtenidas las respuestas, hemos analizados los resultados y elaborado un documento para mejorar el Aprendizaje colaborativo con MT de manera online, intentando establecer mejoras para posteriores años académico