Automatic recognition of texture in Renaissance music

Renaissance music constitutes a resource of immense richness for Western culture, as shown by its central role in digital humanities. Yet, despite the advance of computational musicology in analysing other Western repertoires, the use of computer-based methods to automatically retrieve relevant information from Renaissance music, e. g., identifying word-painting strategies such as madrigalisms, is still underdeveloped. To this end, we propose a score-based machine learning approach for the classification of texture in Italian madrigals of the 16th century. Our outcomes indicate that Low Level Descriptors, such as intervals, can successfully convey differences in High Level features, such as texture. Furthermore, our baseline results, particularly the ones from a Convolutional Neural Network, show that machine learning can be successfully used to automatically identify sections in madrigals associated with specific textures from symbolic sources

Perception and classification of emotions in nonsense speech: humans versus machines

This article contributes to a more adequate modelling of emotions encoded in speech, by addressing four fallacies prevalent in traditional affective computing: First, studies concentrate on few emotions and disregard all other ones (‘closed world’). Second, studies use clean (lab) data or real-life ones but do not compare clean and noisy data in a comparable setting (‘clean world’). Third, machine learning approaches need large amounts of data; however, their performance has not yet been assessed by systematically comparing different approaches and different sizes of databases (‘small world’). Fourth, although human annotations of emotion constitute the basis for automatic classification, human perception and machine classification have not yet been compared on a strict basis (‘one world’). Finally, we deal with the intrinsic ambiguities of emotions by interpreting the confusions between categories (‘fuzzy world’). We use acted nonsense speech from the GEMEP corpus, emotional ‘distractors’ as categories not entailed in the test set, real-life noises that mask the clear recordings, and different sizes of the training set for machine learning. We show that machine learning based on state-of-the-art feature representations (wav2vec2) is able to mirror the main emotional categories (‘pillars’) present in perceptual emotional constellations even in degradated acoustic conditions

Distinguishing between pre- and post-treatment in the speech of patients with chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) causes lung inflammation and airflow blockage leading to a variety of respiratory symptoms; it is also a leading cause of death and affects millions of individuals around the world. Patients often require treatment and hospitalisation, while no cure is currently available. As COPD predominantly affects the respiratory system, speech and non-linguistic vocalisations present a major avenue for measuring the effect of treatment. In this work, we present results on a new COPD dataset of 20 patients, showing that, by employing personalisation through speaker-level feature normalisation, we can distinguish between pre- and post-treatment speech with an unweighted average recall (UAR) of up to 82% in (nested) leave-one-speaker-out cross-validation. We further identify the most important features and link them to pathological voice properties, thus enabling an auditory interpretation of treatment effects. Monitoring tools based on such approaches may help objectivise the clinical status of COPD patients and facilitate personalised treatment plans

Distinguishing between pre- and post-treatment in the speech of patients with chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) causes lung inflammation and airflow blockage leading to a variety of respiratory symptoms; it is also a leading cause of death and affects millions of individuals around the world. Patients often require treatment and hospitalisation, while no cure is currently available. As COPD predominantly affects the respiratory system, speech and non-linguistic vocalisations present a major avenue for measuring the effect of treatment. In this work, we present results on a new COPD dataset of 20 patients, showing that, by employing personalisation through speaker-level feature normalisation, we can distinguish between pre- and post-treatment speech with an unweighted average recall (UAR) of up to 82\,\% in (nested) leave-one-speaker-out cross-validation. We further identify the most important features and link them to pathological voice properties, thus enabling an auditory interpretation of treatment effects. Monitoring tools based on such approaches may help objectivise the clinical status of COPD patients and facilitate personalised treatment plans.Comment: Accepted in INTERSPEECH 202

Associative Learning of Stimuli Paired and Unpaired With Reinforcement: Evaluating Evidence From Maggots, Flies, Bees, and Rats

Finding rewards and avoiding punishments are powerful goals of behavior. To maximize reward and minimize punishment, it is beneficial to learn about the stimuli that predict their occurrence, and decades of research have provided insight into the brain processes underlying such associative reinforcement learning. In addition, it is well known in experimental psychology, yet often unacknowledged in neighboring scientific disciplines, that subjects also learn about the stimuli that predict the absence of reinforcement. Here we evaluate evidence for both these learning processes. We focus on two study cases that both provide a baseline level of behavior against which the effects of associative learning can be assessed. Firstly, we report pertinent evidence from Drosophila larvae. A re-analysis of the literature reveals that through paired presentations of an odor A and a sugar reward (A+) the animals learn that the reward can be found where the odor is, and therefore show an above-baseline preference for the odor. In contrast, through unpaired training (A/+) the animals learn that the reward can be found precisely where the odor is not, and accordingly these larvae show a below-baseline preference for it (the same is the case, with inverted signs, for learning through taste punishment). In addition, we present previously unpublished data demonstrating that also during a two-odor, differential conditioning protocol (A+/B) both these learning processes take place in larvae, i.e., learning about both the rewarded stimulus A and the non-rewarded stimulus B (again, this is likewise the case for differential conditioning with taste punishment). Secondly, after briefly discussing published evidence from adult Drosophila, honeybees, and rats, we report an unpublished data set showing that relative to baseline behavior after truly random presentations of a visual stimulus A and punishment, rats exhibit memories of opposite valence upon paired and unpaired training. Collectively, the evidence conforms to classical findings in experimental psychology and suggests that across species animals associatively learn both through paired and through unpaired presentations of stimuli with reinforcement – with opposite valence. While the brain mechanisms of unpaired learning for the most part still need to be uncovered, the immediate implication is that using unpaired procedures as a mnemonically neutral control for associative reinforcement learning may be leading analyses astray

In vivo inhibition of neutrophil activity by a FAS (CD95) stimulating module: arterial in-line application in a porcine cardiac surgery model

AbstractObjectiveCardiac surgery with cardiopulmonary bypass is associated with aberrant neutrophil activation and potentially severe pathogenic sequelae. This experimental study was done to evaluate a leukocyte inhibition module that rapidly inactivates neutrophils through CD95 stimulation.MethodsGerman landrace pigs (4 groups, each n = 5) underwent cardiac surgery without cardiopulmonary bypass (group I), with cardiopulmonary bypass (group II), with cardiopulmonary bypass plus a leukocyte filter (group III), and with cardiopulmonary bypass plus a leukocyte inhibition module (group IV). The leukocyte filter or leukocyte inhibition module was introduced into the arterial line of the heart-lung machine.ResultsLeukocyte counts were decreased by up to 43% in group IV compared with values in group II (P = .023). In group IV, but not in groups I to III, no delay in spontaneous neutrophil apoptosis was observed after annexin V–propidium iodide staining. Late apoptotic (11.7%) or necrotic neutrophils (9.3%) were detected in 2 animals (group IV). Tumor necrosis factor α serum levels increased over time in groups I to III (>2-fold) but remained at baseline levels in group IV (P < .05). Interleukin 8–mediated chemotactic neutrophil transmigration activity increased over time in groups I to III but was totally abrogated in group IV at any time point. The perioperative increase of creatine kinase and creatine kinase MB levels was lower in groups III (1.5-fold and 1.3-fold, respectively) and IV (1.2-fold and 1.5-fold, respectively) compared with values in group II (both 1.9-fold).ConclusionsThe leukocyte inhibition module downregulated cardiopulmonary bypass–related neutrophil activity and thus might be beneficial in cardiac surgery and other clinical settings with unappreciated neutrophil activation

The voice of COVID-19: acoustic correlates of infection in sustained vowels

COVID-19 is a global health crisis that has been affecting many aspects of our daily lives throughout the past year. The symptomatology of COVID-19 is heterogeneous with a severity continuum. A considerable proportion of symptoms are related to pathological changes in the vocal system, leading to the assumption that COVID-19 may also affect voice production. For the very first time, the present study aims to investigate voice acoustic correlates of an infection with COVID-19 on the basis of a comprehensive acoustic parameter set. We compare 88 acoustic features extracted from recordings of the vowels /i:/, /e:/, /o:/, /u:/, and /a:/ produced by 11 symptomatic COVID-19 positive and 11 COVID-19 negative German-speaking participants. We employ the Mann-Whitney U test and calculate effect sizes to identify features with the most prominent group differences. The mean voiced segment length and the number of voiced segments per second yield the most important differences across all vowels indicating discontinuities in the pulmonic airstream during phonation in COVID-19 positive participants. Group differences in the front vowels /i:/ and /e:/ are additionally reflected in the variation of the fundamental frequency and the harmonics-to-noise ratio, group differences in back vowels /o:/ and /u:/ in statistics of the Mel-frequency cepstral coefficients and the spectral slope. Findings of this study can be considered an important proof-of-concept contribution for a potential future voice-based identification of individuals infected with COVID-19.Comment: 8 page

Neue Forschungen zur mittelalterlichen Bau- und Kunstgeschichte in Franken : Vorträge der Ringvorlesung des Zentrums für Mittelalterstudien der Otto-Friedrich-Universität Bamberg im Sommersemester 2010

Der Band „Neue Forschungen zur mittelalterlichen Bau- und Kunstgeschichte in Franken“ enthält die – um die wissenschaftlichen Anmerkungen ergänzten – Vorträge, die im Rahmen der Ringvorlesung des Zentrums für Mittelalterstudien (ZEMAS) der Otto-Friedrich-Universität Bamberg im Sommersemester 2010 gehalten worden sind. Die hier nun publizierten Beiträge stellen neue Forschungsergebnisse der jeweiligen Referenten vor. Sie gelten mittelalterlichen Themen und wenden sich sakralen wie profanen Bauwerken zu. Das Spektrum beginnt mit bedeutenden Sakralbauten Frankens; behandelt werden das Grab des Papstes Clemens II. im Bamberger Dom, der Kreuzgang des Bamberger Karmeliterklosters St. Theodor und die mittelalterlichen Bildwerke der ehemaligen Zisterzienserabteikirche Ebrach. Ein Aufsatz widmet sich dem Rathaus von Forchheim, das im Kern noch aus dem 14. Jahrhundert stammt und damit zu den ältesten Rathäusern in Franken gehört. Zwei weitere Beiträge stellen fränkische Burgen unter ausgewählten Gesichtspunkten vor, und der Band schließt mit einer bauforscherischen Untersuchung des Schlosses der Truchsesse von Wetzhausen

The Earliest Phases of Star Formation (EPoS): A Herschel Key Program - The precursors to high-mass stars and clusters

(Abridged) We present an overview of the sample of high-mass star and cluster forming regions observed as part of the Earliest Phases of Star Formation (EPoS) Herschel Guaranteed Time Key Program. A sample of 45 infrared-dark clouds (IRDCs) were mapped at PACS 70, 100, and 160 micron and SPIRE 250, 350, and 500 micron. In this paper, we characterize a population of cores which appear in the PACS bands and place them into context with their host cloud and investigate their evolutionary stage. We construct spectral energy distributions (SEDs) of 496 cores which appear in all PACS bands, 34% of which lack counterparts at 24 micron. From single-temperature modified blackbody fits of the SEDs, we derive the temperature, luminosity, and mass of each core. These properties predominantly reflect the conditions in the cold, outer regions. Taking into account optical depth effects and performing simple radiative transfer models, we explore the origin of emission at PACS wavelengths. The core population has a median temperature of 20K and has masses and luminosities that span four to five orders of magnitude. Cores with a counterpart at 24 micron are warmer and bluer on average than cores without a 24 micron counterpart. We conclude that cores bright at 24 micron are on average more advanced in their evolution, where a central protostar(s) have heated the outer bulk of the core, than 24 micron-dark cores. The 24 micron emission itself can arise in instances where our line of sight aligns with an exposed part of the warm inner core. About 10% of the total cloud mass is found in a given cloud's core population. We uncover over 300 further candidate cores which are dark until 100 micron. These are candidate starless objects, and further observations will help us determine the nature of these very cold cores.Comment: Accepted for publication in A&A, 81 pages, 68 figures. For full resolution image gallery (Appendix B), see http://www.mpia.de/~ragan/epos.htm

A lab-on-a-chip system with an embedded porous membrane-based impedance biosensor array for nanoparticle risk assessment on placental Bewo trophoblast cells

The human placenta is a unique organ serving as the lung, gut, liver, and kidney of the fetus, mediating the exchange of different endogenous as well as exogenous substances and gases between the mother and fetus during pregnancy. Additionally, the placental barrier protects the fetus from a range of environmental toxins, bacterial and viral infections, since any contaminant bridging the placenta may have unforeseeable effects on embryonal and fetal development. A more recent concern in placenta research, however, involves the ability of engineered nanoparticles to cross the placental barrier and/or affect its barrier function. To advance nanoparticle risk assessment at the human placental barrier, we have developed as proof-of-principle a highly integrated placenta-on-a-chip system containing embedded membrane-bound impedance microsensor arrays capable of non-invasively monitoring placental barrier integrity. Barrier integrity is continuously and label-free evaluated using porous membrane-based interdigitated electrode structures located on top of a porous PET membrane supporting a barrier of trophoblast-derived BeWo cell barrier in the absence and presence of standardized silicon dioxide (SiO2), titanium dioxide (TiO2), and zinc oxide (ZnO) nanomaterials.This work has been funded by the European Union’s Horizon 2020 research and innovation program under grant agreement No. 685817.Peer reviewe