scholarly journals Spontaneous Melodic Productions of Expert Musicians Contain Sequencing Biases Seen in Language Production

Author(s):  
Roger Beaty ◽  
Klaus Frieler ◽  
Martin Norgaard ◽  
Hannah Merseal ◽  
Maryellen MacDonald ◽  
...  

Language production involves complex action sequencing to produce fluent speech in real-time, placing considerable constraints on working memory that lead to sequencing biases in production. Researchers have speculated that these biases may extend beyond language to other human behaviors involving action sequencing, but this claim has not been empirically investigated. Here we provide a strong test of this hypothesis, examining whether biases seen in language production also constrain one of the most complex and spontaneous human behaviors: musical improvisation. Using a large corpus of improvised solo transcriptions from eminent jazz musicians, we test for the existence of an established production bias observed in language production termed easy first—a tendency for more accessible sequences to occur at the beginning of a phrase, allowing incremental planning of more complex phrases. Our analysis shows consistent evidence of easy first in improvised music. We find that the beginning of improvised musical phrases contains 1) more frequently occurring interval patterns, 2) smaller intervals, 3) less interval variety, 4) less pitch variety, and 5) fewer direction changes. There was no easy first bias in a control corpus containing simulated data with the same structure, indicating that the effects are specific to real-time melodic production and not simply due to stylistic conventions. The findings indicate that even expert jazz musicians, known for spontaneous creative performance, reliably retrieve easily-accessed melodic sequences before creating more complex sequences—consistent with an incremental planning strategy employed in language production—suggesting that similar biases constrain the spontaneous production of music and language.

Molecules ◽  
2020 ◽  
Vol 26 (1) ◽  
pp. 20
Author(s):  
Reynaldo Villarreal-González ◽  
Antonio J. Acosta-Hoyos ◽  
Jaime A. Garzon-Ochoa ◽  
Nataly J. Galán-Freyle ◽  
Paola Amar-Sepúlveda ◽  
...  

Real-time reverse transcription (RT) PCR is the gold standard for detecting Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), owing to its sensitivity and specificity, thereby meeting the demand for the rising number of cases. The scarcity of trained molecular biologists for analyzing PCR results makes data verification a challenge. Artificial intelligence (AI) was designed to ease verification, by detecting atypical profiles in PCR curves caused by contamination or artifacts. Four classes of simulated real-time RT-PCR curves were generated, namely, positive, early, no, and abnormal amplifications. Machine learning (ML) models were generated and tested using small amounts of data from each class. The best model was used for classifying the big data obtained by the Virology Laboratory of Simon Bolivar University from real-time RT-PCR curves for SARS-CoV-2, and the model was retrained and implemented in a software that correlated patient data with test and AI diagnoses. The best strategy for AI included a binary classification model, which was generated from simulated data, where data analyzed by the first model were classified as either positive or negative and abnormal. To differentiate between negative and abnormal, the data were reevaluated using the second model. In the first model, the data required preanalysis through a combination of prepossessing. The early amplification class was eliminated from the models because the numbers of cases in big data was negligible. ML models can be created from simulated data using minimum available information. During analysis, changes or variations can be incorporated by generating simulated data, avoiding the incorporation of large amounts of experimental data encompassing all possible changes. For diagnosing SARS-CoV-2, this type of AI is critical for optimizing PCR tests because it enables rapid diagnosis and reduces false positives. Our method can also be used for other types of molecular analyses.


Author(s):  
Christopher Williams ◽  
Martin Sonderkamp

When we improvise together in music and dance, our bodies, instruments, and environments not only interact; they become mutually dependent. A bassist's shoulder shifts, bow slides, instrument rings . . . vibrations bounce off the walls, reach the dancer's inner ear, filling the lungs, lunging toward the bassist's shoulder: these sounds, movements, spaces, and perceptions form a real-time feedback loop that blurs where you end and I begin. Recent research in embodied and situated cognition by scholars such as Clark and Chalmers (1998), Gallagher (2005, 2007), Hutchins (1995), Noë (2004), and Suchman (2007) provides a theoretical foundation for formalizing this continuity. This literature has inspired us to reconsider how cognitive processes we tacitly know within a specific aesthetic framework are in fact at work throughout everyday life. In four videos taken from an hour-long studio session recorded in February 2012, we explore these processes once again in our own practice, and offer reflections in the form of program notes that invite the audience to perform these connections themselves.


Author(s):  
Michael R. Hummels ◽  
Raymond J. Cipra

Abstract An on-line trajectory modification and path planning strategy is developed which will allow a robot to respond in an efficient manner to real time sensory input. The approach developed here eliminates the need for solving many equations by developing a closed form algorithm. It uses two fourth order curves for the transition phases with a constant velocity section in between. Although this is done by providing additional constraints to the curve, it makes the problem of determining the trajectory much easier to solve, while providing continuous higher derivatives. It also provides a safe and efficient way of modifying trajectories based on the robots joint rate limits, joint acceleration limits, jerk limits, and desired time interval between trajectory modifications for a 4-1-4 trajectory. This method involves the solution of one second order equation and is directed toward real time applications.


Author(s):  
Adilla Anggraeni

This chapter discusses the need for drama, interpersonal closeness, informational susceptibility, and compassion for others and their influence towards gossiping behavior via social chatting applications. Technological advancements have enabled people to communicate with each other at the convenience of their homes and in real time. This change, however, also means the changes in human behaviors, such as computer-mediated communication, can be shaped by the richness of the media that people can use to convey their thoughts and opinions. The existence of different chatting applications has fulfilled the needs of human beings to be connected and to interact with each other, and the interactions that take place can be in the form of gossiping and spreading information that may not necessarily be accurate.


2018 ◽  
Vol 63 (13) ◽  
pp. 135017 ◽  
Author(s):  
Thyrza Jagt ◽  
Sebastiaan Breedveld ◽  
Rens van Haveren ◽  
Ben Heijmen ◽  
Mischa Hoogeman

Author(s):  
Bart Mak ◽  
Bülent Düz

Abstract Being able to give real time on-board advice, without depending on extensive sets of measured data, is the ultimate goal of the digital twin concept. Ideally, the models used in a digital twin only rely on current in-service data, although they have been built using simulated and possibly some measured data. Working with just the 6-DOF motions of a ship, can the local sea state reliably be estimated using the digital twin concept? Does a general model exist to do so, without the need to measure or simulate the particular ship? In this paper, we discuss how simulations of an advancing ship, subjected to various sea states, can be used to estimate the relative wave direction from in-service motion measurements of the corresponding ship. Various types of neural networks are used and evaluated with simulated data and measured data. In order to study the generalization power of the neural networks, a range of ships has been simulated, with varying lengths, drafts and geometries. Neural networks have been trained on selections of the ships in this extended training set and evaluated on the remaining ships. Results show that the developed neural networks give a remarkable performance in simulation data. Furthermore, generalization over geometry is very good, opening the door to train a general model for estimating sea state characteristics. Using the same model for in-service measurements does not perform well enough yet and further research is required. The paper will include discussion on possible causes for this performance gap and some promising ideas for future work.


2020 ◽  
Vol 42 (3) ◽  
pp. 253-270
Author(s):  
Mitchell Atkinson

SummaryI outline an approach to the phenomenology of improvised music which takes typification and the development of multi‐ordered phenomenological structures as central. My approach here is firmly in line with classical Husserlian phenomenology, taking the discussion of types in Experience and Judgment (Husserl, 1973) and Brudzińska (2015) as guide. I provide a phenomenological analysis of musical types as they are found in improvisational contexts, focusing on jazz in the 20th century. Styles are higher‐order musical types. Musical types are structures that are temporally “thick,” relying on sedimented typification and knowledge, driving expectations as definitional. In most forms of music (including improvised music), musical styles involve maintaining a balance between confirming expectations and flouting expectations. I show that improvised music has a phenomenal structure which is enriched by the communicative and “ real‐time” nature of improvised music. Improvised music can be seen as an exploration of a possibility space rendered by the juxtaposition of the musical types afforded by a performance environment (instrumentation, harmonic and melodic traditions, etc.). I show that improvisation in music is a multi‐vectoral form of communication. The communication is founded in what Dieter Lohmar calls “non‐linguistic thinking.” The expression is constituted in the results of active and synthesis. The culmination of improvisational exploration of possibility spaces is the precisification and enrichment of styles‐as‐types, while in some cases developing new styles in the process.


Author(s):  
Matthieu Lagardère ◽  
Ingrid Chamma ◽  
Emmanuel Bouilhol ◽  
Macha Nikolski ◽  
Olivier Thoumine

AbstractFluorescence live-cell and super-resolution microscopy methods have considerably advanced our understanding of the dynamics and mesoscale organization of macro-molecular complexes that drive cellular functions. However, different imaging techniques can provide quite disparate information about protein motion and organization, owing to their respective experimental ranges and limitations. To address these limitations, we present here a unified computer program that allows one to model and predict membrane protein dynamics at the ensemble and single molecule level, so as to reconcile imaging paradigms and quantitatively characterize protein behavior in complex cellular environments. FluoSim is an interactive real-time simulator of protein dynamics for live-cell imaging methods including SPT, FRAP, PAF, and FCS, and super-resolution imaging techniques such as PALM, dSTORM, and uPAINT. The software, thoroughly validated against experimental data on the canonical neurexin-neuroligin adhesion complex, integrates diffusion coefficients, binding rates, and fluorophore photo-physics to calculate in real time the distribution of thousands of independent molecules in 2D cellular geometries, providing simulated data of protein dynamics and localization directly comparable to actual experiments.


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