scratchLOG: interacción sonora con código de barras

[EN] ScratchLOG is a version of the classic record player, which interprets a barcode disc and sonifies it. It¿s based on Bartholomäus Traubeck¿s research on sonification in Years, 2011 and Grégory Lasserre & Anaïs met den Ancxt¿s Echos, as well as in Vynil, Lyota Yagi¿s reinterpretation of the record player from 2006. Referring to the physical part of the interface, scratchLOG is a record player that plays sound from the rings of a circular barcode printed on a disc. As to the programming, Pure Data plays the main role in its functioning. The objective of this interface is to deepen in the relation between concrete music and barcode art at a tangible interface level. The capacity of the Raspberry Pi 2 Model B to create sound from the color of an image is investigated as well.[ES] ScratchLOG es una reinvención del tocadiscos clásico que reinterpreta el código de barras impreso en un disco para sonificarlo. Se basa en la investigación de sonificación de Bartholomäus Traubeck en su obra Years, 2011 y Grégory Lasserre & Anaïs met den Ancxt en la obra Echos, al igual que la reinterpretación del tocadiscos de Lyota Yagi en Vynil, 2006. En lo que respecta a la parte física, scratchLOG es un tocadiscos que reproduce el sonido a partir de los anillos de un código de barras circular impreso en un disco. En cuanto a la programación, el programa Pure Data tiene el papel principal para hacer funcionar todo el mecanismo de sonificación. Con esta interfaz se pretende profundizar en la relación entre música concreta y el barcode art a nivel de interfaces tangibles. Asimismo, se investiga la capacidad de la Raspberry Pi 2 Model B de hacer funcionar una cámara en Pure Data, y generar sonido a partir del movimiento y del color.Gabov Gabova, YS. (2016). scratchLOG: interacción sonora con código de barras. http://hdl.handle.net/10251/74305TFG

Unilateral psoas minor: a case report

Introduction:The posterior abdominal wall is a complex region of human anatomy. It is formed by the lumbar vertebrae, pelvic girdle and the five main posterior abdominal muscles - the iliacus, psoas major, quadratus lumborum, the diaphragm, their associated fascia and the variable psoas minor and tertius muscles. The psoas muscle group is comprised of the long fusiform muscles - major, minor and tertius, with only the psoas major muscle being an obligatory muscle present in all individuals. The psoas muscle group however are extremely variable and have differences not only in their structure and morphology, but also in their innervation. The psoas minor is an extremely variable inconstant muscle, a prime example for a vestigial structure in the human body.Case report:During a standard posterior abdominal wall dissection of an adult female cadaver a unilateral right-sided psoas minor muscle was established, with a complete absence of the same muscle on the contralateral left side. The unilateral right-sided psoas minor muscle was located superficially and laterally to the psoas major muscle, it was fusiform in shape and its body measured 96 mm in length and 16mm in circumference.Conclusion:The psoas muscle group is one of the most variable muscle groups in the human body. It could be bilaterally - located on both sides of the vertebral column on the anterior surface of psoas major muscle. Our case is representative of one of the not so common variations of the psoas minor muscle with muscle morphology extremely representative of this type of unilateral variation

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.Peer reviewe

National identity predicts public health support during a global pandemic

Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = −0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.publishedVersio

National identity predicts public health support during a global pandemic (vol 13, 517, 2022) : National identity predicts public health support during a global pandemic (Nature Communications, (2022), 13, 1, (517), 10.1038/s41467-021-27668-9)

Publisher Copyright: © The Author(s) 2022.In this article the author name ‘Agustin Ibanez’ was incorrectly written as ‘Augustin Ibanez’. The original article has been corrected.Peer reviewe

National identity predicts public health support during a global pandemic.

Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = -0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic

Author Correction: National identity predicts public health support during a global pandemic

Correction to: Nature Communications https://doi.org/10.1038/s41467-021-27668-9, published online 26 January 2022

Modelling and numerical simulation of fire in a coffee storage hall

An approach for modelling of fire in halls at solid materials burning, based on gas phase combustion models in ANSYS/CFX, is proposed. The models are suitable for quick prediction of the flue gases distribution and thermal loads on the building envelopes at a design stage. They was applied for numerical simulation of such processes in a coffee storage hall at different fire positions and forced anti-smoke ventilation. The thermal, fluid flow and concentration field were obtained at the modelled scenarios. Maximal thermal loads on the building envelopes are established at the case of fire near their non-streamlined parts