Non-linear Model Predictive Control for cooling strings of superconducting magnets using superfluid helium

En cada uno de los ocho arcos del Gran Colisionador de Hadrones (LHC) de 27 km de circunferencia, largas cadenas de imánes superconductores de 2.5 km se enfrian con helio II superfluido a 1.9 K. La estabilización de la temperatura es un problema de control retador debido a complejas dinámicas no lineales de la temperatura de los imanes y la presencia de múltiples restricciones operativas. No-linealidades fuertes y tiempos muertos variables de la dinámica se originan en la conductividad de calor eficaz de superfluido dependiendo fuertemente de flujo de calor y pueden variar hasta tres órdenes de magnitud dentro de la gama de posibles condiciones operativas. Con el fin de mejorar la estabilización de la temperatura, se ha realiado una demostración con un Controlador Predictivo No-lineal económico (NMPC) con retroalimentación de salida que se presenta en esta tesis. El controlador se basa en un modelo numerico de primeros principios y de parámetros distribuidos, novedoso y complejo, para la dinámica de la temperatura en un subsector del LHC de 214 m de largo. El modelo se caracteriza por el muy bajo costo computacional de la simulación, necesario en control de procesos avanzado basado en optimización en tiempo real. Se presenta un análisis exhaustivo de los procesos físicos termo-hidráulicos que rigen la dinámica de temperatura, incluido la revisión de programas de I+D relacionados. El análisis explica las principales características de la dinámica de temperatura y ha sido el punto de partida para el desarrollo del modelo y la estrategia de control. También se describen las configuraciones experimentales utilizadas para identificar la dinámica y los parámetros del modelo de este sistema criogénico superfluido único. A través de la tesis, destaco los métodos prácticos utilizados para lograr la factibilidad de tiempo real del controlador, incluyendo: 1) aproximaciones, manejo de rigidez y ecuaciones algebraicas en el modelado y simulación, 2) la aplicación del estimador de estado híbrido Luenberger Observer - Mover Horizonte Estimación que permite el control de retroalimentación de salida a un costo muy bajo de computación, 3) parametrización de las trayectorias de variables optimizadas que reduce significamente el número de variables optimizados, 4) la aproximación del problema de optimización no-lineal original con restricciones de desigualdad usando uno con restricciones de desigualdad tipo caja que es mucho más fácil de resolver y 5) la aplicación de un solo paso de un método Quasi-Newton para el problema de optimización con restricciones tipo caja específico que se resuelve repetidamente en un controlador basado en la optimización. Se presentan dos configuraciones NMPC para la estabilización de la temperatura de los imanes sobre un sub-sector del LHC de 214 m de largo: 1) que manipula dos válvulas de control, probado experimentalmente en el LHC, y 2) que manipula las dos válvulas y 12 calentadores eléctricos, probado en simulaciones. Ambas configuraciones son factibles en tiempo real y presentan un excelente funcionamiento robusto en amplia gama de condiciones de operación, validando así tanto el modelo de parámetros distribuidos y el NMPC en linea con realimentación de salida basado en un modelo complejo de primeros principiosDepartamento de Ingeniería de Sistemas y Automátic

The psychological science accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

A global experiment on motivating social distancing during the COVID-19 pandemic

Finding communication strategies that effectively motivate social distancing continues to be a global public health priority during the COVID-19 pandemic. This cross-country, preregistered experiment (n = 25,718 from 89 countries) tested hypotheses concerning generalizable positive and negative outcomes of social distancing messages that promoted personal agency and reflective choices (i.e., an autonomy-supportive message) or were restrictive and shaming (i.e., a controlling message) compared with no message at all. Results partially supported experimental hypotheses in that the controlling message increased controlled motivation (a poorly internalized form of motivation relying on shame, guilt, and fear of social consequences) relative to no message. On the other hand, the autonomy-supportive message lowered feelings of defiance compared with the controlling message, but the controlling message did not differ from receiving no message at all. Unexpectedly, messages did not influence autonomous motivation (a highly internalized form of motivation relying on one’s core values) or behavioral intentions. Results supported hypothesized associations between people’s existing autonomous and controlled motivations and self-reported behavioral intentions to engage in social distancing. Controlled motivation was associated with more defiance and less long-term behavioral intention to engage in social distancing, whereas autonomous motivation was associated with less defiance and more short- and long-term intentions to social distance. Overall, this work highlights the potential harm of using shaming and pressuring language in public health communication, with implications for the current and future global health challenges

The Psychological Science Accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

PRACE research infrastructure offer for Polish R\&D community

The mission of the PRACE Research Infrastructure is to enable high impactscientific discovery and engineering research and development across all disciplines to enhance European competitiveness for the benefit of society. The paper presents the current state of the computational infrastructure, which is unique on the European level and procedures helping with the seamless access to the European HPC infrastructure: supercomputers, applications,storage. Several Polish computational grants have been called in the paper in order to present examples of the Polish domestic scientific engagement

Antidotes in Clinical Toxicology—Critical Review

Poisoning and overdose are very important aspects in medicine and toxicology. Chemical weapons pose a threat to civilians, and emergency medicine principles must be followed when dealing with patients who have been poisoned or overdosed. Antidotes have been used for centuries and modern research has led to the development of new antidotes that can accelerate the elimination of toxins from the body. Although some antidotes have become less relevant due to modern intensive care techniques, they can still save lives or reduce the severity of toxicity. The availability of antidotes is crucial, especially in developing countries where intensive care facilities may be limited. This article aims to provide information on specific antidotes, their recommended uses, and potential risks and new uses. In the case of poisoning, supportive therapies are most often used; however, in many cases, the administration of an appropriate antidote saves the patient’s life. In this review, we reviewed the literature on selected antidotes used in the treatment of poisonings. We also characterised the antidotes (bio)chemically. We described the cases in which they are used together with the dosage recommendations. We also analysed the mechanisms of action. In addition, we described alternative methods of using a given substance as a drug, an example of which is N-acetylcysteine, which can be used in the treatment of COVID-19. This article was written as part of the implementation of the project of the Polish Ministry of Education and Science, “Toxicovigilance, poisoning prevention, and first aid in poisoning with xenobiotics of current clinical importance in Poland”, grant number SKN/SP/570184/2023

The psychological science accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

The Psychological Science Accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

The Psychological Science Accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/ dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data