Complex Formalism of the Linear Beam Dynamics

It has long been known that the ellipse normally used to model the phase space extension of a beam in linear dynamics may be represented by a complex number which can be interpreted similar to a complex impedance in electrical circuits, so that classical electrical methods might be used for the design of such beam transport lines. However, this method has never been fully developed, and only the transport transformation of single particular elements, like drift spaces or quadrupoles, has been presented in the past. In this article, we complete the complex formalism of linear beam dynamics by obtaining a general differential equation and solving it, to show that the general transformation of a linear beam line is a complex Moebius transformation. This result opens the possibility of studying the effect of the beam line on complete regions of the complex plane and not only on a single point. Taking advantage of this capability of the formalism, we also obtain an important result in the theory of the transport through a periodic line, proving that the invariant points of the transformation are only a special case of a more general structure of the solution, which are the invariant circles of the one-period transformation. Among other advantages, this provides a new description of the betatron functions beating in case of a mismatched injection in a circular acceleratorThis work was supported in part by the Ministerio de Asuntos Economicos y Transformacion Digital (MINECO) under Grant DPI2017-82373-R and in part by Universidad del Pais Vasco/Euskal Herriko Univertsitatea (UPV/EHU) under Grant GIU18/19

ALGUNAS REFLEXIONES SOBRE LA CREATIVIDAD EN LAS DISCIPLINAS PROYECTUALES EN UN MUNDO LLENO DE IMÁGENES E IDEAS Experiencias pedagógicas en la enseñanza de las disciplinas proyectuales al inicio del siglo XXI

A lo largo de más de veinte años de trabajo en el taller de las materias Introducción al Conocimiento Proyectual I y II se han introducido nuevos dispositivos conceptuales que han permitido en los estudiantes cambios significativos en relación con sus posibilidades de propuestas para que propicien nuevas reflexiones sobre los conceptos comunes de las distintas disciplinas del diseño. Esto lleva así, a reformular los procesos de aprendizajes induciendo nuevas formas de mirar, pensar, sentir y proponer

Dispositional mindfulness profiles in pregnant women: relationships with dyadic adjustment and symptoms of depression and anxiety

IntroductionPregnancy is a time of major transition that can be stressful for women. Dispositional mindfulness may protect individuals when they face stress. Recent studies have adopted a person-centered approach to examine the role of mindfulness by identifying subtypes of individuals based on their scores in five mindfulness facets. Latent profile analysis was used to identify different mindfulness profiles in a sample of pregnant women, and we explored the relationships between these profiles, depression and anxiety symptoms, and whether dyadic adjustment mediated these relationships.MethodA total of 535 women aged 18–45 years in their 26th week of pregnancy completed questionnaires regarding mindfulness, dyadic satisfaction and cohesion, and depression and anxiety symptoms.ResultsThree profiles were identified: (1) low mindfulness (53.8%), (2) moderate mindfulness (34.3%), and (3) non-judgmentally aware (11.9%). The most adaptive profile was the non-judgmentally aware profile. Compared to the low mindfulness profile, the non-judgmentally aware profile and the moderate mindfulness profile were related to fewer symptoms of depression and anxiety, and these relationships were partly mediated by dyadic satisfaction.DiscussionThese results suggest that analyzing each pregnant woman’s mindfulness profile can improve the prevention of and interventions for anxiety and depression

Papel del Inflamasoma en la EPOC estable y agudizada

195 p.La EPOC se caracteriza por una respuesta inflamatoria exagerada frente a la inhalación de humo del tabaco, más evidente durante las fases de agudización de la enfermedad. El inflamasoma, un complejo multiproteico participante de la inmunidad innata, es estimulado a través de receptores toll-like y NOD- like y conlleva a la activación de la caspasa-1 y el procesamiento de la proIL1 y la proIL18 en sus formas maduras activas (IL1b e IL18). La hipótesis de este trabajo fue que la actividad del inflamasoma está aumentada en pacientes con EPOC, especialmente durante las agudizaciones. Para demostrar esta hipótesis de trabajo, investigamos el estado del inflamasoma NLRP3, y sus citocinas asociadas en: 1) muestras de tejido pulmonar de 38 pacientes con enfermedad estable EPOC, 15 fumadores con espirometría normal y 14 nunca fumadores; y 2) muestras de esputo y plasma de 56 pacientes con agudización de EPOC, de los cuales 41 pudieron ser reevaluados en la recuperación clínica. Los principales resultados indican que: 1) en muestras de tejido pulmonar de pacientes con EPOC estable, el ARNm de NLRP3 e interleucina (IL)-1ß estaban elevados. Pero tanto la caspasa-1 como la ASC estaban en su mayoría en forma inactiva, y 2) durante las agudizaciones de origen infeccioso, caspasa-1, ASC oligomérico y sus citocinas asociadas (IL-1ß, IL-18) estaban significativamente aumentadas en esputo en comparación con la recuperación clínica posterior. De estos resultados, concluimos que el inflamasoma NLRP3 esta cebado, pero no se activa, en los pulmones de pacientes con EPOC clínicamente estables

Upgrading the Performance of Cholesteric Liquid Crystal Lasers: Improvement Margins and Limitations

The topic of cholesteric-liquid-crystal lasers is a rapidly expanding research area in the field of soft-matter photonics. The increasing interest in this field is due to the high versatility that these lasers may possibly present and the prospects of giving rise to new miniaturized devices. However, further improvements in their operation capabilities are still required for potential applications. In this paper, we critically analyze the main strategies proposed up to now to optimize their performance. We show theoretically and experimentally that possible innovations in the device structure cannot produce lasers with threshold energies below a certain limit. This limit is determined by the light scattering and absorption losses inside the liquid crystal. Even assuming the case of samples free of defects and perfectly non-absorbing, an intrinsic light scattering, typical of mesogens, still remains. Numerical estimates of the thresholds indicate that these lasers could hardly be driven by compact light sources such as current electroluminescent or light-emitting diodes. Since the improvement possibilities regarding cell architecture seem to be exhausted, the advance must come from the use of new dye molecules. These molecules should show enhanced emission cross-sections and be efficiently integrable within the mesogenic solvent. In addition, the fluorescent systems must present very small quantum yields to triplet states if continuous-wave lasing is sought. In this respect, quantum dots are an alternative to explore for further investigations

A Machine Learning Model for the Prognosis of Pulseless Electrical Activity during Out-of-Hospital Cardiac Arrest

Pulseless electrical activity (PEA) is characterized by the disassociation of the mechanical and electrical activity of the heart and appears as the initial rhythm in 20–30% of out-of-hospital cardiac arrest (OHCA) cases. Predicting whether a patient in PEA will convert to return of spontaneous circulation (ROSC) is important because different therapeutic strategies are needed depending on the type of PEA. The aim of this study was to develop a machine learning model to differentiate PEA with unfavorable (unPEA) and favorable (faPEA) evolution to ROSC. An OHCA dataset of 1921 5s PEA signal segments from defibrillator files was used, 703 faPEA segments from 107 patients with ROSC and 1218 unPEA segments from 153 patients with no ROSC. The solution consisted of a signal-processing stage of the ECG and the thoracic impedance (TI) and the extraction of the TI circulation component (ICC), which is associated with ventricular wall movement. Then, a set of 17 features was obtained from the ECG and ICC signals, and a random forest classifier was used to differentiate faPEA from unPEA. All models were trained and tested using patientwise and stratified 10-fold cross-validation partitions. The best model showed a median (interquartile range) area under the curve (AUC) of 85.7(9.8)% and a balance accuracy of 78.8(9.8)% , improving the previously available solutions at more than four points in the AUC and three points in balanced accuracy. It was demonstrated that the evolution of PEA can be predicted using the ECG and TI signals, opening the possibility of targeted PEA treatment in OHCA.This work was supported by the Spanish Ministerio de Ciencia, Innovacion y Universidades through Grant RTI2018-101475-BI00, jointly with the Fondo Europeo de Desarrollo Regional (FEDER), by the Basque Government through Grant IT1229-19 and Grant PRE2020_1_0177, and by the university of the Basque Country (UPV/EHU) under Grant COLAB20/01

Solución Multietapa para Diagnóstico del Ritmo Cardíaco durante la Resucitación Cardiopulmonar

Las compresiones torácicas durante la terapia de resucitación cardiopulmonar (RCP) inducen artefactos en el ECG comprometiendo el diagnóstico de los algoritmos de análisis de ritmo. El objetivo de este trabajo es diseñar un método que diagnostique con precisión el ritmo durante la RCP evitando así tener que interrumpir la terapia. Para ello se diseñó un algoritmo multi-etapa (AME) que incluye dos filtros para la supresión del artefacto basados en un algoritmo recursivo de mínimos cuadrados (RLS), el algoritmo de análisis de ritmo de un desfibrilador comercial y un clasificador de ritmos basado en la pendiente del ECG. Se usó una base de datos compuesta por 87 ritmos desfibrilables y 285 no-desfibrilables adquiridos de pacientes en parada cardiorrespitatoria extra-hospitalaria. Para la optimización y validación de la solución AME los datos se dividieron aleatoriamente por pacientes en un conjunto de entrenamiento (70%) y otro de prueba (30%). Este proceso se repitió 500 veces para estimar la distribución estadística de la sensibilidad (Se), especificidad (Sp) y precisión (Acc) de la solución AME. Los valores medios (desviación estándar) de Se, Sp y Acc fueron 92.1% (6.0), 92.4% (2.9) y 92.2% (3.0), respectivamente. La solución mejora resultados anteriores por hasta 5 puntos de precisión

Arquitecturas de aprendizaje profundo para la detección de pulso en la parada cardiaca extrahospitalaria utilizando el ECG

La detección de la presencia de pulso durante la parada cardiorrespiratoria extrahospitalaria es crucial para la supervivencia del paciente. Se ha demostrado que la toma manual del pulso no es muy fiable y que consume demasiado tiempo, por lo que es necesario desarrollar métodos automáticos que ayuden en la identificación del retorno de la circulación espontánea del paciente en parada. En este trabajo se propone utilizar técnicas de aprendizaje profundo para la discriminación automática de ritmos con pulso (PR) y sin pulso (PEA) utilizando solamente información proveniente del ECG. Se ha utilizado una base de datos que contiene 3914 segmentos de 5 segundos (3372 PR y 1542 PEA), que se dividieron en dos bases de datos con pacientes disjuntos para la optimización y evaluación de los métodos. Los mejores resultados se han obtenido utilizando una red neuronal profunda que contiene dos etapas de convolución y una etapa recurrente para la extracción de características y a continuación un clasificador. El modelo se evalúa en términos de sensibilidad (SE, porcentaje de PRs correctamente detectados) y especificidad (SP, proporción de PEAs correctamente detectados). Sobre la base de evaluación se obtuvieron una SE/SP de 94.2%/91.0%, por lo que puede concluirse que la detección automática del pulso utilizando sólo el ECG es viable mediante técnicas de aprendizaje profundo.Este trabajo ha recibido apoyo económico conjunto del Ministerio de Economía y Competitividad Español y del Fondo Europeo de Desarrollo Regional (FEDER) a través del proyecto (TEC2015-64678-R), de la Universidad del País Vasco/Euskal Herriko Unibertsitatea mediante la ayuda a grupos de investigación GIU17/031, y del Gobierno Vasco a través de la beca PRE_2017_1_0112

Towards the Prediction of Rearrest during Out-of-Hospital Cardiac Arrest

A secondary arrest is frequent in patients that recover spontaneous circulation after an out-of-hospital cardiac arrest (OHCA). Rearrest events are associated to worse patient outcomes, but little is known on the heart dynamics that lead to rearrest. The prediction of rearrest could help improve OHCA patient outcomes. The aim of this study was to develop a machine learning model to predict rearrest. A random forest classifier based on 21 heart rate variability (HRV) and electrocardiogram (ECG) features was designed. An analysis interval of 2 min after recovery of spontaneous circulation was used to compute the features. The model was trained and tested using a repeated cross-validation procedure, on a cohort of 162 OHCA patients (55 with rearrest). The median (interquartile range) sensitivity (rearrest) and specificity (no-rearrest) of the model were 67.3% (9.1%) and 67.3% (10.3%), respectively, with median areas under the receiver operating characteristics and the precision–recall curves of 0.69 and 0.53, respectively. This is the first machine learning model to predict rearrest, and would provide clinically valuable information to the clinician in an automated way.This work was supported by the Spanish Ministerio de Ciencia, Innovación y Universidades through grant RTI2018-101475-BI00, jointly with the Fondo Europeo de Desarrollo Regional (FEDER), and by the Basque Government through grants IT1229-19, PRE_2019_2_0100 and PRE_2019_1_0262. A.I. receives research grants from the US National Institutes of Health (NIH)

Modulating Organic/Inorganic Segregation in Columnar Mesophases

This work reports an uncommon modulation of columnar segregation of metal–organic triphenylene liquid crystals by blending two structurally dissimilar metallomesogens that can self-associate through complementary electron donor–acceptor interactions. The constituent molecules are cis-[PtCl2(CNR)2] (CNR = 2-(6-(4-isocyanophenoxy)hexyloxy)-3,6,7,10,11-pentakisdodecyloxytriphenylene) that displays an organic/inorganic segregated columnar mesophase and [PtCl2(Bipy)] (Bipy = didodecyl 2,2′-bipyridyl-4,4′-dicarboxylate) that shows a lamellar mesomorphism. The phase diagram of this system was constructed using polarized optical microscopy (POM), differential scanning calorimetry (DSC), and X-ray scattering data. The phase diagram corresponds to a typical binary system with an intermediate compound (in this case a supramolecular aggregate) of stoichiometry [PtCl2(CNR)2]/2[PtCl2(Bipy)], which is maintained in solution. This species shows an unusual columnar mesophase formed by the stacking of alternating organic/inorganic fragments. Quantum chemical calculations show that the columnar structure is mainly supported by complementary π electron donor–acceptor interactions between each triphenylene group of the isocyanide complex and a platinum-bipyridine molecule. This induces the elimination of the organic/inorganic columnar segregation of the isocyano parent component and constitutes an unconventional example of modulation of organic/inorganic segregation in columnar mesophases by the intercalation of metal complexes into hexaalkoxytriphenylene stacks.This work was sponsored by the Ministerio de Ciencia e Innovación (Project PID2020-118547GB-I00), the Junta de Castilla y León (Project VA224P20), and the Basque Government (Project IT1458-22). E.D. thanks MECD for a FPU grant. The authors thankfully acknowledge the computer resources at Lusitania II and CIERZO-CAESARAUGUSTA III and the Technical support provided by Cénits-COMPUTAEX (FI-2022-1-0009, FI-2022-3-0008), Centro de Supercomputación de Aragón (QHS-2023-3-0005, QH-2023-1-0002) and Red Española de Supercomputación. We thank Dr. S. Ferrero (University of Valladolid) for his help in the NMR titration experiments