Kinematic active region formation in a three-dimensional solar dynamo model

We propose a phenomenological technique for modelling the emergence of active regions within a three-dimensional, kinematic dynamo framework. By imposing localized velocity perturbations, we create emergent flux tubes out of toroidal magnetic field at the base of the convection zone, leading to the eruption of active regions at the solar surface. The velocity perturbations are calibrated to reproduce observed active region properties (including the size and flux of active regions, and the distribution of tilt angle with latitude), resulting in a more consistent treatment of flux-tube emergence in kinematic dynamo models than artificial flux deposition. We demonstrate how this technique can be used to assimilate observations and drive a kinematic three-dimensional model, and use it to study the characteristics of active region emergence and decay as a source of poloidal field.We find that the poloidal components are strongest not at the solar surface, but in the middle convection zone, in contrast with the common assumption that the poloidal source is located near the solar surface. We also find that, while most of the energy is contained in the lower convection zone, there is a good correlation between the evolution of the surface and interior magnetic fields

Polar Network Index as a magnetic proxy for the solar cycle studies

The Sun has a polar magnetic field which oscillates with the 11 year sunspot cycle. This polar magnetic field is an important component of the dynamo process which is operating in the solar convection zone and produces the sunspot cycle. We have systematic direct measurements of the Sun's polar magnetic field only from about mid 1970s. There are, however, indirect proxies which give us information about this field at earlier times. The Ca K spectroheliograms taken in Kodaikanal Solar Observatory during 1904 - 2007 have now been digitized with the 4k x 4k CCD and have higher resolution (0.86 arcsec) than the other available historical datasets. From these Ca-K spectroheliograms, we have developed a completely new proxy (Polar Network Index, PNI) for the Sun's polar magnetic field. We calculate the PNI from the digitized images using an automated algorithm and calibrate our measured PNI against the polar field as measured by the Wilcox Solar Observatory for the period of 1976 - 1990. This calibration allows us to estimate polar fields for the earlier period up to 1904. The dynamo calculations done with this proxy as input data reproduce the Sun's magnetic behavior for the past century reasonably well.Comment: 19 pages, 5 figures Accepted for publication in APJ

Diagnostico en salud bucal, en ninos de 12 anos del Liceo Basico Fermin del Real Castillo, en la comuna de Chepica, 2008

74 p.INTRODUCCIÓN: Las enfermedades orales son un problema de salud pública. Dentro de los objetivos sanitarios propuestos por el Ministerio de Salud para esta década, consideró disminuir el número de caries en la población de 12 años, logrando un índice COPD de 1.9 en esa edad, por lo cual es necesario obtener datos actualizados sobre la situación de salud bucal de los niños de la comuna de Chépica, ya que estamos próximos al 2010, plazo en que se cumplen los objetivos propuestos por el Ministerio de Salud. OBJETIVO: Diagnosticar el estado de salud bucal, de los niños de 12 años del Liceo Básico Fermín del Real Castillo, en la comuna de Chépica, en el año 2008. MATERIALES Y MÉTODO: Se realizó un estudio descriptivo, no probabilístico, a 66 niños de 12 años de edad. Se les realizó un examen clínico y se aplicaron dos cuestionarios, donde se midió la prevalencia de caries y enfermedad gingival, y los factores que influyen en su incidencia, los cuales fueron evaluados por medio de diversos índices epidemiológicos, como lo son la prevalencia de caries, el índice COPD, el índice de significancia de caries (SiC), la entrevista de riesgo cariogénico de la dieta, el índice de higiene oral (IHO), y el índice de necesidad de tratamiento periodontal comunitario (CPITN). RESULTADOS: La prevalencia de caries encontrada fue de un 77,3%, el índice COPD fue de 4,12, el SiC fue de 5,73, se obtuvo un riesgo cariogénico de la dieta de 78, que corresponde a un riesgo cariogénico medio, el IHO tuvo un valor de 1,3, que equivale a una higiene regular, y el CPITN arrojó una prevalencia de gingivitis de 98,5%. CONCLUSIÓN: En el Liceo Básico Fermín del Real Castillo, de la comuna de Chépica, no se estaría cumpliendo la meta propuesta por el Ministerio de Salud para el año 2010

On the Amplitude of Convective Velocities in the Deep Solar Interior

We obtain lower limits on the amplitude of convective velocities in the deep solar convection zone based only on the observed properties of the differential rotation and meridional circulation together with simple and robust dynamical balances obtained from the fundamental MHD equations. The linchpin of the approach is the concept of gyroscopic pumping whereby the meridional circulation across isosurfaces of specific angular momentum is linked to the angular momentum transport by the convective Reynolds stress. We find that the amplitude of the convective velocity must be at least 30 m s$^{-1}$ in the upper CZ ($r \sim 0.95 R$) and at least 8 m s$^{-1}$ in the lower CZ ($r \sim 0.75 R$) in order to be consistent with the observed mean flows. Using the base of the near-surface shear layer as a probe of the rotational influence, we are further able to show that the characteristic length scale of deep convective motions must be no smaller than 5.5--30 Mm. These results are compatible with convection models but suggest that the efficiency of the turbulent transport assumed in advection-dominated flux-transport dynamo models is generally not consistent with the mean flows they employ.Comment: 16 pages, 4 figures, accepted to the Astrophysical Journa

MEMPSEP III. A machine learning-oriented multivariate data set for forecasting the Occurrence and Properties of Solar Energetic Particle Events using a Multivariate Ensemble Approach

We introduce a new multivariate data set that utilizes multiple spacecraft collecting in-situ and remote sensing heliospheric measurements shown to be linked to physical processes responsible for generating solar energetic particles (SEPs). Using the Geostationary Operational Environmental Satellites (GOES) flare event list from Solar Cycle (SC) 23 and part of SC 24 (1998-2013), we identify 252 solar events (flares) that produce SEPs and 17,542 events that do not. For each identified event, we acquire the local plasma properties at 1 au, such as energetic proton and electron data, upstream solar wind conditions, and the interplanetary magnetic field vector quantities using various instruments onboard GOES and the Advanced Composition Explorer (ACE) spacecraft. We also collect remote sensing data from instruments onboard the Solar Dynamic Observatory (SDO), Solar and Heliospheric Observatory (SoHO), and the Wind solar radio instrument WAVES. The data set is designed to allow for variations of the inputs and feature sets for machine learning (ML) in heliophysics and has a specific purpose for forecasting the occurrence of SEP events and their subsequent properties. This paper describes a dataset created from multiple publicly available observation sources that is validated, cleaned, and carefully curated for our machine-learning pipeline. The dataset has been used to drive the newly-developed Multivariate Ensemble of Models for Probabilistic Forecast of Solar Energetic Particles (MEMPSEP; see MEMPSEP I (Chatterjee et al., 2023) and MEMPSEP II (Dayeh et al., 2023) for associated papers)

MEMPSEP II. -- Forecasting the Properties of Solar Energetic Particle Events using a Multivariate Ensemble Approach

Solar Energetic Particles (SEPs) form a critical component of Space Weather. The complex, intertwined dynamics of SEP sources, acceleration, and transport make their forecasting very challenging. Yet, information about SEP arrival and their properties (e.g., peak flux) is crucial for space exploration on many fronts. We have recently introduced a novel probabilistic ensemble model called the Multivariate Ensemble of Models for Probabilistic Forecast of Solar Energetic Particles (MEMPSEP). Its primary aim is to forecast the occurrence and physical properties of SEPs. The occurrence forecasting, thoroughly discussed in a preceding paper (Chatterjee et al., 2023), is complemented by the work presented here, which focuses on forecasting the physical properties of SEPs. The MEMPSEP model relies on an ensemble of Convolutional Neural Networks, which leverage a multi-variate dataset comprising full-disc magnetogram sequences and numerous derived and in-situ data from various sources. Skill scores demonstrate that MEMPSEP exhibits improved predictions on SEP properties for the test set data with SEP occurrence probability above 50%, compared to those with a probability below 50%. Results present a promising approach to address the challenging task of forecasting SEP physical properties, thus improving our forecasting capabilities and advancing our understanding of the dominant parameters and processes that govern SEP production

First investigation of a novel 2D position-sensitive semiconductor detector concept

This paper presents a first study of the performance of a novel 2D position-sensitive microstrip detector, where the resistive charge division method was implemented by replacing the metallic electrodes with resistive electrodes made of polycrystalline silicon. A characterization of two proof-of-concept prototypes with different values of the electrode resistivity was carried out using a pulsed Near Infra-Red laser. The experimental data were compared with the electrical simulation of the sensor equivalent circuit coupled to simple electronics readout circuits. The good agreement between experimental and simulation results establishes the soundness of resistive charge division method in silicon microstrip sensors and validates the developed simulation as a tool for the optimization of future sensor prototypes. Spatial resolution in the strip length direction depends on the ionizing event position. The average value obtained from the protype analysis is close to 1.2% of the strip length for a 6 MIP signal.Comment: 14 pages, 12 figure

a cross-sectional study

Objectives We determined the seroprevalence and correlates of Toxoplasma gondii infection in pregnant women in Aguascalientes City, Mexico. Design A cross-sectional survey. Setting Pregnant women were enrolled in the central Mexican city of Aguascalientes. Participants We studied 338 pregnant women who attended prenatal care in 3 public health centres. Primary and secondary outcome measures Women were examined for IgG/IgM antibodies to T. gondii by using commercially available enzyme immunoassays, and an avidity test. Multiple analyses were used to determine the association of T. gondii seropositivity with the characteristics of the pregnant women. Results Of the 338 pregnant women studied, 21 (6.2%) had IgG antibodies to T. gondii, and 1 (4.8%) of them was also positive for IgM antibodies to T. gondii. Avidity of IgG antibodies to T. gondii was high in the IgM-positive sample. Logistic regression analysis of sociodemographic, behavioural and housing variables showed that T. gondii seropositivity was associated with white ethnicity (OR=149.4; 95% CI 10.8 to 2054.1; p<0.01), not washing hands before eating (OR=6.41; 95% CI 1.73 to 23.6; p=0.005) and use of latrine (OR=37.6; 95% CI 4.63 to 306.31; p=0.001). Conclusions Results demonstrate that pregnant women in Aguascalientes City have a low seroprevalence of T. gondii infection. However, this low prevalence indicates that most pregnant women are at risk for a primary infection. Factors associated with T. gondii exposure found in this study, including food hygiene, may be useful to determine preventive measures against T. gondii infection and its sequelae