Using the Dipolar and Quadrupolar Moments to Improve Solar-Cycle Predictions Based on the Polar Magnetic Fields

The solar cycle and its associated magnetic activity are the main drivers behind changes in the interplanetary environment and Earth's upper atmosphere (commonly referred to as space weather and climate). In recent years there has been an effort to develop accurate solar cycle predictions, leading to nearly a hundred widely spread predictions for the amplitude of solar cycle 24. Here we show that cycle predictions can be made more accurate if performed separately for each hemisphere, taking advantage of information about both the dipolar and quadrupolar moments of the solar magnetic field during minimum

How many active regions are necessary to predict the solar dipole moment?

We test recent claims that the polar field at the end of Cycle 23 was weakened by a small number of large, abnormally oriented regions, and investigate what this means for solar cycle prediction. We isolate the contribution of individual regions from magnetograms for Cycles 21, 22 and 23 using a 2D surface flux transport model, and find that although the top ~10% of contributors tend to define sudden large variations in the axial dipole moment, the cumulative contribution of many weaker regions cannot be ignored. In order to recreate the axial dipole moment to a reasonable degree, many more regions are required in Cycle 23 than in Cycles 21 and 22 when ordered by contribution. We suggest that the negative contribution of the most significant regions of Cycle 23 could indeed be a cause of the weak polar field at the following cycle minimum and the low-amplitude Cycle 24. We also examine the relationship between a region's axial dipole moment contribution and its emergence latitude, flux, and initial axial dipole moment. We find that once the initial dipole moment of a given region has been measured, we can predict the long-term dipole moment contribution using emergence latitude alone.Comment: 15 pages, 10 figures, accepted for publication in Ap

Efficient labeling of solar flux evolution videos by a deep learning model

Machine learning (ML) is becoming a critical tool for interrogation of large complex data. Labeling, defined as the process of adding meaningful annotations, is a crucial step of supervised ML. However, labeling datasets is time consuming. Here we show that convolutional neural networks (CNNs), trained on crudely labeled astronomical videos, can be leveraged to improve the quality of data labeling and reduce the need for human intervention. We use videos of the solar magnetic field, crudely labeled into two classes: emergence or non-emergence of bipolar magnetic regions (BMRs), based on their first detection on the solar disk. We train CNNs using crude labels, manually verify, correct labeling vs. CNN disagreements, and repeat this process until convergence. Traditionally, flux emergence labelling is done manually. We find that a high-quality labeled dataset, derived through this iterative process, reduces the necessary manual verification by 50%. Furthermore, by gradually masking the videos and looking for maximum change in CNN inference, we locate BMR emergence time without retraining the CNN. This demonstrates the versatility of CNNs for simplifying the challenging task of labeling complex dynamic events.Comment: 16 pages, 7 figures, published in Nature Astronomy, June 27, 202

A preliminary study about treg cells phenotypic alteration

Las células T reguladoras son una subpoblación de los linfocitos T CD4+ de gran importancia en el establecimiento y mantenimiento de la tolerancia y la homeostasis del sistema inmune. Muchos estudios han analizado la frecuencia de las Treg en pacientes infectados por VIH. Sin embargo, los resultados no son concluyentes y existe una gran controversia sobre el papel que juegan las Treg en el curso de la infección. Recientemente se ha demostrado que el VIH puede infectar las células Treg. Trabajos previos de nuestro grupo demuestran que las Treg son susceptibles de infección por el VIH disminuyendo la expresión del Foxp3 en las células infectadas. Este fenómeno produce una alteración en la capacidad supresora de las células Treg. El objetivo de éste estudio es corroborar dicho comportamiento in vivo y determinar el fenotipo de las Treg en pacientes infectados por VIH. Los resultados preliminares indican que efectivamente la frecuencia de células Foxp3+ es inferior en los pacientes infectados por VIH que en los individuos sanos. El estudio sigue en curso para recopilar un número suficiente de muestras que permitan confirmar estos resultados. Este estudio permitirá conocer mejor el papel de las Treg en el curso de la infección por VIHRegulatory T cells (Treg) are a subpopulation of CD4+ T cells that play a crucial role in establishing and maintaining self-tolerance and immune homeostasis. Many studies have explored the frequency of Treg in HIV infected patients. However, there are controversial findings about the role of these cells in the HIV infection. Nowadays, different studies have showed that Treg cells are susceptible to the HIV infection. Our in vitro data has showed that HIV infects Treg and produces a downregulation of Foxp3 expression. This phenomenon also leads Treg cells to a loss of their immune suppressive capacity. The aim of this study is to corroborate if this behavior also occurs in vivo and determine the Treg phenotype in HIVinfected patients. Preliminary results indicate that frequency of Foxp3+ cells is lower in HIVinfected patients than in healthy volunteers. At present, we are recovering enough number of samples to confirm these results. A better understanding of these cells could serve for the effective exploitation of their suppressive functions for clinical benefit

The Minimum of Solar Cycle 23: As Deep as It Could Be?

In this work we introduce a new way of binning sunspot group data with the purpose of better understanding the impact of the solar cycle on sunspot properties and how this defined the characteristics of the extended minimum of cycle 23. Our approach assumes that the statistical properties of sunspots are completely determined by the strength of the underlying large-scale field and have no additional time dependencies. We use the amplitude of the cycle at any given moment (something we refer to as activity level) as a proxy for the strength of this deep-seated magnetic field. We find that the sunspot size distribution is composed of two populations: one population of groups and active regions and a second population of pores and ephemeral regions. When fits are performed at periods of different activity level, only the statistical properties of the former population, the active regions, is found to vary. Finally, we study the relative contribution of each component (small-scale versus large-scale) to solar magnetism. We find that when hemispheres are treated separately, almost every one of the past 12 solar minima reaches a point where the main contribution to magnetism comes from the small-scale component. However, due to asymmetries in cycle phase, this state is very rarely reached by both hemispheres at the same time. From this we infer that even though each hemisphere did reach the magnetic baseline, from a heliospheric point of view the minimum of cycle 23 was not as deep as it could have been

Respuesta del tomate (Lycopersicon sculentum Mill) a la fertilización con N,P,K y varios elementos menores, en suelos aluviales del Valle del Cauca (Colombia)

Se evaluó el efecto de diferentes dosis y combinaciones de varios nutrimentos y de gallinaza, en el rendimiento y calidad de los frutos de tomate. La investigación se realizó en suelos aluviales de 3 municipios del Valle del Cauca, en sitios representativos de la zona cultivada con tomate. Se estudió el efecto de distintos niveles y combinaciones de: N, P, K, S, Fe, B y Zn y materia orgánica (gallinaza). Se emplearon las variedades Chonto y Manalucie. Los resultados obtenidos indican que aún sin aplicaciones de fertilizantes en lotes previamente cultivados y abonados, se pueden obtener altos rendimientos cuando se efectúan las diferentes prácticas culturales oportuna y adecuadamente. La fertilización afecta la producción y calidad de los frutos. Al aplicar 75-150 kg/ha de N; 50 kg/ha de P2O5 y 50 kg/ha de K2O, se incrementaron los rendimientos entre 30 y 180 por ciento, en comparación con el testigo. La aplicación por separado de 60 kg/ha de sulfato de hierro; 30 kg/ha de sulfato de zinc y 15 kg/ha de bórax, tuvieron un efecto significativo en la producción y la calidad de los frutos. La materia orgánica en dosis altas tuvo efectos negativos en los rendimientos y calidad de los frutos, presentándose un mayor porcentaje de frutos rajadosIn the differents tomatoes growing regions, in alluvial soils of the Cauca Valley, were conducted experiments to test the effects on tomatoes of different dosages of N, P, K, organic matter and trace elements: Zn, Fe, Cu, B and SO4. The soils were acids, low in organic matter content and variables in available phosphorus and exchangeable K levels. The test were carried out during 1974 and 1975 utilizing the "Chonto" variety of tomato in Tuluá and Restrepo and the "Manalucie" variety in Florida. The results shows highest yields of quality-large fruits in "Chonto" variety and large fruits and medium fruits in "Manalucie" variety with 75 kg/Ha de Nitrogen alone or 75 a 150 kg/Ha of N plus 50 kg/Ha of P2 05and K2 0. The trace elements Fe, Zn of B in dosages of 60 kg/Ha of FeSO4 , 30 kg/Ha of ZnSO4or 15 kg/Ha of Borax with 10,67c,of B had significantly influenced in yield. Other elements: Cu and S had a negative effect in yield and quality. The organic matter (gallinaza), in high dosages (10 t/Ha) not shows a definitive effect in yield.Tomate-Solanum lycopersicu

Impact of sensor-augmented pump therapy with predictive low-glucose management on hypoglycemia and glycemic control in patients with type 1 diabetes mellitus : 1-year follow-up

Q2Artículo original2625-2631AIMS: To describe real-life experience with sensor-augmented pump therapy with predictive low-glucose management (SAPT-PLGM), in terms of hypoglycemia and glycemic control after one year of follow-up in T1D patients with hypoglycemia as the main indication of therapy. METHODS: Retrospective cohort study under real life conditions. Baseline and one-year follow-up variables of glycemic control, hypoglycemia and glycemic variability were compared. RESULTS: Fifty patients were included, 31 on prior treatment with SAPT with low-glucose suspend (LGS) feature and 19 on multiple dose insulin injections (MDI). Mean HbA1c decreased in the MDI group (8.24%-7.08%; p = 0.0001). HbA1c change was not significant in the SAPT-LGS group. Area under the curve (AUC) below 70 mg/dl improved in both SAPT-LGS and MDI groups while AUC, %time and events below 54 mg/dl decreased in SAPT-LGS group. Glycemic variability improved in the MDI group. Less patients presented severe hypoglycemia with SAPT-PLGM in both groups, however the change was non-significant. CONCLUSIONS: Under real life conditions, SAPT-PLGM reduced metrics of hypoglycemia in patients previously treaded with MDI and SAPT-LGS without deteriorating glycemic control in SAPT-LGS patients, while improving it in patients treated with MDI

Fine-Tuning Tomato Agronomic Properties by Computational Genome Redesign

Considering cells as biofactories, we aimed to optimize its internal processes by using the same engineering principles that large industries are implementing nowadays: lean manufacturing. We have applied reverse engineering computational methods to transcriptomic, metabolomic and phenomic data obtained from a collection of tomato recombinant inbreed lines to formulate a kinetic and constraint-based model that efficiently describes the cellular metabolism from expression of a minimal core of genes. Based on predicted metabolic profiles, a close association with agronomic and organoleptic properties of the ripe fruit was revealed with high statistical confidence. Inspired in a synthetic biology approach, the model was used for exploring the landscape of all possible local transcriptional changes with the aim of engineering tomato fruits with fine-tuned biotechnological properties. The method was validated by the ability of the proposed genomes, engineered for modified desired agronomic traits, to recapitulate experimental correlations between associated metabolites

Probabilistic Super-Resolution of Solar Magnetograms: Generating Many Explanations and Measuring Uncertainties

Machine learning techniques have been successfully applied to super-resolution tasks on natural images where visually pleasing results are sufficient. However in many scientific domains this is not adequate and estimations of errors and uncertainties are crucial. To address this issue we propose a Bayesian framework that decomposes uncertainties into epistemic and aleatoric uncertainties. We test the validity of our approach by super-resolving images of the Sun's magnetic field and by generating maps measuring the range of possible high resolution explanations compatible with a given low resolution magnetogram