Coronal holes are recognized as the primary sources of heliospheric open magnetic flux (OMF). However, a noticeable gap exists between in situ measured OMF and that derived from remote-sensing observations of the Sun. In this study, we investigate the OMF evolution and its connection to solar structures throughout 2014, with special emphasis on the period from September to October, where a sudden and significant OMF increase was reported. By deriving the OMF evolution at 1 au, modeling it at the source surface, and analyzing solar photospheric data, we provide a comprehensive analysis of the observed phenomenon. First, we establish a strong correlation between the OMF increase and the solar magnetic field derived from a potential-field source-surface model (
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Abstract cc Pearson= 0.94). Moreover, we find a good correlation between the OMF and the open flux derived from solar coronal holes (cc Pearson= 0.88), although the coronal holes only contain 14%–32% of the Sun’s total open flux. However, we note that while the OMF evolution correlates with coronal hole open flux, there is no correlation with the coronal hole area evolution (cc Pearson= 0.0). The temporal increase in OMF correlates with the vanishing remnant magnetic field at the southern pole, caused by poleward flux circulations from the decay of numerous active regions months earlier. Additionally, our analysis suggests a potential link between the OMF enhancement and the concurrent emergence of the largest active region in solar cycle 24. In conclusion, our study provides insights into the strong increase in OMF observed during 2014 September–October. -
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Abstract Background Numerous studies show that active and engaging classrooms help students learn and persist in college, but adoption of new teaching practices has been slow. Professional development programs encourage instructors to implement new teaching methods and change the status quo in STEM undergraduate teaching, and structured observations of classrooms can be used in multiple ways to describe and assess this instruction. We addressed the challenge of measuring instructional change with observational protocols, data that often do not lend themselves easily to statistical comparisons. Challenges using observational data in comparative research designs include lack of descriptive utility for holistic measures and problems related to construct representation, non-normal distributions and Type-I error inflation for segmented measures.
Results We grouped 790 mathematics classes from 74 instructors using Latent Profile Analysis (a statistical clustering technique) and found four reliable categories of classes. Based on this grouping we proposed a simple proportional measure we called Proportion Non-Didactic Lecture (PND). The measure aggregated the proportions of interactive to lecture classes for each instructor. We tested the PND and a measure derived from the Reformed Teaching Observation Protocol (RTOP) with data from a professional development study. The PND worked in simple hypothesis tests but lacked some statistical power due to possible ceiling effects. However, the PND provided effective descriptions of changes in instructional approaches from pre to post. In tandem with examining the proportional measure, we also examined the RTOP-Sum, an existing outcome measure used in comparison studies. The measure is based on the aggregated items in a holistic observational protocol. As an aggregate measure we found it to be highly reliable, correlated highly with the PND, and had more statistical power than the PND. However, the RTOP measure did not provide the thick descriptions of teaching afforded by the PND.
Conclusions Findings suggest that useful dependent measures can be derived from both segmented and holistic observational measures. Both have strengths and weaknesses: measures from segmented data are best at describing changes in teaching, while measures derived from the RTOP have more statistical power. Determining the validity of these measures is important for future use of observational data in comparative studies.
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Abstract The arrival time prediction of coronal mass ejections (CMEs) is an area of active research. Many methods with varying levels of complexity have been developed to predict CME arrival. However, the mean absolute error (MAE) of predictions remains above 12 hr, even with the increasing complexity of methods. In this work we develop a new method for CME arrival time prediction that uses magnetohydrodynamic simulations involving data-constrained flux-rope-based CMEs, which are introduced in a data-driven solar wind background. We found that for six CMEs studied in this work the MAE in arrival time was ∼8 hr. We further improved our arrival time predictions by using ensemble modeling and comparing the ensemble solutions with STEREO-A and STEREO-B heliospheric imager data. This was done by using our simulations to create synthetic J-maps. A machine-learning (ML) method called the lasso regression was used for this comparison. Using this approach, we could reduce the MAE to ∼4 hr. Another ML method based on the neural networks (NNs) made it possible to reduce the MAE to ∼5 hr for the cases when HI data from both STEREO-A and STEREO-B were available. NNs are capable of providing similar MAE when only the STEREO-A data are used. Our methods also resulted in very encouraging values of standard deviation (precision) of arrival time. The methods discussed in this paper demonstrate significant improvements in the CME arrival time predictions. Our work highlights the importance of using ML techniques in combination with data-constrained magnetohydrodynamic modeling to improve space weather predictions.
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Abstract Background Double-strand break repair (DSBR) is a highly regulated process involving dozens of proteins acting in a defined order to repair a DNA lesion that is fatal for any living cell. Model organisms such as
Saccharomyces cerevisiae have been used to study the mechanisms underlying DSBR, including factors influencing its efficiency such as the presence of distinct combinations of microsatellites and endonucleases, mainly by bulk analysis of millions of cells undergoing repair of a broken chromosome. Here, we use a microfluidic device to demonstrate in yeast that DSBR may be studied at a single-cell level in a time-resolved manner, on a large number of independent lineages undergoing repair.Results We used engineered
S. cerevisiae cells in which GFP is expressed following the successful repair of a DSB induced by Cas9 or Cpf1 endonucleases, and different genetic backgrounds were screened to detect key events leading to the DSBR efficiency. Per condition, the progenies of 80–150 individual cells were analyzed over 24 h. The observed DSBR dynamics, which revealed heterogeneity of individual cell fates and their contributions to global repair efficacy, was confronted with a coupled differential equation model to obtain repair process rates. Good agreement was found between the mathematical model and experimental results at different scales, and quantitative comparisons of the different experimental conditions with image analysis of cell shape enabled the identification of three types of DSB repair events previously not recognized: high-efficacy error-free, low-efficacy error-free, and low-efficacy error-prone repair.Conclusions Our analysis paves the way to a significant advance in understanding the complex molecular mechanism of DSB repair, with potential implications beyond yeast cell biology. This multiscale and multidisciplinary approach more generally allows unique insights into the relation between in vivo microscopic processes within each cell and their impact on the population dynamics, which were inaccessible by previous approaches using molecular genetics tools alone.
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The increase in fires at the wildland–urban interface has raised concerns about the potential environmental impact of ash remaining after burning. Here, we examined the concentrations and speciation of iron-bearing nanoparticles in wildland–urban interface ash. Total iron concentrations in ash varied between 4 and 66 mg g −1 . Synchrotron X-ray absorption near-edge structure (XANES) spectroscopy of bulk ash samples was used to quantify the relative abundance of major Fe phases, which were corroborated by transmission electron microscopy measurements. Maghemite (γ-(Fe 3+ ) 2 O 3 ) and magnetite (γ-Fe 2+ (Fe 3+ ) 2 O 4 ) were detected in most ashes and accounted for 0–90 and 0–81% of the spectral weight, respectively. Ferrihydrite (amorphous Fe( iii )–hydroxide, (Fe 3+ ) 5 HO 8 ·4H 2 O), goethite (α-Fe 3+ OOH), and hematite (α-Fe 3+ 2 O 3 ) were identified less frequently in ashes than maghemite and magnetite and accounted for 0–65, 0–54, and 0–50% of spectral weight, respectively. Other iron phases identified in ashes include wüstite (Fe 2+ O), zerovalent iron, FeS, FeCl 2 , FeCl 3 , FeSO 4 , Fe 2 (SO 4 ) 3 , and Fe(NO 3 ) 3 . Our findings demonstrate the impact of fires at the wildland–urban interface on iron speciation; that is, fires can convert iron oxides ( e.g. , maghemite, hematite, and goethite) to reduced iron phases such as magnetite, wüstite, and zerovalent iron. Magnetite concentrations ( e.g. , up to 25 mg g −1 ) decreased from black to gray to white ashes. Based on transmission electron microscopy (TEM) analyses, most of the magnetite nanoparticles were less than 500 nm in size, although larger particles were identified. Magnetite nanoparticles have been linked to neurodegenerative diseases as well as climate change. This study provides important information for understanding the potential environmental impacts of fires at the wildland–urban interface, which are currently poorly understood.more » « less
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Abstract Flux-rope-based magnetohydrodynamic modeling of coronal mass ejections (CMEs) is a promising tool for prediction of the CME arrival time and magnetic field at Earth. In this work, we introduce a constant-turn flux rope model and use it to simulate the 2012 July 12 16:48 CME in the inner heliosphere. We constrain the initial parameters of this CME using the graduated cylindrical shell (GCS) model and the reconnected flux in post-eruption arcades. We correctly reproduce all the magnetic field components of the CME at Earth, with an arrival time error of approximately 1 hr. We further estimate the average subjective uncertainties in the GCS fittings by comparing the GCS parameters of 56 CMEs reported in multiple studies and catalogs. We determined that the GCS estimates of the CME latitude, longitude, tilt, and speed have average uncertainties of 5.°74, 11.°23, 24.°71, and 11.4%, respectively. Using these, we have created 77 ensemble members for the 2012 July 12 CME. We found that 55% of our ensemble members correctly reproduce the sign of the magnetic field components at Earth. We also determined that the uncertainties in GCS fitting can widen the CME arrival time prediction window to about 12 hr for the 2012 July 12 CME. On investigating the forecast accuracy introduced by the uncertainties in individual GCS parameters, we conclude that the half-angle and aspect ratio have little impact on the predicted magnetic field of the 2012 July 12 CME, whereas the uncertainties in longitude and tilt can introduce relatively large spread in the magnetic field predicted at Earth.more » « less
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Abstract Phenotypic divergence is an important consequence of restricted gene flow in insular populations. This divergence can be challenging to detect when it occurs through subtle shifts in morphological traits, particularly in traits with complex geometries, like insect wing venation. Here, we employed geometric morphometrics to assess the extent of variation in wing venation patterns across reproductively isolated populations of the social sweat bee,
Halictus tripartitus . We examined wing morphology of specimens sampled from a reproductively isolated population ofH. tripartitus on Santa Cruz Island (Channel Islands, Southern California). Our analysis revealed significant differentiation in wing venation in this island population relative to conspecific mainland populations. We additionally found that this population‐level variation was less pronounced than the species‐level variation in wing venation among three sympatric congeners native to the region,Halictus tripartitus ,Halictus ligatus , andHalictus farinosus . Together, these results provide evidence for subtle phenotypic divergence in an island bee population. More broadly, these results emphasize the utility and potential of wing morphometrics for large‐scale assessment of insect population structure. -
Zou, Di (Ed.)Professional development has been identified as an effective way to increase college STEM instructors’ use of research-based instructional strategies (RBIS) known to benefit student learning and persistence in STEM. Yet only a few studies relate professional development experiences to later teaching behaviors of higher education instructors. This study of 361 undergraduate mathematics instructors, all of whom participated in multi-day, discipline-based workshops on teaching held in 2010–2019, examined the relationship between such participation and later use of RBIS. We found that instructors’ RBIS attitudes, knowledge, and skills strengthened after participating in professional development, and their self-reported use of RBIS became more frequent in the first year after the workshop. Applying the Theory of Planned Behavior as a conceptual framework, we used a structural equation model to test whether this theory could explain the roles of workshop participation and other personal, professional and contextual factors in fostering RBIS use. Findings indicated that, along with workshop participation, prior RBIS experience, class size, and course coordination affected RBIS use. That is, both targeted professional development and elements of the local context for implementation were important in supporting instructors’ uptake of RBIS—but, remarkably, both immediate and longer-term outcomes of professional development did not depend on other individual or institutional characteristics. In this study, the large sample size, longitudinal measurement approach, and consistency of the form and quality of professional development make it possible to distinguish the importance of multiple possible influences on instructors’ uptake of RBIS. We discuss implications for professional development and for institutional structures that support instructors as they apply what they learned, and we offer suggestions for the use of theory in future research on this topic.more » « less
