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1. P acific R im A pplications and G rid M iddleware A ssembly ( PRAGMA ): I nternational clouds for data science

   https://doi.org/10.1002/cpe.4140  

   Plale, Beth ; Chen, Maio ( April 2017 , Concurrency and Computation: Practice and Experience)
2. Developing and validating Next Generation Science Standards ‐aligned learning progression to track three‐dimensional learning of electrical interactions in high school physical science

   https://doi.org/10.1002/tea.21672  

   Kaldaras, Leonora ; Akaeze, Hope ; Krajcik, Joseph ( October 2020 , Journal of Research in Science Teaching)

   The Framework for K‐12 science education (TheFramework) and Next Generation Science Standards (NGSS) emphasize the usefulness of learning progressions in helping align curriculum, instruction, and assessment to organize the learning process. TheFrameworkdefines three dimensions of science as the basis of theoretical learning progressions described in the document and used to develop NGSS. The three dimensions include disciplinary core ideas, scientific and engineering practices, and crosscutting concepts. TheFrameworkdefines three‐dimensional learning (3D learning) as integrating scientific and engineering practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena. Three‐dimensional learning leads to the development of a deep, useable understanding of big ideas that students can apply to explain phenomena and solve real‐life problems. While theFrameworkdescribes the theoretical basis of 3D learning, and NGSS outlines possible theoretical learning progressions for the three dimensions across grades, we currently have very limited empirical evidence to show that a learning progression for 3D learning can be developed and validated in practice. In this paper, we demonstrate the feasibility of developing a 3D learning progression (3D LP) supported by qualitative and quantitative validity evidence. We first present a hypothetical 3D LP aligned to a previously designed NGSS‐based curriculum. We further present multiple sources of validity evidence for the hypothetical 3D LP, including interview analysis and item response theory (IRT) analysis to show validity evidence for the 3D LP. Finally, we demonstrate the feasibility of using the assessment tool designed to probe levels of the 3D LP for assigning 3D LP levels to individual student answers, which is essential for the practical applicability of any LP. This work demonstrates the usefulness of validated 3D LP for organizing the learning process in the NGSS classroom, which is essential for the successful implementation of NGSS.

    

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3. A CRISPR ‐based strategy for targeted sequencing in biodiversity science

   https://doi.org/10.1111/1755-0998.13920  

   Littleford‐Colquhoun, Bethan ; Kartzinel, Tyler R. ( December 2023 , Molecular Ecology Resources)

   Many applications in molecular ecology require the ability to match specific DNA sequences from single‐ or mixed‐species samples with a diagnostic reference library. Widely used methods for DNA barcoding and metabarcoding employ PCR and amplicon sequencing to identify taxa based on target sequences, but the target‐specific enrichment capabilities of CRISPR‐Cas systems may offer advantages in some applications. We identified 54,837 CRISPR‐Cas guide RNAs that may be useful for enriching chloroplast DNA across phylogenetically diverse plant species. We tested a subset of 17 guide RNAs in vitro to enrich plant DNA strands ranging in size from diagnostic DNA barcodes of 1,428 bp to entire chloroplast genomes of 121,284 bp. We used an Oxford Nanopore sequencer to evaluate sequencing success based on both single‐ and mixed‐species samples, which yielded mean chloroplast sequence lengths of 2,530–11,367 bp, depending on the experiment. In comparison to mixed‐species experiments, single‐species experiments yielded more on‐target sequence reads and greater mean pairwise identity between contigs and the plant species' reference genomes. But nevertheless, these mixed‐species experiments yielded sufficient data to provide ≥48‐fold increase in sequence length and better estimates of relative abundance for a commercially prepared mixture of plant species compared to DNA metabarcoding based on the chloroplasttrnL‐P6 marker. Prior work developed CRISPR‐based enrichment protocols for long‐read sequencing and our experiments pioneered its use for plant DNA barcoding and chloroplast assemblies that may have advantages over workflows that require PCR and short‐read sequencing. Future work would benefit from continuing to develop in vitro and in silico methods for CRISPR‐based analyses of mixed‐species samples, especially when the appropriate reference genomes for contig assembly cannot be known a priori.

    

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4. Webs of science: mentor networks influence women's integration into STEM fields

   https://doi.org/10.1002/fee.2666  

   Hernandez, Paul R ; Patterson, Megan S ; Nyanamba, Juliet M ; Adams, Amanda S ; Barnes, Rebecca T ; Bloodhart, Brittany ; Burt, Melissa ; Clinton, Sandra M ; Pollack, Ilana B ; Fischer, Emily V ( July 2023 , Frontiers in Ecology and the Environment)

   Mentorship can be part of the solution to developing a more diverse global scientific workforce, but robust longitudinal evidence is limited. Developmental mentor network theory can advance our understanding of the impact of a wide range of mentors across social contexts by distinguishing between the content of mentorship support (eg career support) and the structural characteristics of an individual's mentor network (eg density of connections among mentors). We tested the influence of mentor network characteristics on longitudinal social integration into the Earth and environmental sciences, as indicated by science identity development (a key indicator of social integration) and graduate‐school applications in STEM (science, technology, engineering, and mathematics)‐related fields of study, based on a sample of 233 undergraduate women at nine universities in the US. Our findings indicated that belonging to close‐knit, larger, and skill‐focused mentorship networks creates a “sticky web” of social connections, providing information and resources that increase retention of college women in the Earth and environmental sciences. 

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5. Epihiper —A high performance computational modeling framework to support epidemic science

   https://doi.org/10.1093/pnasnexus/pgae557  

   Chen, Jiangzhuo ; Hoops, Stefan ; Mortveit, Henning_S ; Lewis, Bryan_L ; Machi, Dustin ; Bhattacharya, Parantapa ; Venkatramanan, Srinivasan ; Wilson, Mandy_L ; Barrett, Chris_L ; Marathe, Madhav_V ; et al ( December 2024 , PNAS Nexus)

   This paper describes Epihiper, a state-of-the-art, high performance computational modeling framework for epidemic science. The Epihiper modeling framework supports custom disease models, and can simulate epidemics over dynamic, large-scale networks while supporting modulation of the epidemic evolution through a set of user-programmable interventions. The nodes and edges of the social-contact network have customizable sets of static and dynamic attributes which allow the user to specify intervention target sets at a very fine-grained level; these also permit the network to be updated in response to nonpharmaceutical interventions, such as school closures. The execution of interventions is governed by trigger conditions, which are Boolean expressions formed using any of Epihiper’s primitives (e.g. the current time, transmissibility) and user-defined sets (e.g. people with work activities). Rich expressiveness, extensibility, and high-performance computing responsiveness were central design goals to ensure that the framework could effectively target realistic scenarios at the scale and detail required to support the large computational designs needed by state and federal public health policymakers in their efforts to plan and respond in the event of epidemics. The modeling framework has been used to support the CDC Scenario Modeling Hub for COVID-19 response, and was a part of a hybrid high-performance cloud system that was nominated as a finalist for the 2021 ACM Gordon Bell Special Prize for high performance computing-based COVID-19 Research.

    

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