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1. Analyzing Multiple-Choice-Multiple-Response Items Using Item Response Theory

   https://doi.org/10.1119/perc.2022.pr.Smith  

   Smith, Trevor I.; Eaton, Philip; White Brahmia, Suzanne; Olsho, Alexis; Zimmerman, Charlotte; Boudreaux, Andrew (September 2022, Analyzing Multiple-Choice-Multiple-Response Items Using Item Response Theory)
2. Methods for utilizing Item response theory with Coupled, Multiple-Response assessments

   https://doi.org/10.1119/perc.2022.pr.Wilcox  

   Wilcox, Bethany R.; Rainey, Katherine D.; Vignal, Michael (September 2022, Physics Education Research Conference Proceedings)

   Recent years have seen a movement within the research-based assessment development community towards item formats that go beyond simple multiple-choice formats. Some have moved towards free-response questions, particularly at the upper-division level; however, free-response items have the constraint that they must be scored by hand. To avoid this limitation, some assessment developers have moved toward formats that maintain the closed-response format, while still providing more nuanced insight into student reasoning. One such format is known as coupled, multiple response (CMR). This format pairs multiple-choice and multiple-response formats to allow students to both commit to an answer in addition to selecting options that correspond with their reasoning. In addition to being machine-scorable, this format allows for more nuanced scoring than simple right or wrong. However, such nuanced scoring presents a potential challenge with respect to utilizing certain testing theories to construct validity arguments for the assessment. In particular, Item Response Theory (IRT) models often assume dichotomously scored items. While polytomous IRT models do exist, each brings with it certain constraints and limitations. Here, we will explore multiple IRT models and scoring schema using data from an existing CMR test, with the goal of providing guidance and insight for possible methods for simultaneously leveraging the affordances of both the CMR format and IRT models in the context of constructing validity arguments for research-based assessments. 

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3. Response and adaptation of the transcriptional heat shock response to pressure

   https://doi.org/10.3389/fmicb.2024.1470617  

   Coffin, Carleton H; Fisher, Luke A; Crippen, Sara; Demers, Phoebe; Bartlett, Douglas H; Royer, Catherine A (November 2024, Frontiers in Microbiology)

   IntroductionThe molecular mechanisms underlying pressure adaptation remain largely unexplored, despite their significance for understanding biological adaptation and improving sterilization methods in the food and beverage industry. The heat shock response leads to a global stabilization of the proteome. Prior research suggested that the heat shock regulon may exhibit a transcriptional response to high-pressure stress. MethodsIn this study, we investigated the pressure-dependent heat shock response inE. colistrains using plasmid-borne green fluorescent protein (GFP) promoter fusions and fluorescence fluctuation microscopy. ResultsWe quantitatively confirm that key heat shock genes-rpoH,rpoE,dnaK, andgroEL- are transcriptionally upregulated following pressure shock in both piezosensitiveEscherichia coliand a more piezotolerant laboratory-evolved strain, AN62. Our quantitative imaging results provide the first single cell resolution measurements for both the heat shock and pressure shock transcriptional responses, revealing not only the magnitude of the responses, but also the biological variance involved. Moreover, our results demonstrate distinct responses in the pressure-adapted strain. Specifically,P_groELis upregulated more thanP_dnaKin AN62, while the reverse is true in the parental strain. Furthermore, unlike in the parental strain, the pressure-induced upregulation ofP_rpoEis highly stochastic in strain AN62, consistent with a strong feedback mechanism and suggesting that RpoE could act as a pressure sensor. DiscussionDespite its capacity to grow at pressures up to 62 MPa, the AN62 genome shows minimal mutations, with notable single nucleotide substitutions in genes of the transcriptionally importantbsubunit of RNA polymerase and the Rho terminator. In particular, the mutation in RNAP is one of a cluster of mutations known to confer rifampicin resistance toE. colivia modification of RNAP pausing and termination efficiency. The observed differences in the pressure and heat shock responses between the parental MG1655 strain and the pressure-adapted strain AN62 could arise in part from functional differences in their RNAP molecules. 

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4. Shape of species climate response curves affects community response to climate change

   https://doi.org/10.1111/ele.13688  

   Bonachela, Juan_A; Burrows, Michael_T; Pinsky, Malin_L; Calcagno, ed., Vincent (February 2021, Ecology Letters)

   Abstract Understanding how community composition is reshaped by changing climate is important for interpreting and predicting patterns of community assembly through time or across space. Community composition often does not perfectly correspond to expectations from current environmental conditions, leading to community‐climate mismatches. Here, we combine data analysis and theory development to explore how species climate response curves affect the community response to climate change. We show that strong mismatches between community and climate can appear in the absence of demographic delays or limited species pools. Communities simulated using species response curves showed temporal changes of similar magnitude to those observed in natural communities of fishes and plankton, suggesting no overall delays in community change despite substantial unexplained variation from community assembly and other processes. Our approach can be considered as a null model that will be important to use when interpreting observed community responses to climate change and variability. 

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5. Response thresholds generalize across problem instances for a deterministic response multiagent system

   Mathias, H. David; Wu, Annie S.; and Dang, Daniel (January 2021, Proceedings of the Genetic and Evolutionary Computation Conference)

   null (Ed.)

   In this work, we use a multiobjective genetic algorithm to evolve agent response thresholds for a decentralized swarm and demonstrate that swarms with evolved thresholds outperform swarms with thresholds set using other methods. In addition, we provide evidence that the effectiveness of evolved thresholds is due in part to the evolutionary process being able to find, not just good distributions of thresholds for a given task across all agents, but also good combinations of thresholds over all tasks for individual agents. Finally, we show that thresholds evolved for some problem instances can effectively generalize to other problem instances with very different task demands. 

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