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We developed the Systems Thinking (ST) and Computational Thinking (CT) Identification Tool (ID Tool) to identify student involvement in ST and CT as they construct and revise computational models. Our ID Tool builds off the ST and CT Through Modeling Framework, emphasizing the synergistic relationship between ST and CT and demonstrating how both can be supported through computational modeling. This paper describes the process of designing and validating the ID Tool with special emphasis on the observable indicators of testing and debugging computational models. We collected 75 hours of students’ interactions with a computational modeling tool and analyzed them using the ID Tool to characterize students’ use of ST and CT when involved in modeling. The results suggest that the ID Tool has the potential to allow researchers and practitioners to identify student involvement in various aspects of ST and CT as they construct and revise computational models. 

This study explores how to support teachers in developing and implementing effective pedagogical strategies to promote students in making sense of phenomena through computational modeling in remote contexts. Qualitative analyses of eight teachers’ interviews were conducted to characterize their pedagogical strategies to achieve three-dimensional learning. Findings indicate that typical teacher strategies include the teacher and students co-constructing a model and using whole class or group discussions to support students’ modeling practices. 

Theβ-delayed neutron-emission probabilities of 28 exotic neutron-rich isotopes of Pm, Sm, Eu, and Gd were measured for the first time at RIKEN Nishina Center using the Advanced Implantation Detector Array (AIDA) and the BRIKEN neutron detector array. The existingβ-decay half-life (T_1/2) database was significantly increased toward more neutron-rich isotopes, and uncertainties for previously measured values were decreased. The new data not only constrain the theoretical predictions of half-lives andβ-delayed neutron-emission probabilities, but also allow for probing the mechanisms of formation of the high-mass wing of the rare-earth peak located atA≈ 160 in ther-process abundance distribution through astrophysical reaction network calculations. An uncertainty quantification of the calculated abundance patterns with the new data shows a reduction of the uncertainty in the rare-earth peak region. The newly introduced variance-based sensitivity analysis method offers valuable insight into the influence of important nuclear physics inputs on the calculated abundance patterns. The analysis has identified the half-lives of¹⁶⁸Sm and of several gadolinium isotopes as some of the key variables among the current experimental data to understand the remaining abundance uncertainty atA= 167–172.

 

Cycles of dehydration and rehydration could have enabled formation of peptides and RNA in otherwise unfavorable conditions on the early Earth. Development of the first protocells would have hinged upon colocalization of these biopolymers with fatty acid membranes. Using atomic force microscopy, we find that a prebiotic fatty acid (decanoic acid) forms stacks of membranes after dehydration. Using LC‐MS‐MS (liquid chromatography‐tandem mass spectrometry) with isotope internal standards, we measure the rate of formation of serine dipeptides. We find that dipeptides form during dehydration at moderate temperatures (55 °C) at least as fast in the presence of decanoic acid membranes as in the absence of membranes. Our results are consistent with the hypothesis that protocells could have formed within evaporating environments on the early Earth.

 

A description is presented of the algorithms used to reconstruct energy deposited in the CMS hadron calorimeter during Run 2 (2015–2018) of the LHC. During Run 2, the characteristic bunch-crossing spacing for proton-proton collisions was 25 ns, which resulted in overlapping signals from adjacent crossings. The energy corresponding to a particular bunch crossing of interest is estimated using the known pulse shapes of energy depositions in the calorimeter, which are measured as functions of both energy and time. A variety of algorithms were developed to mitigate the effects of adjacent bunch crossings on local energy reconstruction in the hadron calorimeter in Run 2, and their performance is compared.