The Effects of Prehydration on Cement Performance

This study investigated the effects of cement prehydration on cement’s engineering properties. Anhydrous cement was exposed over a saturated KCl solution to maintain 85% RH, for 7 and 28 days. Mortar and cement pastes were tested for strength, workability and setting time, with sample analysis by XRD and DTA. Results showed a decreased reactivity of the prehydrated cements resulting in reduced strength and increased setting times. We propose that this may be due to an upset of the sulphate balance in the cement upon prehydration

Anatomy of STEM teaching in North American universities

A large body of evidence demonstrates that strategies that promote student interactions and cognitively engage students with content (1) lead to gains in learning and attitudinal outcomes for students in science, technology, engineering, and mathematics (STEM) courses (1, 2). Many educational and governmental bodies have called for and supported adoption of these student-centered strategies throughout the undergraduate STEM curriculum. But to the extent that we have pictures of the STEM undergraduate instructional landscape, it has mostly been provided through self-report surveys of faculty members, within a particular STEM discipline [e.g., (3–6)]. Such surveys are prone to reliability threats and can underestimate the complexity of classroom environments, and few are implemented nationally to provide valid and reliable data (7). Reflecting the limited state of these data, a report from the U.S. National Academies of Sciences, Engineering, and Medicine called for improved data collection to understand the use of evidence-based instructional practices (8). We report here a major step toward a characterization of STEM teaching practices in North American universities based on classroom observations from over 2000 classes taught by more than 500 STEM faculty members across 25 institutions

Rmi1 stimulates decatenation of double Holliday junctions during dissolution by Sgs1-Top3

double Holliday junction (dHJ) is a central intermediate of homologous recombination that can be processed to yield crossover or non-crossover recombination products. To preserve genomic integrity, cells possess mechanisms to avoid crossing over. We show that Saccharomyces cerevisiae Sgs1 and Top3 proteins are sufficient to migrate and disentangle a dHJ to produce exclusively non-crossover recombination products, in a reaction termed "dissolution." We show that Rmi1 stimulates dHJ dissolution at low Sgs1-Top3 protein concentrations, although it has no effect on the initial rate of Holliday junction (HJ) migration. Rmi1 serves to stimulate DNA decatenation, removing the last linkages between the repaired and template DNA molecules. Dissolution of a dHJ is a highly efficient and concerted alternative to nucleolytic resolution that prevents crossing over of chromosomes during recombinational DNA repair in mitotic cells and thereby contributes to genomic integrity

Motivational decline and recovery in higher education STEM courses

Decline in student motivation is a concern for STEM education, especially for underrepresented groups in the sciences. Using the Science Motivation Questionnaire II, 41 foundational STEM courses were surveyed at the beginning and end of each semester in an academic year at a small primarily undergraduate university. Significant pre- to post-semester declines were observed in each of five measured motivational factors (Intrinsic motivation, Career motivation, Self determination, Self-efficacy, and Grade motivation), with effect sizes ranging from 0.21 to 0.41. However, in the second semester pre-survey, four motivational factors rebounded, including three returning to initial levels, suggesting that the observed motivational decline is not long-lasting. Analysis suggests that declines are not related to survey fatigue or student demographics, but rather to grades and, in the case of one motivational factor, to academic field. These findings suggest that a refocus on grading practices across STEM fields may influence student motivation and persistence in STEM

Collective Lévy walk for efficient exploration in unknown environments

One of the key tasks of autonomous mobile robots is to explore the unknown environment under limited energy and deadline conditions. In this paper, we focus on one of the most efficient random walks found in the natural and biological system, i.e., Lévy walk. We show how Lévy properties disappear in larger robot swarm sizes because of spatial interferences and propose a novel behavioral algorithm to preserve Lévy properties at the collective level. Our initial findings hold potential to accelerate target search processes in large unknown environments by parallelizing Lévy exploration using a group of robots

Anatomy of STEM teaching in North American Universities

A large body of evidence demonstrates that strategies that promote student interactions and cognitively engage students with content lead to gains in learning and attitudinal outcomes for students in science, technology, engineering, and mathematics (STEM) courses. Many educational and governmental bodies have called for and supported adoption of these student centered strategies throughout the undergraduate STEM curriculum

What Comes Next? Evaluating Uncertainty in Neural Text Generators Against Human Production Variability

In Natural Language Generation (NLG) tasks, for any input, multiple communicative goals are plausible, and any goal can be put into words, or produced, in multiple ways. We characterise the extent to which human production varies lexically, syntactically, and semantically across four NLG tasks, connecting human production variability to aleatoric or data uncertainty. We then inspect the space of output strings shaped by a generation system’s predicted probability distribution and decoding algorithm to probe its uncertainty. For each test input, we measure the generator’s calibration to human production variability. Following this instance-level approach, we analyse NLG models and decoding strategies, demonstrating that probing a generator with multiple samples and, when possible, multiple references, provides the level of detail necessary to gain understanding of a model’s representation of uncertainty