A Content Analysis of Sex Trafficking Instruments

International Journal for the Advancement of Counselling - This content analysis examined assessments available for the screening of sex trafficking to provide professional counselors further...     

Untangling Trustworthiness and Uncertainty in Science

Science & Education - This article focuses on uncertainty—ways in which scientists recognize and analyze limits in their studies and conclusions. We distinguish uncertainty from...     

Association between prenatal maternal anxiety and/or stress and offspring's cognitive functioning: A meta-analysis

This meta-analysis examined the relationship between prenatal maternal stress and/or anxiety and the outcomes of children aged 3 months to 9 years. Of the 8754 studies published before June 2021 that were synthesized, 17 conducted in Western countries were included in the meta-analysis (N_total = 23,307; M_males 54%; M_ethnicity White 77%, Pacific 15%, African American/Black 10%, Middle Eastern 7%, Eastern 8%). Effect sizes ranged from −0.41 to 0.15. A weak negative association was found between prenatal stress and/or anxiety exposure and children's general intellectual development. Associations varied based on the type of exposure. Findings are limited to developed counties and cannot be generalized to low- and middle-income countries. Directions for maternal prenatal intervention and future studies are discussed.     

Instructional practices in secondary science: How teachers achieve local and standards-based success

This article reports on analyses of the instructional practices of six middle- and high-school science teachers in the United States who participated in a research-practice partnership that aims to support reform science education goals at scale. All six teachers were well qualified, experienced, and locally successful—respected by students, parents, colleagues, and administrators—but they differed in their success in supporting students' three-dimensional learning. Our goal is to understand how the teachers' instructional practices contributed to their similarities in achieving local success and to differences in enabling students' learning, and to consider the implications of these findings for research-practice partnerships. Data sources included classroom videos supplemented by interviews with teachers and focus students and examples of student work. We also compared students' learning gains by teacher using pre–post assessments that elicited three-dimensional performances. Analyses of classroom videos showed how all six teachers achieved local success—they led effectively managed classrooms, covered the curriculum by teaching almost all unit activities, and assessed students' work in fair and efficient ways. There were important differences, however, in how teachers engaged students in science practices. Teachers in classrooms where students achieved lower learning gains followed a pattern of practice we describe as activity-based teaching, in which students completed investigations and hands-on activities with few opportunities for sensemaking discussions or three-dimensional science performances. Teachers whose students achieved higher learning gains combined the social stability characteristic of local classroom success with more demanding instructional practices associated with scientific sensemaking and cognitive apprenticeship. We conclude with a discussion of implications for research-practice partnerships, highlighting how partnerships need to support all teachers in achieving both local and standards-based success.     

Sub-nanomolar detection of thrombin activity on a microfluidic chip

Bioluminescence resonance energy transfer (BRET) is a form of Förster resonance energy transfer. BRET has been shown to support lower limits of detection than fluorescence resonance energy transfer (FRET) but, unlike FRET, has not been widely implemented on microfluidic devices for bioanalytical sensing. We recently reported a microscope-based microfluidic system for BRET-based biosensing, using a hybrid, high quantum-efficiency, form of BRET chemistry. This paper reports the first optical fiber-based system for BRET detection on a microfluidic chip, capable of quantifying photon emissions from the low quantum-efficiency BRET² system. We investigated the effects of varying core diameter and numerical aperture of optical fibers, as well as varying microfluidic channel design and measurement conditions. We optimized the set-up in order to maximize photon counts and minimize the response time. The optimized conditions supported measurement of thrombin activity, with a limit of detection of 20 pM, which is lower than the microscope-based system and more than 20 times lower than concentrations reported to occur in plasma clots.     

Embellishing Problem-Solving Examples with Deep Structure Information Facilitates Transfer

Appreciation of problem structure is critical to successful learning. Two experiments investigated effective ways of communicating problem structure in a computer-based learning environment and tested whether verbal instruction is necessary to specify solution steps, when deep structure is already embellished by instructional examples. Participants learned to solve algebra-like problems and then solved transfer problems that required adjustment of learned procedures. Experiment 1 demonstrated that verbal instruction helped learning by reducing learners' floundering, but its positive effect disappeared in the transfer. More importantly, students transferred better when they studied with examples that emphasized problem structure rather than solution procedure. Experiment 2 showed that verbal instruction was not necessarily more effective than nonverbal scaffolding to convey problem structure. Final understanding was determined by transparency of problem structure regardless of presence of verbal instruction. However, verbal instruction had a positive impact on learners by having them persist through the task, and optimal instructional choices were likely to differ depending on populations of learners.     

Novel model reference adaptive control laws for improved transient dynamics and guaranteed saturation constraints

In classical model reference adaptive control (MRAC), the adaptive rates must be tuned to meet multiple competing objectives. Large adaptive rates guarantee rapid convergence of the trajectory tracking error to zero. However, large adaptive rates may also induce saturation of the actuators and excessive overshoots of the closed-loop system’s trajectory tracking error. Conversely, low adaptive rates may produce unsatisfactory trajectory tracking performances. To overcome these limitations, in the classical MRAC framework, the adaptive rates must be tuned through an iterative process. Alternative approaches require to modify the plant’s reference model or the reference command input. This paper presents the first MRAC laws for nonlinear dynamical systems affected by matched and parametric uncertainties that constrain both the closed-loop system’s trajectory tracking error and the control input at all times within user-defined bounds, and enforce a user-defined rate of convergence on the trajectory tracking error. By applying the proposed MRAC laws, the adaptive rates can be set arbitrarily large and both the plant’s reference model and the reference command input can be chosen arbitrarily. The user-defined rate of convergence of the closed-loop plant’s trajectory is enforced by introducing a user-defined auxiliary reference model, which converges to the trajectory tracking error obtained by applying the classical MRAC laws before its transient dynamics has decayed, and steering the trajectory tracking error to the auxiliary reference model at a rate of convergence that is higher than the rate of convergence of the plant’s reference model. The ability of the proposed MRAC laws to prescribe the performance of the closed-loop system’s trajectory tracking error and control input is guaranteed by barrier Lyapunov functions. Numerical simulations illustrate both the applicability of our theoretical results and their effectiveness compared to other techniques such as prescribed performance control, which allows to constrain both the rate of convergence and the maximum overshoot on the trajectory tracking error of uncertain systems.