Unraveling the influence of domain knowledge during simulation-based inquiry learning

This study investigated whether the mere knowledge of the meaning of variables can facilitate inquiry learning processes and outcomes. Fifty-seven college freshmen were randomly allocated to one of three inquiry tasks. The concrete task had familiar variables from which hypotheses about their underlying relations could be inferred. The intermediate task used familiar variables that did not invoke underlying relations, whereas the abstract task contained unfamiliar variables that did not allow for inference of hypotheses about relations. Results showed that concrete participants performed more successfully and efficiently than intermediate participants, who in turn were equally successful and efficient as abstract participants. From these findings it was concluded that students learning by inquiry benefit little from knowledge of the meaning of variables per se. Some additional understanding of the way these variables are interrelated seems required to enhance inquiry learning processes and outcomes

Trust in everyday life

Although trust plays a pivotal role in many aspects of life, very little is known about the manifestation of trust and distrust in everyday life. In this work, we integrated several prior approaches to trust and investigated the prevalence and key determinants of trust (vs. distrust) in people’s natural environments, using preregistered experience-sampling methodology. Across more than 4,500 social interactions from a heterogeneous sample of 427 participants, results showed high average levels of trust, but also considerable variability in trust across contexts. This variability was attributable to aspects of trustee perception, social distance, as well as three key dimensions of situational interdependence: conflict of interests, information (un)certainty, and power imbalance. At the dispositional level, average everyday trust was shaped by general trust, moral identity, and zero-sum beliefs. The social scope of most trust-related traits, however, was moderated by social distance: Whereas moral identity buffered against distrusting distant targets, high general distrust and low social value orientation amplified trust differences between close vs. distant others. Furthermore, a laboratory-based trust game predicted everyday trust only with regard to more distant but not close interaction partners. Finally, everyday trust was linked to self-disclosure and to cooperation, particularly in situations of high conflict between interaction partners’ interests. We conclude that trust can be conceptualized as a relational hub that interconnects the social perception of the trustee, the relational closeness between trustor and trustee, key structural features of situational interdependence, and behavioral response options such as self-disclosure

Semimechanistic Clearance Models of Oncology Biotherapeutics and Impact of Study Design: Cetuximab as a Case Study

This study aimed to explore the currently competing and new semimechanistic clearance models for monoclonal antibodies and the impact of clearance model misspecification on exposure metrics under different study designs exemplified for cetuximab. Six clearance models were investigated under four different study designs (sampling density and single/multiple-dose levels) using a rich data set from two cetuximab clinical trials (226 patients with metastatic colorectal cancer) and using the nonlinear mixed-effects modeling approach. A two-compartment model with parallel Michaelis-Menten and time-decreasing linear clearance adequately described the data, the latter being related to post-treatment response. With respect to bias in exposure metrics, the simplified time-varying linear clearance (CL) model was the best alternative. Time-variance of the linear CL component should be considered for biotherapeutics if response impacts pharmacokinetics. Rich sampling at steady-state was crucial for unbiased estimation of Michaelis-Menten elimination in case of the reference (parallel Michaelis-Menten and time-varying linear CL) model

Teaching design engineering in an interdisciplinary programme

ATLAS, the Academy of Technology and Liberal Arts & Sciences, is an interdisciplinary three-year Bachelor of Science honours programme for talented students that opened its doors in September 2013. This international programme uses the concept of project-led education to teach students to integrate both technical and social perspectives into a new engineering approach. It aims to educate the so-called ‘new engineer’: a generalist who can combine technological and societal approaches with design solutions that can be implemented in a range of technical, social, and cultural contexts. The programme has a thematic structure, in which a large project is the foundation of every semester. At the start of the semester the students write their own personal development plan framed by three domains (Engineering, Mathematics and Social Sciences) and six learning lines (Research, Design, Organization, Communication, Learning Capacity and Interdisciplinarity). In an interdisciplinary programme like ATLAS students have to learn to use knowledge from different disciplines and integrate it. This is also demanded by the project description, which is always a complex open-ended interdisciplinary problem. Design models from both engineering and social sciences are combined to develop new solutions for boundary-crossing problems. In this paper we will describe the programme and its underlying educational principles in detail. We will show the interdisciplinary design-engineering model that we use in our programme. We will reflect upon our first experiences with the programme and define a set of challenges for teaching design engineering in an interdisciplinary programme

Towards Finding Optimal Solutions For Constrained Warehouse Layouts Using Answer Set Programming

A minimum requirement of feasible order picking layouts is the accessibility of every storage location. Obeying only this requirement typically leads to a vast amount of different layouts that are theoretically possible. Being able to generate all of these layouts automatically opens the door for new layouts and is valuable training data for reinforcement learning, e.g., for operating strategies of automated guided vehicles. We propose an approach using answer set programming that is able to generate and select optimal order picking layouts with regards to a defined objective function for given warehouse structures in a short amount of time. This constitutes a significant step towards reliable artificial intelligence. In a first step all feasible layout solutions are generated and in a second step an objective function is applied to get an optimal layout with regards to a defined layout problem. In brownfield projects this can lead to non-traditional layouts that are manually hard to find. The implementation can be customized for different use cases in the field of order picking layout generation, while the core logic stays the same

Probing spin and orbital Kondo effects with a mesoscopic interferometer

We investigate theoretically the transport properties of a closed Aharonov-Bohm interferometer containing two quantum dots in the strong coupling regime. We find two distinct physical scenarios depending on the strength of the interdot Coulomb interaction. When the interdot Coulomb interaction is negligible only spin fluctuations are important and each dot develops a Kondo resonance at the Fermi level independently of the applied magnetic flux. The transport is characterized by the interference of these two independent Kondo resonances. On the contrary, for large interdot interaction, only one electron can be accommodated onto the double dot system. In this situation, not only the spin can fluctuate but also the orbital degree of freedom (the pseudo-spin). As a result, we find different ground states depending on the value of the applied flux. When $\phi=\pi$ (mod $2\pi$) ($\phi=2\pi\Phi/\Phi_0$, where $\Phi$ is applied flux, and $\Phi_0=h/e$ the flux quantum) the electronic transport can take place via simultaneous correlations in the spin and pseudo-spin sectors, leading to the highly symmetric SU(4) Kondo state. Nevertheless, we find situations with $\phi>0$ (mod $2\pi$) where the pseudo-spin quantum number is not conserved during tunneling events, giving rise to the common SU(2) Kondo state with an enhanced Kondo temperature. We investigate the crossover between both ground states and discuss possible experimental signatures of this physics as a function of the applied magnetic flux.Comment: 12 pages, 3 figures; extended discussions, improved presentatio