Path planning for complex terrain navigation via dynamic programming

This work considers the problem of planning optimal paths for a mobile robot traversing complex terrain. In addition to the existing obstacles, locations in the terrain where the slope is too steep for the mobile robot to navigate safely without tipping over become mathematically equivalent to extra obstacles. To solve the optimal path problem, the authors use a dynamic programming approach. The dynamic programming approach utilized herein does not suffer the difficulties associated with spurious local minima that the artificial potential field approaches do. In fact, a globally optimal solution is guaranteed to be found if a feasible solution exists. The method is demonstrated on several complex examples including very complex terrains

From aggregation to interpretation:how assessors judge complex data in a competency-based portfolio

While portfolios are increasingly used to assess competence, the validity of such portfolio-based assessments has hitherto remained unconfirmed. The purpose of the present research is therefore to further our understanding of how assessors form judgments when interpreting the complex data included in a competency-based portfolio. Eighteen assessors appraised one of three competency-based mock portfolios while thinking aloud, before taking part in semi-structured interviews. A thematic analysis of the think-aloud protocols and interviews revealed that assessors reached judgments through a 3-phase cyclical cognitive process of acquiring, organizing, and integrating evidence. Upon conclusion of the first cycle, assessors reviewed the remaining portfolio evidence to look for confirming or disconfirming evidence. Assessors were inclined to stick to their initial judgments even when confronted with seemingly disconfirming evidence. Although assessors reached similar final (pass-fail) judgments of students' professional competence, they differed in their information-processing approaches and the reasoning behind their judgments. Differences sprung from assessors' divergent assessment beliefs, performance theories, and inferences about the student. Assessment beliefs refer to assessors' opinions about what kind of evidence gives the most valuable and trustworthy information about the student's competence, whereas assessors' performance theories concern their conceptualizations of what constitutes professional competence and competent performance. Even when using the same pieces of information, assessors furthermore differed with respect to inferences about the student as a person as well as a (future) professional. Our findings support the notion that assessors' reasoning in judgment and decision-making varies and is guided by their mental models of performance assessment, potentially impacting feedback and the credibility of decisions. Our findings also lend further credence to the assertion that portfolios should be judged by multiple assessors who should, moreover, thoroughly substantiate their judgments. Finally, it is suggested that portfolios be designed in such a way that they facilitate the selection of and navigation through the portfolio evidence

YidC and SecY mediate membrane insertion of a type I transmembrane domain

YidC has been identified recently as an evolutionary conserved factor that is involved in the integration of inner membrane proteins (IMPs) in Escherichia coli. The discovery of YidC has inspired the reevaluation of membrane protein assembly pathways in E. coli. In this study, we have analyzed the role of YidC in membrane integration of a widely used model IMP, leader peptidase (Lep). Site-directed photocross-linking experiments demonstrate that both YidC and SecY contact nascent Lep very early during biogenesis, at only 50-amino acid nascent chain length. At this length the first transmembrane domain (TM), which acquires a type I topology, is not even fully exposed outside the ribosome. The pattern of interactions appears dependent on the position of the cross-linking probe in the nascent chain. Upon elongation, nascent Lep remains close to YidC and comes into contact with lipids as well. Our results suggest a role for YidC in both the reception and lipid partitioning of type I TMs

A robust line search for learning control

In this paper a new line search for a Newton Rhapson learning control algorithm is presented. Theorems and rigorous proofs of its increased robustness over existing line searches are provided, and numerical examples are used to further validate the theorems. Also, the previously posed open question of whether robust optimal trajectory learning is possible is also addressed. It is shown that the answer is generally no, at least for gradient-based learning control algorithms