PUBLIC POLICY EDUCATION FOR WETLANDS ISSUES

Environmental Economics and Policy,

Calabi-Yau threefolds with large h^{2, 1}

We carry out a systematic analysis of Calabi-Yau threefolds that are elliptically fibered with section ("EFS") and have a large Hodge number h^{2, 1}. EFS Calabi-Yau threefolds live in a single connected space, with regions of moduli space associated with different topologies connected through transitions that can be understood in terms of singular Weierstrass models. We determine the complete set of such threefolds that have h^{2, 1} >= 350 by tuning coefficients in Weierstrass models over Hirzebruch surfaces. The resulting set of Hodge numbers includes those of all known Calabi-Yau threefolds with h^{2, 1} >= 350, as well as three apparently new Calabi-Yau threefolds. We speculate that there are no other Calabi-Yau threefolds (elliptically fibered or not) with Hodge numbers that exceed this bound. We summarize the theoretical and practical obstacles to a complete enumeration of all possible EFS Calabi-Yau threefolds and fourfolds, including those with small Hodge numbers, using this approach.Comment: 44 pages, 5 tables, 5 figures; v2: minor corrections; v3: minor corrections, moved figure; v4: typo in Table 2 correcte

Challenges and solutions for autism in academic geosciences

Researcher diversity promotes research excellence. But academia is widely perceived as inaccessible to those who work in non-stereotypical ways, and disabled researchers are consequently chronically under-represented within higher education. The barriers that academia presents to the inclusion and success of disabled individuals must therefore be understood and removed in order to enhance researcher diversity and improve the quality and quantity of research. Autism is a disability that is particularly under-represented within higher education, despite many autistic individuals having attributes that are conducive to research excellence. With a focus on geosciences, we use the experiences of an autistic PhD student to evaluate why academia can be inaccessible, and propose simple strategies that can reduce and remove barriers to academic success. We suggest that minor changes to communication, the academic environment and better disability awareness can make significant differences to the inclusion of disabled researchers, particularly those with autism. These changes would also benefit the wider scientific community and promote research and teaching excellence

Output Reachable Set Estimation and Verification for Multi-Layer Neural Networks

In this paper, the output reachable estimation and safety verification problems for multi-layer perceptron neural networks are addressed. First, a conception called maximum sensitivity in introduced and, for a class of multi-layer perceptrons whose activation functions are monotonic functions, the maximum sensitivity can be computed via solving convex optimization problems. Then, using a simulation-based method, the output reachable set estimation problem for neural networks is formulated into a chain of optimization problems. Finally, an automated safety verification is developed based on the output reachable set estimation result. An application to the safety verification for a robotic arm model with two joints is presented to show the effectiveness of proposed approaches.Comment: 8 pages, 9 figures, to appear in TNNL