184,219 research outputs found

    Automated weighing by sequential inference in dynamic environments

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    We demonstrate sequential mass inference of a suspended bag of milk powder from simulated measurements of the vertical force component at the pivot while the bag is being filled. We compare the predictions of various sequential inference methods both with and without a physics model to capture the system dynamics. We find that non-augmented and augmented-state unscented Kalman filters (UKFs) in conjunction with a physics model of a pendulum of varying mass and length provide rapid and accurate predictions of the milk powder mass as a function of time. The UKFs outperform the other method tested - a particle filter. Moreover, inference methods which incorporate a physics model outperform equivalent algorithms which do not.Comment: 5 pages, 7 figures. Copyright IEEE (2015

    Scaling universalities of kth-nearest neighbor distances on closed manifolds

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    Take N sites distributed randomly and uniformly on a smooth closed surface. We express the expected distance from an arbitrary point on the surface to its kth-nearest neighboring site, in terms of the function A(l) giving the area of a disc of radius l about that point. We then find two universalities. First, for a flat surface, where A(l)=\pi l^2, the k-dependence and the N-dependence separate in . All kth-nearest neighbor distances thus have the same scaling law in N. Second, for a curved surface, the average \int d\mu over the surface is a topological invariant at leading and subleading order in a large N expansion. The 1/N scaling series then depends, up through O(1/N), only on the surface's topology and not on its precise shape. We discuss the case of higher dimensions (d>2), and also interpret our results using Regge calculus.Comment: 14 pages, 2 figures; submitted to Advances in Applied Mathematic

    Experiences with Problem-Based Learning: Virginia Initiative for Science Teaching and Achievement

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    The Virginia Initiative for Science Teaching and Achievement (VISTA) provides high-quality professional development for teachers and administrators to enhance the quality of their science instructional programs. One emphasis of this program is helping teachers learn to implement Problem-Based Learning in the elementary science classroom. Problem-Based Learning (PBL) has the potential to produce significant positive outcomes for students, such as increased student engagement, and opportunities for in-depth critical thinking [1]. Teachers find PBL challenging because it does take additional time for planning and material acquisition, but experience has shown that the benefits outweigh these challenges. Setting clear goals, identifying specific learning objectives, and developing big questions that tie these together help increase the success of the unit. Additionally, administrators can help teachers succeed in implementing a Problem-Based Learning unit by understanding the dynamic nature of the PBL environment, providing flexibility with unit pacing, and setting aside time for refining, reflection, and revision of the unit

    Dirac Triplet Extension of the MSSM

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    In this paper we explore extensions of the Minimal Supersymmetric Standard Model involving two SU(2)LSU(2)_L triplet chiral superfields that share a superpotential Dirac mass yet only one of which couples to the Higgs fields. This choice is motivated by recent work using two singlet superfields with the same superpotential requirements. We find that, as in the singlet case, the Higgs mass in the triplet extension can easily be raised to 125GeV125\,\text{GeV} without introducing large fine-tuning. For triplets that carry hypercharge, the regions of least fine tuning are characterized by small contributions to the T\mathcal T parameter, and light stop squarks, mt~1300450GeVm_{\tilde t_1} \sim 300-450\,\text{GeV}; the latter is a result of the tanβ\tan\beta dependence of the triplet contribution to the Higgs mass. Despite such light stop masses, these models are viable provided the stop-electroweakino spectrum is sufficiently compressed.Comment: 26 pages, 4 figure

    Edge usage, motifs and regulatory logic for cell cycling genetic networks

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    The cell cycle is a tightly controlled process, yet its underlying genetic network shows marked differences across species. Which of the associated structural features follow solely from the ability to impose the appropriate gene expression patterns? We tackle this question in silico by examining the ensemble of all regulatory networks which satisfy the constraint of producing a given sequence of gene expressions. We focus on three cell cycle profiles coming from baker's yeast, fission yeast and mammals. First, we show that the networks in each of the ensembles use just a few interactions that are repeatedly reused as building blocks. Second, we find an enrichment in network motifs that is similar in the two yeast cell cycle systems investigated. These motifs do not have autonomous functions, but nevertheless they reveal a regulatory logic for cell cycling based on a feed-forward cascade of activating interactions.Comment: 9 pages, 9 figures, to be published in Phys. Rev.
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