Continuous Blooming of Convex Polyhedra

We construct the first two continuous bloomings of all convex polyhedra. First, the source unfolding can be continuously bloomed. Second, any unfolding of a convex polyhedron can be refined (further cut, by a linear number of cuts) to have a continuous blooming.Comment: 13 pages, 6 figure

Data Structures for Halfplane Proximity Queries and Incremental Voronoi Diagrams

We consider preprocessing a set $S$ of $n$ points in convex position in the plane into a data structure supporting queries of the following form: given a point $q$ and a directed line $\ell$ in the plane, report the point of $S$ that is farthest from (or, alternatively, nearest to) the point $q$ among all points to the left of line $\ell$. We present two data structures for this problem. The first data structure uses $O(n^{1+\varepsilon})$ space and preprocessing time, and answers queries in $O(2^{1/\varepsilon} \log n)$ time, for any $0 < \varepsilon < 1$. The second data structure uses $O(n \log^3 n)$ space and polynomial preprocessing time, and answers queries in $O(\log n)$ time. These are the first solutions to the problem with $O(\log n)$ query time and $o(n^2)$ space. The second data structure uses a new representation of nearest- and farthest-point Voronoi diagrams of points in convex position. This representation supports the insertion of new points in clockwise order using only $O(\log n)$ amortized pointer changes, in addition to $O(\log n)$-time point-location queries, even though every such update may make $\Theta(n)$ combinatorial changes to the Voronoi diagram. This data structure is the first demonstration that deterministically and incrementally constructed Voronoi diagrams can be maintained in $o(n)$ amortized pointer changes per operation while keeping $O(\log n)$-time point-location queries.Comment: 17 pages, 6 figures. Various small improvements. To appear in Algorithmic

Worst-Case Optimal Tree Layout in External Memory

Consider laying out a fixed-topology binary tree of N nodes into external memory with block size B so as to minimize the worst-case number of block memory transfers required to traverse a path from the root to a node of depth D. We prove that the optimal number of memory transfers is Θ([D over lg(1+B))] when D = O(lgN), Θ([lgN over lg(1+[BlgN over D])]) when D=Ω(lgN) and D=O(BlgN), Θ([D over B]) ,when D=Ω(BlgN).National Science Foundation (U.S.) (Grant CCF-0430849)National Science Foundation (U.S.) (Grant OISE-0334653

Amino acid substitutions within the heptad repeat domain 1 of murine coronavirus spike protein restrict viral antigen spread in the central nervous system.

Targeted recombination was carried out to select mouse hepatitis viruses (MHVs) in a defined genetic background, containing an MHV-JHM spike gene encoding either three heptad repeat 1 (HR1) substitutions (Q1067H, Q1094H, and L1114R) or L1114R alone. The recombinant virus, which expresses spike with the three substitutions, was nonfusogenic at neutral pH. Its replication was significantly inhibited by lysosomotropic agents, and it was highly neuroattenuated in vivo. In contrast, the recombinant expressing spike with L1114R alone mediated cell-to-cell fusion at neutral pH and replicated efficiently despite the presence of lysosomotropic agents; however, it still caused only subclinical morbidity and no mortality in animals. Thus, both recombinant viruses were highly attenuated and expressed viral antigen which was restricted to the olfactory bulbs and was markedly absent from other regions of the brains at 5 days postinfection. These data demonstrate that amino acid substitutions, in particular L1114R, within HR1 of the JHM spike reduced the ability of MHV to spread in the central nervous system. Furthermore, the requirements for low pH for fusion and viral entry are not prerequisites for the highly attenuated phenotype

Neuromorphic decoding of spinal motor neuron behaviour during natural hand movements for a new generation of wearable neural interfaces

We propose a neuromorphic framework to process the activity of human spinal motor neurons for movement intention recognition. This framework is integrated into a non-invasive interface that decodes the activity of motor neurons innervating intrinsic and extrinsic hand muscles. One of the main limitations of current neural interfaces is that machine learning models cannot exploit the efficiency of the spike encoding operated by the nervous system. Spiking-based pattern recognition would detect the spatio-temporal sparse activity of a neuronal pool and lead to adaptive and compact implementations, eventually running locally in embedded systems. Emergent Spiking Neural Networks (SNN) have not yet been used for processing the activity of in-vivo human neurons. Here we developed a convolutional SNN to process a total of 467 spinal motor neurons whose activity was identified in 5 participants while executing 10 hand movements. The classification accuracy approached 0.95 ±0.14 for both isometric and non-isometric contractions. These results show for the first time the potential of highly accurate motion intent detection by combining non-invasive neural interfaces and SNN

Merging Active and Passive Data Sets in Travel-Time Tomography: The Case Study of Campi Flegrei Caldera (Southern Italy)

We propose a strategy for merging both active and passive data sets in linearized tomographic inversion. We illustrate this in the reconstruction of 3D images of a complex volcanic structure, the Campi Flegrei caldera, located in the vicinity of the city of Naples, southern Italy. The caldera is occasionally the site of significant unrests characterized by large ground uplifts and seismicity. The P and S velocity models of the caldera structure are obtained by a tomographic inversion based on travel times recorded during two distinct experiments. The first data set is composed of 606 earthquakes recorded in 1984 and the second set is composed of recordings for 1528 shots produced during the SERAPIS experiment in 2001. The tomographic inversion is performed using an improved method based on an accurate finite-difference traveltime computation and a simultaneous inversion of both velocity models and earthquake locations. In order to determine the adequate inversion parameters and relative data weighting factors, we perform massive synthetic simulations allowing one to merge the two types of data optimally. The proper merging provides high resolution velocity models, which allow one to reliably retrieve velocity anomalies over a large part of the tomography area. The obtained images confirm the presence of a high P velocity ring in the southern part of the bay of Pozzuoli and extends its trace inland as compared to previous results. This annular anomaly represents the buried trace of the rim of the Campi Flegrei caldera. Its shape at 1.5 km depth is in good agreement with the location of hydrothermalized lava inferred by gravimetric data modelling. The Vp/Vs model confirms the presence of two characteristic features. At about 1 km depth a very high Vp/Vs anomaly is observed below the town of Pozzuoli and is interpreted as due to the presence of rocks that contain fluids in the liquid phase. A low Vp/Vs body extending at about 3–4 km depth below a large part of the caldera is interpreted as the top of formations that are enriched in gas under supercritical conditions