@inproceedings{140, abstract = {Reachability analysis is difficult for hybrid automata with affine differential equations, because the reach set needs to be approximated. Promising abstraction techniques usually employ interval methods or template polyhedra. Interval methods account for dense time and guarantee soundness, and there are interval-based tools that overapproximate affine flowpipes. But interval methods impose bounded and rigid shapes, which make refinement expensive and fixpoint detection difficult. Template polyhedra, on the other hand, can be adapted flexibly and can be unbounded, but sound template refinement for unbounded reachability analysis has been implemented only for systems with piecewise constant dynamics. We capitalize on the advantages of both techniques, combining interval arithmetic and template polyhedra, using the former to abstract time and the latter to abstract space. During a CEGAR loop, whenever a spurious error trajectory is found, we compute additional space constraints and split time intervals, and use these space-time interpolants to eliminate the counterexample. Space-time interpolation offers a lazy, flexible framework for increasing precision while guaranteeing soundness, both for error avoidance and fixpoint detection. To the best of out knowledge, this is the first abstraction refinement scheme for the reachability analysis over unbounded and dense time of affine hybrid systems, which is both sound and automatic. We demonstrate the effectiveness of our algorithm with several benchmark examples, which cannot be handled by other tools.}, author = {Frehse, Goran and Giacobbe, Mirco and Henzinger, Thomas A}, issn = {03029743}, location = {Oxford, United Kingdom}, pages = {468 -- 486}, publisher = {Springer}, title = {{Space-time interpolants}}, doi = {10.1007/978-3-319-96145-3_25}, volume = {10981}, year = {2018}, } @inproceedings{141, abstract = {Given a model and a specification, the fundamental model-checking problem asks for algorithmic verification of whether the model satisfies the specification. We consider graphs and Markov decision processes (MDPs), which are fundamental models for reactive systems. One of the very basic specifications that arise in verification of reactive systems is the strong fairness (aka Streett) objective. Given different types of requests and corresponding grants, the objective requires that for each type, if the request event happens infinitely often, then the corresponding grant event must also happen infinitely often. All ω -regular objectives can be expressed as Streett objectives and hence they are canonical in verification. To handle the state-space explosion, symbolic algorithms are required that operate on a succinct implicit representation of the system rather than explicitly accessing the system. While explicit algorithms for graphs and MDPs with Streett objectives have been widely studied, there has been no improvement of the basic symbolic algorithms. The worst-case numbers of symbolic steps required for the basic symbolic algorithms are as follows: quadratic for graphs and cubic for MDPs. In this work we present the first sub-quadratic symbolic algorithm for graphs with Streett objectives, and our algorithm is sub-quadratic even for MDPs. Based on our algorithmic insights we present an implementation of the new symbolic approach and show that it improves the existing approach on several academic benchmark examples.}, author = {Chatterjee, Krishnendu and Henzinger, Monika H and Loitzenbauer, Veronika and Oraee, Simin and Toman, Viktor}, location = {Oxford, United Kingdom}, pages = {178--197}, publisher = {Springer}, title = {{Symbolic algorithms for graphs and Markov decision processes with fairness objectives}}, doi = {10.1007/978-3-319-96142-2_13}, volume = {10982}, year = {2018}, } @inproceedings{14198, abstract = {High-dimensional time series are common in many domains. Since human cognition is not optimized to work well in high-dimensional spaces, these areas could benefit from interpretable low-dimensional representations. However, most representation learning algorithms for time series data are difficult to interpret. This is due to non-intuitive mappings from data features to salient properties of the representation and non-smoothness over time. To address this problem, we propose a new representation learning framework building on ideas from interpretable discrete dimensionality reduction and deep generative modeling. This framework allows us to learn discrete representations of time series, which give rise to smooth and interpretable embeddings with superior clustering performance. We introduce a new way to overcome the non-differentiability in discrete representation learning and present a gradient-based version of the traditional self-organizing map algorithm that is more performant than the original. Furthermore, to allow for a probabilistic interpretation of our method, we integrate a Markov model in the representation space. This model uncovers the temporal transition structure, improves clustering performance even further and provides additional explanatory insights as well as a natural representation of uncertainty. We evaluate our model in terms of clustering performance and interpretability on static (Fashion-)MNIST data, a time series of linearly interpolated (Fashion-)MNIST images, a chaotic Lorenz attractor system with two macro states, as well as on a challenging real world medical time series application on the eICU data set. Our learned representations compare favorably with competitor methods and facilitate downstream tasks on the real world data.}, author = {Fortuin, Vincent and Hüser, Matthias and Locatello, Francesco and Strathmann, Heiko and Rätsch, Gunnar}, booktitle = {International Conference on Learning Representations}, location = {New Orleans, LA, United States}, title = {{SOM-VAE: Interpretable discrete representation learning on time series}}, year = {2018}, } @inproceedings{142, abstract = {We address the problem of analyzing the reachable set of a polynomial nonlinear continuous system by over-approximating the flowpipe of its dynamics. The common approach to tackle this problem is to perform a numerical integration over a given time horizon based on Taylor expansion and interval arithmetic. However, this method results to be very conservative when there is a large difference in speed between trajectories as time progresses. In this paper, we propose to use combinations of barrier functions, which we call piecewise barrier tube (PBT), to over-approximate flowpipe. The basic idea of PBT is that for each segment of a flowpipe, a coarse box which is big enough to contain the segment is constructed using sampled simulation and then in the box we compute by linear programming a set of barrier functions (called barrier tube or BT for short) which work together to form a tube surrounding the flowpipe. The benefit of using PBT is that (1) BT is independent of time and hence can avoid being stretched and deformed by time; and (2) a small number of BTs can form a tight over-approximation for the flowpipe, which means that the computation required to decide whether the BTs intersect the unsafe set can be reduced significantly. We implemented a prototype called PBTS in C++. Experiments on some benchmark systems show that our approach is effective.}, author = {Kong, Hui and Bartocci, Ezio and Henzinger, Thomas A}, location = {Oxford, United Kingdom}, pages = {449 -- 467}, publisher = {Springer}, title = {{Reachable set over-approximation for nonlinear systems using piecewise barrier tubes}}, doi = {10.1007/978-3-319-96145-3_24}, volume = {10981}, year = {2018}, } @inproceedings{14201, abstract = {Variational inference is a popular technique to approximate a possibly intractable Bayesian posterior with a more tractable one. Recently, boosting variational inference has been proposed as a new paradigm to approximate the posterior by a mixture of densities by greedily adding components to the mixture. However, as is the case with many other variational inference algorithms, its theoretical properties have not been studied. In the present work, we study the convergence properties of this approach from a modern optimization viewpoint by establishing connections to the classic Frank-Wolfe algorithm. Our analyses yields novel theoretical insights regarding the sufficient conditions for convergence, explicit rates, and algorithmic simplifications. Since a lot of focus in previous works for variational inference has been on tractability, our work is especially important as a much needed attempt to bridge the gap between probabilistic models and their corresponding theoretical properties.}, author = {Locatello, Francesco and Khanna, Rajiv and Ghosh, Joydeep and Rätsch, Gunnar}, booktitle = {Proceedings of the 21st International Conference on Artificial Intelligence and Statistics}, location = {Playa Blanca, Lanzarote}, pages = {464--472}, publisher = {ML Research Press}, title = {{Boosting variational inference: An optimization perspective}}, volume = {84}, year = {2018}, } @inproceedings{14202, abstract = {Approximating a probability density in a tractable manner is a central task in Bayesian statistics. Variational Inference (VI) is a popular technique that achieves tractability by choosing a relatively simple variational family. Borrowing ideas from the classic boosting framework, recent approaches attempt to \emph{boost} VI by replacing the selection of a single density with a greedily constructed mixture of densities. In order to guarantee convergence, previous works impose stringent assumptions that require significant effort for practitioners. Specifically, they require a custom implementation of the greedy step (called the LMO) for every probabilistic model with respect to an unnatural variational family of truncated distributions. Our work fixes these issues with novel theoretical and algorithmic insights. On the theoretical side, we show that boosting VI satisfies a relaxed smoothness assumption which is sufficient for the convergence of the functional Frank-Wolfe (FW) algorithm. Furthermore, we rephrase the LMO problem and propose to maximize the Residual ELBO (RELBO) which replaces the standard ELBO optimization in VI. These theoretical enhancements allow for black box implementation of the boosting subroutine. Finally, we present a stopping criterion drawn from the duality gap in the classic FW analyses and exhaustive experiments to illustrate the usefulness of our theoretical and algorithmic contributions.}, author = {Locatello, Francesco and Dresdner, Gideon and Khanna, Rajiv and Valera, Isabel and Rätsch, Gunnar}, booktitle = {Advances in Neural Information Processing Systems}, isbn = {9781510884472}, issn = {1049-5258}, location = {Montreal, Canada}, publisher = {Neural Information Processing Systems Foundation}, title = {{Boosting black box variational inference}}, volume = {31}, year = {2018}, } @inproceedings{14203, abstract = {We propose a conditional gradient framework for a composite convex minimization template with broad applications. Our approach combines smoothing and homotopy techniques under the CGM framework, and provably achieves the optimal O(1/k−−√) convergence rate. We demonstrate that the same rate holds if the linear subproblems are solved approximately with additive or multiplicative error. In contrast with the relevant work, we are able to characterize the convergence when the non-smooth term is an indicator function. Specific applications of our framework include the non-smooth minimization, semidefinite programming, and minimization with linear inclusion constraints over a compact domain. Numerical evidence demonstrates the benefits of our framework.}, author = {Yurtsever, Alp and Fercoq, Olivier and Locatello, Francesco and Cevher, Volkan}, booktitle = {Proceedings of the 35th International Conference on Machine Learning}, location = {Stockholm, Sweden}, pages = {5727--5736}, publisher = {ML Research Press}, title = {{A conditional gradient framework for composite convex minimization with applications to semidefinite programming}}, volume = {80}, year = {2018}, } @inproceedings{14204, abstract = {Two popular examples of first-order optimization methods over linear spaces are coordinate descent and matching pursuit algorithms, with their randomized variants. While the former targets the optimization by moving along coordinates, the latter considers a generalized notion of directions. Exploiting the connection between the two algorithms, we present a unified analysis of both, providing affine invariant sublinear O(1/t) rates on smooth objectives and linear convergence on strongly convex objectives. As a byproduct of our affine invariant analysis of matching pursuit, our rates for steepest coordinate descent are the tightest known. Furthermore, we show the first accelerated convergence rate O(1/t2) for matching pursuit and steepest coordinate descent on convex objectives.}, author = {Locatello, Francesco and Raj, Anant and Karimireddy, Sai Praneeth and Rätsch, Gunnar and Schölkopf, Bernhard and Stich, Sebastian U. and Jaggi, Martin}, booktitle = {Proceedings of the 35th International Conference on Machine Learning}, pages = {3198--3207}, publisher = {ML Research Press}, title = {{On matching pursuit and coordinate descent}}, volume = {80}, year = {2018}, } @inproceedings{14224, abstract = {Clustering is a cornerstone of unsupervised learning which can be thought as disentangling multiple generative mechanisms underlying the data. In this paper we introduce an algorithmic framework to train mixtures of implicit generative models which we particularize for variational autoencoders. Relying on an additional set of discriminators, we propose a competitive procedure in which the models only need to approximate the portion of the data distribution from which they can produce realistic samples. As a byproduct, each model is simpler to train, and a clustering interpretation arises naturally from the partitioning of the training points among the models. We empirically show that our approach splits the training distribution in a reasonable way and increases the quality of the generated samples.}, author = {Locatello, Francesco and Vincent, Damien and Tolstikhin, Ilya and Ratsch, Gunnar and Gelly, Sylvain and Scholkopf, Bernhard}, booktitle = {6th International Conference on Learning Representations}, location = {Vancouver, Canada}, title = {{Clustering meets implicit generative models}}, year = {2018}, } @inproceedings{143, abstract = {Vector Addition Systems with States (VASS) provide a well-known and fundamental model for the analysis of concurrent processes, parameterized systems, and are also used as abstract models of programs in resource bound analysis. In this paper we study the problem of obtaining asymptotic bounds on the termination time of a given VASS. In particular, we focus on the practically important case of obtaining polynomial bounds on termination time. Our main contributions are as follows: First, we present a polynomial-time algorithm for deciding whether a given VASS has a linear asymptotic complexity. We also show that if the complexity of a VASS is not linear, it is at least quadratic. Second, we classify VASS according to quantitative properties of their cycles. We show that certain singularities in these properties are the key reason for non-polynomial asymptotic complexity of VASS. In absence of singularities, we show that the asymptotic complexity is always polynomial and of the form Θ(nk), for some integer k d, where d is the dimension of the VASS. We present a polynomial-time algorithm computing the optimal k. For general VASS, the same algorithm, which is based on a complete technique for the construction of ranking functions in VASS, produces a valid lower bound, i.e., a k such that the termination complexity is (nk). Our results are based on new insights into the geometry of VASS dynamics, which hold the potential for further applicability to VASS analysis.}, author = {Brázdil, Tomáš and Chatterjee, Krishnendu and Kučera, Antonín and Novotny, Petr and Velan, Dominik and Zuleger, Florian}, isbn = {978-1-4503-5583-4}, location = {Oxford, United Kingdom}, pages = {185 -- 194}, publisher = {IEEE}, title = {{Efficient algorithms for asymptotic bounds on termination time in VASS}}, doi = {10.1145/3209108.3209191}, volume = {F138033}, year = {2018}, } @article{913, abstract = {Coordinated cell polarization in developing tissues is a recurrent theme in multicellular organisms. In plants, a directional distribution of the plant hormone auxin is at the core of many developmental programs. A feedback regulation of auxin on the polarized localization of PIN auxin transporters in individual cells has been proposed as a self-organizing mechanism for coordinated tissue polarization, but the molecular mechanisms linking auxin signalling to PIN-dependent auxin transport remain unknown. We performed a microarray-based approach to find regulators of the auxin-induced PIN relocation in the Arabidopsis thaliana root. We identified a subset of a family of phosphatidylinositol transfer proteins (PITP), the PATELLINs (PATL). Here, we show that PATLs are expressed in partially overlapping cells types in different tissues going through mitosis or initiating differentiation programs. PATLs are plasma membrane-associated proteins accumulated in Arabidopsis embryos, primary roots, lateral root primordia, and developing stomata. Higher order patl mutants display reduced PIN1 repolarization in response to auxin, shorter root apical meristem, and drastic defects in embryo and seedling development. This suggests PATLs redundantly play a crucial role in polarity and patterning in Arabidopsis.}, author = {Tejos, Ricardo and Rodríguez Furlán, Cecilia and Adamowski, Maciek and Sauer, Michael and Norambuena, Lorena and Friml, Jirí}, issn = {00219533}, journal = {Journal of Cell Science}, number = {2}, publisher = {Company of Biologists}, title = {{PATELLINS are regulators of auxin mediated PIN1 relocation and plant development in Arabidopsis thaliana}}, doi = {10.1242/jcs.204198}, volume = {131}, year = {2018}, } @article{9229, author = {Danzl, Johann G}, issn = {2500-2295}, journal = {Opera Medica et Physiologica}, number = {S1}, pages = {11}, publisher = {Lobachevsky State University of Nizhny Novgorod}, title = {{Diffraction-unlimited optical imaging for synaptic physiology}}, doi = {10.20388/omp2018.00s1.001}, volume = {4}, year = {2018}, } @article{9471, abstract = {The DEMETER (DME) DNA glycosylase catalyzes genome-wide DNA demethylation and is required for endosperm genomic imprinting and embryo viability. Targets of DME-mediated DNA demethylation reside in small, euchromatic, AT-rich transposons and at the boundaries of large transposons, but how DME interacts with these diverse chromatin states is unknown. The STRUCTURE SPECIFIC RECOGNITION PROTEIN 1 (SSRP1) subunit of the chromatin remodeler FACT (facilitates chromatin transactions), was previously shown to be involved in the DME-dependent regulation of genomic imprinting in Arabidopsis endosperm. Therefore, to investigate the interaction between DME and chromatin, we focused on the activity of the two FACT subunits, SSRP1 and SUPPRESSOR of TY16 (SPT16), during reproduction in Arabidopsis. We found that FACT colocalizes with nuclear DME in vivo, and that DME has two classes of target sites, the first being euchromatic and accessible to DME, but the second, representing over half of DME targets, requiring the action of FACT for DME-mediated DNA demethylation genome-wide. Our results show that the FACT-dependent DME targets are GC-rich heterochromatin domains with high nucleosome occupancy enriched with H3K9me2 and H3K27me1. Further, we demonstrate that heterochromatin-associated linker histone H1 specifically mediates the requirement for FACT at a subset of DME-target loci. Overall, our results demonstrate that FACT is required for DME targeting by facilitating its access to heterochromatin.}, author = {Frost, Jennifer M. and Kim, M. Yvonne and Park, Guen Tae and Hsieh, Ping-Hung and Nakamura, Miyuki and Lin, Samuel J. H. and Yoo, Hyunjin and Choi, Jaemyung and Ikeda, Yoko and Kinoshita, Tetsu and Choi, Yeonhee and Zilberman, Daniel and Fischer, Robert L.}, issn = {1091-6490}, journal = {Proceedings of the National Academy of Sciences}, keywords = {Multidisciplinary}, number = {20}, pages = {E4720--E4729}, publisher = {National Academy of Sciences}, title = {{FACT complex is required for DNA demethylation at heterochromatin during reproduction in Arabidopsis}}, doi = {10.1073/pnas.1713333115}, volume = {115}, year = {2018}, } @phdthesis{10, abstract = {Genomic imprinting is an epigenetic process that leads to parent of origin-specific gene expression in a subset of genes. Imprinted genes are essential for brain development, and deregulation of imprinting is associated with neurodevelopmental diseases and the pathogenesis of psychiatric disorders. However, the cell-type specificity of imprinting at single cell resolution, and how imprinting and thus gene dosage regulates neuronal circuit assembly is still largely unknown. Here, MADM (Mosaic Analysis with Double Markers) technology was employed to assess genomic imprinting at single cell level. By visualizing MADM-induced uniparental disomies (UPDs) in distinct colors at single cell level in genetic mosaic animals, this experimental paradigm provides a unique quantitative platform to systematically assay the UPD-mediated imbalances in imprinted gene expression at unprecedented resolution. An experimental pipeline based on FACS, RNA-seq and bioinformatics analysis was established and applied to systematically map cell-type-specific ‘imprintomes’ in the mouse brain. The results revealed that parental-specific expression of imprinted genes per se is rarely cell-type-specific even at the individual cell level. Conversely, when we extended the comparison to downstream responses resulting from imbalanced imprinted gene expression, we discovered an unexpectedly high degree of cell-type specificity. Furthermore, we determined a novel function of genomic imprinting in cortical astrocyte production and in olfactory bulb (OB) granule cell generation. These results suggest important functional implication of genomic imprinting for generating cell-type diversity in the brain. In addition, MADM provides a powerful tool to study candidate genes by concomitant genetic manipulation and fluorescent labelling of single cells. MADM-based candidate gene approach was utilized to identify potential imprinted genes involved in the generation of cortical astrocytes and OB granule cells. We investigated p57Kip2, a maternally expressed gene and known cell cycle regulator. Although we found that p57Kip2 does not play a role in these processes, we detected an unexpected function of the paternal allele previously thought to be silent. Finally, we took advantage of a key property of MADM which is to allow unambiguous investigation of environmental impact on single cells. The experimental pipeline based on FACS and RNA-seq analysis of MADM-labeled cells was established to probe the functional differences of single cell loss of gene function compared to global loss of function on a transcriptional level. With this method, both common and distinct responses were isolated due to cell-autonomous and non-autonomous effects acting on genotypically identical cells. As a result, transcriptional changes were identified which result solely from the surrounding environment. Using the MADM technology to study genomic imprinting at single cell resolution, we have identified cell-type-specific gene expression, novel gene function and the impact of environment on single cell transcriptomes. Together, these provide important insights to the understanding of mechanisms regulating cell-type specificity and thus diversity in the brain.}, author = {Laukoter, Susanne}, issn = {2663-337X}, pages = {1 -- 139}, publisher = {Institute of Science and Technology Austria}, title = {{Role of genomic imprinting in cerebral cortex development}}, doi = {10.15479/AT:ISTA:th1057}, year = {2018}, } @article{1012, abstract = {We prove a new central limit theorem (CLT) for the difference of linear eigenvalue statistics of a Wigner random matrix H and its minor H and find that the fluctuation is much smaller than the fluctuations of the individual linear statistics, as a consequence of the strong correlation between the eigenvalues of H and H. In particular, our theorem identifies the fluctuation of Kerov's rectangular Young diagrams, defined by the interlacing eigenvalues ofH and H, around their asymptotic shape, the Vershik'Kerov'Logan'Shepp curve. Young diagrams equipped with the Plancherel measure follow the same limiting shape. For this, algebraically motivated, ensemble a CLT has been obtained in Ivanov and Olshanski [20] which is structurally similar to our result but the variance is different, indicating that the analogy between the two models has its limitations. Moreover, our theorem shows that Borodin's result [7] on the convergence of the spectral distribution of Wigner matrices to a Gaussian free field also holds in derivative sense.}, author = {Erdös, László and Schröder, Dominik J}, issn = {10737928}, journal = {International Mathematics Research Notices}, number = {10}, pages = {3255--3298}, publisher = {Oxford University Press}, title = {{Fluctuations of rectangular young diagrams of interlacing wigner eigenvalues}}, doi = {10.1093/imrn/rnw330}, volume = {2018}, year = {2018}, } @article{10286, abstract = {In this paper, we evaluate clock signals generated in ring oscillators and self-timed rings and the way their jitter can be transformed into random numbers. We show that counting the periods of the jittery clock signal produces random numbers of significantly better quality than the methods in which the jittery signal is simply sampled (the case in almost all current methods). Moreover, we use the counter values to characterize and continuously monitor the source of randomness. However, instead of using the widely used statistical variance, we propose to use Allan variance to do so. There are two main advantages: Allan variance is insensitive to low frequency noises such as flicker noise that are known to be autocorrelated and significantly less circuitry is required for its computation than that used to compute commonly used variance. We also show that it is essential to use a differential principle of randomness extraction from the jitter based on the use of two identical oscillators to avoid autocorrelations originating from external and internal global jitter sources and that this fact is valid for both kinds of rings. Last but not least, we propose a method of statistical testing based on high order Markov model to show the reduced dependencies when the proposed randomness extraction is applied.}, author = {Allini, Elie Noumon and Skórski, Maciej and Petura, Oto and Bernard, Florent and Laban, Marek and Fischer, Viktor}, issn = {2569-2925}, journal = {IACR Transactions on Cryptographic Hardware and Embedded Systems}, number = {3}, pages = {214--242}, publisher = {International Association for Cryptologic Research}, title = {{Evaluation and monitoring of free running oscillators serving as source of randomness}}, doi = {10.13154/tches.v2018.i3.214-242}, volume = {2018}, year = {2018}, } @article{104, abstract = {The biotrophic pathogen Ustilago maydis, the causative agent of corn smut disease, infects one of the most important crops worldwide – Zea mays. To successfully colonize its host, U. maydis secretes proteins, known as effectors, that suppress plant defense responses and facilitate the establishment of biotrophy. In this work, we describe the U. maydis effector protein Cce1. Cce1 is essential for virulence and is upregulated during infection. Through microscopic analysis and in vitro assays, we show that Cce1 is secreted from hyphae during filamentous growth of the fungus. Strikingly, Δcce1 mutants are blocked at early stages of infection and induce callose deposition as a plant defense response. Cce1 is highly conserved among smut fungi and the Ustilago bromivora ortholog complemented the virulence defect of the SG200Δcce1 deletion strain. These data indicate that Cce1 is a core effector with apoplastic localization that is essential for U. maydis to infect its host.}, author = {Seitner, Denise and Uhse, Simon and Gallei, Michelle C and Djamei, Armin}, journal = {Molecular Plant Pathology}, number = {10}, pages = {2277 -- 2287}, publisher = {Wiley}, title = {{The core effector Cce1 is required for early infection of maize by Ustilago maydis}}, doi = {10.1111/mpp.12698}, volume = {19}, year = {2018}, } @article{106, abstract = {The goal of this article is to introduce the reader to the theory of intrinsic geometry of convex surfaces. We illustrate the power of the tools by proving a theorem on convex surfaces containing an arbitrarily long closed simple geodesic. Let us remind ourselves that a curve in a surface is called geodesic if every sufficiently short arc of the curve is length minimizing; if, in addition, it has no self-intersections, we call it simple geodesic. A tetrahedron with equal opposite edges is called isosceles. The axiomatic method of Alexandrov geometry allows us to work with the metrics of convex surfaces directly, without approximating it first by a smooth or polyhedral metric. Such approximations destroy the closed geodesics on the surface; therefore it is difficult (if at all possible) to apply approximations in the proof of our theorem. On the other hand, a proof in the smooth or polyhedral case usually admits a translation into Alexandrov’s language; such translation makes the result more general. In fact, our proof resembles a translation of the proof given by Protasov. Note that the main theorem implies in particular that a smooth convex surface does not have arbitrarily long simple closed geodesics. However we do not know a proof of this corollary that is essentially simpler than the one presented below.}, author = {Akopyan, Arseniy and Petrunin, Anton}, journal = {Mathematical Intelligencer}, number = {3}, pages = {26 -- 31}, publisher = {Springer}, title = {{Long geodesics on convex surfaces}}, doi = {10.1007/s00283-018-9795-5}, volume = {40}, year = {2018}, } @article{1064, abstract = {In 1945, A.W. Goodman and R.E. Goodman proved the following conjecture by P. Erdős: Given a family of (round) disks of radii r1, … , rn in the plane, it is always possible to cover them by a disk of radius R= ∑ ri, provided they cannot be separated into two subfamilies by a straight line disjoint from the disks. In this note we show that essentially the same idea may work for different analogues and generalizations of their result. In particular, we prove the following: Given a family of positive homothetic copies of a fixed convex body K⊂ Rd with homothety coefficients τ1, … , τn> 0 , it is always possible to cover them by a translate of d+12(∑τi)K, provided they cannot be separated into two subfamilies by a hyperplane disjoint from the homothets.}, author = {Akopyan, Arseniy and Balitskiy, Alexey and Grigorev, Mikhail}, issn = {14320444}, journal = {Discrete & Computational Geometry}, number = {4}, pages = {1001--1009}, publisher = {Springer}, title = {{On the circle covering theorem by A.W. Goodman and R.E. Goodman}}, doi = {10.1007/s00454-017-9883-x}, volume = {59}, year = {2018}, } @article{12, abstract = {Molding is a popular mass production method, in which the initial expenses for the mold are offset by the low per-unit production cost. However, the physical fabrication constraints of the molding technique commonly restrict the shape of moldable objects. For a complex shape, a decomposition of the object into moldable parts is a common strategy to address these constraints, with plastic model kits being a popular and illustrative example. However, conducting such a decomposition requires considerable expertise, and it depends on the technical aspects of the fabrication technique, as well as aesthetic considerations. We present an interactive technique to create such decompositions for two-piece molding, in which each part of the object is cast between two rigid mold pieces. Given the surface description of an object, we decompose its thin-shell equivalent into moldable parts by first performing a coarse decomposition and then utilizing an active contour model for the boundaries between individual parts. Formulated as an optimization problem, the movement of the contours is guided by an energy reflecting fabrication constraints to ensure the moldability of each part. Simultaneously, the user is provided with editing capabilities to enforce aesthetic guidelines. Our interactive interface provides control of the contour positions by allowing, for example, the alignment of part boundaries with object features. Our technique enables a novel workflow, as it empowers novice users to explore the design space, and it generates fabrication-ready two-piece molds that can be used either for casting or industrial injection molding of free-form objects.}, author = {Nakashima, Kazutaka and Auzinger, Thomas and Iarussi, Emmanuel and Zhang, Ran and Igarashi, Takeo and Bickel, Bernd}, journal = {ACM Transaction on Graphics}, number = {4}, publisher = {ACM}, title = {{CoreCavity: Interactive shell decomposition for fabrication with two-piece rigid molds}}, doi = {10.1145/3197517.3201341}, volume = {37}, year = {2018}, }