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Institution

Center for Discrete Mathematics and Theoretical Computer Science

FacilityPiscataway, New Jersey, United States
About: Center for Discrete Mathematics and Theoretical Computer Science is a facility organization based out in Piscataway, New Jersey, United States. It is known for research contribution in the topics: Local search (optimization) & Optimization problem. The organization has 140 authors who have published 175 publications receiving 2345 citations.


Papers
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Journal ArticleDOI
TL;DR: This approach provides a tool that can be used by all managers to provide testable hypotheses regarding the occurrence of ER in declining populations, suggest empirical studies to better parameterize the population genetics and conservation-relevant vital rates, and identify the DIER period during which management strategies will be most effective for species conservation.
Abstract: Ecological factors generally affect population viability on rapid time scales. Traditional population viability analyses (PVA) therefore focus on alleviating ecological pressures, discounting potential evolutionary impacts on individual phenotypes. Recent studies of evolutionary rescue (ER) focus on cases in which severe, environmentally induced population bottlenecks trigger a rapid evolutionary response that can potentially reverse demographic threats. ER models have focused on shifting genetics and resulting population recovery, but no one has explored how to incorporate those findings into PVA. We integrated ER into PVA to identify the critical decision interval for evolutionary rescue (DIER) under which targeted conservation action should be applied to buffer populations undergoing ER against extinction from stochastic events and to determine the most appropriate vital rate to target to promote population recovery. We applied this model to little brown bats (Myotis lucifugus) affected by white-nose syndrome (WNS), a fungal disease causing massive declines in several North American bat populations. Under the ER scenario, the model predicted that the DIER period for little brown bats was within 11 years of initial WNS emergence, after which they stabilized at a positive growth rate (λ = 1.05). By comparing our model results with population trajectories of multiple infected hibernacula across the WNS range, we concluded that ER is a potential explanation of observed little brown bat population trajectories across multiple hibernacula within the affected range. Our approach provides a tool that can be used by all managers to provide testable hypotheses regarding the occurrence of ER in declining populations, suggest empirical studies to better parameterize the population genetics and conservation-relevant vital rates, and identify the DIER period during which management strategies will be most effective for species conservation.

50 citations

Journal ArticleDOI
TL;DR: A dynamical law of critical branching is discovered that reveals a self-similar regularity in the modular organization of the network, and allows one to treat the development of a particular cell function in the context of the complex network of human development as a whole.
Abstract: Cell differentiation in multicellular organisms is a complex process whose mechanism can be understood by a reductionist approach, in which the individual processes that control the generation of different cell types are identified. Alternatively, a large-scale approach in search of different organizational features of the growth stages promises to reveal its modular global structure with the goal of discovering previously unknown relations between cell types. Here, we sort and analyze a large set of scattered data to construct the network of human cell differentiation (NHCD) based on cell types (nodes) and differentiation steps (links) from the fertilized egg to a developed human. We discover a dynamical law of critical branching that reveals a self-similar regularity in the modular organization of the network, and allows us to observe the network at different scales. The emerging picture clearly identifies clusters of cell types following a hierarchical organization, ranging from sub-modules to super-modules of specialized tissues and organs on varying scales. This discovery will allow one to treat the development of a particular cell function in the context of the complex network of human development as a whole. Our results point to an integrated large-scale view of the network of cell types systematically revealing ties between previously unrelated domains in organ functions.

47 citations

Journal ArticleDOI
TL;DR: Traditional probability theory and the ``less traditional'' computational approach are applied to the case where permutations are drawn from a set of pattern avoiders to produce many empirical moments and mixed moments and data suggests that some random variables are not asymptotically normal in this setting.
Abstract: We study statistical properties of the random variables Xσ(π), the number of occurrences of the pattern σ in the permutation π. We present two contrasting approaches to this problem: traditional probability theory and the “less traditional” computational approach. Through the perspective of the first one, we prove that for any pair of patterns σ and τ , the random variables Xσ and Xτ are jointly asymptotically normal (when the permutation is chosen from Sn). From the other perspective, we develop algorithms that can show asymptotic normality and joint asymptotic normality (up to a point) and derive explicit formulas for quite a few moments and mixed moments empirically, yet rigorously. The computational approach can also be extended to the case where permutations are drawn from a set of pattern avoiders to produce many empirical moments and mixed moments. This data suggests that some random variables are not asymptotically normal in this setting.

45 citations

Proceedings ArticleDOI
18 Jun 2017
TL;DR: This paper presents a fast and near-optimal algorithm to solve the mixed-cell-height legalization problem, and provides new generic solutions and research directions for various optimization problems that require solving large-scale quadratic programs efficiently.
Abstract: Modern circuits often contain standard cells of different row heights to meet various design requirements. Higher cells give larger drive strengths at the costs of larger areas and power. Multi-row-height standard cells incur challenging issues to layout designs, especially the mixed-cell-height legalization problem due to the heterogeneous cell structures. Honoring the good cell positions from global placement, we present in this paper a fast and near-optimal algorithm to solve the legalization problem. Fixing the cell ordering from global placement and relaxing the right boundary constraints, we first convert the problem into a linear complementarity problem (LCP). With the converted LCP, we split its matrices to meet the convergence requirement of a modulus-based matrix splitting iteration method (MMSIM), and then apply the MMSIM to solve the LCP. This MMSIM method guarantees the optimality if no cells are placed beyond the right boundary of a chip. Finally, a Tetris-like allocation approach is used to align cells to placement sites on rows and fix the placement of out-of-right-boundary cells, if any. Experimental results show that our proposed algorithm can achieve the best cell displacement and wirelength among all published methods in reasonable runtimes. The MMSIM optimality is theoretically proven and empirically validated. In particular, our formulation provides new generic solutions and research directions for various optimization problems that require solving large-scale quadratic programs efficiently.

42 citations

Proceedings ArticleDOI
01 Jan 2017
TL;DR: A dead-space-aware objective function and an optimization scheme to handle the issue of dead spaces become a critical issue in mixed-cell-height legalization, which cannot be handled well with an Abacus variant alone.
Abstract: For circuit designs in advanced technologies, standard-cell libraries consist of cells with different heights; for example, the number of fins determines the height of cells in the FinFET technology. Cells of larger heights give higher drive strengths, but consume larger areas and power. Such mixed cell heights incur new, complicated challenges for layout designs, due mainly to the heterogeneity in cell dimensions and thus their larger solution spaces. There is not much published work on layout designs with mixed-height standard cells. This paper addresses the legalization problem of mixed-height standard cells, which intends to place cells without any overlap and with minimized displacement. We first study the properties of Abacus, generally considered the best legalization method for traditional single-row-height standard cells but criticized not suitable for handling the new challenge, analyze the capability and insufficiencies of Abacus for tackling the new problem, and remedy Abacuss insufficiencies and extend its advantages to develop an effective and efficient algorithm for the addressed problem. For example, dead spaces become a critical issue in mixed-cell-height legalization, which cannot be handled well with an Abacus variant alone. We thus derive a dead-space-aware objective function and an optimization scheme to handle this issue. Experimental results show that our algorithm can achieve the best wirelength among all published methods in reasonable running time, e.g., about 50% smaller wirelength increase than a state-of-the-art work.

42 citations


Authors

Showing all 148 results

NameH-indexPapersCitations
Aravind Srinivasan6026613711
Ding-Zhu Du5242113489
Elena N. Naumova472328593
Rebecca N. Wright371134722
Boris Mirkin351786722
Mona Singh32915451
Fred S. Roberts321815286
Tanya Y. Berger-Wolf311353624
Rephael Wenger26671900
Marios Mavronicolas261512880
Seoung Bum Kim261652260
M. Montaz Ali261013093
Lazaros K. Gallos24694770
Myong K. Jeong24951955
Nina H. Fefferman231072362
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20233
20226
202112
202017
20198
201822