A PageRank-based heuristic for the minimization of open stacks problem.

The minimization of open stacks problem (MOSP) aims to determine the ideal production sequence to optimize the occupation of physical space in manufacturing settings. Most of current methods for solving the MOSP were not designed to work with large instances, precluding their use in specific cases of similar modeling problems. We therefore propose a PageRank-based heuristic to solve large instances modeled in graphs. In computational experiments, both data from the literature and new datasets up to 25 times fold larger in input size than current datasets, totaling 1330 instances, were analyzed to compare the proposed heuristic with state-of-the-art methods. The results showed the competitiveness of the proposed heuristic in terms of quality, as it found optimal solutions in several cases, and in terms of shorter run times compared with the fastest available method. Furthermore, based on specific graph densities, we found that the difference in the value of solutions between methods was small, thus justifying the use of the fastest method. The proposed heuristic is scalable and is more affected by graph density than by size

Singlet Extensions of the MSSM in the Quiver Landscape

We map out possible extensions of the MSSM in the context of type II string theory. We systematically investigate three-stack and four-stack quivers which realize the MSSM spectrum with the addition of a single MSSM singlet S with an allowed S H_u H_d term, which can lead to a dynamical electroweak-scale mu-term. We present the three quivers which satisfy stringent string-theoretic and phenomenological constraints, including the presence of non-zero masses for all three families of quarks and leptons, the perturbative and non-perturbative absence of R-parity violating couplings and rapid dimension-five proton decay, and a mechanism for small neutrino masses. We find that these quivers can realize many models in the class of singlet-extended (supersymmetric) standard models, as D-instanton effects can in principle generate a superpotential of the form f(S), where f is a polynomial. Finally, we address the issue of the stabilization and decoupling of charged moduli which generically appear in D-instanton corrections to the superpotential.Comment: 15 pages, plus references. Version 2: accepted to JHE

Straightening Caenorhabditis elegans images

Motivation: Caenorhabditis elegans, a roundworm found in soil, is a widely studied model organism with about 1000 cells in the adult. Producing high-resolution fluorescence images of C.elegans to reveal biological insights is becoming routine, motivating the development of advanced computational tools for analyzing the resulting image stacks. For example, worm bodies usually curve significantly in images. Thus one must ‘straighten’ the worms if they are to be compared under a canonical coordinate system

Um algoritmo exato para o problema de realocação de blocos usando novos limitantes inferiores

Orientadores: Eduardo Candido Xavier, Carla Negri LintzmayerDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: O Problema de Realocação de Blocos é um problema importante em sistemas de armazenamento. Um exemplo de entrada para este problema consiste em um conjunto de blocos distribuídos em pilhas, onde cada bloco é identicado por um número que representa sua prioridade de recuperação e todas as pilhas têm um mesmo limite de altura. Apenas blocos no topo de uma pilha podem ser movidos, com dois tipos de movimentos: ou um bloco é recuperado, o que ocorre quando ele tem a mais alta prioridade de recuperação entre os blocos empilhados, ou um bloco é realocado do topo de uma pilha para o topo de outra pilha. O objetivo é recuperar todos os blocos, respeitando sua prioridade de recuperação e executando o menor número de realocações. Resolver este problema é crítico em sistemas de armazenamento, pois economiza tempo e recursos operacionais. Apresentamos dois novos limitantes inferiores para o número de realocações em uma solução ótima. Implementamos um algoritmo de deepening A* usando esses limites inferiores propostos e outros limites inferiores bem conhecidos da literatura. Foi realizado um extenso conjunto de experimentos computacionais mostrando que os novos limites inferiores melhoram o desempenho do algoritmo exato, resolvendo mais instâncias otimamente do que quando usando outros limites inferiores na mesma quantidade de tempoAbstract: The Blocks Relocation Problem is an important problem in storage systems. An input instance for this problem consists of a set of blocks distributed in stacks where each block is identified by a retrieval priority number and each stack has the same maximum height limit. Only blocks at the top of a stack can be moved: either a block is retrieved, if it has the highest retrieval priority among the stacked blocks, or it is relocated to the top of another stack. The objective is to retrieve all the blocks, respecting their retrieval priority while performing the minimum number of relocations. Solving this problem is critical in storage systems because it saves operational time and resources. We present two new lower bounds for the number of relocations of an optimal solution. We implemented an iterative deepening A* algorithm using these new proposed lower bounds and other well- known lower bounds from the literature. We performed an extensive set of computational experiments showing that the new lower bounds improve the performance of the exact algorithm, solving to optimality more instances than when using other lower bounds in the same amount of timeMestradoCiência da ComputaçãoMestre em Ciência da ComputaçãoCAPE

Predicting folding pathways between RNA conformational structures guided by RNA stacks

Background: Accurately predicting low energy barrier folding pathways between conformational secondary structures of an RNA molecule can provide valuable information for understanding its catalytic and regulatory functions. Most existing heuristic algorithms guide the construction of folding pathways by free energies of intermediate structures in the next move during the folding. However due to the size and ruggedness of RNA energy landscape, energy-guided search can become trapped in local optima. Results: In this paper, we propose an algorithm that guides the construction of folding pathways through the formation and destruction of RNA stacks. Guiding the construction of folding pathways by coarse grained movements of RNA stacks can help reduce the search space and make it easier to jump out of local optima. RNAEAPath is able to find lower energy barrier folding pathways between secondary structures of conformational switches and outperforms the existing heuristic algorithms in most test cases. Conclusions: RNAEAPath provides an alternate approach for predicting low-barrier folding pathways between RNA conformational secondary structures. The source code of RNAEAPath and the test data sets are available at http://genome.ucf.edu/RNAEAPath

Precise segmentation of densely interweaving neuron clusters using G-Cut

脑是宇宙间最为复杂的系统之一，成人的脑中有约1000亿个神经元，单个神经元通常与其它神经元有成千上万个“突触”连接节点，形成拥有百万亿级连接的极其复杂的脑神经网络。当前多数神经元三维重建和分析工具仅适用于单个神经元的形态学重建，难以从神经元簇图像中正确追踪重建出多个神经元，而神经元的重建质量又影响到量化分析神经元的形态学特征及其功能。针对这一问题，课题组提出一种新的三维神经元簇重建工具G-Cut。具体地，为了度量神经元胞体与神经突起间的关联性，课题组从已有的带有标注的大规模神经元形态学数据集统计分析得到其规律和形态学信息。然后将神经元簇的重建问题转化为神经突起之间连接所形成的拓扑连接图的图分割问题，并结合神经元形态学规律和信息，在所有的神经突起与神经元胞体的关联性中寻找重建问题的最优解。通过在不同的合成数据集以及真实的脑组织图像数据集上测试，和已有的方法相比，G-Cut在不同密度和不同规模的神经元簇图像上均获得了更高的重建正确率。该项研究工作由厦门大学，南加州大学，加州大学洛杉矶分校等高校课题组合作完成，厦门大学信息学院智能科学与技术系为第一完成单位，厦门大学博士生李睿和USC博士生Muye Zhu为论文共同第一作者，张俊松博士和南加州大学的Hong-Wei Dong教授为论文共同通讯作者。厦门大学周昌乐教授和南加州大学的Arthur Toga教授为研究提供了大力支持。【Abstract】Characterizing the precise three-dimensional morphology and anatomical context of neurons is crucial for neuronal cell type classification and circuitry mapping. Recent advances in tissue clearing techniques and microscopy make it possible to obtain image stacks of intact, interweaving neuron clusters in brain tissues. As most current 3D neuronal morphology reconstruction methods are only applicable to single neurons, it remains challenging to reconstruct these clusters digitally. To advance the state of the art beyond these challenges, we propose a fast and robust method named G-Cut that is able to automatically segment individual neurons from an interweaving neuron cluster. Across various densely interconnected neuron clusters, G-Cut achieves significantly higher accuracies than other state-of-the-art algorithms. G-Cut is intended as a robust component in a high throughput informatics pipeline for large-scale brain mapping projects.This work was supported by NIH/NIMH MH094360-01A1 (H.W.D.), MH094360-06 (H.W.D.), NIH/NCI U01CA198932-01 (H.W.D.), NIH/NIMH MH106008 (X.W.Y. and H.W.D.), National Nature Science Foundation of China No. 61772440 (J.S.Z.), and National Basic Research Program of China 2013CB329502 (J.S.Z. and C.L.Z.). We thank a support of Graduate Student International Exchange Project of Xiamen University to R.L. and State Scholarship Fund of China Scholarship Council (No. 201406315023) to J.S.Z. 该项研究得到国家自然科学基金、国家重点基础研究发展计划973项目、国家留学基金、厦门大学研究生国际交流项目、美国脑计划和NIH等课题资助

The Metric-FF Planning System: Translating "Ignoring Delete Lists" to Numeric State Variables

Planning with numeric state variables has been a challenge for many years, and was a part of the 3rd International Planning Competition (IPC-3). Currently one of the most popular and successful algorithmic techniques in STRIPS planning is to guide search by a heuristic function, where the heuristic is based on relaxing the planning task by ignoring the delete lists of the available actions. We present a natural extension of ``ignoring delete lists'' to numeric state variables, preserving the relevant theoretical properties of the STRIPS relaxation under the condition that the numeric task at hand is ``monotonic''. We then identify a subset of the numeric IPC-3 competition language, ``linear tasks'', where monotonicity can be achieved by pre-processing. Based on that, we extend the algorithms used in the heuristic planning system FF to linear tasks. The resulting system Metric-FF is, according to the IPC-3 results which we discuss, one of the two currently most efficient numeric planners

Directed Placement for mVLSI Devices

Continuous-flow microfluidic devices based on integrated channel networks are becoming increasingly prevalent in research in the biological sciences. At present, these devices are physically laid out by hand by domain experts who understand both the underlying technology and the biological functions that will execute on fabricated devices. The lack of a design science that is specific to microfluidic technology creates a substantial barrier to entry. To address this concern, this article introduces Directed Placement, a physical design algorithm that leverages the natural "directedness" in most modern microfluidic designs: fluid enters at designated inputs, flows through a linear or tree-based network of channels and fluidic components, and exits the device at dedicated outputs. Directed placement creates physical layouts that share many principle similarities to those created by domain experts. Directed placement allows components to be placed closer to their neighbors compared to existing layout algorithms based on planar graph embedding or simulated annealing, leading to an average reduction in laid-out fluid channel length of 91% while improving area utilization by 8% on average. Directed placement is compatible with both passive and active microfluidic devices and is compatible with a variety of mainstream manufacturing technologies