Analyzing temporal patterns of topic diversity using graph clustering

The Journal of Supercomputing - During a disaster, social media can be both a source of help and of danger: Social media has a potential to diffuse rumors, and officials involved in disaster...     

Ratiometric bioluminescence indicators for monitoring cyclic adenosine 3',5'-monophosphate in live cells based on luciferase-fragment complementation

Bioluminescent indicators for cyclic 3',5'-monophosphate AMP (cAMP) are powerful tools for noninvasive detection with high sensitivity. However, the absolute photon counts are affected substantially by adenosine 5'-triphosphate (ATP) and d-luciferin concentrations, limiting temporal analysis in live cells. This report describes a genetically encoded bioluminescent indicator for detecting intracellular cAMP based on complementation of split fragments of two-color luciferase mutants originated from click beetles. A cAMP binding domain of protein kinase A was connected with an engineered carboxy-terminal fragment of luciferase, of which ends were connected with amino-terminal fragments of green luciferase and red luciferase. We demonstrated that the ratio of green to red bioluminescence intensities was less influenced by the changes of ATP and d-luciferin concentrations. We also showed an applicability of the bioluminescent indicator for time-course and quantitative assessments of intracellular cAMP in living cells and mice. The bioluminescent indicator will enable quantitative analysis and imaging of spatiotemporal dynamics of cAMP in opaque and autofluorescent living subjects.     

Method for solving nonlinear goal programming with interval coefficients using genetic algorithm

Traditional formulations on reliability optimization problems have assumed that the coefficients of models are known as fixed quantities and reliability design problem is treated as deterministic optimization problems. Because that the optimal design of system reliability is resolved in the same stage of overall system design, model coefficients are highly uncertainty and imprecision during design phase and it is usually very difficult to determine the precise values for them. However, these coefficients can be roughly given as the intervals of confidence.

In this paper, we formulated reliability optimization problem as nonlinear goal programming with interval coefficients and develop a genetic algorithm to solve it. The key point is how to evaluate each solution with interval data. We give a new definition on deviation variables which take interval relation into account. Numerical example is given to demonstrate the efficiency of the proposed approach.     

A solution method for optimal weight design problem of the gear using genetic algorithms

In this paper, we formulate an optimal weight designproblem of a gear for a constrained bending strength of gear, tortional strength of shafts and each gear dimension as a nonlinear integer programming (NIP) problem and solve it directly by keeping the nonlinear constraint by using an improved genetic algorithm (GA). We discuss the efficency of the proposed method.     

Periodic motion synthesis and Fourier compression

Periodic motion is an important class of motion to synthesize, but it is not easy to compute it robustly and efficiently. In this paper we propose a simple, robust and efficient method to compute periodic motion from linear equation systems. The method first calculates the response of the system when an external periodic force is applied during one period, and then sums up the periodically shifted versions of the system response to provide the periodic solution. It is also shown that Fourier decomposition is very effective to compress the motion data without a drop in visual fidelity. © 1998 John Wiley & Sons, Ltd.     

Visualization of nonengineered single mRNAs in living cells using genetically encoded fluorescent probes

Single mRNA imaging in live cells is a useful technique to elucidate its precise localization and dynamics. We developed a method for visualizing endogenous mRNAs in living cells with single molecule sensitivity using genetically encoded probes. An RNA-binding protein of human PUMILIO1 (PUM-HD) was used for recognizing base sequences of a target mRNA, β-actin mRNA. Two PUM-HDs were modified by amino acid mutations to bind specifically to tandem 8-base sequences of the target mRNA. Because each PUM-HD was connected with amino- and carboxyl-terminal fragments of enhanced green fluorescent protein (EGFP), the probes emit fluorescence by reconstitution of EGFP fragments upon binding to β-actin mRNAs. The EGFP reconstituted on the mRNAs was monitored with a total internal reflection fluorescence microscope. Results show that each fluorescent spot in live cells represented a single β-actin mRNA and that distinct spatial and temporal movement of the individual β-actin mRNAs was visualized. We also estimated the average velocity of the movement of the single mRNAs along microtubules in live cells. This method is widely applicable to tracking various mRNAs of interest in the native state of living cells with single-mRNA sensitivity.     

An Efficient Algorithm for Solving Pseudo Clique Enumeration Problem

The problem of finding dense structures in a given graph is quite basic in informatics including data mining and data engineering. Clique is a popular model to represent dense structures, and widely used because of its simplicity and ease in handling. Pseudo cliques are natural extension of cliques which are subgraphs obtained by removing small number of edges from cliques. We here define a pseudo clique by a subgraph such that the ratio of the number of its edges compared to that of the clique with the same number of vertices is no less than a given threshold value. In this paper, we address the problem of enumerating all pseudo cliques for a given graph and a threshold value. We first show that it seems to be difficult to obtain polynomial time algorithms using straightforward divide and conquer approaches. Then, we propose a polynomial time, polynomial delay in precise, algorithm based on reverse search. The time complexity for each pseudo clique is O(Δlog |V|+min {Δ ²,|V|+|E|}). Computational experiments show the efficiency of our algorithm for both randomly generated graphs and practical graphs.