Retrieving Top-N Weighted Spatial k-cliques

Spatial data analysis is a classic yet important topic because of its wide range of applications. Recently, as a spatial data analysis approach, a neighbor graph of a set P of spatial points has often been employed. This paper also considers a spatial neighbor graph and addresses a new problem, namely top-N weighted spatial k-clique retrieval. This problem searches for the N minimum weighted cliques consisting of k points in P, and it has important applications, such as community detection and co-location pattern mining. Recent spatial datasets have many points, and efficiently dealing with such big datasets is one of the main requirements of applications. A straightforward approach to solving our problem is to try to enumerate all k-cliques, which incurs O(nkk2) time. Since k ≥ 3, this approach cannot achieve the main requirement, so computing the result without enumerating unnecessary k-cliques is required. This paper achieves this challenging task and proposes a simple practically-efficient algorithm that returns the exact answer. We conduct experiments using two real spatial datasets consisting of million points, and the results show the efficiency of our algorithm, e.g., it can return the exact top-N result within 1 second when N ≤ 1000 and k ≤ 7.Taniguchi R., Amagata D., Hara T.. Retrieving Top-N Weighted Spatial k-cliques. Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022 , 4952 (2022); https://doi.org/10.1109/BigData55660.2022.10021071

Efficient Retrieval of Top-k Weighted Spatial Triangles

Due to the proliferation of location-based services and IoT devices, a lot of spatial points are being generated. Spatial data analysis is well known to be an important task. As spatial data analysis tools, graphs consisting of spatial points, where each point has edges to its nearby points and the weight of each edge is the distance between the corresponding points, have been receiving much attention. We focus on triangles (one of the simplest sub-graph patterns) in such graphs and address the problem of retrieving the top-k weighted spatial triangles. This problem has important real-life applications, e.g., group search, urban planning, and co-location pattern mining. However, this problem is computationally challenging, because the number of triangles in a graph is generally huge and enumerating all of them is not feasible. To solve this challenge, we propose an efficient algorithm that returns the exact result. Our experimental results on real datasets show the efficiency of our algorithm.This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-00123-9_17

Efficient Retrieval of Top-k Weighted Triangles on Static and Dynamic Spatial Data

Due to the proliferation of location-based services, spatial data analysis becomes more and more important. We consider graphs consisting of spatial points, where each point has edges to its nearby points and the weight of each edge is the distance between the corresponding points, as they have been receiving attention as spatial data analysis tools. We focus on triangles in such graphs and address the problem of retrieving the top- $k$ weighted spatial triangles. This problem is computationally challenging, because the number of triangles in a graph is generally huge and enumerating all of them is not feasible. To overcome this challenge, we propose an algorithm that returns the exact result efficiently. We moreover consider two dynamic data models: (i) fully dynamic data that allow arbitrary point insertions and deletions and (ii) streaming data in a sliding-window model. They often appear in location-based services. The results of our experiments on real datasets show the efficiency of our algorithms for static and dynamic data.Taniguchi R., Amagata D., Hara T.. Efficient Retrieval of Top-k Weighted Triangles on Static and Dynamic Spatial Data. IEEE Access 10, 55298 (2022); https://doi.org/10.1109/ACCESS.2022.3177620

ラット頸動脈内膜肥厚モデルにおけるナノ医療の検証

学位の種別: 課程博士審査委員会委員 : (主査)東京大学教授 小野 稔, 東京大学教授 鄭 雄一, 東京大学特任准教授 位高 啓史, 東京大学講師 石原 聡一郎, 東京大学講師 縄田 寛University of Tokyo(東京大学

Direct ethanol production from cellulosic materials using a diploid strain of Saccharomyces cerevisiae with optimized cellulase expression

<p>Abstract</p> <p>Background</p> <p>Hydrolysis of cellulose requires the action of the cellulolytic enzymes endoglucanase, cellobiohydrolase and β-glucosidase. The expression ratios and synergetic effects of these enzymes significantly influence the extent and specific rate of cellulose degradation. In this study, using our previously developed method to optimize cellulase-expression levels in yeast, we constructed a diploid <it>Saccharomyces cerevisiae </it>strain optimized for expression of cellulolytic enzymes, and attempted to improve the cellulose-degradation activity and enable direct ethanol production from rice straw, one of the most abundant sources of lignocellulosic biomass.</p> <p>Results</p> <p>The engineered diploid strain, which contained multiple copies of three cellulase genes integrated into its genome, was precultured in molasses medium (381.4 mU/g wet cell), and displayed approximately six-fold higher phosphoric acid swollen cellulose (PASC) degradation activity than the parent haploid strain (63.5 mU/g wet cell). When used to ferment PASC, the diploid strain produced 7.6 g/l ethanol in 72 hours, with an ethanol yield that achieved 75% of the theoretical value, and also produced 7.5 g/l ethanol from pretreated rice straw in 72 hours.</p> <p>Conclusions</p> <p>We have developed diploid yeast strain optimized for expression of cellulolytic enzymes, which is capable of directly fermenting from cellulosic materials. Although this is a proof-of-concept study, it is to our knowledge, the first report of ethanol production from agricultural waste biomass using cellulolytic enzyme-expressing yeast without the addition of exogenous enzymes. Our results suggest that combining multigene expression optimization and diploidization in yeast is a promising approach for enhancing ethanol production from various types of lignocellulosic biomass.</p

Cocktail δ-integration: a novel method to construct cellulolytic enzyme expression ratio-optimized yeast strains

<p>Abstract</p> <p>Background</p> <p>The filamentous fungus <it>T. reesei </it>effectively degrades cellulose and is known to produce various cellulolytic enzymes such as β-glucosidase, endoglucanase, and cellobiohydrolase. The expression levels of each cellulase are controlled simultaneously, and their ratios and synergetic effects are important for effective cellulose degradation. However, in recombinant <it>Saccharomyces cerevisiae</it>, it is difficult to simultaneously control many different enzymes. To construct engineered yeast with efficient cellulose degradation, we developed a simple method to optimize cellulase expression levels, named cocktail δ-integration.</p> <p>Results</p> <p>In cocktail δ-integration, several kinds of cellulase expression cassettes are integrated into yeast chromosomes simultaneously in one step, and strains with high cellulolytic activity (i.e., expressing an optimum ratio of cellulases) are easily obtained. Although the total integrated gene copy numbers of cocktail δ-integrant strain was about half that of a conventional δ-integrant strain, the phosphoric acid swollen cellulose (PASC) degradation activity (64.9 mU/g-wet cell) was higher than that of a conventional strain (57.6 mU/g-wet cell). This suggests that optimization of the cellulase expression ratio improves PASC degradation activity more so than overexpression.</p> <p>Conclusions</p> <p>To our knowledge, this is the first report on the expression of cellulase genes by δ-integration and optimization of various foreign genes by δ-integration in yeast. This method should be very effective and easily applied for other multi-enzymatic systems using recombinant yeast.</p

Large-scale Filamentary Structure around the Protocluster at Redshift z=3.1

We report the discovery of a large-scale coherent filamentary structure of Lyman alpha emitters in a redshift space at z=3.1. We carried out spectroscopic observations to map the three dimensional structure of the belt-like feature of the Lyman alpha emitters discovered by our previous narrow-band imaging observations centered on the protocluster at z=3.1. The feature was found to consist of at least three physical filaments connecting with each other. The result is in qualitative agreement with the prediction of the 'biased' galaxy-formation theories that galaxies preferentially formed in large-scale filamentary or sheet-like mass overdensities in the early Universe. We also found that the two known giant Lyman alpha emission-line nebulae showing high star-formation activities are located near the intersection of these filaments, which presumably evolves into a massive cluster of galaxies in the local Universe. This may suggest that massive galaxy formation occurs at the characteristic place in the surrounding large-scale structure at high redshift.Comment: 11 pages, 3 figures, accepted for publication in ApJ Letter

Detection of the Far-infrared [O III] and Dust Emission in a Galaxy at Redshift 8.312: Early Metal Enrichment in the Heart of the Reionization Era

We present the Atacama Large Millimeter/submillimeter Array (ALMA) detection of the [O III] 88 $\mu$m line and rest-frame 90 $\mu$m dust continuum emission in a Y-dropout Lyman break galaxy (LBG), MACS0416_Y1, lying behind the Frontier Field cluster MACS J0416.1-2403. This [O III] detection confirms the LBG with a spectroscopic redshift of $z = 8.3118 \pm 0.0003$, making this object one of the furthest galaxies ever identified spectroscopically. The observed 850 $\mu$m flux density of $137 \pm 26$ $\mu$Jy corresponds to a de-lensed total infrared (IR) luminosity of $L_{\rm IR} = (1.7 \pm 0.3) \times 10^{11} L_{\odot}$ if assuming a dust temperature of $T_{\rm dust} = 50$ K and an emissivity index of $\beta = 1.5$, yielding a large dust mass of $4 \times 10^6 M_{\odot}$. The ultraviolet-to-far IR spectral energy distribution modeling where the [O III] emissivity model is incorporated suggests the presence of a young ($\tau_{\rm age} \approx 4$ Myr), star-forming (SFR $\approx 60 M_{\odot}$ yr$^{-1}$), moderately metal-polluted ($Z \approx 0.2 Z_{\odot}$) stellar component with a mass of $M_{\rm star} = 3 \times 10^8 M_{\odot}$. An analytic dust mass evolution model with a single episode of star-formation does not reproduce the metallicity and dust mass in $\tau_{\rm age} \approx 4$ Myr, suggesting a pre-existing evolved stellar component with $M_{\rm star} \sim 3 \times 10^9 M_{\odot}$ and $\tau_{\rm age} \sim 0.3$ Gyr as the origin of the dust mass.Comment: Accepted by ApJ. 18 pages, 10 figures, 5 table

Role of Electronic Structure in the Martensitic Phase Transition of Ni_2Mn_<1-x>Sn_<1-x> Studied by Hard-X-Ray Photoelectron Spectroscopy and Ab Initio Calculation

We have revealed the underlying mechanism of the martensitic phase transition (MPT) in a new class of ferromagnetic shape memory alloys, Ni2Mn1+xSn1-x, by the combination of bulk-sensitive hard-x-ray photoelectron spectroscopy and a first-principles density-functional calculation. The Ni 3d eg state in the cubic phase systematically shifts towards the Fermi energy with an increase in the number of Mn atoms substituted in the Sn sites. An abrupt decrease of the intensity of the Ni 3d eg states upon MPT for x=0.36–0.42 has been observed in the vicinity of the Fermi level. The energy shift of the Ni 3d minority-spin eg state in the cubic phase originates from hybridization with the antiferromagnetically coupled Mn in the Sn site. Below the MPT temperature, the Ni 3d state splits into two levels located below and above the Fermi energy in order to achieve an energetically stable state