Computing Similarity between a Pair of Trajectories

With recent advances in sensing and tracking technology, trajectory data is becoming increasingly pervasive and analysis of trajectory data is becoming exceedingly important. A fundamental problem in analyzing trajectory data is that of identifying common patterns between pairs or among groups of trajectories. In this paper, we consider the problem of identifying similar portions between a pair of trajectories, each observed as a sequence of points sampled from it. We present new measures of trajectory similarity --- both local and global --- between a pair of trajectories to distinguish between similar and dissimilar portions. Our model is robust under noise and outliers, it does not make any assumptions on the sampling rates on either trajectory, and it works even if they are partially observed. Additionally, the model also yields a scalar similarity score which can be used to rank multiple pairs of trajectories according to similarity, e.g. in clustering applications. We also present efficient algorithms for computing the similarity under our measures; the worst-case running time is quadratic in the number of sample points. Finally, we present an extensive experimental study evaluating the effectiveness of our approach on real datasets, comparing with it with earlier approaches, and illustrating many issues that arise in trajectory data. Our experiments show that our approach is highly accurate in distinguishing similar and dissimilar portions as compared to earlier methods even with sparse sampling

Bacteriophages as a model for studying carbon regulation in aquatic system

The interconversion of carbon in organic, inorganic and refractory carbon is still beyond the grasp of present environmentalists. The bacteria and their phages, being the most abundant constituents of the aquatic environment, represent an ideal model for studing carbon regulation in the aquatic system. The refractory dissolved organic carbon (DOC), a recently coined terminology from the microbe-driven conversion of bioavailable organic carbon into difficult-to-digest refractory DOC by microbial carbon pump (MCP), is suggested to have the potential to revolutionize our view of carbon sequestration. It is estimated that about 95% of organic carbon is in the form of refractory DOC, which is the largest pool of organic matter in the ocean. The refractory DOC is supposed to be the major factor in the global carbon cycle whose source is not yet well understood. A key element of the carbon cycle is the microbial conversion of dissolved organic carbon into inedible forms. The time studies of phage-host interaction under control conditions reveal their impact on the total carbon content of the source and their interconversion among organic, inorganic and other forms of carbon with respect to control source. The TOC- analysis statistics stipulate an increase in inorganic carbon content by 15-25 percent in the sample with phage as compared to the sample without phage. The results signify a 60-70 fold increase in inorganic carbon content in sample with phage, whereas, 50-55 fold in the case of sample without phages as compared with control. This increase in inorganic carbon content may be due to lysis of the host cell releasing its cellular constituents and utilization of carbon constituent for phage assembly and development. It also proves the role of phages in regulating the carbon flow in aquatic systems like oceans, where their concentration outnumbered other species

The arborescence-realization problem

AbstractA {0, 1}-matrix M is arborescence graphic if there exists an arborescence T such that the arcs of T are indexed on the rows of M and the columns of M are the incidence vectors of the arc sets of dipaths of T. If such a T exists, then T is an arborescence realization for M. This paper presents an almost-linear-time algorithm to determine whether a given {0, 1}-matrix is arborescence graphic and, if so, to construct an arborescence realization. The algorithm is then applied to recognize a subclass of the extended-Horn satisfiability problems introduced by Chandru and Hooker (1991)

Physico-chemical Characteristics of Fine Nano-scaled Carbon Fibers from Bacterial Cellulose

Recently, carbon nanofibers have gained immense attention in research due to its tremendous application. Here, this work highlights a simple, cost effective and reliable method to develop carbon nanofibers (CNF) from biomass. The biomass used is bacterial cellulose (BC) synthesized using Acetobacter xylinus. CNF was developed by freeze drying of BC followed by pyrolysis at different temperatures (300ºC - 900ºC). The conversions of BC to CNF were characterized using SEM, FTIR, TGA and XRD respectively. The results exhibit three dimensional, lightweight, fine nanoscale fibers with a diameter of 10nm which are tend to have hydrophobic and lipophilic characters, due to which it can be used in oil – water separation applications.

(E)-2-(2-Formyl­phen­oxy­meth­yl)-3-phenyl­prop-2-ene­nitrile

In the title compound, C17H13NO2, the dihedral angle between the benzene and the phenyl ring is 65.92 (7)°. The carbonitrile side chain is almost linear, the C—C—N angle being 175.55 (14)°. The crystal structure is stabilized by inter­molecular C—H⋯O inter­actions

(2S,5S,6R)-5-(4-Methyl­phen­yl)-3-phenyl-4,8-dioxa-3-aza­tricyclo­[7.4.0.02,6]trideca-1(13),9,11-triene-6-carbonitrile

In the title compound, C24H20N2O2, the six-membered pyran ring adopts a half-chair conformation with one C atom deviating from the mean plane of the remaining ring atoms by 0.654 (6) Å. The five-membered isoxazole ring adopts an N-envelope conformation with the N atom displaced by 0.742 (5) Å from the mean plane formed by the remaining ring atoms. The carbonitrile side chain is almost linear, with a C—C—N angle of 178.6 (5)°. The crystal packing is stabilized by inter­molecular C—H⋯N inter­actions, through bifurcated acceptor hydrogen bonds formed between the carbonitrile N atom and two alternate C atoms in the unsubstituted benzene ring. The mol­ecular structure and crystal packing are further stabilized by intra­molecular and inter­molecular C—H⋯π inter­actions

Trivially extendable graphs

Let G be a simple graph. Let k be a positive integer. G is said to be k-extendable if every independent set of cardinality k is contained in a maximum independent set of G. G is said to be trivially extendable if G is not k-extendable for 1 ≤ k ≤ (β0(G) − 1). A well covered graph is one in which every maximal independent set is maximum. Study of k-extendable graphs has been made in [7,8,9]. In this paper a study of trivially extendable graphs is made. Characterization of graphs with β0(G) = (n − 3) and which is trivially extendable has been done. Similarly graphs with β0(G) = (n − 2) is also studied for trivial extensibility.Publisher's Versio

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Management. We thank the participants at the University of Michigan brown bag workshop for helpful comments and suggestions. Any errors are our own. Do stock prices underreact to SEO announcements? Evidence from SEO Valuation This paper examines whether the market underreacts to the negative information implicit in SEO announcements. We find that it does but conditional on the valuation of SEO firms prior to the SEO issue date. SEO firms that are overvalued relative to their industry peers experience a smaller decline in market value on the SEO announcement day but experience a larger decline over the next five years. The results are robust to various ways of choosing industry peers and valuation multiples and various methodologies for computing risk-adjusted abnormal returns. Cross-sectional regressions indicate SEO P/V ratios (offer-price to value ratio based on relative valuation techniques) are significantly positively related to announcement day returns and significantly negatively related to long-run returns even after controlling for expected growth rates, accruals, and B/M ratios. Additional tests indicate overvalued SEOs earn lower returns around future quarterly earnings announcement dates and do not exhibit superior ex-pos