Compressed Subsequence Matching and Packed Tree Coloring

We present a new algorithm for subsequence matching in grammar compressed strings. Given a grammar of size $n$ compressing a string of size $N$ and a pattern string of size $m$ over an alphabet of size $\sigma$, our algorithm uses $O(n+\frac{n\sigma}{w})$ space and $O(n+\frac{n\sigma}{w}+m\log N\log w\cdot occ)$ or $O(n+\frac{n\sigma}{w}\log w+m\log N\cdot occ)$ time. Here $w$ is the word size and $occ$ is the number of occurrences of the pattern. Our algorithm uses less space than previous algorithms and is also faster for $occ=o(\frac{n}{\log N})$ occurrences. The algorithm uses a new data structure that allows us to efficiently find the next occurrence of a given character after a given position in a compressed string. This data structure in turn is based on a new data structure for the tree color problem, where the node colors are packed in bit strings.Comment: To appear at CPM '1

Tree Compression with Top Trees Revisited

We revisit tree compression with top trees (Bille et al, ICALP'13) and present several improvements to the compressor and its analysis. By significantly reducing the amount of information stored and guiding the compression step using a RePair-inspired heuristic, we obtain a fast compressor achieving good compression ratios, addressing an open problem posed by Bille et al. We show how, with relatively small overhead, the compressed file can be converted into an in-memory representation that supports basic navigation operations in worst-case logarithmic time without decompression. We also show a much improved worst-case bound on the size of the output of top-tree compression (answering an open question posed in a talk on this algorithm by Weimann in 2012).Comment: SEA 201

Dose Optimization for Using the Contrast Agent Gadofosveset in Magnetic Resonance Imaging (MRI) of Domestic Pig Brain

Pigs are useful models in stroke research, and Magnetic Resonance Imaging (MRI) is a useful tool for measurements of brain pathophysiology. Perfusion Weighed Imaging (PWI) with standard Gd-based chelates (i.e. gadobutrol) provides crucial information about breakdown of the Blood-Brain-Barrier (BBB) in patients. Gadofosveset is also a Gd-based contrast agent, but with a higher binding to serum albumin. The prolonged plasma-half life of gadofosveset allows the acquisition of steady state angiographies, which may increase the sensitivity for detection of BBB leakage. We hypothesize that the contrast dosage with gadofosveset can be optimized for PWI and subsequent steady-state Magnetic Resonance Angiography (MRA) in pigs. Anesthetized domestic pigs (females; N=6) were MRI scanned four times in one day: they were initially imaged during a standard gadobutrol bolus injection (0.1 mmol/kg). Then they received three successive gadofosveset bolus injections of varying dosages (0.015-0.09 mmol/kg). Based on projection from our data, we suggest that a bolus injection of 0.0916 mmol/kg gadofosveset would yield contrast similar to that of a standard dose of 0.1 mmol/kg gadobutrol in dynamic susceptibility contrast MRI at 3 T. In conclusion, our results demonstrate the feasibility of gadofosveset based PWI in pig brain research. The relaxation and plasma half-life properties allow detailed steady-state MRA angiographies and may prove useful in detecting subtle BBB disruption of significance in stroke models and human patients

Faster Approximate String Matching for Short Patterns

We study the classical approximate string matching problem, that is, given strings $P$ and $Q$ and an error threshold $k$, find all ending positions of substrings of $Q$ whose edit distance to $P$ is at most $k$. Let $P$ and $Q$ have lengths $m$ and $n$, respectively. On a standard unit-cost word RAM with word size $w \geq \log n$ we present an algorithm using time $$O(nk \cdot \min(\frac{\log^2 m}{\log n},\frac{\log^2 m\log w}{w}) + n)$$ When $P$ is short, namely, $m = 2^{o(\sqrt{\log n})}$ or $m = 2^{o(\sqrt{w/\log w})}$ this improves the previously best known time bounds for the problem. The result is achieved using a novel implementation of the Landau-Vishkin algorithm based on tabulation and word-level parallelism.Comment: To appear in Theory of Computing System

Ramified rectilinear polygons: coordinatization by dendrons

Simple rectilinear polygons (i.e. rectilinear polygons without holes or cutpoints) can be regarded as finite rectangular cell complexes coordinatized by two finite dendrons. The intrinsic $l_1$-metric is thus inherited from the product of the two finite dendrons via an isometric embedding. The rectangular cell complexes that share this same embedding property are called ramified rectilinear polygons. The links of vertices in these cell complexes may be arbitrary bipartite graphs, in contrast to simple rectilinear polygons where the links of points are either 4-cycles or paths of length at most 3. Ramified rectilinear polygons are particular instances of rectangular complexes obtained from cube-free median graphs, or equivalently simply connected rectangular complexes with triangle-free links. The underlying graphs of finite ramified rectilinear polygons can be recognized among graphs in linear time by a Lexicographic Breadth-First-Search. Whereas the symmetry of a simple rectilinear polygon is very restricted (with automorphism group being a subgroup of the dihedral group $D_4$), ramified rectilinear polygons are universal: every finite group is the automorphism group of some ramified rectilinear polygon.Comment: 27 pages, 6 figure

Compressed Membership for NFA (DFA) with Compressed Labels is in NP (P)

In this paper, a compressed membership problem for finite automata, both deterministic and non-deterministic, with compressed transition labels is studied. The compression is represented by straight-line programs (SLPs), i.e. context-free grammars generating exactly one string. A novel technique of dealing with SLPs is introduced: the SLPs are recompressed, so that substrings of the input text are encoded in SLPs labelling the transitions of the NFA (DFA) in the same way, as in the SLP representing the input text. To this end, the SLPs are locally decompressed and then recompressed in a uniform way. Furthermore, such recompression induces only small changes in the automaton, in particular, the size of the automaton remains polynomial. Using this technique it is shown that the compressed membership for NFA with compressed labels is in NP, thus confirming the conjecture of Plandowski and Rytter and extending the partial result of Lohrey and Mathissen; as it is already known, that this problem is NP-hard, we settle its exact computational complexity. Moreover, the same technique applied to the compressed membership for DFA with compressed labels yields that this problem is in P; for this problem, only trivial upper-bound PSPACE was known

Understanding the impact of more realistic low-dose, prolonged engineered nanomaterial exposure on genotoxicity using 3D models of the human liver

Abstract Background With the continued integration of engineered nanomaterials (ENMs) into everyday applications, it is important to understand their potential for inducing adverse human health effects. However, standard in vitro hazard characterisation approaches suffer limitations for evaluating ENM and so it is imperative to determine these potential hazards under more physiologically relevant and realistic exposure scenarios in target organ systems, to minimise the necessity for in vivo testing. The aim of this study was to determine if acute (24 h) and prolonged (120 h) exposures to five ENMs (TiO2, ZnO, Ag, BaSO4 and CeO2) would have a significantly different toxicological outcome (cytotoxicity, (pro-)inflammatory and genotoxic response) upon 3D human HepG2 liver spheroids. In addition, this study evaluated whether a more realistic, prolonged fractionated and repeated ENM dosing regime induces a significantly different toxicity outcome in liver spheroids as compared to a single, bolus prolonged exposure. Results Whilst it was found that the five ENMs did not impede liver functionality (e.g. albumin and urea production), induce cytotoxicity or an IL-8 (pro-)inflammatory response, all were found to cause significant genotoxicity following acute exposure. Most statistically significant genotoxic responses were not dose-dependent, with the exception of TiO2. Interestingly, the DNA damage effects observed following acute exposures, were not mirrored in the prolonged exposures, where only 0.2–5.0 µg/mL of ZnO ENMs were found to elicit significant (p ≤ 0.05) genotoxicity. When fractionated, repeated exposure regimes were performed with the test ENMs, no significant (p ≥ 0.05) difference was observed when compared to the single, bolus exposure regime. There was < 5.0% cytotoxicity observed across all exposures, and the mean difference in IL-8 cytokine release and genotoxicity between exposure regimes was 3.425 pg/mL and 0.181%, respectively. Conclusion In conclusion, whilst there was no difference between a single, bolus or fractionated, repeated ENM prolonged exposure regimes upon the toxicological output of 3D HepG2 liver spheroids, there was a difference between acute and prolonged exposures. This study highlights the importance of evaluating more realistic ENM exposures, thereby providing a future in vitro approach to better support ENM hazard assessment in a routine and easily accessible manner

Fingerprints in Compressed Strings

The Karp-Rabin fingerprint of a string is a type of hash value that due to its strong properties has been used in many string algorithms. In this paper we show how to construct a data structure for a string S of size N compressed by a context-free grammar of size n that answers fingerprint queries. That is, given indices i and j, the answer to a query is the fingerprint of the substring S[i,j]. We present the first O(n) space data structures that answer fingerprint queries without decompressing any characters. For Straight Line Programs (SLP) we get O(logN) query time, and for Linear SLPs (an SLP derivative that captures LZ78 compression and its variations) we get O(log log N) query time. Hence, our data structures has the same time and space complexity as for random access in SLPs. We utilize the fingerprint data structures to solve the longest common extension problem in query time O(log N log l) and O(log l log log l + log log N) for SLPs and Linear SLPs, respectively. Here, l denotes the length of the LCE

Comparison of dust released from sanding conventional and nanoparticle-doped wall and wood coatings

Introduction of engineered nanoparticles (ENPs) into traditional surface coatings (e.g., paints, lacquers, fillers) may result in new exposures to both workers and consumers and possibly also a new risk to their health. During finishing and renovation, such products may also be a substantial source of exposure to ENPs or aggregates thereof. This study investigates the particle size distributions (5.6 nm–19.8 μm) and the total number of dust particles generated during sanding of ENP-doped paints, lacquers, and fillers as compared to their conventional counterparts. In all products, the dust emissions from sanding were found to consist of five size modes: three modes under 1 μm and two modes around 1 and 2 μm. Corrected for the emission from the sanding machine, the sanding dust, was dominated by 100–300 nm size particles, whereas the mass and surface area spectra were dominated by the micrometer modes. Adding ENPs to the studied products only vaguely affected the geometric mean diameters of the particle modes in the sanding dust when compared to their reference products. However, we observed considerable differences in the number concentrations in the different size modes, but still without revealing a clear effect of ENPs on dust emissions from sanding

Nanomaterials Versus Ambient Ultrafine Particles: An Opportunity to Exchange Toxicology Knowledge

BACKGROUND: A rich body of literature exists that has demonstrated adverse human health effects following exposure to ambient air particulate matter (PM), and there is strong support for an important role of ultrafine (nanosized) particles. At present, relatively few human health or epidemiology data exist for engineered nanomaterials (NMs) despite clear parallels in their physicochemical properties and biological actions in in vitro models. OBJECTIVES: NMs are available with a range of physicochemical characteristics, which allows a more systematic toxicological analysis. Therefore, the study of ultrafine particles (UFP, <100 nm in diameter) provides an opportunity to identify plausible health effects for NMs, and the study of NMs provides an opportunity to facilitate the understanding of the mechanism of toxicity of UFP. METHODS: A workshop of experts systematically analyzed the available information and identified 19 key lessons that can facilitate knowledge exchange between these discipline areas. DISCUSSION: Key lessons range from the availability of specific techniques and standard protocols for physicochemical characterization and toxicology assessment to understanding and defining dose and the molecular mechanisms of toxicity. This review identifies a number of key areas in which additional research prioritization would facilitate both research fields simultaneously. CONCLUSION: There is now an opportunity to apply knowledge from NM toxicology and use it to better inform PM health risk research and vice versa.info:eu-repo/semantics/publishedVersio