Feasible edge colorings of trees with cardinality constraints

AbstractA variation of preemptive open shop scheduling corresponds to finding a feasible edge coloring in a bipartite multigraph with some requirements on the size of the different color classes. We show that for trees with fixed maximum degree, one can find in polynomial time an edge k-coloring where for i=1,…,k the number of edges of color i is exactly a given number hi, and each edge e gets its color from a set ϕ(e) of feasible colors, if such a coloring exists. This problem is NP-complete for general bipartite multigraphs. Applications to open shop problems with costs for using colors are described

Nonenzymatic Glycosylation of Lepidopteran-Active \u3ci\u3eBacillus thuringiensis\u3c/i\u3e Protein Crystals

We used high-pH anion-exchange chromatography with pulsed amperometric detection to quantify the monosaccharides covalently attached to Bacillus thuringiensis HD-1 (Dipel) crystals. The crystals contained 0.54% sugars, including, in decreasing order of prevalence, glucose, fucose, arabinose/rhamnose, galactose, galactosamine, glucosamine, xylose, and mannose. Three lines of evidence indicated that these sugars arose from nonenzymatic glycosylation: (i) the sugars could not be removed by N- or O-glycanases; (ii) the sugars attached were influenced both by the medium in which the bacteria had been grown and by the time at which the crystals were harvested; and (iii) the chemical identity and stoichiometry of the sugars detected did not fit any known glycoprotein models. Thus, the sugars detected were the product of fermentation conditions rather than bacterial genetics. The implications of these findings are discussed in terms of crystal chemistry, fermentation technology, and the efficacy of B. thuringiensis as a microbial insecticide

Automated Classification of Airborne Laser Scanning Point Clouds

Making sense of the physical world has always been at the core of mapping. Up until recently, this has always dependent on using the human eye. Using airborne lasers, it has become possible to quickly "see" more of the world in many more dimensions. The resulting enormous point clouds serve as data sources for applications far beyond the original mapping purposes ranging from flooding protection and forestry to threat mitigation. In order to process these large quantities of data, novel methods are required. In this contribution, we develop models to automatically classify ground cover and soil types. Using the logic of machine learning, we critically review the advantages of supervised and unsupervised methods. Focusing on decision trees, we improve accuracy by including beam vector components and using a genetic algorithm. We find that our approach delivers consistently high quality classifications, surpassing classical methods

On Coloring Resilient Graphs

We introduce a new notion of resilience for constraint satisfaction problems, with the goal of more precisely determining the boundary between NP-hardness and the existence of efficient algorithms for resilient instances. In particular, we study $r$-resiliently $k$-colorable graphs, which are those $k$-colorable graphs that remain $k$-colorable even after the addition of any $r$ new edges. We prove lower bounds on the NP-hardness of coloring resiliently colorable graphs, and provide an algorithm that colors sufficiently resilient graphs. We also analyze the corresponding notion of resilience for $k$-SAT. This notion of resilience suggests an array of open questions for graph coloring and other combinatorial problems.Comment: Appearing in MFCS 201

RAFT: Recurrent All-Pairs Field Transforms for Optical Flow

We introduce Recurrent All-Pairs Field Transforms (RAFT), a new deep network architecture for optical flow. RAFT extracts per-pixel features, builds multi-scale 4D correlation volumes for all pairs of pixels, and iteratively updates a flow field through a recurrent unit that performs lookups on the correlation volumes. RAFT achieves state-of-the-art performance. On KITTI, RAFT achieves an F1-all error of 5.10%, a 16% error reduction from the best published result (6.10%). On Sintel (final pass), RAFT obtains an end-point-error of 2.855 pixels, a 30% error reduction from the best published result (4.098 pixels). In addition, RAFT has strong cross-dataset generalization as well as high efficiency in inference time, training speed, and parameter count. Code is available at https://github.com/princeton-vl/RAFT.Comment: fixed a formatting issue, Eq 7. no change in conten

Fast neurotransmitter release regulated by the endocytic scaffold intersectin.

Sustained fast neurotransmission requires the rapid replenishment of release-ready synaptic vesicles (SVs) at presynaptic active zones. Although the machineries for exocytic fusion and for subsequent endocytic membrane retrieval have been well characterized, little is known about the mechanisms underlying the rapid recruitment of SVs to release sites. Here we show that the Down syndrome-associated endocytic scaffold protein intersectin 1 is a crucial factor for the recruitment of release-ready SVs. Genetic deletion of intersectin 1 expression or acute interference with intersectin function inhibited the replenishment of release-ready vesicles, resulting in short-term depression, without significantly affecting the rate of endocytic membrane retrieval. Acute perturbation experiments suggest that intersectin-mediated vesicle replenishment involves the association of intersectin with the fissioning enzyme dynamin and with the actin regulatory GTPase CDC42. Our data indicate a role for the endocytic scaffold intersectin in fast neurotransmitter release, which may be of prime importance for information processing in the brain

An Automatic Digital Terrain Generation Technique for Terrestrial Sensing and Virtual Reality Applications

The identification and modeling of the terrain from point cloud data is an important component of Terrestrial Remote Sensing (TRS) applications. The main focus in terrain modeling is capturing details of complex geological features of landforms. Traditional terrain modeling approaches rely on the user to exert control over terrain features. However, relying on the user input to manually develop the digital terrain becomes intractable when considering the amount of data generated by new remote sensing systems capable of producing massive aerial and ground-based point clouds from scanned environments. This article provides a novel terrain modeling technique capable of automatically generating accurate and physically realistic Digital Terrain Models (DTM) from a variety of point cloud data. The proposed method runs efficiently on large-scale point cloud data with real-time performance over large segments of terrestrial landforms. Moreover, generated digital models are designed to effectively render within a Virtual Reality (VR) environment in real time. The paper concludes with an in-depth discussion of possible research directions and outstanding technical and scientific challenges to improve the proposed approach

Combined biological and chemical assessment of estrogenic activities in wastewater treatment plant effluents

Five wastewater treatment plant effluents were analyzed for known endocrine disrupters and estrogenicity. Estrogenicity was determined by using the yeast estrogen screen (YES) and by measuring the blood plasma vitellogenin (VTG) concentrations in exposed male rainbow trout (Oncorhynchus mykiss). While all wastewater treatment plant effluents contained measurable concentrations of estrogens and gave a positive response with the YES, only at two sites did the male fish have significantly increased VTG blood plasma concentrations after the exposure, compared to pre-exposure concentrations. Estrone (E1) concentrations ranged up to 51ngL−1, estradiol (E2) up to 6ngL−1, and ethinylestradiol (EE2) up to 2ngL−1 in the 90samples analyzed. Alkylphenols, alkylphenolmonoethoxylates and alkylphenoldiethoxylates, even though found at µgL−1 concentrations in effluents from wastewater treatment plants with a significant industrial content, did not contribute much to the overall estrogenicity of the samples taken due to their low relative potency. Expected estrogenicities were calculated from the chemical data for each sample by using the principle of concentration additivity and relative potencies of the various chemicals as determined with the yeast estrogen screen. Measured and calculated estradiol equivalents gave the same order of magnitude and correlated rather well (R 2=0.6