Equipment for Spreading Organic Solid Waste on Forest Land

Forest land utilization is becoming an important disposal alternative for paper mill wastes. Interest in this disposal alternative for other organic solid wastes such as poultry litter and compost is likely to grow as well. Three main types of spreader mechanisms that have been tried for forest waste spreading operations are vertical impeller/blower units, horizontal-axis beater-type spreaders, and horizontal spinner-type spreaders. The main considerations in selecting equipment for forest spreading operations are the carrier, the type of spreading mechanism, hopper configuration, and self-loading capabilities (if the carrier is a forwarder). These considerations are discussed in terms of site/stand conditions as they affect manoeuvrability and access, the materials to be spread, costs, and the scale of the spreading operations

TimeMachine: Timeline Generation for Knowledge-Base Entities

We present a method called TIMEMACHINE to generate a timeline of events and relations for entities in a knowledge base. For example for an actor, such a timeline should show the most important professional and personal milestones and relationships such as works, awards, collaborations, and family relationships. We develop three orthogonal timeline quality criteria that an ideal timeline should satisfy: (1) it shows events that are relevant to the entity; (2) it shows events that are temporally diverse, so they distribute along the time axis, avoiding visual crowding and allowing for easy user interaction, such as zooming in and out; and (3) it shows events that are content diverse, so they contain many different types of events (e.g., for an actor, it should show movies and marriages and awards, not just movies). We present an algorithm to generate such timelines for a given time period and screen size, based on submodular optimization and web-co-occurrence statistics with provable performance guarantees. A series of user studies using Mechanical Turk shows that all three quality criteria are crucial to produce quality timelines and that our algorithm significantly outperforms various baseline and state-of-the-art methods.Comment: To appear at ACM SIGKDD KDD'15. 12pp, 7 fig. With appendix. Demo and other info available at http://cs.stanford.edu/~althoff/timemachine

Darboux transformation for two component derivative nonlinear Schr\"odinger equation

In this paper, we consider the two component derivative nonlinear Schr\"{o}dinger equation and present a simple Darboux transformation for it. By iterating this Darboux transformation, we construct a compact representation for the $N-$soliton solutions.Comment: 12 pages, 2 figure

Vertically Aligned Gold Nanorod Monolayer on Arbitrary Substrates: Self-Assembly and Femtomolar Detection of Food Contaminants

Cataloged from PDF version of article.Public attention to the food scandals raises an urgent need to develop effective and reliable methods to detect food contaminants. The current prevailing detections are primarily based upon liquid chromatography, mass spectroscopy, or colorimetric methods, which usually require sophisticated and time-consuming steps or sample preparation. Herein, we develop a facile strategy to assemble the vertically aligned monolayer of Au nanorods with a nominal 0.8 nm gap distance and demonstrate their applications in the rapid detection of plasticizers and melamine contamination at femtomolar level by surface-enhanced Raman scattering spectroscopy (SERS). The SERS signals of plasticizers are sensitive down to 0.9 fM concentrations in orange juices. It is the lowest detection limit reported to date, which is 7 orders of magnitude lower than the standard of United States (6 ppb). The highly organized vertical arrays generate the reproducible "SERS-active sites" and can be achieved on arbitrary substrates, ranging from silicon, gallium nitride, glass to flexible poly(ethylene naphthalate) substrates

Bin ratio-based histogram distances and their application to image classification

Large variations in image background may cause partial matching and normalization problems for histogram-based representations, i.e., the histograms of the same category may have bins which are significantly different, and normalization may produce large changes in the differences between corresponding bins. In this paper, we deal with this problem by using the ratios between bin values of histograms, rather than bin values' differences which are used in the traditional histogram distances. We propose a bin ratio-based histogram distance (BRD), which is an intra-cross-bin distance, in contrast with previous bin-to-bin distances and cross-bin distances. The BRD is robust to partial matching and histogram normalization, and captures correlations between bins with only a linear computational complexity. We combine the BRD with the ℓ1 histogram distance and the χ2 histogram distance to generate the ℓ1 BRD and the χ2 BRD, respectively. These combinations exploit and benefit from the robustness of the BRD under partial matching and the robustness of the ℓ1 and χ2 distances to small noise. We propose a method for assessing the robustness of histogram distances to partial matching. The BRDs and logistic regression-based histogram fusion are applied to image classification. The experimental results on synthetic data sets show the robustness of the BRDs to partial matching, and the experiments on seven benchmark data sets demonstrate promising results of the BRDs for image classification