University of California

About: University of California is a education organization based out in Oakland, California, United States. It is known for research contribution in the topics: Population & Layer (electronics). The organization has 55175 authors who have published 52933 publications receiving 1491169 citations. The organization is also known as: UC & University of California System.

Bee foraging ranges and their relationship to body size.

Abstract: Bees are the most important pollinator taxon; therefore, understanding the scale at which they forage has important ecological implications and conservation applications. The foraging ranges for most bee species are unknown. Foraging distance information is critical for understanding the scale at which bee populations respond to the landscape, assessing the role of bee pollinators in affecting plant population structure, planning conservation strategies for plants, and designing bee habitat refugia that maintain pollination function for wild and crop plants. We used data from 96 records of 62 bee species to determine whether body size predicts foraging distance. We regressed maximum and typical foraging distances on body size and found highly significant and explanatory nonlinear relationships. We used a second data set to: (1) compare observed reports of foraging distance to the distances predicted by our regression equations and (2) assess the biases inherent to the different techniques that have been used to assess foraging distance. The equations we present can be used to predict foraging distances for many bee species, based on a simple measurement of body size.

Hedges: A Study In Meaning Criteria And The Logic Of Fuzzy Concepts

Abstract: Logicians have, by and large, engaged in the convenient fiction that sentences of natural languages (at least declarative sentences) are either true or false or, at worst, lack a truth value, or have a third value often interpreted as ‘nonsense’. And most contemporary linguists who have thought seriously about semantics, especially formal semantics, have largely shared this fiction, primarily for lack of a sensible alternative. Yet students of language, especially psychologists and linguistic philosophers, have long been attuned to the fact that natural language concepts have vague boundaries and fuzzy edges and that, consequently, natural language sentences will very often be neither true, nor false, nor nonsensical, but rather true to a certain extent and false to a certain extent, true in certain respects and false in other respects.

Simultaneous Detection and Segmentation

Abstract: We aim to detect all instances of a category in an image and, for each instance, mark the pixels that belong to it. We call this task Simultaneous Detection and Segmentation (SDS). Unlike classical bounding box detection, SDS requires a segmentation and not just a box. Unlike classical semantic segmentation, we require individual object instances. We build on recent work that uses convolutional neural networks to classify category-independent region proposals (R-CNN [16]), introducing a novel architecture tailored for SDS. We then use category-specific, top-down figure-ground predictions to refine our bottom-up proposals. We show a 7 point boost (16% relative) over our baselines on SDS, a 5 point boost (10% relative) over state-of-the-art on semantic segmentation, and state-of-the-art performance in object detection. Finally, we provide diagnostic tools that unpack performance and provide directions for future work.

Development of Ozone Reactivity Scales for Volatile Organic Compounds

Abstract: This paper discusses methods for ranking photochemical ozone formation reactivities of volatile organic compounds (VOCs). Photochemical mechanisms for the atmospheric reactions of 118 VOCs were used to calculate their effects on ozone formation under various NOx conditions in model scenarios representing 39 different urban areas. Their effects on ozone were used to derive 18 different ozone reactivity scales, one of which is the Maximum Incremental Reactivity (MIR) scale used in the new California Low Emission Vehicle and Clean Fuel Regulations. These scales are based on three different methods for quantifying ozone impacts and on six different approaches for dealing with the dependencies of reactivity on NOx. The predictions of the scales are compared, the reasons for their similarities and differences are discussed, and the sensitivities of the scales to NOx and other scenario conditions are examined. Scales based on peak ozone levels were highly dependent on NOx, but those based on integrated ...