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An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Project ObjectivesSpatial scales of the food webs that support the growth of juvenile salmonids in California rivers are largely unknown, but such information is essential for management of flows, species, and other ecosystem factors influencing salmonid production. Our project objectives were:1. to determine whether predictable variation in algal d13C with water velocity, and measurements of consumer d13C and d15N could be used to examine energy flow and trophic structure in food webs of the South Fork Eel River, and other salmon-bearing streams in Northern California, and2. to provide this information as a basis for examining how changes in access to energy sources following river regulation or invasions of exotic species might influence the access of various web members, including salmonids, to these sources.
The preparation and analysis of inorganic-organic polymer nanocomposites consisting of inorganic nanowires and multiwire “cables” in a random-coil organic polymer host is reported. Dissolution of inorganic (LiMo 3 Se 3 ) n wires in a strongly coordinating monomer, vinylene carbonate, and the use of a rapid polymerization in the presence of a cross-linking agent produce nanocomposites without phase separation. Polymerization of dilute solutions yields a material containing mostly (Mo 3 Se 3 − ) n mono- and biwires, 6 to 20 angstroms in diameter and 50 to 100 nanometers long. Polymerization of more concentrated liquid crystalline solutions yields a nanocomposite containing oriented multiwire cables, 20 to 40 angstroms in diameter and up to 1500 nanometers long, that display optical anisotropy and electrical conductivity.
The stream-dwelling larvae of the caddisfly Glossosoma spp. are dominant grazers in lotic food webs and are capable of suppressing stream periphyton. We explored a method for developing a scaling relationship between macroinvertebrate density and local hydraulic variables. As an example of this method, we quantified habitat for larval stone-cased caddisflies, Glossosoma califica and Glossosoma penitum, in 3 coastal mountain streams in northern California over 2 y. We applied dimensional analysis to develop a functional relationship from a power law based on dimensionless local hydraulic and larval density variables that was applicable to areas where Glossosoma are present. Glossosoma densities were negatively correlated with streambed relative roughness and positively correlated with the ratio of inertial to gravitational forces in the stream. The proposed functional relationship described 41% of the variance in the spatial distribution of glossosomatid larvae. This expression could predict how density and constraints on effects of these important grazers would change under variable hydraulic conditions. Variogram analysis of Glossosoma spatial density and relative roughness revealed overlap in the variogram range, the separation distance above which point measurements were statistically independent. The analysis resulted in an average variogram range of 0.39 m for Glossosoma density and 0.26 m for roughness height. Abiotic variables are increasingly available from laser altimetry, so even where field sampling is limited the proposed scaling relationship facilitates prediction of larval biomass over a range of scales in lotic ecosystems.
The effect of strong irradiance (2000 micromole photons per square meter per second) on PSII heterogeneity in intact cells of Chlamydomonas reinhardtii was investigated. Low light (LL, 15 micromole photons per square meter per second) grown C. reinhardtii are photoinhibited upon exposure to strong irradiance, and the loss of photosynthetic functioning is due to damage to PSII. Under physiological growth conditions, PSII is distributed into two pools. The large antenna size (PSII(alpha)) centers account for about 70% of all PSII in the thylakoid membrane and are responsible for plastoquinone reduction (Q(b)-reducing centers). The smaller antenna (PSII(beta)) account for the remainder of PSII and exist in a state not yet able to photoreduce plastoquinone (Q(b)-nonreducing centers). The exposure of C. reinhardtii cells to 60 minutes of strong irradiance disabled about half of the primary charge separation between P680 and pheophytin. The PSII(beta) content remained the same or slightly increased during strong-irradiance treatment, whereas the photochemical activity of PSII(alpha) decreased by 80%. Analysis of fluorescence induction transients displayed by intact cells indicated that strong irradiance led to a conversion of PSII(beta) from a Q(b)-nonreducing to a Q(b)-reducing state. Parallel measurements of the rate of oxygen evolution revealed that photosynthetic electron transport was maintained at high rates, despite the loss of activity by a majority of PSII(alpha). The results suggest that PSII(beta) in C. reinhardtii may serve as a reserve pool of PSII that augments photosynthetic electron-transport rates during exposure to strong irradiance and partially compensates for the adverse effect of photoinhibition on PSII(alpha).
ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTInsertion of carbon monoxide into a transition metal-silicon bond. X-ray structure of the silaacyl chloro(trimethylsilyl-.eta.2-carbonyl)bis(.eta.5-cyclopentadienyl)zirconiumT. Don TilleyCite this: J. Am. Chem. Soc. 1985, 107, 13, 4084–4085Publication Date (Print):June 1, 1985Publication History Published online1 May 2002Published inissue 1 June 1985https://pubs.acs.org/doi/10.1021/ja00299a058https://doi.org/10.1021/ja00299a058research-articleACS PublicationsRequest reuse permissionsArticle Views228Altmetric-Citations37LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-AlertscloseSupporting Info (1)»Supporting Information Supporting Information Get e-Alerts
Memristor crossbar architecture is one of the most popular circuit configurations due to its wide range of practical applications. The crossbar architecture can emulate the weighted summation operation, called multiply and accumulate operation (MAC). The errors to MAC computing get introduced due to a range of crossbar variability. We broadly group the variability in three categories: (1) device-to-device variations, (2) programming nonlinearity, and (3) those from peripheral circuits. This tutorial provides insights into the variability and compensation approaches that can be adopted to reduce its impact when designing for practical applications with crossbars.
We describe the problem of automated steering using computer vision, focusing the analysis and design on appropriate lateral controllers. We investigate various static feedback strategies where the measurements obtained from vision, namely offset from the center line at some lookahead distance and the angle between the road tangent and the orientation of the vehicle at some lookahead distance, are directly used for control. Within this setting we explore the role of lookahead, its relation to the vision processing delay, the longitudinal velocity and road geometry. Results from ongoing experiments with our autonomous vehicle system are presented along with simulation results.
