ADVERTISEMENT RETURN TO ISSUEPREVCommunicationNEXTReductive Elimination of Aryl Halides from Palladium(II)Amy H. Roy and John F. HartwigView Author Information Department of Chemistry, Yale University P.O. Box 208107, New Haven, Connecticut 06520-8107 Cite this: J. Am. Chem. Soc. 2001, 123, 6, 1232–1233Publication Date (Web):January 19, 2001Publication History Received22 September 2000Published online19 January 2001Published inissue 1 February 2001https://pubs.acs.org/doi/10.1021/ja0034592https://doi.org/10.1021/ja0034592rapid-communicationACS PublicationsCopyright © 2001 American Chemical SocietyRequest reuse permissionsArticle Views5405Altmetric-Citations192LEARN 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 SUBJECTS:Anions,Aromatic compounds,Crystal cleavage,Oligomers,Reductive elimination Get e-Alerts
In this short essay, I ask whether our current practice of highly selective conferences is helping us achieve SIGCOMM's research goals. 1 This requires first articulating what those goals are, and then evaluating our practices in relation to those goals. To no one's surprise, this essay contends that there is a significant mismatch between what I believe SIGCOMM's goals should be and what our current practices achieve. I then propose a radical restructuring of our conferences that would provide better alignment and, as an additional benefit, a stronger sense of community. However, I wrote this essay not to promote the specifics of a particular proposal, but to encourage our community to (i) engage in a thorough reexamination of how we organize SIGCOMM-sponsored conferences and (ii) seriously entertain the possibility of radical changes in our practices.
<strong class="journal-contentHeaderColor">Abstract.</strong> The maximum rate of Rubisco carboxylation (<span class="inline-formula"><i>V</i><sub>cmax</sub></span>) determines leaf photosynthetic capacity and is a key parameter for estimating the terrestrial carbon cycle, but its spatial information is lacking, hindering global ecological research. Here, we convert leaf chlorophyll content (LCC) retrieved from satellite data to <span class="inline-formula"><i>V</i><sub>cmax</sub></span>, based on plants' optimal distribution of nitrogen between light harvesting and carboxylation pathways. We also derive <span class="inline-formula"><i>V</i><sub>cmax</sub></span> from satellite (GOME-2) observations of sun-induced chlorophyll fluorescence (SIF) as a proxy of leaf photosynthesis using a data assimilation technique. These two independent global <span class="inline-formula"><i>V</i><sub>cmax</sub></span> products agree well (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M5" display="inline" overflow="scroll" dspmath="mathml"><mrow><msup><mi>r</mi><mn mathvariant="normal">2</mn></msup><mo>=</mo><mn mathvariant="normal">0.79</mn><mo>,</mo><mi mathvariant="normal">RMSE</mi><mo>=</mo><mn mathvariant="normal">15.46</mn><mspace width="0.125em" linebreak="nobreak"/><mrow class="unit"><mi mathvariant="normal">µ</mi></mrow></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="129pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="1cb08b9869c7d3facff26f397ef438e1"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="essd-14-4077-2022-ie00001.svg" width="129pt" height="15pt" src="essd-14-4077-2022-ie00001.png"/></svg:svg></span></span>molâm<span class="inline-formula"><sup>â2</sup></span>âs<span class="inline-formula"><sup>â1</sup></span>, <span class="inline-formula"><i>P</i><i><</i>0.001</span>) and compare well with 3672 ground-based measurements (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M9" display="inline" overflow="scroll" dspmath="mathml"><mrow><msup><mi>r</mi><mn mathvariant="normal">2</mn></msup><mo>=</mo><mn mathvariant="normal">0.69</mn><mo>,</mo><mi mathvariant="normal">RMSE</mi><mo>=</mo><mn mathvariant="normal">13.8</mn><mspace linebreak="nobreak" width="0.125em"/><mrow class="unit"><mi mathvariant="normal">µ</mi></mrow></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="123pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="e4b1cd6460782f3283fc52e81199344e"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="essd-14-4077-2022-ie00002.svg" width="123pt" height="15pt" src="essd-14-4077-2022-ie00002.png"/></svg:svg></span></span>molâm<span class="inline-formula"><sup>â2</sup></span>âs<span class="inline-formula"><sup>â1</sup></span> and <span class="inline-formula"><i>P</i><i><</i>0.001</span> for SIF; <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M13" display="inline" overflow="scroll" dspmath="mathml"><mrow><msup><mi>r</mi><mn mathvariant="normal">2</mn></msup><mo>=</mo><mn mathvariant="normal">0.55</mn><mo>,</mo><mi mathvariant="normal">RMSE</mi><mo>=</mo><mn mathvariant="normal">18.28</mn><mrow class="unit"><mi mathvariant="normal">µ</mi></mrow></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="128pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="1e7590bac7c2176af37541ae765f8518"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="essd-14-4077-2022-ie00003.svg" width="128pt" height="15pt" src="essd-14-4077-2022-ie00003.png"/></svg:svg></span></span>molâm<span class="inline-formula"><sup>â2</sup></span>âs<span class="inline-formula"><sup>â1</sup></span> and <span class="inline-formula"><i>P</i><i><</i>0.001</span> for LCC). The LCC-derived <span class="inline-formula"><i>V</i><sub>cmax</sub></span> product is also used to constrain the retrieval of <span class="inline-formula"><i>V</i><sub>cmax</sub></span> from TROPical Ozone Mission (TROPOMI) SIF data to produce an optimized <span class="inline-formula"><i>V</i><sub>cmax</sub></span> product using both SIF and LCC information. The global distributions of these products are compatible with <span class="inline-formula"><i>V</i><sub>cmax</sub></span> computed from an ecological optimality theory using meteorological variables, but importantly reveal additional information on the influence of land cover, irrigation, soil pH, and leaf nitrogen on leaf photosynthetic capacity. These satellite-based approaches and spatial <span class="inline-formula"><i>V</i><sub>cmax</sub></span> products are primed to play a major role in global ecosystem research. The three remote sensing <span class="inline-formula"><i>V</i><sub>cmax</sub></span> products based on SIF, LCC, and SIF<span class="inline-formula">+</span>LCC are available at <a href="https://doi.org/10.5281/zenodo.6466968">https://doi.org/10.5281/zenodo.6466968</a> (Chen et al., 2022), and the code for implementing the ecological optimality theory is available at <span class="uri">https://github.com/SmithEcophysLab/optimal_vcmax_R</span> and <a href="https://doi.org/10.5281/zenodo.5899564">https://doi.org/10.5281/zenodo.5899564</a> (last access: 31 August 2022) (Smith et al., 2022).
We present an algorithm for identifying and tracking independently moving rigid objects from optical flow. The proposed method uses the fact that each distinct object has a unique epipolar constraint associated with its motion. This is in contrast to using local optical flow information for segmentation. Thus motion discontinuities based on self-occlusion are distinguished from those due to separate objects. The use of epipolar geometry allows for the determination of individual motion parameters for each object as well as the recovery of relative depth for each point on the object. The segmentation problem is formulated as a scene partitioning problem and a statistic-based algorithm which uses only nearest neighbor interactions and a finite number of iterations is developed. A Kalman filter based approach is used for tracking motion parameters with time. The algorithm assumes an affine camera where perspective effects are limited to changes in overall scale. No camera calibration parameters are required.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>