713 research outputs found
TESTING DIFFERENCES IN RELATIVE GROWTH-RATE - A METHOD AVOIDING CURVE FITTING AND PAIRING
No full textPoorter, H. and Lewis, C. 1986. Testing differences in relative growth rate: A method avoiding curve fitting and pairing.- Physiol. Plant. 67: 223-226. A method is discussed to test differences in relative growth rates. This method is based on an analysis of variance, with ln-transformed plant weight as dependent vari-able. A significant Group × Time interaction indicates differences in relative growth rates between groups. The advantages over the "classical " and "functional " growth analyses are: (1) No pairing procedure is required. (2) More than two groups may be evaluated in one analysis. (3) No decision is required about the polynomial used to fit the data. (4) By partitioning the interaction effect using orthogonal polynomials in-sight is gained into the nature of differences in relative growth rate. (5) By concen-trating attention on the lower order terms of the polynomials, the influence of extra-neous variation on conclusions may be minimized. Additional key word- Growth analysis
Radiation detection with point-contact Josephson junctions
No full textApplied SciencesApplied Science
A survey on machine learning-based performance improvement of wireless networks: PHY, MAC and network layer
No full textThis paper presents a systematic and comprehensive survey that reviews the latest research efforts focused on machine learning (ML) based performance improvement of wireless networks, while considering all layers of the protocol stack: PHY,MAC and network. First, the related work and paper contributions are discussed, followed by providing the necessary background on data-driven approaches and machine learning to help non-machine learning experts understand all discussed techniques. Then, a comprehensive review is presented on works employing ML-based approaches to optimize the wireless communication parameters settings to achieve improved network quality-ofservice (QoS) and quality-of-experience (QoE).We first categorize these works into: radio analysis, MAC analysis and network prediction approaches, followed by subcategories within each. Finally, open challenges and broader perspectives are discussed.Signal Processing System
Functional linkages between leaf traits and net photosynthetic rate: reconciling empirical and mechanistic models
No full textInternational audience1. We had two objectives: (i) to determine the generality of, and extend the applicability of, a previously reported empirical relationship between leaf-level net photosynthetic rate (A M , nmol g − 1 s − 1), specific leaf area (SLA, m 2 kg − 1) and leaf nitrogen mass fraction (N M , mmol g − 1); and (ii) to compare these empirical results with a mechanistic model of photosynthesis in order to provide a mechanistic justification for the empirical pattern. 2. Our results were based on both literature and original data. There were a total of 160 and 87 data points for the leaf-level and whole-plant data, respectively. 3. Our multiple regression for single leaves was ln(A M) = 0·66 + 0·71 ln(SLA) + 0·79 ln(N M), r 2 = − 0·80; only the intercept (0·11) differed for the whole-plant data. These results are not significantly different from previously published relationships. 4. We then converted the mechanistic model of Evans and Poorter, and a modified version which includes leaf lamina thickness (T) and leaf dry matter (tissue) concentration (C M), into directed acyclic graphs. We then derived reduced graphs that involved only T , C M , SLA, N M and A M. These were tested using structural equation modelling, with measured lamina thickness (T ′) and leaf dry matter ratio (LDMR, g dry mass g − 1 fresh mass) as indicators of T and C M. The original Evans-Poorter model was rejected, but the modified version fitted the structural relationships well. The same qualitative models also applied to the whole-plant data, although the path coefficients sometimes differed. 5. Using simulations, we show that the original Evans-Poorter model predicts a positive correlation between SLA and N M that maximizes A M. The data closely follow this predicted relationship. The correlation between the actual values of A M (standardized units) and the predicted values obtained from the modified Evans-Poorter model was 0·74 and increased to 0·82 once three outlier points were removed. 6. These results provide a mechanistic explanation for the empirical trends relating leaf form and carbon fixation, and predict that SLA and leaf N must be quantitatively coordinated to maximize C fixation
A physiological and genetic analysis of growth characteristics in Hordeum spontaneum
No full textThe aim of this project was to determine to what extent physiological, morphological and chemical growth characteristics are genetically linked and/or caused by common factors. First, 84 accessions of H. spontaneum from different habitats in Israel were screened for their variation in growth traits. A cross was made between contrasting genotypes and the F3 offspring were grown under close to optimal conditions and analysed for their growth characteristics. A map was constructed using AFLP markers. On chromosome 1 two QTLs for relative growth rate and specific leaf area were found at the same location. On chromosome 4 two QTLs for photosynthesis per unit leaf area and stomatal conductance were found at the same position. These traits are probably genetically linked or controlled by a common factor
Analysis of the scalability of UWB indoor localization solutions for high user densities
No full textEffect of climate on traits of dominant and rare tree species in the world’s forests
No full textSpecies’ traits and environmental conditions determine the abundance of tree species across the globe. The extent to which traits of dominant and rare tree species differ remains untested across a broad environmental range, limiting our understanding of how species traits and the environment shape forest functional composition. We use a global dataset of tree composition of >22,000 forest plots and 11 traits of 1663 tree species to ask how locally dominant and rare species differ in their trait values, and how these differences are driven by climatic gradients in temperature and water availability in forest biomes across the globe. We find three consistent trait differences between locally dominant and rare species across all biomes; dominant species are taller, have softer wood and higher loading on the multivariate stem strategy axis (related to narrow tracheids and thick bark). The difference between traits of dominant and rare species is more strongly driven by temperature compared to water availability, as temperature might affect a larger number of traits. Therefore, climate change driven global temperature rise may have a strong effect on trait differences between dominant and rare tree species and may lead to changes in species abundances and therefore strong community
reassembly.EEA Santa Cruz, INTAFil: Hordijk, Iris. Swiss Federal Institute of Technology. Institute of Integrative Biology; SuizaFil: Hordijk, Iris. Wageningen University and Research; Países BajosFil: Poorter, Lourens. Wageningen University and Research; Países BajosFil: Liang, Jingjing. Purdue University. Department of Forestry and Natural Resources; Estados UnidosFil: Reich, Peter B. University of Minnesota. Department of Forest Resources; Estados UnidosFil: Reich, Peter B. Western Sydney University. Hawkesbury Institute for the Environment; Australia.Fil: de-Miguel, Sergio. University of Lleida. Department of Crop and Forest Sciences; EspañaFil: de-Miguel, Sergio. Forest Science and Technology Centre of Catalonia (CTFC); EspañaFil: Nabuurs, Gert-Jan. Wageningen University and Research; Países BajosFil: Gamarra, Javier G. P. Organization of the United Nations. Forestry Division, Food and Agriculture; ItaliaFil: Chen, Han Y. H. Lakehead University. Faculty of Natural Resources Management; Canadá.Fil: Zhou, Mo. Purdue University. Department of Forestry and Natural Resources; Estados UnidosFil: Wiser, Susan. Fil: Wiser, Susan. Landcare Research; Nueva Zelanda.Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Crowther, Thomas W. Institute of Integrative biology. Crowther Lab. Department of environmental Systems Science; Suiz
Seasonal variation in soil and plant water potentials in a Bolivian tropical moist and dry forest
No full textWe determined seasonal variation in soil matric potentials (¿soil) along a topographical gradient and with soil depth in a Bolivian tropical dry (1160 mm y-1 rain) and moist forest (1580 mm y-1). In each forest we analysed the effect of drought on predawn leaf water potentials (¿pd) and drought response (midday leaf water potential at a standardized ¿pd of -0.98 MPa; ¿md) of saplings of three tree species, varying in shade-tolerance and leaf phenology. ¿soil changed during the dry season and most extreme in the dry forest. Crests were drier than slopes and valleys. Dry-forest top soil was drier than deep soil in the dry season, the inverse was found in the wet season. In the moist forest the drought-deciduous species, Sweetia fruticosa, occupied dry sites. In the dry forest the short-lived pioneer, Solanum riparium, occupied wet sites and the shade-tolerant species, Acosmium cardenasii drier sites. Moist-forest species had similar drought response. The dry-forest pioneer showed a larger drought response than the other two species. Heterogeneity in soil water availability and interspecific differences in moisture requirements and drought response suggest great potential for niche differentiation. Species may coexist at different topographical locations, by extracting water from different soil layers and/or by doing so at different moments in tim
A survey on hybrid beamforming techniques in 5G: Architecture and system model perspectives
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