1,721,545 research outputs found
Optimum space diversità detection of weak signals in non-Gaussain noise employing both time and spatial sampling
No full textSINDROME ADENOBRONCHIALE DA BRONCOLITA: TRATTAMENTO ENDOSCOPICO
No full textGLI AUTORI HANNO OSSERVATO UN CASO DI SINDROME ADENOBRONCHIALE DA BRONCOLITA DELL'EMISISTEMA POLMONARE DESTRO TRATTATO CON TERAPIA ENDOSCOPIC
Selection diversity reception of multilevel NCFSK systems in impulsive noise environments
No full textOptimum space diversità detection of weak signals in non-Gaussain noise employing both time and spatial sampling
No full text
Selection diversity reception of multilevel NCFSK systems in impulsive noise environments
No full textIncreasing efficiency of crop production with LEDs
Full text linkLight-emitting diode (LED) technology is paving the way to increase crop production efficiency with electric lamps. Users can select specific wavelengths to elicit targeted photomorphogenic, biochemical, or physiological plants responses. In addition, LEDs can help control the seasonality of flowering plants to accurately schedule uniform flowering based on predetermined market dates. Research has shown that the monochromatic nature of LEDs can help prevent physiological disorders that are common in indoor environments, and help reduce incidence of pest and disease pressure in agriculture, which could ultimately increase crop production efficiency by preventing crop losses. Furthermore, a significant attribute of LED technology is the opportunity to reduce energy costs associated with electric lighting. Studies have shown that by increasing canopy photon capture efficiency and/or precisely controlling light output in response to the environment or to certain physiological parameters, energy efficiency and plant productivity can be optimized with LEDs. Future opportunities with LED lighting include the expansion of the vertical farming industry, applications for space-based plant growth systems, and potential solutions to support off-grid agriculture
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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