986 resultados para random lasing


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The total abundance of small pelagic species in Mozambican waters was estimated to be 100 (plus or minus 45) thousand tonnes of which scad and mackerel constituted 57 (plus or minus 39) thousand tonnes. These abundance estimates must be considered as minimum estimates of biomass as the efficiency of the trawl was assumed to be equal to 1.0.

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The results obtained during the third phase of Nauka are reported concerning the standing stock estimates, population length structure and gonad development of scad and mackerel stocks and the catch composition in Mozambican waters.

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The east and west coast populations of wild Penaeus monodon in India were genetically characterized by RAPD analysis using six highly polymorphic primers reported earlier. The average genetic similarities within populations, based on profiles generated by all the six primers, were 0.828 and 0.851 for the east and west coast populations, respectively, values with individual primers ranging from 0.744 to 0.889. The average genetic similarity between populations across all the primers was 0.774. The number of bands found to be polymorphic were 38 (51.35%) and 37 (50.68%) in the east and west coast populations, respectively. Primer 5 yielded the highest level of polymorphism (63.63%) in the east coast population whereas primer 3 yielded the lowest level of polymorphism (36.36%) in the west coast population. The study reveals the existence of genetic variation in P. monodon stocks providing scope for genetic improvement through selective breeding. It also provides baseline data for future work on population structure analysis of P. monodon.

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Six sample specimens of Trachypithecus francoisi and 3 of T. leucocephalus were analyzed by use of allozyme electrophoresis and random amplified polymorphism DNA (RAPD) in order to clarify the challenged taxonomic status of the white-head langur. Among the 44 loci surveyed, only 1 locus (PGM-2) was found to be polymorphic. Nei's genetic distance was 0.0025. In total, thirty 10-mer arbitrary primers were used for RAPD analysis, of which 22 generated clear bands. Phylogenetic trees were constructed based on genetic distances using neighbor-joining and UPGMA methods. The results show that T. francoisi and T: leucocephalus are not monophyletic. T. francoisi from Guangxi, China and Vietnam could not be clearly distinguished, and they are not divided into 2 clusters. A t-test was performed to evaluate between genetic distances within and between T. leucocephalus and T. francoisi taxa groups. The statistical test shows that the taxa group within T: leucocephalus and T: francoisi does not significantly differ from that between T: leucocephalus and T: francoisi at the 5% level. Our results suggest that the level of genetic differentiation between T, leucocephalus and T. francoisi is relatively low. Recent gene flow might exist between T. francoisi and T. leucocephalus. Combining morphological features, geographical distribution, allozyme data, RAPD data, and mtDNA sequences, we suggest that the white-head langur might be a subspecies of T. francoisi.

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Motor task variation has been shown to be a key ingredient in skill transfer, retention, and structural learning. However, many studies only compare training of randomly varying tasks to either blocked or null training, and it is not clear how experiencing different nonrandom temporal orderings of tasks might affect the learning process. Here we study learning in human subjects who experience the same set of visuomotor rotations, evenly spaced between -60° and +60°, either in a random order or in an order in which the rotation angle changed gradually. We compared subsequent learning of three test blocks of +30°→-30°→+30° rotations. The groups that underwent either random or gradual training showed significant (P < 0.01) facilitation of learning in the test blocks compared with a control group who had not experienced any visuomotor rotations before. We also found that movement initiation times in the random group during the test blocks were significantly (P < 0.05) lower than for the gradual or the control group. When we fit a state-space model with fast and slow learning processes to our data, we found that the differences in performance in the test block were consistent with the gradual or random task variation changing the learning and retention rates of only the fast learning process. Such adaptation of learning rates may be a key feature of ongoing meta-learning processes. Our results therefore suggest that both gradual and random task variation can induce meta-learning and that random learning has an advantage in terms of shorter initiation times, suggesting less reliance on cognitive processes.