Cut-rose production in response to planting density in two contrasting cultivars

Growing in lower planting density, rose plants produce more assimilates, which can be used to produce more and/or heavier flowering shoots. The effect of planting density was investigated during a period including the first five flowering flushes of a young crop. In a heated greenhouse two cut-rose cultivars were grown under bent canopy management. ‘Akito’ on own-roots and ‘Ilios’ on ‘Natal Briar’ rootstock were planted with densities of 8 and 4 plants per m2. Starting at the end of June 2007, flowering shoots were harvested over a time span of eight months. Based on ‘flowering flushes’, times of high harvest rate, the harvesting time span could be divided into five consecutive periods, each including one flush. The cultivars showed contrasting responses to planting density. In the first three periods the response in ‘Ilios’ was extraordinary, because at low density plants did not produce more flowering shoots, as would be expected. However, the response in shoot fresh weight was larger for ‘Ilios’ than for ‘Akito’, 35% compared to 21% over the entire study period. The results imply that there was a genetic difference in the effect of assimilate availability and/or local light environment. During the first three periods, these factors can not have influenced shoot number in ‘Ilios’, while they did in ‘Akito’. It is suggested that decreases of assimilate availability in winter caused the shoot number response to emerge for ‘Ilios’ later on

Evaluation of Machine Learning Tools for Inspection of Steam Generator Tube Structures using Pulsed Eddy Current

Inspection of multi-component systems, such as nuclear steam generator (SG) tube support structures, is complicated by multiple overlapping degradation modes. The simultaneous and precise measurement of more than two interdependent parameters is challenging when standard statistical regression analysis tools are used. Artificial neural networks (ANNs) have recently been applied to pulsed eddy current (PEC) data for inspection of Alloy 800 SG tube fretting, in the presence of tube off-set within a corroded ferromagnetic support structure. Signals were analyzed using modified principal component analysis (MPCA) followed by an ANN analysis, which simultaneously targeted four parameters associated with the support structure. These were hole diameter, tube off-centering in two mutually orthogonal directions and fret depth. In this work, the ANN analysis is compared with that performed by a Support Vector Machine (SVM) analysis of the same data. Comparable results are achieved for some parameters with both machine learning analysis tools. However, parameters with changing signal variance, such as those associated with support structure diameter, are not as easily compensated for using standard SVM analysis. Both techniques also rely on the availability of a representative training data set that may be difficult to come by for general inspection conditions

A Multi-signal Variant for the GPU-based Parallelization of Growing Self-Organizing Networks

Among the many possible approaches for the parallelization of self-organizing networks, and in particular of growing self-organizing networks, perhaps the most common one is producing an optimized, parallel implementation of the standard sequential algorithms reported in the literature. In this paper we explore an alternative approach, based on a new algorithm variant specifically designed to match the features of the large-scale, fine-grained parallelism of GPUs, in which multiple input signals are processed at once. Comparative tests have been performed, using both parallel and sequential implementations of the new algorithm variant, in particular for a growing self-organizing network that reconstructs surfaces from point clouds. The experimental results show that this approach allows harnessing in a more effective way the intrinsic parallelism that the self-organizing networks algorithms seem intuitively to suggest, obtaining better performances even with networks of smaller size.Comment: 17 page

Breaking Synchrony by Heterogeneity in Complex Networks

For networks of pulse-coupled oscillators with complex connectivity, we demonstrate that in the presence of coupling heterogeneity precisely timed periodic firing patterns replace the state of global synchrony that exists in homogenous networks only. With increasing disorder, these patterns persist until they reach a critical temporal extent that is of the order of the interaction delay. For stronger disorder these patterns cease to exist and only asynchronous, aperiodic states are observed. We derive self-consistency equations to predict the precise temporal structure of a pattern from the network heterogeneity. Moreover, we show how to design heterogenous coupling architectures to create an arbitrary prescribed pattern.Comment: 4 pages, 3 figure

Neutron-induced background in the CONUS experiment

CONUS is a novel experiment aiming at detecting elastic neutrino nucleus scattering in the fully coherent regime using high-purity Germanium (Ge) detectors and a reactor as antineutrino ($\bar\nu$) source. The detector setup is installed at the commercial nuclear power plant in Brokdorf, Germany, at a very small distance to the reactor core in order to guarantee a high flux of more than 10$^{13}\bar\nu$/(s$\cdot$cm$^2$). For the experiment, a good understanding of neutron-induced background events is required, as the neutron recoil signals can mimic the predicted neutrino interactions. Especially neutron-induced events correlated with the thermal power generation are troublesome for CONUS. On-site measurements revealed the presence of a thermal power correlated, highly thermalized neutron field with a fluence rate of (745$\pm$30)cm$^{-2}$d$^{-1}$. These neutrons that are produced by nuclear fission inside the reactor core, are reduced by a factor of $\sim$10$^{20}$ on their way to the CONUS shield. With a high-purity Ge detector without shield the $\gamma$-ray background was examined including highly thermal power correlated $^{16}$N decay products as well as $\gamma$-lines from neutron capture. Using the measured neutron spectrum as input, it was shown, with the help of Monte Carlo simulations, that the thermal power correlated field is successfully mitigated by the installed CONUS shield. The reactor-induced background contribution in the region of interest is exceeded by the expected signal by at least one order of magnitude assuming a realistic ionization quenching factor of 0.2.Comment: 28 pages, 28 figure

Evidence of different climatic adaptation strategies in humans and non-human primates

Abstract: To understand human evolution it is critical to clarify which adaptations enabled our colonisation of novel ecological niches. For any species climate is a fundamental source of environmental stress during range expansion. Mammalian climatic adaptations include changes in size and shape reflected in skeletal dimensions and humans fit general primate ecogeographic patterns. It remains unclear however, whether there are also comparable amounts of adaptation in humans, which has implications for understanding the relative importance of biological/behavioural mechanisms in human evolution. We compare cranial variation between prehistoric human populations from throughout Japan and ecologically comparable groups of macaques. We compare amounts of intraspecific variation and covariation between cranial shape and ecological variables. Given equal rates and sufficient time for adaptation for both groups, human conservation of non-human primate adaptation should result in comparable variation and patterns of covariation in both species. In fact, we find similar amounts of intraspecific variation in both species, but no covariation between shape and climate in humans, contrasting with strong covariation in macaques. The lack of covariation in humans may suggest a disconnect in climatic adaptation strategies from other primates. We suggest this is due to the importance of human behavioural adaptations, which act as a buffer from climatic stress and were likely key to our evolutionary success

State-Insensitive Cooling and Trapping of Single Atoms in an Optical Cavity

Single Cesium atoms are cooled and trapped inside a small optical cavity by way of a novel far-off-resonance dipole-force trap (FORT), with observed lifetimes of 2 to 3 seconds. Trapped atoms are observed continuously via transmission of a strongly coupled probe beam, with individual events lasting ~ 1 s. The loss of successive atoms from the trap N = 3 -> 2 -> 1 -> 0 is thereby monitored in real time. Trapping, cooling, and interactions with strong coupling are enabled by the FORT potential, for which the center-of-mass motion is only weakly dependent on the atom's internal state.Comment: 5 pages, 4 figures Revised version to appear in Phys. Rev. Let