The Influence of Temperature on Coumarin 153 Fluorescence Kinetics

The influence of temperature varied in the range 183 K–323 K on the fluorescence quantum yield, fluorescence lifetime, absorption and emission transition moments and non-radiative deactivation rate was determined for the well known and largely used dye Coumarin 153, dissolved in 1-chloropropane. The Kennard-Stepanov relation connecting the absorption and emission spectra was used to check for the presence of more than one absorbing/emitting species and to investigate whether intramolecular vibrational redistribution completes in the C153 excited S1 state before the emission takes place. The emission spectrum corresponding to S1→S0 transition, was fitted at each temperature to the model function including the information on the dye vibrational modes coupling. In this way the displacement in equilibrium distance for the most active vibrational mode was determined for C153 in S1 and in S0. Using the temperature dependence of the fluorescence decay time and quantum yield, the non-radiative deactivation rate was determined. Its temperature dependence was compared to that calculated using the theoretical model with the most active vibrational mode displacement values taken from steady-state spectra analysis. The somewhat surprising dependence of the fluorescence decay time and quantum yield on temperature was related to non-trivial coupling between low-frequency vibrational modes of C153 in the excited and ground states

Micro-Electro-Mechanical-Systems (MEMS) and Fluid Flows

The micromachining technology that emerged in the late 1980s can provide micron-sized sensors and actuators. These micro transducers are able to be integrated with signal conditioning and processing circuitry to form micro-electro-mechanical-systems (MEMS) that can perform real-time distributed control. This capability opens up a new territory for flow control research. On the other hand, surface effects dominate the fluid flowing through these miniature mechanical devices because of the large surface-to-volume ratio in micron-scale configurations. We need to reexamine the surface forces in the momentum equation. Owing to their smallness, gas flows experience large Knudsen numbers, and therefore boundary conditions need to be modified. Besides being an enabling technology, MEMS also provide many challenges for fundamental flow-science research

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Thermalisation of a two-dimensional photonic gas in a 'white-wall' photon box

Bose-Einstein condensation, the macroscopic accumulation of bosonic particles in the energetic ground state below a critical temperature, has been demonstrated in several physical systems. The perhaps best known example of a bosonic gas, blackbody radiation, however exhibits no Bose-Einstein condensation at low temperatures. Instead of collectively occupying the lowest energy mode, the photons disappear in the cavity walls when the temperature is lowered - corresponding to a vanishing chemical potential. Here we report on evidence for a thermalised two-dimensional photon gas with freely adjustable chemical potential. Our experiment is based on a dye filled optical microresonator, acting as a 'white-wall' box for photons. Thermalisation is achieved in a photon number-conserving way by photon scattering off the dye-molecules, and the cavity mirrors both provide an effective photon mass and a confining potential - key prerequisites for the Bose-Einstein condensation of photons. As a striking example for the unusual system properties, we demonstrate a yet unobserved light concentration effect into the centre of the confining potential, an effect with prospects for increasing the efficiency of diffuse solar light collection.Comment: 15 pages, 3 figure

Experimental demonstration of a universally valid error-disturbance uncertainty relation in spin-measurements

The uncertainty principle generally prohibits determination of certain pairs of quantum mechanical observables with arbitrary precision and forms the basis of indeterminacy in quantum mechanics. It was Heisenberg who used the famous gamma-ray microscope thought experiment to illustrate this indeterminacy. A lower bound was set for the product of the measurement error of an observable and the disturbance caused by the measurement. Later on, the uncertainty relation was reformulated in terms of standard deviations, which focuses solely on indeterminacy of predictions and neglects unavoidable recoil in measuring devices. A correct formulation of the error-disturbance relation, taking recoil into account, is essential for a deeper understanding of the uncertainty principle. However, the validity of Heisenberg's original error-disturbance uncertainty relation is justifed only under limited circumstances. Another error-disturbance relation, derived by rigorous and general theoretical treatments of quantum measurements, is supposed to be universally valid. Here, we report a neutron optical experiment that records the error of a spin-component measurement as well as the disturbance caused on another spin-component measurement. The results confirm that both error and disturbance completely obey the new, more general relation but violate the old one in a wide range of an experimental parameter.Comment: 11 pages, 5 figures, Nature Physics (in press

Some comments on the significance and development of midline behavior during infancy

With the waning of the tonic neck reflex beginning with the 8th to 12th week, and disappearing, in most instances, by the 16th week, the infant begins to become bilateral and makes symmetrical movements and engages his hands in the midline usually over the chest while in a supine position. The developmental significance of such behavior is considered—for example, its participation in the emerging sense of self and its role in the consolidation of emerging ego skills. Consideration is given to the possible implications of faulty midline behavior for development, and to whether failure to engage in an optimal amount of midline behavior, in interaction with other factors, can be used to alert observers to possible future developmental disturbances.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43965/1/10578_2005_Article_BF01435498.pd

Native diversity buffers against severity of non-native tree invasions.

This is the final version. Available from Nature Research via the DOI in this record. Data availability: Data used in this study can be found in cited references for the Global Naturalized Alien Flora (GloNAF) database6 (non-native status), the KEW Plants of the World database5 (native ranges) and the Global Environmental Composite63,77 (environmental data layers). Plant trait data were extracted from Maynard et al.78. Data from the Global Forest Biodiversity Initiative (GFBI) database57 are not available due to data privacy and sharing restrictions, but can be obtained upon request via Science-I (https://science-i.org/) or GFBI (gfbinitiative.org) and an approval from data contributors.Code availability All code used to complete analyses for the manuscript is available at the following link: https://github.com/thomaslauber/Global-Tree-Invasion. Data analyses were conducted and were visualizations generated in R (v. 4.2.2), Python (v. 3.9.7), Google Earth Engine (earthengine-api 0.1.306), QGIS-LTR (v. 3.16.7) and the ETH Zurich Euler cluster.Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.Swiss National Science FoundationSwiss National Science FoundationBernina FoundationDOB Ecolog

The global biogeography of tree leaf form and habit

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: Tree occurrence data from the Global Forest Biodiversity initiative (GFBi) is available upon request via Science-I (https://science-i.org) or the GFBi website (https://www.gfbiinitiative.org/). Information on leaf habit (evergreen vs deciduous) and leaf form (broadleaved vs needle-leaved) came from the TRY database (https://www.try-db.org). Additional, leaf-type data came from the Tallo dataset (https://zenodo.org/record/6637599). Plot-level soil information came from the World Soil Information Service (WOSIS) dataset (https://www.isric.org/explore/wosis).Code availability: All code is available at https://doi.org/10.5281/zenodo.7967245.Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling