Imaging-based Parametric Resonance in an Optical Dipole Atom Trap

We report sensitive detection of parametric resonances in a high-density sample of ultracold $^{87}Rb$ atoms confined to a far-off-resonance optical dipole trap. Fluorescence imaging of the expanded ultracold atom cloud after a period of parametric excitation shows significant modification of the atomic spatial distribution and has high sensitivity compared with traditional measurements of parametrically-driven trap loss. Using this approach, a significant shift of the parametric resonance frequency is observed, and attributed to the anharmonic shape of the dipole trap potential

Australia's national health programs: An ontological mapping

Australia has a large number of health program initiatives whose comprehensive assessment will help refine and redefine priorities by highlighting areas of emphasis, under-emphasis, and non-emphasis. The objectives of our research are to: (a) systematically map all the programs onto an ontological framework, and (b) systemically analyse their relative emphases at different levels of granularity. We mapped all the health program initiatives onto an ontology with five dimensions, namely: (a) Policy-scope, (b) Policy-focus, (c) Outcomes, (d) Type of care, and (e) Population served. Each dimension is expanded into a taxonomy of its constituent elements. Each combination of elements from the five dimensions is a possible policy initiative component. There are 30,030 possible components encapsulated in the ontology. It includes, for example: (a) National financial policies on accessibility of preventive care for family, and (b) Local-urban regulatory policies on cost of palliative care for individual-aged. Four of the authors mapped all of Australia's health programs and initiatives on to the ontology. Visualizations of the data are used to highlight the relative emphases in the program initiatives. The dominant emphasis of the program initiatives is: [National] [educational, personnel-physician, information] policies on [accessibility, quality] of [preventive, wellness] care for the [community]. However, although (a) information is emphasized technology is not and (b) accessibility and quality are emphasized cost, satisfaction, and quality are not. The ontology and the results of the mapping can help systematically reassess and redirect the relative emphases of the programs and initiatives from a systemic perspective

Catalysis of Stark-Tuned Interactions Between Ultracold Rydberg Atoms

We have experimentally investigated a catalysis effect in the resonant energy transfer between ultracold 85Rb Rydberg atoms. We studied the time dependence of the process, 34p+34p→34s+35s, and observed an enhancement of 34s state population when 34d state atoms are added. We have also performed numerical model simulations, which are in qualitative agreement with experiment and indicate that the enhancement arises from a redistribution of p-state atoms due to the presence of the d-state atoms

Catalysis of Stark-tuned Interactions Between Ultracold Rydberg Atoms

We have experimentally investigated a catalysis effect in the resonant energy transfer between ultracold 85Rb Rydberg atoms. We studied the time dependence of the process, 34p + 34p → 34s + 35s, and observed an enhancement of 34s state population when 34d state atoms are added.We have also performed numerical model simulations, which are in qualitative agreement with experiment and indicate that the enhancement arises from a redistribution of p-state atoms due to the presence of the d-state atoms

Characterizing and mapping cropping patterns in a complex agro-ecosystem: An iterative participatory mapping procedure using machine learning algorithms and MODIS vegetation indices

Accurate and up-to-date spatial agricultural information is essential for applications including agro-environmental assessment, crop management, and appropriate targeting of agricultural technologies. There is growing research interest in spatial analysis of agricultural ecosystems applying satellite remote sensing technologies. However, usability of information generated from many of remotely sensed data is often constrained by accuracy problems. This is of particular concern in mapping complex agro-ecosystems in countries where small farm holdings are dominated by diverse crop types. This study is a contribution to the ongoing efforts towards overcoming accuracy challenges faced in remote sensing of agricultural ecosystems. We applied time-series analysis of vegetation indices (Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI)) derived from the Moderate Resolution Imaging Spectrometer (MODIS) sensor to detect seasonal patterns of irrigated and rainfed cropping patterns in five townships in the Central Dry Zone of Myanmar, which is an important agricultural region of the country has been poorly mapped with respect to cropping practices. To improve mapping accuracy and map legend completeness, we implemented a combination of (i) an iterative participatory approach to field data collection and classification, (ii) the identification of appropriate size and types of predictor variables (VIs), and (iii) evaluation of the suitability of three Machine Learning algorithms: Support Vector Machine (SVM), Random Forest (RF), and C5.0 algorithms under varying training sample sizes. Through these procedures, we were able to progressively improve accuracy and achieve maximum overall accuracy of 95% When a small sized training dataset was used, accuracy achieved by RF was significantly higher compared to SVM and C5.0 (P < 0.01), but as sample size increased, accuracy differences among the three machine learning algorithms diminished. Accuracy achieved by use of NDVI was consistently better than that of EVI (P < 0.01). The maximum overall accuracy was achieved using RF and 8-days NDVI composites for three years of remote sensing data. In conclusion, our findings highlight the important role of participatory classification, especially in areas where cropping systems are highly diverse and differ over space and time. We also show that the choice of classifiers and size of predictor variables are essential and complementary to the participatory mapping approach in achieving desired accuracy of cropping pattern mapping in areas where other sources of spatial information are scarce

The complete conformal spectrum of a sl(2∣1)sl(2|1) invariant network model and logarithmic corrections

We investigate the low temperature asymptotics and the finite size spectrum of a class of Temperley-Lieb models. As reference system we use the spin-1/2 Heisenberg chain with anisotropy parameter $\Delta$ and twisted boundary conditions. Special emphasis is placed on the study of logarithmic corrections appearing in the case of $\Delta=1/2$ in the bulk susceptibility data and in the low-energy spectrum yielding the conformal dimensions. For the $sl(2|1)$ invariant 3-state representation of the Temperley-Lieb algebra with $\Delta=1/2$ we give the complete set of scaling dimensions which show huge degeneracies.Comment: 18 pages, 5 figure