Empirical comparison of correlation measures and pruning levels in complex networks representing the global climate system

Climate change is an issue of growing economic, social, and political concern. Continued rise in the average temperatures of the Earth could lead to drastic climate change or an increased frequency of extreme events, which would negatively affect agriculture, population, and global health. One way of studying the dynamics of the Earth's changing climate is by attempting to identify regions that exhibit similar climatic behavior in terms of long-term variability. Climate networks have emerged as a strong analytics framework for both descriptive analysis and predictive modeling of the emergent phenomena. Previously, the networks were constructed using only one measure of similarity, namely the (linear) Pearson cross correlation, and were then clustered using a community detection algorithm. However, nonlinear dependencies are known to exist in climate, which begs the question whether more complex correlation measures are able to capture any such relationships. In this paper, we present a systematic study of different univariate measures of similarity and compare how each affects both the network structure as well as the predictive power of the clusters. © 2011 IEEE

High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder

Recent progress in quantum algorithms and hardware indicates the potential importance of quantum computing in the near future. However, finding suitable application areas remains an active area of research. Quantum machine learning is touted as a potential approach to demonstrate quantum advantage within both the gate-model and the adiabatic schemes. For instance, the Quantum-assisted Variational Autoencoder has been proposed as a quantum enhancement to the discrete VAE. We extend on previous work and study the real-world applicability of a QVAE by presenting a proof-of-concept for similarity search in large-scale high-dimensional datasets. While exact and fast similarity search algorithms are available for low dimensional datasets, scaling to high-dimensional data is non-trivial. We show how to construct a space-efficient search index based on the latent space representation of a QVAE. Our experiments show a correlation between the Hamming distance in the embedded space and the Euclidean distance in the original space on the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset. Further, we find real-world speedups compared to linear search and demonstrate memory-efficient scaling to half a billion data points

Questionnaire of chronic illness care in primary care-psychometric properties and test-retest reliability

<p>Abstract</p> <p>Background</p> <p>The Chronic Care Model (CCM) is an evidence-based approach to improving the structure of care for chronically ill patients with multimorbidity. The Assessment of Chronic Illness Care (ACIC), an instrument commonly used in international research, includes all aspects of the CCM, but cannot be easily extended to the German context. A new instrument called the "Questionnaire of Chronic Illness Care in Primary Care" (QCPC) was developed for use in Germany for this reason. Here, we present the results of the psychometric properties and test-retest reliability of QCPC.</p> <p>Methods</p> <p>A total of 109 family doctors from different German states participated in the validation study. Participating physicians completed the QCPC, which includes items concerning the CCM and practice structure, at baseline (T0) and 3 weeks later (T1). Internal consistency reliability and test-retest reliability were evaluated using Cronbach's alpha and Pearson's r, respectively.</p> <p>Results</p> <p>The QCPC contains five elements of the CCM (decision support, delivery system design, self-management support, clinical information systems, and community linkages). All subscales demonstrated moderate internal consistency and moderate test-retest reliability over a three-week interval.</p> <p>Conclusions</p> <p>The QCPC is an appropriate instrument to assess the structure of chronic illness care. Unlike the ACIC, the QCPC can be used by health care providers without CCM training. The QCPC can detect the actual state of care as well as areas for improvement of care according to the CCM.</p

Evaluation of job satisfaction of practice staff and general practitioners: an exploratory study

Contains fulltext : 95875.pdf (publisher's version ) (Open Access

Suspension fluorescence in situ hybridization (S-FISH) combined with automatic detection and laser microdissection for STR profiling of male cells in male/female mixtures

Laser microdissection is a valuable tool for isolating specific cells from mixtures, such as male cells in a mixture with female cells, e.g., in cases of sexual assault. These cells can be stained with Y-chromosome-specific probes. We developed an automatic screening method to detect male cells after fluorescence in situ hybridization in suspension (S-FISH). To simulate forensic casework, the method was tested on female saliva after cataglottis (a kiss involving tongue-to-tongue contact) and on licking traces (swabs of dried male saliva on female skin) even after drying. After isolation of the detected cells, short tandem repeat profiling was performed. Full DNA profiles could consistently be obtained from as little as ten buccal cells. Isolation of five cells resulted in a mean of 98% (SD of 3.4%) of the alleles detected, showing that the developed S-FISH staining had no significant negative influence on DNA recovery and can be used in forensic casework

Azimuthal Correlations in the Target Fragmentation Region of High Energy Nuclear Collisions

Results on the target mass dependence of proton and pion pseudorapidity distributions and of their azimuthal correlations in the target rapidity range $-1.73 \le \eta \le 1.32$ are presented. The data have been taken with the Plastic-Ball detector set-up for 4.9 GeV p + Au collisions at the Berkeley BEVALAC and for 200 $A\cdot$GeV/$c$ p-, O-, and S-induced reactions on different nuclei at the CERN-SPS. The yield of protons at backward rapidities is found to be proportional to the target mass. Although protons show a typical ``back-to-back'' correlations, a ``side-by-side'' correlation is observed for positive pions, which increases both with target mass and with impact parameter of a collision. The data can consistently be described by assuming strong rescattering phenomena including pion absorption effects in the entire excited target nucleus.Comment: 7 pages, figures included, complete postscript available at ftp://qgp.uni-muenster.de/pub/paper/azi-correlations.ps submitted to Phys. Lett.

Climate Dynamics: A Network-Based Approach for the Analysis of Global Precipitation

Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can enhance high precipitation gradients, leading to a systematic absence of long-range patterns

Local Difference Measures between Complex Networks for Dynamical System Model Evaluation

Acknowledgments We thank Reik V. Donner for inspiring suggestions that initialized the work presented herein. Jan H. Feldhoff is credited for providing us with the STARS simulation data and for his contributions to fruitful discussions. Comments by the anonymous reviewers are gratefully acknowledged as they led to substantial improvements of the manuscript.Peer reviewedPublisher PD