A Version of Jung’s Synchronicity in the Event of Correlation of Mental Processes in the Past and the Future: Possible Role of Quantum Entanglement in Quantum Vacuum

This paper deals with the version of Jung’s synchronicity in which correlation between mental processes of two different persons takes place not just in the case when at a certain moment of time the subjects are located at a distance from each other, but also in the case when both persons are alternately (and sequentially, one after the other) located in the same point of space. In this case, a certain period of time lapses between manifestation of mental process in one person and manifestation of mental process in the other person. Transmission of information from one person to the other via classical communication channel is ruled out. The author proposes a hypothesis, whereby such manifestation of synchronicity may become possible thanks to existence of quantum entanglement between the past and the future within the light cone. This hypothesis is based on the latest perception of the nature of quantum vacuu

Dotplots of CEN versus MCC.

<p>(a) and CEN versus tMCC (b) for 200 000 random confusion matrices of different dimensions.</p

Examples of CEN and MCC for different confusion matrices.

<p>Examples of CEN and MCC for different confusion matrices.</p

Integrating predictive profiling methods from machine learning and complex networks in the bioinformatics analysis of NGS metagenomics data

<p>We propose an integration of machine learning and network medicine methods with state-of-art bioinformatics solutions for the quantitative analysis of microbial communities of clinical interest. In particular, we have developed a framework for functional metagenomics studies based on Next Generation Sequencing (NGS) data in a clinical research setup. Machine Learning and differential network analysis methods are now available. Applications are presented for inflammatory bowel disease (IBD) NGS metagenomics and on microbial community data induced by diet diversity in mice. <em>Poster presented at the "Microbiota and Immunity in Human Diseases" International Symposium (MIHD-OBG), Rome, Italy, 2013.</em></p

Running on HPC Galaxy-based workflows for predictive biomarkers from RNA-Seq clinical data

<p>Poster presented at the Galaxy Community Conference 2013, Oslo, Norway.</p

Ratio between Core and Complete measures vs. ratio between the length of partial lists and the size of the full feature set for about 7000 instances of couples of partial lists.

<p>Lists pairs have the same length and they are randomly permuted, with partial lists length ranging between 1 and 5000 and full set size ranging between 10 and 100000.</p

Levelplot of the values computed on the lists produced by filtering methods (75% threshold) and SRDA models, with Complete Canberra Measure computed on their whole list sets.

<p>Levelplot of the values computed on the lists produced by filtering methods (75% threshold) and SRDA models, with Complete Canberra Measure computed on their whole list sets.</p

Ανέκδοτα εκκλησιαστικά έγγραφα των χρόνων της Τουρκοκρατίας αποκείμενα εν τω Μουσείω Ηρακλείου (μέρος 3ο)

<p>Multidimensional Scaling (MDS) on two components computed on the lists produced by filtering methods (75% threshold) and SRDA models, with Complete Canberra Measure computed on their Borda lists.</p

Core and Complete normalized Canberra dissimilarity measure for two partial lists of 10 features extracted from a set of features.

<p>The partial lists are either identical, randomly permuted (average distance) or maximally distant. The Core Measure for Identical partial lists is zero.</p

Operational steps in computing the Complete Canberra Dissimilarity Measure between two partial lists.

<p>Example on two lists of length 3 and 4 on an alphabet of 6 features, by the closed form Eq. (5) and through the open formula Eq. (3).</p