The Constitution and the Synthesis of the Alkaloid Anonaine

The constitution of the alkaloid anonaine has been investigated. The following structural formula was suggested: It is based chiefly on the following experimental results: 1. Empirical formula for anonaine C17H15O2N. 2. Proof a methylenedioxy and a secondary amino-group. 3. Negative tests for methoxy, carbonyl, phenolic and alcoholic hydroxy groups. 4. The details of the Hofmann degradation as well as the effect of chloroethylcarbonate upon N. methyl-anonaine proved the isoquinoline structure of anonaine. 5. The formation of phthalic acid in the oxydation of anonaine proved that anonaine does not possess a papaverine structure. It showed further, that ring C is unsubstituted. By analogy the methylenedioxy group was assumed to be in position 5,6. The correctness of the suggested formula was proved by the synthesis of the alkaloid. d,1-anonaine and also d,1-N-methyl-anonaine were synthesised. These synthetic alkaloids were deprived of their asymmetric centres by a Hofmann degradationand the products thus obtained were proved to be identical with the corresponding degradation compounds of natural anonaine

Interactions between perception and rule-construction in human and machine concept learning

Weitnauer E. Interactions between perception and rule-construction in human and machine concept learning. Bielefeld: Universität Bielefeld; 2016.Concepts are central to human cognition and one important type of concepts can be represented naturally with symbolic rules. The learning of such rule-based concepts from examples relies both on a process of perception, which extracts information from the presented examples, and a process of concept construction, which leads to a rule that matches the given examples and can be applied to categorize new ones. This thesis introduces PATHS, a novel cognitive process model that learns structured, rule-based concepts and takes the active and explorative nature of perception into account. In contrast to existing models, the PATHS model tightly integrates perception and rule construction. The model is applied to a challenging problem domain, the physical Bongard problems, and its performance under different learning conditions is analyzed and compared to that of human solvers

Aggregated Packet Transmission in Duty-Cycled WSNs: Modeling and Performance Evaluation

[EN] Duty cycling (DC) is a popular technique for energy conservation in wireless sensor networks (WSNs) that allows nodes to wake up and sleep periodically. Typically, a single-packet transmission (SPT) occurs per cycle, leading to possibly long delay. With aggregated packet transmission (APT), nodes transmit a batch of packets in a single cycle. The potential benefits brought by an APT scheme include shorter delay, higher throughput, and higher energy efficiency. In the literature, different analytical models have been proposed to evaluate the performance of SPT schemes. However, no analytical models for the APT mode on synchronous DC medium access control (MAC) mechanisms exist. In this paper, we first develop a 3-D discrete-time Markov chain (DTMC) model to evaluate the performance of an APT scheme with packet retransmission enabled. The proposed model captures the dynamics of the state of the queue of nodes and the retransmission status and the evolution of the number of active nodes in the network, i.e., nodes with a nonempty queue. We then study the number of retransmissions needed to transmit a packet successfully. Based on the observations, we develop another less-complex DTMC model with infinite retransmissions, which embodies only two dimensions. Furthermore, we extend the 3-D model into a 4-D model by considering error-prone channel conditions. The proposed models are adopted to determine packet delay, throughput, packet loss, energy consumption, and energy efficiency. Furthermore, the analytical models are validated through discrete-event-based simulations. Numerical results show that an APT scheme achieves substantially better performance than its SPT counterpart in terms of delay, throughput, packet loss, and energy efficiency and that the developed analytical models reveal precisely the behavior of the APT scheme.This work was supported in part by the EU FP7-PEOPLE-IRSES Program under Grant 247083 (Project S2EuNet). The work of J. Martinez-Bauset was supported in part by the Ministry of Economy and Competitiveness of Spain under Grant TIN2013-47272-C2-1-R. The work of M. A. Weitnauer was supported in part by the U.S. National Science Foundation under Grant CNS-1017984.Guntupalli, L.; Martínez Bauset, J.; Li, FY.; Weitnauer, MA. (2017). Aggregated Packet Transmission in Duty-Cycled WSNs: Modeling and Performance Evaluation. IEEE Transactions on Vehicular Technology. 66(1):563-579. https://doi.org/10.1109/TVT.2016.2536686S56357966

Mapping grip force to motor networks.

There is ongoing debate about the role of cortical and subcortical brain areas in force modulation. In a whole-brain approach, we sought to investigate the anatomical basis of grip force whilst acknowledging interindividual differences in connectivity patterns. We tested if brain lesion mapping in patients with unilateral motor deficits can inform whole-brain structural connectivity analysis in healthy controls to uncover the networks underlying grip force. Using magnetic resonance imaging (MRI) and whole-brain voxel-based morphometry in chronic stroke patients (n=55) and healthy controls (n=67), we identified the brain regions in both grey and white matter significantly associated with grip force strength. The resulting statistical parametric maps (SPMs) provided seed areas for whole-brain structural covariance analysis in a large-scale community dwelling cohort (n=977) that included beyond volume estimates, parameter maps sensitive to myelin, iron and tissue water content. The SPMs showed symmetrical bilateral clusters of correlation between upper limb motor performance, basal ganglia, posterior insula and cortico-spinal tract. The covariance analysis with the seed areas derived from the SPMs demonstrated a widespread anatomical pattern of brain volume and tissue properties, including both cortical, subcortical nodes of motor networks and sensorimotor areas projections. We interpret our covariance findings as a biological signature of brain networks implicated in grip force. The data-driven definition of seed areas obtained from chronic stroke patients showed overlapping structural covariance patterns within cortico-subcortical motor networks across different tissue property estimates. This cumulative evidence lends face validity of our findings and their biological plausibility

D6.2: Intermediate Standardisation and Dissemination Activity Report

This report documents the standardisation and dissemination activities performed by the ORPHEUS project consortium from December 2015 to February 2017

A novel satellite mission concept for upper air water vapour, aerosol and cloud observations using integrated path differential absorption LiDAR limb sounding

We propose a new satellite mission to deliver high quality measurements of upper air water vapour. The concept centres around a LiDAR in limb sounding by occultation geometry, designed to operate as a very long path system for differential absorption measurements. We present a preliminary performance analysis with a system sized to send 75 mJ pulses at 25 Hz at four wavelengths close to 935 nm, to up to 5 microsatellites in a counter-rotating orbit, carrying retroreflectors characterized by a reflected beam divergence of roughly twice the emitted laser beam divergence of 15 µrad. This provides water vapour profiles with a vertical sampling of 110 m; preliminary calculations suggest that the system could detect concentrations of less than 5 ppm. A secondary payload of a fairly conventional medium resolution multispectral radiometer allows wide-swath cloud and aerosol imaging. The total weight and power of the system are estimated at 3 tons and 2,700 W respectively. This novel concept presents significant challenges, including the performance of the lasers in space, the tracking between the main spacecraft and the retroreflectors, the refractive effects of turbulence, and the design of the telescopes to achieve a high signal-to-noise ratio for the high precision measurements. The mission concept was conceived at the Alpbach Summer School 2010

Feature biases in early word learning : network distinctiveness predicts age of acquisition

Do properties of a word’s features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge lengths computed using various distance measures. Feature distinctiveness was computed as a distance measure, showing how far an object in a network is from other objects based on shared and non-shared features. Feature distinctiveness predicted order of acquisition across all measures; words that were further away from other words in the network space were learned earlier. The best distance measures were based only on non-shared features (object dissimilarity) and did not include shared features (object similarity). This indicates that shared features may play less of a role in early word learning than non-shared features. In addition, the strongest effects were found for visual form and surface features. Cluster analysis further revealed that this effect is a localized effect in the object feature space, where objects’ distances from their cluster centroid were inversely correlated with their age of acquisition. Together, these results suggest a role for feature distinctiveness in early word learning

Mining Social Interaction Data in Virtual Worlds

Virtual worlds and massively multi-player online games are rich sources of information about large-scale teams and groups, offering the tantalizing possibility of harvesting data about group formation, social networks, and network evolution. However these environments lack many of the cues that facilitate natural language processing in other conversational settings and different types of social media. Public chat data often features players who speak simultaneously, use jargon and emoticons, and only erratically adhere to conversational norms. This chapter presents techniques for inferring the existence of social links from unstructured conversational data collected from groups of participants in the Second Life virtual world