NOSA, an Analytical Toolbox for Multicellular Optical Electrophysiology

Understanding how neural networks generate activity patterns and communicate with each other requires monitoring the electrical activity from many neurons simultaneously. Perfectly suited tools for addressing this challenge are genetically encoded voltage indicators (GEVIs) because they can be targeted to specific cell types and optically report the electrical activity of individual, or populations of neurons. However, analyzing and interpreting the data from voltage imaging experiments is challenging because high recording speeds and properties of current GEVIs yield only low signal-to-noise ratios, making it necessary to apply specific analytical tools. Here, we present NOSA (Neuro-Optical Signal Analysis), a novel open source software designed for analyzing voltage imaging data and identifying temporal interactions between electrical activity patterns of different origin. In this work, we explain the challenges that arise during voltage imaging experiments and provide hands-on analytical solutions. We demonstrate how NOSA’s baseline fitting, filtering algorithms and movement correction can compensate for shifts in baseline fluorescence and extract electrical patterns from low signal-to-noise recordings. NOSA allows to efficiently identify oscillatory frequencies in electrical patterns, quantify neuronal response parameters and moreover provides an option for analyzing simultaneously recorded optical and electrical data derived from patch-clamp or other electrode-based recordings. To identify temporal relations between electrical activity patterns we implemented different options to perform cross correlation analysis, demonstrating their utility during voltage imaging in Drosophila and mice. All features combined, NOSA will facilitate the first steps into using GEVIs and help to realize their full potential for revealing cell-type specific connectivity and functional interactions

Predicting the outcomes of organic reactions via machine learning: are current descriptors sufficient?

As machine learning/artificial intelligence algorithms are defeating chess masters and, most recently, GO champions, there is interest -and hope -that they will prove equally useful in assisting chemists in predicting outcomes of organic reactions. This paper demonstrates, however, that the applicability of machine learning to the problems of chemical reactivity over diverse types of chemistries remains limited -in particular, with the currently available chemical descriptors, fundamental mathematical theorems impose upper bounds on the accuracy with which raction yields and times can be predicted. Improving the performance of machine-learning methods calls for the development of fundamentally new chemical descriptors

Machine learning for molecular and materials science

Here we summarize recent progress in machine learning for the chemical sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future in which the design, synthesis, characterization and application of molecules and materials is accelerated by artificial intelligence.</p

PDA – Remote Display Interaction Framework

This paper discusses the design of a PDA-driven remote display control system which was designed for a pervasive computing scenario. Our solution enables a PDA to perform as an interaction device (such as keyboard or mouse) to operate applications which are using remote displays. Our system consists of two components: one devoted to pair users and remote display according to their relative position, and one to provide the PDA with appropriate graphical interfaces and ad-hoc communication protocols. Besides a case study on the use of remote displays during a course with in our department, this paper discusses system highlights, components, and experiments as for standard multimedia and office applications

The eXtensible Dynamic Presentation Manager for content adaptation

Human Computer Interaction studies deals with systems and tools that are able to improve user experience during interaction with computer. For this purpose, modern web application are expected to supply multimodal and multi-channel access, adaptivity and transcoding features. We will present in this work the eXtensible Dynamic Presentation Manager (XDPM) which is a set of innovative tools that support the eXtensible Presentation Language (XPL) in the adaptation of contents to different working contexts. The adaptation is performed according to the delivery context information which have been formalized by means of a profiler system. A profile holds information about the specific access device, the user preferences and the device working conditions

Z.06 Il quartiere ZEN e la Piana dei Colli. Un parco attorno al quartiere

L’intervento progettuale si inserisce in un fragile contesto territoriale (al centro della Piana dei Colli), che si configura come un enclave isolato, in cui pesanti interventi di trasformazione urbana continuano a sovrapporsi ai segni della storia. Tali trasformazioni, nel tempo, hanno determinato gravi fenomeni di degrado fisico e sociale. Dalla rilettura della stratificazione delle permanenze storiche (beni architettonici, borgate, viabilità, aree agricole di pregio) e del rapporto con il sistema insediativo urbano e naturale extraurbano, il progetto propone la ri-significazione delle diverse tipologie di aree libere che circondano lo ZEN 2 come un sistema di parchi – Parco agricolo della Biodiversità e Giardino della Sostenibilità – dal valore evocativo, culturale ed etico

Guaianolides from the aerial parts of Centaurea hololeuca

Seven guaianolides were isolated from the acetone extract of the aerial parts of Centaurea hololeuca Boiss. The antifeedant activity of the natural compounds (1-7) and of four chloro derivatives (8-11), synthesized from repin (1) and janerin (3) were tested against larvae of Spodoptera littoralis. Cebellin J (6) and chlorojanerin (11) showed significant antifeedant activity at 100 ppm, whereas at this concentration cebellin G (4) and 15-deschloro-15- hydroxychlorojanerin (7) stimulated feeding. Cebellin G (4) stimulated larvae of S. littoralis to feed at low concentration, but deterred feeding at high concentrations. The addition of chlorine to repin (1) resulted in an increase in antifeedant activity