FreesoundVR: soundscape composition in virtual reality using online sound repositories

Virtual Reality - The intersection between sound and music computing and Virtual Reality (VR) has grown significantly over the past decades, amounting to an established area of research today....     

Photonic-aware neural networks

Neural Computing and Applications - Photonics-based neural networks promise to outperform electronic counterparts, accelerating neural network computations while reducing power consumption and...     

A Novel Particle/Photon Detector Based on a Superconducting Proximity Array of Nanodots

The current frontiers in the investigation of high-energy particles demand for new detection methods. Higher sensitivity to low-energy deposition, high-energy resolution to identify events and improve the background rejection, and large detector masses have to be developed to detect even an individual particle that weakly interacts with ordinary matter. Here, we will describe the concept and the layout of a novel superconducting proximity array which show dynamic vortex Mott insulator to metal transitions, as an ultra-sensitive compact radiation-particle detector.     

Unsupervised tissue classification of brain MR images for voxel‐based morphometry analysis

In this article, a fully unsupervised method for brain tissue segmentation of T1‐weighted MRI 3D volumes is proposed. The method uses the Fuzzy C‐Means (FCM) clustering algorithm and a Fully Connected Cascade Neural Network (FCCNN) classifier. Traditional manual segmentation methods require neuro‐radiological expertise and significant time while semiautomatic methods depend on parameter's setup and trial‐and‐error methodologies that may lead to high intraoperator/interoperator variability. The proposed method selects the most useful MRI data according to FCM fuzziness values and trains the FCCNN to learn to classify brain’ tissues into White Matter, Gray Matter, and Cerebro‐Spinal Fluid in an unsupervised way. The method has been tested on the IBSR dataset, on the BrainWeb Phantom, on the BrainWeb SBD dataset, and on the real dataset “University of Palermo Policlinico Hospital” (UPPH), Italy. Sensitivity, Specificity, Dice and F‐Factor scores have been calculated on the IBSR and BrainWeb datasets segmented using the proposed method, the FCM algorithm, and two state‐of‐the‐art brain segmentation software packages (FSL and SPM) to prove the effectiveness of the proposed approach. A qualitative evaluation involving a group of five expert radiologists has been performed segmenting the real dataset using the proposed approach and the comparison algorithms. Finally, a usability analysis on the proposed method and reference methods has been carried out from the same group of expert radiologists. The achieved results show that the segmentations of the proposed method are comparable or better than the reference methods with a better usability and degree of acceptance.     

Engineered Multifunctional Albumin‐Decorated Porous Silicon Nanoparticles for FcRn Translocation of Insulin

The last decade has seen remarkable advances in the development of drug delivery systems as alternative to parenteral injection‐based delivery of insulin. Neonatal Fc receptor (FcRn)‐mediated transcytosis has been recently proposed as a strategy to increase the transport of drugs across the intestinal epithelium. FcRn‐targeted nanoparticles (NPs) could hijack the FcRn transcytotic pathway and cross the epithelial cell layer. In this study, a novel nanoparticulate system for insulin delivery based on porous silicon NPs is proposed. After surface conjugation with albumin and loading with insulin, the NPs are encapsulated into a pH‐responsive polymeric particle by nanoprecipitation. The developed NP formulation shows controlled size and homogeneous size distribution. Transmission electron microscopy (TEM) images show successful encapsulation of the NPs into pH‐sensitive polymeric particles. No insulin release is detected at acidic conditions, but a controlled release profile is observed at intestinal pH. Toxicity studies show high compatibility of the NPs with intestinal cells. In vitro insulin permeation across the intestinal epithelium shows approximately fivefold increase when insulin is loaded into FcRn‐targeted NPs. Overall, these FcRn‐targeted NPs offer a toolbox in the development of targeted therapies for oral delivery of insulin.     

Dynamics and self-assembly of bio-functionalized gold nanoparticles in solution: Reactive molecular dynamics simulations

The self-assembling properties, stability, and dynamics of hybrid nanocarriers (gold nanoparticles (AuNPs) functionalized with cysteine-based peptides) in solution are studied through a series of classical molecular dynamics simulations based on a recently parametrized reactive force field. The results reveal, at the atomic level, all the details regarding the peptide adsorption mechanisms, nanoparticle stabilization, aggregation, and sintering. The data confirm and explain the experimental findings and disclose aspects that cannot be scrutinized by experiments. The biomolecules are both chemisorbed and physisorbed; self-interactions of the adsorbates and formation of stable networks of interconnected molecules on the AuNP surfaces limit substrate reconstructions, protect the AuNPs from the action of the solvent, and prevent direct interactions of the gold surfaces. The possibility of agglomeration of the functionalized nanoparticles, compared with the sintering of the bare supports in a water solution, is demonstrated through relatively long simulations and fast steered dynamics. The analysis of the trajectories reveals that the AuNPs were well stabilized by the peptides. This prevented particle sintering and kept the particles far apart; however, part of their chains could form interconnections (crosslinks) between neighboring gold vehicles. The excellent agreement of these results with the literature confirm the reliability of the method and its potential application to the modeling of more complex materials relevant to the biomedical sector.

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A declarative two-level framework to specify and verify workflow and authorization policies in service-oriented architectures

The specification of distributed service-oriented applications spans several levels of abstraction, e.g., the protocol for exchanging messages, the set of interface functionalities, the types of the manipulated data, the workflow, the access policy, etc. Many (even executable) specification languages are available to describe each level in separation. However, these levels may interact in subtle ways (for example, the control flow may depend on the values of some data variables) so that a precise abstraction of the application amounts to more than the sum of its per level components. This problem is even more acute in the design phase when automated analysis techniques may greatly help the difficult task of building “correct” applications faced by designers. To alleviate this kind of problems, this paper introduces a framework for the formal specification and automated analysis of distributed service-oriented applications in two levels: one for the workflow and one for the authorization policies. The former allows one to precisely describe the control and data parts of an application with their mutual dependencies. The latter focuses on the specification of the criteria for granting or denying third-party applications the possibility to access shared resources or to execute certain interface functionalities. These levels can be seen as abstractions of one or of several levels of specification mentioned above. The novelty of our proposal is the possibility to unambiguously specify the—often subtle—interplay between the workflow and policy levels uniformly in the same framework. Additionally, our framework allows us to define and investigate verification problems for service-oriented applications (such as executability and invariant checking) and give sufficient conditions for their decidability. These results are non-trivial because their scope of applicability goes well beyond the case of finite state spaces allowing for applications manipulating variables ranging over infinite domains. As proof of concept, we show the suitability and flexibility of our approach on two quite different examples inspired by industrial case studies.     

Mediating debate through on-line large-scale argumentation: Evidence from the field

Web 2.0 technologies, such as forums and wikis, are enabling an explosion of global knowledge sharing through distributed large-scale conversations, but they seem to be less successful at supporting collaborative deliberation around complex and controversial questions. In order to cope with this limitation, many scholars have proposed to adopt on-line argumentation platforms to improve information visualization, organization and reuse. However, such research has mostly focused on the design of adequate argument-based knowledge formalisms. Less attention has been paid to the empirical analysis of actual interactions mediated by argumentation technology with reasonably large user communities. In this paper, we present an in-depth analysis of the data obtained in the empirical test of an argumentation platform where a 160-member community created, in 3 weeks, what is to our knowledge the largest single online argument map ever built (around 5000 posts). Our results show that (i) users were able to quickly and comprehensively explore and map the debate on the selected discussion topic; (ii) substantial moderation was needed to ensure that the argument map was well-organized and users were confident with the argumentation formalism; (iii) considerable out-of-the map communication occurred, possibly as a way to allow for conversational flows inhibited by the argumentation formalism, (iv) formal rating of contributions favored exploration of the map, understanding the debate structure, and improving the quality of content.     

Sound synthesis and evaluation of interactive footsteps and environmental sounds rendering for virtual reality applications

We propose a system that affords real-time sound synthesis of footsteps on different materials. The system is based on microphones, which detect real footstep sounds from subjects, from which the ground reaction force (GRF) is estimated. Such GRF is used to control a sound synthesis engine based on physical models. Two experiments were conducted. In the first experiment, the ability of subjects to recognize the surface they were exposed to was assessed. In the second experiment, the sound synthesis engine was enhanced with environmental sounds. Results show that, in some conditions, adding a soundscape significantly improves the recognition of the simulated environment.     

Performance of One-Round Walks in Linear Congestion Games

We investigate the approximation ratio of the solutions achieved after a one-round walk in linear congestion games. We consider the social functions Sum, defined as the sum of the players’ costs, and Max, defined as the maximum cost per player, as a measure of the quality of a given solution. For the social function Sum and one-round walks starting from the empty strategy profile, we close the gap between the upper bound of \(2+\sqrt{5}\approx 4.24\) given in Christodoulou et al. (Proceedings of the 23rd International Symposium on Theoretical Aspects of Computer Science (STACS), LNCS, vol. 3884, pp. 349–360, Springer, Berlin, 2006) and the lower bound of 4 derived in Caragiannis et al. (Proceedings of the 33rd International Colloquium on Automata, Languages and Programming (ICALP), LNCS, vol. 4051, pp. 311–322, Springer, Berlin, 2006) by providing a matching lower bound whose construction and analysis require non-trivial arguments. For the social function Max, for which, to the best of our knowledge, no results were known prior to this work, we show an approximation ratio of \(\Theta(\sqrt[4]{n^{3}})\) (resp. \(\Theta(n\sqrt{n})\)), where n is the number of players, for one-round walks starting from the empty (resp. an arbitrary) strategy profile.