The Influence of Silicon Nanoclusters on the Optical Properties of a-SiNx Samples: A Theoretical Study

By means of ab-initio calculations we investigate the optical properties of pure a-SiN$_x$ samples, with $x \in [0.4, 1.8]$, and samples embedding silicon nanoclusters (NCs) of diameter $0.5 \leq d \leq 1.0$ nm. In the pure samples the optical absorption gap and the radiative recombination rate vary according to the concentration of Si-N bonds. In the presence of NCs the radiative rate of the samples is barely affected, indicating that the intense photoluminescence of experimental samples is mostly due to the matrix itself rather than to the NCs. Besides, we evidence an important role of Si-N-Si bonds at the NC/matrix interface in the observed photoluminescence trend

Mitochondria and neuroprotection in stroke: Cationic arginine-rich peptides (CARPs) as a novel class of mitochondria-targeted neuroprotective therapeutics

Stroke is the second leading cause of death globally and represents a major cause of devastating long-term disability. Despite sustained efforts to develop clinically effective neuroprotective therapies, presently there is no clinically available neuroprotective agent for stroke. As a central mediator of neurodamaging events in stroke, mitochondria are recognised as a critical neuroprotective target, and as such, provide a focus for developing mitochondrial-targeted therapeutics. In recent years, cationic arginine-rich peptides (CARPs) have been identified as a novel class of neuroprotective agent with several demonstrated mechanisms of action, including their ability to target mitochondria and exert positive effects on the organelle. This review provides an overview on neuronal mitochondrial dysfunction in ischaemic stroke pathophysiology and highlights the potential beneficial effects of CARPs on mitochondria in the ischaemic brain following stroke

Proteomic analysis of cortical neuronal cultures treated with poly-arginine peptide-18 (R18) and exposed to glutamic acid excitotoxicity

Poly-arginine peptide-18 (R18) has recently emerged as a highly effective neuroprotective agent in experimental stroke models, and is particularly efficacious in protecting cortical neurons against glutamic acid excitotoxicity. While we have previously demonstrated that R18 can reduce excitotoxicity-induced neuronal calcium influx, other molecular events associated with R18 neuroprotection are yet to investigated. Therefore, in this study we were particularly interested in protein expression changes in R18 treated neurons subjected to excitotoxicity. Proteomic analysis was used to compare protein expression patterns in primary cortical neuronal cultures subjected to: (i) R18-treatment alone (R18); (ii) glutamic acid excitotoxic injury (Glut); (iii) R18-treatment and glutamic acid injury (R18 + Glut); (iv) no treatment (Cont). Whole cell lysates were harvested 24 h post-injury and subjected to quantitative proteomic analysis (iTRAQ), coupled with liquid chromatography-tandem mass spectrometry (LC-MS/ MS) and subsequent bioinformatic analysis of differentially expressed proteins (DEPs). Relative to control cultures, R18, Glut, and R18 + Glut treatment resulted in the detection of 5, 95 and 14 DEPs respectively. Compared to Glut alone, R18 + Glut revealed 98 DEPs, including 73 proteins whose expression was also altered by treatment with Glut and/or R18 alone, as well as 25 other uniquely regulated proteins. R18 treatment reversed the up- or down-regulation of all 73 Glut-associated DEPs, which included proteins involved in mitochondrial integrity, ATP generation, mRNA processing and protein translation. Analysis of protein-protein interactions of the 73 DEPs showed they were primarily associated with mitochondrial respiration, proteasome activity and protein synthesis, transmembrane trafficking, axonal growth and neuronal differentiation, and carbohydrate metabolism. Identified protein pathways associated with proteostasis and energy metabolism, and with pathways involved in neurodegeneration. Collectively, the findings indicate that R18 neuroprotection following excitotoxicity is associated with preservation of neuronal protein profiles, and differential protein expression that assists in maintaining mitochondrial function and energy production, protein homeostasis, and membrane trafficking

Trends Prediction Using Social Diffusion Models

The importance of the ability of predict trends in social media has been growing rapidly in the past few years with the growing dominance of social media in our everyday's life. Whereas many works focus on the detection of anomalies in networks, there exist little theoretical work on the prediction of the likelihood of anomalous network pattern to globally spread and become "trends". In this work we present an analytic model the social diffusion dynamics of spreading network patterns. Our proposed method is based on information diffusion models, and is capable of predicting future trends based on the analysis of past social interactions between the community's members. We present an analytic lower bound for the probability that emerging trends would successful spread through the network. We demonstrate our model using two comprehensive social datasets - the "Friends and Family" experiment that was held in MIT for over a year, where the complete activity of 140 users was analyzed, and a financial dataset containing the complete activities of over 1.5 million members of the "eToro" social trading community.Comment: 6 Pages + Appendi

The INGV tectonomagnetic network: 2004?2005 preliminary dataset analysis

International audienceIt is well established that earthquakes and volcanic eruption can produce small variations in the local geomagnetic field. The Italian Istituto Nazionale di Geofisica e Vulcanologia (INGV) tectonomagnetic network was installed in Central Italy since 1989 to investigate possible effects on the local geomagnetic field related to earthquakes occurrences. At the present time, total geomagnetic field intensity data are collected in four stations using proton precession magnetometers. We report the complete dataset for the period of years 2004?2005. The data of each station are differentiated respect to the data of the other stations in order to detect local field anomalies removing the contributions from the other sources, external and internal to the Earth. Unfortunately, no correlation between geomagnetic anomalies and the local seismic activity, recorded in Central Italy by the INGV Italian Seismic National Network, was found in this period. Some deceptive structures present in the differentiated data are pointed out

ZyON: Enabling Spike Sorting on APSoC-Based Signal Processors for High-Density Microelectrode Arrays

Multi-Electrode Arrays and High-Density Multi-Electrode Arrays of sensors are a key instrument in neuroscience research. Such devices are evolving to provide ever-increasing temporal and spatial resolution, paving the way to unprecedented results when it comes to understanding the behaviour of neuronal networks and interacting with them. However, in some experimental cases, in-place low-latency processing of the sensor data acquired by the arrays is required. This poses the need for high-performance embedded computing platforms capable of processing in real-time the stream of samples produced by the acquisition front-end to extract higher-level information. Previous work has demonstrated that Field-Programmable Gate Array and All-Programmable System-On-Chip devices are suitable target technology for the implementation of real-time processors of High-Density Multi-Electrode Arrays data. However, approaches available in literature can process a limited number of channels or are designed to execute only the first steps of the neural signal processing chain. In this work, we propose an All-Programmable System-On-Chip based implementation capable of sorting neural spikes acquired by the sensors, to associate the shape of each spike to a specific firing neuron. Our system, implemented on a Xilinx Z7020 All-Programmable System-On-Chip is capable of executing on-line spike sorting up to 5500 acquisition channels, 43x more than state-of-the-art alternatives, supporting 18KHz acquisition frequency. We present an experimental study on a commonly used reference dataset, using on-line refinement of the sorting clusters to improve accuracy up to 82%, with only 4% degradation with respect to off-line analysis

The INGV tectonomagnetic network: 2004-2005 preliminary dataset analysis

It is well established that earthquakes and volcanic eruption can produce small variations in the local geomagnetic field. The Italian Istituto Nazionale di Geofisica e Vulcanologia (INGV) tectonomagnetic network was installed in Central Italy since 1989 to investigate possible effects on the local geomagnetic field related to earthquakes occurrences. At the present time, total geomagnetic field intensity data are collected in four stations using proton precession magnetometers. We report the complete dataset for the period of years 2004-2005. The data of each station are differentiated respect to the data of the other stations in order to detect local field anomalies removing the contributions from the other sources, external and internal to the Earth. Unfortunately, no correlation between geomagnetic anomalies and the local seismic activity, recorded in Central Italy by the INGV Italian Seismic National Network, was found in this period. Some deceptive structures present in the differentiated data are pointed out

Tailoring confining jacket for concrete column using ultra high performance-fiber reinforced cementitious composites (UHP-FRCC) with high volume fly ash (HVFA)

Ultra-High Performance Fibre-Reinforced Cementitious Composites (UHP-FRCC) show excellent mechanical performances in terms of strength, ductility, and durability. Therefore, these cementitious materials have been successfully used for repairing, strengthening, and seismic retrofitting of old structures. However, UHP-FRCCs are not always environmental friendly products, especially in terms of the initial cost, due to the large quantity of cement that is contained in the mixture. Different rates of fly ash substitute herein part of the cement, and the new UHP-FRCCs are used to retrofit concrete columns to overcome this problem. To simulate the mechanical response of these columns, cylindrical specimens, which are made of normal concrete and reinforced with different UHP-FRCC jackets, are tested in uniaxial compression. Relationships between the size of the jacket, the percentage of cement replaced by fly ash, and the strength of the columns are measured and analyzed by means of the eco-mechanical approach. As a result, a replacement of approximately 50% of cement with fly ash, and a suitable thickness of the UHP-FRCC jacket, might ensure the lowest environmental impact without compromising the mechanical performances