On combining Big Data and machine learning to support eco-driving behaviours

A conscious use of the battery is one of the key elements to consider while driving an electric vehicle. Hence, supporting the drivers, with information about it, can be strategic in letting them drive in a better way, with the purpose of optimizing the energy consumption. In the context of electric vehicles, equipped with regenerative brakes, the driver\u2019s braking style can make a significant difference. In this paper, we propose an approach which is based on the combination of big data and machine learning techniques, with the aim of enhancing the driver\u2019s braking style through visual elements (displayed in the vehicle dashboard, as a Human\u2013Machine Interface), actuating eco-driving behaviours. We have designed and developed a system prototype, by exploiting big data coming from an electric vehicle and a machine learning algorithm. Then, we have conducted a set of tests, with simulated and real data, and here we discuss the results we have obtained that can open interesting discussions about the use of big data, together with machine learning, so as to improve drivers\u2019 awareness of eco-behaviours

Convolutional LSTM Networks for Subcellular Localization of Proteins

Machine learning is widely used to analyze biological sequence data. Non-sequential models such as SVMs or feed-forward neural networks are often used although they have no natural way of handling sequences of varying length. Recurrent neural networks such as the long short term memory (LSTM) model on the other hand are designed to handle sequences. In this study we demonstrate that LSTM networks predict the subcellular location of proteins given only the protein sequence with high accuracy (0.902) outperforming current state of the art algorithms. We further improve the performance by introducing convolutional filters and experiment with an attention mechanism which lets the LSTM focus on specific parts of the protein. Lastly we introduce new visualizations of both the convolutional filters and the attention mechanisms and show how they can be used to extract biological relevant knowledge from the LSTM networks

Search for dark Higgsstrahlung in e+ e- -> mu+ mu- and missing energy events with the KLOE experiment

We searched for evidence of a Higgsstrahlung process in a secluded sector, leading to a final state with a dark photon U and a dark Higgs boson h', with the KLOE detector at DAFNE. We investigated the case of h' lighter than U, with U decaying into a muon pair and h' producing a missing energy signature. We found no evidence of the process and set upper limits to its parameters in the range 2m_mu<m_U<1000 MeV, m_h'<m_U.Comment: 16 pages, 7 figures, submitted to Physics Letters

Towards quantum 3d imaging devices

We review the advancement of the research toward the design and implementation of quantum plenoptic cameras, radically novel 3D imaging devices that exploit both momentum–position entanglement and photon–number correlations to provide the typical refocusing and ultra-fast, scanning-free, 3D imaging capability of plenoptic devices, along with dramatically enhanced performances, unattainable in standard plenoptic cameras: diffraction-limited resolution, large depth of focus, and ultra-low noise. To further increase the volumetric resolution beyond the Rayleigh diffraction limit, and achieve the quantum limit, we are also developing dedicated protocols based on quantum Fisher information. However, for the quantum advantages of the proposed devices to be effective and appealing to end-users, two main challenges need to be tackled. First, due to the large number of frames required for correlation measurements to provide an acceptable signal-to-noise ratio, quantum plenoptic imaging (QPI) would require, if implemented with commercially available high-resolution cameras, acquisition times ranging from tens of seconds to a few minutes. Second, the elaboration of this large amount of data, in order to retrieve 3D images or refocusing 2D images, requires high-performance and time-consuming computation. To address these challenges, we are developing high-resolution single-photon avalanche photodiode (SPAD) arrays and high-performance low-level programming of ultra-fast electronics, combined with compressive sensing and quantum tomography algorithms, with the aim to reduce both the acquisition and the elaboration time by two orders of magnitude. Routes toward exploitation of the QPI devices will also be discussed

Reply to: New Meta- and Mega-analyses of Magnetic Resonance Imaging Findings in Schizophrenia: Do They Really Increase Our Knowledge About the Nature of the Disease Process?

This work was supported by National Institute of Biomedical Imaging and Bioengineering Grant No. U54EB020403 (to the ENIGMA consortium)

Study of Dalitz decay phi -> eta e+e- with KLOE detector

We have studied the vector to pseudoscalar conversion decay phi -> eta e+e-, with eta -> pi0pi0pi0, with the KLOE detector at DAPHNE. The data set of 1.7 fb-1 of e+e- collisions at sqrt(s)~Mphi contains a clear conversion decay signal of ~31,000 events from which we measured a value of BR(phi -> eta e+e-)=(1.075+-0.007+-0.038)x10-4. The same sample is used to determine the transition form factor by a fit to the e+e- invariant mass spectrum, obtaining b(phi eta) =(1.17 +- 0.10 + 0.07) GeV-2, that improves by a factor of five the precision of the previous measurement and is in good agreement with VMD expectations.Comment: 13 pages, 6 figures, submitted to PL

Valorization of By-Products from Biofuel Biorefineries: Extraction and Purification of Bioactive Molecules from Post-Fermentation Corn Oil

The aim of this work was to develop innovative and sustainable extraction, concentration, and purification technologies aimed to recover target substances from corn oil, obtained as side stream product of biomass refineries. Residues of bioactive compounds such as carotenoids, phytosterols, tocopherols, and polyphenols could be extracted from this matrix and applied as ingredients for food and feeds, nutraceuticals, pharmaceuticals, and cosmetic products. These molecules are well known for their antioxidant and antiradical capacity, besides other specific biological activities, generically involved in the prevention of chronic and degenerative diseases. The project involved the development of methods for the selective extraction of these minor components, using as suitable extraction technique solid phase extraction. All the extracted and purified fractions were evaluated by NMR spectroscopic analyses and UV–Vis spectrophotometric techniques and characterized by quali-quantitative HPLC analyses. TPC (total phenolic content) and TFC (total flavonoid content) were also determined. DPPH and ABTS radical were used to evaluate radical quenching abilities. Acetylcholinesterase (AChE), amylase, glucosidase, and tyrosinase were selected as enzymes in the enzyme inhibitory assays. The obtained results showed the presence of a complex group of interesting molecules with strong potential in market applications according to circular economy principles

Caenorhabditis elegans SMA-10/LRIG Is a Conserved Transmembrane Protein that Enhances Bone Morphogenetic Protein Signaling

Bone morphogenetic protein (BMP) pathways control an array of developmental and homeostatic events, and must themselves be exquisitely controlled. Here, we identify Caenorhabditis elegans SMA-10 as a positive extracellular regulator of BMP–like receptor signaling. SMA-10 acts genetically in a BMP–like (Sma/Mab) pathway between the ligand DBL-1 and its receptors SMA-6 and DAF-4. We cloned sma-10 and show that it has fifteen leucine-rich repeats and three immunoglobulin-like domains, hallmarks of an LRIG subfamily of transmembrane proteins. SMA-10 is required in the hypodermis, where the core Sma/Mab signaling components function. We demonstrate functional conservation of LRIGs by rescuing sma-10(lf) animals with the Drosophila ortholog lambik, showing that SMA-10 physically binds the DBL-1 receptors SMA-6 and DAF-4 and enhances signaling in vitro. This interaction is evolutionarily conserved, evidenced by LRIG1 binding to vertebrate receptors. We propose a new role for LRIG family members: the positive regulation of BMP signaling by binding both Type I and Type II receptors