Status of the Cylindical-GEM project for the KLOE-2 Inner Tracker

The status of the R&D on the Cylindrical-GEM (CGEM) detector foreseen as Inner Tracker for KLOE-2, the upgrade of the KLOE experiment at the DAFNE phi-factory, will be presented. The R&D includes several activities: i) the construction and complete characterization of the full-size CGEM prototype, equipped with 650 microns pitch 1-D longitudinal strips; ii) the study of the 2-D readout with XV patterned strips and operation in magnetic field (up to 1.5T), performed with small planar prototypes in a dedicated test at the H4-SPS beam facility; iii) the characterization of the single-mask GEM technology for the realization of large-area GEM foils.Comment: 4 pages, 10 figures, Presented at Vienna Conference on Instrumentation (Feb 15-20, 2010, Vienna, Austria). Submitted to the Proceeding

A primer on machine learning techniques for genomic applications

High throughput sequencing technologies have enabled the study of complex biological aspects at single nucleotide resolution, opening the big data era. The analysis of large volumes of heterogeneous “omic” data, however, requires novel and efficient computational algorithms based on the paradigm of Artificial Intelligence. In the present review, we introduce and describe the most common machine learning methodologies, and lately deep learning, applied to a variety of genomics tasks, trying to emphasize capabilities, strengths and limitations through a simple and intuitive language. We highlight the power of the machine learning approach in handling big data by means of a real life example, and underline how described methods could be relevant in all cases in which large amounts of multimodal genomic data are available

Random forests highlight the combined effect of environmental heavy metals exposure and genetic damages for cardiovascular diseases

Heavy metals are a dangerous source of pollution due to their toxicity, permanence in the environment and chemical nature. It is well known that long-term exposure to heavy metals is related to several chronic degenerative diseases (cardiovascular diseases, neoplasms, neurodegenerative syndromes, etc.). In this work, we propose a machine learning framework to evaluate the severity of cardiovascular diseases (CVD) from Human scalp hair analysis (HSHA) tests and genetic analysis and identify a small group of these clinical features mostly associated with the CVD risk. Using a private dataset provided by the DD Clinic foundation in Caserta, Italy, we cross-validated the classification performance of a Random Forests model with 90 subjects affected by CVD. The proposed model reached an AUC of 0.78 ± 0.01 on a three class classification problem. The robustness of the predictions was assessed by comparison with different cross-validation schemes and two state-ofthe-art classifiers, such as Artificial Neural Network and General Linear Model. Thus, is the first work that studies, through a machine learning approach, the tight link between CVD severity, heavy metal concentrations and SNPs. Then, the selected features appear highly correlated with the CVD phenotype, and they could represent targets for future CVD therapies

u-PAR expression in cancer associated fibroblast: new acquisitions in multiple myeloma progression

BACKGROUND: Multiple Myeloma (MM) is a B-cell malignancy in which clonal plasma cells progressively expand within the bone marrow (BM) as effect of complex interactions with extracellular matrix and a number of microenvironmental cells. Among these, cancer-associated fibroblasts (CAF) mediate crucial reciprocal signals with MM cells and are associated to aggressive disease and poor prognosis. A large body of evidence emphasizes the role of the urokinase plasminogen activator (u-PA) and its receptor u-PAR in potentiating the invasion capacity of tumor plasma cells, but little is known about their role in the biology of MM CAF. In this study, we investigated the u-PA/u-PAR axis in MM-associated fibroblasts and explore additional mechanisms of tumor/stroma interplay in MM progression. METHODS: CAF were purified from total BM stromal fraction of 64 patients including monoclonal gammopathy of undetermined significance, asymptomatic and symptomatic MM, as well as MM in post-treatment remission. Flow cytometry, Real Time PCR and immunofluorescence were performed to investigate the u-PA/u-PAR system in relation to the level of activation of CAF at different stages of the disease. Moreover, proliferation and invasion assays coupled with silencing experiments were used to prove, at functional level, the function of u-PAR in CAF. RESULTS: We found higher activation level, along with increased expression of pro-invasive molecules, including u-PA, u-PAR and metalloproteinases, in CAF from patients with symptomatic MM compared to the others stages of the disease. Consistently, CAF from active MM as well as U266 cell line under the influence of medium conditioned by active MM CAF, display higher proliferative rate and invasion potential, which were significantly restrained by u-PAR gene expression inhibition. CONCLUSIONS: Our data suggest that the stimulation of u-PA/u-PAR system contributes to the activated phenotype and function of CAF during MM progression, providing a biological rationale for future targeted therapies against MM

Development of CGEM technology for ultra-light tracking detectors : the KLOE-2 Inner Tracker

KLOE-2 at the $\phi$ -factory DA\Phi NE of INFN Laboratori Nazionali di Frascati (LNF), is the first experiment using the GEM technology with a cylindrical geometry (CGEM), developed at the LNF by the Inner Tracker group and within the RD51 Collaboration. Four layers with 26$\div$ 41 cm diameters and L = 70 cm, each realized as a Triple-GEM detector, compose this new detector. To produce GEM foils of unprecedented size, the novel single-mask manufacturing procedure has been developed with the TE-MPE-EM CERN group, together with the realization of a novel XV readout pattern. The adopted solutions allowed the total material budget to be kept below 2% of the radiation length $X_{0}$. The final assembly of the Inner Tracker has been completed on March 14, 2014. The production procedure will be reported together with the validation test results

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Performance and Operation of the CMS Electromagnetic Calorimeter

The operation and general performance of the CMS electromagnetic calorimeter using cosmic-ray muons are described. These muons were recorded after the closure of the CMS detector in late 2008. The calorimeter is made of lead tungstate crystals and the overall status of the 75848 channels corresponding to the barrel and endcap detectors is reported. The stability of crucial operational parameters, such as high voltage, temperature and electronic noise, is summarised and the performance of the light monitoring system is presented

A geo-chemo-mechanical study of a highly polluted marine system (Taranto, Italy) for the enhancement of the conceptual site model

The paper presents the results of the analysis of the geo-chemo-mechanical data gathered through an innovative multidisciplinary investigation campaign in the Mar Piccolo basin, a heavily polluted marine bay aside the town of Taranto (Southern Italy). The basin is part of an area declared at high environmental risk by the Italian government. The cutting-edge approach to the environmental characterization of the site was promoted by the Special Commissioner for urgent measures of reclamation, environmental improvements and redevelopment of Taranto and involved experts from several research fields, who cooperated to gather a new insight into the origin, distribution, mobility and fate of the contaminants within the basin. The investigation campaign was designed to implement advanced research methodologies and testing strategies. Differently from traditional investigation campaigns, aimed solely at the assessment of the contamination state within sediments lying in the top layers, the new campaign provided an interpretation of the geo-chemo-mechanical properties and state of the sediments forming the deposit at the seafloor. The integrated, multidisciplinary and holistic approach, that considered geotechnical engineering, electrical and electronical engineering, geological, sedimentological, mineralogical, hydraulic engineering, hydrological, chemical, geochemical, biological fields, supported a comprehensive understanding of the influence of the contamination on the hydro-mechanical properties of the sediments, which need to be accounted for in the selection and design of the risk mitigation measures. The findings of the research represent the input ingredients of the conceptual model of the site, premise to model the evolutionary contamination scenarios within the basin, of guidance for the environmental risk management. The study testifies the importance of the cooperative approach among researchers of different fields to fulfil the interpretation of complex polluted eco-systems

Impact of magnetic field on the stability of the CMS GE1/1 GEM detector operation

The Gas Electron Multiplier (GEM) detectors of the GE1/1 station of the CMS experiment have been operated in the CMS magnetic field for the first time on the 7$^{th}$ of October 2021. During the magnetic field ramps, several discharge phenomena were observed, leading to instability in the GEM High Voltage (HV) power system. In order to reproduce the behavior, it was decided to conduct a dedicated test at the CERN North Area with the Goliath magnet, using four GE1/1 spare chambers. The test consisted in studying the characteristics of discharge events that occurred in different detector configurations and external conditions. Multiple magnetic field ramps were performed in sequence: patterns in the evolution of the discharge rates were observed with these data. The goal of this test is the understanding of the experimental conditions inducing discharges and short circuits in a GEM foil. The results of this test lead to the development of procedure for the optimal operation and performance of GEM detectors in the CMS experiment during the magnet ramps. Another important result is the estimation of the probability of short circuit generation, at 68 % confidence level, p$_{short}$$^{HV}$ $^{OFF}$ = 0.42$^{-0.35+0.94}$% with detector HV OFF and p$_{short}$$^{HV}$ $^{OFF}$ < 0.49% with the HV ON. These numbers are specific for the detectors used during this test, but they provide a first quantitative indication on the phenomenon, and a point of comparison for future studies adopting the same procedure