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The DsTau(NA65) experiment at CERN was proposed to measure an inclusive differential cross-section of D s production with decay to tau lepton and tau neutrino in p – A interactions. The DsTau detector is based on the nuclear emulsion technique, which provides excellent spatial resolution for detecting short-lived particles like charmed hadrons. This paper presents the first results of the analysis of the pilot-run (2018 run) data and reports the accuracy of the proton interaction vertex reconstruction. High precision in vertex reconstruction enables detailed measurement of proton interactions, even in environments with high track density. The measured data has been compared with several Monte Carlo event generators in terms of multiplicity and angular distribution of charged particles. The multiplicity distribution obtained in p–W interactions is tested for KNO-G scaling and is found to be nearly consistent. The interaction length of protons in tungsten is measured to be 93.7 ± 2.6 mm . The results presented in this study can be used to validate event generators of p – A interactions.

Time series prediction is a remarkable research interest that is widely followed by scientists and researchers. Because many fields include processes of such time series analyses, different kinds of approaches, methods, and techniques are employed often in order to achieve alternative ways of prediction. It appears that artificial-intelligence-based solutions have strong potential for providing effective and accurate prediction approaches in even most complicated time series structures. For further details and explanation, this study aims to introduce an alternative artificial-intelligence-based approach to artificial neural networks and cognitive development optimization algorithm, as a recent intelligent optimization technique introduced by the authors. This study aims to predict different kinds of time series by using the introduced system/approach. In this way, it is possible to discuss application potential of the hybrid system and report findings related to its success of prediction. The authors believe that the study provides a good chance to support the literature with an alternative solution approach and see the potential of a newly developed, artificial-intelligence-based optimization algorithm for different applications.

The Deep Underground Neutrino Experiment (DUNE) is the next very large scale neutrino science and proton decay experiment. DUNE will consist of large-scale near and far detectors. The core elements of these detector systems are liquid argon Time Projection Chambers (LAr TPCs) and light readout systems. Two prototype far detectors were built and operated at CERN Neutrino Platform and extensive developments are underway for improved and upgraded detectors. In order to evaluate various design alternatives and validate new concepts of light readout related to large-scale LAr detectors, we have performed several experiments with a fifty liter liquid argon TPC at CERN. Among the long list of configurations we probed, study of various wavelength shifters, operation in dual phase mode and Xe and N 2 doping under different scenarios can be listed. Here we report on the details of the various test campaigns and discuss our findings and their impact on the design and operational parameters.

The NESSiE Collaboration has been setup to undertake a conclusive experiment to clarify the muon-neutrino disappearance measurements at short baselines in order to put severe constraints to models with more than the three-standard neutrinos. To this aim the current FNAL-Booster neutrino beam for a Short-Baseline experiment was carefully evaluated by considering the use of magnetic spectrometers at two sites, near and far ones. The detector locations were studied, together with the achievable performances of two OPERA-like spectrometers. The study was constrained by the availability of existing hardware and a time-schedule compatible with the undergoing project of multi-site Liquid–Argon detectors at FNAL. The settled physics case and the kind of proposed experiment on the Booster neutrino beam would definitively clarify the existing tension between the ν μ disappearance and the ν e appearance/disappearance at the eV mass scale. In the context of neutrino oscillations the measurement of ν μ disappearance is a robust and fast approach to either reject or discover new neutrino states at the eV mass scale. We discuss an experimental program able to extend by more than one order of magnitude (for neutrino disappearance) and by almost one order of magnitude (for antineutrino disappearance) the present range of sensitivity for the mixing angle between standard and sterile neutrinos. These extensions are larger than those achieved in any other proposal presented so far.

Diagnosis of vascular disease and selection and planning of therapy are to a large extent based on the geometry of the diseased vessel. Treatment of a particular vascular disease is usually considered if the geometrical parameter that characterizes the severity of the disease, e.g. % vessel narrowing, exceeds a threshold. The thresholds that are used in clinical practice are based on epidemiological knowledge, which has been obtained by clinical studies including large numbers of patients. They may apply “on average”, but they can be sub-optimal for individual patients. To realize more patient-specific treatment decision criteria, more detailed knowledge may be required about the vascular hemodynamics, i.e. the blood flow and pressure in the diseased vessel and the biomechanical reaction of the vessel wall to this flow and pressure. Over the last decade, a substantial number of publications have appeared on hemodynamic modeling. Some studies have provided first evidence that this modeling may indeed be used to support therapeutic decisions. The goal of the research reported in this paper is to go one step further, namely to investigate the feasibility of a patient-specific hemodynamic modeling methodology that is not only effective (improves therapeutic decisions), but that is also efficient (easy to use, fast, as much as possible automatic) and robust (insensitive to variation in the quality of the input data, same outcome for different users). A review is presented of our research performed during the last 5 years and the results that were achieved. This research focused on the risk assessment for one particular disease, namely abdominal aortic aneurysm, a life-threatening dilatation of the abdominal aorta.

The smart cities necessitate the advanced operational information and communication technology to share and improve efficiency with the nation. The datasets of high traffic roads were examined for 4 different European Countries namely Germany, Greece, Turkey, and Romania for this study. Moreover, the study involves the identifying the busy traffic time on the roads and identifies the solution of following the other routes enabling the commuter to reach the destination on time. This is carried out with deep learning techniques in GIS environment using ArcGIS to identify the different route-finding scenario. The Dijkstra’s algorithm is best suited for this routing model. This study revolves around multimodal transport planning within smart cities for smart traffic flow for smart living. A case study of Greece street roads was considered; the linear regression model was implemented for the datasets. The obtained p > |t| for average speed is Stratigou Makrigianni (0.906), Agias Annis (0.754), Mystra (0.675), and Komvos Ag.loanni Renti (0.470). The study reflects the traffic congestion on four European Countries with best roads and national highways in the world. However, the traffic in these countries seems to be heavy during the peak hours or unusual hours. With GIS, one can trace the traffic routes and also take proper decision to avoid the traffic, and move toward the destination with different paths. This approach will help the closeby places to be free from the pollution.

Aneurysms of the abdominal aorta enlarge until rupture occurs. We assume that this is the result of remodelling to restore wall stress. We developed a numerical model to predict aneurysm expansion based on this assumption. In addition, we obtained aneurysm geometry of 11 patients from computed tomography angiographic images to obtain patient specific calculations. The assumption of a wall stress related expansion indeed resulted in a series of local expansions, adjusting global geometry in an exponential fashion similar as in patients. Furthermore, it revealed that location of peak wall stress changed over time. The assumptions of this model are discussed in detail in this manuscript, and the implications are related to literature findings.

A bstract The OPERA experiment has discovered the tau neutrino appearance in the CNGS muon neutrino beam, in agreement with the 3 neutrino flavour oscillation hypothesis. The OPERA neutrino interaction target, made of Emulsion Cloud Chambers, was particularly efficient in the reconstruction of electromagnetic showers. Moreover, thanks to the very high granularity of the emulsion films, showers induced by electrons can be distinguished from those induced by π 0 s, thus allowing the detection of charged current interactions of electron neutrinos. In this paper the results of the search for electron neutrino events using the full dataset are reported. An improved method for the electron neutrino energy estimation is exploited. Data are compatible with the 3 neutrino flavour mixing model expectations and are used to set limits on the oscillation parameters of the 3+1 neutrino mixing model, in which an additional mass eigenstate m 4 is introduced. At high Δ m 41 2 (≳0.1 eV 2 ), an upper limit on sin 2 2 θ μe is set to 0.021 at 90% C.L. and Δ m 41 2  ≳ 4 × 10 − 3 eV 2 is excluded for maximal mixing in appearance mode.

A bstract A first result of the search for ν μ → ν e oscillations in the OPERA experiment, located at the Gran Sasso Underground Laboratory, is presented. The experiment looked for the appearance of ν e in the CNGS neutrino beam using the data collected in 2008 and 2009. Data are compatible with the non-oscillation hypothesis in the three-flavour mixing model. A further analysis of the same data constrains the non-standard oscillation parameters θ new and suggested by the LSND and MiniBooNE experiments. For large values ( > 0.1 eV 2 ), the OPERA 90% C.L. upper limit on sin 2 (2 θ new ) based on a Bayesian statistical method reaches the value 7 . 2 × 10 −3 .

A bstract The OPERA neutrino experiment is designed to perform the first observation of neutrino oscillations in direct appearance mode in the ν μ → ν τ channel, via the detection of the τ -leptons created in charged current ν τ interactions. The detector, located in the underground Gran Sasso Laboratory, consists of an emulsion/lead target with an average mass of about 1.2 kt, complemented by electronic detectors. It is exposed to the CERN Neutrinos to Gran Sasso beam, with a baseline of 730 km and a mean energy of 17 GeV. The observation of the first ν τ candidate event and the analysis of the 2008-2009 neutrino sample have been reported in previous publications. This work describes substantial improvements in the analysis and in the evaluation of the detection efficiencies and backgrounds using new simulation tools. The analysis is extended to a sub-sample of 2010 and 2011 data, resulting from an electronic detector-based pre-selection, in which an additional ν τ candidate has been observed. The significance of the two events in terms of a ν μ → ν τ oscillation signal is of 2.40 σ .