The criteria to qualify a geographical term as generic: Are we moving from a European to a US perspective?

This article discusses the transformation of a distinctive trade sign into a generic term. Any distinctive trade sign carries this risk, primarily if it benefits from a high level of reputation or prestige, and the product identified is unique in the market. This is probably the most critical danger for such signs, especially if they are industrial property rights. Several criteria have been developed to determine if a sign has been transformed into a generic term. These criteria have economic and political relevance, as genericness is not a trivial issue. The European Court of Justice (ECJ) has taken a position in this matter, as have the European Union Regulations on trademarks and geographical indications. However, the bilateral and multilateral agreements are the critical arena for conflicts concerning geographical terms’ qualification as common terms. The European Union (EU) and the United States (US) have been in the spotlight for a long time, while China is also reaching a prominent place in this dispute. The most recent bilateral agreements have been twisting the criteria applied when assessing a geographical term’s genericness

Preliminary comparison of magmatic manifestations, calc-alkaline affinity and stephanian-permian age, in the Iberian Chain

[Resumen] En este trabajo se estudian, de forma sintética y actualizada, las manifestaciones (hipovolcánicas y volcanoclásticas) calco-alcalinas que, con carácter epizonal, pluriepisódico y edad Stephaniense-Pérmico, afloran en la Cadena Ibérica. El estudio del magmatismo en la cuenca de Sauquillo de Alcázar (Soria) permite identificar la geometría y la modalidad de este magmatismo con mayor precisi6n, respecto a lo obtenido en los cuatro afloramientos volcano-clásticos seleccionados. Los resultados obtenidos facilitan realizar consideraciones sobre el estudio espacio-temporal de este magmatismo..[Abstract] A synthetic and actualized study of several magmatic calc-alkaline manifestations of Stephanian-Permian age, of the Iberian Chain, is proposed in this papero The Sauquillo de Alcázar (Soria) outcrop allows a more complete study (with drilling logs and a surface profile) giving improved spacetime information on the geometry and evolution of this magmatism. Four pyroclastic outcrops are integrated in this compariso

Simulations and analysis tools for charge-exchange (d,2He)(d,{}^{2}\text{He}) reactions in inverse kinematics with the AT-TPC

Charge-exchange $(d,{}^{2}\text{He})$ reactions in inverse kinematics at intermediate energies are a very promising method to investigate the Gamow-Teller transition strength in unstable nuclei. A simulation and analysis software based on the $\rm{\scriptsize ATTPCROOT}$ package was developed to study these type of reactions with the active-target time projection chamber (AT-TPC). The simulation routines provide a realistic detector response that can be used to understand and benchmark experimental data. Analysis tools and correction routines can be developed and tested from simulations in $\rm{\scriptsize ATTPCROOT}$, because they are processed in the same way as the real data. In particular, we study the feasibility of using coincidences with beam-like particles to unambiguously identify the $(d,{}^{2}\text{He})$ reaction channel, and to develop a kinematic fitting routine for future applications. More technically, the impact of space-charge effects in the track reconstruction, and a possible correction method are investigated in detail. This analysis and simulation package constitutes an essential part of the software development for the fast-beams program with the AT-TPC

Design and performance of a 35-ton liquid argon time projection chamber as a prototype for future very large detectors

Liquid argon time projection chamber technology is an attractive choice for large neutrino detectors, as it provides a high-resolution active target and it is expected to be scalable to very large masses. Consequently, it has been chosen as the technology for the first module of the DUNE far detector. However, the fiducial mass required for far detectors of the next generation of neutrino oscillation experiments far exceeds what has been demonstrated so far. Scaling to this larger mass, as well as the requirement for underground construction places a number of additional constraints on the design. A prototype 35-ton cryostat was built at Fermi National Acccelerator Laboratory to test the functionality of the components foreseen to be used in a very large far detector. The Phase I run, completed in early 2014, demonstrated that liquid argon could be maintained at sufficient purity in a membrane cryostat. A time projection chamber was installed for the Phase II run, which collected data in February and March of 2016. The Phase II run was a test of the modular anode plane assemblies with wrapped wires, cold readout electronics, and integrated photon detection systems. While the details of the design do not match exactly those chosen for the DUNE far detector, the 35-ton TPC prototype is a demonstration of the functionality of the basic components. Measurements are performed using the Phase II data to extract signal and noise characteristics and to align the detector components. A measurement of the electron lifetime is presented, and a novel technique for measuring a track\u27s position based on pulse properties is described

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.Comment: Preprint to be submitted to The European Physical Journal

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level