Otal, A., Celada, F., Chimeno, J., Vijande, J., Pellejero, S., Perez-Calatayud, M. J., et al. (2022). Review on Treatment Planning Systems for Cervix Brachytherapy (Interventional Radiotherapy): Some Desirable and Convenient Practical Aspects to Be Implemented from Radiation Oncologist and Medical Physics Perspectives. Cancers, 14(14), 3467–15pp.
Abstract: Simple Summary There are no brachytherapy treatment planning systems (TPS) exclusively for the treatment of cervical tumours, so general-purpose TPSs are used. However, these treatments have some particular features concerning the treatment of other pathologies, especially in the case of exclusive use of MRI as an imaging modality and the presence of gynaecological applicators in combination with an interstitial part. That is why it is essential to review the latest versions of commercial TPSs to find the potential features to improve with the help of a group of experimented medical physicists and radiation oncologists. Furthermore, after reviewing the recent literature for advances applicable to cervical brachytherapy and through his own clinical experience, possible improvements are proposed to software providers for the development of new tools. Intracavitary brachytherapy (BT, Interventional Radiotherapy, IRT), plays an essential role in the curative intent of locally advanced cervical cancer, for which the conventional approach involves external beam radiotherapy with concurrent chemotherapy followed by BT. This work aims to review the different methodologies used by commercially available treatment planning systems (TPSs) in exclusive magnetic resonance imaging-based (MRI) cervix BT with interstitial component treatments. Practical aspects and improvements to be implemented into the TPSs are discussed. This review is based on the clinical expertise of a group of radiation oncologists and medical physicists and on interactive demos provided by the software manufacturers. The TPS versions considered include all the new tools currently in development for future commercial releases. The specialists from the supplier companies were asked to propose solutions to some of the challenges often encountered in a clinical environment through a questionnaire. The results include not only such answers but also comments by the authors that, in their opinion, could help solve the challenges covered in these questions. This study summarizes the possibilities offered nowadays by commercial TPSs, highlighting the absence of some useful tools that would notably improve the planning of MR-based interstitial component cervix brachytherapy.
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Barenboim, G. (2022). Some Aspects About Pushing the CPT and Lorentz Invariance Frontier With Neutrinos. Front. Physics, 10, 813753–7pp.
Abstract: The CPT symmetry, which combines Charge Conjugation, Parity, and Time Reversal, is a cornerstone of our model-building method, and its probable violation will endanger the most extended tool we presently utilize to explain physics, namely local relativistic quantum fields. However, the kaon system's conservation constraints appear to be rather severe. We will show in this paper that neutrino oscillation experiments can enhance this limit by many orders of magnitude, making them an excellent instrument for investigating the basis of our understanding of Nature. As a result, verifying CPT invariance does not evaluate a specific model, but rather the entire paradigm. Therefore, as the CPT's status in the neutrino sector, linked or not to Lorentz invariance violation, will be assessed at an unprecedented level by current and future long baseline experiments, distinguishing it from comparable experimental fingerprints coming from non-standard interactions is critical. Whether the entire paradigm or simply the conventional model of neutrinos is at jeopardy is significantly dependent on this.
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Calefice, L., Hennequin, A., Henry, L., Jashal, B. K., Mendoza, D., Oyanguren, A., et al. (2022). Effect of the high-level trigger for detecting long-lived particles at LHCb. Front. Big Data, 5, 1008737–13pp.
Abstract: Long-lived particles (LLPs) show up in many extensions of the Standard Model, but they are challenging to search for with current detectors, due to their very displaced vertices. This study evaluated the ability of the trigger algorithms used in the Large Hadron Collider beauty (LHCb) experiment to detect long-lived particles and attempted to adapt them to enhance the sensitivity of this experiment to undiscovered long-lived particles. A model with a Higgs portal to a dark sector is tested, and the sensitivity reach is discussed. In the LHCb tracking system, the farthest tracking station from the collision point is the scintillating fiber tracker, the SciFi detector. One of the challenges in the track reconstruction is to deal with the large amount of and combinatorics of hits in the LHCb detector. A dedicated algorithm has been developed to cope with the large data output. When fully implemented, this algorithm would greatly increase the available statistics for any long-lived particle search in the forward region and would additionally improve the sensitivity of analyses dealing with Standard Model particles of large lifetime, such as KS0 or Lambda (0) hadrons.
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de Azcarraga, J. A. (2022). The new Spanish educational legislation: why public education will not improve. Rev. Esp. Pedagog., 80(281), 111–129.
Abstract: This paper provides some reasons that explain, in the view of the author, why the present eagerness of the Spanish Educational Authorities to reform all levels of education, from primary school to the universities, will not improve the quality of the Spanish educational system.
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Garcia Navarro, J. E., Fernandez-Prieto, L. M., Villaseñor, A., Sanz, V., Ammirati, J. B., Diaz Suarez, E. A., et al. (2022). Performance of Deep Learning Pickers in Routine Network Processing Applications. Seismol. Res. Lett., 93, 2529–2542.
Abstract: Picking arrival times of P and S phases is a fundamental and time‐consuming task for the routine processing of seismic data acquired by permanent and temporary networks. A large number of automatic pickers have been developed, but to perform well they often require the tuning of multiple parameters to adapt them to each dataset. Despite the great advance in techniques, some problems remain, such as the difficulty to accurately pick S waves and earthquake recordings with a low signal‐to‐noise ratio. Recently, phase pickers based on deep learning (DL) have shown great potential for event identification and arrival‐time picking. However, the general adoption of these methods for the routine processing of monitoring networks has been held back by factors such as the availability of well‐documented software, computational resources, and a gap in knowledge of these methods. In this study, we evaluate recent available DL pickers for earthquake data, comparing the performance of several neural network architectures. We test the selected pickers using three datasets with different characteristics. We found that the analyzed DL pickers (generalized phase detection, PhaseNet, and EQTransformer) perform well in the three tested cases. They are very efficient at ignoring large‐amplitude transient noise and at picking S waves, a task that is often difficult even for experienced analysts. Nevertheless, the performance of the analyzed DL pickers varies widely in terms of sensitivity and false discovery rate, with some pickers missing a significant percentage of true picks and others producing a large number of false positives. There are also variations in run time between DL pickers, with some of them requiring significant resources to process large datasets. In spite of these drawbacks, we show that DL pickers can be used efficiently to process large seismic datasets and obtain results comparable or better than current standard procedures.
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HISPEC-DESPEC Collaboration(Polettini, M. et al), Algora, A., Morales, A. I., & Orrigo, S. E. A. (2022). Decay studies in the A similar to 225 Po-Fr region from the DESPEC campaign at GSI in 2021. Nuovo Cim. C, 45(5), 125–4pp.
Abstract: The HISPEC-DESPEC collaboration aims at investigating the struc-ture of exotic nuclei formed in fragmentation reactions with decay spectroscopymeasurements, as part of the FAIR Phase-0 campaign at GSI. This paper reportson first results of an experiment performed in spring 2021, with a focus on beta-decaystudies in the Po-Fr nuclei in the 220 < A <230 island of octupole deformationexploiting the DESPEC setup. Ion-beta correlations and fast-timing techniques arebeing employed, giving an insight into this difficult-to-reach region.
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Capra, S. et al, & Gadea, A. (2022). GALTRACE: A highly segmented silicon detector array for charged particle spectroscopy and discrimination. Nuovo Cim. C, 45(5), 98–4pp.
Abstract: GALTRACE is an array of segmented silicon detectors specifically built to work as an ancillary of the GALILEO gamma-ray spectrometer at Legnaro National Laboratory of INFN. GALTRACE consists of four telescopic Delta E-Edetectors which allow discriminating light charged particles also via pulse-shape analysis techniques. The good angular and energy resolutions, together with particle discrimination capabilities, make GALTRACE suitable for experiments where coincidences with specific emitted particles allow for the selection of reaction channels with very low cross section. The first in-beam experiment is reported here, aiming at identifying a narrow resonance, near-proton-threshold state in B-11, currently under discussion.
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Albiol, A., Albiol, F., Paredes, R., Plasencia-Martinez, J. M., Blanco Barrio, A., Garcia Santos, J. M., et al. (2022). A comparison of Covid-19 early detection between convolutional neural networks and radiologists. Insights Imaging, 13(1), 122–12pp.
Abstract: Background The role of chest radiography in COVID-19 disease has changed since the beginning of the pandemic from a diagnostic tool when microbiological resources were scarce to a different one focused on detecting and monitoring COVID-19 lung involvement. Using chest radiographs, early detection of the disease is still helpful in resource-poor environments. However, the sensitivity of a chest radiograph for diagnosing COVID-19 is modest, even for expert radiologists. In this paper, the performance of a deep learning algorithm on the first clinical encounter is evaluated and compared with a group of radiologists with different years of experience. Methods The algorithm uses an ensemble of four deep convolutional networks, Ensemble4Covid, trained to detect COVID-19 on frontal chest radiographs. The algorithm was tested using images from the first clinical encounter of positive and negative cases. Its performance was compared with five radiologists on a smaller test subset of patients. The algorithm's performance was also validated using the public dataset COVIDx. Results Compared to the consensus of five radiologists, the Ensemble4Covid model achieved an AUC of 0.85, whereas the radiologists achieved an AUC of 0.71. Compared with other state-of-the-art models, the performance of a single model of our ensemble achieved nonsignificant differences in the public dataset COVIDx. Conclusion The results show that the use of images from the first clinical encounter significantly drops the detection performance of COVID-19. The performance of our Ensemble4Covid under these challenging conditions is considerably higher compared to a consensus of five radiologists. Artificial intelligence can be used for the fast diagnosis of COVID-19.
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n_TOF Collaboration(Lederer-Woods, C. et al), Domingo-Pardo, C., Tain, J. L., & Tarifeño-Saldivia, A. (2022). Ge-74(n, gamma) cross section below 70 keV measured at n_TOF CERN. Eur. Phys. J. A, 58(12), 239–9pp.
Abstract: Neutron capture reaction cross sections on Ge-74 are of importance to determine Ge-74 production during the astrophysical slow neutron capture process. We present new resonance data on Ge-74(n, gamma ) reactions below 70 keV neutron energy. We calculate Maxwellian averaged cross sections, combining our data below 70 keV with evaluated cross sections at higher neutron energies. Our stellar cross sections are in agreement with a previous activation measurement performed at Forschungszentrum Karlsruhe by Marganiec et al., once their data has been re-normalised to account for an update in the reference cross section used in that experiment.
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R3B Collaboration(Heil, M. et al), & Nacher, E. (2022). A new Time-of-flight detector for the (RB)-B-3 setup. Eur. Phys. J. A, 58(12), 248–19pp.
Abstract: We present the design, prototype developments and test results of the new time-of-flight detector (ToFD) which is part of the R3B experimental setup at GSI and FAIR, Darmstadt, Germany. The ToFD detector is able to detect heavy-ion residues of all charges at relativistic energies with a relative energy precision sigma_Delta E/Delta E of up to 1% and a time precision of up to 14 ps (sigma). Together with an elaborate particle-tracking system, the full identification of relativistic ions from hydrogen up to uranium in mass and nuclear charge is possible.
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