Previous detections of individual astrophysical sources of neutrinos are limited to the Sun and the supernova 1987A, whereas the origins of the diffuse flux of high-energy cosmic neutrinos remain unidentified. On 22 September 2017, we detected a high-energy neutrino, IceCube-170922A, with an energy of ~290 tera-electron volts. Its arrival direction was consistent with the location of a known γ-ray blazar, TXS 0506+056, observed to be in a flaring state. An extensive multiwavelength campaign followed, ranging from radio frequencies to γ-rays. These observations characterize the variability and energetics of the blazar and include the detection of TXS 0506+056 in very-high-energy γ-rays. This observation of a neutrino in spatial coincidence with a γ-ray-emitting blazar during an active phase suggests that blazars may be a source of high-energy neutrinos.

FLASH radiotherapy delivers a high dose (≥10 Gy) at a high rate (≥40 Gy/s). In this way, particles are delivered in pulses as short as a few nanoseconds. At that rate, intertrack reactions between chemical species produced within the same pulse may affect the heterogeneous chemistry stage of water radiolysis. This stochastic process suits the capabilities of the Monte Carlo method, which can model intertrack effects to aid in radiobiology research, including the design and interpretation of experiments. In this work, the TOPAS-nBio Monte Carlo track-structure code was expanded to allow simulations of intertrack effects in the chemical stage of water radiolysis. Simulation of the behavior of radiolytic yields over a long period of time (up to 50 s) was verified by simulating radiolysis in a Fricke dosimeter irradiated by 60 Co γ rays. In addition, LET-dependent G values of protons delivered in single squared pulses of widths, 1 ns, 1 μs and 10 μs, were obtained and compared to simulations using no intertrack considerations. The Fricke simulation for the calculated G value of Fe 3+ ion at 50 s was within 0.4% of the accepted value from ICRU Report 34. For LET-dependent G values at the end of the chemical stage, intertrack effects were significant at LET values below 2 keV/μm. Above 2 keV/μm the reaction kinetics remained limited locally within each track and thus, effects of intertrack reactions remained low. Therefore, when track structure simulations are used to investigate the biological damage of FLASH irradiation, these intertrack reactions should be considered. The TOPAS-nBio framework with the expansion to intertrack chemistry simulation provides a useful tool to assist in this task.

Purpose The simulation of individual particle tracks and the chemical stage following water radiolysis in biological tissue is an effective means of improving our knowledge of the physico‐chemical contribution to the biological effect of ionizing radiation. However, the step‐by‐step simulation of the reaction kinetics of radiolytic species is the most time‐consuming task in Monte Carlo track‐structure simulations, with long simulation times that are an impediment to research. In this work, we present the implementation of the independent reaction times (IRT) method in Geant4‐DNA Monte Carlo toolkit to improve the computational efficiency of calculating G‐values, defined as the number of chemical species created or lost per 100 eV of deposited energy. Methods The computational efficiency of IRT, as implemented, is compared to that from available Geant4‐DNA step‐by‐step simulations for electrons, protons and alpha particles covering a wide range of linear energy transfer (LET). The accuracy of both methods is verified using published measured data from fast electron irradiations for •OH and eaq‐ for time‐dependent G‐values. For IRT, simulations in the presence of scavengers irradiated by cobalt‐60 γ‐ray and 2 MeV protons are compared with measured data for different scavenging capacities. In addition, a qualitative assessment comparing measured LET‐dependent G‐values with Geant4‐DNA calculations in pure liquid water is presented. Results The IRT improved the computational efficiency by three orders of magnitude relative to the step‐by‐step method while differences in G‐values by 3.9% at 1 μs were found. At 7 ps, •OH and eaq‐ yields calculated with IRT differed from recent published measured data by 5% ± 4% and 2% ± 4%, respectively. At 1 μs, differences were 9% ± 5% and 6% ± 7% for •OH and eaq‐, respectively. Uncertainties are one standard deviation. Finally, G‐values at different scavenging capacities and LET‐dependent G‐values reproduced the behavior of measurements for all radiation qualities. Conclusion The comprehensive validation of the Geant4‐DNA capabilities to accurately simulate the chemistry following water radiolysis is an ongoing work. The implementation presented in this work is a necessary step to facilitate performing such a task.

The Multi-Purpose Detector (MPD) is to be installed at the Nuclotron Ion Collider fAcility (NICA) of the Joint Institute for Nuclear Research (JINR). Its main goal is to study the phase diagram of the strongly interacting matter produced in heavy-ion collisions. These studies, while providing insight into the physics of heavy-ion collisions, are relevant for improving our understanding of the evolution of the early Universe and the formation of neutron stars. In order to extend the MPD trigger capabilities, we propose to include a beam-beam monitoring detector (BE-BE) to provide a level-0 trigger signal with an expected time resolution of 30 ps. This new detector will improve the determination of the reaction plane by the MPD experiment, a key measurement for flow studies that provides physics insight into the early stages of the reaction. In this work, we show the potential of such a detector to help determine the event plane resolution in simulated Au+Au collisions at NICA energies. We also show our results for the time resolution studies of two prototype cells carried out at the T10 CERN facility.

The High Altitude Water Cherenkov (HAWC) observatory and the High Energy Stereoscopic System (H.E.S.S.) are two leading instruments in the ground-based very-high-energy γ-ray domain. HAWC employs the water Cherenkov detection (WCD) technique, while H.E.S.S. is an array of Imaging Atmospheric Cherenkov Telescopes (IACTs). The two facilities therefore differ in multiple aspects, including their observation strategy, the size of their field of view, and their angular resolution, leading to different analysis approaches. Until now, it has been unclear if the results of observations by both types of instruments are consistent: several of the recently discovered HAWC sources have been followed up by IACTs, resulting in a confirmed detection only in a minority of cases. With this paper, we go further and try to resolve the tensions between previous results by performing a new analysis of the H.E.S.S. Galactic plane survey data, applying an analysis technique comparable between H.E.S.S. and HAWC. Events above 1 TeV are selected for both data sets, the point-spread function of H.E.S.S. is broadened to approach that of HAWC, and a similar background estimation method is used. This is the first detailed comparison of the Galactic plane observed by both instruments. H.E.S.S. can confirm the γ-ray emission of four HAWC sources among seven previously undetected by IACTs, while the three others have measured fluxes below the sensitivity of the H.E.S.S. data set. Remaining differences in the overall γ-ray flux can be explained by the systematic uncertainties. Therefore, we confirm a consistent view of the γ-ray sky between WCD and IACT techniques.

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Accuracy of glioma grading is fundamental for the diagnosis, treatment planning and prognosis of patients. The purpose of this work was to develop a low-cost and easy-to-implement classification model which distinguishes low-grade gliomas (LGGs) from high-grade gliomas (HGGs), through texture analysis applied to conventional brain MRI. Different combinations of MRI contrasts (T 1Gd and T 2) and one segmented glioma region (necrotic and non-enhancing tumor core, NCR/NET) were studied. Texture features obtained from the gray level size zone matrix (GLSZM) were calculated. An under-sampling method was proposed to divide the data into different training subsets and subsequently extract complementary information for the creation of distinct classification models. The sensitivity, specificity and accuracy of the models were calculated, and the best model explicitly reported. The best model included only three texture features and reached a sensitivity, specificity and accuracy of 94.12%, 88.24% and 91.18%, respectively. According to the features of the model, when the NCR/ NET region was studied, HGGs had a more heterogeneous texture than LGGs in the T 1Gd images, and LGGs had a more heterogeneous texture than HGGs in the T 2 images. These novel results partially contrast with results from the literature. The best model proved to be useful for the classification of gliomas. Complementary results showed that the heterogeneity of gliomas depended on the MRI contrast studied. The chosen model stands out as a simple, low-cost, easy-to-implement, reproducible and highly accurate glioma classifier. Importantly, it should be accessible to populations with reduced economic and scientific resources.

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