High-energy Data Research Articles

Real-Time and Efficient Traffic Information Acquisition via Pavement Vibration IoT Monitoring System.

Traditional road-embedded monitoring systems for traffic monitoring have the disadvantages of a short life, high energy consumption and data redundancy, resulting in insufficient durability and high cost. In order to improve the durability and efficiency of the road-embedded monitoring system, a pavement vibration monitoring system is developed based on the Internet of things (IoT). The system includes multi-acceleration sensing nodes, a gateway, and a cloud platform. The key design principles and technologies of each part of the system are proposed, which provides valuable experience for the application of IoT monitoring technology in road infrastructures. Characterized by low power consumption, distributed computing, and high extensibility properties, the pavement vibration IoT monitoring system can realize the monitoring, transmission, and analysis of pavement vibration signal, and acquires the real-time traffic information. This road-embedded system improves the intellectual capacity of road infrastructure and is conducive to the construction of a new generation of smart roads.

A Cluster-Based Energy Optimization Algorithm in Wireless Sensor Networks with Mobile Sink.

Aiming at high network energy consumption and data delay induced by mobile sink in wireless sensor networks (WSNs), this paper proposes a cluster-based energy optimization algorithm called Cluster-Based Energy Optimization with Mobile Sink (CEOMS). CEOMS algorithm constructs the energy density function of network nodes firstly and then assigns sensor nodes with higher remaining energy as cluster heads according to energy density function. Meanwhile, the directivity motion performance function of mobile sink is constructed to enhance the probability of remote sensor nodes being assigned as cluster heads. Secondly, based on Low Energy Adaptive Clustering Hierarchy Protocol (LEACH) architecture, the energy density function and the motion performance function are introduced into the cluster head selection process to avoid random assignment of cluster head. Finally, an adaptive adjustment function is designed to improve the adaptability of cluster head selection by percentage of network nodes death and the density of all surviving nodes of the entire network. The simulation results show that the proposed CEOMS algorithm improves the cluster head selection self-adaptability, extends the network life, reduces the data delay, and balances the network load.

StellarICS: inverse Compton emission from the quiet Sun and stars from keV to TeV

The study of the quiet Sun in gamma rays started over adecade ago, and rapidly gained a wide interest.Gamma rays from the quiet Sun are produced by Galactic Cosmic Rays (CRs) interacting with its surface (disk component) and with its photon field (spatially extended inverse-Compton component, IC). The latter component is maximum close to the Sun and it is above the background even at large angular distances, extending over the whole sky. First detected with EGRET, it is studied now with Fermi-LAT with high statistical significance.Observations of the IC component allow us to obtain information on CR electrons and positrons close to the Sun and in the heliosphere for the various periods of solar activity and polarity. They allow to learn about CR interactions and propagation in the stellar photosphere and heliosphere, and to understand the solar environment and its activity. Analyses of solar observations are usually model-driven.Hence advances in model calculations and constraints from precise CR measurements are timely and needed.Here we present our StellarICS code to compute the gamma-ray IC emission from the Sun and also from single stars.The code is publicly available and it is extensively used by the scientific community to analyze Fermi-LAT data. It has been used by the Fermi-LAT collaboration to produce the solar models released with the FSSC Fermi Tools.Our modeling provides the basis for analyzing and interpreting high-energy data of the Sun and of stars.After presenting examples of updated solar IC models in the Fermi-LAT energy range that account for the various CR measurements, we extend the models to keV, MeV, and TeV energies for predictions for present and future possible telescopes such as AMEGO, GECCO, an e-ASTROGAM-like instrument, HAWC, LHAASO, SWGO, and X-ray telescopes. We also present predictions for some of the closest and most luminous stars.

Two components model for TeV $\gamma $-ray emission from extreme high-energy BL Lac objects

Extreme high-energy peaked BL Lac objects (EHBLs) are an emerging class of blazars with exceptional spectral properties, e.g., enhanced emission in the hard X-ray region and a hard spectrum at very high $\gamma $ -ray energies. Currently, no suitable model exists to explain the high-energy radiation mechanism of EHBLs. Here we apply a new model of the emission process to describe the Spectral Energy Distribution (SED) of EHBLs composed of two separate components. The internal component occurs in the jet, describes synchrotron radiation and inverse Compton (IC) scattering of ultra-relativistic electrons; the two processes produce two humps of SED. The external component occurs out of the jet and considers the interaction of the proton accelerated in the jet with the cosmic microwave background (CMB), which generates electron pairs and, in turn, a cascade spectrum due to the IC scattering of those pairs with soft photons. We reproduce the SED of eight EHBLs by finding suitable values of the parameters, meanwhile, compare the $\gamma $ -ray flux with the sensitivity of Large High Altitude Air Shower Observatory (LHAASO) and verify if these objects will be observable with LHAASO. Furthermore, we discuss the influence of intergalactic magnetic fields (IGMFs) of strength $5\times 10^{-18}\;\mathrm{{G}\leq B_{IG}\leq 5\times 10^{-14}\;}\mathrm{{G}}$ and the region of proton’s turbulence acceleration. Finally, we find that the model may be employed to explain the high-energy emission mechanism and predict that LHAASO may detect the high-energy data of 1ES 0347-121, 1ES 1218+304, 1ES 1959+650, 1ES 2344+514 and RGB J0710+591 in the near future.

Amorphous dispersions of flubendazole in hydroxypropyl methylcellulose: Formulation stability assisted by pair distribution function analysis

We use X-ray pair distribution function (PDF) analysis applied to high-energy synchrotron X-ray powder diffraction data to evaluate the amorphous solid dispersions interactions and their aging stability. The obtained systems are based on hydroxypropyl methylcellulose (hypromellose) derivatives and flubendazole (FBZ) drug dispersions prepared using a spray-dryer technique. We carry out stability studies under aging parameters (40 °C/75% relative humidity) to tune the systems’ recrystallization. The results reveal that ion-base interactions between the drug-polymer matrix are responsible for reducing clustering processes yielding slower recrystallization and different ordering in the hypromellose phthalate (HPMCP/FBZ) and hypromellose acetate succinate (HPMC-AS/FBZ) systems and complete drug clustering in hypromellose (HPMC-E3/FBZ). The structural ordering was accessed using differential X-ray PDFs that revealed the region between 3.5 Å and 5.0 Å could be related to FBZ intermolecular interactions and is more ordered for the least stable system (HPMC-E3/FBZ) and less ordered for the most stable system (HPMCP/FBZ). These results show that the ion-base interactions between drug and matrix occur at these intermolecular distances.

Jupiter high-energy/high-latitude electron environment from Juno’s JEDI and UVS science instrument background noise

Spectral modeling combining the Jupiter Energetic-particle Detector Instrument (JEDI) differential flux and simulations of the Ultraviolet Spectrograph (UVS) background noise data were used to obtain the integral electron fluxes for energies of >1 MeV and >6 MeV at points along the Juno spacecraft’s trajectory. These high energy electrons are understood to dominate the Jovian energetic particle environment and their characterization for energies above 1 MeV is a critical aspect of understanding particle acceleration in Giant Planet magnetospheres. The measurements will reduce uncertainties in existing Jovian radiation models, which will enable a reduction in margins when designing future missions to Jupiter. These high energy data will also assist in better understanding the Juno instruments’ responses to the radiation environment and help to avoid misinterpreting radiation contamination as a true signal. Results of the analysis are compared with measurements from Pioneer 11 as well as with predictions using the Galileo Interim Radiation Electron (GIRE3) model.

Starburst galaxies strike back: a multi-messenger analysis with Fermi-LAT and IceCube data

ABSTRACT Starburst galaxies, which are known as ‘reservoirs’ of high-energy cosmic-rays, can represent an important high-energy neutrino ‘factory’ contributing to the diffuse neutrino flux observed by IceCube. In this paper, we revisit the constraints affecting the neutrino and gamma-ray hadronuclear emissions from this class of astrophysical objects. In particular, we go beyond the standard prototype-based approach leading to a simple power-law neutrino flux, and investigate a more realistic model based on a data-driven blending of spectral indexes, thereby capturing the observed changes in the properties of individual emitters. We then perform a multi-messenger analysis considering the extragalactic gamma-ray background (EGB) measured by Fermi-LAT and different IceCube data samples: the 7.5-yr high-energy starting events (HESE) and the 6-yr high-energy cascade data. Along with starburst galaxies, we take into account the contributions from blazars and radio galaxies as well as the secondary gamma-rays from electromagnetic cascades. Remarkably, we find that, differently from the highly-constrained prototype scenario, the spectral index blending allows starburst galaxies to account for up to $40{{\ \rm per\ cent}}$ of the HESE events at $95.4{{\ \rm per\ cent}}$ CL, while satisfying the limit on the non-blazar EGB component. Moreover, values of $\mathcal {O}(100\, \mathrm{PeV})$ for the maximal energy of accelerated cosmic-rays by supernovae remnants inside the starburst are disfavoured in our scenario. In broad terms, our analysis points out that a better modelling of astrophysical sources could alleviate the tension between neutrino and gamma-ray data interpretation.

Proton inelastic cross section at ultrahigh energies

We study the consequences of high-energy collider data on the best fits to total, elastic, and inelastic cross sections for $pp$ and $p\bar{p}$ scattering using two very distinct unitarisation schemes: the eikonal and the $U$-matrix. Despite their analytic differences, we find that the two schemes lead to almost identical predictions up to EeV energies, with differences only becoming significant at GUT-scale and higher energies.

New reconstruction of event-integrated spectra (spectral fluences) for major solar energetic particle events

Aims. Fluences of solar energetic particles (SEPs) are not easy to evaluate, especially for high-energy events (i.e. ground-level enhancements, GLEs). Earlier estimates of event-integrated SEP fluences for GLEs were based on partly outdated assumptions and data, and they required revisions. Here, we present the results of a full revision of the spectral fluences for most major SEP events (GLEs) for the period from 1956 to 2017 using updated low-energy flux estimates along with greatly revisited high-energy flux data and applying the newly invented reconstruction method including an improved neutron-monitor yield function. Methods. Low- and high-energy parts of the SEP fluence were estimated using a revised space-borne/ionospheric data and ground-based neutron monitors, respectively. The measured data were fitted by the modified Band function spectral shape. The best-fit parameters and their uncertainties were assessed using a direct Monte Carlo method. Results. A full reconstruction of the event-integrated spectral fluences was performed in the energy range above 30 MeV, parametrised and tabulated for easy use along with estimates of the 68% confidence intervals. Conclusions. This forms a solid basis for more precise studies of the physics of solar eruptive events and the transport of energetic particles in the interplanetary medium, as well as the related applications.

Assessment of Proton Direct Ionization for the Radiation Hardness Assurance of Deep Submicron SRAMs Used in Space Applications

Proton direct ionization (PDI) from low-energy protons has been shown to have a potentially significant impact on the accuracy of prediction methods used to calculate the upset rates (URs) of memory devices in space applications for state-of-the-art deep submicron technologies. The general approach nowadays is to consider a safety margin to apply over the UR computed from high-energy proton and heavy-ion experimental data. The data reported here present a challenge to this approach. Different UR prediction methods are used and compared in order to establish the impact of PDI on the total UR. Regardless of the method employed, the findings suggest that PDI can contribute to up to 90% of the total UR, on average, for a general selection of space orbits, with peaks of up to 99%. Such results suggest that an approach based on the characterization of the low-energy portion of the proton spectrum would be more convenient for similar technologies than the application of a general safety margin. Based on data presented here, the previously proposed margin of 5 is exceeded, by large amounts in some cases.

Estimating dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network.

Dual-energy computed tomography (DECT) is of great significance for clinical practice due to its huge potential to provide material-specific information. However, DECT scanners are usually more expensive than standard single-energy CT (SECT) scanners and thus are less accessible to undeveloped regions. In this paper, we show that the energy-domain correlation and anatomical consistency between standard DECT images can be harnessed by a deep learning model to provide high-performance DECT imaging from fully-sampled low-energy data together with single-view high-energy data. We demonstrate the feasibility of the approach with two independent cohorts (the first cohort including contrast-enhanced DECT scans of 5753 image slices from 22 patients and the second cohort including spectral CT scans without contrast injection of 2463 image slices from other 22 patients) and show its superior performance on DECT applications. The deep-learning-based approach could be useful to further significantly reduce the radiation dose of current premium DECT scanners and has the potential to simplify the hardware of DECT imaging systems and to enable DECT imaging using standard SECT scanners.

Design Options for Long-lasting, Efficient and Open Hardware and Software

High energy consumption and data traffic, critical production conditions and proprietary software ensure that the production and use of digital technologies and applications have so far been environmentally and socially problematic. We present basic approaches and policy measures for a sustainable design of hardware and software.

Testing wormhole solutions in extended gravity through the Poynting-Robertson effect

We develop a model-independent procedure to single out static and spherically symmetric wormhole solutions based on the general relativistic Poynting-Robertson effect and the extension of the ray-tracing formalism in generic static and spherically symmetric wormhole metrics. Simulating the flux emitted by the Poynting-Robertson critical hypersurface (i.e., a stable structure where gravitational and radiation forces attain equilibrium) or also from another X-ray source in these general geometrical environments toward a distant observer, we are able to reconstruct, only locally to the emission region, the wormhole solutions which are in agreement with the high-energy astrophysical observational data. This machinery works only if wormhole evidences have been detected. Indeed, in our previous paper we showed how the Poynting-Robertson critical hypersurfaces can be located in regions of strong gravitational field and become valuable astrophysical probe to observationally search for wormholes' existence. As examples, we apply our method to selected wormhole solutions in different extended theories of gravity by producing lightcurves, spectra, and images of an accretion disk. In addition, the present approach may constitute a procedure to also test the theories of gravity. Finally, we discuss the obtained results and draw the conclusions.

A Generic Streaming Software Platform Design for High-Energy Physics Data Acquisition Systems

The data acquisition (DAQ) system is a vital component in the high-energy physics experiment. To reduce duplication of work during development and improving efficiency, D-Matrix-S, a generic platform, has been developed as the software part of a software and hardware combination streaming DAQ system. D-Matrix-S is based on stream processing. Its philosophy is to abstract different tasks in the stream processing and encapsulate them as reusable modules with standard intermodule connectors. Furthermore, customizable DAQ systems could be built by calling appropriate modules and connecting them freely. D-Matrix-S adopts a layered design method during its development. The underlying construction is divided into stream source layers, stream transport layer, and stream processing layer. In the source layer, all types of data sources are streamed to help build a unified transmission model. The transport layer in a software environment achieves efficient and flexible stream transmission through dual shared memory space and plug-in transceivers. As for the processing layer, some common services for high-energy physics experiments such as configurable, generic event building, and multiroot, tree-like slow controlling are provided by the combination of standard modules. This article presents the design philosophy of a generic DAQ system and optimization made to improve flexibility and provides an application of the D-Matrix-S platform in the end.

Optimization of the differentiation and quantification of high-Z nanoparticles incorporated in medical devices for CT-guided interventions.

Material differentiation has been made possible using dual-energy computed tomography (DECT), in which the unique, energy-dependent attenuating characteristics of materials can provide new diagnostic information. One promising application is the clinical integration of biodegradable polymers as temporary implantable medical devices impregnated with high-atomic number (high-Z) materials. The purpose of this study was to explore the incorporation of high atomic number (high-Z) contrast materials in a bioresorbable inferior vena cava filter for advanced CT-based monitoring of its location and differentiating from surrounding materials. Imaging optimization and calibration studies were performed using a body phantom. The dual-energy CT (DECT) ratios for iron, zirconium, barium, gadolinium, ytterbium, tantalum, tungsten, gold, and bismuth were generated for peak kilovoltage combinations of 80/150Sn, 90/150Sn, and 100/150Sn kVp in dual-source CT via linear regression of the CT numbers at low and high energies. A secondary calibration of the material map to the nominal material concentration was generated to correct for use of materials other than iodine. CT number was calibrated to the material concentration based on single-energy CT (SECT) with additional filtration (150Sn kVp). These quantification methods were applied to monitoring of biodegradable inferior vena cava filters (IVCFs) made of braided poly(p-dioxanone) sutures infused with ultrasmall bismuth nanoparticles (BiNPs) implanted in an adult domestic pig. Qualitative material differentiation was optimal for high-Z (>73) contrast agents in DECT. However, quantification became nonlinear and inaccurate as the K-edge of the material increased. Using the high-energy (150Sn kVp) data component as a SECT scan, the linearity of quantification curves was maintained with lower limits of detection than with DECT. Among the materials tested, bismuth had optimal differentiation from iodine in DECT while maintaining increased contrast in high-energy SECT for quantification (11.5% error). Coating the IVCF with BiNPs resulted in markedly greater radiopacity (maximum CT number, 2028HU) than that of an uncoated IVCF (maximum CT number, 127HU). Using DECT imaging and processing, the BiNP-IVCF could be clearly differentiated from iodine contrast injected into the inferior vena cava of the pig. These findings may improve widespread integration of medical devices incorporated with high-Z materials into the clinic, where technical success, possible complications, and device integrity can be assessed intraoperatively and postoperatively via DECT imaging.

Short range order and crystallization of Cu–Hf metallic glasses

Detailed information on the atomic arrangement of glassy Cu54Hf46, Cu61Hf39 and Cu69Hf31 alloys has been obtained by the reverse Monte Carlo (RMC) simulation using high-energy X-ray diffraction and neutron diffraction data as input. Dominant cluster units are identified by means of the radical Voronoï tessellation technique. Cu-centred clusters show a stronger ordering level than the Hf-centred ones. Results are compared with those previously reported for analogous binary amorphous systems such as Zr–Cu and Zr–Ni. Additionally, the thermal stability of the studied Cu–Hf alloys has been inspected by in-situ high-temperature X-ray diffraction and differential scanning calorimetry measurements. A different structural evolution is observed for Cu69Hf31 compared with Cu54Hf46 and Cu61Hf39. Products of devitrification are identified and quantified. The better glass forming ability of Cu54Hf46 and Cu61Hf39 compared with Cu69Hf31 is explained in the view of short range order differences of glassy states and corresponding crystalline phases formed during devitrification.

Froissart bound, diffraction scattering of hadrons, and scaling at asymptotic energies

The Froissart bound on the total cross section is subjected to test against very high energy data. We have found no clear evidence for its violation. The scaling property of differential cross section in the diffraction region is investigated. It exhibits scaling in the ISR, SPS, Tevatron and LHC energy domain which had hitherto remained unexplored. The slope of the diffraction peak is fitted and the data are tested against the rigorous bounds.

Electric-field-induced structural changes for cubic system of lead-free and lead-based perovskite-type oxides

Changes in crystal structures of lead-free BaTiO3 (BT) and lead-based 0.70Pb(Mg1/3Nb2/3)–0.30PbTiO3 (PMN–PT) single crystals with a perovskite-type structure have been investigated under applied electric field by analyzing the high-energy synchrotron radiation X-ray diffraction data. The experiment is performed within the cubic phase in the phase diagram with the range of temperatures and electric fields where no electric field-induced phase transition is caused. The crystal structure analysis demonstrates that the crystal system is change to a tetragonal system by electrostriction when the electric field is applied along the crystal axis. The atomic arrangement in BT corresponds to the displacement pattern attributed to the Slater mode where Ti and O ions are mutually shifted in the opposite directions along the electric field, while that in PMN–PT is of the Last mode where Pb ions and (Mg, Nb)O6 oxygen octahedra are mutually shifted. The electron charge density study demonstrates that the Ba–O bonding in BT is ionic, whereas the Pb–O bonding in PMN–PT is highly covalent in the cubic structure. PMN–PT is revealed to have a characteristic Pb–O covalent bond which induces the atomic displacement attributed to the Last mode under applied electric field within the cubic phase despite no phase transition.

GRB 200415A: A Short Gamma-Ray Burst from a Magnetar Giant Flare?

Abstract The giant flares of soft gamma-ray repeaters (SGRs) have long been proposed to contribute to at least a subsample of the observed short gamma-ray bursts (GRBs). In this paper, we perform a comprehensive analysis of the high-energy data of the recent bright short GRB 200415A, which was located close to the Sculptor galaxy. Our results suggest that a magnetar giant flare provides the most natural explanation for most observational properties of GRB 200415A, including its location, temporal and spectral features, energy, statistical correlations, and high-energy emissions. On the other hand, the compact star merger GRB model is found to have difficulty reproducing such an event in a nearby distance. Future detections and follow-up observations of similar events are essential to firmly establish the connection between SGR giant flares and a subsample of nearby short GRBs.

Evaluation of a commercial deformable image registration algorithm for dual-energy CT processing.

PurposeSeveral dual‐energy computed tomography (DECT) techniques require a deformable image registration to correct for motion between the acquisition of low and high energy data. However, current DECT software does not provide tools to assess registration accuracy or allow the user to export deformed images, presenting a unique challenge for image registration quality assurance (QA). This work presents a methodology to evaluate the accuracy of DECT deformable registration and to quantify the impact of registration errors on end‐product images.MethodsThe deformable algorithm implemented in Siemen Healthineers's Syngo was evaluated using a deformable abdomen phantom and a rigid phantom to mimic sliding motion in the thorax. Both phantoms were imaged using sequential 80 and 140 kVp scans with motion applied between the two scans. Since Syngo does not allow the export of the deformed images, this study focused on quantifying the accuracy of various end‐product, dual‐energy images resulting from processing of deformed images.ResultsThe Syngo algorithm performed well for the abdomen phantom with a mean registration error of 0.4 mm for landmark analysis, Dice similarity coefficients (DSCs) > 0.90 for five organs contoured, and mean iodine concentrations within 0.2 mg/mL of values measured on static images. For rigid sliding motion, the algorithm performed poorer and resulted in noticeable registration errors toward the superior and inferior scan extents and DSCs as low as 0.41 for iodine rods imaged in the phantom. Additionally, local iodine concentration errors in areas of misregistration exceeded 3 mg/mL.ConclusionsThis work represents the first methodology for DECT image registration QA using commercial software. Our data support the clinical use of the Syngo algorithm for abdominal sites with limited motion (i.e., pancreas and liver). However, dual‐energy images generated with this algorithm should be used with caution for quantitative measurements in areas with sliding motion.