Escape Of Particles Research Articles

Time-dependent Acceleration and Escape of Charged Particles at Traveling Shocks in the Near-Sun Environment

Current multi-spacecraft in situ measurements allow for the investigation of the time evolution of energetic particles at interplanetary shocks (IPs) at small (≲0.1 au) heliocentric distances. The energy spectrum of accelerated particles at IPs was shown by a previous 1D transport model that includes both self-excited plus preexisting turbulence and a term representing the escape of particles from the system to gradually steepen as a result of a finite acceleration-to-escape timescales ratio; such a model was found in excellent agreement with the entire sample of the ground-level enhancement spectra of solar cycle 23. We solve the time-dependent case of such a model in the case of diffusion dominated by preexisting turbulence. The average timescale for particle acceleration at various heliocentric distances, from 1 au down to the inner heliosphere (<0.1 au), is shorter than in the no-escape case, as higher energy particles have a shorter time to accelerate before completely leaving the system into the upstream medium. A simple scaling with time of the time-dependent spectrum is provided. We compare the “nose” structure at a few ∼100s keV protons first measured in situ by Parker Solar Probe in crossing the very fast 2022 September 5 shock at 0.07 au; we find that the nose is reasonably well explained by a lack of the highest energy particles not yet produced by the young shock by both our model and the no-escape version.

Cosmic-ray acceleration and escape from supernova remnant W44 as probed by Fermi-LAT and MAGIC

Context. The supernova remnant (SNR) W44 and its surroundings are a prime target for studying the acceleration of cosmic rays (CRs). Several previous studies established an extended gamma-ray emission that is set apart from the radio shell of W44. This emission is thought to originate from escaped high-energy CRs that interact with a surrounding dense molecular cloud complex. Aims. We present a detailed analysis of Fermi-LAT data with an emphasis on the spatial and spectral properties of W44 and its surroundings. We also report the results of the observations performed with the MAGIC telescopes of the northwestern region of W44. Finally, we present an interpretation model to explain the gamma-ray emission of the SNR and its surroundings. Methods. We first performed a detailed spatial analysis of 12 years of Fermi-LAT data at energies above 1 GeV, in order to exploit the better angular resolution, while we set a threshold of 100 MeV for the spectral analysis. We performed a likelihood analysis of 174 hours of MAGIC data above 130 GeV using the spatial information obtained with Fermi-LAT. Results. The combined spectra of Fermi-LAT and MAGIC, extending from 100 MeV to several TeV, were used to derive constraints on the escape of CRs. Using a time-dependent model to describe the particle acceleration and escape from the SNR, we show that the maximum energy of the accelerated particles has to be ≃40 GeV. However, our gamma-ray data suggest that a small number of lower-energy particles also needs to escape. We propose a novel model, the broken-shock scenario, to account for this effect and explain the gamma-ray emission.

Ultra-High-Energy Cosmic Rays Accelerated by Magnetically Dominated Turbulence

Abstract Ultra-high-energy cosmic rays (UHECRs), particles characterized by energies exceeding 1018 eV, are generally believed to be accelerated electromagnetically in high-energy astrophysical sources. One promising mechanism of UHECR acceleration is magnetized turbulence. We demonstrate from first principles, using fully kinetic particle-in-cell simulations, that magnetically dominated turbulence accelerates particles on a short timescale, producing a power-law energy distribution with a rigidity-dependent, sharply defined cutoff well approximated by the form f cut E , E cut = sech ( E / E cut ) 2 . Particle escape from the turbulent accelerating region is energy dependent, with t esc ∝ E −δ and δ ∼ 1/3. The resulting particle flux from the accelerator follows dN / dEdt ∝ E − s sech ( E / E cut ) 2 , with s ∼ 2.1. We fit the Pierre Auger Observatory’s spectrum and composition measurements, taking into account particle interactions between acceleration and detection, and show that the turbulence-associated energy cutoff is well supported by the data, with the best-fitting spectral index being s = 2.1 − 0.13 + 0.06 . Our first-principles results indicate that particle acceleration by magnetically dominated turbulence may constitute the physical mechanism responsible for UHECR acceleration.

HESPERIA REleASE+: Improving Solar Proton Event Forecasting by Means of Automated Recognition of Type‐III Radio Bursts

AbstractThis work reports on an attempt toward improving the Relativistic Electron Alert System for Exploration (REleASE): the occurrence of a type‐III radio burst as a precondition for a REleASE forecast. REleASE forecasts are based on the detection of early arrival of near‐relativistic electrons ahead of more hazardous protons from Solar Energetic Particle (SEP) events. The goal is to allow astronauts on a Lunar or Mars mission sufficient advance warning to reach a radiation shelter to minimize radiation dose exposure. We test a new system that sets a condition of the occurrence of a type‐III radio burst, thus adding independent evidence of particle escape from the Sun, with the aim of reducing known sources of false‐alarms of the existing REleASE system. The High Energy Solar Particle Events foRecastIng and Analysis (HESPERIA) REleASE+ system, which takes advantage of availability of real‐time solar radio observations during the passage of STEREO‐A by Earth in 2023, has now been incorporated in the HESPERIA framework. We discuss the techniques used for automatic detection of type‐III radio bursts preparing for its real‐time implementation, the determination of selection criteria for type‐III bursts that are candidates for solar proton events in the Earth‐moon system, and first results of the combined system.

Analysis and Experimental Study on the Influence of Louver Separation Device on the Sand Collection Efficiency of Wind Erosion Instrument

A wind erosion instrument is a core instrument for collecting sand particles in wind and sand flows and studying the laws of wind and sand movement. To study the influence of the internal structure of the wind erosion instrument on its sand collection efficiency, a built-in louver separation device was designed. Based on CFD and Fluent 2022 software, numerical analysis was conducted using an RNG k-ε model, and the discrete phase model (DPM) method was used to calculate the sand collection efficiency. The flow field analysis of the new wind–sand separator was carried out. The influence of blade inclination angle, blade thickness, and blade number on sand collection efficiency was studied using single-factor and response surface analysis methods. The optimal parameter combination was obtained as blade inclination angle of 30°, blade thickness of 1.25 mm, and blade number of 10. A simulation model was established based on the optimal combination parameters, and the performance of the wind erosion instrument before and after the addition of the louver separation device was compared. The simulation results show that adding a louver separation device can increase static pressure, alleviate short-circuit flow and back-mixing phenomena, and stabilize the flow field; increasing tangential velocity leads to an increase in particle centrifugal force; reduce axial velocity, prolong particle stagnation time, and minimize particle escape. The particle trajectory pattern is mostly a continuous spiral path, which is conducive to capturing particles and improving sand collection efficiency. Compared with the original structure, for particles with diameters ranging from 0.001–0.05 mm, 0.005–0.01 mm, 0.01–0.05 mm, 0.05–0.1 mm, and 0.1–0.5 mm, the addition of a louver separation device increased the sand collection efficiency by 32.74%, 22.55%, 33.17%, 11.45%, and 0.13%, respectively. When the wind speed is 13.8 m/s and the diameter range is 0.001–0.5 mm, the average sand collection efficiency obtained from simulation tests and wind tunnel tests is 86.18% and 84.32%, respectively, with an error of 2.2%. The simulation results are reliable. The research results show that adding a louver separation device can improve the sand collection efficiency of the wind erosion instrument, and has better overall performance compared to the original wind–sand separator. This study provides a basis for further research on the structure of wind erosion gauges and the environmental protection of farmland. Strengthening land management can effectively protect soil resources, reduce wind erosion, ensure the stability of the ecosystem, and lay the foundation for promoting the sustainable use of land.

Binocular camera calibration using a BP algorithm optimized by an improved subtraction-average-based optimizer

The BP algorithm exhibits drawbacks such as reduced precision and extended iteration duration during the process of calibrating a binocular camera system. A technique employing an improved subtraction-average-based optimizer to optimize the BP algorithm (ISABO-BP) is introduced to address these limitations and complete the calibration of the binocular camera. The pixel values of the corner in 2D space and the coordinate values in 3D space are used as the input and output for the BP algorithm, respectively. First, the logistic chaotic mapping is used to initialize the population to increase the diversity of the initial population. The piecewise mapping is employed to generate random values to replace the coefficient values in the individual position update formula, making the population distribution more uniform. The golden sine strategy is adopted to help particles escape from local optima. The ISABO-BP algorithm is utilized to perform the process of calibrating a binocular camera. Then, through numerical experiments, the mean calibration precision for the BP algorithm is 0.1501 and 0.0445 cm for the ISABO-BP algorithm. The calibration precision has been enhanced by 70.4%. The iterative steps of the BP algorithm are 353 epochs, while the ISABO-BP algorithm are 76 epochs, and the iterative speed is increased by nearly four times. It is evident that the ISABO-BP algorithm enhances the calibration precision and expedites the convergence rate. Finally, other intelligent algorithms to optimize the BP algorithm for calibrating a binocular camera are compared, and the superiority of this algorithm is also verified.

Validation of numerical method of unsteady Reynolds-averaged Navier–Stokes coupled with discrete phase model and optimization for the snow-resistance performance of bogies of a high-speed train

This paper presents an investigation aimed at enhancing the snow resistance of bogies in a three-car grouped alpine high-speed train (HST) that operates in a snowy region. The study employs a combination of the unsteady Reynolds-averaged Navier–Stokes model, coupled with the discrete phase model. This modeling approach has been validated through wind tunnel tests, including flow field tests, two-phase flow tests, and snow-ice tests. The study comprehensively compares the characteristics of the wind-snow flow, spatial snow concentration, and the distribution of snow on the train's underbody between two scenarios: the original train's underbody structure and the multifactor collaborative optimization scheme (MCOS). The results indicate that the MCOS case facilitates the escape of snow particles from the bogie cavities by weakening the upward and reverse flows. Furthermore, the MCOS case significantly reduces the concentration of snow particles around the heat-producing elements and decreases the accumulation of snow on both the lower and upper surfaces of the bogies. As a result, it reduces snow accumulation on the bogies by 50.6%, 56.4%, 60.8%, and 62.4% at train speeds of 200, 250, 300, and 350 km/h, respectively. In summary, this research provides valuable insights for improving the snow resistance of HSTs operating in snowy regions, with potential applications in enhancing railway transportation safety and efficiency.

Coherence of Multidimensional Pair Production Discharges in Polar Caps of Pulsars

We report on the first self-consistent multidimensional particle-in-cell numerical simulations of nonhomogeneous pair discharges in polar caps of rotation-powered pulsars. By introducing strong inhomogeneities in the initial plasma distribution in our simulations, we analyze the degree of self-consistently emerging coherence of discharges across magnetic field lines. In 2D, we study discharge evolution for a wide range of physical parameters and boundary conditions corresponding to both the absent and free escape of charged particles from the surface of a neutron star. We also present the results of the first 3D simulations of discharges in a polar cap with a distribution of the global magnetospheric current appropriate for a pulsar with 60° inclination angle. For all parameters, we find the coherence scale of pair discharges across magnetic field lines to be of the order of the gap height. We also demonstrate that the popular “spark” model of pair discharges is incompatible with the universally adopted force-free magnetosphere model: intermittent discharges fill the entire zone of the polar cap that allows pair cascades, leaving no space for discharge-free regions. Our findings disprove the key assumption of the spark model about the existence of isolated distinct discharge columns.

Study on the performance of electrostatic agglomeration enhances magnetic filter material for filtering fugitive particles in the iron and steel industry

In this work, a new method is proposed to utilize a magnetic filter material to suppress the escape of fugitive particles in the iron and steel industry. The magnetic filter material was prepared using the impregnation method, exhibiting superior demagnetization resistance. The magnetic field effect generated by magnetic filter material was combined with the diffusion, interception, and inertial effects of traditional filtration mechanisms to enhance the removal of fugitive particles. The magnetic polyimide filter material improves the filtration efficiency of particles with a diameter less than 2.0 μm by approximately 20% compared with polyimide filter materials. In addition, the filtration performance was further enhanced through electrostatic agglomeration. When the positive electrode voltage is +18 kV, and the negative electrode voltage is −16 kV, after the bipolar pre-charging treatment of fugitive particles with a diameter of 0.1–1.0 μm, the magnetic polyimide filter material can achieve a filtration efficiency of more than 90%, the magnetic polyimide (P84), magnetic polyphenylene sulfide (PPS), and magnetic fiberglass filter materials all achieve a filtration efficiency of over 94% with a diameter of 0.5–1.0 μm. This study lays the foundation for the proposal new dust removal methods for the iron and steel industry.

Particle acceleration, escape, and non-thermal emission from core-collapse supernovae inside non-identical wind-blown bubbles

Context. In the core-collapse scenario, supernova remnants (SNRs) evolve inside complex wind-blown bubbles structured by massive progenitors during their lifetime. Therefore, particle acceleration and the emissions from these SNRs can carry the fingerprints of the evolutionary sequences of the progenitor stars. Aims. We investigate the impact of the ambient environment of core-collapse SNRs on particle spectra and emissions for two progenitors with different evolutionary tracks while accounting for the spatial transport of cosmic rays (CRs) and the magnetic turbulence that scatters CRs. Methods. We used the RATPaC code to model the particle acceleration at the SNRs with progenitors having zero-age main sequence (ZAMS) masses of 20 M⊙ and 60 M⊙. We constructed the pre-supernova circumstellar medium (CSM) by solving the hydrodynamic equations for the lifetime of the progenitor stars. Then, the transport equation for cosmic rays, the magnetic turbulence in test-particle approximation, and the induction equation for the evolution of a large-scale magnetic field were solved simultaneously with the hydro-dynamic equations for the expansion of SNRs inside the pre-supernova CSM in 1-D spherical symmetry. Results. The profiles of gas density and temperature of the wind bubbles along with the magnetic field and the scattering turbulence regulate the spectra of accelerated particles for both of the SNRs. For the 60 M⊙ progenitor, the spectral index reaches 2.4, even below 10 GeV, during the propagation of the SNR shock inside the hot shocked wind. In contrast, we did not observe a persistent soft spectra at earlier evolutionary stages of the SNR with the 20 M⊙ progenitor, for which the spectral index becomes 2.2 only for a brief period during the interaction of SNR shock with the dense shell of red supergiant (RSG) wind material. At later stages of evolution, the spectra become soft above ~10 GeV for both SNRs, as weak driving of turbulence permits the escape of high-energy particles from the remnants. The emission morphology of the SNRs strongly depends on the type of progenitors. For instance, the radio morphology of the SNR with the 20 M⊙ progenitor is centre-filled at early stages, whereas that of the more massive progenitor is shell-like.

Artificial electric field algorithm with repulsion mechanism

AbstractDue to its outstanding performance in addressing optimization problems, artificial electric field (AEF) algorithm has garnered increasing notice in recent years. Nevertheless, numerous studies indicate that AEF is susceptible to premature convergence when the region influenced by the global optimum constitutes a small fraction of the entire solution space. By conducting micro‐level research on the particles during the evolution process of AEF, it is revealed that the primary factors influencing optimization performance are the Coulomb's electrostatic force mechanism and the fixed attenuation factor. Inspired by this observation, we propose an improved version named artificial electric field algorithm with repulsion mechanism (RMAEF). Specifically, in RMAEF, a repulsion mechanism is incorporated to make particles escape from local optima. Furthermore, an adaptive attenuation factor is employed to update dynamically Coulomb's constant. RMAEF is compared with AEF and its state‐of‐art variants under 44 test functions from CEC 2005 and CEC 2014 test suites. From the experiment results, it is obvious that among 14 benchmark functions from CEC 2005 on 30D and 50D optimization, the RMAEF algorithm exhibits superior performance on 8 and 9 functions compared with advanced variants of AEF. For CEC 2014 on 30D and 50D optimization, the RMAEF algorithm produces the best results on 11 and 12 functions, respectively. In addition, three real‐world problems are also used to verify the versatility and robustness. The results demonstrate that RMAEF outperforms its competitors in terms of overall performance.

Bridging Macroscopic Diffusion and Microscopic Cavity Escape of Brownian and Active Particles in Irregular Porous Networks.

While irregular and geometrically complex pore networks are ubiquitous in nature and industrial processes, there is no universal model describing nanoparticle transport in these environments. 3D super-resolution nanoparticle tracking was employed to study the motion of passive (Brownian) and active (self-propelled) species within complex networks, and universally identified a mechanism involving successive cavity exploration and escape. In all cases, the long-time ensemble-averaged diffusion coefficient was proportional to a quantity involving the characteristic length scale and time scale associated with microscopic cavity exploration and escape (D ∼ r2/ttrap), where the proportionality coefficient reflected the apparent porous network connectivity. For passive nanoparticles, this coefficient was always lower than expected theoretically for a random walk, indicating reduced network accessibility. In contrast, the coefficient for active nanomotors, in the same pore spaces, aligned with the theoretical value, suggesting that active particles navigate "intelligently" in porous environments, consistent with kinetic Monte Carlo simulations in networks with variable pore sizes. These findings elucidate a model of successive cavity exploration and escape for nanoparticle transport in porous networks, where pore accessibility is a function of motive force, providing insights relevant to applications in filtration, controlled release, and beyond.

Extended gamma-ray emission from particle escape in pulsar wind nebulae. Application to HESS J1809-193 and HESS J1825-137

There is growing evidence from gamma-ray observations at high and very high energies that particle escape is a key aspect shaping the morphological properties of pulsar wind nebulae (PWNe) at various evolutionary stages. We aim to provide a simple model for the gamma-ray emission from these objects including the transport of particles across the different components of the system. We applied it to sources HESS J1809$-$193 and HESS J1825$-$137. We developed a multi-zone framework applicable to dynamically young PWNe, taking into account the diffusive escape of relativistic electron-positron pairs out of the nebula into the parent supernova remnant (SNR) and their confinement downstream of the magnetic barrier of the forward shock until an eventual release into the surrounding interstellar medium (ISM). For a wide range of turbulence properties in the nebula, the GeV-TeV inverse-Compton radiation from pairs that escaped into the remnant can be a significant if not dominant contribution to the emission from the system. It may dominate the pion-decay radiation from cosmic rays accelerated at the forward shock and advected downstream of it. In the TeV-PeV range, the contribution from particles escaped into the ISM can exceed by far that of the SNR+PWN components. Applied to HESS J1809$-$193 and HESS J1825$-$137, we found that spatially extended GeV-TeV emission components can be accounted for mostly from particles escaped into the ISM, while morphologically more compact components above $50-100$ are ascribed to the PWNe. In these two cases, the model suggests high turbulence in the nebula and a forward shock accelerating cosmic rays up to $ at most. The model provides the temporal and spectral properties of the flux of particles originally energized by the pulsar wind and ultimately released in the ISM. It can be used to constrain the transport of particles in the vicinity of pulsar-PWN-SNR systems from broadband gamma-ray observations, or in studies of the contribution of pulsar-related systems to the local positron flux.

The investigation on the ceiling of inlet velocity regarding to fine particle separation in a cyclone

The maximum efficiency inlet velocity (MEIV) serves as the upper limit for the inlet velocity that defines the separation efficiency in cyclone design and operation. In this paper, a combination of numerical and experimental methods is used to study MEIV. Experimental findings indicate that the MEIV is 22 m/s for a median particle size of 12.39 μm (coarse powder) and 35 m/s for a median particle size of 2.93 μm (fine powder). Meanwhile, the amount of escaped fine powder is reduced by 25% compared to that at an inlet velocity of 22 m/s. Computational fluid dynamics (CFD) simulations have shown that the inconsistency between tangential and axial velocity growth of inlet velocity with respect to various powder diameters can explain this phenomenon. As the inlet velocity increases, the peak axial velocity exhibits a stepwise increase. When the peak value remains constant, the peak width increases. This phenomenon is called stagnation of the axial velocity. During the axial velocity stagnation step, the residence time of back-mixed particles vary. In contrast, the tangential velocity increases linearly with the inlet velocity, resulting in an enhanced secondary separation of the inner vortex. Both factors hinder the escape of fine particles due to entrainment by a rapid upward airflow. The inlet velocity range corresponding to the stagnation step of the fine powder is larger than that of the coarse powder. Therefore, the MEIV of the fine powder is higher.

Improved Dual-Center Particle Swarm Optimization Algorithm

This paper proposes an improved dual-center particle swarm optimization (IDCPSO) algorithm which can effectively improve some inherent defects of particle swarm optimization algorithms such as being prone to premature convergence and low optimization accuracy. Based on the in-depth analysis of the velocity updating formula, the most innovative feature is the vectorial decomposition of the velocity update formula of each particle to obtain three different flight directions. After combining these three directions, six different flight paths and eight intermediate positions can be obtained. This method allows the particles to search for the optimal solution in a wider space, and the individual extreme values are greatly improved. In addition, in order to improve the global extreme value, it is designed to construct the population virtual center and the optimal individual virtual center by using the optimal position and the current position searched by the particle. Combining the above strategies, an adaptive mutation factor that accumulates the coefficient of mutation according to the number of iterations is added to make the particle escape from the local optimum. By running the 12 typical test functions independently 50 times, the results show an average improvement of 97.9% for the minimum value and 97.7% for the average value. The IDCPSO algorithm in this paper is better than other improved particle swarm optimization algorithms in finding the optimum.

Phase control of escapes in the fractional damped Helmholtz oscillator

We analyze the nonlinear Helmholtz oscillator in the presence of fractional damping, a characteristic feature in several physical situations. In our specific scenario, as well as in the non-fractional case, for large enough excitation amplitudes, all initial conditions are escaping from the potential well. To address this, we incorporate the phase control technique into a parametric term, a feature commonly encountered in real-world situations. In the non-fractional case it has been shown that, a phase difference of ϕOPT≈π, is the optimal value to avoid the escapes of the particles from the potential well. Here, our investigation focuses on understanding when particles escape, considering both the phase difference ϕ and the fractional parameter α as control parameters. Our findings unveil the robustness of phase control, as evidenced by the consistent oscillation of the optimal ϕ value around its non-fractional counterpart when varying the fractional parameter. Additionally, our results underscore the pivotal role of the fractional parameter in governing the proportion of bounded particles, even when utilizing the optimal phase.

Shape deformation, disintegration, and coalescence of suspension drops: Efficient simulation enabled by graph neural networks

Understanding the behaviors of suspension drops (particle swarms) as they settle in a viscous fluid holds significant importance across various applications. Due to hydrodynamic interactions (HIs), suspension drops would undergo a series of intricate behaviors, including shape deformation, disintegration, and coalescence. This work presents the hydrodynamic interaction graph neural network (HIGNN), developed in our prior work (Ma et al., 2022), as an efficient and accurate modeling framework for simulating the dynamics of suspension drops and investigating the various behaviors they exhibit. The HIGNN effectively incorporates the many-body nature of HIs, a feature lacking in most previous simulations that employ the Stokeslet assumption. In the meanwhile, the HIGNN achieves superior computational efficiency compared to traditional, high-fidelity numerical tools such as Stokesian dynamics and PDE solvers. Moreover, the HIGNN, once trained, is applicable to predicting suspension drops across a range of particle concentrations and under diverse forces (such as gravity and Coulombic interactions). Training the HIGNN only requires the data containing a small number of particles, leading to low training cost. Our results demonstrate that the HIGNN can effectively reproduce the various behaviors of suspension drops that were previously reported in literature. More specifically, a single, initially spherical drop slowly evolves into a torus-shaped drop, as particles escape from its rear and form a tail along the sedimenting direction. Subsequently, the torus breaks into secondary droplets, each undergoing a similar transition (deformation into a torus followed by disintegration), thereby leading to a repeating cascade. Further, we quantitatively analyze the correlation between the drop’s sedimentation velocity and volume fraction. We also propose new scaling laws for evaluating both the leakage rate of particles and the expansion rate of the horizontal radius of a suspension drop. For single suspension drops, we also systematically investigate how their dynamics is affected by their initial shapes and the formed tori’s aspect ratios, as well as with or without Coulombic interactions between particles. For a pair of suspension drops, we study the process of coalescence of two vertically aligned particles and examine the effect of introducing a horizontal offset on the subsequent breakup of the coalesced drop. All simulations were executed on a single GPU, with the computation of velocities for several thousand particles requiring less than five seconds per time step. This computational efficiency enables fast and resource-saving simulations of large suspension drops over extended time scales.

Gamma-ray detection of newly discovered Ancora supernova remnant: G288.8–6.3

Context. The supernova remnant (SNR) G288.8–6.3 was recently discovered as a faint radio shell at high Galactic latitude using observations with the Australian Square Kilometre Array Pathfinder (ASKAP) in the Evolutionary Map of the Universe (EMU) survey. Aims. We performed the first detailed investigation of the γ-ray emission from the G288.8–6.3 region, aiming to characterise the high-energy emission in the GeV regime from the newly discovered SNR, dubbed Ancora. Methods. Fifteen years of Fermi-Large Area Telescope (LAT) data were analysed at energies between 400 MeV and 1 TeV, and the excess seen in the region was modelled using different spatial and spectral models. Results. We detect spatially extended γ-ray emission coinciding with the radio SNR, with detection significance up to 8.8 σ. A radial disk spatial model in combination with a power-law spectral model with an energy flux of (4.80 ± 0.91) × 10−6 MeV cm−2 s−1, with the spectrum extending up to around 5 GeV was found to be the preferred model. Morphologically, hotspots seen above 1 GeV are well correlated with the bright western part of the radio shell. The emission is more likely to be of leptonic origin, given the estimated gas density in the region and the estimated distance and age of the SNR, but a hadronic scenario cannot be ruled out. Conclusions. Ancora is the seventh confirmed SNR detected at high Galactic latitude with Fermi-LAT. The study of this new population of remnants can provide insights into the evolutionary aspects of SNRs and their properties, and further advance efforts of constraining the physics of particle diffusion and escape from SNRs into the Galaxy.

Evaluation of Personal Protective Equipment Using Low-cost Aerosol Monitors

Rapid, low-cost evaluation of personal protective equipment (PPE) is important for providing widespread and easy-to-access testing of aerosols through and round masks and shields. Most related literature has focused on how well PPE protects the wearer, not reducing aerosol transmission to the environment. Few studies have compared the efficacy for particle escape at exhalation or inhalation of face masks and face shields. Measurements of particulate matter escaping through PPE could provide information regarding the efficacy on the wearer and on the surrounding of the PPE and guide the selection of appropriate PPE to wear in different conditions. Research grade particle technology devices are not widely available. Low-cost options which are simple to use may provide a practical alternative. In this study, we measured particulate matter with a diameter less than 2.5 µm (PM2.5) emitted by a manikin placed upright at the head of a stretcher. Measurements were made using three low-cost sensors and an Optical Particle Sizer (OPS) at distances of 2, 4, and 6 feet repeated at 0, 45, and 90°, given at a horizontal plane, with respect to the mannikin. The low-cost sensors correlated well with the OPS used as a reference method and may provide a simple, low-cost, widely available alternative.

Aerosol deposition and emission from a United States Pharmacopeia‐induction port when using a pressurized metered‐dose inhaler with and without a valved holding chamber

AbstractThe testing of pharmaceutical aerosols includes measuring the aerodynamic particle size distribution, which is usually performed on cascade impactors. In the next generation impactor (NGI), the aerosol dose is introduced through an induction port (IP), being separated into different aerodynamic diameter ranges by seven stages and a micro‐orifice collector. The IP plays an important role in estimating the oropharyngeal deposition fraction. While the IP retains mainly large particles, it also tends to retain particles in the respirable range. In this work, the deposition of particles in the IP of an NGI is studied, both experimentally and through computational fluid dynamic (CFD) simulations. Experimental tests are conducted both with the pressurized metered‐dose inhaler (pMDI) alone and in conjunction with a cylindrical valved holding chamber (VHC). For each case, the total mass deposition that occurs in the VHC, IP, and NGI stages is measured, as well as the mass median aerodynamic diameter of the aerosol leaving the IP. The CFD simulations show minimal variations in results regardless of the injection method due to the relatively low velocity and spray angle of the pMDI‐generated aerosol. If the flap‐valve is removed from the VHC, significant particle deposition occurs upstream or within the valve region, with downstream air recirculation contributing to small particle deposition. Based on the CFD results, a correlation is proposed to accurately predict the particle escape fraction of the IP and VHC, which allows estimation of the tannin distribution of particles collected in the NGI stages, especially those corresponding to the range of respirable particles.