Br. Birkeland (Norway)

Abattoirs provide a valuable opportunity to assess the impact of porcine pleuropneumonia, as lesions caused by Actinobacillus pleuropneumoniae remain visible at postmortem inspections. This study evaluated an artificial intelligence (AI)-based system for scoring pleurisy in slaughtered pigs under field conditions. The trial was conducted in a Norwegian abattoir, where a collaborative robot automatically captured carcass images. A convolutional neural network assessed pleurisy according to the “ Pleurisy Evaluation on the Parietal Pleura ” method. In parallel, veterinarians and meat inspectors from the Norwegian Food Safety Authority scored pleurisy using a binary system, based on the presence or absence of lesions exceeding 15 cm. Moreover, a subset of 500 images were scored by two academic veterinarians (one has been working for decades in farm animals’ pathology, and the other is a PhD student studying farm animals’ respiratory pathology) using the “ Pleurisy Evaluation on the Parietal Pleura ” method. The same veterinarians recorded lesions larger than 15 cm. The AI system detected pleurisy in 9.80% of pigs, demonstrating high specificity and sensitivity (> 95%) compared with veterinary assessments of digital images. Norwegian meat inspection staff reported pleurisy in 5.18% of pigs, showing a moderately strong correlation with the AI system (Spearman’s ρ = 0.67). Very large lesions were identified in 3.4-4.6% of digital images by veterinarians. Prevalence results aligned with historical data, being consistent with the high health status of Norwegian pig herds. Lesions were mainly located on the caudal chest wall, supporting Actinobacillus pleuropneumoniae as a major causative agent. This study highlights the potential of AI-driven tools to enhance disease surveillance, reduce observer variability, and facilitate large-scale data collection in slaughterhouse environments. • An AI-based system was evaluated for scoring pleurisy in pigs, under industrial abattoir conditions. • The AI-based system demonstrated good performance when compared to veterinary assessments. • The AI-based system outperformed routine scoring provided by the official meat inspection personell. • Data provide reliable prevalence of lesions indicative of Actinobacillus pleuropneumoniae infection in Norwegian pig herds.

Autonomous systems are increasingly exposed to emergent security threats that can impact their operational safety. Although anomaly detection techniques are widely used to identify these attacks, they are mostly validated in offline settings. This paper introduces an innovative attack detection system that leverages unsupervised learning for real-time deployment. The effectiveness of this system is confirmed through experimental validation on unmanned aerial vehicles during their operation.

ABSTRACT We present a timing study of the gamma and X-ray observations and analysis of a sample of bright gamma-ray bursts (GRBs; i.e. GRB 180720B, GRB 181222B, GRB 211211A, and GRB 220910A), including the very bright and long GRB 211211A (a.k.a. kilonova candidate). They have been detected and observed by the Atmosphere–Space Interactions Monitor (ASIM) installed on the International Space Station (ISS) and the Gamma-ray Burst Monitor (GBM) onboard the Fermi mission. The early (${\rm T}-{\rm T}_{0}{\approx }$ s) and high-energy (0.3–20 MeV) ASIM High Energy Detector (HED) and (150 keV–30 MeV) Fermi (BGO) light curves show well-defined peaks with a low quasi-periodic oscillation (QPO) frequency between 2.5 and 3.5 Hz that could be identified with the spin of the neutron star (NS) in the binary mergers originating these GRBs. These QPOs consist on the first detection of low-frequency QPOs (${\le }10$ Hz) detected in magnetars so far. We also detect a strong QPO at $21.8-22$ Hz in GRB 181222B together with its (less significant) harmonics. The low-frequency QPO would correspond to the signal of the orbiting NS previous to the final coalescence giving rise to the gravitational wave (GW) signal.

During ASIM operations from June 2018 until the end of 2019, 486 TGFs were observed. For this task, the ASDC (ASIM Science Data Center) dealt with numerous triggers from the instrument (5000 per week). The relocation of the instrument from EPF SDX to EPF SDN (Starboard Deck Nadir) of the Columbus ISS Module on January 10, 2022, demonstrated that the MXGS location capabilities could be used not only for TGF location but also for imaging GRB events, as its Field of View in the SDN port encompasses both Earth and space. It's worth noting that only a few of the ASIM triggers correspond to TGF events. There is a screening process employing a series of algorithms to detect and discard false positives (triggers that are not TGFs). Nevertheless, the ASIM archive retains all data from every trigger. Due to the extended operational time, there is currently a sufficiently large database that enables us to present the initial results here using novel machine learning methods, such as kernel methods or neural networks, for the automatic categorization of both present and future events. Furthermore, our interest goes beyond mere classification, as we are currently investigating whether various explainability methods applied to these techniques can assist in identifying the relevant features of the signal for such classification. The aim of this work is to provide a tool to quantify new physical processes that could be the cause of instrument triggers and to examine whether there is a connection with the Earth-Space global circuit.

An estimate of the height of the aurora is often required for the derivation or interpretation of other auroral or ionospheric parameters, such as horizontal spatial scales, velocities, neutral temperatures, or electron precipitation energies. We have performed a large statistical study of the peak emission height of coincident green 557.7 nm and blue 427.8 nm aurora using a network of ground-based all-sky cameras stationed in northern Finland and Sweden. We have obtained almost 58000 simultaneous measurements of both emissions between 2000 and 2007, and found that both emissions typically peak at about 114 km, but the distribution of peak emission heights is more skewed for blue aurora than for green aurora.During low-energy electron precipitation (< 4 keV), when the two emissions peak above about 110 km, it is more likely for the blue emission to peak above the green emission than vice-versa. Modelling has shown that this is because the dominant mechanism producing the O(1S) upper state of the green line is energy transfer from N2. The rate of that process depends on the product of the N2 and O number densities, which both decrease to higher altitude. The blue line is produced through electron impact ionisation of N2, and so depends on the N2 number density only, and consequently peaks below the green emission.During high-energy electron precipitation the two emissions typically peak at very similar altitude. In those circumstances, where the emissions peak below the peak in O number density, energy transfer from N2 must not be the dominant production mechanism of O(1S). Dissociative recombination of O2+ seems most likely to be the dominant mechanism, but modelling cannot fully reproduce observations and there may be an additional mechanism which is currently unaccounted for.The observations are best reproduced using a Maxwellian shaped electron precipitation spectrum at low energies, but a Gaussian shaped electron precipitation spectrum at high energies.

Abstract Inverse modeling has become one of the primary methods for studying ionospheric electrodynamics, especially when using magnetic field measurements from below the ionosphere. We present a method for quantifying the spatial resolution in an inverse model for non‐uniformly sampled spatial data. This method provides a tool for assessing if a model can resolve the physical phenomena of interest. We quantify the spatial resolution for the Spherical Elementary Current System basis functions to model the ionospheric dynamics. Our results apply to models with spatially confined model parameters, unlike spherical harmonics where the model parameters describe the amplitude of global surface functions. The method is demonstrated for the upcoming Electrojet Zeeman Imaging Explorer cubesat mission which will provide spatially distributed remote sensing measurements of the magnetic field in the mesosphere. We show that, including measurements from a single ground magnetometer can significantly improve the spatial resolution. However, the impact of including a ground magnetometer depends on the relative position of the station with respect to the mesospheric measurements. In addition, a method for reducing two regularization parameters to one is presented. Reducing the amount of regularization parameters simplifies the optimization problem and facilitates a fair comparison between the models with and without a ground magnetometer.

In the recent years, significant attention has been given to the combined effect of Interplanetary Magnetic Field (IMF) duskward component (By) and dipole tilt on the global magnetosphere-ionosphere system response. Numerous studies have pointed out that when the Earth’s magnetic dipole is tilted away from the Sun (negative dipole tilt during northern winter), and IMF has a positive By component, the effects on ionospheric currents, particle precipitation, ionospheric convection, and average size of the auroral oval, is significantly more enhanced, compared to when IMF By is negative. Furthermore, this IMF By polarity effect reverses when Earth’s dipole is tilted in the opposite direction. The underlying cause has remained unclear. Our analysis shows that substorms tend to be stronger during the same IMF By and dipole tilt polarity combination. Taken together with earlier results showing also more frequent substorms during the same conditions, our observations suggests that when IMF By and dipole tilt have opposite signs, there is a more efficient global dayside reconnection rate. We also show analysis of the occurrence frequency of periods of Steady Magnetospheric Convection, substorm onset latitude, and the isotropic boundary of proton precipitation, that are all consistent with our conclusion that the combination of IMF By and dipole tilt polarity affect the global dayside reconnection rate.

<strong class="journal-contentHeaderColor">Abstract.</strong> We investigate the bulk behaviour of auroral structures and peak emission height as a function of magnetic local time (MLT). These data are collected from the Fennoscandian Lapland and Svalbard latitudes from seven identical auroral all-sky cameras (ASC) over about one solar cycle. The analysis focusses on green auroral emission, which is where the morphology is most clearly visible and the number of images is the highest. The typical peak emission height of the green and blue aurora varies from 110 km on the nightside to about 118 km in the morning MLT over the Lapland region. It stays systematically higher (at 118–120 km) at high latitudes (Svalbard) during the nighttime and reaches 140 km at around magnetic noon. During high solar wind speed (above 500 <span class="inline-formula">km s^−1</span>), nightside emission heights appear about 5 km lower than during slow solar wind speed (below 400 <span class="inline-formula">km s^−1</span>). The sign of the interplanetary magnetic field (IMF) has nearly no effect on the emission heights in the night sector, but the northward IMF causes lower emission heights at dawn over Lapland and during the noon hours over Svalbard. While the former is interpreted as a change in the particle population within the field-of-view (FoV), the latter is rather due to the movement of the cusp location due to the IMF orientation. The morning sector heights also show a pronounced difference when previously detected pulsating aurora (PsA) events have been excluded/included in the dataset, suggesting that this type of aurora is a dominant phenomenon in the morning and an important dissipation mechanism. An increase of complex auroral structures in the midnight hours agrees with the average substorm occurrence. This increase is amplified during stronger solar wind driving and during higher geomagnetic activity (as measured by auroral electrojet index, AL). During high solar wind speed, the high latitude auroral evolution shows particularly complex morphology, which is not limited to the nightside but rather only excludes the magnetic noon hours. An increase in the geomagnetic activity further enhances the structural complexity of the aurora in the morning sector.

We investigated the morphology of poleward moving auroral forms (PMAFs) qualitatively by visual inspection of all sky camera (ASC) images and quantitatively using the arciness index. The PMAFs in this study were initially identified with a meridian scanning photometer located at Kjell Henriksen Observatory (KHO), Svalbard, and analyzed using ASC images taken by cameras at KHO and in Ny-Ålesund, Svalbard. We present a detailed six-step evolution of PMAF morphology in two dimensions. This evolution includes (1) an equatorward expansion of the auroral oval and an intensification of auroral brightness at the open-closed boundary, (2) the appearance of an arc-like structure in the oval, (3) poleward and possible west/eastward propagation, (4) azimuthal expansion events, (5) rebrightening of the PMAF and eventual (6) fading away. While there have been previous studies commenting on PMAF morphology this is the first work dedicated to the morphological evolution of PMAFs and it includes more detailed discussion and novel aspects, such as the observation of initial merging of 557.7 nm auroral patches to form a PMAF. Moreover, the morphology of PMAFs is quantified using the arciness index, which is a number describing how arc-like auroral forms appear in ASC images. We present the results of a superposed epoch analysis of arciness in relation to PMAF occurrence. This analysis uncovered that arciness increases suddenly during the onset of a PMAF event and decreases over the PMAF lifetime to return to its baseline value once the event has concluded. This behavior may be understood based on changes in the morphology of PMAFs and the auroral oval and furthermore may be used to identify PMAFs from arciness data.

Characteristics of pulsating aurora (PsA) at the equatorward part of the auroral oval have been well described in the literature by previous studies. We extend our knowledge on high-latitude PsA observations by analysing 68 PsA events from the optical observatory on Svalbard, at 75° magnetic latitude. We found that the pulsating emission structures are particularly large and transient, they do not experience drift motion, or their drift motion cannot be traced. Our results show that the high-latitude PsA events relate to lower geomagnetic activity and weaker solar wind driving than the lower latitude PsA. The high-latitude PsA events also occur less frequently, which is in agreement with their association to lower-than-average geomagnetic activity. We further show that the ionospheric electron density values during high-latitude PsA events are low compared to the lower latitude PsA. This, together with the non-traceable nature of the pulsating emission structures, suggests that these events are strongly dominated by a sub-type called Amorphous Pulsating Aurora (APA). We therefore conclude that, unlike the lower latitude PsA events, the high-latitude PsA events are not likely to cause direct changes in the chemical composition of the mesosphere.