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There has been continuous and growing interest in edible insects. Worldwide, various levels of insect farming are emerging, ranging from small domestic farms to vertical farms reaching heights of 36 meters, accommodating several million growing insects. The appeal of insects lies in their ecological benefits, as they contribute to the valorization of underutilized organic residues while requiring minimal space and water. The selection of insect species is influenced not only by their biology and behavior but also by local preferences and customs, varying with the scale of production and geographical location. This review article aims to provide an updated overview of the main insect species produced across different continents, their current level of industrialization, and production prospects based on available literature. 

We consider the problem of online learning in the linear contextual bandits setting, but in which there are also strong individual fairness constraints governed by an unknown similarity metric. These constraints demand that we select similar actions or individuals with approximately equal probability, which may be at odds with optimizing reward, thus modeling settings where profit and social policy are in tension. We assume we learn about an unknown Mahalanobis similarity metric from only weak feedback that identifies fairness violations, but does not quantify their extent. This is intended to represent the interventions of a regulator who “knows unfairness when he sees it” but nevertheless cannot enunciate a quantitative fairness metric over individuals. Our main result is an algorithm in the adversarial context setting that has a number of fairness violations that depends only logarithmically on T, while obtaining an optimal O(√T) regret bound to the best fair policy. 

A search for proton decay into $e^{+}/{\mu }^{+}$and a $\eta$meson has been performed using data from a $0.373\mathrm{Mton}·\mathrm{year}$exposure (6050.3 live days) of Super-Kamiokande. Compared to previous searches this work introduces an improved model of the intranuclear $\eta$interaction cross section, resulting in a factor of 2 reduction in uncertainties from this source and $\sim 10\%$increase in signal efficiency. No significant data excess was found above the expected number of atmospheric neutrino background events resulting in no indication of proton decay into either mode. Lower limits on the proton partial lifetime of $1.4\times {10}^{34}\mathrm{years}$for $p\to e^{+}\eta$and $7.3\times {10}^{33}\mathrm{years}$for $p\to {\mu }^{+}\eta$at the 90% CL were set. These limits are around 1.5 times longer than our previous study and are the most stringent to date. Published by the American Physical Society2024 

We present the results of the charge ratio ( $R$) and polarization ( $P_0^{\mu }$) measurements using decay electron events collected between September 2008 and June 2022 with the Super-Kamiokande detector. Because of its underground location and long operation, we are able to perform high-precision measurements by accumulating cosmic-ray muons. We measured the muon charge ratio to be $R=1.32\pm 0.02(\mathrm{stat}+\mathrm{syst})$at $E_{\mu }\cos {\theta }_{\text{Zenith}}={0.7}_{-0.2}^{+0.3}\mathrm{TeV}$, where $E_{\mu }$is the muon energy and ${\theta }_{\text{Zenith}}$is the zenith angle of incoming cosmic-ray muons. This result is consistent with the Honda flux model while indicating a tension with the $\pi K$model of $1.9\sigma$. We also measured the muon polarization at the production location to be $P_0^{\mu }=0.52\pm 0.02(\mathrm{stat}+\mathrm{syst})$at the muon momentum of ${0.9}_{-0.1}^{+0.6}\mathrm{TeV}/c$at the surface of the mountain; this also suggests a tension with the Honda flux model of $1.5\sigma$. This is the most precise measurement ever to experimentally determine the cosmic-ray muon polarization near $1\mathrm{TeV}/c$. These measurement results are useful to improve atmospheric neutrino simulations. Published by the American Physical Society2024 

Abstract The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours. 

The determination of the direction of a stellar core collapse via its neutrino emission is crucial for the identification of the progenitor for a multimessenger follow-up. A highly effective method of reconstructing supernova directions within the Deep Underground Neutrino Experiment (DUNE) is introduced. The supernova neutrino pointing resolution is studied by simulating and reconstructing electron-neutrino charged-current absorption on ${}^{40}\mathrm{Ar}$and elastic scattering of neutrinos on electrons. Procedures to reconstruct individual interactions, including a newly developed technique called “brems flipping,” as well as the burst direction from an ensemble of interactions are described. Performance of the burst direction reconstruction is evaluated for supernovae happening at a distance of 10 kpc for a specific supernova burst flux model. The pointing resolution is found to be 3.4 degrees at 68% coverage for a perfect interaction-channel classification and a fiducial mass of 40 kton, and 6.6 degrees for a 10 kton fiducial mass respectively. Assuming a 4% rate of charged-current interactions being misidentified as elastic scattering, DUNE’s burst pointing resolution is found to be 4.3 degrees (8.7 degrees) at 68% coverage. Published by the American Physical Society2025 

The Super-Kamiokande and T2K Collaborations present a joint measurement of neutrino oscillation parameters from their atmospheric and beam neutrino data. It uses a common interaction model for events overlapping in neutrino energy and correlated detector systematic uncertainties between the two datasets, which are found to be compatible. Using 3244.4 days of atmospheric data and a beam exposure of $19.7\left(16.3\right)\times {10}^{20}$protons on target in (anti)neutrino mode, the analysis finds a $1.9\sigma$exclusion of $CP$conservation (defined as $J_{CP}=0$) and a $1.2\sigma$exclusion of the inverted mass ordering. Published by the American Physical Society2025