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The eXtreme Multi-label Classification (XMC) problem seeks to find relevant labels from an exceptionally large label space. Most of the existing XMC learners focus on the extraction of semantic features from input query text. However, conventional XMC studies usually neglect the side information of instances and labels, which can be of use in many real-world applications such as recommendation systems and e-commerce product search. We propose Predicted Instance Neighborhood Aggregation (PINA), a data enhancement method for the general XMC problem that leverages beneficial side information. Unlike most existing XMC frameworks that treat labels and input instances as featureless indicators and independent entries, PINA extracts information from the label metadata and the correlations among training instances. Extensive experimental results demonstrate the consistent gain of PINA on various XMC tasks compared to the state-of-the-art methods: PINA offers a gain in accuracy compared to standard XR-Transformers on five public benchmark datasets. Moreover, PINA achieves a ∼ 5% gain in accuracy on the largest dataset LF-AmazonTitles-1.3M. Our implementation is publicly available https://github.com/amzn/pecos/ tree/mainline/examples/pina. 

The EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been designed to address the full scope of the proposed Electron Ion Collider (EIC) physics program as presented by the National Academy of Science and provide a deeper understanding of the quark–gluon structure of matter. To accomplish this, the ECCE detector offers nearly acceptance and energy coverage along with excellent tracking and particle identification. The ECCE detector was designed to be built within the budget envelope set out by the EIC project while simultaneously managing cost and schedule risks. This detector concept has been selected to be the basis for the EIC project detector. 

Applying enzymatic reactions to produce useful molecules is a central focus of chemical biology. Iron and 2-oxoglutarate (Fe/2OG) enzymes are found in all kingdoms of life and catalyze a broad array of oxidative transformations. Herein, we demonstrate that the activity of an Fe/2OG enzyme can be redirected when changing the targeted carbon hybridization from sp3 to sp2. During leucine 5-hydroxylase catalysis, installation of an olefin group onto the substrate redirects the Fe(IV)−oxo species reactivity from hydroxylation to asymmetric epoxidation. The resulting epoxide subsequently undergoes intramolecular cyclization to form the substituted piperidine, 2S,5S-hydroxypipecolic acid. 

The increasingly sophisticated at-home screening systems for obstructive sleep apnea (OSA), integrated with both contactless and contact-based sensing modalities, bring convenience and reliability to remote chronic disease management. However, the device pairing processes between system components are vulnerable to wireless exploitation from a noncompliant user wishing to manipulate the test results. This work presents SIENNA, an insider-resistant context-based pairing protocol. SIENNA leverages JADE-ICA to uniquely identify a user’s respiration pattern within a multi-person environment and fuzzy commitment for automatic device pairing, while using friendly jamming technique to prevent an insider with knowledge of respiration patterns from acquiring the pairing key. Our analysis and test results show that SIENNA can achieve reliable (> 90% success rate) device pairing under a noisy environment and is robust against the attacker with full knowledge of the context information. 

New results are presented on a high-statistics measurement of Collins and Sivers asymmetries of charged hadrons produced in deep inelastic scattering of muons on a transversely polarized ${}^6\mathrm{LiD}$target. The data were taken in 2022 with the COMPASS spectrometer using the 160 GeV muon beam at CERN, statistically balancing the existing data on transversely polarized proton targets. The first results from about two-thirds of the new data have total uncertainties smaller by up to a factor of three compared to the previous deuteron measurements. Using all the COMPASS proton and deuteron results, both the transversity and the Sivers distribution functions of the $u$and $d$quark, as well as the tensor charge in the measured $x$range are extracted. In particular, the accuracy of the $d$quark results is significantly improved. Published by the American Physical Society2024 

The COMPASS Collaboration performed measurements of the Drell-Yan process in 2015 and 2018 using a $190\mathrm{GeV}/c$ ${\pi }^{-}$beam impinging on a transversely polarized ammonia target. Combining the data of both years, we present final results on the amplitudes of five azimuthal modulations, which correspond to transverse-spin-dependent azimuthal asymmetries (TSAs) in the dimuon production cross section. Three of them probe the nucleon leading-twist Sivers, transversity, and pretzelosity transverse-momentum dependent (TMD) parton distribution functions (PDFs). The other two are induced by subleading effects. These TSAs provide unique new inputs for the study of the nucleon TMD PDFs and their universality properties. In particular, the Sivers TSA observed in this measurement is consistent with the fundamental QCD prediction of a sign change of naive time-reversal-odd TMD PDFs when comparing the Drell-Yan process with deep inelastic scattering. Also, within the context of model predictions, the observed transversity TSA is consistent with the expectation of a sign change for the Boer-Mulders function. Published by the American Physical Society2024