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Reactions of the bicompartmental bis(phenolato) compound 6,6′-methylenebis(2-((bis(pyridin-2-ylmethyl)amino)methyl)-4-chlorophenol)hemihydrate (H 2 L ½H 2 O) with 3d metal( ii ) ions afforded novel fully structurally characterized bridged acetato dinuclear complexes [Mn 2 (HL)(μ 1,2 -OAc) 2 ]PF 6 (1) [Zn 2 (HL)(μ 1,2 -OAc)(H 2 O) 0.75 (MeOH) 0.25 ](PF 6 ) 2 ·0.45(H 2 O) (5) and [Cd 2 (HL)(μ 1,1,2 -OAc)(OAc)(H 2 O)]PF 6 ·H 2 O (6) as well as the polymeric bridged-azido tetranuclear catena -[Cu 4 (HL) 2 (μ 1,1 -N 3 ) 2 (μ 1,3 -N 3 ) 2 ](NO 3 ) 2 ·5H 2 O (4). The complex [Cu 4 (HL) 2 (ClO 4 ) 3 (H 2 O) 5 ](ClO 4 ) 3 ·5H 2 O (2) was partially characterized. In addition, three more dinuclear complexes [Cu 2 (H 2 L)(NO 3 ) 2 (H 2 O) 2 ](NO 3 ) 2 (3), [Cu 2 (HL)(OAc)(CH 3 OH)](PF 6 ) 2 (7) and [Cu 2 (HL)(NCS) 2 ]NO 3 ·2H 2 O (8) were also isolated. All complexes were characterized by CHN elemental analysis, IR and UV-Vis spectroscopy, ESI-MS, conductivity measurements and X-ray single crystal crystallography for compounds 1, 4, 5 and 6, where the bis(phenolato) ligand displayed different deprotonation (H 2 L, HL − and L 2− ). The magnetic susceptibility measurements over the temperature range 2–300 K revealed very weak antiferromagnetic coupling in dimanganese( ii ) 1 ( J = −1.64(1) cm −1 ) and almost negligible magnetic interaction in dicopper( ii ) 2 ( J = 0(3) cm −1 ). In the azido catena -[Cu 4 (HL) 2 (μ 1,1 -N 3 ) 2 (μ 1,3 -N 3 ) 2 ](NO 3 ) 2 ·5H 2 O (4) complex, the J value of −133(3) cm −1 was obtained upon moderate-to-strong antiferromagnetic coupling through the di-μ 1,3 -N 3 -bridged dicopper( ii ) unit with no magnetic interaction between the two copper( ii ) ions in the di-μ 1,1 -N 3 -bridged unit. 

Echinoderms are a phylum of marine invertebrates that include model organisms, keystone species, and animals commercially harvested for seafood. Despite their scientific, ecological, and economic importance, there is little known about the diversity of RNA viruses that infect echinoderms compared to other invertebrates. We screened over 900 transcriptomes and viral metagenomes to characterize the RNA virome of 38 echinoderm species from all five classes (Crinoidea, Holothuroidea, Asteroidea, Ophiuroidea and Echinoidea). We identified 347 viral genome fragments that were classified to genera and families within nine viral orders - Picornavirales, Durnavirales, Martellivirales, Nodamuvirales, Reovirales, Amarillovirales, Ghabrivirales, Mononegavirales, and Hepelivirales . We compared the relative viral representation across three life stages (embryo, larvae, adult) and characterized the gene content of contigs which encoded complete or near-complete genomes. The proportion of viral reads in a given transcriptome was not found to significantly differ between life stages though the majority of viral contigs were discovered from transcriptomes of adult tissue. This study illuminates the biodiversity of RNA viruses from echinoderms, revealing the occurrence of viral groups in natural populations. 

A<sc>bstract</sc> A measurement is performed of Higgs bosons produced with high transverse momentum (p_T) via vector boson or gluon fusion in proton-proton collisions. The result is based on a data set with a center-of-mass energy of 13 TeV collected in 2016–2018 with the CMS detector at the LHC and corresponds to an integrated luminosity of 138 fb⁻¹. The decay of a high-p_THiggs boson to a boosted bottom quark-antiquark pair is selected using large-radius jets and employing jet substructure and heavy-flavor taggers based on machine learning techniques. Independent regions targeting the vector boson and gluon fusion mechanisms are defined based on the topology of two quark-initiated jets with large pseudorapidity separation. The signal strengths for both processes are extracted simultaneously by performing a maximum likelihood fit to data in the large-radius jet mass distribution. The observed signal strengths relative to the standard model expectation are$$ {4.9}_{-1.6}^{+1.9} $$ ${4.9}_{-1.6}^{+1.9}$and$$ {1.6}_{-1.5}^{+1.7} $$ ${1.6}_{-1.5}^{+1.7}$for the vector boson and gluon fusion mechanisms, respectively. A differential cross section measurement is also reported in the simplified template cross section framework. 

Abstract Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors. 

Abstract A search is reported for charge-parity$$CP$$ $\mathrm{CP}$violation in$${{{\textrm{D}}}^{{0}}} \rightarrow {{\textrm{K}} _{\text {S}}^{{0}}} {{\textrm{K}} _{\text {S}}^{{0}}} $$ ${\text{D}}^0\to {\text{K}}_{\text{S}}^0{\text{K}}_{\text{S}}^0$decays, using data collected in proton–proton collisions at$$\sqrt{s} = 13\,\text {Te}\hspace{-.08em}\text {V} $$ $\sqrt{s}=13\text{Te}\text{V}$recorded by the CMS experiment in 2018. The analysis uses a dedicated data set that corresponds to an integrated luminosity of 41.6$$\,\text {fb}^{-1}$$ ${\text{fb}}^{-1}$, which consists of about 10 billion events containing a pair of b hadrons, nearly all of which decay to charm hadrons. The flavor of the neutral D meson is determined by the pion charge in the reconstructed decays$${{{\textrm{D}}}^{{*+}}} \rightarrow {{{\textrm{D}}}^{{0}}} {{{\mathrm{\uppi }}}^{{+}}} $$ $\text{D}_{}^{\ast +}\to {\text{D}}^0{\pi }^{+}$and$${{{\textrm{D}}}^{{*-}}} \rightarrow {\overline{{\textrm{D}}}^{{0}}} {{{\mathrm{\uppi }}}^{{-}}} $$ $\text{D}_{}^{\ast -}\to {\overline{\text{D}}}^0{\pi }^{-}$. The$$CP$$ $\mathrm{CP}$asymmetry in$${{{\textrm{D}}}^{{0}}} \rightarrow {{\textrm{K}} _{\text {S}}^{{0}}} {{\textrm{K}} _{\text {S}}^{{0}}} $$ ${\text{D}}^0\to {\text{K}}_{\text{S}}^0{\text{K}}_{\text{S}}^0$is measured to be$$A_{CP} ({{\textrm{K}} _{\text {S}}^{{0}}} {{\textrm{K}} _{\text {S}}^{{0}}} ) = (6.2 \pm 3.0 \pm 0.2 \pm 0.8)\%$$ $A_{\mathrm{CP}}\left({\text{K}}_{\text{S}}^0{\text{K}}_{\text{S}}^0\right)=(6.2\pm 3.0\pm 0.2\pm 0.8)\%$, where the three uncertainties represent the statistical uncertainty, the systematic uncertainty, and the uncertainty in the measurement of the$$CP$$ $\mathrm{CP}$asymmetry in the$${{{\textrm{D}}}^{{0}}} \rightarrow {{\textrm{K}} _{\text {S}}^{{0}}} {{{\mathrm{\uppi }}}^{{+}}} {{{\mathrm{\uppi }}}^{{-}}} $$ ${\text{D}}^0\to {\text{K}}_{\text{S}}^0{\pi }^{+}{\pi }^{-}$decay. This is the first$$CP$$ $\mathrm{CP}$asymmetry measurement by CMS in the charm sector as well as the first to utilize a fully hadronic final state. 

Abstract This paper describes theCombinesoftware package used for statistical analyses by the CMS Collaboration. The package, originally designed to perform searches for a Higgs boson and the combined analysis of those searches, has evolved to become the statistical analysis tool presently used in the majority of measurements and searches performed by the CMS Collaboration. It is not specific to the CMS experiment, and this paper is intended to serve as a reference for users outside of the CMS Collaboration, providing an outline of the most salient features and capabilities. Readers are provided with the possibility to runCombineand reproduce examples provided in this paper using a publicly available container image. Since the package is constantly evolving to meet the demands of ever-increasing data sets and analysis sophistication, this paper cannot cover all details ofCombine. However, the online documentation referenced within this paper provides an up-to-date and complete user guide. 

Abstract Surface meltwater accumulating on Antarctic ice shelves can drive fractures through to the ocean and potentially cause their collapse, leading to increased ice discharge from the continent. Implications of increasing surface melt for future ice shelf stability are inadequately understood. The southern Amery Ice Shelf has an extensive surface hydrological system, and we present data from satellite imagery and ICESat‐2 showing a rapid surface disruption there in winter 2019, covering ∼60 km². We interpret this as an ice‐covered lake draining through the ice shelf, forming an ice doline with a central depression reaching 80 m depth amidst over 36 m uplift. Flexural rebound modeling suggests 0.75 km³of water was lost. We observed transient refilling of the doline the following summer with rapid incision of a narrow meltwater channel (20 m wide and 6 m deep). This study demonstrates how high‐resolution geodetic measurements can explore critical fine‐scale ice shelf processes. 

Abstract The CERN LHC provided proton and heavy ion collisions during its Run 2 operation period from 2015 to 2018. Proton-proton collisions reached a peak instantaneous luminosity of 2.1× 10³⁴cm^-2s^-1, twice the initial design value, at √(s)=13 TeV. The CMS experiment records a subset of the collisions for further processing as part of its online selection of data for physics analyses, using a two-level trigger system: the Level-1 trigger, implemented in custom-designed electronics, and the high-level trigger, a streamlined version of the offline reconstruction software running on a large computer farm. This paper presents the performance of the CMS high-level trigger system during LHC Run 2 for physics objects, such as leptons, jets, and missing transverse momentum, which meet the broad needs of the CMS physics program and the challenge of the evolving LHC and detector conditions. Sophisticated algorithms that were originally used in offline reconstruction were deployed online. Highlights include a machine-learning b tagging algorithm and a reconstruction algorithm for tau leptons that decay hadronically.