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At least 721 records · Page 40

Configuration and performance of the ATLAS b -jet triggers in Run 2

Several improvements to the ATLAS triggers used to identify jets containing b-hadrons (b-jets) were implemented for data-taking during Run 2 of the Large Hadron Collider from 2016 to 2018. These changes include reconfiguring the b-jet trigger software to improve primary-vertex finding and allow more stable running in conditions with high pile-up, and the implementation of the functionality needed to run sophisticated taggers used by the offline reconstruction in an online environment. These improvements yielded an order of magnitude better light-flavour jet rejection for the same b-jet identification efficiency compared to the performance in Run 1 (2011–2012). The efficiency to identify b-jets in the trigger, and the conditional efficiency for b-jets that satisfy offline b-tagging requirements to pass the trigger are also measured. Correction factors are derived to calibrate the b-tagging efficiency in simulation to match that observed in data. The associated systematic uncertainties are substantially smaller than in previous measurements. In addition, b-jet triggers were operated for the first time during heavy-ion data-taking, using dedicated triggers that were developed to identify semileptonic b-hadron decays by selecting events with geometrically overlapping muons and jets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Observation of seasonal variations of the flux of high-energy atmospheric neutrinos with IceCube

Atmospheric muon neutrinos are produced by meson decays in cosmic-ray-induced air showers. The flux depends on meteorological quantities such as the air temperature, which affects the density of air. Competition between decay and re-interaction of those mesons in the first particle production generations gives rise to a higher neutrino flux when the air density in the stratosphere is lower, corresponding to a higher temperature. A measurement of a temperature dependence of the atmospheric νμ flux provides a novel method for constraining hadronic interaction models of air showers. It is particularly sensitive to the production of kaons. Studying this temperature dependence for the first time requires a large sample of high-energy neutrinos as well as a detailed understanding of atmospheric properties. We report the significant (> 10 σ) observation of a correlation between the rate of more than 260,000 neutrinos, detected by IceCube between 2012 and 2018, and atmospheric tem peratures of the stratosphere, measured by the Atmospheric Infrared Sounder (AIRS) instrument aboard NASA’s AQUA satellite. For the observed 10% seasonal change of effective atmospheric temperature we measure a 3.5(3)% change in the muon neutrino flux. This observed correlation deviates by about 2-3 standard deviations from the expected correla tion of 4.3% as obtained from theoretical predictions under the assumption of various hadronic interaction models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A precise measurement of the Z -boson double-differential transverse momentum and rapidity distributions in the full phase space of the decay leptons with the ATLAS experiment at $\sqrt{s}=8$ TeV

This paper presents for the first time a precise measurement of the production properties of the Z boson in the full phase space of the decay leptons. This is in contrast to the many previous precise unfolded measurements per formed in the fiducial phase space of the decay leptons. The measurement is obtained from proton–proton collision data collected by the ATLAS experiment in 2012 at $\sqrt{s}$ = 8 TeV at the LHC and corresponding to an integrated luminosity of 20.2 fb -1 . The results, based on a total of 15.3 million Z boson decays to electron and muon pairs, extend and improve a previous measurement of the full set of angular coefficients describing Z-boson decay. The double-differential cross section distributions in Z-boson transverse momentum pT and rapidity y are measured in the pole region, defined as 80 < m ℓℓ < 100 GeV, over the range |y| < 3.6. The total uncertainty of the normalised cross-section measurements in the peak region of the pT distribution is dominated by statistical uncertainties over the full range and increases as a function of rapidity from 0.5–1.0% for |y| < 2.0 to 2 - 7% at higher rapidities. The results for the rapidity-dependent transverse momentum distributions are compared to state of-the-art QCD predictions, which combine in the best cases approximate N 4 LL resummation with N 3 LO fixed-order per turbative calculations. The differential rapidity distributions integrated over pT are even more precise, with accuracies from 0.2–0.3% for |y| < 2.0 to 0.4–0.9% at higher rapidities, and are compared to fixed-order QCD predictions using the most recent parton distribution functions. The agreement between data and predictions is quite good in most cases.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for Θ+ in KLp→K+n reaction in KLF at JLab

The possibility of the existence of multiquark hadrons made of 4-quarks for mesons and 5-quarks for baryons was predicted by Gell-Mann [Phys. Lett. 8, 214 (1964)]. The renewed interest for the search for exotic pentaquark states was initiated by the paper by Diakonov, Petrov, and Polyakov [Z. Phys. A 359, 305 (1997)]. The 2003 experimental reports on the observation of [Formula: see text] pentaquark with [Formula: see text] quark content created a great excitement and many following experiments have reported its observation [K. H. Hicks, Eur. Phys. J. H 37, 1 (2012)]. After high-statistics experiments at JLab, which did not confirm previous claims by the CLAS collaboration, the community concluded that the [Formula: see text] pentaquark either does not exist at all or has an extremely small cross-section, making it currently unobserved. There were different review papers on this subject, questioning the existence of [Formula: see text] or trying to explain the reasons why reaching a conclusion based on production experiments is challenging [M. Amaryan, Eur. Phys. J. Plus 137, 684 (2022)]. To address the challenge of minimal 3-body final states, a formation experiment with a projectile-kaon beam is proposed. In the following, we discuss how the [Formula: see text] could be observed in the [Formula: see text] reaction in the KLF experiment at JLab [M. Amaryan et al. [KLF Collaboration], arXiv:2008.08215 [nucl-ex]].

Astronomy & Astrophysics↗

kynema-fmb [SWR-23-07]

Kynema-FMB (FKA: Kynema) is an open-source performance portable flexible multibody (FMB) dynamics solver designed for time-domain simulations. While originally tailored for wind turbine structural dynamics, the formulation and implementation are those of a general flexible-multidbody dynamics solver that can readily be applied to a wide range of systems. Kynema was designed with a narrow focus, namely to provide a lightweight, fast, accurate FMD solver for coupling to computational-fluid-dynamics (CFD) codes, especially the CFD codes in the Kynema suite, for fluid-structure-interaction (FSI) simulations. Kynema-FMB is equipped to model systems that can be represented as a collection of beams and rigid bodies that are connected through constraints. Degrees of freedom are defined in the inertial/global frame of reference and include displacements and rotations (formally as rotation matrices, but stored as quaternions). The underlying formulation is built on a Lie-group time integrator designed for index-3 differential-algebraic equations, which is second-order accurate in time (Bruls et al., 2012). Beam models are based on geometrically exact beam theory and are discretized as high-order spectral finite elements similar to those in BeamDyn (Wang et al., 2017). The governing equations for a FMD system like a wind turbine constitute a highly nonlinear system of constrained partial-differential equations. Kynema-FMB uses analytical Jacobians in the nonlinear-system solves in each time step. Linear systems use sparse storage and several third-party sparse-linear-system solvers are enabled. Ill conditioning of linear systems is mitigated with preconditioning described in Bottasso et al, 2008. Kynema-FMB is integrated with a simple open-source controller (ROSCO). There is an application programming interface (API) for coupling to geometry-resolved CFD (like that in Sharma et al., 2023) and actuator-force CFD (like that in Kuhn et al., 2025). In the latter, for actuator-line models, Kynema-FMB includes an internal blade-element solver that depends on user-provided lookup tables for coefficients of lift and drag, i.e., aerodynamic polars. Kynema-FMB is written in C++ and leverages Kokkos and Kokkos-Kernels (KokkosEcosystem) as its performance portability layer enabling simulations on both CPU and GPU systems. The repository is equipped with extensive automated testing at the unit and regression/system levels. The following describes the high-level development objectives conceived for Kynema: *Kynema will follow modern software development best practices, including test-driven development (TDD), version control, hierarchical automated testing, and continuous integration (CI) for a robust development environment. *The core data structures are memory efficient and enable vectorization and parallelization at multiple levels. *Data structures are data-oriented to exploit methods for accelerated computing including high utilization of chip resources (e.g., single instruction multiple data (SIMD) instruction sets) and parallelization using GP-GPUs. *The computational algorithms incorporate robust open-source libraries for mathematical operations, resource allocation, and data management. *The API design considers multiple stakeholder needs and ensure integration with existing and future ecosystems for data science, machine learning, and AI. *Kynema-FMB is written in modern C++ and leverages Kokkos as its performance-portability library with inspiration from the kynema stack.

Sprague, MichaelA.↗

Predicting September Arctic Sea Ice: A Multimodel Seasonal Skill Comparison

This study quantifies the state of the art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multimodel dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 17 dynamical models. Prediction skill is compared over the period 2001–20 for predictions of pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on 1 June, 1 July, 1 August, and 1 September. This diverse set of statistical and dynamical models can individually predict linearly detrended pan-Arctic SIE anomalies with skill, and a multimodel median prediction has correlation coefficients of 0.79, 0.86, 0.92, and 0.99 at these respective initialization times. Regional SIE predictions have similar skill to pan-Arctic predictions in the Alaskan and Siberian regions, whereas regional skill is lower in the Canadian, Atlantic, and central Arctic sectors. The skill of dynamical and statistical models is generally comparable for pan-Arctic SIE, whereas dynamical models outperform their statistical counterparts for regional and local predictions. The prediction systems are found to provide the most value added relative to basic reference forecasts in the extreme SIE years of 1996, 2007, and 2012. SIE prediction errors do not show clear trends over time, suggesting that there has been minimal change in inherent sea ice predictability over the satellite era. Overall, this study demonstrates that there are bright prospects for skillful operational predictions of September sea ice at least 3 months in advance.

54 ENVIRONMENTAL SCIENCES↗

Characteristics of Ice Cloud–Precipitation of Warm Season Mesoscale Convective Systems over the Great Plains

Abstract In this study, the mesoscale convective systems (MCSs) are tracked using high-resolution radar and satellite observations over the U.S. Great Plains during April–August from 2010 to 2012. The spatiotemporal variability of MCS precipitation is then characterized using the Stage IV product. We found that the spatial variability and nocturnal peaks of MCS precipitation are primarily driven by the MCS occurrence rather than the precipitation intensity. The tracked MCSs are further classified into convective core (CC), stratiform rain (SR), and anvil clouds regions. The spatial variability and diurnal cycle of precipitation in the SR regions of MCSs are not as significant as those of MCS precipitation. In the SR regions, the high-resolution, long-term ice cloud microphysical properties [ice water content (IWC) and ice water paths (IWPs)] are provided. The IWCs generally decrease with height. Spatially, the IWC, IWP, and precipitation are all higher over the southern Great Plains than over the northern Great Plains. Seasonally, those ice and precipitation properties are all higher in summer than in spring. Comparing the peak timings of MCS precipitation and IWPs from the diurnal cycles and their composite evolutions, it is found that when using the peak timing of IWPSR as a reference, the heaviest precipitation in the MCS convective core occurs earlier, while the strongest SR precipitation occurs later. The shift of peak timings could be explained by the stratiform precipitation formation process. The IWP and precipitation relationships are different at MCS genesis, mature, and decay stages. The relationships and the transition processes from ice particles to precipitation also depend on the low-level humidity.

54 ENVIRONMENTAL SCIENCES↗

Examining Rail Transportation Route of Crude Oil in the United States Using Crowdsourced Social Media Data

Safety issues associated with transporting crude oil by rail have been a concern since the boom of the U.S. domestic shale oil production in 2012. During the last decade, over 300 crude-oil-by-rail incidents have occurred in the United States. Some of them have caused adverse consequences including fire and hazardous materials leakage. However, only limited information on crude-on-rail routes and their associated risks is available to the public. To this end, this study proposed an unconventional way to reconstruct crude-on-rail routes using geotagged photos harvested from the Flickr website. The proposed method linked the geotagged photos of crude oil trains posted online with national railway networks to identify potential railway segments that those crude oil trains were traveling on. Here, a shortest path-based method was applied to infer the complete crude-on-rail routes, by utilizing the confirmed railway segments as well as their directional information. Validation of the inferred routes was performed using a public map and official crude oil incident data. The results suggested that the inferred routes based on geotagged photos had high coverage, with approximately 96% of the documented crude oil incidents aligned with the reconstructed crude-on-rail network. The inferred crude oil train routes were found to pass through several metropolitan areas of high population density, who were exposed to potential risk. These findings could improve situational awareness for policy makers and transportation planners. In addition, with the inferred routes, this study has established a good foundation for future crude oil train risk-analyses along the rail route.

42 ENGINEERING↗

Contraceptive Sabotage and Contraceptive Use at the Time of Pregnancy: An Analysis of People with a Recent Live Birth in the United States

Contraceptive sabotage and other forms of intimate partner violence (IPV) can interfere with contraceptive use. We used 2012 to 2015 Pregnancy Risk Assessment Monitoring System data from 8,981 people residing in five states who reported that when they became pregnant, they were not trying to get pregnant. We assessed the relationships between ever experiencing contraceptive sabotage and physical IPV 12 months before pregnancy (both by the current partner) and contraceptive use at the time of pregnancy using multivariable logistic regression. We also assessed the joint associations between physical IPV 12 months before pregnancy and ever experienced contraceptive sabotage with contraceptive use at the time of pregnancy. Few people ever experienced contraceptive sabotage (1.8%; 95% confidence interval [CI]: 1.4, 2.3) or physical IPV 12 months before pregnancy (2.8%; 95% CI: 2.3, 3.3). In models adjusted for age, race/ethnicity, marital status, education, and state of residence, ever experiencing contraceptive sabotage was associated with contraceptive use at the time of pregnancy (adjusted odds ratio [aOR]: 1.73; 95% CI: 1.06, 2.82), but not with physical IPV 12 months before pregnancy (aOR: 0.69; 95% CI: 0.46, 1.02). When examining the joint association, compared to not ever experiencing contraceptive sabotage or physical IPV 12 months before pregnancy, ever experiencing contraceptive sabotage was significantly related to contraceptive use at the time of pregnancy (aOR: 1.72; 95% CI: 1.00, 2.95). However, it was not associated with experiencing physical IPV 12 months before pregnancy (aOR: 0.68; 95% CI: 0.45, 1.04) or with experiencing both contraceptive sabotage and physical IPV 12 months before pregnancy (aOR: 1.21; 95% CI: 0.42, 3.50), compared to not ever experiencing contraceptive sabotage or physical IPV 12 months before pregnancy. Our study highlights that current partner contraceptive sabotage may motivate those not trying to get pregnant to use contraception; however, all people in our sample still experienced a pregnancy.

Huber-Krum, Sarah↗

Analysis of the first ten years of FDA’s rare pediatric disease priority review voucher program: designations, diseases, and drug development

Abstract Background The Rare Pediatric Disease (RPD) Priority Review Voucher (PRV) Program was enacted in 2012 to support the development of new products for children. Prior to requesting a voucher, applicants can request RPD designation, which confirms their product treats or prevents a rare disease in which the serious manifestations primarily affect children. This study describes the trends and characteristics of these designations. Details of RPD designations are not publicly disclosable; this research represents the first analysis of the RPD designation component of the program. Results We used an internal US Food and Drug Administration database to analyze all RPD designations between 2013 and 2022. Multiple characteristics were analyzed, including the diseases targeted by RPD designation, whether the product targeted a neonatal disease, product type (drug/biologic), and the level of evidence (preclinical/clinical) to support designation. There were 569 RPD designations during the study period. The top therapeutic areas were neurology (26%, n = 149), metabolism (23%, n = 131), oncology (18%, n = 105). The top diseases targeted by RPD designation were Duchenne muscular dystrophy, neuroblastoma, and sickle cell disease. Neonatology products represented 6% (n = 33), over half were for drug products and 38% were supported by clinical data. Conclusions The RPD PRV program was created to encourage development of new products for children. The results of this study establish that a wide range of diseases have seen development—from rare pediatric cancers to rare genetic disorders. Continued support of product development for children with rare diseases is needed to find treatments for all children with unmet needs.

Mease, Catherine (ORCID:000900050156198X)↗

Water-soluble saponins accumulate in drought-stressed switchgrass and may inhibit yeast growth during bioethanol production

Abstract Background Developing economically viable pathways to produce renewable energy has become an important research theme in recent years. Lignocellulosic biomass is a promising feedstock that can be converted into second-generation biofuels and bioproducts. Global warming has adversely affected climate change causing many environmental changes that have impacted earth surface temperature and rainfall patterns. Recent research has shown that environmental growth conditions altered the composition of drought-stressed switchgrass and directly influenced the extent of biomass conversion to fuels by completely inhibiting yeast growth during fermentation. Our goal in this project was to find a way to overcome the microbial inhibition and characterize specific compounds that led to this inhibition. Additionally, we also determined if these microbial inhibitors were plant-generated compounds, by-products of the pretreatment process, or a combination of both. Results Switchgrass harvested in drought (2012) and non-drought (2010) years were pretreated using Ammonia Fiber Expansion (AFEX). Untreated and AFEX processed samples were then extracted using solvents (i.e., water, ethanol, and ethyl acetate) to selectively remove potential inhibitory compounds and determine whether pretreatment affects the inhibition. High solids loading enzymatic hydrolysis was performed on all samples, followed by fermentation using engineered Saccharomyces cerevisiae . Fermentation rate, cell growth, sugar consumption, and ethanol production were used to evaluate fermentation performance. We found that water extraction of drought-year switchgrass before AFEX pretreatment reduced the inhibition of yeast fermentation. The extracts were analyzed using liquid chromatography–mass spectrometry (LC–MS) to detect compounds enriched in the extracted fractions. Saponins, a class of plant-generated triterpene or steroidal glycosides, were found to be significantly more abundant in the water extracts from drought-year (inhibitory) switchgrass. The inhibitory nature of the saponins in switchgrass hydrolysate was validated by spiking commercially available saponin standard (protodioscin) in non-inhibitory switchgrass hydrolysate harvested in normal year. Conclusions Adding a water extraction step prior to AFEX-pretreatment of drought-stressed switchgrass effectively overcame inhibition of yeast growth during bioethanol production. Saponins appear to be generated by the plant as a response to drought as they were significantly more abundant in the drought-stressed switchgrass water extracts and may contribute toward yeast inhibition in drought-stressed switchgrass hydrolysates.

59 BASIC BIOLOGICAL SCIENCES↗

Relationship Between Radiation Dose and Markers of Insulin Resistance and Inflammation in Atomic Bomb Survivors

Abstract Context In recent studies of childhood cancer survivors, diabetes has been considered a late effect associated with high therapeutic doses of radiation therapy. Our recent study of atomic bomb (A-bomb) survivors also suggested an association between radiation dose and diabetes incidence, with exposure city and age at exposure as radiation dose effect modifiers. Insulin resistance mediated by systemic inflammation and abnormal body composition has been suggested as a possible primary mechanism for the incidence of diabetes after total body irradiation; however, no studies have examined low to moderate radiation exposure (<4 Gy) and insulin resistance in A-bomb survivors. Objective To examine the association between radiation dose and markers of inflammation and insulin resistance. Methods This study investigated 3152 survivors who underwent a health examination between 2008 and 2012 and who were younger than 15 years at exposure. Multivariate linear regression analyses were used to evaluate the radiation effects on levels of markers of inflammation and insulin resistance. Results Radiation dose was significantly and positively associated with levels of C-reactive protein, triglycerides, homeostasis model assessment of β-cell function (HOMA-β), and HOMA of insulin resistance (HOMA-IR) after adjustment for relevant covariates including sex, city, and age at exposure. Adiponectin and high-density lipoprotein cholesterol levels were also associated significantly and negatively with radiation dose. However, city was not a dose modifier of the radiation response on these markers of inflammation and insulin resistance. Conclusion Insulin resistance might be a possible factor in radiation-related diabetes incidence in A-bomb survivors.

Endocrinology & Metabolism↗

Cylinders’ percolation: Decoupling and applications

In this paper we establish a strong decoupling inequality for the cylinder’s percolation process introduced by Tykesson and Windisch (Probab. Theory Related Fields 154 (2012) 165–191). This model features a very strong dependency structure, making it difficult to study, and this is why such decoupling inequalities are desirable. It is important to notice that the type of dependencies featured by cylinder’s percolation is particularly intricate, given that the cylinders have infinite range (unlike some models like Boolean percolation) while at the same time being rigid bodies (unlike processes such as random interlacements). Here our work introduces a new notion of fast decoupling, proves that it holds for the model in question and finishes with an application. More precisely, we prove that for a small enough density of cylinders, a random walk on a connected component of the vacant set is transient for all dimensions d≥3.

97 MATHEMATICS AND COMPUTING↗

Data for Aboveground rather than belowground productivity drives variability in Miscanthus x giganteus net primary productivity

This dataset contains the data used for the publication “Aboveground rather than belowground productivity drives variability in Miscanthus x giganteus net primary productivity”. This dataset contains Miscanthus x giganteus biomass, carbon, and nitrogen tissue data for aboveground and belowground plant parts collected in 2021 for three different sites in Iowa with three different nitrogen application rates. Data at the Iowa sites were collected via biometric hand harvesting, belowground excavations, and soil coring both in-clump and beside-clump. Data were collected at two collection timepoints to calculate the contributions of belowground parts to Miscanthus x giganteus net primary productivity. This dataset also includes Miscanthus x giganteus and Switchgrass soil coring and excavation data collected in 2012 at the University of Illinois Urbana Champaign Energy Farm.

Belowground Biomass↗

Tokenized Data for FORGE Foundation Models

This dataset comprises a vast corpus of 257 billion tokens, accompanied by the corresponding vocabulary file employed in the pre-training of FORGE foundation models. The primary data source for this corpus is scientific documents derived from diverse origins, and they have been tokenized using the Hugging Face BPE tokenizer. Further details about this research can be found in the publication titled FORGE: Pre-Training Open Foundation Models for Science authored by Junqi Yin, Sajal Dash, Feiyi Wang, and Mallikarjun (Arjun) Shankar, presented at SC'23. The data tokenization pipeline and resulting artifacts use CORE data [Ref: Knoth, P., and Zdrahal, Z. (2012). CORE: three access levels to underpin open access. D-Lib Magazine, 18(11/12)]. For use of these data sets for any purpose, please follow the guidelines provided in https://core.ac.uk/terms .

Yin, Junqi↗

NAPAbench 2: A network synthesis algorithm for generating realistic protein-protein interaction (PPI) network families

Comparative network analysis provides effective computational means for gaining novel insights into the structural and functional compositions of biological networks. In recent years, various methods have been developed for biological network alignment, whose main goal is to identify important similarities and critical differences between networks in terms of their topology and composition. A major impediment to advancing network alignment techniques has been the lack of gold-standard benchmarks that can be used for accurate and comprehensive performance assessment of such algorithms. The original NAPAbench (network alignment performance assessment benchmark) was developed to address this problem, and it has been widely utilized by many researchers for the development, evaluation, and comparison of novel network alignment techniques. In this work, we introduce NAPAbench 2—a major update of the original NAPAbench that was introduced in 2012. NAPAbench 2 includes a completely redesigned network synthesis algorithm that can generate protein-protein interaction (PPI) network families whose characteristics closely match those of the latest real PPI networks. Furthermore, the network synthesis algorithm comes with an intuitive GUI that allows users to easily generate PPI network families with an arbitrary number of networks of any size, according to a flexible user-defined phylogeny. In addition, NAPAbench 2 provides updated benchmark datasets—created using the redesigned network synthesis algorithm—which can be used for comprehensive performance assessment of network alignment algorithms and their scalability.

42 ENGINEERING↗

Characterizing juvenile salmon predation risk during early marine residence

Predation mortality can influence the distribution and abundance of fish populations. While predation is often assessed using direct observations of prey consumption, potential predation can be predicted from co-occurring predator and prey densities under varying environmental conditions. Juvenile Pacific salmon Oncorhynchus spp. (i.e., smolts) from the Columbia River Basin experience elevated mortality during the transition from estuarine to ocean habitat, but a thorough understanding of the role of predation remains incomplete. We used a Holling type II functional response to estimate smolt predation risk based on observations of piscivorous seabirds (sooty shearwater [ Ardenna griseus ] and common murre [ Uria aalge ]) and local densities of alternative prey fish including northern anchovy ( Engraulis mordax ) in Oregon and Washington coastal waters during May and June 2010–2012. We evaluated predation risk relative to the availability of alternative prey and physical factors including turbidity and Columbia River plume area, and compared risk to returns of adult salmon. Seabirds and smolts consistently co-occurred at sampling stations throughout most of the study area (mean = 0.79 ± 0.41, SD), indicating that juvenile salmon are regularly exposed to avian predators during early marine residence. Predation risk for juvenile coho ( Oncorhynchus kisutch ), yearling Chinook salmon ( O . tshawytscha ), and subyearling Chinook salmon was on average 70% lower when alternative prey were present. Predation risk was greater in turbid waters, and decreased as water clarity increased. Juvenile coho and yearling Chinook salmon predation risk was lower when river plume surface areas were greater than 15,000 km 2 , while the opposite was estimated for subyearling Chinook salmon. These results suggest that plume area, turbidity, and forage fish abundance near the mouth of the Columbia River, all of which are influenced by river discharge, are useful indicators of potential juvenile salmon mortality that could inform salmonid management.

Phillips, Elizabeth M. (ORCID:0000000327752563)↗

High-resolution hypernuclear decay pion spectroscopy at MAMI and future

Hypernuclear decay pion spectroscopy was established in 2012 at MAMI as a mass spectroscopy method for light hypernuclei. A monochromatic pion peak from $^4_Λ$H was successfully observed, and the Λ binding energy was determined to be B Λ = 2.157±0.005(stat.)±0.077(syst.) MeV in the 2014 run. In 2022, an upgrade experiment for $^3_Λ$H spectroscopy was conducted using a newly developed Li target. The absolute electron beam energy will be measured by the synchrotron radiation interferometry, which will be applied with the spectrometer calibration to improve the systematic error. The decay pion spectroscopy is planned to be performed at JLab Hall-C, which would significantly increase the statistics thanks to the higher energy beam, the better K + identification, and the faster data acquisition system. This experiment has been submitted as a Letter of Intent in JLab PAC51. The upgraded decay pion spectroscopy method is expected to provide new, accurate hypernuclear data, which will contribute to the advancement of our understanding of hypernuclear physics

47 OTHER INSTRUMENTATION↗