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Increasing shares of microfibers are being detected in environmental samples and a closer look to identify the risk associated with them using ecologically relevant endpoints, especially at sensitive early life stages, is needed. To assess exposure hazards, we used rope samples representative of fiber types ubiquitous in coastal systems, where microfibers are often the most common debris type found in the water column. To compare responses to natural vs. synthetic microfibers, we used rinsed “natural” cotton, polyester, and polypropylene microfibers (80-150 µm length, 8-20 µm width) created from the rope. Larval and juvenile estuarine indicator species Inland Silverside (Menidia beryllina) and mysid shrimp (Americamysis bahia) , respectively, were exposed to these three microfiber types at three concentrations (3, 10, 30 particles/ml) along a 5-25 PSU salinity gradient to mimic estuarine conditions. Behavioral responses, growth, and ingestion were measured. The cotton microfibers were not detected in the digestive tracts of Silversides, however, both the polyester and polypropylene microfibers were detected in the Silversides’ stomach and gut lining. None of the fiber types were detected in mysid shrimps. Mysids exposed to cotton microfibers had fewer behavioral effects compared to Silversides, who responded more to cotton. Cotton exerted no effect on growth in Silversides but did cause reduced growth in the mysids at the two lower salinities. In contrast, polyester and polypropylene were identified to have a significant dose dependent effect on mysid and Silverside behavior as well as growth was affected in at least one of the three salinities at concentrations as low as 3 particles/ml. Cotton impacted both the organism’s behavior more at higher salinities, whereas polyester and polypropylene had more impacts at lower salinities. This raises concerns for microfiber impacts on estuarine ecosystems and the need for policies to limit microfiber production and outfall into the aquatic environment. 

The Carbon monOxide Mapping Array Project (COMAP) Pathfinder survey continues to demonstrate the feasibility of line-intensity mapping using high-redshift carbon monoxide (CO) line emission traced at cosmological scales. The latest COMAP Pathfinder power spectrum analysis is based on observations through the end of Season 2, covering the first three years of Pathfinder operations. We use our latest constraints on the CO(1–0) line-intensity power spectrum atz~ 3 to update corresponding constraints on the cosmological clustering of CO line emission and thus the cosmic molecular gas content at a key epoch of galaxy assembly. We first mirror the COMAP Early Science interpretation, considering how Season 2 results translate to limits on the shot noise power of CO fluctuations and the bias of CO emission as a tracer of the underlying dark matter distribution. The COMAP Season 2 results place the most stringent limits on the CO tracer bias to date, at ⟨T b⟩ < 4.8 μK, which translates to a molecular gas density upper limit ofρ_H2< 1.6 × 10⁸M_⊙Mpc⁻³atz~ 3 given additional model assumptions. These limits narrow the model space significantly compared to previous CO line-intensity mapping results while maintaining consistency with small-volume interferometric surveys of resolved line candidates. The results also express a weak preference for CO emission models used to guide fiducial forecasts from COMAP Early Science, including our data-driven priors. We also consider directly constraining a model of the halo–CO connection, and show qualitative hints of capturing the total contribution of faint CO emitters through the improved sensitivity of COMAP data. With continued observations and matching improvements in analysis, the COMAP Pathfinder remains on track for a detection of cosmological clustering of CO emission. 

The CO Mapping Array Project (COMAP) Pathfinder is performing line intensity mapping of CO emission to trace the distribution of unresolved galaxies at redshiftz ∼ 3. We present an improved version of the COMAP data processing pipeline and apply it to the first two Seasons of observations. This analysis improves on the COMAP Early Science (ES) results in several key aspects. On the observational side, all second season scans were made in constant-elevation mode, after noting that the previous Lissajous scans were associated with increased systematic errors; those scans accounted for 50% of the total Season 1 data volume. In addition, all new observations were restricted to an elevation range of 35–65 degrees to minimize sidelobe ground pickup. On the data processing side, more effective data cleaning in both the time and map domain allowed us to eliminate all data-driven power spectrum-based cuts. This increases the overall data retention and reduces the risk of signal subtraction bias. However, due to the increased sensitivity, two new pointing-correlated systematic errors have emerged, and we introduced a new map-domain PCA filter to suppress these errors. Subtracting only five out of 256 PCA modes, we find that the standard deviation of the cleaned maps decreases by 67% on large angular scales, and after applying this filter, the maps appear consistent with instrumental noise. Combining all of these improvements, we find that each hour of raw Season 2 observations yields on average 3.2 times more cleaned data compared to the ES analysis. Combining this with the increase in raw observational hours, the effective amount of data available for high-level analysis is a factor of eight higher than in the ES analysis. The resulting maps have reached an uncertainty of 25–50 μK per voxel, providing by far the strongest constraints on cosmological CO line emission published to date. 

We present updated constraints on the cosmological 3D power spectrum of carbon monoxide CO(1–0) emission in the redshift range 2.4–3.4. The constraints are derived from the two first seasons of Carbon monOxide Mapping Array Project (COMAP) Pathfinder line intensity mapping observations aiming to trace star formation during the epoch of galaxy assembly. These results improve on the previous Early Science results through both increased data volume and an improved data processing methodology. On the methodological side, we now perform cross-correlations between groups of detectors (“feed groups”), as opposed to cross-correlations between single feeds, and this new feed group pseudo power spectrum (FGPXS) is constructed to be more robust against systematic effects. In terms of data volume, the effective mapping speed is significantly increased due to an improved observational strategy as well as a better data selection methodology. The updated spherically and field-averaged FGPXS,C^~(k), is consistent with zero, at a probability-to-exceed of around 34%, with an excess of 2.7σin the most sensitive bin. Our power spectrum estimate is about an order of magnitude more sensitive in our six deepest bins across 0.09 Mpc⁻¹<k< 0.73 Mpc⁻¹, compared to the feed-feed pseudo power spectrum (FPXS) of COMAP ES. Each of these bins individually constrains the CO power spectrum tok P_CO(k) < 2400–4900 μK²Mpc²at 95% confidence. To monitor potential contamination from residual systematic effects, we analyzed a set of 312 difference-map null tests and found that these are consistent with the instrumental noise prediction. In sum, these results provide the strongest direct constraints on the cosmological 3D CO(1–0) power spectrum published to date. 

A<sc>bstract</sc> A measurement of the angular structure of inclusive jets and those containing a prompt D⁰meson in proton-proton collisions at the LHC at a center-of-mass energy of 5.02 TeV is presented. The data corresponding to an integrated luminosity of 301 pb⁻¹were collected by the CMS experiment in 2017. Two jet grooming algorithms, late-k_Tand soft drop, are used to study the intrajet radiation pattern using iterative Cambridge-Aachen declustering. The splitting-angle distributions of jets with transverse momentum (p_T) of around 100 GeV, obtained with these two algorithms, show that there is a shift of the distribution for jets containing a prompt D⁰meson with respect to inclusive jets. The suppression of emissions at small angles observed in the late-k_Tgrooming approach is consistent with the dead-cone effect, whereas the similar suppression for splittings selected with the soft-drop algorithm appears to be induced by gluon splitting to charm quark-antiquark pairs at large angles. The measured distributions are corrected to the particle level and can be used to constrain model predictions for the substructure of high-p_Tcharm quark jets. 

A hot and dense state of nuclear matter, known as the quark-gluon plasma, is created in collisions of ultrarelativistic heavy nuclei. Highly energetic quarks and gluons, collectively referred to as partons, lose energy as they travel through this matter, leading to suppressed production of particles with large transverse momenta ( $p_{\mathrm{T}}$). Conversely, high- $p_{\mathrm{T}}$particle suppression has not been seen in proton-lead collisions, raising questions regarding the minimum system size required to observe parton energy loss. Oxygen-oxygen (OO) collisions examine a region of effective system size that lies between these two extreme cases. The CMS detector at the CERN LHC has been used to quantify charged-particle production in inclusive OO collisions for the first time via measurements of the nuclear modification factor ( $R_{\mathrm{AA}}$). The $R_{\mathrm{AA}}$is derived by comparing particle production to expectations based on proton-proton ( $pp$) data and has a value of unity in the absence of nuclear effects. The data for OO and $pp$collisions at a nucleon-nucleon center-of-mass energy $\sqrt{s_{\mathrm{NN}}}=5.36\mathrm{TeV}$correspond to integrated luminosities of $6.1{\mathrm{nb}}^{-1}$and $1.02{\mathrm{pb}}^{-1}$, respectively. The $R_{\mathrm{AA}}$is below unity with a minimum of $0.69\pm 0.04$around $p_{\mathrm{T}}=6\mathrm{GeV}$. The data exhibit better agreement with theoretical models incorporating parton energy loss as compared to baseline models without energy loss. 

A<sc>bstract</sc> A measurement of the substructure of bottom quark jets (b jets) in proton-proton (pp) collisions is presented. The measurement uses data collected in pp collisions at$$ \sqrt{s}=5.02 $$ $\sqrt{s}=5.02$TeV, with a low number of simultaneous interactions per bunch crossing, recorded by the CMS experiment in 2017, corresponding to an integrated luminosity of 301 pb⁻¹. An algorithm to identify and cluster the charged decay daughters of b hadrons is developed for this analysis, which facilitates the exposure of the gluon radiation pattern of b jets using iterative Cambridge-Aachen declustering. The soft-drop-groomed jet radius,R_g, and momentum balance,z_g, of b quark jets are presented. These observables can be used to test perturbative quantum chromodynamics predictions that account for mass effects. Because the b hadron is partially reconstructed from its charged decay daughters, only charged particles are used for the jet substructure studies. In addition, a jet fragmentation function,z_b,ch, is measured, which is defined as the distribution of the ratio of the transverse momentum (p_T) of the partially reconstructed b hadron with respect to the charged-particle component of the jetp_T. The substructure variable distributions are unfolded to the charged-particle level. The b jet substructure is compared to the substructure of jets in an inclusive jet sample that is dominated by light-quark and gluon jets in order to assess the role of the b quark mass. A strong suppression of emissions at smallR_gvalues is observed for b jets when compared to inclusive jets, consistent with the dead-cone effect. The measurement is also compared with theoretical predictions from Monte Carlo event generators. This is the first substructure measurement of b jets that clusters together the b hadron decay daughters independent of the b hadron species and decay channel.