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Water vapor (H₂O) is one of the brightest molecular emitters after carbon monoxide (CO) in galaxies with high infrared (IR) luminosity, allowing us to investigate the warm and dense phase of the interstellar medium (ISM) where star formation occurs. However, due to the complexity of its radiative spectrum, H₂O is not frequently exploited as an ISM tracer in distant galaxies. Therefore, H₂O studies of the warm and dense gas at high-zremain largely unexplored. In this work, we present observations conducted with the Northern Extended Millimeter Array (NOEMA) toward threez > 6 IR-bright quasarsJ2310+1855,J1148+5251, andJ0439+1634targeted in their multiple para- and ortho-H₂O transitions (3₁₂ − 3₀₃, 1₁₁ − 0₀₀, 2₂₀ − 2₁₁, and 4₂₂ − 4₁₃), as well as their far-IR (FIR) dust continuum. By combining our data with previous measurements from the literature, we estimated the dust masses and temperatures, continuum optical depths, IR luminosities, and star formation rates (SFR) from the FIR continuum. We modeled the H₂O lines using the MOLPOP-CEP radiative transfer code, finding that water vapor lines in our quasar host galaxies are primarily excited in the warm, dense (with a gas kinetic temperature and density ofT_kin = 50 K,n_H2 ∼ 10^4.5 − 10⁵ cm⁻³) molecular medium with a water vapor column density ofN_H2O ∼ 2 × 10¹⁷ − 3 × 10¹⁸ cm⁻³. High-JH₂O lines are mainly radiatively pumped by the intense optically-thin far-IR radiation field associated with a warm dust component at temperatures ofT_dust ∼ 80 − 190 K that account for < 5 − 10% of the total dust mass. In the case of J2310+1855, our analysis points to a relatively high value of the continuum optical depth at 100 μm (τ₁₀₀ ∼ 1). Our results are in agreement with expectations based on the H₂O spectral line energy distribution of local and high-zultra-luminous IR galaxies and active galactic nuclei (AGN). The analysis of the Boltzmann diagrams highlights the interplay between collisions and IR pumping in populating the high H₂O energy levels and it allows us to directly compare the excitation conditions in the targeted quasar host galaxies. In addition, the observations enable us to sample the high-luminosity part of the H₂O–total-IR (TIR) luminosity relations (L_H2O − L_TIR). Overall, our results point to supralinear trends that suggest H₂O–TIR relations are likely driven by IR pumping, rather than the mere co-spatiality between the FIR continuum- and line-emitting regions. The observedL_H2O/L_TIRratios in ourz > 6 quasars do not show any strong deviations with respect to those measured in star-forming galaxies and AGN at lower redshifts. This supports the notion that H₂O can be likely used to trace the star formation activity buried deep within the dense molecular clouds.

 

German cockroaches (Blattella germanica L.) harbor and disperse medically important pathogens and are a source of allergens that impact human health and wellbeing. Management of this pest requires an understanding of their distribution and dispersal. In this study, we collected German cockroaches from three apartment buildings in New Jersey, USA. We identified single-nucleotide polymorphisms (SNPs) from DNA extractions using next generation sequencing. We analyzed the SNPs and characterized cockroach population genetic structure using Fst, principal component, phylogenetic, and STRUCTURE analyses. We found significant differences in German cockroach population structure among the buildings. Within buildings, we found variable population structure that may be evidence for multiple colonization events. This study shows that SNPs derived from next generation sequencing provide a powerful tool for analyzing the genetic population structure of these medically important pests.

 

ABSTRACT The final phase of the reionization process can be probed by rest-frame UV absorption spectra of quasars at z ≳ 6, shedding light on the properties of the diffuse intergalactic medium within the first Gyr of the Universe. The ESO Large Programme ‘XQR-30: the ultimate XSHOOTER legacy survey of quasars at z ≃ 5.8–6.6’ dedicated ∼250 h of observations at the VLT to create a homogeneous and high-quality sample of spectra of 30 luminous quasars at z ∼ 6, covering the rest wavelength range from the Lyman limit to beyond the Mg ii emission. Twelve quasar spectra of similar quality from the XSHOOTER archive were added to form the enlarged XQR-30 sample, corresponding to a total of ∼350 h of on-source exposure time. The median effective resolving power of the 42 spectra is R ≃ 11 400 and 9800 in the VIS and NIR arm, respectively. The signal-to-noise ratio per 10 km s−1 pixel ranges from ∼11 to 114 at λ ≃ 1285 Å rest frame, with a median value of ∼29. We describe the observations, data reduction, and analysis of the spectra, together with some first results based on the E-XQR-30 sample. New photometry in the H and K bands are provided for the XQR-30 quasars, together with composite spectra whose characteristics reflect the large absolute magnitudes of the sample. The composite and the reduced spectra are released to the community through a public repository, and will enable a range of studies addressing outstanding questions regarding the first Gyr of the Universe. 

This paper presents a bilinear log model, for predicting temperature-dependent ultimate strength of high-entropy alloys (HEAs) based on 21 HEA compositions. We consider the break temperature,T_break, introduced in the model, an important parameter for design of materials with attractive high-temperature properties, one warranting inclusion in alloy specifications. For reliable operation, the operating temperature of alloys may need to stay belowT_break. We introduce a technique of global optimization, one enabling concurrent optimization of model parameters over low-temperature and high-temperature regimes. Furthermore, we suggest a general framework for joint optimization of alloy properties, capable of accounting for physics-based dependencies, and show how a special case can be formulated to address the identification of HEAs offering attractive ultimate strength. We advocate for the selection of an optimization technique suitable for the problem at hand and the data available, and for properly accounting for the underlying sources of variations.