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We present a computationally efficient galaxy archetype-based redshift estimation and spectral classification method for the Dark Energy Survey Instrument (DESI) survey. The DESI survey currently relies on a redshift fitter and spectral classifier using a linear combination of principal component analysis-derived templates, which is very efficient in processing large volumes of DESI spectra within a short time frame. However, this method occasionally yields unphysical model fits for galaxies and fails to adequately absorb calibration errors that may still be occasionally visible in the reduced spectra. Our proposed approach improves upon this existing method by refitting the spectra with carefully generated physical galaxy archetypes combined with additional terms designed to absorb data reduction defects and provide more physical models to the DESI spectra. We test our method on an extensive data set derived from the survey validation (SV) and Year 1 (Y1) data of DESI. Our findings indicate that the new method delivers marginally better redshift success for SV tiles while reducing catastrophic redshift failure by 10%-30%. At the same time, results from millions of targets from the main survey show that our model has relatively higher redshift success and purity rates (0.5%-0.8% higher) for galaxy targets while having similar success for QSOs. These improvements also demonstrate that the main DESI redshift pipeline is generally robust. Additionally, it reduces the false-positive redshift estimation by 5%−40% for sky fibers. We also discuss the generic nature of our method and how it can be extended to other large spectroscopic surveys, along with possible future improvements.

The Dark Energy Spectroscopic Instrument (DESI) completed its 5 month Survey Validation in 2021 May. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra.

Accurate mock galaxy catalogues are crucial to validate analysis pipelines used to constrain dark energy models. We present a fast HOD-fitting method which we apply to the AbacusSummit simulations to create a set of mock catalogues for the DESI Bright Galaxy Survey, which contain r-band magnitudes and colours (g - r) The halo tabulation method fits HODs for different absolute magnitude threshold samples simultaneously, preventing unphysical HOD crossing between samples. We validate the HOD fitting procedure by fitting to real-space clustering measurements and galaxy number densities from the MXXL BGS mock, which was tuned to the SDSS and GAMA surveys. The best-fitting clustering measurements and number densities are mostly within the assumed errors, but the clustering for the faint samples is low on large scales. The best-fitting HOD parameters are robust when fitting to simulations with different realizations of the initial conditions. When varying the cosmology, trends are seen as a function of each cosmological parameter. We use the best-fitting HOD parameters to create cubic box and cut sky mocks from the AbacusSummit simulations, in a range of cosmologies. As an illustration, we compare the sample of galaxies in the mock with BGS measurements from the DESI one-percent survey. We find good agreement in the number densities, and the projected correlation function is reasonable, with differences that can be improved in the future by fitting directly to BGS clustering measurements. The cubic box and cut-sky mocks in different cosmologies are made publicly available.

We present initial results from the Dark Energy Spectroscopic Instrument (DESI) complete calibration of the colour–redshift relation (DC3R2) secondary target survey. Our analysis uses 230 k galaxies that overlap with KiDS-VIKING ugriZYJHKs photometry to calibrate the colour–redshift relation and to inform photometric redshift (photo-z) inference methods of future weak lensing surveys. Together with emission line galaxies (ELGs), luminous red galaxies (LRGs), and the Bright Galaxy Survey (BGS) that provide samples of complementary colour, the DC3R2 targets help DESI to span 56 per cent of the colour space visible to Euclid and LSST with high confidence spectroscopic redshifts. The effects of spectroscopic completeness and quality are explored, as well as systematic uncertainties introduced with the use of common Self-Organizing Maps trained on different photometry than the analysis sample. We further examine the dependence of redshift on magnitude at fixed colour, important for the use of bright galaxy spectra to calibrate redshifts in a fainter photometric galaxy sample. We find that noise in the KiDS-VIKING photometry introduces a dominant, apparent magnitude dependence of redshift at fixed colour, which indicates a need for carefully chosen deep drilling fields, and survey simulation to model this effect for future weak lensing surveys.

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg2 over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI was evaluated during a 5 month survey validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar Milky Way Survey (MWS), Bright Galaxy Survey (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the 5 yr program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a One-Percent Survey conducted at the conclusion of SV covering 140 deg2 using the final target selection algorithms with exposures of a depth typical of the main survey. The SV indicates that DESI will be able to complete the full 14,000 deg2 program with spectroscopically confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval z < 1.1, 0.39% over the redshift interval 1.1 < z < 1.9, and 0.46% over the redshift interval 1.9 < z < 3.5.

The Dark Energy Spectroscopic Instrument (DESI) Survey has obtained a set of spectroscopic measurements of galaxies to validate the final survey design and target selections. To assist in these tasks, we visually inspect DESI spectra of approximately 2500 bright galaxies, 3500 luminous red galaxies (LRGs), and 10,000 emission-line galaxies (ELGs) to obtain robust redshift identifications. We then utilize the visually inspected redshift information to characterize the performance of the DESI operation. Based on the visual inspection (VI) catalogs, our results show that the final survey design yields samples of bright galaxies, LRGs, and ELGs with purity greater than 99%. Moreover, we demonstrate that the precision of the redshift measurements is approximately 10 km s−1 for bright galaxies and ELGs and approximately 40 km s−1 for LRGs. The average redshift accuracy is within 10 km s−1 for the three types of galaxies. The VI process also helps improve the quality of the DESI data by identifying spurious spectral features introduced by the pipeline. Finally, we show examples of unexpected real astronomical objects, such as Lyα emitters and strong lensing candidates, identified by VI. These results demonstrate the importance and utility of visually inspecting data from incoming and upcoming surveys, especially during their early operation phases.

The Dark Energy Spectroscopic Instrument (DESI) embarked on an ambitious 5 yr survey in 2021 May to explore the nature of dark energy with spectroscopic measurements of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the baryon acoustic oscillation method to measure distances from the nearby universe to beyond redshift z > 3.5, and employ redshift space distortions to measure the growth of structure and probe potential modifications to general relativity. We describe the significant instrumentation we developed to conduct the DESI survey. This includes: a wide-field, 3.°2 diameter prime-focus corrector; a focal plane system with 5020 fiber positioners on the 0.812 m diameter, aspheric focal surface; 10 continuous, high-efficiency fiber cable bundles that connect the focal plane to the spectrographs; and 10 identical spectrographs. Each spectrograph employs a pair of dichroics to split the light into three channels that together record the light from 360-980 nm with a spectral resolution that ranges from 2000-5000. We describe the science requirements, their connection to the technical requirements, the management of the project, and interfaces between subsystems. DESI was installed at the 4 m Mayall Telescope at Kitt Peak National Observatory and has achieved all of its performance goals. Some performance highlights include an rms positioner accuracy of better than 0.″1 and a median signal-to-noise ratio of 7 of the [O ii] doublet at 8 × 10-17 erg s-1 cm-2 in 1000 s for galaxies at z = 1.4-1.6. We conclude with additional highlights from the on-sky validation and commissioning, key successes, and lessons learned.

The Dark Energy Spectroscopic Instrument (DESI) has embarked on an ambitiousfive-year survey to explore the nature of dark energy with spectroscopy of 40million galaxies and quasars. DESI will determine precise redshifts and employthe Baryon Acoustic Oscillation method to measure distances from the nearbyuniverse to z > 3.5, as well as measure the growth of structure and probepotential modifications to general relativity. In this paper we describe thesignificant instrumentation we developed for the DESI survey. The newinstrumentation includes a wide-field, 3.2-deg diameter prime-focus correctorthat focuses the light onto 5020 robotic fiber positioners on the 0.812 mdiameter, aspheric focal surface. The positioners and their fibers are dividedamong ten wedge-shaped petals. Each petal is connected to one of tenspectrographs via a contiguous, high-efficiency, nearly 50 m fiber cablebundle. The ten spectrographs each use a pair of dichroics to split the lightinto three channels that together record the light from 360 - 980 nm with aresolution of 2000 to 5000. We describe the science requirements, technicalrequirements on the instrumentation, and management of the project. DESI wasinstalled at the 4-m Mayall telescope at Kitt Peak, and we also describe thefacility upgrades to prepare for DESI and the installation and functionalverification process. DESI has achieved all of its performance goals, and theDESI survey began in May 2021. Some performance highlights include RMSpositioner accuracy better than 0.1", SNR per \sqrt{\AA} > 0.5 for a z > 2quasar with flux 0.28e-17 erg/s/cm^2/A at 380 nm in 4000s, and median SNR = 7of the [OII] doublet at 8e-17 erg/s/cm^2 in a 1000s exposure for emission linegalaxies at z = 1.4 - 1.6. We conclude with highlights from the on-skyvalidation and commissioning of the instrument, key successes, and lessonslearned. (abridged)

Over the past decade, with increasing scientific scrutiny on forensic reporting practices, there have been several efforts to introduce statistical thinking and probabilistic reasoning into forensic practice. These efforts have been met with mixed reactions - a common one being scepticism, or downright hostility, towards this objective. For probabilistic reasoning to be adopted in forensic practice, more than statistical knowledge will be necessary. Social scientific knowledge will be critical to effectively understand the sources of concern and barriers to implementation. This study reports the findings of a survey of forensic fingerprint examiners about reporting practices across the discipline and practitioners' attitudes and characterizations of probabilistic reporting. Overall, despite its adoption by a small number of practitioners, community-wide adoption of probabilistic reporting in the friction ridge discipline faces challenges. We found that almost no respondents currently report probabilistically. Perhaps more surprisingly, most respondents who claimed to report probabilistically, in fact, do not. Furthermore, we found that two-thirds of respondents perceive probabilistic reporting as 'inappropriate' - their most common concern being that defence attorneys would take advantage of uncertainty or that probabilistic reports would mislead, or be misunderstood by, other criminal justice system actors. If probabilistic reporting is to be adopted, much work is still needed to better educate practitioners on the importance and utility of probabilistic reasoning in order to facilitate a path towards improved reporting practices.

We search for the baryon acoustic oscillations in the projected cross-correlation function binned into transverse comoving radius between the SDSS-IV DR16 eBOSS quasars and a dense photometric sample of galaxies selected from the DESI Legacy Imaging Surveys. We estimate the density of the photometric sample of galaxies in this redshift range to be about 2900 deg−2, which is deeper than the official DESI emission line galaxy selection, and the density of the spectroscopic sample is about 20 deg−2. In order to mitigate the systematics related to the use of different imaging surveys close to the detection limit, we use a neural network approach that accounts for complex dependences between the imaging attributes and the observed galaxy density. We find that we are limited by the depth of the imaging surveys that affects the density and purity of the photometric sample and its overlap in redshift with the quasar sample, which thus affects the performance of the method. When cross-correlating the photometric galaxies with quasars in the range 0.6 ≤ z ≤ 1.2, the cross-correlation function can provide better constraints on the comoving angular distance DM (6 per cent precision) compared to the constraint on the spherically averaged distance DV (9 per cent precision) obtained from the autocorrelation. Although not yet competitive, this technique will benefit from the arrival of deeper photometric data from upcoming surveys that will enable it to go beyond the current limitations we have identified in this work.

We present the steps taken to produce a reliable and complete input galaxy catalogue for the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey (BGS) using the photometric Legacy Survey DR8 DECam. We analyse some of the main issues faced in the selection of targets for the DESI BGS, such as star-galaxy separation, contamination by fragmented stars and bright galaxies. Our pipeline utilizes a new way to select BGS galaxies using Gaia photometry and we implement geometrical and photometric masks that reduce the number of spurious objects. The resulting catalogue is cross-matched with the Galaxy And Mass Assembly (GAMA) survey to assess the completeness of the galaxy catalogue and the performance of the target selection. We also validate the clustering of the sources in our BGS catalogue by comparing with mock catalogues and the Sloan Digital Sky Survey (SDSS) data. Finally, the robustness of the BGS selection criteria is assessed by quantifying the dependence of the target galaxy density on imaging and other properties. The largest systematic correlation we find is a 7 per cent suppression of the target density in regions of high stellar density.

BackgroundHeart failure with preserved ejection fraction (HFpEF) is a common syndrome with a pressing shortage of therapies. Exercise intolerance is a cardinal symptom of HFpEF, yet its pathophysiology remains uncertain.MethodsWe investigated the mechanism of exercise intolerance in 134 patients referred for cardiopulmonary exercise testing: 79 with HFpEF and 55 controls. We performed cardiopulmonary exercise testing with invasive monitoring to measure hemodynamics, blood gases, and gas exchange during exercise. We used these measurements to quantify 6 steps of oxygen transport and utilization (the O2 pathway) in each patient with HFpEF, identifying the defective steps that impair each one's exercise capacity (peak Vo2). We then quantified the functional significance of each O2 pathway defect by calculating the improvement in exercise capacity a patient could expect from correcting the defect.ResultsPeak Vo2 was reduced by 34±2% (mean±SEM, P

BackgroundHeart failure with preserved ejection fraction (HFpEF) is a common syndrome with a pressing shortage of therapies. Exercise intolerance is a cardinal symptom of HFpEF, yet its pathophysiology remains uncertain.MethodsWe investigated the mechanism of exercise intolerance in 134 patients referred for cardiopulmonary exercise testing: 79 with HFpEF and 55 controls. We performed cardiopulmonary exercise testing with invasive monitoring to measure hemodynamics, blood gases, and gas exchange during exercise. We used these measurements to quantify 6 steps of oxygen transport and utilization (the O2 pathway) in each patient with HFpEF, identifying the defective steps that impair each one's exercise capacity (peak Vo2). We then quantified the functional significance of each O2 pathway defect by calculating the improvement in exercise capacity a patient could expect from correcting the defect.ResultsPeak Vo2 was reduced by 34±2% (mean±SEM, P

Our understanding of subsurface processes suffers from a profound observation bias: seismometers are sparse and clustered on continents. A new seismic recording approach, distributed acoustic sensing (DAS), transforms telecommunication fiber-optic cables into sensor arrays enabling meter-scale recording over tens of kilometers of linear fiber length. We analyze cataloged earthquake observations from three DAS arrays with different horizontal geometries to demonstrate some possibilities using this technology. In Fairbanks, Alaska, we find that stacking ground motion records along 20 m of fiber yield a waveform that shows a high degree of correlation in amplitude and phase with a colocated inertial seismometer record at 0.8–1.6 Hz. Using an L-shaped DAS array in Northern California, we record the nearly vertically incident arrival of an earthquake from The Geysers Geothermal Field and estimate its backazimuth and slowness via beamforming for different phases of the seismic wavefield. Lastly, we install a fiber in existing telecommunications conduits below Stanford University and show that little cable-to-soil coupling is required for teleseismic P and S phase arrival detection.

UNLABELLED: Essentials Plasminogen activator inhibitor-1 (PAI-1) advanced cellular senescence in experiment studies. No population study exists on the association between PAI-1 and biological aging in American Indians. We found cross-sectional and longitudinal associations between higher PAI-1 and shorter telomere length. Our findings suggest a pathway linking PAI-1 with biological aging beyond metabolic factors. SUMMARY: Background Plasminogen activator inhibitor-1 (PAI-1) promotes cellular aging both in vitro and in vivo. Telomere length is a marker of biological aging. Objectives To examine the cross-sectional and longitudinal associations between plasma PAI-1 and leukocyte telomere length in a large-scale epidemiological study of American Indians. Methods We measured leukocyte telomere length (LTL) and plasma PAI-1 in 2560 American Indians who were free of overt cardiovascular disease (CVD) and participated in the Strong Heart Family Study (SHFS) clinical examination in 2001-2003. LTL and PAI-1 were repeatedly measured in 475 participants who attended SHFS clinical visits in both 2001-2003 and 1998-1999. A generalized estimating equation model was used to examine the cross-sectional and longitudinal associations between PAI-1 and LTL, adjusting for known risk factors. Results A higher level of plasma PAI-1 was negatively associated with shorter age-adjusted LTL (β = -0.023; 95% CI, -0.034 to -0.013). This association was attenuated (β = -0.015; 95% CI, -0.029 to -0.002) after adjustments for demographics, study site, lifestyle (smoking, drinking and physical activity) and metabolic factors (obesity, blood pressure, fasting glucose, insulin, lipids and kidney function). Further adjustment for hsCRP did not change this association (β = -0.015; 95% CI, -0.029 to -0.001). Longitudinal analysis revealed that change in plasma PAI-1 was also inversely associated with change in LTL after adjusting for demographics, follow-up years, lifestyle factors, changes in metabolic factors, baseline levels of PAI-1 and LTL (β = -0.0005; 95% CI, -0.0009 to -0.0001). Conclusions A higher level of plasma PAI-1 was associated with shorter LTL in American Indians. This finding may suggest a potential role of PAI-1 in biological aging among American Indians.

BACKGROUND: Distinct gene expression profiles in peripheral blood mononuclear cells (PBMCs) consistent with increased sympathetic nervous system activity have been described in different populations under chronic stress. Neuroinflammatory brain changes, possibly related to the migration of primed monocytes to the brain, have been implicated in the pathophysiology of chronic pain. Irritable bowel syndrome (IBS) is a stress-sensitive gastrointestinal disorder associated with altered brain-gut interactions and increased sympathetic/vagal tone and anxiety. Reports about immune alterations in IBS are conflicting. This pilot study aimed to test how PBMC gene expression inflammatory profiles are correlated with altered brain signatures in the salience system. METHODS: Sixteen IBS and 16 healthy controls (HCs) completed resting state MRI scans. Gene expression profiles in PBMCs were assessed using human transcriptome array-2. Bioinformatic analyses determined differential expression of PBMCs between IBS and HCs. Partial least squares, a multivariate analysis technique, was used to identify disease correlations between PBMC gene expression profiles and functional activity in the brains salience network. KEY RESULTS: Regions of the salience network, including the mid cingulate cortex, and mid and superior temporal gyrus were positively correlated with several pro-inflammatory genes (interleukin 6, APOL2) in IBS, but negatively correlated with several anti-inflammatory genes (KRT8, APOA4) in HCs. CONCLUSIONS & INFERENCES: Based on rodent studies, one may speculate that chronically activated stress signaling pathways in IBS maintain a pro-inflammatory state in the periphery. Alternatively, primed monocytes may migrate to the brain during stress, inducing regional neuroinflammatory changes in salience regions involved in the modulation of visceral sensitivity.

Pan-STARRS1 has carried out a set of distinct synoptic imaging sky surveysincluding the $3\pi$ Steradian Survey and the Medium Deep Survey in 5 bands($grizy_{P1}$). The mean 5$\sigma$ point source limiting sensitivities in thestacked 3$\pi$ Steradian Survey in $grizy_{P1}$ are (23.3, 23.2, 23.1, 22.3,21.4) respectively. The upper bound on the systematic uncertainty in thephotometric calibration across the sky is 7-12 millimag depending on thebandpass. The systematic uncertainty of the astrometric calibration using theGaia frame comes from a comparison of the results with Gaia: the standarddeviation of the mean and median residuals ($ \Delta ra, \Delta dec $) are(2.3, 1.7) milliarcsec, and (3.1, 4.8) milliarcsec respectively. The Pan-STARRSsystem and the design of the PS1 surveys are described and an overview of theresulting image and catalog data products and their basic characteristics aredescribed together with a summary of important results. The images, reduceddata products, and derived data products from the Pan-STARRS1 surveys areavailable to the community from the Mikulski Archive for Space Telescopes(MAST) at STScI.

Pan-STARRS1 has carried out a set of distinct synoptic imaging sky surveysincluding the $3\pi$ Steradian Survey and the Medium Deep Survey in 5 bands($grizy_{P1}$). The mean 5$\sigma$ point source limiting sensitivities in thestacked 3$\pi$ Steradian Survey in $grizy_{P1}$ are (23.3, 23.2, 23.1, 22.3,21.4) respectively. The upper bound on the systematic uncertainty in thephotometric calibration across the sky is 7-12 millimag depending on thebandpass. The systematic uncertainty of the astrometric calibration using theGaia frame comes from a comparison of the results with Gaia: the standarddeviation of the mean and median residuals ($ \Delta ra, \Delta dec $) are(2.3, 1.7) milliarcsec, and (3.1, 4.8) milliarcsec respectively. The Pan-STARRSsystem and the design of the PS1 surveys are described and an overview of theresulting image and catalog data products and their basic characteristics aredescribed together with a summary of important results. The images, reduceddata products, and derived data products from the Pan-STARRS1 surveys areavailable to the community from the Mikulski Archive for Space Telescopes(MAST) at STScI.

Aims: Close to one third of patients with major depression show increases in pro-inflammatory cytokines, which are in turn associated with risk for inflammatory disease. Genetic variants that enhance immune reactivity may thus enhance inflammatory and depressive reactions to stress. The aim of the present study was to investigate a trio of functional SNPs in the promoter regions of IL6 (-174G>C, rs1800795), IL1β (-511C>T, rs16944), and TNF (-308G>A, rs1800629) as moderators of the relationship between chronic stress exposure and elevations in depressive symptoms. Methods: Participants were 444 Australian youth (mean age = 20.12) whose exposure to chronic stress in the past 6. months was assessed using the semi-structured UCLA Life Stress Interview, and who completed the Beck Depression Inventory II at ages 15 and 20. Between ages 22 and 25, all participants in the selected sample provided blood samples for genotyping. Results: In line with a hypothesized moderation effect, -174G allele carriers at IL6 had fewer depressive symptoms following interpersonal stress, relative to C/C homozygotes with equal interpersonal stress exposure. However, IL6 genotype did not moderate the effects of non-interpersonal stress exposure (i.e., financial, work and health-related difficulties) on depression. Also in line with hypotheses, the -511C allele in IL1β, previously associated with higher IL-1β expression, was associated with more severe depression following chronic interpersonal stress exposure, relative to T/T homozygotes. Again, the moderating effect was specific to interpersonal stressors and did not generalize to non-interpersonal stress. TNF was not a moderator of the effects of either interpersonal or non-interpersonal stress on later depression outcomes. Conclusion: Findings were consistent with the hypothesis that pro-inflammatory genetic variation increases the risk of stress-induced depression. The present results provide evidence of a genetic mechanism contributing to individual differences in depressive symptomatology following interpersonal stress exposure.