2D k-th nearest neighbor statistics: a highly informative probe of galaxy clustering

Beyond standard summary statistics are necessary to summarize the rich information on non-linear scales in the era of precision galaxy clustering measurements. For the first time, we introduce the 2D k-th nearest neighbor (kNN) statistics as a summary statistic for discrete galaxy fields. This is a direct generalization of the standard 1D kNN by disentangling the projected galaxy distribution from the redshift-space distortion signature along the line-of-sight. We further introduce two different flavors of 2D $k$NNs that trace different aspects of the galaxy field: the standard flavor which tabulates the distances between galaxies and random query points, and a ''DD'' flavor that tabulates the distances between galaxies and galaxies. We showcase the 2D kNNs' strong constraining power both through theoretical arguments and by testing on realistic galaxy mocks. Theoretically, we show that 2D kNNs are computationally efficient and directly generate other statistics such as the popular 2-point correlation function, voids probability function, and counts-in-cell statistics. In a more practical test, we apply the 2D kNN statistics to simulated galaxy mocks that fold in a large range of observational realism and recover parameters of the underlying extended halo occupation distribution (HOD) model that includes velocity bias and galaxy assembly bias. We find unbiased and significantly tighter constraints on all aspects of the HOD model with the 2D kNNs, both compared to the standard 1D kNN, and the classical redshift-space 2-point correlation functions.Comment: Submitted to MNRAS, comments welcom

A Farmer’s Perspective on the Relevance of Grassland-Related Innovations in Mediterranean Dehesa Systems

Grasslands are of key importance for the provision of ecosystem services (ES). Suitable management is essential to guarantee their persistence and functionality. There is a growing interest in innovations such as new technologies aimed at facilitating and improving the management of grasslands while increasing their provision of ES. The uptake of innovations by farmers is a complex process, and relevant socio-economic or technological factors that are crucial to farmers are often overlooked. This information can be useful for increasing the adoption of these innovations through the design of public policies to facilitate them. This paper analyses the relevance of the main innovations that can be applied to the management of the grasslands of Dehesa farms for the farmers and the factors that might affect this relevance. Through questionaries, we gathered information on the relevance that farmers give to the selected innovations and analysed it by cumulative link models. The results show that innovations aimed at increasing the biomass production of grasslands and resilience such as the use of seed mixtures and the use of forage drought-resistant species are considered highly relevant by Dehesa farmers. However, high-tech innovations such as GPS collars were poorly rated which could denote low applicability to the context of Dehesas or the existence of barriers hindering the adoption but also a need for further development and better information on their potential. Characteristics of the farmer and farm such as age, education level, and stocking rate seem to be related to the relevance given to some of the innovations. These results provide insightful information for the implementation and research of relevant grassland-related innovations in the context of Mediterranean Dehesa/Montado systems, as well as for the design of policies supporting them

La Mejora del Sistema de lnformación Contable Mediante la Integración de las Tecnologías Emergentes: The Improvement of Accounting lnformation Systems through the Integration of Emerging Technologies

The accounting information system (hereafter AIS) can be considered as the basic support to satisfy demands for information during the decision making process. Inadequacies in the information supplied to decision makers implies, necessarily, the need to modify the AIS so that it can continue to be the main support in the decision making process. This paper, on the one hand, describes the characteristics that these systems should have in each 01 their operational phases in order to increase the quantity and quality of information. On the other hand, it outlines the possibilities of achieving such demands by integrating artificial intelligence tools in traditional AIS’s.El sistema de información contable (en adelante, SIC) se configura como el soporte básico para la satisfacción de las necesidades informativas en el proceso de toma de decisiones. La falta de adecuación de la información suministrada a las demandas de sus distintos usuarios conlleva, necesariamente, la modificación del SIC, pues sólo así seguirá siendo el principal pilar en el proceso decisional. En este trabajo, por un lado, se describen las características que deberían reunir estos sistemas en cada una de las fases que componen su esquema de funcionamiento a fin de aumentar la cantidad y calidad de la información y, por otro, se presentan las posibilidades que ofrece la integración en los SIC tradicionales de las distintas herramientas que la Inteligencia Artificial pone a nuestra disposición para lograr tales exigencias

Dietary polyphenols, metabolic syndrome and cardiometabolic risk factors: An observational study based on the DCH-NG subcohort

Background and aims: Polyphenol-rich foods have beneficial properties that may lower cardiometabolic risk. We aimed to prospectively investigate the relationship between intakes of dietary polyphenols, and metabolic syndrome (MetS) and its components, in 676 Danish residents from the MAX study, a subcohort of the Danish Diet, Cancer and Health–Next Generations (DCH-NG) cohort. Methods and results: Dietary data were collected using web-based 24-h dietary recalls over one year (at baseline, and at 6 and 12 months). The Phenol-Explorer database was used to estimate dietary polyphenol intake. Clinical variables were also collected at the same time point. Generalized linear mixed models were used to investigate relationships between polyphenol intake and MetS. Participants had a mean age of 43.9y, a mean total polyphenol intake of 1368 mg/day, and 75 (11.6%) had MetS at baseline. Compared to individuals with MetS in Q1 and after adjusting for age, sex, lifestyle and dietary confounders, those in Q4 – for total polyphenols, flavonoids and phenolic acids–had a 50% [OR (95% CI): 0.50 (0.27, 0.91)], 51% [0.49 (0.26, 0.91)] and 45% [0.55 (0.30, 1.00)] lower odds of MetS, respectively. Higher total polyphenols, flavonoids and phenolic acids intakes as continuous variable were associated with lower risk for elevated systolic blood pressure (SBP) and low high-density lipoprotein cholesterol (HDL-c) (p < 0.05). Conclusions: Total polyphenol, flavonoid and phenolic acid intakes were associated with lower odds of MetS. These intakes were also consistently and significantly associated with a lower risk for higher SBP and lower HDL-c concentrations

Plasma metabolomic profiles of plant-based dietary indices reveal potential pathways for metabolic syndrome associations

Background and aims: Plant-based dietary patterns have been associated with improved health outcomes. This study aims to describe the metabolomic fingerprints of plant-based diet indices (PDI) and examine their association with metabolic syndrome (MetS) and its components in a Danish population. Methods: The MAX study comprised 676 participants (55% women, aged 18-67 y) from Copenhagen. Sociodemographic and dietary data were collected using questionnaires and three 24-h dietary recalls over one year (at baseline, and at 6 and 12 months). Mean dietary intakes were computed, as well as overall PDI, healthful (hPDI) and unhealthful (uPDI) scores, according to food groups for each plant-based index. Clinical variables were also collected at the same time points in a health examination that included complete blood tests. MetS was defined according to the International Diabetes Federation criteria. Plasma metabolites were measured using a targeted metabolomics approach. Metabolites associated with PDI were selected using random forest models and their relationships with PDIs and MetS were analyzed using generalized linear mixed models. Results: The mean prevalence of MetS was 10.8%. High, compared to low, hPDI and uPDI scores were associated with a lower and higher odd of MetS, respectively [odds ratio (95%CI); hPDI: 0.56 (0.43–0.74); uPDI: 1.61 (1.26–2.05)]. Out of 411 quantified plasma metabolites, machine-learning metabolomics fingerprinting revealed 13 metabolites, including food and food-related microbial metabolites, like hypaphorine, indolepropionic acid and lignan-derived enterolactones. These metabolites were associated with all PDIs and were inversely correlated with MetS components (p < 0.05). Furthermore, they had an explainable contribution of 12% and 14% for the association between hPDI or uPDI, respectively, and MetS only among participants with overweight/obesity. Conclusions: Metabolites associated with PDIs were inversely associated with MetS and its components, and may partially explain the effects of plant-based diets on cardiometabolic risk factors

Dietary Sources of Anthocyanins and Their Association with Metabolome Biomarkers and Cardiometabolic Risk Factors in an Observational Study

Anthocyanins (ACNs) are (poly)phenols associated with reduced cardiometabolic risk. Associations between dietary intake, microbial metabolism, and cardiometabolic health benefits of ACNs have not been fully characterized. Our aims were to study the association between ACN intake, considering its dietary sources, and plasma metabolites, and to relate them with cardiometabolic risk factors in an observational study. A total of 1351 samples from 624 participants (55% female, mean age: 45 \ub1 12 years old) enrolled in the DCH-NG MAX study were studied using a targeted metabolomic analysis. Twenty-four-hour dietary recalls were used to collect dietary data at baseline, six, and twelve months. ACN content of foods was calculated using Phenol Explorer and foods were categorized into food groups. The median intake of total ACNs was 1.6mg/day. Using mixed graphical models, ACNs from different foods showed specific associations with plasma metabolome biomarkers. Combining these results with censored regression analysis, metabolites associated with ACNs intake were: salsolinol sulfate, 4-methylcatechol sulfate, linoleoyl carnitine, 3,4-dihydroxyphenylacetic acid, and one valerolactone. Salsolinol sulfate and 4-methylcatechol sulfate, both related to the intake of ACNs mainly from berries, were inversely associated with visceral adipose tissue. In conclusion, plasma metabolome biomarkers of dietary ACNs depended on the dietary source and some of them, such as salsolinol sulfate and 4-methylcatechol sulfate may link berry intake with cardiometabolic health benefits

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

US SOLAS Science Report

The article of record may be found at https://doi.org/10.1575/1912/27821The Surface Ocean – Lower Atmosphere Study (SOLAS) (http://www.solas-int.org/) is an international research initiative focused on understanding the key biogeochemical-physical interactions and feedbacks between the ocean and atmosphere that are critical elements of climate and global biogeochemical cycles. Following the release of the SOLAS Decadal Science Plan (2015-2025) (Brévière et al., 2016), the Ocean-Atmosphere Interaction Committee (OAIC) was formed as a subcommittee of the Ocean Carbon and Biogeochemistry (OCB) Scientific Steering Committee to coordinate US SOLAS efforts and activities, facilitate interactions among atmospheric and ocean scientists, and strengthen US contributions to international SOLAS. In October 2019, with support from OCB, the OAIC convened an open community workshop, Ocean-Atmosphere Interactions: Scoping directions for new research with the goal of fostering new collaborations and identifying knowledge gaps and high-priority science questions to formulate a US SOLAS Science Plan. Based on presentations and discussions at the workshop, the OAIC and workshop participants have developed this US SOLAS Science Plan. The first part of the workshop and this Science Plan were purposefully designed around the five themes of the SOLAS Decadal Science Plan (2015-2025) (Brévière et al., 2016) to provide a common set of research priorities and ensure a more cohesive US contribution to international SOLAS.This report was developed with federal support of NSF (OCE-1558412) and NASA (NNX17AB17G).This report was developed with federal support of NSF (OCE-1558412) and NASA (NNX17AB17G)

US SOLAS Science Report

The Surface Ocean – Lower Atmosphere Study (SOLAS) (http://www.solas-int.org/) is an international research initiative focused on understanding the key biogeochemical-physical interactions and feedbacks between the ocean and atmosphere that are critical elements of climate and global biogeochemical cycles. Following the release of the SOLAS Decadal Science Plan (2015-2025) (Brévière et al., 2016), the Ocean-Atmosphere Interaction Committee (OAIC) was formed as a subcommittee of the Ocean Carbon and Biogeochemistry (OCB) Scientific Steering Committee to coordinate US SOLAS efforts and activities, facilitate interactions among atmospheric and ocean scientists, and strengthen US contributions to international SOLAS. In October 2019, with support from OCB, the OAIC convened an open community workshop, Ocean-Atmosphere Interactions: Scoping directions for new research with the goal of fostering new collaborations and identifying knowledge gaps and high-priority science questions to formulate a US SOLAS Science Plan. Based on presentations and discussions at the workshop, the OAIC and workshop participants have developed this US SOLAS Science Plan. The first part of the workshop and this Science Plan were purposefully designed around the five themes of the SOLAS Decadal Science Plan (2015-2025) (Brévière et al., 2016) to provide a common set of research priorities and ensure a more cohesive US contribution to international SOLAS.This report was developed with federal support of NSF (OCE-1558412) and NASA (NNX17AB17G)

A Randomized Trial of Prophylactic Antibiotics for Miscarriage Surgery.

BACKGROUND: Surgical intervention is needed in some cases of spontaneous abortion to remove retained products of conception. Antibiotic prophylaxis may reduce the risk of pelvic infection, which is an important complication of this surgery, particularly in low-resource countries. METHODS: We conducted a double-blind, placebo-controlled, randomized trial investigating whether antibiotic prophylaxis before surgery to complete a spontaneous abortion would reduce pelvic infection among women and adolescents in low-resource countries. We randomly assigned patients to a single preoperative dose of 400 mg of oral doxycycline and 400 mg of oral metronidazole or identical placebos. The primary outcome was pelvic infection within 14 days after surgery. Pelvic infection was defined by the presence of two or more of four clinical features (purulent vaginal discharge, pyrexia, uterine tenderness, and leukocytosis) or by the presence of one of these features and the clinically identified need to administer antibiotics. The definition of pelvic infection was changed before the unblinding of the data; the original strict definition was two or more of the clinical features, without reference to the administration of antibiotics. RESULTS: We enrolled 3412 patients in Malawi, Pakistan, Tanzania, and Uganda. A total of 1705 patients were assigned to receive antibiotics and 1707 to receive placebo. The risk of pelvic infection was 4.1% (68 of 1676 pregnancies) in the antibiotics group and 5.3% (90 of 1684 pregnancies) in the placebo group (risk ratio, 0.77; 95% confidence interval [CI], 0.56 to 1.04; P = 0.09). Pelvic infection according to original strict criteria was diagnosed in 1.5% (26 of 1700 pregnancies) and 2.6% (44 of 1704 pregnancies), respectively (risk ratio, 0.60; 95% CI, 0.37 to 0.96). There were no significant between-group differences in adverse events. CONCLUSIONS: Antibiotic prophylaxis before miscarriage surgery did not result in a significantly lower risk of pelvic infection, as defined by pragmatic broad criteria, than placebo. (Funded by the Medical Research Council and others; AIMS Current Controlled Trials number, ISRCTN97143849.)