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Abstract Smoke particulate matter emitted by fires in the Amazon Basin poses a threat to human health. Past research on this threat has mainly focused on the health impacts on countries as a whole or has relied on hospital admission data to quantify the health response. Such analyses do not capture the impact on people living in Indigenous territories close to the fires and who often lack access to medical care and may not show up at hospitals. Here we quantify the premature mortality due to smoke exposure of people living in Indigenous territories across the Amazon Basin. We use the atmospheric chemistry transport model GEOS-Chem to simulate PM_2.5from fires and other sources, and we apply a recently updated concentration dose-response function. We estimate that smoke from fires in South America accounted for ∼12 000 premature deaths each year from 2014–2019 across the continent, with about ∼230 of these deaths occurring in Indigenous lands. Put another way, smoke exposure accounts for 2 premature deaths per 100 000 people per year across South America, but 4 premature deaths per 100 000 people in the Indigenous territories. Bolivia and Brazil represent hotspots of smoke exposure and deaths in Indigenous territories in these countries are 9 and 12 per 100 000 people, respectively. Our analysis shows that smoke PM_2.5from fires has a detrimental effect on human health across South America, with a disproportionate impact on people living in Indigenous territories. 

Different analytic techniques operate optimally with different types of data. As the use of EHR-based analytics expands to newer tasks, data will have to be transformed into different representations, so the tasks can be optimally solved. We classified representations into broad categories based on their characteristics and proposed a new knowledge-driven representation for clinical data mining as well as trajectory mining, called Severity Encoding Variables (SEVs). Additionally, we studied which characteristics make representations most suitable for particular clinical analytics tasks including trajectory mining. Our evaluation shows that, for regression, most data representations performed similarly, with SEV achieving a slight (albeit statistically significant) advantage. For patients at high risk of diabetes, it outperformed the competing representation by (relative) 20%. For association mining, SEV achieved the highest performance. Its ability to constrain the search space of patterns through clinical knowledge was key to its success. 

Extensive development of shale gas has generated some concerns about environmental impacts such as the migration of natural gas into water resources. We studied high gas concentrations in waters at a site near Marcellus Shale gas wells to determine the geological explanations and geochemical implications. The local geology may explain why methane has discharged for 7 years into groundwater, a stream, and the atmosphere. Gas may migrate easily near the gas wells in this location where the Marcellus Shale dips significantly, is shallow (∼1 km), and is more fractured. Methane and ethane concentrations in local water wells increased after gas development compared with predrilling concentrations reported in the region. Noble gas and isotopic evidence are consistent with the upward migration of gas from the Marcellus Formation in a free-gas phase. This upflow results in microbially mediated oxidation near the surface. Iron concentrations also increased following the increase of natural gas concentrations in domestic water wells. After several months, both iron and SO 4 2− concentrations dropped. These observations are attributed to iron and SO 4 2− reduction associated with newly elevated concentrations of methane. These temporal trends, as well as data from other areas with reported leaks, document a way to distinguish newly migrated methane from preexisting sources of gas. This study thus documents both geologically risky areas and geochemical signatures of iron and SO 4 2− that could distinguish newly leaked methane from older methane sources in aquifers. 

Abstract Sea turtles are vulnerable to climate change since their reproductive output is influenced by incubating temperatures, with warmer temperatures causing lower hatching success and increased feminization of embryos. Their ability to cope with projected increases in ambient temperatures will depend on their capacity to adapt to shifts in climatic regimes. Here, we assessed the extent to which phenological shifts could mitigate impacts from increases in ambient temperatures (from 1.5 to 3°C in air temperatures and from 1.4 to 2.3°C in sea surface temperatures by 2100 at our sites) on four species of sea turtles, under a “middle of the road” scenario (SSP2‐4.5). Sand temperatures at sea turtle nesting sites are projected to increase from 0.58 to 4.17°C by 2100 and expected shifts in nesting of 26–43 days earlier will not be sufficient to maintain current incubation temperatures at 7 (29%) of our sites, hatching success rates at 10 (42%) of our sites, with current trends in hatchling sex ratio being able to be maintained at half of the sites. We also calculated the phenological shifts that would be required (both backward for an earlier shift in nesting and forward for a later shift) to keep up with present‐day incubation temperatures, hatching success rates, and sex ratios. The required shifts backward in nesting for incubation temperatures ranged from −20 to −191 days, whereas the required shifts forward ranged from +54 to +180 days. However, for half of the sites, no matter the shift the median incubation temperature will always be warmer than the 75th percentile of current ranges. Given that phenological shifts will not be able to ameliorate predicted changes in temperature, hatching success and sex ratio at most sites, turtles may need to use other adaptive responses and/or there is the need to enhance sea turtle resilience to climate warming. 

Abstract ATHENA has been designed as a general purpose detector capable of delivering the full scientific scope of the Electron-Ion Collider. Careful technology choices provide fine tracking and momentum resolution, high performance electromagnetic and hadronic calorimetry, hadron identification over a wide kinematic range, and near-complete hermeticity.This article describes the detector design and its expected performance in the most relevant physics channels. It includes an evaluation of detector technology choices, the technical challenges to realizing the detector and the R&D required to meet those challenges.