Explore the vast range of titles available.

CONTEXT: The urban heat island (UHI) is a well-documented pattern of warming in cities relative to rural areas. Most UHI research utilizes remote sensing methods at large scales, or climate sensors in single cities surrounded by standardized land cover. Relatively few studies have explored continental-scale climatic patterns within common urban microenvironments such as residential landscapes that may affect human comfort. OBJECTIVES: We tested the urban homogenization hypothesis which states that structure and function in cities exhibit ecological “sameness” across diverse regions relative to the native ecosystems they replaced. METHODS: We deployed portable micrometeorological sensors to compare air temperature and humidity in residential yards and native landscapes across six U.S. cities that span a range of climates (Phoenix, AZ; Los Angeles, CA; Minneapolis-St. Paul, MN; Boston, MA; Baltimore, MD; and Miami, FL). RESULTS: Microclimate in residential ecosystems was more similar among cities than among native ecosystems, particularly during the calm morning hours. Maximum regional actual evapotranspiration (AET) was related to the morning residential microclimate effect. Residential yards in cities with maximum AET <50–65 cm/year (Phoenix and Los Angeles) were generally cooler and more humid than nearby native shrublands during summer mornings, while yards in cities above this threshold were generally warmer (Baltimore and Miami) and drier (Miami) than native forests. On average, temperature and absolute humidity were ~6 % less variable among residential ecosystems than among native ecosystems from diverse regions. CONCLUSIONS: These data suggest that common residential land cover and structural characteristics lead to microclimatic convergence across diverse regions at the continental scale.

Although ecosystem services have been intensively examined in certain domains (e.g., forests and wetlands), little research has assessed ecosystem services for the most dominant landscape type in urban ecosystems—namely, residential yards. In this paper, we report findings of a cross-site survey of homeowners in six U.S. cities to 1) examine how residents subjectively value various ecosystem services, 2) explore distinctive dimensions of those values, and 3) test the urban homogenization hypothesis. This hypothesis posits that urbanization leads to similarities in the social-ecological dynamics across cities in diverse biomes. By extension, the thesis suggests that residents’ ecosystem service priorities for residential landscapes will be similar regardless of whether residents live in the humid East or the arid West, or the warm South or the cold North. Results underscored that cultural services were of utmost importance, particularly anthropocentric values including aesthetics, low-maintenance, and personal enjoyment. Using factor analyses, distinctive dimensions of residents’ values were found to partially align with the Millennium Ecosystem Assessment’s categories (provisioning, regulating, supporting, and cultural). Finally, residents’ ecosystem service priorities exhibited significant homogenization across regions. In particular, the traditional lawn aesthetic (neat, green, weed-free yards) was similarly important across residents of diverse U.S. cities. Only a few exceptions were found across different environmental and social contexts; for example, cooling effects were more important in the warm South, where residents also valued aesthetics more than those in the North, where low-maintenance yards were a greater priority.

Every second greater than 10 25 antineutrinos radiate to space from Earth, shining like a faint antineutrino star. Underground antineutrino detectors have revealed the rapidly decaying fission products inside nuclear reactors, verified the long-lived radioactivity inside our planet and informed sensitive experiments for probing fundamental physics. Mapping the anisotropic antineutrino flux and energy spectrum advance geoscience by defining the amount and distribution of radioactive power within Earth while critically evaluating competing compositional models of the planet. We present the Antineutrino Global Map 2015 (AGM2015), an experimentally informed model of Earth’s surface antineutrino flux over the 0 to 11 MeV energy spectrum, along with an assessment of systematic errors. The open source AGM2015 provides fundamental predictions for experiments, assists in strategic detector placement to determine neutrino mass hierarchy and aids in identifying undeclared nuclear reactors. We use cosmochemically and seismologically informed models of the radiogenic lithosphere/mantle combined with the estimated antineutrino flux, as measured by KamLAND and Borexino, to determine the Earth’s total antineutrino luminosity at . We find a dominant flux of geo-neutrinos, predict sub-equal crust and mantle contributions, with ~1% of the total flux from man-made nuclear reactors.

The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is determined, based on a full simulation, reconstruction, and event selection of the far detector and a full simulation and parameterized analysis of the near detector. Detailed uncertainties due to the flux prediction, neutrino interaction model, and detector effects are included. DUNE will resolve the neutrino mass ordering to a precision of 5 σ , for all δ CP values, after 2 years of running with the nominal detector design and beam configuration. It has the potential to observe charge-parity violation in the neutrino sector to a precision of 3 σ (5 σ ) after an exposure of 5 (10) years, for 50% of all δ CP values. It will also make precise measurements of other parameters governing long-baseline neutrino oscillation, and after an exposure of 15 years will achieve a similar sensitivity to sin 2 2 θ 13 to current reactor experiments.

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours.

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours.

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours.

The Earth has cooled since its formation, yet the decay of radiogenic isotopes, and in particular uranium, thorium and potassium, in the planet’s interior provides a continuing heat source. The current total heat flux from the Earth to space is 44.2±1.0 TW, but the relative contributions from residual primordial heat and radiogenic decay remain uncertain. However, radiogenic decay can be estimated from the flux of geoneutrinos, electrically neutral particles that are emitted during radioactive decay and can pass through the Earth virtually unaffected. Here we combine precise measurements of the geoneutrino flux from the Kamioka Liquid-Scintillator Antineutrino Detector, Japan, with existing measurements from the Borexino detector, Italy. We find that decay of uranium-238 and thorium-232 together contribute  TW to Earth’s heat flux. The neutrinos emitted from the decay of potassium-40 are below the limits of detection in our experiments, but are known to contribute 4 TW. Taken together, our observations indicate that heat from radioactive decay contributes about half of Earth’s total heat flux. We therefore conclude that Earth’s primordial heat supply has not yet been exhausted. Relative contributions to Earth’s total heat flux from the radioactive decay of isotopes versus primordial heat are debated. Measurements of geoneutrino particles emitted during radioactive decay in the Earth’s interior indicate that radiogenic isotopes contribute only about half of the total heat flux.

New developments in liquid scintillators, high-efficiency, fast photon detectors, and chromatic photon sorting have opened up the possibility for building a large-scale detector that can discriminate between Cherenkov and scintillation signals. Such a detector could reconstruct particle direction and species using Cherenkov light while also having the excellent energy resolution and low threshold of a scintillator detector. Situated deep underground, and utilizing new techniques in computing and reconstruction, this detector could achieve unprecedented levels of background rejection, enabling a rich physics program spanning topics in nuclear, high-energy, and astrophysics, and across a dynamic range from hundreds of keV to many GeV. The scientific program would include observations of low- and high-energy solar neutrinos, determination of neutrino mass ordering and measurement of the neutrino CP-violating phase δ , observations of diffuse supernova neutrinos and neutrinos from a supernova burst, sensitive searches for nucleon decay and, ultimately, a search for neutrinoless double beta decay, with sensitivity reaching the normal ordering regime of neutrino mass phase space. This paper describes Theia , a detector design that incorporates these new technologies in a practical and affordable way to accomplish the science goals described above.