Showing papers by "University of Oregon published in 2021"

Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog

Abstract: We report on the population of 47 compact binary mergers detected with a false-alarm rate of 0.01 are dynamically assembled. Third, we estimate merger rates, finding RBBH = 23.9-+8.614.3 Gpc-3 yr-1 for BBHs and RBNS = 320-+240490 Gpc-3 yr-1 for binary neutron stars. We find that the BBH rate likely increases with redshift (85% credibility) but not faster than the star formation rate (86% credibility). Additionally, we examine recent exceptional events in the context of our population models, finding that the asymmetric masses of GW190412 and the high component masses of GW190521 are consistent with our models, but the low secondary mass of GW190814 makes it an outlier.

Observation of Gravitational Waves from Two Neutron Star–Black Hole Coalescences

Abstract: We report the observation of gravitational waves from two compact binary coalescences in LIGO’s and Virgo’s third observing run with properties consistent with neutron star–black hole (NSBH) binaries. The two events are named GW200105_162426 and GW200115_042309, abbreviated as GW200105 and GW200115; the first was observed by LIGO Livingston and Virgo and the second by all three LIGO–Virgo detectors. The source of GW200105 has component masses 8.9−1.5+1.2 and 1.9−0.2+0.3M⊙ , whereas the source of GW200115 has component masses 5.7−2.1+1.8 and 1.5−0.3+0.7M⊙ (all measurements quoted at the 90% credible level). The probability that the secondary’s mass is below the maximal mass of a neutron star is 89%–96% and 87%–98%, respectively, for GW200105 and GW200115, with the ranges arising from different astrophysical assumptions. The source luminosity distances are 280−110+110 and 300−100+150Mpc , respectively. The magnitude of the primary spin of GW200105 is less than 0.23 at the 90% credible level, and its orientation is unconstrained. For GW200115, the primary spin has a negative spin projection onto the orbital angular momentum at 88% probability. We are unable to constrain the spin or tidal deformation of the secondary component for either event. We infer an NSBH merger rate density of 45−33+75Gpc−3yr−1 when assuming that GW200105 and GW200115 are representative of the NSBH population or 130−69+112Gpc−3yr−1 under the assumption of a broader distribution of component masses.

Mental health and clinical psychological science in the time of COVID-19: Challenges, opportunities, and a call to action.

Abstract: COVID-19 presents significant social, economic, and medical challenges. Because COVID-19 has already begun to precipitate huge increases in mental health problems, clinical psychological science must assert a leadership role in guiding a national response to this secondary crisis. In this article, COVID-19 is conceptualized as a unique, compounding, multidimensional stressor that will create a vast need for intervention and necessitate new paradigms for mental health service delivery and training. Urgent challenge areas across developmental periods are discussed, followed by a review of psychological symptoms that likely will increase in prevalence and require innovative solutions in both science and practice. Implications for new research directions, clinical approaches, and policy issues are discussed to highlight the opportunities for clinical psychological science to emerge as an updated, contemporary field capable of addressing the burden of mental illness and distress in the wake of COVID-19 and beyond. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Ligand-engineered bandgap stability in mixed-halide perovskite LEDs.

Abstract: Lead halide perovskites are promising semiconductors for light-emitting applications because they exhibit bright, bandgap-tunable luminescence with high colour purity1,2. Photoluminescence quantum yields close to unity have been achieved for perovskite nanocrystals across a broad range of emission colours, and light-emitting diodes with external quantum efficiencies exceeding 20 per cent-approaching those of commercial organic light-emitting diodes-have been demonstrated in both the infrared and the green emission channels1,3,4. However, owing to the formation of lower-bandgap iodide-rich domains, efficient and colour-stable red electroluminescence from mixed-halide perovskites has not yet been realized5,6. Here we report the treatment of mixed-halide perovskite nanocrystals with multidentate ligands to suppress halide segregation under electroluminescent operation. We demonstrate colour-stable, red emission centred at 620 nanometres, with an electroluminescence external quantum efficiency of 20.3 per cent. We show that a key function of the ligand treatment is to 'clean' the nanocrystal surface through the removal of lead atoms. Density functional theory calculations reveal that the binding between the ligands and the nanocrystal surface suppresses the formation of iodine Frenkel defects, which in turn inhibits halide segregation. Our work exemplifies how the functionality of metal halide perovskites is extremely sensitive to the nature of the (nano)crystalline surface and presents a route through which to control the formation and migration of surface defects. This is critical to achieve bandgap stability for light emission and could also have a broader impact on other optoelectronic applications-such as photovoltaics-for which bandgap stability is required.

Development of Quantum Interconnects (QuICs) for Next-Generation Information Technologies

Abstract: Just as classical information technology rests on a foundation built of interconnected information-processing systems, quantum information technology (QIT) must do the same. A critical component of such systems is the interconnect, a device or process that allows transfer of information between disparate physical media, for example, semiconductor electronics, individual atoms, light pulses in optical fiber, or microwave fields. While interconnects have been well engineered for decades in the realm of classical information technology, quantum interconnects (QuICs) present special challenges, as they must allow the transfer of fragile quantum states between different physical parts or degrees of freedom of the system. The diversity of QIT platforms (superconducting, atomic, solid-state color center, optical, etc.) that will form a quantum internet poses additional challenges. As quantum systems scale to larger size, the quantum interconnect bottleneck is imminent, and is emerging as a grand challenge for QIT. For these reasons, it is the position of the community represented by participants of the NSF workshop on Quantum Interconnects that accelerating QuIC research is crucial for sustained development of a national quantum science and technology program. Given the diversity of QIT platforms, materials used, applications, and infrastructure required, a convergent research program including partnership between academia, industry and national laboratories is required.

A gravitational-wave measurement of the Hubble constant following the second observing run of Advanced LIGO and Virgo

Abstract: This paper presents the gravitational-wave measurement of the Hubble constant (H 0) using the detections from the first and second observing runs of the Advanced LIGO and Virgo detector network. The presence of the transient electromagnetic counterpart of the binary neutron star GW170817 led to the first standard-siren measurement of H 0. Here we additionally use binary black hole detections in conjunction with galaxy catalogs and report a joint measurement. Our updated measurement is H 0 = km s−1 Mpc−1 (68.3% of the highest density posterior interval with a flat-in-log prior) which is an improvement by a factor of 1.04 (about 4%) over the GW170817-only value of km s−1 Mpc−1. A significant additional contribution currently comes from GW170814, a loud and well-localized detection from a part of the sky thoroughly covered by the Dark Energy Survey. With numerous detections anticipated over the upcoming years, an exhaustive understanding of other systematic effects are also going to become increasingly important. These results establish the path to cosmology using gravitational-wave observations with and without transient electromagnetic counterparts.

Fluorination-enabled Reconstruction of NiFe Electrocatalysts for Efficient Water Oxidation.

Abstract: Developing low-cost and efficient electrocatalysts to accelerate oxygen evolution reaction (OER) kinetics is vital for water and carbon-dioxide electrolyzers. The fastest-known water oxidation catalyst, Ni(Fe)OxHy, usually produced through an electrochemical reconstruction of precatalysts under alkaline condition, has received substantial attention. However, the reconstruction in the reported catalysts usually leads to a limited active layer and poorly controlled Fe-activated sites. Here, we demonstrate a new electrochemistry-driven F-enabled surface-reconstruction strategy for converting the ultrathin NiFeOxFy nanosheets into an Fe-enriched Ni(Fe)OxHy phase. The activated electrocatalyst shows a low OER overpotential of 218 ± 5 mV at 10 mA cm-2 and a low Tafel slope of 31 ± 4 mV dec-1, which is among the best for NiFe-based OER electrocatalysts. Such superior performance is caused by the effective formation of the Fe-enriched Ni(Fe)OxHy active-phase that is identified by operando Raman spectroscopy and the substantially improved surface wettability and gas-bubble-releasing behavior.

Upper limits on the isotropic gravitational-wave background from Advanced LIGO and Advanced Virgo’s third observing run

Abstract: We report results of a search for an isotropic gravitational-wave background (GWB) using data from Advanced LIGO’s and Advanced Virgo’s third observing run (O3) combined with upper limits from the earlier O1 and O2 runs. Unlike in previous observing runs in the advanced detector era, we include Virgo in the search for the GWB. The results of the search are consistent with uncorrelated noise, and therefore we place upper limits on the strength of the GWB. We find that the dimensionless energy density Ω GW ≤ 5.8 × 10 − 9 at the 95% credible level for a flat (frequency-independent) GWB, using a prior which is uniform in the log of the strength of the GWB, with 99% of the sensitivity coming from the band 20–76.6 Hz; Ω GW ( f ) ≤ 3.4 × 10 − 9 at 25 Hz for a power-law GWB with a spectral index of 2 / 3 (consistent with expectations for compact binary coalescences), in the band 20–90.6 Hz; and Ω GW ( f ) ≤ 3.9 × 10 − 10 at 25 Hz for a spectral index of 3, in the band 20–291.6 Hz. These upper limits improve over our previous results by a factor of 6.0 for a flat GWB, 8.8 for a spectral index of 2 / 3 , and 13.1 for a spectral index of 3. We also search for a GWB arising from scalar and vector modes, which are predicted by alternative theories of gravity; we do not find evidence of these, and place upper limits on the strength of GWBs with these polarizations. We demonstrate that there is no evidence of correlated noise of magnetic origin by performing a Bayesian analysis that allows for the presence of both a GWB and an effective magnetic background arising from geophysical Schumann resonances. We compare our upper limits to a fiducial model for the GWB from the merger of compact binaries, updating the model to use the most recent data-driven population inference from the systems detected during O3a. Finally, we combine our results with observations of individual mergers and show that, at design sensitivity, this joint approach may yield stronger constraints on the merger rate of binary black holes at z ≳ 2 than can be achieved with individually resolved mergers alone.

Jet energy scale and resolution measured in proton-proton collisions at s =13 TeV with the ATLAS detector

Abstract: Jet energy scale and resolution measurements with their associated uncertainties are reported for jets using 36-81 fb$^{-1}$ of proton-proton collision data with a centre-of-mass energy of $\sqrt{s}=13$ TeV collected by the ATLAS detector at the LHC. Jets are reconstructed using two different input types: topo-clusters formed from energy deposits in calorimeter cells, as well as an algorithmic combination of charged-particle tracks with those topo-clusters, referred to as the ATLAS particle-flow reconstruction method. The anti-$k_t$ jet algorithm with radius parameter $R=0.4$ is the primary jet definition used for both jet types. Jets are initially calibrated using a sequence of simulation-based corrections. Next, several $\textit{in situ}$ techniques are employed to correct for differences between data and simulation and to measure the resolution of jets. The systematic uncertainties in the jet energy scale for central jets ($|\eta| 2.5$ TeV). The relative jet energy resolution is measured and ranges from ($24 \pm 1.5$)% at 20 GeV to ($6 \pm 0.5$)% at 300 GeV.

Atomically precise single-crystal structures of electrically conducting 2D metal–organic frameworks

Abstract: Electrically conducting 2D metal–organic frameworks (MOFs) have attracted considerable interest, as their hexagonal 2D lattices mimic graphite and other 2D van der Waals stacked materials. However, understanding their intrinsic properties remains a challenge because their crystals are too small or of too poor quality for crystal structure determination. Here, we report atomically precise structures of a family of 2D π-conjugated MOFs derived from large single crystals of sizes up to 200 μm, allowing atomic-resolution analysis by a battery of high-resolution diffraction techniques. A designed ligand core rebalances the in-plane and out-of-plane interactions that define anisotropic crystal growth. We report two crystal structure types exhibiting analogous 2D honeycomb-like sheets but distinct packing modes and pore contents. Single-crystal electrical transport measurements distinctively demonstrate anisotropic transport normal and parallel to the π-conjugated sheets, revealing a clear correlation between absolute conductivity and the nature of the metal cation and 2D sheet packing motif. Two-dimensional MOFs can possess porosity and electrical conductivity but are difficult to grow as single crystals. Here, by balancing in-plane and out-of-plane interactions, single crystals of sizes up to 200 µm are grown, allowing in-plane transport measurements and atomic-resolution analysis.

Human alteration of global surface water storage variability.

Abstract: Knowing the extent of human influence on the global hydrological cycle is essential for the sustainability of freshwater resources on Earth1,2. However, a lack of water level observations for the world’s ponds, lakes and reservoirs has limited the quantification of human-managed (reservoir) changes in surface water storage compared to its natural variability3. The global storage variability in surface water bodies and the extent to which it is altered by humans therefore remain unknown. Here we show that 57 per cent of the Earth’s seasonal surface water storage variability occurs in human-managed reservoirs. Using measurements from NASA’s ICESat-2 satellite laser altimeter, which was launched in late 2018, we assemble an extensive global water level dataset that quantifies water level variability for 227,386 water bodies from October 2018 to July 2020. We find that seasonal variability in human-managed reservoirs averages 0.86 metres, whereas natural water bodies vary by only 0.22 metres. Natural variability in surface water storage is greatest in tropical basins, whereas human-managed variability is greatest in the Middle East, southern Africa and the western USA. Strong regional patterns are also found, with human influence driving 67 per cent of surface water storage variability south of 45 degrees north and nearly 100 per cent in certain arid and semi-arid regions. As economic development, population growth and climate change continue to pressure global water resources4, our approach provides a useful baseline from which ICESat-2 and future satellite missions will be able to track human modifications to the global hydrologic cycle. Data from the ICESat-2 satellite quantifying the variability of water levels in natural and human-managed water bodies show that a disproportionate majority of global water storage variability occurs in human-managed reservoirs.

Secondary Transition Predictors of Postschool Success: An Update to the Research Base:

Abstract: Research suggests youth with disabilities are less likely to experience positive outcomes compared to peers without disabilities. Identification of in-school predictors of postschool success can pr...

Global impact of COVID-19 on stroke care.

Abstract: BackgroundThe COVID-19 pandemic led to profound changes in the organization of health care systems worldwide.AimsWe sought to measure the global impact of the COVID-19 pandemic on the volumes for m...

LIGO Detector Characterization in the Second and Third Observing Runs

Abstract: The characterization of the Advanced LIGO detectors in the second and third observing runs has increased the sensitivity of the instruments, allowing for a higher number of detectable gravitational-wave signals, and provided confirmation of all observed gravitational-wave events. In this work, we present the methods used to characterize the LIGO detectors and curate the publicly available datasets, including the LIGO strain data and data quality products. We describe the essential role of these datasets in LIGO–Virgo Collaboration analyses of gravitational-waves from both transient and persistent sources and include details on the provenance of these datasets in order to support analyses of LIGO data by the broader community. Finally, we explain anticipated changes in the role of detector characterization and current efforts to prepare for the high rate of gravitational-wave alerts and events in future observing runs.

Humans and Technology: Forms of Conjoined Agency in Organizations

Abstract: Organizations are increasingly deploying technologies that have the ability to parse through large amounts of data, acquire skills and knowledge, and operate autonomously. These technologies diverg...

An Integrative approach to supply chain disruption risk and resilience management: a literature review

Abstract: A fundamental question in supply chain resilience is identifying its antecedents and investigating the relative importance of each antecedent in improving resilience to supply chain disruptions. In...

Muon reconstruction and identification efficiency in ATLAS using the full Run 2 pp collision data set at √ s = 13 TeV

Abstract: This article documents the muon reconstruction and identification efficiency obtained by the ATLAS experiment for 139 $$\hbox {fb}^{-1}$$ fb - 1 of pp collision data at $$\sqrt{s}=13$$ s = 13 TeV collected between 2015 and 2018 during Run 2 of the LHC. The increased instantaneous luminosity delivered by the LHC over this period required a reoptimisation of the criteria for the identification of prompt muons. Improved and newly developed algorithms were deployed to preserve high muon identification efficiency with a low misidentification rate and good momentum resolution. The availability of large samples of $$Z\rightarrow \mu \mu $$ Z → μ μ and $$J/\psi \rightarrow \mu \mu $$ J / ψ → μ μ decays, and the minimisation of systematic uncertainties, allows the efficiencies of criteria for muon identification, primary vertex association, and isolation to be measured with an accuracy at the per-mille level in the bulk of the phase space, and up to the percent level in complex kinematic configurations. Excellent performance is achieved over a range of transverse momenta from 3 GeV to several hundred GeV, and across the full muon detector acceptance of $$|\eta |<2.7$$ | η | < 2.7 .

The climate change mitigation effects of daily active travel in cities

Abstract: Active travel (walking or cycling for transport) is considered the most sustainable form of personal transport. Yet its net effects on mobility-related CO2 emissions are complex and under-researched. Here we collected travel activity data in seven European cities and derived life cycle CO2 emissions across modes and purposes. Daily mobility-related life cycle CO2 emissions were 3.2 kgCO2 per person, with car travel contributing 70% and cycling 1%. Cyclists had 84% lower life cycle CO2 emissions than non-cyclists. Life cycle CO2 emissions decreased by −14% per additional cycling trip and decreased by −62% for each avoided car trip. An average person who ‘shifted travel modes’ from car to bike decreased life cycle CO2 emissions by 3.2 kgCO2/day. Promoting active travel should be a cornerstone of strategies to meet net zero carbon targets, particularly in urban areas, while also improving public health and quality of urban life.

The hygiene hypothesis, the COVID pandemic, and consequences for the human microbiome.

Abstract: The COVID-19 pandemic has the potential to affect the human microbiome in infected and uninfected individuals, having a substantial impact on human health over the long term. This pandemic intersects with a decades-long decline in microbial diversity and ancestral microbes due to hygiene, antibiotics, and urban living (the hygiene hypothesis). High-risk groups succumbing to COVID-19 include those with preexisting conditions, such as diabetes and obesity, which are also associated with microbiome abnormalities. Current pandemic control measures and practices will have broad, uneven, and potentially long-term effects for the human microbiome across the planet, given the implementation of physical separation, extensive hygiene, travel barriers, and other measures that influence overall microbial loss and inability for reinoculation. Although much remains uncertain or unknown about the virus and its consequences, implementing pandemic control practices could significantly affect the microbiome. In this Perspective, we explore many facets of COVID-19-induced societal changes and their possible effects on the microbiome, and discuss current and future challenges regarding the interplay between this pandemic and the microbiome. Recent recognition of the microbiome's influence on human health makes it critical to consider both how the microbiome, shaped by biosocial processes, affects susceptibility to the coronavirus and, conversely, how COVID-19 disease and prevention measures may affect the microbiome. This knowledge may prove key in prevention and treatment, and long-term biological and social outcomes of this pandemic.

The climate change mitigation impacts of active travel: Evidence from a longitudinal panel study in seven European cities

Abstract: Active travel (walking or cycling for transport) is considered the most sustainable and low carbon form of getting from A to B Yet the net effects of changes in active travel on changes in mobility-related CO2 emissions are complex and under-researched Here we collected longitudinal data on daily travel behavior, journey purpose, as well as personal and geospatial characteristics in seven European cities and derived mobility-related lifecycle CO2 emissions over time and space Statistical modelling of longitudinal panel (n = 1849) data was performed to assess how changes in active travel, the ‘main mode’ of daily travel, and cycling frequency influenced changes in mobility-related lifecycle CO2 emissions We found that changes in active travel have significant lifecycle carbon emissions benefits, even in European urban contexts with already high walking and cycling shares An increase in cycling or walking consistently and independently decreased mobility-related lifecycle CO2 emissions, suggesting that active travel substituted for motorized travel – ie the increase was not just additional (induced) travel over and above motorized travel To illustrate this, an average person cycling 1 trip/day more and driving 1 trip/day less for 200 days a year would decrease mobility-related lifecycle CO2 emissions by about 05 tonnes over a year, representing a substantial share of average per capita CO2 emissions from transport The largest benefits from shifts from car to active travel were for business purposes, followed by social and recreational trips, and commuting to work or place of education Changes to commuting emissions were more pronounced for those who were younger, lived closer to work and further to a public transport station Even if not all car trips could be substituted by active travel the potential for decreasing emissions is considerable and significant The study gives policy and practice the empirical evidence needed to assess climate change mitigation impacts of urban transport measures and interventions aimed at mode shift to more sustainable modes of transport Investing in and promoting active travel whilst ‘demoting’ private car ownership and use should be a cornerstone of strategies to meet ‘net zero’ carbon targets, particularly in urban areas, while also reducing inequalities and improving public health and quality of urban life in a post-COVID-19 world

NBD-based synthetic probes for sensing small molecules and proteins: design, sensing mechanisms and biological applications

Abstract: Compounds with a nitrobenzoxadiazole (NBD) skeleton exhibit prominent useful properties including environmental sensitivity, high reactivity toward amines and biothiols (including H2S) accompanied by distinct colorimetric and fluorescent changes, fluorescence-quenching ability, and small size, all of which facilitate biomolecular sensing and self-assembly. Amines are important biological nucleophiles, and the unique activity of NBD ethers with amines has allowed for site-specific protein labelling and for the detection of enzyme activities. Both H2S and biothiols are involved in a wide range of physiological processes in mammals, and misregulation of these small molecules is associated with numerous diseases including cancers. In this review, we focus on NBD-based synthetic probes as advanced chemical tools for biomolecular sensing. Specifically, we discuss the sensing mechanisms and selectivity of the probes, the design strategies for multi-reactable multi-quenching probes, and the associated biological applications of these important constructs. We also highlight self-assembled NBD-based probes and outline future directions for NBD-based chemosensors. We hope that this comprehensive review will facilitate the development of future probes for investigating and understanding different biological processes and aid the development of potential theranostic agents.

Digital Cognitive Behavioral Therapy for Insomnia Promotes Later Health Resilience During the Coronavirus Disease 19 (COVID-19) Pandemic.

Abstract: Study objectives Stressful life events contribute to insomnia, psychosocial functioning, and illness. Though individuals with a history of insomnia may be especially vulnerable during stressful life events, risk may be mitigated by prior intervention. This study evaluated the effect of prior digital cognitive-behavioral therapy for insomnia (dCBT-I) versus sleep education on health resilience during the COVID-19 pandemic. Methods COVID impact, insomnia, general- and COVID-related stress, depression, and global health were assessed in April 2020 in adults with a history of insomnia who completed a randomized controlled trial of dCBT-I (n = 102) versus sleep education control (n = 106) in 2016-2017. Regression analyses were used to evaluate the effect of intervention conditions on subsequent stress and health during the pandemic. Results Insomnia symptoms were significantly associated with COVID-19 related disruptions, and those who previously received dCBT-I reported less insomnia symptoms, less general stress and COVID-related cognitive intrusions, less depression, and better global health than those who received sleep education. Moreover, the odds for resurgent insomnia was 51% lower in the dCBT-I versus control condition. Similarly, odds of moderate to severe depression during COVID-19 was 57% lower in the dCBT-I condition. Conclusions Those who received dCBT-I had increased health resilience during the COVID-19 pandemic in adults with a history of insomnia and ongoing mild to moderate mental health symptoms. These data provide evidence that dCBT-I is a powerful tool to promote mental and physical health during stressors, including the COVID-19 pandemic. Clinical trial registration NCT02988375.

Contracting in the Smart Era: The Implications of Blockchain and Decentralized Autonomous Organizations for Contracting and Corporate Governance

Abstract: This paper explores blockchain technology’s potential to alter contracting both in the market and within organizations. We identify and discuss how blockchain reduces certain types of transaction c...

A Multilab Replication of the Ego Depletion Effect.

Abstract: There is an active debate regarding whether the ego depletion effect is real. A recent preregistered experiment with the Stroop task as the depleting task and the antisaccade task as the outcome task found a medium-level effect size. In the current research, we conducted a preregistered multilab replication of that experiment. Data from 12 labs across the globe (N = 1,775) revealed a small and significant ego depletion effect, d = 0.10. After excluding participants who might have responded randomly during the outcome task, the effect size increased to d = 0.16. By adding an informative, unbiased data point to the literature, our findings contribute to clarifying the existence, size, and generality of ego depletion.

Constraints on Cosmic Strings Using Data from the Third Advanced LIGO–Virgo Observing Run

Abstract: We search for gravitational-wave signals produced by cosmic strings in the Advanced LIGO and Virgo full O3 dataset Search results are presented for gravitational waves produced by cosmic string loop features such as cusps, kinks, and, for the first time, kink-kink collisions A template-based search for short-duration transient signals does not yield a detection We also use the stochastic gravitational-wave background energy density upper limits derived from the O3 data to constrain the cosmic string tension Gμ as a function of the number of kinks, or the number of cusps, for two cosmic string loop distribution models Additionally, we develop and test a third model that interpolates between these two models Our results improve upon the previous LIGO-Virgo constraints on Gμ by 1 to 2 orders of magnitude depending on the model that is tested In particular, for the one-loop distribution model, we set the most competitive constraints to date: Gμ≲4×10^{-15} In the case of cosmic strings formed at the end of inflation in the context of grand unified theories, these results challenge simple inflationary models

Unwatched Pollution: The Effect of Intermittent Monitoring on Air Quality

Abstract: Intermittent monitoring of environmental standards may induce strategic changes in polluting activities. This paper documents local strategic responses to a cyclical, once-every-six-day air quality monitoring schedule under the federal Clean Air Act. Using satellite data of monitored areas, I show that air quality is significantly worse on unmonitored days. This effect is explained by short-term suppression of pollution on monitored days, especially during high-pollution periods when the city's noncompliance risk is high. Cities' use of air quality warnings increases on monitored days, which suggests local governments' role in coordinating emission reductions.

Soil-plant-atmosphere interactions: structure, function, and predictive scaling for climate change mitigation

Abstract: It is well established that the functioning of terrestrial ecosystems depends on biophysical and biogeochemical feedbacks occurring at the soil-plant-atmosphere (SPA) interface. However, dynamic biophysical and biogeochemical processes that operate at local scales are seldom studied in conjunction with structural ecosystem properties that arise from broad environmental constraints. As a result, the effect of SPA interactions on how ecosystems respond to, and exert influence on, the global environment remains difficult to predict. We review recent findings that link structural and functional SPA interactions and evaluate their potential for predicting ecosystem responses to chronic environmental pressures. Specifically, we propose a quantitative framework for the integrated analysis of three major plant functional groups (evergreen conifers, broadleaf deciduous, and understory shrubs) and their distinct mycorrhizal symbionts under rising levels of carbon dioxide, changing climate, and disturbance regime. First, we explain how symbiotic and competitive strategies involving plants and soil microorganisms influence scale-free patterns of carbon, nutrient, and water use from individual organisms to landscapes. We then focus on the relationship between those patterns and structural traits such as specific leaf area, leaf area index, and soil physical and chemical properties that constrain root connectivity and canopy gas exchange. Finally, we use those relationships to predict how changes in ecosystem structure may affect processes that are important for climate stability. On the basis of emerging ecological theory and empirical biophysical and biogeochemical knowledge, we propose ten interpretive hypotheses that serve as a primary set of hierarchical relationships (or scaling rules), by which local SPA interactions can be spatially and temporally aggregated to inform broad climate change mitigation efforts. To this end, we provide a series of numerical formulations that simplify the net outcome of complex SPA interactions as a first step towards anticipating shifts in terrestrial carbon, water, and nutrient cycles.

Current Best Practice for Presenting Probabilities in Patient Decision Aids: Fundamental Principles

Abstract: BackgroundShared decision making requires evidence to be conveyed to the patient in a way they can easily understand and compare. Patient decision aids facilitate this process. This article reviews...