495 research outputs found
Groundcover community assembly in high-diversity pine savannas: seed arrival and fire-generated environmental filtering
Environmental filtering—abiotic and biotic constraints on the demographic performance of individual organisms—is a widespread mechanism of selection in communities. A given individual is “filtered out” (i.e., selectively removed) when environmental conditions or disturbances like fires preclude its survival and reproduction. Although interactions between these filters and dispersal from the regional species pool are thought to determine much about species composition locally, there have been relatively few studies of dispersal × filtering interactions in species-rich communities and fewer still where fire is also a primary selective agent. We experimentally manipulated dispersal and filtering by fire (pre-fire fuel loads and post-fire ash) in species-rich groundcover communities of the longleaf pine ecosystem. We tested four predictions: (1) That species richness would increase with biologically realistic dispersal (seed addition); (2) that the immediate effect of increased fuels in burned communities would be to decrease species richness, whereas the longer-term effects of increased fuels would be to open recruitment opportunities in the groundcover, increase species richness, and increase individual performance (growth) of immigrating species; (3) that adding ash would increase species richness; and (4) that increased dispersal would generate larger increases in species richness in plots with increased fuels compared to plots with decreased fuels. We found that dispersal interacted with complex fire-generated filtering during and after fires. Dispersal increased species richness more in burned communities with increased and decreased fuels compared to burned controls. Moreover, individuals of immigrating species generally grew to larger sizes in burned communities with increased fuels compared to burned controls. In contrast to dispersal and fuels, ash had no effect on species richness directly or in combination with other treatments. We conclude that filtering occurs both during fires and in the post-fire environment and that these influences interact with dispersal such that the consequences are only fully revealed when all are considered in combination. Our experiment highlights the importance of considering the dynamic interplay of dispersal and selection in the assembly of species-rich communities
Does pyrogenicity protect burning plants?
Pyrogenic plants dominate many fire-prone ecosystems. Their prevalence suggests some advantage to their enhanced flammability, but researchers have had difficulty tying pyrogenicity to individual-level advantages. Based on our review, we propose that enhanced flammability in fire-prone ecosystems should protect the belowground organs and nearby propagules of certain individual plants during fires. We base this hypothesis on five points: (1) organs and propagules by which many fire-adapted plants survive fires are vulnerable to elevated soil temperatures during fires; (2) the degree to which burning plant fuels heat the soil depends mainly on residence times of fires and on fuel location relative to the soil; (3) fires and fire effects are locally heterogeneous, meaning that individual plants can affect local soil heating via their fuels; (4) how a plant burns can thus affect its fitness; and (5) in many cases, natural selection in fire-prone habitats should therefore favor plants that burn rapidly and retain fuels off the ground. We predict an advantage of enhanced flammability for plants whose fuels influence local fire characteristics and whose regenerative tissues or propagules are affected by local variation in fires. Our pyrogenicity as protection hypothesis has the potential to apply to a range of life histories. We discuss implications for ecological and evolutionary theory and suggest considerations for testing the hypothesis. © 2010 by the Ecological Society of America
Translating Radiology Reports into Plain Language using ChatGPT and GPT-4 with Prompt Learning: Promising Results, Limitations, and Potential
The large language model called ChatGPT has drawn extensively attention
because of its human-like expression and reasoning abilities. In this study, we
investigate the feasibility of using ChatGPT in experiments on using ChatGPT to
translate radiology reports into plain language for patients and healthcare
providers so that they are educated for improved healthcare. Radiology reports
from 62 low-dose chest CT lung cancer screening scans and 76 brain MRI
metastases screening scans were collected in the first half of February for
this study. According to the evaluation by radiologists, ChatGPT can
successfully translate radiology reports into plain language with an average
score of 4.27 in the five-point system with 0.08 places of information missing
and 0.07 places of misinformation. In terms of the suggestions provided by
ChatGPT, they are general relevant such as keeping following-up with doctors
and closely monitoring any symptoms, and for about 37% of 138 cases in total
ChatGPT offers specific suggestions based on findings in the report. ChatGPT
also presents some randomness in its responses with occasionally
over-simplified or neglected information, which can be mitigated using a more
detailed prompt. Furthermore, ChatGPT results are compared with a newly
released large model GPT-4, showing that GPT-4 can significantly improve the
quality of translated reports. Our results show that it is feasible to utilize
large language models in clinical education, and further efforts are needed to
address limitations and maximize their potential
Fuels and fires influence vegetation via above- and below-ground pathways in a high-diversity plant community
1. Fire strongly influences plant populations and communities around the world, making it an important agent of plant evolution. Fire influences vegetation through multiple pathways, both above- and belowground. Few studies have yet attempted to tie these pathways together in a mechanistic way through soil heating even though the importance of soil heating for plants in fire-prone ecosystems is increasingly recognized. 2. Here we combine an experimental approach with structural equation modelling (SEM) to simultaneously examine multiple pathways through which fire might influence herbaceous vegetation. In a high-diversity longleaf pine groundcover community in Louisiana, USA, we manipulated fine-fuel biomass and monitored the resulting fires with high-resolution thermocouples placed in vertical profile above- and belowground. 3. We predicted that vegetation response to burning would be inversely related to fuel load owing to relationships among fuels, fire temperature, duration and soil heating. 4. We found that fuel manipulations altered fire properties and vegetation responses, of which soil heating proved to be a highly accurate predictor. Fire duration acting through soil heating was important for vegetation response in our SEMs, whereas fire temperature was not. 5. Our results indicate that in this herbaceous plant community, fire duration is a good predictor of soil heating and therefore of vegetation response to fire. Soil heating may be the key determinant of vegetation response to fire in ecosystems wherein plants persist by resprouting or reseeding from soil-stored propagules. 6. Synthesis. Our SEMs demonstrate how the complex pathways through which fires influence plant community structure and dynamics can be examined simultaneously. Comparative studies of these pathways across different communities will provide important insights into the ecology, evolution and conservation of fire-prone ecosystems
Patient Awareness and Approval for an Opt-Out Genomic Biorepository
Aim: In this study, we sought to assess patient awareness and perceptions of an opt-out biorepository. Materials & methods: We conducted exit interviews with adult patients and parents of pediatric patients having their blood drawn as part of their clinical care at Vanderbilt University Medical Center (TN, USA). Results: 32.9% of all patients and parents of pediatric patients report having heard of the opt-out biorepository, while 92.4% approve of this research effort based on a brief description. Awareness that leftover blood could be used for research increased among adult patients during the study period, from 34.3 to 50.0%. Conclusion: These findings will inform ongoing assessments of the suitability of opt-out and opt-in methods as alternatives to written informed consent for inclusion in a biorepository
The Time-Domain Spectroscopic Survey: Understanding the Optically Variable Sky with SEQUELS in SDSS-III
The Time-Domain Spectroscopic Survey (TDSS) is an SDSS-IV eBOSS subproject
primarily aimed at obtaining identification spectra of ~220,000
optically-variable objects systematically selected from SDSS/Pan-STARRS1
multi-epoch imaging. We present a preview of the science enabled by TDSS, based
on TDSS spectra taken over ~320 deg^2 of sky as part of the SEQUELS survey in
SDSS-III, which is in part a pilot survey for eBOSS in SDSS-IV. Using the
15,746 TDSS-selected single-epoch spectra of photometrically variable objects
in SEQUELS, we determine the demographics of our variability-selected sample,
and investigate the unique spectral characteristics inherent in samples
selected by variability. We show that variability-based selection of quasars
complements color-based selection by selecting additional redder quasars, and
mitigates redshift biases to produce a smooth quasar redshift distribution over
a wide range of redshifts. The resulting quasar sample contains systematically
higher fractions of blazars and broad absorption line quasars than from
color-selected samples. Similarly, we show that M-dwarfs in the TDSS-selected
stellar sample have systematically higher chromospheric active fractions than
the underlying M-dwarf population, based on their H-alpha emission. TDSS also
contains a large number of RR Lyrae and eclipsing binary stars with
main-sequence colors, including a few composite-spectrum binaries. Finally, our
visual inspection of TDSS spectra uncovers a significant number of peculiar
spectra, and we highlight a few cases of these interesting objects. With a
factor of ~15 more spectra, the main TDSS survey in SDSS-IV will leverage the
lessons learned from these early results for a variety of time-domain science
applications.Comment: 17 pages, 14 figures, submitted to Ap
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Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons
Purpose: The Medical Imaging and Data Resource Center (MIDRC) open data commons was launched to accelerate the development of artificial intelligence (AI) algorithms to help address the COVID-19 pandemic. The purpose of this study was to quantify longitudinal representativeness of the demographic characteristics of the primary MIDRC dataset compared to the United States general population (US Census) and COVID-19 positive case counts from the Centers for Disease Control and Prevention (CDC). Approach: The Jensen-Shannon distance (JSD), a measure of similarity of two distributions, was used to longitudinally measure the representativeness of the distribution of (1) all unique patients in the MIDRC data to the 2020 US Census and (2) all unique COVID-19 positive patients in the MIDRC data to the case counts reported by the CDC. The distributions were evaluated in the demographic categories of age at index, sex, race, ethnicity, and the combination of race and ethnicity. Results: Representativeness of the MIDRC data by ethnicity and the combination of race and ethnicity was impacted by the percentage of CDC case counts for which this was not reported. The distributions by sex and race have retained their level of representativeness over time. Conclusion: The representativeness of the open medical imaging datasets in the curated public data commons at MIDRC has evolved over time as the number of contributing institutions and overall number of subjects have grown. The use of metrics, such as the JSD support measurement of representativeness, is one step needed for fair and generalizable AI algorithm development.</p
Baryon Acoustic Oscillations in the Ly{\alpha} forest of BOSS DR11 quasars
We report a detection of the baryon acoustic oscillation (BAO) feature in the
flux-correlation function of the Ly{\alpha} forest of high-redshift quasars
with a statistical significance of five standard deviations. The study uses
137,562 quasars in the redshift range from the Data Release
11 (DR11) of the Baryon Oscillation Spectroscopic Survey (BOSS) of SDSS-III.
This sample contains three times the number of quasars used in previous
studies. The measured position of the BAO peak determines the angular distance,
and expansion rate, , both on a scale set by the sound
horizon at the drag epoch, . We find
and
where . The optimal
combination, is determined with a precision of
. For the value , consistent with the CMB power
spectrum measured by Planck, we find
and . Tests with mock
catalogs and variations of our analysis procedure have revealed no systematic
uncertainties comparable to our statistical errors. Our results agree with the
previously reported BAO measurement at the same redshift using the
quasar-Ly{\alpha} forest cross-correlation. The auto-correlation and
cross-correlation approaches are complementary because of the quite different
impact of redshift-space distortion on the two measurements. The combined
constraints from the two correlation functions imply values of and
that are, respectively, 7% low and 7% high compared to the
predictions of a flat CDM cosmological model with the best-fit Planck
parameters. With our estimated statistical errors, the significance of this
discrepancy is .Comment: Accepted for publication in A&A. 17 pages, 18 figure
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