109 research outputs found
Generalized Cross-Validation as a Method of Hyperparameter Search for MTGV Regularization
The concept of generalized cross-validation (GCV) is applied to modified
total generalized variation (MTGV) regularization. Current implementations of
the MTGV regularization rely on manual (or semi-manual) hyperparameter
optimization, which is both time-consuming and subject to bias. The combination
of MTGV-regularization and GCV allows for a straightforward hyperparameter
search during regularization. This significantly increases the efficiency of
the MTGV-method, because it limits the number of hyperparameters, which have to
be tested and, improves the practicality of MTGV regularization as a standard
technique for inversion of NMR signals. The combined method is applied to
simulated and experimental NMR data and the resulting reconstructed
distributions are presented. It is shown that for all data sets studied the
proposed combination of MTGV and GCV minimizes the GCV score allowing an
optimal hyperparameter choice
Infrared Emission from the Nearby Cool Core Cluster Abell 2597
We observed the brightest central galaxy (BCG) in the nearby (z=0.0821) cool
core galaxy cluster Abell 2597 with the IRAC and MIPS instruments on board the
Spitzer Space Telescope. The BCG was clearly detected in all Spitzer
bandpasses, including the 70 and 160 micron wavebands. We report aperture
photometry of the BCG. The spectral energy distribution exhibits a clear excess
in the FIR over a Rayleigh-Jeans stellar tail, indicating a star formation rate
of ~4-5 solar masses per year, consistent with the estimates from the UV and
its H-alpha luminosity. This large FIR luminosity is consistent with that of a
starburst or a Luminous Infrared Galaxy (LIRG), but together with a very
massive and old population of stars that dominate the energy output of the
galaxy. If the dust is at one temperature, the ratio of 70 to 160 micron fluxes
indicate that the dust emitting mid-IR in this source is somewhat hotter than
the dust emitting mid-IR in two BCGs at higher-redshift (z~0.2-0.3) and higher
FIR luminosities observed earlier by Spitzer, in clusters Abell 1835 and Zwicky
3146.Comment: Accepted at Ap
De-implementation of low value castration for men with prostate cancer: protocol for a theory-based, mixed methods approach to minimizing low value androgen deprivation therapy (DeADT)
Abstract
Background
Men with prostate cancer are often castrated with long-acting injectable drugs termed androgen deprivation therapy (ADT). Although many benefit, ADT is also used in patients with little or nothing to gain. The best ways to stop this practice are unknown, and range from blunt pharmacy restrictions to informed decision-making. This study will refine and pilot two different de-implementation strategies for reducing ADT use among those unlikely to benefit in preparation for a comparative effectiveness trial.
Methods/design
This innovative mixed methods research program has three aims. Aim 1: To assess preferences and barriers for de-implementation of chemical castration in prostate cancer. Guided by the theoretical domains framework (TDF), urologists and patients from facilities with the highest and lowest castration rates across the VA will be interviewed to identify key preferences and de-implementation barriers for reducing castration as prostate cancer treatment. This qualitative work will inform Aim 2 while gathering rich information for two proposed pilot intervention strategies. Aim 2: To use a discrete choice experiment (DCE), a novel barrier prioritization approach, for de-implementation strategy tailoring. The investigators will conduct national surveys of urologists to prioritize key barriers identified in Aim 1 for stopping incident castration as localized prostate cancer treatment using a DCE experiment design. These quantitative results will identify the most important barriers to be addressed through tailoring of two pilot de-implementation strategies in preparation for Aim 3 piloting. Aim 3: To pilot two tailored de-implementation strategies to reduce castration as localized prostate cancer treatment. Building on findings from Aims 1 and 2, two de-implementation strategies will be piloted. One strategy will focus on formulary restriction at the organizational level and the other on physician/patient informed decision-making at different facilities. Outcomes will include acceptability, feasibility, and scalability in preparation for an effectiveness trial comparing these two widely varying de-implementation strategies.
Discussion
Our innovative approach to de-implementation strategy development is directly aligned with state-of-the-art complex implementation intervention development and implementation science. This work will broadly advance de-implementation science for low value cancer care, and foster participation in our de-implementation evaluation trial by addressing barriers, facilitators, and concerns through pilot tailoring.
Trial registration
ClinicalTrials.gov Identifier:
NCT03579680
, First Posted July 6, 2018.https://deepblue.lib.umich.edu/bitstream/2027.42/146541/1/13012_2018_Article_833.pd
Unpacking overuse of androgen deprivation therapy for prostate cancer to inform de-implementation strategies
Peer reviewe
Post-depositional fracturing and subsidence of pumice flow deposits: Lascar Volcano, Chile
Unconsolidated pyroclastic flow deposits of the
1993 eruption of Lascar Volcano, Chile, have, with time,
become increasingly dissected by a network of deeply
penetrating fractures. The fracture network comprises
orthogonal sets of decimeter-wide linear voids that form a
pseudo-polygonal grid visible on the deposit surface. In this
work, we combine shallow surface geophysical imaging
tools with remote sensing observations and direct field
measurements of the deposit to investigate these fractures
and their underlying causal mechanisms. Based on ground
penetrating radar images, the fractures are observed to have
propagated to depths of up to 10 m. In addition, orbiting radar interferometry shows that deposit subsidence of up to
1 cm/year occurred between 1993 and 1996 with continued
subsidence occurring at a slower rate thereafter. In situ
measurements show that 1 m below the surface, the 1993
deposits remain 5°C to 15°C hotter, 18 years after
emplacement, than adjacent deposits. Based on the observed
subsidence as well as estimated cooling rates, the fractures are
inferred to be the combined result of deaeration, thermal
contraction, and sedimentary compaction in the months to
years following deposition. Significant environmental factors,
including regional earthquakes in 1995 and 2007, accelerated
settling at punctuated moments in time. The spatially variable
fracture pattern relates to surface slope and lithofacies
variations as well as substrate lithology. Similar fractures
have been reported in other ignimbrites but are generally
exposed only in cross section and are often attributed to
formation by external forces. Here we suggest that such
interpretations should be invoked with caution, and deformation
including post-emplacement subsidence and fracturing of
loosely packed ash-rich deposits in the months to years postemplacement
is a process inherent in the settling of pyroclastic
material
Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales
While wetlands are the largest natural source of methane (CH4) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by similar to 17 +/- 11 days, and lagged air and soil temperature by median values of 8 +/- 16 and 5 +/- 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4. At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.Peer reviewe
MLSys: The New Frontier of Machine Learning Systems
Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains a significant obstacle, in large part due to the radically different development and deployment profile of modern ML methods, and the range of practical concerns that come with broader adoption. We propose to foster a new systems machine learning research community at the intersection of the traditional systems and ML communities, focused on topics such as hardware systems for ML, software systems for ML, and ML optimized for metrics beyond predictive accuracy. To do this, we describe a new conference, MLSys, that explicitly targets research at the intersection of systems and machine learning with a program committee split evenly between experts in systems and ML, and an explicit focus on topics at the intersection of the two
Crime, media and the will-to-representation: Reconsidering relationships in the new media age
This paper considers the ways in which the rise of new media might challenge commonplace criminological assumptions about the crime–media interface. Established debates around crime and media have long been based upon a fairly clear demarcation between production and consumption, between object and audience – the media generates and transmits representations of crime, and audiences engage with them. However, one of the most noticeable changes occurring in the wake of the development of new media is the proliferation of self-organised production by ‘ordinary people’ – everything ranging from self-authored web pages and ‘blogs’, to self-produced video created using hand-held camcorders, camera-phones and ‘webcams’. Today we see the spectacle of people them, send them and upload them to the Internet. This kind of ‘will to representation’ may be seen in itself as a new kind of causal inducement to law- and rule-breaking behaviour. It may be that, in the new media age, the terms of criminological questioning need to be sometimes reversed: instead of asking whether ‘media’ instigates crime or fear of crime, we must ask how the very possibility of bound up with the genesis of criminal behaviour.performing acts of crime and deviance in order to recordmediating oneself to an audience through self-representation might be bound up with the genesis of criminal behaviour
Plasma Apolipoprotein Levels Are Associated with Cognitive Status and Decline in a Community Cohort of Older Individuals
<div><h3>Objectives</h3><p>Apolipoproteins have recently been implicated in the etiology of Alzheimer’s disease (AD). In particular, Apolipoprotein J (ApoJ or clusterin) has been proposed as a biomarker of the disease at the pre-dementia stage. We examined a group of apolipoproteins, including ApoA1, ApoA2, ApoB, ApoC3, ApoE, ApoH and ApoJ, in the plasma of a longitudinal community based cohort.</p> <h3>Methods</h3><p>664 subjects (257 with Mild Cognitive Impairment [MCI] and 407 with normal cognition), mean age 78 years, from the Sydney Memory and Aging Study (MAS) were followed up over two years. Plasma apolipoprotein levels at baseline (Wave 1) were measured using a multiplex bead fluorescence immunoassay technique.</p> <h3>Results</h3><p>At Wave 1, MCI subjects had lower levels of ApoA1, ApoA2 and ApoH, and higher levels of ApoE and ApoJ, and a higher ApoB/ApoA1 ratio. Carriers of the apolipoprotein E ε4 allele had significantly lower levels of plasma ApoE, ApoC3 and ApoH and a significantly higher level of ApoB. Global cognitive scores were correlated positively with ApoH and negatively with ApoJ levels. ApoJ and ApoE levels were correlated negatively with grey matter volume and positively with cerebrospinal fluid (CSF) volume on MRI. Lower ApoA1, ApoA2 and ApoH levels, and higher ApoB/ApoA1 ratio, increased the risk of cognitive decline over two years in cognitively normal individuals. ApoA1 was the most significant predictor of decline. These associations remained after statistically controlling for lipid profile. Higher ApoJ levels predicted white matter atrophy over two years.</p> <h3>Conclusions</h3><p>Elderly individuals with MCI have abnormal apolipoprotein levels, which are related to cognitive function and volumetric MRI measures cross-sectionally and are predictive of cognitive impairment in cognitively normal subjects. ApoA1, ApoH and ApoJ are potential plasma biomarkers of cognitive decline in non-demented elderly individuals.</p> </div
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