Wavelet Decomposition of Forced Turbulence: Applicability of the Iterative Donoho-Johnstone Threshold

We examine the decomposition of forced Taylor-Green and Arn’old-Beltrami- Childress (ABC) flows into coherent and incoherent components using an orthonormal wavelet decomposition. We ask whether wavelet coefficient thresh- olding based on the Donoho-Johnstone criterion can extract a coherent vortex signal while leaving behind Gaussian random noise. We find that no threshold yields a strictly Gaussian incoherent component, and that the most Gaussian incoherent flow is found for data compression lower than that achieved with the fully iterated Donoho-Johnstone threshold. Moreover, even at such low compression, the incoherent component shows clear signs of large-scale spatial correlations that are signatures of the forcings used to drive the flows

3D Radiative Hydrodynamics for Disk Stability Simulations: A Proposed Testing Standard and New Results

Recent three-dimensional radiative hydrodynamics simulations of protoplanetary disks report disparate disk behaviors, and these differences involve the importance of convection to disk cooling, the dependence of disk cooling on metallicity, and the stability of disks against fragmentation and clump formation. To guarantee trustworthy results, a radiative physics algorithm must demonstrate the capability to handle both the high and low optical depth regimes. We develop a test suite that can be used to demonstrate an algorithm's ability to relax to known analytic flux and temperature distributions, to follow a contracting slab, and to inhibit or permit convection appropriately. We then show that the radiative algorithm employed by Meji\'a (2004) and Boley et al. (2006) and the algorithm employed by Cai et al. (2006) and Cai et al. (2007, in prep.) pass these tests with reasonable accuracy. In addition, we discuss a new algorithm that couples flux-limited diffusion with vertical rays, we apply the test suite, and we discuss the results of evolving the Boley et al. (2006) disk with this new routine. Although the outcome is significantly different in detail with the new algorithm, we obtain the same qualitative answers. Our disk does not cool fast due to convection, and it is stable to fragmentation. We find an effective $\alpha\approx 10^{-2}$. In addition, transport is dominated by low-order modes.Comment: Submitted to Ap

Cal Poly Climate Action Plan

The Cal Poly Climate Action Plan (PolyCAP) is designed to achieve the California State University (CSU) Chancellor’s mandate to reduce greenhouse gas (GHG) emissions to 1990 levels by 2020 and 80% below 1990 levels by 2040 (CSU, 2014). California Polytechnic State University, San Luis Obispo (Cal Poly) Facility Management and Development (FM&D) and the City and Regional Planning (CRP) Senior Community Planning Laboratory developed the PolyCAP during the Fall 2015 and Winter 2016 quarters, with editing and refinement in subsequent quarters. The goal of the PolyCAP is to reduce Cal Poly’s GHG emissions and to adapt the Campus to a changing climate. The PolyCAP aims to exceed the CSU mandate and achieve Net Zero GHG emissions by 2050, in accordance with Cal Poly’s signing of the Second Nature Climate Commitment. Cal Poly is updating its Master Plan to 2035, examining University academics, buildings, housing, transportation, agriculture, and more. The PolyCAP is intended to aid the Draft Master Plan Update to achieve its goal to be responsive to climate change. Many strategies of the PolyCAP can also be implemented as mitigation measures in the Draft Master Plan Update Environmental Impact Report (EIR)

Workshop on the Development and Evaluation of Digital Therapeutics for Health Behavior Change: Science, Methods, and Projects

The health care field has integrated advances into digital technology at an accelerating pace to improve health behavior, health care delivery, and cost-effectiveness of care. The realm of behavioral science has embraced this evolution of digital health, allowing for an exciting roadmap for advancing care by addressing the many challenges to the field via technological innovations. Digital therapeutics offer the potential to extend the reach of effective interventions at reduced cost and patient burden and to increase the potency of existing interventions. Intervention models have included the use of digital tools as supplements to standard care models, as tools that can replace a portion of treatment as usual, or as stand-alone tools accessed outside of care settings or direct to the consumer. To advance the potential public health impact of this promising line of research, multiple areas warrant further development and investigation. The Center for Technology and Behavioral Health (CTBH), a P30 Center of Excellence supported by the National Institute on Drug Abuse at the National Institutes of Health, is an interdisciplinary research center at Dartmouth College focused on the goal of harnessing existing and emerging technologies to effectively develop and deliver evidence-based interventions for substance use and co-occurring disorders. The CTBH launched a series of workshops to encourage and expand multidisciplinary collaborations among Dartmouth scientists and international CTBH affiliates engaged in research related to digital technology and behavioral health (eg, addiction science, behavioral health intervention, technology development, computer science and engineering, digital security, health economics, and implementation science). This paper summarizes a workshop conducted on the Development and Evaluation of Digital Therapeutics for Behavior Change, which addressed (1) principles of behavior change, (2) methods of identifying and testing the underlying mechanisms of behavior change, (3) conceptual frameworks for optimizing applications for mental health and addictive behavior, and (4) the diversity of experimental methods and designs that are essential to the successful development and testing of digital therapeutics. Examples were presented of ongoing CTBH projects focused on identifying and improving the measurement of health behavior change mechanisms and the development and evaluation of digital therapeutics. In summary, the workshop showcased the myriad research targets that will be instrumental in promoting and accelerating progress in the field of digital health and health behavior change and illustrated how the CTBH provides a model of multidisciplinary leadership and collaboration that can facilitate innovative, science-based efforts to address the health behavior challenges afflicting our communities

ABCA7 p.G215S as potential protective factor for Alzheimer’s disease

Genome-wide association studies (GWASs) have been effective approaches to dissect common genetic variability underlying complex diseases in a systematic and unbiased way. Recently, GWASs have led to the discovery of over 20 susceptibility loci for Alzheimer’s disease (AD). Despite the evidence showing the contribution of these loci to AD pathogenesis, their genetic architecture has not been extensively investigated, leaving the possibility that low frequency and rare coding variants may also occur and contribute to the risk of disease. We have used exome and genome sequencing data to analyse the single independent and joint effect of rare and low frequency protein coding variants in 9 AD GWAS loci with the strongest effect sizes after APOE (BIN1, CLU, CR1, PICALM, MS4A6A, ABCA7, EPHA1, CD33, CD2AP) in a cohort of 332 sporadic AD cases and 676 elderly controls of British and North American ancestry. We identified coding variability in ABCA7 as contributing to AD risk. This locus harbors a low frequency coding variant (p.G215S, rs72973581, MAF=4.3%) conferring a modest but statistically significant protection against AD (p-value= 6x10-4, OR=0.57, 95% CI 0.41-0.80). Notably, our results are not driven by an enrichment of loss of function variants in ABCA7, recently reported as main pathogenic factor underlying AD risk at this locus. In summary, our study confirms the role of ABCA7 in AD and provide new insights that should address functional studies

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Mendelian adult-onset leukodystrophy genes in Alzheimer's disease:critical influence of CSF1R and NOTCH3

Mendelian adult-onset leukodystrophies are a spectrum of rare inherited progressive neurodegenerative disorders affecting the white matter of the central nervous system. Among these, cerebral autosomal dominant and recessive arteriopathy with subcortical infarcts and leukoencephalopathy, cerebroretinal vasculopathy, metachromatic leukodystrophy, hereditary diffuse leukoencephalopathy with spheroids, and vanishing white matter disease present with rapidly progressive dementia as dominant feature and are caused by mutations in NOTCH3, HTRA1, TREX1, ARSA, CSF1R, EIF2B1, EIF2B2, EIF2B3, EIF2B4, and EIF2B5, respectively. Given the rare incidence of these disorders and the lack of unequivocally diagnostic features, leukodystrophies are frequently misdiagnosed with common sporadic dementing diseases such as Alzheimer's disease (AD), raising the question of whether these overlapping phenotypes may be explained by shared genetic risk factors. To investigate this intriguing hypothesis, we have combined gene expression analysis (1) in 6 different AD mouse strains (APPPS1, HOTASTPM, HETASTPM, TPM, TAS10, and TAU) at 5 different developmental stages (embryo [E15], 2, 4, 8, and 18 months), (2) in APPPS1 primary cortical neurons under stress conditions (oxygen-glucose deprivation) and single-variant–based and single-gene–based (c-alpha test and sequence kernel association test (SKAT)) genetic screening in a cohort composed of 332 Caucasian late-onset AD patients and 676 Caucasian elderly controls. Csf1r was significantly overexpressed (log2FC &gt; 1, adj. p-value &lt; 0.05) in the cortex and hippocampus of aged HOTASTPM mice with extensive Aβ dense-core plaque pathology. We identified 3 likely pathogenic mutations in CSF1R TK domain (p.L868R, p.Q691H, and p.H703Y) in our discovery and validation cohort, composed of 465 AD and mild cognitive impairment (MCI) Caucasian patients from the United Kingdom. Moreover, NOTCH3 was a significant hit in the c-alpha test (adj p-value = 0.01). Adult-onset Mendelian leukodystrophy genes are not common factors implicated in AD. Nevertheless, our study suggests a potential pathogenic link between NOTCH3, CSF1R, and sporadic late-onset AD, which warrants further investigation.</p