1,519 research outputs found
Verifying continuous-variable entanglement in finite spaces
Starting from arbitrary Hilbert spaces, we reduce the problem to verify
entanglement of any bipartite quantum state to finite dimensional subspaces.
Hence, entanglement is a finite dimensional property. A generalization for
multipartite quantum states is also given.Comment: 4 page
Enriched Computational Homogenization Schemes Applied to Pattern-Transforming Elastomeric Mechanical Metamaterials
Elastomeric mechanical metamaterials exhibit unconventional mechanical
behaviour owing to their complex microstructures. A clear transition in the
effective properties emerges under compressive loading, which is triggered by
local instabilities and pattern transformations of the underlying cellular
microstructure. Such transformations trigger a non-local mechanical response
resulting in strong size effects. For predictive modelling of engineering
applications, the effective homogenized material properties are generally of
interest. For mechanical metamaterials, these can be obtained in an expensive
manner by ensemble averaging of the direct numerical simulations for a series
of translated microstructures, applicable especially in the regime of small
separation of scales. To circumvent this expensive step, computational
homogenization methods are of benefit, employing volume averaging instead.
Classical first-order computational homogenization, which relies on the
standard separation of scales principle, is unable to capture any size and
boundary effects. Second-order computational homogenization has the ability to
capture strain gradient effects at the macro-scale, thus accounting for the
presence of non-localities. Another alternative is micromorphic computational
homogenization scheme, which is tailored to pattern-transforming metamaterials
by incorporating prior kinematic knowledge. In this contribution, a systematic
study is performed, assessing the predictive ability of computational
homogenization schemes in the realm of elastomeric metamaterials. Three
representative examples with distinct mechanical loading are employed for this
purpose: uniform compression and bending of an infinite specimen, and
compression of a finite specimen. Qualitative and quantitative analyses are
performed for each of the load cases where the ensemble average solution is set
as a reference.Comment: 32 pages, 19 figures, 1 table, abstract shortened to fulfil 1920
character limi
Independent nonclassical tests for states and measurements in the same experiment
We show that one single experiment can test simultaneously and independently
both the nonclassicality of states and measurements by the violation or
fulfillment of classical bounds on the statistics. Nonideal measurements
affected by imperfections can be characterized by two bounds depending on
whether we test the ideal measurement or the real one.Comment: 9 pages, 3 figures. Proceedings of 17th CEWQO 201
γδ T cells affect IL-4 production and B-cell tolerance
γδ T cells can influence specific antibody responses. Here, we report that mice deficient in individual γδ T-cell subsets have altered levels of serum antibodies, including all major subclasses, sometimes regardless of the presence of αβ T cells. One strain with a partial γδ deficiency that increases IgE antibodies also displayed increases in IL-4–producing T cells (both residual γδ T cells and αβ T cells) and in systemic IL-4 levels. Its B cells expressed IL-4–regulated inhibitory receptors (CD5, CD22, and CD32) at diminished levels, whereas IL-4–inducible IL-4 receptor α and MHCII were increased. They also showed signs of activation and spontaneously formed germinal centers. These mice displayed IgE-dependent features found in hyper-IgE syndrome and developed antichromatin, antinuclear, and anticytoplasmic autoantibodies. In contrast, mice deficient in all γδ T cells had nearly unchanged Ig levels and did not develop autoantibodies. Removing IL-4 abrogated the increases in IgE, antichromatin antibodies, and autoantibodies in the partially γδ-deficient mice. Our data suggest that γδ T cells, controlled by their own cross-talk, affect IL-4 production, B-cell activation, and B-cell tolerance
Ultra-high field imaging, plasma markers and autopsy data uncover a specific rostral locus coeruleus vulnerability to hyperphosphorylated tau
Autopsy data indicate that the locus coeruleus (LC) is one of the first sites in the brain to accumulate hyperphosphorylated tau pathology, with the rostral part possibly being more vulnerable in the earlier stages of the disease. Taking advantage of recent developments in ultra-high field (7 T) imaging, we investigated whether imaging measures of the LC also reveal a specific anatomic correlation with tau using novel plasma biomarkers of different species of hyperphosphorylated tau, how early in adulthood these associations can be detected and if are associated with worse cognitive performance. To validate the anatomic correlations, we tested if a rostro-caudal gradient in tau pathology is also detected at autopsy in data from the Rush Memory and Aging Project (MAP). We found that higher plasma measures of phosphorylated tau, in particular ptau231, correlated negatively with dorso-rostral LC integrity, whereas correlations for neurodegenerative plasma markers (neurofilament light, total tau) were scattered throughout the LC including middle to caudal sections. In contrast, the plasma Aβ42/40 ratio, associated with brain amyloidosis, did not correlate with LC integrity. These findings were specific to the rostral LC and not observed when using the entire LC or the hippocampus. Furthermore, in the MAP data, we observed higher rostral than caudal tangle density in the LC, independent of the disease stage. The in vivo LC-phosphorylated tau correlations became significant from midlife, with the earliest effect for ptau231, starting at about age 55. Finally, interactions between lower rostral LC integrity and higher ptau231 concentrations predicted lower cognitive performance. Together, these findings demonstrate a specific rostral vulnerability to early phosphorylated tau species that can be detected with dedicated magnetic resonance imaging measures, highlighting the promise of LC imaging as an early marker of AD-related processes
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Pre-Randomization Predictors of Study Discontinuation in a Preclinical Alzheimers Disease Randomized Controlled Trial.
BACKGROUND: Participant discontinuation from study treatment in a clinical trial can leave a trial underpowered, produce bias in statistical analysis, and limit interpretability of study results. Retaining participants in clinical trials for the full study duration is therefore as important as participant recruitment. OBJECTIVE: This analysis aims to identify associations of pre-randomization characteristics of participants with premature discontinuation during the blinded phase of the Anti-Amyloid treatment in Asymptomatic AD (A4) Study. DESIGN: All A4 trial randomized participants were classified as having prematurely discontinued study during the blinded period of the study for any reason (dropouts) or completed the blinded phase of the study on treatment (completers). SETTING: The trial was conducted across 67 study sites in the United States, Canada, Japan and Australia through the global COVID-19 pandemic. PARTICIPANTS: The sample consisted of all 1169 A4 trial randomized participants. MEASUREMENTS: Pre-randomization demographic, clinical, amyloid PET and genetic predictors of study discontinuation were evaluated using a univariate generalized linear mixed model (GLMM), with discontinuation status as the binary outcome, each predictor as a fixed effect, and site as a random effect to account for differences among study sites in the trial. Characteristics significant at p<0.10 were then included in a multivariable GLMM. RESULTS: Among randomized participants, 339 (29%) discontinued the study during the blinded period (median follow-up time in trial: 759 days). From the multivariable analysis, the two main predictors of study discontinuation were screening State-Trait Anxiety Inventory (STAI) scores (OR = 1.07 [95%CI = 1.02; 1.12]; p=0.002) and age (OR = 1.06 [95%CI = 1.03; 1.09]; p<0.001). Participants with a family history of dementia (OR = 0.75 [95%CI = 0.55; 1.01]; p=0.063) and APOE ε4 carriers (OR = 0.79 [95%CI = 0.6; 1.04]; p=0.094) were less likely to discontinue from the study, with the association being marginally significant. In these analyses, sex, race and ethnicity, cognitive scores and amyloid/tau PET scores were not associated with study dropout. CONCLUSIONS: In the A4 trial, older participants and those with higher levels of anxiety at baseline as measured by the STAI were more likely to discontinue while those who had a family history of dementia or were APOE ε4 carriers were less likely to drop out. These findings have direct implications for future preclinical trial design and selection processes to identify those individuals at greatest risk of dropout and provide information to the study team to develop effective selection and retention strategies in AD prevention studies
Chapter 11 - Agriculture, forestry and other land use (AFOLU)
Agriculture, Forestry, and Other Land Use (AFOLU) plays a central role for food security and sustainable development. Plants take up carbon dioxide (CO2) from the atmosphere and nitrogen (N) from the soil when they grow, re-distributing it among different pools, including above and below-ground living biomass, dead residues, and soil organic matter. The CO2 and other non-CO2 greenhouse gases (GHG), largely methane (CH4) and nitrous oxide (N2O), are in turn released to the atmosphere by plant respiration, by decomposition of dead plant biomass and soil organic matter, and by combustion. Anthropogenic land-use activities (e.g., management of croplands, forests, grasslands, wetlands), and changes in land use / cover (e.g., conversion of forest lands and grasslands to cropland and pasture, afforestation) cause changes superimposed on these natural fluxes. AFOLU activities lead to both sources of CO2 (e.g., deforestation, peatland drainage) and sinks of CO2 (e.g., afforestation, management for soil carbon sequestration), and to non-CO2 emissions primarily from agriculture (e.g., CH4 from livestock and rice cultivation, N2O from manure storage and agricultural soils and biomass burning.
The main mitigation options within AFOLU involve one or more of three strategies: reduction / prevention of emissions to the atmosphere by conserving existing carbon pools in soils or vegetation that would otherwise be lost or by reducing emissions of CH4 and N2O; sequestration - enhancing the uptake of carbon in terrestrial reservoirs, and thereby removing CO2 from the atmosphere; and reducing CO2 emissions by substitution of biological products for fossil fuels or energy-intensive products. Demand-side options (e.g., by lifestyle changes, reducing losses and wastes of food, changes in human diet, changes in wood consumption), though known to be difficult to implement, may also play a role.
Land is the critical resource for the AFOLU sector and it provides food and fodder to feed the Earth's population of ~7 billion, and fibre and fuel for a variety of purposes. It provides livelihoods for billions of people worldwide. It is finite and provides a multitude of goods and ecosystem services that are fundamental to human well-being. Human economies and quality of life are directly dependent on the services and the resources provided by land. Figure 11.1 shows the many provisioning, regulating, cultural and supporting services provided by land, of which climate regulation is just one. Implementing mitigation options in the AFOLU sector may potentially affect other services provided by land in positive or negative ways.
In the Intergovernmental Panel on Climate Change (IPCC) Second Assessment Report (SAR) and in the IPCC Fourth Assessment Report (AR4), agricultural and forestry mitigation were dealt with in separate chapters. In the IPCC Third Assessment Report (TAR), there were no separate sectoral chapters on either agriculture or forestry. In the IPCC Fifth Assessment Report (AR5), for the first time, the vast majority of the terrestrial land surface, comprising agriculture, forestry and other land use (AFOLU), is considered together in a single chapter, though settlements (which are important, with urban areas forecasted to triple in size from 2000 global extent by 2030), are dealt with in Chapter 12. This approach ensures that all land-based mitigation options can be considered together; it minimizes the risk of double counting or inconsistent treatment (e.g., different assumptions about available land) between different land categories, and allows the consideration of systemic feedbacks between mitigation options related to the land surface. Considering AFOLU in a single chapter allows phenomena common across land-use types, such as competition for land and water, co-benefits, adverse side-effects and interactions between mitigation and adaptation to be considered consistently. The complex nature of land presents a unique range of barriers and opportunities, and policies to promote mitigation in the AFOLU sector need to take account of this complexity.
In this chapter, we consider the competing uses of land for mitigation and for providing other services. Unlike the chapters on agriculture and forestry in AR4, impacts of sourcing bioenergy from the AFOLU sector are considered explicitly in a dedicated appendix. Also new to this assessment is the explicit consideration of food / dietary demand-side options for GHG mitigation in the AFOLU sector, and some consideration of freshwater fisheries and aquaculture, which may compete with the agriculture and forestry sectors, mainly through their requirements for land and / or water, and indirectly, by providing fish and other products to the same markets as animal husbandry.
This chapter deals with AFOLU in an integrated way with respect to the underlying scenario projections of population growth, economic growth, dietary change, land-use change (LUC), and cost of mitigation. We draw evidence from both "bottom-up" studies that estimate mitigation potentials at small scales or for individual options or technologies and then scale up, and multi-sectoral "top-down" studies that consider AFOLU as just one component of a total multi-sector system response. In this chapter, we provide updates on emissions trends and changes in drivers and pressures in the AFOLU sector, describe the practices available in the AFOLU sector, and provide refined estimates of mitigation costs and potentials for the AFOLU sector, by synthesising studies that have become available since AR4. We conclude the chapter by identifying gaps in knowledge and data, providing a selection of Frequently Asked Questions, and presenting an Appendix on bioenergy to update the IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation (SRREN)
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Amyloid and Tau Prediction of Cognitive and Functional Decline in Unimpaired Older Individuals: Longitudinal Data from the A4 and LEARN Studies.
BACKGROUND: Converging evidence suggests that markers of Alzheimers disease (AD) pathology in cognitively unimpaired older individuals are associated with high risk of cognitive decline and progression to functional impairment. The Anti-Amyloid Treatment in Asymptomatic Alzheimers disease (A4) and Longitudinal Evaluation of Amyloid and Neurodegeneration Risk (LEARN) Studies enrolled a large cohort of cognitively normal older individuals across a range of baseline amyloid PET levels. Recent advances in AD blood-based biomarkers further enable the comparison of baseline markers in the prediction of longitudinal clinical outcomes. OBJECTIVES: We sought to evaluate whether biomarker indicators of higher levels of AD pathology at baseline predicted greater cognitive and functional decline, and to compare the relative predictive power of amyloid PET imaging, tau PET imaging, and a plasma P-tau217 assay. DESIGN: All participants underwent baseline amyloid PET scan, plasma P-tau217; longitudinal cognitive testing with the Primary Alzheimer Cognitive Composite (PACC) every 6 months; and annual functional assessments with the clinical dementia rating (CDR), cognitive functional index (CFI), and activities of daily living (ADL) scales. Baseline tau PET scans were obtained in a subset of participants. Participants with elevated amyloid (Aβ+) on screening PET who met inclusion/exclusion criteria were randomized to receive placebo or solanezumab in a double-blind phase of the A4 Study over 240+ weeks. Participants who did not have elevated amyloid (Aβ-) but were otherwise eligible for the A4 Study were referred to the companion observational LEARN Study with the same outcome assessments over 240+ weeks. SETTING: The A4 and LEARN Studies were conducted at 67 clinical trial sites in the United States, Canada, Japan and Australia. PARTICIPANTS: Older participants (ages 65-85) who were cognitively unimpaired at baseline (CDR-GS=0, MMSE 25-30 with educational adjustment, and Logical Memory scores within the normal range LMIIa 6-18) were eligible to continue in screening. Aβ+ participants were randomized to either placebo (n=583) or solanezumab (n=564) in the A4 Study. A subset of Aβ+ underwent tau PET imaging in A4 (n=350). Aβ- were enrolled into the LEARN Study (n=553). MEASUREMENTS: Baseline 18-F Florbetapir amyloid PET, 18-F Flortaucipir tau PET in a subset and plasma P-tau217 with an electrochemiluminescence (ECL) immunoassay were evaluated as predictors of cognitive (PACC), and functional (CDR, CFI and ADL) change. Models were evaluated to explore the impact of baseline tertiles of amyloid PET and tertiles of plasma P-tau217 on cognitive and functional outcomes in the A4 Study compared to LEARN. Multivariable models were used to evaluate the unique and common variance explained in longitudinal outcomes based on baseline predictors, including effects for age, gender, education, race/ethnic group, APOEε4 carrier status, baseline PACC performance and treatment assignment in A4 participants (solanezumab vs placebo). RESULTS: Higher baseline amyloid PET CL and P-tau217 levels were associated with faster rates of PACC decline, and increased likelihood of progression to functional impairment (CDR 0.5 or higher on two consecutive measurements), both across LEARN Aβ- and A4 Aβ+ (solanezumab and placebo arms). In analyses considering all baseline predictor variables, P-tau217 was the strongest predictor of PACC decline. Among participants in the highest tertiles of amyloid PET or P-tau217, >50% progressed to CDR 0.5 or greater. In the tau PET substudy, neocortical tau was the strongest predictor of PACC decline, but plasma P-tau217 contributed additional independent predictive variance in commonality variance models. CONCLUSIONS: In a large cohort of cognitively unimpaired individuals enrolled in a Phase 3 clinical trial and companion observational study, these findings confirm that higher baseline levels of amyloid and tau markers are associated with increased rates of cognitive decline and progression to functional impairment. Interestingly, plasma P-tau217 was the best predictor of decline in the overall sample, superior to baseline amyloid PET. Neocortical tau was the strongest predictor of cognitive decline in the subgroup with tau PET, suggesting that tau deposition is most closely linked to clinical decline. These findings indicate that biomarkers of AD pathology are useful to predict decline in an older asymptomatic population and may prove valuable in the selection of individuals for disease-modifying treatments
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