Stress response inside perturbed particle assemblies

The effect of structural disorder on the stress response inside three dimensional particle assemblies is studied using computer simulations of frictionless sphere packings. Upon applying a localised, perturbative force within the packings, the resulting {\it Green's} function response is mapped inside the different assemblies, thus providing an explicit view as to how the imposed perturbation is transmitted through the packing. In weakly disordered arrays, the resulting transmission of forces is of the double-peak variety, but with peak widths scaling linearly with distance from the source of the perturbation. This behaviour is consistent with an anisotropic elasticity response profile. Increasing the disorder distorts the response function until a single-peak response is obtained for fully disordered packings consistent with an isotropic description.Comment: 8 pages, 7 figure captions To appear in Granular Matte

Genetics of intellectual disability in consanguineous families

Autosomal recessive (AR) gene defects are the leading genetic cause of intellectual disability (ID) in countries with frequent parental consanguinity, which account for about 1/7th of the world population. Yet, compared to autosomal dominant de novo mutations, which are the predominant cause of ID in Western countries, the identification of AR-ID genes has lagged behind. Here, we report on whole exome and whole genome sequencing in 404 consanguineous predominantly Iranian families with two or more affected offspring. In 219 of these, we found likely causative variants, involving 77 known and 77 novel AR-ID (candidate) genes, 21 X-linked genes, as well as 9 genes previously implicated in diseases other than ID. This study, the largest of its kind published to date, illustrates that high-throughput DNA sequencing in consanguineous families is a superior strategy for elucidating the thousands of hitherto unknown gene defects underlying AR-ID, and it sheds light on their prevalence

Age at symptom onset and death and disease duration in genetic frontotemporal dementia : an international retrospective cohort study

Background: Frontotemporal dementia is a heterogenous neurodegenerative disorder, with about a third of cases being genetic. Most of this genetic component is accounted for by mutations in GRN, MAPT, and C9orf72. In this study, we aimed to complement previous phenotypic studies by doing an international study of age at symptom onset, age at death, and disease duration in individuals with mutations in GRN, MAPT, and C9orf72. Methods: In this international, retrospective cohort study, we collected data on age at symptom onset, age at death, and disease duration for patients with pathogenic mutations in the GRN and MAPT genes and pathological expansions in the C9orf72 gene through the Frontotemporal Dementia Prevention Initiative and from published papers. We used mixed effects models to explore differences in age at onset, age at death, and disease duration between genetic groups and individual mutations. We also assessed correlations between the age at onset and at death of each individual and the age at onset and at death of their parents and the mean age at onset and at death of their family members. Lastly, we used mixed effects models to investigate the extent to which variability in age at onset and at death could be accounted for by family membership and the specific mutation carried. Findings: Data were available from 3403 individuals from 1492 families: 1433 with C9orf72 expansions (755 families), 1179 with GRN mutations (483 families, 130 different mutations), and 791 with MAPT mutations (254 families, 67 different mutations). Mean age at symptom onset and at death was 49\ub75 years (SD 10\ub70; onset) and 58\ub75 years (11\ub73; death) in the MAPT group, 58\ub72 years (9\ub78; onset) and 65\ub73 years (10\ub79; death) in the C9orf72 group, and 61\ub73 years (8\ub78; onset) and 68\ub78 years (9\ub77; death) in the GRN group. Mean disease duration was 6\ub74 years (SD 4\ub79) in the C9orf72 group, 7\ub71 years (3\ub79) in the GRN group, and 9\ub73 years (6\ub74) in the MAPT group. Individual age at onset and at death was significantly correlated with both parental age at onset and at death and with mean family age at onset and at death in all three groups, with a stronger correlation observed in the MAPT group (r=0\ub745 between individual and parental age at onset, r=0\ub763 between individual and mean family age at onset, r=0\ub758 between individual and parental age at death, and r=0\ub769 between individual and mean family age at death) than in either the C9orf72 group (r=0\ub732 individual and parental age at onset, r=0\ub736 individual and mean family age at onset, r=0\ub738 individual and parental age at death, and r=0\ub740 individual and mean family age at death) or the GRN group (r=0\ub722 individual and parental age at onset, r=0\ub718 individual and mean family age at onset, r=0\ub722 individual and parental age at death, and r=0\ub732 individual and mean family age at death). Modelling showed that the variability in age at onset and at death in the MAPT group was explained partly by the specific mutation (48%, 95% CI 35\u201362, for age at onset; 61%, 47\u201373, for age at death), and even more by family membership (66%, 56\u201375, for age at onset; 74%, 65\u201382, for age at death). In the GRN group, only 2% (0\u201310) of the variability of age at onset and 9% (3\u201321) of that of age of death was explained by the specific mutation, whereas 14% (9\u201322) of the variability of age at onset and 20% (12\u201330) of that of age at death was explained by family membership. In the C9orf72 group, family membership explained 17% (11\u201326) of the variability of age at onset and 19% (12\u201329) of that of age at death. Interpretation: Our study showed that age at symptom onset and at death of people with genetic frontotemporal dementia is influenced by genetic group and, particularly for MAPT mutations, by the specific mutation carried and by family membership. Although estimation of age at onset will be an important factor in future pre-symptomatic therapeutic trials for all three genetic groups, our study suggests that data from other members of the family will be particularly helpful only for individuals with MAPT mutations. Further work in identifying both genetic and environmental factors that modify phenotype in all groups will be important to improve such estimates. Funding: UK Medical Research Council, National Institute for Health Research, and Alzheimer's Society

Economic modeling of directed technical change: the case of CO2 emission reduction

The potential of technical change for cost-effective pollution abatement typically differs from technology to technology. It therefore is the aim of this thesis to study how policy instruments can direct technical change to those technologies with the greatest potential for cost-effective pollution abatement. In the light of the climate change problem, this thesis uses climate policy and concomitant reduction of carbon dioxide (CO2) emissions associated with energy use as a case study.A first part of the study deals with the determinants of directed technical change. 1 derive these determinants using an economic model analysis of directed technical change. A main finding is that the consumption side of the economy is important for the direction of technical change. In particular, the extent to which consumers can substitute between goods determines the direction. Technology externalities reinforce the existing direction of technical change. Further, I explore a frontier approach for empirical analysis of delayed feedback in technical change that is based on the literature of productive efficiency analysis. 1 illustrate this approach using aggregate production data of25 OECD countries for the years 1980 through 1997. I find evidence that the benefits of technical change accrue gradually over time, with the delayed response continuing up to eight years.A second part of the study deals with the possibilities of directed technical change and technology externalities for the design of climate policy. Applying the model analysis at the aggregate level of the current Dutch economy, I find that CO2 emission reduction becomes more cost effective if climate policy takes the form of a combination of traditional environmental policy and technology policy. Regardless of the particular policy instruments chosen, however, I find that technology externalities can justify differentiation of climate policy between non-CO2 intensive- and CO2-intensive sectors, such that the latter face a higher CO2 price. This result is considerably different from the conventional environmental economic conclusion that equal marginal abatement costs across the economy 1ead to a cost-effective emission reduction. Finally, focusing the model analysis more on the energy sector of the Dutch economy, I study cost effectiveness of combining the environmental policy with technology policy aimed at reducing the cost and speeding the adoption of a specific CO2 abatement technology, I take CO2 capture and storage in the Dutch electricity sector as a case study. I find that such a policy combination leads to faster adoption of CO2 capture and storage and improves cost effectiveness of the emission reduction

Directed technical change and the adoption of CO2 abatement technology: The case of CO2 capture and storage

This paper studies the cost-effectiveness of combining traditional environmental policy, such as CO2-trading schemes, and technology policy that has aims of reducing the cost and speeding the adoption of CO2 abatement technology. For this purpose, we develop a dynamic general equilibrium model that captures empirical links between CO2 emissions associated with energy use, directed technical change and the economy. We specify CO2 capture and storage (CCS) as a discrete CO2 abatement technology. We find that combining CO2-trading schemes with an adoption subsidy is the most effective instrument to induce adoption of the CCS technology. Such a subsidy directly improves the competitiveness of the CCS technology by compensating for its markup over the cost of conventional electricity. Yet, introducing R&D subsidies throughout the entire economy leads to faster adoption of the CCS technology as well and in addition can be cost-effective in achieving the abatement target

Energy biased technical change: A CGE analysis

This paper studies energy bias in technical change. For this purpose, we develop a computable general-equilibrium model that builds on endogenous growth models. The model explicitly captures links between energy, the rate and direction of technical change, and the economy. We show the importance of feedback in technical change, substitution possibilities between final goods, and general-equilibrium effects for energy bias in technical change. If the feedback effect is strong, or the substitution elasticity large, or both, our model tends to a corner solution in which only technologies are developed that are appropriate for production of non-energy intensive goods

Directed technical change and differentiation of climate policy

This paper studies the cost effectiveness of climate policy if there are technology externalities. For this purpose, we develop a forward looking model that captures empirical links between CO2 emissions associated with energy use, directed technical change and the economy. We find our most cost effective climate policy to include a combination of R&D subsidies and CO2 emission constraints, although R&D subsidies raise the shadow value of the CO2 constraint (i.e. CO2 price) because of a strong rebound effect from stimulating innovation. Furthermore, we find that cost effectiveness of climate policy improves if it is differentiated between technologies. Even our rudimentary distinction between CO2 intensive technologies and non-CO2 intensive technologies lead to this result. Such differentiated climate policy encourages growth in the non-CO2 intensive sectors and discourages growth in CO2 intensive sectors by harnessing positive effects of technology externalities on total factor productivity in the former and letting the latter bear relatively more of the abatement burden. This result is robust to whether emission constraints, R&D subsidies or combinations of both are used as climate policy instruments

Energy Biased Technical Change. A CGE Analysis

This paper studies energy bias in technical change. For this purpose, we develop a computable general equilibrium model that builds on endogenous growth models. The model explicitly captures links between energy, the rate and direction of technical change, and the economy. We derive the equilibrium determinants of biased technical change and show the importance of feedback in technical change, substitution possibilities between final goods, and general-equilibrium effects for the equilibrium bias. If the feedback effect is strong, or the substitution elasticity large, or both, our model tends to a corner solution in which only technologies are developed that are appropriate for production of non-energy intensive good