Selective dilution and magnetic properties of La_{0.7}Sr_{0.3}Mn_{1-x}M'_xO_3 (M' = Al, Ti)

The magnetic lattice of mixed-valence Mn ions in La$_{0.7}$Sr$_{0.3}$MnO$_3$ is selectively diluted by partial substitution of Mn by Al or Ti. The ferromagnetic transition temperature and the saturation moment decreases with substitution in both series. The volume fraction of the non-ferromagnetic phases evolves non-linearly with the substitution concentration and faster than theoretically expected. By presenting the data in terms of selective dilutions, the reduction of $T_\mathrm{c}$ is found to be scaled by the relative ionic concentrations and is consistent with a prediction derived from molecular-field theory.Comment: 6 pages, 5 figures, REVTex4.0. Submitted to PR

The SPLASH Survey: Quiescent Galaxies Are More Strongly Clustered but Are Not Necessarily Located in High-density Environments

We use the stellar-mass-selected catalog from the Spitzer Large Area Survey with Hyper-Suprime-Cam (SPLASH) in the COSMOS field to study the environments of galaxies via galaxy density and clustering analyses up to z ~ 2.5. The clustering strength of quiescent galaxies exceeds that of star-forming galaxies, implying that quiescent galaxies are preferentially located in more massive halos. When using local density measurement, we find a clear positive quiescent fraction–density relation at z 1.5, the quiescent fraction depends little on the local density, even though clustering shows that quiescent galaxies are in more massive halos. We argue that at high redshift the typical halo size falls below 10^(13)M⊙, where intrinsically the local density measurements are so varied that they do not trace the halo mass. Our results thus suggest that in the high-redshift universe, halo mass may be the key in quenching the star formation in galaxies, rather than the conventionally measured galaxy density

Shape optimization for the generalized Graetz problem

We apply shape optimization tools to the generalized Graetz problem which is a convection-diffusion equation. The problem boils down to the optimization of generalized eigen values on a two phases domain. Shape sensitivity analysis is performed with respect to the evolution of the interface between the fluid and solid phase. In particular physical settings, counterexamples where there is no optimal domains are exhibited. Numerical examples of optimal domains with different physical parameters and constraints are presented. Two different numerical methods (level-set and mesh-morphing) are show-cased and compared

Rewriting a Deep Generative Model

A deep generative model such as a GAN learns to model a rich set of semantic and physical rules about the target distribution, but up to now, it has been obscure how such rules are encoded in the network, or how a rule could be changed. In this paper, we introduce a new problem setting: manipulation of specific rules encoded by a deep generative model. To address the problem, we propose a formulation in which the desired rule is changed by manipulating a layer of a deep network as a linear associative memory. We derive an algorithm for modifying one entry of the associative memory, and we demonstrate that several interesting structural rules can be located and modified within the layers of state-of-the-art generative models. We present a user interface to enable users to interactively change the rules of a generative model to achieve desired effects, and we show several proof-of-concept applications. Finally, results on multiple datasets demonstrate the advantage of our method against standard fine-tuning methods and edit transfer algorithms.Comment: ECCV 2020 (oral). Code at https://github.com/davidbau/rewriting. For videos and demos see https://rewriting.csail.mit.edu

Strategic green infrastructure planning in Germany and the UK: a transnational evaluation of the evolution of urban greening policy and practice

The evolution of Green Infrastructure (GI) planning has varied dramatically between nations. Although a grounded set of principles are recognized globally, there is increasing variance in how these are implemented at a national and sub-national level. To investigate this the following paper presents an evaluation of how green infrastructure has been planned for in England and Germany illustrating how national policy structures facilitate variance in application. Adopting an evaluative framework linked to the identification of GI, its development and monitoring/ feedback the paper questions the impacts on delivery of intersecting factors including terminology, spatial distribution and functionality on effective GI investment. This process reviews how changing policy structures have influenced the framing of green infrastructure policy, and subsequent impact this has on the delivery of green infrastructure projects

Comparison of the environmental assessment of an identical office building with national methods

The IEA EBC Annex 72 focuses on the assessment of the primary energy demand, greenhouse gas emissions and environmental impacts of buildings during production, construction, use (including repair and replacement) and end of life (dismantling), i.e. during the entire life cycle of buildings. In one of its activities, reference buildings (size, materialisation, operational energy demand, etc.) were defined on which the existing national assessment methods are applied using national (if available) databases and (national/regional) approaches. The ?be2226? office building in Lustenau, Austria was selected as one of the reference buildings. TU Graz established a BIM model and quantified the amount of building elements as well as construction materials required and the operational energy demand. The building assessment was carried out using the same material and energy demand but applying the LCA approach used in the different countries represented by the participating Annex experts. The results of these assessments are compared in view of identifying major discrepancies. Preliminary findings show that the greenhouse gas emissions per kg of building material differ up to a factor of two and more. Major differences in the building assessments are observed in the transports to the construction site (imports) and the construction activities as well as in the greenhouse gas emissions of the operational energy demand (electricity). The experts document their practical difficulties and how they overcame them. The results of this activity are used to better target harmonisation efforts.IEA -International Association for the Evaluation of Educational Achievement(Slovenia

Colocalization of coregulated genes: a steered molecular dynamics study of human chromosome 19

The connection between chromatin nuclear organization and gene activity is vividly illustrated by the observation that transcriptional coregulation of certain genes appears to be directly influenced by their spatial proximity. This fact poses the more general question of whether it is at all feasible that the numerous genes that are coregulated on a given chromosome, especially those at large genomic distances, might become proximate inside the nucleus. This problem is studied here using steered molecular dynamics simulations in order to enforce the colocalization of thousands of knowledge-based gene sequences on a model for the gene-rich human chromosome 19. Remarkably, it is found that most, ~80% gene pairs can be brought simultaneously into contact. This is made possible by the low degree of intra-chromosome entanglement and the large number of cliques in the gene coregulatory network. A clique is a set of genes coregulated all together as a group. The constrained conformations for the model chromosome 19 are further shown to be organised in spatial macrodomains that are similar to those inferred from recent HiC measurements. The findings indicate that gene coregulation and colocalization are largely compatible and that this relationship can be exploited to draft the overall spatial organization of the chromosome in vivo. The more general validity and implications of these findings could be investigated by applying to other eukaryotic chromosomes the general and transferable computational strategy introduced here