The Automated Administrative State: A Crisis of Legitimacy

The legitimacy of the administrative state is premised on our faith in agency expertise. Despite their extra-constitutional structure, administrative agencies have been on firm footing for a long time in reverence to their critical role in governing a complex, evolving society. They are delegated enormous power because they respond expertly and nimbly to evolving conditions.In recent decades, state and federal agencies have embraced a novel mode of operation: automation. Agencies rely more and more on software and algorithms in carrying out their delegated responsibilities. The automated administrative state, however, is demonstrably riddled with concerns. Legal challenges regarding the denial of benefits and rights—from travel to disability—have revealed a pernicious pattern of bizarre and unintelligible outcomes.Scholarship to date has explored the pitfalls of automation with a particular frame, asking how we might ensure that automation honors existing legal commitments such as due process. Missing from the conversation are broader, structural critiques of the legitimacy of agencies that automate. Automation throws away the expertise and nimbleness that justify the administrative state, undermining the very case for the existence and authority of agencies.Yet the answer is not to deny agencies access to technology. This article points toward a positive vision of the administrative state that adopts tools only when they enhance, rather than undermine, the underpinnings of agency legitimacy

Patterns of variability in early life traits of a Mediterranean coastal fish

Spawning dates and pelagic larval duration (PLD) are early life traits (ELT) crucial for understanding life cycles, properly assessing patterns of connectivity and gathering indications about patchiness or homogeneity of larval pools. Considering that little attention has been paid to spatial variability in these traits, we investigated variability of ELT from the analysis of otolith microstructure in the common two-banded sea bream Diplodus vulgaris. In the southwestern Adriatic Sea, along ~200 km of coast (∼1° in latitude, 41.2° to 40.2°N), variability of ELT was assessed at multiple spatial scales. Overall, PLD (ranging from 25 to 61 d) and spawning dates (October 2009 to February 2010) showed significant variability at small scales (i.e. <6 km), but not at larger scales. These outcomes suggest patchiness of the larval pool at small spatial scales. Multiple causal processes underlying the observed variability are discussed, along with the need to properly consider spatial variability in ELT, for example when delineating patterns of connectivity. Copyright © 2013 Inter-Research

Graph grammar-based multi-frontal parallel direct solver for two-dimensional isogeometric analysis

This paper introduces the graph grammar based model for developing multi-thread multi-frontal parallel direct solver for two dimensional isogeometric finite element method. Execution of the solver algorithm has been expressed as the sequence of graph grammar productions. At the beginning productions construct the elimination tree with leaves corresponding to finite elements. Following sequence of graph grammar productions generates element frontal matrices at leaf nodes, merges matrices at parent nodes and eliminates rows corresponding to fully assembled degrees of freedom. Finally, there are graph grammar productions responsible for root problem solution and recursive backward substitutions. Expressing the solver algorithm by graph grammar productions allows us to explore the concurrency of the algorithm. The graph grammar productions are grouped into sets of independent tasks that can be executed concurrently. The resulting concurrent multi-frontal solver algorithm is implemented and tested on NVIDIA GPU, providing O(NlogN) execution time complexity where N is the number of degrees of freedom. We have confirmed this complexity by solving up to 1 million of degrees of freedom with 448 cores GPU. © 2012 Published by Elsevier Ltd

Dynamic programming algorithm for generation of optimal elimination trees for multi-frontal direct solver over h-refined grids

In this paper we present a dynamic programming algorithm for finding optimal elimination trees for computational grids refined towards point or edge singularities. The elimination tree is utilized to guide the multi-frontal direct solver algorithm. Thus, the criterion for the optimization of the elimination tree is the computational cost associated with the multi-frontal solver algorithm executed over such tree. We illustrate the paper with several examples of optimal trees found for grids with point, isotropic edge and anisotropic edge mixed with point singularity. We show the comparison of the execution time of the multi-frontal solver algorithm with results of MUMPS solver with METIS library, implementing the nested dissection algorithm. © The Authors. Published by Elsevier B.V

The novel MAPT mutation K298E:mechanisms of mutant tau toxicity, brain pathology and tau expression in induced fibroblast-derived neurons

Frontotemporal lobar degeneration (FTLD) consists of a group of neurodegenerative diseases characterized by behavioural and executive impairment, language disorders and motor dysfunction. About 20-30 % of cases are inherited in a dominant manner. Mutations in the microtubule-associated protein tau gene (MAPT) cause frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17T). Here we report a novel MAPT mutation (K298E) in exon 10 in a patient with FTDP-17T. Neuropathological studies of post-mortem brain showed widespread neuronal loss and gliosis and abundant deposition of hyperphosphorylated tau in neurons and glia. Molecular studies demonstrated that the K298E mutation affects both protein function and alternative mRNA splicing. Fibroblasts from a skin biopsy of the proband taken at post-mortem were directly induced into neurons (iNs) and expressed both 3-repeat and 4-repeat tau isoforms. As well as contributing new knowledge on MAPT mutations in FTDP-17T, this is the first example of the successful generation of iNs from skin cells retrieved post-mortem

Telescopic hybrid fast solver for 3D elliptic problems with point singularities

This paper describes a telescopic solver for two dimensional h adaptive grids with point singularities. The input for the telescopic solver is an h refined two dimensional computational mesh with rectangular finite elements. The candidates for point singularities are first localized over the mesh by using a greedy algorithm. Having the candidates for point singularities, we execute either a direct solver, that performs multiple refinements towards selected point singularities and executes a parallel direct solver algorithm which has logarithmic cost with respect to refinement level. The direct solvers executed over each candidate for point singularity return local Schur complement matrices that can be merged together and submitted to iterative solver. In this paper we utilize a parallel multi-thread GALOIS solver as a direct solver. We use Incomplete LU Preconditioned Conjugated Gradients (ILUPCG) as an iterative solver. We also show that elimination of point singularities from the refined mesh reduces significantly the number of iterations to be performed by the ILUPCG iterative solver

Combining 4D Flow MRI and Complex Networks Theory to Characterize the Hemodynamic Heterogeneity in Dilated and Non-dilated Human Ascending Aortas

Motivated by the evidence that the onset and progression of the aneurysm of the ascending aorta (AAo) is intertwined with an adverse hemodynamic environment, the present study characterized in vivo the hemodynamic spatiotemporal complexity and organization in human aortas, with and without dilated AAo, exploring the relations with clinically relevant hemodynamic and geometric parameters. The Complex Networks (CNs) theory was applied for the first time to 4D flow magnetic resonance imaging (MRI) velocity data of ten patients, five of them presenting with AAo dilation. The time-histories along the cardiac cycle of velocity-based quantities were used to build correlation-based CNs. The CNs approach succeeded in capturing large-scale coherent flow features, delimiting flow separation and recirculation regions. CNs metrics highlighted that an increasing AAo dilation (expressed in terms of the ratio between the maximum AAo and aortic root diameter) disrupts the correlation in forward flow reducing the correlation persistence length, while preserving the spatiotemporal homogeneity of secondary flows. The application of CNs to in vivo 4D MRI data holds promise for a mechanistic understanding of the spatiotemporal complexity and organization of aortic flows, opening possibilities for the integration of in vivo quantitative hemodynamic information into risk stratification and classification criteria

A Eulerian method to analyze wall shear stress fixed points and manifolds in cardiovascular flows

Based upon dynamical systems theory, a fixed point of a vector field such as the wall shear stress (WSS) at the luminal surface of a vessel is a point where the vector field vanishes. Unstable/stable manifolds identify contraction/expansion regions linking fixed points. The significance of such WSS topological features lies in their strong link with “disturbed” flow features like flow stagnation, separation and reversal, deemed responsible for vascular dysfunction initiation and progression. Here, we present a Eulerian method to analyze WSS topological skeleton through the identification and classification of WSS fixed points and manifolds in complex vascular geometries. The method rests on the volume contraction theory and analyzes the WSS topological skeleton through the WSS vector field divergence and Poincare´ index. The method is here applied to computational hemodynamics models of carotid bifurcation and intracranial aneurysm. An in-depth analysis of the time dependence of the WSS topological skeleton along the cardiac cycle is provided, enriching the information obtained from cycle-average WSS. Among the main findings, it emerges that on the carotid bifurcation, instantaneous WSS fixed points co-localize with cycle-average WSS fixed points for a fraction of the cardiac cycle ranging from 0 to 14.5 % ; a persistent instantaneous WSS fixed point confined on the aneurysm dome does not co-localize with the cycle-average low-WSS region. In conclusion, the here presented approach shows the potential to speed up studies on the physiological significance of WSS topological skeleton in cardiovascular flows, ultimately increasing the chance of finding mechanistic explanations to clinical observations

Quasi-optimal elimination trees for 2D grids with singularities

We construct quasi-optimal elimination trees for 2D finite element meshes with singularities.These trees minimize the complexity of the solution of the discrete system. The computational cost estimates of the elimination process model the execution of the multifrontal algorithms in serial and in parallel shared-memory executions. Since the meshes considered are a subspace of all possible mesh partitions, we call these minimizers quasi-optimal.We minimize the cost functionals using dynamic programming. Finding these minimizers is more computationally expensive than solving the original algebraic system. Nevertheless, from the insights provided by the analysis of the dynamic programming minima, we propose a heuristic construction of the elimination trees that has cost O(log(Ne log(Ne)), where N e is the number of elements in the mesh.We show that this heuristic ordering has similar computational cost to the quasi-optimal elimination trees found with dynamic programming and outperforms state-of-the-art alternatives in our numerical experiments