“A Cloud of Constitutional Illegitimacy”: Prospectivity and the De Facto Doctrine in the Gerrymandering Context

Courts have traditionally shielded the acts of malapportioned or otherwise illegally constituted legislatures from dissolution by employing the “de facto doctrine,” an ancient common law policy tool with medieval roots. In its most basic form, the de facto doctrine seeks to safeguard the acts of unlawful but well-intentioned public officials from collateral attack out of concern for third-party reliance and a bald recognition of necessity. However, the doctrine as traditionally articulated only serves to validate past official acts; once the official in question has lost the “color of authority,” the doctrine no longer affords his actions de facto validity. Although this has not prevented courts from extending the doctrine, or something like it, to cover prospective acts in certain scenarios, courts have generally avoided “taking a look under the hood” and wrestling with the policy concerns underlying the doctrine to see if they still apply prospectively. This Note examines the potential use of the de facto doctrine in the gerrymandering context. Both racial and partisan gerrymandering present distinct challenges for courts seeking to prospectively apply the de facto doctrine to acts of a state legislature: generally, gerrymanders are created intentionally, making it harder to apply any “good faith” exception; illegal gerrymandering by its nature trespasses on important constitutional guarantees; and the traditional motivations for the de facto doctrine—necessity and reliance—arguably do not apply to legislation crafted by an unconstitutional government body seeking to preserve its power. By examining the historical roots of the doctrine, tracing its modern development, and considering its underlying policy rationales, this Note seeks to answer two questions: (1) how have courts expanded the de facto doctrine and its animating principles prospectively?; and (2) how do those expansions shape the prospective application of the doctrine in the gerrymandering context

From Social Simulation to Integrative System Design

As the recent financial crisis showed, today there is a strong need to gain "ecological perspective" of all relevant interactions in socio-economic-techno-environmental systems. For this, we suggested to set-up a network of Centers for integrative systems design, which shall be able to run all potentially relevant scenarios, identify causality chains, explore feedback and cascading effects for a number of model variants, and determine the reliability of their implications (given the validity of the underlying models). They will be able to detect possible negative side effect of policy decisions, before they occur. The Centers belonging to this network of Integrative Systems Design Centers would be focused on a particular field, but they would be part of an attempt to eventually cover all relevant areas of society and economy and integrate them within a "Living Earth Simulator". The results of all research activities of such Centers would be turned into informative input for political Decision Arenas. For example, Crisis Observatories (for financial instabilities, shortages of resources, environmental change, conflict, spreading of diseases, etc.) would be connected with such Decision Arenas for the purpose of visualization, in order to make complex interdependencies understandable to scientists, decision-makers, and the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

“To Be a Yardstick”: Individual Rebellion and Social Conformity in Cathy Park Hong’s Engine Empire

[Abstract] This Master’s thesis engages in a multidisciplinary humanistic analysis of Cathy Park Hong’s triptych Engine Empire. Said analysis is divided into three parts, each one corresponding to one of the poem’s sections. Following Sigmund Freud’s anthropological ideas on the origin and development of civilization, every chapter deals with the struggles of individuals who refuse to abide by the social norms imposed on them. Freud’s theory is complemented with the works of Michel Foucault regarding the means by which the ruling power exerts control over its subjects. Together with the analysis of the poem proper, the aim of this paper is to show how a literary work, namely a work of poetry, can elicit critical thinking.Traballo fin de mestrado (UDC.FIL). Estudos ingleses avanzados e as súas aplicacións. Curso 2018/201

BPS Spectra, Barcodes and Walls

BPS spectra give important insights into the non-perturbative regimes of supersymmetric theories. Often from the study of BPS states one can infer properties of the geometrical or algebraic structures underlying such theories. In this paper we approach this problem from the perspective of persistent homology. Persistent homology is at the base of topological data analysis, which aims at extracting topological features out of a set of points. We use these techniques to investigate the topological properties which characterize the spectra of several supersymmetric models in field and string theory. We discuss how such features change upon crossing walls of marginal stability in a few examples. Then we look at the topological properties of the distributions of BPS invariants in string compactifications on compact threefolds, used to engineer black hole microstates. Finally we discuss the interplay between persistent homology and modularity by considering certain number theoretical functions used to count dyons in string compactifications and by studying equivariant elliptic genera in the context of the Mathieu moonshine

HARD: Hybrid Adaptive Resource Discovery for Jungle Computing

In recent years, Jungle Computing has emerged as a distributed computing paradigm based on simultaneous combination of various hierarchical and distributed computing environments which are composed by large number of heterogeneous resources. In such a computing environment, the resources and the underlying computation and communication infrastructures are highly-hierarchical and heterogeneous. This creates a lot of difficulty and complexity for finding the proper resources in a precise way in order to run a particular job on the system efficiently. This paper proposes Hybrid Adaptive Resource Discovery (HARD), a novel efficient and highly scalable resource-discovery approach which is built upon a virtual hierarchical overlay based on self-organization and self-adaptation of processing resources in the system, where the computing resources are organized into distributed hierarchies according to a proposed hierarchical multi-layered resource description model. The proposed approach supports distributed query processing within and across hierarchical layers by deploying various distributed resource discovery services and functionalities in the system which are implemented using different adapted algorithms and mechanisms in each level of hierarchy. The proposed approach addresses the requirements for resource discovery in Jungle Computing environments such as high-hierarchy, high-heterogeneity, high-scalability and dynamicity. Simulation results show significant scalability and efficiency of the proposed approach over highly heterogeneous, hierarchical and dynamic computing environments

Goal → New Heuristic Model of Ideality: Logos → Coincidentia Oppositorum → Primordial Generating Structure

Fundamental knowledge endures deep conceptual crisis manifested in total crisis of understanding, crisis of interpretation and representation, loss of certainty, troubles with physics, crisis of methodology. Crisis of understanding in fundamental science generates deep crisis of understanding in global society. What way should we choose for overcoming total crisis of understanding in fundamental science? It should be the way of metaphysical construction of new comprehensive model of ideality on the basis of the "modified ontology". Result of quarter-century wanderings: sum of ideas, concepts and eidoses, new understanding of space, time, consciousness

Stream Learning in Energy IoT Systems: A Case Study in Combined Cycle Power Plants

The prediction of electrical power produced in combined cycle power plants is a key challenge in the electrical power and energy systems field. This power production can vary depending on environmental variables, such as temperature, pressure, and humidity. Thus, the business problem is how to predict the power production as a function of these environmental conditions, in order to maximize the profit. The research community has solved this problem by applying Machine Learning techniques, and has managed to reduce the computational and time costs in comparison with the traditional thermodynamical analysis. Until now, this challenge has been tackled from a batch learning perspective, in which data is assumed to be at rest, and where models do not continuously integrate new information into already constructed models. We present an approach closer to the Big Data and Internet of Things paradigms, in which data are continuously arriving and where models learn incrementally, achieving significant enhancements in terms of data processing (time, memory and computational costs), and obtaining competitive performances. This work compares and examines the hourly electrical power prediction of several streaming regressors, and discusses about the best technique in terms of time processing and predictive performance to be applied on this streaming scenario.This work has been partially supported by the EU project iDev40. This project has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 783163. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Austria, Germany, Belgium, Italy, Spain, Romania. It has also been supported by the Basque Government (Spain) through the project VIRTUAL (KK-2018/00096), and by Ministerio de Economía y Competitividad of Spain (Grant Ref. TIN2017-85887-C2-2-P)