An Ethical Framework for Artificial Intelligence and Sustainable Cities

The digital revolution has brought ethical crossroads of technology and behavior, especially in the realm of sustainable cities. The need for a comprehensive and constructive ethical framework is emerging as digital platforms encounter trouble to articulate the transformations required to accomplish the sustainable development goal (SDG) 11 (on sustainable cities), and the remainder of the related SDGs. The unequal structure of the global system leads to dynamic and systemic problems, which have a more significant impact on those that are most vulnerable. Ethical frameworks based only on the individual level are no longer sufficient as they lack the necessary articulation to provide solutions to the new systemic challenges. A new ethical vision of digitalization must comprise the understanding of the scales and complex interconnections among SDGs and the ongoing socioeconomic and industrial revolutions. Many of the current social systems are internally fragile and very sensitive to external factors and threats, which lead to unethical situations. Furthermore, the multilayered net-like social tissue generates clusters of influence and leadership that prevent communities from a proper development. Digital technology has also had an impact at the individual level, posing several risks including a more homogeneous and predictable humankind. To preserve the core of humanity, we propose an ethical framework to empower individuals centered on the cities and interconnected with the socioeconomic ecosystem and the environment through the complex relationships of the SDGs. Only by combining human-centered and collectiveness-oriented digital development will it be possible to construct new social models and interactions that are ethical. Thus, it is necessary to combine ethical principles with the digital innovation undergoing in all the dimensions of sustainability

Error control in simplification before generation algorithms for symbolic analysis of large analogue circuits

Circuit reduction is a fundamental first step in addressing the symbolic analysis of large analogue circuits. A new algorithm for simplification before generation is presented which is very efficient in terms of speed and the amount of circuit reduction, and solves the accuracy problems of previously reported approaches

An error-controlled methodology for approximate hierarchical symbolic analysis

Limitations of existing approaches for symbolic analysis of large analog circuits are discussed. To address their solution, a new methodology for hierarchical symbolic analysis is introduced. The combination of a hierarchical modeling technique and approximation strategies, comprising circuit reduction, graph-based symbolic solution of circuit equations and matrix-based error control, provides optimum results in terms of speech and quality of results.European Commission ESPRIT 21812Comisión Interministerial de Ciencia y Tecnología TIC97-058

A New Point of View on Skin-Friction Contributions in Adverse-Pressure-gradient Turbulent Boundary Layers

Skin-friction decompositions such as the so-called FIK identity (Fukagata et al., 2002) are useful tools in identifying relevant contributions to the friction, but may also lead to results difficult to interpret when the total friction is recovered from cancellation of multiple terms with large values. We propose a new formulation of the FIK contributions related to streamwise inhomogeneity, which is derived from the convective form of the momentum equation and using the concept of dynamic pressure. We examine turbulent boundary layers subjected to various pressure-gradient conditions, including cases with drag-reducing control. The new formulation distinguishes more precisely the roles of the free-stream pressure distribution, wall-normal convection, and turbulent fluctuations. Our results allow to identify different regimes in adverse-pressure-gradient turbulent boundary layers, corresponding to different proportions of the various contributions, and suggest a possible direction towards studying the onset of mean separation

Aerodynamic Effects of Uniform Blowing and Suction on a NACA4412 Airfoil

We carried out high-fidelity large-eddy simulations to investigate the effects of uniform blowing and uniform suction on the aerodynamic efficiency of a NACA4412 airfoil at the moderate Reynolds number based on chord length and incoming velocity of Rec= 200 , 000. We found that uniform blowing applied at the suction side reduces the aerodynamics efficiency, while uniform suction increases it. This result is due to the combined impact of blowing and suction on skin friction, pressure drag and lift. When applied to the pressure side, uniform blowing improves aerodynamic efficiency. The Reynolds-number dependence of the relative contributions of pressure and friction to the total drag for the reference case is analysed via Reynolds-averaged Navier–Stokes simulations up to Rec= 10 , 000 , 000. The results suggest that our conclusions on the control effect can tentatively be extended to a broader range of Reynolds numbers

Assessing whether artificial intelligence is an enabler or an inhibitor of sustainability at indicator level

"Since the early phase of the artificial-intelligence (AI) era expectations towards AI are high, with experts believing that AI paves the way for managing and handling various global challenges. However, the significant enabling and inhibiting influence of AI for sustainable development needs to be assessed carefully, given that the technology diffuses rapidly and affects millions of people worldwide on a day-to-day basis. To address this challenge, a panel discussion was organized by the KTH Royal Institute of Technology, the AI Sustainability Center and MIT Massachusetts Institute of Technology, gathering a wide range of AI experts. This paper summarizes the insights from the panel discussion around the following themes: The role of AI in achieving the Sustainable Development Goals (SDGs) AI for a prosperous 21st century Transparency, automated decision-making processes, and personal profiling and Measuring the relevance of Digitalization and Artificial Intelligence (D&AI) at the indicator level of SDGs. The research-backed panel discussion was dedicated to recognize and prioritize the agenda for addressing the pressing research gaps for academic research, funding bodies, professionals, as well as industry with an emphasis on the transportation sector. A common conclusion across these themes was the need to go beyond the development of AI in sectorial silos, so as to understand the impacts AI might have across societal, environmental, and economic outcomes. The recordings of the panel discussion can be found at: https://www.kth.se/en/2.18487/evenemang/the-role-of-ai-in-achieving-the-sdgs-enabler-or-inhibitor-1.1001364?date=2020â 08â 20&length=1&orglength=185&orgdate=2020â 06â 30 Short link: https://bit.ly/2Kap1tE © 2021"The authors acknowledge the KTH Sustainability Office and the KTH Digitalization Platform for their provided funding, which enabled the organization of this panel discussion. SG acknowledges the funding provided by the German Federal Ministry for Education and Research (BMBF) for the project “digitainable”. SDL acknowledges support through the Spanish Governmen

Follicular helper T cells are required for systemic autoimmunity

Production of high-affinity pathogenic autoantibodies appears to be central to the pathogenesis of lupus. Because normal high-affinity antibodies arise from germinal centers (GCs), aberrant selection of GC B cells, caused by either failure of negative selection or enhanced positive selection by follicular helper T (TFH) cells, is a plausible explanation for these autoantibodies. Mice homozygous for the san allele of Roquin, which encodes a RING-type ubiquitin ligase, develop GCs in the absence of foreign antigen, excessive TFH cell numbers, and features of lupus. We postulated a positive selection defect in GCs to account for autoantibodies. We first demonstrate that autoimmunity in Roquinsan/san (sanroque) mice is GC dependent: deletion of one allele of Bcl6 specifically reduces the number of GC cells, ameliorating pathology. We show that Roquinsan acts autonomously to cause accumulation of TFH cells. Introduction of a null allele of the signaling lymphocyte activation molecule family adaptor Sap into the sanroque background resulted in a substantial and selective reduction in sanroque TFH cells, and abrogated formation of GCs, autoantibody formation, and renal pathology. In contrast, adoptive transfer of sanroque TFH cells led to spontaneous GC formation. These findings identify TFH dysfunction within GCs and aberrant positive selection as a pathway to systemic autoimmunity