Intelligent Microgrids

Center for Electromechanic

Complexity theory of psychopathology

There is a renewed interest for complex adaptive system approaches that can account for the inherently complex and dynamic nature of psychopathology. Yet a theory of psychopathology grounded in the principles of complex adaptive systems is lacking. Here, we present such a theory based on the notion of dynamic patterns: patterns that are formed over time. We propose that psychopathology can be understood as a dynamic pattern that emerges from self-organized interactions between interdependent biopsychosocial processes in a complex adaptive system comprising a person in their environment. Psychopathology is emergent in the sense that it refers to the person-environment system as a whole and cannot be reduced to specific system parts. Psychopathology as a dynamic pattern is also self-organized, meaning that it arises solely from the interdependencies in the system: the interactions between countless biopsychosocial variables. All possible manifestations of psychopathology will correspond to a wide variety of dynamic patterns. Yet we propose that the development of these patterns over time can be described by general principles of pattern formation in complex adaptive systems. A discussion of implications for classification, intervention, and public health concludes the article. (PsycInfo Database Record (c) 2023 APA, all rights reserved).</p

Towards Conceptualizing EU Cybersecurity Law. ZEI Discussion Paper C253 2019

The European Union has a wide spectrum of legal instruments addressing various aspects of cybersecurity, ranging from electronic communication laws, data protection regulations through network and information security legislation to instruments dealing with cybercrime and recommendations on coordinated response to large scale cyber incidents – all this without having a commonly accepted definition of cybersecurity

Report on DIMACS Working Group Meeting: Mathematical Sciences Methods for the Study of Deliberate Releases of Biological Agents and their Consequences

55 pages, 1 article*Report on DIMACS Working Group Meeting: Mathematical Sciences Methods for the Study of Deliberate Releases of Biological Agents and their Consequences* (Castillo-Chavez, Carlos; Roberts, Fred S.) 55 page

DB1000N SOFTWARE AS UKRAINE’S MILITARY UTILITY TO COUNTER RUSSIAN INVASION IN 2022

As Russia launched an invasion in every domain of warfare, including cyberspace, Ukraine employed an Information Technology (IT) army equipped with software called db1000n on March 2022. This article seeks to explain how the use of db1000n helps Ukraine against the 2022 Russian invasion. Using a case study as the research method and Susan Martin’s military utility concept as the analytical framework, this article found that db1000n helps to support Ukraine’s cyber warfare effort by being Distributed Denial of Service (DDoS) attack software that possesses three types of military utility, namely technical utility, tactical utility, and strategic utility. Nevertheless, db1000n still has some limitations that cannot secure an easy victory in cyber warfare.

A Widening Attack Plain

A glimpse of our digital future includes diverse actors operating on a widening attack plain with affects ranging from data disruption to death and destruction. How do we craft meaningful narratives of the future that can advise our community today? How do we combat the weaponization of data and future technology? Where do we even start? Threatcasting is a conceptual framework and process that enables multidisciplinary groups to envision and systematically plan against threats ten years in the future. In August 2016, the Army Cyber Institute convened a cross section of public, private and academic participants to model future digital threats using this process with inputs from social science, technical research, cultural history, economics, trends, expert interviews and even a little science fiction. Renowned futurist Brian David Johnson and Army Major Natalie Vanatta will explore the results of this project that not only describes tomorrow’s threats but also identifies specific actions, indicators and concrete steps that can be taken today to disrupt, mitigate and recover from these future threats.https://digitalcommons.usmalibrary.org/aci_books/1034/thumbnail.jp

The segregated connectome of late-life depression: a combined cortical thickness and structural covariance analysis.

Late-life depression (LLD) has been associated with both generalized and focal neuroanatomical changes including gray matter atrophy and white matter abnormalities. However, previous literature has not been consistent and, in particular, its impact on the topology organization of brain networks remains to be established. In this multimodal study, we first examined cortical thickness, and applied graph theory to investigate structural covariance networks in LLD. Thirty-three subjects with LLD and 25 controls underwent T1-weighted, fluid-attenuated inversion recovery and clinical assessments. Freesurfer was used to perform vertex-wise comparisons of cortical thickness, whereas the Graph Analysis Toolbox (GAT) was implemented to construct and analyze the structural covariance networks. LLD showed a trend of lower thickness in the left insular region (p < 0.001 uncorrected). In addition, the structural network of LLD was characterized by greater segregation, particularly showing higher transitivity (i.e., measure of clustering) and modularity (i.e., tendency for a network to be organized into subnetworks). It was also less robust against random failure and targeted attacks. Despite relative cortical preservation, the topology of the LLD network showed significant changes particularly in segregation. These findings demonstrate the potential for graph theoretical approaches to complement conventional structural imaging analyses and provide novel insights into the heterogeneous etiology and pathogenesis of LLD.This work was supported by the NIHR Biomedical Research Unit in Dementia and the Biomedical Research Centre awarded to Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge, and the NIHR Biomedical Research Unit in Dementia and the Biomedical Research Centre awarded to Newcastle upon Tyne Hospitals NHS Foundation Trust and the Newcastle University. Elijah Mak was in receipt of a Gates Cambridge, PhD studentship.This is the author accepted manuscript. It first appeared from Elsevier at http://dx.doi.org/10.1016/j.neurobiolaging.2016.08.013