ENER-BI: Integrating Energy and Spatial Data for Cities’ Decarbonisation Planning

Given the current climate emergency, our planet is suffering. Mitigation measures must be urgently deployed in urban environments, which are responsible for more than 70% of global CO2 emissions. In this sense, a deeper integration between energy and urban planning disciplines is a key factor for effective decarbonisation in urban environments. This is addressed in the Cities4ZERO decarbonisation methodology. This method specifically points out the need for technology-based solutions able to support that integration among both disciplines at a local level, enriching decision-making in urban decarbonisation policy-making, diagnosis, planning, and follow-up tasks, incorporating the spatial dimension to the whole process (GIS-based), as well as the possibilities of the digital era. Accordingly, this paper explores the demands of both integrated urban energy planning and European/Basque energy directives, to set the main requisites and functionalities that Decision Support Systems (DSSs) must fulfil to effectively support city managers and the urban decarbonisation process.This research was funded by European Commission, grant number 691883

ENER-BI: Integrating Energy and Spatial Data for Cities’ Decarbonisation Planning

Given the current climate emergency, our planet is suffering. Mitigation measures must be urgently deployed in urban environments, which are responsible for more than 70% of global CO2 emissions. In this sense, a deeper integration between energy and urban planning disciplines is a key factor for effective decarbonisation in urban environments. This is addressed in the Cities4ZERO decarbonisation methodology. This method specifically points out the need for technology-based solutions able to support that integration among both disciplines at a local level, enriching decision-making in urban decarbonisation policy-making, diagnosis, planning, and follow-up tasks, incorporating the spatial dimension to the whole process (GIS-based), as well as the possibilities of the digital era. Accordingly, this paper explores the demands of both integrated urban energy planning and European/Basque energy directives, to set the main requisites and functionalities that Decision Support Systems (DSSs) must fulfil to effectively support city managers and the urban decarbonisation process.This research was funded by European Commission, grant number 691883

Dwelling Quietly in the Rich Club: Brain Network Determinants of Slow Cortical Fluctuations

For more than a century, cerebral cartography has been driven by investigations of structural and morphological properties of the brain across spatial scales and the temporal/functional phenomena that emerge from these underlying features. The next era of brain mapping will be driven by studies that consider both of these components of brain organization simultaneously -- elucidating their interactions and dependencies. Using this guiding principle, we explored the origin of slowly fluctuating patterns of synchronization within the topological core of brain regions known as the rich club, implicated in the regulation of mood and introspection. We find that a constellation of densely interconnected regions that constitute the rich club (including the anterior insula, amygdala, and precuneus) play a central role in promoting a stable, dynamical core of spontaneous activity in the primate cortex. The slow time scales are well matched to the regulation of internal visceral states, corresponding to the somatic correlates of mood and anxiety. In contrast, the topology of the surrounding "feeder" cortical regions show unstable, rapidly fluctuating dynamics likely crucial for fast perceptual processes. We discuss these findings in relation to psychiatric disorders and the future of connectomics.Comment: 35 pages, 6 figure

Gene co-expression analysis identifies brain regions and cell types involved in migraine pathophysiology

Migraine is a common disabling neurovascular brain disorder typically characterised by attacks of severe headache and associated with autonomic and neurological symptoms. Migraine is caused by an interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified over a dozen genetic loci associated with migraine. Here, we integrated migraine GWAS data with high-resolution spatial gene expression data of normal adult brains from the Allen Human Brain Atlas to identify specific brain regions and molecular pathways that are possibly involved in migraine pathophysiology. To this end, we used two complementary methods. In GWAS data from 23,285 migraine cases and 95,425 controls, we first studied modules of co-expressed genes that were calculated based on human brain expression data for enrichment of genes that showed association with migraine. Enrichment of a migraine GWAS signal was found for five modules that suggest involvement in migraine pathophysiology of: (i) neurotransmission, protein catabolism and mitochondria in the cortex; (ii) transcription regulation in the cortex and cerebellum; and (iii) oligodendrocytes and mitochondria in subcortical areas. Second, we used the high-confidence genes from the migraine GWAS as a basis to construct local migraine-related co-expression gene networks. Signatures of all brain regions and pathways that were prominent in the first method also surfaced in the second method, thus providing support that these brain regions and pathways are indeed involved in migraine pathophysiology

Absence of cardiovascular manifestations in a haploinsufficient TGFBR1 mouse model

Loeys-Dietz syndrome (LDS) is an autosomal dominant arterial aneurysm disease belonging to the spectrum of transforming growth factor beta (TGF beta)-associated vasculopathies. In its most typical form it is characterized by the presence of hypertelorism, bifid uvula/cleft palate and aortic aneurysm and/or arterial tortuosity. LDS is caused by heterozygous loss of function mutations in the genes encoding TGF beta receptor 1 and 2 (TGFBR1 and -2), which lead to a paradoxical increase in TGF beta signaling. To address this apparent paradox and to gain more insight into the pathophysiology of aneurysmal disease, we characterized a new Tgfbr1 mouse model carrying a p.Y378* nonsense mutation. Study of the natural history in this model showed that homozygous mutant mice die during embryonic development due to defective vascularization. Heterozygous mutant mice aged 6 and 12 months were morphologically and (immuno) histochemically indistinguishable from wild-type mice. We show that the mutant allele is degraded by nonsense mediated mRNA decay, expected to result in haploinsufficiency of the mutant allele. Since this haploinsufficiency model does not result in cardiovascular malformations, it does not allow further study of the process of aneurysm formation. In addition to providing a comprehensive method for cardiovascular phenotyping in mice, the results of this study confirm that haploinsuffciency is not the underlying genetic mechanism in human LDS

From modularity to emergence: a primer on the design and science of complex systems

Electrical networks, flocking birds, transportation hubs, weather patterns, commercial organisations, swarming robots... Increasingly, many of the systems that we want to engineer or understand are said to be ‘complex’. These systems are often considered to be intractable because of their unpredictability, non-linearity, interconnectivity, heterarchy and ‘emergence’. Such attributes are often framed as a problem, but can also be exploited to encourage systems to efficiently exhibit intelligent, robust, self-organising behaviours. But what does it mean to describe systems as complex? How do these complex systems differ from the more easily understood ‘modular’ systems that we are familiar with? What are the underlying similarities between different systems, whether modular or complex? Answering these questions is a first step in approaching the design and science of complexity. However, to do so, it is necessary to look beyond the specifics of any particular system or field of study. We need to consider the fundamental nature of systems, looking for a common way to view ostensibly different phenomena. This primer introduces a domain-neutral framework and diagrammatic scheme for characterising the ways in which systems are modular or complex. Rather than seeing modularity and complexity as inherent attributes of systems, we instead see them as ways in which those systems are characterised by those who are interested in them. The framework is not tied to any established mode of representation (e.g. networks, equations, formal modelling languages) nor to any domain-specific terminology (e.g. ‘vertex’, ‘eigenvector’, ‘entropy’). Instead, it consists of basic system constructs and three fundamental attributes of modular system architecture, namely structural encapsulation, function-structure mapping and interfacing. These constructs and attributes encourage more precise descriptions of different aspects of complexity (e.g. emergence, self-organisation, heterarchy). This allows researchers and practitioners from different disciplines to share methods, theories and findings related to the design and study of different systems, even when those systems appear superficially dissimilar