Visual Analytics to Support Evidence-Based Decision Making

The aim of this thesis is the design of visual analytics solutions to support evidence-based decision making. Due to the ever-growing complexity of the world, strategical decision making has become an increasingly challenging task. At the business level, decisions are not solely driven by economic factors anymore. Environmental and social aspects are also taken into account in modern business decisions. At the political level, sustainable decision making is additionally influenced by the public opinion, since politicians target the conservation of their power. Decision makers face the challenge of taking all these factors into consideration and, at the same time, of increasing their efficiency to immediately react on abrupt changes in their environment. Due to the digitization era, large amounts of data are digitally stored. The knowledge hidden in these datasets can be used to address the mentioned challenges in decision making. However, handling large datasets, extracting knowledge from them, and incorporating this knowledge into the decision making process poses significant challenges. Additional complexity is added by the varying expertises of stakeholders involved in the decision making process. Strategical decisions today are not solely made by individuals. In contrast, a consortium of advisers, domain experts, analysts, etc. support decision makers in their final choice. The amount of involved stakeholders bears the risk of hampering communication efficiency and effectiveness due to knowledge gaps coming from different expertise levels. Information systems research has reacted to these challenges by promoting research in computational decision support systems. However, recent research shows that most of the challenges remain unsolved. During the last decades, visual analytics has evolved as a research field for extracting knowledge from large datasets. Therefore, combining human perception capabilities and computers’ processing power offers great analysis potential, also for decision making. However, despite obvious overlaps between decision making and visual analytics, theoretical foundations for applying visual analytics to decision making have been missing. In this thesis, we promote the augmentation of decision support systems with visual analytics. Our concept comprises a methodology for the design of visual analytics systems that target decision making support. Therefore, we first introduce a general decision making domain characterization, comprising the analysis of potential users, relevant data categories, and decision making tasks to be supported with visual analytics technologies. Second, we introduce a specialized design process for the development of visual analytics decision support systems. Third, we present two models on how visual analytics facilitates the bridging of knowledge gaps between stakeholders involved in the decision making process: one for decision making at the business level and one for political decision making. To prove the applicability of our concepts, we apply our design methodology in several design studies targeting concrete decision making support scenarios. The presented design studies cover the full range of data, user, and task categories characterized as relevant for decision making. Within these design studies, we first tailor our general decision making domain characterization to the specific domain problem at hand. We show that our concept supports a consistent characterization of user types, data categories and decision making tasks for specific scenarios. Second, each design study follows the design process presented in our concept. And third, the design studies demonstrate how to bridge knowledge gaps between stakeholders. The resulting visual analytics systems allow the incorporation of knowledge extracted from data into the decision making process and support the collaboration of stakeholders with varying levels of expertises

Forcing-dependent dynamics and emergence of helicity in rotating turbulence

The effects of large-scale mechanical forcing on the dynamics of rotating turbulent flows are studied by means of direct numerical simulations, systematically varying the nature of the mechanical force in time. We find that the statistically stationary solutions of these flows depend on the nature of the forcing mechanism. Rapidly enough rotating flows with a forcing that has a persistent direction relative to the axis of rotation bifurcate from a non-helical state to a helical state despite the fact that the forcing is non-helical. We demonstrate that the nature of the mechanical force in time and the emergence of helicity have direct implications for the cascade dynamics of these flows, determining the anisotropy in the flow, the energy condensation at large scales and the power-law energy spectra that are consistent with previous findings and phenomenologies under strong and weak turbulence

Avaliação das consequências de galgamento sobre estruturas portuárias: caso de estudo da praia da Vitória, Açores

Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em HidráulicaA presente dissertação, inserida na área de especialização de hidráulica de engenharia civil, procura avaliar o risco de galgamento sobre estruturas portuárias. Devido à ocorrência de galgamentos, há necessidade em garantir a segurança de bens, pessoas, equipamentos, estruturas e atividades junto a elas desenvolvidas e, ainda, em precaver gastos a nível económico. Nesse sentido, recorre-se neste trabalho a previsões da agitação marítima em águas profundas fornecidas pelo modelo WAM que, acoplado aos modelos SWAN e DREAMS, permite a caracterização do estado de agitação do mar junto à estrutura portuária. Posteriormente, aplica-se a ferramenta neuronal NN_OVERTOPPING2 que fornece os caudais médios galgados nas estruturas. Seguidamente, recorre-se a três metodologias distintas para avaliar as consequências do galgamento: uma metodologia simples, Analytic Hierarchy Process (AHP) e Analytic Network Process (ANP). As metodologias multicritério AHP e ANP tornam-se mais vantajosas em relação à metodologia simples, na medida em que permitem análises espaciais definindo o risco a que cada área está sujeita. Estas melhorias sustentam uma avaliação do risco mais fiável, o que é fundamental para o apoio à tomada de decisão e numa gestão eficaz das zonas costeiras e portuárias. Por fim, aplica-se o procedimento descrito ao porto da Praia da Vitória (Açores, Portugal).Abstract: This dissertation, developed within the hydraulics branch of civil engineering, aims at contributing to the assessment of the risk associated to the wave overtopping of port structures. Due to the occurrence of overtopping, there is a requirement to ensure the safety of goods, people, equipment, structures and activities developed in their surroundings and, still, avoid economic spending. Therefore, the study uses forecast wave conditions in deep water, provided by the WAMmodel, which coupled to SWAN and DREAMS models, allows to characterize the sea state near the port structure. Subsequently, the NN_OVERTOPPING2 artificial neuronal tool is applied, which provides the mean flow overtopping discharge over the structures. Finally, three different methodologies to assess the consequences of wave overtopping are used: a simple methodology, the Analytic Hierarchy Process (AHP) and the Analytic Network Process (ANP). The multi-criteria AHP and ANP methodologies are more advantageous in comparison with the simplistic methodology, since they allow spatial analysis and definition of the risk that each area is subject to. These improvements support a more reliable risk assessment, which is essential in the decision-making process and in a effective management of coastal and port areas. The procedure in this study is applied in the port of Praia da Vitória (Azores, Portugal).N/

Paramedics experiences and expectations concerning advance directives: A prospective, questionnaire-based, bi-centre study

Background: Advance directives and palliative crisis cards are means by which palliative care patients can exert their autonomy in end-of-life decisions. Aim: To examine paramedics’ attitudes towards advance directives and end-of-life care. Design: Questionnaire-based investigation using a self-administered survey instrument. Setting/participants: Paramedics of two cities (Hamburg and Goettingen, Germany) were included. Participants were questioned as to (1) their attitudes about advance directives, (2) their clinical experiences in connection with end-of-life situations (e.g. resuscitation), (3) their suggestions in regard to advance directives, ‘Do not attempt resuscitation’ orders and palliative crisis cards. Results: Questionnaires were returned by 728 paramedics (response rate: 81%). The majority of paramedics (71%) had dealt with advance directives and end-of-life decisions in emergency situations. Most participants (84%) found that cardiopulmonary resuscitation in end-of-life patients is not useful and 75% stated that they would withhold cardiopulmonary resuscitation in the case of legal possibility. Participants also mentioned that more extensive discussion of legal aspects concerning advance directives should be included in paramedic training curricula. They suggested that palliative crisis cards should be integrated into end-of-life care. Conclusions: Decision making in prehospital end-of-life care is a challenge for all paramedics. The present investigation demonstrates that a dialogue bridging emergency medical and palliative care issues is necessary. The paramedics indicated that improved guidelines on end-of-life decisions and the termination of cardiopulmonary resuscitation in palliative care patients may be essential. Participants do not feel adequately trained in end-of-life care and the content of advance directives. Other recent studies have also demonstrated that there is a need for training curricula in end-of-life care for paramedics

The association between frailty and MRI features of cerebral small vessel disease

Abstract: Frailty is a common syndrome in older individuals that is associated with poor cognitive outcome. The underlying brain correlates of frailty are unclear. The aim of this study was to investigate the association between frailty and MRI features of cerebral small vessel disease in a group of non-demented older individuals. We included 170 participants who were classified as frail (n = 30), pre-frail (n = 85) or non-frail (n = 55). The association of frailty and white matter hyperintensity volume and shape features, lacunar infarcts and cerebral perfusion was investigated by regression analyses adjusted for age and sex. Frail and pre-frail participants were older, more often female and showed higher white matter hyperintensity volume (0.69 [95%-CI 0.08 to 1.31], p = 0.03 respectively 0.43 [95%-CI: 0.04 to 0.82], p = 0.03) compared to non-frail participants. Frail participants showed a non-significant trend, and pre-frail participants showed a more complex shape of white matter hyperintensities (concavity index: 0.04 [95%-CI: 0.03 to 0.08], p = 0.03; fractal dimensions: 0.07 [95%-CI: 0.00 to 0.15], p = 0.05) compared to non-frail participants. No between group differences were found in gray matter perfusion or in the presence of lacunar infarcts. In conclusion, increased white matter hyperintensity volume and a more complex white matter hyperintensity shape may be structural brain correlates of the frailty phenotype

Genome-wide association analysis of genetic generalized epilepsies implicates susceptibility loci at 1q43, 2p16.1, 2q22.3 and 17q21.32

Genetic generalized epilepsies (GGEs) have a lifetime prevalence of 0.3% and account for 20-30% of all epilepsies. Despite their high heritability of 80%, the genetic factors predisposing to GGEs remain elusive. To identify susceptibility variants shared across common GGE syndromes, we carried out a two-stage genome-wide association study (GWAS) including 3020 patients with GGEs and 3954 controls of European ancestry. To dissect out syndrome-related variants, we also explored two distinct GGE subgroups comprising 1434 patients with genetic absence epilepsies (GAEs) and 1134 patients with juvenile myoclonic epilepsy (JME). Joint Stage-1 and 2 analyses revealed genome-wide significant associations for GGEs at 2p16.1 (rs13026414, Pmeta = 2.5 × 10−9, OR[T] = 0.81) and 17q21.32 (rs72823592, Pmeta = 9.3 × 10−9, OR[A] = 0.77). The search for syndrome-related susceptibility alleles identified significant associations for GAEs at 2q22.3 (rs10496964, Pmeta = 9.1 × 10−9, OR[T] = 0.68) and at 1q43 for JME (rs12059546, Pmeta = 4.1 × 10−8, OR[G] = 1.42). Suggestive evidence for an association with GGEs was found in the region 2q24.3 (rs11890028, Pmeta = 4.0 × 10−6) nearby the SCN1A gene, which is currently the gene with the largest number of known epilepsy-related mutations. The associated regions harbor high-ranking candidate genes: CHRM3 at 1q43, VRK2 at 2p16.1, ZEB2 at 2q22.3, SCN1A at 2q24.3 and PNPO at 17q21.32. Further replication efforts are necessary to elucidate whether these positional candidate genes contribute to the heritability of the common GGE syndrome

Identification of a Putative Network of Actin-Associated Cytoskeletal Proteins in Glomerular Podocytes Defined by Co-Purified mRNAs

The glomerular podocyte is a highly specialized and polarized kidney cell type that contains major processes and foot processes that extend from the cell body. Foot processes from adjacent podocytes form interdigitations with those of adjacent cells, thereby creating an essential intercellular junctional domain of the renal filtration barrier known as the slit diaphragm. Interesting parallels have been drawn between the slit diaphragm and other sites of cell-cell contact by polarized cells. Notably mutations in several genes encoding proteins localized to the foot processes can lead to proteinuria and kidney failure. Mutations in the Wilm's tumor gene (WT1) can also lead to kidney disease and one isoform of WT1, WT1(+KTS), has been proposed to regulate gene expression post-transcriptionally. We originally sought to identify mRNAs associated with WT1(+KTS) through an RNA immunoprecipitation and microarray approach, hypothesizing that the proteins encoded by these mRNAs might be important for podocyte morphology and function. We identified a subset of mRNAs that were remarkably enriched for transcripts encoding actin-binding proteins and other cytoskeletal proteins including several that are localized at or near the slit diaphragm. Interestingly, these mRNAs included those of α-actinin-4 and non-muscle myosin IIA that are mutated in genetic forms of kidney disease. However, isolation of the mRNAs occurred independently of the expression of WT1, suggesting that the identified mRNAs were serendipitously co-purified on the basis of co-association in a common subcellular fraction. Mass spectroscopy revealed that other components of the actin cytoskeleton co-purified with these mRNAs, namely actin, tubulin, and elongation factor 1α. We propose that these mRNAs encode a number of proteins that comprise a highly specialized protein interactome underlying the slit diaphragm. Collectively, these gene products and their interactions may prove to be important for the structural integrity of the actin cytoskeleton in podocytes as well as other polarized cell types

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Clouds and convective self-aggregation in a multi-model ensemble of radiative-convective equilibrium simulations

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique amongst intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than un-aggregated simulations