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This paper presents the design and manufacturing of two novel small floating Darrieus vertical axis wind turbines (VAWT) developed for a wind-wave basin test campaign. As with typical designs, the rotor design needed to satisfy the traditional structural safety requirements (such as strain, deflection, resonant-free dynamics) from design standards along with other manufacturing and assembly constraints. In addition, for this particular design, some special conditions are present as the facility (the wind-wave basin itself) and use of existing Floating Offshore-wind and Controls Advanced Laboratory (FOCAL) semi-submersible floating platform (originally designed for HAWT test) imposed an additional set of design requirements including wind speed and size constraints, and specific, target overturning moments and rotor mass. Addressing all these constraints (facility, existing hull, structural safety, and manufacturing) presented a challenging design task in this case, thus the focus of this paper is presenting the design approach and results leading to final designs satisfying all these competing requirements. Using the presented design process, two Darrieus troposkein-shaped vertical axis wind turbines (two-bladed and three-bladed versions) were designed and manufactured, after ensuring compliance with all the design requirements. The presented study can aid researchers interested in developing similar floating turbine test campaigns.

Is the continued escalation of environmental problems indicative of an incompleteness in rationality or a failure of rationality? In their efforts to protect nature, environmentalists ostensibly abide by the findings of ecological science; yet environmental policy largely takes for granted the potential perfectibility of economic tools as rational representations of nature. Are these epistemologies commensurable? Which tools would constitute an appropriate language to articulate and ameliorate environmental problems? This dissertation is an ethnography of knowledge production at the intersection of ecology and economics. My field site is both a social group—the heterodox community of ecological economists—and an epistemic process—that group’s attempts to illuminate, articulate, and implement a distinction between the application of economic instruments to nature (orthodoxy) and their own efforts to incorporate ecological principles into economics (heterodoxy). I draw on ten years of participant-observation of environmental public policy, including in-depth interviews with foundational, emerging, and transient participants in heterodox efforts, and analysis of the epistemic content they produce. I theorize the process by which the social and epistemic practices of a social science—economics—might be rearticulated to comply with the epistemology of a natural science—ecology. This investigation of an interdisciplinary interface takes an interdisciplinary approach to analysis. I draw on the tools of sociological ethnography, science and technology studies (STS), and the science of ecology to examine the context in which economic tools are commensurated with ecological entities. I find that the epistemic project of ecological economics is seeking to operationalize a transition to heterodox environmental policy by valuing the epistemology of ecological knowledge at an equal level to the content of ecological knowledge. I theorize the possibility of an analytical inversion: a norm of calculation that grants primacy to the embeddedness of societies and economies in a biophysical context, and foregrounds the purpose and effects of calculation over efficiency in or parsimony of calculation. I explore whether a heterodox epistemic mission may require pluralist tension, even as its professed goal is the coherence of a concerted alternative. I draw the outlines of a theory of social and epistemic dynamics at an “unboundary,” a space of shared discourse containing demonstrably incompatible epistemic commitments in the service of pragmatic ends. This dissertation furthers our understanding of interdisciplinary knowledge creation, and of the practical challenges of developing a policy framework that respects ecological ontology.

Population data represent an essential component in studies focusing on human–nature interrelationships, disaster risk assessment and environmental health. Several recent efforts have produced global- and continental-extent gridded population data which are becoming increasingly popular among various research communities. However, these data products, which are of very different characteristics and based on different modeling assumptions, have never been systematically reviewed and compared, which may impede their appropriate use. This article fills this gap and presents, compares and discusses a set of large-scale (global and continental) gridded datasets representing population counts or densities. It focuses on data properties, methodological approaches and relative quality aspects that are important to fully understand the characteristics of the data with regard to the intended uses. Written by the data producers and members of the user community, through the lens of the “fitness for use” concept, the aim of this paper is to provide potential data users with the knowledge base needed to make informed decisions about the appropriateness of the data products available in relation to the target application and for critical analysis.

Differentiating between bipolar disorder and major depressive disorder can be challenging for clinicians. The diagnostic process might benefit from new ways of monitoring the phenotypes of these disorders. Smartphone data might offer insight in this regard. Today, smartphones collect dense, multimodal data from which behavioral metrics can be derived. Distinct patterns in these metrics have the potential to differentiate the two conditions. To examine the feasibility of smartphone-based phenotyping, two study sites (Mayo Clinic, Johns Hopkins University) recruited patients with bipolar I disorder (BPI), bipolar II disorder (BPII), major depressive disorder (MDD), and undiagnosed controls for a 12-week observational study. On their smartphones, study participants used a digital phenotyping app (mindLAMP) for data collection. While in use, mindLAMP gathered real-time geolocation, accelerometer, and screen-state (on/off) data. mindLAMP was also used for EMA delivery. MindLAMP data was then used as input variables in binary classification, three-group k-nearest neighbors (KNN) classification, and k-means clustering. The best-performing binary classification model was able to classify patients as control or non-control with an AUC of 0.91 (random forest). The model that performed best at classifying patients as having MDD or bipolar I/II had an AUC of 0.62 (logistic regression). The k-means clustering model had a silhouette score of 0.46 and an ARI of 0.27. Results support the potential for digital phenotyping methods to cluster depression, bipolar disorder, and healthy controls. However, due to inconsistencies in accuracy, more data streams are required before these methods can be applied to clinical practice.

In the burgeoning area of clinical digital phenotyping research, there is a dearth of literature that details methodology, including the key challenges and dilemmas in developing and implementing a successful architecture for technological infrastructure, patient engagement, longitudinal study participation, and successful reporting and analysis of diverse passive and active digital data streams. This article provides a narrative rationale for our study design in the context of the current evidence base and best practices, with an emphasis on our initial lessons learned from the implementation challenges and successes of this digital phenotyping study. We describe the design and implementation approach for a digital phenotyping pilot feasibility study with attention to synthesizing key literature and the reasoning for pragmatic adaptations in implementing a multisite study encompassing distinct geographic and population settings. This methodology was used to recruit patients as study participants with a clinician-validated diagnostic history of unipolar depression, bipolar I disorder, or bipolar II disorder, or healthy controls in 2 geographically distinct health care systems for a longitudinal digital phenotyping study of mood disorders. We describe the feasibility of a multisite digital phenotyping pilot study for patients with mood disorders in terms of passively and actively collected phenotyping data quality and enrollment of patients. Overall data quality (assessed as the amount of sensor data obtained vs expected) was high compared to that in related studies. Results were reported on the relevant demographic features of study participants, revealing recruitment properties of age (mean subgroup age ranged from 31 years in the healthy control subgroup to 38 years in the bipolar I disorder subgroup), sex (predominance of female participants, with 7/11, 64% females in the bipolar II disorder subgroup), and smartphone operating system (iOS vs Android; iOS ranged from 7/11, 64% in the bipolar II disorder subgroup to 29/32, 91% in the healthy control subgroup). We also described implementation considerations around digital phenotyping research for mood disorders and other psychiatric conditions. Digital phenotyping in affective disorders is feasible on both Android and iOS smartphones, and the resulting data quality using an open-source platform is higher than that in comparable studies. While the digital phenotyping data quality was independent of gender and race, the reported demographic features of study participants revealed important information on possible selection biases that may result from naturalistic research in this domain. We believe that the methodology described will be readily reproducible and generalizable to other study settings and patient populations given our data on deployment at 2 unique sites.

This study provides a parallel characterization of the cytokine and chemokine response to stroke in the human and mouse brain at different stages of infarct resolution. The study goal was to address the hypothesis that chronic inflammation may contribute to stroke-related dementia. We used C57BL/6 and BALB/c mice to control for strain related differences in the mouse immune response. Our data indicate that in both mouse strains, and humans, there is increased granulocyte macrophage colony-stimulating factor (GM-CSF), interleukin-6 (IL-6), interleukin-12 p70 (IL-12p70), interferon gamma-induced protein-10 (IP-10), keratinocyte chemoattractant/interleukin-8 (KC/IL-8), monocyte chemoattractant protein-1 (MCP-1), macrophage inflammatory protein-1α (MIP-1α), macrophage inflammatory protein-1β (MIP-1β), regulated on activation, normal T cell expressed and secreted (RANTES), and Tumor necrosis factor-α (TNF-α) in the infarct core during the acute time period. Nevertheless, correlation and two-way ANOVA analyses reveal that despite this substantial overlap between species, there are still significant differences, particularly in the regulation of granulocyte colony-stimulating factor (G-CSF), which is increased in mice but not in humans. In the weeks after stroke, during the stage of liquefactive necrosis, there is significant resolution of the inflammatory response to stroke within the infarct. However, CD68+ macrophages remain present, and levels of IL-6 and MCP-1 remain chronically elevated in infarcts from both mice and humans. Furthermore, there is a chronic T cell response within the infarct in both species. This response is differentially polarized towards a T helper 1 (Th1) response in C57BL/6 mice, and a T helper 2 (Th2) response in BALB/c mice, suggesting that the chronic inflammatory response to stroke may follow a different trajectory in different patients. To control for the fact that the average age of the patients used in this study was 80 years, they were of both sexes, and many had suffered from multiple strokes, we also present findings that reveal how the chronic inflammatory response to stroke is impacted by age, sex, and multiple strokes in mice. Our data indicate that the chronic cytokine and chemokine response to stroke is not substantially altered in 18-month old compared to 3-month old C57BL/6 mice, although T cell infiltration is attenuated. We found a significant correlation in the chronic cytokine response to stroke in males and females. However, the chronic cytokine response to stroke was mildly exacerbated by a recurrent stroke in both C57BL/6 and BALB/c mice.