Exploring Uncertainties in Households’ Hurricane Evacuations

Hurricane Matthew was the most powerful hurricane during the Atlantic Hurricane Season in 2016. It caused tremendous damages to infrastructure and coastal areas of the United States. This thesis uses survey data collected in 2017 from residents in the Jacksonville Metropolitan Area after Hurricane Matthew. Survey questions were designed to capture evacuation-related decisions, information sources usage, socio-economic factors, perceived certainty and intra-familial interactions. The first part of the thesis modeled households’ perceived certainty to identify factors that affect different perceived certainty topics. Certainty topics included were: whether one lives in an evacuation zone, time of hurricane impact, evacuation preparation time needed, when to evacuate, evacuation travel mode, evacuation route, and evacuation destination. The modeling results showed similarities and disparities among perceived certainty topics. Household archetypes were created to offer insights for both decision makers and stakeholders for hurricane emergency management. The second part of this thesis explored the connection between the evacuation decision and perceived certainty using a two-stage modeling concept. Adding contextual factors usually leads to endogeneity bias which means parameters of variables will be overestimated or underestimated. A control function approach was used to account for potential endogeneity bias when linking perceived certainty with the evacuate/stay decision caused by unobserved attributes. The uncorrected base model was found to have a downward bias of the perceived certainty of evacuation destination, and with endogeneity bias corrected the parameter for this variable increased by 91.6%

Ectopic tissue engineered ligament with silk collagen scaffold for ACL regeneration: A preliminary study

Anterior cruciate ligament (ACL) reconstruction remains a formidable clinical challenge because of the lack of vascularization and adequate cell numbers in the joint cavity. In this study, we developed a novel strategy to mimic the early stage of repair in vivo, which recapitulated extra-articular inflammatory response to facilitate the early ingrowth of blood vessels and cells. A vascularized ectopic tissue engineered ligament (ETEL) with silk collagen scaffold was developed and then transferred to reconstruct the ACL in rabbits without interruption of perfusion. At 2 weeks after ACL reconstruction, more well-perfused cells and vessels were found in the regenerated ACL with ETEL, which decreased dramatically at the 4 and 12 week time points with collagen deposition and maturation. ACL treated with ETEL exhibited more mature ligament structure and enhanced ligament-bone healing post-reconstructive surgery at 4 and 12 weeks, as compared with the control group. In addition, the ETEL group was demonstrated to have higher modulus and stiffness than the control group significantly at 12 weeks post-reconstructive surgery. In conclusion, our results demonstrated that the ETEL can provide sufficient vascularity and cellularity during the early stages of healing, and subsequently promote ACL regeneration and ligament-bone healing, suggesting its clinic use as a promising therapeutic modality. Statement of Significance Early inflammatory cell infiltration, tissue and vessels ingrowth were significantly higher in the extra articular implanted scaffolds than theses in the joint cavity. By mimicking the early stages of wound repair, which provided extra-articular inflammatory stimulation to facilitate the early ingrowth of blood vessels and cells, a vascularized ectopic tissue engineered ligament (ETEL) with silk collagen scaffold was constructed by subcutaneous implantation for 2 weeks. The fully vascularized TE ligament was then transferred to rebuild ACL without blood perfusion interruption, and was demonstrated to exhibit improved ACL regeneration, bone tunnel healing and mechanical properties. (C) 2017 Published by Elsevier Ltd on behalf of Acta Materialia Inc

Metropolitan Innovation Systems: Inquiry into the co-evolving relations between Industry, University and Government

Innovation is crucial and decisive for the long-term development of a metropolitan region in the global economy. While firms certainly play a significant role in the development of specific innovation, the environment that nur-tures innovative firms and disseminates innovations in the economy involves a complex web of interactions among a range of actors, including firms, universities, and local governments. The performance of these actors, but also their interactions, have significant impacts on the overall innovation performance of the region. The great complexity of these interactions makes it challenging for many regions to strengthen the innovation per-formance of their areas. To address this challenge, the main innovation actors â ranging from firms and universi-ties to governments â have made great efforts to learn from the famous example of Silicon Valley. However, despite some self-promotion, almost all such efforts of these regions have failed. The root of this failure lies in the lack of holistic and historical view in the learning process and the lack of proper coordination among actors in the implementation process. The existing learning about the Silicon Valley model mostly focuses on the period since the 1970s when Silicon Valleyâs success has been widely acknowledged; and it provides static analysis by listing the key features of an already successful metropolitan innovation system. While such an approach cer-tainly helps with understanding, it could be misleading, since the actors often implement the lessons learned from the advanced stage that do not fit the current stage of the region. Hence, this thesis studies the 170 years of Silicon Valleyâs development to shed light on how the actors in the three institutional spheres interact and coordi-nate in the development process. Provided that the changed global environment and the different local cultures invite the additional issue of whether the learnings are applicable to the new contexts, three case studies have been conducted in this thesis â about Beijing, Shenzhen, and Hangzhou in China â over a time span of 70 years (from 1950 to 2020). These cases are then analyzed with the framework and theory grounded from the case of Silicon Valley. Synthesizing the analysis of the four selected cases, the development path of the Metropolitan Innovation System (MIS) in Beijing most closely resembles the Silicon Valley model, since both moved from a âlaissez-faireâ model to a balanced âTriple Helixâ model (where industry, university, and government have intensive interactions and play interwoven roles). The MIS in Shenzhen reveals a path that starts from the âstatistâ model, while the one in Hangzhou started with a semi-balanced Triple Helix model. The three paths converge in the sense of heading towards the balanced Triple Helix model and all three improve the interaction and coordination between the ac-tors in the three spheres in a process that ultimately creates an open and conducive environment. This includes the ability to attract high-quality talent and cognitive capital to the region. By providing thick-descriptions of the four cases and the tentative theory about the development of MIS, this the-sis contributes to the literature of innovation system, the Triple Helix model, and the New Institutional Economics, and contributes to practice by providing 20 recommendations for the actors in the three spheres

Distributionally Invariant Learning: Rationalization and Practical Algorithms

The invariance property across environments is at the heart of invariant learning methods for the Out-of-Distribution (OOD) Generalization problem. Although intuitively reasonable, strong assumptions on the availability and quality of environments have to be made for the learnability of the strict invariance property. Recently, to relax the requirements for environments empirically, some works propose to learn pseudo-environments for invariant learning. However, it could be misleading when pursuing strict invariance under latent heterogeneity, since the underlying invariance could have been violated during the pseudo-environment learning procedure. To this end, we come up with the distributional invariance property as a relaxed alternative to the strict invariance, which considers the invariance only among sub-populations down to a prescribed scale and allows a certain degree of variation. We reformulate the invariant learning problem under latent heterogeneity into a relaxed form that pursues the distributional invariance, based on which we propose our novel Distributionally Invariant Learning (DIL) framework as well as two implementations named DIL-MMD and DIL-KL. Theoretically, we provide the guarantees for the distributional invariance as well as bounds of the generalization error gap. Extensive experimental results validate the effectiveness of our proposed algorithms

Cumulative inflammatory burden is independently associated with increased arterial stiffness in patients with psoriatic arthritis: a prospective study

10.1186/s13075-015-0570-0Arthritis Research and Therapy1717

P(VDF-TrFE)/PMMA Blended Films with Enhanced Electrowetting Responses and Superior Energy Storage Performance

P(VDF-TrFE) (vinylidene fluoride-co-trifluoroethylene)/PMMA (PVT/PMMA) blended films synthesized through a facile solution-blending method show outstanding performance for practical electrowetting and energy storage applications. The van der Waals forces and dipolar interactions in neighboring P(VDF-TrFE) and PMMA chains, together with the suppressed free volume (or defect) are critical to the significantly-enhanced electrical properties. Typical, Teflon-covered P(VDF-TrFE)/PMMA blended film exhibits a high dielectric constant of 13 with low dielectric loss (~0.05) at 100 Hz and a large initial contact angle of 122°. Its electrowetting response with a contact angle modulation of 50° in air and low contact angle hysteresis demonstrate that it is promising for low-voltage electrowetting applications. Furthermore, with an energy density of 11.8 J/cm3, approximately double that of pure P(VDF-TrFE), PVT/PMMA blended films containing 20 wt % PMMA turn out to be superior materials for energy storage applications, due to their significantly-enhanced polarization and reduced remnant polarization