The Role of Nature in Japanese American Internment Narratives: Julie Otsuka’s When the Emperor Was Divine.

The relocation and internment of US residents of Japanese heritage during World War II has been well documented, both historically and in literature. The critical examination of internment narratives has, however, largely failed to consider the highly consequential role of the natural environment in the internment experience and subsequent internment literature. In this paper, I examine Julie Otsuka’s When the Emperor was Divine, in conjunction with historical sources, through an ecocritical and environmental justice lens. In doing so, I reveal that the natural environment played a dual, and often contradictory, role in the internment experience. On the one hand, nature was as a source of hardship for interned people, as the harsh, alien environments of the camps were a source of physical and emotional pain, and thus acted as one of many tools of oppression. On the other hand, nature offered spaces of defiance and sanctuary, and thus provided a means to actualize and process the traumatic experience of internment. Through this analysis, I not only highlight the importance of the natural world in Otsuka’s text, but also stress the importance of further ecocritical examinations of internment narratives

Field effects during consolidation of metallic powders

High electric current has been shown to enhance sintering kinetics during consolidation of many ceramic and metallic based powder materials using the process known as Electric Field Assisted Sintering (EFAS) or Spark Plasma Sintering (SPS). More recently, processes employing higher voltages and electric field strengths than these “current assisted” techniques have been shown to dramatically increase the sintering kinetics in ceramic materials in what has become known as “flash sintering”. While much work has been conducted in the area of ceramics little attention has been paid to higher field processing of metallic powders, and in general, the fundamental mechanisms governing enhanced kinetics during field assisted sintering of metallic powders are poorly understood. Furthermore, EFAS processes are typically complex and employ many variables which may include pressure, temperature, current, and electric field, the effects of which can be difficult to decouple. In this work aluminum 5083 (AA5083) alloy powders are processed using pressure-less sintering while applying DC electric fields ranging from 0-300 V/cm to examine the effect on the sintering kinetics of AA5083 powder. In-situ sintering kinetics were quantified using digital image correlation (DIC) and it was found that the application of a DC field results in a discontinuous change in volume at a critical temperature similar to the flash effect observed in ceramics. Microstructural characterization was used to confirm the flash corresponds to formation of necks due to sintering in the material. The temperature at which this phenomena occurs was found to decrease with increasing field strength. Joule heating during the flash was quantified using full field IR camera measurements and found to not generate enough heat to account for the enhanced sintering kinetics observed. Micromechanical modeling is used to quantify localized Joule heating at particle-particle contacts to further explore the possibility of enhanced kinetics due to localized thermal runaway, and to predict evolution of electrical conductivity with density of the compact

Beyond Dystopia: The effect of reading hopeful climate fiction on climate anxiety and environmental self-efficacy

Climate communication and climate storytelling have thus far been unrelentingly bleak. However, growing evidence suggests that the barrage of negative, technical communication may result in negative mental health impacts and doesn’t necessarily translate into climate action. Rather than continuing to focus on technical and fear-based communication, there are calls to shifts towards narrative communication and hopeful communication frames. In this study, I investigate what effect hopeful climate fiction has on readers through three related avenues of inquiry using the popular solarpunk novella A Psalm for the Wild Built as an experimental text. I examined (1) what effect, if any, the text had on readers’ climate anxiety, (2) what effect, if any, the text had on readers’ environmental self-efficacy, and (3) what elements of the text were salient to participants and how they made meaning from the text. To answer these questions, I employed a mixed-methods approach combining a longitudinal survey with semi-structured interviews. There seems to be a notable positive effect on reader’s environmental efficacy, particularly regarding community efficacy, although cynicism about individual action remained. The text had a more complex impact on reader’s mental health, but appears to have assisted in positively reframing readers’ climate action, their role in their community, and their commitment to self-care. This reframing effect was most strong for those with mild to moderate reported climate anxiety. These results reaffirm recent studies about community action and framing in other areas of climate research and points the way to many avenues of further inquir

Bird Collision Mitigation Report Fall 2020

Bird Strike Mitigation Project Report for Sustainability Exchange, Washington University in St. Louis, Fall 202

Probabilistic Feasibility Design of a Laser Powder Bed Fusion Process Using Integrated First-Order Reliability and Monte Carlo Methods

Quality inconsistency due to uncertainty hinders the extensive applications of a laser powder bed fusion (L-PBF) additive manufacturing process. To address this issue, this study proposes a new and efficient probabilistic method for the reliability analysis and design of the L-PBF process. The method determines a feasible region of the design space for given design requirements at specified reliability levels. If a design point falls into the feasible region, the design requirement will be satisfied with a probability higher or equal to the specified reliability. Since the problem involves the inverse reliability analysis that requires calling the direct reliability analysis repeatedly, directly using Monte Carlo simulation (MCS) is computationally intractable, especially for a high reliability requirement. In this work, a new algorithm is developed to combine MCS and the first-order reliability method (FORM). The algorithm finds the initial feasible region quickly by FORM and then updates it with higher accuracy by MCS. The method is applied to several case studies, where the normalized enthalpy criterion is used as a design requirement. The feasible regions of the normalized enthalpy criterion are obtained as contours with respect to the laser power and laser scan speed at different reliability levels, accounting for uncertainty in seven processing and material parameters. The results show that the proposed method dramatically alleviates the computational cost while maintaining high accuracy. This work provides a guidance for the process design with required reliability

Machine Learning in Additive Manufacturing: A Review

In this review article, the latest applications of machine learning (ML) in the additive manufacturing (AM) field are reviewed. These applications, such as parameter optimization and anomaly detection, are classified into different types of ML tasks, including regression, classification, and clustering. The performance of various ML algorithms in these types of AM tasks are compared and evaluated. Finally, several future research directions are suggested

Estimating dominant runoff modes across the conterminous United States

Effective natural resource planning depends on understanding the prevalence of runoff generating processes. Within a specific area of interest, this demands reproducible, straightforward information that can complement available local data and can orient and guide stakeholders with diverse training and backgrounds. To address this demand within the contiguous United States (CONUS), we characterized and mapped the predominance of two primary runoff generating processes: infiltration‐excess and saturation‐excess runoff (IE vs. SE, respectively). Specifically, we constructed a gap‐filled grid of surficial saturated hydraulic conductivity using the Soil Survey Geographic and State Soil Geographic soils databases. We then compared surficial saturated hydraulic conductivity values with 1‐hr rainfall‐frequency estimates across a range of return intervals derived from CONUS‐scale random forest models. This assessment of the prevalence of IE versus SE runoff also incorporated a simple uncertainty analysis, as well as a case study of how the approach could be used to evaluate future alterations in runoff processes resulting from climate change. We found a low likelihood of IE runoff on undisturbed soils over much of CONUS for 1‐hr storms with return intervals \u3c5 years. Conversely, IE runoff is most likely in the Central United States (i.e., Texas, Louisiana, Kansas, Missouri, Iowa, Nebraska, and Western South Dakota), and the relative predominance of runoff types is highly sensitive to the accuracy of the estimated soil properties. Leveraging publicly available data sets and reproducible workflows, our approach offers greater understanding of predominant runoff generating processes over a continental extent and expands the technical resources available to environmental planners, regulators, and modellers

Direct activation of KCC2 arrests benzodiazepine refractory status epilepticus and limits the subsequent neuronal injury in mice

Hyperpolarizing GABAAR currents, the unitary events that underlie synaptic inhibition, are dependent upon efficient Cl− extrusion, a process that is facilitated by the neuronal specific K+/Cl− co-transporter KCC2. Its activity is also a determinant of the anticonvulsant efficacy of the canonical GABAAR-positive allosteric: benzodiazepines (BDZs). Compromised KCC2 activity is implicated in the pathophysiology of status epilepticus (SE), a medical emergency that rapidly becomes refractory to BDZ (BDZ-RSE). Here, we have identified small molecules that directly bind to and activate KCC2, which leads to reduced neuronal Cl− accumulation and excitability. KCC2 activation does not induce any overt effects on behavior but prevents the development of and terminates ongoing BDZ-RSE. In addition, KCC2 activation reduces neuronal cell death following BDZ-RSE. Collectively, these findings demonstrate that KCC2 activation is a promising strategy to terminate BDZ-resistant seizures and limit the associated neuronal injury

Comparing ocean surface boundary vertical mixing schemes including langmuir turbulence

Six recent Langmuir turbulence parameterization schemes and five traditional schemes are implemented in a common single‐column modeling framework and consistently compared. These schemes are tested in scenarios versus matched large eddy simulations, across the globe with realistic forcing (JRA55‐do, WAVEWATCH‐III simulated waves) and initial conditions (Argo), and under realistic conditions as observed at ocean moorings. Traditional non‐Langmuir schemes systematically underpredict large eddy simulation vertical mixing under weak convective forcing, while Langmuir schemes vary in accuracy. Under global, realistic forcing Langmuir schemes produce 6% (−1% to 14% for 90% confidence) or 5.2 m (−0.2 m to 17.4 m for 90% confidence) deeper monthly mean mixed layer depths than their non‐Langmuir counterparts, with the greatest differences in extratropical regions, especially the Southern Ocean in austral summer. Discrepancies among Langmuir schemes are large (15% in mixed layer depth standard deviation over the mean): largest under wave‐driven turbulence with stabilizing buoyancy forcing, next largest under strongly wave‐driven conditions with weak buoyancy forcing, and agreeing during strong convective forcing. Non‐Langmuir schemes disagree with each other to a lesser extent, with a similar ordering. Langmuir discrepancies obscure a cross‐scheme estimate of the Langmuir effect magnitude under realistic forcing, highlighting limited understanding and numerical deficiencies. Maps of the regions and seasons where the greatest discrepancies occur are provided to guide further studies and observations