Pilot-scale continuous-flow hydrothermal liquefaction of filamentous fungi cultivated in thin stillage

With an ever increasing demand for energy and a better awareness of its environmental consequences, renewable fuels have become a desirable solution. The growing industry of second generation biofuels, such as renewable diesel, can further supplement energy needs and decrease reliance on fossil fuels. Lipid-rich biomass is a prime candidate for new drop-in biofuel feedstocks. While it has received only minor attention from researchers, fungi has the potential to become an effective source of biofuel. Due to its high moisture content, fungi is well suited for the process of hydrothermal liquefaction. This thermochemical process uses water under near-supercritical conditions to convert biomass into biocrude oil. The use of water eliminates the need for energy-intensive drying processes needed in pyrolysis or gasification. A 1.5-L pilot-scale continuous-flow hydrothermal liquefaction process was optimized for the conversion of filamentous fungi Rhizopus oligosporus to biocrude. To increase efficiency of a pilot-scale fungi-to-fuel process, improvements to fungal cultivation methods were studied. Large variation in growth yields have been noted for fungi cultivated in thin stillage, and were presumed to be the result of bacterial contamination. However, it was unknown if variations in growth were due to the quality of the thin stillage, contamination during collection, or contamination during lab procedures. Therefore, a lab-scale study was conducted to determine the source of diminished fungal growth yields, and possible methods to overcome these challenges were studied. Specifically, hydrogen peroxide was employed as a disinfectant for thin stillage, and its effect on fungal yields were observed. Results from lab-scale tests helped inform methods used during pilot-scale cultivation of fungi in a 1600-L bioreactor

Rural Transformation, Inequality, and the Origins of Microfinance

What determines the development of rural financial markets? Starting from a simple theoretical framework, we derive the factors shaping the market entry of rural microfinance institutions across time and space. We provide empirical evidence for these determinants using the expansion of credit cooperatives in the 236 eastern counties of Prussia between 1852 and 1913. This setting is attractive as it provides a free market benchmark scenario without public ownership, subsidization, or direct regulatory intervention. Furthermore, we exploit features of our historical set-up to identify causal effects. The results show that declining agricultural staple prices, as a feature of structural transformation, leads to the emergence of credit cooperatives. Similarly, declining bank lending rates contribute to their rise. Low asset sizes and land inequality inhibit the regional spread of cooperatives, while ethnic heterogeneity has ambiguous effects. We also offer empirical evidence suggesting that credit cooperatives accelerated rural transformation by diversifying farm outputs

The Fiscal State in Africa: Evidence from a Century of Growth

What is the level of state capacity in developing countries today, and what have been its drivers over the past century? We construct a comprehensive new dataset of tax and revenue collection for 46 African polities from 1900 to 2015. Descriptive analysis shows that many polities in Africa have been characterized by strong growth in fiscal capacity. As a next step, we explain this growth using a fixed-effects long-run panel setting. The results show that canonical state-building factors such as democratic institutions and interstate warfare can increase revenue collection, while government turnover reduces it. Access to external credit and foreign aid are even more important, and both negatively affect fiscal capacity. In addition, access to external revenues, especially from commodity exports and debt, moderates the operation of canonical state-building factors such as democracy and conflict. These insights add important nuances to established theories of state building. Not only are states in Africa more capable than hitherto thought, but the international environment shapes their capacity, both directly and indirectly

The Night is Young and You\u27re so Beautiful

Illustration of cowgirl on bucking horsehttps://scholarsjunction.msstate.edu/cht-sheet-music/10474/thumbnail.jp

Capturing Multivariate Spatial Dependence: Model, Estimate and then Predict

Physical processes rarely occur in isolation, rather they influence and interact with one another. Thus, there is great benefit in modeling potential dependence between both spatial locations and different processes. It is the interaction between these two dependencies that is the focus of Genton and Kleiber's paper under discussion. We see the problem of ensuring that any multivariate spatial covariance matrix is nonnegative definite as important, but we also see it as a means to an end. That "end" is solving the scientific problem of predicting a multivariate field. [arXiv:1507.08017].Comment: Published at http://dx.doi.org/10.1214/15-STS517 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Have You Forgotten?

Illustration of clouds and roseshttps://scholarsjunction.msstate.edu/cht-sheet-music/12601/thumbnail.jp

Whistling In The Dark

Picture of Guy and Carmen Lombardo; Illustration of a city off in distance, man standing by water, and a walkway through the grasshttps://scholarsjunction.msstate.edu/cht-sheet-music/11000/thumbnail.jp

Wilson confidence intervals for the two-sample log-odds-ratio in stratified 2 x 2 contingency tables

Large-sample Wilson-type con fidence intervals (CIs) are derived for a parameter of interest in many clinical trials situations: the log-odds-ratio, in a two sample experiment comparing binomial success proportions, say between cases and controls. The methods cover several scenarios: (i) results embedded in a single 2 x 2 contingency table, (ii) a series of K 2 x 2 tables with common parameter, or (iii) K tables, where the parameter may change across tables under the influence of a covariate. The calculations of the Wilson CI require only simple numerical assistance, and for example are easily carried out using Excel. The main competitor, the exact CI, has two disadvantages: It requires burdensome search algorithms for the multi-table case and results in strong over-coverage associated with long confidence intervals. All the application cases are illustrated through a well-known example. A simulation study then investigates how the Wilson CI performs among several competing methods. The Wilson interval is shortest, except for very large odds ratios, while maintaining coverage similar to Wald-type intervals. An alternative to the Wald CI is the Agresti-Coull CI, calculated from Wilson and Wald CIs, which has same length as the Wald CI but improved coverage

Ambivalent surfaces: An encounter with Rococo paintings

This project sets out from an encounter with a series of rococo paintings by Francois Boucher's and my unexpected fascination with them that I try to understand. I presume it is the mimetic texture of a fabric and the shimmer of the paint itself that prompts me to the strange difference between them. In the sensual absorption, on the other hand, paint becomes its own presentation. This in turn raises questions about the painting surface. The surface carries judgement, that is intertwined with the judgement about the rococo. With formalism as the dominant art criticism of modernity, I discuss the concept of the painting surface as predicated on a split between material and image, connected to the distinctions of form and idea, presentation and representation. My key research question thus concerns the role of the surface. The surface is not understood as an isolated picture plane but rather as one of passages and relationships. The play between substance, subject and surface constitutes a network of meaning. The relevance to my practice is explored through the figures of the stain and the splotch, plastic surfaces, and movement on the surface. The research method is developed as an exchange between three main component strands of writing. The poetic serves as a generative, intuitive interface, the art historical and aesthetic a sober grounding for observation, attentions, and factual encounters, and the philosophical arena provides the structure for speculation and projection. There is in turn no privileging of one over the other but rather a series of passages and circulations that provide connections. This triangulation serves to articulate other structural conjunctions such as the relationship between affects, percepts, and concepts, and the structure of spacing within the project of the studio, gallery, and library, which all serve as a play of triangles within triangles. Boucher's paintings evoke ambivalent affects in me. I partially feel repulsion towards their representations and simultaneous attraction to the way they are painted and the effects of their materiality. An object of research that puts me in a place of uncertainty allows for an exploration that is open to experiment, experience, and surprise as is the process in the studio. Ambivalence, as the suspension of judgment, opens up a space for me to move within and inhabit different positions. I thus consider a politics of ambivalence and pose the question of its capability as a method or even as an aim. The key references this thesis is built around are Boucher's paintings as much as the recent discussion by Ewa Lajer-Burcharth that investigates Boucher's artistic individuation through the materiality of his work. This provided me with perspectives that in turn entered the act of looking to forge connections with my practice. Rococo spatiality evokes a floating movement. Another key reference is Timothy Morton's argument for an (im-)possible ecology sensibility within consumerism that connects ambivalence and floating in speculating about the potential of ambivalence to question our categorical dualist thinking of subject and object at the expense of the latter. What this project proposes is therefore a way of looking that opens out another way of encountering art history that is usually governed by the authority of iconography that in turn relies on representation as the dominant system of signification. With this, it is also an exploration of how looking differently can be a method to painting. The contribution of rococo to practice is a notion of the in-betweenness of the surface of painting that de-centres the subject and opens out to a subject/object encounter in the experience of ambivalence. The starting point of this research was a state of ambivalence the object of research put me or I put the object in. From this moment of suspended judgment, ambivalence finds its expression in the a-signifying movements of floating and drifting. This gives rise to the exploration of contradiction, the production of dialectics and the liberation of uncertainty

Analysis and Diagnostics of Categorical Variables with Multiple Outcomes

Surveys often contain qualitative variables for which respondents may select any number of the outcome categories. For instance, for the question "What type of contraceptive have you used?" with possible responses (oral, condom, lubricated condom, spermicide, and diaphragm), respondents would be instructed to select as many of the J = 5 outcomes as apply. This situation is known as multiple responses and outcomes are referred to as items. This thesis discusses several approaches to analysing such data. For stratified multiple response data, we consider three ways of defining the common odds ratio, a summarising measure for the conditional association between a row variable and the multiple response variable, given a stratification variable. For each stratum, we define the odds ratio in terms of: 1 item and 2 rows, 2 items and 2 rows, and 2 items and 1 row. Then we consider two estimation approaches for the common odds ratio and its (co)variance estimators for these types of odds ratios. The model-based approach treats the J items as a Jdimensional binary response and then uses logit models directly for the marginal distribution of each item by applying the generalised estimating equation (GEE) (Liang and Zeger 1986) method. The non-model-based approach uses Mantel-Haenszel (MH) type estimators. The model-based (or marginal model) approach is still applicable for more than two explanatory variables. Preisser and Qaqish (1996) proposed regression diagnostics for GEE. Another model fitting approach is the homogeneous linear predictor model (HLP) based on maximum likelihood (ML) introduced by Lang (2005). We investigate deletion diagnostics as the Cook distance and DBETA for multiple response data using HLPmodels (Lang 2005), which have not been considered yet, and propose a simple "delete=replace" method as an alternative approach for deletion. Methods are compared with the GEE approach. We also discuss the modelling of a repeated multiple response variable, a categorical variable for which subjects can select any number of categories on repeated occasions. Multiple responses have been considered in the literature by various authors; however, repeated multiple responses have not been considered yet. Approaches include the marginal model approach using the GEE and HLP methods, and generalised linear mixed models (GLMM). For the GEE method, we also consider possible correlation structures and propose a groupwise correlation estimation method yielding more efficient parameter estimates if the correlation structure is indeed different for different groups, which is confirmed by a simulation study. Ordered categorical variables occur in many applications and can be seen as a special case of multiple responses. The proportional odds model, which uses logits of cumulative probabilities, is currently the most popular model. We consider two approaches focusing on the mis-specification of a covariate. The binary approach considers the proportional oddsmodel as J-1 logistic regression models and applies the cumulative residual process introduced by Arbogast and Lin (2005) for logistic regression. The multivariate approach views the proportional odds model as a member of the class of multivariate generalised linear models (MGLM), where the response variable is a vector of indicator responses