Carbon monoxide-ethanol desulfurization of Illinois high sulfur coal demonstration : final project report for the period September 1, 1987 through November 30, 1990

Illinois Department of Energy and Natural ResourcesOpe

Do Gender Differences in Perceived Prototypical Computer Scientists and Engineers Contribute to Gender Gaps in Computer Science and Engineering?

Women are vastly underrepresented in the fields of computer science and engineering (CS&E). We examined whether women might view the intellectual characteristics of prototypical individuals in CS&E in more stereotype-consistent ways than men might and, consequently, show less interest in CS&E. We asked 269 U.S. college students (187, 69.5% women) to describe the prototypical computer scientist (Study 1) or engineer (Study 2) through open-ended descriptions as well as through a set of trait ratings. Participants also rated themselves on the same set of traits and rated their similarity to the prototype. Finally, participants in both studies were asked to describe their likelihood of pursuing future college courses and careers in computer science (Study 1) or engineering (Study 2). Across both studies, we found that women offered more stereotype-consistent ratings than did men of the intellectual characteristics of prototypes in CS (Study 1) and engineering (Study 2). Women also perceived themselves as less similar to the prototype than men did. Further, the observed gender differences in prototype perceptions mediated the tendency for women to report lower interest in CS&E fields relative to men. Our work highlights the importance of prototype perceptions for understanding the gender gap in CS&E and suggests avenues for interventions that may increase women’s representation in these vital fields

Influence of production variables and starting material on charcoal stable isotopic and molecular characteristics

We present a systematic study on the effect of starting species, gas composition, temperature, particle size and duration of heating upon the molecular and stable isotope composition of high density (mangrove) and low density (pine) wood. In both pine and mangrove, charcoal was depleted in o13C relative to the starting wood by up to 1.6% and 0.8%, respectively. This is attributed predominantly to the progressive loss of isotopically heavier polysaccharides, and kinetic effects of aromatization during heating. However, the pattern of o13C change was dependant upon both starting species and atmosphere, with different structural changes associated with charcoal production from each wood type elucidated by Solid-State o13C Nuclear Magnetic Resonance Spectroscopy. These are particularly evident at lower temperatures, where variation in the oxygen content of the production atmosphere results in differences in the thermal degradation of cellulose and lignin. It is concluded that production of charcoal from separate species in identical conditions, or from a single sample exposed to different production variables, can result in significantly different o13C of the resulting material, relative to the initial wood. These results have implications for the use of charcoal isotope composition to infer past environmental change

Learning by doing: do economics students self-evaluation skills improve?

This paper attempts to (1) measure the students' ability to accurately self-evaluate the quality of their own work, (2) see if this level of accuracy changes when students evaluate a second year essay, having evaluated a similar piece of work in the first year, (3) Investigate whether there is any significant variation in any of the observed changes and (4) identify any factors that might explain any of the observed variation. The data is generated from one cohort of students who were studying for an economics degree at a UK university. The self-evaluation exercise was introduced on two out-of-class essay assessments – one in the first year and one in the second year. Statistical analysis revealed that, on average, the students were significantly more accurate at self-evaluating the quality of their work in the second year than they had been in the first year. However there was considerable variation in this improvement. Those students who demonstrated the greatest improvement were firstly those who were awarded higher marks by the tutor for their second year essay and secondly, those who had been the least accurate at judging the quality of their first year essay. Other student characteristics such as different measures of student ability and gender had no significant impact on the changes in accuracy. However, there is no clear picture about what exactly is driving the improvement

Characterizing L2L_2Boosting

We consider $L_2$Boosting, a special case of Friedman's generic boosting algorithm applied to linear regression under $L_2$-loss. We study $L_2$Boosting for an arbitrary regularization parameter and derive an exact closed form expression for the number of steps taken along a fixed coordinate direction. This relationship is used to describe $L_2$Boosting's solution path, to describe new tools for studying its path, and to characterize some of the algorithm's unique properties, including active set cycling, a property where the algorithm spends lengthy periods of time cycling between the same coordinates when the regularization parameter is arbitrarily small. Our fixed descent analysis also reveals a repressible condition that limits the effectiveness of $L_2$Boosting in correlated problems by preventing desirable variables from entering the solution path. As a simple remedy, a data augmentation method similar to that used for the elastic net is used to introduce $L_2$-penalization and is shown, in combination with decorrelation, to reverse the repressible condition and circumvents $L_2$Boosting's deficiencies in correlated problems. In itself, this presents a new explanation for why the elastic net is successful in correlated problems and why methods like LAR and lasso can perform poorly in such settings.Comment: Published in at http://dx.doi.org/10.1214/12-AOS997 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Knowledge Graphs in Manufacturing and Production: A Systematic Literature Review

Knowledge graphs in manufacturing and production aim to make production lines more efficient and flexible with higher quality output. This makes knowledge graphs attractive for companies to reach Industry 4.0 goals. However, existing research in the field is quite preliminary, and more research effort on analyzing how knowledge graphs can be applied in the field of manufacturing and production is needed. Therefore, we have conducted a systematic literature review as an attempt to characterize the state-of-the-art in this field, i.e., by identifying exiting research and by identifying gaps and opportunities for further research. To do that, we have focused on finding the primary studies in the existing literature, which were classified and analyzed according to four criteria: bibliometric key facts, research type facets, knowledge graph characteristics, and application scenarios. Besides, an evaluation of the primary studies has also been carried out to gain deeper insights in terms of methodology, empirical evidence, and relevance. As a result, we can offer a complete picture of the domain, which includes such interesting aspects as the fact that knowledge fusion is currently the main use case for knowledge graphs, that empirical research and industrial application are still missing to a large extent, that graph embeddings are not fully exploited, and that technical literature is fast-growing but seems to be still far from its peak

Gasifier feed: Tailor-made from Illinois coals

The purpose of this research is to develop a coal slurry from waste streams using Illinois coal that is ideally suited for a gasification feed. The principle items to be studied are (1) methods of concentrating pyrite and decreasing other ash forming minerals into a high grade gasification feed using froth flotation and gravity separation techniques; (2) chemical and particle size analyses of coal slurries; (3) determination of how that slurry can be densified and to what degree of densification is optimum from the pumpability and combustibility analyses; and (4) reactivity studies