On Decomposing the Complete Symmetric Digraph into Orientations of K4-e - Bunge, R.C.; Darrow, B.D.; Dubczuk, T.M.; El-Zanati, S.I.; Hao, H.H.; Keller, G.L.; Newkirk, G.A.; Roberts, D.P. (Discussiones Mathematicae - Graph Theory, 2019)
Let D be any of the 10 digraphs obtained by orienting the edges of K4 - e. We establish necessary and sufficient conditions for the existence of a (K∗ n,D)-design for 8 of these digraphs. Partial results as well as some nonexistence results are established for the remaining 2 digraphs. © 2019 Ryan C. Bunge et al., published by Sciendo 2019.
Keywords: dept.mat; digraph decompositions; orientations of K4-e; peer-reviewed

Comparison of Support Vector Machine and Gradient Boosting Regression Tree for Predicting Spatially Explicit Life Cycle Global Warming and Eutrophication Impacts: A case study in corn production - Romeiko, X.X.; Guo, Z.; Pang, Y. (Institute of Electrical and Electronics Engineers Inc., 2019)
Agriculture ranks one of the top contributors to global warming and nutrient pollution. Quantifying life cycle environmental impacts from agricultural production serves as scientific foundation for forming effective remediation strategies. However, the methods capable of accurately and efficiently calculating spatially explicit life cycle global warming and eutrophication impacts at a fine spatial scale over a geographic region are lacking. The objective of this study was to compare two regression models for estimating spatially explicit life cycle global warming and eutrophication, with corn production in the Midwest region as a demonstrating example. The results indicated that the gradient boosting regression tree model built with monthly weather features yielded higher predictive accuracy for life cycle global warming impact and life cycle EU. Moreover, predictive accuracy was improved at the cost of simulation time. The gradient boosting regression tree model required longer training time. Additionally, all machine learning models were million times faster than the traditional process-based model and were suitable for use in computationally-intensive applications like optimization and predication. © 2019 IEEE.
Keywords: Agricultural productions; Agriculture; Big data; Environmental impact; Eutrophication; Forestry; Global warming; Learning systems; Life Cycle Assessment (LCA); Life cycle; Life cycle assessment; Life-cycle environmental impact; Machine learning; Machine learning models; Process-based modeling; Remediation strategies; Scientific foundations; Spatial assessment; Support vector machines; Support vector regression; dept.mat

Colorings, cliques and relaxations of planarity - Pinciu, Val (Matemática Contemporânea, 2019)
A conjecture by Albertson states that if χ(G) ≥ n then cr(G) ≥ cr(Kn), where χ(G) is the chromatic number of G and cr(G) is the crossing number of G. This conjecture is true for positive integers n ≤ 16, but it is still open for n ≥ 17. In this paper we consider the statements corresponding to this conjecture where the crossing number of G is replaced with the skewness µ(G) (the minimum number of edges whose removal makes G planar), the genus γ(G) (the minimum genus of the orientable surface on which G is embeddable), and the thickness θ(G) (the minimum number of planar subgraphs of G whose union is G.) We show that the corresponding statements are true for all positive integers n when cr(G) is replaced with µ(G) or γ(G). We also show that the corresponding statement is true for inﬁnitely many values of n, but not for all n, when cr(G) is replaced with θ(G).
Keywords: dept.mat; peer-reviewed; ⛔ No DOI found

Genus, skewness, thickness and coloring theorems - Pinciu, Valeriu (Southeastern International Conference on Combinatorics, Graph Theory & Computing, 2019)
Keywords: dept.mat; ⛔ No DOI found

On the minimum skewness of certain classes of graphs - Pinciu, Valeriu (BGW 2019, 2019)
Keywords: dept.mat; ⛔ No DOI found

Conceptualizing discursive teaching capacity: A case study of a middle school mathematics teacher - Kim, Dong-Joong; Shin, Jaehong; Lee, Ji-Eun; Lim, Woong; Lee, Younhee; Choi, Sang-Ho (School Mathematics, 2019)
Keywords: dept.mat; peer-reviewed

Ten-year trends and differences in alcohol consumption among black and white female undergraduates - Barton, Barbara A; Bulmer, Sandra Minor; Mugno, Raymond; Misencik, Leann (Journal of Substance Use, 2019)
Background: Few studies have explored changing patterns of alcohol consumption among young females and differences based on race/ethnicity. Objective: This study examined differences in alcohol consumption between black and white undergraduate females and compared trends in three different measures of alcohol consumption over a 10-year period from 2004 to 2014. Methods: The CORE Alcohol and Drug Survey was used to collect data from female undergraduates attending a public university in the northeastern USA. Classes were randomly selected into the sample; class acceptance was 68% and student participation was 96%. The chi-square test examined differences between groups and the Cochrane Armitage Test for Trend assessed changes over time. Results: In 2014, for every measure of alcohol consumption examined, a significantly larger percentage of white females engaged in the behavior compared to black females. Trend analysis from 2004 to 2014 demonstrated a narrowing of this gap. Controlling for age, any alcohol use in past 30 days and binge drinking in the past 2 weeks increased significantly for black females 21 years or older. Any alcohol use in the past 30 days decreased significantly for white females under 21 years. Conclusion: These findings introduce many questions which should be explored through additional research.
Keywords: Alcohol; Article; Black person; Caucasian; United States; adult; alcohol; alcohol consumption; binge drinking; college females; dept.hhs; dept.mat; dept.pch; drinking trends; female; human; major clinical study; peer-reviewed; priority journal; race difference; undergraduate student

Finding the volume and surface area in the gut - Lim, Woong; Lee, Younhee; Lee, Ji-Eun (Australian Mathematics Educational Journal, 2019)
Keywords: dept.mat; ⛔ No DOI found