3D Mapping with an Unmanned Aerial Vehicle

Missionary aviation pilots often have to land their planes on remote airstrips that might be unsafe due to runway obstructions such as encroaching vegetation or large objects that were unknowingly placed on the runway. The Falcon Unmanned Aerial Vehicle (UAV) team is partnering with ITEC to develop an imaging system using a UAV to scan these airstrips to detect these obstructions. ITEC was founded by Steve Saint, the son of martyred missionary Nate Saint, to develop technologies to aid missionaries in their work. This video highlights the work of the Falcon UAV team and the basic terms and definitions for understanding the work of the team. The Falcon UAV team focuses primarily on the use of automated 3D mapping and photogrammetry by drones to help identify obstructions to pilots landing on remote airstrips. In this video, we will explore 3D mapping and compare different options for drones to purchase and software to use in the process of mapping information.https://mosaic.messiah.edu/engr2020/1007/thumbnail.jp

Empirical Studies of Evolving Systems

This paper describes the results of the working group investigating the issues of empirical studies for evolving systems. The groups found that there were many issues that were central to successful evolution and this concluded that this is a very important area within software engineering. Finally nine main areas were selected for consideration. For each of these areas the central issues were identified as well as success factors. In some cases success stories were also described and the critical factors accounting for the success analysed. In some cases it was later found that a number of areas were so tightly coupled that it was important to discuss them together

Take Care- Use Antibiotics Responsibly Swine Practitioner Project

The Take Care - Use Antibrotics Responsibly® program is an antimicrobial resistance and use educat1on and awareness program for pork producers. The program is based on principles and guidelines intended to minimize the development of antimicrobial resistance whrle maximizing animal health The program was developed by the National Pork Board, but veterinarians are key in the delivery of the program on farm. Since there are many factors that contribute to the amounts and types of antimicrobrals used on farm it was decided that the best way to measure program effectiveness was through measurement of changes in the attitude and behaviors of program particrpants

Open-Ended Evolutionary Robotics: an Information Theoretic Approach

This paper is concerned with designing self-driven fitness functions for Embedded Evolutionary Robotics. The proposed approach considers the entropy of the sensori-motor stream generated by the robot controller. This entropy is computed using unsupervised learning; its maximization, achieved by an on-board evolutionary algorithm, implements a "curiosity instinct", favouring controllers visiting many diverse sensori-motor states (sms). Further, the set of sms discovered by an individual can be transmitted to its offspring, making a cultural evolution mode possible. Cumulative entropy (computed from ancestors and current individual visits to the sms) defines another self-driven fitness; its optimization implements a "discovery instinct", as it favours controllers visiting new or rare sensori-motor states. Empirical results on the benchmark problems proposed by Lehman and Stanley (2008) comparatively demonstrate the merits of the approach

Mechanistic Studies on Selective Trimerization of Linear α-Olefins over a Supported Titanium Catalyst

The supported titanium catalyst s(FI)Ti, generated by adding (FI)TiCl3 to MAO-treated SiO2 (FI = (N-(5-methyl-3-(1-adamantyl)salicylidene)-2’-(2”-methoxyphenyl)anilinato)], effects the selective trimerization of the linear α-olefins (LAOs) propene, 1-pentene, 1-hexene, 1-decene, with >95% selectivity for trimers and ~85% selectivity to a single isomer thereof (2,3,5-trialkyl-1-hexene). Mechanistic interpretations are offered for the high regioselectivity as well as for some unusual kinetics behavior, including third-order dependence on LAO concentration and nearly identical initial rates at 0 and 25 °C

Population coding by globally coupled phase oscillators

A system of globally coupled phase oscillators subject to an external input is considered as a simple model of neural circuits coding external stimulus. The information coding efficiency of the system in its asynchronous state is quantified using Fisher information. The effect of coupling and noise on the information coding efficiency in the stationary state is analyzed. The relaxation process of the system after the presentation of an external input is also studied. It is found that the information coding efficiency exhibits a large transient increase before the system relaxes to the final stationary state.Comment: 7 pages, 9 figures, revised version, new figures added, to appear in JPSJ Vol 75, No.

Diet-microbiome-immune interplay in multiple sclerosis: Understanding the impact of phytoestrogen metabolizing gut bacteria

Multiple sclerosis (MS) is a chronic and progressive autoimmune disease of the central nervous system (CNS), with both genetic and environmental factors contributing to the pathobiology of the disease. Although HLA genes have emerged as the strongest genetic factor linked to MS, consensus on the environmental risk factors is lacking. Recently, the gut microbiota has garnered increasing attention as a potential environmental factor in MS, as mounting evidence suggests that individuals with MS exhibit microbial dysbiosis (changes in the gut microbiome). Thus, there has been a strong emphasis on understanding the role of the gut microbiome in the pathobiology of MS, specifically, factors regulating the gut microbiota and the mechanism(s) through which gut microbes may contribute to MS. Among all factors, diet has emerged to have the strongest influence on the composition and function of gut microbiota. As MS patients lack gut bacteria capable of metabolizing dietary phytoestrogen,we will specifically discuss the role of a phytoestrogen diet and phytoestrogen metabolizing gut bacteria in the pathobiology of MS. A better understanding of these mechanisms will help to harness the enormous potential of the gut microbiota as potential therapeutics to treat MS and other autoimmune diseases

On Hilberg's Law and Its Links with Guiraud's Law

Hilberg (1990) supposed that finite-order excess entropy of a random human text is proportional to the square root of the text length. Assuming that Hilberg's hypothesis is true, we derive Guiraud's law, which states that the number of word types in a text is greater than proportional to the square root of the text length. Our derivation is based on some mathematical conjecture in coding theory and on several experiments suggesting that words can be defined approximately as the nonterminals of the shortest context-free grammar for the text. Such operational definition of words can be applied even to texts deprived of spaces, which do not allow for Mandelbrot's ``intermittent silence'' explanation of Zipf's and Guiraud's laws. In contrast to Mandelbrot's, our model assumes some probabilistic long-memory effects in human narration and might be capable of explaining Menzerath's law.Comment: To appear in Journal of Quantitative Linguistic

Benchmarking Relatedness Inference Methods with Genome-Wide Data from Thousands of Relatives

Inferring relatedness from genomic data is an essential component of genetic association studies, population genetics, forensics, and genealogy. While numerous methods exist for inferring relatedness, thorough evaluation of these approaches in real data has been lacking. Here, we report an assessment of 12 state-of-the-art pairwise relatedness inference methods using a data set with 2485 individuals contained in several large pedigrees that span up to six generations. We find that all methods have high accuracy (92–99%) when detecting first- and second-degree relationships, but their accuracy dwindles to \u3c43% for seventh-degree relationships. However, most identical by descent (IBD) segment-based methods inferred seventh-degree relatives correct to within one relatedness degree for \u3e76% of relative pairs. Overall, the most accurate methods are Estimation of Recent Shared Ancestry (ERSA) and approaches that compute total IBD sharing using the output from GERMLINE and Refined IBD to infer relatedness. Combining information from the most accurate methods provides little accuracy improvement, indicating that novel approaches, such as new methods that leverage relatedness signals from multiple samples, are needed to achieve a sizeable jump in performance