The Design and Development of a Multi-Disciplinary Project in Embedded Systems Design

As has been noted over the past ten years, “The wall between computer science and electrical engineering has kept the potential of embedded systems at bay. It is time to build a new scientific foundation with embedded systems design as the cornerstone, which will ensure a systematic and even-handed integration of the two fields.”[1] In Baylor University’s School of Engineering & Computer Science, the Embedded Systems course in the Department of Computer Science, and the Embedded Systems Design course in the Department of Electrical and Computer Engineering have been offered independent of each other in the recent past. In the past year, however, this is beginning to change, with plans developing to combine the project portion of the two courses into one multi-disciplinary group project. This paper will document the two courses – scope and sequence, as well as emphasis, equipment used, and delivery style – highlighting the need for a new and innovative approach at the systematic integration of software and hardware in the design and development of a mutli-disciplinary group project. The beta test of this group project is occurring in the fall 2017 semester, with full first-time full-scale deployment during the spring 2018 semester. The results of this beta test will be discussed, and the lessons learned and planned modifications to the course will be considered.Cockrell School of Engineerin

Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research

Research in environmental health is becoming increasingly reliant upon data science and computational methods that can more efficiently extract information from complex datasets. Data science and computational methods can be leveraged to better identify relationships between exposures to stressors in the environment and human disease outcomes, representing critical information needed to protect and improve global public health. Still, there remains a critical gap surrounding the training of researchers on these in silico methods. We aimed to address this gap by developing the inTelligence And Machine lEarning (TAME) Toolkit, promoting trainee-driven data generation, management, and analysis methods to “TAME” data in environmental health studies. Training modules were developed to provide applications-driven examples of data organization and analysis methods that can be used to address environmental health questions. Target audiences for these modules include students, post-baccalaureate and post-doctorate trainees, and professionals that are interested in expanding their skillset to include recent advances in data analysis methods relevant to environmental health, toxicology, exposure science, epidemiology, and bioinformatics/cheminformatics. Modules were developed by study coauthors using annotated script and were organized into three chapters within a GitHub Bookdown site. The first chapter of modules focuses on introductory data science, which includes the following topics: setting up R/RStudio and coding in the R environment; data organization basics; finding and visualizing data trends; high-dimensional data visualizations; and Findability, Accessibility, Interoperability, and Reusability (FAIR) data management practices. The second chapter of modules incorporates chemical-biological analyses and predictive modeling, spanning the following methods: dose-response modeling; machine learning and predictive modeling; mixtures analyses; -omics analyses; toxicokinetic modeling; and read-across toxicity predictions. The last chapter of modules was organized to provide examples on environmental health database mining and integration, including chemical exposure, health outcome, and environmental justice indicators. Training modules and associated data are publicly available online (https://uncsrp.github.io/Data-Analysis-Training-Modules/). Together, this resource provides unique opportunities to obtain introductory-level training on current data analysis methods applicable to 21st century science and environmental health

Problems in Developing a Constructivist Approach to Teaching: One Teacher\u27s Transition from Teacher Preparation to Teaching

This article reports a case study of an elementary school teacher moving from her university teacher education program into her first full-time job teaching a K/first-grade class. Using activity theory, we analyzed her conceptualization of teaching as she moved through the key settings of her university program, student teaching, and first job. This conceptualization began with the university\u27s emphasis on constructivism, a notion that diffused as she moved from the formal environment of the university to the practical environment of the schools. Data for the study included preteaching interviews, classroom observations, pre- and postobservation interviews, group concept map activities, interviews with supervisors and administrators, and artifacts from schools and teaching. Data analysis sought to identify tools for teaching and the ways in which those tools were supported by the environments of teaching. Results center on 2 aspects of constructivist teaching: the teacher\u27s use of integrations and the decentering of the classroom. The analysis showed that the teacher, rather than developing and sustaining a concept of constructivist teaching, instead developed what Vygotsky calls a complex, that is, a less unified understanding and application of the abstraction. Implications of the study concern ways of thinking about the common pedagogical problem teacher educators face when students of their programs abandon the theoretical principles stressed in university programs

A U.S. Isolate of <i>Theileria orientalis</i> Ikeda Is Not Transstadially Transmitted to Cattle by <i>Rhipicephalus microplus</i>

Theileria orientalis Ikeda has caused an epidemic of bovine anemia and abortion across several U.S. states. This apicomplexan hemoparasite is transmitted by Haemaphysalis longicornis ticks; however, it is unknown if other North American ticks are competent vectors. Since the disease movement is largely determined by the host tick range(s), the prediction of the T. orientalis spread among U.S. cattle populations requires determination of additional competent tick vectors. Although Rhipicephalus microplus has mostly been eradicated from the U.S., outbreaks in populations occur frequently, and the U.S. remains at risk for reintroduction. Since R. microplus is a vector of Theileria equi and T. orientalis DNA has been detected in R. microplus, the goal of this study was to determine whether R. microplus is a competent vector of T. orientalis. Larval R. microplus were applied to a splenectomized, T. orientalis Ikeda-infected calf for parasite acquisition, removed as molted adults, and applied to two T. orientalis naïve, splenectomized calves for transmission. After 60 days, the naïve calves remained negative for T. orientalis by PCR and cytology. Additionally, T. orientalis was not detected in the salivary glands or larval progeny of acquisition-fed adults. These data suggest that R. microplus is not a competent vector of the U.S. T. orientalis Ikeda isolate

<i>Dermacentor variabilis</i> Does Not Transstadially Transmit the U.S. Isolate of <i>Theileria orientalis</i> Ikeda: A Controlled Acquisition and Transmission Study

Theileria orientalis Ikeda, an emerging U.S. bovine hemoparasite, causes anemia, abortion, ill-thrift, and occasionally death. While Haemaphysalis longicornis is the primary vector, it is possible that other U.S. ticks are capable of parasite transmission and may contribute to disease spread. Dermacentor variabilis is highly prevalent in the U.S., exhibits a similar geographical distribution to T. orientalis, and is a competent vector of the related parasite, Theileria equi. Herein, we conducted controlled acquisition and transmission studies using splenectomized calves to assess whether D. variabilis can transstadially transmit T. orientalis. D. variabilis nymphs were applied to an infected, splenectomized calf for parasite acquisition and subsequently incubated to molt into adults. Freshly molted adults were applied to two splenectomized T. orientalis-naïve calves to investigate parasite transmission. Calves were monitored for 59 days, and no evidence of parasite transmission was detected using PCR for the T. orientalis Ikeda major piroplasm surface protein gene, blood smear cytology, complete blood counts, or physical examination. Salivary glands from a subset of D. variabilis adults were assessed for T. orientalis using PCR, and the parasite was not detected. These findings support the conclusion that D. variabilis is not capable of transstadial transmission of the U.S. T. orientalis Ikeda isolate

From the Field to the Laboratory: Air Pollutant-Induced Genomic Effects in Lung Cells

Current in vitro studies do not typically assess cellular impacts in relation to real-world atmospheric mixtures of gases. In this study, we set out to examine the feasibility of measuring biological responses at the level of gene expression in human lung cells upon direct exposures to air in the field. This study describes the successful deployment of lung cells in the heavily industrialized Houston Ship Channel. By examining messenger RNA (mRNA) levels from exposed lung cells, we identified changes in genes that play a role as inflammatory responders in the cell. The results show anticipated responses from negative and positive controls, confirming the integrity of the experimental protocol and the successful deployment of the in vitro instrument. Furthermore, exposures to ambient conditions displayed robust changes in gene expression. These results demonstrate a methodology that can produce gas-phase toxicity data in the field