Alien Registration- Daigle, Francis J. (Bar Harbor, Hancock County)

https://digitalmaine.com/alien_docs/19254/thumbnail.jp

Testicular toxicity and the potential for 1, 2 -ethlyene dichloride (EDC) to initiate epigenetic disruption of the paternal genome

Our genetic inheritance begins with one genome copy from each parent. The presence of one or more errors in either the maternal or the paternal genome can lead to genetic disease or disruption of the embryonic program and potential loss of the offspring. Numerous chemical and physical toxicants are known to produce germ line mutagenesis based on their ability to produce DNA sequence mutations. Exposures to these cytotoxic and mutagenic agents pose a risk for human offspring. However, very little is known regarding the sensitivity of the epigenetic patterns involved in reproductive functions to adverse effects of chemical agents. The present study was undertaken to address the potential for ethylene dichloride (EDC) to disrupt the epigenetic programming of the paternal genome in mammalian (mouse) sperm. Unfortunately, it is very difficult to study developing germ cells such as spermatogonia and their precursor spermatogonial stem cells within the in vivo mouse testis model. Thus, an in vitro mouse spermatogonial stem cell model was developed that enabled the triggering of a spermatogenesis differentiation pathway in these stem cell cultures. Since the epigenetic imprint patterns are reported to be established in the spermatogonial stem cell of prior to meiosis, this in vitro model enabled the treatment and study of the effects of EDC on DNA, 5-methlcytosine and histone modifications in the paternal gamete. Paternally imprinted genes, such as H19, Gtl2, and Rasgrf1, showed changes in histone methylation modifications in ethylene dichloride treated spermatogonia. These data demonstrate that ethylene dichloride can disrupt the genomic imprint in developing sperm, and thus perturb the embryonic programming of potential offspring in the mouse model. This work suggests that EDC may have the potential to cause genetic diseases in offspring from exposed males

Alien Registration- Daigle, Xavier J. (Calais, Washington County)

https://digitalmaine.com/alien_docs/1217/thumbnail.jp

Alien Registration- Daigle, Joseph P J. (Fort Fairfield, Aroostook County)

https://digitalmaine.com/alien_docs/35923/thumbnail.jp

MR449: Allagash Wilderness Waterway Visitor Survey 2019

Quality in outdoor recreation can be defined as the degree to which recreation opportunities provide the experiences for which they are designed and managed. Key to protecting the backcountry experiences is an understanding of the different types of visitors to the Allagash Wilderness Waterway, each one with different needs and expectations, and the different levels of importance they place on recreation opportunities and conditions. In this report, visitor management implications and suggested further research focus on the diversity of use of the Allagash Wilderness Waterway in order to maximize the quality of the visitor experiences while protecting the unique natural setting.https://digitalcommons.library.umaine.edu/aes_miscreports/1030/thumbnail.jp

M-BISON: Microarray-based integration of data sources using networks

BACKGROUND: The accurate detection of differentially expressed (DE) genes has become a central task in microarray analysis. Unfortunately, the noise level and experimental variability of microarrays can be limiting. While a number of existing methods partially overcome these limitations by incorporating biological knowledge in the form of gene groups, these methods sacrifice gene-level resolution. This loss of precision can be inappropriate, especially if the desired output is a ranked list of individual genes. To address this shortcoming, we developed M-BISON (Microarray-Based Integration of data SOurces using Networks), a formal probabilistic model that integrates background biological knowledge with microarray data to predict individual DE genes. RESULTS: M-BISON improves signal detection on a range of simulated data, particularly when using very noisy microarray data. We also applied the method to the task of predicting heat shock-related differentially expressed genes in S. cerevisiae, using an hsf1 mutant microarray dataset and conserved yeast DNA sequence motifs. Our results demonstrate that M-BISON improves the analysis quality and makes predictions that are easy to interpret in concert with incorporated knowledge. Specifically, M-BISON increases the AUC of DE gene prediction from .541 to .623 when compared to a method using only microarray data, and M-BISON outperforms a related method, GeneRank. Furthermore, by analyzing M-BISON predictions in the context of the background knowledge, we identified YHR124W as a potentially novel player in the yeast heat shock response. CONCLUSION: This work provides a solid foundation for the principled integration of imperfect biological knowledge with gene expression data and other high-throughput data sources

Facilitating Bloom\u27s Level One through Active Learning and Collaboration

Bloom\u27s taxonomy provides a means of structuring learning activities according to levels of comprehension ranging from factual knowledge to the creation of new knowledge. There are problems with presenting factual knowledge in the traditional lecture mode: student motivation, time-to-present, and course priorities. However, in Bloom\u27s taxonomy, Level 1 (factual) knowledge is the basis for knowledge comprehension at higher levels. Therefore, it is essential that the fact base comprehension be attained so that higher levels of knowledge can be addressed. Active learning and collaborative approaches have been shown to be effective in promoting learning. How can active learning and collaboration be used to overcome the problems associated with promoting Level 1 comprehension? In our introductory Computer Information Science (CIS) course, we attempt to answer this question for the topic history of computing. We have combined a student research and collaborative assignment to acquire Level 1 comprehension with a culminating College Bowl activity to reach the goal of Level 2 comprehension. In this paper we discuss course organization, course goals, the College Bowl format of quizzing, contest results, and overall observation of the process

Current Pressure Transducer Application of Model-based Prognostics Using Steady State Conditions

Prognostics is the process of predicting a system's future states, health degradation/wear, and remaining useful life (RUL). This information plays an important role in preventing failure, reducing downtime, scheduling maintenance, and improving system utility. Prognostics relies heavily on wear estimation. In some components, the sensors used to estimate wear may not be fast enough to capture brief transient states that are indicative of wear. For this reason it is beneficial to be capable of detecting and estimating the extent of component wear using steady-state measurements. This paper details a method for estimating component wear using steady-state measurements, describes how this is used to predict future states, and presents a case study of a current/pressure (I/P) Transducer. I/P Transducer nominal and off-nominal behaviors are characterized using a physics-based model, and validated against expected and observed component behavior. This model is used to map observed steady-state responses to corresponding fault parameter values in the form of a lookup table. This method was chosen because of its fast, efficient nature, and its ability to be applied to both linear and non-linear systems. Using measurements of the steady state output, and the lookup table, wear is estimated. A regression is used to estimate the wear propagation parameter and characterize the damage progression function, which are used to predict future states and the remaining useful life of the system

Student Attitudes Towards Computers Before And After Taking An Introductory AIS Course

Computer attitudes are measured before students take an introductory AIS course. Attitudes are positive, regardless of gender or traditional vs. non-traditional student status. No difference is noted by gender, but non-traditional students have more positive attitudes. Prior computer experience appears to explain these findings. Attitudes are measured again at semester end. Attitudes either remain the same or slightly improve for respective subgroups studied. Little if any gender difference exists, but the gap by student status is slightly greater. Impact of findings on AIS education is discussed