25 research outputs found
A comparison of engineering students' reflections on their first-year experiences
Background: The introduction of a mentoring program at the University of Notre Dame in which upperclass engineering students serve as a resource to first-year students was the focus of this study. A retrospective survey was administered to classes of sophomores and juniors. Purpose: (Hypothesis) The survey was focused on impressions of the first-year engineering experiences motivated by a desire to assess the new program. This assessment was used to address research questions relating to students' comfort approaching faculty/upperclass students and transition. Design/Method: The survey was first administered during January 2006, prior to program introduction, and again in January 2008, after the program was in place for two years. Responses were analyzed using descriptive statistics and regression models for statistically significant differences. Results: Findings indicate: (1) students are more comfortable approaching upperclass students than faculty for advice in many situations, (2) no measurable student benefit could be concluded as a result of the mentoring program introduction, (3) gender differences exist in terms of a student's comfort with their decision to stay in engineering, and (4) gender was not a statistically significant factor in predicting adjustment to engineering. Conclusions: Results support continued focus on increasing academic confidence in women and men entering engineering programs to support the adjustment to engineering. The affinity of students for obtaining advice from more experienced students rather than faculty suggests that support programs such as mentoring should aide that adjustment, yet it is clear that the success of such programs is sensitive to conditions that are not easily controlled
Supplementary Tables S1 and S2 from The Origin of Highly Elevated Cell-Free DNA in Healthy Individuals and Patients with Pancreatic, Colorectal, Lung, or Ovarian Cancer
Supplementary Table 1. Demographic, clinical, and plasma cfDNA data for the patients included in the study deconvoluted by Sun et al. (3) and Moss et al. (43) by QP and NNLS. NA, not available.
Supplementary Table 2. Demographic, clinical, and plasma cfDNA data for the patients included in the study deconvoluted by Loyfer et al. (44) NA, not available.</p
Figure S5 from The Origin of Highly Elevated Cell-Free DNA in Healthy Individuals and Patients with Pancreatic, Colorectal, Lung, or Ovarian Cancer
Supplemental Figure 5. Methylation profiles using quadratic programming vs. non-negative least- squares regression using the reference matrix described in Moss et al. (43). Pearson’s correlation coefficient and p values are presented at the bottom of this figure, showing the derived contributions from each of the 25 tissue types that could be assessed.</p
Figure S1 from The Origin of Highly Elevated Cell-Free DNA in Healthy Individuals and Patients with Pancreatic, Colorectal, Lung, or Ovarian Cancer
Supplemental Figure 1. Overview of the patient samples included in the present study.</p
Supplementary Notes 1-5 from The Origin of Highly Elevated Cell-Free DNA in Healthy Individuals and Patients with Pancreatic, Colorectal, Lung, or Ovarian Cancer
Supplementary Notes 1-5. Supplementary Note 1: Origins of cell-free DNA. Supplementary Note 2: Leukocyte Lysis. Supplementary Note 3: Reference datasets and deconvolution algorithms used to interpret whole genome bisulfite sequencing data. Supplementary Note 4: Turnover rates. Supplementary Note 5: Relationships between ctDNA and tissue specific cfDNA in cancer patients.</p
Figure S4 from The Origin of Highly Elevated Cell-Free DNA in Healthy Individuals and Patients with Pancreatic, Colorectal, Lung, or Ovarian Cancer
Supplemental Figure 4. Methylation profiles using quadratic programming vs. non-negative least- squares regression using the reference matrix described in Sun et al. (3). Pearson’s correlation coefficient and p values are presented at the bottom of this figure, showing the derived contributions from each of the 12 tissue types that could be assessed.</p