First-year interest groups and 1st semester BME design class exposure to improve engineering student outcomes

First year Biomedical Engineering (BME) students at The University of Texas at Austin have the option of joining a First-year Interest Group (FIG). FIGs can increase student interest and retention in the major by allowing groups of 15-20 students to attend a weekly seminar and their first engineering classes together. [1] BME 303L Introduction to BME Engineering Design is a required course for first year BME students; students who join a FIG facilitated by the BME advising office enroll in BME 303L together during their first semester (fall) on campus. Approximately 80% of fall semester BME 303L enrollment is FIG students, while the other 20% are not part of a BME FIG. The same course taught by the same instructor is also offered during the following spring semester, and spring enrollment is exclusively made up of first year students who did not participate in a fall FIG. While FIGs have been shown to increase retention[1] and we have observed a positive impact on attitudes toward engineering, we have not yet been able to correlate these successes to engineering student outcomes as defined by the Accreditation Board for Engineering and Technology (ABET). In order to better understand if the FIG success is correlated to engineering student outcomes, the authors surveyed all first year BME students at the end of the fall 2017 semester to measure their own perception of teamwork, communication skills, lifelong learning, and ability to use engineering tools. This paper presents initial results of the survey comparing engineering student outcome perceptions from students who just completed a FIG and BME 303L in the fall semester, and students who did not participate in FIG and are enrolled in BME 303L in the spring semester. These data will be used to optimize advising and curriculum for first year students and improve engineering outcomes for all students. Future surveys are planned for sophomore and junior years as well.Cockrell School of Engineerin

The Feasibility of Wearable Sensors for the Automation of Distal Upper Extremity Ergonomic Assessment Tools

Work-related distal upper limb musculoskeletal disorders are costly conditions that many companies and researchers spend significant resources on preventing. Ergonomic assessments evaluate the risk of developing a work-related musculoskeletal disorder (WMSD) by quantifying variables such as the force, repetition, and posture (among others) that the task requires. Accurate and objective measurements of force and posture are challenging due to equipment and location constraints. Wearable sensors like the Delsys Trigno Quattro combine inertial measurement units (IMUs) and surface electromyography to solve collection difficulties. The purpose of this work was to evaluate the joint angle estimation of IMUs and the relationship between sEMG and overall task intensity throughout a controlled wrist motion. Using a 3 degrees-of-freedom wrist manipulandum, the feasibility of a small, lightweight wearable was evaluated to collect accurate wrist flexion and extension angles and to use sEMG to quantify task intensity. The task was a repeated 95º arc in flexion/ extension with six combinations of wrist torques and grip requirements. The mean wrist angle difference (throughout the range of motion) between the WristBot and the IMU of 1.70° was not significant (p= 0.057); but significant differences existed throughout the range of motion. The largest difference between the IMU and the WristBot was 10.7° at 40° extension; this discrepancy is smaller than typical visual inspection joint angle estimate errors by ergonomists of 15.6°. All sEMG metrics (flexor muscle root mean square (RMS), extensor muscle RMS, mean RMS, integrated sEMG (iEMG), physiological cross-sectional area weighted RMS) and ratings of perceived exertion (RPE) had significant regression results with the task intensity. Variance in RPE was better explained by task intensity than the best sEMG metric (iEMG) with R2 values of 0.35 and 0.21, respectively. Wearable sensors can be used in occupational settings to increase the accuracy of postural assessments; additional research is required on relationships between sEMG and task intensity to be used effectively in ergonomics. There is potential for sEMG to be a powerful tool; however, the dynamic nature and combined exertion (grip and flexion/ extension) make it difficult to quantify task intensit

Spectrophotometry of nearby field galaxies: the data

We have obtained integrated and nuclear spectra, as well as U, B, R surface photometry, for a representative sample of 196 nearby galaxies. These galaxies span the entire Hubble sequence in morphological type, as well as a wide range of luminosities (M_B=-14 to -22). Here we present the spectrophotometry for these galaxies. The selection of the sample and the U, B, R surface photometry is described in a companion paper (Paper I). Our goals for the project include measuring the current star formation rates and metallicities of these galaxies, and elucidating their star formation histories, as a function of luminosity and morphology. We thereby extend the work of Kennicutt (1992a) to lower luminosity systems. We anticipate that our study will be useful as a benchmark for studies of galaxies at high redshift. We describe the observing, data reduction and calibration techniques, and demonstrate that our spectrophotometry agrees well with that of Kennicutt. The spectra span the range 3550--7250 A at a resolution (FWHM) of ~6 A, and have an overall relative spectrophotometric accuracy of +/- 6 per cent. We present a spectrophotometric atlas of integrated and nuclear rest-frame spectra, as well as tables of equivalent widths and synthetic colors. We study the correlations of galaxy properties determined from the spectra and images. Our findings include: (1) galaxies of a given morphological class display a wide range of continuum shapes and emission line strengths if a broad range of luminosities are considered, (2) emission line strengths tend to in- crease and continua tend to get bluer as the luminosity decreases, and (3) the scatter on the general correlation between nuclear and integrated H_alpha emission line strengths is large.Comment: Accepted for publication in ApJS (scheduled for Vol.127, 2000 March); 63 pages, LateX, 9 figures and 6 tables included, a spectrophotometric atlas is provided as GIF images, fig 1 as a JPEG image, in a single tar-file; a full 600 dpi version is available at http://www.astro.rug.nl/~nfgs

A climate of trust : exploring adaptation policy

Bibliography: leaves 24-27.This paper aims to tease out and unpack the different value positions that inhere in the range of discourses and methods that currently permeate the field of climate change. In doing so, I will examine the underlying concepts, methods and their application by various actors and institutions

Cryogenic silicification of microorganisms in hydrothermal fluids

Silica-rich hydrothermal fluids that experience freezing temperatures precipitate cryogenic opal-A (COA) within ice-bound brine channels. We investigated cryogenic silicification as a novel preservation pathway for chemo- and photo-lithotrophic Bacteria and Archaea. We find that the co-partitioning of microbial cells and silica into brine channels causes microorganisms to become fossilised in COA. Rod- and coccoidal-form Bacteria and Archaea produce numerous cell casts on COA particle surfaces, while Chloroflexus filaments are preserved inside particle interiors. COA particles precipitated from natural Icelandic hot spring fluids possess similar biomorphic casts, including those containing intact microbial cells. Biomolecules and inorganic metabolic products are also captured by COA precipitation, and are detectable with a combination of visible - shortwave infrared reflectance, FTIR, and Raman spectroscopy. We identify cryogenic silicification as a newly described mechanism by which microbial biosignatures can be preserved within silica-rich hydrothermal environments. This work has implications for the interpretation of biosignatures in relic hydrothermal settings, and for life-detection on Mars and Enceladus, where opaline silica indicative of hydrothermal activity has been detected, and freezing surface conditions predominate

Forest ecosystem properties emerge from interactions of structure and disturbance

Forest structural diversity and its spatiotemporal variability are constrained by environmental and biological factors, including species pools, climate, land-use history, and legacies of disturbance regimes. These factors influence forest responses to disturbances and their interactions with structural diversity, potentially creating structurally mediated emergent properties at local to continental spatial scales and over evolutionary time. Here, we present a conceptual framework for exploring the emergent properties that arise from interactions between forest structural diversity and disturbances. We synthesize and present definitions for key terms, including emergent property, disturbance, and resilience, and highlight various types and examples of emergent properties, such as (1) interactions with species composition, (2) interactions with disturbance frequency and intensity, and (3) evolutionary changes to communities. Although emergent properties in forest ecosystems remain poorly understood, we describe a foundation for study and applied management of forest structural diversity to enhance forest restoration and resilience

Increased signal-to-noise ratios within experimental field trials by regressing spatially distributed soil properties as principal components

Environmental variability poses a major challenge to any field study. Researchers attempt to mitigate this challenge through replication. Thus, the ability to detect experimental signals is deter-mined by the degree of replication and the amount of environmental variation, noise, within the experimental system. A major source of noise in field studies comes from the natural heterogeneity of soil properties which create microtreatments throughout the field. In addition, the variation within different soil properties is often nonrandomly distributed across a field. We explore this challenge through a sorghum field trial dataset with accompanying plant, microbiome, and soil property data. Diverse sorghum genotypes and two watering regimes were applied in a split-plot design. We describe a process of identifying, estimating, and controlling for the effects of spatially distributed soil properties on plant traits and microbial communities using minimal degrees of freedom. Importantly, this process provides a method with which sources of environmental variation in field data can be identified and adjusted, improving our ability to resolve effects of interest and to quantify subtle phenotypes