The engineering classroom is still relevant

Citation: Fitzsimmons, E. J., Tucker-Kulesza, S. E., Li, X., Jeter, W., & Fallin, J. R. (2016). The engineering classroom is still relevant.Attrition in engineering is a complex issue with dynamically linked variables related to teaching methods in the classroom, student learning behaviors, and student perceptions of difficult material. Extensive research has been conducted in order to understand common, yet ineffective teaching practices in engineering that result in the loss of numerous future engineers. The objective of this study was to determine student actions necessary to achieve a desired grade in any engineering course, regardless of course delivery method and instructor effectiveness in the classroom. An anonymous survey was disseminated and logistic regression models were developed in order to determine relationships between self-regulated learning behaviors and final grades in seven freshman to senior engineering classes taught by civil engineering faculty. A total of five prediction models were developed for each letter grade, with the failing grade "F" serving as the baseline condition, or null model. The models found three significant variables that affect a student's final grade: regular class attendance, note-taking during class, and if he or she could keep up with the instructor during lecture. These interactive learning behaviors were all identified as critical for success, defining success as receiving an "A" in an engineering course. The combination of students taking notes and attending class showed the highest probability of a student receiving an "A." Results of this study have been summarized into a graphic that the authors show and discuss during the first class with students. This powerful graphic shows students what they can do in classes of all levels of civil engineering to succeed in their ever-changing learning environment. © American Society for Engineering Education, 2016

Characterization of Claypan Soils in Southeastern Kansas

Soil erosion reduces topsoil depth. In areas with a claypan, removal of productive topsoil reduces crop yield where the claypan layer is near the surface. The topsoil and claypan layer each have unique characteristics that impact crop production and within-field variability. To better understand these differences, the soil from an area of low crop yield and high crop yield were collected and laboratory tests were performed to determine the soil classification and undrained shear strength. Understanding the soil properties and the interaction between the topsoil and claypan layers may aid in under­standing the process by which topsoil is being eroded

Electrical Resistivity Tomography of Claypan Soils in Southeastern Kansas

Claypan soils cover approximately 10 million acres across several states in the central United States. The soils are characterized by a highly impermeable clay layer within the profile that impedes water flow and root growth. While some claypan soils can be productive, they must be carefully managed to avoid reductions to crop productivity due to root restrictions, water, and nutrient limitations. Clay soils are usually resistant to erosion but may exacerbate erosion of the silt-loam topsoil. Soil production potential is the capacity of soil to produce at a given level (yield per acre). The productive capacity is tied to soil characteristics, which can be highly variable within a field. In this project, we have used imagery analysis to study the aerial images and terrain of fields during different productive times of the year to identify where soil samples should be collected for more discrete analysis. Soil samples provide valuable information; however, the amount of data obtained from a relatively small area within a field does not provide sufficient information to delineate the subsurface characteristics. To address the limitations of sampling, we have also employed the use of yield maps collected from commercial yield monitors on production-scale combines and surface electrical conductivity measurements (Sassenrath and Kulesza, 2017). Soil conductivity is a measurement of how well a representative volume of soil conducts electricity. Soil conductivity is a function of the soil clay content, moisture content, and other measurable soil properties (Kitchen et al., 2003); as such, it has become a valuable tool for mapping in-field variability. The main advantage of a soil conductivity measurement is that the entire surface of a field can be imaged. The disadvantage of a soil conductivity measurement is that data are only collected near the surface (10 – 30 inches) and the measurements are relative measurements. This means that the conductivity mappers can identify changes in soil properties, but they cannot directly tell researchers what caused these changes. Electrical resistivity tomography (ERT) is a popular near-surface geophysical measurement for geophysical and engineering applications. The term “near-surface” generally means down to around 30 feet in the subsurface. Electrical resistivity is the reciprocal measurement of electrical conductivity; therefore, both systems measure differences in the same soil properties. ERT measurements are different than surface electrical conductivity measurements because ERT collects a “slice” of data into the subsurface, as opposed to only changes at the surface area. Relative measurements, similar to those collected in an electrical conductivity survey, are collected; however, in ERT studies the data are mathematically inverted to yield the true electrical resistivity of the soil with depth. This allows an interpretation of the changing soil properties with depth to reduce the required amount of sampling. A disadvantage of an ERT survey is that the data acquisition is stationary so mapping an entire field is not feasible. We have used a coupled process of imagery and terrain analysis, yield maps, and electrical conductivity measurements to guide the locations of ERT surveys in this project (Tucker-Kulesza et al. 2017)

Search for supersymmetry in events with photons and low missing transverse energy in pp collisions at √s=7 TeV

This is the pre-print version of the Article. The official published version can be accessed from the links below - Copyright @ 2013 Elsevier.Many models of new physics, including versions of supersymmetry (SUSY), predict production of events with low missing transverse energy, electroweak gauge bosons, and many energetic final-state particles. The stealth SUSY model yields this signature while conserving R-parity by means of a new hidden sector in which SUSY is approximately conserved. The results of a general search for new physics, with no requirement on missing transverse energy, in events with two photons and four or more hadronic jets are reported. The study is based on a sample of proton–proton collisions at √s=7 TeV corresponding to 4.96 fb−1 of integrated luminosity collected with the CMS detector in 2011. Based on good agreement between the data and the standard model expectation, the data are used to determine model-independent cross-section limits and a limit on the squark mass in the framework of stealth SUSY. With this first study of its kind, squark masses less than 1430 GeV are excluded at the 95% confidence level.This study is supported by the BMWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); MEYS (Czech Republic); MoER, SF0690030s09 and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF and WCU (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); MSI (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MON, RosAtom, RAS and RFBR (Russia); MSTD (Serbia); SEIDI and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); ThEP, IPST and NECTEC (Thailand); TUBITAK and TAEK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA)

Search for direct pair production of scalar top quarks in the single- and dilepton channels in proton-proton collisions at √s=8 TeV

Results are reported from a search for the top squark et1, the lighter of the two supersymmetric partners of the top quark. The data sample corresponds to 19.7 fb−1 of proton-proton collisions at √ s = 8 TeV collected with the CMS detector at the LHC. The search targets et1 → bχe ± 1 and et1 → t (∗)χe 0 1 decay modes, where χe ± 1 and χe 0 1 are the lightest chargino and neutralino, respectively. The reconstructed final state consists of jets, b jets, missing transverse energy, and either one or two leptons. Leading backgrounds are determined from data. No significant excess in data is observed above the expectation from standard model processes. The results exclude a region of the two-dimensional plane of possible et1 and χe 0 1 masses. The highest excluded et1 and χe 0 1 masses are about 700 GeV and 250 GeV, respectively

Review of soil salinity assessment for agriculture across multiple scales using proximal and/or remote sensors

Mapping and monitoring soil spatial variability is particularly problematic for temporally and spatially dynamic properties such as soil salinity. The tools necessary to address this classic problem only reached maturity within the past 2 decades to enable field- to regional-scale salinity assessment of the root zone, including GPS, GIS, geophysical techniques involving proximal and remote sensors, and a greater understanding of apparent soil electrical conductivity (ECa) and multi- and hyperspectral imagery. The concurrent development and application of these tools have made it possible to map soil salinity across multiple scales, which back in the 1980s was prohibitively expensive and impractical even at field scale. The combination of ECa-directed soil sampling and remote imagery has played a key role in mapping and monitoring soil salinity at large spatial extents with accuracy sufficient for applications ranging from field-scale site-specific management to statewide water allocation management to control salinity within irrigation districts. The objective of this paper is: (i) to present a review of the geophysical and remote imagery techniques used to assess soil salinity variability within the root zone from field to regional scales; (ii) to elucidate gaps in our knowledge and understanding of mapping soil salinity; and (iii) to synthesize existing knowledge to give new insight into the direction soil salinity mapping is heading to benefit policy makers, land resource managers, producers, agriculture consultants, extension specialists, and resource conservation field staff. The review covers the need and justification for mapping and monitoring salinity, basic concepts of soil salinity and its measurement, past geophysical and remote imagery research critical to salinity assessment, current approaches for mapping salinity at different scales, milestones in multi-scale salinity assessment, and future direction of field- to regional-scale salinity assessment