Tomato production in Missouri

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Commercial strawberry culture in Missouri

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Selecting fruit varieties

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Career Trajectories of Mathematics Professors of African Heritage

This research investigated the career trajectories of mathematics professors of African heritage. The principal objective was to determine the factors that promoted self-efficacy, which made them complete a PhD in mathematics or an EdD in mathematics education regardless of the obstacles they encountered. I investigated 10 professors, males and females, of African heritage at the City University of the Northeast by using open-ended biographical questionnaires and individual interviews Several themes emerged from the data collected. The major themes that impacted the career trajectories of African American male and female mathematics professors were (a) family influence; (b) teacher influence; (c) peer influence; (d) problem solving approach; (e) perceptions of mathematics; (f) prior experience; (g) and individual perseverance (determination) and commitment (obligation). The findings of this research suggested that there are opportunities for young men and women of African heritage to develop into successful mathematicians (the term successful mathematicians is used to denote those men and women of African heritage who have completed their terminal degree, in mathematics or mathematics related subjects) provided that parents, teachers, and peers act their part

An integrated deep learning and object-based image analysis approach for mapping debris- covered glaciers

Evaluating glacial change and the subsequent water stores in high mountains is becoming increasingly necessary, and in order to do this, models need reliable and consistent glacier data. These often come from global inventories, usually constructed from multi-temporal satellite imagery. However, there are limitations to these datasets. While clean ice can be mapped relatively easily using spectral band ratios, mapping debris-covered ice is more difficult due to the spectral similarity of supraglacial debris to the surrounding terrain. Therefore, analysts often employ manual delineation, a time-consuming and subjective approach to map debris-covered ice extents. Given the increasing prevalence of supraglacial debris in high mountain regions, such as High Mountain Asia, a systematic, objective approach is needed. The current study presents an approach for mapping debris-covered glaciers that integrates a convolutional neural network and object-based image analysis into one seamless classification workflow, applied to freely available and globally applicable Sentinel-2 multispectral, Landsat-8 thermal, Sentinel-1 interferometric coherence, and geomorphometric datasets. The approach is applied to three different domains in the Central Himalayan and the Karakoram ranges of High Mountain Asia that exhibit varying climatic regimes, topographies and debris-covered glacier characteristics. We evaluate the performance of the approach by comparison with a manually delineated glacier inventory, achieving F-score classification accuracies of 89.2%–93.7%. We also tested the performance of this approach on declassified panchromatic 1970 Corona KH-4B satellite imagery in the Manaslu region of Nepal, yielding accuracies of up to 88.4%. We find our approach to be robust, transferable to other regions, and accurate over regional (>4,000 km2) scales. Integrating object-based image analysis with deep-learning within a single workflow overcomes shortcomings associated with convolutional neural network classifications and permits a more flexible and robust approach for mapping debris-covered glaciers. The novel automated processing of panchromatic historical imagery, such as Corona KH-4B, opens the possibility of exploiting a wealth of multi-temporal data to understand past glacier changes.publishedVersio

Determination of Interface Atomic Structure and Its Impact on Spin Transport Using Z-Contrast Microscopy and Density-Functional Theory

We combine Z-contrast scanning transmission electron microscopy with density-functional-theory calculations to determine the atomic structure of the Fe/AlGaAs interface in spin-polarized light-emitting diodes. A 44% increase in spin-injection efficiency occurs after a low-temperature anneal, which produces an ordered, coherent interface consisting of a single atomic plane of alternating Fe and As atoms. First-principles transport calculations indicate that the increase in spin-injection efficiency is due to the abruptness and coherency of the annealed interface.Comment: 16 pages (including cover), 4 figure

Executive Pay and Performance:The Moderating Effect of CEO Power and Governance Structure

This paper examines the crucial question of whether chief executive officer (CEO) power and corporate governance (CG) structure can moderate the pay-for-performance sensitivity (PPS) using a large up-to-date South African dataset. Our findings are three-fold. First, when direct links between executive pay and performance are examined, we find a positive, but relatively small PPS. Second, our results show that in a context of concentrated ownership and weak board structures; the second-tier agency conflict (director monitoring power and opportunism) is stronger than the first-tier agency problem (CEO power and self-interest). Third, additional analysis suggests that CEO power and CG structure have a moderating effect on the PPS. Specifically, we find that the PPS is higher in firms with more reputable, founding and shareholding CEOs, higher ownership by directors and institutions, and independent nomination and remuneration committees, but lower in firms with larger boards, more powerful, and long-tenured CEOs. Overall, our evidence sheds new important theoretical and empirical insights on explaining the PPS with specific focus on the predictions of the optimal contracting and managerial power hypotheses. The findings are generally robust across a raft of econometric models that control for different types of endogeneities, pay, and performance proxies