EVALUATION OF A QUANTITATIVE PROCEDURE TO SELECT AMONG ALTERNATIVE MARKETING STRATEGIES TO REDUCE PRICE RISKS OF STOCKER OPERATORS

Marketing,

Alien Registration- Davis, James H. (Lubec, Washington County)

https://digitalmaine.com/alien_docs/2325/thumbnail.jp

The curious case of large-N expansions on a (pseudo)sphere

We elucidate the large-N dynamics of one-dimensional sigma models with spherical and hyperbolic target spaces and find a duality between the Lagrange multiplier and the angular momentum. In the hyperbolic model we propose a new class of operators based on the irreducible representations of hyperbolic space. We also uncover unexpected zero modes which lead to the double scaling of the 1/N expansion and explore these modes using Gelfand-Dikiy equations.Comment: 18 pages, 3 figure

Faculty ethics unveiled: scholarship—et tu, brute?

Little actual research has been conducted to explore the ethics of the faculty of higher education. A review of the literature has discovered four primary categories of faculty ethics, which include scholarship, teaching, service, and professional (e.g. consulting, treatment of colleagues and peers). This paper will focus on the scholarship category and includes research (e.g. authorship, conflicts of interest, plagiarism/citing-including self-plagiarism, ethical approval, research design, redundant publications, misconduct, accuracy, personal criticism of others) and review of other\u27s work as a reviewer or editor (e.g. unbiased, speed/timeliness, accuracy, responsibility, objectivity, confidentiality, conflicts of interest). The purpose of this paper is to survey and classify key ideas in the literature, present research propositions, and outline ideas for future research in this area

Bubble Column Apparatus for Separating Wax from Catalyst Slurry

Novel methods and devices for production of liquid hydrocarbon products from gaseous reactants are disclosed. In one aspect, a method for separating a liquid hydrocarbon, typically a wax, from a catalyst containing slurry is provided, comprising passing the slurry through at least one downcomer extending from an overhead separation chamber and discharging into the bottom of a slurry bubble column reactor. The downcomer includes a cross-flow filtration element for separating a substantially particle-free liquid hydrocarbon for downstream processing. In another aspect, a method for promoting plug-flow movement in a recirculating slurry bubble column reactor is provided, comprising discharging the recirculating slurry into the reactor through at least one downcomer which terminates near the bottom of the reactor. Devices for accomplishing the above methods are also provided

Patch-based Convolutional Neural Network for Whole Slide Tissue Image Classification

Convolutional Neural Networks (CNN) are state-of-the-art models for many image classification tasks. However, to recognize cancer subtypes automatically, training a CNN on gigapixel resolution Whole Slide Tissue Images (WSI) is currently computationally impossible. The differentiation of cancer subtypes is based on cellular-level visual features observed on image patch scale. Therefore, we argue that in this situation, training a patch-level classifier on image patches will perform better than or similar to an image-level classifier. The challenge becomes how to intelligently combine patch-level classification results and model the fact that not all patches will be discriminative. We propose to train a decision fusion model to aggregate patch-level predictions given by patch-level CNNs, which to the best of our knowledge has not been shown before. Furthermore, we formulate a novel Expectation-Maximization (EM) based method that automatically locates discriminative patches robustly by utilizing the spatial relationships of patches. We apply our method to the classification of glioma and non-small-cell lung carcinoma cases into subtypes. The classification accuracy of our method is similar to the inter-observer agreement between pathologists. Although it is impossible to train CNNs on WSIs, we experimentally demonstrate using a comparable non-cancer dataset of smaller images that a patch-based CNN can outperform an image-based CNN

The Relationship between Growth Scores and the Overall Observation Ratings for Teachers in a Public School System in Tennessee

The purpose of this study was to investigate the relationship between the TVAAS growth score given by the Tennessee Department of Education and the overall Tennessee Educator Assessment Model (TEAM) observation rating for teachers in grades 3 through 8. The participating county public school system for this study is located in Northeast Tennessee. Participants were teachers in the school system teaching Math, English/Language Arts, Science, and Social Studies in grades 3 through 8 in 10 elementary schools, 6 middle schools, and 2 K-8 schools. Specifically, this research examined the relationship between the TEAM observation scores and overall TVAAS growth score given to the teacher from the Tennessee Department of Education based upon yearly-standardized test scores. Research reinforced mixed views about the validity and purpose of teacher evaluation systems and the use of Tennessee Value-Added Assessment System. Five research questions guided this study and quantitative data were analyzed using a Pearson correlation, one-way MANOVAs and a one-way ANOVA. Results indicated a moderate positive relationship between a teacher’s TEAM observation score and the TVAAS growth score given by the Tennessee Department of Education

The Relationship between Growth Scores and the Overall Observation Ratings for Teachers in a Public School System in Tennessee

Abstract is available to download

Coral reef drag coefficients—surface gravity wave enhancement

Author Posting. © American Meteorological Society, 2018. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 48 (2018): 1555-1566, doi:10.1175/JPO-D-17-0231.1.A primary challenge in modeling flow over shallow coral reefs is accurately characterizing the bottom drag. Previous studies over continental shelves and sandy beaches suggest surface gravity waves should enhance the drag on the circulation over coral reefs. The influence of surface gravity waves on drag over four platform reefs in the Red Sea is examined using observations from 6-month deployments of current and pressure sensors burst sampling at 1Hz for 4–5min. Depth-average current fluctuations U0 within each burst are dominated by wave orbital velocities uw that account for 80%–90%of the burst variance and have a magnitude of order 10 cm s21, similar to the lower-frequency depth-average current Uavg. Previous studies have shown that the cross-reef bottom stress balances the pressure gradient over these reefs. A bottom stress estimate that neglects the waves (rCdaUavgjUavgj, where r is water density and Cda is a drag coefficient) balances the observed pressure gradient when uw is smaller than Uavg but underestimates the pressure gradient when uw is larger than Uavg (by a factor of 3–5 when uw 5 2Uavg), indicating the neglected waves enhance the bottom stress. In contrast, a bottom stress estimate that includes the waves [rCda(Uavg 1 U0)jUavg 1 U0j)] balances the observed pressure gradient independent of the relative size of uw and Uavg, indicating that this estimate accounts for the wave enhancement of the bottom stress. A parameterization proposed by Wright and Thompson provides a reasonable estimate of the total bottom stress (including the waves) given the burst-averaged current and the wave orbital velocity.The Red Sea field program was supported by Awards USA 00002 and KSA 00011 made by KAUST. S. Lentz was supported for the analysis by NSF Award OCE-1558343.2019-01-1