Genetic Variation Linked to Neuroticism Is Associated with Amygdala Function

From the Washington University Office of Undergraduate Research Digest (WUURD), Vol. 12, 05-01-2017. Published by the Office of Undergraduate Research. Joy Zalis Kiefer, Director of Undergraduate Research and Associate Dean in the College of Arts & Sciences; Lindsey Paunovich, Editor; Helen Human, Programs Manager and Assistant Dean in the College of Arts and Sciences Mentor: Ryan Bogda

ECONOMICALLY OPTIMAL NITROGEN FERTILIZATION FOR YIELD AND PROTEIN IN HARD RED SPRING WHEAT

This analysis determines profit maximizing N fertilization levels of hard red spring wheat (HRSW) for various wheat prices, N prices, and protein-based HRSW price premium/discount (P/D) structures for south eastern Washington data. Fertilizer response data consisting of rates of N fertilization (lb/ac), grain yield (bu/ac), and grain protein (%) were used to statistically estimate regression relationships that predicted yield and protein in response to N. All predicted net return maximizing N, protein, and yield levels were within the data range. Increasing P/D incentives for protein increased optimal N, the expected economic result. At the high P/D structures, the P/D structure dominated N and wheat prices in determining optimal N application levels. Overall, net return-maximizing yields varied only modestly with changes in both N and wheat price in this data set. However, in all scenarios, as P/D incentives increased, net return maximizing N levels were beyond the level that resulted in maximum yield. At the two lowest P/D structures, which provided the lowest reward for protein, it was most profitable to fertilize for slightly less than 14% expected protein. These results indicate that it is not always profitable to use 14% protein as an N fertilization goal. Abbreviations: CT, conventional tillage; HRSW, hard red spring wheat; HRWW, hard red winter wheat; N, nitrogen; NO3, nitrate; NT, No Tillage; P/D, premium/discount; SWSW, soft white spring wheat; SWW, soft white wheat.Crop Production/Industries,

Using Google’s Mobility Data to understand park visitation during the COVID-19 pandemic: A note of caution

The COVID-19 pandemic has dramatically impacted park visitation around the globe. In an effort to un-derstand the factors influencing these changes, nu-merous attempts have been made to use big data to monitor changes in park use (e.g., Venter et al., 2020). Google\u27s Community Mobility Reports repre-sent a dataset with significant potential in this re-gard. Released in April 2020, these reports were gen-erated on the hypothesis that aggregated, anony-mized data could be helpful [to] make critical deci-sions to combat COVID-19 (Fitzpatrick & DeSalvo, 2020, para. 1). The heading on the reports\u27 website asks browsers to see how your community is mov-ing around differently due to COVID-19 (Google 2020b). The data released through the reports are generated from aggregated, anonymized sets of data from [Google] users who have turned on the Lo-cation History setting, which is off by default (Google 2020b)

Testing The Mean For Business Data: Should One Use The Z-Test, T-Test, F-Test, The Chi-Square Test, Or The P-Value Method?

In testing the mean of a population or comparing the means from two populations. There are several statistics available: the t-test, z-test, F-test and the chi-square test. Both the t-test and the z-test are usually used for continuous populations, and the chi-square test is used for categorical data. The F-test is used for comparing more than two means. In this paper we will discuss: 1) the conditions on using these tests; 2) the relationship among these test; and 3) illustration of the p-values of these tests by graphs. Some concluding remarks will be provided

A MATLAB-Aided Method For Teaching Calculus-Based Business Mathematics

MATLAB is a powerful package for numerical computation. MATLAB contains a rich pool of mathematical functions and provides flexible plotting functions for illustrating mathematical solutions. The course of calculus-based business mathematics consists of two major topics: 1) derivative and its applications in business; and 2) integration and its applications in business. Both topics involve various mathematical functions that may scare many business students. Fortunately, MATLAB provides an easy solution to handling the derivative and integration of various mathematical functions. With the help of MATLAB, all elementary formulas for derivative and integration in the textbooks of calculus-based business mathematics become less important to those students who have difficulty in learning and using mathematical formulas to find solutions to quantitative business problems. With the wide availability of various business data bases including the MATLAB package in the Samuel S. Bergami, Jr. Learning Center for Finance and Technology at the University of New Haven, in this paper, we illustrate how to use MATLAB to help students’ learning of calculus-based business mathematics and apply the calculus principles to find solutions to real quantitative business problems. Our experience shows that MATLAB greatly saves students’ efforts in learning difficult and pure calculus formulas and it is easy for business students to acquire the basic internal functions in using MATLAB

Upper Ocean Physical and Biological Response to Typhoon Cimaron (2006) in the South China Sea

The physical dynamic and biological response processes to Typhoon Cimaron (2006) in the South China Sea are investigated through the three‐dimensional Regional Ocean Modeling System (ROMS). For sea surface temperatures, ROMS achieves a correlation of more than 0.84, with respect to satellite observations, indicating a generally high level of skill for simulating the sea surface temperature variations during Typhoon Cimaron (2006). However, detailed analysis shows that ROMS underestimates the sea surface temperature cooling and mixed layer deepening because of insufficient mixing in the model simulations. We show that the simulation accuracy can be enhanced by adding a wave‐induced mixing term (BV) to the nonlocal K‐profile parameterization (KPP) scheme. Simulation accuracy is needed to investigate nutrients, which are deeply entrained to the oligotrophic sea surface layer by upwelling induced by Typhoon Cimaron, and which plays a remarkable role in the subsequent phytoplankton bloom. Simulations show that the phytoplankton bloom was triggered 5 days after the passage of the storm. The surface ocean was restored to its equilibrium ocean state by about 10–20 days after the typhoon\u27s passage. However, on this time‐scale, the resulting concentrations of nitrate and chlorophyll a remained higher than those in the pre-typhoon equilibrium

Impact Of Chinas Yuan Revaluation

In the past two years, the Bush Administration, members of Congress and a few senators, such as Sen. Charles Schumer of New York and Sen. Lindsey Graham of South Carolina and others have put pressure on China to abandon her peg the Chinese Yuan to the U.S. Dollar. These efforts finally succeed. On July 21, 2005, Peoples Bank of China announced that the Chinese Yuan is no long pegged solely to the U.S. dollar, instead, the Yuan is now linked to a basket of currencies, including Dollar, the Euro, the Japanese Yen, the Korean Won and other currency from any country that had at least $10 billion trade with China. In this paper we ask the questions: what is the impact of China Yuan revaluation decision? Does this means that China no long stockpile U.S. Treasury Bills? The American consumers can no longer benefit from the low-priced consumer goods manufactured in China? And in what way the U.S. economy will be affected, if at all

Storage hexamer utilization in two lepidopterans: differences correlated with the timing of egg formation

Most insects produce two or more storage hexamers whose constituents and developmental profiles are sufficiently different to suggest specialization in the ways that they support metamorphosis and reproduction. Hexamerin specializations are compared here in the Cecropia moth (Hyalophora cecropia), which produces eggs during the pupal-adult molt, and the Monarch butterfly (Danaus plexippus), which produces eggs under long-day conditions after adult eclosion. In both sexes of both species, reserves of arylphorin (ArH) were exhausted by the end of metamorphosis. In Cecropia, the same was true for the high-methionine hexamerins, V-MtH and M-MtH. But in short day Monarch females 20–30% of the pupal reserves of V-MtH and M-MtH survived metamorphosis, persisting until long-day conditions were imposed to stimulate egg formation. Differences in storage sites have been documented in other lepidopterans, with MtH reserves being found primarily in fat body protein granules and the ArH reserve being found primarily in the hemolymph. Similar differences could explain how a fraction of the MtH's, but not of ArH, escapes utilization during metamorphosis in a species with post-eclosion egg formation. No differences in utilization schedules were detected between V- and M-MtH, despite divergent compositions and antigenic reactivity

Storage hexamer utilization in Manduca sexta

In preparing for metamorphosis insects store in their hemolymph and fat bodies a major nutrient reserve of 500-kDa hexamerins. At least three hexamerins serve this function in Lepidoptera, including arylphorin (ArH) and two high methionine proteins (M-MtH and V-MtH). Six day-old adults of Manduca sexta Abbreviation: / ArH: arylphorin M-MtH: moderately high methionine hexamerin PBS: phosphate buffered saline V-MtH: very high methionine hexamerin Vg: vitellogeni

Testing The Mean For Business Data: Should One Use The Z-Test, T-Test, F-Test, The Chi-Square Test, Or The P-Value Method?

Purpose – The overall purpose of this research is to discuss the relationship among the tests for population mean that are taught in the Business Statistics course for business majors. Design/methodology/approach – The approach to this study is to describe the types of business data according to one-sample, two-sample, and multi-sample cases first and then combine tests for categorical data with tests for continuous data into a unified format on testing the mean of a population. Under this unified format, we summarize the methodology on the topic of testing the mean in business statistics course. Findings – One of the important topics in testing hypothesis in the business statistics course is testing the mean of a population or comparing the means from two populations. There are several statistics available for this purpose in existing textbooks for the business statistics course. Based on our experience in teaching the business statistics course, we observe that many business students often get confused about which one to use for a given business data set with some specific purpose. In this paper we will summarize some comments or our experience on teaching business students how to use these tests in various business applications by focusing on the following points: 1) the conditions on using these tests; 2) the relationship among these tests; and 3) illustration of the p-values of these tests by graphs. Some concluding remarks will be provided. Practical implications – The discussions on various tests for the population mean for business data in this paper set up a bridge for connecting different tests into one unified format. This demonstrates that most tests taught in the Business Statistics course actually belong to the topic of testing the mean value. Therefore, there is usually more than one method that can be used for the same purpose and one can choose whichever that is available in statistical tables or software programs. Originality/value – The study in this paper clarifies the equivalence relationship among various tests for the population mean that are commonly taught in Business Statistics course for business majors. The equivalence relationship has not been pointed out or mentioned in currently available textbooks for Business Statistics course. This study can provide business students with better understanding in the major topic in testing hypothesis in Business Statistics course. Keywords – Chi-square test, F-test, t-test, z-test Acknowledgment: This work was supported by a University of New Haven 2005 Summer Faculty Fellowship