Study of Weight Gain in Freshman Students at the University of Arkansas

This study was designed to examine the poor (non-nutritional) food choices that college freshman make when living on-campus and eating at on-campus dining facilities. These poor choices lead to excessive weight gain, eating disorders, declining health and wellness, and mental health issues (i.e. depression, anxiety, lack of self-confidence). These side effects can lead to a less than desirable 1st year college experience and lack of academic success. Based on these concerns, different investigations have been performed to determine the causes of this phenomena. Given adolescent weight gain is highly linked to being overweight and obesity in adults, a better understanding of university student weight gain is crucial if we are to combat the rising adult obesity. This study found that selection and amount of students’ food consumption are valuable for scheduling on-campus dining/Greek house menus and future plans for freshmen’ consumption patterns. It is important for college students to eat a healthy diet as it improves energy, memory and focus. Additionally, students who eat a healthy diet are less likely to contract illnesses as a nutrient-rick diet that is low in processed foods, and sugars while high in vegetable intake assists in creating a robust immune system. Furthermore, there is significant research that shows a correlation between dietary habits and anxiety and depression. Universities cannot control their students’ sleep patterns or physical activity habits, but they can direct students and assist them with healthy eating patterns by providing leadership, education, and more health conscious on-campus dining menus and options. This will assist students in making choices that sway them from choosing cheap, unhealthy foods by providing quality, convenient and healthy options

Study of Weight Gain in Freshman Students at the University of Arkansas

This study was designed to examine the poor (non-nutritional) food choices that college freshman make when living on-campus and eating at on-campus dining facilities. These poor choices lead to excessive weight gain, eating disorders, declining health and wellness, and mental health issues (i.e. depression, anxiety, lack of self-confidence). These side effects can lead to a less than desirable 1st year college experience and lack of academic success. Based on these concerns, different investigations have been performed to determine the causes of this phenomena. Given adolescent weight gain is highly linked to being overweight and obesity in adults, a better understanding of university student weight gain is crucial if we are to combat the rising adult obesity. This study found that selection and amount of students’ food consumption are valuable for scheduling on-campus dining/Greek house menus and future plans for freshmen’ consumption patterns. It is important for college students to eat a healthy diet as it improves energy, memory and focus. Additionally, students who eat a healthy diet are less likely to contract illnesses as a nutrient-rick diet that is low in processed foods, and sugars while high in vegetable intake assists in creating a robust immune system. Furthermore, there is significant research that shows a correlation between dietary habits and anxiety and depression. Universities cannot control their students’ sleep patterns or physical activity habits, but they can direct students and assist them with healthy eating patterns by providing leadership, education, and more health conscious on-campus dining menus and options. This will assist students in making choices that sway them from choosing cheap, unhealthy foods by providing quality, convenient and healthy options

The reactive and dissociative behavior of size-selected clusters and ion complexes in the gas phase

Molecular complexation properties of several types of size-selected ions are examined in the gas phase by mass spectrometric techniques. Transition metal oxide clusters of (MoO₃)[subscript n]⁻ where n = 2-12 and (WO₃)[subscript n]⁻ extending to n = 8 are generated by field and laser desorption, and electron capture in the negative ionization mode. The structures of these clusters are characterized by low energy collision induced dissociation (CID). The clusters dissociate by the neutral loss of metal trioxide units. Reactions of ligands such as ethylene oxide and cyclohexene sulfide are examined to distinguish the structural variations of the clusters. The systematic evaluation of the size effect in molecular recognition processes is examined by association reactions of crown ether macrocyclic hosts with alkali metal ions and primary amine substrates. Ion complexes of crown ethers with two different alkali metals are formed by liquid secondary ion mass spectrometry. These complexes produce crown ether/alkali metal adduct ions upon gas-phase isolation and high energy dissociation. The abundance ratios of product ions are correlated to the alkali metal ion selectivites of the crown ether. The selectivity of 18-crown-6 follows the order of Na⁺ ≥ K⁺ > Li⁺ > Rb⁺ > Cs⁺, and the concept of 'maximum contact point' (MCP) describes this order. In contrast, the high energy activation of alkali metal ion adducts of crown ethers results in homolytic cleavages of C-C or C-O bonds. The metastable ion dissociation of hydrogen bonded complexes of crown ethers with ammonium or methyl-ammonium shows a stability order of 21-crown-7 > 18-crown-6 > 15-crown-5. High energy CID of the ion complexes proceeds by cavity size dependent intramolecular ring opening reactions of the host. Complexes of crown ethers with methyl- and tosyl-hydrazinium ions dissociate by covalent bond cleavages of the N-N or N-S bonds of the guest substrates. Finally, reactions of perfluorinated cyclic or bicyclic ether anions with O₂ are examined as models of oxygen transport by perfluorinated compounds. These complexes show binding strengths that reflect both the topological and chemical nature of the hosts.Chemistr

A descent subgradient method using Mifflin line search for nonsmooth nonconvex optimization

We propose a descent subgradient algorithm for minimizing a real function, assumed to be locally Lipschitz, but not necessarily smooth or convex. To find an effective descent direction, the Goldstein subdifferential is approximated through an iterative process. The method enjoys a new two-point variant of Mifflin line search in which the subgradients are arbitrary. Thus, the line search procedure is easy to implement. Moreover, in comparison to bundle methods, the quadratic subproblems have a simple structure, and to handle nonconvexity the proposed method requires no algorithmic modification. We study the global convergence of the method and prove that any accumulation point of the generated sequence is Clarke stationary, assuming that the objective $f$ is weakly upper semismooth. We illustrate the efficiency and effectiveness of the proposed algorithm on a collection of academic and semi-academic test problems

Analysis of Genetic Relationship Among 11 Iranian Ethnic Groups with Bayesian Multidimensional Scaling Using HLA Class II Data

Background: The key feature of Bayesian methods is their lack of dependence on defaults necessary for classical statistics. Because of the high volume of simulation, Bayesian methods have a high degree of accuracy. They are efficient in data mining and analyzing large volumes of data, and can be upgraded by entering new data. Objective: We used Bayesian multidimensional scaling (MDS) to analyze the genetic relationships among 11 Iranian ethnic groups based on HLA class II data. Method: Allele frequencies of three HLA loci from 816 unrelated individuals belonging to 11 Iranian ethnic groups were analyzed by Bayesian MDS using R and WinBUGS software. Results: like the results of correspondence analysis as a prototype of classical MDS analysis, the results of Bayesian MDS also showed Arabs from Famur, Balochis, Zoroastrians and Jews to be separate from other Iranian ethnic groups. Decreases stress in Bayesian MDS method compared to classical method revealed the accuracy of Bayesian MDS for HLA data analyses. Conclusion: This study reports the first application of Bayesian multidimensional scaling to HLA data analysis with Nei's DA genetic distances. Stress reduction in Bayesian MDS compared to classical MDS showed that the Bayesian approach can improve the accuracy of genetic data analysis

Investigating the Nature of Interaction at Elementary and Intermediate EFL Classes

Classroom research mainly concentrates on what happens in classrooms and tries to explore these events. One aspect that has been under investigation in this area is 'classroom interaction'. The current work was inspired by Kumaravadivelu's (2006) classification of interaction types: textual, interpersonal and ideational interaction. The main objective of the present study was to investigate the nature of interaction types proposed by Kumaravadivelu, the extent of their occurrence and their contribution to L2 development regarding two levels of Elementary and Intermediate. During data collection process, 20 sessions of EFL classes in a Language Institute were observed and the main events regarding the types of interaction under investigation were written in the form of field notes and audio-recorded for later reflection. The results were analyzed both qualitatively and quantitatively. The quantitative data from the observation were analyzed through inferential statistics. Qualitative analysis of data was carried out through transcription of important events. The quantitative results indicated that the difference between means of time spent on three types of interaction regarding two levels was not significant. For the qualitative analysis, the nature of these three types of interaction was compared based on two levels and some similarities and differences were found