The Effect of Molar Peroxide Ratio on the Oxidation of Bisphenol A in an Ultraviolet Light Emitting Diode/Hydrogen Peroxide Advanced Oxidation Process

Bisphenol A is a compound widely used in industry that is detrimental to human health and ecological systems. Ultraviolet light emitting diodes and hydrogen peroxide can be combined t produces hydroxyl radicals. These highly reactive radicals have the potential to degrade contaminants in water. This research utilized 50, 100, 250, 500, and 1000:1 H2O2:BPA molar ratios for analysis. These results illustrated that the reactions at the 50, 100, and 250:1 ratios were hydrogenperoxide limited. The 1000:1 results exhibited evidence of radical scavenging that limited the degradation of BPA

Personality and Programming

Information systems students continue to struggle to successfully complete computer programming classes. Leaming how to program is difficult, and failure and attrition rates in college level programming classes remain at an unacceptably high rate. Since many IS students take a programming course as part of their program of study, IS educators should better understand why IS students tend to achieve low success rates in programming courses and what can be done to improve success rates. Little research to date has addressed potential reasons for student failure in programming principles courses. Many educators simply assume that high failure rates are acceptable - that computer programming is difficult and some students simply will not succeed. Some researchers have studied personality as a predictor of success in computer programming courses. However, no studies have attempted to gather cognitive profiles and match performance to profile type exhibited. In our study, we identified the primary cognitive profile in a sample of beginning programming students in a southeastern university and matched profile to final average in Programming Principles I. Intuitive thinkers tended to perform better in Programming Principles I than sensor feelers. We found no other differences in performance between profile types. We recommend instructional strategies that may be used to reach fully motivated and intellectually capable sensor feelers, while not detracting from the learning experience of the other profiles

Personality as a Predictor of Student Success in Programming Principles

Large numbers of college students continue to fail to successfully complete programming principles courses. However, little research has addressed potential reasons for student failure. Many educators simply assume that high failure rates are acceptable – that computer programming is difficult and some students simply “don’t get it.” Some researchers (i.e., Bishop-Clark & Wheeler, 1994; Carland & Carland, 1990) have studied personality as a predictor of success in computer programming courses. However, with the exception of Woszczynski & Guthrie (2003), few studies have attempted to gather cognitive profiles (Krause, 2000) and match performance to profile type exhibited. Krause’s work shows that students with identified profiles can apply certain study skills to improve the probability of success in the classroom, and Woszczynski & Guthrie (2003) extended this research to the programming classroom, identifying underperforming cognitive profile groups. This study identified the primary cognitive profile of 236 students in a programming principles course at a southeastern university and matched profile to final average in programming principles I. Overall, intuitive thinkers (NT) tended to perform better in programming principles I than sensor feelers (SF). We found no other differences in performance between other paired profiles. We recommend a number of interventions to reach underperforming groups

Assembly of seed-associated microbial communities within and across successive plant generations

Background and aims Seeds are involved in the transmission of microorganisms from one plant generation to another and consequently may act as the initial inoculum source for the plant microbiota. In this work, we assessed the structure and composition of the seed microbiota of radish (Raphanus sativus) across three successive plant generations. Methods Structure of seed microbial communities were estimated on individual plants through amplification and sequencing of genes that are markers of taxonomic diversity for bacteria (gyrB) and fungi (ITS1). The relative contribution of dispersal and ecological drift in inter-individual fluctuations were estimated with a neutral community model. Results Seed microbial communities of radish display a low heritability across plant generations. Fluctuations in microbial community profiles were related to changes in community membership and composition across plant generations, but also to variation between individual plants. Ecological drift was an important driver of the structure of seed bacterial communities, while dispersal was involved in the assembly of the fungal fraction of the seed microbiota. Conclusions These results provide a first glimpse of the governing processes driving the assembly of the seed microbiota

Interpreting 16S metagenomic data without clustering to achieve sub-OTU resolution

The standard approach to analyzing 16S tag sequence data, which relies on clustering reads by sequence similarity into Operational Taxonomic Units (OTUs), underexploits the accuracy of modern sequencing technology. We present a clustering-free approach to multi-sample Illumina datasets that can identify independent bacterial subpopulations regardless of the similarity of their 16S tag sequences. Using published data from a longitudinal time-series study of human tongue microbiota, we are able to resolve within standard 97% similarity OTUs up to 20 distinct subpopulations, all ecologically distinct but with 16S tags differing by as little as 1 nucleotide (99.2% similarity). A comparative analysis of oral communities of two cohabiting individuals reveals that most such subpopulations are shared between the two communities at 100% sequence identity, and that dynamical similarity between subpopulations in one host is strongly predictive of dynamical similarity between the same subpopulations in the other host. Our method can also be applied to samples collected in cross-sectional studies and can be used with the 454 sequencing platform. We discuss how the sub-OTU resolution of our approach can provide new insight into factors shaping community assembly.Comment: Updated to match the published version. 12 pages, 5 figures + supplement. Significantly revised for clarity, references added, results not change

Finite Element Modeling of Resonance in Polycrystalline Materials for Resonance Ultrasound Spectroscopy

Validation of models that predict the performance of aerospace engine materials depends on the ability to obtain accurate single crystal elastic constants. Resonance Ultrasound Spectroscopy (RUS) is a nondestructive technique in which the natural resonances of a material are utilized to obtain these constants. Traditional RUS utilizes an analytic approach to determine the resonance frequencies of a specimen given an initial guess set of elastic constants. A nonlinear optimization process then fits the elastic constants to experimentally measured data. This approach is limited both in its ability to handle specimens with complex geometry and to handle polycrystalline materials. These more complex scenarios can be approached by utilizing a finite element forward model to obtain sample resonances. A finite element forward model is being developed utilizing COMSOL Multiphysics to compute specimen resonance frequencies. Elastic constants are obtained utilizing a bounded nonlinear optimization routine in MATLAB by way of COMSOL\u27s LiveLink for MATLAB interface. Validation of this forward model has been performed on single crystal specimens, including a nickel superalloy parallelepiped and a fused silica cylinder with a chamfer, ultimately producing lower residual error after optimization than the traditional RUS approach. Model validation is also being performed on a Nickel Aluminide (NiAl) bicrystal. This paper presents the details of this validation process. Also presented is an examination of error sources and the impact they can play in the ability to accurately obtain elastic constants