A nested mixture model for protein identification using mass spectrometry

Mass spectrometry provides a high-throughput way to identify proteins in biological samples. In a typical experiment, proteins in a sample are first broken into their constituent peptides. The resulting mixture of peptides is then subjected to mass spectrometry, which generates thousands of spectra, each characteristic of its generating peptide. Here we consider the problem of inferring, from these spectra, which proteins and peptides are present in the sample. We develop a statistical approach to the problem, based on a nested mixture model. In contrast to commonly used two-stage approaches, this model provides a one-stage solution that simultaneously identifies which proteins are present, and which peptides are correctly identified. In this way our model incorporates the evidence feedback between proteins and their constituent peptides. Using simulated data and a yeast data set, we compare and contrast our method with existing widely used approaches (PeptideProphet/ProteinProphet) and with a recently published new approach, HSM. For peptide identification, our single-stage approach yields consistently more accurate results. For protein identification the methods have similar accuracy in most settings, although we exhibit some scenarios in which the existing methods perform poorly.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS316 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

An investigation into the numerical prediction of boundary layer transition using the K.Y. Chien turbulence model

Assessments were made of the simulation capabilities of transition models developed at the University of Minnesota, as applied to the Launder-Sharma and Lam-Bremhorst two-equation turbulence models, and at The University of Texas at Austin, as applied to the K. Y. Chien two-equation turbulence model. A major shortcoming in the use of the basic K. Y. Chien turbulence model for low-Reynolds number flows was identified. The problem with the Chien model involved premature start of natural transition and a damped response as the simulation moved to fully turbulent flow at the end of transition. This is in contrast to the other two-equation turbulence models at comparable freestream turbulence conditions. The damping of the transition response of the Chien turbulence model leads to an inaccurate estimate of the start and end of transition for freestream turbulence levels greater than 1.0 percent and to difficulty in calculating proper model constants for the transition model

Re-Queering the Trans Binary: Gender Nonconforming Individuals’ Experiences in Counseling and Therapeutic Settings

This study sought to unearth the narratives of gender nonconforming (GNC) individuals’ experiences of mental health services. The term gender nonconforming refers to individuals who do not identify with a strictly male or female concept of gender identity. There is an insubstantial research that has been conducted into the provision of effective mental health services for gender nonconforming individuals. Most of the studies in the literature review used the term transgender to highlight gender minority experience of counseling. This study used gender nonconforming to separate from this terminology confusion. Individuals who identify with the identity label of transgender can be gender nonconforming, but not always is this the case due to the varied individual meanings of these terminology. In order to uncover the narrative of the target population, the participants of the study were purposefully selected to include only those who hold a nonbinary definition of their gender identity. This hermeneutic phenomenological study was informed by Queery theory and Hycner’s (1985) guidelines to phenomenological research. The study was conducted with a total of nine interviews who identified with the study’s definition of gender nonconforming. The results of the study identified themes that address the participants queer identity development, internal and external barriers for therapy, and factors that promoted positive and negative experiences of counseling. The limitations, implications of the study, suggestions for future research, and questions for future research are included

Evaluation of the Goal System™ Version 2.2 Solution Method for Interactive Constraint Scheduling Situations

THE GOAL SYSTEM™ version 2.2 is the latest in a lineage that includes Optimized Production Technology (OPT) and DISASTER™. Earlier work with DISASTER™ revealed potential shortcomings with sequential schedule building algorithms when multiple interactive constraints exist. Since THE GOAL SYSTEM™ version 2.2 has a capacity for simultaneous schedule building, this study evaluated differences between the two algorithms. Using benchmark scheduling problems developed during the earlier evaluation of DISASTER™, a set of THE GOAL SYSTEM™ solutions was created and compared quantitatively to both DISASTER™ solutions and solutions which optimally minimize maximum tardiness. A broad set of performance measurement criteria were also used to obtain a more comprehensive evaluation of the solutions. Performance of THE GOAL SYSTEM™ was quite good with respect to maximum tardiness. Performance with respect to average flow time, percentage of tardy jobs, and total days late for a set of job orders was markedly poorer than the DISASTER™ solutions. The results were unexpected, since the simultaneous scheduling algorithm is less restricted in its options for schedule creation. The author concluded that the simultaneous feature of THE GOAL SYSTEM™ was better suited for conflict resolution during an iterative process than as a stand alone scheduling algorithm

Symphony Orchestra Concerto Competition Concert

Kennesaw State University School of Music presents Concerto Competition Concert featuring competition winner Theresa Stephens, clarinet.https://digitalcommons.kennesaw.edu/musicprograms/1618/thumbnail.jp

The great Polar controversy: Dr. Cook, Mt.McKinley, and the quest for the Poles

pp. 377-40