Job Expectations, Job Preference, and Learning Expectations of Apparel Merchandising and Design College Students

The majority of current college students represent Gen Y (born between 1977 and 1992). The current workplace population includes 42% of Gen Yers, 31% of baby boomers, and 27% of Gen Xers; Gen Yers will make up 75% of the American workforce by 2025 (Treuren & Anderson, 2010). As they are just starting to impact the workplace, it is critical to understand the characteristics of Gen Y that might influence workplace environment

Study of Single W production in e-gamma collisions through the decay lepton spectrum to probe gamma-WW couplings

We investigate the effect of anomalous gamma-W-W couplings in e-gamma --> nu W through the angular and energy spectrum of the secondary leptons. Within the narrow-width approximation, a semi-analytical study of the secondary lepton energy-angle double distribution is considered. Utility of observables derived from this is demonstrated by considering the anomalous coupling, delta-kappa-gamma. Results of our investigation for typical ILC machine considered at Ecm = 300-1000 GeV re-affirms potential of this collider as a precision machine.Comment: Typos corrected, discussion added in section 2 for clarity, error in fig.2 corrected, figures 7 and 8 replaced with better resolutio

Global Competence and Sustainability in the Apparel and Textile curriculum

n response to the changing global climate and the growing ethnic and cultural diversity in the U.S., there is a widely recognized need to add a global and cultural competency dimension to our educational programs. In addition to global learning, sustainability focused education has increased in importance since the UN’s declaration of education for sustainable development (Connell & Kozar, 2012). However, despite the need for such educational opportunities, few studies have examined the current curriculum to determine if these two critical issues have been addressed. Therefore, the purpose of this study is to examine the current apparel and textile curriculum in the U.S. higher education system and to explore the extent to which each course in the apparel and textile field has implemented global competence and sustainability in its course objectives

Light and neutron scattering studies of the OH stretching band in liquid and supercritical water

The hydrogen projected OH stretching density of states has been determined by an inelastic neutron scattering experiment in liquid and supercritical water, The results, compared with new measurements of the isotropic Raman spectra at the same state conditions, support the interpretation of the Raman spectra in terms of superposition of the allowed nu(1) band with the overtone of the nu(2) band. (C) 1998 American Institute of Physics

Combining Several ASR Outputs in a Graph-Based SLU System

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-25751-8_66In this paper, we present an approach to Spoken Language Understanding (SLU) where we perform a combination of multiple hypotheses from several Automatic Speech Recognizers (ASRs) in order to reduce the impact of recognition errors in the SLU module. This combination is performed using a Grammatical Inference algorithm that provides a generalization of the input sentences by means of a weighted graph of words. We have also developed a specific SLU algorithm that is able to process these graphs of words according to a stochastic semantic modelling.The results show that the combinations of several hypotheses from the ASR module outperform the results obtained by taking just the 1-best transcriptionThis work is partially supported by the Spanish MEC under contract TIN2014-54288-C4-3-R and FPU Grant AP2010-4193.Calvo Lance, M.; Hurtado Oliver, LF.; García-Granada, F.; Sanchís Arnal, E. (2015). Combining Several ASR Outputs in a Graph-Based SLU System. En Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer. 551-558. https://doi.org/10.1007/978-3-319-25751-8_66S551558Bangalore, S., Bordel, G., Riccardi, G.: Computing consensus translation from multiple machine translation systems. In: ASRU, pp. 351–354 (2001)Benedí, J.M., Lleida, E., Varona, A., Castro, M.J., Galiano, I., Justo, R., de Letona, I.L., Miguel, A.: Design and acquisition of a telephone spontaneous speech dialogue corpus in Spanish: DIHANA. In: LREC, pp. 1636–1639 (2006)Bonneau-Maynard, H., Lefèvre, F.: Investigating stochastic speech understanding. In: IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), pp. 260–263 (2001)Calvo, M., García, F., Hurtado, L.F., Jiménez, S., Sanchis, E.: Exploiting multiple hypotheses for multilingual spoken language understanding. In: CoNLL, pp. 193–201 (2013)Fiscus, J.G.: A post-processing system to yield reduced word error rates: recognizer output voting error reduction (ROVER). In: 1997 IEEE Workshop on Automatic Speech Recognition and Understanding, pp. 347–354 (1997)Hahn, S., Dinarelli, M., Raymond, C., Lefèvre, F., Lehnen, P., De Mori, R., Moschitti, A., Ney, H., Riccardi, G.: Comparing stochastic approaches to spoken language understanding in multiple languages. IEEE Transactions on Audio, Speech, and Language Processing 6(99), 1569–1583 (2010)Hakkani-Tür, D., Béchet, F., Riccardi, G., Tür, G.: Beyond ASR 1-best: Using word confusion networks in spoken language understanding. Computer Speech & Language 20(4), 495–514 (2006)He, Y., Young, S.: Spoken language understanding using the hidden vector state model. Speech Communication 48, 262–275 (2006)Larkin, M.A., Blackshields, G., Brown, N.P., Chenna, R., McGettigan, P.A., McWilliam, H., Valentin, F., Wallace, I.M., Wilm, A., Lopez, R., Thompson, J.D., Gibson, T.J., Higgins, D.G.: ClustalW and ClustalX version 2.0. Bioinformatics 23(21), 2947–2948 (2007)Segarra, E., Sanchis, E., Galiano, M., García, F., Hurtado, L.: Extracting Semantic Information Through Automatic Learning Techniques. IJPRAI 16(3), 301–307 (2002)Tür, G., Deoras, A., Hakkani-Tür, D.: Semantic parsing using word confusion networks with conditional random fields. In: INTERSPEECH (2013

High-entropy energy materials: Challenges and new opportunities

The essential demand for functional materials enabling the realization of new energy technologies has triggered tremendous efforts in scientific and industrial research in recent years. Recently, high-entropy materials, with their unique structural characteristics, tailorable chemical composition and correspondingly tunable functional properties, have drawn increasing interest in the fields of environmental science and renewable energy technology. Herein, we provide a comprehensive review of this new class of materials in the energy field. We begin with discussions on the latest reports on the applications of high-entropy materials, including alloys, oxides and other entropy-stabilized compounds and composites, in various energy storage and conversion systems. In addition, we describe effective strategies for rationally designing high-entropy materials from computational techniques and experimental aspects. Based on this overview, we subsequently present the fundamental insights and give a summary of their potential advantages and remaining challenges, which will ideally provide researchers with some general guides and principles for the investigation and development of advanced high-entropy materials

Multi-scale initial conditions for cosmological simulations

We discuss a new algorithm to generate multi-scale initial conditions with multiple levels of refinements for cosmological "zoom-in" simulations. The method uses an adaptive convolution of Gaussian white noise with a real space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first (1LPT) or second order Lagrangian perturbation theory (2LPT). The new algorithm achieves RMS relative errors of order 10^(-4) for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches. In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier-space induced interference ringing. An optional hybrid multi-grid and Fast Fourier Transform (FFT) based scheme is introduced which has identical Fourier space behaviour as traditional approaches. Using a suite of re-simulations of a galaxy cluster halo our real space based approach is found to reproduce correlation functions, density profiles, key halo properties and subhalo abundances with per cent level accuracy. Finally, we generalize our approach for two-component baryon and dark-matter simulations and demonstrate that the power spectrum evolution is in excellent agreement with linear perturbation theory. For initial baryon density fields, it is suggested to use the local Lagrangian approximation in order to generate a density field for mesh based codes that is consistent with Lagrangian perturbation theory instead of the current practice of using the Eulerian linearly scaled densities.Comment: 22 pages, 24 figures. MNRAS in press. Updated affiliation

Dark Matter Halo Growth II: Diffuse Accretion and its Environmental Dependence

Dark matter haloes in Lambda CDM simulations grow by mergers with other haloes as well as accretion of "diffuse" non-halo material. We quantify the mass growth rates via these two processes, dM_mer/dt and dM_dif/dt, and their dependence on halo environment using the ~500,000 haloes in the Millennium simulation. Adopting a local mass density parameter as a measure of halo environment, we find the two rates show strong but opposite environmental dependence, with mergers playing an increasingly important role for halo growths in overdense regions and diffuse accretion dominating growth in voids. This behaviour is independent of the mass cuts used to define haloes vs non-haloes. For galaxy-scale haloes, these two opposite correlations largely cancel out, but a weak environmental dependence remains that results in a slightly lower mean total growth rate, and hence an earlier mean formation redshift, for haloes in denser regions. The mean formation redshift of the ~5000 cluster-mass haloes, on the other hand, appears to have no correlation with halo environment. The origin of the positive correlation of dM_mer/dt with local density can be traced to the surrounding mass reservoir outside the haloes, where more progenitor haloes are available in denser regions. The negative correlation of dM_dif/dt with density, however, is not explained by the available diffuse mass in the reservoir, which is in fact larger in denser regions. The non-halo component may therefore be partially comprised of truly diffuse dark matter particles that are dynamically hotter and are accreted at a suppressed rate in denser regions. We also discuss the implications of these results for how to modify the Extended Press-Schechter model of halo growth, which in its original form does not predict environmental dependence.Comment: 15 pages, 9 figures, accepted in MNRA

Elevated levels of circulating microRNA-200 family members correlate with serous epithelial ovarian cancer

Background: There is a critical need for improved diagnostic markers for high grade serous epithelial ovarian cancer (SEOC). MicroRNAs are stable in the circulation and may have utility as biomarkers of malignancy. We investigated whether levels of serum microRNA could discriminate women with high-grade SEOC from age matched healthy volunteers.Methods: To identify microRNA of interest, microRNA expression profiling was performed on 4 SEOC cell lines and normal human ovarian surface epithelial cells. Total RNA was extracted from 500 μL aliquots of serum collected from patients with SEOC (n = 28) and age-matched healthy donors (n = 28). Serum microRNA levels were assessed by quantitative RT-PCR following preamplification. Results: microRNA (miR)-182, miR-200a, miR-200b and miR-200c were highly overexpressed in the SEOC cell lines relative to normal human ovarian surface epithelial cells and were assessed in RNA extracted from serum as candidate biomarkers. miR-103, miR-92a and miR -638 had relatively invariant expression across all ovarian cell lines, and with small-nucleolar C/D box 48 (RNU48) were assessed in RNA extracted from serum as candidate endogenous normalizers. No correlation between serum levels and age were observed (age range 30-79 years) for any of these microRNA or RNU48. Individually, miR-200a, miR-200b and miR-200c normalized to serum volume and miR-103 were significantly higher in serum of the SEOC cohort (P < 0.05; 0.05; 0.0005 respectively) and in combination, miR-200b + miR-200c normalized to serum volume and miR-103 was the best predictive classifier of SEOC (ROC-AUC = 0.784). This predictive model (miR-200b + miR-200c) was further confirmed by leave one out cross validation (AUC = 0.784). Conclusions: We identified serum microRNAs able to discriminate patients with high grade SEOC from age-matched healthy controls. The addition of these microRNAs to current testing regimes may improve diagnosis for women with SEOC. © 2012 Kan et al.; licensee BioMed Central Ltd

Dissecting the genetic basis for seed coat mucilage heteroxylan biosynthesis in plantago ovata using gamma irradiation and infrared spectroscopy

Seeds from the myxospermous species Plantago ovata release a polysaccharide-rich mucilage upon contact with water. This seed coat derived mucilage is composed predominantly of heteroxylan (HX) and is utilized as a gluten-free dietary fiber supplement to promote human colorectal health. In this study, a gamma-irradiated P. ovata population was generated and screened using histological stains and Fourier Transform Mid Infrared (FTMIR) spectroscopy to identify putative mutants showing defects in seed coat mucilage HX composition and/or structure. FTMIR analysis of dry seed revealed variation in regions of the IR spectra previously linked to xylan structure in Secale cereale (rye). Subsequent absorbance ratio and PCA multivariate analysis identified 22 putative mutant families with differences in the HX IR fingerprint region. Many of these showed distinct changes in the amount and subtle changes in structure of HX after mucilage extrusion, while 20% of the putative HX mutants identified by FTMIR showed no difference in staining patterns of extruded mucilage compared to wild-type. Transcriptional screening analysis of two putative reduced xylan in mucilage (rxm) mutants, rxm1 and rxm3, revealed that changes in HX levels in rxm1 correlate with reduced transcription of known and novel genes associated with xylan synthesis, possibly indicative of specific co-regulatory units within the xylan biosynthetic pathway. These results confirm that FTMIR is a suitable method for identifying putative mutants with altered mucilage HX composition in P. ovata, and therefore forms a resource to identify novel genes involved in xylan biosynthesis.Matthew R. Tucker, Chao Ma, Jana Phan, Kylie Neumann, Neil J. Shirley, Michael G. Hahn, Daniel Cozzolino and Rachel A. Burto