HOUSEHOLD DEMAND FOR FINFISH: A GENERALIZED DOUBLE-HURDLE MODEL

This study estimates household demand for finfish in the United States using a limited dependent variable model that accounts for both participation and consumption decisions and also accommodates nonnormal heteroskedastic errors. Results suggest that own-price elasticity is near unitary and income elasticity is small. Price of finfish, shopping frequency, Northeast, Black and other non-Whites, and the life-cycle variable “"young, single, no children”" are they key factors that affect significantly both the probability of participation and the level of finfish consumption. Furthermore, a variable may exert opposite effects on the probability and level of consumption.Consumer/Household Economics, Demand and Price Analysis,

CROSS-SECTIONAL ESTIMATION OF U.S. DEMAND FOR BEEF PRODUCTS: A CENSORED SYSTEM APPROACH

Demands for beef products are investigated using the U.S. Department of AgricultureÂ’'s 1987-88 Nationwide Food Consumption Survey data. The censored translog demand system is estimated with full-information and simulated maximum-likelihood procedures. These procedures represent different approaches to evaluation of multiple probability integrals in the likelihood function, but produce very similar parameter and elasticity estimates. Findings suggest sociodemographic variables play important roles in the demand for beef, and that demand for different cuts of beef should be treated differently.Demand and Price Analysis,

ESTIMATION OF A DEMAND SYSTEM WITH LIMITED DEPENDENT VARIABLES

The study employs the full-information maximum-likelihood method to estimate a censored translog demand system. U.S. household consumption of steak, roast, and ground beef are used to demonstrate the application of the estimation procedure. The proposed methodology produces more efficient estimates than the popular two-step procedures found in demand literature.Demand and Price Analysis,

Thermal-flow technique for reducing surface roughness and controlling gap size in polymer microring resonators

QQ factors of microring resonator waveguide devices are primarily limited by the surface-roughness-induced scattering loss. Such surface roughness loss has been observed in waveguides that are fabricated from various types of materials, including semiconductors, dielectrics, and polymers. In this letter, we show that the surface roughness of polymer waveguides can be greatly reduced by a thermal-flow technique, and the effective reduction in waveguide loss was verified experimentally. In addition to smoothing surfaces, this technique can simultaneously shrink the gap distance in the coupling region of polymer microring resonators. This, in turn, provides higher coupling, lessens the difficulty of fabricating submicron gaps, and leads to more compact devices. © 2004 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71218/2/APPLAB-84-14-2479-1.pd

Biochemical sensors based on polymer microrings with sharp asymmetrical resonance

Photonic microresonators have great potential in the application of highly sensitive sensors due to high Q-factor resonances and steep slopes between zero and unity transmission. A microring resonator with increased resonance slopes is proposed by introducing two partially reflecting elements implemented by waveguide offsets. This configuration produces a Fano-resonant line shape and can greatly enhance the sensitivity of the sensor. Polystyrene microring resonators were fabricated by the nanoimprinting technique, and the optical spectra were measured in glucose solutions of different concentrations. The shift in resonant wavelength and variation of the normalized transmitted intensity are linearly related to the concentration of the glucose solution. © 2003 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/69921/2/APPLAB-83-8-1527-1.pd

Ultrasound detection using polymer microring optical resonator

Application of polymer waveguide microring resonators for high-frequency ultrasound detection is presented. The device consists of a microring optical resonator coupled to a straight optical waveguide which serves as input and output ports. Acoustic waves irradiating the ring waveguide induce strain modifying the waveguide cross section. As a consequence, the effective refractive index of optical waves propagating along the ring is modified. The sharp wavelength dependence of the high QQ-factor resonator enhances the optical response to acoustic strain. High sensitivity is demonstrated experimentally in detecting broadband ultrasound pulses from a 10 MHz10 MHz transducer. Methods of extending the technique to form multi-element ultrasonic arrays for imaging applications are proposed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70498/2/APPLAB-85-22-5418-1.pd

High expression FUT1 and B3GALT5 is an independent predictor of postoperative recurrence and survival in hepatocellular carcinoma.

Cancer may arise from dedifferentiation of mature cells or maturation-arrested stem cells. Previously we reported that definitive endoderm from which liver was derived, expressed Globo H, SSEA-3 and SSEA-4. In this study, we examined the expression of their biosynthetic enzymes, FUT1, FUT2, B3GALT5 and ST3GAL2, in 135 hepatocellular carcinoma (HCC) tissues by qRT-PCR. High expression of either FUT1 or B3GALT5 was significantly associated with advanced stages and poor outcome. Kaplan Meier survival analysis showed significantly shorter relapse-free survival (RFS) for those with high expression of either FUT1 or B3GALT5 (P = 0.024 and 0.001, respectively) and shorter overall survival (OS) for those with high expression of B3GALT5 (P = 0.017). Combination of FUT1 and B3GALT5 revealed that high expression of both genes had poorer RFS and OS than the others (P < 0.001). Moreover, multivariable Cox regression analysis identified the combination of B3GALT5 and FUT1 as an independent predictor for RFS (HR: 2.370, 95% CI: 1.505-3.731, P < 0.001) and OS (HR: 2.153, 95% CI: 1.188-3.902, P = 0.012) in HCC. In addition, the presence of Globo H, SSEA-3 and SSEA-4 in some HCC tissues and their absence in normal liver was established by immunohistochemistry staining and mass spectrometric analysis

The Space-Time Conservative Schemes for Large-Scale, Time-Accurate Flow Simulations with Tetrahedral Meshes

Despite decades of development of unstructured mesh methods, high-fidelity time-accurate simulations are still predominantly carried out on structured, or unstructured hexahedral meshes by using high-order finite-difference, weighted essentially non-oscillatory (WENO), or hybrid schemes formed by their combinations. In this work, the space-time conservation element solution element (CESE) method is used to simulate several flow problems including supersonic jet/shock interaction and its impact on launch vehicle acoustics, and direct numerical simulations of turbulent flows using tetrahedral meshes. This paper provides a status report for the continuing development of the space-time conservation element solution element (CESE) numerical and software framework under the Revolutionary Computational Aerosciences (RCA) project. Solution accuracy and large-scale parallel performance of the numerical framework is assessed with the goal of providing a viable paradigm for future high-fidelity flow physics simulations

Do logarithmic proximity measures outperform plain ones in graph clustering?

We consider a number of graph kernels and proximity measures including commute time kernel, regularized Laplacian kernel, heat kernel, exponential diffusion kernel (also called "communicability"), etc., and the corresponding distances as applied to clustering nodes in random graphs and several well-known datasets. The model of generating random graphs involves edge probabilities for the pairs of nodes that belong to the same class or different predefined classes of nodes. It turns out that in most cases, logarithmic measures (i.e., measures resulting after taking logarithm of the proximities) perform better while distinguishing underlying classes than the "plain" measures. A comparison in terms of reject curves of inter-class and intra-class distances confirms this conclusion. A similar conclusion can be made for several well-known datasets. A possible origin of this effect is that most kernels have a multiplicative nature, while the nature of distances used in cluster algorithms is an additive one (cf. the triangle inequality). The logarithmic transformation is a tool to transform the first nature to the second one. Moreover, some distances corresponding to the logarithmic measures possess a meaningful cutpoint additivity property. In our experiments, the leader is usually the logarithmic Communicability measure. However, we indicate some more complicated cases in which other measures, typically, Communicability and plain Walk, can be the winners.Comment: 11 pages, 5 tables, 9 figures. Accepted for publication in the Proceedings of 6th International Conference on Network Analysis, May 26-28, 2016, Nizhny Novgorod, Russi