Molecular cloning of a novel melanocortin receptor

Using the technique of the polymerase chain reaction primed with oligonucleotides based on the homologous transmembrane regions of seven transmembrane G protein-linked receptors, we isolated three full-length human genes that encode a novel subgroup of this receptor family. Recently, two of these receptors were identified as specific for alpha-melanocyte-stimulating hormone (alpha-MSH) and adrenocorticotropic hormone. We report the molecular cloning and pharmacologic characterization of a third member of this subgroup. The gene for this receptor encodes a protein of 361 amino acids in length. Its pharmacology characterizes it as an MSH receptor specific to the heptapeptide core common to adrenocorticotropic hormone and alpha-, beta-, and gamma-MSH. By Northern blot hybridization and polymerase chain reaction, it is expressed in brain, placental, and gut tissues but not in melanoma cells or in the adrenal gland. These findings may yield insight into the physiology of peptides derived from pro-opiomelanocortin post-translational processing.     

Optical scattering in beef steak to predict tenderness using hyperspectral imaging in the VIS-NIR region

The objective of this research is to develop a non-destructive method for predicting cooked beef tenderness using optical scattering of light on fresh beef muscle tissue. A hyperspectral imaging system (λ = 496–1,036 nm) that consists of a CCD camera and an imaging spectrograph, was used to acquire beef steak images. The hyperspectral image consisted of 120 bands with spectral intervals of 4.54 nm. Sixty-one fresh beef steaks, including 44 strip loin and 17 tenderloin cuts, were collected. After imaging, the steaks were cooked and Warner-Bratzler shear (WBS) force values were collected as tenderness references. The optical scattering profiles were derived from the hyperspectral images and fitted to the modified Lorentzian function. Parameters, such as the peak height, full scattering width at half maximum (FWHM), and the slope around the FWHM were determined at each wavelength. Stepwise regression was used to identify 7 key wavelengths and parameters. The parameters were then used to predict the WBS scores. The model was able to predict WBS scores with an R = 0.67. Optical scattering implemented with hyperspectral imaging shows limited success for predicting current status of tenderness in beef steak.     

A facile antistatic modification of polyester fiber based on ion-exchange reaction of sulfonate-modified polyester and various cationic surfactants

A new technique for imparting antistatic properties to poly(ethylene terephthalate) (PET) fiber has been developed. In this technique, blend polyester fibers containing poly(ethylene terephthalate/5-sulfoisophthalate) (SIP-PET) were prepared by blend spinning and then treated with various cationic surfactants in the process of dyeing. The surfactants could effectively be immobilized on the fiber as the counter cations of the sulfonate groups of the 5-sulfoisophthalate (SIP) units and aid the release of static electrons formed in the fiber. Thus, the half-life time (t_1/2) of leakage of static charge and the surface resistivity (Rs) of the blend PET fibers became much lower after treating. The best result was obtained with a methylated quaternary ammonium salt of a stearylamine-ethylene oxide (EO) adduct or hydrochloride of a laurylamine-EO adduct as the surfactant of which the number of EO units was around ten. Even after five washing cycles the t_1/2 value of the fibers treated with these surfactants was kept lower than 30 s with the Rs value maintained in the order of 10¹³ Ω cm^-2. Therefore, the present technique could be useful for practical production of polyester fibers with “semi-permanent” antistatic properties which can be recovered by re-treatment even if they were lost.     

Uncertainty propagation in puff-based dispersion models using polynomial chaos

Atmospheric dispersion is a complex nonlinear physical process with numerous uncertainties in model parameters, inputs, source parameters, initial and boundary conditions. Accurate propagation of these uncertainties through the dispersion models is crucial for a reliable prediction of the probability distribution of the states and assessment of risk. A simple three-dimensional Gaussian puff-based dispersion model is used as a test case to study the effect of uncertainties in the model parameters and initial conditions on the output concentration. A polynomial chaos based approach is used to numerically investigate the evolution of the model output uncertainties due to initial condition and parametric uncertainties. The polynomial chaos solution is found to be an accurate approximation to ground truth, established by Monte Carlo simulation, while offering an efficient computational approach for large nonlinear systems with a relatively small number of uncertainties.     

Linear stochastic approximation driven by slowly varying Markov chains

We study a linear stochastic approximation algorithm that arises in the context of reinforcement learning. The algorithm employs a decreasing step-size, and is driven by Markov noise with time-varying statistics. We show that under suitable conditions, the algorithm can track the changes in the statistics of the Markov noise, as long as these changes are slower than the rate at which the step-size of the algorithm goes to zero.     

Partial least squares analysis of near-infrared hyperspectral images for beef tenderness prediction

Tenderness is a primary determinant of consumer satisfaction of beef steaks. The objective of this study was to implement and test near-infrared (NIR) hyperspectral imaging to forecast 14-day aged, cooked beef tenderness from the hyperspectral images of fresh ribeye steaks (n = 319) acquired at 3–5 day post-mortem. A pushbroom hyperspectral imaging system (wavelength range: 900–1700 nm) with a diffuse-flood lighting system was developed. After imaging, steaks were vacuum-packaged and aged until 14 days postmortem. After aging, the samples were cooked and slice shear force (SSF) values were collected as a tenderness reference. After reflectance calibration, a Region-of-Interest (ROI) of 150 × 300 pixels at the center of longissimus muscle was selected. Partial least squares regression (PLSR) was carried out on each ROI image to reduce the dimension along the spectral axis. Gray-level textural co-occurrence matrix analysis with two quantization levels (64 and 256) was conducted on the PLSR bands to extract second-order statistical textural features. These features were then used in a canonical discriminant model to predict three beef tenderness categories, namely tender (SSF ≤ 205.80 N), intermediate (205.80 N < SSF < 254.80 N), and tough (SSF ≥ 254.80 N). The model with a quantization level of 256 performed better than the one with a quantization level of 64. This model correctly classified 242 out of 314 samples with an overall accuracy of 77.0%. Fat, protein, and water absorption bands were identified between 900 and 1700 nm. Our results show that NIR hyperspectral imaging holds promise as an instrument for forecasting beef tenderness.     

Effect of carbon monoxide packaging and lactate enhancement on the color stability of beef steaks stored at 1°C for 9 days

Our objective was to assess the effects of lactate enhancement in combination with different packaging systems on beef longissimus lumborum and psoas major steak color. Strip loins and tenderloins (n = 16) were assigned to one of four injection treatments (non-injected control, water-injected control, 1.25%, and 2.5% lactate in the finished product). Steaks were individually packaged in either vacuum, high-oxygen (80% O₂/20% CO₂), or 0.4% CO (30% CO₂/69.6% N₂) and stored for either 0, 5, or 9 days at 1 °C. The L^∗ and a^∗ values of both the longissimus and psoas responded similarly to lactate, which at 2.5% darkened steaks (P < 0.05) packaged in all atmospheres and improved (P < 0.05) the redness of steaks packaged in high-oxygen. Packaging steaks in CO did not counteract the darkening effects of lactate. Nevertheless, CO improved (P < 0.05) color stability compared with high-oxygen packaging.     

Estimation of temperature dependent heat transfer coefficient in a vertical rectangular fin using liquid crystal thermography

This paper presents a methodology for the estimation of temperature dependent heat transfer coefficient for a vertical rectangular fin by using the inverse heat transfer method with Liquid crystal thermography (LCT) data. Steady state, laminar natural convection experiments have been done on a vertical rectangular fin of size 150 × 250 × 4, (L × w × t, all dimensions are in mm). The variation of heat transfer coefficient is considered as a power law function of temperature excess (h = a_oθ^b) and is derived from the basic Nusselt number equation used for laminar natural convection, Nu = aRa^b. With this functional form, the one dimensional fin equation in finite difference form is repeatedly solved using the Gauss–Seidel iterative method. Treating this as a one parameter estimation in ‘a’ the sum of the squares of the difference between the simulated and Thermochromic Liquid Crystal (TLC) measured temperatures is minimized with the Golden section search algorithm to retrieve ‘a’. Estimate of ‘a’ and the accompanying uncertainties are first reported for synthetically generated temperature distribution for assumed values of ‘a’. The effect of noise on the estimate of ‘a’ is discussed. This is followed by retrievals with experimentally obtained TLC temperature distribution for a range of heat inputs to the fin base. The required temperature distributions for accomplishing the retrievals over the surface are obtained using calibrated R40C5W Thermochromic Liquid Crystal (TLC) sheets. As an additional proof of the accuracy of the method, the retrieved value of ‘a’ is used to simulate the temperature distribution in the fin which is then compared with the actual TLC measured temperature distribution.     

Creating Shared Information Spaces to Support Collaborative Design Work

The provision of computer support for collaborative work is a central concern for Information Systems (IS) research and practice. In this paper we present the details of an information flow study undertaken in the household division of a large European design and manufacturing company (Delta). The goal of the study was to elicit user requirements for a computer system to facilitate the collaborative work of new product design teams. These requirements form the basis for the design and development of a Web-based LIRÉ (Living Repository) prototype system, the functionalities, features, and rationale of which are discussed. We also present the results of the evaluation of LIRÉ by the users at Delta and our observations on enhancing the sophistication and usefulness of this class of system. A production version based on the prototype but using commercially available software is currently in use by the New Product Development group at Delta.