Formulas establish audio range inductance in beryllium coils

Mathematical modeling is used to determine the effects of resistance and capacitance upon the audio-inductance range of beryllium hammer coils and beryllium nylon-potted coils

Some Molds Associated with Meat in Cold Storage Lockers in Iowa

In the past few years throughout the United States cold storage locker plants have been introduced as a new industry, offering their services to the public as storage depots for perishable foods, particularly meats. The wide-spread popularity of this industry is attested by the existence of approximately two thousand cold storage locker plants in the United States of which two hundred are located in Iowa. Over one hundred of these plants in Iowa were introduced during the past year, and there is every indication that their number win continue to increase

Pore-blockade Times for Field-Driven Polymer Translocation

We study pore blockade times for a translocating polymer of length $N$, driven by a field $E$ across the pore in three dimensions. The polymer performs Rouse dynamics, i.e., we consider polymer dynamics in the absence of hydrodynamical interactions. We find that the typical time the pore remains blocked during a translocation event scales as $\sim N^{(1+2\nu)/(1+\nu)}/E$, where $\nu\simeq0.588$ is the Flory exponent for the polymer. In line with our previous work, we show that this scaling behaviour stems from the polymer dynamics at the immediate vicinity of the pore -- in particular, the memory effects in the polymer chain tension imbalance across the pore. This result, along with the numerical results by several other groups, violates the lower bound $\sim N^{1+\nu}/E$ suggested earlier in the literature. We discuss why this lower bound is incorrect and show, based on conservation of energy, that the correct lower bound for the pore-blockade time for field-driven translocation is given by $\eta N^{2\nu}/E$, where $\eta$ is the viscosity of the medium surrounding the polymer.Comment: 14 pages, 6 figures, slightly shorter than the previous version; to appear in J. Phys.: Cond. Ma

Is it really possible to grow isotropic on-lattice diffusion-limited aggregates?

In a recent paper (Bogoyavlenskiy V A 2002 \JPA \textbf{35} 2533), an algorithm aiming to generate isotropic clusters of the on-lattice diffusion-limited aggregation (DLA) model was proposed. The procedure consists of aggregation probabilities proportional to the squared number of occupied sites ($k^2$). In the present work, we analyzed this algorithm using the noise reduced version of the DLA model and large scale simulations. In the noiseless limit, instead of isotropic patterns, a $45^\circ$ ($30^\circ$) rotation in the anisotropy directions of the clusters grown on square (triangular) lattices was observed. A generalized algorithm, in which the aggregation probability is proportional to $k^\nu$, was proposed. The exponent $\nu$ has a nonuniversal critical value $\nu_c$, for which the patterns generated in the noiseless limit exhibit the original (axial) anisotropy for $\nu<\nu_c$ and the rotated one (diagonal) for $\nu>\nu_c$. The values $\nu_c = 1.395\pm0.005$ and $\nu_c = 0.82\pm 0.01$ were found for square and triangular lattices, respectively. Moreover, large scale simulations show that there are a nontrivial relation between noise reduction and anisotropy direction. The case $\nu=2$ (\bogo's rule) is an example where the patterns exhibit the axial anisotropy for small and the diagonal one for large noise reduction.Comment: 12 pages, 8 figure

Development of a valid mathematical formula or group of formulas to establish within an accuracy of 5 percent the inductance audio range resulting in beryllium coil assemblies Final report

Mathematical formulas to determine net inductance in audio range of both hammer coil and cryogenic sealing coi

DACH1: its role as a classifier of long term good prognosis in luminal breast cancer

Background: Oestrogen receptor (ER) positive (luminal) tumours account for the largest proportion of females with breast cancer. Theirs is a heterogeneous disease presenting clinical challenges in managing their treatment. Three main biological luminal groups have been identified but clinically these can be distilled into two prognostic groups in which Luminal A are accorded good prognosis and Luminal B correlate with poor prognosis. Further biomarkers are needed to attain classification consensus. Machine learning approaches like Artificial Neural Networks (ANNs) have been used for classification and identification of biomarkers in breast cancer using high throughput data. In this study, we have used an artificial neural network (ANN) approach to identify DACH1 as a candidate luminal marker and its role in predicting clinical outcome in breast cancer is assessed. Materials and methods: A reiterative ANN approach incorporating a network inferencing algorithm was used to identify ER- associated biomarkers in a publically available cDNA microarray dataset. DACH1 was identified in having a strong influence on ER associated markers and a positive association with ER. Its clinical relevance in predicting breast cancer specific survival was investigated by statistically assessing protein expression levels after immunohistochemistry in a series of unselected breast cancers, formatted as a tissue microarray. Results: Strong nuclear DACH1 staining is more prevalent in tubular and lobular breast cancer. Its expression correlated with ER-alpha positive tumours expressing PgR, epithelial cytokeratins (CK)18/19 and 'luminal-like' markers of good prognosis including FOXA1 and RERG (p , 0.05). DACH1 is increased in patients showing longer cancer specific survival and disease free interval and reduced metastasis formation (p , 0.001). Nuclear DACH1 showed a negative association with markers of aggressive growth and poor prognosis. Conclusion: Nuclear DACH1 expression appears to be a Luminal A biomarker predictive of good prognosis, but is not independent of clinical stage, tumour size, NPI status or systemic therapy

Heat Capacity Mapping Mission

The Tasman Front was delineated by airborne expendable bathythermograph survey; and an Heat Capacity Mapping Mission (HCMM) IR image on the same day shows the same principal features as determined from ground-truth. It is clear that digital enhancement of HCMM images is necessary to map ocean surface temperatures and when done, the Tasman Front and other oceanographic features can be mapped by this method, even through considerable scattered cloud cover