Response Functions Improving Performance in Analog Attractor Neural Networks

In the context of attractor neural networks, we study how the equilibrium analog neural activities, reached by the network dynamics during memory retrieval, may improve storage performance by reducing the interferences between the recalled pattern and the other stored ones. We determine a simple dynamics that stabilizes network states which are highly correlated with the retrieved pattern, for a number of stored memories that does not exceed $\alpha_{\star} N$, where $\alpha_{\star}\in[0,0.41]$ depends on the global activity level in the network and $N$ is the number of neurons.Comment: 13 pages (with figures), LaTex (RevTex), to appear on Phys.Rev.E (RC

Neuro-flow Dynamics and the Learning Processes

A new description of the neural activity is introduced by the neuro-flow dynamics and the extended Hebb rule. The remarkable characteristics of the neuro-flow dynamics, such as the primacy and the recency effect during awakeness or sleep, are pointed out.Comment: 8 pages ,10 Postscript figures, LaTeX file, to appear in Chaos, Solitons and Fractal

Fabrication and Characterization of Titanium-doped Hydroxyapatite Thin Films

Hydroxyapatite [Ca10(PO4)6(OH)2, HA] is used in many biomedical applications including bone grafts and joint replacements. Due to its structural and chemical similarities to human bone mineral, HA promotes growth of bone tissue directly on its surface. Substitution of other elements has shown the potential to improve the bioactivity of HA. Magnetron co-sputtering is a physical vapour deposition technique which can be used to create thin coatings with controlled levels of a substituting element. Thin films of titanium-doped hydroxyapatite (HA-Ti) have been deposited onto silicon substrates at three different compositions. With direct current (dc) power to the Ti target of 5, 10, and 15W films with compositions of 0.7, 1.7 and 2.0 at.% titanium were achieved. As-deposited films, 1.2 μm thick, were amorphous but transformed into a crystalline film after heat-treatment at 700C. Raman spectra of the PO4 band suggests the titanium does not substitute for phosphorous. X-ray diffraction revealed the c lattice parameter increases with additional titanium content. XRD traces also showed titanium may be phase separating into TiO2, a result which is supported by analysis of the Oxygen 1s XPS spectrum. In-vitro observations show good adhesion and proliferation of human osteoblast (HOB) cells on the surface of HA-Ti coatings. Electron microscopy shows many processes (i.e. filopodia) extended from cells after day one in-vitro and a confluent, multi-layer of HOB cells after day three. These finding indicate that there may be potential for HA-Ti films as a novel implant coating to improve upon the bioactivity of existing coatings.National Science Foundation (US

Modeling of wax precipitation

Thesis (M.S.) University of Alaska Fairbanks, 2007Due to increasing oil demand, oil companies are moving into deep water and arctic environments for oil production. In these regions, due to lower temperature, wax starts depositing when the temperature in wellbore falls below Wax Appearance Temperature (WAT). This leads to reduced production rates and larger pressure drops. Wax problems in production wells are very costly due to production down time and removal of wax. Therefore, it is necessary to develop the solution to overcome wax deposition. Wax precipitation is one of the most important phenomena in wax deposition, and hence, it needs to be modeled. There are various models present in literature. The purpose of this study is to compare two major classes of wax precipitation models. Won's model which considers the wax phase as a non-ideal solution and Pedersen's model which considers the wax phase as an ideal-solution were compared. Comparison indicated that Pedersen's model gives better results but the assumption of wax phase as an ideal solution is not realistic. Hence, Won's model was modified to consider different precipitation characteristics of the different constituents in the hydrocarbon fraction. The results obtained from the modified Won's model were compared with existing models and it was found that predictions from the modified model are encouraging

Peri-prostatic fat volume measurement as a predictive tool for castration resistance in advanced prostate cancer

Background: Obesity and aggressive prostate cancer (PC) may be linked, but how local peri-prostatic fat relates to tumour response following androgen deprivation therapy (ADT) is unknown. Objective: To test if peri-prostatic fat volume (PPFV) predicts tumour response to ADT. Design, setting, and participants: We performed a retrospective study on consecutive patients receiving primary ADT. From staging pelvic magnetic resonance imaging scans, the PPFV was quantified with OsirixX 6.5 imaging software. Statistical (univariate and multivariate) analysis were performed using R Version 3.2.1. Results and limitations: Of 224 consecutive patients, 61 with advanced (≥T3 or N1 or M1) disease had (3-mm high resolution axial sections) pelvic magnetic resonance imaging scan before ADT. Median age = 75 yr; median PPFV = 24.8 cm3 (range, 7.4–139.4 cm3). PPFV was significantly higher in patients who developed castration resistant prostate cancer (CRPC; n = 31), with a median of 37.9 cm3 compared with 16.1 cm3 (p < 0.0001, Wilcoxon rank sum test) in patients who showed sustained response to ADT (n = 30). Multivariate analysis using Cox proportional hazards models were performed controlling for known predictors of CRPC. PPFV was shown to be independent of all included factors, and the most significant predictor of time to CRPC. Using our multivariate model consisting of all known factors prior to ADT, PPFV significantly improved the area under the curve of the multivariate models receiver operating characteristic analysis. The main study limitation is a relatively small cohort to account for multiple variables, necessitating a future large-scale prospective analysis of PPFV in advanced PC. Conclusions: PPFV quantification in patients with advanced PC predicts tumour response to ADT

Quantum Effects in Neural Networks

We develop the statistical mechanics of the Hopfield model in a transverse field to investigate how quantum fluctuations affect the macroscopic behavior of neural networks. When the number of embedded patterns is finite, the Trotter decomposition reduces the problem to that of a random Ising model. It turns out that the effects of quantum fluctuations on macroscopic variables play the same roles as those of thermal fluctuations. For an extensive number of embedded patterns, we apply the replica method to the Trotter-decomposed system. The result is summarized as a ground-state phase diagram drawn in terms of the number of patterns per site, $\alpha$, and the strength of the transverse field, $\Delta$. The phase diagram coincides very accurately with that of the conventional classical Hopfield model if we replace the temperature T in the latter model by $\Delta$. Quantum fluctuations are thus concluded to be quite similar to thermal fluctuations in determination of the macroscopic behavior of the present model.Comment: 34 pages, LaTeX, 9 PS figures, uses jpsj.st

Simple formulas for lattice paths avoiding certain periodic staircase boundaries

There is a strikingly simple classical formula for the number of lattice paths avoiding the line x = ky when k is a positive integer. We show that the natural generalization of this simple formula continues to hold when the line x = ky is replaced by certain periodic staircase boundaries--but only under special conditions. The simple formula fails in general, and it remains an open question to what extent our results can be further generalized.Comment: Accepted version (JCTA); proof of Corollary 7 expanded, and 2 new refs adde