Sclera solar diameter observations

Focus is given to possible variations in solar luminosity and accurate methods of monitoring it. Aside from direct bolometry, one methodology for this type of research makes use of measurements of the solar diameter and limb darkening function as indirect indicators of the solar luminosity. This approach was reviewed

An Optical Implementation of Adaptive Resonance Utilizing Phase Conjugation

A novel adaptive resonance theory (ART) device has been conceived that is fully optical in the input-output processing path. This device is based on holographic information processing in a phase-conjugating crystal. This sets up an associative pattern retrieval in a resonating loop utilizing angle-multiplexed reference beams for pattern classification. A reset mechanism is used to reject any given beam, allowing an ART search strategy. The design is similar to that of an existing nonlearning optical associative memory, but is does allow learning and makes use of information the other device discards. This new device is expected to offer higher information storage density that alternative ART implementation

An Optical Adaptive Resonance Neural Network Utilizing Phase Conjugation

An adaptive resonance (ART) device has been conceived that is fully optical in the input-output processing path. It is based on holographic information processing in a phase-conjugating crystal. This sets up an associative pattern retrieval in a resonating loop utilizing angle-multiplexed reference beams for pattern classification. A reset mechanism is used to reject any given beam, allowing an ART search strategy. The design is similar to an existing nonlearning optical associative memory, but it does allow learning and makes use of information the other device discards. This device is expected to offer higher information storage density than alternative ART implementations

Mathematical Modeling of Radiotherapy: Impact of Model Selection on Estimating Minimum Radiation Dose for Tumor Control

INTRODUCTION: Radiation therapy (RT) is one of the most common anticancer therapies. Yet, current radiation oncology practice does not adapt RT dose for individual patients, despite wide interpatient variability in radiosensitivity and accompanying treatment response. We have previously shown that mechanistic mathematical modeling of tumor volume dynamics can simulate volumetric response to RT for individual patients and estimation personalized RT dose for optimal tumor volume reduction. However, understanding the implications of the choice of the underlying RT response model is critical when calculating personalized RT dose. METHODS: In this study, we evaluate the mathematical implications and biological effects of 2 models of RT response on dose personalization: (1) cytotoxicity to cancer cells that lead to direct tumor volume reduction (DVR) and (2) radiation responses to the tumor microenvironment that lead to tumor carrying capacity reduction (CCR) and subsequent tumor shrinkage. Tumor growth was simulated as logistic growth with pre-treatment dynamics being described in the proliferation saturation index (PSI). The effect of RT was simulated according to each respective model for a standard schedule of fractionated RT with 2 Gy weekday fractions. Parameter sweeps were evaluated for the intrinsic tumor growth rate and the radiosensitivity parameter for both models to observe the qualitative impact of each model parameter. We then calculated the minimum RT dose required for locoregional tumor control (LRC) across all combinations of the full range of radiosensitvity and proliferation saturation values. RESULTS: Both models estimate that patients with higher radiosensitivity will require a lower RT dose to achieve LRC. However, the two models make opposite estimates on the impact of PSI on the minimum RT dose for LRC: the DVR model estimates that tumors with higher PSI values will require a higher RT dose to achieve LRC, while the CCR model estimates that higher PSI values will require a lower RT dose to achieve LRC. DISCUSSION: Ultimately, these results show the importance of understanding which model best describes tumor growth and treatment response in a particular setting, before using any such model to make estimates for personalized treatment recommendations

Modelling Radiation Cancer Treatment with a Death-Rate Term in Ordinary and Fractional Differential Equations

Fractional calculus has recently been applied to the mathematical modelling of tumour growth, but its use introduces complexities that may not be warranted. Mathematical modelling with differential equations is a standard approach to study and predict treatment outcomes for population-level and patient-specific responses. Here, we use patient data of radiation-treated tumours to discuss the benefits and limitations of introducing fractional derivatives into three standard models of tumour growth. The fractional derivative introduces a history-dependence into the growth function, which requires a continuous death-rate term for radiation treatment. This newly proposed radiation-induced death-rate term improves computational efficiency in both ordinary and fractional derivative models. This computational speed-up will benefit common simulation tasks such as model parameterization and the construction and running of virtual clinical trials

Quantification of HTLV-I proviral load in experimentally infected rabbits

BACKGROUND: Levels of proviral load in HTLV-1 infected patients correlate with clinical outcome and are reasonably prognostic. Adaptation of proviral load measurement techniques is examined here for use in an experimental rabbit model of HTLV-1 infection. Initial efforts sought to correlate proviral load with route and dose of inoculation and with clinical outcome in this model. These methods contribute to our continuing goal of using the model to test treatments that alleviate virus infection. RESULTS: A real-time PCR assay was used to measure proviral load in blood and tissue samples from a series of rabbits infected using HTLV-1 inocula prepared as either cell-free virus particles, infected cells or blood, or by naked DNA injection. Proviral loads from asymptomatically infected rabbits showed levels corresponding to those reported for human patients with clinically silent HTLV-1 infections. Proviral load was comparably increased in 50% of experimentally infected rabbits that developed either spontaneous benign or malignant tumors while infected. Similarly elevated provirus was found in organs of rabbits with experimentally induced acute leukemia/lymphoma-like disease. Levels of provirus in organs taken at necropsy varied widely suggesting that reservoirs of infections exist in non-lymphoid organs not traditionally thought to be targets for HTLV-1. CONCLUSION: Proviral load measurement is a valuable enhancement to the rabbit model for HTLV-1 infection providing a metric to monitor clinical status of the infected animals as well as a means for the testing of treatment to combat infection. In some cases proviral load in blood did not reflect organ proviral levels, revealing a limitation of this method for monitoring health status of HTLV-1 infected individuals

An Optoelectronic Implementation of the Adaptive Resonance Neural Network

A solution to the problem of implementation of the adaptive resonance theory (ART) of neural networks that uses an optical correlator which allows the large body of correlator research to be leveraged in the implementation of ART is presented. The implementation takes advantage of the fact that one ART-based architecture, known as ART1, can be broken into several parts, some of which are better to implement in parallel. The control structure of ART, often regarded as its most complex part, is actually not very time consuming and can be done in electronics. The bottom-up and top-down gated pathways, however, are very time consuming to simulate and are difficult to implement directly in electronics due to the high number of interconnections. In addition to the design, the authors present experiments with a laboratory prototype to illustrate its feasibility and to discuss implementation details that arise in practice. This device can potentially outperform alternative implementations of ART1 by as much as two to three orders of magnitude in problems requiring especially large input field