Quality of life, symptom experience, and use of complementary and alternative medicine among women with ovarian cancer

The objectives of this dissertation were to determine the quality of life in women with ovarian cancer and the association of their physical and emotional well-being with the number of symptoms, duration of symptoms, and the scores of common symptoms of ovarian cancer; to study the prevalence of complementary and alternative medicine techniques for symptom relief and its association with the number of symptoms, age, education, insurance, comorbidity, and satisfaction with medical care they received, and their pre-diagnostic experience of symptoms.^ This study was based on a secondary data analysis of a study of early detection of ovarian cancer. A sample of 139 women with ovarian cancer was recruited and was administered a questionnaire comprised of questions on their quality of life, their symptoms and what they did about the symptoms, whether they used any complementary and alternative medicine techniques, and other medical conditions they had. Out of this sample, 53 patients underwent in-depth interviews relating to their symptoms before the diagnosis and their experiences with the health care system leading to the ovarian cancer diagnosis. ^ In article #1, ovarian cancer patients were observed to have significantly poorer quality of life on all subscales and summary scores except pain, compared to that of the general population of US women. Physical well-being scores were negatively associated with the number of symptoms before diagnosis and a significant negative association of comorbidity index was observed with physical well-being. Higher education and increase in time since diagnosis was found to have better physical scores. Emotional well-being scores showed marginally significant associations with number of symptoms and bloating. ^ In article #2, a thematic content analysis of the ovarian cancer patients’ interviews revealed that on recognition of their symptoms women first assumed their symptoms to be a normal transient occurrence due to a pre-existing disease condition, or due to some other disease. A series of misattributions of their symptoms on their and their doctors’ part impacted their health care seeking.In article #3, a significantly greater likelihood of CAM use with an increase in the number of symptoms was observed.^ Based on the foregoing results, it is important to educate women on possible signs of ovarian cancer and also to educate doctors about the results of current research regarding ovarian cancer diagnosis. This will help to avoid a delay in getting a diagnosis and improve women’s quality of life. It emphasizes the diagnosis of ovarian cancer in earlier stages by more sensitive screening techniques. This study emphasizes the importance of consideration of comorbidity in any quality of life research. Additionally, educating women in the safe use of CAM techniques carries immense significance because the efficacy and safety of many of the currently advertized CAM products has not been scientifically validated. Further research is needed to confirm the findings of this study. ^

EVALUATION OF THE EFFECTIVENESS OF ANISOTROPIC ANALYTICAL ALGORITHM IN FLATTENED AND FLATTENING-FILTER-FREE BEAMS FOR HIGH ENERGY LUNG DOSE DELIVERY USING THE RADIOLOGICAL PHYSICS CENTER LUNG PHANTOM

The effectiveness of the Anisotropic Analytical Algorithm (AAA) implemented in the Eclipse treatment planning system (TPS) was evaluated using theRadiologicalPhysicsCenteranthropomorphic lung phantom using both flattened and flattening-filter-free high energy beams. Radiation treatment plans were developed following the Radiation Therapy Oncology Group and theRadiologicalPhysicsCenterguidelines for lung treatment using Stereotactic Radiation Body Therapy. The tumor was covered such that at least 95% of Planning Target Volume (PTV) received 100% of the prescribed dose while ensuring that normal tissue constraints were followed as well. Calculated doses were exported from the Eclipse TPS and compared with the experimental data as measured using thermoluminescence detectors (TLD) and radiochromic films that were placed inside the phantom. The results demonstrate that the AAA superposition-convolution algorithm is able to calculate SBRT treatment plans with all clinically used photon beams in the range from 6 MV to 18 MV. The measured dose distribution showed a good agreement with the calculated distribution using clinically acceptable criteria of ±5% dose or 3mm distance to agreement. These results show that in a heterogeneous environment a 3D pencil beam superposition-convolution algorithms with Monte Carlo pre-calculated scatter kernels, such as AAA, are able to reliably calculate dose, accounting for increased lateral scattering due to the loss of electronic equilibrium in low density medium. The data for high energy plans (15 MV and 18 MV) showed very good tumor coverage in contrast to findings by other investigators for less sophisticated dose calculation algorithms, which demonstrated less than expected tumor doses and generally worse tumor coverage for high energy plans compared to 6MV plans. This demonstrates that the modern superposition-convolution AAA algorithm is a significant improvement over previous algorithms and is able to calculate doses accurately for SBRT treatment plans in the highly heterogeneous environment of the thorax for both lower (≤12 MV) and higher (greater than 12 MV) beam energies.

Are trading partners complementary in international trade?

We use a unique dataset on trading transactions at the firm level to investigate a complementary effect in international transactions between sellers and buyers; trading transactions are more likely to be international when both sellers and buyers are large in size than when either sellers or buyers are large. Our econometric analysis provides evidence for the complementary effect between trading partners on the likelihood of international trade, which is most prominent for exports from North to South.

New methods for the estimation of Takagi-Sugeno model based extended Kalman filter and its applications to optimal control for nonlinear systems

This paper describes new approaches to improve the local and global approximation (matching) and modeling capability of Takagi–Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem encountered is that T-S identification method cannot be applied when the membership functions are overlapped by pairs. This restricts the application of the T-S method because this type of membership function has been widely used during the last 2 decades in the stability, controller design of fuzzy systems and is popular in industrial control applications. The approach developed here can be considered as a generalized version of T-S identification method with optimized performance in approximating nonlinear functions. We propose a noniterative method through weighting of parameters approach and an iterative algorithm by applying the extended Kalman filter, based on the same idea of parameters’ weighting. We show that the Kalman filter is an effective tool in the identification of T-S fuzzy model. A fuzzy controller based linear quadratic regulator is proposed in order to show the effectiveness of the estimation method developed here in control applications. An illustrative example of an inverted pendulum is chosen to evaluate the robustness and remarkable performance of the proposed method locally and globally in comparison with the original T-S model. Simulation results indicate the potential, simplicity, and generality of the algorithm. An illustrative example is chosen to evaluate the robustness. In this paper, we prove that these algorithms converge very fast, thereby making them very practical to use.

Dual-Band Tunable Recursive Active Filter

This letter presents a novel recursive active filter topology that provides dual-band performance, with independent tuning capability in both bands. The dual-band operation is achieved by using two independent feedback lines. Additionally, linear phase shifters based on left-handed cells are included in these two branches in order to tune the center frequency of both pass bands.

From irradiance to output power fluctuations: the pv plant as a low pass filter

The power generated by large grid-connected photovoltaic (PV) plants depends greatly on the solar irradiance. This paper studies the effects of the solar irradiance variability analyzing experimental 1-s data collected throughout a year at six PV plants, totaling 18 MWp. Each PV plant was modeled as a first order filter function based on an analysis in the frequency domain of the irradiance data and the output power signals. An empiric expression which relates the filter parameters and the PV plant size has been proposed. This simple model has been successfully validated precisely determining the daily maximum output power fluctuation from incident irradiance measurements.