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The increase in the demand for a reliable electricity supply by the utilities and consumers has necessitated the evaluation of the reliability of power systems. A reliable electricity supply is characterized by no or minimal duration and frequency of supply outages. This has triggered the necessity of using renewable energy sources (RESs) with optimization methods for reliability improvement of electricity systems and reduction of greenhouse gas (GHG) emissions. The main objective of this study is to optimize micro-grid systems operations, improve reliability, reduce emissions and balance the demand and supply of energy through RESs and battery energy storage system (BESS). The adaptive model predictive control (AMPC) method is used to address the issues of micro-grid operation. The AMPC algorithm solves the optimization problem of disturbance prediction in a micro-grid with different types of RESs and BESS integration. This optimization problem considers different constraints for minimum operating costs in different case scenarios. The financial viability of the proposed method is investigated. Solar photovoltaic (Solar PV), wind plant (WP) and BESSs are used with the AMPC method to investigate the impacts of annual real interest rates on cost and emission parameters, quantification of the emission oxides from different case scenarios, reduction of the cost of electricity (Ccoe), and power system reliability improvement. A modified Roy Billinton Test System (RBTS) is used to confirm the reliability enhancement and financial feasibility of the system. Case studies are used to confirm the proposed methods using climatic data for the city of Pietermaritzburg (29.37° S and 30.23° E), South Africa. The results obtained establish that the incorporation of RESs and BESSs using the AMPC method gives satisfactory outcomes.

The reliability of the power supply depends on the reliability of the structure of the grid. Grid networks are exposed to varying weather events, which makes them prone to faults. There is a growing concern that climate change will lead to increasing numbers and severity of weather events, which will adversely affect grid reliability and electricity supply. Predictive models of electricity reliability have been used which utilize computational intelligence techniques. These techniques have not been adequately explored in forecasting problems related to electricity outages due to weather factors. A model for predicting electricity outages caused by weather events is presented in this study. This uses the back-propagation algorithm as related to the concept of artificial neural networks (ANNs). The performance of the ANN model is evaluated using real-life data sets from Pietermaritzburg, South Africa, and compared with some conventional models. These are the exponential smoothing (ES) and multiple linear regression (MLR) models. The results obtained from the ANN model are found to be satisfactory when compared to those obtained from MLR and ES. The results demonstrate that artificial neural networks are robust and can be used to predict electricity outages with regards to faults caused by severe weather conditions.

Background: Current research examining the effect of exercise on immune responses in cancer survivors is limited., Objective: The aim of this pilot study was to examine the effect of 1 bout of intermittent exercise on natural killer (NK) cell numbers in breast cancer survivors., Methods: A total of 9 women with stage I to III invasive breast cancer who were 3 to 6 months posttreatment and 9 sedentary women without a history of cancer completed 10 three-minute intervals of aerobic exercise on the cycle ergometer at 60% of VO2peak (peak oxygen uptake). Whole blood samples were taken pre-exercise, immediately postexercise, and at 2 hours and 24 hours postexercise. NK cell counts were assessed using flow cytometry., Results: In both groups, NK cell counts significantly increased immediately postexercise compared with pre-exercise (P = .004-.008) and returned to near pre-exercise levels during recovery (P = .129-.547). Absolute NK cell counts were significantly lower in breast cancer survivors immediately postexercise when compared with controls (P = .046)., Conclusions: The breast cancer survivor group exhibited NK cell responses to 30 minutes of moderate-intensity intermittent aerobic exercise that were comparable with that in the group of physically similar women without a history of cancer. Immune changes related to cancer treatments may be related to the lower absolute NK cell counts observed in the breast cancer survivor group. Although the results of this study are preliminary in nature, they suggest that this type of exercise does not disrupt this aspect of innate immunity in recent breast cancer survivors, thereby supporting current exercise recommendations for this population., (© The Author(s) 2015.)

The aim of this study was to compare select aspects of exercise energy metabolism in patients with breast cancer with that of healthy controls across a variety of exercise intensities. Posttreated patients with breast cancer were matched with healthy women based on age, physical fitness level, and menopausal status. Subjects participated in low-, moderate-, and high-intensity submaximal exercise sessions that corresponded with 40% of maximal oxygen consumption (Vo(2max)), 60% Vo(2max), and 70% Vo(2max). Oxygen consumption and respiratory exchange ratio were taken during submaximal exercise sessions to determine substrate oxidation rates for carbohydrate (CHO) and fat. Blood lactate and blood glucose were also measured before and after each of the submaximal exercise sessions as indices of CHO metabolism. Results indicate that the patients with breast cancer had a significantly (P≤.05) lower CHO oxidation rate and higher fat oxidation rate at all exercise intensities compared with healthy women. The patients with breast cancer had a significantly (P≤.05) lower blood lactate response to exercise across all intensities compared with the healthy women. Glucose responses tended (P<.08) to be more elevated in patients with cancer both before and after the exercise sessions. The findings indicate that posttreated patients with breast cancer have augmented fat metabolism and a reduced CHO-based energy metabolism during submaximal exercise. It is unclear whether these changes are the result of the patient's cancer or their treatment regimen for the cancer., (© The Author(s) 2011)

Purpose: This study compared the heart rate (HR), rate of perceived exertion (RPE), and blood lactate (BL) responses to aerobic exercise between posttreated breast cancer patients and apparently healthy, age-matched controls., Methods: Seven patients and 7 control subjects underwent a submaximal treadmill test for the estimation of Vo(2max). Exercise intensities of 40%, 60%, and 70% of Vo(2max) were calculated from the treadmill test and randomly examined between groups during three 9-minute exercise bouts on 3 different days. Independent samples t tests were used to examine the HR, RPE, and BL responses at each intensity between groups., Results: No significant differences were observed between the control and patient groups for HR, RPE, and BL at 40% (101 +/- 9 vs 101 +/- 11 bpm, P = .979; 8 +/- 1 vs 9 +/- 3, P = .237; and 1.11 +/- 0.73 vs 1.26 +/- 0.64 mmol/L, P = .188, respectively) and 60% (127 +/- 17 vs 117 +/- 13 bpm, P = .523; 12 +/- 2 vs 11 +/- 3, P = .267, and 3.83 +/- 2.48 vs 2.23 +/- 1.65 mmol/L, P = .237, respectively) of Vo(2max) . At 70% of Vo(2max), no significant differences were found for HR (151 +/- 27 vs 135 +/- 13 bpm, P = .704) and RPE (14 +/- 1 vs 13 +/- 3, P = .181), but lower BL responses were observed in the patient group (7.70 +/- 1.62 vs 3.29 +/- 1.08 mmol/L, P < .0005)., Conclusions: The results suggest similar HR, RPE, and BL responses between patients and control subjects at 40%, 60%, and 70% of Vo(2max) , except for BL at 70% of Vo(2max). The lower BL response in the patient group at 70% of Vo(2max) was somewhat unexpected. Further research is needed to confirm or refute the results of this study to allow for a clearer understanding of the physiological responses of breast cancer patients to aerobic exercise at moderate or higher intensities so that safer aerobic exercise prescriptions can be developed for this population.

Purpose: To assess the impact of induction chemotherapy, and associated tumor shrinkage, on the subsequent radiation-related changes in pulmonary function and tumor response., Methods and Materials: As part of a prospective institutional review board-approved study, 91 evaluable patients treated definitively with thoracic radiation therapy (RT) for unresectable lung cancer were analyzed. The rates of RT-associated pulmonary toxicity and tumor response were compared in the patients with and without pre-RT chemotherapy. In the patients receiving induction chemotherapy, the rates of RT-associated pulmonary toxicity and tumor response were compared in the patients with and without a response (modified Response Evaluation Criteria in Solid Tumor criteria) to the pre-RT chemotherapy. Comparisons of the rates of improvements in pulmonary function tests (PFTs) post-RT, dyspnea requiring steroids, and percent declines in PFTs post-RT were compared in patient subgroups using Fisher's exact test, analysis of variance, and linear or logistic regression., Results: The use of pre-RT chemotherapy appears to increase the rate of radiation-induced pneumonitis (p = 0.009-0.07), but has no consistent impact on changes in PFTs. The degree of induction chemotherapy-associated tumor shrinkage is not associated with the rate of subsequent RT-associated pulmonary toxicity. The degree of tumor response to chemotherapy is not related to the degree of tumor response to RT., Conclusions: Additional study is needed to better clarify the impact of chemotherapy on radiation-associated disfunction.

Purpose: Clinical and 3D dosimetric parameters are associated with symptomatic radiation pneumonitis rates in retrospective studies. Such parameters include: mean lung dose (MLD), radiation (RT) dose to perfused lung (via SPECT), and pre-RT lung function. Based on prior publications, we defined pre-RT criteria hypothesized to be predictive for later development of pneumonitis. We herein prospectively test the predictive abilities of these dosimetric/functional parameters on 2 cohorts of patients from Duke and The Netherlands Cancer Institute (NKI)., Methods and Materials: For the Duke cohort, 55 eligible patients treated between 1999 and 2005 on a prospective IRB-approved study to monitor RT-induced lung injury were analyzed. A similar group of patients treated at the NKI between 1996 and 2002 were identified. Patients believed to be at high and low risk for pneumonitis were defined based on: (1) MLD; (2) OpRP (sum of predicted perfusion reduction based on regional dose-response curve); and (3) pre-RT DLCO. All doses reflected tissue density heterogeneity. The rates of grade > or =2 pneumonitis in the "presumed" high and low risk groups were compared using Fisher's exact test., Results: In the Duke group, pneumonitis rates in patients prospectively deemed to be at "high" vs. "low" risk are 7 of 20 and 9 of 35, respectively; p = 0.33 one-tailed Fisher's. Similarly, comparable rates for the NKI group are 4 of 21 and 6 of 44, respectively, p = 0.41 one-tailed Fisher's., Conclusion: The prospective model appears unable to accurately segregate patients into high vs. low risk groups. However, considered retrospectively, these data are consistent with prior studies suggesting that dosimetric (e.g., MLD) and functional (e.g., PFTs or SPECT) parameters are predictive for RT-induced pneumonitis. Additional work is needed to better identify, and prospectively assess, predictors of RT-induced lung injury.

Purpose: The aim of this study was to assess the impact of patient-specific factors, left ventricle (LV) volume, and treatment set-up errors on the rate of perfusion defects 6 to 60 months post-radiation therapy (RT) in patients receiving tangential RT for left-sided breast cancer., Methods and Materials: Between 1998 and 2005, a total of 153 patients were enrolled onto an institutional review board-approved prospective study and had pre- and serial post-RT (6-60 months) cardiac perfusion scans to assess for perfusion defects. Of the patients, 108 had normal pre-RT perfusion scans and available follow-up data. The impact of patient-specific factors on the rate of perfusion defects was assessed at various time points using univariate and multivariate analysis. The impact of set-up errors on the rate of perfusion defects was also analyzed using a one-tailed Fisher's Exact test., Results: Consistent with our prior results, the volume of LV in the RT field was the most significant predictor of perfusion defects on both univariate (p = 0.0005 to 0.0058) and multivariate analysis (p = 0.0026 to 0.0029). Body mass index (BMI) was the only significant patient-specific factor on both univariate (p = 0.0005 to 0.022) and multivariate analysis (p = 0.0091 to 0.05). In patients with very small volumes of LV in the planned RT fields, the rate of perfusion defects was significantly higher when the fields set-up "too deep" (83% vs. 30%, p = 0.059). The frequency of deep set-up errors was significantly higher among patients with BMI > or =25 kg/m2 compared with patients of normal weight (47% vs. 28%, p = 0.068)., Conclusions: BMI > or =25 kg/m2 may be a significant risk factor for cardiac toxicity after RT for left-sided breast cancer, possibly because of more frequent deep set-up errors resulting in the inclusion of additional heart in the RT fields. Further study is necessary to better understand the impact of patient-specific factors and set-up errors on the development of RT-induced perfusion defects.

The purpose of the study was to reassess the utility of transforming growth factor-beta-1 (TGF-beta1) together with dosimetric and tumor parameters as a predictor for radiation pneumonitis (RP). Of the 121 patients studied, 32 (26.4%) developed grade > or =1 RP, and 27 (22.3%) developed grade > or =2 RP. For the endpoint of grade > or =1 RP, those with V30>30% and an end-RT/baseline TGF-beta1 ratio> or =1 had a significantly higher incidence of RP than did those with V30>30% and an end-RT/baseline TGF-beta1 ratio<1. For most other patient groups, there were no clear associations between TGF-beta1 values and rates of RP. These findings suggest that TGF-beta1 is generally not predictive for RP except for the group of patients with a high V30.