The state vector of a power system varies with time owing to the dynamic nature of system loads. Therefore, it is necessary to establish a dynamic model for the time evolution of the state vector. The dynamic state estimation approach consists of predicting the state vector based on past estimations, followed by a filtering process performed when a new set of measurements is available. This paper presents a new algorithm for forecasting and filtering the state vector, using exponential smoothing and least-squares estimation techniques. The proposed algorithm is compared with another one based on standard Kalman filtering theory. Numerical results showing the performance for both dynamic estimators under different operational conditions are presented and discussed. Detection and identification of multiple bad data are also included. The new dynamic estimator exploiting state forecasting is extremely useful to real-time monitoring of power systems.

OBJECTIVE:To evaluate the influence of pain on quality of life in breast cancer patients.METHODS:A cross-sectional study of 400 patients, including 118 without metastasis, 160 with loco-regional metastasis and 122 with distant metastasis. The instruments used were the European Organization for Research and Treatment for Cancer Quality of Life Questionnaire-Core 30 and the Breast Cancer-specific 23 and short McGill Pain Questionnaire.RESULTS:In total, 71.7% of patients reported pain. The most frequent sensory descriptor used by patients was ‘jumping.’ In the evaluative dimension, the main descriptor chosen was troublesome. The Global Health self-assessment showed pain to be inversely correlated with quality of life: the group without metastasis had a mean score of 55.3 (SD=24.8) for those in pain, which rose to 69.7 (SD=19.2) for those without pain (p=0.001). Subjects with loco-regional metastasis had score of 59.1 (SD=21.3) when in pain, and those without pain had a significantly higher score of 72.4 (SD=18.6) (p<0.001). Patients from the distant metastasis group showed similar results with a mean score of 48.6 (SD=23.1) for those in pain and 67.6 (SD=20.4) for those without pain (p=0.002). Regarding the association of pain intensity and quality of life, patients with distant metastasis and intense pain had the worst scores for quality of life with a functional scale mean of 49.9 (SD=17.3) (p<0.009), a Symptom Scale score of 50.0 (SD=20.1) (p<0.001) and a Global Health Scale score of 39.7 (SD=24.7) (p<0.006).CONCLUSIONS:Pain compromises the quality of life of patients with breast cancer, particularly those with advanced stages of the disease.

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To identify pregnancy as a causative factor of sexual dysfunction among expectant women. A prospective study with 225 expectant mothers seen in the prenatal clinic of a federal university. Sexual function was evaluated by means of the Female Sexual Function Index (FSFI), and all domains were analyzed (desire, arousal, lubrication, orgasm, satisfaction, and pain). Initially, a univariate analysis of the sample was done. The averages for each domain according to the risk of sexual dysfunction (FSFI ≤ 26.5) were compared using the Student's-test for independent samples. The strength of the correlation between sexual dysfunction and all sociodemographic, clinical and behavioral variables was measured by the Chi-Square (χ) test. Then, odds ratios (ORs) and their confidence intervals were assigned to perform a bivariate analysis. Any values less than 0.05 were considered significant. Approximately two-thirds of the women (66.7%) showed signs of risk of sexual dysfunction (FSFI ≤ 26.5). Within these cases, all sexual dysfunction domains (desire, arousal, lubrication, orgasm, satisfaction, and pain) were found to be statistically significant ( < 0.001). The domains most affected were desire (2.67), satisfaction (2.71) and arousal (2.78). Pregnancy appears to be an important causative factor of sexual dysfunction among pregnant women.

IntroductionThe number of patients taking oral chemotherapy is increasing around the world. It is essential to maximise the adherence to oral chemotherapy to improve the overall survival and life expectancy of the patients. In this systematic review and meta-analysis, we aim to evaluate the effectiveness of mobile applications in improving the adherence to oral chemotherapy and adjuvant hormonal therapy in cancer survivors.Methods and analysisMEDLINE, Embase, LILACS, clinicaltrials.gov, Scopus and the Cochrane Central Register of Controlled Trials will be searched for randomised or quasi-experimental studies published between January 2009 and July 2019. This systematic review and meta-analysis will include studies investigating the use of mobile applications by cancer survivors to aid adherence to oral chemotherapy and adjuvant hormonal therapy. Patient education, reminder tools, calendars, pillboxes and electronic reminders will not be evaluated. The primary outcome will be the improvement in adherence to anticancer drugs. The secondary outcomes will be an improvement in the overall survival and life expectancy, improved quality of life and control of cancer-related symptoms. Three independent reviewers will select the studies and extract data from the original publications. The risk-of-bias will be assessed using the Cochrane risk-of-bias tool. Data synthesis will be performed using the Review Manager software (RevMan V.5.2.3). To assess heterogeneity, we will compute the I2 statistics. Additionally, a quantitative synthesis will be performed if the included studies are sufficiently homogenous.Ethics and disseminationThis study will be a review of the published data, and thus, ethical approval is not required. Findings of this systematic review will be published in a peer-reviewed journal.PROSPERO registration numberCRD42018102172.