Fast model predictive control scheme for attitude control systems of rigid-flexible satellite

In recent years, the applications related to artificial satellites have considerably grown in several areas such as telecommunications, astronomy and meteorology. An important point that must be taken into account to place a satellite in orbit is the design of Attitude Control System (ACS) to control the angular position according to a fixed reference frame. Most satellites have in their structure the presence of flexible appendices such as solar panels, sails, or even antennas that may produce undesirable oscillations during satellite maneuvers and this can excite the whole system’s structure. Therefore, it is important to develop an ACS that limits the excursion of the flexible structure and meet the control requirements for attitude stabilization. In this paper, a Model Predictive Control (MPC) scheme is proposed for ACS of a Rigid-Flexible Satellite. MPC handles structurally the system’s constraints in problem formulation by solving at each sampling instant an optimization problem that express the control objectives. As a result, MPC is able to track efficiently the references for attitude control by keeping the displacement of flexible structure within predetermined limits reducing vibration of the system. Moreover, MPC also deals with constraints on control inputs since actuators are physically bounded by its maximum allowable value. Another important feature of the proposed control strategy is the parameterization of MPC which reduces considerably the complexity of the optimization problem enabling short computation times. Simulation results are shown to emphasize the efficiency of the parameterized MPC strategy and a comparison with a Linear Quadratic Regulator (LQR) is also performed

Abnormal repetitive behaviors in zebrafish and their relevance to human brain disorders

Abnormal repetitive behaviors (ARBs) are a prominent symptom of numerous human brain disorders and are commonly seen in rodent models as well. While rodent studies of ARBs continue to dominate the field, mounting evidence suggests that zebrafish (Danio rerio) also display ARB-like phenotypes and may therefore be a novel model organism for ARB research. In addition to clear practical research advantages as a model species, zebrafish share high genetic and physiological homology to humans and rodents, including multiple ARB-related genes and robust behaviors relevant to ARB. Here, we discuss a wide spectrum of stereotypic repetitive behaviors in zebrafish, data on their genetic and pharmacological modulation, and the overall translational relevance of fish ARBs to modeling human brain disorders. Overall, the zebrafish is rapidly emerging as a new promising model to study ARBs and their underlying mechanisms. © 2019 Elsevier B.V

A retrospective analysis of clinicopathological and prognostic characteristics of ovarian tumors in the State of Espírito Santo, Brazil

<p>Abstract</p> <p>Background</p> <p>Ovarian cancer is sixth most common cancer among women and the leading cause of death in women with gynecological malignancies. Despite the great impact ovarian cancer has on women's health and its great impact in public economy, Brazil still lacks valuable information concerning epidemiological aspects of this disease</p> <p>Methods</p> <p>We've compiled clinical data of all ovarian tumors registered at the two public hospitals of reference (1997 - 2007), such as: patients' age at diagnosis, tumor histological type, tumor stage, chemotherapy regimens, chemotherapy responsiveness, disease-free survival, and overall survival.</p> <p>Results</p> <p>Women's mean age at diagnosis was 54.67 ± 13.84 for ovarian cancer, 46.15 ± 11.15 for borderline tumors, and 42.01 ± 15.06 for adenomas. Among epithelial ovarian cancer cases, 30.1% were of serous, 13.7% were of mucinous, and 13.7% were of endometrioid type; exceptionally serous carcinoma was diagnosed in women younger than 30 years old. Endometrioid cancer had lower disease-free survival than others (p < 0.05). Cases were predominantly diagnosed as poor prognosis disease (FIGO III and IV, 56.2%). Regarding responsiveness to platinum-based therapy, 17.1% of patients were resistant, whereas 24.6%, susceptible. From these, we found equally responsiveness to platinum alone or its association with paclitaxel or cyclophosphamide.</p> <p>Discussion</p> <p>Our data agreed with other studies regarding mean patients' age at diagnosis, histological type frequency, FIGO stages distribution, and chemotherapy regimens. However, the histological type distribution, with equal contribution of mucinous and endometrioid types seems to be a unique characteristic of the studied highly miscegenated population.</p> <p>Conclusion</p> <p>We have enlighten the profile of the studied ovarian cancer population, which might enable the development of more efficient political strategies to control this malignancy that is the fifth leading cause of cancer-related deaths among women.</p

Mitigation of nitrous oxide emissions in grazing systems through nitrification inhibitors: a meta-analysis

Grasslands are the largest contributor of nitrous oxide (N2O) emissions in the agriculture sector due to livestock excreta and nitrogen fertilizers applied to the soil. Nitrification inhibitors (NIs) added to N input have reduced N2O emissions, but can show a range of efficiencies depending on climate, soil, and management conditions. A meta-analysis study was conducted to investigate the factors that influence the efficiency of NIs added to fertilizer and excreta in reducing N2O emissions, focused on grazing systems. Data from peer-reviewed studies comprising 2164 N2O emission factors (EFs) of N inputs with and without NIs addition were compared. The N2O EFs varied according to N source (0.0001-8.25%). Overall, NIs reduced the N2O EF from N addition by 56.6% (51.1-61.5%), with no difference between NI types (Dicyandiamide-DCD; 3,4-Dimethylpyrazole phosphate-DMPP; and Nitrapyrin) or N source (urine, dung, slurry, and fertilizer). The NIs were more efficient in situations of high N2O emissions compared with low; the reduction was 66.0% when EF > 1.5% of N applied compared with 51.9% when EF 10 kg ha(-1). NIs were less efficient in urine with lower N content (<= 7 g kg(-1)). NI efficiency was negatively correlated with soil bulk density, and positively correlated with soil moisture and temperature. Better understanding and management of NIs can optimize N2O mitigation in grazing systems, e.g., by mapping N2O risk and applying NI at variable rate, contributing to improved livestock sustainability