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On the issues of global environment protection, the renewable energy systems have been widely considered. The photovoltaic (PV) system converts solar power into electricity and significantly reduces the consumption of fossil fuels from environment pollution. Besides introducing new materials for the solar cells to improve the energy conversion efficiency, the maximum power point tracking (MPPT) algorithms have been developed to ensure the efficient operation of PV systems at the maximum power point (MPP) under various weather conditions. The integration of reinforcement learning and deep learning, named deep reinforcement learning (DRL), is proposed in this paper as a future tool to deal with the optimization control problems. Following the success of deep reinforcement learning (DRL) in several fields, the deep Q network (DQN) and deep deterministic policy gradient (DDPG) are proposed to harvest the MPP in PV systems, especially under a partial shading condition (PSC). Different from the reinforcement learning (RL)-based method, which is only operated with discrete state and action spaces, the methods adopted in this paper are used to deal with continuous state spaces. In this study,DQN solves the problem with discrete action spaces, while DDPG handles the continuous action spaces. The proposed methods are simulated in MATLAB/Simulink for feasibility analysis. Further tests under various input conditions with comparisons to the classical Perturb and observe (P&O) MPPT method are carried out for validation. Based on the simulation results in this study, the performance of the proposed methods is outstanding and efficient, showing its potential for further applications.Background and Objectives Delirium is a common and major complication subsequent to cardiac surgery. Despite scientific efforts, there are no parameters which reliably predict postoperative delirium. In delirium pathology, natriuretic peptides (NPs) interfere with the blood-brain barrier and thus promote delirium. Therefore, we aimed to assess whether NPs may predict postoperative delirium and long-term outcomes. Materials and Methods To evaluate the predictive value of NPs for delirium we retrospectively analyzed data from a prospective, randomized study for serum levels of atrial natriuretic peptide (ANP) and the precursor of C-type natriuretic peptide (NT-proCNP) in patients undergoing coronary artery bypass grafting (CABG) with or without cardiopulmonary bypass (off-pump coronary bypass grafting; OPCAB). Delirium was assessed by a validated chart-based method. Long-term outcomes were assessed 10 years after surgery by a telephone interview. Results The overall incidence of delirium in the total cohort was 48% regardless of the surgical approach (CABG vs. find more OPCAB). Serum ANP levels >64.6 pg/mL predicted delirium with a sensitivity (95% confidence interval) of 100% (75.3-100) and specificity of 42.9% (17.7-71.1). Serum NT-proCNP levels >1.7 pg/mL predicted delirium with a sensitivity (95% confidence interval) of 92.3% (64.0-99.8) and specificity of 42.9% (17.7-71.1). Both NPs could not predict postoperative survival or long-term cognitive decline. Conclusions We found a positive correlation between delirium and preoperative plasma levels of ANP and NT-proCNP. A well-powered and prospective study might identify NPs as biomarkers indicating the risk of delirium and postoperative cognitive decline in patients at risk for postoperative delirium.As an innovative and economical material, hydroxyapatite does little harm to the environment. In this study, a magnesium hydroxyapatite (Mg-HAP) adsorbent was prepared by doping magnesium. Magnesium doping can increase the hydroxyl groups on the surface of Mg-HAP to form more adsorption sites and improve the removal effect of the heavy metal Zn(II) in water. This study was implemented to survey the effect of different sorption elements, including the liquor initial pH, initial concentration, dose of adsorbents, and other factors, on the adsorption effect. The outcomes show that the sorption effect was best at the time that the liquor was weakly acidic (pH = 6); At a pH of 6, the temperature of 25 °C when the optimal dosage of adsorbent is 0.25 g, the maximum adsorption amount is 62.11 mg/g. Through data fitting, the adsorption process can be accurately described as a pseudo-second-order dynamics model and the Langmuir isotherm equation. According to the thermodynamic analysis, the sorption of zinc ions by Mg-HAP belongs to the process of spontaneous endothermic and entropy increase, and the increase of temperature was conducive to adsorption. Material characterization and analysis indicate that surface complexation and dissolution-precipitation was the main mechanism for adsorption of Zn(II).Background Determination of psychotropic drugs in clinical study is significant, and the establishment of methodologies for these drugs in biological matrices is essential for patients' safety. The search for new methods for their detection is one of the most important challenges of modern scientific research. The methods for analyzing of psychotropic drugs and their metabolites in different biological samples should be based on combining a very efficient separation technique including high-performance liquid chromatography (HPLC), with a sensitive detection method and effectively sample preparation methods. Objective Retention, peaks symmetry and system efficiency of vortioxetine on Hydro RP, Polar RP, HILIC A (with silica stationary phase), HILIC-B (with aminopropyl stationary phase), and ACE HILIC-N (with polyhydroxy stationary phase and SCX columns were investigated. Various mobile phases containing methanol or acetonitrile as organic modifiers and different additives were also applied to obtained optimalarious properties of stationary phases resulted in differences in vortioxetine retention, systems' efficiency, and peaks' shape. Lipophilicity parameters were also determined using different HPLC conditions. The most optimal systems were chosen for the analysis of vortioxetine in biological samples. Both serum and urine or saliva samples collected from patients treated with vortioxetine can be used for the drug determination. For the first time, vortioxetine was detected in patient's saliva. Obtained results indicate on possibility of application of saliva samples, which collection are non-invasive and painless, for determination and therapeutic drug monitoring in patients.
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