Maximum Power Point Tracking of Photovoltaic System Based on Reinforcement Learning.

The maximum power point tracking (MPPT) technique is often used in photovoltaic (PV) systems to extract the maximum power in various environmental conditions. The perturbation and observation (P&O) method is one of the most well-known MPPT methods; however, it may face problems of large oscillations around maximum power point (MPP) or low-tracking efficiency. In this paper, two reinforcement learning-based maximum power point tracking (RL MPPT) methods are proposed by the use of the Q-learning algorithm. One constructs the Q-table and the other adopts the Q-network. These two proposed methods do not require the information of an actual PV module in advance and can track the MPP through offline training in two phases, the learning phase and the tracking phase. From the experimental results, both the reinforcement learning-based Q-table maximum power point tracking (RL-QT MPPT) and the reinforcement learning-based Q-network maximum power point tracking (RL-QN MPPT) methods have smaller ripples and faster tracking speeds when compared with the P&O method. In addition, for these two proposed methods, the RL-QT MPPT method performs with smaller oscillation and the RL-QN MPPT method achieves higher average power.

Breast cancer pre-clinical screening using infrared thermography and artificial intelligence: a prospective, multicentre, diagnostic accuracy cohort study.

BACKGROUND: Given the limited access to breast cancer (BC) screening, the authors developed and validated a mobile phone-artificial intelligence-based infrared thermography (AI-IRT) system for BC screening. MATERIALS AND METHODS: This large prospective clinical trial assessed the diagnostic performance of the AI-IRT system. The authors constructed two datasets and two models, performed internal and external validation, and compared the diagnostic accuracy of the AI models and clinicians. Dataset A included 2100 patients recruited from 19 medical centres in nine regions of China. Dataset B was used for independent external validation and included 102 patients recruited from Langfang People's Hospital. RESULTS: The area under the receiver operating characteristic curve of the binary model for identifying low-risk and intermediate/high-risk patients was 0.9487 (95% CI: 0.9231-0.9744) internally and 0.9120 (95% CI: 0.8460-0.9790) externally. The accuracy of the binary model was higher than that of human readers (0.8627 vs. 0.8088, respectively). In addition, the binary model was better than the multinomial model and used different diagnostic thresholds based on BC risk to achieve specific goals. CONCLUSIONS: The accuracy of AI-IRT was high across populations with different demographic characteristics and less reliant on manual interpretations, demonstrating that this model can improve pre-clinical screening and increase screening rates.

Investigation of T site variation in spinel aluminates TAl2O4 (T= Mg, Zn & Cu), and formation of electrocatalyst CuAl2O4/carbon for efficient sensing application.

Spinel structured aluminates TAl2O4 (T = Mg, Zn, and Cu) were synthesized by a facile hydrothermal method. The resultant enhancement in the electrochemical behavior was achieved due to the covalent synergism among the elements coexisting together. Structural and morphological characterizations were performed by X-ray diffraction, Fourier transform infrared spectroscopy, Raman spectroscopy, and field emission scanning electron microscopy. MgAl2O4, ZnAl2O4 and CuAl2O4 has displayed same space group Fd3m of Laue class lattice type of the cubic structure as they were synthesized at same temperature (600 °C). CuAl2O4 spinel structure displayed a nanoneedle like structure along with the small sized cylindrical particles alongside to which CuAl2O4 spinel is combined with activated carbon (CuAl/C) and was applied to develop a facile sensor for the electrochemical detection of Acetaminophen (ACAP) using cyclic voltammetry (CV) and differential pulse voltammetry (DPV), which exhibited maximum conductivity, and a substantial electroactive surface area. Finally, the defect-rich composite, CuAl/C, showed excellent sensor performance towards DPV with 21.5 nM limit of detection (LOD) in a wide linear working range of 0.199 µM-165.88 µM ACAP concentration, with a high sensitivity of 19.1221 µA µM-1cm2. Additionally, the sensor showed excellent recovery results in real-time analysis for environmental aquatic samples like industrial wastewater and Tuna Fish.

The Association of Diabetic Retinopathy and Cardiovascular Disease: A 13-Year Nationwide Population-Based Cohort Study.

OBJECTIVES: Previous studies have demonstrated that patients with diabetic retinopathy (DR) have a higher prevalence of risk factors known to be associated with cardiovascular disease (CVD). We hypothesized that patients with more severe DR could have a higher relative risk of CVD. METHODS: To test this hypothesis, we used the National Health Insurance Research Database (NHIRD) to evaluate whether associations exist between DR and CVD. The data for this nationwide population-based retrospective cohort study were obtained from the NHIRD in Taiwan from 2001 to 2013. The assessed study outcome used was the incidence and other statistical analyses of CVD in patients with DR during a 13-year follow-up period. RESULTS: Our findings obtained from 2001 to 2013 suggest that the incidence rates of CVD are 2.026 times that of diabetes mellitus (DM) without DR (95% C.I. = 1.876-2.187) and 2.75 times that of DM with DR (95% C.I. = 2.487-3.04) compared with the Non-DM group. CONCLUSION: The relative risk of CVD in DR was greater than that in the Non-DM group for both men and women. Targeted monitoring of DM, especially the co-existence of diabetic retinopathy, is of utmost importance in the clinical care of the DM population.

Oligomerization is crucial for the stability and function of heme oxygenase-1 in the endoplasmic reticulum.

Heme oxygenase-1 (HO-1), a stress-inducible enzyme anchored in the endoplasmic reticulum (ER) by a single transmembrane segment (TMS) located at the C terminus, interacts with NADPH cytochrome P450 reductase and biliverdin reductase to catalyze heme degradation to biliverdin and its metabolite, bilirubin. Previous studies suggested that HO-1 functions as a monomer. Using chemical cross-linking, co-immunoprecipitation, and fluorescence resonance energy transfer (FRET) experiments, here we showed that HO-1 forms dimers/oligomers in the ER. However, oligomerization was not observed with a truncated HO-1 lacking the C-terminal TMS (amino acids 266-285), which exhibited cytosolic and nuclear localization, indicating that the TMS is essential for the self-assembly of HO-1 in the ER. To identify the interface involved in the TMS-TMS interaction, residue Trp-270, predicted by molecular modeling as a potential interfacial residue of TMS alpha-helices, was mutated, and the effects on protein subcellular localization and activity assessed. The results showed that the W270A mutant was present exclusively in the ER and formed oligomers with similar activity to those of the wild type HO-1. Interestingly, the W270N mutant was localized not only in the ER, but also in the cytosol and nucleus, suggesting it is susceptible to proteolytic cleavage. Moreover, the microsomal HO activity of the W270N mutant was significantly lower than that of the wild type. The W270N mutation appears to interfere with the oligomeric state, as revealed by a lower FRET efficiency. Collectively, these data suggest that oligomerization, driven by TMS-TMS interactions, is crucial for the stabilization and function of HO-1 in the ER.