An Adaptive Switching Control Strategy under Heavy–Light Load for the Bidirectional LLC Considering Parasitic Capacitance

The LLC topology is widely used to link renewable energy and inverters to provide constant voltage in the smart grid. Due to its characteristics, the voltage regulation range under light load conditions is limited, so that the output voltage cannot be maintained constant. The adaptive switching control strategy is proposed in this paper to keep the output constant. Under heavy load conditions, the voltage is kept constant by adjusting the frequency to ensure the accuracy of the control. The phase shift is adjusted to achieve constant voltage, considering the influence of parasitic capacitance on the modeling process for the changing trend of output voltage in light load conditions. The switching point is calculated from the characteristic curve to ensure that the output voltage is stable during mode switching. In addition, there is a new hysteresis control which is robust near the switching point to cope with the instability of the new energy itself and frequent disturbance under light load. Finally, a 400V–36V–1KW prototype is used to verify this control strategy

Attention Guided Network for Salient Object Detection in Optical Remote Sensing Images

Due to the extreme complexity of scale and shape as well as the uncertainty of the predicted location, salient object detection in optical remote sensing images (RSI-SOD) is a very difficult task. The existing SOD methods can satisfy the detection performance for natural scene images, but they are not well adapted to RSI-SOD due to the above-mentioned image characteristics in remote sensing images. In this paper, we propose a novel Attention Guided Network (AGNet) for SOD in optical RSIs, including position enhancement stage and detail refinement stage. Specifically, the position enhancement stage consists of a semantic attention module and a contextual attention module to accurately describe the approximate location of salient objects. The detail refinement stage uses the proposed self-refinement module to progressively refine the predicted results under the guidance of attention and reverse attention. In addition, the hybrid loss is applied to supervise the training of the network, which can improve the performance of the model from three perspectives of pixel, region and statistics. Extensive experiments on two popular benchmarks demonstrate that AGNet achieves competitive performance compared to other state-of-the-art methods. The code will be available at https://github.com/NuaaYH/AGNet.Comment: accepted by ICANN2022, The code is available at https://github.com/NuaaYH/AGNe

Additional file 3: Figure S3. of Thrombin-induced, TNFR-dependent miR-181c downregulation promotes MLL1 and NF-κB target gene expression in human microglia

Schematic overview of thrombin’s effects upon miR-181c and MLL1 in human microglia. Thrombin (via PAR4) induces TNF-α secretion from human microglia [21]. Thrombin-induced TNF-α (via TNFR) suppresses miR-181c levels. This suppression of the inhibitory miR-181c promotes MLL1 expression, increases NF-κB activity, and upregulates downstream NF-κB target gene expression in human microglia. (JPG 456 kb

Additional file 2: Figure S2. of Thrombin-induced, TNFR-dependent miR-181c downregulation promotes MLL1 and NF-κB target gene expression in human microglia

Thrombin’s proteolytic activity contributed to its effects upon miR-181c and MLL1 expression in human microglia. (A) Validation of the thrombin-specific proteolytic inhibitor PPACK’s inhibition of thrombin activity. Thrombin’s proteolytic activity was measured via a chromogenic assay following pre-incubation in the absence or presence of various concentrations of PPACK. Heat-inactivated (boiled) thrombin was applied as a negative control. *p < 0.05 versus control, †p < 0.05 versus boiled thrombin, ‡p < 0.05 versus thrombin. (B) Pre-incubating with PPACK significantly inhibited thrombin’s effects upon miR-181c and MLL1 expression. *p < 0.05 versus control, †p < 0.05 versus thrombin. (TIF 598 kb

Critical care admission following elective surgery was not associated with survival benefit: prospective analysis of data from 27 countries

This was an investigator initiated study funded by Nestle Health Sciences through an unrestricted research grant, and by a National Institute for Health Research (UK) Professorship held by RP. The study was sponsored by Queen Mary University of London

Prospective observational cohort study on grading the severity of postoperative complications in global surgery research

Background The Clavien–Dindo classification is perhaps the most widely used approach for reporting postoperative complications in clinical trials. This system classifies complication severity by the treatment provided. However, it is unclear whether the Clavien–Dindo system can be used internationally in studies across differing healthcare systems in high- (HICs) and low- and middle-income countries (LMICs). Methods This was a secondary analysis of the International Surgical Outcomes Study (ISOS), a prospective observational cohort study of elective surgery in adults. Data collection occurred over a 7-day period. Severity of complications was graded using Clavien–Dindo and the simpler ISOS grading (mild, moderate or severe, based on guided investigator judgement). Severity grading was compared using the intraclass correlation coefficient (ICC). Data are presented as frequencies and ICC values (with 95 per cent c.i.). The analysis was stratified by income status of the country, comparing HICs with LMICs. Results A total of 44 814 patients were recruited from 474 hospitals in 27 countries (19 HICs and 8 LMICs). Some 7508 patients (16·8 per cent) experienced at least one postoperative complication, equivalent to 11 664 complications in total. Using the ISOS classification, 5504 of 11 664 complications (47·2 per cent) were graded as mild, 4244 (36·4 per cent) as moderate and 1916 (16·4 per cent) as severe. Using Clavien–Dindo, 6781 of 11 664 complications (58·1 per cent) were graded as I or II, 1740 (14·9 per cent) as III, 2408 (20·6 per cent) as IV and 735 (6·3 per cent) as V. Agreement between classification systems was poor overall (ICC 0·41, 95 per cent c.i. 0·20 to 0·55), and in LMICs (ICC 0·23, 0·05 to 0·38) and HICs (ICC 0·46, 0·25 to 0·59). Conclusion Caution is recommended when using a treatment approach to grade complications in global surgery studies, as this may introduce bias unintentionally