An Input-to-State Stability-Based Load Restoration Approach for Isolated Power Systems

An isolated power system (IPS) is usually operated under a bad environment and is influenced by external disturbances. Advanced load restoration technology is an important way to enhance the survivability and reliability of IPS. This paper proposes a fast load restoration approach based on Input-to-State Stability (ISS) theory for IPS. The method can recover load after an outage happens in an IPS under severe perturbations. In the proposed restoration approach, both stability and security constraints are considered based on the ISS theory, which can guarantee the stable and secure operation of IPS during the restoration dynamic process. These constraints have good adaptability for topology transformation and operation status transition of IPS. A heuristic approach to efficiently solve the load restoration problem is proposed, where bisection search is used to check the feasibility of the loads to be restored. Case studies on a typical IPS are used to verify the proposed method

Noninvasive Assessment of Interstitial Fibrosis and Tubular Atrophy in Renal Transplant by Combining Point-Shear Wave Elastography and Estimated Glomerular Filtration Rate

The purpose of this study was to evaluate the feasibility of the combination of point-shear wave elastography (p-SWE) and estimated glomerular filtration rate (eGFR) for assessing different stages of interstitial fibrosis and tubular atrophy (IF/TA) in patients with chronic renal allograft dysfunction (CAD). From September 2020 to August 2021, 47 patients who underwent renal biopsy and p-SWE examinations were consecutively enrolled in this study. The areas under the receiver operating characteristic curves (AUCs) were calculated to evaluate overall accuracy and to identify the optimal cutoff values for different IF/TA stages. A total of 43 patients were enrolled in this study. The renal cortical stiffness and eGFR showed a significant difference between IF/TA Grade 0–1 and Grade 2–3 (p p = 0.02) or tubular atrophy (AUC, 0.88 vs. 0.74, p = 0.02). There was no difference between p-SWE and eGFR in assessing moderate-to-severe IF/TA (AUC, 0.85 vs. 0.79, p = 0.61). Therefore, combining p-SWE and eGFR is worthy of clinical popularization and application

Combinational biosynthesis of phycocyanobilin using genetically-engineered Escherichia coli

Genes of the key enzymes for phycocyanobilin (PCB) biosynthesis were cloned into E. coli and combinationally expressed to produce phycocyanobilin, with autologous heme as substrate. Culture conditions were optimized to achieve similar to 3 mg PCB/l. A protocol for the purification of recombinant phycocyanobilin was established using solvent extraction combined with chromatography, which resulted in a final yield of similar to 0.3 mg PCB/l with a purity > 95 %. Recombinant phycocyanobilin could scavenge hydroxyl radicals with an EC50 of 0.1 mu M.Genes of the key enzymes for phycocyanobilin (PCB) biosynthesis were cloned into E. coli and combinationally expressed to produce phycocyanobilin, with autologous heme as substrate. Culture conditions were optimized to achieve similar to 3 mg PCB/l. A protocol for the purification of recombinant phycocyanobilin was established using solvent extraction combined with chromatography, which resulted in a final yield of similar to 0.3 mg PCB/l with a purity > 95 %. Recombinant phycocyanobilin could scavenge hydroxyl radicals with an EC50 of 0.1 mu M

Grid-to-Point Deep-Learning Error Correction for the Surface Weather Forecasts of a Fine-Scale Numerical Weather Prediction System

Forecasts of numerical weather prediction models unavoidably contain errors, and it is a common practice to post-process the model output and correct the error for the proper use of the forecasts. This study develops a grid-to-multipoint (G2N) model output error correction scheme which extracts model spatial features and corrects multistation forecasts simultaneously. The model was tested for an operational high-resolution model system, the precision rapid update forecasting system (PRUFS) model, running for East China at 3 km grid intervals. The variables studied include 2 m temperature, 2 m relative humidity, and 10 m wind speed at 311 standard ground-based weather stations. The dataset for training G2N is a year of historical PRUFS model outputs and the surface observations of the same period and the assessment of the G2N performance are based on the output of two months of real-time G2N. The verification of the real-time results shows that G2N reduced RMSEs of the 2 m temperature, 2 m relative humidity, and 10 m wind speed forecast errors of the PRUFS model by 19%, 24%, and 42%, respectively. Sensitivity analysis reveals that increasing the number of the target stations for simultaneous correction helps to improve the model performance and reduces the computational cost as well indicating that enhancing the loss function with spatial regional meteorological structure is helpful. On the other hand, adequately selecting the size of influencing grid areas of the model input is also important for G2N to incorporate enough spatial features of model forecasts but not to include the information from the grids far from the correcting areas. G2N is a highly efficient and effective tool that can be readily implemented for real-time regional NWP models

Occurrence and fate of N-nitrosamines in full-scale domestic wastewater treatment plants and their impact on receiving waters along the Lijiang River, China

Domestic wastewaters contaminated with N-nitrosamines pose a significant threat to river ecosystems worldwide, particularly in urban areas with riparian cities. Despite widespread concern, the precise impact of these contaminants on receiving river waters remains uncertain. This study investigated eight N-nitrosamines in wastewater treatment plants (WWTPs) and their adjacent receiving river, the Lijiang River in Guilin City, Southwest China. By analyzing thirty wastewater samples from five full-scale WWTPs and twenty-three river water samples from Guilin, we quantified the mass loads of N-nitrosamines discharged into the surrounding watershed via domestic effluents. The results revealed that N-nitrosodimethylamine (10–60 ng/L), N-nitrosodiethylamine (3.4–22 ng/L), and N-nitrosopyrrolidine (not detected–4.5 ng/g) were predominant in influents, effluents, and sludge, respectively, with the overall removal efficiencies ranging from 17.7 to 65.6% during wastewater treatment. Cyclic activated sludge system and ultraviolet disinfection were effective in removing N-nitrosamines (rates of 59.6% and 24.3%), while chlorine dioxide disinfection promoted their formation. A total of 30.4 g/day of N-nitrosamine mass loads were observed in the Lijiang River water, with domestic effluents contributing about 31.3% (19.4 g/day), followed by livestock breeding wastewater (34.5%, 12.0 g/day), and unknown sources (24.7%, 7.5 g/day). These findings highlight the critical role of WWTPs in transporting N-nitrosamines to watersheds and emphasize the urgent need for further investigation into other potential sources of N-nitrosamine pollution within watersheds

Guest editorial: Sustainably intelligent mobility (SIM)

Guest editorial

circCYP24A1 promotes Docetaxel resistance in prostate Cancer by Upregulating ALDH1A3

Abstract Background Docetaxel (DTX) is the most widely prescribed first-line chemotherapy for advanced prostate cancer (PCa). Unfortunately, DTX resistance invariably emerges, leading to worse prognosis of PCa. Growing evidence has shown that circRNAs had complex spatiotemporal specificity during the tumor development and oncogenesis. This study was designed to investigate the biological functions and possible molecular mechanisms of circRNAs in DTX resistance of PCa. Methods circRNAs in established DTX-resistant DU145 cell line were identified by RNA sequencing. Biological function of circCYP24A1 was verified in vitro and in vivo. The potential role of circCYP24A1 in the development of DTX-resistant PCa was investigated via dual-luciferase reporter assays, RIP assays and RNA pull-down assays. Univariate and multivariate logistic regression analyses was used to predict DTX-chemotherapy response based on patients’ clinical and biological information. Results CircCYP24A1 was identified to be upregulated in DTX-resistant DU145 cells. Upregulated circCYP24A1 was found to suppress the DTX chemosensitivity in vitro and in vivo. Furthermore, we found that circCYP24A1 promoted DTX resistance in PCa via regulating ALDH1A3 expression by sponging miR-1301-3p and activating PI3K/AKT/mTOR signaling pathway. Statistical analyses elucidated that circCYP24A1 was an independent risk factor to predict DTX response (OR = 0.165; 95% CI: 0.038–0.723; P = 0.017). Conclusions This study demonstrated that circCYP24A played an essential role in DTX resistance in PCa, suggesting that circCYP24A1 could be a promising biomarker to predict DTX response and a potential therapeutic target in PCa patients resistant to DTX chemotherapy