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The traditional Power Flow Calculation (PLF) method of the distribution network is affected by the accuracy of model parameters, the convergence of the solution method, and other factors. At the same time, the accuracy of the PLF of the distribution network will directly affect the optimization effect of the distribution network. In this paper, a data-driven power flow analysis and the volt/var optimization control strategy for the distribution network are proposed. Firstly, the CatBoost machine learning model for the distribution network power flow analysis is proposed, and the nonlinear mapping relationship between the distribution network state and power flow results is described from the data-driven perspective. Secondly, the influence of PhotoVoltaic (PV) power supply on the distribution network is analyzed, and the volt/var optimization model based on PV power supply is proposed. Then, the volt/var optimization strategy of the distribution network based on data-driven power flow analysis is proposed to ensure the safe and stable operation of the distribution network voltage and reduce the operating network loss of the distribution network without the need for network parameters and other information. Finally, the IEEE 33 node system is used to verify the effectiveness of the proposed strategy, the results of the example show that the data-driven PLF method can accurately perceive the voltage and loss of the distribution network. The proposed optimization strategy can stabilize the voltage of the distribution network in the range of 0.95–1.05, and the loss of the distribution network is reduced from 6.879 MWh to 3.369 MWh.

Due to the fluctuation of PV power, it is difficult to keep the active power of the PV grid-connected inverter constant. To address the above problems, this paper proposed a new three-level integrated photovoltaic storage machine consisting of a T-type three-level DC/AC converter, a three-level Boost converter and a three-level bi-directional DC/DC converter and related control strategies. The three-level structure allowed for lower switching losses resulting in higher system efficiency and wider voltage range adaptability. In terms of control, frequency differentiation and deviation control were introduced in the control of the energy storage DC/DC converter to achieve frequency regulation of the transient/static support of the active power of the parallel network. The simulation and experiment show that when the frequency fluctuation range is 50.02~49.97 Hz (meeting the national standard), the new optical storage all-in-one machine proposed in this paper can operate stably and be easily realized.

ObjectiveTo investigate the biological function and molecular mechanism of long non-coding RNA Linc‑pint in colorectal cancer.MethodsQuantitative real‑time quantitative （qRT‑PCR） was performed to detect the expression level of Linc‑pint in 31 pairs of colorectal cancer tumor and adjacent normal tissues； correlation between the expression level of Linc‑pint and the clinicopathological characteristics was analyzed by the chi‑square test. Kaplan-Meier survival analysis was used to assess the relationship between Linc‑pint expression level and the prognosis of patients. Cox regression model was used to analyze the relationship between clinicopathological characteristics and the prognosis of patients. Expression level of Linc‑pint were detected by qRT‑PCR in 5 common colorectal cancer cell lines. Effect of Linc‑pint on cell proliferation， invasion and migration was measured by cell counting kit‑8 assay， Transwell assay and harvested xenografts from nude mice. qRT‑PCR was performed to detect the expression level of Linc‑pint's target gene micro RNA（miR）‑21 in 31 pairs of colorectal cancer tumor tissues and adjacent normal tissues. Pearson correlation coefficient was used to assess the correlation between Linc‑pint and miR‑21. qRT‑PCR was used to detect the expression of overexpression of Linc‑pint on miR‑21 in colorectal cancer cells.ResultsExpression level of Linc‑pint in normal tissues （3.95±1.16） was significantly higher than that in colorectal cancer tissues （2.74±0.95） （t=6.17， P

The present study investigates the relationship between the near-infrared (NIR) spectral characteristics of cross-linked polyethylene (XLPE) insulation materials and their macroscopic properties, with the aim of establishing a reference framework for non-destructive material aging analysis. Accelerated thermal aging tests were conducted on samples of XLPE cables. These samples underwent Fourier-transform infrared spectroscopy (FTIR), elongation at break (EAB), and tensile strength (TS) tests. The temporal variation curves of the carbonyl index (CI), EAB, and TS were obtained at aging temperatures of 105 °C, 135 °C, 155 °C, and 180 °C. Additionally, NIR spectroscopy was performed on the aged XLPE samples, producing absorbance curves corresponding to different aging times at these temperatures. The absorption peaks of 'C-H (-CH2-)' (1730 nm/1764 nm) were analyzed to determine their temporal variation patterns. Finally, a correlation analysis was conducted between the NIR results and those of the FTIR, EAB, and TS tests, revealing numerical relationships between NIR characteristic peaks and FTIR, EAB, and TS data. These quantified correlations demonstrate that NIR can effectively represent macroscopic mechanical properties, thereby simplifying the procedures for monitoring material aging and providing valuable results without requiring destructive testing. Results indicate that there is a certain feasibility in replacing traditional cable aging tests with NIR. [ABSTRACT FROM AUTHOR]

A laser welding with wire filler feeding was developed to replace traditional arc welding process for joining aluminium alloy railcar body components. A three-dimensional (3D) thermo-elastic-plastic finite element (FE) model was applied to compute the plastic strains of weld zone in a downsized aluminium alloy plate with butt-joint, T-joint and fillet-joint configurations, respectively, combined with corresponding experimental validations. The achieved plastic strains at the weld zone were then input as inherent strain loadings into elastic structural FE model of fully sized aluminium alloy railcar body components to predict the welding induced distortion with the experimentally measured out-of-plane distortions. The experimentally validated FE model was then further applied for optimizing the inverse pre-deformation of plates to counteract the welding induced deformation, finally to mitigate the welding distortion issues. [ABSTRACT FROM AUTHOR]

Antimicrobial therapy remains one of the major global challenges, particularly in the absence of effective treatment strategies for drug‐resistant bacteria. In this study, a comprehensive treatment approach is proposed for drug‐resistant bacterial wound infections based on the development of thermal‐cascade multifunctional therapeutic systems (MTSs), spanning from the design of functional nanoscale materials to macroscopic smart hydrogel. Within the MTSs, functional antibiotic‐loaded hybrid nanoclusters enable targeted therapeutic delivery and synergistic mild hyperthermia‐antibiotic treatment, strongly suppressing drug‐resistant bacteria while demonstrating excellent biocompatibility with normal cells and tissues. Furthermore, near‐infrared irradiation can trigger the photothermal effects of hybrid nanoclusters to induce gelation of thermal‐sensitive hydrogel, forming MTSs to serve as highly adaptable, drug‐enriched protective dressings for infected wounds. Both in vitro and in vivo results substantiate that MTSs enhance the bioavailability of therapeutic agents (including bacterial internalization and tissue penetration), exert synergistic effects to completely eradicate drug‐resistant bacteria, promoted wound healing and revascularization, and demonstrate excellent biocompatibility. This work offers an innovative demonstration to address drug‐resistant bacterial infections through the advancement of sophisticated material systems. [ABSTRACT FROM AUTHOR]