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Oil–paper insulation is the critical insulation element in the modern power system. Under a harsh operating environment, oil–paper insulation will deteriorate gradually, resulting in electrical accidents. Thus, it is important to evaluate and monitor the insulation state of oil–paper insulation. Firstly, this paper introduces the geometric structure and physical components of oil–paper insulation and shows the main reasons and forms of oil–paper insulation's degradation. Then, this paper reviews the existing condition assessment techniques for oil–paper insulation, such as the dissolved gas ratio analysis, aging kinetic model, cellulose–water adsorption isotherm, oil–paper moisture balance curve, and dielectric response technique. Additionally, the advantages and limitations of the above condition assessment techniques are discussed. In particular, this paper highlights the dielectric response technique and introduces its evaluation principle in detail: (1) collecting the dielectric response data, (2) extracting the feature parameters from the collected dielectric response data, and (3) establishing the condition assessment models based on the extracted feature parameters and the machine learning techniques. Finally, two full potential studies are proposed, which research hotspots' oil–paper insulation and the electrical–chemical joint evaluation technique. In summary, this paper concludes the principles, advantages and limitation of the existing condition assessment techniques for oil–paper insulation, and we put forward two potential research avenues. [ABSTRACT FROM AUTHOR]

Protection of cultural relics and sites is of great significance. In this study, the new gray-green thin-layer biological crust on the rammed soil surface at the Shanhaiguan Great Wall in China was found. The emergence of this material has substantially improved the resistance of the rammed Earth Great Wall to rain erosion. 16S rRNA gene sequencing on the surface crusts of rammed Earth was performed. Results show the biological crusts were mainly algae-based composite crusts containing fungi. At the genus level, microalgae and Sphingomycetes were predominant. Under scanning electron microscopy (SEM), algae filaments dominated by filamentous algae overlapped and intertwined with each other. Furthermore, polysaccharide organic matter secreted by algae formed a covering film. The two formed a complex spatial network structure to envelop soil particles, which enhances erosion resistance. The conformable biological crusting is expected to be used as a new civil engineering material for the protection of rammed Earth sites in the future. [ABSTRACT FROM AUTHOR]

The evaluation of the state of transformer oil-immersed insulation based on the traditional methods becomes unreliable due to the nonuniform aging effect. To address this issue, a novel model for accessing the aging information of transformer oil-immersed insulation at the hotspot is proposed. In this article, frequency-domain spectroscopy (FDS) is selected as the carrier for characterizing the aging states of oil-immersed insulation. The multiobjective function for reversing the FDS of the hotspot is constructed based on the dielectric response equivalent circuit. Then, the nondominated sorting genetic algorithm with the multiconstraint scheme is proposed to solve the multiobjective function, by which the FDS data of the transformer hotspot region are acquired. The verification results indicate that the average standard deviation between the computed FDS of the hotspot region and the measured data is less than 0.26. The contribution of this article is in the exploration of the proposed model as a potential tool to extract the FDS data of the hotspot region. This will promote a more reliable aging evaluation of the transformer oil-immersed paper insulation at the hotspot. [ABSTRACT FROM AUTHOR]

The multi format test signal generator mentioned in this paper is the video signal generator named TG8000 produced by Tektronix Company. I will introduce the function about remote control for signal generator, how to connect the computer to the instrument, and how to remote control. My topic uses my computer to connect the instrument through the 10/100/1000 BASE-T port on the rear panel of TG8000. Then I write program to transmit SCPI (Standard Commands for Programmable Instruments) to control TG8000. The application is running on the Windows operating system, the programming language is C#, development environment is Microsoft Visual Studio 2010, using the TCP/IP protocol based on Socket. And the method of remote control refers to the application called TGSetup which is developed by Tektronix Company. This paper includes a brief summary of the basic principle, and introduce for details about the process of remote control software development, and how to use my software. In the end, I will talk about the advantages of my software compared with another one.

The traditional method for transformer moisture diagnosis is to establish empirical equations between feature parameters extracted from frequency domain spectroscopy (FDS) and the transformer’s moisture content. However, the established empirical equation may not be applicable to a novel testing environment, resulting in an unreliable evaluation result. In this regard, it is acknowledged that FDS combined with machine learning is more suitable for estimating moisture content in a variety of test environments. Nonetheless, the accuracy of the estimation results obtained using the existing method is limited by the algorithm’s inability to generalize. To address this issue, we propose an AdaBoost algorithm-enhanced back-propagation neural network (BP_AdaBoost). This study creates a database by extracting feature parameters from the FDS that characterize the insulation states of the prepared samples. Then, using the BP_AdaBoost algorithm and the newly constructed database, the moisture estimation models are trained. Finally, the results of the estimation are discussed in terms of laboratory and field transformers. By comparing the proposed BP_AdaBoost algorithm to other intelligence algorithms, it is demonstrated that it not only performs better in generalization, but also maintains a high level of accuracy. [ABSTRACT FROM AUTHOR]

The generation and distribution of furfural are significantly affected by moisture content in the insulating paper. However, the diffusion mechanism of furfural under moisture effect is not clear, hence, this study investigates the effect of moisture on the diffusion characteristics of furfural by combining macro experiment and micro molecular dynamics simulation. The simulation results demonstrate that the increased moisture content in paper accelerates the diffusion of furfural from paper to oil, which is also proved by the experimental data. Then, the results of interaction energy analysis indicate that the increase of moisture enhances the van der Waals force between oil and furfural. The present findings are expected to improve the theoretical level of furfural analysis, which will facilitate the aging evaluation of the transformer insulating paper based on furfural. [ABSTRACT FROM AUTHOR]

The predictive model of aging indicator based on intelligent algorithms has become an auxiliary method for the aging condition of transformer polymer insulation. However, most of the current research on the concentration prediction of aging products focuses on dissolved gases in oil, and the concentration prediction of alcohols in oil is ignored. As new types of aging indicators, alcohols (methanol, ethanol) are becoming prevalent in the aging evaluation of transformer polymer insulation. To address this, this study proposes a prediction model for the concentration of alcohols based on a genetic-algorithm-optimized support vector machine (GA-SVM). Firstly, accelerated thermal aging experiments on oil-paper insulation are conducted, and the concentration of alcohols is measured. Then, the data of the past 4 days of aging are used as the input feature of SVM, and the GA algorithm is utilized to optimize the kernel function parameter and penalty factor of SVM. Moreover, the concentrations of methanol and ethanol are predicted, after which the prediction accuracy of other algorithms and GA-SVM are compared. Finally, an industrial software program for predicting the concentration of methanol and ethanol is established. The results show that the mean square errors (MSE) of methanol and ethanol concentration predictions of the model proposed in this paper are 0.008 and 0.003, respectively. The prediction model proposed in this paper can track changes in methanol and ethanol concentrations well, providing a theoretical basis for the field of alcohol concentration prediction in transformer oil. [ABSTRACT FROM AUTHOR]

The space charge effect of transformer insulating paper will distort its internal electric field, and its space charge effect will be more prominent under extremely complex working conditions. At present, the micromechanism of charge transport and electric field distortion characteristics of paperboard are not clear under complex working conditions. So in this article, based on the bipolar carrier transport (BCT) model and the dynamic carrier balance model, the effects of high temperature, aging degree, moisture content, and bent degree on charges accumulation in paperboard are studied under dc high voltage by numerical simulation and the measured data needed for simulation. The results show that the higher temperature strengthens the carrier migration, deepens the injection depth of the charge, and aggravates the distortion of electric field intensity in paperboard. The more extended the aging time of paperboard, the greater the internal trap density and the deeper the trap depth, which lead to charges migration difficultly. Increasing water content in the paperboard will accelerate space charges to reach a steady state, while further increasing it will slow down this process, which is related to the shallow trap getting deeper. When the critical part of paperboard is extruded, many traps are introduced, resulting in charges accumulation seriously. The research results can reference the design of paperboard and the maintenance of transformer insulation system. [ABSTRACT FROM AUTHOR]

Stellar-mass black holes are found in X-ray-emitting binary systems, where their mass can be determined from the dynamics of their companion stars (1-3). Models of stellar evolution have difficulty producing [...]

Objective: This research probed into the molecular mechanisms of long non-coding RNA (lncRNA) VPS9D1 Antisense RNA 1 (VPS9D1-AS1) in lung adenocarcinoma (LUAD). Methods: lncRNA expression level was evaluated bioinformatically, and its downstream miRNA/mRNA regulatory axis was predicted by bioinformatics methods as well. qRT-PCR was used to measure VPS9D1-AS1, miRNA-30a-5p, and kinesin family member 11 (KIF11) expression. Western blot was performed to measure KIF11 protein expression. Proliferation, migration, and invasion of LUAD cells were all observed by cell biological function experiments. Dual-luciferase assay detected binding between miRNA-30a-5p and VPS9D1-AS1 or KIF11, respectively. RIP experiment detected interaction between VPS9D1-AS1 and miRNA-30a-5p. Results: VPS9D1-AS1 and KIF11 were increased in LUAD, whereas miRNA-30a-5p was decreased. VPS9D1-AS1 promoted the malignant progression of LUAD cells and could sponge miRNA-30a-5p. MiRNA-30a-5p could restore the impact of VPS9D1-AS1 on LUAD cells. KIF11 was a target downstream of miRNA-30a-5p. VPS9D1-AS1 could upregulate KIF11 expression through competitively sponging miRNA-30a-5p, and KIF11 could restore the impact of miRNA-30a-5p on LUAD cells. Conclusion: VPS9D1-AS1 could foster malignant progression of LUAD via regulating miRNA-30a-5p/KIF11 axis, suggesting that VPS9D1-AS1 is key to regulating the malignant progression of LUAD. [ABSTRACT FROM AUTHOR]

This work investigates which acid can mainly lead to the reduction of alcohols contents in insulating oil during transformer oil-paper insulation aging. In terms of the activation free energy barrier theory, the microscopic mechanisms for the preferential reactions of methanol and ethanol with formic, acetic, naphthenic and stearic acids are analyzed. It is revealed that the decrease in alcohols concentrations in the middle and late stages of transformer oil-paper insulation aging is mainly caused by the reaction between alcohols and naphthenic acid. The results are cross-validated by utilizing the frontier molecular orbital theory and accelerated thermal aging experiments. Additionally, it is observed that methanol is more susceptible to the effect of acids than ethanol in the middle and late stages of aging. The obtained conclusions, in this paper, could provide a theoretical basis for using alcohols in oil as aging indicators to characterize the full-stage aging status of transformer paper insulation. [ABSTRACT FROM AUTHOR]

A growing body of evidence suggests that the ethanol dissolved in the oil can be used as an indicator to effectively monitor the aging behavior of insulating paper. In this study, thermal aging experiments are performed on oil-paper systems with different initial moisture contents and aging temperatures, and then a gas chromatography-mass spectrometer equipped with an automatic headspace sampler is used to test the ethanol contents of the oil samples. The variations and correlations of ethanol contents with temperature, moisture and aging degree are analyzed. The experimental results show that the ethanol contents in oil had a strong correlation with temperature, and is also affected by the cellulose hydrolysis. In addition, a preliminary lifespan assessment of the oil-paper systems under laboratory conditions is conducted by establishing the relationship between ethanol and the degree of polymerization. Then, the time-temperature superposition method is applied to the relationship, and a lifespan model with any temperature is determined according to the ethanol kinetic equation. Based on the model, further observation of the fitting parameters in the case of the two moisture contents (0.8%, 2.3%), the goodness of fit reached higher values of 0.961 and 0.973, respectively. The results of this promising model can help us to a better understanding of ethanol indicator to condition assessment for the transformer paper insulation. [ABSTRACT FROM AUTHOR]

The heterocharge accumulated in the oil‐paper insulation system of the converter transformer will enhance the local electric field and cause insulation deterioration. Numerical simulation is an effective method to analyze heterocharge. Currently, the numerical simulation of heterocharge is mainly based on the bipolar charge transport (BCT) model and the impurity ion transport (IIT) model. However, the effects of temperature, conductivity, and thickness of oil‐impregnated paper on charge transport have not been considered in these models. In view of this, a modified charge transport (MCT) model by introducing the Maxwell–Wagner model and heat conduction equation is proposed in this paper based on the BCT model and IIT model. Then, the influence of multi‐factors (temperature gradient, moisture content, and oil‐impregnated paper thickness) on heterocharge accumulation is investigated by using the MCT model. The simulation results obtained by the MCT model are more consistent with the experimental results than the BCT model, which proves the accuracy and superiority of the MCT model. Moreover, the increase in temperature gradient, moisture content, and oil‐impregnated paper thickness will enlarge the ion dissociation rate, conductivity, and trap density, and thus promote the generation of heterocharge. In that respect, the MCT model is expected to optimize the insulation design and provide a reference for space charge dynamic simulation. [ABSTRACT FROM AUTHOR]

The total/partial oil change treatment can affect the furfural partitioning in oil-paper-pressboard insulation, resulting in poor accuracy of furfural analysis. Moreover, due to the high cost of total oil change, partial oil change is more practical during transformer operation. This paper investigates the furfural partitioning in the oil-paper-pressboard insulation under partial oil change conditions. First, the initial furfural partitioning equation with non-oil change is proposed based on the obtained furfural content in oil, paper, and pressboard. Then, the modified furfural partitioning model under partial oil change condition is established by introducing a correction factor. Moreover, a preliminary correction scheme for the furfural partitioning model considering the influence of moisture and acid is provided. Finally, furfural content in oil-Kraft paper and oil-thermally upgraded Kraft (TUK) paper insulation are discussed, and results indicate that the proposed modified furfural partitioning model is not suitable for the oil-TUK paper insulation. This work can provide theoretical support for furfural analysis of oil-immersed transformers. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study is to investigate and analyze the prevalence and influencing factors of stroke in hypertensive patients aged 60 and above in Jiading District, Shanghai. Methods: The population-based study included 18,724 screened people with hypertension (age ≥ 60 years, 48.7% women). From 2016 to 2019, data on demographics, potential influencing factors and health status were collected through face-to-face interviews, physical examinations, and laboratory tests. Logistic multivariate logistic regression model was used to analyze the influencing factors associated with stroke. Results: Among the object of study from 2016 to 2019, 2,025 patients were screened for stroke, with the overall prevalence rate of 10.82% (10.41%-11.23%). Multivariate adjusted model analysis showed that dyslipidemia (OR:1.31,95%CI:1.19–1.45), lack of exercise (OR:1.91,95%CI:1.32–2.76), atrial fibrillation [OR:1.49,95%CI:1.35–1.65), family history of stroke (OR:2.18,95%CI:1.6–2.88) were the significant independent influencing factors of stroke in hypertensive patients over 60 years old. When these four factors were combined, compared with participants without any of these factors, the multi-adjusted odds ratios (95% confidence interval) of risk of stroke for persons concurrently having one, two and three or more of these factors were 1.89 (1.67–2.13), 2.15 (1.86–2.47) and 6.84 (4.90–9.55), respectively (linear trend P < 0.001); after multivariate adjustment, the family history of stroke had additive interaction with lack of exercise [RERI = 1.08(0.22–1.94), AP = 0.19(0.04–0.35), S = 1.31(1.02–1.69)], dyslipidemia [RERI = 0.87(0.41–1.33), AP = 0.23(0.08–0.38), S = 1.46(1.04–2.05)]. Conclusion: The prevalence of stroke was high in hypertensive patients aged 60 and above in Jiading District, Shanghai. Dyslipidemia, lack of exercise, atrial fibrillation and family history of stroke were significantly associated with stroke in hypertensive population. Stroke risk can be increased especially when multiple factors coexisting, and family history of stroke combined with a lack of exercise or dyslipidemia. [ABSTRACT FROM AUTHOR]

The accuracy and feasibility of the traditional XY model of transformer oil–paper insulation system are disputable since it ignored the effect of non‐uniform aging and conductance on dielectric response property. Given this issue, this work attempted to report a modified XY model to overcome these defects. The novelty of this work is in the exploration of the modified XY model as a potential tool for establishing the quantitative correlation among the complex relative permittivity of the liquid insulation, solid insulation, and liquid–solid composite insulation. In that respect, the presented verification experiments proved the feasibility and accuracy of the reported model. The contributions are expected to provide a theoretical basis for the condition evaluation of transformer solid insulation under non‐uniform aging conditions. [ABSTRACT FROM AUTHOR]

Moisture accumulates with the growing aging progress of oil-paper insulation and further shortens the remaining life of the transformer. The frequency-domain spectroscopy (FDS) technique can be used to realize the moisture estimation. However, the moisture estimation results would be unreliable once the aging effect on FDS was ignored. Given this issue, an alternative model including the aging effect is thus proposed using FDS and intelligent algorithm. In this work, the feature parameters of FDS data are used to build the databases for characterizing the aging degree and moisture. Then, the moisture estimation models are developed using the weighted K-nearest neighbor (K-NN) algorithm. The accuracy and applicability of the proposed models are finally discussed in laboratory and field conditions. In that respect, the findings reveal that the reported model is available for moisture estimation of transformer oil-paper insulation under various aging degrees and test temperatures. [ABSTRACT FROM AUTHOR]

The influence of nonuniform aging has not been considered in the prediction of the frequency domain spectroscopy (FDS) of the transformer oil-paper insulation (OPI) when using the finite element method (FEM). Given this issue, the modified simulation model was constructed based on the XY model and FEM. In the current work, the dielectric response property of the pressboards with different aging conditions in the modified model was characterized by its dielectric response parameters measured in the lab. Then the modified simulation model constructed in a 3-D system would be applied to study the effect of both nonuniform aging and the axial geometry on the FDS of OPI. Finally, the feasibility of the proposed models was verified by comparing the measured FDS and the predicted FDS. This article is expected to provide a model for predicting the FDS of the transformer OPI including the effect of nonuniform aging. [ABSTRACT FROM AUTHOR]

One of the key tasks of the overhead line power equipment inspection based on aerial images acquired by unmanned aerial vehicles is to determine whether the insulators are faulty. However, the fault area on the insulator string occupies a relatively small portion of the entire image, which will make detection difficult. This article presents an intelligent fault detection method for overhead line insulators based on aerial images and improved you only look once (YOLOv3) deep learning technology. In our model, a densely connected feature pyramid network (FPN) is proposed. First, this network can improve the utilization rate of the strong semantic information of deep features and the localization information of shallow features, thereby improving the small insulator fault (missing-cap) detection performance of the YOLOv3 model. Second, this network reduces the number of parameters of the YOLOv3 model, resulting in a low risk of network over-fitting for small datasets. The experimental results on the CPLID dataset show that our model has higher detection accuracy in localization of overhead line insulators and detection of insulator missing-cap faults compared with the existing works. [ABSTRACT FROM AUTHOR]

Accumulating evidence has suggested that extracellular vesicles (EVs) play a crucial role in lung cancer treatment. Thus, we aimed to investigate the modulatory role of bone marrow mesenchymal stem cell (BMSC)‐EV‐derived let‐7i and their molecular mechanism in lung cancer progression. Microarray‐based analysis was applied to predict lung cancer‐related miRNAs and their downstream genes. RT‐qPCR and Western blot analyses were conducted to determine Let‐7i, lysine demethylase 3A (KDM3A), doublecortin‐like kinase 1 (DCLK1) and FXYD domain‐containing ion transport regulator 3 (FXYD3) expressions, after which dual‐luciferase reporter gene assay and ChIP assay were used to identify the relationship among them. After loss‐ and gain‐of‐function assays, the effects of let‐7i, KDM3A, DCLK1 and FXYD3 on the biological characteristics of lung cancer cells were assessed. Finally, tumour growth in nude mice was assessed by xenograft tumours in nude mice. Bioinformatics analysis screened out the let‐7i and its downstream gene, that is KDM3A. The findings showed the presence of a high expression of KDM3A and DCLK1 and reduced expression of let‐7i and FXYD3 in lung cancer. KDM3A elevated DCLK1 by removing the methylation of H3K9me2. Moreover, DCLK1 suppressed the FXYD3 expression. BMSC‐EV‐derived let‐7i resulted in the down‐regulation of KDM3A expression and reversed its promoting role in lung cancer development. Consistently, in vivo experiments in nude mice also confirmed that tumour growth was suppressed by the BMSC‐EV‐derived let‐7i. In conclusion, our findings demonstrated that the BMSC‐EV‐derived let‐7i possesses an inhibitory role in lung cancer progression through the KDM3A/DCLK1/FXYD3 axis, suggesting a new molecular target for lung cancer treatment. [ABSTRACT FROM AUTHOR]

In recent years, MXene has become a hotspot because of its good conductivity, strong broadband absorption, and tunable band gap. In this contribution, 0D MXene Ti3C2Tx quantum dots are synthesized by a liquid exfoliation method and a wideband nonlinear optical response from 800 to 1550 nm is studied, which have a larger nonlinear absorption coefficient β of –(11.24 ± 0.14) × 10–2 cm GW–1. The carrier dynamic processes of 0D MXene are explored with ultrahigh time resolution nondegenerate transient absorption (TA) spectroscopy, which indicates that the TA signal reaches its maximum in 1.28 ps. Furthermore, 0D MXene is used to generate ultrashort pulses in erbium or ytterbium‐doped fiber laser cavity. High signal‐to‐noise (72 dB) femtosecond lasers with pulse durations as short as 170 fs with spectrum bandwidth of 14.8 nm are obtained. Finally, an ultranarrow fiber laser based on 0D MXene is also investigated and has a full width at half maximum of only 5 kHz, and the power fluctuation is less than 0.75% of the average power. The experimental works prove that 0D MXene is an excellent SA and has a promising application in ultrafast and ultranarrow photonics. [ABSTRACT FROM AUTHOR]

Background: The value of identifying and targeting population demographics at high risk of stroke based on patient-reported outcomes (PROs) with electronic health records (EHRs) in Shanghai is largely undiscovered. Aim: To test the hypothesis that establishing an evidence-based support system composed of PROs integrated with EHRs could be effective at identifying individuals at high risk of suffering from stroke. Methods: The patients included in this study joined the hypertensive patient management system from 2014 to 2018. We merged the Hypertension Patients Management Database and the Diabetes Mellitus Patients Management Database of Shanghai Jiading district, then kept the hypertension patients with or without diabetes. We subsequently performed a screen analysis utilizing EHRs to target the population with any risk factor for stroke, namely, hypertension, diabetes mellitus, obesity, smoking and physical inactivity. We also calculated the distribution of each risk factor and the combinations of risk factors. Results: In the Jiading District of Shanghai, 46,580 hypertensive patients with complete baseline information joined the hypertensive patient management system from 2014 to 2018. The majority of the patients were aged above 60 years old. Physical inactivity (83.24%), smoking (24.07%), diabetes (16.87%), and obesity (12.23%) were highly prevalent in hypertensive participants. Approximately 4377 patients were diagnosed with hypertension exclusively, accounting for 9.70% of the total number of patients in this study. Meanwhile, approximately 52.47% of the patients were diagnosed with two concurrent risk factors, and 38.13% of the patients had hypertension, meaning that 17,762 patients could be labeled as the high-risk population for stroke according to the criteria established by the National Stroke Screening Survey. Conclusion: Our exploratory findings demonstrate the feasibility of pinpointing and targeting populations at high risk of stroke using the EHRs of hypertensive patients. [ABSTRACT FROM AUTHOR]

The dielectric modulus Μ∗(ω) is used for studying the frequency domain response and activation energy (E a) of transformer immersed cellulose insulation. Existing literatures show that the temperature is a crucial factor affecting the Μ∗(ω) and aging rate of transformer oil-paper insulation, while the E a can be regarded as an indicator to reflect the average aging rate of the transformer immersed cellulose insulation. Therefore, the discussion of the temperature-dependence on both Μ∗(ω) and E a is of great significance. This paper attempts to report an approach for understanding the temperature impact on both Μ∗(ω) and E a. The obtained knowledge can be used to establish two available models for temperature correction on Μ∗(ω) and activation energy prediction of transform immersed cellulose insulation, respectively. These findings are expected to promote the reliability of the condition prediction result of transformer immersed cellulose insulation by using Μ∗(ω) and E a technique. [ABSTRACT FROM AUTHOR]

Background and Aims. To investigate the clinical effect of preservation or nonpreservation of the left colic artery (LCA) in total mesorectal excision (TME) under laparoscopy. Methods. The words, like "rectal cancer," "left colonic artery," and "laparoscopy," were used as the retrieval terms, and the keyword retrieval method was adopted. The retrieval period was set as from January 1, 2013, to June 1, 2018. We searched databases including PubMed, Web of Science, and China National Knowledge Infrastructure (CNKI) to collect randomized and controlled trials which compared the effect of preservation or nonpreservation of the LCA in TME under laparoscopy. Two researchers independently carried out literature screening, data extraction, and literature quality evaluation; Review Manager 5.3 was used for the meta-analysis. Results. Seven studies including 1467 cases were identified for the meta-analysis. As showed by the meta-analysis, compared with the LCA nonpreservation group, the LCA preservation group had significantly reduced incidence of anastomotic leakage (OR = 0.44 , CI = 0.30 , 0.65 , P < 0.0001) and postoperative urinary and sexual dysfunction (OR = 0.26 , CI = 0.09 , 0.78 , P = 0.02) and significantly shorter time for intestinal function recovery (WMD = − 0.26 , CI = − 0.41 , − 0.11 , P = 0.0008). There were no significant differences between the two groups in the duration of surgery, blood loss, number of dissected lymph nodes, or postoperative hospital stay. Conclusions. From the results, the LCA preservation group seems to achieve comparable success with acceptable safety outcomes. Therefore, this surgical method can be recommended in the clinical practice. [ABSTRACT FROM AUTHOR]

The results of frequency domain spectroscopy (FDS) will be affected by moisture which often leads to an unreliable condition prediction of oil-immersed cellulose insulation in transformers. In view of this, a solution is proposed in this study by adopting a fitting fingerprint database (FFD) technique, which can be utilized for condition prediction of aging and moisture content. In the current work, the relevant fingerprints that could characterize the insulation aging condition and moisture content are extracted from the FDS curves and the DC conductivity of the transformer oil. The FFD is then constructed by fitting fingerprints. The accuracy of the reported FFD technique is verified from tests on oil-immersed pressboard prepared in the lab and a transformer from the field. In this respect, the present contribution highlights FFD might be used as a powerful tool for condition prediction of oil-immersed cellulose insulation in transformers. [ABSTRACT FROM AUTHOR]

Over the past few years, frequency domain spectroscopy (FDS) has been widely utilized to assess transformer insulation. Many investigations have revealed that the FDS measurement has been observed to be dependent on service conditions (aging, moisture, geometry, and temperature). During the onsite FDS measurement, the inner insulation temperature of the de-energized transformer gradually decreases, which affects the FDS results due to moisture migration from oil to the cellulose insulation. This process gives rise to misinterpreting of the condition of the transformer insulation. Presently, the master curve technique reported by several researchers is utilized for temperature correction in FDS measurements. In fact, various researchers have obtained different master curves, so making a universal approach to temperature correction has become an important topic. In the present investigations, a series of experiments was performed on oil-impregnated pressboard insulation under laboratory conditions which was followed by FDS measurements at lower than operating temperature and a universal master curve for temperature correction was studied. Activation energies from oil-impregnated pressboard tests support the effectiveness of the proposed universal approach for temperature correction. [ABSTRACT FROM AUTHOR]