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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 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]

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]

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]

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]

We recall the definition of the O -operators on bimodules over associative algebras (also called generalized Rota-Baxter operators), and we introduce the notions of compatible O -operators and of O N -structures. We show that an O N -structure gives rise to a hierarchy of O -operators and that a solution of the strong Maurer-Cartan equation on the associative twilled algebra associated to an O -operator gives rise to a pair of O N -structures which are naturally in duality. We introduce the notions of PN-, ΩN- and P Ω -structures on associative algebras and study their relations. [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]

In this paper, we introduce the notion of a left-symmetric bialgebroid as a geometric generalization of a left-symmetric bialgebra and construct a left-symmetric bialgebroid from a pseudo-Hessian manifold. We also introduce the notion of a Manin triple for left-symmetric algebroids, which is equivalent to a left-symmetric bialgebroid. The corresponding double structure is a pre-symplectic algebroid rather than a left-symmetric algebroid. In particular, we establish a relation between Maurer–Cartan type equations and Dirac structures of the pre-symplectic algebroid which is the corresponding double structure for a left-symmetric bialgebroid. [ABSTRACT FROM AUTHOR]

The life expectancy of a transformer is largely depended on the service life of transformer polymer insulation materials. Nowadays, several papers have reported that the traditional system poles obtained from polarization and depolarization current (PDC) data can be used to assess the condition of transformer insulation systems. However, the traditional system poles technique only provides limited ageing information for transformer polymer insulation. In this paper, the modified system poles obtained from PDC data are proposed to assess the ageing condition of transformer polymer insulation. The aim of the work is to focus on reporting a comparative investigation on the performance of modified system poles and traditional system poles for assessing the ageing condition of a transformer polymer insulation system. In the present work, a series of experiments have been performed under controlled laboratory conditions. The PDC measurement data, degree of polymerization (DP) and moisture content of the oil-immersed polymer pressboard specimens were carefully monitored. It is observed that, compared to the relationships between traditional system poles and DP values, there are better correlations between the modified system poles and DP values, because the modified system poles can obtain much more ageing information on transformer polymer insulation. Therefore, the modified system poles proposed in the paper are more suitable for the diagnosis of the ageing condition of transformer polymer insulation. [ABSTRACT FROM AUTHOR]

In this paper, first we modify the definition of a Hom-Lie algebroid introduced by Laurent-Gengoux and Teles and give its equivalent dual description. Many results that are parallel to Lie algebroids are given. In particular, we give the notion of a Hom-Poisson manifold and show that there is a Hom-Lie algebroid structure on the pullback of the cotangent bundle of a Hom-Poisson manifold. Then we give the notion of a Hom-Lie bialgebroid, which is a natural generalization of a purely Hom-Lie bialgebra and a Lie bialgebroid. We show that the base manifold of a Hom-Lie bialgebroid is a Hom-Poisson manifold. Finally, we introduce the notion of a Hom-Courant algebroid and show that the double of a Hom-Lie bialgebroid is a Hom-Courant algebroid. The underlying algebraic structure of a Hom-Courant algebroid is a Hom-Leibniz algebra, or a Hom-Lie 2-algebra. [ABSTRACT FROM AUTHOR]

Investigation of the rheological characteristics of deep-sea sediments is very important for understanding submarine disasters. Three reconstituted deep-sea soils with different plasticity and activity values from the South Sea China are considered in this study. A series of steady rheological tests are conducted on samples of three soils with different water contents and temperatures by a rate-controlled rotational rheometer operated in a steady-state regime. Rheological results show that shear stress and apparent viscosity can be decreased by a maximum of 65% when the temperature varies from 1 °C to 25 °C, and the three deep-sea soils are typical shear thinning non-Newtonian fluids with yield stress. The state of the samples can be divided into three phases during the shearing process, which implies that with an increase in the shear strain rate, all samples first behave as a solid, then transition from solid to liquid, and last behave as a liquid. The three phases are distinguished by the static yield stress (SYS) and fluidic yield stress (FYS), and a simple method for dividing the three phases is proposed. The SYS and FYS decreased with increasing temperature and water content. The relationships between yield stresses (SYS and FYS) and soil properties (water content and activity) and temperature are established. In addition, a unified strength model for deep-sea sediments is suggested, and the validity of the model is verified by comparing the prediction results of the model and test results. The results of this study could be useful for deep-sea submarine mudflow and landslide modelling. • A simple method to determine the values of SYS and FYS in steady rheological shearing tests is proposed. • Model for SYS and FYS that considering influence of LI, activity and temperature is established. • A unified strength model that considering effects of shear rate, temperature, water content, and activity is proposed. [ABSTRACT FROM AUTHOR]

The ageing rate of cellulose insulation materials (paper/pressboard) in oil‐impregnated transformers is largely determined by moisture. In this paper, several experiments were conducted under controlled laboratory conditions to quantitatively diagnose the amount of moisture in cellulose insulation using frequency domain spectroscopy (FDS) technique, which has been proven to be an effective tool to predict the insulation condition in oil‐impregnated power equipment. The frequency dielectric response in oil‐impregnated pressboards, moisture content as well as test temperature, was monitored carefully, and a new dielectric characteristic parameter for the diagnosis of moisture content was proposed. In addition, the master curve technique was introduced to calibrate the temperature effect on FDS measurement results. These experiments revealed that a strong correlation exists between frequency dielectric parameter and moisture content in cellulose insulation. Such correlation can be utilised for better prediction of moisture content in paper–oil insulation. A modified assessment method for the diagnosis of moisture content in paper–oil insulation was investigated and its effectiveness was also demonstrated using a case. [ABSTRACT FROM AUTHOR]

In order to distinguish the influences of moisture and aging on the frequency domain dielectric response of oil-paper insulation and better apply frequency domain spectroscopy (FDS) to assess the insulation condition of power transformers, the oil-paper insulation samples with different moisture contents and different aging states were prepared in the laboratory. The FDS of the samples were tested and a group of characteristic parameters were extracted from dissipation factor (tan?) curves which could be used to assess the moisture content and aging states of oil-paper insulation respectively. The quantitative relationship among characteristic parameters, degree of polymerization (DP) and moisture contents (Km.c) was accurately established. The observations show that the proposed characteristic parameters are sensitive to the moisture in 10-3-102Hz, while the aging states influence the characteristic parameters in 10-3-10-1Hz. Meanwhile, an exponential relationship equation which could be used to assess the oil-paper insulation condition was established among the characteristic parameters, DP and the moisture content. Finally, the evaluation technique proposed in this paper was used to diagnose the insulation condition of several field transformers in this way, and its validity was preliminary and reasonably verified. [ABSTRACT FROM AUTHOR]

• Considered the significant impact of the COVID-19 on electricity load. • Developed a novel method based on multi-task learning using parameters sharing layers. • Used the real mobility data from Google and Apple and load data from large power enterprises and public institutions. • The universally adaptable model can control the forecasting error at a low level in the COVID-19. • Implemented the Shapley additive explanations technology to enhance interpretability. Affected by the new coronavirus (COVID-19) pandemic, global energy production and consumption have changed a lot. It is unknown whether conventional short-term load forecasting methods based on single-task, single-region, and conventional indicators can accurately capture the load pattern during the COVID-19 and should be carefully studied. In this paper, we make the following contributions: 1) A mobility-optimized load forecasting method based on multi-task learning and long short-term memory network is innovatively proposed to alleviate the impact of the COVID-19 on short-term load forecasting. The incorporation of mobility data and data sharing layers potentially reduces the difficulty of capturing the load patterns and improves the generalization of the load forecasting models. 2) The real public data collected from multiple agencies and companies in the United States and European countries are used to conduct horizontal and vertical tests. These tests prove the failure of the conventional models and methods in the COVID-19 and demonstrate the high accuracy (error mostly less than 1%) and robustness of the proposed model. 3) The Shapley additive explanations technology based on game theory is innovatively introduced to improve the objectivity of the models. It visualizes that mobility indicators are of great help to the accurate load forecasting. Besides, the non-synchronous relationships between the indicators' correlations and contributions to the load have been proved. [ABSTRACT FROM AUTHOR]

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]

The distribution behavior of furfural in insulation systems is influenced by the oil–pressboard mass ratio. In addition, the equilibrium distribution of furfural between oil and pressboard will be disturbed after oil replacement. Therefore, it is of great significance to study the distribution ratio of furfural in oil with various oil–pressboard mass ratios after oil replacement. In this research, an accelerated thermal aging experiment and oil replacement experiment were conducted in the lab. Furthermore, the equilibrium characteristics of furfural dissolved in oil with various oil–pressboard mass ratios were studied. Multiple regression analysis was used to analyze the relationship between the oil–pressboard mass ratios and the distribution ratio of furfural in oil. The equilibrium distribution model of furfural was thus obtained. Afterwards, the modified furfural distribution model under oil replacement conditions was established. A novel scheme is provided for analyzing the equilibrium characteristics of furfural under various oil–pressboard mass ratios after oil replacement. The work of this paper is expected to improve the accuracy of furfural analysis. [ABSTRACT FROM AUTHOR]

Operating temperature is an important parameter of thyristors to ensure the stable operation of power electronic devices. Thermal management technology is of great significance for improving the reliability of thyristors. In this study, the performance of a phase change material (PCM) mesh-finned heat sink is investigated for the thermal management of thyristors. A multi-physical coupling model of the PCM mesh-finned heat sink is established to analyze the effects of different power losses, air velocities, heights of fins, and thickness of PCM on the thermal performance of the PCM heat sink. The influence of thermal and flow fields on PCM is considered in this model. Furthermore, the heat sink design is optimized to improve the thermal performance based on the calculation results of thermal network parameters. The results show that the power losses, the air velocity, the height of fins, and the thickness of PCM significantly affect the protection ability of the PCM heat sink. After optimizing the heat sink, the PCM heat sink provides 80 s protection time and 100 s recovery time. The PCM mesh-finned heat sink demonstrated good potential for the thermal management of thyristors. [ABSTRACT FROM AUTHOR]

Mobile source emissions have significantly contributed to fine particulate matter (PM 2.5) pollution in urban atmospheric environments. Few studies have explored on-road vehicular PM 2.5 emissions and the health effects attributed to these emissions under different traffic conditions. Based on driving data obtained from 20000 taxi receipts, a motor vehicle emission simulator (MOVES) model was used to estimate the PM 2.5 emission levels of motor vehicles in the urban area within the Sixth Ring Road of Beijing (SRRB) on weekdays and weekends, respectively. Two different PM 2.5 exposure scenarios were further simulated using an atmospheric dispersion model. Subsequently, the health effects attributable to traffic-related PM 2.5 exposure were quantified by using exposure-response function to calculate the population acute morbidity and premature mortality during different time periods. We found that PM 2.5 emission levels of motor vehicles on normal weekdays were overall higher than those on weekends. The median vehicular PM 2.5 dispersion concentration in the study area was 2.68 μg/m3 on weekdays and 1.82 μg/m3 on weekends. Annually, there were 4435 premature deaths attributed to vehicle emissions (95% confidence interval (CI): 3655, 4904) under weekday exposure conditions, and this number sharply decreased to 3462 (95% CI: 3052, 4011) on weekends. Considering the hourly measurements, road traffic emissions have the greatest impact on public health during morning rush hour (8:00 a.m.). Total PM 2.5 emissions were closely associated with road traffic conditions and largely determined the magnitude of the health impacts caused by traffic-related PM 2.5 exposure. These findings provide information to aid in formulating reasonable public health policies to address vehicular PM 2.5 emission-induced health implications. Image 1 • PM 2.5 emissions of on-road urban vehicles in different time periods were estimated. • Health effects attributed to vehicular PM 2.5 were quantified with E-R functions. • People could suffer worse health effects exposed to vehicular PM 2.5 on weekdays. • Traffic situation greatly affects the PM 2.5 pollution and public health burden. [ABSTRACT FROM AUTHOR]

The aging kinetics model is of great interest to scholars since it is capable of describing the variation law between the degree of polymerization (DP) and the aging duration of transformer polymer (cellulose) insulation. However, it is difficult to determine the moisture content inside the transformer polymer insulation without destroying it, so that the model parameters cannot be confirmed. Such limitation greatly restricts its application. It is interesting to note that as long as the moisture content of the transformer polymer insulation could be characterized (replaced) by a certain feature parameter, the above issue will be solved naturally. The existing researches indicate that the Frequency Domain Spectroscopy (FDS) is sensitive to moisture. Consequently, the feature parameter that could characterize the moisture inside transformer polymer insulation (extracted from the FDS curve) can be used to report a modified aging kinetics model, which could perform the aging condition prediction of transformer polymer insulation under various test conditions, including aging duration, aging temperature, and initial moisture. In that respect, the average relative error of prediction results of prepared samples is equal to 7.41%, which reveals that the reported model might be serviced as a potential tool for the aging condition prediction of transformer polymer insulation. [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]

It is a fact that the frequency domain spectroscopy (FDS) curve at different temperatures can be corrected by the shift factor (αT) extracted from the master curve. However, the αT and master curve reported by previous works are distinctive due to the difference in the construction algorithm. Therefore, it is of great significance to report a universal approach for extracting αT. In this work, the unaged oil-immersed pressboards with different moisture content (mc%) are firstly prepared and selected as the research specimen. Then, the αT of FDS curves on the above pressboard is extracted based upon the master curve technique. The influence mechanism under the various test temperature (T) and mc% is therefore analyzed so as to establish a universal model for predicting the αT. The present findings reveal that the αT value extracted from FDS curves is both temperature-dependent and moisture-dependent. In addition, the predicted αT is not only suitable for temperature correction on FDS curve of same type pressboard with different insulation conditions (moisture contents and aging degrees), but also maintains considerable accuracy when applied to different types of pressboard. Therefore, the obtained conclusions will provide a universal method for temperature correction on FDS curve of transformer polymer insulation. [ABSTRACT FROM AUTHOR]

A solution for forecasting the dissolved gases in oil-immersed transformers has been proposed based on the wavelet technique and least squares support vector machine. In order to optimize the hyper-parameters of the constructed wavelet LS-SVM regression, the imperialist competition algorithm was then applied. In this study, the assessment of prediction performance is based on the squared correlation coefficient and mean absolute percentage error methods. According to the proposed method, this novel procedure was applied to a simulated case and the experimental results show that the dissolved gas contents could be accurately predicted using this method. Besides, the proposed approach was compared to other prediction methods such as the back propagation neural network, the radial basis function neural network, and generalized regression neural network. By comparison, it was inferred that this method is more effective than previous forecasting methods. [ABSTRACT FROM AUTHOR]

Identifying the anomalies of wind turbine (WT) and maintaining in time will improve the reliability of wind turbine and the efficiency of energy use, however it is difficult toidentify the wind turbine's abnormal operation by the traditional threshold settings because the anomalies can be induced by multiple factors. Therefore, this paper presents an anomaly identification model for wind turbine state parameters, and the model can identify abnormal state which the fluctuation range of the condition parametersis within the SCADA alarm threshold. The main work is as follows: 1) in order to increase the accuracy of the prediction model, a novel BPNN model integrated genetic algorithm (GA) was employed to optimize the training method (called GABP method), data samples, and input parameter selection, respectively; 2) on this basis, the distribution characteristics of state parameter prediction errors were depicted by a T-location scale (TLS) distribution with the shift factor and elastic coefficient; 3)error abnormal index (EAI) is defined to quantify the abnormal level of the prediction error, which is used as an indicator of the wind turbine anomaly. The proposed method has been applied on areal 1.5 MW wind turbine, and the analysis shows that the proposed method is effective in wind turbine anomaly identification. [ABSTRACT FROM AUTHOR]

In the electrical industry, there are many hazardous gases that pollute the environment and even jeopardize human health, so timely detection and effective control of these hazardous gases is of great significance. In this work, the gas-sensitive properties of Pd-modified g-C 3 N 4 interface for each hazardous gas molecule were investigated from a microscopic viewpoint, taking the hazardous gases (CO, NO x) that may be generated in the power industry as the detection target. Then, the performance of Pd-modifiedg-C 3 N 4 was evaluated for practical applications as a gas sensor material. Novelly, an unconventional means was designed to briefly predict the effect of humidity on the adsorption properties of this sensor material. The final results found that Pd-modified g-C 3 N 4 is most suitable as a potential gas-sensitizing material for NO 2 gas sensors, followed by CO. Interestingly, Pd-modified g-C 3 N 4 is less suitable as a potential gas-sensitizing material for NO gas sensors, but has the potential to be used as a NO cleaner (adsorbent). Unconventional simulation explorations of humidity effects show that in practical applications Pd-modified g-C 3 N 4 remains a promising material for gas sensing in specific humidity environments. This work reveals the origin of the excellent properties of Pd-modified g-C 3 N 4 as a gas sensor material and provides new ideas for the detection and treatment of these three hazardous gases. [Display omitted] • The sensing properties of Pd-modified g-C 3 N 4 interface were evaluated for CO, NO x. • A new experiment for the prediction of humidity-influenced interface performance was designed. • This work enriches new schemes for the preparation of g–C 3 N 4 –based gas sensors. • This work provides new ideas for addressing hazardous gases generated in the electrical industry. [ABSTRACT FROM AUTHOR]

Insulation performance testing of gas-insulated switchgear (GIS) and treatment of SF 6 decomposition products under partial discharge are two crucial studies. In this paper, the adsorption behavior and sensor properties of five characteristic decomposition gases of SF 6 (HF, H 2 S, SO 2 , SOF 2 , SO 2 F 2) on intrinsic and CoO-doped SnSe monolayers are investigated in detail based on density-functional theory. The results showed that the adsorption behaviors of HF, H 2 S, SOF 2 and SO 2 F 2 on SnSe monolayers were all physisorption among which the best adsorption was SO 2 with an adsorption energy of −0.618 eV, which is a weak chemisorption. After doping with CoO, the adsorption capacity of SnSe monolayer for five gases was significantly enhanced, in which the adsorption energies for SO 2 and SOF 2 reached −1.356 eV and −1.175 eV, respectively. In addition, the conductivity of the system is greatly improved, with the bandgap changing from 1.129 eV to 0 eV. The microscopic mechanism of the interaction of gas molecules with CoO-SnSe monolayers has been revealed by energy band structure (E g), density of states (DOS), Milligan charge analysis (∆ Q) and electrostatic potential. Finally, the sensitivity (S) and desorption time (τ) of the five adsorption systems were calculated to illustrate the macroscopic gas-sensitive properties of the system. This work will help to explore the application of CoO-SnSe monolayers in SF 6 decomposition gas sensing detection and adsorption treatment. [Display omitted] • Doping greatly improves the conductivity of the system, and the adsorption effect of doped system on SO 2 and SOF 2 is significantly improved. • The change of electronic characteristics of doped system is expounded. • The sensing characteristics of adsorption system are calculated, and the possibility of SOF 2 as the target gas for CoO-SnSe sensing device to evaluate GIS insulation performance is explored. [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]

The spatial mismatch between energy resources and water resources has been widely concerned. Electricity trade drives virtual water flows from electricity production sides to consumption sides, which can aggravate or alleviate regional water scarcity. Investigating the historical evolution of virtual water transmission and its impacts on water scarcity benefits the sustainable development of energy and water. To reduce data uncertainties, in this study, we built provincial water intensity of electricity generation inventory considering the impacts of factors such as electricity generation types, cooling technologies and generator units. Besides, to investigate how the direction and quantity of virtual water flows aggravate or alleviate the regional water scarcity, the impact assessment model was built, and the impact assessment index was defined. The results showed that the water consumption of electricity generation and interprovincial virtual water transfer increased by 2.61 times and 5.12 times during 2005–2015, respectively. Changes in the amount of electricity generation and the electricity transmission structure were the two main drivers of increases in virtual water flows, contributing to a total increase of 85.28%. A large amount of virtual water was transferred from the southwest and the northwest to the eastern coastal areas. There were many "positive flows" from the southwest to Jiangsu-Zhejiang-Shanghai, while "negative flows" were concentrated in Xinjiang-Henan, Gansu-Qinghai and Gan-Shaanxi. The nodes with the largest impact assessment index value were Hubei, Sichuan and Shanghai, while the lowest were Gansu, Xinjiang and Qinghai. This study can provide a basis for optimizing the electricity generation mix and electricity transmission structure, alleviating the growing tension between energy and water, and realizing the sustainable development of water resources. • The provincial water intensity for electricity generation inventory is built. • The amount of virtual water flows increased 5.12 times from 2005 to 2014. • The virtual outflows of the southwestern regions alleviated national water scarcity. [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]

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]

Along with electricity transmission, virtual water is transferred from electricity generation provinces to load hubs, reallocating spatial water resources and impacting regional water scarcity. To assess whether virtual water in electricity transmission mitigated or aggravated national water scarcity, a rationality assessment model was proposed from energy-water nexus perspective. The interprovincial virtual water flows were calculated based on provincial water intensity and electricity transmission considering the provincial electricity generation mix. The flow rationality index and node rationality index were proposed and defined to evaluate the net benefit of virtual water flows and provinces, respectively, according to the interprovincial differences in water stress index. The results show that: 1) a large amount of virtual water was transferred from the northwest and southwest provinces to the southeast provinces and Beijing-Tianjin-Hebei region; 2) the flow with the highest flow rationality index is Inner Mongolia-to-Hebei (29.8), while the lowest one is Shanxi-to-Hubei (−102.5); 3) the node with the highest node rationality index is Hebei (32.0), while the lowest one is Shanxi (−104.7). By quantifying the impacts of electricity transmission on provincial and national water stress, this study aims to provide guidance for national virtual water strategy by electricity transmission to mitigate national water scarcity. • Virtual water transfers embodied in China's interprovincial electricity trade is calculated in 2014. • A rationality assessment model is proposed to evaluate whether the water transfers positively or negatively impacts overall water scarcity for a region. • Based rationality assessment model, the rationality index for flows and provinces is analyzed. [ABSTRACT FROM AUTHOR]

In China, electricity transmission has increased rapidly over the past decades, and a large amount of virtual water is delivered from power generation provinces to load hubs. Understanding the evolution of the virtual water network embodied in electricity transmission is vital for mitigating water scarcity. However, previous studies mainly calculated the virtual water transferred in short periods in low-spatial resolution and failed to reveal driving forces of the evolution of virtual water. To solve this problem, we investigated the historical evolution of the virtual water network and virtual scarce water network embodied in interprovincial electricity transmission between 2005 and 2014. The driving forces of the evolution of virtual (scarce) water networks were analyzed at both national level and provincial level. The results show that the overall virtual water transmission and virtual scarce water transmission increased by five times, and the direction was mainly from southwest and northwest provinces to eastern provinces. Sichuan, Yunnan, and Guizhou played an increasingly important role in virtual water exporting, and northwestern provinces had dominated the virtual scarce water exporting in the decade. At the national level, the increase of virtual water is mainly driven by the change of power generation mix and power transmission. At the provincial level, the increase of virtual water transmission in the largest virtual water exporter (Sichuan) is driven by the power generation mix and the power transmission, between 2005 and 2010, and 2010 and 2014, respectively. Considering the expanding of electricity transmission, the development of hydropower in the southwestern provinces and other renewable energies (solar and wind) in the northeastern provinces would overall mitigate the water scarcity in China. [ABSTRACT FROM AUTHOR]

Dissolved gas analysis (DGA) has been widely used in various scenarios of power transformers' online monitoring and diagnoses. However, the diagnostic accuracy of traditional DGA methods still leaves much room for improvement. In this context, numerous new DGA diagnostic models that combine artificial intelligence with traditional methods have emerged. In this paper, a new DGA artificial intelligent diagnostic system is proposed. There are two modules that make up the diagnosis system. The two modules are the optimal feature combination (OFC) selection module based on 3-stage GA–SA–SVM and the ABC–SVM fault diagnosis module. The diagnosis system has been completely realized and embodied in its outstanding performances in diagnostic accuracy, reliability, and efficiency. Comparing the result with other artificial intelligence diagnostic methods, the new diagnostic system proposed in this paper performed superiorly. [ABSTRACT FROM AUTHOR]

Dissolved gas analysis (DGA) is widely used to detect the incipient fault of power transformers. However, the accuracy is greatly limited by selection of DGA features and performance of fault diagnostic model. This paper proposed a fault diagnostic method integrating feature selection and diagnostic model optimization. Firstly, this paper set up three feature sets with eight basic DGA gases, 28 DGA gas ratios and 36 hybrid DGA features, respectively. Then, to eliminate the interference of weak-relevant and irrelevant features, the genetic-algorithm-SVM-feature-screen (GA-SVM-FS) model was built to screen out the optimal hybrid DGA features subset (OHFS) from three feature sets. Next, using the OHFS as the input, the support vector machine (SVM) multi-classifier optimized by ISGOSVM (SVM classifier optimized by improved social group optimization) was built to diagnose fault types of transformers. Finally, the performance of OHFS and ISGOSVM diagnostic model was tested and compared with traditional DGA features and diagnostic models, respectively. The results show that the OHFS screened out is comprised of 14 features, including 12 gas ratios and two gases. The accuracy of OHFS is 3–30% higher than traditional DGA features, and the accuracy of ISGOSVM can increase by 3% to 14% compared with the SGOSVM (SVM classifier optimized by social group optimization), GASVM (SVM classifier optimized by genetic algorithm optimization), PSOSVM (SVM classifier optimized by particle swarm optimization), and SVM diagnostic models. The proposed approach integrating the OHFS with ISGOSVM achieves the highest accuracy of fault diagnose (92.86%). [ABSTRACT FROM AUTHOR]

Abstract The sources, levels and health risks of volatile organic compounds emitted from the entire furniture manufacturing process in workshops were investigated. A probabilistic health assessment model was established to estimate the health risks of workers and managers caused by VOCs (volatile organic compounds) based on the inhalation risk model and the Monte Carlo method. Sensitivity analyses and uncertainty analyses were implemented to screen out the crucial input parameters and to identify the possible influential factors in the evaluation process. The results demonstrate that the highest concentration of VOCs occurs in the topcoating process, followed by the veneering, undercoating, edge bonding, polishing varnish, drying, and paint mixing processes. Overall, a total of 17 VOCs, including aromatic hydrocarbons, alkanes, halogenated alkanes, ketones, and saturated aliphatic esters, exist in 7 VOC emission processes in the wood processing workshop and the painting workshop. For health impacts, workers in the topcoating, undercoating, and veneering positions suffer the greatest carcinogenic risks, with mean values above 1.00E-05, which mainly originate from ethylbenzene, dichloromethane, and benzene. The carcinogenic risks in other positions are relatively lower and are in the sequence of polishing varnish, paint mixing, drying, and edge bonding. Sensitivity analyses indicated that exposure duration had the greatest impact on carcinogenic and non-carcinogenic risk, with an average contribution of 0.78 and 0.93, respectively. These comprehensive evaluations for exposure level and health risk can yield insight into the occupational hazards of VOC emissions and will contribute to informed decision-making related to abatement measures and risk management in furniture manufacturing workplaces. Graphical abstract Image Highlights • The VOCs emission processes were firstly investigated in furniture manufacturing. • A total of 17 VOCs during 7 emission processes were identified and qualified. • Probabilistic risks were estimated by Monte Carlo method and inhalation risk model. • Topcoating shows the greatest risk and ethylbenzene should be prior controlled. • Exposure duration have greatest impact on carcinogenic and non-carcinogenic risk. [ABSTRACT FROM AUTHOR]

• Fe3+ modified Bronsted acidity and CTS altered hydrophilicity for NaY catalysts. • Fe3+ exchanged NaY display shortened Si-OH and electronically reconfigured Fe3+ sites. • CTS modified FeY materials show 18-fold activity improvement. • CTS modified FeY catalysts display remarkable stability. Solketal is known as a promising non-BPA plasticizer. However, fast and robust synthesis of solketal from bio-oxygenates remains a grand challenge, as strong surface polarization often deactivates acidic catalysts. We proposed and validated a dual designing strategy, involving (1) Fe3+ modified Bronsted acidity and (2) chlorotrimethylsilane (CTS) altered hydrophilicity for enhanced activity and stability of NaY catalysts. As one of the key findings, Fe3+ exchanged NaYs display an unusual shortened Si-OH bond and electronically reconfigured Fe3+ sites for a 4-fold activity enhancement. Furthermore, CTS modified FeY materials further alleviate surface passivation of glycerol and water, leading to an 18-fold activity improvement and better durability for acetalization of glycerol. CTS modified FeY catalysts display remarkable stability against varies impurity molecules. The dual modification methodology provides useful information on rational design of durable catalysts for synthesis of various other non-BPA derivatives. [ABSTRACT FROM AUTHOR]

The volume of landfill gas (LFG) produced during municipal solid waste (MSW) decomposition in local landfills has increased rapidly in recent years. To promote circular economy (CE) applications through resource recovery, this article investigates the feasibility of utilizing LFG as a sustainable energy to power data centers (DCs) in Xiamen (China) and evaluates the implications of waste heat reuse on the energy consumption of DC. The objective of this study was to investigate the environmental impacts and economic benefits of this scheme based on a SFC model. With respect to its novelty, LFG is utilized as an energy supply to DCs, while the waste heat generated in the energy production is recovered. The socio-economic benefits generated in this process are also elaborated. It was found that a large number of MSW was completely recycled to generate energy. The LFG enterprise could benefit from energy sale, while the energy satisfied the annual demand for DC power consumption. Utilizing this energy output resulted in the reduction of primary energy and less CO₂ emissions. By reusing the waste heat for domestic heating, the energy efficiency could be improved, while primary energy could be further saved, avoiding more CO₂ emissions. This implies that utilizing LFG output and waste heat to power DCs not only facilitate resource recovery from unused resources to improve energy efficiency and obtain socio-economic benefits, but also promote the digitalization of DCs and sustainable development of urban cities in the framework of CE. [Display omitted] • LFG can be used to power data centers (DCs) in order to promote CE. • The recovery of waste heat from LFG generation reduced CO 2 emission of 8.46 × 108kg. • Within 15 years, 4.97 × 10 10 kg of MSW can generate 4.65 × 109 kW ⋅ h of electricity. • The recovery of waste heat benefited landfill operators and DC firms financially. [ABSTRACT FROM AUTHOR]

The service life of a transformer is determined by the condition of its oil?paper insulation. A modified Cole?Cole model was introduced to describe the frequency domain spectroscopy (FDS) curves based on the classic Debye relaxation model and thereby accurately determined the ageing state of the insulation of a power transformer using FDS. Oil?paper insulation samples with different ageing states are prepared under laboratory conditions, and a characteristic parameter is extracted to quantify their ageing states after a detailed investigation of the frequency domain dielectric properties of the samples. Results reveal that the modified Cole?Cole model, including the ? relaxation components, dc and hopping conductivity components, can be employed to effectively model the frequency dielectric characteristics of oil?paper insulation. Furthermore, the extracted characteristic parameter from this model, ??, can be utilized in the quantitative evaluation of the ageing states of transformer insulation. A case example is discussed to demonstrate the applicability of the proposed technique in the condition assessment of field power transformers. [ABSTRACT FROM AUTHOR]

• A multi-objective energy-water nexus optimization framework is established. • The provincial economic trade's impact on energy and water stress is quantified. • The economic development level is the key to optimize the resources reallocation. • The rapid trade growth among provinces may aggravate the risk of resource scarcity. With China's vast territory and high regional heterogeneity in the spatial energy and water resources distribution, provincial-level embodied energy (EE) and virtual water (VW) reallocation are critical to regional energy and water recourse management but unfortunately, remain far from completed. In this paper, considering the heterogeneity of energy and water resources endowments among provinces, we constructed a dual objectives optimization framework to minimize national energy stress and water stress. Also, we evaluated the EE and VW flows' synergy impact on mitigating energy and water stress. We found that the spatial resources reallocation has a significant role on mitigating energy and water stress in high-stress regions. The results show that the net energy inflow can increase by 33.5%, and the net water inflow can increase by 42.1% in high-stress regions. The EE and VW flows' impact on mitigating resource stress is affected by the spatial resource endowments' heterogeneity. The flows that have the most positive impact on mitigating regional energy and water stress are Shanxi-Jiangsu and Jiangxi-Shanghai, respectively, while the most negative flows are Jiangsu-Henan and Xinjiang-Heilongjiang, respectively. The EE and VW flows among provinces have synergy in mitigating energy and water stress. Policy makers should not only focus on the local resources' consumption, but on the inter-provincial recourse flow and spatial resource endowments' heterogeneity. Inter-provincial cooperation is recommended, with reducing the scale of EE and VW trade that has negative impact, which can mitigate regional energy and water stress. [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. Models of stellar evolution have difficulty producing black holes in close binaries with masses more than ten times that of the Sun (>10; ref. 4), which is consistent with the fact that the most massive stellar black holes known so far all have masses within one standard deviation of 10. Here we report a mass of (15.65 ± 1.45) for the black hole in the recently discovered system M 33 X-7, which is located in the nearby galaxy Messier 33 (M 33) and is the only known black hole that is in an eclipsing binary. To produce such a massive black hole, the progenitor star must have retained much of its outer envelope until after helium fusion in the core was completed. On the other hand, in order for the black hole to be in its present 3.45-day orbit about its (70.0 ± 6.9) companion, there must have been a ‘common envelope’ phase of evolution in which a significant amount of mass was lost from the system. We find that the common envelope phase could not have occurred in M 33 X-7 unless the amount of mass lost from the progenitor during its evolution was an order of magnitude less than what is usually assumed in evolutionary models of massive stars. [ABSTRACT FROM AUTHOR]

The measurement of polarization and depolarization currents (PDC) based on time–domain response is an effective method for state assessment of cellulose insulation material in oil-immersed electrical equipment. However, the versatility of the data obtained at different temperatures is limited because of the temperature dependence of the PDC. In this respect, the universal conversion of PDC data at different temperatures is an essential aspect to improve the accuracy of the determination of insulating properties of cellulose materials immersed in the oil. Thus, an innovative temperature conversion method based on polarization time-varying current (PTC, obtained by multiplying the polarization current and time) is proposed in this article. In the current work, the PTC data at different temperatures are obtained from the oil-immersed cellulose pressboards with different moisture. Afterwards, the functional model based on the power series theory is used to simulate the PTC data, through which the coefficients of the power series are found related to the test temperature of the PTC and the moisture content (mc%) of the oil-immersed cellulose pressboards. Furthermore, the functional relationship among moisture, test temperatures, and the feature parameter calculated by these coefficients is established. Thus, the PTC data at various temperatures can be calculated by the established function. The potential application ability of the proposed method is verified by comparing the calculated results with the measured results obtained from the various samples. [ABSTRACT FROM AUTHOR]