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BACKGROUND Pathological manifestations of hepatic tumours are often associated with prognosis. Although surgical specimens (SS) can provide more information, currently, pre-treatment needle core biopsy (NCB) is increasingly showing important value in understanding the nature of liver tumors and even in diagnosis and treatment decisions. However, the concordance of the clinicopathological characteristics and immunohistochemical (IHC) staining between NCB and SS from patients with hepatic tumours were less concerned. AIM To introduce a more accurate method for interpreting the IHC staining results in order to improve the diagnostic value of hepatic malignancy in NCB samples. METHOD A total of 208 patients who underwent both preoperative NCB and surgical resection for hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICC) between 2008 and 2015 were enrolled in this study. The expression of CK19, GPC3, and HepPar1 were detected by IHC staining. Clinicopathological, NCB, and surgical data were collected and analysed using χ2 and kappa statistics. RESULTS Morphologically, the presence of compact tumour nests or a cord-like structure in NCB was considered the primary cause of misdiagnosis of HCC from ICC. The kappa statistic showed a moderate agreement in histomorphology (k = 0.504) and histological grade (k = 0.488) between NCB and SS of the tumours. A 4-tier (+++, ++, +, and -) scoring scheme that emphasized the focal neoplastic cell immunoreactivity of tumour cells revealed perfect concordance of CK19, GPC3 and HepPar1 between NCB and SS (k = 0.717; k = 0.768; k = 0.633). Furthermore, with the aid of a binary classification derived from the 4-tier score, a high concordance was achieved in interpreting the IHC staining of the three markers between NCB and final SS (k = 0.931; k = 0.907; k = 0.803), increasing the accuracy of NCB diagnosis C (k = 0.987; area under the curve = 0.997, 95%CI: 0.990-1.000; P < 0.001). CONCLUSION These findings imply that reasonable interpretation of IHC results in NCB is vital for improving the accuracy of tumour diagnosis. The simplified binary classification provides an easy and applicable approach.

Amino acid as a green and non-toxic capping agent was used to regulate TiO2 crystal face exposure and morphology replaced common inorganic F− ions. In this paper, the hexagonal multi-walled tubular anatase TiO2 with hierarchical structure exposed to {010} and {101} planes were synthesized by solvothermal method via optimizing the amino acid (glutamine). The microstructure, crystal plane exposure and photocatalytic activity of TiO2 samples were tested comprehensively, and the formation mechanism of hexagonal multi-walled tubular anatase TiO2 was proposed. The {010} active plane exposure ratio was 70.76% thanks to the appropriate ratios of glutamine to SO42− and the band gap reduced to 2.95 eV for better visible region absorption. The degradation rate of the material for MO reached 94.6% within 80 min, which was 9.37 times than the sample without capping agent. Both high surface area and the synergy effect between the {010} and {101} facets contribute to the improvement of photocatalytic activity.

This paper numerically investigates bubble nucleation, growth, merger, and departure characteristics as well as the heat transfer distributions on the surface, and compared the simulation results with experimental results. Micro-heaters are utilized in experiments to provide constant temperature as well as measure the time-resolved heat flux variations. Bubble images and corresponding heat flux distributions under bubbles are obtained in experiments. A 3-dimensional computational domain with two symmetry planes is built and 5 heating elements are arranged at the bottom surface of the domain to simulate the real heaters used in experiments. The temperatures of these elements are set constant and the local heat fluxes were calculated. Liquid-vapor interface is captured with a volume of fluid (VOF) method in numerical simulations. Bubble growth and merger characteristics and heat flux distributions under bubbles calculated in numerical simulations are analyzed and compared to experimental observations. The heat transfer contributions of different heat transfer modes are calculated. The heat transfer mechanisms during nucleate boiling are better interpreted by the coupling of bubble dynamics and time- and space-resolved heat flux variations on the surface.

In this work, a systematic research was undertaken to predict the nugget size of the welding joints in real time through monitoring the dynamic power signature for TC2 titanium alloy. The welding current in the welding process was measured by a Rogowski coil and the welding voltage was obtained by means of clipping two leads onto the upper and lower electrodes during the welding process. The power signal and the corresponding dynamic resistance were compared with each other. As the constant high frequency alternating welding current was employed in the whole welding process, the power waveform indicated the similar characteristics of the dynamic resistance, besides; the power signal could better reveal an explicit physical meaning of the heat input applied to the welding zone. The disparities and differences of the power waveforms with different welding qualities were also investigated. Four features were extracted from the power waveform so as to indicate the variations of welding power profile in the welding process. A process quality prediction model based on Kriging method was set up to correlate the four extracted characteristics with nugget diameter of the welding joints. Verification test results proved that the method proposed in this paper effectively evaluated the welding qualities within the ranges of process parameters being studied, which could monitor the welding performances in the resistance spot welding process as feasibly and effectively as possible.

Herein, silver (Ag)-based urchin-like E-graphite carbon nitride/titanium dioxide (E-g-C3N4/TiO2) ternary composite was successfully synthesised via hydrothermal process and it showed excellent photocatalytic activity. The large interfacial contact between three-dimensional (3D) urchin-like TiO2 (UT) and g-C3N4 leads to high photocatalytic activity, compared with pure 3D UT. To enlarge the response of light and enhance the charge carriers’ transfer, the Ag nanoparticles with average sizes of 13 nm were loaded on the surface of g-C3N4/TiO2. Photodegradation test results of RhB shown that the 3% Ag-based urchin-like E-g-C3N4/TiO2 composite has the highest catalytic activity, which reaches 97.98%. Thus, the material has a promising application for the degradation of organics.

Large-scale wind and solar power generations have got rapid development in recent years in China and abroad. They always connect to load centres through high-voltage direct current (HVDC) transmission or ultra HVDC (UHVDC) transmission lines. Such systems are so large and it is necessary to make appropriate equivalence according to the purpose of different research. At present, the analysis model of this kind of real system is few, and simplified single-machine infinite-bus system or IEEE example system is adopted most of the time, which may affect the accuracy of analysis results. Here, the UHVDC project from a practical renewable energy base to load centres in China is chosen as an example, the actual structure and parameters are used to establish a typical example system for AC/DC hybrid power grid with high-proportion renewable energy. The new-generation synchronous condenser with large capacity and the supporting synchronous generators are all considered. First, the installed power generation, power grid structure, and load configuration of example system are introduced. Then the load flow distribution and transient stability characteristics are analysed by using DIgSILENT PowerFactory software. Finally, the feasibility of the proposed example system is shown by simulation results.

With the rapid development of power system, wind power becomes an important generating way in AC/DC hybrid power grid. Due to the interference between the wind power and the AC network, the risk of DC system continuous commutation failure will be affected. In order to evaluate this effect reasonably, a method for running out of the fault set is presented in this study. Firstly, a distribution factor is proposed to determine the power line transfer after wind power or power line fault, the line with maximum load rate is chosen as the candidate failure lines; Secondly, the η short-circuit ratio and η effective short-circuit ratio indexes of the DC system is evaluated after every fault; they are used to judge whether the cascading fault of AC system induces the transient overvoltage of the converter bus to lead to wind turbines to take off the power grid net. Thus, a cascading fault sequence of the AC system is formed, and a cascading fault set that causes the transient overvoltage of the converter bus is completed. Finally, the simulation results calculated by power system department-bonneville power administration show that when the commutation failure occurs in the DC system, the system runs out immediately, and the validity of the method is verified.

The profile of the welding bead changes with the welding process parameters during the gas metal arc welding (GMAW) process, the reinforcement disappears and the penetration becomes sunken when the excessive welding heat input is applied. However, little research work is specially planned to cope with the studying of welding bead at these stages. A systematic studying of the relationships among the welding process variables and welding bead geometric features and optimization of the welding quality is presented. The influences of the welding technological parameters (voltage, welding speed, and wire feed speed) on the welding geometry were revealed and the models correlating them were established. The features of the weld bead geometry were composed of top reinforcement width, top reinforcement height, penetration depth, bottom reinforcement width, and bottom reinforcement height. By the desirability function approach, the recommendation of suitable welding parameters to meet the contradicting demands of multiple bead geometric features is fulfilled. The microstructure in different welding regions and mechanical performances of the welding joints produced by the verification test were also studied.

Photocatalytic CO

High share of renewable energy will be one of the basic features of power systems in the future around the world. Compared with photovoltaic (PV) and wind power, concentrating solar power (CSP) equipped with heat storage system has similar regulation characteristics with thermal power units, and it can effectively overcome the intermittent and volatility of PV and wind power generation. Meanwhile, the CSP units can strongly support the voltage, frequency and short-circuit capacity of power systems. So, CSP is a very promising power generation technology for the future power system. The CSP unit has better ramp ability than thermal power unit, and can generally reach a speed between 2% and 5% of rated power per minute. Stated thus, the CSP unit has a good potential to participate in the primary frequency regulation of power grid. At present, there are many researches on the performance of each subsystem of the CSP unit in worldwide, and there are also some theoretical researches on the participation of CSP unit in the dispatching operation of power system. However, there is a lack of research reports on CSP plant’s participation in the primary frequency regulation of the power grid, which is an urgently needed feature for the future power systems with high share of renewable energy. In this paper, a model with primary frequency regulation ability of CSP unit is established in DIgSILENT PowerFactory software. A revised two-area four-machine system is used to investigate the CSP unit’s participation in primary frequency regulation of power system. The simulation results show the good frequency regulation performance of CSP unit, which can effectively support the stable operation of power system with high share of renewable energy in the future.

Integrated energy distribution system (IEDS) could improve the efficiency of energy utilization and minimize environmental pollution based on the multi-energy coupling link. Firstly, the model of distributed energy station is established; secondly, the optimization model for optimal dispatching of IEDS considering AC power flow of distribution system, gas flow of natural gas distribution network and the distributed energy station is established; thirdly, an optimization method for optimal dispatching of IEDS based on the second-order cone relaxation method is proposed. Finally, case studies are performed on IEDS including the modified IEEE 33-node distribution system, the modified 11-node natural gas system and 5 distributed energy stations to verify the effectiveness and efficiency of the proposed method.

A flexible load active management method in optimization operation of distribution networks is proposed to discuss the significant role of active management of flexible load in regulating load curve. The models of translatable load, shiftable load and curtailable load are established and they are divided into price incentive flexible load and contract incentive flexible load firstly. Secondly, a multi-objective optimal dispatch model considering electricity purchasing cost, load peak valley difference and users' acceptance is established for different types of flexible load. Then, considering the proportion of different types of flexible load in different user types, the flexible load response model of residential load, industrial load and commercial load are obtained. Finally, the regulation effects of load curve and dispatch strategies of the overall flexible load are obtained by summarizing the dispatch strategies of different user types.

The focus of financial work is risk prevention and control, and this is also an important part of the overall national security concept. China has repeatedly stressed that strengthening financial supervision, preventing and defusing financial risks, especially systemic financial risks are the fundamental tasks of financial work. Strengthening financial supervision requires financial institutions to continuously enhance compliance awareness and take the initiative to improve compliance management. Relying on new technologies such as big data, blockchain, and artificial intelligence (AI), compliance technology (CompTech) strives to provide faster and more effective supervision schemes for financial institutions. Given the complexity of financial transactions and the huge amounts of data involved, AI and machine learning are playing an increasingly important role for financial institutions and regulators. CompTech needs to grasp the trend of AI, realize timely and efficient supervision and compliance, maintain financial security, and prevent system risks.

Increasingly applied to the financial market over recent years, AI is on track to alleviate the pain points of the market, promote the fast, sustainable development of the financial industry and spearhead transformation of the market. Compared with practices abroad, the application of intelligent finance is at a nascent stage in China, where the regulatory system still requires improvement. In this context, the Chinese financial industry should strengthen self-discipline, enhance the quality and efficiency of financial services, and control the risk of technological innovation to maintain the steady development of the industry.

Since the coining of the term “Artificial Intelligence” (AI), its definition scope has evolved from an application program with pre-set rules of logic, to a technology that simulates human cognitive function. The goal of AI is to allow computers to imitate human intelligence, perception, thinking, and action, so as to achieve automation and gain analytical insights. To imitate human intelligence, AI applications adopt two methods: rule-based and non-rule-based algorithms. Rule-based AI uses pre-set rules to “learn”, while non-rule-based AI uses machine learning algorithms to “learn” and a trained AI model to “think”. The key driving force for the development of AI is the huge increase of available data and the great improvement of computing power in traditional computers and mobile devices, as well as the continuous development of machine learning algorithms. Commercial banks conduct large numbers of customer capital transactions, and hold large amounts of account management information. The application of AI in commercial banks will effectively improve the retail service level, enhance customer experience, and alleviate difficulties such as “financial disintermediation” and fierce market competition, or become the next profit growth point of commercial banks.

Since 2013, when Yu’E Bao ushered in an era of Internet wealth management in China, the country’s “Internet + Wealth Management” market has developed rapidly. Online wealth management meets the demand for wealth management by long-tailed investors, which cannot be fulfilled by traditional wealth management modes. It will provide more constructive policy suggestions to the benefit of the better integrated development of wealth management industry and AI in China in the future by searching thoroughly the history and environment of online wealth management, learning from the effective experience of wealth management by AI abroad and combining with the current integrated development of “AI + wealth management” service industry in China.

The change of payment mode from barter to natural currency, to paper money and today’s e-payment, is a progressive process that continuously improves transaction efficiency on the premise of security and reliability. Today, with the rapid development of information science and technology, what will be the next innovation of payment mode? Already, artificial intelligence has penetrated deeply and extensively into all levels of payment, and is continuously evolving towards further intelligence and diversification. It plays a vital role in elevating payment efficiency, improving user experience, and implementing financial regulation.

A robo-advisor is an investment advisor based on core artificial intelligence technology. The technology encompasses perceptual intelligence, related to human sensory awareness such as vision and hearing; and cognitive intelligence, linked to human language, understanding and logic, such as learning, reasoning, thinking, and planning. At the current stage of development, perceptual AI mainly comprises image recognition technology, including iris and facial recognition, and unmanned driving as regards vision; and speech synthesis, voiceprint recognition, and speech evaluation as regards hearing. Cognitive AI, which is applied in games, chess, and most notably in natural language processing (NLP), includes semantic analysis, pragmatic analysis, machine translation, text matching, text classification, and dialogue system. Hence, AI technology must correspond to at least one of “eyes, ears and mouth”. Any non-human advisor in the financial industry that does not involve one of these three is simply an application of traditional network engineering technology, and cannot be included under the term robo-advisor.

Telecare medicine information systems (TMISs) provide e-health services such that patients can access medical resources conveniently and doctors can prescribe treatments rapidly. Authentication is an essential security requirement in TMISs. In particular, the growth of password-based remote patient authenticated key exchange combining extended chaotic maps has enhanced the level of secure communications for TMISs. Recently, Lee suggested an improved random-number-based password-authenticated key exchange (PAKE) using extended chaotic maps and synchronized-clock-based PAKE using extended chaotic maps on Guo and Zhang and Xiao et al.’s PAKE. Unfortunately, we found that the nonce-based scheme of Lee is insecure against known session-specific temporary information and server spoofing attacks. To cope with the aforementioned defects, this study aims to provide a new secure PAKE based on extended chaotic maps with more security functionalities for TMISs. Additionally, we show that the proposed scheme for TMISs provides high security along with low communication cost, computational cost, and a variety of security features.

With the deep integration of big data, cloud computing, artificial intelligence, Internet of Things, and other information technologies with financial services, financial boundaries have been repeatedly broken and reconstructed, while scientific and technological forces are providing continuous innovation vitality for financial services. FinTech, as defined by the Financial Stability Board (FSB) in 2016, is technology driven financial innovation, aimed at transforming or innovating financial products and services by using existing high-tech achievements, planning modern business models, and optimizing business processes, so as to promote continuous financial transformation and upgrading and improve quality and efficiency.

Sigmoid sinus wall dehiscence (SSWD) is a common pathophysiology of patients with pulsatile tinnitus (PT). However, the pathological mechanism of SSWD is unclear. This study aimed to investigate the relationship between the position of the SSWD and blood flow pattern of the transverse sinus and sigmoid sinus (TS-SS) junction. The impact of the blood flow was hypothesized to be the pathological mechanism of SSWD. Twenty patients and two healthy volunteers were analyzed retrospectively, and transient computer fluid dynamics was used to verify this hypothesis. A 4D flow magnetic resonance imaging experiment was performed to validate the numerical simulation. The position of high-velocity blood flow impacting the vessel wall (17/20) was consistent with SSWD. In healthy volunteers, the temporal bone was thin where the blood flow impacted the blood vessel wall. The average wall shear stress (20/20) and pressure (18/20) of the SSWD area (peak) were higher than those of sigmoid sinus wall anomalies (the contact area between the vessel wall and the temporal bone at the TS-SS junction). The average wall pressure percentage differences of 16/20, 11/20, and 4/20 patients were more than 5%, 10%, and 20%, respectively. The average wall shear stress percentage differences of 20/20, 18/20, and 16/20 patients were more than 5%, 10%, and 20%, respectively. In brief, the blood flow of the TS-SS junction impacted the vessel wall and increased wall pressure, which might be an important pathological mechanism of SSWD. This study could serve as a basis for the diagnosis and SSWD resurfacing surgery of patients with PT induced by SSWD.

Liu, S. and Zhao, D., 2020. The representation of dynamic factor marine element structure upgrading model based on two kinds of DSGE models. In: Li, L. and Huang, X. (eds.), Sustainable Development in Coastal Regions: A Perspective of Environment, Economy, and Technology. Journal of Coastal Research, Special Issue No. 112, pp. 337-339. Coconut Creek (Florida), ISSN 0749-0208.At present, with the deepening of the implementation of the marine strategy, the transformation and reform of the marine economic structure urgently need to conduct in-depth analysis of the wave driving factors of the marine economy. The dynamic factor analysis of the DSGE model dynamic factor model has important value for the long-term and short-term dynamic adjustment process of the marine factor structure. Based on this, this paper first studies the dynamic factor model representation of DSGE model, then analyzes the upgrading mechanism model based on the spatial-temporal configuration of marine elements, and finally gives the application of dynamic factors based on two kinds of DSGE model in the upgrading model of marine element structure.

Silver-Silver direct bonding has been developed as an alternative interconnection technique for 3D power integration which can form high-strength and low-resistance Ag joints under solid-state conditions. However, the reliability and failure mechanisms of these direct bonded joints have not been characterized yet. In this study, four direct bonded structures were accelerated aged with two different temperature cycling tests (TCT) in the temperature range between -55 °C and 220 °C. The thermally induced stresses in the metallization during TCT can be relieved by elastic and plastic deformation of the Ag films and the debonding at the interface. At higher temperatures above 150 °C, plastic deformation mechanisms dominate the stress relaxation. Stress-driven void migration along grain boundaries may lead to cracking and interfacial failure. Metallization with a diffusion barrier and large grain size can restrict the void formation and diffusion, therefore, provide a higher temperature capability. The results indicate that both the adhesion of the Ag metallization and the Ag-Ag direct bonding remain stable after 1000 thermal cycles.

As the penetration rate of new energy sources such as wind power in the power grid continues to increase, the power grid generally puts forward requirements for its participating in the primary frequency regulation of power grid. At present, the commonly adopted strategy for wind farms to participate in frequency regulation is that each wind farm should participate in primary frequency regulation of power grid, and frequent adjustment will bring a certain degree of life loss to wind power equipment. On account of this reason, this paper presents a coordinated control strategy for the frequency regulation of wind farms based on a multi-layer hierarchical structure. When the grid frequency fluctuates, the active power of some wind farms with superior performance can be adjusted according to specific circumstances to complete frequency regulation target. The simulation results verify the effectiveness of the strategy and achieve a good frequency regulation effect.

Background Hepatocellular carcinoma (HCC) is the most common malignant tumor of the liver, and its morbidity and mortality have been increasing in recent years. The early diagnosis and prompt treatment of small HCC are crucial to improve the prognosis and quality of life of patients. In China, hepatitis B virus infection is the main cause. HCC with a single tumor nodule of ≤ 3 cm in diameter, or HCC with a number of nodules, in which each nodule is ≤ 2 cm in diameter, with a total diameter of ≤ 3 cm, is considered as small HCC. The MRI liver-specific contrast agent can detect small HCC at the early stage. This has important clinical implications for improving the survival rate of patients. Main body Gd-EOB-DTPA-enhanced MRI can significantly improve the sensitivity and specificity of the detection of HBV-related small hepatocellular carcinoma, providing an important basis for the clinical selection of appropriate personalized treatment. Gd-EOB-DTPA-enhanced MRI can reflect the degree of HCC differentiation, and the evaluation of HCC on Gd-EOB-DTPA-enhanced MRI would be helpful for the selection of the treatment and prognosis of HCC patients. The present study reviews the progress of the application of Gd-EOB-DTPA in the early diagnosis of small HCC, its clinical treatment, the prediction of the degree of differentiation, and the assessment of recurrence and prognosis of HCC, including the pharmacoeconomics and application limitations of Gd-EOB-DTPA. The value of the application of HCC with the Gd-EOB-DTPA was summarized to provide information for improving the quality of life and prolonging the survival of patients. Conclusion Gd-EOB-DTPA-enhanced MRI has the diagnostic capability for small HCC with a diameter of ≤ 2 cm. This will have a broader application prospect in the early diagnosis of small liver cancer with a diameter of ≤ 1 cm in the future. The relationship between GD-EOB-DTPA-MRI and the degree of HCC differentiation has a large research space, and Gd-EOB-DTPA is expected to become a potential tool for the preoperative prediction and postoperative evaluation of HCC, which would be beneficial for more appropriate treatments for HCC patients.

Structure heterogeneity and host nucleic acids contamination are two major problems for virus-like particles (VLPs) produced by various host cells. In this study, an in vitro optimized disassembly-purification-reassembly process was developed to obtain uniform and nucleic acid free hepatitis B core (HBc) based VLPs from E. coli fermentation. The process started with ammonium sulfate precipitation of all heterogeneous HBc structures after cell disintegration. Then, dissolution and disassembly of pellets into basic subunits were carried out under the optimized disassembly condition. All contaminants, including host nucleic acids and proteins, were efficiently removed with affinity chromatography. The purified subunits reassembled into VLPs by final removal of the chaotropic agent. Two uniform and nucleic acid free HBc-based VLPs, truncated HBc149 and chimeric HBc183-MAGE3 I, were successfully prepared. It was found that disassembly degree of HBc-based VLPs had a great influence on the protein yield, nucleic acid removal and reassembly efficiency. 4 M urea was optimal because lower concentration would not disassemble the particles completely while higher concentration would further denature the subunits into disordered aggregate and could not be purified and reassembled efficiently. For removal of strong binding nucleic acids such as in the case of HBc183-MAGE3 I, benzonase nuclease was added to the disassembly buffer before affinity purification. Through the optimized downstream process, uniform and nucleic acid free HBc149 VLPs and HBc183-MAGE3 I VLPs were obtained with purities above 90% and yields of 55.2 and 43.0 mg/L, respectively. This study would be a reference for efficient preparation of other VLPs.

There is currently enormous and growing demand for flexible electronics for personalized mobile equipment, human-machine interface units, wearable medical-healthcare systems, and bionic intelligent robots. Cellulose is a well-known natural biopolymer that has multiple advantages including low cost, renewability, easy processability, and biodegradability, as well as appealing mechanical performance, dielectricity, piezoelectricity, and convertibility. Because of its multiple merits, cellulose is frequently used as a substrate, binder, dielectric layer, gel electrolyte, and derived carbon material for flexible electronic devices. Leveraging the advantages of cellulose to design advanced functional materials will have a significant impact on portable intelligent electronics. Herein, the unique molecular structure and nanostructures (nanocrystals, nanofibers, nanosheets, etc.) of cellulose are briefly introduced, the structure-property-application relationships of cellulosic materials summarized, and the processing technologies for fabricating cellulose-based flexible electronics considered. The focus then turns to the recent advances of cellulose-based functional materials toward emerging intelligent electronic devices including flexible sensors, optoelectronic devices, field-effect transistors, nanogenerators, electrochemical energy storage devices, biomimetic electronic skins, and biological detection devices. Finally, an outlook of the potential challenges and future prospects for developing cellulose-based wearable devices and bioelectronic systems is presented.

With the increasing complexity of power systems and the widespread penetration of renewable energy sources (RES), real-time situational awareness for power systems is of great significance for operation scheduling. With the impact of RES on power system operation considered, a situational awareness key performance index (KPI) system for power systems with high proportion of RES is proposed in this work, which consists of reserve capacity abundance, ramp resource abundance, center of inertia (COI) frequency deviation, interface power flow margin, synthesized voltage stability, and angle stability margin. Then, the KPIs are synthesized and visualized by decision tree method and radar chart method, respectively, for monitoring the operation states (i.e., normal, alert, and emergency states) of power systems with high proportion of RES. Numerical simulations are conducted in the revised New England 16-machine 68-bus power system and the actual CEPRI-RE power system in the northwest region of China with high proportion of RES. The results show that the proposed KPI-based situational awareness method is able to monitor the real-time state of power systems with high proportion of RES accurately, and can assist power dispatchers to make effective decisions.

In recent years, with the continuous promulgation of relevant national energy storage strategies and policies and the rapid development of electrochemical energy storage technology, energy storage systems are being used more and more widely in power grids. Lithium-ion batteries have become the main battery for energy storage system applications by virtue of their high energy density, high cycle times, low self-discharge rate and low environmental pollution. In grid energy storage applications, it is often necessary to connect a large number of batteries in series and parallel to meet capacity and voltage requirements, which can lead to the amplification of very small differences in parameters between individual batteries and accumulate during charging and discharging work, eventually causing a decrease in the energy efficiency of the battery pack, a decrease in service life, and even explosive accidents. The equalization technology can well improve the imbalance problem caused by the inconsistent performance parameters between single cells, and has become a hot spot for research in recent years. In this paper, based on the analysis of battery characteristics and the characteristics of energy storage applications, we design an equalization current algorithm for battery pack under charging and discharging conditions, and design a bi-directional equalization circuit for single battery equalization, and use a modular structure and combine the current equalization algorithm to give a design scheme for a series battery pack equalization system.

Designing and fabricating an efficient and reusable photocatalyst has become a pursuit, as photocatalyst plays a key role in solving the energy crisis and the environmental pollution. However, the major stumbling blocks such as low photo-efficiency, non-reusability and serious electron–hole recombination hinder practical application of photocatalyst. Herein, a novel self-growing ZnO with numerous nanosheets grown on the surface of dumbbell-shape have been successfully synthesized via a simple hydrothermal growth, meanwhile, the nanosheet was exposed high-energy (101) crystal plane. Electrochemical impedance spectroscopy measurements show that nanosheets with exposed (101) facet were dominantly promote charge generation, separation and transfer. In order to inhibit the photocorrosion of ZnO, the graphene was loaded on the surface of ZnO via secondary hydrothermal process. Moreover, in the measurements of degradation RhB, the rate constant of samples follow the sequence: RGO@ZnO-10 (0.0568 min−1) > ZnO-10 (0.0460 min−1) > ZnO-9 (0.0148 min−1), which is demonstrated that nanosheet enhances the photoelectrocatalytic properties. Therefore, the novel ZnO structure not only has a promising application in dealing with environmental and industrial pollutants, but also provides a new strategy to design and fabricate reusable and high efficiency photocatalysts.

Clinically significant portal hypertension (CSPH) is associated with an incremental risk of esophageal varices and overt clinical decompensations. However, hepatic venous pressure gradient (HVPG) measurement, the gold standard for defining CSPH (HVPG≥10 mm Hg) is invasive and therefore not suitable for routine clinical practice. This study aims to develop and validate a radiomics-based model as a noninvasive method for accurate detection of CSPH in cirrhosis. The prospective multicenter diagnostic trial (CHESS1701, ClinicalTrials.gov identifier: NCT03138915 ) involved 385 patients with cirrhosis from five liver centers in China between August 2016 and September 2017. Patients who had both HVPG measurement and contrast-enhanced CT within 14 days prior to the catheterization were collected. The noninvasive radiomics model, termed rHVPG for CSPH was developed based on CT images in a training cohort consisted of 222 consecutive patients and the diagnostic performance was prospectively assessed in 163 consecutive patients in four external validation cohorts. rHVPG showed a good performance in detection of CSPH with a C-index of 0·849 (95%CI: 0·786–0·911). Application of rHVPG in four external prospective validation cohorts still gave excellent performance with the C-index of 0·889 (95%CI: 0·752–1·000, 0·800 (95%CI: 0·614–0·986), 0·917 (95%CI: 0·772–1·000), and 0·827 (95%CI: 0·618–1·000), respectively. Intraclass correlation coefficients for inter- and intra-observer agreement were 0·92–0·99 and 0·97–0·99, respectively. A radiomics signature was developed and prospectively validated as an accurate method for noninvasive detection of CSPH in cirrhosis. The tool of rHVPG assessment can facilitate the identification of CSPH rapidly when invasive transjugular procedure is not available.

The critical heat flux (CHF) is one of the main thermal-hydraulics safety limits in water-cooled reactors. At CHF, a film of vapor is formed on the heated wall and the wall temperature can sharply increase in a short period of time, which may lead to damage of the heater surface. In spite of many studies, the CHF mechanisms are still not well understood due to the complexity of this two-phase phenomenon and its dependence on local thermal-hydraulic conditions. Two-phase boiling experiments have been conducted to observe CHF and post-CHF behavior in prototypical conditions for small modular reactors (mass flux: 560–1570 kg/m2.s, pressure: 7.6–16.4 MPa, inlet subcooling: 160–440 kJ/kg) in a 2 × 2 square rod bundle geometry with a chopped-cosine power profile at the University of Wisconsin-Madison. The fuel rods temperature history during and following CHF were used in the solution of the two-dimension inverse heat transfer problem to estimate the wall temperatures and wall heat fluxes. This analysis showed different transient boiling curves for different flow regimes that differ qualitatively and quantitatively from the typical boiling curve considered in steady-state two-phase heat transfer analysis. The experiments suggest that the inverse heat transfer analysis approach can be used to estimate the post-CHF heat transfer and to better understand the CHF mechanisms at high pressure typical of water-cooled reactors.

Models for simulation are vital for the authenticity of the simulation. Modeling doubly fed induction generation (DFIG) for power system stability analysis has attracted a great deal of research interests in the past few years due to the wide applications of DFIG in wind power generation. The models developed by the wind generator manufacturers are not only complicated, but also proprietary and very specific to their own products. Many simplified generic models have been proposed. Among them, the current-source based model is most widely used for power system stability analysis. The validation work on this model so far has been based on the selected simulation scenarios or limited real measurements. However, there has been no systematic and theoretic analysis on the validity of the current-source based model, which may cause inappropriate applications of this type of model in real engineering practices. This paper presents the conditions for using the current-source based model for power system stability analysis; then examines the model's validity under symmetrical and asymmetrical fault conditions. Our practices for modeling and validating a real wind farm in North China confirm the validity analysis of this work on the current-source based DFIG model.

A temperature controlled low field nuclear magnetic resonance (LF-NMR) T2 relaxometry technique based on the mobility changes of water trapped in hydrogels, was successfully used for on-line determination of the sol-gel transition temperature for chitosan/β-glycerophosphate (CS/GP) hydrogels in real time. The LF-NMR results indicated that the gelation temperature decreased gradually with increasing GP concentration, and the results were supported by both thermogravimetric differential scanning calorimetry (DSC) and rheological findings; however, LF-NMR allows non-destructive monitoring of samples during continuous heating. Moreover, as the mobility of water molecules varies greatly during the sol-gel phase transition, the LF-NMR measurement was more sensitive and accurate (RSD ≤ 0.1 %, n = 5) compared with DSC (RSD: 1.2 %–3.7 %, n = 5) and rheology (RSD: 1.1 %–2.3 %, n = 5).

Sigmoid sinus wall anomalies (SSWA) are a common pathophysiology of pulsatile tinnitus (PT) and usually treated by sigmoid sinus wall dehiscence (SSWD) resurfacing surgery. However, symptoms of tinnitus remain unrelieved after surgery in some patients with PT, and even new tinnitus appears. The cause of the difference in therapeutic effects is unclear. In this study, eight patient-specific SSWA geometric models were reconstructed on the basis of computed tomography angiography, including four cases of postoperative rehabilitation (group 1, 1–4 cases) and four cases of non-rehabilitation (group 2, 5–8 cases). Transient-state computational fluid dynamics (CFD) was performed to clarify the SS blood flow pattern and hemodynamic states. The wall pressure distribution on SSWA area, pressure difference, and flow pattern in SS were calculated to evaluate the hemodynamic changes of rehabilitation and non-rehabilitation patients before and after surgery. The difference of hemodynamics between these patients was statistically analyzed. The accuracy of CFD simulation was evaluated by cross validating the numerical and particle image velocimetry experimental results. Results showed that the SSWA area in patients with PT was loaded with high pressure. No difference was found in the hemodynamic characteristics between the two groups pre- and postoperation. When the average pressure (Pavg) and time-average Pavg (TAPavg) on the SSWA area were studied, the TAPavg difference pre- and postoperation between the two groups was found significant (p = 0.0021). The TAPavg difference had a negative change in postoperative rehabilitation patients (case 1, -44.49 Pa vs. case 2, -15.85 Pa vs. case 3, -25.88 Pa vs. case 4, -16.58 Pa). The postoperative TAPavg of non-rehabilitation patients was higher than the preoperative one (case 5, 24.70 Pa vs. case 6, 28.56 Pa vs. case 7, 5.81 Pa vs. case 8, 13.04 Pa). The velocity streamlines in the SS with rehabilitation became smoother and more regular than that without rehabilitation. By contrast, the velocity streamlines in SS without rehabilitation showed increased twisting and curling. No difference was found in time-average volume-averaged vorticity (TAVavgV) between the two groups. Therefore, the high pressure of the vessel wall on SSWA area was one of the causes of PT. The variation of SSWA wall pressure difference before and after PT was the cause of the difference in therapeutic effects after SSWD resurfacing surgery. In patients with SSWA, disordered blood flow in SS was another cause of PT. SSWD repair may relieve tinnitus to some extent, but blood flow disorders may still arise.

© 2018 Elsevier Ltd A parallel algorithm is proposed for scalable generation of large-scale tetrahedral meshes. The key innovation is the use of a mesh-simplification based domain decomposition approach. This approach works on a background mesh with both its surface and its interior elements much larger than the final elements desired, and decomposes the domain into subdomains containing no undesirable geometric features in the inter-domain interfaces. In this way, the most time-consuming part of domain decomposition can be efficiently parallelized, and other sequential parts consume reasonably limited computing time since they treat a very coarse background mesh. Meanwhile, the subsequent parallel procedures of mesh generation and improvement are most efficient because they can treat individual subdomains without compromising element quality. Compared with published state-of-the-art parallel algorithms, the developed parallel algorithm can reduce the clock time required by the creation of one billion elements on 512 computer cores from roughly half an hour to less than 4 minutes.

Seeking nodes whose removal can effectively dismantle networks is closely related to the robustness of networks under targeted attacks or malicious software. Modern systems, such as critical infrastructure networks and cyber-physical systems, however, become increasingly dependent on others, which can be encapsulated into the framework of interdependent networks. In this brief, we focus on the optimal dismantling of interdependent networks, and propose a novel algorithm, named inverse explosive percolation (IEP), to find the optimal removal nodes. The IEP proceeds by first identifying the nodes which make the least contribution to the giant mutual connected cluster of interdependent networks. When nodes have the same contribution, the one with the smallest overlapping degree is selected. We apply the IEP algorithm to interdependent networks composed of real-world power grids, Internet networks and artificial networks, and find IEP performs much better than the existing methods in various kinds of networks. Based on its efficiency, IEP can be applied to large-scale systems.