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ABSTRACTVirtual geographical scenes aim to naturally represent the real world and aid in comprehending geographic information. However, current virtual geographical scene modeling methods have problems detecting change information and low efficiency in dynamic modeling. Additionally, the modeling process lacks guidance from domain experts, resulting in poor modeling standardization. Therefore, this paper proposes a combined data-driven and knowledge-driven virtual geographical scene twin modeling method. We discuss the three-domain association geographical scene knowledge graph, change information detection network based on knowledge graph and deep learning, and knowledge-guided semantic modeling algorithms in detail. These methods enhance the ability of virtual geographical scenes to describe the changing real world. Furthermore, we select an urban bridge construction geographical scene with obvious change characteristics as a typical case, develop a prototype system, and conduct an experimental analysis. The results show that our method can fully and effectively utilize the geographical scene data and knowledge and improve the reusability of the knowledge. The average change detection accuracy in geographical scene information reaches 92.46%, and the dynamic modeling efficiency of virtual geographical twin scenes reaches 29.97 fps. Compared to other 3D modeling methods, the proposed method can represent the dynamic real world more timely, accurately, completely, and comprehensively.

[Introduction] Global climate change and its negative impacts are serious humanitarian challenges. Accelerating the construction of a new energy system and promoting energy transition to green and low-carbon are the key to addressing the above challenge. Building a new power system is the central link in planning and constructing a new energy system. [Method] The characteristics and challenges in the six stages of constructing a new power system with new energy source as the main body, and potential roles of energy storage were described and analyzed. The viewpoint that energy storage, especially long-term energy storage, is a key technology for building a new power system was proposed. [Result] To deal with vague concept, unclear technical system and undefined R&D system for long duration energy storage in China, by analyzing the international use cases, the concept system of long-duration energy storage and its technology system covering four categories (including mechanical energy storage, thermal storage, electrochemical energy storage, and chemical energy storage) are proposed. And the R&D trends in developed countries are shown. [Conclusion] It is expected that the relevant content can provide reference for the research and application of long duration energy storage in China.

ABSTRACTPerson searches aim to simultaneously locate and identify persons to be queried from different scenes, which is crucial for disaster emergency management and public safety. However, the high variability of environmental features in different video scenes, along with the susceptibility of people searching for occlusions or dense populations, results in existing methods suffering from inefficiency and poor accuracy in searching for cross-view persons. Therefore, we propose a cross-view intelligent person search method based on multifeature constraints. First, we establish the global-local context-aware (GLCA) module, which fully extracts the differential personnel features. Second, we construct the semantic complementarity and feature aggregation (SCFA) module for personnel-scale feature constraints in different contexts. Third, we constrain the method in terms of person spatial, person identity, and detection confidence features to improve person search accuracy. Finally, we construct a case experiment dataset, select two public benchmark datasets, and conduct a detailed experimental analysis based on them. The results show that our method can be applied to personnel search tasks in complex scenarios well, and the search results outperform those of 25 other state-of-the-art algorithms, with mAPs improved by 0.41%−19.71%. This approach effectively enhances the informatization level of disaster emergency rescue and public safety management.

Crowd evacuation simulation using virtual reality (VR) is significant for digital emergency response construction. However, existing evacuation simulation studies suffer from poor adaptation to complex environments, inefficient evacuations, and poor simulation effects and do not fully consider the impacts of specific disaster environments on crowd evacuation. To more realistically express the crowd evacuation results obtained under the influence of fire environments and the subjective consciousness of pedestrians in subway stations, we designed a dynamic pedestrian evacuation path planning method under multiple constraints, analysed the influences of an ‘environmental role’ and a ‘subjective initiative’ on crowd evacuation, established an improved social force model (ISFM)-based crowd evacuation simulation method in VR, developed a prototype system and conducted experimental analyses. The experimental results show that the crowd evacuation time of the ISFM is affected by the disaster severity. In simulation experiments without disaster scenarios, the improved model's crowd evacuation efficiency improved by averages of 12.53% and 15.37% over the commercial Pathfinder software and the original social force model, respectively. The method described herein can effectively support real-time VR crowd evacuation simulation under multiexit and multifloor conditions and can provide technical support for emergency evacuation learning and management decision analyses involving subway fires.

Holographic projection technology can provide a more intuitive and efficient visualization effect for a digital twin bridge construction scene. However, pre-rendering methods in the existing research work are usually used to implement holographic visualization, which is static display. The above-mentioned methods for static display have many shortcomings, such as poor adaptability, low rendering efficiency and lack of real-time. A dynamic holographic modelling approach is proposed for the augmented visualization of digital twin scenes for bridge construction. Firstly, a dynamic segmentation algorithm with adaptive screen size was designed to high-efficiently generate holographic scenes. Secondly, a motion blur control method was designed to improve the rendering efficiency of holographic scenes according to human visual characteristics. Finally, a prototype system was developed, and the corresponding experimental analysis was completed. The experimental results show that the method proposed in this article can support adaptive screen size image segmentation and real-time generation of holographic scenes for bridge construction. The amount of scene data can be reduced to more than 30%, which significantly improves rendering efficiency and reduces glare.

In this study, a Co-30Ni-10Al-6Ta-10Cr alloy was designed based on CALPHAD (Calculation of Phase Diagrams) method targeting high γ′ phase fraction and solvus, and optimal thermal processing window. Experimental results concurred with the calculations and validated Cr as a γ phase-forming element in Co-Ni-Al-Ta-based alloys. The incorporation of Cr in the alloy helps mitigate lattice misfit, coarsening rate, and alloy density, while enhancing microstructural stability. A certain amount of Cr led to the development of a superalloy with both high mechanical performance γ′ solvus and low density. Moreover, the oxidation resistance of the Co-Ni-Al-Ta-based high-temperature alloy can be substantially elevated by the introduction of Cr. At 1000 °C, the Co-30Ni-10Al-6Ta-10Cr alloy displayed comparatively low oxidation weight gain, which signifies its excellent oxidation resistance. This is mainly attributed to the formation of continuous (Co,Ni)(Al,Cr)2O4 spinel oxide layers during prolonged oxidation.

This study presents the effect of small additions of Cr, Mo, or V on the microstructure, crystallographic features of martensitic transformation, and shape memory effect of Cu-13.5Al–4Ni master alloy. The results show that the studied alloys consist of dominant β'1 (18R) martensitic structure and fine bcc precipitates, which are riched in the alloying elements but poor in the Cu content. The martensitic transformation starts temperatures of the alloys are 414K, 385K, and 394K when X = 0.5Cr, 0.5Mo, or 0.5V, respectively. More importantly, a drop in grain size was achieved in the studied alloys, which improved the shape memory effect in Cu-13.5Al–4Ni alloys. As a result, the studied alloys exhibit a steady increase of shape memory effect as the pre-strain changed from 6% to 10%, which the maximum shape memory effect reaching 6.2%, 5.8%, and 5.5% for X = 0.5Cr, 0.5Mo, and 0.5V, respectively.

It is essential to establish a digital twin scene, which helps to depict the dynamically changing geographical environment accurately. Digital twins could improve the refined management level of intelligent tunnel construction; however, research on geographical twin models primarily focuses on modeling and visual description, which has low analysis efficiency. This paper proposes a knowledge-guided intelligent analysis method for the geometric deformation of tunnel excavation profile twins. Firstly, a dynamic data-driven knowledge graph of tunnel excavation twin scenes was constructed to describe tunnel excavation profile twin scenes accurately. Secondly, an intelligent diagnosis algorithm for geometric deformation of tunnel excavation contour twins was designed by knowledge guidance. Thirdly, multiple visual variables were jointly used to support scene fusion visualization of tunnel excavation profile twin scenes. Finally, a case was selected to implement the experimental analysis. The experimental results demonstrate that the method in this article can achieve an accurate description of objects and their relationships in tunnel excavation twin scenes, which supports rapid geometric deformation analysis of the tunnel excavation profile twin. The speed of geometric deformation diagnosis is increased by more than 90% and the cognitive efficiency is improved by 70%. The complexity and difficulty of the deformation analysis operation are reduced, and the diagnostic analysis ability and standardization of the geographic digital twin model are effectively improved.

A Cu–10Al–6Mn–3Fe–4Ga (wt.%) single crystal was simply prepared, and its microstructure, reversible martensitic transformation, mechanical and SME properties were investigated. The results show that this single crystal consists of dominant 2H martensite retained L21 parent and fine Fe-rich nanoparticles. Its reversible martensitic transformation temperatures are respectively 313 K (Ms), 299 K (Mf), 339 K (As), and 354 K (Af), which are suitable for practical applications. A large stress platform with a strain of approximately 8% was associated with the reorientation of existing martensite and stabilization of stress-induced martensite. Furthermore, full shape recovery characteristics are obtained all the time while changing the pre-strains from 6% to 11%. The maximum shape memory effect is up to 9.2% with a 100% shape recovery rate.

Abstract Objective To assess the anti-tumor activity and side effects of different dosages of paclitaxel (albumin binding type) (hereinafter referred to as nab-P) combined with Apatinib (hereinafter referred to as AP) in platinum-resistant ovarian cancer cell line and xenograft models. Methods SKOV-3/DDP cell line was selected as the research object in cytology experiment. Firstly, we divided it into three groups for experiments to explore the individual effects of nab-P and AP. a): Control group, blank control, no drug intervention; b): nab-P group, nab-P 40 μmol/l; c): AP group, AP 50 μmol/l (Drug doses were IC-50 values that detected by MTT assay). Apoptosis related protein (Bax, bcl-2), vascular related protein(p-VEGFR-2), invasion related protein (MMP-2) expression were detected by Western blot and Cellular immunofluorescence, the invasion ability of tumor cells were detected by Transwell and Cell scratch test. Based on these dates, secondly, establishing different doses of nab-P combined with Ap to explore the curative effect of combination therapy. a): Control group, blank control, no drug intervention; b): Group-1, nab-P 5 μmol/l + AP 10 μmol/l, c): Group-2, nab-P 4.5 μmol/l + AP 10 μmol/l, d): Group-3, nab-P 4 μmol/l + AP 10 μmol/l, e): nab-P group, nab-P 5 μmol/l, f): AP group, AP 10 μmol/l (MTT assay). The combination index was analyzed by Compusyn software, Western blot, Immunofluescence, Transwell and Cell scratch test also were also chose to observe of inhibition effect. Thirdly, we used xenograft models to verify the results of cytological experiments. Tumor-forming BALB/c female nude mice were randomly divided into 4 groups, a): Control group, no drug intervention, only saline injection, b): nab-P 20 mg/kg + AP 150 mg/kg, c): nab-P 18 mg/kg + AP 150 mg/kg, d): nab-P 16 mg/kg + AP 150 mg/kg (The doses were guided by the pharmaceutical manufacturers). The tumor growth curve was analyzed during the experiment. And the apoptosis related protein (Bax, bcl-2), angiogenesis related protein (CD31, p-VEGFR-2) and invasion related protein (MMP-2) were observed by Western blot, Immunofluescence and Immunohistochemistry to analysis the ant-tumor effects. The quality of life in nude mice were observed to analysed the drug-induced side effects. Result In the separate medication section, (1) The IC-50 value of nab-P was 45.53 ± 4.06 μmol/l, while the AP was 50.66 ± 4.96 umol/L (48 h). (2) The expressions of bcl-2 (nab-P group, AP group), p-VEGFR-2 (AP group), MMP-2(nab-P group, AP group) were higher than Control group, while Bax (nab-P group, AP group) lower (P

Fe additives may play an important role in the preparation of aluminum-based hydrolysis hydrogen powder, with high hydrogen yield, low cost, and good oxidation resistance. Therefore, it is necessary to ascertain the effect of Fe on the hydrogen production performance of Al-Bi-Sn composite powders. According to the calculated vertical cross-section of the Al-10Bi-7Sn-(0~6)Fe (wt.%) quasi-binary system, Al-10Bi-7Sn-xFe (x = 0, 0.5, 1.5, 3) wt.% composite powders for hydrogen production were prepared by the gas-atomization method. The results showed that the Al-10Bi-7Sn-1.5Fe (wt.%) powder exhibited an extremely fast hydrogen generation rate at 50 °C, which reached 1105 mL·g−1 in 27 min in distilled water, 1086 mL·g−1 in 15 min in 0.1 mol·L−1 NaCl solution, and 1086 mL·g−1 in 15 min in 0.1 mol·L−1 CaCl2 solution. In addition, the antioxidant properties of these powders were also investigated. The results showed that the hydrogen production performance of the Al-10Bi-7Sn-1.5Fe (wt.%) powder could retain 91% of its hydrogen production activity, even though the powder was exposed to 25 °C and 60 RH% for 72 h. The addition of Fe not only promoted the hydrogen generation rate of the Al-Bi-Sn composite powders, but also improved their oxidation resistance. The Al-10Bi-7Sn-1.5Fe (wt.%) composite powder shows great potential for mobile hydrogen source scenarios with rapid hydrogen production.

In this work, two isothermal sections of the Co-Ta-Si ternary system at 900 °C and 1100 °C are constructed in the whole composition range via phase equilibrium determination with the help of electron probe microanalysis (EPMA) and X-ray diffraction (XRD) techniques. Firstly, several reported ternary phases G (Co16Ta6Si7), G″ (Co4TaSi3), E (CoTaSi), L (Co3Ta2Si) and V (Co4Ta4Si7) are all re-confirmed again. The G″ phase is found to be a kind of high-temperature compound, which is unstable at less than 1100 °C. Additionally, the L phase with a large composition range (Co32–62Ta26–36Si10–30) crystallizes with a hexagonal crystal structure (space group: P63/mmc, C14), which is the same as that of the binary high-temperature λ1-Co2Ta phase. It can be reasonably speculated that the ternary L phase results from the stabilization toward low-temperature of the binary λ1-Co2Ta through adding Si. Secondly, the binary CoTa2 and SiTa2 phases are found to form a continuous solid solution phase (Co, Si)Ta2 with a body-centered tetragonal structure. Thirdly, the elemental Si shows a large solid solubility for Co-Ta binary compounds while the Ta and Co are hardly dissolved in Co-Si and Ta-Si binary phases, respectively.

In this paper, based on CMF high voltage and liquid precipitation method, the ternary precursor is prepared; then by mixing it with lithium carbonate, the analysis is made for their properties through the XRD and thermogravimetry; finally, the ternary cathode material of lithium ion battery is prepared under the high temperature reaction for the mixture of the precursors and lithium carbonate, and the electrochemical properties of the material are investigated. The oxidative dehydration process of the ternary precursor is mainly concentrated at 250°C-350°C under the CMF high voltage. As the temperature increases to 200°C and 300°C respectively, the ternary precursors are developed into Me(OH) 2 and CoNiOOH structures respectively; as the temperature further increases CoNiOOH was anhydrated into Mn (Ni, Co) 2O4, and the material surface becomes very dense; at 300-500°C, the mixture shows the characteristics of the composite oxide (LiNi0.5Co0.2Mn0.3O2); at 600°C above, the diffraction peak belonging to lithium carbonate completely disappears, and LiNi0.5Co0.2Mn0.3O2 is basically generated. The electrochemical analysis of LiNi0.5Co0.2Mn0.3O2 shows that the maximum specific capacity of the battery for the first charge and discharge is 172 mAh/g, and the Coulomb efficiency is 90.1%. When the lithium content in the material is set to be 1.09, the battery parameters such as median voltage and discharge platform all reach the optimal value.

This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1186/s13048-021-00785-1.

During the past decades, the production performance analysis and optimization have played a significant role in queueing network system production planning and operation design for the manufacturing plants, but how to model the optimized production system performance and solve it is facing great challenges. Since the more and more wide use of queueing network, the non-conforming product scenarios such as rework and departure, cause mass random interference. These problems when modelled in the conventional analysis and optimization models are extremely difficult to solve as they are coupled and NP-hard problems. This paper considers a modified M/M/n/m-first come first service (M/M/n/m-FCFS) queueing network approximation model that is developed to maximize utilization and profit by analysing the queue time and queue length of the products under the constraint conditions. A hybrid meta-heuristics is applied to solve the approximation model, both the service rate and buffer allocation of the queueing network system can be determined. Finally, to assess the effectiveness of the proposed method, extensive numerical experimental results from the approximation model are compared to the ARENA simulation, and sensitivity and validation analysis are also conducted, which prove it accurate, believable, and effective.

C2H2, C2H4, and C2H6 are important oil-dissolved gases in power transformers. Detection of the composition and content of oil-dissolved gases in transformers is very significant in the diagnosis and assessment of the state of transformer operations. The commonly used oil-gas analysis methods have many disadvantages, so this paper proposes a Ni-doped carbon nanotube (Ni-CNT) gas sensor to effectively detect oil-dissolved gases in a transformer. The gas-sensing properties of the sensor to C2H2, C2H4, and C2H6 were studied using the test device. Based on the density functional theory (DFT) the adsorption behaviors of the three gases on intrinsic carbon nanotubes (CNTs) and Ni-CNTs were calculated. The adsorption energy, charge transfer, and molecular frontier orbital of the adsorption system were also analyzed. Results showed that the sensitivity of the CNT sensor to the three kinds of gases was in the following order: C2H2 > C2H4 > C2H6. Moreover, the doped Ni improved the sensor response, and the sensor response and gas concentration have a good linear relationship.

The tunability of semi-conductivity in SrTiO3 single crystal substrates has been realized by a simple encapsulated annealing method under argon atmosphere. This high temperature annealing-induced property changes are characterized by the transmission spectra, scanning electron microscopy (SEM) and synchrotron-based X-ray absorption (XAS). We find the optical property is strongly influenced by the annealing time (with significant decrease of transmittance). A sub gap absorption at ~427 nm is detected which is attributed to the introduction of oxygen vacancy. Interestingly, in the SEM images, annealing-induced regularly rectangle nano-patterns are directly observed which is contributed to the conducting filaments. The XAS of O K-edge spectra shows the changes of electronic structure by annealing. Very importantly, resistance switching response is displayed in the annealed SrTiO3 single crystal. This suggests a possible simplified route to tune the conductivity of SrTiO3 and further develop novel resistance switching materials.

The detection of partial discharge and analysis of SF6 gas components in gas-insulated switchgear (GIS) is important for the diagnosis and operating state assessment of power equipment. The use of a Pt-doped TiO2 nanotube arrays sensor for detecting sulfur hexafluoride (SF6) decomposition products is proposed in this paper. The electrochemical pulse deposition method is employed to prepare the sensor array. The sensor’s response to the main characteristic gaseous decomposition products of SF6 is evaluated. The gas sensing characteristic curves of the Pt-doped TiO2 nanotube sensor and intrinsic TiO2 nanotube arrays sensor are compared. The mechanism of the sensitive response is discussed. Test results showed that the Pt-doped nanoparticles not only change the gas sensing selectivity of the TiO2 nanotube arrays sensor with respect to the main characteristic SF6 decomposition products, but also reduce the operating temperature of the sensor.

The detection of partial discharge through analysis of SF6 gas components in gas-insulated switchgear, is significant for the diagnosis and assessment of the operating state of power equipment. The present study proposes the use of a TiO2 nanotube array sensor for detecting the SF6 decomposition product SO2, and the application of the anodic oxidation method for the directional growth of highly ordered TiO2 nanotube arrays. The sensor response of 10–50 ppm SO2 gas is tested, and the sensitive response mechanism is discussed. The test results show that the TiO2 nanotube sensor array has good response to SO2 gas, and by ultraviolet radiation, the sensor can remove attached components very efficiently, shorten recovery time, reduce chemical poisoning, and prolong the life of the components.

In this study, the isothermal sections of the Co-Re-Ta ternary system at 1100, 1200, and 1300 °C have been experimentally investigated by means of electron probe microanalysis and X-ray diffraction. The results indicated the following: (1) The solid solubilities of the λ3, (εCo, Re), χ-Re7Ta3, and bcc-(Ta) phases were large and changed very little from 1100 to 1300 °C; (2) more interestingly, the λ2 phase, with a very limited solubility of Re, was surrounded by the λ3 phase; (3) the solubility of Re for the μ-Co6Ta7 phase increased slowly from 1100 to 1300 °C. These experimental results will be useful for Co-based high-temperature alloys, especially as a supplement for thermodynamic databases.

Two isothermal sections of the Ni-V-Ta ternary system at 1200 °C and 1000 °C have been experimentally established using X-ray diffraction, electron probe microanalysis, energy dispersive spectroscopy, and differential scanning calorimeter with equilibrated key alloys. The equilibrium composition of each phase is measured by electron probe microanalysis and energy dispersive spectroscopy. The results indicate that: (1) nine three-phase and eight three-phase regions were confirmed in the isothermal section at 1200 °C and 1000 °C, respectively; (2) the C14 phase with a large solubility of about 51.2 at. % Ni was observed at 1200 °C, while it forms a single-phase region at 1000 °C; (3) a small liquid region was confirmed at 1200 °C, but disappeared at 1000 °C.

Aiming at the problems of high investment and low efficiency in the planning and construction of electric vehicle (EV) charging stations in cities, an optimization model for site selection and capacity determination of charging stations considering the uncertainty of users' dynamic charging demands is proposed. Firstly, based on the travel chain theory and the Origin-Destination (OD) matrix, the travel characteristics of EVs are studied, and the spatial and temporal distribution prediction model of EV charging load is established through the dynamic Dijkstra algorithm combined with the Monte Carlo method. Secondly, a site selection model for the charging station is established which takes the minimum annualized cost of the charging station operator and the annualized economic loss of the EV users as the goal. At the same time, the weighted Voronoi diagram and Adaptive Simulated Annealing Particle Swarm Optimization algorithm (ASPSO) are adopted to determine the optimal number/site selection and service scope of charging stations. Finally, an uncertain scenario set is introduced into the capacity determination model to describe the uncertainty of the users' dynamic charging demands, and the robust optimization theory is utilized to solve the capacity of the charging station. A case study is carried out for the EV charging station planning problem in some urban areas of a northern city, and the validity of the model is verified. [ABSTRACT FROM AUTHOR]

Person searches aim to simultaneously locate and identify persons to be queried from different scenes, which is crucial for disaster emergency management and public safety. However, the high variability of environmental features in different video scenes, along with the susceptibility of people searching for occlusions or dense populations, results in existing methods suffering from inefficiency and poor accuracy in searching for cross-view persons. Therefore, we propose a cross-view intelligent person search method based on multifeature constraints. First, we establish the global-local context-aware (GLCA) module, which fully extracts the differential personnel features. Second, we construct the semantic complementarity and feature aggregation (SCFA) module for personnel-scale feature constraints in different contexts. Third, we constrain the method in terms of person spatial, person identity, and detection confidence features to improve person search accuracy. Finally, we construct a case experiment dataset, select two public benchmark datasets, and conduct a detailed experimental analysis based on them. The results show that our method can be applied to personnel search tasks in complex scenarios well, and the search results outperform those of 25 other state-of-the-art algorithms, with mAPs improved by 0.41%-19.71%. This approach effectively enhances the informatization level of disaster emergency rescue and public safety management. [ABSTRACT FROM AUTHOR]

Introduction: Post‑anaesthesia care unit (PACU) delirium affects 5%–45% of patients after surgery and is associated with postoperative delirium and increased mortality. Up to 40% of PACU delirium is preventable, but it remains under‑recognised due to a lack of awareness of its diagnosis. The nursing delirium screening scale (Nu‑DESC) has been validated for diagnosing PACU delirium, but is not routinely used locally. This study aimed to use Nu‑DESC to establish the incidence and risk factors of PACU delirium in patients undergoing non‑cardiac surgery in the surgical population. Methods: We conducted an audit of eligible patients undergoing major surgery in three public hospitals in Singapore over 1 week. Patients were assessed for delirium 30–60 min following their arrival in PACU using Nu‑DESC, with a total score of ≥2 indicative of delirium. Results: A total of 478 patients were assessed. The overall incidence rate of PACU delirium was 18/478 (3.8%), and the incidence was 9/146 (6.2%) in patients aged > 65 years. Post‑anaesthesia care unit delirium was more common in females, patients with malignancy and those who underwent longer operations. Logistic regression analysis showed that the use of bispectral index (P < 0.001) and the presence of malignancy (P < 0.001) were significantly associated with a higher incidence of PACU delirium. Conclusion: In this first local study, the incidence of PACU delirium was 3.8%, increasing to 6.2% in those aged > 65 years. Understanding these risk factors will form the basis for which protocols can be established to optimise resource management and prevent long‑term morbidities and mortality in PACU delirium. [ABSTRACT FROM AUTHOR]