Search

The modern technological advancement influences the growth of the cyber–physical system and cyber–social system to a more advanced computing system cyber–physical–social system (CPSS). Therefore, CPSS leads the data science revolution by promoting tri-space information resource from a single space. The establishment of CPSSs increases the related privacy concerns. To provide privacy on CPSSs data, various privacy-preserving schemes have been introduced in the recent past. However, technological advancement in CPSSs requires the modifications of previous techniques to suit its dynamics. Meanwhile, differential privacy has emerged as an effective method to safeguard CPSSs data privacy. To completely comprehend the state-of-the-art developments and learn the field’s research directions, this article provides a comprehensive review of differentially private data fusion and deep learning in CPSSs. Additionally, we present a novel differentially private data fusion and deep learning Framework for Cyber–Physical–Social Systems , and various future research directions for CPSSs.

Large-scale group decision-making (LSGDM), which involves dozens to hundreds of decision-makers (DMs), is attracting extensive attention and has become an interesting and hot topic in recent years. Because of various backgrounds and expression habits, DMs tend to elicit preferences with different preference representation structures. Moreover, due to various attitudes and interests, some DMs may adopt noncooperative behaviors to further benefit themselves in LSGDM. To cope with these issues, this study develops an adaptive consensus framework to support heterogeneous LSGDM. A cosine similarity based optimization model is constructed and its analytical solution is derived to directly obtain the collective priority vector of the group using heterogeneous preferences. An extended k -means algorithm is then used to classify DMs. Subsequently, a two-stage uninorm-based behavior management method is developed to generate personalized weight feedback to each DM and subcluster according to their cooperative and noncooperative degrees in the consensus-reaching process. Finally, an illustrative example followed by simulation and comparative analyses is provided to reveal the advantages and features of the proposed approach.

Probabilistic linguistic preference relation (PLPR) provides an effective and flexible tool with which preference degrees of decision-makers can be captured when they vacillatingly express linguistic preference values among several linguistic terms. Individual consistency and group consensus are two important research topics of PLPRs in group decision making (GDM). Considering the problems associated with these two topics, this study proposes a novel GDM framework with consistency-driven and consensus-driven optimization models based on a personalized normalization method for managing complete and incomplete PLPRs. First, existing limitations of the traditional normalization method for probabilistic linguistic term sets (PLTSs) managing ignorance information are specifically discussed. Given the potential valuable information hidden in PLTSs, a personalized normalization method is newly proposed through a two-stage decision-making process with a comprehensive fusion mechanism. Then, based on the proposed normalization method for PLTSs, consistency-driven optimization models that aim to minimize the overall adjustment amount of a PLPR are constructed to improve consistency. Moreover, the developed models are extended to improve consistency and estimate the missing values of an incomplete PLPR. Subsequently, a consensus-driven optimization model that aims to maximize group consensus by adjusting experts’ weights is constructed to support the consensus-reaching process. Finally, an illustrative example, followed by some comparative analyses is presented to demonstrate the application and advantages of the proposed approach.

Solid solution 0.94Na0.5Bi0.5TiO3–6BaTiO3 (NBT–6BT) is considered to be one kind of lead‐free piezoelectric materials with excellent electrical properties due to the existence of morphotropic phase boundary (MPB). However, its relatively lower depolarization temperature is a long‐standing bottleneck for the application of NBT‐based piezoelectric ceramics. In this work, the influence of thermal quenching on depolarization temperature and electrical properties of rare‐earth Ho‐doped NBT–6BT lead‐free ceramics was investigated. It was shown that the relative high piezoelectric performance, as well as an improvement of depolarization temperature (Td), can be realized by thermal quenching. The results showed that the quenching process induced high concentration of oxygen vacancy, giving rise to the change of octahedra mode and enhanced lattice distortion, which is benefit to the temperature stability of piezoelectric and ferroelectric properties. Furthermore, up‐conversion photoluminescence (PL) of Ho‐doped NBT–6BT could be effectively tuned by the introduction of oxygen vacancy, suggesting a promising potential in optical–electrical multifunctional devices.

Inter-satellite links (ISLs) can be employed in global navigation satellite systems (GNSSs) for space-based telemetry, telecommand and ranging, which reduces the requirement for a large number of ground stations (GSs). However, the polling time division duplex (PTDD) ranging hierarchy of the ISLs raises the topology design problem of the networks. To optimize the communication performance with the constraint of ranging for precise orbit determination in GNSSs, we model the ISLs network with finite state automation (FSA) and solve the optimization problem with integer linear programming (ILP). With the proposed method, for the first time, optimal delay and throughput are both achieved for data transmission between satellites and GSs with guaranteed ranging performance. Simulation results corroborate that, compared with two existing methods, the proposed scheme largely improves the communication performance, i.e., the average delay and the network throughput by 46.9% and 11%, respectively.

In high-altitude electromagnetic pulse (HEMP) field tests, coupling currents under a given illuminated electromagnetic field are important to the design of electronic systems and electromagnetic (EM) shielding. Compared to calculating the arithmetic average (AA) of the amplitude of coupling currents, reference field normalization (RFN) method is a data processing method of HEMP field tests studied in this article. In this method, a reference field is introduced and measured during each repeated illumination of the HEMP field test to minimize the impact of deviations of the illuminated EM field produced by a HEMP simulator. To evaluate the RFN method, uncertainty analysis is carried out. Then the uncertainty and relative error are calculated and compared between the RFN method and the AA method by the coupling currents data both from Monte Carlo method and real test. The results show that the RFN method has a better performance compared to the AA method both from the aspect of uncertainty and relative error.

Around the world, farming decision-making has been receiving increasing attention from the academic circles, while there is currently an important research gap regarding coastal farmers' farming decision-making. Natural disasters occur frequently in coastal zones. Farmers, as a rational agent, inevitably have heterogeneous risk preferences. However, few studies have distinguished between subjective and objective risk preferences, and have analyzed the influence of these differences on the final results. In this paper, the Shankou Town in the Hepu County, Beihai City, Guangxi Zhuang Autonomous Region, China was selected as a typical coastal zone research area. The aim of this study was to analyze subjective and objective risk preferences, build a multi-agent model, and simulate farmers' real farming decision-making. By providing targeted policy recommendations, we believe that our research can contribute to reducing land abandonment. In fact, a wrong perception of the risk preferences may lead to differences in the prediction of future land abandonment. In many cases, farmers do not understand the risk-taking behavior. Therefore, through this method, the severity of land abandonment can be predicted in advance. so that the government can take the necessary measures to prevent and control it, and raise the willingness of farmers for land reconversion.

This article introduces a bias controllable integrated optics electric field measurement system fabricated by LiNbO3 (LN) that can be used for the measurement of 10-kV/m subnanosecond rise time electromagnetic pulse (EMP). Combined with the structure of birefringence modulation (BRM) and the 1550-nm tunable laser, this probe has simple structure measures 1.5 cm $\times 2$ cm $\times4.5$ cm. It realized the set of bias to any value during $2\pi $ with less than 1-nm change of the wavelength of the tunable laser, despite the influence of the environment. Furthermore, an optimal bias automatic feedback controller based on Newton iteration algorithm is constructed to lock the bias at a fixed point. The statistical result (average ± standard deviation) of the bias under controlled is 90.4 ± 0.8°. Calibrated results show that it shows consistent response to the pulse with rise time of 200 ps, and the minimum and maximum measurement amplitude is 0.3 and 45 kV/m, respectively.

Accurately obtaining the temperature distribution of the medium in the shutdown pipe-line of waxy crude-oil has important guiding significance for making maintenance plan and restart plan. The phase transition process of waxy crude-oil involves complex problems such as natural-convection heat transfer, latent heat release, and difficulty in tracing liquid-solid interface. In this paper, the concept and significance of breaking point were proposed. Taking the breaking point and the freezing point as dividing point, a new zonal partition model was established based on the influence of phase change of crude-oil wax crystal on heat transfer mode, with the corresponding governing equations being established for different regions. With the proposed model, the effects of natural-convection on heat transfer, latent heat release, location change of condensate reservoir, heat transfer mechanism, and other key issues in the process of oil phase transition were analyzed.

The occurrences of gold as lattice-bound ionic Au+ and nanoparticulate Au0 inclusions, collectively termed “invisible gold”, in pyrite have long been recognized as a most important characteristic of Carlin-type gold deposits. Yet, till now, few studies have quantitatively resolved the two chemical states of Au, reflecting substantial challenges in the characterization of Carlin-type gold ores. In this work, quantitative XPS analysis of “invisible gold” was carried out for the first time, which revealed valuable results including the total Au concentration, percentages of Au+ and Au0, size of Au0 nanoparticles, and Au/As ratio at different depths of the pyrite surface. A simple acid etching approach, which effectively removed the signal-blocking outermost pyrite rim of low Au content and the signal-interfering Mg carbonates, was demonstrated to be the key to enhancing the Au signal in XPS. The ascending Au concentration (0.0017–0.24 at%) with increasing depth and the variation of Au0 fraction (31.2 to 59.8 at%) with relatively stable As concentration (∼2 at%) indicate heterogeneous distribution of Au chemical states in pyrite particles, while the small Au nanoparticle size (minimum 1–2 nm) confirms the challenge of microscopic observation of “invisible gold”. Unlike ion beam etching techniques potentially suffering from sample damages, the non-oxidative acid etching method used in our study is considered non-destructive and capable of obtaining chemical states with reasonable statistical significance. We believe that the new findings from this work will provide useful information to improve our understanding of the still puzzling ore-forming mechanisms and to boost the related metallurgical efficiencies. Furthermore, our methodology may also be applied to the characterization of poorer Au ores and even other geological samples.

New types of Ce-doped CexBi7-xTi4.5W0.5O21 (BTW-BIT-xCe) Aurivillius intergrowth ceramics with high Curie temperatures were synthesized to improve the piezoelectric performances as well as the conduction behaviour, and these ceramics exhibit great potential for high-temperature lead-free piezoelectric applications. The crystal structure, electrical properties and conduction behaviour of BTW-BIT-xCe samples were analysed thoroughly. The XRD patterns combined with Rietveld refinements of the patterns showed that the crystal structure transformed from orthorhombic structure towards pseudo-tetragonal structure with increasing CeO2 dopant, indicating that a higher symmetry was obtained. The dielectric properties of Ce-doped samples were improved, accompanied by a significant drop in the dielectric loss and a slight decreased Curie temperature (705 °C–683 °C). An enhanced piezoelectric constant d33 of 25.3 pC/N was obtained in BTW-BIT-0.12Ce, which may be attributed to a common decrease in the electrical conductivity and coercive field. Besides, a low electrical conductivity of 2 × 10-6 S/cm at 540 °C was achieved in the same component owing to a decreased concentration of the oxygen vacancies, which was verified by analyses on XPS spectra. The above results indicate that Ce-doped BTW-BIT samples have great development potential for high temperature piezoelectric applications.

In view of the worldwide serious health threat of type 2 diabetes mellitus (T2DM), natural sources of chemotherapies have been corroborated as the promising alternatives, with the excellent antidiabetic activities, bio-safety, and more cost-effective properties. However, their clinical application is somewhat limited, because of the poor solubility, instability in the gastrointestinal tract (GIT), low bioavailability, and so on. Nowadays, to develop nanoscaled systems has become a prominent strategy to improve the drug delivery of phytochemicals. In this review, we primarily summarized the intervention mechanisms of phytocompounds against T2DM and presented the recent advances in various nanosystems of antidiabetic phytocompounds. Selected nanosystems were grouped depending on their classification and structures, including polymeric NPs, lipid-based nanosystems, vesicular systems, inorganic nanocarriers, and so on. Based on this review, the state-of-the-art nanosystems for phytocompounds in T2DM treatment have been presented, suggesting the preponderance and potential of nanotechnologies.

Quality function deployment (QFD) is an effective customer-oriented technique for enhancing healthcare service quality. Implementing QFD, patient requirements (PRs) should be firstly identified and...

Shale oil is an unconventional oil resource with great potential. Oil saturation ([Formula: see text]) is an essential parameter for formation evaluation. However, due to the complexity of matrix mineral components and pore structure, Archie’s law cannot be used directly to calculate [Formula: see text] in shale oil reservoirs. We have developed a new saturation model for shale oil reservoirs. This model allows us to separate the organic from the inorganic pores, eliminate the background conductivity mainly caused by the borehole fluid or conductive minerals and determine the effective conductive porosity, which rules out nonconductive porosity, including isolated pores and the pore space affected by the fluid distribution. By analyzing the logging and core experimental data from the Qianjiang Sag, Jianghan Oilfield, we found that the T2 cutoff porosities of nuclear magnetic resonance logging are strongly related to the nonconductive porosities. After we determine the T2 cutoff value using the core experimental data, we can use it to obtain nonconductive porosity fraction in each depth point, which allows us to efficiently calculate [Formula: see text]. We calculate oil saturation values and use them to estimate the oil content. The results are coherent with the core experimental data, which indicates the efficiency of this model.

This paper presents the study of the fitting method for the sensitivity calibration data of a time-domain high-altitude electromagnetic pulse (HEMP) measuring system combined with the engineering practice. Due to the simple and practical requirements in engineering applications, this paper discussed and compared three different fitting methods and two different fitting models typically used in the HEMP measuring system: conversion coefficient averaging method, least square method, and relative least square method with direct proportion model and linear model. Uncertainty is used as the judgment of fitting performance in this paper. Both type A and type B uncertainties are analyzed. The statistical method is used in the analysis of type A uncertainty. Results of 50 different measuring systems with a different fitting method are observed and compared. And the standard deviation is used to represent the relative standard uncertainty of fitting. The GUM method with an ideal linear assumption of the sensitivity is used and the strict expressions of uncertainties are deduced in the analysis of type B uncertainty. The results show that the relative least square method is more suitable than the least square method in the fitting of HEMP measuring system calibration. The averaging method with direct proportion model is preferable considering the convenience and efficiency in practice. And the relative least square method with both the direct proportion model and linear model can be considered as well. The least square method with the linear model is not recommended in the application of time-domain HEMP measuring systems.

With the advent of the 5G era, the Internet of Things (IoT) will flourish in the future. Millions of IoT devices will be connected by 5G networks, which will bring great challenges to network management. Software-defined network (SDN) is a novel solution for managing a large number of IoT devices over the network. In order to solve the problems of secure data analysis in SDN-based IoT, a differentially private tensor computing model (DPTCM) is proposed in this article. Our approach utilizes tensor to model and analyze the SDN-based IoT big data, and an algorithm named differentially private tensor train decomposition (DPTTD) is proposed to achieve secure computing in SDN-based IoT. The algorithm can make full use of the flexible computing power of edge-cloud computing so as to realize collaborative computing between edges, cloud, and the third party. By separating the calculation process of the private data and nonprivate data, the algorithm implements the localized calculation and preservation of the original data which can protect the data security from the source. Meanwhile, we use the differential privacy technology to protect the privacy of data transmitted to the cloud. Finally, we prove that the algorithm satisfies $\varepsilon $ -differential privacy. In the experiments, we verify our model on two real-world data sets. The experimental results show that differential privacy has a little side effect on prediction results, and our model has good performance in data prediction.

In this work, BaBi8(Ti1-xTax)7O27 (x = 0, 0.005, 0.01, 0.015, 0.02 and 0.03) intergrowth bismuth layer-structured ferroelectric ceramics (BLSFs) were prepared by traditional solid reaction method, and Ta5+ was designed to replace Ti4+ to regulate crystal structure and improve electrical properties. The results show that Ta5+ as a donor increases an orthogonal distortion, while reducing the concentration of oxygen vacancies in the ceramics. The results show that the structural distortion increases with Ta doping due to the larger radius of the Ta ion compared to that of the Ti ion. At the same time, proper Ta5+ doping as a donor can effectively inhibit the formation of oxygen vacancies, which reduces high temperature leakage, and can cause a sharp reduction of grain size. However, excessive Ta5+ doping also results in a serious structural distortion, and consequently a serious deterioration of electrical properties. BaBi8(Ti0.995Ta0.005)7O27 shows an optimal piezoelectric performance with a piezoelectric constant d33 of 19 pC/N, which is twice as large as that of pure BaBi8Ti7O27 (~8 pC/N), and verifies its possibility as a potential candidate material for high temperature piezoelectric field.

SDN (Software Defined Network) has emerged as a revolutionary technology in network, a substantial amount of researches have been dedicated to security of SDNs to support their various applications. The paper firstly analyzes State-of-the-Art of SDN security from data perspectives. Then some typical network attack detection (NAD) methods are surveyed, including machine learning based methods and statistical methods. After that, a novel tensor based network attack detection method named tensor principal component analysis (TPCA) is proposed to detect attacks. After surveying the last data-driven SDN frameworks, a tensor based big data-driven SDN attack detection framework is proposed for SDN security. In the end, a case study is illustrated to verify the effectiveness of the proposed framework.

Background Digital health technologies can support primary care delivery, but clinical uptake in primary care is limited. This study explores enablers and barriers experienced by primary care providers when adopting new digital health technologies, using the example of the electronic Patient Reported Outcome (ePRO) tool; a mobile application and web portal designed to support goal-oriented care. To better understand implementation drivers and barriers primary care providers’ usage behaviours are compared to their perspectives on ePRO utility and fit to support care for patients with complex care needs. Methods This qualitative sub-analysis was part of a larger trial evaluating the use of the ePRO tool in primary care. Qualitative interviews were conducted with providers at the midpoint (i.e. 4.5–6 months after ePRO implementation) and end-point (i.e. 9–12 months after ePRO implementation) of the trial. Interviews explored providers’ experiences and perceptions of integrating the tool within their clinical practice. Interview data were analyzed using a hybrid thematic analysis and guided by the Technology Acceptance Model. Data from thirteen providers from three distinct primary care sites were included in the presented study. Results Three core themes were identified: (1) Perceived usefulness: perceptions of the tool’s alignment with providers’ typical approach to care, impact and value and fit with existing workflows influenced providers’ intention to use the tool and usage behaviour; (2) Behavioural intention: providers had a high or low behavioural intention, and for some, it changed over time; and (3) Improving usage behaviour: enabling external factors and enhancing the tool’s perceived ease of use may improve usage behaviour. Conclusions Multiple refinements/iterations of the ePRO tool (e.g. enhancing the tool’s alignment with provider workflows and functions) may be needed to enhance providers’ usage behaviour, perceived usefulness and behavioural intention. Enabling external factors, such as organizational and IT support, are also necessary to increase providers’ usage behaviour. Lessons from this study advance knowledge of technology implementation in primary care. Trial registration Clinicaltrials.gov Identified NCT02917954. Registered September 2016, https://www.clinicaltrials.gov/ct2/show/study/NCT02917954

The waxy crude oil is cooled and the waxy crystals form a grid structure after the shutdown, which leads to a very complicated heat transfer process. The degree of temperature drop of crude...

The steel-concrete (SC) or steel-concrete-steel (SCS) composite structures are widely used in large-scale structures like immersed tunnels, protection structures, etc., due to their superior performances in capacity, ductility, waterproofness, construction efficiency, etc. The steel plates in these structures are usually stiffened with ribs to increase the out-of-plane rigidity and to improve the local buckling performance. While there have been several applications, the buckling design of the composite stiffened plates, based on the methods for steel structures, is still immature and conservative. To deal with this problem, a selected series method (SSM) based the energy theory is proposed, which could both be utilized in composite stiffened plates and steel stiffened plates. The special series shape functions, which could efficiently and accurately represent the 3-dimentional spatial buckling deformation of the stiffened plates with multiple stiffeners, are selected. The explicit high-order solutions for the buckling stress of stiffened plates are derived. Furthermore, a finite element model (FEM) is established. Based on the FEM, a numerical database including most common design parameters is derived, and extensive numerical analyses are conducted to modify and verify the proposed SSM. It is found that, for steel structures, the SSM has a 10%–20% improvement in accuracy compared with the existing methods, and for composite structures, the SSM fills the blank in this area and has acceptable accuracy for design. Finally, from the above studies, the design suggestions are given and discussed.

Experts are assumed to be mutually independent and incomplete decision matrices are used, in traditional large-scale group decision-making (LSGDM). Social network analysis (SNA) methods are useful for managing LSGDM problems considering the social relationships among experts. This study develops a novel SNA-based decision framework for addressing LSGDM problems with incomplete interval type-2 fuzzy information. First, a community detection algorithm is designed to classify experts, and a trust propagation and aggregation mechanism is developed to obtained experts’ indirect trust values and weights based on the social trust network. Second, a multi-objective programming model integrated with trust relationships among experts is constructed to estimate the missing values in incomplete interval type-2 fuzzy decision matrices. The proposed estimation approach is robust and effectively estimates missing values while maintaining high discrimination levels. Subsequently, an SNA-based consensus-reaching model is designed for achieving a group consensus based on a twofold feedback adjustment mechanism, namely, adaptive judgment and weight feedback. Finally, an illustrative example is presented to demonstrate the applicability of the proposed approach. A simulation and comparison study is conducted to verify the efficiency and advantages of the SNA-based consensus-supporting framework for LSGDM.

The acoustic scattering is theoretically studied in this paper for three-dimensional spherical cloak composed of unideal pentamode material, for which small shear rigidity is always inevitable for a real designed microstructure. A theoretical formulation is developed to efficiently evaluate the cloaking performance. The generic scattering feature of the cloak and the effects of material imperfectness and inner cloak boundary constraints are systematically examined. The preferable constraint type and the critical imperfectness parameter of the material are identified for possible broadband invisibility. In addition, a very practical lining shell scheme is proposed to tune the constraint strength on the inner boundary. By combining the theoretical model with optimization algorithm, it is further proved that the cloak can be reduced by several piecewise-uniform layers and optimized to achieve excellent invisibility in targeted frequency bands. The study will provide valuable guidance for the future microstructural design of cloaks.

Based on two quasi-static experiments of steel tube confined reinforced concrete columns (STRC) under pure torsion load, detailed finite element (FE) simulation and theoretical derivation of the corresponding calculation methods were conducted in this paper. FE models of STRC specimens under pure torsion were established using the finite element software ABAQUS, the feasibility of which was then validated against the testing results in terms of both ultimate torsional capacity and failure modes. Comprehensive parametric analysis was presented, including the yield strength of steel tube, the thickness of steel tube, the dimension of cross-section, the strength of concrete, the yield strength of longitudinal reinforcement, the ratio of longitudinal reinforcement, the yield strength and the ratio of stirrup, to investigate the influence on the torsional capacity of STRC columns with important structural factors. It can be found from the parametric analysis results that, the thickness of steel tube, the dimension of cross-section and the ratio of longitudinal reinforcement are the most important parameters for the torsional capacity of STRC. Based on the results parametric analysis, an accurate and simplified calculation method for the ultimate torsional capacity of STRC columns under pure torsion was proposed.

Nowadays, reinforced concrete core wall–steel frame hybrid structural systems are widely used in high-rise buildings. In this type of structural system, the steel beam–concrete wall (SBCW) joints bear significant cyclic tensile and compressive loads under earthquake motions. Considering that most of the compressive loads are transferred to the slabs rather than the joint core, the pulling resistant capacity of the joints plays a very important role in the seismic behaviour of the entire structure when neglecting the tensile strength contribution of concrete slabs. In this study, the pullout behaviour of a new form of SBCW pinned joints with T-shaped steel connectors was tested, and the load–displacement curves, failure modes, as well as stress and strain development of the specimens were analyzed. Two failure modes were observed in the experiments: one is the breakout failure mode characterized by the pullout of the concrete pyramid with lower strength and stiffness, and the other is the web yield failure mode characterized by the yielding of the web plate of the T-shaped steel connector with higher strength and stiffness. The failure mode that was experienced mainly depended on the embedded depth of the T-shaped steel connector. Then, an analytical model for predicting the pulling resistant capacity of the joint was proposed. In this model, the calculation method corresponding to the breakout failure mode, which is based on the principle of virtual work, can assess the respective contributions of concrete, shear studs and stirrups to the pulling resistance capacity of the joint, and the calculation method corresponding to the web yield failure mode is simplified by calculating the yield strength of the web plate of the T-shaped steel connector. Finally, the proposed model was verified by experimental results.

This study aims to develop an integrated approach for solving probabilistic linguistic multi-criteria decision-making (MCDM) problems. This study first reveals the limitations in the existing metho...

For the purpose of expanding the application scope of HEA coating manufactured on the surface modification of materials, in this work, the Al1.5CrFeNiTi0.5 and Al1.5CrFeNiTi0.5W0.5 HEA coatings were successfully manufactured using laser cladding method on SUS304. The microstructures and wear resistance of coatings are researched systematically. It is found that the W0 and W0.5 HEA coatings all exhibit the dendritic structure, which are constituted by BCC phases and Laves phases. With W element addition, the phase structures of W0.5 coating remain unchanged. W is dissolved in both two phases, but the solid solubility in Laves phase is higher compared to that in BCC phase. W0.5 coating with the highest microhardness of 848.34 HV, and the W0 coating with the microhardness of 811.45 HV, both of whose microhardness are four times more than that of SUS304 substrate. Among all samples, the W0.5 coating shows the optimal wear performance because of its larger content of hard second phase ( Laves phase).

Composite floor systems rely on shear connection, commonly using headed steel stud anchors, to ensure that the steel beam and concrete slab work together as a unit, but also to transfer load from the diaphragm to the lateral force-resisting system. Under cyclic loading, slip and degradation can occur at the shear connection, affecting the seismic response of the floor and building systems. For composite floors using anchors welded through profiled steel deck, the slip and degradation may be more severe than floors with solid concrete slabs. In this paper, a series of push-out tests were conducted to study the monotonic and cyclic behavior of headed steel stud anchors in composite beams with profiled steel deck. The parameters that were investigated include the profile type, steel deck direction, and loading conditions. The results show both the monotonic and cyclic response are affected by the shape of the profile with newer, closed profiles, performing better than others tested. Additionally, comparisons are made between the test results and several design codes.

Precast beam-column joints are key components of precast reinforced concrete (RC) frame structures. The complex reinforcement details in the joint zone due to high seismic demand have made the prefabrication and construction process in regions with high earthquake intensity difficult to perform. As a type of high-performance fiber-reinforced cementitious composites (HPFRCCs), low-shrinkage engineered cementitious composite (LSECC) exhibits stable strain hardening and multiple cracking properties with a dry shrinkage even lower than that of normal concrete. A partial substitution of concrete with LSECC can significantly improve the seismic performance and damage tolerance of beam-column joints and help simplify the reinforcement details in the joint zone. This paper proposes a novel precast LSECC/RC composite beam-column joint using U-shaped precast LSECC beam shells. Five interior beam-column sub-assemblages were tested under cyclic loading, including one monolithic and four precast specimens. Parameters including lap splice length, transverse and longitudinal reinforcement ratios were studied. The proposed construction process was proven to be both easy and fast. The performance of the precast joints were evaluated in terms of the ultimate capacity, deformation, energy dissipation, shear distortion and strength of the joint core. The test results showed that the proposed joints could effectively simplify the joint reinforcement details while maintaining the required seismic performance. The diagonal cracks in the joint zone without transverse reinforcement were well controlled. A few stirrups in the joint zone could reduce the shear deformation and improve the energy dissipation capacity. The shear strength of the LSECC joints without any transverse reinforcement were found to be similar to the nominal shear strength of well-confined normal concrete joints suggested by ACI 318-14.

Global warming is one of the issues of great concern in the world. The large-scale use of fossil fuels has led to the continuous increase in carbon emissions, resulting in global energy shortages and environmental pollution. Reasonable and strict environmental regulation promotes technological innovation by enterprises to achieve a win-win situation between the economy and environment, which is the core idea of the Porter hypothesis. The choice of China, as the world's largest energy consumer and carbon emitter, is not only related to the country's own mode of economic growth but also determines the development of the world's low-carbon economy. We used the panel data from 2000 to 2016 of 30 provincial-level administrative regions in China and adopted the Propensity Score Matching–Difference in Differences method to test the impact of China's carbon trading pilot system on the transformation of a low-carbon economy. The empirical results show that under the constraints of the established resources and environment, there is a positive relationship to some extent between China's carbon trading system and low-carbon economic transformation. This relationship can realize the win-win situation of environmental and economic benefits as advocated by the Porter hypothesis and further verify the applicability of the Porter hypothesis.

The simulation of various rock properties based on three-dimensional digital cores plays an increasingly important role in oil and gas exploration and development. The accuracy of 3D digital core reconstruction is important for determining rock properties. In this paper, existing 3D digital core-reconstruction methods are divided into two categories: 3D digital cores based on physical experiments and 3D digital core stochastic reconstructions based on two-dimensional (2D) slices. Additionally, 2D slice-based digital core stochastic reconstruction techniques are classified into four types: a stochastic reconstruction method based on 2D slice mathematical-feature statistical constraints, a stochastic reconstruction method based on statistical constraints that are related to 2D slice morphological characteristics, a physics process-based stochastic reconstruction method, and a hybrid stochastic reconstruction method. The progress related to these various stochastic reconstruction methods, the characteristics of constructed 3D digital cores, and the potential of these methods are analysed and discussed in detail. Finally, reasonable prospects are presented based on the current state of this research area. Currently, studies on digital core reconstruction, especially for the 3D digital core stochastic reconstruction method based on 2D slices, are still very rough, and much room for improvement remains. In particular, we emphasize the importance of evaluating functions, multiscale 3D digital cores, multicomponent 3D digital cores, and disciplinary intersection methods in the 3D construction of digital cores. These four directions should provide focus, alongside challenges, for this research area in the future. This review provides important insights into 3D digital core reconstruction.

The performance of welded reinforcement grids (WRGs) made of smooth rebar, as shear reinforcement for RC beams, was investigated through monotonic and cyclic loading tests, in comparison to conventional bent smooth and deformed stirrups. The influence of the two main differences of the WRG to the conventional bent stirrups, i.e. the low bond stress and the limited strength of weld, on the performance of specimens was analyzed, based on the test observations, load-displacement curves and strain in the shear reinforcement. Test results showed that the WRG-reinforced beams had similar behavior and failure modes to the specimens reinforced with bent smooth stirrups, in both monotonic and cyclic loading tests. However, under cyclic loads, the shear capacity of beams was negatively influenced by the insufficient bond stress between smooth rebar and concrete. To overcome this deficiency, a new type of WRG, with an additional horizontal rebar branch to provide mechanical anchorage, was proposed and its effectiveness was experimentally examined. Finally, modifications were made to an existing formula to predict the contribution of the WRG to the shear capacity, based on the actual strength of weld covered by the concrete, obtained using the an experimental method proposed in this study.

Land speculation can increase idle or inefficient land use, thus causing a number of problems, which many countries around the world address with reasonable administrative intervention. According to China’s “Disposal Measures for Idle Land”, the land development time is limited to two years. If this time is exceeded, the government will restore the land use rights to the state without compensation for the developer. 1 Using the perspective of American call options, this study combines the Optimal Stopping Time and the Martingale Theory in Real Option Pricing Theory. Both land and house price data from 2010 to 2016 have been integrated for Beijing, Wuhan, and Nanning in China. Furthermore, an empirical analysis of the optimal stopping time for land development has been conducted in these three cities to study whether the imposed limit on land development time reduces land prices. The results show that the optimal stop-time fluctuation of land development is large due to factors such as house price and land price volatility as well as social rates of return. In addition, the optimal stopping time for land development differs in specific regions and periods of different levels of economic development. Limiting the land development time will sometimes lower the land price and exert a stronger impact on low-price areas. Although limiting the land development time can help certain areas to reduce idle land, the suppression of land speculation and the stabilization of land prices are not obvious. This strategy will, however, obstruct the development of real estate economy. The conclusions of this study will help the government to formulate a sound policy, control land speculation, improve land use efficiency, and reduce the occurrence of land waste.

Industrial structure optimization model can effectively support sustainable economic development. This study firstly summarized four types existing industrial structure optimization models. Based on reviews of these models, this study proposed an inexact chance-constrained fuzzy programming model for industrial structure optimization. This model has three features: (1) the model considers many social economic and ecological environment factors which can provide various of sustainable development strategies; (2) the model considers three uncertainties which are discrete intervals, fuzzy sets and probabilities; therefore, the model can reflect uncertain features of the industrial structure system without excessive hypothesis; (3) the model can effectively reflect the quantitive relationship between economic benefit increasing and ecological environmental cost retardant in the industrial system. The proposed model is applied to industrial structure optimization of Hefeng County, Hubei Province, China. The results provided a series of desired industrial structure patterns and environmental emission scenarios under uncertainty which could help government and industry decision makers in the study area to formulate appropriate industrial policies which could balance the social economic development and ecological environment protection. The modelling results can support quantity and deeply analysis of industrial structure patterns and trade-off between economical development and ecological environment protection.

Er3+-doped SrBi4Ti4O15-Bi4Ti3O12 (SBT-BIT-xEr3+, x = 0.00, 0.05, 0.10, 0.15 and 0.20) inter-growth ceramics were synthesized by the solid-state reaction method. Structural, electrical and up-conversion properties of SBT-BIT-xEr3+ were investigated. All samples showed a single phase of the orthorhombic structure. Raman spectroscopy indicated that the Er3+ substitution for Bi3+ at A sites of the pseudo-perovskite layer increases the lattice distortion of SBT-BIT-xEr3+ ceramics. The substitution of Bi3+ by Er3+ leads to a decrease of dielectric loss tanδ and an increase of conductivity activation energy. Piezoelectric constant d33 was slightly improved, but dielectric constant was decreased with the Er3 + doping. The SBT-BIT-xEr3+ ceramic with x = 0.15 exhibits the optimized electrical behavior (d33 ~17 pC/N, tanδ ~0.83%). Moreover, two bright green (532 and 548 nm) and one red (670 nm) emission bands were observed under the 980 nm excitation. Optimized emission intensity was also obtained when x = 0.15 for the SBT-BIT-xEr3+ ceramic. Therefore, this kind of ceramics ought to be promising candidates for multifunctional optoelectronic applications.

Mining and analysis of time series data (TSD) have drawn a great concern, especially in the TSD clustering, classification, and forecast. In the industrial field, e.g., the work condition monitoring and the environmental safety, it is crucial to follow the trend of the corresponding TSD for a safety forecast, and few studies have been devoted to such a trend following. Motivated by this, we propose a trend following the strategy of TSD by using a long short-term memory (LSTM) network for safety forecast, in which the training method aggregates the particle swarm optimization (PSO) algorithm with gradient descent (GD) to obtain more competitive model parameters. Three kinds of trend representations of TSD are first defined based on the corresponding research in stock option. Then, the LSTM optimized with the PSO-GD is developed to perform the trend following. From the viewpoint of safety forecast, the trends varied in different time length are further predicted and analyzed. The superiority of the proposed algorithm is experimentally demonstrated by applying it to the electromagnetic radiation intensity TSD sampled from an actual coal mine and PM2.5 in UCI repository.

The performance of ultra-high performance concrete (UHPC)-steel composite beams is dependent on the connection between the UHPC and steel. In this study, bending tests were conducted on UHPC-steel composite beams with different interfaces: UHPC directly cast on different plate textures, bonding using an epoxy-based adhesive, and traditional headed studs. The connection between the UHPC and the plates was extremely weak, but the adhesive performed well, failing after the steel beam yielded. Three-dimensional finite element models of the adhesively bonded beams were then established using ABAQUS and agreed well with the test results, successfully predicting the failure of the adhesive bonds.

As a convex surrogate of tensor multi rank, recently the tensor nuclear norm (TNN) obtains promising results in the tensor completion. However, only considering the low-tubal-rank prior is not enough for recovering the target tensor, especially when the ratio of available elements is extremely low. To address this problem, we suggest a novel low-rank tensor completion model by exploiting both low-tubal-rankness and smoothness. Especially, motivated by the capability of framelet preserving details, we characterize the spatial smoothness by framelet regularization and the smoothness of the third mode by total variation (TV) regularization. The resulting convex optimization problem is efficiently tackled by a carefully designed alternating direction method of multipliers (ADMM) algorithm. Extensive numerical results including color images, videos, and fluorescence microscope images validate the superiority of our method over the competing methods.

This paper analytically formulates the ultimate capacities for various failure modes of composite beams consisting of a modular fiber reinforced polymer (FRP) web-flange sandwich deck supported by a steel girder. Pultruded FRP box sections are incorporated between two flat panels to form the web-flange sandwich deck, in which the pultrusion direction of box sections can be either parallel or perpendicular to the span direction. Such a deck can then be assembled via adhesive bonding or blind bolt connections to a supporting steel girder to form a composite beam system. On the basis of theoretical analysis of critical sections for such composite beams at ultimate states, potential failure modes are identified, including flexural failure of the steel girder yielding in tension and GFRP deck failure in compression, vertical shear failure, and horizontal shear failure at adhesive bonding at bolted connections and at webs of FRP box sections. For each failure mode, the corresponding ultimate capacity is analytically formulated; thereby, the critical failure mode and ultimate load capacity can be determined. The developed ultimate limit design approaches are validated by experimental results from the literature for such FRP-steel composite beams.

Precast reinforced concrete (RC) frame structures in areas with high seismicity typically suffer from extremely complicated reinforcement details in the joint zone, thereby leading to significant construction difficulties. Engineered cementitious composites (ECC) is a new type of cement-based materials with tension strain-hardening, multi-cracking and ultra-ductility that can be adopted in the joint zone to simplify the rebar layout and enhance seismic performance. The study proposes a novel precast concrete beam-column connection using cast-in-situ low-shrinkage ECC (LSECC). Three beam specimens were first tested to preliminarily demonstrate the applicability and advantage of the joint. Meanwhile, proper reinforcement details were proposed to prevent interface damage. Then seven large-scale beam-column assemblages were cyclically loaded to examine the seismic performance of the proposed joint and to reveal the influences of quantities of stirrups in the joint zone, rebar diameter in the beam, anchorage length of the bottom rebar and axial load. The cracking pattern, failure mode, hysteretic curves, ductility and dissipated energy, as well as the deformation and strength in the joint zone were analysed in detail. The results indicated that the cast-in-situ LSECC was very suitable for the precast beam-column joint. The LSECC joint with only half of the confining reinforcement in monolithic RC joint exhibited better hysteretic performance with enhanced energy dissipation capacity, improved ductility and less damage. Similar results were obtained for the LSECC precast joint without any stirrups and increased axial load on the column. The other joints without any stirrups in the joint zone showed almost equivalent seismic performance as the monolithic RC joint, despite the slight pinching of hysteretic curves and decrease of dissipated energy after 3%-4% beam rotation which was caused by the slip of top beam reinforcement. Therefore, the proposed joint provides a new option for the design and construction of precast RC frames in high seismic region.

The sustainability challenge is increasingly driving the adoption of supercritical water gasification (SCWG) technology to ensure the elimination and recovery of pollution produced by sewage sludge treatment (SST). Risk evaluation by failure mode and effects analysis (FMEA) plays a crucial role in guaranteeing the reliability and safety of SCWG systems. However, some limitations in existing FMEA methods need to be ameliorated. Multiple risk factors are involved in prioritizing risk levels for failure modes in SCWG systems, it is essential a multiple criteria decision making (MCDM) process, in which overall assessments of failure modes should be provided according to their performances from several points during a system operation period. Due to differences in knowledge backgrounds and experiences, FMEA team members prefer to utilize multi-granular linguistic term sets to express their assessments of system risk. A hybrid risk evaluation model by FMEA is exploited with multi-granular linguistic distribution assessments to suit practical case. Best-worst and maximizing derivation methods are adopted to determine subjective and objective combined weights for distinguishing the importance of risk factors. Complex proportional assessment method is used to prioritize failure modes for explicitly and effectively reflecting the risk level of each failure mode. The proposed model is applied in a practical case of an SCWG system used in SST. Results derived from comparative and sensitivity analyses fully demonstrate the reliability and validity of the model.

Cracking of the reinforced concrete (RC) slab is a critical problem for a composite beam subjected to a hogging moment, which hinders its application to indeterminate composite structural systems. An efficient numerical method based on the fiber beam-column model is developed for predicting the full-process nonlinear crack width development of composite beams. Several significant modeling issues involving the modeling strategies, selection of material constitutive laws, consideration of shrinkage effect, and determination of average crack spacing are discussed in detail. Rational modeling parameters are recommended and validated by several previous experiments: (i) the slight mesh-dependency can be neglected, and the midpoint integration rule with 6 and 4 uniformly distributed fibers for the slab concrete and the steel beam web, respectively, can give results with sufficient accuracy; (ii) the crack width–load curve obtained through FE analysis should be modified to rationally consider the shrinkage effect of the slab concrete with the initial shrinkage strain of about 300 μe; (iii) it is rational to select the value of the average crack spacing as the transverse reinforcement spacing of the RC slab; and (iv) the constitutive laws of the tensile slab concrete and reinforcement have minor influence on the global crack width–load response, especially in the stage after the stabilization of the cracking distances. The selected smeared material constitutive laws are recommended to give a smooth and rational curve for the stage before stabilized cracking.

This study focuses on consensus-reaching in social network group decision-making. Using Archimedean t-norms and t-conorms as the basis, this study introduces a family of interval-valued dual trust propagation (IVDTP) operators. A perfect knowledge degree-induced ordered weighted averaging (PKD-IOWA) aggregation operator is also put forward for obtaining the overall trust and distrust values. The proposed PKD-IOWA aggregation operator makes full use of the knowledge in each trust path, which can effectively overcome the limitations of existing trust aggregation operators. The weights of the experts can then be derived by combining the IVDTP operators and the PKD-IOWA aggregation operator. Three levels of consensus indices are defined to identify the incompatible experts in a group. A two-fold feedback mechanism comprising a judgment feedback mechanism (JFM) and a weight feedback mechanism (WFM), is designed to reach consensus. In each round of this interaction model, the most incompatible expert is advised to modify his/her judgments on the basis of the JFM. If the expert rejects the suggestion, then his/her weight will be reduced according to the WFM, which can act as an incentive or penalty to force him/her to accept the judgment feedback suggestion. Two illustrative examples are used to validate the feasibility and effectiveness of the proposed approach, followed by comparative analysis and discussion.

Background Biological composite scaffolds are increasingly being used in abdominal wall reconstruction but still have certain shortcomings. The present study describes here a novel three-dimensional (3D) scaffold fabricated by combining 3D printing (3DP) and electrospinning (ESP). Methods Biological composite scaffolds are composed of integrated 3DP interconnected macrofiber and random ESP microfiber networks. The 3DP scaffold retains intact 3D architecture and mechanical properties, while the ESP network serves as a cell entrapment system at the extracellular matrix (ECM) scale. Biological composite scaffolds are implanted in a defective rat abdominal wall to detect if it could induce early vascularization and reconstruction of the tissue defect. Results SEM analysis reveals a pore diameter of 424.47 ± 58.49 μm and a porosity of 70.46 ± 2.48% for biological composite scaffolds. In the in vitro test of cell proliferation, biological composite scaffolds do not affect rat dermal fibroblast proliferation in a time- and dose-dependent manner. The animal experiments show tissue remodeling and early angiogenesis as compared to 3DP scaffolds. Conclusions Our experiment prepares a biological scaffold with both a macro- and microscale structure by ESP and 3DP technology. Thus, the integration of 3DP and ESP techniques provides a new set of smart scaffolds for abdominal wall defect and hernia repair.

This paper contrasts and analyzes the image enhancement processing algorithm, median filtering and histogram equalization in the face recognition preprocessing process. The advantages and use methods of the OpenCV machine vision library are analyzed. The analyzed algorithm is implemented in the development environment of VC ++ 6.0 and MATLAB, and experiments are conducted on the ORL face library. The experimental results show that the algorithm used in this paper has obvious effect on processing face samples, has strong pertinence, and is suitable for preprocessing face images, and the OpenCV machine vision library can be used as a development tool for face recognition systems.

This paper develops a novel multi-criteria group decision-making method for resolving single-valued neutrosophic group decision-making problems with unknown weight information. Firstly, considering the different knowledge backgrounds of decision-makers (DMs), two distance-based methods are developed to obtain the weights of DMs and criteria. One of these methods focuses on the closeness between the decision matrix given by an individual DM and that of the group judgment, and the proximity between the decision matrix given by an individual DM and the matrices given by all the other DMs to determine the weights of DMs with respect to each criterion. The other method extends the maximizing deviation method to objectively obtain the weights of criteria. Secondly, an extended ELECTRE (ELimination Et Choix Traduisant la REalite) II is investigated to effectively circumvent the issue that criteria cannot compensate for each other. In this method, three levels of concordance and discordance sets are constructed to fully denote the underlying preference information and specify the outranking degrees of alternatives. Finally, two illustrative examples are presented to demonstrate the feasibility of the proposed approach, followed by a sensitivity analysis and a comparative analysis to test its robustness and effectiveness.

Carbon fiber/ceramic composite demonstrates excellent electro-thermal performance that can be applied in various heating applications. However high temperature ceramization inevitably causes oxidation of carbon fiber and negatively influences its electro-thermal property. Herein, a graphene coated carbon fiber/ceramic composite via one-step firing with rapid and stable temperature responsiveness is proposed. Crystal structure, morphological feature, electrical property and electrothermal behavior of the modified carbon fibers and carbon fiber/ceramic composite were investigated. The results showed effectively protective effect of coating and sintering of carbon fiber under N2 environment, resulting in greatly improved electro-thermal and mechanical properties. The composite based on 24 k carbon fibers and 1 cm thickness ceramic sintering reached about 65 °C at 6 V in only 10 min and the cooling process lasted 30 min from 82 °C to room temperature, presenting highly responsive heating and good temperature storage performance. The tensile strength and elongation at break of the single graphene coated carbon fiber increased 12% and 200%. The great electro-thermal features and strong mechanical properties of the modified carbon fibers make the carbon fiber/ceramic composite a good candidate for in-door temperature control and out-door deicing applications.

Polycrystalline (Ba0.85Ca0.15)(Zr0.10Ti0.90)O3–xLiTaO3 ceramics were designed and synthesized using a solid-state reaction to improve both the Curie temperature and the electrical properties of (Ba0.85Ca0.15)(Zr0.10Ti0.90)O3 lead-free piezoelectric ceramics. The effect that the addition of LiTaO3 has on the structure and electrical properties of BCZT ceramics was studied systemically. The results show that the Curie temperature and the piezoelectric properties of BCZT can be substantially enhanced by adding LiTaO3. The Curie temperature increased from 93 °C to 102 °C after adding LT of 0.3 mol.%. X-ray diffraction and Raman spectral analysis of the ceramics reveal the coexistence of orthorhombic (O) and tetragonal (T) phases. This coexistence of O and T phases at room temperature helps improve the ferroelectric and piezoelectric properties. The ceramic with x = 0.3 mol.% exhibits the highest values for d33 = 433 pC/N, d 33 * = 858 pm/V (at 1 kV/mm) and kp = 44.6%. Furthermore, giant electrostrictive coefficients (Q33 ≈ 0.040–0.050 m4/C2) were also obtained for these LT-doped BCZT ceramics. These properties confirm that BCZT-xLT is a promising candidate system for lead-free piezoelectric ceramic materials.

An appropriate greenhouse gas (GHG) emissions’ institution largely affects long-term development of cement corporates. The primary objective of this paper is to investigate a scientific method for selecting an optimal institution for a cement corporate. The paper mainly makes the following contributions to effectively resolving this selection problem. Given the capacity of picture 2-tuple linguistic sets (P2TLSs) in depicting voting information, they are used as evaluation representation in this case. Another contribution is that this paper newly proposes a prospect theory-based score function to rank picture 2-tuple linguistic numbers (P2TLNs). The proposed score function effectively overcomes the limitations in the existing score function by considering the voting potential of those decision-makers (DMs) who hold “abstain” opinion. Meanwhile, this proposed score function also adequately considers the rational-bounded behavior of DMs, thereby making the evaluation more approximate to the reality. Furthermore, this paper investigates a hybrid outranking method to select institution in the context of P2TLSs. It takes different types of preference functions and the Elimination and Choice Translating Reality (ELECTRE) method into account simultaneously. Compared with other similar type methods, this hybrid method can flexibly choose criteria type and provide specific values to represent quantitative dominance relation rather than qualitative judgment. Finally, an illustrative example and comparative analyses are provided to certify the availability and reliability of the proposed method.