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Acute kidney injury (AKI) is a frequently occurring severe disease with high mortality. Cystatin C (Cys-C), as a biomarker of early kidney failure, can be used to detect and prevent acute renal injury. In this paper, a biosensor based on a silicon nanowire field-effect transistor (SiNW FET) was studied for the quantitative detection of Cys-C. Based on the spacer image transfer (SIT) processes and channel doping optimization for higher sensitivity, a wafer-scale, highly controllable SiNW FET was designed and fabricated with a 13.5 nm SiNW. In order to improve the specificity, Cys-C antibodies were modified on the oxide layer of the SiNW surface by oxygen plasma treatment and silanization. Furthermore, a polydimethylsiloxane (PDMS) microchannel was involved in improving the effectiveness and stability of detection. The experimental results show that the SiNW FET sensors realize the lower limit of detection (LOD) of 0.25 ag/mL and have a good linear correlation in the range of Cys-C concentration from 1 ag/mL to 10 pg/mL, exhibiting its great potential in the future real-time application.

Improvement of channel mobility is required to improve the performance of the inversion channel MOSFETs using diamond. The previous studies have suggested that high interface defect density (Dit) at the Al2O3/diamond (111) interface has a significant impact on the carrier transport property on a channel region. To investigate the physical origins of the high Dit, especially from microscopic point of view, here we investigate Al2O3/p-type diamond (111) interfaces using scanning nonlinear dielectric microscopy (SNDM). We find the high spatial fluctuations of Al2O3/hydroxyl (OH)-terminated diamond (111) interface properties and their difference by the flatness of the diamond surface.

With the intensification of conflicts between different ecosystem services, how to achieve a win-win situation between socio-economic development and ecological protection is an important issue that needs to be addressed nowadays. In particular, how to better quantify and assess the intensity of ecosystem service trade-offs and their relative benefits, and to identify the influencing factors are issues that need to be studied in depth. Based on the INVEST model, this paper analyzed the evolution of spatial and temporal patterns of ecosystem services such as Carbon Storage (CS), Food Production (FP), Habitat Quality (HQ), and Water Yield (WY) in the Shandong Yellow River Basin (SYRB) in 2000, 2010 and 2020. Next, we quantitatively measured the trade-off intensity and revealed the key influencing factors of the trade-off intensity evolution using automatic linear models, root mean square deviation, and geographically weighted regressions. Subsequently, we further analyzed the impact of the correlation between environmental and socio-economic factors on the trade-off intensity of ecosystem services. The results indicated that the temporal and spatial changes of the four main ecosystem services in SYRB area were inconsistent. WY showed a fluctuating trend, with a large interannual gap. CS and FP are on the rise, while HQ is on the decline. Spatially, WY and HQ showed a decreasing distribution from the center to the periphery, while FP and CS showed a decreasing distribution from the southwest to the northeast. The location characteristics of SYRB’s four ecosystem services and their trade-offs were obvious. FP had absolute location advantage in ecosystem service trade-offs. Most of the four ecosystem services showed significant trade-offs, and the trade-off intensity had significant spatial heterogeneity, but the trade-off between FP and CS was relatively weak. At the same time, there were also differences in the trends of trade-off intensities. Counties with low trade-off intensity were mostly located in mountainous areas; these areas are less disturbed by human activities, and most of them are areas without prominent services. Counties with high trade-off intensities were mostly concentrated in areas with relatively developed agriculture; these areas are more disturbed by human activities and are mostly prominent in FP. The trade-off intensity of ecosystem services in SYRB was affected by several factors together, and there were difference characteristics in the degree and direction of influence of each factor. Moreover, these influencing factors have gradually changed over 20 years. In terms of the spatial distribution at the county scale, the influence areas of the dominant drivers of different trade-off types varied greatly, among which the areas with NDVI, CON, and PRE as the dominant factors were the largest. In the future, in effectively balancing regional economic development and ecological environmental protection, quantifiable correspondence strategies should be developed from the administrative perspective of counties and regions based on comprehensive consideration of the locational advantages of each ecosystem service and changes in trade-offs.

Accumulated hard tissue debris (AHTD) is an inevitable by-product during endodontic treatment and is difficult to remove completely using traditional syringe and needle irrigation (SNI). Adjunctive irrigation is proposed to assist the clean-up of AHTD. This systematic review and meta-analysis aimed to evaluate the AHTD removal efficacy of different root canal irrigation devices using micro-computed tomography (Micro-CT). A literature search was carried out within the main scientific databases until 20 June 2022. All results were screened with detailed eligibility criteria. Eleven studies were included for analysis. SNI, passive ultrasonic irrigation (PUI), negative pressure systems, sonically activated irrigation (SAI), mechanical-activated system and laser-activated irrigation (LAI) were assessed. PUI is superior to SNI for debris removal and LAI has better AHTD removal performance than PUI. The negative pressure system and mechanical-activated system were proved to be less effective. Registration: PROSPERO (CRD42021273892).

This article reviews the state of the art in inversion-type p-channel diamond MOSFETs. We successfully developed the world’s first inversion-channel homoepitaxial and heteroepitaxial diamond MOSFETs. We investigated the dependence of phosphorus concentration (NP) of the n-type body on field-effect mobility (μFE) and interface state density (Dit) for the inversion channel homoepitaxial diamond MOSFETs. With regard to the electrical properties of both the homoepitaxial and heteroepitaxial diamond MOSFETs, they suffer from low μFE and one main reason is high Dit. To improve the interface quality, we proposed a novel technique to form OH-termination by using H-diamond followed by wet annealing, instead of the previous OH-termination formed on O-diamond. We made precise interface characterization for diamond MOS capacitors by using the high-low C–V method and the conductance method, providing further insights into the trap properties at Al2O3/diamond interface, which would be beneficial for performance enhancement of the inversion-type p-channel diamond MOSFETs. Graphic abstract

This paper presents an efficient polynomial chaos expansion approach for structural uncertainty analysis in conjunction with the multiplicative dimensional reduction method. The development of a standard polynomial chaos expansion model needs to evaluate a large number of multivariate integrals for the expansion coefficient. The utility of the multiplicative dimensional reduction approach is able to approximate the multivariate integral as the product of univariate and bivariate expectations. Together with the standard Gauss-quadrature scheme for accurate low-variate integration results, an effective polynomial chaos expansion model is proposed to mimic the true performance function for structural uncertainty analysis. Since only dimensionally reduced univariate and bivariate component functions are involved, the proposed algorithm is able to overcome the curse of dimensionality problem in the ordinary polynomial chaos expansion procedure. Engineering applications of the proposed approach are demonstrated by several structural reliability and reliability-based design optimization problems in the literature. Compared to benchmark results provided by the brutal force Monte Carlo simulation, the high accuracy and efficiency of the multiplicative dimensional reduction–based polynomial chaos expansion algorithm have justified its potential applications for various structural uncertainty problems.

We successfully fabricated the inversion-type p-channel metal–oxide–semiconductor field-effect transistor (MOSFET) on heteroepitaxially grown free-standing diamond using silicon-based substrates. The drain current–drain voltage (Ids–Vds) and drain current–gate voltage (Ids–Vgs) characteristics were examined. The maximum drain current density and the peak field effect mobility (μFE) were around 0.35 mA/mm and 2.7 cm2 V−1s−1, which were lower than our reported results of the homoepitaxial diamond MOSFETs fabricated on high-pressure, high-temperature (HPHT) substrates. The interface state density (Dit) extracted from the subthreshold region was around 5.5 × 1012 cm−2eV−1, comparable to our reported results of the homoepitaxial diamond MOSFET. To further examine the reason for the low μFE, atomic force microscopy (AFM) measurements were performed for the n-type body of the heteroepitaxial diamond MOSFET, and we found that the surface roughness was much larger than our reported ones of the homoepitaxial diamond MOSFET. It can be deduced that the surface roughness would be one main limiting factor for the field effect mobility of the heteroepitaxial diamond MOSFET. The imperfect diamond heteroepitaxy would also degrade the field effect mobility. This work explores the potential of the inversion-type p-channel heteroepitaxial diamond MOSFETs, which would facilitate the practical application of diamond power devices.

The paper presents a hybrid active-learning approach for structural reliability analysis via adaptive Kriging surrogate models. The quasi first-order reliability method is first proposed for characteristic truncation point of a structural performance function. This is used to define a truncation boundary via the joint probability distribution function of input random variables. To reduce simulation time for new training samples, a U-function based criterion is further implemented to refine the candidate sample set. Since the reliability-based expected improvement function and U functions are combined together to evaluate new training samples, it finalizes a hybrid active-learning Kriging (HALK) to develop adaptive surrogate models for the structural reliability analysis. Several numerical examples are presented to demonstrate potential applications of the proposed HALK algorithm. Compared to benchmark results provided by the brutal force Monte-Carlo simulation method, the effectiveness of the HALK approach has been justified by dealing with various structural reliability problems.

Aleatory and epistemic uncertainties usually coexist within a mechanistic model, which motivates the hybrid structural reliability analysis considering random and interval variables in this paper. An introduction of the interval variable requires one to recursively evaluate embedded optimizations for the extremum of a performance function. The corresponding structural reliability analysis, hence, becomes a rather computationally intensive task. In this paper, physical characteristics for potential optima of the interval variable are first derived based on the Karush-Kuhn-Tucker condition, which is further programmed as a simulation procedure to pair qualified candidate samples. Then, an outer truncation boundary provided by the first-order reliability method is used to link the size of a truncation domain with the targeted failure probability, whereas the U function is acted as a refinement criterion to remove inner samples for an increased learning efficiency. Given new samples detected by the revised reliability-based expected improvement function, an adaptive Kriging surrogate model is determined to tackle the hybrid structural reliability analysis. Several numerical examples in the literature are presented to demonstrate applications of this proposed algorithm. Compared to benchmark results provided by the brute-force Monte Carlo simulation, the high accuracy and efficiency of this proposed approach have justified its potentials for the hybrid structural reliability analysis.

Based on the Bouc-Wen model, a nonlinear hysteretic restoring force model is established with dynamic equations. The hardening and softening of the material after reaching the yield limit are described by the nonlinear restoring force-displacement hysteretic curve. The Gamultiobj algorithm and the group search optimization (GSO) algorithm are used to fit and identify the material softening and hardening hysteresis curves, respectively. The effectiveness of the optimization algorithm for identifying the parameters of the hysteretic model is verified, and the optimization effects of the two algorithms are compared. The results show that the Gamultiobj algorithm has better parameter identification ability and curve fitting ability for the hysteretic model. Then, the hysteresis curve describing the nonlinear characteristics of a clamp is obtained through the static stiffness experiment of the clamp. The experimental curve is fitted by the Gamultiobj algorithm. As a result, the nonlinear Bouc-Wen model parameters of the clamp are obtained, and the stiffness and damping of the clamp are recognized. The distribution statistics of the obtained parameters are performed, and it is found that each parameter satisfies a certain probability distribution, which indicates that the parameter identification result is reasonable.

To investigate the penetration mechanism of spherical projectiles into soft tissues, ballistic gelatin was used as tissue substitute in ballistic tests. A theoretical motion model was established based on the cavity expansion theory. We first presented a quasi-static cylindrical cavity expansion model for the radial stress at the cavity wall of a cracked-hyperelastic material. The pressure on the cavity surface, PS, was also defined as the energy required to open a unit volume in the medium quasi-statically. Based on this interpretation, we proposed an approximate expression for the dynamic pressure, P, acting on the surface of the cavity by analyzing the energy transformation and conservation. Then, based on the analysis and solutions of the cylindrical cavity expansion model, we obtained a resistance force model for spherical projectiles, which consisted of an inertial term and a rate-dependent strength term. Subsequently, ballistic tests, in which gelatin blocks were penetrated by spherical projectiles of different materials and sizes, were analyzed, and the parameters in the resistance model were identified using the test results obtained from the 3 mm steel projectile. Further, the ability of the motion model to describe the motion of spherical projectiles penetrating ballistic gelatin was verified by comparing the calculated and measured results from projectiles of different materials and sizes. The proposed motion model based on the cavity expansion theory can therefore provide a basis for understanding the interaction of small arms ammunition and soft tissues.

In our previous work, we demonstrated the world’s first inversion-type p-channel diamond metal–oxide–semiconductor field-effect transistor (MOSFET). However, it exhibited low channel mobility due to high interface state density (Dit). In this study, the electronic states of Al2O3/diamond interfaces above the valence band edge (Ev) were carefully examined by capacitance–voltage (C–V) measurements in a wide frequency range of 1 Hz–10 MHz at 300, 350, and 400 K, providing an accurate characterization of deeper interface state density compared with our previous work (from 10 Hz to 10 kHz at room temperature) within the limitations of the high-low method. We observed humps in C–V curves, which became wider as the temperature increased and the frequency decreased, indicating the presence of interface states at deep energy levels. They can act as Coulomb scattering centers in diamond MOSFETs; thus, their characterization at low frequencies and high temperatures is necessary. The energy distribution of Dit was estimated using the high-low method at 400 K, indicating that Dit was in the range of (0.4–1.5) × 1012 cm−2eV−1 within 0.23–0.76 eV from Ev of diamond. More effective passivation techniques are required to reduce interface states at deep energy levels.

Special tariffs have been increasingly adopted to protect domestic industries from potential injury caused by unfair international trade. In this study, a multinomial logit model is employed to examine the patterns and determinants of antidumping duty investigations in the global forest products industry. From 1995 to 2015, a total of 372 relevant cases are identified. The number of firms and the inclusion of unions as a petitioner generally improve the probability of an affirmative decision. The characteristics of petition countries have shown more impacts on the decisions than those of target countries. Developing countries have initiated a larger number of antidumping duty investigations in the global forest products industry, and furthermore, they are more inclined to adopt antidumping duties than developed countries. Countries with abundant forest resources and more forest products trade are more likely to make an affirmative decision. These findings will provide helpful information to industrial firms and government agencies in dealing with the challenges of global competition. Study Implications The findings reveal that getting more stakeholders involved in an antidumping duty investigation will increase the probability of trade intervention. The economic status in petition countries is the primary determinant of the decisions from antidumping duty investigations in the global forest products industry. Developing countries not only have initiated a large number of antidumping duty investigations in the forest products industry but also have been more inclined to adopt antidumping duties. Antidumping duty investigations offer an opportunity to countries with abundant forest resources and extensive forest products trade in case of unfair international competition.

This paper presents an effective approach for uncertain aerodynamic analysis of airfoils via the polynomial chaos expansion (PCE). To achieve this, the multivariate polynomial is first setup to represent random factors within the aerodynamic model, whereas the expansion coefficient is expressed as the multivariate stochastic integral of the input random vector. In this regard, the statistical regression in conjunction with a small number of representative samples is employed to determine the expansion coefficient. Then, a combination of the PCE surrogate model with brutal-force Monte Carlo simulation allows to determine numerical results for the uncertain aerodynamic analysis. Potential applications of this approach are first illustrated by the uncertainty analysis of the Helmholtz equation with spatially varied wave-number random field, and its effectiveness is further examined by the uncertain aerodynamic analysis of the NACA 63-215 airfoil. Results for the small regression error and a close agreement between simulated and benchmark results have confirmed numerical accuracy and efficiency of this approach. It, therefore, has a potential to deal with computationally demanding aerodynamical models for the uncertainty analysis.

Based on the converse flexoelectric effect, flexoelectric actuator is designed and used to control the dynamic displacement of cantilever beams. First, shell-type stress expression based on double-curvature shell induced by the converse flexoelectric effect is developed, which can be simplified to a flexoelectric-laminated cantilever beam by applying two Lamé parameters and beam radius of curvature. Then, the flexoelectric actuator is designed with a conductive atomic force microscope probe and a flexoelectric layer. An inhomogeneous electric field is generated when the external voltage is applied on the atomic force microscope probe and the flexoelectric layer, which leads to stress in the longitudinal direction of beam and control moment. With the flexoelectric-induced bending moment, displacement induced by the external force and flexoelectric actuator is derived. The displacement is related to many parameters, such as actuation voltage, atomic force microscope probe radius and flexoelectric layer thickness. Cases are studied to optimize the control effect with different parameters. Results show that vibration control effect is enhanced with a higher actuation voltage and a smaller atomic force microscope probe radius for each mode. Besides, the thicker flexoelectric layer enhances the control effect with a larger bending moment arm for each mode. Dynamic vibration is controlled effectively by converse flexoelectric effect.

Due to manufacturing errors and material deteriorations in the metal rubber of clamps, the clamp stiffness of the pipeline is uncertain. This paper presents a non-intrusive multi-dimensional Chebyshev polynomial approximation method (M-CPAM) to evaluate uncertain characteristics of the frequency response function (FRF) of the clamp-pipeline system (CPS), where the clamp stiffness parameters are taken as unknown but bounded interval variables. Firstly, a finite element model of the clamp-pipeline system is established. Secondly, the variance-based global sensitivity analysis is implemented to determine significant stiffness parameters. Then, the uncertain intervals of the clamp stiffness are measured by experiments and the dispersion of the clamp stiffness is described. Finally, based on the measured stiffness interval, the uncertain frequency responses of the CPS under different tightening torques are analyzed by the proposed M-CPAM, and the effectiveness of simulation results is verified by experiments. Compared with the results obtained from the Monte Carlo simulation, the experimental measurements, and the polynomial chaos expansion, the proposed M-CPAM provides a more accurate, time-saving and practical method for solving the uncertain frequency responses of the CPS with interval stiffness variables. The results show that the clamp stiffness has great dispersion under the same tightening torque. A frequency shift phenomenon will be observed when the clamp stiffness is uncertain. Moreover, the dispersion of the frequency response of the CPS tends to be concentrated with the increase of the tightening torques.

The functionally graded material (FGM) has a potential to replace ordinary ones in engineering reality due to its superior thermal and dynamical characteristics. In this regard, the paper presents an effective approach for uncertain natural frequency analysis of composite beams with axially varying material properties. Rather than simply assuming the material model as a deterministic function, we further extend the FGM property as a random field, which is able to account for spatial variability in laboratory observations and in-field data. Due to the axially varying input uncertainty, natural frequencies of the stochastically FGM (S-FGM) beam become random variables. To this end, the Karhunen–Loeve expansion is first introduced to represent the composite material random field as the summation of a finite number of random variables. Then, a generalized eigenvalue function is derived for stochastic natural frequency analysis of the composite beam. Once the mechanistic model is available, the brutal Monte-Carlo simulation (MCS) similar to the design of experiment can be used to estimate statistical characteristics of the uncertain natural frequency response. To alleviate the computational cost of the MCS method, a generalized polynomial chaos expansion model developed based on a rather small number of training samples is used to mimic the true natural frequency function. Case studies have demonstrated the effectiveness of the proposed approach for uncertain natural frequency analysis of functionally graded material beams with axially varying stochastic properties.

Based on the electromechanical coupling of piezoelectricity, a piezoelectric ring energy harvester is designed and tested in this study, such that the harvester can be used to power electric devices in the closed-circuit condition. Output energies across the external resistive load are evaluated when the ring energy harvester is subjected to harmonic excitations, and various design parameters are discussed to maximize the power output. In order to validate the theoretical energy harvesting results, laboratory experiments are conducted. Comparing experiment results with theoretical ones, the errors between them are under 10% for the output voltage. Laboratory experiments demonstrate that the ring energy harvester is workable in practical applications.

The uncertainty simulation related to a spatially varying physical property requires the theory of the random field discretization. A random field in definition consists of an infinite number of random variables that are attached to all points within the simulation domain. The utility of the Karhunen–Loeve (K–L) expansion allows representing a second-order random field as the summation of a few deterministic functions and standard random variables. However, the K–L expansion depends on exact eigensolutions of the Fredholm integral equation of the second kind. Along with an emerging trend of the random field simulation combined with a complex geometry, analytical expansion results are increasingly inapplicable in engineering reality. To this end, the paper presents a high-order polynomial based Ritz–Galerkin approach. To implement, the Legendre, the Chebyshev, and the Gegenbauer orthogonal polynomials are used to realize the Ritz–Galerkin approximation. Together with the Gaussian-quadrature based interpolation scheme in approximating covariance models, numerical results for eigensolutions have demonstrated the spectral accuracy of the proposed approach. Results for the non-stationary, non-Gaussian and multivariate random field simulations have validated the high-order polynomial based Ritz–Galerkin approach has engineering applications.

To alleviate the greenhouse effect, increasing the carbon storage of forest and harvested wood products is an effective way. As one of the most important components of forest resources, bamboo plays an important role in carbon sequestration. China possesses the richest bamboo resources in the world. In this study, we developed a comprehensive carbon model including the supply chain from bamboo forest to final products to estimate the carbon pool for China's bamboo industry from 1993 to 2018. To examine the changes in carbon storage, we conducted a spatiotemporal analysis for 15 provinces employing a simple linear regression model. Additionally, a stochastic simulation was employed to test the parameter uncertainty in carbon estimation. Results show the carbon storage of China's bamboo industry has steadily improved, including both bamboo forest and products. In 2018, the carbon storage of bamboo vegetation, soil, and ground layer reached 448.30 TgC, 396.75 TgC, and 11.20 TgC, respectively. The carbon storage of bamboo products also increased gradually, with the storage and emission being 55.33 TgC and 1.70 TgC, respectively. The total carbon storage of China's bamboo industry in 2018 is 909.88 TgC. Moreover, the spatiotemporal analysis quantifies the annual change of the carbon storage for each province. It reveals the spatiotemporal change pattern of total bamboo carbon storage as similar to the bamboo forest. The provinces with more carbon storage tend to increase more rapidly per year. The bamboo industry is immensely significant for both the economy and the environment.

The paper presents an effective surrogate model for system reliability analysis of mechanisms based on an extreme-value kinematic error model and the Kriging approximation. In this regard, two types of kinematic reliability problems are considered, i.e., the system reliability that requires the kinematic error remains within an accuracy threshold along an entire output trajectory, whereas the time-dependent reliability accounts for gradually propagated system failure domain due to the varied pseudo-time parameter from its beginning to the current realization. Both kinematic reliability problems need to evaluate the extreme-valued error function presented in the mixture of absolute and maximum operators. By contrast, the simple position-based error function allows developing accurate surrogate models with a rather small number of training samples. Therefore, an approximation model was proposed to deal with kinematic reliability problems of steering mechanisms. Compared to available reliability methods in the literature, results have demonstrated high accuracy of the proposed method for various kinematic reliability problems. Note that the proposed method for time-dependent reliability analysis requires only one round of design of experiment, rather than repeatedly running the kinematic model like the first-order reliability method. It therefore provides an effective simulation tool for kinematic reliability analysis of mechanisms.

Erythropoietin (EPO) is a 34-kDa glycoprotein that possesses the potential for angiogenesis, as well as anti-inflammatory and anti-apoptotic properties. The present study aimed to examine the effect of EPO on the angiogenesis of dental pulp cells (DPCs) and to explore the underlying mechanisms of these effects. It was demonstrated that EPO not only promoted DPCs proliferation but also induced angiogenesis of DPCs in a paracrine fashion. EPO enhanced the angiogenic capacity by stimulating DPCs to secrete a series of angiogenic cytokines. ELISA confirmed that high concentrations of EPO increased the production of MMP-3 and angiopoietin-1 but decreased the secretion of IL-6. Furthermore, EPO activated the ERK1/2 and p38 signaling pathways in DPCs, while inhibition of these pathways diminished the angiogenesis capacity of DPCs. The present study suggested that EPO may have an important role in the repair and regeneration of dental pulp.

With the development of information communication technology and Internet of Things technology, the number of devices connected to the network and the amount of data generated are exponentially increasing, thus resulting in a series of new application scenarios. The traditional centralized cloud computing big data processing model can no longer content the current data growth needs. Thus, born edge computing, a new computing model that migrates some or all of the computing tasks of the original cloud computing center to near the data source, gradually received extensive attention from all walks of life. According to the current cloud computing and edge computing application scenarios, analyze some security threats faced by edge computing in applications. Analyze and organize the security part of the existing edge computing reference architecture, and refine the edge computing security protection architecture and principles. By introducing trusted computing and blockchain technology, the credibility and adaptability of the edge computing security protection system is increased, making it more adaptable to the current practical application scenarios.

The regeneration of periodontal tissues to cure periodontitis remains a medical challenge. Therefore, it is of great importance to develop a novel biomaterial that could induce cementogenesis and osteogenesis in periodontal tissue engineering. Calcium silicate (Ca-Si) based ceramics have been found to be potential bioactive materials due to their osteostimulatory effect. Recently, it is reported that zirconium modified calcium-silicate-based (Ca