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[Display omitted] • RBD for the tunnel face stability utilizing a simplified inverse FORM. • The iHLRF-x algorithm integrated with 3D FELA modelling. • Optimal support pressure interval obtained by probability analysis. • Influence of the COV and correlation on tunnel face stability. In order to maintain the safety of underground constructions that significantly involve geo-material uncertainties, this paper delivers a new computation framework for conducting reliability-based design (RBD) of shallow tunnel face stability, utilizing a simplified inverse first-order reliability method (FORM). The limit state functions defining tunnel face stability are established for both collapse and blow-out modes of the tunnel face failure, respectively, and the deterministic results of the tunnel face support pressure are obtained through three-dimensional finite element limit analysis (FELA). Because the inverse reliability method can directly capture the design support pressure according to prescribed target reliability index, the computational cost for probabilistic design of tunnel face stability is greatly reduced. By comparison with Monte Carlo simulation results, the accuracy and feasibility of the proposed method are verified. Further, this study presents a series of reliability-based design charts for vividly understanding the limit support pressure on tunnel face in both cohesionless (sandy) soil and cohesive soil stratums, and their optimal support pressure ranges are highlighted. The results show that in the case of sandy soil stratum, the blowout failure of tunnel face is extremely unlikely, whereas the collapse is the only possible failure mode. The parametric study of various geotechnical uncertainties also reveals that ignoring the potential correlation between soil shear strength parameters will lead to over-designed support pressure, and the coefficient of variation of internal friction angle has a greater influence on the tunnel face failure probability than that of the cohesion. [ABSTRACT FROM AUTHOR]

Most slope collapses have three-dimensional (3D) characteristics due to the uniform soil. The traditional plane-strain analyses neglect the 3D effects and could yield an overestimation or underestimation of the slope stability. The present study analyzes the stability of 3D slopes characterized by spatially variable undrained shear strength. A 3D slope reliability analysis approach that can fully consider the spatial variability of soil properties is proposed based on the plastic limit analysis upper-bound theorem. Within the framework of Monte Carlo simulation, the effects of strength gradient, the coefficient of variation, and the scale of fluctuation of soil undrained shear strength on the slope reliability index are examined. The length of the 3D failure surface is highlighted as an essential characteristic in 3D slope analysis. The slope failure mechanisms are classified, and the occurrence probability of each type is quantified. The obtained results indicate that the degree of nonstationarity and the coefficient of variation of undrained shear strength have significant impacts on the slope failure width, and the variation of failure mechanism highly depends on the combined effect of slope inclination and soil strength. The findings could guide slope reinforcement and facilitate a more efficient and accurate risk evaluation of slopes. [ABSTRACT FROM AUTHOR]

Formaldehyde (HCHO) is an important precursor for secondary pollution in the atmosphere and is carcinogenic. Previous studies have underscored the substantial contribution of non-road construction equipment (NRCE) to HCHO emissions, yet the understanding of HCHO emissions from NRCE remains limited. In this study, we conducted real-world measurements on six China III forklifts, which are an important type of NRCE in China, to characterize their second-by-second HCHO emission patterns. We quantified the fuel-based emission factors (EFs) of HCHO under various conditions including operating conditions, engine power, and the presence of an after-treatment device. Results showed that the cumulative weighted HCHO EF for the low-power forklifts was 1.37 ± 0.74 g/kg fuel, which was 3 times greater than that for high-power forklifts. Higher HCHO EFs were found under idling conditions than under moving and working conditions. Notably, the installation of a diesel particulate filter (DPF) potentially resulted in an increase in HCHO emissions. Our research indicates that the HCHO emissions from forklifts were considerably high and may have been previously underestimated by offline measurements, which suggests the need for further investigation of HCHO emissions from forklifts utilizing advanced online techniques. • Formaldehyde (HCHO) emissions from six China III forklifts were measured in real-world conditions using online devices. • Higher HCHO emission factors of forklifts were found under idling conditions. • A diesel particulate filter (DPF) installation in forklifts could potentially increase HCHO emissions from forklifts. • HCHO emissions from forklifts are likely underestimated by off-line measurements. [ABSTRACT FROM AUTHOR]

Because nearby construction has harmful effects, precisely predicting blast-induced ground vibration is critical. In this paper, a hybrid artificial bee colony (ABC) and support vector machine (SVM) model was proposed for predicting the value of peak particle velocity (PPV), which is used to describe blast-induced ground vibration. To construct the model, 5 potentially relevant factors, including controllable and uncontrollable parameters, were considered as input parameters, and PPV was set as the output parameter. Forty-five samples were recorded from the Hongling lead-zinc mine. An ABC-SVM model was developed and trained on 35 samples via 5-fold cross-validation (CV). A testing set (10 samples) was used to evaluate the prediction performance of the ABC-SVM model. SVM and four empirical models (United States Bureau of Mines (USBM), Amraseys-Hendron (A-H), Langefors-Kihstrom (L-K), and Central Mining Research Institute (CMRI)) also were introduced for comparison. Next, the performances of the models were analyzed by using 3 statistical parameters: the correlation coefficient (R2), root-mean-square error (RMSE), and variance accounted for (VAF). ABC-SVM had the highest R2 and VAF values followed by the SVM, A-H, USBM, CMRI, and L-K methods. The results demonstrated that ABC-SVM outperformed SVM and the empirical predictors for predicting PPV. Moreover, the best results from the R2, RMSE, and VAF indices were 0.9628, 0.2737, and 96.05% for the ABC- SVM model. The sensitivities of the parameters also were investigated, and the height difference between the blast point and the monitoring station was found to be the parameter that had the most influence on PPV. [ABSTRACT FROM AUTHOR]

Accurate prediction of tunnel convergence is important to ensure the stability of tunnel structures. Reliability analysis of tunnel convergence on spatially variable soils was performed based on Monte Carlo simulations. The Young's modulus of soils was shown to be spatially varied. The influence of the coefficient of variation, the vertical scale of fluctuation and the distribution type (i.e. beta distribution, gamma distribution and lognormal distribution) of soils on the tunnel convergence were systematically discussed. From measuring the mean and standard deviation of tunnel convergence, and the probability of exceeding some thresholds, it was found that the distribution type significantly influenced the results. The results were accompanied by a detailed analysis of the mechanisms of tunnel convergence in spatially random soils. [ABSTRACT FROM AUTHOR]

The objective of this paper is to investigate how the non-stationary features of soil properties affect the stochastic result of bearing capacity of embedded shallow foundations. Undrained shear strength was modelled as a non-stationary random field with mean value increasing with depth. A nonlinear finite element analysis combined with random fields generated by the Spectral Representation Method was employed to obtain the bearing capacity in random soils. Monte Carlo simulations were applied to obtain statistical characteristics of the resulting bearing capacity. The effect of non-stationary features of random soil properties on foundations with different embedment depths is discussed from three aspects, i.e. the failure mechanisms, the statistical characteristics of the bearing capacity factors, and the probability of failure of the foundation. Interestingly, it was found that the effects of non-stationary random soil properties on some of the three aspects change with the embedment depths of the foundations. Furthermore, some suggestions for foundation design are given, based on the obtained results. [ABSTRACT FROM AUTHOR]

• A modified SRM is proposed to consider wave-passage effect in vector process. • Wave-passage effect is presented in the simulation of non-Gaussian vector process. • It is proved the wave-passage part is not changed in the nonlinear translation. Wave-passage effect is always of great importance when performing the dynamic analysis of lager scale structures. This effect can be easily considered in the simulation of Gaussian vector process, but there is not an efficient way to consider it in simulating non-Gaussian vector process. In this paper, a method is proposed to generate stationary non-Gaussian vector process considering wave-passage effect. In the simulation of vector process, wave-passage effect leads to a complex-defined cross spectral density matrix (CSDM). To separate the phase part from the CSDM, an improved form of spectral representation method (SRM) is proposed, in which the phase part representing the wave-passage effect can be directly expressed in an explicit form in the simulation formula. Then the characteristic of phase part representing the wave-passage effect during the nonlinear translation (translating underlying Gaussian vector process to the prescribed non-Gaussian vector process) is investigated. Interestingly, it is found that, the phase part is not changed. Based on this good feature, the modified SRM and the iterative scheme can be combined to simulate non-Gaussian vector process considering wave-passage effect. Two examples, involving the simulation of seismic ground motions and wind velocity time histories, are presented to show the characteristics of the simulated vector process and to verify the capabilities of the proposed method. [ABSTRACT FROM AUTHOR]

Surface irregularities on the earth, such as hills and ridges, can amplify the ground motion caused by earthquakes and cause damage to buildings. Hence, it is crucial to study the ground motion amplification on hills and their environs under the effect of earthquakes. In this research, the seismic response of a triangular rocky hill subject to cylindrical horizontally polarized shear (SH) waves is investigated by means of a boundary integral equation method. A comparison is made to verify the feasibility of the present method. Parametric studies are performed to evaluate the influences of source location and hill shape on the ground accelerations on the hill and its environs under cylindrical SH waves of different frequencies. The results show that the ground accelerations near the hill are strongly relative to the source location. For a near-source scattering problem, the cylindrical wavefront assumption is more appropriate than the plane wave assumption. The thinner hill is more likely to cause multiple reflections of the seismic waves inside it, resulting in a stronger ground motion near the hillcrest. The acceleration response spectrum at the hillcrest is amplified in a wide period range of 0–4 s, and increasing the hill height will strengthen the amplification effect. The presence of the hill also results in the amplification of the acceleration response spectrum in the period range of 0–0.7 s on the flat ground surface. Highlights: The seismic response of a triangular hill to cylindrical SH waves was investigated. Necessity of cylindrical wavefront assumption for near-source problem was verified. Mechanism of ground motion amplification on a triangular hill was revealed. [ABSTRACT FROM AUTHOR]

Green metal-electrode batteries call for the clean production of s-block metals. Herein, we developed an electrolysis–displacement–distillation (EDD) approach for producing s-block metals with low-carbon emissions and no chlorine gas evolution. The clean production stems from the choice of a molten NaCl–Na2CO3 electrolyte to prevent chlorine gas evolution, an inert nickel-based anode to produce oxygen, and a liquid metal cathode to make the cathodic product (e.g., Na–Sn) sit at the bottom of the electrolytic cell. Later, M–Sn (M = Li, Mg, Ca, Sr, and Ba) alloys were successfully prepared by a displacement reaction between the Na–Sn alloy and molten NaCl–LiCl, NaCl–MgCl2, NaCl–CaCl2, NaCl–SrCl2, or NaCl–BaCl2 with a displacement efficiency of >96.0%. Furthermore, Li, Mg, Ca, Sr, and Ba metals were separated from M–Sn alloys using vacuum distillation with a separation rate of >95.0%. We achieved a current efficiency of 81.0% for the electrolytic production of 100 kg of a liquid Na–Sn alloy, which holds promise to produce s-block metals at a large scale. [ABSTRACT FROM AUTHOR]

In this paper, a novel energy-based trajectory tracking control strategy for under-actuated unmanned surface vessels (USVs) in the presence of unknown environmental disturbances is presented. The port-Hamiltonian framework is utilized to propose a passivity-based control model in body-fixed coordinates of the USVs. An adaptive disturbance estimation method is detailed and used to accurately estimate the environmental disturbances affecting USV motion. Furthermore, a passive and Hamiltonian structure-preserving controller is employed to achieve the desired trajectory of the USV system, and the stability of the desired target dynamic system is rigorously proven. The effectiveness of the proposed controller is demonstrated through simulations and experiments on a USV experimental platform, showcasing its capability of trajectory tracking performance and mitigating the effects of disturbances. • A novel port-Hamiltonian modeling approach is developed for under-actuated USVs. • Adaptive disturbance observer counters environmental disruptions. • A passivity-based controller is employed to achieve the desired trajectory. • Simulation and experimental results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A novel deep learning method based on the two-dimensional convolutional neural network (2D-CNN) was proposed to predict the horizontal and vertical convergences of high-speed railway tunnels considering the spatial variability of soil Young's modulus. The input and output of the neural network were the soil Young's modulus random field and tunnel convergence, respectively. The coefficient of determination (R2) and the relative error of the predicted results were determined to evaluate the prediction performance and extrapolating ability of the proposed CNN model. The prediction accuracy increased with increasing scale of fluctuation (SOF) from 10 to 60 m as the R2 increased. Two prediction data sets with 10,000 samples (per set) were generated to illustrate the model, where the R2 values were greater than 0.99. Also, the relative errors of the limit values of 90% and 99% exceeding the probability between the CNN-predicted and random finite difference method (RFDM)-calculated convergences were within 0.64%. The computational efficiency was significantly improved by 2,371 times with satisfactory accuracy. The trained CNN model showed excellent extrapolation ability in solving cases with an anisotropic random field and variation of COV. Results indicated that the proposed CNN model is a promising surrogate of RFDM with Monte Carlo simulations to analyze tunnel convergence considering soil Young's modulus in an isotropic random field. The spatial variability of soil parameters is commonly believed to have a significant influence in assessing tunnel reliability. Traditional probabilistic analysis of tunnel deformation was generally conducted by time-inefficient random finite-element/difference methods with Monte Carlo simulations. Recently, machine learning methods are vastly applied in geotechnical engineering with the rapid development of computational techniques, aiming to improve calculation efficiency. This study develops a two-dimensional convolutional neural network-based model to predict tunnel convergence with consideration of soil spatial variability. The input and output of the surrogate model are the soil Young's modulus random field and tunnel convergence, respectively. The coefficient of determination, mean square error, and relative error are used to evaluate the prediction performance. The surrogate model is trained by isotropic random field data sets and performs excellent extrapolation ability on the data sets of the anisotropic random field. It suggests that the proposed model can conduct a probabilistic analysis of tunnel convergence in spatially variable soil with high accuracy. [ABSTRACT FROM AUTHOR]

The kinematic approach of limit analysis is explored in three-dimensional face stability of large-diameter tunnels in soils with linearly increasing undrained strength with depth. Due to the slurry density by a shield machine, the support pressure is not uniformly distributed on the face. Such a non-uniform distribution cannot be ignored, especially for the large-diameter shield tunnels. This paper includes it into the stability analysis of the tunnel face subjected to local and global failures. The failure mechanism with a spherical cap is adopted to obtain the least upper-bound solutions of local stability of the tunnel face. To evaluate its global stability, a continuous velocity field with a toric envelope is employed and yields the critical pressures on tunnel face against collapse and blow-out. The calculated results are compared with the solutions derived from other well-established methods for verification of the presented approach. An approximation formula based on the derived upper-bound solutions, is given to directly calculate the necessary collapse and blow-out pressures, which can be used for preliminary design in practice. An example is given to illustrate its convenient use. [ABSTRACT FROM AUTHOR]

• A molten salt electrolysis method to separate Sb from Pb alloys is developed. • The separation of Sb is realized by selectively generating Ca-Sb alloy. • The purity of Pb obtained can reach 99.859%. Lead-acid batteries (LABs) are widely used in electric motorcycles, uninterruptible power systems, and stationary energy storage devices. However, spent LABs should be recycled to reuse lead (Pb) and thereby close the Pb cycle and avoid Pb contamination. In order to reuse the recovered Pb, the purity of recovered Pb should meet the required standard. Since antimony (Sb) is a common alloying element in Pb alloy grid such as the Pb-Sb alloy, separating Sb from the recovered Pb is necessary. In this paper, we proposed a molten salt electrolysis method to separate Sb from liquid Pb-Sb alloys in terms of forming a solid Ca-Sb intermetallic at the top of the liquid Pb-Sb cathode. The electrochemical separation process was performed in molten NaCl-CaCl 2. The content of Sb (atomic percent) in the Pb-Sb alloy was reduced from 1% to less than 0.01% (atomic ratio). The recovery principle lies in the different alloying potentials between Ca-Sb and Ca-Pb. Hence, molten salt electrolysis is a promising separation method to recover pure Pb from spent Sb-containing Pb alloys. [ABSTRACT FROM AUTHOR]

To identify microbial resources for dehalogenation, develop effective remediation strategies, and reveal their significance in "One Health", it is crucial to understand the occurrence, distribution, and drivers of soil dehalogenation functional traits and taxonomy groups at a broad scale, which is currently not well understood. To address the gaps, we characterized the biogeography of both dehalogenation traits and taxa assigned to six dehalogenation pathways, by metagenomic profiling global 4821 soils from eight habitats, based on a manually curated dehalogenase database (DhgaseDB). We found dehalogenation genes and microbes assigned to different pathways are everywhere, but varied consistently across habitats. The similarity of dehalogention traits and taxa composition declines with geographic distance, and that patterns are strongly correlated with geo-environmental factors. We identified anthropogenic organohalide pesticide inputs as the most influential factor on dehalogenation gene abundance, while soil properties, particularly pH, exert a larger impact on dehalogenation taxa diversity. Ultimately, we generated predictive maps of soil dehalogenation gene abundance and taxa diversity for the first time, highlighting the microbial dehalogenation hotpots in East Asia, Australia, Southern Africa, and coastal regions. Collectively, our study highlights the significant role of various microbial dehalogenation processes in organohalide biotransformation and environmental microecology, providing the necessary methodological basis for a deeper comprehension of the underlying mechanisms, thereby contributing to the advancement of tailored strategies for organohalide remediation. • DhgaseDB was established for fast and accurate analysis of dehalogenation genes and taxa. • Dehalogenation genes and microbes are prevalent in global soils, but varied consistently across habitats. • Pesticide inputs are key to gene abundance, while soil pH significantly affects microbial diversity. • The first predictive maps of soil dehalogenation gene abundance and taxa diversity were generated. [ABSTRACT FROM AUTHOR]

Abstract: Fe3O4 hollow spheres/carbon nanotubes (Fe3O4-HSs/CNTs) composites were synthesized by a facile solvothermal method, without any template. Compared to the Fe3O4 hollow spheres (Fe3O4-HSs), the Fe3O4-HSs/CNTs composites showed a better suitability as anode materials for lithium-ion batteries. After 70 cycles, the Fe3O4-HSs/CNTs composites exhibited a reversible capacity of 1153.8mAhg−1 at 0.1Ag−1 as well as good cycling performance. When the current density was 0.4, 0.7 and 1.0Ag−1, the composites still displayed reversible capacity of 1038.4, 848.8 and 778.5mAhg−1, respectively. In addition, the Fe3O4-HSs/CNTs composites showed improved long-life cycling performance even at high current. [Copyright &y& Elsevier]

In this paper, we consider the stabilization of an axially moving Kirchhoff-type beam with rotational inertia under controls of force and torque at one boundary. The proposed negative feedbacks of the transverse velocity and angular velocity applied at the control end cover a large class of nonlinear feedback functions. The well-posedness of the resulting closed-loop system is established by means of the nonlinear semigroup theory, where the solution is shown to be depending continuously on the initial value. The asymptotic stability of the closed-loop system is guaranteed by resolving a dissipative ordinary differential equation. The decay rates of the vibration for some special nonlinear feedback functions can be estimated by the dissipative ordinary differential equation provided that growth restrictions on these nonlinear feedbacks near the origin are required. Three types of examples including exponential, polynomial and polynomial-logarithmic decay forms are deduced, and the numerical simulations are presented to verify the proposed control approach. [ABSTRACT FROM AUTHOR]

In geological surveys of coastal regions, data interpretation and site identification are usually affected by underground water (including salinity). This study aimed to investigate the effect of pore-water salinity on soil identification via in situ CPTs. Combinations of triaxial shearing, cone penetration, and vane shear tests were also performed at a laboratory scale on Lianyungang marine clay with different pore-water salinities. The results suggested that the effective friction angles and shear strength increased with the pore-water salinity. The in situ CPTs showed that the normalized tip resistances increased with an increase in pore-water salinity, whereas no significant correlation between the normalized sleeve fraction and salinities was found. The use of the conventional soil identification method (soil-behavior-type chart, i.e., SBT chart) may be effective in very low-salinity conditions despite that it does not take into account the pore-water salinity effect. The salinity investigation of Lianyungang marine clay suggests that an inhomogeneous salinity distribution significantly influences soil identification when with rich clay mineral of montmorillonite and high pore-water salinity. From the theoretical and practical analyses, an improved soil identification method considering pore-water salinity modification was proposed to avoid the misclassification of in situ soil. • Effective friction angles and shear strengths increases with an increase in pore water salinity. • Normalized tip resistances increases withpore water salinity. • Soil identification by cone penetration tests is influenced by pore water salinity. • An improved model based on an SBT chart considering the salinity effect is proposed. [ABSTRACT FROM AUTHOR]

Spudcan foundations have been widely used in offshore oil and gas engineering for jack-up rigs. During penetration into seabed soil, spudcan foundations may encounter large uncertainties in soil properties, which have a strong impact on its bearing capacity. A large number of studies have been conducted to demonstrate the failure mechanisms and the bearing capacity of spudcan foundations in soils with deterministic properties, but the influence of spatially variable soil properties on spudcan foundations remains unclear and should be accounted for. In this study, we aimed to investigate the failure mechanisms and the bearing capacity of a spudcan foundation embedded in soils where the mean undrained shear strength increased linearly with depth. The spectral representation method (SRM) was used to generate a non-stationary non-Gaussian random field. The random finite element method (RFEM) in conjunction with Monte Carlo simulations was carried out to evaluate the statistical characteristics of the bearing capacity for spudcan foundations, followed by a series of comparisons and discussion. The results indicated that the mean bearing capacity for the spatial variability of undrained shear strength was smaller than that obtained from the corresponding deterministic case. The probability of failure decreased slightly with an increase in the degree of non-stationarity under the constant coefficient of variation (COV) condition. Upon comparing the results obtained from different random field models, we found that the probability of failure under the non-constant condition was smaller than that under the stationary and constant COV conditions. • A modified spectral representation method is proposed to generate two different kinds of non-stationary random fields. • Establish the connection between dimensionless bearing capacities and failure mechanism modes. • Typical factors of safety under different degrees of non-stationarity are calculated and compared. [ABSTRACT FROM AUTHOR]

• A new method of simulating soil spatial variability based on the UHPM is proposed. • Ignoring soil spatial variability leads to small monitoring result. • The influence of horizontal and vertical SOF on the crown settlement is studied. High-speed railways (HSRs) are extensively constructed in China, with the help of tunnels to cross through complex geological conditions. The sequential excavation method (SEM) is vastly adopted in the construction of loess tunnel. This study performs a probabilistic analysis of crown settlement, taking into account the spatial variability of the surrounding soil through Monte Carlo (MC) simulations. To illustrate the influence of horizontal and vertical scale fluctuations (SOFs) on crown settlement, an anisotropic random field of loess elastic modulus is simulated using the spectral representation method (SRM) and unified Hermite polynomial model (UHPM) for the random finite difference method (RFDM). The mean crown settlements obtained through stochastic analysis are consistently larger than the deterministic results in the 1st, 6th, and 9th construction steps. The maximum probabilities of stochastic crown settlement exceeding the deterministic results are 77.3% and 78.2% with varying horizontal and vertical SOFs, respectively. Amplification factors of 1.417 and 1.306 are necessary to ensure that the stochastic crown settlement of the HSR tunnel, constructed in spatially variable loess, satisfies a 5% and 10% exceeding probability. This study provides valuable guidance for the construction of HSR tunnels. [ABSTRACT FROM AUTHOR]

Fatigue damages of an offshore wind turbine (OWT) would be caused by long-term wind and wave loads, necessitating the importance of fatigue life analysis to ensure the in-service behaviors of OWT. This study evaluates the fatigue damage and predicts the fatigue life of OWT considering full-directional wind inflow under the coupling effects of non-Gaussian wind field and wave. The forces and bending moments are assessed in three types of the wind field, i.e., Gaussian, softening non-Gaussian, and hardening non-Gaussian, according to the Kaimal spectrum by using OpenFAST. The dynamic responses of OWT are implemented by a three-dimensional finite element model (FEM) established by ABAQUS. The fatigue life is assessed in the tower base section and the pile of OWT under different loading combinations. Results show that the crack initiation life is greatly affected by the non-Gaussian wind field, while the crack propagation life is not that sensitive. The fatigue life of OWT under a full-directional wind inflow is approximately three times longer than that under a single-directional wind inflow. It is recommended to consider full-directional wind inflow in the non-Gaussian wind field for OWT design. • It is found that the crack initiation life is greatly affected by the non-Gaussian wind field. • The fatigue life of OWT under a full-directional wind inflow is longer than that under a single-directional wind inflow. • It is recommended to consider full-directional wind inflow in the non-Gaussian wind field for OWT design. [ABSTRACT FROM AUTHOR]

The reflectance spectra of the Al/double cermet Al-AlN/AlO x N y solar selective absorbing coating are simulated. Two methods have been found to effectively tune the position of reflectance transition of the Al-AlN cermet solar selective absorbing coating, which is crucial to obtain a low emittance at elevated temperature. The position of reflectance transition is mainly determined by the high metal volume fraction (HMVF) cermet layer. It is effectively tuned to shift to lower wavelength by reducing the metal volume fraction or the thickness of the HMVF layer. This provides easy ways to tune the position of reflectance transition. [ABSTRACT FROM AUTHOR]

Abstract: A novel MoSi2–Al2O3 solar selective absorbing coating deposited on stainless steel (SS) substrate by magnetron sputtering is reported. The effects of the HMVF and LMVF absorption layers thickness and metal volume fraction on optical properties of the coatings are investigated. As the thickness or metal volume fraction of the HMVF or LMVF layers increases, it is found that the absorptance first increases and then decreases, this can be explained by the regularly changes of the reflectance spectrum. The position of the cutoff limit has a redshift as the thickness of the HMVF or LMVF layers or the metal volume fraction of the HMVF layer increases, which will induce the quick increase of the emittance with temperature. The cutoff limit is almost unchanged as the metal volume fraction of the LMVF layer increases. Most of the experimental results are consistent with the simulated results in the trends. [Copyright &y& Elsevier]

Highlights: [•] We first proposed to use a AlNi alloy to fabricated cermet absorption coating. [•] We obtained an excellent optical property AlNi–Al2O3 absorbing coating. [•] Preliminary thermal stability tests show AlNi–Al2O3 coating is promising for CSP. [ABSTRACT FROM AUTHOR]

The artificial freezing method is an effective method of shaft construction in water-rich soft rock beds. Engineering frozen walls involves the use of intact rock material, flaws and ice. To better understand the mechanical properties of frozen walls, explore the failure laws of frozen fractured rock, and solve the problem of complex ice-rock coupling, it is necessary to carry out laboratory triaxial tests on frozen fractured rock. Herein, X-ray diffraction and mesostructure observations are used to analyse the mineral composition and microstructural characteristics of red sandstone specimens taken from the Shilawusu coal mine. Then, the strength, deformation and crack evolution behaviour of red sandstone containing two pre-existing ice-filled fissures are obtained under triaxial compression using the self-developed DRTS−500 subzero rock triaxial testing system. The experimental results show that the peak strength and elastic modulus of the specimens with pre-existing flaws are all much lower than those of the intact specimens, and the strength parameters are distinctly related to the flaw combinations. For the frozen red sandstone containing two intermittent ice-filled fissures, the peak strength, elastic modulus and shear strength parameters all have a linear relationship with the confining pressure and temperature, whereas the shear strength (σ 1 − σ 3) has a nonlinear relationship with the confining pressure. The deviatoric stress-strain curve of the samples is divided by four characteristic stresses (compacting stress, crack initiation stress, dilatancy stress and peak stress) into five stages from loading to failure. The lower the confining pressure or temperature is, the faster the curve falls after reaching the stress-strain peak value, indicating that the sample exhibits increasingly brittle characteristics. The ultimate failure modes of the specimens containing two pre-existing ice-filled flaws include mixtures of several types of cracks (shear cracks, main cracks, secondary cracks, tensile cracks, coplanar cracks, slip cracks and wing cracks), which depend on the flaw combinations. An obvious crack coalescence failure mode can be observed in the GG and GS specimens, but no obvious crack coalescence phenomenon can be observed in the SS specimens. • Triaxial tests are conducted under different confining pressure and temperature. • The strength of pre-flawed specimens were much lower than those of intact specimens. • The relationships between the strength parameters and flaw combinations were studied. • The crack growth is affected by the combination of pre-existing flaws. [ABSTRACT FROM AUTHOR]

The freezing method is an effective method for shaft construction in water-rich strata. To determine the mechanical properties of frozen walls that contain ice, study the fracture and instability of frozen rock walls, and solve ice-rock coupling problems, it is necessary to research frozen rock masses under triaxial compressive stress. In this paper, using X-ray diffraction and mesostructure observation, the microstructural characteristics and deformation mechanism of frozen red sandstone specimens taken from the Shilawusu coal mine at a depth of 300 m in the Ordos Basin were studied. A series of tests were performed on frozen red sandstone samples under triaxial compression at 4 temperatures and 4 confining pressures using self-developed DRTS−500 subzero rock triaxial test system. The strength and deformation characteristics of the frozen red sandstone under three-dimensional loading were examined. Test results showed that the bonding water formed by charge adsorption on the surface of the mineral particles and the freezing of pore gravity water enhance the cementation of the mineral particles and the flow plasticity under high stress. At constant temperature, the peak strength and elastic modulus of the frozen red sandstone increase with increasing confining pressure. At constant confining pressure, the peak strength and elastic modulus of the frozen red sandstone increase with decreasing temperature, but temperature has little effect on the peak strain. The internal friction angle of the frozen red sandstone is between 28° and 35° and decreases linearly with decreasing temperature. The cohesion is between 4 and 9 MPa and increases linearly with decreasing temperature. At high freezing temperatures, with an increase in confining pressure, the main factors controlling of the triaxial strength of the rock samples change from the cohesive force to the biting force caused by the mineral particles and ice crystals and the friction between them, and the failure mode of the rock samples changes from tension to shear failure. When the temperature is low, the main controlling factors for sample failure are the cohesive force and friction bite force, and the swelling failure and tension-shear composite failure are the main factors. Based on the parabolic strength criterion and the statistical damage theory derived from the strain equivalence principle, a statistical damage constitutive model that considers the void compaction stage and residual strength deformation stage is established, and the analytical expressions for the model parameters are given, which verify the rationality and validity of the model. • The mineral composition and microstructural characteristics of frozen red sandstone were obtained. • A series of triaxial compression tests were conducted on frozen red sandstone. • The strength, deformation and failure modes of frozen red sandstone were studied. • A new constitutive model based on statistical damage theory is proposed. [ABSTRACT FROM AUTHOR]

Bone metastasis is a significant contributor to the poor prognosis in prostate cancer. Recent evidence highlights the pivotal role of pseudouridine synthases in solid tumor progression, yet the specific enzyme driving prostate cancer metastasis remains unidentified. This study uncovers a novel regulatory mechanism of the FOXA1/PUS1/EIF3b signaling axis in prostate cancer bone metastasis. We identified elevated PUS1 expression in prostate cancer tissues, correlating with higher clinical grade and worse prognosis. Knockdown of PUS1 inhibited metastasis independently of its enzymatic activity, with EIF3b acting as a downstream effector, protected from ubiquitin-mediated degradation by PUS1. Overexpression of EIF3b countered the metastasis suppression due to PUS1 knockdown. Additionally, FOXA1 was shown to enhance PUS1 expression by binding to its promoter. Mogroside IV-E, a specific PUS1 inhibitor, demonstrated potent anti-metastatic effects by reducing PUS1 expression. Our findings highlight the FOXA1/PUS1/EIF3b axis as a critical mediator of prostate cancer bone metastasis and suggest that targeting this pathway could be a promising therapeutic strategy., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Prostate cancer (PCa) is one of the most prevalent urogenital malignancies. Bone metastasis from PCa reduces patient survival rates significantly. There currently exists no effective treatment for bone metastatic PCa, and the underlying mechanisms remain unclear. This study performed transcriptomic screening on PCa bone metastasis specimens and intersection analysis in public databases and identified SERPINH1 as a potential target for treatment. SERPINH1 was found to be upregulated in PCa bone metastases and with poor prognosis, high Gleason score, and advanced metastatic status. SERPINH1 induced PCa cells' bone metastasis in vivo , promoted their proliferation, and mitigated apoptosis. Mechanistically, SERPINH1 bound to P62, reducing TRIM21-mediated K63-linked ubiquitination degradation of P62 and promoting proliferation and resistance to apoptosis of PCa. This study suggests the regulation of ubiquitination degradation of P62 by SERPINH1 that promotes PCa bone metastasis and can be considered as a potential target for treatment of bone metastatic PCa., Competing Interests: The authors declare no competing interests., (© 2024 The Authors.)

Muscle atrophy and skeletal muscle fibrosis are significant pathological manifestations of primary sarcopenia. The regulation of C2C12 myoblast and skeletal muscle fibroblast apoptosis is associated with these pathological changes. Previous studies have indicated that irisin, the cleaved form of fibronectin type III domain-containing protein 5 (FNDC5), can alleviate primary sarcopenia. However, the mechanisms of the effect of irisin in age-related apoptosis remain unknown. Our present research aimed to explore the effect of irisin and the underlying mechanism of D-galactose (D-gal)-induced apoptosis in skeletal muscle fibroblasts and C2C12 myoblasts. We found the opposite effects of D-gal on C2C12 myoblasts and fibroblasts. We also found that irisin suppressed C2C12 cell apoptosis and promoted fibroblast apoptosis. Mechanistically, irisin altered D-gal-induced apoptosis by increasing caveolin-1 expression. Taken together, these findings further demonstrated that irisin is a potential agent that can treat aged-relative muscle atrophy and fibrosis., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Coronavirus disease 2019 (COVID-19) is an infectious disease spreading rapidly worldwide. As it quickly spreads and can cause severe disease, early detection and treatment may reduce mortality. Therefore, the study aims to construct a risk model and a nomogram for predicting the mortality of COVID-19., Methods: The original data of this study were from the article " Neurologic Syndromes Predict Higher In-Hospital Mortality in COVID-19." The database contained 4,711 multiethnic patients. In this secondary analysis, a statistical difference test was conducted for clinical demographics, clinical characteristics, and laboratory indexes. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis were applied to determine the independent predictors for the mortality of COVID-19. A nomogram was conducted and validated according to the independent predictors. The area under the curve (AUC), the calibration curve, and the decision curve analysis (DCA) were carried out to evaluate the nomogram., Results: The mortality of COVID-19 is 24.4%. LASSO and multivariate logistic regression analysis suggested that risk factors for age, PCT, glucose, D-dimer, CRP, troponin, BUN, LOS, MAP, AST, temperature, O 2 Sats, platelets, Asian, and stroke were independent predictors of CTO. Using these independent predictors, a nomogram was constructed with good discrimination (0.860 in the C index) and internal validation (0.8479 in the C index), respectively. The calibration curves and the DCA showed a high degree of reliability and precision for this clinical prediction model., Conclusion: An early warning model based on accessible variates from routine clinical tests to predict the mortality of COVID-19 were conducted. This nomogram can be conveniently used to facilitate identifying patients who might develop severe disease at an early stage of COVID-19. Further studies are warranted to validate the prognostic ability of the nomogram., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Shi, Zheng, Wang, Wu, Liu and Liu.)

Background: Despite several previous studies that have explored the predictors of high morbidity in coronary artery disease (CAD) and developed nomograms for CAD patients prior to coronary angiography (CAG), there is a lack of models available to predict chronic total occlusion (CTO). The aim of this study is to develop a risk model and a nomogram for predicting the probability of CTO prior to CAG., Methods: The study included 1,105 patients with CAG-diagnosed CTO in the derivation cohort and 368 patients in the validation cohort. Clinical demographics, echocardiography results, and laboratory indexes were analyzed using statistical difference tests. Independent risk factors affecting the CTO indication were selected using least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis. A nomogram was built and validated based on these independent indicators. The performance of the nomogram was evaluated using area under the curve (AUC), calibration curve, and decision curve analysis (DCA)., Results: LASSO and multivariate logistic regression analysis revealed that 6 variables, including sex (male), lymphocyte percentage (LYM%), ejection fraction (EF), myoglobin (Mb), non-high-density lipoprotein cholesterol (non-HDL), and N-terminal pro-B-type natriuretic peptide (NT-proBNP), were independent predictors of CTO. The nomogram constructed based on these variables showed good discrimination (C index of 0.744) and external validation (C index of 0.729). The calibration curves and DCA demonstrated high reliability and precision for this clinical prediction model., Conclusions: The nomogram based on sex (male), LYM%, EF, Mb, non-HDL, and NT-proBNP could be used to predict CTO in CAD patients, enhancing the ability to predict their prognosis in clinical practice. Further research is needed to validate the efficacy of the nomogram in other populations., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://cdt.amegroups.com/article/view/10.21037/cdt-22-466/coif). The authors have no conflicts of interest to declare., (2023 Cardiovascular Diagnosis and Therapy. All rights reserved.)

In this paper, a closed-form analytical solution of option price under the Bi-Heston model is derived. Through empirical analysis, the advantages and disadvantages of the parametric pricing model are compared and analysed with those of the non-parametric model. The analysis shows that: (1) the parametric pricing model significantly outperforms the machine learning model in terms of in-sample pricing effects, while the Bi-Heston model slightly outperforms the Heston model. (2) In terms of out-of-sample pricing, the machine learning model is inferior to the parametric model for call options, while the Bi-Heston model is significantly better than the other two models for put options, and the other two models are similar. (3) In the robustness analysis of the three pricing models, the machine learning model shows strong instability, while the Bi-Heston model shows a more stable side., Competing Interests: The authors declare no conflict of interest., (© 2022 The Author(s).)

Naproxen (NAP) is a nonsteroidal anti-inflammatory drug which has been widely used and frequently detected in water environments. This study investigated the NAP degradation in the chlorination and UV/chlorine disinfection processes, which usually acted as the last barriers for water treatment. The results showed that both chlorination and UV/chlorine disinfection could remove NAP effectively. At various chlorine dosages (0.1~0.5 mM), the contributions of chlorination and reactive radicals to the degradation of NAP in the UV/chlorine process were calculated to be 50.5~56.9% and 43.1~49.5%, respectively. However, the reactive radicals dominated in NAP degradation in alkaline solutions, while chlorination dominated in acidic conditions. The HCO 3 - (10~50 mM) slightly inhibited, Cl - (10~50 mM) gradually promoted, and HA (1~5 mg/L) significantly reduced NAP degradation by UV/chlorine process. The degradation intermediates and products were obtained via high-performance liquid chromatography with QE-MS/MS; NAP was degraded by demethylation, acetylation, and dicarboxylic acid pathways during the chlorination and UV/chlorination processes.

Intercellular communications play a pivotal role in several cardiac pathophysiological processes. One subtype of extracellular vesicles, so-called exosomes, became known as important intercellular communication mediators in the heart. Exosomes are lipid bilayer biological nanovesicles loaded with diverse proteins, lipids, and mRNAs/microRNAs. All major cardiac cell types can modulate recipient cellular function via the release of exosomes. After myocardial infarction (MI), exosomes, especially those secreted by different cardiac stem cells, have been shown to confer cardioprotective effects, activate regenerative signals, and participate into cardiac repair. In this review, we rapidly recall the biology of exosomes at the beginning. Then we summarize the exosomes secreted by different myocardial cells and their function in cardiac intercellular communication. At last, we discuss the role of these vesicles in cardiac repair after MI.

Purpose: Telomerase activity is associated with cellular immortalization and is present in most human tumors but absent in normal tissues. The activity of telomerase reverse transcriptase (TERT), a catalytic telomerase subunit, correlates with telomerase activity in tumors. The objective of this study was to investigate TERT promoter methylation and its prognostic impact in gastric cancer (GC)., Patients and Methods: The analysis of TERT promoter methylation was performed in tumors and corresponding normal tissues of 116 patients with GC using a highly sensitive Sequenom Epityper assay. The expression of TERT in GC tissues was measured by quantitative real-time polymerase chain reaction., Results: The levels of TERT promoter methylation in GC samples were significantly higher than in normal adjacent tissues (P=0.002). Hypermethylation of TERT promoter was associated with high T-stage (P=0.024), late N-stage (P=0.006), and lymphovascular/neural invasion (P=0.035), without correlation with age, sex, or histological grade. Simple linear regression analysis showed that TERT mRNA correlated positively with TERT methylation (R (2)=0.562, P=0.001). Also, higher TERT mRNA expression was related to hypermethylation of TERT promoter in GC samples (P=0.005). Univariate analysis demonstrated that N-stage (P=0.002) and TERT promoter methylation (P=0.004) were predictive of overall survival. Furthermore, multivariate analysis confirmed that N-stage (P=0.013) and TERT promoter methylation (P=0.031) were independent prognostic indicators for overall survival., Conclusion: Our data suggested that hypermethylation of TERT promoter may contribute to gastric wall invasion, lymph node metastasis, lymphovascular/neural invasion, and poor prognosis in GC. GC patients with hypermethylation of TERT promoter could be eligible for close follow-up.