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It is of great significance to accurately evaluate the end-bearing capacity of rock-socketed piles based on multiple parameters. This study presents a hybrid model coupling extreme gradient boosting (XGBoost) with Bayesian optimization (BO) method for predicting the end-bearing capacity of rock-socketed piles. 138 data samples collected from the literature were used to construct the model. Five parameters, unconfined compressive strength of intact rock σc, geological strength index GSI, pile length within the soil layer Hs, pile length within the rock layer Hr and pile diameter B, are used as the input variables. The BO-XGBoost model was compared with two empirical formulas, as well as random forest (RF), gene expression programming (GEP), back propagation neural network (BPNN) and group method of data handling (GMDH). The results show that the coefficient of determination, root mean squared error and mean absolute error of the hybrid BO-XGBoost model for all datasets are 0.963, 0.634 and 0.240, respectively, and the accuracy order of these models is BO-XGBoost > RF > GEP > BPNN > GMDH > empirical formulas. In addition, the sensitivity analysis results show that σc is the most important parameter for predicting the end-bearing capacity of rock-socketed piles. Highlights: Extreme gradient boosting approach is used for predicting the end-bearing capacity of rock-socketed piles. Bayesian optimization is used to optimize the hyperparameters of the extreme gradient boosting model. Compare the proposed model with two empirical formulas as well as four other artificial intelligence models. [ABSTRACT FROM AUTHOR]

Bond strength is the key factor to determine the strengthening performance of fiber-reinforced polymer (FRP) and concrete, so it is important to establish a bond strength prediction model. To solve the problem that the parameters considered are not comprehensive enough and the accuracy needs to be improved, multivariate adaptive regression splines (MARS) and wavelet neural network (WNN) methods are proposed to estimate the bond strength of concrete confined by FRP. A total of 749 specimens and ten input variables collected from the literature were used to develop the MARS and WNN models. To verify the prediction performance of the proposed models, an improved particle swarm optimization method based on the shrinkage factor method was used to calibrate ten empirical models. The recalibrated empirical models were then compared with MARS and WNN models. The root mean squared error (RMSE), mean absolute error (MAE), coefficient of determination (R2), root relative squared error (RRSE), mean absolute percentage error (MAPE) and integral absolute error (IAE) values of MARS and WNN models were 3.454, 2.635, 0.917, 0.289, 0.153 and 0.127; 3.277, 2.516, 0.925, 0.274, 0.164 and 0.122, respectively, for the training datasets and 3.454, 2.701, 0.94, 0.245, 0.153 and 0.121; 3.652, 2.751, 0.933, 0.259, 0.184 and 0.123, respectively, for the testing datasets. While the RMSE, MAE, R2, RRSE, MAPE and IAE values of the training set and test set of the ten recalibrated empirical models are 7.081–11.293, 4.386–6.994, 0.410–0.701, 0.571–0.807, 0.215–0.306 and 0.212–0.312, respectively. The results show that the accuracy of MARS and WNN models is much higher than that of the ten recalibrated empirical models. [ABSTRACT FROM AUTHOR]

The present study reports the successful fabrication of ZnO/α-Fe 2 O 3 heterojunctions by facile and simple hydrothermal and spin-coating methods. The effect of spin-coating different FeCl 3 precursor layers on the photoelectrochemical performance has been investigated. Additionally, the procedure of spin-coating FeCl 3 precursors was simulated by fluent software. It is noteworthy that ZnO/α-Fe 2 O 3 heterojunctions increase the absorption of visible light, promote the separation and transfer of photogenerated charge carriers, reduce the interfacial resistance between the photoelectrode and electrolyte, and provide a larger electrochemically active contact area in contrast to pure ZnO nanorods. The highest photocurrent density and the highest IPCE (incident photon-to-current efficiency) reach 1.82 mA cm−2 and 40 % respectively when spin-coating three layers. Moreover, the mechanism of enhanced PEC performance was further discussed via EIS (electrochemical impedance spectroscopy), Mott-Schottky curves, Energy band structure diagram, and the electrochemical active surface area (ECSA) test. • ZnO/α-Fe 2 O 3 heterojunctions were synthesized by facile and simple hydrothermal and spin-coating methods. • The fluent simulation was utilized to demonstrate the procedure of FeCl 3 droplet distribution on the ZnO nanorods. • The mechanism of the enhanced photoelectrochemical performance for ZnO/α-Fe 2 O 3 heterojunctions was investigated. [ABSTRACT FROM AUTHOR]

Failure Mode and Effects Analysis (FMEA), as a risk assessment tool for identifying types of failures, their causes and consequences in product design or manufacturing processes, is widely used in various areas to improve the reliability and safety of systems. However, some obvious shortcomings in the traditional FMEA methodology have been exposed in practical applications, such as the neglect of ambiguity and uncertainty in the assessment information, the problem of the same risk priority number (RPN), the lack of relative weights among risk factors, and the neglect of correlation among risk factors. In order to improve these shortcomings, this paper defines the Fermatean fuzzy Z-number (FFZ) by integrating the Fermatean fuzzy set (FFS) and Z-number to express the evaluation information more completely. Meanwhile, a new Fermatean fuzzy Z-number weighted Muirhead mean (FFZWMM) operator is obtained by introducing the Muirhead mean (MM) operator, which is used to aggregate the evaluation information. On this basis, a new FMEA framework based on FFZWMM operator is proposed. Finally, the validity and superiority of the method are verified by applying the method to two numerical cases and conducting a comparative analysis. [Display omitted] • A new Failure Modes and Risk Analysis (FMEA) framework that takes uncertainty into account. • The prioritization of failure risks is more comprehensive and accurate. • A new Fermatean fuzzy Z-number weighted Muirhead mean (FFZWMM) aggregation operator is proposed and derived. • A new Fermatean fuzzy Z-number (FFZ) fuzzy set is proposed and defined. [ABSTRACT FROM AUTHOR]

[Display omitted] • S 2 O 8 2-/Fe2+ and SO 3 2-/Fe2+ processes were compared for pretreating sludge. • SO 3 2- was hardly activated by Fe2+ in sludge for generation SO 4 -•. • Destruction of sludge floc by SO 4 -• facilitated dewatering. • Capillary suction time decreased by 68.4 % following the S 2 O 8 2-/Fe2+ process. • S 2 O 8 2-/Fe2+ efficiently removed the ARGs and coliforms. The remarkable performance of SO 4 -• based advanced oxidation processes in improving waste activated sludge (WAS) dewatering has recently received considerable attention. However, its potential effect on the removal of emerging pollutants is often overlooked. In this study, two types of pretreatment methods (S 2 O 8 2-/Fe2+ and SO 3 2-/Fe2+) were employed to comprehensively evaluate their performance in improving the dewatering of WAS and the removal of antibiotic resistance genes (ARGs) and pathogenic microorganisms. At the optimal dosage of 1.2/1.5 mmol-S 2 O 8 2-/Fe2+/g-VS, the capillary suction time reduction rate of WAS after S 2 O 8 2-/Fe2+ was 1.8 times than that of SO 3 2-/Fe2+. Notably, both S 2 O 8 2-/Fe2+ and SO 3 2-/Fe2+ could remove the 12 types of ARGs identified in WAS. Nonetheless, S 2 O 8 2-/Fe2+ was more effective in removing ARGs, with a range of removal rate (0.96–2.17 log-units), and reduced the propagation and proliferation potential of residual ARGs. Furthermore, the coliforms content in WAS after S 2 O 8 2-/Fe2+ decreased significantly with a minimum of 1.84 ± 0.24 log (MPN/g-TS) compared to SO 3 2-/Fe2+. Further analysis indicated that the redistribution of bound extracellular polymeric substances (EPS) in WAS, especially the variations in protein, was the key factor affecting the dewaterability. In contrast to SO 3 2-/Fe2+, the S 2 O 8 2-/Fe2+ could quickly destroy the EPS structure to release bound water, accelerate the dissociation of WAS flocs, and cause cell lysis and DNA dissolution because of the continuous production and accumulation of SO 4 -• in the hostile conditions inside. Therefore, S 2 O 8 2-/Fe2+ is an efficient, economical, and green method to improve WAS dewatering and the removal of pollutants. [ABSTRACT FROM AUTHOR]

Fiber-reinforced polymer (FRP) is widely used in the field of structural engineering, for example, as a confining material for concrete. The ultimate conditions (i.e., compressive strength and ultimate axial strain) are key factors that need to be considered in the practical applications of FRP-confined concrete cylinders. However, the prediction accuracy of existing confinement models is low and cannot provide an effective reference for practical applications. In this paper, a database containing experimental data of 221 FRP-confined normal concrete cylinder specimens was collected from the available literature, and eleven parameters such as the confining stress, stiffness ratio and strain ratio were selected as the input parameters. Then, a promising machine learning algorithm, i.e., group method of data handling (GMDH), was applied to establish a confinement model. The GMDH model was compared with nine existing models, and the prediction results of these models were evaluated by five comprehensive indicators. The results indicated that the GMDH model had higher prediction accuracy and better stability than existing confinement models, with determination coefficients of 0.97 (compressive strength) and 0.91 (ultimate axial strain). Finally, a convenient graphical user interface (GUI) was developed, which can provide a quick and efficient reference for engineering design and is freely available. [ABSTRACT FROM AUTHOR]

An efficient and widely tunable Si-prism-array coupled terahertz-wave parametric oscillator (TPO) with a very narrow linewidth is demonstrated by using a shallow surface cross-pump configuration. The shallow surface cross-pumping form was realized by totally reflect the pump beam at the THz-wave exit surface. Widely THz-wave tuning range of 0.6–3.9 THz is realized with a 1-mm diameter pump, and the high-frequency end even reached 5.5 THz with a 2-mm diameter pump to increase the nonlinear gain length. The measured Stokes linewidth was 0.07 nm, which is compressed by 70% for that of the conventional TPOs. The highest THz-wave output energy of 2.4 μJ was achieved at 2 THz under 15 mJ pumping, corresponding to an energy conversion efficiency of 1.6 × 10−4. The mechanism of the frequency-selection effect in cross-pumped stimulated polariton scatterings was discussed by calculating the single-pass parametric gain for different phase mismatches. [ABSTRACT FROM AUTHOR]

The coefficient of permeability is the most important parameter for characterizing the permeability characteristics of soil. In this study, a database of the coefficient of permeability (k) for soils was compiled firstly, including effective size (d 10), mean grain size (d 50), the particle diameters at the cumulative percent content of 60% (d 60) and void ratio (e), which can reflect the impact of the particle size distribution characteristics. Gene expression programming (GEP), was employed to develop a predictive equation of k , which is convenient for engineering application. The GEP model was compared with eight empirical models and other artificial intelligence models (i.e., random forest (RF) and group method of data handling (GMDH)). The results show that the GEP model and RF model have the highest accuracy, followed by GMDH model and empirical models. Then, the sensitivity analysis was conducted. According to the results, k increases with increasing d 10 , d 50 and e ; the effective size d 10 has the largest influence on k , followed by d 50 and e , which indicates that fine particle content has the control effect on seepage and the effect of soil gradation parameters on k is greater than that of void ratio. Additionally, the SHAP and PDP analysis were conducted to investigate the feature importance and conditional expectation of each feature. The feature importance order is d 10 > d 50 > e > d 60 , and the SHAP values of d 10 , d 50 and e increase with the increase of them, while the SHAP value of d 60 is basically unchanged. [ABSTRACT FROM AUTHOR]

A modified three-level laser kinetics model for a pulsed high-power optically pumped gas terahertz laser is introduced and used to model the lasing kinetics process of a gas terahertz laser system. We, for the first time to our knowledge, investigated the time evolution dynamics process of the pump intensity, population distribution among the energy levels, pump and THz signal gain coefficient, and the THz laser intensity within the pulsed D2O gas THz laser. High-power THz pulse with peak power of about 7.4 kW and pulse width of 145 ns at wavelength of 385 μm were obtained in the simulation, using an incident pump pulse with peak power of 2.2 MW and pulse width of 110 ns. THz pulse delay of 40 ns and pulse broadening of 35 ns were quantitatively analyzed. In addition, the experimental results for the pulse profile, pulse width, pulse broadening, pulse energy, and peak power are in agreement with the theoretical simulation results. [ABSTRACT FROM AUTHOR]

• A group method of data handling (GMDH) technique is proposed to predict the effective thermal conductivity of rock. • The effective thermal conductivity changes in three stages with the increase of pressure, including the weak nonlinear increase trend, nonlinear stage and stable stage. • These existing models can only reflect the effect of temperature on the thermal conductivity, while the GMDH model can reflect the effects of more parameters (e.g., temperature, pressure, porosity and density). • A graphical user interface (GUI) of calculating the effective thermal conductivity of rock is established for practical application. The effective thermal conductivity of rock (ETCR) is widely used in the field of geology engineering. However, the ETCR is influenced by various factors, and the determination of ETCR is difficult. This paper presents a group method of data handling (GMDH) technique to predict the ETCR. Totally 270 measurements containing four input variables (i.e., temperature T , pressure P , porosity n and density ρ) were collected. A GMDH model of rock thermal conductivity was proposed based on this database, with R2 and RMSE values of 0.940 and 0.126. In addition, several existing models are employed to compare with the GMDH model. According to the results, these models have similar change tendency. However, these existing models can only reflect the effect of temperature on the ETCR, while the GMDH model can reflect the effects of more parameters. Moreover, a sensitivity analysis was performed. The results indicate that this model can well characterize the coupling relationship between the ETCR and two main parameters, i.e., temperature and pressure. The predicted ETCR increases with the increase of pressure, while it decreases with the increase of temperature. Finally, a graphical user interface (GUI) was established for practical application. [ABSTRACT FROM AUTHOR]

This study presents two approaches (i.e., the material point method (MPM) and gene expression programming (GEP)) for prediction of landslide runout. The MPM was modified based on a strain-softening constitutive model. A collapse test and physical model test were conducted to verify the suitability of the modified MPM. The sensitivity analysis was performed to investigate the importance of the softening parameters on the motion characteristics and final accumulation state. In addition, a predictive equation for prediction of the maximum horizontal distance was proposed based on GEP, with the coefficient of determination of 0.8825. The effects of the maximum vertical distance, landslide volume and landslide posture on the maximum horizontal distance were quantitatively analyzed. Moreover, the GEP model was verified by comparison with other machine learning approaches. Finally, taking the Jiweishan landslide as an example, the simulation and prediction results obtained from the MPM and GEP approaches were compared. The results show that the two are both within a reasonable range, with the errors of 14.1% and 10.6%, respectively. [ABSTRACT FROM AUTHOR]

Gears are important mechanical components for power transmissions. Tooth wear is one of the most common failure modes, which can present throughout a gear’s lifetime. It is significant to accurately monitor gear wear progression in order to take timely predictive maintenances. Motor current signature analysis (MCSA) is an effective and non-intrusive approach which is able to monitor faults from both electrical and mechanical systems. However, little research has been reported in monitoring the gear wear and estimating its severity based on MCSA. This paper presents a novel gear wear monitoring method through a modulation signal bispectrum based motor current signal analysis (MSB-MCSA). For a steady gear transmission, it is inevitable to exist load and speed oscillations due to various errors including wears. These oscillations can induce small modulations in the current signals of the driving motor. MSB is particularly effective in characterising such small modulation signals. Based on these understandings, the monitoring process was implemented based on the current signals from a run-to-failure test of an industrial two stages helical gearbox under a moderate accelerated fatigue process. At the initial operation of the test, MSB analysis results showed that the peak values at the bifrequencies of gear rotations and the power supply can be effective monitoring features for identifying faulty gears and wear severity as they exhibit agreeable changes with gear loads. A monotonically increasing trend established by these features allows a clear indication of the gear wear progression. The dismantle inspection at 477 h of operation, made when one of the monitored features is about 123% higher than its baseline, has found that there are severe scuffing wear marks on a number of tooth surfaces on the driving gear, showing that the gear endures a gradual wear process during its long test operation. Therefore, it is affirmed that the MSB-MSCA approach proposed is reliable and accurate for monitoring gear wear deterioration. [ABSTRACT FROM AUTHOR]

We demonstrate a terahertz-wave parametric oscillator (TPO) with an asymmetrical porro-prism (PP) resonator configuration, consisting of a close PP corner reflector and a distant output mirror relative to the MgO:LiNbO crystal. Based on this cavity, frequency tuning of Stokes and the accompanied terahertz (THz) waves is realized just by rotating the plane mirror. Furthermore, THz output with high efficiency and wide tuning range is obtained. Compared with a conventional TPO employing a plane-parallel resonator of the same cavity length and output loss, the low end of the frequency tuning range is extended to 0.96 THz from 1.2 THz. The highest output obtained at 1.28 THz is enhanced by about 25%, and the oscillation threshold pump energy measured at 1.66 THz is reduced by about 4.5%. This resonator configuration also shows some potential to simplify the structure and application for intracavity TPOs. [ABSTRACT FROM AUTHOR]

This study presents an artificial intelligence approach, namely multi expression programming (MEP), for determining ultimate bearing capacity of shallow foundations on cohesionless soils. Five governing parameters (i.e., internal friction angle, soil unit weight, the length to width ratio of foundation, foundation depth and foundation width) were used as input variables to develop the MEP model. Through the determination of the optimal parameter setting of MEP, a group of expressions were proposed. Then, the MEP model was compared with linear multiple regression, non-linear multiple regression and several previous models, and three statistical indices (i.e., coefficient of determination (R 2), root mean squared error (RMSE) and mean absolute error (MAE)) were employed to evaluate the prediction accuracy of these models. The results show that the proposed model has higher prediction precision than the other models, with higher R 2 value and lower RMSE and MAE values. Additionally, a monotonicity analysis was performed to verify the correct relationship between ultimate bearing capacity and various factors. From the monotonicity analysis, the ultimate bearing capacity increases with the increase of internal friction angle (φ), soil unit weight (γ), foundation width (B) and foundation depth (D), whereas it decreases with the increase of the length to width ratio of foundation (L/B). Then, a sensitivity analysis was performed. Through the sensitivity analysis, the effect rank of the five input parameters on ultimate bearing capacity is φ > B > D > γ > L/B. Finally, a graphical user interface (GUI) of the MEP model is developed for practical application. [ABSTRACT FROM AUTHOR]

This study presents a gene expression programming (GEP) method for determining soil thermal conductivity (k). A large and reliable database containing 444 thermal conductivity measurements was collected and employed to develop the GEP model. Four governing parameters (i.e., porosity, saturation degree, quartz content and temperature) were selected as inputs based on a Pearson correlation analysis. Through the determination of the optimal parameter setting of GEP, a predictive equation was first proposed. Then, the proposed GEP model was evaluated and compared with several previous models. The results indicate the proposed GEP model has higher prediction precision than the other models. In addition, a monotonicity analysis was performed to validate the rationality of the proposed GEP model. According to the monotonicity analysis results, the soil thermal conductivity increases with the increase of saturation degree, quartz content and temperature, and it decreases with the increasing of the porosity. Finally, a parametric analysis was conducted to investigate the significance of the inputs. The results show that the effect rank of these four input variables on soil thermal conductivity is saturation degree > porosity > temperature > quartz content, which can provide a reference for similar projects. [ABSTRACT FROM AUTHOR]

Sludge management represents a critical challenge because of complex compositions and poor dewaterability. Fe2+-activated persulfate oxidation (Fe2+/S 2 O 8 2−) is an effective, and widely investigated method for enhancing sludge dewatering. However, the potential effects of Fe2+/S 2 O 8 2− on sludge drying efficiency, anaerobic biodegradation behaviors and potential recycling of sludge residua are not yet well-known. In this study, a new sludge disposal route (step i: enhanced dewatering via Fe2+/S 2 O 8 2−, and step ii: drying-incineration or anaerobic digestion) was proposed and appraised comprehensively. Results showed that Fe2+/S 2 O 8 2− oxidation destroyed extracellular polymeric substances, lysed sludge cells and enhanced the dewaterability greatly. Capillary suction time and mechanical filtration time at 2.0/1.6 mmol-Fe2+/S 2 O 8 2−/g-VS decreased by 88.0% and 79.6%, respectively. Moreover, 89.8% of micro-pollutants (e.g., methylbenzene, ethylbenzene, p -m-xylene and o -xylene) in sludge were removed. Besides, the pretreatment was able to alter sludge drying behaviors and methane-producing potential. Pretreated sludge exhibited faster drying rate and shorter lag-time for methane production. Incineration residua of dewatered sludge could be re-coupled with S 2 O 8 2− as the conditioner to enhance sludge dewaterability, thereby reducing the chemical input and disposal cost. This study provides a novel, self-sustainable strategy for sludge management, reutilization and final safe disposal. • A comprehensive sludge treatment route was proposed. • The capillary suction time of sludge was reduced by 87.9% within 1 min. • Fe2+/S 2 O 8 2− pretreatment efficiently removed micro-pollutants. • Fe2+/S 2 O 8 2− pretreatment reduced mechanical filtration and drying time. • Sludge ash can replace Fe2+ to activate S 2 O 8 2− for improving sludge dewaterability. [ABSTRACT FROM AUTHOR]

[Display omitted] • DMC-activated PDS oxidation was used to pretreat sludge. • Pretreatment promoted the dissolution of intracellular polymers. • Methane productivity was notably enhanced by pretreatment. • Modified Gompertz model was used to simulate biodegradation kinetics. The potential of disordered mesoporous carbon (DMC) as catalyst of peroxydisulfate (PDS) to improve sludge solubilization and methane production was investigated. Results showed that DMC activated PDS (DMC/PDS) to produce sulfate radicals (SO 4 −), facilitating cells rupture and sludge matrix dissociation by degrading the carbonyl and amide groups in organic biopolymers (especially proteins, polysaccharides and humus). At the optimal DMC/PDS dosage of 0.04/1.2 g-mmol/g-VS, SCOD was increased from initial 294.0 to 681.5 mg/L, with the methane production rate of 12.6 mL/g-VS/day. Moreover, DMC could serve as electron mediator to accelerate electron transfer of microorganisms, building a more robust anaerobic metabolic environment. Modelling analysis further demonstrated the crucial role of DMC/PDS pretreatment in biological degradation and methane productivity. This study indicated that DMC/PDS pretreatment can prominently enhance the release of soluble substances and methane production, aiding the utilization of PDS oxidation technology for improving anaerobic bioconversion of sludge. [ABSTRACT FROM AUTHOR]

This paper presents two artificial intelligence techniques (e.g., gene expression programming (GEP) and random forest (RF)) for predicting the bond strength of near-surface-mounted (NSM) fiber-reinforced polymer (FRP) strips or rods bonded to concrete. Experimental data from 145 direct pullout tests collected from the literature and five parameters, namely, the bond length, FRP axial rigidity, groove depth-to-width ratio, epoxy tensile strength, and concrete compressive strength, were used to develop the GEP and RF models. A comparison was conducted between the proposed GEP and RF models and two existing empirical models, namely, Seracino's model and Zhang's model, and six statistical indices were used to evaluate the performance of these four models. The results show that the proposed GEP and RF models had higher coefficient of determination (R2) values and lower root mean squared error (RMSE), mean absolute error (MAE), root relative squared error (RRSE), mean absolute percentage error (MAPE), and integral absolute error (IAE) values than the two existing empirical models. Finally, a detailed parametric study was conducted to investigate the influence of each input variable on the bond strength. The results showed that the bond strength increased with increasing bond length, FRP axial rigidity, groove depth-to-width ratio, and concrete compressive strength, while the epoxy tensile strength had little effect on the bond strength. [ABSTRACT FROM AUTHOR]

The paper proposes and verifies a small-angle measurement method based on the defect spot mode of the position-sensitive detector (PSD). With the output characteristics of the PSD in the defect spot mode and the size transformation properties of a focused beam, the measurement sensitivity can be significantly improved. Calibration experiments with the piezoelectric transducer (PZT) indicate that compared with the current PSD-based autocollimation method, the proposed method can improve the sensitivity of small-angle measurement by 57 times, and the measurement sensitivity of the proposed method can be further improved by optimizing the system parameters, while the proposed method has the advantages of a simple system and high real-time performance. Therefore, the proposed method is expected to be used in high-precision motion error detection, as well as in shape and position measurement. [ABSTRACT FROM AUTHOR]

Fischer–Tropsch (F–T) fuel, synthesized from coal-to-liquid (CTL), is an alternative fuel with clean and efficient characteristics. In this study, a surrogate fuel model was developed, including n-dodecane (n-C12H26) and iso-octane (i-C8H18), which represents the n-alkane and iso-alkane in F–T fuel synthesized from CTL, respectively. The proportions of the components in the surrogate fuel are determined by the characteristics of the practical fuel, including cetane number (CN), C/H ration and component composition. For the establishment of the skeletal mechanism model, firstly, based on a two-step direct relationship graph (DRG) and the computational singular perturbation (CSP) importance index method, a reduced model of n-dodecane was developed involving 159 species and 399 reactions, while the detailed n-dodecane mechanism consists of 1279 species and 5056 reactions. Then, the n-dodecane skeletal mechanism was constructed based on a decoupling methodology, involving the skeletal C12 mechanism from the reduced mechanism, a C2-C3 sub mechanism and a detailed H2/CO/C1 sub mechanism. Finally, the skeletal mechanism for the F–T surrogate fuel was developed, including the n-dodecane skeletal mechanism and an iso-octane macromolecular skeletal mechanism. The final mechanism for the F–T diesel surrogate fuel consists of 169 species and 406 reactions. The n-dodecane skeletal mechanism and iso-octane skeletal mechanism were validated on various fundamental experiments, including the ignition delay in shock tubes, the primary species concentrations in jet-stirred reactors and the premixed laminar flame over wide operating conditions, which show great agreement between the predictions and measurements. Moreover, an F–T surrogate fuel mechanism was employed to simulate the combustion characteristics of an engine using computational fluid dynamics (CFD). The results show that the mechanism can predict the performance of F–T fuel combustion in engine accurately. [ABSTRACT FROM AUTHOR]

Gears are important components of the transmission system. Tooth wear and bearing clearance are significant factors affecting the dynamics of the gear system. In order to reveal the effects of gradual wears and bearing clearance on the gear system dynamics, a six-degrees-of-freedom bending-torsion coupled model of gear-rotor-bearing which considers surface wear, bearing clearance and backlash is established. The Rung-Kutta method is used to solve the nonlinear dynamic system, and the dynamic responses of the system are obtained. The results show that the time-varying mesh stiffness decreases with the tooth surface from the unworn phase to severe wear phase. At the same time, the change of the mesh stiffness in the double-tooth mesh area and single-tooth area are different. Moreover, the amplitude of the X-displacement, Y-displacement and relative gear mesh displacement will be enlarged slightly with the increase of wear depth or bearing clearance. By analyzing variation tendency in the frequency domain, the different order harmonics show the different change characteristic with the variation of the wear phases or bearing clearances. This study provides a theoretical basis for improving the transmission performance and the selection of the bearing clearances in the gear system. [ABSTRACT FROM AUTHOR]

[Display omitted] • Mineral-activated perxymonosulfate (PMS) shows dewaterability and triclosan removal. • Iron-rich minerals are more economical than traditional sources of Fe2+. • Rheological test demonstrates that siderite/PMS can promote sludge fragmentation. • Siderite could release Fe2+ more sustainably to persistently produce free radicals. High water and pharmaceutical and care products (PPCPs) bounded in sludge flocs limit its utilization and disposal. The advanced oxidation process of perxymonosulfate (PMS) catalyzed by iron salts has been widely used in sludge conditioning. In this study, two iron-rich minerals pyrite and siderite were proposed to enhance sludge dewatering performance and remove the target contaminant of triclosan (TCS). The permanent release of Fe2+ in the activation of PMS made siderite more effective in enhancing sludge dewater with capillary suction time (CST) diminishing by 60.5 %, specific resistance to filtration (SRF) decreasing by 79.2 %, and bound water content (BWC) dropping from 37.1 % to 2.6 % at siderite/PMS dosages of 0.36/0.20 mmol/g-TSS after 20 min of pretreatment. Pyrite/PMS performed slightly inferior under the same conditions and the corresponding CST and SRF decreased by 51.5 % and 71.8 % while the BWC only declined to 17.8 %. Rheological characterization was employed to elucidate the changes in sludge dewatering performance, with siderite/PMS treated sludge showing a 48.3 % reduction in thixotropy, higher than 28.4 % of pyrite/PMS. Oscillation and creep tests further demonstrated the significantly weakened viscoelastic behavior of the sludge by siderite/PMS pretreatment. For TCS mineralization removal, siderite/PMS achieved a high removal efficiency of 43.9 %, in comparison with 39.9 % for pyrite/PMS. The reduction in the sludge solids phase contributed the most to the TCS removal. Free radical quenching assays and EPR spectroscopy showed that both siderite/PMS and pyrite/PMS produced SO 4 -· and ·OH, with the latter acting as the major radicals. Besides, the dosage of free radicals generated from siderite/PMS exhibited a lower time-dependence, which also allowed it to outperform in destroying EPS matrix, neutralizing the negative Zeta potential of sludge flocs, and mineralizing macromolecular organic matter. [ABSTRACT FROM AUTHOR]

Highlights • A high efficient, high power gas THz laser based on L-shaped cavity is present. • THz output performance was investigated both in theory and experiment. • The optimum output coupling is 0.8 and the optimum gas pressure is 500 Pa. • The maximum THz pulse energy is 8.4 mJ under the pumping energy of 1.6 J. Abstract A high power gas terahertz laser based on L-shaped cavity was demonstrated. We, for the first time, investigated the output performances of D 2 O gas 385 μm THz laser by optimizing the output coupler transmittance of the L-shaped cavity both in theory and experiment. Under the pump energy of 1.6 J, the optimum output coupler transmittance was about 0.78 and the optimum gas pressure was about 500 Pa. Up to 8.4 mJ pulse energy at 385 μm was achieved at output coupler transmittance of 0.8, corresponding to a photon conversion efficiency of 43.7%. Pulse width of 120 ns, and beam quality factor M2 of 1.58 were obtained at the highest output energy. In addition, the experimental results are in agreement with the theoretical simulation results. [ABSTRACT FROM AUTHOR]

Highlights • Gradient doses of ciprofloxacin were used to generate the resistant strain in vitro. • Acetylation was compared between resistant and susceptible Salmonella strains. • Protein acetylation was identified as associated with Salmonella drug resistance. • 14 drug resistance-related proteins were differentially acetylated in the two strains. Abstract Salmonella are becoming increasingly resistant to fluoroquinolones (FQs), therefore determining the resistance mechanism is very important. Recent studies have shown that protein post-translational modifications (PTM) play a role in bacterial antibiotic resistance. One such type of PTM, lysine acetylation, is a reversible and highly regulated PTM which has been found to be associated with antibiotic resistance in Mycobacterium and Acinetobacter species. Salmonella Typhimurium are major zoonotic pathogens, which are becoming increasingly resistant to FQs, the antibiotics of choice where therapy is indicated. To date, however, there have been no studies on the relationship between PTM and drug resistance in Salmonella. Therefore, in the present study, ciprofloxacin-resistant and susceptible strains of Salmonella were used as the research objects, and tandem mass tag labeling and acetylation enrichment techniques were used to screen for the different expression of actylated proteins between the two strains, and for quantitative and bioinformatics analysis. We identified a total of 631 acetylated proteins involving 1259 lysine acetylation sites. Among the quantified sites, compared with the susceptible strain, the expression of lysine acetylation was upregulated for 112 sites and downregulated for 149 sites in the resistant strain. Bioinformatic analyses showed that the main enrichment pathways for these differentially acetylated proteins are microbial metabolic process, biosynthesis of antibiotics, and bacterial chemotaxis. Among the differentially acetylated proteins, 14 proteins related to bacterial antibiotic resistance were identified (excluding metabolic and virulence-related proteins), and the lysine acetylation expression of these proteins was significantly different between the resistant and susceptible strains. These results indicated that protein lysine acetylation is not only related to metabolism and virulence, but also to antibiotic resistance. The results provide an important basis for in-depth studies of the relationship between protein lysine acetylation and bacterial antibiotic resistance. [ABSTRACT FROM AUTHOR]

Gear wear is a common fault that occurs in a gear transmission system that degrades the operating efficiency and may cause other catastrophic failures such as tooth breakage and fatigue. The progressive wear of a helical gear and its influences on vibration responses are rarely investigated due to the combined effects of the complicated lubrication state and the time-varying characteristic. To fill this gap, a numerical study was put forward to investigate the interactions between gear wear and dynamic response. In this study, an Archard's wear model with elastohydradynamic lubrication (EHL) effect is adopted to simulate the helical gear wear, which is incorporated with an eight-degree of freedom dynamic model for understanding the gear dynamic at different wear degrees. The wear model shows that the gear wear mainly happens at the gear root due to the relative high slide-to-roll ratio. The dynamic modelling results demonstrate that the wear causes a reduction in time-varying gear mesh stiffness further leads to more vibration. Besides, the simulated vibration responses and experimental validation show that the wear cause increases in the amplitudes of the gear mesh frequency and its harmonics, which can reflect the evolution of progressive gear wear and can be used as monitoring features of gear wear. [ABSTRACT FROM AUTHOR]

Vehicles are subject to a variety of road unevenness and random road excitations that potentially cause the vehicle to undergo a significant amount of energy dissipation, while compromising energy efficiency. This paper focuses on designing a novel piezoelectric energy harvester and aims to assess the energy harvesting potential, from the vehicle suspension, under random and pulse road excitations. To describe the energy harvesting process, a dual‐mass suspension system vibration model of a light electric logistics vehicle, equipped with a piezoelectric energy harvester, is developed. Various parameters, such as driving speed, ratio of the moment arms of the lever, and piezoelectric material cross‐sectional area, are included in the model, for basic harvesting energy. The root mean square (RMS) value of harvested power, in the case of random road, is up to 18.83 W, while the maximum respective value, in the case of pulse road, is 102.24 W and is obtained at 30 km/h. The harvested electricity is very valuable and useful, as it can be used to power automotive electrical equipment. The results of this paper provide an important reference frame for future research, related to energy harvesting from vehicle suspension. [ABSTRACT FROM AUTHOR]

Fluid flow in fractures partially filled with porous media is commonly encountered in engineering and scientific research, yet understanding of its nonlinear seepage characteristics remains limited. In this study, we employed 2D numerical simulations, utilizing the Navier-Stokes and Darcy-Brinkman-Forchheimer equations to model free and seepage flow in unfilled and filled fracture regions, respectively. By conducting free-seepage flow coupling simulations, we systematically investigated the effects of filling degree, shape, and porous media properties (intrinsic permeability and porosity) on fluid motion characteristics in partially filled fractures. Our results reveal that filling media reduces the main flow region width and enhances nonlinear seepage development, with the non-Darcy effect becoming more pronounced as the filling degree increases and permeability decreases. Due to the influence of the filling medium, the location of the maximum velocity in the fracture is not at the center of the smallest free-flow channel, but rather in a region further back from that position. With the increase of inertia effect, the recirculation zone (RZ) exhibits a complex evolution influenced by the permeability characteristics, with high-permeability filling media initially increasing RZ volume before decreasing (or no RZ is formed), while low-permeability media leads to a gradual increase in RZ volume. Moreover, we developed a novel nonlinear seepage model to evaluate non-Darcy effects in partially filled fractures, incorporating viscous and inertial permeabilities (with R2 = 0.942, 0.988) obtained via gene expression programming (GEP) based on 432 data sets (from 12,528 simulations). [ABSTRACT FROM AUTHOR]

An efficient cavity oscillator for a 192-μm pulsed laser radiation is presented when pumped with a transverse excited atmospheric (TEA) CO laser. A maximum power of 7.1 kW is achieved from a 100-cm cavity. The oscillation behavior of the 192-μm laser has resulted in an increase in energy of 45 % as compared with a mirror-less process and an energy conversion efficiency of 0.1 %. Oscillation characteristics are discussed including the pulse width and time delay. The laser spot size is measured according to the knife-edge scan technique while the output beam quality M factor is about 1.33. [ABSTRACT FROM AUTHOR]

This paper presents an online method for the assessment of the dynamic performance of the chassis frame in a heavy-duty dump truck based on a novel stochastic subspace identification (SSI) method. It introduces the use of an average correlation signal as the input data to conventional SSI methods in order to reduce the noisy and nonstationary contents in the vibration signals from the frame, allowing accurate modal properties to be attained for realistically assessing the dynamic behaviour of the frame when the vehicle travels on both bumped and unpaved roads under different operating conditions. The modal results show that the modal properties obtained online are significantly different from the offline ones in that the identifiable modes are less because of the integration of different vehicle systems onto the frame. Moreover, the modal shapes between 7 Hz and 40 Hz clearly indicate the weak section of the structure where earlier fatigues and unsafe operations may occur due to the high relative changes in the modal shapes. In addition, the loaded operations show more modes which cause high deformation on the weak section. These results have verified the performance of the proposed SSI method and provide reliable references for optimizing the construction of the frame. [ABSTRACT FROM AUTHOR]

An efficient pulsed CHF mirror-less cavity is presented. The output energy of the 192 μm far-infrared emission is studied as a function of gas pressure, cell length, and the pump intensity. Maximum pulse energy of 0.4 mJ is achieved from a 185-cm long gas cell at 6 Torr, and the photon conversion efficiency is 2.5 %. Characteristics of this mirror-less system and possibilities for higher output energy are also discussed. [ABSTRACT FROM AUTHOR]

[Display omitted] • CH 4 generation reached 298.0 mL/L/d at −1.0 V vs. Ag/AgCl with η CE of 75.8%. • Moderate EPS played a curial role in aggregation and stability of biofilm. • hdrA , ehaA , and ehbC were putative genes for direct extracellular electron transfer. • Potential extracellular electron transfer pathway for CH 4 formation was proposed. Bioeletromethanogenesis, as a cutting-edge option to capture CO 2 and produce multi-carbon biofuels, has received extensive attraction. However, how electroactive biofilm (EAB) as the biocatalyst drives CO 2 electromethanogenesis is still not well recognized. In this study, a two-chamber bioelectrochemical cell equipped with a hybrid skirt-shaped cathode was constructed and the electrocatalytic performance of EAB and the electron shuttling mechanisms involved in extracellular electron transfer (EET) were systematically studied. The EAB colonizing on biocathode showed an excellent cathodic electrocatalytic activity and the minimum charge transfer resistance. The CH 4 production rate of 298.0 ± 46.7 mL/L/d was obtained at the cathodic potential of −1.0 V vs. Ag/AgCl with the highest Coulombic efficiency of 75.8 ± 9.9%. The gel-like extracellular polymeric substances, secreted by EAB, facilitated the adhesion/aggregation of microbes and EAB development. Further analysis suggested that CO 2 electromethanogenesis exhibited a positive association with Methanobacterium (54.4%) in EAB. Moreover, metagenome analysis confirmed the presence of direct EET-related genes (i.e., hdrA , ehaA , and ehbC), which accelerated the formation of corresponding functional protein complexes (particularly heterodisulfide reductase A, HdrA) and electron exchange. The mechanism for electron shuttling process in catalyzing CO 2 electromethanogenesis was further proposed. This study provides a new insight into direct extracellular electron transfer (DEET) mechanisms of CO 2 electromethanogenesis, and is useful for promoting EAB electrocatalytic activities and CO 2 emission reduction and reuse. [ABSTRACT FROM AUTHOR]

Purified terephthalic acid (PTA) wastewater with properties of poor biodegradation and high toxicity is produced from refining and synthesis of petrochemical products. In this study, a lab-scale hollow fiber membrane bioreactor (HF-AnMBR) fed with synthetic PTA wastewater was operated over 200 days with stepwise decreased hydraulic retention time (HRT) to investigate the long-term performance, membrane fouling mechanism and microbial community evolution. Results showed that a stable chemical oxygen demand (COD) removal rate of 65.8 ± 4.1% was achieved at organic loading rate of 3.1 ± 0.3 g-COD/ L -reactor/d and HRT 24 h, under which the methane production rate reached 0.33 ± 0.02 L/ L -reactor/d. Further shortening HRT, however, led to the decreased COD removal efficiency and low methane bioconversion. A mild membrane fouling occurred due to the production of colloidal biopolymers and the interaction between increased colloidal substances secreted/cracked by microorganisms and membrane interface. Further 16S rRNA analysis indicated that microbial diversity and richness had changed with the variation of HRT while Methanosaeta, and Methanolinea species were always the dominant methanogens responsible for methane production. The results verify that HF-AnMBR is an alternative technology for PTA wastewater treatment along with energy harvesting, and provide a new avenue toward sustainable petrochemical wastewater management. [Display omitted] • Pollutant removal and biogas production decreased as HRT was decreased. • The optimum HRT was proved to be 24 h when considering methane production. • Membrane fouling was closely related with biomass characteristics. • The dominant methanogens were identified as Methanoseata and Methanolinea. [ABSTRACT FROM AUTHOR]

A bioelectrochemical anammox system (BEAnS) was constructed and operated at low temperature to investigate the effect of weak electrical stimulation (continuous or intermittent) on metabolism behaviors, electrochemical activity, nitrogen removal, and spatial distribution of anammox biofilms. Results showed that the continuously stimulated biocathode exhibited the highest electron transfer system activity (34.2 ± 6.9 μg mg−1 h−1), the fastest electron transfer coefficient (0.0412 s−1), the largest current density (0.25 A cm−2), and the smallest polarization resistance (∼4 Ω). This led to an enhanced nitrogen removal of 60.6 ± 5.6% and energy recovery of 289.1 mW m−3, compared with that of the control. Confocal laser scanning microscopy and fluorescence in situ hybridization analysis confirmed that continuous weak electrical stimulation could accelerate the secretion of extracellular polymer substances, which facilitated the aggregation/adhesion of single cell and subsequent development of compact and stratified co-existing biofilms on cathode. Microbial analysis further demonstrated the proliferation of electrotrophic denitrifying microorganisms (i.e., Thauera , Hydrogenophaga , and Ignavibacterium), nitrifier (Candidatus_Nitrotoga), and denitrifier (Denitratisoma), except for anammox bacteria (i.e., Candidatus_Brocadia , and Candidatus_Jettenia), implying the critical role of weak electrical stimulation in diversifying N-degrading microbial community and creating a more robust nitrogen metabolic pathway. These findings can provide a novel insight into autotrophic electroactive anammox biofilm enrichment and their activity enhancement by weak electrical stimulation. [Display omitted] • Constructing an electro-anammox system to explore weak electrical stimulation. • Verifying a positive impact of continuous stimulation on microbial activity. • Visualizing the spatial structure of a co-existing cathode biofilm. • Revealing a synergetic electrotrophic bacteria in biocathode for nitrogen removal. [ABSTRACT FROM AUTHOR]

The stabilization and disposal of the large amounts of sewage sludge pose a worldwide challenging problem. To solve this problem, the technical feasibility of coupled alkali-microwave–H 2 O 2 –oxidation pretreatment with in-situ bioelectrochemical regulation was used for enhancing sludge biodegradability and methane productivity. The optimum condition of the combined pretreatment was pH 10.0 ± 0.1, microwave 700 W and H 2 O 2 0.4 g/g TS. In this case, soluble chemical oxygen demand (SCOD) of pretreated sludge was increased from initial 330.9 ± 10.0 to 3328.8 ± 49.6 mg/L. The highest accumulative methane yield of 234.3 mL CH 4 /g VS was obtained for pretreated sludge at the cathodic potential of −0.8 V vs. Ag/AgCl, increasing by 4.3-, and 1.9-fold compared with the raw and pretreated sludge, respectively. The microbial community analysis further provided a compelling evidence that bioelectrochemical regulation stimulated the growth of the functional microorganisms, especially in protein-degrading (Firmicutes), polysaccharides-utilizing (Chloroflexi), electroactive (Geobacter , and Desulfomicrobium) and methane-producing (Methanobacterium) microorganisms. In addition, pH adjustment of pretreated sludge by addition of H 2 SO 4 could further enrich the abundance of microbial community and build a strong syntrophic interaction, accordingly provoking the hydrolysis and subsequent methane production. The result of this study will contribute to the establishment of an efficient sludge stabilization and bioenergy recovery strategy. [Display omitted] • Alkali-MW–H 2 O 2 –oxidation pretreatment can enhance sludge solubilization • Methane yield increased by 4.3-fold via Bioelectrochemical regulation • Bioelectrochemical regulation enhanced syntrophic interaction of organisms • pH adjustment by addition of H 2 SO 4 enriched the microbial community • Internal mechanism of bioelectrochemical process was proposed [ABSTRACT FROM AUTHOR]