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Transition-metal phosphides have been investigated for microwave absorption applications owing to their excellent conduction loss and magnetic property. In this study, novel composites comprised of porous Al 2 O 3 matrix loaded with Fe x Co y P (Fe x Co y P/Al 2 O 3) were prepared by vacuum impregnation, hydrothermal, and low-temperature phosphatizing methods. The experimental results show that Fe x Co y P is uniformly deposited on the surface of porous Al 2 O 3 ceramic, and the Fe x Co y P transforms from needle-like to particle-like structures as the Fe/Co ratio increases from 1:3 to 3:1. The minimum reflection loss (RL min) of FeCo 3 P/Al 2 O 3 composite reaches −26.19 dB at 12.4 GHz with a matching thickness of 2.6 mm, and the maximum effective absorption bandwidth (EAB) achieves 4.2 GHz in the whole X-band at 3.2 mm thicknesses. This study confirmed that the porous Fe x Co y P/Al 2 O 3 composites are potential candidates for microwave absorption applications, and their microwave absorption properties can be enhanced by adjusting the ratio of Fe to Co. [ABSTRACT FROM AUTHOR]

Hydrogen technology is widely considered a novel clean energy source, and electrolysis is an effective method for hydrogen evolution. Therefore, efficient hydrogen evolution reaction (HER) catalysts are urgently needed to replace precious metal catalysts and meet ecological and environmental protection standards. Herein, Ni–Mn–P electrocatalysts are synthesized using facile electrodeposition technology. The influence of the Mn addition on the catalytic behavior is studied by the comprehensive analysis of catalytic performance and morphology of the catalysts. Among them, the Ni–Mn–P0.01 catalyst exhibits small coral-like structures, greatly improving the adsorption and desorption of hydrogen ions and reducing the overpotential hydrogen evolution. Consequently, overpotential at 10 mA cm−2 electric current density is 113 mV, and the value of the Tafel slope achieves 74 mV/dec. Furthermore, the Ni–Mn–P catalyst shows long-time (20 h) stability at current densities of 10 and 60 mA/cm2. The results confirm that the synergistic effect of Ni, Mn, and P accelerates the electrochemical reaction. Meanwhile, the addition of manganese element can change the micromorphology of the catalyst, thereby exposing more active sites to participate in the reaction, enhancing water ionization, improving the catalytic performance. This study opens a new way toward improving the activity of the catalyst by adjusting Mn concentration during the electrodeposition process. [Display omitted] • Ni–Mn–P electrocatalysts are synthesized by facile electrodeposition technology. • 3D spherical microstructure Ni–Mn–P catalyst can be formed. • 3D spherical microstructure improves the adsorption and desorption of hydrogen ions. • Ni–Mn–P catalyst improves the hydrogen evolution reaction and longtime stability. [ABSTRACT FROM AUTHOR]

In present work, the creep rupture life of 9% Cr heat-resistant steel (P91) was evaluated based on the creep cavitation modelling. At 873 K, a series of creep rupture tests were carried out under the stresses of 140–190 MPa to achieve several sets of ruptured specimens. The constrained and unconstrained models of cavity growth were introduced to investigate the creep behaviour of P91 steel. The obtained results showed that the rupture mechanism of these specimens was mainly attributed to the ductile rupture under the present creep conditions. Besides, reasonable extrapolations were calculated to predict the creep rupture life of P91 steel by combining different constitutive equations with the cavity growth model. It suggested that the model predictions with constraints were better than those with unconstrained conditions. In particular, the Sinh equation based constrained cavity model shows greater potential in predicting the long-term creep life of P91 steel. [ABSTRACT FROM AUTHOR]

The present work deals with the microstructure evolution during creep of P91 steel. In particular, the changes of prior austenite grain (PAG) and low-angle grain boundary (LAGB) during creep were studied using the electron backscatter diffraction (EBSD). Firstly, a series of crept specimens of P91 steel were prepared at 893 K under a constant stress of 145 MPa. Then, the EBSD measurements of these specimens were carried out. Subsequently, the PAGs were reconstructed successfully with the measured EBSD data, and the resultant distribution of LAGBs was calculated. Consequently, the obtained results suggested that the size of PAGs has not changed significantly during the whole creep. For the distribution of LAGBs, however, the peak shifted obviously to high angles during creep. In addition, it demonstrated that the EBSD method offers an effective and quantitative tool to characterise the microstructure evolution during creep of P91 steel. [ABSTRACT FROM AUTHOR]

In order to predict the long-term creep life of P91 steel, this work proposed a coupled model, combining the error-trained back-propagation artificial neural network (BP-ANN) and an improved θ model. Both the short-term rupture life obtained by creep experiments and the related creep data of National Institute for Materials Science (NIMS) database were used to validate the above model. In this model, creep parameters (temperature, stress) were used as the input and relative error of 5 θ model extrapolations as the output. Then, the prediction errors of BP-ANN method were introduced to correct the 5 θ model extrapolation results to achieve a more accurate prediction. Consequently, the long-term creep life of P91 steel was predicted. It demonstrated that with the proposed model, the prediction capability for long-term creep life of P91 steel with 200,000 h is much better than those of other θ methods, which has a prediction uncertainty less than 5%. • A model coupled the improved 5 θ model with BP-ANN was proposed. • The proposed model based on error-training predicted the long-term creep life of P91 steel successfully. • The prediction accuracy of proposed model was much better than those of the 4 θ and 5 θ models. [ABSTRACT FROM AUTHOR]

This paper introduces a parallel-batching scheduling problem with deterioration and learning effects on parallel machines, where the actual processing time of a job is subject to the phenomena of deterioration and learning. All jobs are first divided into different parallel batches, and the processing time of the batches is equal to the largest processing time of their belonged jobs. Then, the generated batches are assigned to parallel machines to be processed. Motivated by the characteristics of machine maintenance activities in a semiconductor manufacturing process, we take the machine preventive maintenance into account, i.e., the machine should be maintained after a fixed number of batches have been completed. In order to solve the problem, we analyze several structural properties with respect to the batch formation and sequencing. Based on these properties, a hybrid BRKGA-DE algorithm combining biased random-key genetic algorithm (BRKGA) and Differential Evolution (DE) is proposed to solve the parallel-batching scheduling problem. A series of computational experiments is conducted to demonstrate the effectiveness and efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This research investigates the parallel-batching scheduling problems with a time-dependent learning effect where the job processing time is a decreasing function of its starting time. Both the single-machine and parallel-machine circumstances are considered, and the objective is to minimize the makespan. For the single parallel-batching machine scheduling problem, some structural properties and a heuristic algorithm are developed to solve it. Since the parallel-batching machines scheduling problem is NP-hard, a hybrid CS-JADE algorithm combining improved cuckoo search algorithm (CS) and self-adaptive differential evolution (DE) is proposed to solve this problem. The computational experiments indicate that the proposed hybrid algorithm performs well both in effectiveness and efficiency. [ABSTRACT FROM AUTHOR]

The creep rupture behaviours and microstructural changes of a modified 9Cr-1Mo heat-resistant steel were investigated at 853 K. Analysis of creep results suggests that dislocation climb is the dominant deformation mechanism with true stress exponent of 5 under the present conditions. Based on the microstructural analysis, strengthening contributions from M23C6 carbides and MX carbonitrides were clarified. The M23C6 carbides can promote grain boundary strengthening by exerting Zener pinning forces, whereas MX carbonitrides can enhance the creep strength by interacting with mobile dislocations to induce threshold stress. Besides, softening of the steel is related not only to the decrease of dislocations, but also the coarsening of precipitates and substructures. The value of creep damage tolerance factor is close to 6.6, which further confirms that the creep damage is mainly attributed to the microstructural degradations, such as the coarsening of precipitates and substructures and decrease of dislocations. [ABSTRACT FROM AUTHOR]

The complement system is essential to host defense, but its excessive activation caused by severe pathogen invasion is a driving force in adverse inflammatory. The binding of complement component 5a (C5a) and complement component 5a receptor 1 (C5aR1) is the key to trigger complement-mediated inflammatory response in mammals. However, the role of C5a-C5aR1 axis in fish immune response remains obscure. In this study, the role of C5a-C5aR1 axis of zebrafish (Danio rerio) after serious infection with Aeromonas hydrophila was investigated. C5a and C5aR1 of zebrafish were cloned, with CDS sequences of 228 and 1041 bp, respectively, and they were widely expressed in various tissues with the highest expression in the liver and spleen, respectively. The survival of zebrafish was closely correlated to the dose of A. hydrophila. The cytokine storm occurred at high concentrations of A. hydrophila infection. At 24 h post infection (hpi), the expression of C5a and C5aR1 in the spleen increased 26.8-fold and 9.9-fold in treatment group 1 (TG1, 3.0 × 107 CFU/mL) (P < 0.01), and 4.7-fold and 3.4-fold in treatment group 2 (TG2, 1.0 × 107 CFU/mL) (P < 0.05), respectively. Correspondingly, proinflammatory cytokines interleukin-1β (IL-1β), interleukin-8 (IL-8), and interleukin-17 (IL-17) were positively correlated to C5a and C5aR1 at mRNA and protein expression levels. The expression of IL-1β was significantly increased in the spleen at 6 hpi, with a 599.2-fold and 203.2-fold upregulation in TG1 and TG2 (P < 0.001), respectively. Moreover, after inhibition of C5a-C5aR1 binding treated with C5aR1 antagonist (W-54011), zebrafish showed lower expression of C5a , C5aR1 , and cytokines, less intestinal damage, and significantly enhancement of survival (P < 0.05) after A. hydrophila challenge. This study revealed that the inflammatory effect of C5a was achieved by binding to C5aR1 in zebrafish, providing novel insights into using C5a-C5aR1 axis as an effective target to reduce bacterial inflammation and disease in fish. • C5a-C5aR1 axis was activated by bacterial infection with dose effect. • Hyperactivation of C5a-C5aR1 axis triggered a "cytokine storm" at both mRNA and protein levels in zebrafish. • Inhibition of C5a-C5aR1 axis significantly reduced the inflammatory response after bacterial infection in zebrafish. • The inflammatory effect of C5a was achieved by binding to C5aR1. [ABSTRACT FROM AUTHOR]

Abstract Using the internal friction measurement, this work dealt with the change of dislocation configuration during the creep of 9Cr 1Mo steel at 873 K. At different creep times, specimens of this steel were firstly prepared by the interrupted test to simulate various creep states. Then, the internal friction of these specimens was measured by a dynamic mechanical analyzer (DMA) to characterize the dislocation configuration. Based on the analysis of internal friction results, it showed that both the density and distribution of diffusion-controlled dislocations vary continuously with creep time, and there has a density peak at the end of primary creep. Meanwhile, the kinetics of dislocation motions was introduced to study the evolution of dislocations during present creep in detail. In comparison with the calculated results, the movement mechanism of above diffusion-controlled dislocations was clarified successfully by the modeled dislocations. In addition, the present work offered a powerful tool to evaluate the configuration of dislocations rather than mobile dislocations. Highlights • The diffusion-controlled dislocations during creep of 9Cr-1Mo steel was successfully characterized using internal friction measurement. • It revealed that these diffusion-controlled dislocations are actually the immobile dislocations forming during creep. • The internal friction measurement offers a potential method to characterize the configuration of dislocations rather than mobile dislocations. [ABSTRACT FROM AUTHOR]

In this paper, we study a single machine scheduling problem by simultaneously considering the processing method of serial-batching, learning effect, resource-dependent processing times, and setup operations. We consider minimizing the makespan as the objective of the studied problem under the constraint that the total resource consumption does not exceed a given limit. For the special case where the resource allocation is given, we first propose the structural properties for job batching policies and batching sequencing, and an optimal batching policy is derived based on these properties. Then, we develop a novel hybrid GSA–TS algorithm which combines the Gravitational Search Algorithm (GSA) and the Tabu Search (TS) algorithm to solve the general case. Computational experiments with different scales show the effectiveness and efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Dark excitons are fascinating for condensed matter physics, quantum information processing, and optoelectronics due to their long lifetimes. However, direct optical access to dark excitons is still challenging due to the violation of the spin selection rule. Here, a new scheme for the brightening of spin‐forbidden dark exciton in WS2 monolayers by creating artificial out‐of‐plane shear strain that induces an effective in‐plane pseudo‐magnetic field is proposed. To reveal dark excitons, low‐temperature magneto‐photoluminescence experiments on the strained WS2 monolayers are performed. It is found that the dark excitons appear at 59 meV below the bright ones and exhibit an asymmetric magnetic field dependence, which is in agreement with the model taking into account the effect of the out‐of‐plane shear strain on spin‐flip processes of exciton states. The fieldless scheme has great potential in the application of dark excitons for new quantum information processing devices. [ABSTRACT FROM AUTHOR]

In this paper, we study a scheduling model in which the features of deteriorating jobs, serial batches, multiple job types, and setup times are considered simultaneously. In this proposed model, the jobs of each type are first partitioned into serial batches, and then all batches of different job types are processed on a single serial-batching machine. The actual job processing time is an increasing function of its starting time, and the setup time of the batches is sequence-dependent, i.e., setup time is required only when a new batch is processed first on the machine or immediately after a batch belonging to another job type. We develop optimization algorithms to solve the makespan minimization problem, the maximum tardiness minimization problem, the maximum lateness minimization problem, and the maximum earliness minimization problem, respectively. We also propose optimization algorithms to solve the problem of minimizing the number of tardy jobs under a certain agreeable condition. Finally, we discuss two special cases of the total completion time minimization problem and develop optimization algorithms to solve them. [ABSTRACT FROM AUTHOR]

In this study, the change of geometrically necessary dislocation (GND) has been investigated during the elevated temperature creep of P91 steel. Firstly, the crept microstructures of P91 steel at 873 K and 165 MPa were characterized by electron backscatter diffraction (EBSD). Then, the resultant GND distributions were analyzed in detail. Meanwhile, the GND density was quantitatively estimated by two methods of kernel average misorientation (KAM) and Nye's dislocation density tensor, respectively. The obtained results indicated that during creep of P91 steel, the values of GND density calculated by the KAM method are highly consistent with those of Nye's dislocation density tensor method. Besides, the GND density increases significantly during the initial creep stage and attains the maximum approximately at the transition from initial creep to steady creep. During the subsequent creep, it gradually decreases. In addition, it suggested that the internal stress predicted by the obtained GND density is consistent with previous experimental data. Accordingly, it further demonstrated that the present characterization of GND evolution offers a convenient tool for the microstructure degradation analysis of P91 steel during creep. • The microstructure of P91 steel during creep has been investigated by EBSD method. • The change of GND density was quantitatively characterized by KAM and Ney's dislocation density tensor, respectively. • The GND densities obtained by the above methods are highly consistent. • The GND densities vary closely with the creep stage, resulting from the interaction between dislocation and precipitates. [ABSTRACT FROM AUTHOR]

Many dynamic events exist in real manufacturing systems, such as arbitrary machine breakdowns and dynamic job arrivals, which makes the scheduling problem even more complicated. In this paper, we address a serial-batching scheduling problem with the above dynamic events. Jobs need to be processed on the serial-batching machines of two manufacturers and then transported by vehicles to a customer for further processing. The objective of the scheduling problem is to minimize the makespan, and the problem is proved to be strongly NP-hard. Some structural properties and a lower bound of the problem are also proved or derived. On the basis of job arrival times, we divide the problem into two phases and propose different rules regarding these two phases. Based on these properties and rules, a heuristic algorithm is developed to solve the problem and its worst case performance is analyzed. The heuristic algorithm is tested on a large set of randomly generated problem instances, and the relative gaps between the found lower bound and the solutions of the proposed heuristic algorithm are reported. The experimental results illustrate the high efficiency and effectiveness of the proposed heuristic algorithm compared with other four classic approaches. [ABSTRACT FROM AUTHOR]

The reliable prediction of long-term creep life is of great importance in order to ensure the service safety of high-temperature components. In this work, the novel Wilshire-Cano-Stewart (WCS) relationships were introduced to model the creep behavior and predict the long-term creep life of P91 steel based on the short-term creep data. The accelerated creep experiments were firstly carried out at the temperature range of 580–620 °C, while the stresses varied from 135 to 200 MPa. According to the analyses of normalized-mean-squared error (NMSE) and mean logarithmic error (MLE), it demonstrated that the WCS model can express all the obtained creep data very well due to the average relative errors lower than 10%. Meanwhile, these values are much lower than those of traditional Time-Temperature-Parameter (TTP) models. In addition, the WCS model can provide the reasonable estimates of 200,000 h creep life with accelerated creep measurements lasting up to only 2000 h. • WCS model made full use of Wilshire and Sinh model respective advantages and eliminated known weaknesses. • Results of WCS model are better than the traditional L-M model in life prediction. • Results of WCS model are accurate enough in life prediction. [ABSTRACT FROM AUTHOR]

Recovery of the end-of-use products has become a topic of considerable interest in the advanced manufacturing industry due in part to uncertainties in the quality and volume of product returns. The Internet of Things (IoT) that enables the tracing, detecting, storing, and analyzing the product life cycle data for each individual item can mitigate or eliminate these uncertainties. In this paper, an integrated three-stage model is presented based on IoT technology for the optimization of procurement, production and product recovery, pricing and strategy of return acquisition. The remaining value is used to measure the return condition. The model considers three recovery options related to refurbishing, component reuse and disposal, and the value deterioration for satisfying the product demand in each stage of product life cycle (PLC). A novel particle swarm optimization (PSO) algorithm based on two heuristic methods is proposed to solve the problem. A numerical example and sensitivity analysis are used to illustrate the performance of both algorithm and applicability of the model. [ABSTRACT FROM AUTHOR]

Motivated by applications in manufacturing industry, we consider a supply chain scheduling problem, where each job is characterised by non-identical sizes, different release times and unequal processing times. The objective is to minimise the makespan by making batching and sequencing decisions. The problem is formalised as a mixed integer programming model and proved to be strongly NP-hard. Some structural properties are presented for both the general case and a special case. Based on these properties, a lower bound is derived, and a novel two-phase heuristic (TP-H) is developed to solve the problem, which guarantees to obtain a worst case performance ratio of. Computational experiments with a set of different sizes of random instances are conducted to evaluate the proposed approach TP-H, which is superior to another two heuristics proposed in the literature. Furthermore, the experimental results indicate that TP-H can effectively and efficiently solve large-size problems in a reasonable time. [ABSTRACT FROM PUBLISHER]

This paper investigates a scheduling model with certain co-existing features of serial-batching, dynamic job arrival, multi-types of job, and setup time. In this proposed model, the jobs of all types are first partitioned into serial batches, which are then processed on a single serial-batching machine with an independent constant setup time for each new batch. In order to solve this scheduling problem, we divide it into two phases based on job arrival times, and we also derive and prove certain constructive properties for these two phases. Relying on these properties, we develop a two-phase hybrid algorithm (TPHA). In addition, a valid lower bound of the problem is also derived. This is used to validate the quality of the proposed algorithm. Computational experiments, both with small- and large-scale problems, are performed in order to evaluate the performance of TPHA. The computational results indicate that TPHA outperforms seven other heuristic algorithms. For all test problems of different job sizes, the average gap percentage between the makespan, obtained using TPHA, and the lower bound does not exceed 5.41 %. [ABSTRACT FROM AUTHOR]

Using the nonlinear Lamb wave, this work investigated the damage resulting from microstructure evolution during the creep of 9Cr 1Mo steel at 873 K in detail. At eight creep times, specimens of this steel were firstly prepared by the interrupted test to simulate various creep states, respectively. Then, the measurement of acoustic nonlinearity parameter, and microstructure observation were employed to characterize the resultant damage. The experiment results showed that the measured value of this parameter is strongly dependent upon the creep state. Meanwhile, the hierarchical microstructure of 9Cr 1Mo steel evolves during creep. In order to conduct the quantitative assessment, both the analytical model of acoustic nonlinearity, and the kinetics of microstructure evolution were applied to calculating the acoustic nonlinearity parameter during creep. By comparison of the measured and calculated results, the predominated component of acoustic nonlinearity during the present creep of 9Cr 1Mo steel was clarified successfully by the modeled microstructures. Above all, the present work provided an effective way to monitor and evaluate the creep damage quantitatively. • Acoustic nonlinearity parameter of eight crept specimens with different states was measured using the nonlinear Lamb wave. • A quantitative model was provided to predict quite similar variations of the measured acoustics nonlinearity parameters. • The change of acoustic nonlinearity during the whole creep is determined by the configuration of substructure boundary. [ABSTRACT FROM AUTHOR]

The Tsiolkovsky crater is located on the farside of the Moon. It formed in the late Imbrian epoch and was filled with a large area of mare basalts. Multisource remote sensing data are used to interpret the geological features of the Tsiolkovsky area. Compared with previous studies, new remote sensing data and a chronological model based on crater size–frequency distribution are used to further refine the stratigraphic units and determine the absolute ages of the mare basalt units. The evolution of volcanic activity in this crater is discussed. The results are as follows: Abundances of major elements, Th, and silicate minerals suggest that the mare basalt in the crater floor is not a uniform unit but rather nine units with different compositions. The nine basalt units are divided into two episodes of volcanic activity: The first occurred at 3.5–3.7 Ga, when highly evolved lava erupted at the crater floor at a large scale; the second occurred at ~3.4 Ga, when a small area of more primitive lava extended to the northern portion of the crater floor. [ABSTRACT FROM AUTHOR]

Cytochrome P450s (CYPs) play crucial roles in regulating plant growth, development, and stress tolerance. In this study, a perennial ryegrass (Lolium perenne) CYP gene, LpCYP72A15, was identified as a candidate gene regulating plant osmotic stress tolerance based on a cDNA library screening in the background of yeast ∆hog1 mutant. LpCYP72A15 is localized in the plastids, and its expression was regulated by osmotic stress and ABA treatment. Overexpressing LpCYP72A15 significantly enhanced plant drought tolerance in both Arabidopsis and perennial ryegrass. Under drought stress, the transgenic ryegrass showed significant lower reactive oxygen species (ROS) levels, higher ROS‐scavenging enzymatic activities, and higher soluble sugar contents than the wildtype plants. Transient over‐expressing the gene also enhanced survival rates of ryegrass mesophyll protoplasts under H2O2‐induced oxidative or mannitol‐enforced osmotic stresses. Taken together, LpCYP72A15 confers oxidative‐ and osmotic‐stress tolerances that positively regulates plant drought tolerance in perennial ryegrass. [ABSTRACT FROM AUTHOR]

The analysis of aircraft fuel consumption remains an important topic as fuel consumption constitutes a large portion of airline operational costs, and exhaust emissions generated by aircraft gradually have become an essential aspect of urban air pollution, especially during takeoff and descent. Previous studies have focused mainly on optimizing fuel loss and greenhouse gases emission via three key methods: reducing additional aircraft load, using inventive air transfer control methods, and identifying the best-performing aviation systems for all conditions. However, there are few studies that have considered the relationships among fuel consumption, pilot behavior, and flight factors. This study fills this gap by focusing on the relationships between fuel consumption and three factors during the descent phase: altitude, weight, and speed. Further, we propose an improved K-means clustering algorithm to analyze the flight data, conducting clustering analysis on multi-dimensional data based on real flight records of Boeing 737s operated by China Eastern Airlines. We conclude the highlights of this study into three aspects: (1) the relationship between aircraft descent and fuel consumption is investigated through clustering analysis to find a fuel-efficient aircraft descent. (2) an improved K-means clustering algorithm is proposed to analyze flight data. (3) the better aircraft descent is the suggestion for pilots by analyzing the clustering results, which is a good supplement to the Flight Crew Operating Manual (FCOM). In the case study, the improved K-means algorithm is used for the cluster analysis of data from the quick access recorders of two aircraft descending into Chengdu Shuangliu Airport (CTU) in China. Compared with the method that does not use the analysis results for the descending, the average fuel consumption per unit of time decreases by 17.5% when we use our proposed method. In the Shanghai Pudong Airport (PVG), our proposed method reduces average fuel consumption per unit of time by 19.3%. [ABSTRACT FROM AUTHOR]

This paper introduces the serial batching scheduling problems with position-based learning effect, where the actual job processing time is a function of its position. Two scheduling problems respectively for single-machine and parallel-machine are studied, and in each problem the objectives of minimizing maximum earliness and total number of tardy jobs are both considered respectively. In the proposed scheduling models, all jobs are first partitioned into serial batches, and then all batches are processed on the serial-batching machine. We take some practical production features into consideration, i.e., setup time before processing each batch increases with the time, regarded as time-dependent setup time, and we formalize it as a linear function of its starting time. Under the single-machine scheduling setting, structural properties are derived for the problems with the objectives of minimizing maximum earliness and number of tardy jobs respectively, based on which optimization algorithms are developed to solve them. Under the parallel-machine scheduling setting, a hybrid VNS-GSA algorithm combining variable neighborhood search (VNS) and gravitational search algorithm (GSA) is proposed to solve the problems with these two objectives respectively, and the effectiveness and efficiency of the proposed VNS-GSA are demonstrated and compared with the algorithms of GSA, VNS, and simulated annealing (SA). This paper demonstrates that the consideration of different objectives leads to various optimal decisions on jobs assignment, jobs batching, and batches sequencing, which generates a new insight to investigate batching scheduling problems with learning effect under single-machine and parallel-machine settings. [ABSTRACT FROM AUTHOR]

This paper deals with a parallel machine scheduling problem with linearly increasing energy consumption cost. Maintenance activities are considered in the problem. After maintenance, the machine energy consumption cost returns to the normal level. Thus, an important decision is how to determine a reasonable number of maintenance activities to enable a significant tradeoff between the maintenance cost and the energy consumption cost. We define the jobs processed between two adjacent maintenance activities as a batch since the job processing cannot be interrupted. A further decision is how to batch the jobs. To solve the investigated problem, we first study a special case where there is only one single machine. A heuristic approach is proposed to solve the single machine scheduling problem. Then, we present a variable neighborhood search (VNS) algorithm for general cases, where the heuristic approach for the single machine case is intergrated. Extensive computational experiments are conducted and the results show that the proposed VNS algorithm is superior to artificial bee colony (ABC) algorithm, genetic algorithm (GA), ant colony optimization (ACO) algorithm, Tabu search (TS)algorithm, and greedy randomized adaptive search procedure (GRASP) algorithm. [ABSTRACT FROM AUTHOR]

Maintenance cost of aircraft engine is an important component of aircraft operation cost. The prediction of aircraft engine maintenance cost can provide decision support for airline to make reasonable maintenance plan and maintenance fund management. Considering that the prediction accuracy of engine maintenance cost is not high in the case of small samples, this paper proposes a bootstrapped support vector regression (SVR) prediction method based on improved recursive feature elimination, which realizes the point and interval prediction of engine maintenance cost in aircraft operation phase. First, the recursive feature elimination (RFE) is improved and then combined with SVR to select feature subsets. Second, particle swarm optimization (PSO) algorithm is applied to optimize the improved RFE-SVR model (IRFE-SVR) parameters. Finally, the point and interval estimates are obtained by bootstrapped IRFE-SVR. To demonstrate the performance of the bootstrapped IRFE-SVR, experiments on UCI and a real case study of engine maintenance cost prediction are conducted. The results on UCI and real datasets show that the bootstrapped IRFE-SVR method has high accuracy and reliability. [ABSTRACT FROM AUTHOR]

This paper investigates coordinated scheduling on uniform parallel batch machines with batch transportation. Jobs are characterized by different processing time and sizes, and they are first delivered to manufacturers in batches and then processed on the uniform parallel batch machines. The manufacturers are distributed in different geographic zones and there exists one parallel batch machine in each manufacturer. A mixed integer programming model is developed for the studied problem, and its objective is to minimize the makespan. In addition, the structural properties of the problem are analyzed. A hybrid algorithm combining the merits of discrete particle swarm optimization (DPSO) and genetic algorithm (GA) is proposed to solve this problem. In the hybrid algorithm, a heuristic and a local search strategy are introduced. Finally, computational experiments are conducted and the results show that the proposed hybrid algorithm can effectively and efficiently solve the problem within a reasonable time, particularly in large-scale instances. [ABSTRACT FROM AUTHOR]

Aquaculture plays important roles in global food security. Prized as a valuable commercial species, the aquaculture industry of half-smooth tongue sole (Cynoglossus semilaevis) has faced unprecedented challenge due to bacterial diseases, including vibriosis caused by Vibrio anguillarum. Alternative splicing (AS) is an important layer of post-transcriptional regulation, being involved in almost all biological processes, including development, reproduction, and immunity. However, its roles in immunity in half-smooth tongue sole remain elusive. In this study, therefore, we profiled the changes of alternative splicing in half-smooth tongue sole after infection with different concentrations of V. anguillarum , and investigated their functions by both enrichment analysis and targeted gene transcript overexpression analysis with half-smooth tongue sole macrophages. Intriguingly, differentially alternatively spliced (DAS) genes were found to be involved in RNA splicing for each bacterial treatment and for the shared gene set, consistent with previous studies that splicing factor themselves often underwent alternative splicing. A set of 12 immune-related shared DAS genes were identified, including hp , c5 , and traf2b. Targeted gene analysis using the shared DAS gene, haptoglobin (hp), showed that alternative splicing resulted in changes of protein domains, and overexpression analysis demonstrated that two transcripts of hp exhibited contrary roles in stimulating or reducing the expression of immune factors in response to lipopolysaccharides (LPS), reflecting the vital roles of alternative splicing in immunity of tongue sole. DAS events were further verified by qRT-PCR (20 primer pairs for 10 DAS events) to confirm the reliability of our bioinformatics analysis. This study, for the first time, revealed the involvement of alternative splicing in immune responses of half-smooth tongue sole using both omics data and targeted gene functional analysis, setting a solid foundation for further analysis and providing clues for potential usage in controlling bacterial diseases in aquaculture. • RNA splicing was enriched for DAS genes in each comparison and the shared gene set. • A set of 12 immune-related genes were identified in 104 shared DAS genes. • Two hp splicing isoforms exhibited contrary roles in stimulation of immune factors. [ABSTRACT FROM AUTHOR]

Understanding hot carrier dynamics between plasmonic nanomaterials and its adsorbate is of great importance for plasmon‐enhanced photoelectronic processes such as photocatalysis, optical sensing and spectroscopic analysis. However, it is often challenging to identify specific dominant mechanisms for a given process because of the complex pathways and ultrafast interactive dynamics of the photoelectrons. Here, using CO2 reduction as an example, the underlying mechanisms of plasmon‐driven catalysis at the single‐molecule level using time‐dependent density functional theory calculations is clearly probed. The CO2 molecule adsorbed on two typical nanoclusters, Ag20 and Ag147, is photoreduced by optically excited plasmon, accompanied by the excitation of asymmetric stretching and bending modes of CO2. A nonlinear relationship has been identified between laser intensity and reaction rate, demonstrating a synergic interplay and transition from indirect hot‐electron transfer to direct charge transfer, enacted by strong localized surface plasmons. These findings offer new insights for CO2 photoreduction and for the design of effective pathways toward highly efficient plasmon‐mediated photocatalysis. [ABSTRACT FROM AUTHOR]

This research investigates an integrated inventory and production scheduling problem (IIPSP) in a manufacturer that deals with the perishable goods. The objective is to find an optimal schedule to minimize the sum of inventory cost and production cost. Both single-plant problem and multi-plant problem are investigated in this paper. For the single-plant problem, we prove that it is optimal to arrange the processing of raw materials in descending order of the value of the product of consumption rate and unit inventory cost. For the more complex multi-plant problem, we first prove that it is NP-hard, and then, we propose a hybrid intelligent algorithm to solve it. The experiments show that the proposed algorithm is superior to several other algorithms in both effectiveness and efficiency. [ABSTRACT FROM AUTHOR]

Based on phase space reconstruction (PSR) and hybrid VNS-SVR model, a remaining useful life (RUL) prediction method for aircraft engines is proposed. The proposed hybrid model combines support vector regression (SVR), which has been successfully adopted for regression problems, with the variable neighborhood search (VNS). First, the phase space reconstruction is used to transform the selected one-dimensional performance sequences of aircraft engines into matrix forms, which increases the data information and improve the learning efficiency of the model effectively. Then, SVR is used to construct the prediction model. Meanwhile, a VNS algorithm is proposed to optimize the kernel parameters. Finally, the hybrid model is used to RUL prediction of the aircraft engines. The experimental results show that the method has a good prediction performance. [ABSTRACT FROM AUTHOR]

The high-end equipment features with high value, complicated manufacturing process, and high status, and it thus brings a huge challenge to increase reliability, quality, and productivity during the production. In order to tackle this challenge and achieve automation, integration, and intelligence this paper proposes a hybrid metaheuristic for an integrated order scheduling and maintenance planning model with position-based processing time, parallel-batching processing, and multiple manufacturers. During the production, the continuous operation of the machine increases the probability of failure, and the repair work can eliminate the failure For each order, we derive some useful lemmas and develop an optimal algorithm to schedule jobs within it. Then, given the order assignment and sequence in the manufacturers, we propose a dynamic programing algorithm to make the decision on the maintenance planning. Subsequently, the investigated problem is proved to be NP-hard, thus, we propose a hybrid discrete black hole algorithm and variable neighborhood search (DBH-VNS) approach to solve the integrated problem. Some improvements are integrated into the proposed algorithm to obtain the competitive results, which include discrete encoding-based population updating scheme, the modified neighborhoods, and the VNS-based local search. Finally, we conduct computational experiments and the results demonstrate the effectiveness and validity of the proposed hybrid metaheuristic. • We propose a new integrated order scheduling and maintenance planning model. • An optimal algorithm for scheduling jobs within the order is proposed. • A dynamic programing algorithm is proposed to schedule maintenance activities. • A hybrid DBH-VNS is designed to solve the problem in general case. [ABSTRACT FROM AUTHOR]

This paper addresses a serial-batching scheduling problem where the jobs with arbitrary release times are scheduled on parallel machines with the objective to minimize the makespan. The effects of learning and deterioration are considered simultaneously, and each job's actual processing time depends on the sum of previous jobs' processing times and the position of the current job. Each machine can process up to c jobs in the manner of serial batch, i.e., one after another with a setup time for each batch. Structural properties are identified for the special cases of the studied problem. Based on these derived structural properties, we propose a novel hybrid SC-VNS algorithm to solve the studied problem, which combines Society and Civilization (SC) algorithm with Variable Neighborhood Search (VNS). Computational experiments are conducted to evaluate the performance of the proposed hybrid algorithm and some other well-known algorithms. The results demonstrate that the proposed hybrid SC-VNS algorithm performs quite better than the compared algorithms in terms of the solution quality and the required running time. [ABSTRACT FROM AUTHOR]

MicroRNAs play crucial roles in various biological processes, including but not limited to differentiation, development, disease, and immunity. However, their immunoregulatory roles in half-smooth tongue sole are lacking. Our previous studies indicated that miR-722 could target C5aR1 to modulate the complement pathway to alleviate inflammatory response and even affect the mortality after the bacterial infection with Vibrio anguillarum. Driven by the purpose of revealing the underlying mechanisms, in this study, we investigated the effects of miR-722 on the gene expression and alternative splicing (AS) in the liver of half-smooth tongue sole after Vibrio anguillarum infection, with the approach of miR-722 overexpression/silencing and subsequent RNA-seq. Among the different comparisons, the I group (miR-722 inhibitor and V. anguillarum) versus blank control (PBS) exhibited the highest number of differentially expressed genes (DEGs), suggesting that the immune response was overactivated after inhibiting the miR-722. In addition, enrichment analyses were performed to reveal the functions of DEGs and differential AS (DAS) genes, reflecting the enrichment of RNA splicing and immune-related pathways including NF-κB and T cell receptor signaling pathway. Comparing the M group (miR-722 mimic and V. anguillarum) with the negative control (random sequence and V. anguillarum), two immune-related genes, cd48 and mapk8 , were differentially expressed, of which mapk8 was also differentially spliced, indicating their importance in the immune response. Furthermore, representative gene analysis was performed, suggesting their corresponding functional changes due to AS. To verify the RNA-seq data, quantitative real-time PCR was employed with twenty pairs of primers for DEGs and DAS events. Overall, our results demonstrated that miR-722 could mediate the transcriptome-wide changes of gene expression and AS in half-smooth tongue sole, and provided insights into the regulatory role of miR-722 in immune responses, laying the foundation for further functional analyses and practical applications in aquaculture. • miR-722 mediated the transcriptome-wide changes of gene expression and AS in tongue sole. • DAS contributed significantly to the immune response after the bacterial infection. • mapk8 was the only gene that underwent both differential expression and DAS in M vs N. [ABSTRACT FROM AUTHOR]

The type-B response regulator (ARR) family members represent the elements of two-component regulatory systems and play crucial roles in the cytokinin signaling, plant growth, and stress responses. The objective of this study was to characterize type-B ARR genes from perennial ryegrass, and to investigate their roles in regulating to salt tolerance. Twelve type-B ARRs , namely LpARR1 - 12 , were identified in perennial ryegrass. They were clustered into three subgroups and were unevenly distributed on chromosomes. The stress responsive elements (SREs) and hormone responsive elements (HREs) were identified in LpARRs promoters and the transcription of LpARRs genes were responsive to various abiotic stress (heat, salt, and osmotic) and hormonal (cytokinin, ABA, and ethylene) treatments. LpARR10 was strong induced by salt stress, therefore it was selected for function analysis. Overexpressing LpARR10 in Arabidopsis led to a significant improvement in salt tolerance. The LpARR10 -overexpressing (LpARR10 -OE) lines exhibited lower levels of Na+ content compared to WT plants, and the expression levels of SOS1 and SOS3 were significantly higher in the LpARR10 -OE lines. Results of yeast auto-transactivation and plant cell transcriptional activity assays shows LpARR10 is a nucleus localized transcriptional activator and directly bind and transactivated the promoter of SOS1 and SOS3. Together, LpARR10 enhances salt tolerance may via trans-activating SOS1 / SOS3 in Arabidopsis. Knowledge gained in this study will facilitate further functional analysis of LpARRs for molecular breeding of ryegrass and other related grass species. • Overexpressing LpARR10 resulted in a reduction in Na+ content compared to WT plants. • The LpARR10 -OE lines exhibited significantly higher expression levels of SOS1 and SOS3. • LpARR10 acts as a transcriptional activator and positively regulates salt tolerance by up-regulating the expressions of SOS1 and SOS3. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are small non-coding RNAs involved in various biological processes, including immunity. Previously, we investigated the miRNAs of half-smooth tongue sole (Cynoglossus semilaevis) and found that miR-722 (designated Cse -miR-722) was significantly differentially expressed after infection with Vibrio anguillarum , reflecting its importance in immune response. Our preliminary bioinformatic analysis suggested that Cse -miR-722 could target C5aR1 (designated CsC5aR1), which was known to play crucial roles in complement activation and inflammatory response, as a receptor of C5a. However, the underlying mechanisms of their interactions and specific functions in inflammatory and immune response are still enigmas. In this study, we successfully cloned the precursor sequence of Cse -miR-722 (94 bp) and the full length of CsC5aR1 (1541 bp, protein molecular weight 39 kDa). The target gene of Cse -miR-722 was verified as CsC5aR1 by a dual luciferase reporter assay, and Cse -miR-722 was confirmed to regulate CsC5aR1 at the protein level using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting. The expression of CsC5aR1 and Cse -miR-722 in liver cells and four immune tissues of half-smooth tongue sole changed significantly after LPS stimulation and infection with V. anguillarum. To explore the functional role of Cse -miR-722 in half-smooth tongue sole, we performed both in vitro and in vivo experiments. Cse -miR-722 was observed to affect phagocytosis and respiratory burst activity of macrophages by regulating CsC5aR1 in half-smooth tongue sole. Furthermore, we found that Cse -miR-722 regulated the expression of CsC5aR1 , CsC5a , and the inflammatory factors CsIL1-β , CsIL6 , CsIL8 , and CsTNF-α both in vitro and in vivo. In addition, Cse -miR-722 reduced mortality and pathological damage. This study clarified the regulatory mechanism of Cse- miR-722 on CsC5aR1 and provided insight into the regulatory roles of Cse- miR-722 in immune responses, laying a theoretical foundation for the feasibility of using miR-722 to prevent and control bacterial diseases in teleost. • Cse -miR-722 targeted CsC5aR1 and silenced CsC5aR1 at the translation level. • Cse -miR-722 affected the phagocytic activity and respiratory burst of macrophages. • Cse -miR-722 regulated immune responses through the C5a/C5aR1 complement pathway. • Cse -miR-722 reduced mortality and body damage after Vibrio anguillarum infection. [ABSTRACT FROM AUTHOR]

This paper investigates a competitive two-agent parallel-batching scheduling problem with aging effect on parallel machines. The objective is to minimize the makespan of agent A with the constraint that the makespan of agent B is no more than a given threshold. Some key structural properties are first identified in two different cases, and based on these structural properties a novel decision tree of scheduling rules is constructed and a heuristic algorithm is designed. Then, an effective hybrid BF-VNS algorithm combining Bacterial Foraging (BF) with variable neighborhood search (VNS) is developed to tackle the studied problem. Computational experiments are conducted to evaluate the performance of the proposed hybrid algorithm and some other well-known algorithms. The experimental results indicate that the hybrid BF-VNS algorithm performs quite better than the compared algorithms. [ABSTRACT FROM AUTHOR]

This paper investigates an order acceptance and scheduling problem with an energy consumption budget, a machine launch budget, and the order release time in a green manufacturing system. The phenomenon of deteriorating jobs is considered in the production of the accepted orders. The objective of the study is to maximize the net revenue and a modified variable neighborhood search (MVNS) Algorithm that combines a novel encoding and decoding procedure as well as a dynamic programming algorithm is developed to solve it. To show the effectiveness and efficiency of the proposed algorithm, we first employ the MVNS algorithm and seven VNS-based algorithms to solve the problems with different configurations of orders and machines. The results show that the MVNS algorithm obtains better solutions than existing VNS-based algorithms. Then, the proposed algorithm is compared with three meta-heuristic algorithms. The experimental results show that the proposed algorithm has significant advantages in terms of solution optimality. [ABSTRACT FROM AUTHOR]

Frequently occurred bacterial diseases have seriously affected the aquaculture industry of half-smooth tongue sole (Cynoglossus semilaevis). Notably, vibriosis, with Vibrio anguillarum as one of the causative pathogens, is the most severe bacterial disease with severe inflammatory response of the host, leading to high mortality rates. In the present study, we explored the relationship between bacterial concentrations and host mortality, inflammatory reaction, and immune response in half-smooth tongue sole after infection with V. anguillarum at different concentrations (Treatment 1, 6.4 × 105 CFU/mL; Treatment 2, 6.4 × 106 CFU/mL). The mortality of Treatment 2 (77.5%) was significantly higher than that of Treatment 1 (10%), corresponding with bacterial concentrations. Although the number of deaths varies, intensive deaths were observed within 24 h post infection (hpi) in both bacterial concentration groups. Histopathological analyses revealed that fish tissues were most severely damaged at 24 or 48 hpi, and Treatment 2 was more severe than Treatment 1. A qRT-PCR-based detection method with virulence factor gene empA was established to quantify the bacterial loads in various tissues, and the bacterial loads were the highest at 24 hpi in Treatment 2, and at 48 hpi in Treatment 1. Additionally, the expression levels of complement genes (C5a , C3 , C5 , and C6), inflammatory factors (IL-1β , TNF-α , and IL-1 0), and other immune-related genes (jak2 , NF-κB1 , stat3 , and tlr3) were increased in various tissues after infection in both treatment groups, with most genes being most expressed at 24 or 48 hpi, and expression levels of inflammatory factors in Treatment 2 were higher than those in Treatment 1. Moreover, the expression of C5a was positively correlated with that of proinflammatory cytokines in both bacterial concentration groups. According to the results of this study, 24–48 hpi was a key node for early vibriosis detection and intervention. Compared with the low mortality of Treatment 1, the mass death of fish in Treatment 2 was suggested to be caused by uncontrolled excessive inflammatory reaction induced by the overactivation of complement system, especially C5a. We believe these results could provide theoretical basis for prevention, evaluation, and treatment of vibrio disease in tongue sole aquaculture, and lay a solid foundation for future functional analyses. • The mortality, inflammation response, host histopathological damage and bacterial loads of tongue sole after Vibrio anguillarum infection peaked at 24–48 hpi. • Inflammatory factors (IL-1β , TNF-α , and IL-10), complement genes (C5a , C3 , C5 , and C6), and other immune genes (jak2 , NF-κB1 , stat3 , and tlr3) were up-regulated after infection, with a bacterial dose effect. • The observed mass death under high bacterial concentration infection was suggested to be caused by the excessive inflammatory response mainly induced by C5a overactivation. [ABSTRACT FROM AUTHOR]

Grazing exclusion has been proposed as an effective practice to enhance ecosystem carbon stocks in arid-semiarid degraded grasslands. However, in humid regions, the effects of grazing exclusion on ecosystem carbon stocks and their components in degraded grasslands remain largely unknown. Here, the effects of enclosure on ecosystem carbon stocks and their components were explored using four enclosure ages, each paired with adjacent grazed areas. Moreover, the results were synthesized with previous studies to test if enclosure's effects in semihumid-humid regions differed from those in arid-semiarid regions. The field experiment found that six months to 1 year of grazing exclusion sequestrated 14.6 % higher carbon in the enclosed grasslands than in paired-grazed grasslands as a consequence of increased carbon storage of plants and topsoils. However, compared to grazed areas, enclosures over 3–6 years contained 14.4 % less ecosystem carbon stocks, primarily due to markedly decreased soil carbon sequestration, despite increased plant carbon stocks. Structural equation models further suggested that the decrease in soil carbon stock might be owing to the decomposition of organic matter induced by low phosphorus. Additionally, compared with the northern slope of the mountain, ecosystem carbon stocks on the southern slope showed a lagged and weak response to grazing exclusion. The results, combined with a meta-analysis, revealed that plant and soil carbon stocks in semihumid-humid grasslands were more sensitive to enclosure than in arid-semiarid grasslands. These results highlight that short-term fencing (e.g., six months to 1 year), rather than long-term, is a practical strategy to foster degraded grassland ecosystem carbon sequestration in semihumid-humid regions, thus contributing to climate change mitigation. • Six months to 1 year of grazing exclusion promoted ecosystem carbon stocks • 3–6 years' fencing reduced ecosystem carbon stocks as the decrease in soil stock • The decrease in soil carbon stock was mainly owing to the imbalance of soil nutrients • Northern slope' carbon stock responded strongly compared to southern slope • Carbon stocks in humid grasslands was more sensitive than in arid grasslands [ABSTRACT FROM AUTHOR]

This paper deals with the problem of preemptive scheduling in a two-stage supply chain framework. The supply chain environment contains two stages: production and transportation. In the production stagejobs are processed on a manufacturer's bounded serial batching machine, preemptions are allowed, and set-up time is required before a new batch is processed. In the transportation stage each batch is delivered to a customer by a single vehicle. The objective is to minimize the makespan by making decisions for both mutually coordinated stages. Specifically, two versions are studied. The first one is that all jobs are available to be processed at time zero, and the second one is that jobs have different release times. Antime algorithm is developed for the first version, and we show that it can produce the optimal schedule for the entire problem. For the second version, based on some useful properties we have designed antime heuristic and a novel lower bound. The worst-case performance ratio of our algorithm is bounded by 2. Our computational study with random instances of different scales shows high-quality solutions for either small-scale or large-scale instances returned in a reasonable PC times. [ABSTRACT FROM AUTHOR]