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The instance segmentation model based on deep learning has addressed the challenges in intelligently detecting water leakage in shield tunneling. Due to the limited generalization ability of the baseline model, occurrences of missed detections, false detections, and repeated detections are encountered during the actual detection of tunnel water leakage. This paper adopts Mask R-CNN as the baseline model and introduces a mask cascade strategy to enhance the quality of positive samples. Additionally, the backbone network in the model is replaced with RegNetX to enlarge the model's receptive field, and MDConv is introduced to enhance the model's feature extraction capability in the edge receptive field region. Building upon these improvements, the proposed model is named Cascade-MRegNetX. The backbone network MRegNetX features a symmetrical block structure, which, when combined with deformable convolutions, greatly assists in extracting edge features from corresponding regions. During the dataset preprocessing stage, we augment the dataset through image rotation and classification, thereby improving both the quality and quantity of samples. Finally, by leveraging pre-trained models through transfer learning, we enhance the robustness of the target model. This model can effectively extract features from water leakage areas of different scales or deformations. Through instance segmentation experiments conducted on a dataset comprising 766 images of tunnel water leakage, the experimental results demonstrate that the improved model achieves higher precision in tunnel water leakage mask detection. Through these enhancements, the detection effectiveness, feature extraction capability, and generalization ability of the baseline model are improved. The improved Cascade-MRegNetX model achieves respective improvements of 7.7%, 2.8%, and 10.4% in terms of AP, AP0.5, and AP0.75 compared to the existing Cascade Mask R-CNN model. [ABSTRACT FROM AUTHOR]

In shield tunneling, the joint is one of the most vulnerable parts of the segmental lining. Opening of the joint reduces the overall stiffness of the ring, leading to structural damage and issues such as water leakage. Currently, the Winkler method is commonly used to calculate structural deformation, simplifying the interaction between segments and soil as radial and tangential Winkler springs. However, when introducing connection springs or reduction factors to simulate the joint stiffness of segments, the challenge lies in determining the reduction coefficient and the stiffness of the springs. Currently, the hyperstatic reflection method cannot simulate the discontinuity effect at the connection of the tunnel segments, while the state space method overlooks the nonlinear interaction between the tunnel and the soil. Therefore, this paper proposes a numerical simulation method considering the interaction between the tunnel and the soil, which is subjected to compression rather than tension, and the discontinuity of the joints between the segments. The model structure and external load are symmetrical, resulting in symmetrical calculation results. This method is based on the soft soil layers and shield tunnel structures of the Shanghai Metro, and the applicability of the model is verified through deformation calculations using three-dimensional laser scanning point clouds of sections from the Shanghai Metro Line 5. When the subgrade reaction coefficient is 5000 k N / m 3 , the model can effectively simulate the deformation of operational tunnels. By adjusting the bending stiffness of individual connection springs, we investigate the influence of bending stiffness reduction on the bending moment, radial displacement, and rotational displacement of the ring. The results indicate that a decrease in joint bending stiffness significantly affects the mechanical response of the ring, and the extent and degree of this influence are correlated with the joint position and the magnitude of joint bending stiffness. [ABSTRACT FROM AUTHOR]

Greenbug [Schizaphis graminum (Rondani)] is a serious insect pest that not only damages cereal crops, but also transmits several destructive viruses. The emergence of new greenbug biotypes in the field makes it urgent to identify novel greenbug resistance genes in wheat. CWI 76364 (PI 703397), a synthetic hexaploid wheat (SHW) line, exhibits greenbug resistance. Evaluation of an F2:3 population from cross OK 14319 × CWI 76364 indicated that a dominant gene, designated Gb9, conditions greenbug resistance in CWI 76364. Selective genotyping of a subset of F2 plants with contrasting phenotypes by genotyping-by-sequencing identified 25 SNPs closely linked to Gb9 on chromosome arm 7DL. Ten of these SNPs were converted to Kompetitive allele-specific polymerase chain reaction (KASP) markers for genotyping the entire F2 population. Genetic analysis delimited Gb9 to a 0.6-Mb interval flanked by KASP markers located at 599,835,668 bp (Stars-KASP872) and 600,471,081 bp (Stars-KASP881) on 7DL. Gb9 was 0.5 cM distal to Stars-KASP872 and 0.5 cM proximal to Stars-KASP881. Allelism tests indicated that Gb9 is a new greenbug resistance gene which confers resistance to greenbug biotypes C, E, H, I, and TX1. TX1 is one of the most widely virulent biotypes and has overcome most known wheat greenbug resistance genes. The introgression of Gb9 into locally adapted wheat cultivars is of economic importance, and the KASP markers developed in this study can be used to tag Gb9 in cultivar development. [ABSTRACT FROM AUTHOR]

The use of alternative fuels is a primary means for decarbonising the maritime industry. Liquefied natural gas (LNG), liquid hydrogen (LH2), and liquid ammonia (LNH3) are liquified gases among the alternative fuels. The safety risks associated with these fuels differ from traditional fuels. In addition to their low-temperature hazards, the flammability of LNG and LH2 and the high toxicity of LNH3 present challenges in fuel handlings due to their high likelihood of fuel release during bunkering. This study aims at drawing extensive comparisons of the evaporation and vapour dispersion behaviours for the three fuels after release accidents during bunkering and discuss their safety issues. The study involved the release event of the three fuels on the main deck area of a reference bulk carrier with a deadweight of 208,000 tonnes. Two release scenarios were considered: Scenario 1 involved a release of 0.3 m3 of fuel, and Scenario 2 involved a release of 100 kg of fuel. An empirical equation was used to calculate the fuel evaporation process, and the Computational Fluid Dynamic (CFD) code FDS was employed to simulate the dispersion of vapour clouds. The obtained results reveal that LH2 has the highest evaporation rate, followed by LNG and LNH3. The vapour clouds of LNG and LNH3 spread along the main deck surface, while the LH2 vapour cloud exhibits upward dispersion. The flammable vapour clouds of LNG and LH2 remain within the main deck area, whereas the toxic gas cloud of LNH3 disperses towards the shore and spreads near the ground on the shore side. Based on the dispersion behaviours, the hazards of LNG and LH2 are comparable, while LNH3 poses significantly higher hazards. In terms of hazard mitigations, effective water curtain systems can suppress the vapour dispersion. • The LNG, LH2, and LNH3 vapour dispersions are compared under identical release scenarios. • LH2 exhibits the highest evaporation rate, followed by LNG and LNH3. • The hazards associated with LNG and LH2 are comparable. • LNH3 poses greater hazards when compared to LH2 and LNG. [ABSTRACT FROM AUTHOR]

At the present stage, the identification of dangerous behaviors in public places mostly relies on manual work, which is subjective and has low identification efficiency. This paper proposes an automatic identification method for dangerous behaviors in public places, which analyzes group behavior and speech emotion through deep learning network and then performs multimodal information fusion. Based on the fusion results, people can judge the emotional atmosphere of the crowd, make early warning, and alarm for possible dangerous behaviors. Experiments show that the algorithm adopted in this paper can accurately identify dangerous behaviors and has great application value. [ABSTRACT FROM AUTHOR]

Prompt detection of landslides is crucial for reducing the disaster risk and preventing landslides. However, landslide detection in practical applications still faces many challenges, such as the complexity of environmental backgrounds, the diversity of target scales, and the enormity of model weights. To address these issues, this paper proposes a lightweight LBE-YOLO model for real-time landslide detection. Firstly, a lightweight model is designed by integrating the GhostConv lightweight network with the YOLOv8n model. Inspired by GhostConv, this study innovatively designed the GhostC2f structure, which leverages linear thinking to further reduce the model parameters and computational burden. Additionally, the newly designed EGC2f structure, incorporating an attention mechanism, not only maintains the model's lightweight characteristics but also enhances the network's capability to extract valid information. Subsequently, the Path Aggregation Network (PAN) was optimized by introducing a bidirectional feature propagation mechanism to improve the model's feature fusion ability. Additionally, the Bijie landslide dataset was expanded through data augmentation strategies, thereby further improving the model's generalization capability. The experimental results indicate that, compared to the YOLOv8n model, the proposed model increased accuracy by 4.2%, while the model's weight and computational load were reduced by 32.0% and 35.5%, respectively. This verifies the superiority of the LBE-YOLO model in landslide target detection, which will help mitigate the impacts of natural disasters. [ABSTRACT FROM AUTHOR]

Crack detection plays a critical role in ensuring road safety and maintenance. Traditional, manual, and semi-automatic detection methods have proven inefficient. Nowadays, the emergence of deep learning techniques has opened up new possibilities for automatic crack detection. However, there are few methods with both localization and segmentation abilities, and most perform poorly. The consistent nature of pavement over a small mileage range gives us the opportunity to make improvements. A novel data-augmentation strategy called CrackMover, specifically tailored for crack detection methods, is proposed. Experiments demonstrate the effectiveness of CrackMover for various methods. Moreover, this paper presents a new instance segmentation method for crack detection. It adopts a redesigned backbone network and incorporates a cascade structure for the region-based convolutional network (R-CNN) part. The experimental evaluation showcases significant performance improvements achieved by these approaches in crack detection. The proposed method achieves an average precision of 33.3%, surpassing Mask R-CNN with a Residual Network 50 backbone by 8.6%, proving its effectiveness in detecting crack distress. [ABSTRACT FROM AUTHOR]

The application of three-dimensional laser scanning technology in the field of tunnel deformation monitoring has changed the traditional measurement method. It provides an automated and intelligent solution for monitoring the geometric deformation of tunnel sections due to its high efficiency and independence from environmental influences. In this paper, based on B-spline fitting and iterative nearest point (ICP) alignment, the calculation of the difference between the radial distance and the design radius of a tunnel is transformed into a curve transformation that iterates over the nearest-neighbor points and calculates the difference in the distance between the corresponding points. The innovation of this paper is that the high-precision tunnel deformation monitoring method integrating B-spline fitting and ICP alignment can automatically compensate for the missing point clouds, is not affected by the point clouds of the tunnel inner and outer liner appendages, is more sensitive in the local deformation feedback and can be applied to a variety of tunnel shapes. The results indicate that our method maximally improves the accuracy of the horizontal convergence calculation by 28.6 mm and the accuracy of the vault settlement by 27.8 mm in comparison with the least squares circle fitting algorithm. [ABSTRACT FROM AUTHOR]

Ensuring road safety, structural stability and durability is of paramount importance, and detecting road cracks plays a critical role in achieving these goals. We propose a GM-ResNet-based method to enhance the precision and efficacy of crack detection. Leveraging ResNet-34 as the foundational network for crack image feature extraction, we consider the challenge of insufficient global and local information assimilation within the model. To overcome this, we incorporate the global attention mechanism into the architecture, facilitating comprehensive feature extraction across the channel and the spatial width and height dimensions. This dynamic interaction across these dimensions optimizes feature representation and generalization, resulting in a more precise crack detection outcome. Recognizing the limitations of ResNet-34 in managing intricate data relationships, we replace its fully connected layer with a multilayer fully connected neural network. We fashion a deep network structure by integrating multiple linear, batch normalization and activation function layers. This construction amplifies feature expression, stabilizes training convergence and elevates the performance of the model in complex detection tasks. Moreover, tackling class imbalance is imperative in road crack detection. Introducing the focal loss function as the training loss addresses this challenge head-on, effectively mitigating the adverse impact of class imbalance on model performance. The experimental outcomes on a publicly available crack dataset emphasize the advantages of the GM-ResNet in crack detection accuracy compared to other methods. It is worth noting that the proposed method has better evaluation indicators in the detection results compared with alternative methodologies, highlighting its effectiveness. This validates the potency of our method in achieving optimal crack detection outcomes. [ABSTRACT FROM AUTHOR]

Bird cherry‐oat aphid (BCOA) and greenbug pose a persistent threat to wheat production in many wheat‐growing regions. Currently, greenbug resistance genes are limited for wheat improvement, and BCOA resistance sources are even more scarce. Thus, it is urgent to identify BCOA and greenbug resistance sources in wheat gene pools. An Aegilops tauschii (Ae. tauschii) panel of 260 accessions, which accounted for 48% of the total Ae. tauschii accessions available in global germplasm banks, was evaluated for BCOA resistance, and a set of BCOA‐resistant lines were identified. The same panel was evaluated for response to greenbug biotypes C, E, F, G, I, and TX1. A total of 102 lines exhibited 14 unique resistance profiles or phenotypes featuring resistance to at least one biotype. The frequency of resistant lines varied among lineages or subspecies, from 62% in Lineage 1 (subspecies tauschii) to 18% in Lineage 2 (subspecies stangulata), indicating conservation of genetic variance for greenbug resistance was nonrandom. Ae. tauschii accessions resistant to both BCOA and greenbug were identified for enhancing aphid resistance. Core Ideas: A bird cherry‐oat aphid (BCOA) assay protocol was developed.BCOA‐resistant Ae. tauschii lines were identified.Ae. tauschii lines with a wide spectrum of resistance to greenbug were found.Ae. tauschii lines resistant to both BCOA and greenbug were identified. [ABSTRACT FROM AUTHOR]

Under the engaging process, excessive temperature of clutch plates may lead to thermal failure. Existing research has failed to find the hot spot and the radial temperature difference real-timely. They also neglected the influence of dynamic sliding process and hydraulic characteristics. Thus, a multi-domain dynamic model of the whole clutch was proposed, involving the mechanical dynamics, the hydraulic dynamics and thermics. With the thermal resistance network method, the real-time axial and radial temperature prediction of clutch plates was realized. The highest temperature occurs on the friction pairs of axial middle and the maximum value occurs on the radial 5th mass. Compared with the results by FEM, the deviation is about 6.5 %, but the time duration is reduced significantly. Furthermore, the influence of the outer hub vibration (160 Hz, 0.2 Hz) on the dynamic characteristics was discussed. This work was tested to be an effective and good basis for the health prediction of wet clutches. [ABSTRACT FROM AUTHOR]

With the rapid development of urban rail transit and the aging of transportation infrastructure, the demand for shield tunnel disaster detection is about to break out. Most of the traditional monitoring methods require considerable manpower and time costs, which cannot satisfy the increasing requirements of tunnel operation and maintenance. Free-form model construction and deviation mechanism analysis are investigated in this paper to monitor the geometric deformation information of shield tunnels quickly and accurately. A method for identifying geometric features of tunnel sections based on the free-form B-spline approximation is proposed. The innovation of this paper lies in the intelligent recognition of common interference targets by the residual classification method. Furthermore, various Root Mean Squared Error (RMSE) distributions are investigated, which successfully realizes and verifies the clustering analysis of certain point cloud features. [ABSTRACT FROM AUTHOR]

Owing to its high theoretical specific capacity, Mn2SnO4 has been regarded as a promising electrode material for lithium-ion batteries. However, in suffering from huge volume expansion and pulverization amidst the alloying/dealloying processes, it presents difficulties in applications as an anode material. Herein, a core–shell-structured Mn2SnO4@Void@C anode material was successfully synthesized using a layer-wise assembly and selective etching method. Tetraethyl silicate (TEOS) and resorcinol formaldehyde resin, serving, respectively, as sacrificial template (SiO2) and carbon layer sources, were coated successively onto Mn2SnO4 particles. Adopting an alkali etching process, the SiO2 template was removed, and a Mn2SnO4@Void@C was therewith constructed. As Mn2SnO4 is well wrapped by a carbon shell and there are enough voids therein, its volume expansion whilst cycling can be significantly buffered. Moreover, the porous structure in Mn2SnO4@Void@C can provide convenient channels for ion transport and alleviate volume changes. Mn2SnO4@Void@C exhibits upgraded capacity and long cycling stability, since its specific capacity is maintained at 783.1 mA h g−1 at 100 mA g−1 after 150 cycles and at 553.3 mA h g−1 at 1000 mA g−1 after 1000 cycles. [ABSTRACT FROM AUTHOR]

Multi-speed transmission is the main development direction of hybrid transmission, which has brought higher shift quality requirements than traditional fuel vehicle transmission. However, there is less research on the shifting control of hybrid transmission, especially for the shifting control of dedicated hybrid transmission (DHT), which uses the wet clutch as a shift element. This paper studies the power-on downshift process of a two-speed series-parallel hybrid transmission, proposes a shifting control strategy based on motor active speed regulation, and deeply analyzes the causes of maximum impact during the shifting process. The results show that the reverse torque produced in the process of eliminating the remaining slip is the root cause of the maximum impact. On this basis, two optimization strategies are proposed to reduce the shift impact and improve the shift quality. The simulation results show that the proposed optimization strategies can effectively suppress the shift impact. In the meanwhile, for any control pressure of the OG (off-going) clutch in the speed phase within the range of (2.44–2.53 bar), a high shift quality in which the maximum impact is controlled lower than 10 m/s3 can be achieved, which has high engineering value and practical significance. [ABSTRACT FROM AUTHOR]

Key message: The novel, leaf rust seedling resistance gene, Lr81, was identified in a Croatian breeding line and mapped to a genomic region of less than 100 Kb on chromosome 2AS. Leaf rust, caused by Puccinia triticina, is the most common and widespread rust disease in wheat. Races of Puccinia triticina evolve rapidly in the southern Great Plains of the USA, and leaf rust resistance genes often lose effectiveness shortly after deployment in wheat production. PI 470121, a wheat breeding line developed by the University of Zagreb in Croatia, showed high resistance to Puccinia triticina races collected from Oklahoma, suggesting that PI 470121 could be a leaf rust resistance source for the southern Great Plains of the USA. Genetic analysis based on an F2 population and F2:3 families derived from the cross PI 470121 × Stardust indicated that PI 470121 carries a dominant seedling resistance gene, designated as Lr81. Linkage mapping delimited Lr81 to a genomic region of 96,148 bp flanked by newly developed KASP markers Xstars-KASP320 and Xstars-KASP323 on the short arm of chromosome 2A, spanning 67,030,206–67,132,354 bp in the Chinese Spring reference assembly (IWGSC RefSeq v1.0). Deletion bin mapping assigned Lr81 to the terminal bin 2AS-0.78–1.00. Allelism tests indicated that Lr81 is a distinctive leaf rust resistance locus with the physical order Lr65-Lr17-Lr81. Marker-assisted selection based on a set of markers closely linked to leaf rust resistance genes in PI 470121 and Stardust enabled identification of a recombinant inbred line RIL92 carrying Lr81 only. Lr81 is a valuable leaf rust resistance source that can be rapidly introgressed into locally adapted cultivars using KASP markers Xstars-KASP320 and Xstars-KASP323. [ABSTRACT FROM AUTHOR]

Automation and intelligent health monitoring technologies will be one of the most important development directions for rail transit operation and maintenance considering the continuous expansion of the scale of urban rail transit and the increase of labor costs. The highly accurate, full-field data acquisition based on vision measurement technology, which is combined with photogrammetry and three-dimensional scanning technology, is an effective way to improve the intelligence of monitoring. In this paper, accuracy tests of vision measurement and total station technology in multipoint measurement is carried out under the same conditions where the accuracy and reliability are compared according to the various datasets which are collected from experiment and testing. A novel visual measurement technology is proposed for the deformation monitoring of tunnel structures, such as settlement and convergence. The results show that the measurement system has a resolution of 0.01 mm which is better than the total station resolution, and the deviation ratios of the vertical and horizontal displacement are 1.6% and 2.5%, which demonstrate the proposed system has a good potential for practical applications in terms of resolution and accuracy. [ABSTRACT FROM AUTHOR]

Gabion has been extensively used in retaining walls and slope protection. This study carries out a safety risk analysis of a new structure combining basalt fiber reinforcement (BFR) and the traditional gabion structure. The micro-parameters of BFR and soil were calibrated by using the 3D discrete element method after the tensile test of BFR was completed. The mechanical property of the gabion unit was investigated by using a refined model and a numerical test of uniaxial compression. This work developed a simplified method to simulate the seepage effect. The stress condition and sliding displacement between gabions were also investigated. Deformation, stress, and porosity were all used to evaluate the stability of the new type of gabion slope. According to this study, BFR has a tensile strength of 68.22 MPa, and the safety factor increased by 25.68% after using these BFR gabions. The damage is mainly manifested by bending the BFRs and the dislocation of the gabion units, as the slope does not slip. It is indicated this novel gabion structure has a lower safety risk compared to traditional ones, and thus can be popularized and used in retaining walls and slope protection. [ABSTRACT FROM AUTHOR]

In the development of high-performance lithium-ion batteries (LIBs), the composition and structure of electrode materials are of critical importance. Silicon has a theoretical specific capacity 10 times that of graphite, nonetheless, its application as an anode material confronts challenge as it undergoes huge volume change and pulverization amidst the alloying and dealloying processes. Herein, a novel method to prepare a multilayer Si-based anode was proposed. Three layers, SiO 2 , nickel and triethylene glycol (TEG), were coated successively on Si nanoparticles, which served respectively as the sources of SiO x , sacrificial templates and carbon. Nickel can not only serve as a hollow template, but also play a catalytic role, which makes carbonization and redox reactions occur synchronously under a mild condition. Amid the carbonization process of TEG at 450 °C, several-nm-thick SiO 2 layer can react with the as-derived carbon to form a silicon suboxides (SiO x (0 < x < 2)) intermedium layer. After removing the nickel template, a micro-nano scaled Si@SiO x @void@C with conformal multilayer-structure can be obtained. The BET specific surface area and pore volume of powders were increased dramatically because of the derivation of abundant voids, which can not only buffer the swelling effect of silicon, but also provide richer ionic conductivity. The as-assembled half-cell with Si@SiOx@void@C as the anode material possesses high capacity (∼1000 mAh g−1 at 3 A g−1), long cycle life (300 cycles with 77% capacity retention) and good rate performance (558 mAh g−1 at 5 A g−1). [Display omitted] [ABSTRACT FROM AUTHOR]

Thin-walled structures have been widely adopted in engineering projects because of the advantages of good load-bearing capacity, light weight and low cost. In this paper, a refined finite element method (FEM) based on the Carrera Unified Formula (CUF) is performed to analyze the free vibration of thin-walled beams with the variables cross-section, length and boundary. The low-dimensional FEM method could improve the efficiency of numerical analysis and reduce the time consumption. The one-dimensional (1D) CUF is employed in which the models are assumed to be a beam-like axis-oriented structures. In this case, the geometry of the thin-walled beam can be discretized as a limited number of 1D beam elements along the axis, while the Lagrange polynomial expansion may be used to approximate the displacement field on the cross-beam surface. Thus, FEM matrices and vectors can be written in terms of fundamental nuclei whose forms are independent of beam theories. The validity and capabilities of the method presented are examined in some numerical examples, and a comparative study is carried out between the method proposed and the three-dimensional element method with and without warping solutions. The results obtained by CUF 1D models are in close agreement with the reference solutions. In addition, it has been argued that the innovative approach presented in this paper can be used as a precise tool for structural analysis for complex cross-section thin-walled beams to reduce computational costs. [ABSTRACT FROM AUTHOR]

To address the comprehensive optimization problem of driving performance and fuel economy in the driving process of hybrid electric vehicles (HEV) in the car-following scene in the connected environment, an energy management strategy (EMS) based on front vehicle speed prediction and ego vehicle speed planning is designed by combining intelligent transportation system (ITS) technology. The front vehicle speed predictor is first established based on the long short-term memory neural network (LSTM). Then, based on the predicted speed of the front car, the predictive cruise control (PCC) strategy is designed for realizing the speed control in the car-following scene by combining it with the adaptive cruise control (ACC). Finally, based on the planned vehicle speed, deep reinforcement learning (DRL)-based EMS is used to optimize the power distribution among different power components of HEVs. The analysis of simulation results under the SUMO-Python joint simulation platform verifies the proposed strategy. • A novel speed prediction method based on LSTM is proposed. • The established method improves the prediction accuracy effectively. • An advanced PCC strategy proposed to improve the safety and comfort of the vehicle. • A hierarchical control strategy combining car-following control and energy management is proposed and verified. [ABSTRACT FROM AUTHOR]

In the process of target detection with active light sources as calibration objects, air scattering and air absorption cause a significant loss of light energy, resulting in distortion and fragmentation of the spot shape. Inspired by band-pass filtering, this study proposes a target detection method based on variable frame rate sampling of an active light source. It primarily adopts i) image modulation for collecting the active light source signal with a specified frequency and subtracting the background, and ii) variable frame rate sampling for further weighted average to attenuate the dynamic noise. The experimental results show that the proposed method can efficiently eliminate static background, suppress dynamic noise, and detect the target location without illumination and background requirements. [ABSTRACT FROM AUTHOR]

Driven by electrostatic attraction, Ce4+ ions or/and positively charged detonation nanodiamond (DND) particles can absorb onto negatively charged polystyrene (PS) spherical colloids. Three types of core-shell structured composite abrasives, PS@CeO 2 , PS@DND and PS@CeO 2 /DND, can thus be assembled. When PS@CeO 2 and PS@DND were used to polish sapphire wafer at pad rotating speed of 120–150 r/min and load pressure of ~3 kg, the material removing rate (MRR) exceeded 1.0 μm h−1, 10–20 % higher than unitary abrasives. The surface profile roughness (Ra) for wafer polished by these two composite abrasives was respectively 1.25 and 0.63 nm, which is superior to CeO 2 (Ra = 1.38 nm) and DND (Ra = 1.29 nm). When using PS@CeO 2 /DND, the polishing interface area can be increased owing to the combined effect of elastic PS spheres and intensively coated CeO 2 and DND. Meanwhile, the synergistic mechanism of sapphire-CeO 2 chemical reaction and the strong mechanical abrasion of DND particles benefit the polishing efficiency. MRR for this ternary composite abrasive attained 1.4–1.7 μm h−1 while sapphire can be smoothed to a sub-nanoscale roughness. [Display omitted] [ABSTRACT FROM AUTHOR]

Greenbug (Schizaphisgraminum Rondani) is one of the aphids causing significant cereal yield losses worldwide, and greenbug Biotype H is virulent to all known greenbug resistance genes in barley (Hordeum L.). Wild barley (Hordeum vulgare ssp. spontaneum) accession WBDC336 (PI 682028) exhibits resistance to greenbug Biotypes C, E, H, I, WY81, WY12 MC, and WY86. To investigate the genetics of greenbug resistance in WBDC336, a recombinant inbred line (RIL) population was developed from the cross Weskan × WBDC336. The RIL population was evaluated for responses to greenbug Biotype E and genotyped using genotyping‐by‐sequencing. Among 67,238 single nucleotide polymorphisms (SNPs) identified, 3,907 high quality SNPs were selected for gene mapping after several filtering steps. Linkage analysis positioned the greenbug resistance gene to a 1.14‐Mb interval in the terminal region of the long arm of chromosome 3H in WBDC336, where the greenbug resistance gene Rsg1 resides. Greenbug assays and an allelism test indicated that the greenbug resistance gene in WBDC336 is likely an allele at the Rsg1 locus and was given the allele designation Rsg1.a3. Two Kompetitive allele‐specific polymerase chain reaction (KASP) markers were developed from SNPs closely linked to Rsg1.a3, and these markers can be used to tag both alleles at the Rsg1 locus in breeding program utilizing marker‐assisted selection. Core Ideas: The first barley gene conferring resistance to greenbug Biotype H was identified in WBDC366.The greenbug resistance gene in WBDC366, designated Rsg1.a3, is likely allelic to Rsg1.Two KASP markers closely linked to Rsg1.a3 were developed for marker‐assisted selection. [ABSTRACT FROM AUTHOR]

Architectural structures today are increasingly complex and structural health monitoring plays an important role in guaranteeing their safety. How to improve the reliability of deformation analysis is, thus, one of the key problems. This article combines laser-based measurement technology and the Carrera unified formulation (CUF) method to investigate the deformation of engineering structures. Within this article, we simulate architectural structures using the CUF geometric model, which is consistent with the results of the laser tracker experiment. We aimed at constructing an intelligent and efficient CUF model which can be applied extensively in the monitoring of various constructs, such as tunnels and bridges. The innovation of this article is that high-accuracy laser tracker technology is integrated with an effective CUF model to investigate the load-displacement relationship considering lateral displacement. [ABSTRACT FROM AUTHOR]

Freeform parameterizations to reproduce structure deformation are increasingly important topics in laser-scanner-based deformation analyses. High-accuracy assurance of free-form surface approximation is extremely critical for reliable deformation analysis. One main challenge in this field is the model selection. Improper model complexity could result in under-fitting the real object shape or overfitting data noises, and thus a failure of deformation analysis. A multi-sensor system could integrate advantages of different sensors and improve the quality of mission completed. This paper combines terrestrial laser scanning (TLS) and laser tracker (LT) technologies, to enhance high-accuracy surface modeling in deformation analysis. A surface-based B-spline approximation and a multi-sensor system are investigated, the latter of which focuses mainly on the combination of TLS and LT technologies. The innovation of this paper is that the surface-based B-spline approximation is validated and optimized with LT corner cube reflectors. Hypothesis testing is adopted to select the best parameter setting by judging most consistency of TLS and LT in various epochs. In the B-spline surface modeling, both instrumental and numerical uncertainties are considered. We use the instrumental uncertainty model based on intensity value, as well as numerical uncertainty based on adjustment theories. A sampling strategy is proposed to avoid data gaps and obtain even distributed data points. [ABSTRACT FROM AUTHOR]

In recent years, vortex recognition method based on velocity gradient has rapidly become a research hotspot, accompanied by a wide range of applications. As a linear velocity field with the origin as its critical point uniquely corresponds to the velocity gradient, its streamline pattern (SP), especially the spiral streamline structure when the velocity gradient has a couple of complex eigenvalues, is studied using the right eigen representation based on the real Schur form. Compared with the left eigen representation, the right eigen representation of velocity gradient is seldom concerned. In this paper, the right eigen representation is carried out in terms of the spectral representation, and its relation with the left eigen representation is also derived. For two-dimensional case, the SP classification is listed and the typical streamlines are illustrated. After detailed investigation, it is shown that the parameters extracted from the right eigen representation would be more suitable to describe the geometrical features of the spiral streamline pattern around the critical point, and the dual directivity of spiral streamline structure is clarified. Some discussions and an illustrative example from the direct numerical simulation (DNS) data are presented. [ABSTRACT FROM AUTHOR]

This paper deals with the speed synchronization control of a connected vehicle subject to a replay attack. A large number of replay attack signals are injected into controller area network (CAN) through external network, which greatly reduces the real-time control performance of a connected integrated motor-transmission (IMT) system. In order to ensure the performance of an IMT speed tracking system under large random message delays, a robust reset controller combined with a delay-robust speed synchronization controller satisfying energy-to-peak performance is designed in this paper. The uncertain impact caused by a replay attack is described by large random network delays which are modeled by polytopic inclusion. Then, a dynamic output-feedback controller considering the uncertainty caused by attack-delays is proposed for online speed tracking. Moreover, a robust reset controller is designed to obtain comparatively better transient response in the case of large attack-delays. In this control strategy, once the reset condition is triggered, the after-reset value calculated by linear matrix inequalities (LMIs) would replace the dynamic state vector. Finally, the effectiveness of the proposed controller is verified by comparing it with model predictive control (MPC), existing PD control considering delays and energy-to-peak robust control in terms of performance. [ABSTRACT FROM AUTHOR]

Neuromuscular blocking agents (NMBAs) are routinely used during anesthesia to relax skeletal muscle. Nicotinic acetylcholine receptors (nAChRs) are ligand-gated ion channels; NMBAs can induce muscle paralysis by preventing the neurotransmitter acetylcholine (ACh) from binding to nAChRs situated on the postsynaptic membranes. Despite widespread efforts, it is still a great challenge to find new NMBAs since the introduction of cisatracurium in 1995. In this work, an effective ensemble-based virtual screening method, including molecular property filters, 3D pharmacophore model, and molecular docking, was applied to discover potential NMBAs from the ZINC15 database. The results showed that screened hit compounds had better docking scores than the reference compound d-tubocurarine. In order to further investigate the binding modes between the hit compounds and nAChRs at simulated physiological conditions, the molecular dynamics simulation was performed. Deep analysis of the simulation results revealed that ZINC257459695 can stably bind to nAChRs' active sites and interact with the key residue Asp165. The binding free energies were also calculated for the obtained hits using the MM/GBSA method. In silico ADMET calculations were performed to assess the pharmacokinetic properties of hit compounds in the human body. Overall, the identified ZINC257459695 may be a promising lead compound for developing new NMBAs as an adjunct to general anesthesia, necessitating further investigations. [ABSTRACT FROM AUTHOR]

Greenbug [Schizaphis graminum (Rondani)] is a destructive pest of wheat (Triticum aestivum L.) worldwide. Incorporation of wheat greenbug resistance genes in wheat‐breeding pipelines is critical to improve wheat production. The greenbug resistance gene Gb5, originally identified in Triticum speltoides chromosome 7S and transferred to wheat chromosome 7A, confers resistance to several economically important greenbug biotypes. The T. speltoides chromosome segment carrying Gb5 was previously shortened by means of homoeologous recombination induced by the ph1b gene, which minimized linkage drag and made Gb5 a useful gene for improvement of greenbug resistance in wheat. This study characterized the shortened T. speltoides chromosome segment in PI 603919 and developed kompetitive allele‐specific polymerase chain reaction (KASP) markers to facilitate its introgression in wheat breeding. A set of 21 simple sequence repeat (SSR) markers specific to wheat 7AL chromosome were developed to determine the length and location of the T. speltoides chromosome segment. The T. speltoides segment in PI 603919 was estimated to be about 79.5–87.8 Mb in the Chinese Spring reference sequence IWGSC RefSeq v.1.0. A recombinant inbred line (RIL) population derived from a cross between CI 17884, which carries the original wheat‐T. speltoides 7A‐7S translocation chromosome segment, and Bainong 418 was genotyped using the genotyping‐by‐sequencing (GBS) approach and evaluated for responses to greenbug biotype E. Three GBS‐derived single nucleotide polymorphisms (SNPs) on the shortened translocation segment were converted to KASP markers. These KASP markers were evaluated for efficacy to select Gb5 in wheat breeding. [ABSTRACT FROM AUTHOR]

A nanocomposite, reduced graphene oxide (RGO) modified ZnCo2O4 (ZnCo2O4–RGO) was synthesized via one-step solvothermal method for activating persulfate (PS) to degrade bisphenol A (BPA). The morphology and structure of the nanocomposite were identified by X-ray diffraction, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, scanning electron microscopy, and transmission electron microscopy. RGO provides nucleation sites for ZnCo2O4 to grow and inhibits the agglomeration of the nanoparticles. The influence of different reaction conditions on the oxidation of BPA catalyzed by ZnCo2O4–RGO was investigated, including the content of RGO, the dosage of catalyst, the concentration of humic acid (HA), anions in the environment, the reaction temperature, and pH. BPA can be totally degraded within 20 min under optimized reaction conditions. The presence of HA, Cl−, and NO3− only has a slight effect on the oxidation of BPA, whereas the presence of either H2PO4− or HCO3− can greatly inhibit the reaction. ZnCo2O4–RGO shows good cycling stability and practical application potential. A reaction mechanism of the degradation of BPA was also explored. [ABSTRACT FROM AUTHOR]

Tomato leaf mould disease is a serious foliar disease caused by Cladosporium fulvum, resulting in a significant reduction in yield and quality, especially under protected cultivation. Finding new resistant genes against leaf mould has become one of the important goals of tomato breeding. Cf‐12‐tomato showed good resistance to several C. fulvum races. The Cf‐12 was mapped using re‐sequencing and BSA methods. Allelism test for Cf‐12, Cf‐5 and Cf‐9 was performed. The results showed that Cf‐12 is an independently assigned C. fulvum resistance gene. About 67,853 high‐quality polymorphic SNPs were found and 233 genes were annotated in three associated regions of 5.85 Mb on Chr. 6s. Three genes with typical Cf‐type characters encoding the leucine‐rich repeat receptor‐like protein were screened out. Using qRT‐PCR, structural and phylogenetic analysis, only the Solyc06g008265.1.1‐CGN7495 was finally identified. An effective InDel marker, InD‐3F/1R, was designed for MAS breeding. Our research provides new insights into the mapping of the Cf‐12, and provides a basis for Cf‐12 cloning and the Cf genetic evolution analysis. [ABSTRACT FROM AUTHOR]

The Russian wheat aphid (RWA, Diuraphis noxia Kurdjumov) is a global pest of wheat (Triticum aestivum L.) that became a significant problem to wheat and barley (Hordeum vulgare L.) in the United States soon after it was detected in 1986. Russian wheat aphid‐resistant wheat varieties expressing the Dn4 gene were effective in managing the first biotype, RWA1, from 1995–2003 until a new biotype, RWA2, overcame this resistance in 2003. Currently, only three genes are useful in developing RWA2 resistance in wheat. A new gene, Dn10, was recently discovered that is resistant to RWA2. This study characterized the effects that RWA1 and RWA2 had on the damage (leaf chlorosis and leaf roll) and growth components (plant height and leaf number) of plants expressing RWA resistance genes Dn4, Dn7, Dn10, Dn2401, Dn626580, and Dn2414 and the susceptible 'Yuma' 22 d after infestation. All plant genotypes that were RWA resistant expressed strong resistance to leaf chlorosis and leaf roll after RWA1 feeding. Results were similar for RWA2 except for the Dn4 genotype, which was equally susceptible as Yuma. Plant height was reduced by 50% for susceptible Yuma and Dn626580 by RWA1 and RWA2 feeding. Plant height and leaf reduction from RWA2 feeding on the susceptible Dn4 genotype were also reduced by 50%, whereas Dn7, Dn10, and Dn2414 reductions were <23%. Dn10 exhibited strong resistance to RWA1 and RWA2 feeding damage comparable with Dn7 and Dn2414 and showed less reduction in plant height than Dn2401 and Dn626580, which makes it a potentially valuable gene for wheat breeding programs. [ABSTRACT FROM AUTHOR]

Russian wheat aphid (Diuraphis noxia Kurdjumov [RWA]) is one of the most invasive and detrimental pests, and host plant resistance is the most efficient approach to manage RWA. Wheat (Triticum aestivum L.) accessions resistant to RWA biotype 1 (RWA1) and biotype 2 (RWA2) were previously identified by screening wheat accessions available at the USDA‐ARS National Small Grains Collection. However, RWA biotypic variation necessitates a continuous search for sources of resistance to new RWA biotypes. The objective of this study was to identify wheat accessions resistant to all major RWA biotypes in the United States. A set of 172 RWA‐resistant wheat accessions, mainly Iranian landraces, were evaluated for responses to five predominant U.S. biotypes—RWA1, RWA2, RWA3, RWA6, and RWA8—in controlled environments. Of these, 137 accessions showed homogeneous or heterogeneous resistance to at least one biotype, and 14 of them were resistant or highly resistant to all five biotypes. Another set of 19 accessions were resistant or highly resistant to two to four biotypes. These RWA‐resistant accessions are valuable sources for RWA resistance improvement, and further purification of some accessions and characterization of the underlying RWA resistance genes are imperative for their utilization in wheat breeding. [ABSTRACT FROM AUTHOR]

Spherical Ni2SnO4 nanoparticles were uniformly loaded on reduced graphene oxide (RGO) sheets via a hydrothermal process. The obtained nickel stannate–reduced graphene oxide (Ni2SnO4–RGO) composite was used as a catalyst for activating persulfate (PS). The heterostructure composed of Ni2SnO4 and RGO prevents both the agglomeration of Ni2SnO4 nanoparticles and the restacking of RGO sheets. The synergy between the two components affords enhanced Ni2SnO4–RGO catalytic activity. Using Ni2SnO4–RGO to activate PS can degrade bisphenol A (BPA) at a faster rate with less PS, in comparison with the most recently reported catalysts. BPA solution (50 mL, 0.10 mM) can be 100% degraded by PS (0.02 g) within 30 min at pH 8 using Ni2SnO4–RGO (0.02 g) as the catalyst. Moreover, the preparation of Ni2SnO4–RGO is simple, inexpensive and environment-friendly. The radical scavenging study indicates that sulfate radicals () and hydroxyl radicals (˙OH) are involved in the oxidation, in which plays a leading role. In addition, Ni2SnO4–RGO retains high catalytic activity after four consecutive cycles, exhibiting greatly enhanced stability in comparison with Ni2SnO4. Besides, the effect of different inorganic anions on the degradation was also explored. [ABSTRACT FROM AUTHOR]

The hazards of cracks, which could badly decrease reliability and safety of structures, are receiving increasing attention with the popularity of tunnel constructions. Traditional crack inspection relies on visual examination, which is time-, cost- and labor-intensive. Therefore, how to identify and measure cracks intelligently is significantly essential. The paper focuses on the Canny method to extract cracks of tunnel structures by the intensity value of reflectivity. We propose and investigate a novel method which combines dilation and the Canny algorithm to identify and extract the cracks automatically and intelligently based on the point cloud data of terrestrial laser scanning measurement. In order for measurement of cracks, the projection of summed edge pixels is adopted, where a synthesis is carried out on the detection results with all sampling parameters. Based on the synthesized image, vertical crack presents two sharp peaks where the space of the peaks indicates the average width of the crack, as well as its position. The advantage of the method is that it does not require determination of Canny detector parameters. The deviation between manual measurement and Canny detection is 2.92%. [ABSTRACT FROM AUTHOR]

Key message: A new greenbug resistance gene Gb8 conferring broad resistance to US greenbug biotypes was identified in hard red winter wheat line PI 595379-1 and was mapped to the terminal region of chromosome 7DL. Greenbug [Schizaphis graminum (Rondani)] is a worldwide insect pest that poses a serious threat to wheat production. New greenbug resistance genes that can be readily used in wheat breeding are urgently needed. The objective of this study was to characterize a greenbug resistance gene in PI 595379-1, a single plant selection from PI 595379. Genetic analysis of response to greenbug biotype E in an F2:3 population derived from a cross between PI 595379-1 and PI 243735 indicated that a single gene, designated Gb8, conditioned resistance. Linkage analysis placed Gb8 in a 2.7-Mb interval in the terminal bin of chromosome 7DL (7DL3-082-1.0), spanning 595.6 to 598.3 Mb in the Chinese Spring IWGSC RefSeq version 1.0 reference sequence. Gb8 co-segregated with a newly developed SSR marker Xstars508, positioned at 596.4 Mb in the reference sequence. Allelism tests showed that Gb8 was different from three permanently named genes on the same chromosome arm and the estimated genetic distance between Gb8 and Gb3 was 15.35 ± 1.35 cM. Gb8 can be directly used in wheat breeding to enhance greenbug resistance. [ABSTRACT FROM AUTHOR]

Based on the cognition of the physiological structure of the human visual system, this paper considers that the mechanism of the human visual system to perceive the image color appearance includes the adaptive mechanism of the retinal photoreceptor to the ambient light and the spatial frequency response mechanism of the Neuronal receptive field in the visual pathway. In this paper, we first provide the computing framework of the image color appearance model related to human cognitive process, then propose using Gabor wavelet as the basis function of the visual nerve cells response to apply CIECAT02 model to the calculation of image color adaption and to simulate the multi-scale superposition of human visual spatial frequency tuning curves, and finally accomplish the development of the algorithm for predicting image color appearance. The results show that the prediction algorithm proposed in this paper is closer to the visual perception of human eyes than the similar algorithm. [ABSTRACT FROM AUTHOR]

With the increasing of tunnel mileage, one of the most vital problems of broad-scale structures is the intelligent identification and location of structural defects, which require massive data storage capacity and high data processing efficiency. The full-field point cloud data collected by terrestrial laser scanning (TLS) can be extracted to construct three-dimensional measured models more accurately, therefore, the fusion of TLS and the finite element method (FEM) is particularly beneficial to the deformation analysis of tunnel structures. This paper combines numerical simulation and full-field measurement to interactively verify the reliability of deformation analysis based on FEM simulation and point cloud processing. The innovation of this paper is that a three-dimensional FEM is validated through the measured point cloud data of the tunnel structure. The result of this study indicated that FEM simulation and the structural health monitoring analysis are consistent. [ABSTRACT FROM AUTHOR]

Morphology control and heterostructure construction are two essential aspects in designing and synthesizing photocatalysts. Herein, hollow microsphere heterojunctions of CeO 2 and Ce3+ doped BiOBr (Ce-BiOBr) were fabricated adopting a facile one-pot solvothermal approach. Owing to the positively charged Ce species, the interlamellar repulsion can be reduced and the specific surface area of these microsphere can be increased. The as-generated Ce4+/Ce3+ redox centers can synergistically improve the transfer and separation efficiency of photogenerated carriers. When used to treat Congo red (CR), 0.1CBOB with a Ce/Bi molar ratio of 0.1:1 exhibits the best photodegradation efficiency (94.63%) and kinetic rate (0.01119 min−1) under visible light-emitting diode (LED) light irradiation, which are remarkably superior to pure BiOBr and CeO 2. The results of radical capture experiment show that photogenerated hole (h+), superoxide radical (·O 2 −) are the main active species in the process of photocatalytic degradation. [Display omitted] • CeO 2 /BiOBr microsphere heterojunctions assembled via one-pot solvothermal route. • CeO 2 can weaken interflake electrostatic repulsion and enlarge special surface area. • Heterojunction and Ce4+/Ce3+ center donate jointly better photocatalytic efficiency. • Mechanisms for heterojunction construction and photodegradation well investigated. [ABSTRACT FROM AUTHOR]

A new gear tooth modification model of planetary gear system was established by considering the characteristics of tooth longitudinal crowning modification and tooth profile modification. Using this model, the influences of modification parameters on the time-varying mesh stiffness, transmission error, contact spots and dynamic response of the planetary gear system were analyzed through numerical analysis. The results show that tooth profile modification can effectively restrain the mesh stiffness sudden variation in the single and double tooth alternation of both the internal and external mesh pairs, and significantly decrease the transmission error fluctuation. However, longitudinal crowning modification has no marked influence on mesh stiffness sudden variation or transmission error fluctuation. The tooth profile modification can significantly reduce the sudden variation of tooth surface load during gear mesh course. Longitudinal crowning modification can make the tooth surface load evenly distributed in tooth width direction. When the external meshing pairs are modified at the tooth profile individually, the magnitude values of main response resonance peaks of internal meshing pairs have a great reduction, but those values of external meshing pairs change slightly. In the case of tooth profile modification of the internal meshing pairs, the phenomenon is reversed. By contrast with tooth profile modification, longitudinal crowning modification has little influence on the resonance peaks of internal and external meshing pairs. [ABSTRACT FROM AUTHOR]

Graphical abstract Mechanism of the activation on PS by NiFe 0.7 Co 1.3 O 4 -RGO for the degradation of BPA. Highlights • Magnetic NiFe 0.7 Co 1.3 O 4 -RGO 1 was fabricated via a simple hydrothermal route. • Bisphenol A was completely removed by NiFe 0.7 Co 1.3 O 4 -RGO/PS in 25 min. • Co doping enhances the activity of the catalyst for persulfate activation. • BPA degradation is achieved partly via nonradical pathway promoted by RGO. • The influence of reaction parameters for the mineralization of BPA was evaluated. Abstract A simple route was reported for the synthesis of reduced graphene oxide (RGO) based NiFe 2−x Co x O 4 nanocomposite (NiFe 2−x Co x O 4 -RGO), a catalyst to activate persulfate (PS) for the degradation of bisphenol A (BPA). The crystalline structure and morphology of the composite were characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and thermogravimetric analysis (TGA). It is confirmed that spherical NiFe 2−x Co x O 4 nanoparticles with a size around 14 nm are uniformly anchored on RGO sheets. Compared with recently reported catalysts, NiFe 0.7 Co 1.3 O 4 -RGO 1 exhibits impressively higher catalytic activity, leading to much faster degradation of BPA with pretty less PS used. Moreover, the excellent catalytic performance can be maintained in a wide range of pH. The radical scavenging study and EPR experiments indicate that free radical, surface-bound radical and nonradical processes are involved in the degradation of BPA. In addition, the degradation of various organic contaminants other than BPA were also carried out, indicating that NiFe 0.7 Co 1.3 O 4 -RGO 1 /PS system has higher catalytic activity toward BPA. [ABSTRACT FROM AUTHOR]

Similar to auditory perception of sound system, color perception of the human visual system also presents a multi-frequency channel property. In order to study the multi-frequency channel mechanism of how the human visual system processes color information, the paper proposed a psychophysical experiment to measure the contrast sensitivities based on 17 color samples of 16 spatial frequencies on CIELAB opponent color space. Correlation analysis was carried out on the psychophysical experiment data, and the results show obvious linear correlations of observations for different spatial frequencies of different observers, which indicates that a linear model can be used to model how human visual system processes spatial frequency information. The results of solving the model based on the experiment data of color samples show that 9 spatial frequency tuning curves can exist in human visual system with each lightness, R–G and Y–B color channel and each channel can be represented by 3 tuning curves, which reflect the "center-around" form of the human visual receptive field. It is concluded that there are 9 spatial frequency channels in human vision system. The low frequency tuning curve of a narrow-frequency bandwidth shows the characteristics of lower level receptive field for human vision system, the medium frequency tuning curve shows a low pass property of the change of medium frequent colors and the high frequency tuning curve of a width-frequency bandwidth, which has a feedback effect on the low and medium frequency channels and shows the characteristics of higher level receptive field for human vision system, which represents the discrimination of details. [ABSTRACT FROM AUTHOR]

Highlights • A P2 hybrid powertrain model is built to support developing control strategy. • A multiphase control strategy is developed for different engine-start situations. • A nonlinear feedforward-feedback controller is designed for trajectory tracking. • Simulations and experiments have verified the developed control strategy. Abstract Instead of using conventional starter, engine can be started through slipping of the disconnect clutch in P2 hybrid automatic transmission. However, both riding comfort and engine-start time are challenges for control of the starting process. In order to achieve smooth and quick engine start, this paper proposed an optimized control strategy with respect to different engine-start situations. Firstly, a model of P2 hybrid powertrain is developed to characterize the transient behavior during engine start and provide support for developing control strategies. A multiphase control strategy is then proposed to cope with the control objective of either good riding comfort or short starting time depending on different driving situations. A nonlinear feedforward-feedback controller based on differential flatness and proportional-integral-derivative (PID) algorithm is developed to regulate the current of direct operating solenoid valve. Thus the pressure of the disconnect clutch can be fine-tuned and good tracking capability for the reference trajectory of engine speed can be realized. Finally, simulation and test results demonstrate that the proposed control strategy and controller can satisfy different requirements for engine start. Both riding comfort and engine-start time of a P2 hybrid vehicle can be effectively improved in the engine starting process. [ABSTRACT FROM AUTHOR]

Biofloc technology is an efficient approach for intensive shrimp culture. However, the extent to which this process can influence the composition of intestinal microbial community is still unknown. Here, we surveyed the shrimp intestinal bacteria as well as the floc water from three biofloc systems with different stock densities. Our study revealed a similar variation trend in phylum taxonomy level between floc bacteria and gut microbiota. Microbial community varied notably in floc water from different stock densities, while a core genus with dominating relative abundance was detected in gut samples. Extensive variation was discovered in gut microbiota, but still clustered into groups according to stock density. Our results indicated that shrimp intestinal microbiota as well as bacteria aggregated in flocs assembled into distinct communities from different stock densities, and the intestinal communities were more similar with the surrounding environment as the increase of stock density and resulting high floc biomass. The high stock density changed the core gut microbiota by reducing the relative abundance of Paracoccus and increasing that of Nocardioides, which may negatively influence shrimp performance. Therefore, this study helps us to understand further bacteria and host interactions in biofloc system. [ABSTRACT FROM AUTHOR]

Highlights • A simulation model considering time-varying tooth profile was presented. • A fatigue criterion to predict the crack initiation position was developed. • A wear rate model to predict material removal from the tooth flank was proposed. • Experiments were carried out to verify the validity of the simulation model. Abstract Micro-pitting is an early-stage failure mode commonly found in gears. It leads to macro-pitting, spalling, and even tooth fracture failure, which cause destructive damage to gearboxes. A simulation model to predict the initiation and propagation of micro-pitting on tooth flanks of spur gears is presented. The model simulates the actual gear meshing process, considering the time-varying tooth profile. The contact pressure distribution, sliding velocities, rolling velocities, film thicknesses, and shear stresses along the contact line are accurately calculated. A new crack criterion is proposed to predict the initial crack position. A novel wear rate model was developed by considering the influence of crack density to predict the propagation of micro-pitting and the removal of material from the tooth flank. The results of experiments carried out for gear pairs with different tooth tip reliefs and surface roughness showed good agreement with the simulation results. This verified the model validity. [ABSTRACT FROM AUTHOR]

Abstract Terrestrial laser scanning is extensively adopted in the area of high-precision monitoring and three-dimensional measurement. Architectural structures today are increasingly complex and health monitoring plays an important role in guaranteeing their safety. Therefore, how reliability deformation monitoring can be improved is one of the key problems in the field of engineering. This paper combines the three-dimensional laser scanning technology and finite element method (FEM) to investigate the deformation mechanism of arched structures. Within this paper, we simulated arched structures using the FEM, which is consistent with the result of terrestrial laser scanner (TLS) measurement. We aimed at constructing an intelligent and efficient FEM model which can be extensively applied in the monitoring of many constructs, such as bridges and ancient architecture. The focus in this research lies mainly on deformation analysis, which is based on FEM model simulation with the calibration of TLS measurement. [ABSTRACT FROM AUTHOR]

Abstract Automatically modeling and intelligently monitoring composite tunnel structures is of great significance considering the development of composite and diverse tunnel construction materials. Therefore, how to efficiently analyze the deformation of all kinds of tunnel structures with its expanding application is becoming increasingly important. In this paper, we analyze the over- and under-fitting problems under different point cloud profiles to generate an automatic and robust B-spline model which is a suitable method for high accuracy approximation capable of optimizing the composite tunnel model by adjusting the parameters. The innovation of this research is that we combine the maximum likelihood function and the degree of freedom to obtain the optimal parameters model of composite tunnels, which are validated by the various profiles. [ABSTRACT FROM AUTHOR]

Abstract The problem of the arch loading case is studied by the combination of finite element analysis (FEA) and B-Splines, which provides a highly accurate solution to the calibration problem of the FEA model. Attention is paid to the assessment of FEA by a high-accuracy two-dimensional B-Spline model using point clouds from terrestrial laser scanning (TLS) which is one of the most accurate measurement tools. In the current paper, a B-Spline-based optimized model, comparing to an idealized model, is applied in the FEA. Meanwhile, characteristics of arched nodal displacement and stress are discussed. The target function of the optimization is to reduce the displacement error. It is revealed that the B-Spline optimized model based on TLS data with high-accuracy could carry out FEA efficiently with fewer displacement errors, which is an important part of the automatic calibration of FEA. Finally, the equivalent stress in the post-computation is applied to predict the possible crack regions and carry out the damage monitoring. [ABSTRACT FROM AUTHOR]

Abstract Nowadays, with the development of demand for construction, the use of composite structures in architectures become more and more popularity. How to improve the intelligent level of deformation monitoring has become one of the key problems. A detailed understanding about deformation behavior is significant for better monitoring of structures, especially in terms of accuracy and detail. The innovation of this paper focuses on that terrestrial laser scanning (TLS) measurement is adopted to investigate deformation of the composite masonry structures. In this paper, deformation segmentation and analysis of the masonry structures are investigated and the deformation tendency is compared and analyzed, based on the intelligent data extraction by window selection method, where high precision 3D laser technology provides reliable experimental data for this research. The deformation of different surfaces of a composite arch is considered and the maximum displacement distribution is analyzed through partially comparing the deformation of different epoch data. [ABSTRACT FROM AUTHOR]

Abstract Terrestrial laser scanning (TLS) technology plays an important role in the field of deformation monitoring nowadays, and a lot of the architectures are arched composite structures, which are required to be further understood for their mechanical and physical properties. Only a theoretical numerical analysis is sometimes difficult and defective to achieve, due to varying loads and other factors influencing the stability and reliability of such structures. Therefore, measurements can improve the theoretical analysis in several ways. One of the most important issues is the deformation analysis within load experiments. This paper focuses on the presentation of new possibilities for surface-based measurement techniques and their applicability in the deformation analysis of arched structures. The goal of this paper is to investigate the difference of load-displacement relationships between arched and beam structures though a static load experiment based on high accuracy TLS measurement techniques and the surface analysis method. In this paper, we try to reveal the influencing mechanism of ‘prestressing-like’ force and interpret why arched structures can withstand a surprisingly greater load than beam structures under the same conditions. [ABSTRACT FROM AUTHOR]