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The drying-free preparation of coated magnetic particles has been proven to significantly improve the comprehensive performance and preparation efficiency of magnetorheological (MR) fluid. Due to the magnetic separation technique in the drying-free process, the residual anhydrous ethanol and silicone oil form a Pickering emulsion, whose influence on the properties of MR fluid is ignored in existing mechanical models. In this study, in order to improve the application accuracy of MR fluid and provide methods for further improvement of MR fluid performance, with consideration of the influence of the Pickering emulsion caused by the drying-free process, the tight simple cubic (TSC) structure model and the body-centered cubic (BCC) structure model of MR fluid were proposed based on the mechanism of chain formation of MR fluid and the magnetic dipole theory. To reflect the coexistence and transformation mechanism of these two structures, a distribution probability function was introduced and a hybrid spatial structure model comprised of both TSC and BCC structures was established. The validity and accuracy of the models were verified by the comparison with the experimental data. The proposed hybrid spatial structure micromechanical model considers the influence of Pickering emulsion on the microstructure of MR fluid and can accurately describe the properties of MR fluid prepared by the drying-free process. [ABSTRACT FROM AUTHOR]

Cancer remains a leading cause of mortality and poses a substantial threat to public health. Studies have revealed that Long noncoding RNA DANCR is a cytoplasmic lncRNA whose aberrant expression plays a pivotal role in various cancer types. Within tumour biology, DANCR exerts regulatory control over crucial processes such as proliferation, invasion, metastasis, angiogenesis, inflammatory responses, cellular energy metabolism reprogramming, and apoptosis. By acting as a competitive endogenous RNA for miRNAs and by interacting with proteins and mRNAs at the molecular level, DANCR contributes significantly to cancer progression. Elevated DANCR levels have also been linked to heightened resistance to anticancer drugs. Moreover, the detection of circulating DANCR holds promise as a valuable biomarker for aiding in the clinical differentiation of different cancer types. This article offers a comprehensive review and elucidation of the primary functions and molecular mechanisms through which DANCR influences tumours. [ABSTRACT FROM AUTHOR]

Building information modeling (BIM) can store a large amount of civil engineering information and has become a high-value economic and social resource. To improve BIM data interoperability, Industry Foundation Class (IFC) was proposed. However, the IFC instance data usually exceeds megabytes, and the logical relationship of the data is complex and changeable. Therefore, how to further enhance the usability of IFC instance data will become very important. To this end, this paper proposes a data deconstruction model 'Topological Induction Model (TIM)', which deconstructs the IFC instance data into a network structure 'Topological Induction Network (TIN)'. Through the analysis and operation of TIN, more effective utilization of IFC instance data can be realized. Based on TIN, the skeleton structure, citation structure and corresponding acquisition algorithm of IFC instance data are discussed, and the hierarchical characteristic, internal aggregation characteristic and data similarity of data topology are found. Subsequently, the working performance of TIM (TIN) is evaluated and compared with existing data deconstruction strategies. The results show that the overall performance of TIM (TIN) is better than traditional methods. Finally, we show how TIM (TIN) can be used in a graph database to enhance the usability of IFC instance data. [ABSTRACT FROM AUTHOR]

Building Information Modeling (BIM) has attracted much attention as a vital information method in civil engineering. BIM data research has become increasingly important with the continuous understanding of BIM. The database designed especially for storing BIM data (IFC data) is called a BIM database. To realize centralized storage and sharing of complex building information, how to design and develop a BIM database will be a hot topic. However, the BIM database designed using an existing logical model (such as a relational model) is unsuitable for storing and managing a large amount of BIM data. To this end, we propose a database logical model for BIM database development called 'logical object structure'. Based on the database design methodology, the logical schema of the BIM database is discussed, and five relation forms are established to describe the feature of engineering information. According to the relation forms, the logical object structure is presented, and the corresponding system implementation process is discussed. Finally, four workloads are set to test the logical object structure. The results show that the logical object structure can well support interactive behaviors of BIM data and provide good performance for the BIM database. [ABSTRACT FROM AUTHOR]

In confronting the urgent challenges within the realm of international development, it has become imperative to explore novel pathways for economic growth, diminish the income disparity among diverse societal segments, and alleviate the discrepancies between urban and rural regions. However, previous research has yet to comprehensively investigate whether information infrastructure holds the potential to narrow the urban-rural development gap. Furthermore, the distinctive contributions of traditional infrastructure and information infrastructure to economic development have been insufficiently explored and compared. Drawing upon data from the China Household Panel Study (CFPS) spanning the period 2010–2018, this study extensively examines the role and advantages of information infrastructure in bridging the urban-rural development gap. By employing the fixed effect model and employing the ‘Broadband China’ strategy as a proxy variable for information infrastructure enhancement, the study reveals that the improvement of information infrastructure significantly amplifies the total income of Chinese households, with a pronounced impact in rural areas. The emergence of a ‘catch-up effect’ serves to diminish the income disparity between urban and rural areas. Moreover, when contrasted with contemporaneous investments in traditional infrastructure, which have reached a state of relative saturation in China, the positive effect of information infrastructure upgrading surpasses that of traditional infrastructure investment. Hence, upgrading information infrastructure effectively addresses the imbalances in urban and rural development and narrows the income gap. These findings carry considerable implications for government bodies in formulating development policies. [ABSTRACT FROM AUTHOR]

With economic development and the burgeoning need for energy, numerous underground gas pipelines have been deployed for operation. Buried gas pipelines often suffer failures as a result of adverse factors, including corrosion, uneven subsidence, and damage caused by third parties. To investigate and predict the diffusion behavior following a natural gas pipeline leakage, Fluent software is utilized to develop a numerical model for the leakage and diffusion of high-pressure natural gas within a confined space. This model incorporates the Soave–Redlich–Kwong equation of state, which is widely recognized for its exceptional precision in characterizing the behavior of natural gas under high-pressure conditions. The study focuses on the analysis of leakage and diffusion behavior as well as the examination of how pipeline operating pressure and leakage diameter have an impact on the dispersion of leaked gas. Further, the prediction model for the diffusion distance of the hazardous area is developed, employing the least-square method and finite element calculations. The results show that, during the leakage process, a vortex and velocity region emerge, extending along the confined space. The farther away from the leakage hole above the pipeline, the higher the overall concentration of the gas. Moreover, the horizontal diffusion distance of gas at the bottom of the pipeline is considerably smaller than that above it. However, gas tends to readily accumulate in a high concentration area at the bottom of the pipeline. Elevating the leakage diameter and the operation pressure leads to a significant rise in gas concentration and the horizontal diffusion of the hazardous area. It is worth noting that the leakage diameter has a more pronounced effect on gas diffusion than does the pressure. The prediction model proposed in this study effectively anticipates the horizontal diffusion of the hazardous area within confined spaces. [ABSTRACT FROM AUTHOR]

This paper proposes an improved matching pursuit (MP) method with a multicomponent interference dictionary (MCID) based on a pipeline guided wave reflection model. The proposed method separates the overlapped time domain reflections from the notch edges and extracts parameters such as amplitude, time of flight (TOF), and phase to identify the number and axial dimensions of notches in pipes. Firstly, the performance of the method in identifying parameters of overlapped components affected by noise and reverberation under different signal-to-noise ratios (SNRs) and frequencies is analyzed using four error metrics. Secondly, finite-element (FE) models of pipes with a single notch and double notches are established, and the accuracy of the reflection model is validated by comparing the predicted amplitudes, TOF, and phase of reflections with the FE results. Finally, experimental validation is conducted on aluminum pipes with multiple notches. The consistency between the experimental results, theoretical results, and FE results in wave packet parameters confirmed the accuracy of the proposed reflection models. The method accurately captures the parameters of the reflections from each notch edge in the experimental pipes, enabling the identification of the number and axial dimensions of the notches. The method holds the potential for identifying a greater number of notches in pipelines and characterizing their axial dimensions. This can provide a reliable reference for developing maintenance plans based on pipeline operational conditions, thereby preventing major safety incidents. [ABSTRACT FROM AUTHOR]

Pipeline guided wave inspection is an efficient tool for determining the defect location. However, quantifying the defect size remains a challenging task. This paper proposes a quantification method for corrosion-like defects in pipelines based on the multifrequency identification of nondispersive torsional guided waves. First, a theoretical scattering model describing the T(0,1) wave's interaction with a simplified corrosion-like defect is introduced. Subsequently, a multifrequency identification method is proposed, enabling the inverse quantification of defect parameters by a defined spectral defect index (SDI). To implement this approach, a pseudo pulse-echo configuration is devised, which contains two rings of piezoelectric transducers attached on the pipeline's outer surface. Finite-element (FE) models are employed to test the performance of the proposed method for both axisymmetric and nonaxisymmetric defects, and an analysis of the robustness of the method is also conducted. The results show that this method has good accuracy even for signals with a very low signal-to-noise (SNR) ratio. Furthermore, an FE model is developed to validate the feasibility of this method for long-distance detection considering attenuation effect. Finally, experimental validation of the proposed method demonstrates close agreement between predicted and actual defect sizes, showing its potential for practical applications. [ABSTRACT FROM AUTHOR]

Traditional physics-based mathematical models of viscoelastic (VE) damper often exhibit different degrees of prediction errors under complex working conditions, whereas data-driven approaches have shown significant potential for overcoming such problems, and have not been introduced into any study to describe the dynamic mechanical properties of VE damper. In this paper, the architecture of microsphere model is adopted to represent the spatial distribution of molecular chain structure of VE damping material, which is categorized into free chains and elastic chains. Then, the physics-informed neural network surrogates are introduced to describe the statistical stress–strain behaviors of free chains and elastic chains. Finally, by constructing the physics-constrained loss function based on the combination of physics-based model and data-driven model, a physics-constrained data-driven model is proposed to characterize the dynamic mechanical behaviors of VE damper used for structure vibration control. Based on the existing experimental data, the prediction ability and robustness of the proposed model are comparatively verified, the results reveal that the proposed model can accurately reflect the stiffness and energy dissipation of VE damper under different ambient temperatures, excitation frequencies, and deformation conditions. This study proves the potential of physics-informed neural network theory in characterizing the complex mechanical behaviors of VE damper. [ABSTRACT FROM AUTHOR]

A conventional plate-type viscoelastic damper (VED) can easily crack at the interfaces of steel plates and viscoelastic components. In the present work, grooved VEDs, which are a new type of interfacial enhanced VEDs with interfacial grooves, are designed to improve the damping capacity and anti-cracking ability of conventional dampers. The dynamic property experiments of the normal and grooved VEDs are carried out and the interfacial cracking failure of the VEDs are simulated and analyzed by using bilayer cohesive constitutive model with ABAQUS. The grooved VED exhibits excellent dynamic performance and energy dissipation capacity at different temperatures, frequencies, and displacement amplitudes. Experiments and finite element analysis prove that the energy dissipation performance and interfacial bonding strength of the grooved VED are effectively improved. A modified fractional standard linear solid model, in which the Payne effect and temperature–frequency equivalent principle are combined and implemented, is proposed. This model can portray the influence of the excitation displacement, surrounding temperature and external excitation frequency on damper properties at the same time. The fillers and molecular chains affections at micro- and meso-scale are also taken into account. The model’s numerical calculations and experimental results comparisons present that the modified fractional standard linear solid model has sufficient accuracy and performs well in depicting the dynamic properties of the interfacial grooved VED. The errors between the theoretical and experimental values of G1 and G2 for the grooved VED are mostly within 20% at representative conditions. The interfacial groove structures can well enhance the interfacial bonding and improve the service life of conventional dampers. The modified fractional standard linear solid model is simple and has clear physical meanings for each macro/micro parameters, making it convenient for application in engineering practice. The present research is of great significance in improving the work stability of VEDs and promoting the application of viscoelastic damping technology. [ABSTRACT FROM AUTHOR]

Anaerobes dominate the microbiota of the gastrointestinal (GI) tract, where a significant portion of small molecules can be degraded or modified. However, the enormous metabolic capacity of gut anaerobes remains largely elusive in contrast to aerobic bacteria, mainly due to the requirement of sophisticated laboratory settings. In this study, we employed an in silico machine learning platform, MoleculeX, to predict the metabolic capacity of a gut anaerobe, Clostridium sporogenes, against small molecules. Experiments revealed that among the top seven candidates predicted as unstable, six indeed exhibited instability in C. sporogenes culture. We further identified several metabolites resulting from the supplementation of everolimus in the bacterial culture for the first time. By utilizing bioinformatics and in vitro biochemical assays, we successfully identified an enzyme encoded in the genome of C. sporogenes responsible for everolimus transformation. Our framework thus can potentially facilitate future understanding of small molecules metabolism in the gut, further improve patient care through personalized medicine, and guide the development of new small molecule drugs and therapeutic approaches. [ABSTRACT FROM AUTHOR]

Anaerobes dominate the microbiota of the gastrointestinal (GI) tract, where a significant portion of small molecules can be degraded or modified. However, the enormous metabolic capacity of gut anaerobes remains largely elusive in contrast to aerobic bacteria, mainly due to the requirement of sophisticated laboratory settings. In this study, we employed an in silico machine learning platform, MoleculeX, to predict the metabolic capacity of a gut anaerobe, Clostridium sporogenes, against small molecules. Experiments revealed that among the top seven candidates predicted as unstable, six indeed exhibited instability in C. sporogenes culture. We further identified several metabolites resulting from the supplementation of everolimus in the bacterial culture for the first time. By utilizing bioinformatics and in vitro biochemical assays, we successfully identified an enzyme encoded in the genome of C. sporogenes responsible for everolimus transformation. Our framework thus can potentially facilitate future understanding of small molecules metabolism in the gut, further improve patient care through personalized medicine, and guide the development of new small molecule drugs and therapeutic approaches. [ABSTRACT FROM AUTHOR]

The isolation technologies are adopted to protect the long-span space structures from serious damage under the action of earthquakes. When the isolation system is applied to the space structures, both horizontal and vertical vibration control effects on the structures should be concerned. In this paper, a two-dimensional earthquake isolation and mitigation device (TEIMD) composed of a high-damping viscoelastic (VE) core pad and VE dampers is proposed. Based on the dynamic shear experiment results of the VE damper, the energy dissipation capability of VE material is preferable. Then, the nonlinear equivalent stiffness and equivalent damping ratio of the TEIMD in horizontal and vertical directions are evaluated by using the numerical simulation method. The TEIMDs are arranged on the column top of a double-layer grid structure to assess the isolation effectiveness of the novel device. The dynamic analysis results of the double-layer grid structure with and without TEIMD reveal that this novel device can significantly reduce the acceleration response of the upper grid by relying on the strong energy dissipation performances in the horizontal and vertical directions. This research also verifies the feasibility of applying the TEIMD to the double-layer grid structure, which can effectively dissipate the vertical vibration energy of the structure. [ABSTRACT FROM AUTHOR]

In the last few decades, nanoparticles have been a prominent topic in various fields, particularly in agriculture, due to their unique physicochemical properties. Herein, molybdenum copper lindgrenite Cu3(MoO4)2(OH)2 (CM) nanoflakes (NFs) are synthesized by a one-step reaction involving α-MoO3 and CuCO3⋅Cu(OH)2⋅xH2O solution at low temperature for large scale industrial production and developed as an effective antifungal agent for the oilseed rape. This synthetic method demonstrates great potential for industrial applications. Infrared spectroscopy and X-ray diffraction (XRD) results reveal that CM samples exhibit a pure monoclinic structure. TG and DSC results show the thermal stable properties. It can undergo a phase transition form copper molybdate (Cu3Mo2O9) at about 300 °C. Then Cu3Mo2O9 nanoparticles decompose into at CuO and MoO3 at 791 °C. The morphology of CM powder is mainly composed of uniformly distributed parallelogram-shaped nanoflakes with an average thickness of about 30 nm. Moreover, the binding energy of CM NFs is measured to be 2.8 eV. To assess the antifungal properties of these materials, both laboratory and outdoor experiments are conducted. In the pour plate test, the minimum inhibitory concentration (MIC) of CM NFs against Sclerotinia sclerotiorum (S. sclerotiorum) is determined to be 100 ppm, and the zone of inhibiting S. sclerotiorum is 14 mm. When the concentration is above 100 nm, the change rate of the hyphae circle slows down a little and begins to decrease until to 200 ppm. According to the aforementioned findings, the antifungal effects of a nano CM NFs solution are assessed at different concentrations (0 ppm (clear water), 40 ppm, and 80 ppm) on the growth of oilseed rape in an outdoor setting. The results indicate that the application of CM NFs led to significant inhibition of S. sclerotiorum. Specifically, when the nano CM solution was sprayed once at the initial flowering stage at a concentration of 80 ppm, S. sclerotiorum growth was inhibited by approximately 34%. Similarly, when the solution was sprayed once at the initial flowering stage and once at the rape pod stage, using a concentration of 40 ppm, a similar level of inhibition was achieved. These outcomes show that CM NFs possess the ability to bind with more metal ions due to their larger specific surface area. Additionally, their semiconductor physical properties enable the generation of reactive oxygen species (ROS). Therefore, CM NFs hold great potential for widespread application in antifungal products. [ABSTRACT FROM AUTHOR]

In the last few decades, nanoparticles have been a prominent topic in various fields, particularly in agriculture, due to their unique physicochemical properties. Herein, molybdenum copper lindgrenite Cu3(MoO4)2(OH)2 (CM) nanoflakes (NFs) are synthesized by a one-step reaction involving α-MoO3 and CuCO3⋅Cu(OH)2⋅xH2O solution at low temperature for large scale industrial production and developed as an effective antifungal agent for the oilseed rape. This synthetic method demonstrates great potential for industrial applications. Infrared spectroscopy and X-ray diffraction (XRD) results reveal that CM samples exhibit a pure monoclinic structure. TG and DSC results show the thermal stable properties. It can undergo a phase transition form copper molybdate (Cu3Mo2O9) at about 300 °C. Then Cu3Mo2O9 nanoparticles decompose into at CuO and MoO3 at 791 °C. The morphology of CM powder is mainly composed of uniformly distributed parallelogram-shaped nanoflakes with an average thickness of about 30 nm. Moreover, the binding energy of CM NFs is measured to be 2.8 eV. To assess the antifungal properties of these materials, both laboratory and outdoor experiments are conducted. In the pour plate test, the minimum inhibitory concentration (MIC) of CM NFs against Sclerotinia sclerotiorum (S. sclerotiorum) is determined to be 100 ppm, and the zone of inhibiting S. sclerotiorum is 14 mm. When the concentration is above 100 nm, the change rate of the hyphae circle slows down a little and begins to decrease until to 200 ppm. According to the aforementioned findings, the antifungal effects of a nano CM NFs solution are assessed at different concentrations (0 ppm (clear water), 40 ppm, and 80 ppm) on the growth of oilseed rape in an outdoor setting. The results indicate that the application of CM NFs led to significant inhibition of S. sclerotiorum. Specifically, when the nano CM solution was sprayed once at the initial flowering stage at a concentration of 80 ppm, S. sclerotiorum growth was inhibited by approximately 34%. Similarly, when the solution was sprayed once at the initial flowering stage and once at the rape pod stage, using a concentration of 40 ppm, a similar level of inhibition was achieved. These outcomes show that CM NFs possess the ability to bind with more metal ions due to their larger specific surface area. Additionally, their semiconductor physical properties enable the generation of reactive oxygen species (ROS). Therefore, CM NFs hold great potential for widespread application in antifungal products. [ABSTRACT FROM AUTHOR]

The earthquake usually causes multi-dimensional vibration for the large span grid structure, how to effectively isolate and mitigate the vibration response of structure is an important problem in engineering. In this paper, a novel viscoelastic bio-inspired multi-dimensional vibration isolation (VBM-VI) device is proposed under the inspiration of bionic design of the bird legs, which possesses multi-dimensional vibration isolation performance by constituting of viscoelastic core pad and VE-LLS device together. The property experiment of the VBM-VI device is performed to explore the mechanical performance at vertical and horizonal directions, the hysteretic curves and characteristic parameters are discussed to reveal the influence of the excitation frequency and amplitude on the mechanical properties of the VBM-VI device, the experimental results show that the mechanical properties express significant frequency and amplitude dependence at vertical and horizontal directions. To further describe the mechanical proprieties of the VBM-VI device, the mathematical models are established at vertical and horizontal directions respectively, and the comparison analysis between experimental and theoretical results indicates that the established mathematical models can precisely describe mechanical performance of the VBM-VI device. [ABSTRACT FROM AUTHOR]

The high-damping viscoelastic (VE) materials are widely used to reduce unwanted vibrations in civil structures. However, the significant frequency and temperature dependences from high-damping VE materials cause a challenge in efficiently analyzing the structural dynamic behaviors. The aim of this study is to propose a generalized dynamic analysis method for the linear structural system with VE elements. The implementation steps and advantages of the dynamic analysis method are presented. In this method, the frequency-dependent matrices and non-proportional damping induced by VE elements are fully considered in modal coordinates, and then the state-space representation converted from the modal-based transfer function is adopted to implement the time-domain simulation. Any popular VE constitutive models which accurately describe frequency-dependent matrices can be applied to the method. The number of the state-space representation can be adjusted according to the interested frequency range. Numerical applications performed on a viscoelastically damped structure, a VE base-isolated structure, and a structure with a VE tuned mass damper (TMD) demonstrate the numerical accuracy, efficiency, and generality of the proposed dynamic analysis method. [ABSTRACT FROM AUTHOR]

Conducting in-situ measurements of planetary environments is a key scientific goal in the geoscience field for the extraterrestrial exploration, such as the Moon or Mars. Among these measurements, determining the thermal properties of regolith is particularly challenging due to the material's inhomogeneities. In this paper, an active thermal probing technique is proposed, utilizing a transient hot-wire technique with a needle-like probe structure integrated with temperature sensors and a heater. It is capable of measuring in-situ temperature variations and inner heat flux without disturbing the surrounding regolith. In addition, a machine-learning-based method is proposed for inverting in-situ thermophysical properties, including density, thermal conductivity, and heat capacity. An embedded artificial neural network model has been developed and trained with data sets from both finite element simulations and experiments. This machine learning model is capable of efficiently predicting temperature responses for different lunar regolith simulants. For total 12 parameters, the errors of ten cases are less than 10%, and other two cases are 12.23% and 13.17%. Finally, the proposed method is verified by heat measurement experiments under normal pressure and vacuum, and the variation of thermal properties with different compactness is obtained. The proposed probing technique provides novel ideas to measure the in-situ thermal properties of extraterrestrial regolith. [ABSTRACT FROM AUTHOR]

Based on the low cost and superior damping performance of viscoelastic dampers, the new structural system strengthened with viscoelastic energy dissipation braces (VEDB) is proposed to upgrade the reinforced concrete frame structures with insufficient seismic capability. For the dynamic performance researches and damage evolution predictions of this structure system during earthquakes, the dynamic performance of six RCFs (reinforced concrete frames) and six VEFs (another six special reinforced concrete frames with VEDB) are studied under sinusoidal wide frequency range loading excitation horizontally. On this basis, the qualitative and quantitative relations on the damage growing at the material-level and the member-level performance deteriorating about the frame structures are conducted. Furthermore, the empirical calculation model on the cross-level damage evolution of VEFs are established and verified. Finally, a set of useful and robust cross-level judgment criteria for damage performance rates is proposed. The research found that, the installation of VEDB can significantly improve the load bearing capacity, the lateral stiffness and the energy dissipation capacity of the structures. The damage pattern of the structures is improved by VEDB, and it ensures the design criteria of "strong joints and weak members." The empirical calculation model on the cross-level damage evolution and judgment criteria for damage performance rates proposed in this paper are useful and stable in practical engineering. [ABSTRACT FROM AUTHOR]

The article offers information on a case involving a 68-year-old Chinese woman with a replaced metal mitral valve who developed severe tricuspid valve insufficiency. Topics include the patient's history of mechanical mitral valve replacement, the transcatheter tricuspid valve replacement (TTVR) procedure using the LuX-Valve system, and the positive changes observed in the patient six months after TTVR through heart color ultrasound, chest computed tomography (CT).

Buried gas pipelines frequently experience failures as a consequence of adverse factors. The studies of gas leakage diffusion behavior and prediction of hazardous areas following pipeline failure hold profound significance in mitigating the risk of accidents. This paper exemplifies a specific segment of long-distance transportation gas pipeline in the "West-to-East Gas Transmission" project, employing the Soave-Redlich-Kwong (SRK) equation of state (EOS) to develop a numerical model for high-pressure gas leakage and diffusion, while considering box culvert protection. The characteristics of gas leakage diffusion and the effects of pressure, leakage diameter, and soil type on gas diffusion are presented. Furthermore, the prediction models for leakage rate, fastest hazardous time (FHT), fastest hazardous distance (FHD), and lateral hazardous distance (LHD) are introduced. The results show that the pressure and velocity at the beginning of the leakage manifest an annular diffusion centered on the leakage hole, stabilizing within 300 s. The gas primarily diffuses along the horizontal direction within the box culvert, and the peaks of gas concentration at the surface are situated at a distance of 2.35 m on either side of the pipeline. Variations in pressure and leakage diameter influence the gas concentration but do not alter the locations of the concentration peaks observed at the surface. The greater the viscous and inertial resistance of the soil, the shorter the overall diffusion distance becomes. However, backfilling the loam within the box culvert significantly elevates the concentration of gas that leaks to the surface. The leakage rate, FHT, FHD, and LHD can be well calculated by the prediction models proposed in this study. [Display omitted] [ABSTRACT FROM AUTHOR]

Lunar-based equipment undertakes the task of movement and transportation in the construction of unmanned lunar base. In the process of moving, the mechanical legs of the equipment are influenced by the lunar soil with special mechanical properties. In order to avoid these uncertainties caused by the lunar soil and other lunar environmental conditions affecting the safety during the mission, a new robust control method with the form of sectionalized expression is proposed based on the dynamic model of the leg-soil system. Lyapunov second method is introduced to demonstrate that the proposed control method can maintain the stability of the leg-soil system successfully. In order to clarify the contact force in the dynamics model, CAS-1 lunar soil simulant that can accurately simulate real lunar soil is used in the calibration test to obtain the precise mechanical parameters. Simulation and experiment are also carried out to verify the proposed control method and the traditional control methods are introduced to make a comparison. Both the simulation and experiment results show that the proposed control method has a better control effect than traditional methods. The proposed method improves the accuracy by an average of 75.7% and 55.9% compared to the traditional methods and the error is limited to 0.2%. By maintaining the stability and accuracy of the leg-soil system, the stability of the lunar-based equipment is improved when performing construction tasks. This study lays the foundation for the construction of unmanned lunar base in advance. [ABSTRACT FROM AUTHOR]

Cancer cells are in vivo situated in a complex and heterogeneous tumor microenvironment (TME) that includes various biochemical and biophysical cues, such as the elasticity of extracellular matrix (ECMwo) and the viscosity of extracellular fluid (ECF). ECF viscosity in TME is much higher than in normal tissue, but it is unclear how this increased viscosity works simultaneously with other biophysical cues (e.g., ECM stiffness) to influence cancer cell behavior. We experimentally observed that ECF viscosity can significantly enhance cellular mechanosensing behaviors (e.g., cell spreading, cell adhesion, and YAP/TAZ nuclear translocation) only on a stiff substrate, representing a novel enhancement of cell behaviors by distinct mechanical signals. To explore the mechanical mechanisms behind such enhancement phenomenon, we developed a viscosity-based motor-clutch model, with which we found that cells sense and respond to ECF viscosity and ECM stiffness by regulating integrin-ECM bonds in cell adhesion dynamics. These findings help us understand how different mechanical signals in the complex tumor microenvironment collaborate to influence cancer cell behaviors during the development of cancers. [ABSTRACT FROM AUTHOR]

Research on the movement of lunar-based equipment is an essential subject in lunar exploration. The uncertainties of the complex lunar surface environment affect the steady movement of lunar-based equipment. In this paper, a novel robust control strategy, namely model-based p -sectionalized control strategy (MPS control), is proposed for the mechanical legs of lunar-based equipment to maintain stability. The novel robust controller is designed based on the dynamic model of the mechanical leg and the controller is proven theoretically based on Lyapunov stability theory. A numerical simulation and the real-time experiment were carried out, and traditional controllers are introduced in the comparison. The results of both the simulation and the experiment verify the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

Dual targeting to immune checkpoints has achieved a better therapeutic efficacy than single targeting due to synergistic extrication of tumour immunity. However, most dual targeting strategies are usually antibody dependent which facing drawbacks of antibodies, such as poor solid tumour penetration and unsatisfied affinity. To meet the challenges, we engineered a cell membrane displaying a fusion protein composed of SIRPa and PD-1 variants, the high-affinity consensus (HAC) of wild-type molecules, and with which prepared nanovesicles (NVs). Through disabling both SIRPa/CD47 and PD-1/PD-L1 signalling, HAC NVs significantly preserved the phagocytosis and antitumour effect ofmacrophages and T cells, respectively. In vivo study revealed that HAC NVs had better tumour penetration than monoclonal antibodies and higher binding affinity to CD47 and PD-L1 on tumour cells compared with the NVs expressing wild-type fusion protein. Exhilaratingly, dual-blockade of CD47 and PD-L1 with HAC NVs exhibited excellent therapeutic efficacy and biosafety. This study provided a novel biomaterial against tumoural immune escape and more importantly an attractive biomimetic technology of protein delivery formulti-targeting therapies. [ABSTRACT FROM AUTHOR]

During the transient process of gas drilling conditions, the monitoring data often has obvious nonlinear fluctuation features, which leads to large classification errors and time delays in the commonly used intelligent classification models. Combined with the structural features of data samples obtained from monitoring while drilling, this paper uses convolution algorithm to extract the correlation features of multiple monitoring while drilling parameters changing with time, and applies RBF network with nonlinear classification ability to classify the features. In the training process, the loss function component based on distance mean square error is used to effectively adjust the best clustering center in RBF. Many field applications show that, the recognition accuracy of the above nonlinear classification network model for gas production, water production and drill sticking is 97.32%, 95.25% and 93.78%. Compared with the traditional convolutional neural network (CNN) model, the network structure not only improves the classification accuracy of conditions in the transition stage of conditions, but also greatly advances the time points of risk identification, especially for the three common risk identification points of gas production, water production and drill sticking, which are advanced by 56, 16 and 8 s. It has won valuable time for the site to take correct risk disposal measures in time, and fully demonstrated the applicability of nonlinear classification neural network in oil and gas field exploration and development. [ABSTRACT FROM AUTHOR]

Two distributed extended high‐gain observers are studied for the generalized strict‐feedback system in presence of external disturbance. The system state dynamics are reconstructed admissibly based on the limited measured output. First, a distributed high‐gain observer is constructed to ensure the semiglobal ultimate uniform convergence of the state estimation error between the estimated state in each local observer and system state, for any prescribed initial system values. However, the dimension of the proposed distributed observer is n + 1 and the high‐gain parameter is powered up to n + 1. Therefore, a 2(n + 1)‐dimension distributed high‐gain low‐power observer is delicately designed, with the high‐gain parameter powered fixed to 2. The formulated distributed observer is easy‐implementation and the estimation error can reach fast convergence. Finally, a chaotic oscillator and a pendulum‐cart system are introduced to verify the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

To expand the inclusiveness of hybrid test platform research, enhance the flexibility of hybrid test platforms using various control strategies, and promote the development of hybrid test techniques, a low-cost user-configurable electric actuator hybrid test platform is established in this paper. This platform can be transferred to other medium or large electric actuator hybrid test platform, the research applications of this platform cannot be limited by their proposed setup. Firstly, the hardware system design including hybrid test facility integrated control system core architecture and all related signal routings are carried out. Then, the improved equivalent force control feedback method based on force-loading control is proposed, and the software system development including hybrid test process control system software and user-configurable STM32 microcontroller (UCSM) software are conducted. Next, the mechanical performance of viscoelastic damper is tested, and the mechanical model parameters of viscoelastic damper are regressed. The accuracy of electric actuator force control (inner control loop), of which the control tasks get executed on the UCSM is verified using the experimental substructure of viscoelastic damper. The hybrid test of viscoelastic damping system verifies the reliability and robustness of hybrid test platform (outer control loop). Finally, the developed hybrid test platform implements various hybrid tests of viscoelastic damping system under broad temperature range and different seismic intensities. The test results reveal the influence of temperature and seismic intensities on the seismic control effect of viscoelastic damper. [ABSTRACT FROM AUTHOR]

Pipeline condition assessment is a cost-effective method to determine the status of pipeline structure and predict failure probability. Although 100% inspection may not be feasible for decision makers, recent advancements in machine learning techniques have enabled more effective pipeline condition assessment. This paper provides a comprehensive review of machine learning applications in pipeline condition assessment, covering aspects such as fault diagnosis, risk prediction, parameter prediction, and visual defect recognition. The present study endeavors to make the following contributions: (1) extraction of the model, data size, and other relevant information from 91 papers, (2) in-depth analysis of the state of the art and frameworks of the models discussed in the 91 papers, (3) summary of the data characteristics, input variables, and accuracy of machine learning models, and (4) exploration of the potential avenues for future research in the use of machine learning for pipeline condition assessment. This review aims to serve as a practical reference for scholars engaged in related research. The review highlights the fact that the majority of the models employed in pipeline condition assessment are original, and the utilization of hybrid models remains limited. Transfer learning and reinforcement learning are identified as potential avenues for future research because they hold promise in facilitating the adaptive selection of model inputs and the transfer of models to similar projects. Furthermore, breaking down data barriers is deemed essential for advancing the use of machine learning in pipeline condition assessment. [ABSTRACT FROM AUTHOR]

Because of the rather low melt strength, poor processability, and brittleness, polylactide (PLA) is yet to fulfill its promise as an advanced biobased and biodegradable film to replace fossil-based polymer films. In this work, through the grafting of maleic anhydride (MA) on PLA chains and then based on epoxy-anhydride chemistry and Zn2+-catalyzed transesterification exchange, PLA covalent adaptive networks (CANs) with biobased epoxidized soybean oil (ESO) as dynamic crosslinks are in situ constructed in a twin-screw extruder, which can be scaled up for industrial production. The ionic dipole interaction between Zn2+ and MA weakens the complexation of Zn2+ with the ester groups on PLA chains, maintaining the thermal stability of PLA CANs. PLA CANs show strain-hardening behavior under extensional flow, indicating enhanced melt strength. The combination of accelerated exchange of dynamic covalent bonds and decoupled ionic dipole interaction by elevated temperature and mechanical activation prompts the macroscopic flow, providing rapid reprocessibility for PLA CANs. Thus, PLA CANs can be stably processed by extrusion film blowing, and a high blow-up ratio of 3.71 is reached. Interestingly, the flexible crosslinked network that is highly elastically stretched during film blowing allows the film to exhibit unexpectedly enhanced ductility in both take-up direction (MD) and transverse direction (TD), and the film shows elongation at break of 132.1% in MD and 111.0% in TD at an ESO content of 6.42 wt%. Furthermore, the PLA CAN film presents lower environmental impacts than petroleum-based plastic films in terms of low CO2 emissions, low fossil resource scarcity, and potential to biodegrade. Such a strategy combining enhanced melt strength and toughness enabled by PLA CANs with ESO as dynamic crosslinks will open up a new avenue toward advanced PLA films in response to severe plastic film pollution. [ABSTRACT FROM AUTHOR]

This study aims to develop a high-performance acrylate viscoelastic damper (HAVED), which is suitable for the low-frequency vibration control of building structures. To reveal the influence of ambient temperature, excitation frequency, and displacement amplitude on the dynamic mechanical performance and energy dissipation capacity of a HAVED, a series of dynamic mechanical performance tests were performed on a HAVED within the extensive temperature (10°C–50°C), frequency (0.1–3 Hz), and displacement (0.5–4 mm) range. The analysis results show that a HAVED has excellent energy dissipation capacity and good adaptability to the external environment. The loss factor of a HAVED can reach up to 1.85, and it remains above 0.28 even in a high-temperature environment of 50°C. The dynamic mechanical properties and energy dissipation capacity of a HAVED show strong dependences and obvious coupling effects on temperature, frequency, and displacement amplitude. Based on the experimental research of a HAVED, the micromechanical properties of viscoelastic materials are analyzed, and the high-order fractional derivative model is used to comprehensively describe the mechanical characterization of microscopic molecular chains. The Kraus theory is introduced to consider the influence of filler particles, and the high-order fractional derivative micro–macro cross-scale mathematical model is proposed by combining with the temperature-frequency equivalence principle. Through the experimental results, the prediction capabilities of the model that have been established have been verified. The analysis results show that the proposed model can comprehensively describe the influence of ambient temperature, excitation frequency, displacement amplitude, microscopic molecular chain structure, and filler particles on the mechanical properties of a HAVED. [ABSTRACT FROM AUTHOR]

The bionics design method has been proverbially applied at vibration control field, and how to make bionic vibration control device possess excellent mechanical property and stable energy dissipation capacity is an important subject. In this paper, a bionic viscoelastic limb-like-structure (VE-LLS) device is proposed in conjunction with the viscoelastic (VE) damper and the limb-like-structure (LLS) device together, and the proposed device simultaneously possesses excellent mechanical propriety and energy dissipation capacity. Firstly, the mechanical property test of the VE-LLS device is conducted to investigate the effect of ambient temperature, excitation amplitude and frequency on its dynamic mechanical property and energy dissipation capacity. The energy dissipation contribution caused by the LLS joint friction for the VE-LLS device is discussed. Then, the energy dissipation model of the VE-LLS device is established by simultaneously considering the viscoelastic and friction factors, and the comparison result indicates that the established energy dissipation model can accurately describe the energy dissipation capacity of the VE-LLS device under different ambient temperature, exaction amplitude and frequency. Finally, to further promote the stability of energy dissipation capacity of the VE-LLS device at different temperature and frequency, an energy dissipation compensation strategy is proposed by increasing the energy dissipation of the LLS joint friction to compensate for the energy dissipation attenuation of the VE damper caused by high temperature and low frequency, and the results shows that the compensation strategy expresses excellent effect for the energy dissipation stability of the VE-LLS device. [ABSTRACT FROM AUTHOR]

For the first time, an ultrathin type of ultra‐high molecular weight polyethylene (UHMWPE) membrane of only 350 nm thickness is surface modified by direct fluorination and plasma treatments. Then a notable suppression in crystallinity is observed. A total of four kinds of thickness, from 350 nm to 6 µm, are investigated to correlate the modification effect on the thickness. Microscopically, the continuous shish‐kebab structure transforms into scattered lamellae clusters. And the damage to the surface morphologies increases as the thickness decreases, yet the resultant contact angles remain almost constant. Especially for the 350 nm thin UHMWPE, the mildest fluorination treatment slightly changes the contact angle, while the multiscale structure changes significantly from crystalline to mesoscopic level. As thickness decreases from 6 µm to 350 nm, the modified volume ratio of membranes increases, and the volumetric modification is almost realized for the 350 nm membrane. [ABSTRACT FROM AUTHOR]

Efficient and nondestructive technology for identifying wood species facilitates the transition from digital forestry to smart forestry. While near-infrared spectroscopy applied to wood identification is well documented, the detailed mechanisms for chemometrics remain unclear. In this study, twelve wood species were identified by using near-infrared spectroscopy combined with six machine learning algorithms (support vector machine, logistic regression, naïve Bayes, k-nearest neighbors, random forest, and artificial neural network). Above all, isolated forest and local outlier factor were used to detect and exclude outliers. Then feature engineering strategies were developed from three perspectives to process feature matrices: feature selection, feature extraction, and feature selection combined with feature extraction. Next, the learning curve, grid search method, and K-fold cross-validation were used to optimize the model parameters. Finally, the accuracy, operation time, and confusion matrix were used to evaluate the model performance. When the local outlier factor was used to remove outliers and principal component analysis was used to extract features, the support-vector-machine-based wood-species identification model produced the most accurate results, with 98.24% accuracy. These results offer new avenues for constructing automatic wood-identification systems. [ABSTRACT FROM AUTHOR]

Through silicon via technology is a promising and preferred way to realize the reliable interconnection for 3-D integrated circuit (3-D IC), which can transfer heat from multiple dies to the heat sink in vertical direction. In this paper, a new general model of the through-silicon via (TSV) is proposed to investigate the thermal performance of the 3-D IC. The heat transfer characteristics of conical-annular TSV are studied for the first time. The impacts of different sidewall inclination angles and insulating layer thicknesses of TSV on the heat dissipation of 3-D IC were compared and analyzed in detail. As expected, our proposed model is in good agreement with the results of the existing models, which shows that the proposed model considering the lateral heat transfer and TSV structures can predict the distribution of temperature more efficiently and accurately. Furthermore, it is found that conical-annular TSV has more excellent heat dissipation performance. [ABSTRACT FROM AUTHOR]

• Explored the optimum pyrolysis temperature and activation conditions of MPS. • The quantized promotion degree of maize growth by MPS-char was obtain. • Nitrogen release delayed and concentration was improved by 16% with MPS-char. • Physical property of MPS-char mad the root development advance than others. Pyrolyzing and returning to farmland is one of the potential methods for farmland plastic film waste. This study explored both pyrolyzation and activation optimum conditions of a mixture of plastic film (polyethylene) and maize straw (MPS) in a 1:5 ratio to produce MPS-char, investigated the action of the char on the maize seedling stage (for 30 days). The results showed that the char promoted the root to be more advanced than aboveground part, therefore, this study experimentally clarified the role MPS-char played when added to the soil. The functional groups of the char were varied by the participation of polyethylene. Carbon-based groups were observed, such as carbonyl or carboxyl groups, which could constitute an NH 4 + absorption release system to increase the existence of urea in soil, therefore the average nitrogen concentration was improved by 16.18 %. However, the shallow soil temperature increased by 2.03 °C, and the deep soil temperature slightly decreased with the effect of MPS-char. While, the soil moisture content was slightly reduced in the second half of the experiment, and the soil oxygen content increased by 7.64 % throughout the whole experiment. Overall, returning MPS-char to farmland showed a positive effect on maize growth, which was caused by the variation of both chemical and physical properties. This variation provides opportunities for further promotion of rhizosphere development. [ABSTRACT FROM AUTHOR]

Legged robots have the advantage of strong terrain adaptability in lunar exploration. A new robust controller is designed for axial flux permanent magnet motors applied on the legged lunar robots to diminish the disturbance from uncertainty and external circumstance. The theoretical verification is carried out through Lyapunov stability theory. The numerical simulation and real-time experiment are carried out to access the stability and dynamic property of the systems adopting the proposed controller. The results are compared with the traditional control strategies to demonstrate the advantages of the proposed controller. The new robust controller contributes to the dynamic stability of legged lunar robots and is also appropriate for the similar mechanical systems. [ABSTRACT FROM AUTHOR]

The fractional-order derivative Zener (FDZ) model can reasonably predict the frequency dependence behavior of rubber-like materials. However, its capability to capture nonlinear behaviors is limited. In our previous work, we built a horizontal shear model of a multidimensional rubber-like base isolation bearing, modifying the FDZ model to compensate for its inability to reproduce the nonlinear behaviors of amplitude dependence and slow stabilization. In this paper, the tension-compression behavior of the same bearing in the vertical direction is studied, where strain-stiffening nonlinear behavior is exhibited. A different strategy is used to establishing the modified tension-compression FDZ (CFDZ) model, which is shown to have good agreement with experimental results. State-space representation of the CFDZ model is presented and included in modelling a train-bridge-bearing system for dynamic analysis. Simulation results demonstrate that the proposed bearing achieves a high base isolation performance in the vertical direction. [ABSTRACT FROM AUTHOR]

Because of their adverse impact on social infrastructure and economic property, gas explosions are among the most dangerous disasters that can befall utility tunnels. Flame propagation is the most intuitive manifestation during the explosion process. It can be significantly influenced by spatial obstacles. To analyze the propagation law of gas explosions in utility tunnels more realistically, an explosion model of the utility tunnel was established by considering actual spatial obstacles, including the pipeline support and reserved frame. The flame propagation characteristics, including the flame shape, temperature distribution, and propagation velocity, were analyzed systematically. Results demonstrate that spatial obstacles have a prominent influence on flame evolution laws. Flame propagation is disturbed but not completely blocked by spatial obstacles. Rather, irregular flame shapes and wrinkles of the flame front are easily developed. The explosion process is insufficient because of the existence of residual methane in the obstacle area. Flame propagation velocity is improved remarkably, whereas temperature distribution is affected slightly. In particular, the spread velocity increases with the increase of propagation distance. The maximum velocity of monitoring surfaces can be improved by 60% under conditions with obstacles. [ABSTRACT FROM AUTHOR]

The viscoelastic damping materials (VDMs) used in the viscoelastic (VE) damping equipment may undergo thermal-oxidative aging during long-time exposure to complicated working environments and exhibit significant property degradation in their lifespan. Therefore, it is imperative to comprehend the mechanical performance of VDMs after aging. In this paper, the molecular chains of VDMs are categorized into elastic chains and free chains, and the effects of variable physical–chemical reactions in the thermal-oxidative aging process on these two kinds of chains are analyzed and then mathematically described based on the theory of chemical kinetics. By introducing the molecular chain statistical model to consider the influence of microstructure change on the macroscopic mechanical behavior of VDMs, a hyperelastic hybrid molecular chain model for thermal-oxidative aging VDMs is addressed in conjunction with the tube constraint model and filler reinforcement theory. Combined with the test data, the accuracy and applicability of the proposed model are comparatively evaluated, and the sensitivity analyses on the mechanical parameters and aging parameters of the proposed model are also conducted. The verified results suggest that the proposed model can reflect the mechanical behavior of aging VDMs during thermal-oxidative conditions with remarked accuracy. The results of the parameters analyses display that the macroscopic mechanical property of VDMs is prominently affected by their macromolecular chain structure, and the physical–chemical reactions occurring in the aging process synthetically play a collaborative influence on the mechanical performance of aging VDMs. [ABSTRACT FROM AUTHOR]

4.3 (400.0 mg) which was purified by Sephadex LH-20 (MeOH-H SB 2 sb O, 5:5) and semipreparative HPLC (CH SB 3 sb CN-H SB 2 sb O, 11:9). SP 1 sp H NMR (400 MHz, CDCl SB 3 sb , , ppm, J/Hz): 7.06 (2H, d, J = 8.4, H-2', 6'), 6.85 (2H, d, J = 8.4, H-3', 5'), 6.48 (1H, d, J = 11.6, H-20), 5.88 (1H, ddd, J = 15.0, 9.9, 2.2, H-13), 5.60 (1H, d, J = 11.6, H-19), 5.21 (1H, ddd, J = 15.0, 10.9, 3.8, H-14), 4.38 (1H, br.s, H-7), 3.77 (3H, s, 4'-OCH SB 3 sb ), 3.70 (1H, m, H-3), 2.99 (1H, dd, J = 5.2, 2.6, H-4), 2.93 (1H, ddd, J = 11.6, 6.8, 2.2, H-16), 2.83 (1H, dd, J = 13.7, 4.6, H-10a), 2.65 (1H, d, J = 4.6, H-10b), 2.62 (1H, overlapped, H-15a), 2.60 (1H, overlapped, H-8), 2.27 (1H, dd, J = 7.4, 5.2, H-5), 2.14 (1H, m, H-15b), 1.47 (3H, s, H-23), 1.25 (3H, s, H-12), 1.15 (3H, d, J = 6.8, H-22), 1.08 (3H, d, J = 7.4, H-11). SP 1 sp H NMR (400 MHz, DMSO-d SB 6 sb , , ppm): 9.19 (1H, s, 2-NH), 8.08 (1H, s, 4'-OH), 6.95 (2H, d, J = 8.4, H-2', 6'), 6.67 (2H, d, J = 8.4, H-3', 5'), 6.33 (1H, d, J = 12.7, H-20), 5.60 (1H, overlapped, H-19), 5.57 (1H, overlapped, H-13), 5.33 (1H, ddd, J = 15.2, 10.8, 4.3, H-14), 5.26 (1H, d, J = 2.2, H-7), 4.03 (1H, q, J = 7.1, H-3), 3.32 (1H, m, H-18), 2.93 (1H, m, H-4), 2.88 (1H, d, J = 9.2, H-8), 2.74 (2H, m, H-10), 2.71 (1H, m, H-16), 2.68 (1H, m, H-5), 2.46 (1H, m, H-15a), 2.03 (1H, m, H-15b), 1.67 (3H, s, H-12), 1.16 (3H, d, J = 6.9, H-22), 1.11 (3H, d, J = 6.8, H-23), 0.70 (3H, d, J = 7.2, H-11). [Extracted from the article]

We consider the diffusive Holling-Tanner predator-prey model subject to the homogeneous Neumann boundary condition. We first apply Lyapunov function method to prove some global stability results of the unique positive constant steadystate. And then, we derive a non-existence result of positive non-constant steady-states by a novel approach that can also be applied to the classical Sel'kov model to obtain the non-existence of positive non-constant steady-states if 0 < p = 1. [ABSTRACT FROM AUTHOR]

Nitrile‐butadiene rubber (NBR) has been wildly applied in vibration control technology, it is usually mixed with organic small molecular modifiers and well vulcanized, which can greatly enhance the mechanical and damping properties of the material. This work aims to design the optimum blending ratio of hindered phenol A/B/NBR composite with the best damping property by means of molecular dynamics (MD) simulation, and investigate the mechanical performance from the molecular level. The shear deformation simulation is conducted on pure NBR models to study the impact of rubber crosslink degree (CD) on elasticity and plasticity of NBR. To research the damping mechanism of the material, detailed analyses of the micro molecular structure and reciprocating shear simulation are carried out on NBR composite models with different hindered phenol A/B ratio. The simulation results indicate a strong positive correlation between intermolecular H‐bonds and loss factor η, and the NBR composite with hindered phenol A/B per hundred rubber (phr) 30/30 shows the best damping performance. [ABSTRACT FROM AUTHOR]

Micro structures of viscoelastic materials (VEM) play an important role in their mechanical properties and energy dissipation capacities. This work shows a mathematical modeling of VEMs considering molecular chain-network configurations, and the temperature effects on mechanical properties of VEMs can also be characterized based on the equivalent relationship between temperature and frequency. The Dynamic Thermomechanical Analyzer (DMA) test is carried out to observe dynamic behaviors of the VEM and prove the accuracy of the proposed new mathematical model. The experimental data of viscoelastic damper (VED) are utilized to further verify the correctness of the proposed model with different ambient temperatures. [ABSTRACT FROM AUTHOR]

Building information modeling (BIM) creates tremendous value for civil engineering through information integration. Not only does it make the formulation of data storage strategies more important at the beginning of a civil engineering project, but it also shows the potential value of further research into a unified BIM model that highly integrates all information in the project life cycle. However, it is not easy to store all the information in the project life cycle into a unified BIM model. To achieve this goal, this study proposed a shareable BIM back-end data system object-oriented database for BIM front-end applications (BIM-OODB), and established its complete system configuration. Based on the database design theory, three main aspects of BIM-OODB design are discussed, namely use case design, architecture design, and schema design. Then, four demonstration cases were selected to discuss the system implementation process of BIM-OODB in building and infrastructure projects. The results show that BIM-OODB has the potential to enable all participants to work around the unified shareable data system throughout the project life cycle. This study provides a reference for civil engineers to formulate data storage strategies in the early stage of a civil engineering projects and IT engineers to develop civil engineering data applications. [ABSTRACT FROM AUTHOR]

Tolerance intervals (TIs) are commonly employed in numerous industries, ranging from engineering to pharmaceuticals. However, closed-form TIs are unavailable for most distributions. Although some approximate methods can be used to obtain TIs, coverage probabilities (CPs) of these TIs cannot achieve the nominal level, or can be even far different from the nominal level. In this study, we propose two contentadjusted procedures for TIs based on bootstrap. The first one is based on the bootstrap sample quantile, while the second one is based on the asymptotic normality of empirical distribution. The simulation results show that the two calibration procedures can improve CPs of TIs for some non-normal distributions according to extensive numerical simulations, and they are both proved to be effective through real data examples. [ABSTRACT FROM AUTHOR]

With the rapid increase in the incidence of diabetes, non-healing diabetic wounds have posed a huge challenge to public health. Endothelial progenitor cell (EPC) has been widely reported to promote wound repairing, while its number and function were suppressed in diabetes. However, the specific mechanisms and competing endogenous RNA (ceRNA) network of EPCs in diabetes remain largely unknown. Thus, the transcriptome analyses were carried in the present study to clarify the mechanism underlying EPCs dysfunction in diabetes. EPCs were successfully isolated from rats. Compared to the control, diabetic rat-derived EPCs displayed impaired proliferation, migration, and tube formation ability. The differentially expressed (DE) RNAs were successfully identified by RNA sequencing in the control and diabetic groups. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses indicated that DE mRNAs were significantly enriched in terms and pathways involved in the functions of EPCs and wound healing. Protein–protein interaction networks revealed critical DE mRNAs in the above groups. Moreover, the whole lncRNA–miRNA–mRNA ceRNA network was constructed, in which 9 lncRNAs, 9 mRNAs, and 5 miRNAs were further validated by quantitative real-time polymerase chain reaction. Rno-miR-10b-5p and Tgfb2 were identified as key regulators of EPCs dysfunction in diabetes. The present research provided novel insight into the underlying mechanism of EPCs dysfunction in diabetes and prompted potential targets to restore the impaired functions, thus accelerating diabetic wound healing. Key messages: • Compared to the control, diabetic rat-derived EPCs displayed impaired proliferation, migration, and tube formation ability. • The DE RNAs were successfully identified by RNA sequencing in the control and diabetic groups and analyzed by DE, GO, and KEGG analysis. • PPI and lncRNA–miRNA–mRNA ceRNA networks were constructed. • 9 lncRNAs, 9 mRNAs, and 5 miRNAs were further validated by qRT-PCR. • Rno-miR-10b-5p and Tgfb2 were identified as key regulators of EPCs dysfunction in diabetes. [ABSTRACT FROM AUTHOR]

The control–structure interaction (CSI) affects the performance and robustness of protective structures in active control system, and it is important to consider the CSI effect to achieve high performance in structural vibration control. In this paper, the electro-mechanical model of the torsional servomotor is derived by establishing dynamic voltage equilibrium equation. Three different active control models (non-CSI, reduced-order CSI, and higher-order CSI model) which considering different accuracy requirements of the electro-mechanical relationship are established to investigate the influence of the CSI on active tuned mass damper (ATMD) control system. The frequency- and time-domain responses of a three-story steel frame structure during different excitations are investigated, and as a comparison, the responses of the uncontrolled and tuned mass damper (TMD) control system are also studied. It can be concluded that the control performance of the active control system is reduced due to the CSI effect, especially at resonance frequency region of the structure (around 2.7 Hz, 8.2 Hz, and 13.2 Hz). The input voltage, velocity of the top floor, velocity of active mass, and higher-order of control forces have an important influence on the servomotor output control force. Furthermore, it can be found that, to achieve the same control effect, the required control voltage has been significantly increased due to the CSI effect. [ABSTRACT FROM AUTHOR]

ZnMoO4 nanoparticles with two different morphologies were successfully synthesized by the industrial dry method. Both nano-ZnMoO4 belong to α crystalline phase, and the valence state of Mo was verified to be + 6. The polyhedral-shaped particles and a mixture of polyhedral and rod-shaped particles exists, respectively. The average size of ZnMoO4 nanoparticles with polyhedral structure was 50 nm in diameter, while the diameter of the cross-section of ZnMoO4 nanoparticles (NPs) with rod-like structure was less than 50 nm. To evaluate the antibacterial properties of two materials, the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of two kinds of nano-ZnMoO4 against staphylococcus aureus were determined using an agar medium. The results showed that the MIC and MBC values of polyhedral nano-ZnMoO4 were 20 ppm and 40 ppm; the MIC and MBC values of rod-shaped and polyhedral hybrid nano-ZnMoO4 were 10 ppm and 20 ppm, respectively. The antibacterial effect of both nanoparticles was better than that of conventional ZnMoO4 with the size above 1 µm at the concentration of 200 ppm. This confirms the crystalline structure in relation to the crystal size/morphology and the concentration of powder in suspension can influence on the antibacterial efficiency. Furthermore, these two shaped nano-ZnMoO4 samples had different atomic percentages, so different spatial hinge structures were the important reason for the unequal antibacterial performance of these shaped nano-ZnMoO4 powder. [ABSTRACT FROM AUTHOR]

Prefabricated buildings, as the development center of architectural industrialization, will produce a lot of point-cloud data in the process of information detection and management. These point-cloud data can be used for reverse modeling to restore the physical characteristics of prefabricated concrete components, which can provide a basis for prefabricated building informatics. However, traditional point-cloud data processing methods have limitations in the high-precision and high-efficiency restoration of physical entities. To solve this problem, this study assumes the reconstruction of the prefabricated point-cloud geometric model as the research object and builds a prefabricated concrete component model in industry foundation class (IFC) format using the equal-interval segmentation slice mapping method. The geometric surface quality of the prefabricated concrete component was determined by comparing the as-built and as-designed models. This study automated the steps in the data processing process through code and established the framework of a three-dimensional (3D) as-built model reconstruction platform on the assembly construction site. The feasibility of this method was verified using the prefabricated concrete component point-cloud data collected on site. This study solves the problems of easy loss of local details, noise point interference, and manual processing in the quality inspection process of prefabricated buildings. It is conducive to the construction quality management process of prefabricated buildings. The experimental results showed that this method is efficient, the code running time is less than 0.12 s, and the accuracy satisfies standard requirements. [ABSTRACT FROM AUTHOR]