Complex Structure Research Articles

Structural studies of intrinsically disordered MLL-fusion protein AF9 in complex with peptidomimetic inhibitors.

AF9 (MLLT3) and its paralog ENL(MLLT1) are members of the YEATS family of proteins with important role in transcriptional and epigenetic regulatory complexes. These proteins are two common MLL fusion partners in MLL-rearranged leukemias. The oncofusion proteins MLL-AF9/ENL recruit multiple binding partners, including the histone methyltransferase DOT1L, leading to aberrant transcriptional activation and enhancing the expression of a characteristic set of genes that drive leukemogenesis. The interaction between AF9 and DOT1L is mediated by an intrinsically disordered C-terminal ANC1 homology domain (AHD) in AF9, which undergoes folding upon binding of DOT1L and other partner proteins. We have recently reported peptidomimetics that disrupt the recruitment of DOT1L by AF9 and ENL, providing a proof-of-concept for targeting AHD and assessing its druggability. Intrinsically disordered proteins, such as AF9 AHD, are difficult to study and characterize experimentally on a structural level. In this study, we present a successful protein engineering strategy to facilitate structural investigation of the intrinsically disordered AF9 AHD domain in complex with peptidomimetic inhibitors by using maltose binding protein (MBP) as a crystallization chaperone connected with linkers of varying flexibility and length. The strategic incorporation of disulfide bonds provided diffraction-quality crystals of the two disulfide-bridged MBP-AF9 AHD fusion proteins in complex with the peptidomimetics. These successfully determined first series of 2.1-2.6 Å crystal complex structures provide high-resolution insights into the interactions between AHD and its inhibitors, shedding light on the role of AHD in recruiting various binding partner proteins. We show that the overall complex structures closely resemble the reported NMR structure of AF9 AHD/DOT1L with notable difference in the conformation of the β-hairpin region, stabilized through conserved hydrogen bonds network. These first series of AF9 AHD/peptidomimetics complex structures are providing insights of the protein-inhibitor interactions and will facilitate further development of novel inhibitors targeting the AF9/ENL AHD domain.

Environmental heterogeneity caused by large-scale cultivation of Pyropia haitanensis shapes multi-group biodiversity distribution in coastal areas

The response of marine biodiversity to mariculture has long been a research focus in marine ecology. However, the effects of seaweed cultivation on biological community assembly are poorly understood, especially in diverse communities with distinct ecological characteristics. In this study, we used environmental DNA metabarcoding to investigate the spatial distribution patterns of bacterial, protistan, and metazoan diversity, aiming to reveal the mechanisms of community assembly in the Pyropia haitanensis cultivation zone along the Fujian coast, China. We found that, compared with the biological communities in control zones, those in P. haitanensis cultivation zones exhibited stronger geographic distance-decay patterns and displayed more complex and stable network structures. Deterministic processes (environmental selection) played a more important role in the assembly of bacterial, protistan, and metazoan communities in P. haitanensis cultivation zones, especially metazoan communities. Variance partitioning analysis showed that environmental variables made greater contributions to the diversity of the three types of communities within the P. haitanensis cultivation zones than in the control zones. Partial least squares path modeling analysis identified nitrate‑nitrogen (NO3-N), pH, particulate organic carbon (POC), and dissolved organic carbon (DOC) as the key environmental variables affecting biodiversity. Overall, the environmental heterogeneity caused by the large-scale cultivation of P. haitanensis could be the crucial factor influencing the composition and structure of various biological communities. Our results highlight the importance of the responses of multi-group organisms to the cultivation of seaweed, and provide insights into the coexistence patterns of biodiversity at the spatial scale.

Research on Establishment of Digital-Twin System for Intelligent Control of Cutting Tools Sintering Process Driven by Data-Model Combination

In the manufacturing process of tungsten cemented carbide cutting tools, the changes in temperature, pressure and vacuum during the sintering process of the cutting tools can have a significant impact on the quality of the cutting tools. This effect is particularly significant in the vacuum sintering stage, so this paper focuses on cutting tools sintering in the vacuum stage. The cutting tools sintering process is carried out in a closed space in a sintering furnace with a complex internal structure. Therefore, it is extremely difficult to accurately predict the heating condition of the cutting tools in the furnace and monitor the sintering quality of the cutting tools. In this study, a digital twin system for the sintering process of cemented carbide cutting tools is proposed, which combines monitoring rolling data analysis and sintering quality prediction model. Firstly, the radiative thermodynamic model of cutting tools sintering temperature was established in this system. The model predicts the time-varying state of the heat distribution at any location in the furnace during the vacuum phase. Subsequently, based on the convolutional neural network, the mapping relationship between the sintering parameters and the grain size in the vacuum stage is constructed, and a dynamic evaluation model of cutting tools sintering quality is proposed. The model enables real-time prediction of sintering quality in the vacuum stage. The system realizes the prediction of the time-varying state of the sintering quality of the cutting tools. The digital twin system realizes the adaptive temperature control of the vacuum stage of cutting tools sintering based on the fuzzy control algorithm. The application of this system has increased the yield rate of cemented carbide cutting tools manufacturing to 98.9%. This breaks through the problem of timing modulation of cutting tools sintering quality in the vacuum stage of cutting tools sintering.

Eosin Y derivatives for visible light-mediated free-radical polymerization: Applications in 3D-photoprinting and bacterial photodynamic inactivation

This study reports the design and the subsequent use of mono-allylated (EY-MA) and di-allylated (EY-DA) derivatives of eosin Y (EY) as highly efficient visible light-sensitive photosensitizers (PS) of bio-based H-donor molecules (cysteamine (Cys) or N-acetyl-L-cysteine (NAC)) and an electron donor (N-methyldiethanolamine, MDEA) for free-radical and thiol-acrylate polymerizations of a biobased monomer derived from soybean oil (SOA) upon exposure to visible light. High final acrylate conversions for SOA polymerization (up to 80 %) evidence the efficient photoinitiating properties of the eosin derivatives systems under irradiation with light emitting diodes (LEDs) centred at 405, 455 and 505 nm, and outperform those obtained with EY and other common photosensitizers such as camphorquinone or benzophenone. As described by fluorescence and phosphorescence analyses, laser flash photolysis (LFP) and electron paramagnetic resonance spin-trapping (EPR-ST) experiments, EY-MA and EY-DA can react via a proton/proton-coupled electron transfer reaction with Cys (or NAC) and MDEA respectively. The efficient singlet oxygen generation of the EY-MA-based materials upon exposure to visible light leads to excellent antibacterial properties, against both Gram-positive Staphylococcus aureus (S. aureus) and Gram-negative Escherichia coli (E. coli). A 3-log decrease of E. coli adhesion on the surface of the materials is observed and 100 % adhesion inhibition of S. aureus is also demonstrated. The co-polymerization of the eosin-derived PS with the polymer matrix ensures sustainable antibacterial properties against both bacteria strains upon visible light exposure as it prevents their leakage out of the polymer network. Finally, finely complex 3D structures are successfully obtained by a 3D-photoprinting technology with the investigated EY-MA-based formulation using LED@405 nm.

A developed convolutional neural network model for accurately and stably predicting effective thermal conductivity of gradient porous ceramic materials

Accurate and stable prediction of the effective thermal conductivity (ETC) of porous ceramic materials is of great significance for their application in areas such as optimizing the design of thermal barrier coatings and improving energy conversion efficiency. Porous ceramic materials exhibit complex porous structures with gradient porosity distributions that pose a great challenge for effective medium theory (EMT) and conventional convolutional neural networks (CNN) in attempting to accurately and stably predict the ETC of porous media. In this study, a CNN model that integrates self-attention and a multiscale feature-fusion mechanism is proposed to predict the ETC of porous media with greater accuracy and stability. The integration of the self-attention and multiscale feature-fusion mechanisms enhances the CNN's ability to learn long-range dependencies and preserve detailed information. The optimization of the CNN's accuracy and stability is visually illustrated using gradient-weighted class activation mapping (Grad-CAM) for ETC. Additionally, by employing the proposed gradient quartet structure generation set (QSGS), a gradient porous ceramic media dataset comprising 10 000 images was built to train the CNN model. Finally, the prediction results and relative error distribution of the ETC were compared across different models. Our model demonstrated improvements in statistical metrics, including a 33.7 % decrease in mean error, 25.2 % decrease in median error, and 59.6 % decrease in maximum error. The decreases in these metrics and Grad-CAM for the ETC strongly demonstrates that the model proposed in this work greatly improved the accuracy and stability of predicting the ETC of ceramic materials with gradient porosity distributions.

Observations on the anatomy of the funiculus spermaticus and the testis in Brachyteles sp. (SPIX, 1823) primates - Atelidae.

Analysing the literature about the reproductive anatomy on New World Primates, one can see the need of standardisation on the description methods and, more importantly, the lack of detailed information. The problem is aggravated by the difficult access to specimens of the endangered species such as Brachyteles sp. This paper's objective was to extend knowledge on the male reproductive anatomy of these primates. The testis and funiculus spermaticus of Brachyteles are described in detail. We utilised one individual of Brachyteles arachnoides, two hybrids (B. arachnoides × Brachyteles hypoxanthus) and photographs of the testis of a third fresh specimen of a hybrid individual. The septum formed by tunica dartos adheres to the testis and separates the scrotum in two testicular cavities. Passed the spermatic cord, the external spermatic fascia continues with the tunica dartos, covering the cranial half of the testis. The fascia cremasterica divides itself in bundles of fibres and forms loops around the testicles creating a sac like structure that seems to be unique among Neotropical Primates. The appendix testis is described for the first time in platyrrhini. It is presented as a sessile structure in the extremitas capitata of the testis. Previous literature on the reproductive anatomy of platyrrhini is limited. Despite that, it can be said that the large size and volume of the testis, and complex structure of the cremaster, could consist of a heat loss reduction strategy in cold and humid forest environments. Except for the larger size of the testicles in hybrid individuals, no other significant morphological differences were found between B. arachnoides and hybrids (B. arachnoides × B. hypoxanthus).

Removal of cadmium and chromium heavy metals from aqueous medium using composite bacterial cellulose membrane

Bacterial cellulose (BC) membranes produced from biomass are emerging as an eco-friendly solution for water decontamination. The abundance of hydroxyl groups and the high surface-to-volume ratio of this material allow for the integration of diverse functional groups, providing the potential for targeted water purification applications. Beyond their intriguing mechanical properties and unique complex structure, bacterial cellulose membranes are biodegradable into sugar molecules and can be processed with minimal handling and using mild chemicals. Taken together, these features make them a compelling choice for water filtration in the context of environmental responsibility. In their natural state, BC membranes have limited potential for targeted wastewater treatment. One strategy for enhancing their functionality is to graft customized molecules onto their surface. Therefore, this study aims to impart multifunctionality to BC membrane for water filtration. Hence a novel precursor with hard and soft base functionalities consisting of amines, carbonyls, amides, hydroxyls etc. is designed and grafted onto BC membranes, grown to ensure surface uniformity and membrane-to-membrane repeatability of the properties. The structure of the synthesized precursors and the effective functionalization of the membrane are then validated through various structural characterization techniques. Changes in the morphology of BC membranes are examined using Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM). Both the pristine and modified BC membranes undergo a series of tests to assess their filtration capabilities under low-pressure regime and their efficiency in removing representative cadmium and chromium ions. The modified BC membrane exhibits superior filtration performance and water permeability than pristine-BC. The targeted metal ions were rejected more than 90% from the effluent. The modified membranes demonstrated a flux recovery of above 90% maintaining its effectiveness even after five successive cleaning-filtration cycles.

Mutational and structural studies of (βα)8-barrel fold methylene-tetrahydropterin reductases utilizing a common catalytic mechanism.

Methylene-tetrahydropterin reductases catalyze the reduction of a methylene to a methyl group bound to a reduced pterin as C1 carrier in various one-carbon (C1) metabolisms. F420-dependent methylene-tetrahydromethanopterin (methylene-H4MPT) reductase (Mer) and the flavin-independent methylene-tetrahydrofolate (methylene-H4F) reductase (Mfr) use a ternary complex mechanism for the direct transfer of a hydride from F420H2 and NAD(P)H to the respective methylene group, whereas FAD-dependent methylene-H4F reductase (MTHFR) uses FAD as prosthetic group and a ping-pong mechanism to catalyze the reduction of methylene-H4F. A ternary complex structure and a thereof derived catalytic mechanism of MTHFR is available, while no ternary complex structures of Mfr or Mer are reported. Here, Mer from Methanocaldococcus jannaschii (jMer) was heterologously produced and the crystal structures of the enzyme with and without F420 were determined. A ternary complex of jMer was modeled on the basis of the jMer-F420 structure and the ternary complex structure of MTHFR by superimposing the polypeptide after fixing hydride-transferring atoms of the flavins on each other, and by the subsequent transfer of the methyl-tetrahydropterin from MTHFR to jMer. Mutational analysis of four functional amino acids, which are similarly positioned in the three reductase structures, indicated despite the insignificant sequence identity, a common catalytic mechanism with a 5-iminium cation of methylene-tetrahydropterin as intermediate protonated by a shared glutamate. According to structural, mutational and phylogenetic analysis, the evolution of the three reductases most likely proceeds via a convergent development although a divergent scenario requiring drastic structural changes of the common ancestor cannot be completely ruled out.

Maintaining the validity of inference from linear mixed models in stepped-wedge cluster randomized trials under misspecified random-effects structures.

Linear mixed models are commonly used in analyzing stepped-wedge cluster randomized trials. A key consideration for analyzing a stepped-wedge cluster randomized trial is accounting for the potentially complex correlation structure, which can be achieved by specifying random-effects. The simplest random effects structure is random intercept but more complex structures such as random cluster-by-period, discrete-time decay, and more recently, the random intervention structure, have been proposed. Specifying appropriate random effects in practice can be challenging: assuming more complex correlation structures may be reasonable but they are vulnerable to computational challenges. To circumvent these challenges, robust variance estimators may be applied to linear mixed models to provide consistent estimators of standard errors of fixed effect parameters in the presence of random-effects misspecification. However, there has been no empirical investigation of robust variance estimators for stepped-wedge cluster randomized trials. In this article, we review six robust variance estimators (both standard and small-sample bias-corrected robust variance estimators) that are available for linear mixed models in R, and then describe a comprehensive simulation study to examine the performance of these robust variance estimators for stepped-wedge cluster randomized trials with a continuous outcome under different data generators. For each data generator, we investigate whether the use of a robust variance estimator with either the random intercept model or the random cluster-by-period model is sufficient to provide valid statistical inference for fixed effect parameters, when these working models are subject to random-effect misspecification. Our results indicate that the random intercept and random cluster-by-period models with robust variance estimators performed adequately. The CR3 robust variance estimator (approximate jackknife) estimator, coupled with the number of clusters minus two degrees of freedom correction, consistently gave the best coverage results, but could be slightly conservative when the number of clusters was below 16. We summarize the implications of our results for the linear mixed model analysis of stepped-wedge cluster randomized trials and offer some practical recommendations on the choice of the analytic model.

Utilising redundancy in musculoskeletal systems for adaptive stiffness and muscle failure compensation: a model-free inverse statics approach.

Vertebrates possess a biomechanical structure with redundant muscles, enabling adaptability in uncertain and complex environments.
Harnessing this inspiration, musculoskeletal systems offer advantages like variable stiffness and resilience to actuator failure and fatigue.
Despite their potential, the complex structure presents modelling challenges that are difficult to explicitly formulate and control. This difficulty arises from the need for comprehensive knowledge of the musculoskeletal system, including details such as muscle arrangement, and fully accessible muscle and joint states.
Whilst existing model-free methods do not need explicit formulations, they also underutilise the benefits of muscle redundancy. 
Consequently, they necessitate retraining in the event of muscle failure and require manual tuning of parameters to control joint stiffness limiting their applications under unknown payloads. 
Presented here is a model-free local inverse statics controller for musculoskeletal systems, employing a feedforward neural network trained on motor babbling data. Experiments with a musculoskeletal leg model showcase the controller's adaptability to complex structures, including mono and bi-articulate muscles. The controller can compensate for changes such as weight variations, muscle failures, and environmental interactions, retaining reasonable accuracy without the need for any additional retraining.&#xD.

Enhancing Load-Bearing Capacity of Calcareous Sands through Gel Stabilization: A Mechanical and Material Characterization Study

Calcareous sands often display wide ring grain configurations, high intragranular porosity, a complex structure, and low grain hardness. These attributes typically do not meet the strength criteria necessary to sustain overlying infrastructure in civil engineering applications. This study investigates gel stabilization techniques, blending gel material with calcareous sand at concentrations ranging from 5% to 22%, followed by curing periods of 3 to 28 days to evaluate the load-bearing capacity. Subsequently, an unconfined compressive test is performed to determine the gel material content in stabilized specimens and investigate the influence of gel material types. The gel material-to-sand ratios employed are set at 5%, 10%, and 16% for Portland cement and 13%, 16%, and 22% for gypsum. After that, a triaxial consolidated undrained test is conducted to assess mechanical behavior, pore water pressure, and mechanical properties. The findings reveal increased dilation, stress–strain hardening, and softening post-yield, regardless of gel material type. Principal stress ratios, secant modulus, and cohesion show a positive correlation with maintenance duration and binder content, with implications for improved load-bearing capacity. The study also elucidates the qualitative relationship between secant modulus E50 and confining pressure.

Regiodivergent biosynthesis of bridged bicyclononanes

Medicinal compounds from plants include bicyclo[3.3.1]nonane derivatives, the majority of which are polycyclic polyprenylated acylphloroglucinols (PPAPs). Prototype molecules are hyperforin, the antidepressant constituent of St. John’s wort, and garcinol, a potential anticancer compound. Their complex structures have inspired innovative chemical syntheses, however, their biosynthesis in plants is still enigmatic. PPAPs are divided into two subclasses, named type A and B. Here we identify both types in Hypericum sampsonii plants and isolate two enzymes that regiodivergently convert a common precursor to pivotal type A and B products. Molecular modelling and substrate docking studies reveal inverted substrate binding modes in the two active site cavities. We identify amino acids that stabilize these alternative binding scenarios and use reciprocal mutagenesis to interconvert the enzymatic activities. Our studies elucidate the unique biochemistry that yields type A and B bicyclo[3.3.1]nonane cores in plants, thereby providing key building blocks for biotechnological efforts to sustainably produce these complex compounds for preclinical development.

A cooperative control method and application for series multivariable coupled system

Series multivariable coupled system is a typical controlled object in process control industry. The interaction of various state variables between multiple inputs and outputs in the system forms a complex series multivariable coupled structure. This coupled structure makes the control of a controlled object in the system affect the controlled object in the upper and lower control loop. As a result, it is difficult to control one or more control loops in the system without changing the state of other links in the system. In this paper, a cooperative control method for series multivariable coupled system is proposed. A decoupling controller is designed to remove the coupling effect caused by the interaction between stages, and the system is decoupled into several independent control loops. Differential leading PI (proportional-integral) error compensation method is introduced to ensure the following performance of the controller without static error. The proposed cooperative control method satisfies the Lyapunov stability, and has been successfully applied in the simulation experiment of cascade pumping station system of Beijing East-to-West water transfer project. The proposed method reduces the difficulty to controlling the water level of forebay of each pumping station and ensures the efficient operation of the cascade pumping station system.

Morphological aspects and the effectiveness of photodynamic inactivation against Rhizopus oryzae in different life cycles.

Mucormycosis is an extremely aggressive fungal disease with a high mortality rate, especially in people with compromised immune systems. Most cases of mucormycosis are caused by the fungus Rhizopus oryzae. The treatments used are based on high doses of antifungals, associated with surgical resections, when it is possible. However, even with this aggressive treatment, the estimated attributable mortality rate is high. There is therefore a need to develop adjuvant treatments. Photodynamic Inactivation (PDI) may be an auxiliary therapeutic option for mucormycosis. Due to the lack of reports in the literature on the morphology and photodynamic inactivation of R. oryzae, characterization of the fungus using Confocal Microscopy and Transmission Electron Microscopy, and different protocols using Photodithazine® (PDZ), a chlorin e6 compound, as a photosensitizer, were performed. The fungus growth rate under different concentrations and incubation times of the photosensitizer and its association with the surfactant Sodium Dodecyl Sulphate (SDS) was evaluated. For the hyphae, both in the light and dark phases, in the protocols using only PDZ, no effective photodynamic response was observed. Meanwhile with the combination of SDS 0.05% and PDZ, inhibition growth rates of 98% and 72% were achieved for the white and black phase, respectively. In the conidia phase, only a 1.7 log10 reduction of the infective spores was observed. High concentration of melanin and the complex and resistant structures, especially at the black phase, results in a high limitation of the PDI inactivation response. The combined use of the SDS resulted in an improved response, when compared to the one obtained with the amphotericin B treatment.

Research on the Motion Features Model for Underwater Targets with Multiple Highlights and Multiple Micro-Motion Forms

Motion characterization, including Doppler and micro-Doppler, is crucial for the detection and identification of high-speed underwater targets. Under high-frequency and short-range conditions, underwater targets cannot be simply regarded as single highlight targets as they exhibit a complex structure with multiple scattering centers accompanied by distinct micro-motions. To address this multi-highlight and multi-micro-motion scenario, a model is proposed to characterize the motion features of underwater targets. Firstly, a mathematical model is established to represent the micro-Doppler features based on the single-highlight model. Subsequently, considering the overlap of multiple highlight echoes caused by the high-speed translation of the target and the long pulse detection signal, precise representation is achieved by setting motion positions and calculating time delays within the model. The results represent the echoes of moving targets with multiple highlights and micromotions. Finally, a time-frequency analysis method is employed to extract motion features and estimate target parameters, thereby validating the accuracy and effectiveness of the proposed model. This research provides a theoretical foundation for the modeling of underwater moving targets.

Fine Segmentation of Chinese Character Strokes Based on Coordinate Awareness and Enhanced BiFPN

Considering the complex structure of Chinese characters, particularly the connections and intersections between strokes, there are challenges in low accuracy of Chinese character stroke extraction and recognition, as well as unclear segmentation. This study builds upon the YOLOv8n-seg model to propose the YOLOv8n-seg-CAA-BiFPN Chinese character stroke fine segmentation model. The proposed Coordinate-Aware Attention mechanism (CAA) divides the backbone network input feature map into four parts, applying different weights for horizontal, vertical, and channel attention to compute and fuse key information, thus capturing the contextual regularity of closely arranged stroke positions. The network’s neck integrates an enhanced weighted bi-directional feature pyramid network (BiFPN), enhancing the fusion effect for features of strokes of various sizes. The Shape-IoU loss function is adopted in place of the traditional CIoU loss function, focusing on the shape and scale of stroke bounding boxes to optimize the bounding box regression process. Finally, the Grad-CAM++ technique is used to generate heatmaps of segmentation predictions, facilitating the visualization of effective features and a deeper understanding of the model’s focus areas. Trained and tested on the public Chinese character stroke datasets CCSE-Kai and CCSE-HW, the model achieves an average accuracy of 84.71%, an average recall rate of 83.65%, and a mean average precision of 80.11%. Compared to the original YOLOv8n-seg and existing mainstream segmentation models like SegFormer, BiSeNetV2, and Mask R-CNN, the average accuracy improved by 3.50%, 4.35%, 10.56%, and 22.05%, respectively; the average recall rates improved by 4.42%, 9.32%, 15.64%, and 24.92%, respectively; and the mean average precision improved by 3.11%, 4.15%, 8.02%, and 19.33%, respectively. The results demonstrate that the YOLOv8n-seg-CAA-BiFPN network can accurately achieve Chinese character stroke segmentation.

Effect of polymer crosslinking to the failure behavior of thermoplastic composite remelting interface: Molecular dynamics simulation and experimental verification

AbstractThe forming interface is the weak link of thermoplastic composite complex structures. To explore the effect of polymer crosslinking on the failure behavior of thermoplastic composite remelting interface using “Preforming + Remelting bonding” process, the all‐atom models of different types of interfaces were established, and a molecular dynamics (MD) simulation was conducted on the uniaxial tensile failure process of the remelting interface. The failure behavior of the remelting interface with different preforming processes was tested to verify the correctness of MD simulation, and the influencing mechanism of polymer crosslinking reactions in the preforming stage to the remelting interface properties was clarified. The results showed that the yield stress of the uncrosslinked interface reaches 283.2 MPa and 16.0% and 50.6% higher than that of the unilateral and bilateral crosslinked interfaces respectively. The polymer crosslinking reaction during the preforming stage will reduce the interlaminar bonding performance. The interlaminar shear strength (ILSS) of the uncrosslinked interface is 87.46 MPa and 7.21% and 27.36% higher than that of the unilateral and bilateral crosslinked interface respectively, and only 3.95% lower than that of the non‐remelting sample formed by standard process. This research provides a new approach for predicting and analyzing the effect of polymer crosslinking on remelting interface properties of thermoplastic composite using “Preforming + Remelting bonding” process.Highlights The failure behavior of different thermoplastic composite remelting interfaces was studied. MD simulation was conducted on the uniaxial tensile failure process of the remelting interface. The influencing mechanism of polymer crosslinking reactions in the preforming stage to the remelting interface properties was clarified. It is effective to explore the failure mechanism of thermoplastic remelting interface by MD simulation.

Investigation of Frequency-Dependent Characteristics of Wire Rope under Tension Based on Transfer Function Method

Wire rope is a complex structure made by twisting wires of various sizes in the longitudinal direction. It is used to support or move engineering structures and is subject to various tensions. Dynamic properties are important parameters to evaluate the resistance to bending deformation and vibration reduction of various structures. They are affected by the magnitude of tension. In this study, an experimental method for measuring the frequency-dependent characteristics of wire rope under tension is proposed. The study analyzed flexural wave propagation employing a vibration transfer function. Experimental results showed that the transfer function of wire rope under tension is affected by tension and bending stiffness. The Newton–Raphson method was employed to numerically measure wavenumbers of the wire rope. The bending stiffness and loss factor were determined from the wavenumbers. Changes in the bending stiffness and loss factor as the tension increased were explained by the dynamic behavior of the structure under tension. As the tension increased, the bending stiffness increased, and the loss factor decreased. Hysteresis analysis indicated that the energy dissipation of wire rope is greater than that of a steel beam due to the friction between the wires. Statistical analysis confirmed a significant correlation between dynamic characteristics and tension in wire rope.

The Polysaccharides from Pinellia ternata and Their Derivatives: Preparation, Structure Characteristics, and Activities inVitro.

Three polysaccharides, PTC, PTH, and PTB, were extracted from Pinellia ternata using three different extraction conditions: room temperature water, hot water, and 2% Na2CO3 solution. PTC and PTH were composed of rhamnose, glucose, galactose, mannose, glucuronic acid, galacturonic acid, and arabinose, which combine to form complex structures. PTB was composed solely of glucose and rhamnose. Further analysis indicated that PTC and PTB exhibited triple-helix structures. PTC showed the highest scavenging capacity against DPPH, superoxide anion, and hydroxyl radicals, with half maximal inhibitory concentrations (IC50) of 1004.1, 1584.1, and 1584.1 μg/mL, respectively. Additionally, PTC, PTH, and PTB were subjected to sulfation, phosphorylation, and selenization, resulting in the production of nine derivates. The distinctive absorptive bands of these derivates were determined through infrared spectroscopy. Selenized and sulfated derivates have shown significant antitumor and immunoenhancing properties. Our findings revealed that at 400 μg/mL, the inhibition rate of selenated PTB on HeLa cells was 54.2% and that on HepG2 cells was 43.1%. Additionally, selenized PTC displayed significant immunoenhancing activity, with a proliferation rate of 63.7% at 400 μg/mL in RAW264.7 cells. These results provide valuable evidence supporting the consideration of polysaccharides from Pinellia ternata as a potential candidate for the development of antineoplastic drugs.

Nonlinear dynamical modeling and response analysis of complex structures based on assumed mode weighting

The assumed mode method (AMM) is widely used for dynamical modeling but faces increasing challenges in developing low-dimensional and high-precision models of complex structures for investigations of nonlinear dynamical responses and active vibration control. This is mainly because the current complex structure has an increasing number of components, each of which needs to be discretized by multiple assumed modes in dynamical modeling, leading to increasing degrees of freedom for the system. To address this issue, this paper proposes a dimension-reduced method based on the assumed mode weighting method, referred to as Mode Weighting Method (MWM). The modeling process of a multi-beam structure is fully presented as an example to show the strategy of the MWM. During this process, the assumed mode (AM) model (the dynamic model derived in terms of a set of assumed modes) is developed first where the joints of the structure between its components are considered as artificial springs and each component is discretized by its vibration modes without constraints. The components of the eigenvector of the characteristic equation derived from the AM model are taken as the weighting coefficients to get the approximate analytical global modes of the structure by multiplying the corresponding assumed modes. Consequently, a nonlinear dynamic model with a few degree of freedom is obtained by discretizing the structure with the weighted modes. Moreover, a technique for simply obtaining the weighted mode (WM) models by directly processing the AM model through a transformation matrix is presented. To validate the proposed method, the simulations on the natural characteristics and the dynamical responses for both linear and nonlinear models, are performed respectively based on the WM and the finite element models, where both results are well matched each other. This work provides a new way of developing advanced dynamical modeling methods for structural dynamics design, optimization, and active vibration control.