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Patients with malignant tumors are prone to present hypercoagulability of blood and form thrombosis, and its pathogenesis is complex involving various factors from clinical and histopathological to genetic influences. Current studies on the potential mechanism of blood hypercoagulability in patients with malignant tumors focus on the following aspects but are not limited: (1) tumor cells release coagulant-promoting substances, (2) tumor cells interact with the fibrinolytic system, (3) tumor cell-mediated platelet activation, (4) tumor-associated complement activation, and (5) genetic factors and clinical factors. Especially, the pathogenesis of blood hypercoagulability is in-depth analyzed covering tumor cells' release of procoagulant substances, the interplay of cancer cells and fibrinolytic system, platelet activation mediated by cancer cells, cancer-associated complement activation, and the action of genetic and clinical factors. We review the pathogenesis of blood hypercoagulability in patients with malignant tumors, which will assist in the research and development of new drugs and providing theoretical support for the formulation of the best treatment plan for patients, to prolong the survival of patients.

The triboelectric nanogenerator (TENG), as a novel energy harvesting technology, has garnered widespread attention. As a relatively young field in nanogenerator research, investigations into various aspects of the TENG are still ongoing. This review summarizes the development and dissemination of the fundamental principles of triboelectricity generation. It outlines the evolution of triboelectricity principles, ranging from the fabrication of the first TENG to the selection of triboelectric materials and the confirmation of the electron cloud overlapping model. Furthermore, recent advancements in TENG application scenarios are discussed from four perspectives, along with the research progress in performance optimization through three primary approaches, highlighting their respective strengths and limitations. Finally, the paper addresses the major challenges hindering the practical application and widespread adoption of TENGs, while also providing insights into future developments. With continued research on the TENG, it is expected that these challenges can be overcome, paving the way for its extensive utilization in various real-world scenarios.

With the continuous development of renewable energy, it has become important to make efficient use of renewable energy. However, the uncertainty and randomness of renewable energy can cause instability in the operation of power systems and can lead to the problem of abandoning PV power and wind power. To reduce the waste of renewable energy and increase the use of renewable energy, this paper proposes a provincial-city–county spatial scale energy storage configuration model based on the power supply and load situation of the power grid in recent years, which can better adapt to different scenarios. The objective function has been redesigned to take into account the differences in investment returns in different regions, with the objective of minimizing costs, making full use of energy storage devices to reduce the abandonment of renewable energy, achieving efficient use of renewable energy and ensuring system power balance. The proposed model further takes into account the difference in dispatching capacity of different regions and effectively reduces the occurrence of load cutting according to regional characteristics. Finally, the reasonableness of the model is verified by simulation with power grid data for a typical day in spring and a typical day in autumn in a region of China.

A novel Ti–2Al–1.3V (wt.%) alloy was prepared by thermomechanical consolidation of a composite powder produced by high-energy ball milling of a mixture of TiH2 granules with a low oxygen content (0.1wt.%) and Ti–6Al–4V machining chips with a high oxygen content (0.8wt.%) at a mass ratio of 2:1. The microstructures and mechanical properties of the alloy in as-extruded state and after different heat treatments were investigated. The as-extruded alloy exhibits a martensite microstructure consisting of ultrafine and nanometer sized α’ laths and aciculae and domains of layered structure containing δ(TiH) layers. The alloy in this state is brittle and fractures prematurely before yielding due to the ultrafine martensitic microstructure and hydrogen embrittlement associated with the high hydrogen content of the alloy. After vacuum annealing at 700°C for 6 h followed by furnace cooling, the alloy is further dehydrogenated with the hydrogen content being reduced to 0.008wt.%, the microstructure of the alloy changes into a full α/β lamellar microstructure with the continuous and discontinuous β layers being only 80–90 nm thick and the lamellar colony sizes being 10–30μm. The fine structured alloy in this heat treatment condition shows an excellent combination of high tensile yield strength of 996 MPa and ductility of 13.9%. After a further heat treatment of 980°C for 1 h followed by air cooling, the microstructure of the alloy consists of equiaxed α grains and α/βt lamellar structured domains (βt = β transformed structure), and unfortunately, this microstructure leads to a significant decrease of both the tensile yield strength (to 876 MPa) and the tensile ductility (to 7.4%). The fracture behavior of the alloy in different states is also studied, and the correlation between the microstructure and mechanical properties is discussed.

In order to improve face recognition accuracy, an IFC face recognition algorithm based on image feature compensation strategy for face recognition is proposed in this paper. The strategy adopts the method of extracting the image feature description by using the computational factors to compensate the features of the original image. Since the size of the feature compensation coefficients directly affects the recognition rate of the face recognition system, a modified PSO algorithm is proposed for solving the optimal combination of feature compensation coefficients for multiple computation factors, so that the recognition rate of the system can be improved. Firstly, this paper introduces the relative concepts of feature compensation strategy and calculation factor. Secondly, the process and implementation of face recognition algorithm using feature compensation strategy are described. Thirdly, the improved PSO algorithm for solving the optimal solution of the feature compensation coefficient is designed, during which the evaluation method is constructed to evaluate the merits of the feature compensation coefficient, and the implementation process of the improved PSO algorithm is conceived. Finally, the algorithm proposed in this paper is verified by simulation experiment platform. It is demonstrated that the modified PSO algorithm can significantly enhance the recognition rate of the system following its application to the feature compensation strategy face recognition system. On the ORL dataset, the recognition rate can be enhanced from 93.05% to 99.00% when the training image reaches 5, meanwhile, it still exhibits good performance on other datasets.

In this paper, the free vibration response of a stiffened functionally graded graphene nanoplatelet (GPL)-reinforced composite multilayer cylindrical shell panel is studied for the first time. The shell is stiffened by both stringers and rings. Additionally, the effect of reinforcing the shell panel, ring and stinger with GPLs is independently studied. Halpin–Tsai relations are employed to evaluate the mechanical properties of the shell panel, rings and stringers. The first-order shear deformation shell theory, accompanied by the Lekhnitsky smeared stiffener model, using the numerical finite element method and Hamilton principle, is employed to develop the governing motion equations of the shell panel. Four different types of GPL patterns, including FG-A, FG-X, FG-O and UD, are assumed across the thickness of the shell panel, rings and stringers. The effects of different factors, including various weight fractions and patterns of GPLs nanofillers, the geometry of the shell panel and stiffeners and two displacement boundary conditions, on the natural frequencies of the shell panel, have been studied.

The contact process of stator and slider described by the Coulomb friction model is basically in a pure sliding friction state, and a mechanical model based on the Dahl friction theory was proposed to describe the contact process between stator and slider of V-shape linear ultrasonic motor. With consideration for the tangential compliance of stator and slider, the dynamic contact and friction processes of stator and slider were addressed in stages. The simulation results show that the ratio of the friction positive work decreases with the increase of the preload, and the vibration amplitude of the stator increases the proportion of positive work of the friction force. Improving the contact stiffness of the stator and slider is conducive to improving the output performance of the ultrasonic motor. The asymmetry of the left and right performance of the V-shaped vibrator will cause a difference in the left and right running speeds of the ultrasonic motor. The improved Dahl friction-driving model makes up for the discontinuity of tangential contact force calculated by the Coulomb friction model. This study demonstrates that the friction-driving model based on the Dahl theory is reliable and reasonable for linear ultrasonic motors according to the experimental results.

Most studies on the corrosion inhibition performance of organic molecules and (nano)materials were conducted within “carbon steel/1.0 M HCl” solution system using similar experimental and theoretical methods. As such, the numerous research findings in this system are sufficient to conduct comparative studies to select the best-suited inhibitor type that generally refers to a type of inhibitor with low concentration/high inhibition efficiency, nontoxic properties, and a simple and cost-economic synthesis process. Before data collection, to help readers have a clear understanding of some crucial elements for the evaluation of corrosion inhibition performance, we introduced the mainstay of corrosion inhibitors studies involved, including the corrosion and inhibition mechanism of carbon steel/HCl solution systems, evaluation methods of corrosion inhibition efficiency, adsorption isotherm models, adsorption thermodynamic parameters QC calculations, MD/MC simulations, and the main characterization techniques used. In the classification and statistical analysis section, organic compounds or (nano)materials as corrosion inhibitors were classified into six types according to their molecular structural characteristics, molecular size, and compound source, including drug molecules, ionic liquids, surfactants, plant extracts, polymers, and polymeric nanoparticles. We outlined the important conclusions obtained from recent literature and listed the evaluation methods, characterization techniques, and contrastable experimental data of these types of inhibitors when used for carbon steel corrosion in 1.0 M HCl solution. Finally, statistical analysis was only performed based on these data from carbon steel/1.0 M HCl solution system, from which some conclusions can contribute to reducing the workload of the acquisition of useful information and provide some reference directions for the development of new corrosion inhibitors.

Bent micro-tubes have been frequently applied in electronics, medical devices and aerospace for heat transfer due to the increasing heat flux in high-density electric packages. Rotary-draw bending (RDB) is a commonly used process in forming tubes due to its versatility. However, the control of forming defects is the key problem in micro-tube bending in terms of wall thinning, cross-sectional deformation and wrinkling. In this paper, a three-dimensional (3D) finite-elements (FE) modeling of electrically-assisted (EA) RDB of 6063 aluminum alloy micro-tubes is developed with the implicit method in ABAQUS. The multi-field coupled behavior was simulated and analyzed during the EA RDB of micro-tubes. Several process parameters such as micro-tube diameter, bending radius, current density and electrical load path were selected to study their effects on the bending defects of the Al6063 micro-tubes. The simulated results showed that the cross-sectional distortion could be improved when electrical current mainly pass through the vicinity of the tangent point in the micro-tube RDB, and the cross-sectional distortion tended to decrease with the increases of current density and tube diameter, and the decreases of bending speed and radius. A trade-off should be made between the benefit and side effect due to electrical current since the risk of wall thinning and wrinkling may increase.

Exposure to fine particulate matter (PM2.5) is associated with adverse health impacts on the population. Satellite observations and machine learning algorithms have been applied to improve the accuracy of the prediction of PM2.5 concentrations. In this study, we developed a PM2.5 retrieval approach using machine-learning methods, based on aerosol products from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the NASA Earth Observation System (EOS) Terra and Aqua polar-orbiting satellites, near-ground meteorological variables from the NASA Goddard Earth Observing System (GEOS), and ground-based PM2.5 observation data. Four models, which are orthogonal regression (OR), regression tree (Rpart), random forests (RF), and support vector machine (SVM), were tested and compared in the Beijing⁻Tianjin⁻Hebei (BTH) region of China in 2015. Aerosol products derived from the Terra and Aqua satellite sensors were also compared. The 10-repeat 5-fold cross-validation (10 × 5 CV) method was subsequently used to evaluate the performance of the different aerosol products and the four models. The results show that the performance of the Aqua dataset was better than that of the Terra dataset, and that the RF algorithm has the best predictive performance (Terra: R = 0.77, RMSE = 43.51 μg/m3; Aqua: R = 0.85, RMSE = 33.90 μg/m3). This study shows promise for predicting the spatiotemporal distribution of PM2.5 using the RF model and Aqua aerosol product with the assistance of PM2.5 site data.

Wear behavior is influential to improve friction drive and wear lifespan of actuators or motors, which work at an elliptical locus vibration. Sliding wear tests of metallic friction pairs are conducted by a laboratory rig of ultrasonic vibration. Surfaces of the different metallic sliders are characterized using surface roughness, Abbott curves and fractal dimension. Results show that surface roughness is reduced to varying degrees in the metallic sliders due to ultrasonic polishing and/or micro-rolling effect. Variations in the fractal dimensions of contact surfaces are consistent with that of surface roughness. Wear traces demonstrate that plastic deformation and cracking are the primary failure modes. Where the driving tip on the slider is in intermittent contact followed by impact effects, ripples of 3~5 μm traces suggest the occurrence of fretting in duralumin sliders. Nodular cast iron showed a favorable performance during running of ultrasonic motor, exhibiting a stable output performance and durable wear life.