Evaluation of Cell's Passability in the ECM Network.

The microstructure of the extracellular matrix (ECM) plays a key role in affecting cell migration, especially nonproteolytic migration. It is difficult, however, to measure some properties of the ECM, such as stiffness and the passability for cell migration. On the basis of a network model of collagen fiber in the ECM, which has been well applied to simulate mechanical behaviors such as the stress-strain relationship, damage, and failure, we proposed a series of methods to study the microstructural properties containing pore size and pore stiffness and to search for the possible migration paths for cells. Finally, with a given criterion, we quantitatively evaluated the passability of the ECM network for cell migration. The fiber network model with a microstructure and the analysis method presented in this study further our understanding of and ability to evaluate the properties of an ECM network.

Principal Component Analysis Method with Space and Time Windows for Damage Detection.

Long-term structural health monitoring (SHM) has become an important tool to ensure the safety of infrastructures. However, determining methods to extract valuable information from large amounts of data from SHM systems for effective identification of damage still remains a major challenge. This paper provides a novel effective method for structural damage detection by introduction of space and time windows in the traditional principal component analysis (PCA) technique. Numerical results with a planar beam model demonstrate that, due to the presence of space and time windows, the proposed double-window PCA method (DWPCA) has a higher sensitivity for damage identification than the previous method moving PCA (MPCA), which combines only time windows with PCA. Further studies indicate that the developed approach, as compared to the MPCA method, has a higher resolution in localizing damage by space windows and also in quantitative evaluation of damage severity. Finally, a finite-element model of a practical bridge is used to prove that the proposed DWPCA method has greater sensitivity for damage detection than traditional methods and potential for applications in practical engineering.

An Objective Injury Threshold for the Maximum Principal Strain Criterion for Brain Tissue in the Finite Element Head Model and Its Application.

Although the finite element head model (FEHM) has been widely utilized to analyze injury locations and patterns in traumatic brain injury, significant controversy persists regarding the selection of a mechanical injury variable and its corresponding threshold. This paper aims to determine an objective injury threshold for maximum principal strain (MPS) through a novel data-driven method, and to validate and apply it. We extract the peak responses from all elements across 100 head impact simulations to form a dataset, and then determine the objective injury threshold by analyzing the relationship between the combined injury degree and the threshold according to the stationary value principle. Using an occipital impact case from a clinical report as an example, we evaluate the accuracy of the injury prediction based on the new threshold. The results show that the injury area predicted by finite element analysis closely matches the main injury area observed in CT images, without the issue of over- or underestimating the injury due to an unreasonable threshold. Furthermore, by applying this threshold to the finite element analysis of designed occipital impacts, we observe, for the first time, supra-tentorium cerebelli injury, which is related to visual memory impairment. This discovery may indicate the biomechanical mechanism of visual memory impairment after occipital impacts reported in clinical cases.

Quantitative assessment of brain injury and concussion induced by an unintentional soccer ball impact.

BACKGROUND: Accidental impact on a player's head by a powerful soccer ball may lead to brain injuries and concussions during games. It is crucial to assess these injuries promptly and accurately on the field. However, it is challenging for referees, coaches, and even players themselves to accurately recognize potential injuries and concussions following such impacts. Therefore, it is necessary to establish a list of minimum ball velocity thresholds that can result in concussions at different impact locations on the head. Additionally, it is important to identify the affected brain regions responsible for impairments in brain function and potential clinical symptoms. METHODS: By using a full human finite element model, dynamic responses and brain injuries caused by unintentional soccer ball impacts on six distinct head locations (forehead, tempus, crown, occiput, face, and jaw) at varying ball velocities (10, 15, 20, 25, 30, 35, 40, and 60 m/s) were simulated and investigated. Intracranial pressure, Von-Mises stress, and first principal strain were analyzed, the ball velocity thresholds resulting in concussions at different impact locations were evaluated, and the damage evolution patterns in the brain tissue were analyzed. RESULTS: The impact on the occiput is most susceptible to induce brain injuries compared to all other impact locations. For a conservative assessment, the risk of concussion is present once the soccer ball reaches 17.2 m/s in a frontal impact, 16.6 m/s in a parietal impact, 14.0 m/s in an occipital impact, 17.8 m/s in a temporal impact, 18.5 m/s in a facial impact or 19.2 m/s in a mandibular impact. The brain exhibits the most significant dynamic responses during the initial 10-20 ms, and the damaged regions are primarily concentrated in the medial temporal lobe and the corpus callosum, potentially causing impairments in brain functions. CONCLUSIONS: This work offers a framework for quantitatively assessing brain injuries and concussions induced by an unintentional soccer ball impact. Determining the ball velocity thresholds at various impact locations provides a benchmark for evaluating the risks of concussion. The examination of brain tissue damage evolution introduces a novel approach to linking biomechanical responses with possible clinical symptoms.

Influence of centroid acceleration acquisition and filtering class on head injury criterion evaluation.

BACKGROUND: Although the Head Injury Criteria (HIC) has been widely applied to assess head impact injuries, it faces two outstanding problems: 1) HIC is affected strongly by the cut-off frequency when processing acceleration signals. And these cut-off frequencies are experiential and lack unified guidelines; 2) If the head was impacted on a different part, should the corresponding HIC threshold be the same? If these problems are not resolved, it could potentially lead to a critical misinterpretation of the safety assessment. METHODS: Finite element method was used to reconstruct head impacts. The head model includes tissues like skull, brainstem, cerebrospinal fluid, etc. The head model was impacted in the frontal, occipital, parietal or lateral direction with different impact velocities. Acceleration signals of the head model were extracted directly from the skull and the head centroid node. To obtain a robust HIC, the filtering class of acceleration signals were analyzed carefully. Then, the relation between rigid body HIC and the centroid node HIC were studied systematically. RESULTS: When the filtering class of rigid body acceleration and centroid node acceleration reached the cut-off frequency, the corresponding derivative of HIC tended to change smoothly. Using these cut-off frequencies, robust HICs were obtained. The rigid body HIC far exceeded that of centroid node HIC, such as 8, 9, 14 and 31 times exceeded in the frontal, occipital, parietal and lateral impact conditions, respectively. Moreover, approximate linear relations were found between the rigid body HIC and the centroid node HIC in different impact directions, respectively. From these relations, the injury thresholds of rigid body HIC of various directions were given quantitatively. CONCLUSIONS: The rational filtering class like CFC 800 and CFC 700 were given for rigid body HIC and centroid node HIC, respectively. The rigid body HIC had a significant discrepancy from the centroid node HIC. Linear relations between the rigid body HIC and centroid node HIC were found, and their slopes changed with impact directions. From these relations, we can adjust the injury thresholds reasonably if the head receives different impacts. These findings can effectively enhance the applicability of HIC.

The Efficient Energy Collection of an Autoregulatory Driving Arm Harvester in a Breeze Environment.

Breezes are a common source of renewable energy in the natural world. However, effectively harnessing breeze energy is challenging with conventional wind generators. These generators have a relatively high start-up wind speed requirement due to their large and steady rotational inertia. This study puts forth the idea of an autoregulatory driving arm (ADA), utilizing a stretchable arm for every wind cup and an elastic thread to provide adjustable rotational inertia and a low start-up speed. The self-adjustable rotational inertia of the harvester is achieved through coordinated interaction between the centrifugal and elastic forces. As the wind speed varies, the arm length of the wind cup automatically adjusts, thereby altering the rotational inertia of the harvester. This self-adjustment mechanism allows the harvester to optimize its performance and adapt to different wind conditions. By implementing the suggested ADA harvester, a low start-up speed of 1 m/s is achieved due to the small rotational inertia in its idle state. With the escalation of wind speed, the amplified centrifugal force leads to the elongation of the driving arms. When compared to a comparable harvester with a constant driving arm (CDA), the ADA harvester can generate more power thanks to this stretching effect. Additionally, the ADA harvester can operate for a longer time than the CDA harvester even after the wind has stopped. This extended operation time enables the ADA harvester to serve as a renewable power source for sensors and other devices in natural breeze environments. By efficiently utilizing and storing energy, the ADA harvester ensures a continuous and reliable power supply in such settings.

Mechanical behaviors and probabilistic multiphase network model of polyvinyl alcohol hydrogel after being immersed in sodium hydroxide solution.

Because of the advantages of a uniform distribution of reinforcing particles and in situ preparation, in situ precipitation has become an important way to prepare magnetic and other smart hydrogels. An important step in this process is to immerse hydrogels in alkaline solution to implant magnetic particles. Previous studies generally have ignored the effect of this process on the network structure and mechanical properties of hydrogels. In this study, we immersed polyvinyl alcohol (PVA) hydrogel samples in sodium hydroxide solutions of different concentrations to study changes in mechanical properties, such as stress-strain relationship, self-recovery, and fracture failure. The results showed that after the immersion process, the hydrogel's tensile and compressive properties changed significantly, and the failure behavior changed from brittle fracture to ductile fracture. Through a microscopic mechanism, the alkaline solution caused a high degree of phase separation and crystallization within the polymer network, thereby changing the PVA hydrogel network from a single phase to a multiphase. Hence, we used a continuous multiphase network model with a certain probability distribution to describe this tensile behavior. This model well described the stress-strain relationship of the hydrogel from stretching to fracture and revealed that the macroscopic failure corresponded to the peak of fracture distribution. Studies have shown that attention should be paid to the influence of the in situ precipitation on the mechanical properties, and the probabilistic multiphase network model can be used to predict the mechanical behavior of hydrogels with multiple phase separation.

An Experimental Study on the Dynamic Mechanical Properties of Epoxy Polymer Concrete under Ultraviolet Aging.

Epoxy polymer concrete (EPC) is widely applied in engineering for its excellent mechanical properties. The impact loads and severe climatic conditions such as ultraviolet radiation, temperature change and rain erosion are in general for its engineering practice, potentially degrading the performance of EPC. In this paper, a procedure of accelerated aging for EPC, imitating the aging effect of ultraviolet radiation and hygrothermal conditions based on the meteorological statistics of Guangzhou city, was designed. After various periods of accelerated aging, the dynamic behaviors of EPC were studied by using a Split Hopkinson Pressure Bar (SHPB). The verification of the experimental data was performed. The two-stage dynamic compression stress-strain curves were obtained: (a) linear growth stage following by strain hardening stage at impact velocity 12.2 m/s and 18.8 m/s, (b) linear growth stage and then a horizontal stage when impact velocity is 25.0 m/s, (c) linear growth stage following by strain softening stage at impact velocity 29.2 m/s. The experimental results show that the specimens after longer accelerated aging tend to be more easily broken, especially at impact velocity 12.2 m/s and 18.8 m/s, while the strain rate is the main factor affecting the compression strength and stiffness. Ultimately the influence of strain rate and equivalent aging time on dynamic increase factor was revealed by a fitting surface.

Residual Flexural Performance of Epoxy Polymer Concrete under Hygrothermal Conditions and Ultraviolet Aging.

Epoxy polymer concrete (EPC) has found increasing applications in infrastructure as a rising candidate among civil engineering materials. In most of its service environments, EPC is inevitably exposed to severe weather conditions, e.g., violent changes in temperature, rain, and ultraviolet (UV) radiation. In this paper, we designed an accelerated aging test for EPC, which includes periodic variation of temperature and water spray, as well as intensive UV-light irradiation, imitating the outdoor environment in South China. The experimental results show that the flexural performance of EPC is found deteriorate with the aging time. An aging process equivalent to four years (UV radiation dose) results in up to 8.4% reduction of flexural strength. To explore the mechanisms of observed performance degradation, the EPC specimen in the four-point-bending test is considered as a layered beam. The analysis indicates that the loss of flexural load-carrying capacity of an aged EPC beam is dominated by the reduction of mechanical properties of the surface layer. The mechanical properties of the surface layer are closely associated with the aging of epoxy mortar, which can be approximated as a reciprocal function of the aging time. By introducing damage to the surface layer into the layered beam, the proposed model demonstrates a good ability to predict the residual flexural strength of EPC during the aging process.

Modeling of Compressive Strength for Unidirectional Fiber Reinforced Composites with Nanoparticle Modified Epoxy Matrix.

Incorporation of nanoparticles into polymer matrix was found to considerably improve the compressive performance of unidirectional fiber reinforced composites. In our experimental study, an increase by 62.7% in the longitudinal compressive strength of unidirectional carbon fiber reinforced composites is attained by dispersing 8.7 vol.% SiO2 nanoparticles into epoxy matrix. A compressive strength model is established to quantitatively describe the reinforcing effects of nanoparticles, which combines a modified microbuckling model for unidirectional fiber reinforced composites and a constitutive model for nanocomposite matrices under compression. In the two models, the coupling of damage and plasticity is considered to contribute to the nonlinear response of nanocomposite matrix. The proposed strength model demonstrates excellent prediction capability in experimental verification. A small relative deviation below 8.2% is achieved between the predicted compressive strength of unidirectional fiber reinforced composites and the measured values, which is at the same level of random error in experiments.