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The nerve trunk healing process of a transected peripheral nerve trunk is composed of angiogenesis, nerve fiber regeneration, and scarring. Nerve trunk healing and neuroma formation probably share identical molecular mediators and similar regulations. At the nerve transection site, angiogenesis is sufficient and necessary for nerve fiber regeneration. Angiogenesis and nerve fiber regeneration reveal a positive correlation in the early time. Scarring and nerve fiber regeneration show a negative correlation in the late phase. We hypothesize that anti-angiogenesis suppresses neuromas. Subsequently, we provide potential protocols to test our hypothesis. Finally, we recommend employing anti-angiogenic small-molecule protein kinase inhibitors to investigate nerve transection injuries.

Abstract With a large number of film capacitors being deployed in critical locations in electrical and electronic systems, artificial intelligence (AI) technology is also expected to address the problems encountered in this process. According to our findings, AI applications can cover the entire lifecycle of film capacitors. However, the AI safety hazards in these applications have not received the attention they deserve. To meet this, the authors argue, with specific examples, risks that flawed, erratic, and unethical AI can introduce in the design, operation, and evaluation of film capacitors. Human‐AI common impact and more multi‐dimensional evaluation for AI are proposed to better cope with unknown, ambiguity, and known risks brought from AI in film capacitors now and in the future.

Abstract Film capacitors are playing an increasingly important role in power‐related fields, driven by the continuous development of dielectric materials and practical needs. Long‐term accumulation has also led to an increasing wealth of data related to film capacitors. Sonification opens up a new way for people to make good use of data from film capacitors. A framework for sonifying film capacitors data based on TwoTone is presented. Based on the analysis and discussion, it is clear that the sonification results can easily represent the monotonic variation pattern of film capacitors data. What's more, the sonification results increase the possibility that people pay attention to the changing trend of film capacitors data when there is no significant difference in the visual perception of the data. In addition to providing a new way of music generation of electrical equipment, the method proposed is expected to contribute to theory reference in typical scenarios, such as factory calibration of film capacitors, monitoring of film capacitor operation status, and presentation of statistical data of film capacitors' dielectric materials, which will help us to better understand the distribution characteristics of polymer films.

Highlights A bilayer dielectric film is prepared via coating boron nitride nanosheets (BNNSs) by solution casting on the surface of polyethylene terephthalate (PET) film. The BNNS layer acts as the efficient barrier layer to suppress the charge injection, thereby making the surface-modified PET films exhibit excellent breakdown strength and electrostatic energy storage performance. The surface coating methods are accessible and suitable for large-scale roll-to-roll process production of dielectric films.

The relative permittivity is one of the essential parameters determines the physical polarization behaviors of the nanocomposite dielectrics in many applications, particularly for capacitive energy storage. Predicting the relative permittivity of particle/polymer nanocomposites from the microstructure is of great significance. However, the classical effective medium theory and physics-based numerical calculation represented by finite element method are time-consuming and cumbersome for complex structures and nonlinear problem. The work explores a novel architecture combining the convolutional neural network (ConvNet) and finite element method (FEM) to predict the relative permittivity of nanocomposite dielectrics with incorporated barium titanite (BT) particles in polyvinylidene fluoride (PVDF) matrix. The ConvNet was trained and evaluated on big datasets with 14266 training data and 3514 testing data generated form a programmatic algorithm. Through numerical experiments, we demonstrate that the trained network can efficiently provide an accurate agreement between the ConvNet model and FEM by virtue of the significant evaluation metrics R2, which reaches as high as 0.9783 and 0.9375 on training and testing data, respectively. The strong universality of the presented method allows for an extension to fast and accurately predict other properties of the nanocomposite dielectrics.

Metallized Film Capacitors (MFC) are vital devices in many important fields such as energy, transportation, and aviation, whilst Digital Twin (DT) technology opens a new channel to leverage existing data resources of metallized film capacitors. This paper review current knowledge about metallized film capacitors and digital twin, list the key issues, propose frameworks, and provide the outlook to clarify the potential of digital twin’s application in metallized film capacitors. First, based on the development history and research status of metallized film capacitors, this review sorts out the key research issues of data utilization. Then, the connotation and typical characteristics of the digital twin definition are combed and refined, and the typical architecture of digital twin implementation is presented. Furthermore, the overall application architecture of digital twin in metallized film capacitors is constructed, and the technology system of each application scenario and the role of digital twin are analyzed. Finally, the main challenges in the application of the digital twin in metallized film capacitors and the future development directions are discussed. This review promotes the performance improvement, cost reduction and application expansion of metallized film capacitors, which can be used as a guide for the application of digital twin in other power equipment of energy system.

AimsThis study aimed to build a prediction model to early diagnose intracranial atherosclerosis (ICAS)-related large vascular occlusion (LVO) in acute ischemic stroke patients before digital subtractive angiography.MethodsPatients enrolled in the DIRECT-MT trial (NCT03469206) were included in our secondary analysis and distributed into ICAS-LVO and non-ICAS-LVO groups. We also retrieved demographic data, medical histories, clinical characteristics, and pre-operative imaging data. Hypothesis testing was used to compare data of the two groups, and univariate logistic regression was used to identify the predictors of ICAS-LVO primarily. Then, we used multivariate logistic regression to determine the independent predictors and formulate the prediction model. Model efficacy was estimated by the area under the receiver operating characteristic (ROC) curve (AUC) and diagnostic parameters generated from internal and external validations.ResultsThe subgroup analysis included 45 cases in the ICAS-LVO group and 611 cases in the non-ICAS-LVO group. Variates with p < 0.1 in the comparative analysis were used as inputs in the univariate logistic regression. Next, variates with p < 0.1 in the univariate logistic regression were used as inputs in the multivariate logistic regression. The multivariate logistic regression indicated that the atrial fibrillation history, hypertension and smoking, occlusion located at the proximal M1 and M2, hyperdense artery sign, and clot burden score were related to the diagnosis of ICAS-LVO. Then, we constructed a prediction model based on multivariate logistics regression. The sensitivity and specificity of the model were 84.09 and 74.54% in internal validation and 73.11 and 71.53% in external validation.ConclusionOur current prediction model based on clinical data of patients from the DIRECT-MT trial might be a promising tool for predicting ICAS-LVO.

Abstract Background High temperatures, particularly at night, decrease rice yield and quality. As high nighttime temperatures (HNTs) become increasingly frequent due to climate change, it is imperative to develop rice crops that tolerate HNTs. DNA methylation may represent a potential avenue for HNT-tolerant rice strain development, as this mechanism regulates gene activity and cellular phenotype in response to adverse environmental conditions without changing the nucleotide sequence. Results After HNT exposure, the methylation patterns of cytosines in the CHH context differed noticeably between two coisogenic rice strains with significantly different levels in heat tolerance. Methylation differences between strains were primarily observed on successive cytosines in the promoter or downstream regions of transcription factors and transposon elements. In contrast to the heat-sensitive rice strain, the regions 358–359 bp and 2–60 bp downstream of two basal transcriptional factors (TFIID subunit 11 and mediator of RNA polymerase II transcription subunit 31, respectively) were fully demethylated in the heat-tolerant strain after HNT exposure. In the heat-tolerant strain, HNTs reversed the methylation patterns of successive cytosines in the promoter regions of various genes involved in abscisic acid (ABA)-related reactive oxygen species (ROS) equilibrium pathways, including the pentatricopeptide repeat domain gene PPR (LOC_Os07g28900) and the homeobox domain gene homeobox (LOC_Os01g19694). Indeed, PRR expression was inhibited in heat-sensitive rice strains, and the methylation rates of the cytosines in the promoter region of PRR were greater in heat-sensitive strains as compared to heat-tolerant strains. Conclusions After HNT exposure, cytosines in the CHH context were more likely than cytosines in other contexts to be methylated differently between the heat-sensitive and heat-tolerant rice strains. Methylation in the promoter regions of the genes associated with ABA-related oxidation and ROS scavenging improved heat tolerance in rice. Our results help to clarify the molecular mechanisms underlying rice heat tolerance.

Enterovirus 71 (EV71) is the major causative agent of hand, foot and mouth disease (HFMD) in children, causing severe clinical outcomes and even death. Here, we report an important role of the highly conserved alanine residue at position 107 in the capsid protein VP1 (VP1A107) in the efficient replication of EV71. Substitutional mutations of VP1A107 significantly diminish viral growth kinetics without significant effect on viral entry, expression of viral genes and viral production. The results of mechanistic studies reveal that VP1A107 regulates the efficient cleavage of the VP0 precursor during EV71 assembly, which is required, in the next round of infection, for the transformation of the mature virion (160S) into an intermediate or A-particle (135S), a key step of virus uncoating. Furthermore, the results of molecular dynamic simulations and hydrogen-bond networks analysis of VP1A107 suggest that flexibility of the VP1 BC loop or the region surrounding the VP1107 residue directly correlates with viral infectivity. It is possible that sufficient flexibility of the region surrounding the VP1107 residue favors VP0 conformational change that is required for the efficient cleavage of VP0 as well as subsequent viral uncoating and viral replication. Taken together, our data reveal the structural role of the highly conserved VP1A107 in regulating EV71 maturation. Characterization of this novel determinant of EV71 virulence would promote the study on pathogenesis of Enteroviruses.

The transmission of infectious diseases has been studied by mathematical methods since 1760s, among which SIR model shows its advantage in its epidemiological description of spread mechanisms. Here we established a modified SIR model with nonlinear incidence and recovery rates, to understand the influence by any government intervention and hospitalization condition variation in the spread of diseases. By analyzing the existence and stability of the equilibria, we found that the basic reproduction number [Formula: see text] is not a threshold parameter, and our model undergoes backward bifurcation when there is limited number of hospital beds. When the saturated coefficient a is set to zero, it is discovered that the model undergoes the Saddle-Node bifurcation, Hopf bifurcation, and Bogdanov-Takens bifurcation of codimension 2. The bifurcation diagram can further be drawn near the cusp type of the Bogdanov-Takens bifurcation of codimension 3 by numerical simulation. We also found a critical value of the hospital beds bc at [Formula: see text] and sufficiently small a, which suggests that the disease can be eliminated at the hospitals where the number of beds is larger than bc. The same dynamic behaviors exist even when a ≠ 0. Therefore, it can be concluded that a sufficient number of the beds is critical to control the epidemic.