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Silique development exerts significant impacts on crop yield. CRPs (Cysteine-rich peptides) can mediate cell–cell communication during plant reproduction and development. However, the functional characterization and regulatory mechanisms of CRPs in silique development remain unclear. In this study, we identified many CRP genes downstream of the CRP gene TPD1 (TAPETUM DETERMINANT1) during silique development using a microarray assay. The novel Arabidopsis thaliana pollen-borne CRPs, the PCP-Bs (for pollen coat protein B-class) gene AtPCP-Ba, along with TPD1, are essential for silique development. The AtPCP-Ba was significantly down-regulated in tpd1 flower buds but up-regulated in OE-TPD1 flower buds and siliques. The silencing of AtPCP-Ba compromised the wider silique of OE-TPD1 plants and inhibited the morphology of OE-TPD1 siliques to the size observed in the wild type. A total of 258 CRPs were identified with the bioinformatic analysis in Arabidopsis, Brassica napus, Glycine max, Oryza sativa, Sorghum bicolor, and Zea mays. Based on the evolutionary tree classification, all CRP members can be categorized into five subgroups. Notably, 107 CRP genes were predicted to exhibit abundant expression in flowers and fruits. Most cysteine-rich peptides exhibited high expression levels in Arabidopsis and Brassica napus. These findings suggested the involvement of the CRP AtPCP-Ba in the TPD1 signaling pathway, thereby regulating silique development in Arabidopsis.

Bolt loosening can significantly impact the accuracy, stability, and safety of equipment. The detection of bolt loosening in a timely manner is crucial for ensuring the safety, reliability, performance, and service life of equipment, structures, and systems. Various methods exist for detecting bolt loosening, such as strain gauges and ultrasonic waves. However, these technologies have some limitations that impede their widespread application. In this paper, for the high-pressure pipe manifolds that may experience leakage accidents due to the loosening of bolts, an early bolt loosening detection method based on digital image correlation is proposed. Initially, a model is established through tensile tests to relate the average strain on the side of the bolt head to the axial force. Subsequently, an industrial camera captures images of bolts with random speckles under operational conditions. Using digital image correlation technology, the average strain in a specific region on the side of the bolt head is calculated. By integrating the average strain into the established relationship model between the average strain and axial force, the axial force of the bolt under operational conditions can be predicted, enabling the early assessment of bolt loosening. The findings show that the average strain on the side of the bolt head increases proportionally with the axial force, indicating a strong linear relationship. This method enables accurate prediction of the bolt’s axial force, offering a new approach for identifying the early loosening of bolts in high-pressure manifolds and monitoring structural health.

Skateboarding is an Olympic event with frequent jumping and landing, where the cushioning effect by the foot structure (from the arch, metatarsals, etc.) and damping performance by sports equipment (shoes, insoles, etc.) can greatly affect an athlete’s sports performance and lower the risk of limb injury. Skateboarding is characterized by the formation of a “man–shoe–skateboard system,” which makes its foot cushioning mechanism different from those of other sports maneuvers, such as basketball vertical jump and gymnastics broad jump. Therefore, it is necessary to clarify the cushioning mechanism of the foot structure upon landing on a skateboard. To achieve this, a multibody finite element model of the right foot, shoe, and skateboard was created using Mimics, Geomagic, and ANSYS. Kinetic data from the ollie maneuver were used to determine the plantar pressure and Achilles tendon force at three characteristics (T1, T2, and T3). The stress and strain on the foot and metatarsals (MT1–5) were then simulated. The simulation results had an error of 6.98% compared to actual measurements. During landing, the force exerted on the internal soft tissues tends to increase. The stress and strain variations were highest on MT2, MT3, and MT4. Moreover, the torsion angle of MT1 was greater than those of the other metatarsals. Additionally, the displacements of MT2, MT3, and MT4 were higher than those of the other parts. This research shows that skateboarders need to absorb the ground reaction force through the movements of the MTs for ollie landing. The soft tissues, bones, and ligaments in the front foot may have high risks of injury. The developed model serves as a valuable tool for analyzing the foot mechanisms in skateboarding; furthermore, it is crucial to enhance cushioning for the front foot during the design of skateboard shoes to reduce potential injuries.

Quantum Convolutional Neural Network (QCNN) has achieved significant success in solving various complex problems, such as quantum many-body physics and image recognition. In comparison to the classical Convolutional Neural Network (CNN) model, the QCNN model requires excellent numerical performance or efficient computational resources to showcase its potential quantum advantages, particularly in classical data processing tasks. In this paper, we propose a computationally resource-efficient QCNN model referred to as RE-QCNN. Specifically, through a comprehensive analysis of the complexity associated with the forward and backward propagation processes in the quantum convolutional layer, our results demonstrate a significant reduction in computational resources required for this layer compared to the classical CNN model. Furthermore, our model is numerically benchmarked on recognizing images from the MNIST and Fashion-MNIST datasets, achieving high accuracy in these multi-class classification tasks.

Monoterpenes are a class of volatile organic compounds that play crucial roles in imparting floral and fruity aromas to Muscat-type grapes. However, our understanding of the regulatory mechanisms underpinning monoterpene biosynthesis in grapes, particularly following abscisic acid (ABA) treatment, remains elusive. This study aimed to explore the impact of exogenous ABA on monoterpene biosynthesis in Ruiduhongyu grape berries by employing Headspace Solid-Phase Micro-Extraction Gas Chromatography–Mass Spectrometry (HS-SPME/GC–MS) analysis and transcriptome sequencing. The results suggested significant differences in total soluble solids (TSS), pH, and total acid content. ABA treatment resulted in a remarkable increase in endogenous ABA levels, with concentrations declining from veraison to ripening stages. ABA treatment notably enhanced monoterpene concentrations, particularly at the E_L37 and E_L38 stages, elevating the overall floral aroma of grape berries. According to the variable gene expression patterns across four developmental stages in response to ABA treatment, the E_L37 stage had the largest number of differential expressed genes (DEGs), which was correlated with a considerable change in free monoterpenes. Furthermore, functional annotation indicated that the DEGs were significantly enriched in primary and secondary metabolic pathways, underlining the relationship between ABA, sugar accumulation, and monoterpene biosynthesis. ABA treatment upregulated key genes involved in the methylerythritol phosphate (MEP) pathway, enhancing carbon allocation and subsequently impacting terpene synthesis. This study also identified transcription factors, including MYB and AP2/ERF families, potentially modulating monoterpene and aroma-related genes. Weighted gene co-expression network analysis (WGCNA) linked ABA-induced gene expression to monoterpene accumulation, highlighting specific modules enriched with genes associated with monoterpene biosynthesis; one of these modules (darkgreen) contained genes highly correlated with most monoterpenes, emphasizing the role of ABA in enhancing grape quality during berry maturation. Together, these findings provide valuable insights into the multifaceted effects of exogenous ABA on monoterpene compounds and grape berry flavor development, offering potential applications in viticulture and enology.

The phytohormone gibberellic acid (GA3) is widely used in the table grape industry. However, there is a paucity of information concerning the effects of GA3 on fruit quality and sink strength. This study investigated the effects of exogenous GA3 treatments (elongating cluster + seedless + expanding, T1; seedless + expanding, T2; expanding, T3; and water, CK) on the content of sugars, organic acids, and endogenous hormones and sink strength. Results showed that T2 treatment displayed the highest fructose and glucose levels at 100 days after treatment (DAT), whereas its effect on tartaric acid, malic acid, and citric acid concentrations at 80 and 100 DAT was relatively weak. Under GA3 treatments, GA3, IAA, and CTK contents increased, whereas ABA content decreased at 1, 2, 4, 8, and 48 h. Analysis of sugar phloem unloading revealed that T2 treatment exhibited the highest values during softening and ripening stages. Our findings indicate that appropriate GA3 application can positively influence sink strength by regulating sink size and activity, including berry size enlargement, sugar phloem unloading, and sugar accumulation in grape sink cells.

The push-off angle is an important factor affecting speed-skating performance. However, quantitative evidence for the relationship between the push-off angle and foot injury is incomplete. This study aimed to establish a three-dimensional (3D) finite element model (FEM) and investigate the mechanical responses of foot structures to stress and strain to explore the relationship between injury and movement. A 3D FEM was reconstructed using CT and 3D scan data and validated by comparing the FEM-predicted and in vivo measurement data in the balanced standing state. A push-off angle obtained from a video of a champion was loaded into the FEM. The error rates of validation were less than 10%. With a decrease in the push-off angle, the stress on the metatarsal increased; the stress on the talus, ankle joint cartilage and plantar fascia decreased, as did the strain on the ankle joint cartilage and plantar fascia. The FEM was considered reasonable. Not all foot structures had an increased risk of injury with a decrease in the push-off angle from 70° to 42°. The FEM established in this study provides a possibility for further determining and quantifying the relationship between foot injury and skating technique.

Natural Language Processing (NLP) has gained prominence in diagnostic radiology, offering a promising tool for improving breast imaging triage, diagnosis, lesion characterization, and treatment management in breast cancer and other breast diseases. This review provides a comprehensive overview of recent advances in NLP for breast imaging, covering the main techniques and applications in this field. Specifically, we discuss various NLP methods used to extract relevant information from clinical notes, radiology reports, and pathology reports and their potential impact on the accuracy and efficiency of breast imaging. In addition, we reviewed the state-of-the-art in NLP-based decision support systems for breast imaging, highlighting the challenges and opportunities of NLP applications for breast imaging in the future. Overall, this review underscores the potential of NLP in enhancing breast imaging care and offers insights for clinicians and researchers interested in this exciting and rapidly evolving field.

The application of quantum computation to accelerate machine learning algorithms is one of the most promising areas of research in quantum algorithms. In this paper, we explore the power of quantum learning algorithms in solving an important class of Quantum Phase Recognition (QPR) problems, which are crucially important in understanding many-particle quantum systems. We prove that, under widely believed complexity theory assumptions, there exists a wide range of QPR problems that cannot be efficiently solved by classical learning algorithms with classical resources. Whereas using a quantum computer, we prove the efficiency and robustness of quantum kernel methods in solving QPR problems through Linear order parameter Observables. We numerically benchmark our algorithm for a variety of problems, including recognizing symmetry-protected topological phases and symmetry-broken phases. Our results highlight the capability of quantum machine learning in predicting such quantum phase transitions in many-particle systems.

In recent years, Topic Detection and Tracking (TDT) has served as a core technology for searching, organizing and structuring news oriented textual materials from a variety of internet news and social media. The biggest challenges of TDT are the sparsity and complexity of data, organization of topic granularity, unexpectedness of emergency topics, and the unpredictability of topics evolution. This paper proposes a new TDT method based on event ontology for hierarchical topic detection and tracking topic evolution, named TDTEO. As domain-oriented event knowledge base, the event ontology provides event classes hierarchy based on domain common sense, as well a set of scenario models that describe the occurrence and evolution of different types of emergency events. The proposed method solves the problem that new emerging events are easy to be missed in the process of topic detection, and solves the problem that the topic model is easy to result in semantics drift due to the dynamic evolution of topic, and it can effectively improve the accuracy of topic detection and tracking. Experiments show our models achieve satisfactory performance of topic detection with a maximum macro-F1 value of 85.25%, and the (CDet)Norm of topic tracking in the datasets is as low as 0.1028. Experimental results show that hierachical topic model can effectively detect the topics and tracking model based on event scenario can reflect the trend of topic evolution.

In this paper, we propose a novel design, called MixNN, for protecting deep learning model structure and parameters since the model consists of several layers and each layer contains its own structure and parameters. The layers in a deep learning model of MixNN are fully decentralized. It hides communication address, layer parameters and operations, and forward as well as backward message flows among non-adjacent layers using the ideas from mix networks. MixNN has the following advantages: (i) an adversary cannot fully control all layers of a model, including the structure and parameters; (ii) even some layers may collude but they cannot tamper with other honest layers; (iii) model privacy is preserved in the training phase. We provide detailed descriptions for deployment. In one classification experiment, we compared a neural network deployed in a virtual machine with the same one using the MixNN design on the AWS EC2. The result shows that our MixNN retains less than 0.001 difference in terms of classification accuracy, while the whole running time of MixNN is about 7.5 times slower than the one running on a single virtual machine.

Nanofiber-structured La2NiO4+δ (LNO) and LaNi0.6Fe0.4O3-δ (LNF) cathodes, which were fabricated by an electrospinning technique, were used for proton-conducting solid oxide fuel cells (H-SOFCs) for the first time, aiming to develop high-performance cobalt-free cathodes for H-SOFCs. High porosity and large specific surface area of LNO, LNF nanofiber-structured cathodes were beneficial for the cathode reactions, resulting in an encouraging peak power density of 508 mWcm−2 and 551 mWcm−2 for LNO and LNF cathode cell at 700 °C, respectively. The nanofiber-structured cathodes showed a higher fuel cell performance and lower polarization resistance compared with that of the cell using corresponding powder cathode, suggesting the construction of nanofiber-structured cathode provided an alternative and promising route to prepare high performance cathodes for H-SOFCs. Keywords: Proton conductor, Cobalt-free cathode, Nanofiber, Solid oxide fuel cells

Abstract Background Hereditary hearing loss (HL) is heterogeneous in terms of their phenotypic features, modes of inheritance, and causative gene mutations. The contribution of genetic variants to sporadic HL remains largely expanding. Either recessive or de novo dominant variants could result in an apparently sporadic occurrence of HL. In an attempt to find such variants we recruited 128 Chinese patients with sporadic nonsyndromic sensorineural HL (NSHL) and performed targeted deafness multigene sequencing in these unrelated trios‐families to elucidate the molecular basis. Methods We analyzed a total of 384 available members (probands and their two parents) from 128 unrelated Chinese families presenting with bilateral sensorineural HL, in which previous screening had found no mutations with the GJB2, SLC26A4, and MT‐RNR1 genes. We used a targeted genomic enrichment platform to simultaneously capture exons, splicing sites, and immediate flanking intron sequences of 127 known deafness genes. Sanger sequencing was used to identify probands and their two parents segregating causative variants in the candidate gene. Results We observed that two heterozygous de novo WFS1 mutations in exon 8: c.2051C>T (p.A684V) and c.2590G>A (p.E864K) in five families. The two de novo WFS1 mutations were found in 3.9% (5/128) of sporadic HL patients. We found that four of the five patients had the same de novo p.A684V mutation, and their audiograms showed symmetrical bilateral and profound sensorineural hearing impairments at all frequencies, but only the proband with de novo p.E864K mutation demonstrated significantly bilateral moderate low–mid frequency sensorineural HL. Our data suggest that this WFS1 p.A684V is likely to be a de novo mutational hot spot. Conclusions We found 3.9% (5/128) of sporadic NSHL is caused by de novo WFS1 mutations. Our data provide that the de novo p.E864K mutation is first identified and de novo p.A684V mutation is likely to be a mutational hot spot in WFS1. It is the first study to highlight that WFS1 gene with the two de novo mutations has been indicated to classify the distinct hearing impairment phenotypes. Furthermore, de novo p.A684V serves as a WFS1 mutational hot spot that was found in the Chinese population with sporadic childhood NSHL, and our study also provides pointers toward the necessity for sequencing of asymptomatic parents of a sporadic case with an apparent dominant pathogenic variant.

ABA plays a crucial role in controlling several ripening-associated processes in grape berries. The soluble proteins named as PYR (pyrabactin resistant)/PYL (PYR-like)/RCAR (regulatory component of ABA receptor) family have been characterized as ABA receptors. Here, the function of a grape PYL1 encoding gene involved in the response to ABA was verified through heterologous expression. The expression level of VlPYL1 was highest in grape leaf and fruit tissues of the cultivar Kyoho, and the expression of VlPYL1 was increased during fruit development and showed a reduction in ripe berries. Over-expression of VlPYL1 enhances ABA sensitivity in Arabidopsis. Using the transient overexpression technique, the VlPYL1 gene was over-expressed in grape berries. Up-regulation of the VlPYL1 gene not only promoted anthocyanin accumulation but also induced a set of ABA-responsive gene transcripts, including ABF2 and BG3. Although tobacco rattle virus (TRV)-induced gene silencing (VIGS) was not successfully applied in the “Kyoho” grape, the application of the transient overexpression technique in grape fruit could be used as a novel tool for studying grape fruit development.

This research aimed to comparatively evaluate the influences of root restriction (RR) cultivation and traditional cultivation (RC) on grape berry skin metabolomics using a non-targeted metabolomics method. Two-hundred-and-ninety-one metabolites were annotated and the kinetics analyses showed that berry skin metabolome is stage- and cultivation-dependent. Our results showed that RR influences significantly the metabolomes of berry skin tissues, particularly on secondary metabolism, and that this effect is more obvious at pre-veraison stage, which was evidenced by the early and fast metabolic shift from primary to secondary metabolism. Altogether, this study provided an insight into metabolic adaptation of berry skin to RR stress and expanded general understanding of berry development.

We present an in-depth analysis of aroma profiles and sensory attributes, employing solid-phase microextraction gas chromatography/mass spectrometry (SPME-GC-MS) to identify the key compounds driving consumer preference in 19 unfamiliar cultivars. In combination with popular cultivars, we identified a total of 100 compounds in all table grapes, of which 26 key volatiles were correlated with consumer liking. Based on this relationship, five aroma combinations (AC) were formulated, wherein 33 compounds contributed to aroma intensity, and thus, were viewed as active volatiles. The fruity, floral, and sweet aromas were further divided into secondary aromatic series, of which the apple, citrus, orange, rose, geranium, violet, and honey aromas constituted the predominant series in unfamiliar cultivars. Xiangyue and Heikuixiang emerged as the preferred table grapes according to our analysis. By comparison, the popular cultivars showed relatively fewer volatiles, but their contents were much greater than the large number of volatiles identified in the unfamiliar cultivars.

With the aid of computer algebra system Mathematica 8.0 and by the integral factor method, for a family of generalized nilpotent systems, we first compute the first several quasi-Lyapunov constants, by vanishing them and rigorous proof, and then we get sufficient and necessary conditions under which the systems admit analytic centers at the origin. In addition, we present that seven amplitude limit cycles can be created from the origin. As an example, we give a concrete system with seven limit cycles via parameter perturbations to illustrate our conclusion. An interesting phenomenon is that the exponent parameter n controls the singular point type of the studied system. The main results generalize and improve the previously known results in Pan.

'Taishanzaoxia' fruit rapid softening and dehiscence during ripening stage and this process is very sensitive to endogenous ethylene. In this study, we cloned five ethylene signal transcription factors (ZMdEIL1, ZMdEIL2, ZMdEIL3, ZMdERF1 and ZMdERF2) and one functional gene, ZMdPG1, encoding polygalacturonase that could loose the cell connection which associated with fruit firmness decrease and fruit dehiscence to illustrate the reasons for this specific fruit phenotypic and physiological changes. Expression analysis showed that ZMdERF1 and ZMdEIL2 transcription were more abundant in 'Taishanzaoxia' softening fruit and dehiscent fruit and their expression was inhibited by an ethylene inhibitor 1-methylcyclopropene. Therefore, ZMdERF1 and ZMdEIL2 expression were responses to endogenous ethylene and associated with fruit softening and dehiscence. ZMdPG1 expression was induced when fruit softening and dehiscence but this induction can be blocked by 1-MCP, indicating that ZMdPG1 was essential for fruit softening and dehiscence and its expression was mediated by the endogenously occurred ethylene. ZMdPG1 overexpression in Arabidopsis led to silique early dehiscence while suppressing ZMdPG1 expression by antisense ZMdPG1 prevented silique naturally opening. The result also suggested that ZMdPG1 related with the connection between cells that contributed to fruit softening and dehiscence. ZMdERF1 was more closely related with ethylene signaling but it was not directly regulated the ZMdPG1, which might be regulated by the synergic pattern of ethylene transcription factors because of both the ZMdERF1 and ZMdERF2 could interact with ZMdEIL2.

A periodic discrete time three species competition system is investigated. With the aid of differential equations with piecewise constant arguments, a discrete analogue of continuous nonautonomous three species competition system is proposed. By using Gaines and Mawhin's continuation theorem of coincidence degree theory, sufficient conditions for the existence of positive periodic solutions of the model are obtained.

We propose and deal with a discrete mutualism model with infinite deviating arguments and feedback controls. Sufficient conditions which guarantee the permanence of the system are obtained by using the difference inequality theory. The paper ends with brief conclusions.

A ratio-dependent predator-prey model with two delays is investigated. The conditions which ensure the local stability and the existence of Hopf bifurcation at the positive equilibrium of the system are obtained. It shows that the two different time delays have different effects on the dynamical behavior of the system. An example together with its numerical simulations shows the feasibility of the main results. Finally, main conclusions are included.

We solve theoretically the center problem and the cyclicity of the Hopf bifurcation for two families of Kukles-like systems with their origins being nilpotent and monodromic isolated singular points.

A Lotka-Volterra predator-prey model with time-varying delays is investigated. By using the differential inequality theory, some sufficient conditions which ensure the permanence and global asymptotic stability of the system are established. The paper ends with some interesting numerical simulations that illustrate our analytical predictions.

The linearizability (or isochronicity) problem is one of the open problems for polynomial differential systems which is far to be solved in general. A progressive way to find necessary conditions for linearizability is to compute period constants. In this paper, we are interested in the linearizability problem of p : −q resonant degenerate singular point for polynomial differential systems. Firstly, we transform degenerate singular point into the origin via a homeomorphism. Moreover, we establish a new recursive algorithm to compute the so-called generalized period constants for the origin of the transformed system. Finally, to illustrate the effectiveness of our algorithm, we discuss the linearizability problems of 1 : −1 resonant degenerate singular point for a septic system. We stress that similar results are hardly seen in published literatures up till now. Our work is completely new and extends existing ones.

A delayed predator-prey model with disease in the prey is investigated. The conditions for the local stability and the existence of Hopf bifurcation at the positive equilibrium of the system are derived. The effect of the two different time delays on the dynamical behavior has been given. Numerical simulations are performed to illustrate the theoretical analysis. Finally, the main conclusions are drawn.

This paper deals with the problems of integrability and linearizable conditions at degenerate singular point in a class of quasianalytic septic polynomial differential system. We solve the problems by an indirect method, that is, we transform the quasianalytic system into an analytic system firstly, and the degenerate singular point into an elementary singular point. Then we calculate the singular values at the origin of the analytic system by the known classical methods. We obtain the center conditions and isochronous center conditions. Accordingly, integrability and pseudolinearizable conditions at degenerate singular point in the quasianalytic system are obtained. Especially, when 𝜆=1, the system has been studied in Wu and Zhang (2010).