Research on solitons interactions' in one-dimensional indium chains on Si(111) surfaces

Solitons have garnered significant attention across various fields, yet a contentious debate persists regarding the precise structure of solitons on indium chains. Currently, multiple forms of solitons in one-dimensional atomic chains have been reported. STM provides an effective means to study the precise atomic structure of solitons, particularly their dynamics and interactions. However, limited research has been conducted on soliton interactions and soliton-chain interactions, despite their profound impact on relative soliton motions and the overall physical properties of the system. In this work, we characterized the structures of the soliton dimer and trimer, observed the displacements induced by the soliton entity and statisticized the dynamic behaviors of soliton dimers over time evolution or temperature. To reveal the soliton mechanism, we further utilized STM to investigate the CDWs between two solitons when two monomers were encountered. Additionally, we achieved the manipulation of the monomer on the indium chain by the STM tip. Our work serves as an important approach to elucidate interactions in correlated electronic systems and advance the development of potential topological soliton computers

Safety Risk Analysis of Unmanned Ships in Inland Rivers Based on a Fuzzy Bayesian Network

Risk factor identification is the basis for risk assessment. To quantify the safety risks of unmanned vessels in inland rivers, through analysis of previous studies, the safety risk impact factor framework of unmanned vessels in inland rivers is established based on three aspects: the ship aspect, the environmental aspect, and the management and control aspect. Relying on Yangtze River, a fuzzy Bayesian network of the sailing safety risk of unmanned ships in inland rivers is constructed. The proposed safety risk model has considered different operational and environmental factors that affect shipping operations. Based on the fuzzy set theory, historical data, and expert judgments and on previous works are used to estimate the base value (prior values) of various risk factors. The case study assessed the safety risk probabilities of unmanned vessels in Yangtze River. By running uncertainty and sensitivity analyses of the model, a significant change in the likelihood of the occurrence of safety risk is identified, and suggests a dominant factor in risk causation. The research results can provide effective information for analyzing the current safety status for navigation systems of unmanned ships in inland rivers. The estimated safety risk provides early warning to take appropriate preventive and mitigative measures to enhance the overall safety of shipping operations. Document type: Articl

Actuator and Sensor Fault Classification for Wind Turbine Systems Based on Fast Fourier Transform and Uncorrelated Multi-Linear Principal Component Analysis Techniques

In response to the high demand of the operation reliability and predictive maintenance, health monitoring and fault diagnosis and classification have been paramount for complex industrial systems (e.g., wind turbine energy systems). In this study, data-driven fault diagnosis and fault classification strategies are addressed for wind turbine energy systems under various faulty scenarios. A novel algorithm is addressed by integrating fast Fourier transform and uncorrelated multi-linear principal component analysis techniques in order to achieve effective three-dimensional space visualization for fault diagnosis and classification under a variety of actuator and sensor faulty scenarios in 4.8 MW wind turbine benchmark systems. Moreover, comparison studies are implemented by using multi-linear principal component analysis with and without fast Fourier transform, and uncorrelated multi-linear principal component analysis with and without fast Fourier transformation data pre-processing, respectively. The effectiveness of the proposed algorithm is demonstrated and validated via the wind turbine benchmark

Atomic structure, energetics, and dynamics of topological solitons in Indium chains on Si(111) surfaces

Based on scanning tunneling microscopy and first-principles theoretical studies, we characterize the precise atomic structure of a topological soliton in In chains grown on Si(111) surfaces. Variable-temperature measurements of the soliton population allow us to determine the soliton formation energy to be ~60 meV, smaller than one half of the band gap of ~200 meV. Once created, these solitons have very low mobility, even though the activation energy is only about 20 meV; the sluggish nature is attributed to the exceptionally low attempt frequency for soliton migration. We further demonstrate local electric field-enhanced soliton dynamics.Comment: 5 pages, 3 figure

Data Tracking Analysis of the Geomagnetic Fixed-Station Network in China

Data tracking analysis is an important mechanism for increasing data analysis capacity and eliminating interference from observational data. In this study, the technique was applied to the geomagnetic fixed-station network to improve the efficiency and accuracy of analysis to extract useful information. This paper introduces the scope, workflow, analysis platform, abnormal variation status, and results of the geomagnetic data tracking analysis. We present some typical examples of abnormal variations in addition to our proposals for future work

DDX5 facilitates HIV-1 replication as a cellular co-factor of Rev.

HIV-1 Rev plays an important role in the late phase of HIV-1 replication, which facilitates export of unspliced viral mRNAs from the nucleus to cytoplasm in infected cells. Recent studies have shown that DDX1 and DDX3 are co-factors of Rev for the export of HIV-1 transcripts. In this report, we have demonstrated that DDX5 (p68), which is a multifunctional DEAD-box RNA helicase, functions as a new cellular co-factor of HIV-1 Rev. We found that DDX5 affects Rev function through the Rev-RRE axis and subsequently enhances HIV-1 replication. Confocal microscopy and co-immunoprecipitation analysis indicated that DDX5 binds to Rev and this interaction is largely dependent on RNA. If the DEAD-box motif of DDX5 is mutated, DDX5 loses almost all of its ability to bind to Rev, indicating that the DEAD-box motif of DDX5 is required for the interaction between DDX5 and Rev. Our data indicate that interference of DDX5-Rev interaction could reduce HIV-1 replication and potentially provide a new molecular target for anti-HIV-1 therapeutics

Data-Driven Fault Classification for Non-Inverting Buck–Boost DC–DC Power Converters Based on Expectation Maximisation Principal Component Analysis and Support Vector Machine Approaches

Data-driven fault classification for power converter systems has been taking more into considerations in power electronics, machine drives, and electric vehicles. It is challenging to classify the different topologies of faults in the real time monitoring control systems. In this paper, a data-driven and supervised machine learning-based fault classification technique is adopted by combining and consolidating with Expectation Maximisation Principal Component Analysis (EMPCA) and Support Vector Machine (SVM) to substantiate the availability of fault classification. The proposed methodology is applied to the non-inverting Buck–Boost DC–DC power converter systems subjected to the incipient fault and serious fault, respectively. Finally, the feasibility of the approach is validated by intensive simulations and comparison studies

Lens differentiation is controlled by the balance between PDGF and FGF signaling

How multiple receptor tyrosine kinases coordinate cell fate determination is yet to be elucidated. We show here that the receptor for platelet-derived growth factor (PDGF) signaling recruits the p85 subunit of Phosphoinositide 3-kinase (PI3K) to regulate mammalian lens development. Activation of PI3K signaling not only prevents B-cell lymphoma 2 (BCL2)-Associated X (Bax)- and BCL2 Antagonist/Killer (Bak)-mediated apoptosis but also promotes Notch signaling to prevent premature cell differentiation. Reducing PI3K activity destabilizes the Notch intracellular domain, while the constitutive activation of Notch reverses the PI3K deficiency phenotype. In contrast, fibroblast growth factor receptors (FGFRs) recruit Fibroblast Growth Factor Receptor Substrate 2 (Frs2) and Rous sarcoma oncogene (Src) Homology Phosphatase 2 (Shp2) to activate Mitogen-Activated Protein Kinase (MAPK) signaling, which induces the Notch ligand Jagged 1 (Jag1) and promotes cell differentiation. Inactivation of Shp2 restored the proper timing of differentiation in the p85 mutant lens, demonstrating the antagonistic interaction between FGF-induced MAPK and PDGF-induced PI3K signaling. By selective activation of PI3K and MAPK, PDGF and FGF cooperate with and oppose each other to balance progenitor cell maintenance and differentiation