We report the observation of electron-transfer-mediated decay (ETMD) involving magnesium (Mg) clusters embedded in helium (He) nanodroplets. ETMD is initiated by the ionization of He followed by removal of two electrons from the Mg clusters of which one is transferred to the He ion while the other electron is emitted into the continuum. The process is shown to be the dominant ionization mechanism for embedded clusters for photon energies above the ionization potential of He. For Mg clusters larger than five atoms we observe stable doubly ionized clusters. Thus, ETMD provides an efficient pathway to the formation of doubly ionized cold species in doped nanodroplets.
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http://dx.doi.org/10.1103/PhysRevLett.116.203001 | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
Guangdong Institute of Intelligence Science and Technology, 519031 Hengqin, Zhuhai, Guangdong, China.
Manifold learning techniques have emerged as crucial tools for uncovering latent patterns in high-dimensional single-cell data. However, most existing dimensionality reduction methods primarily rely on 2D visualization, which can distort true data relationships and fail to extract reliable biological information. Here, we present DTNE (diffusive topology neighbor embedding), a dimensionality reduction framework that faithfully approximates manifold distance to enhance cellular relationships and dynamics.
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January 2025
Department of Civil Engineering, Transilvania University of Brașov, 5 Turnului Str., 500152 Brașov, Romania.
Pollution is one of the most important issues currently affecting the global population and environment. Therefore, determining the zones where stringent measures should be taken is necessary. In this study, Principal Component Analysis (PCA), Factor Analysis (FA), and t-distributed Stochastic Neighbor Embedding (t-SNE) were utilized for dimensionality reduction and clustering of data series containing the concentration of 10 heavy metals collected at 14 locations.
View Article and Find Full Text PDFJ Intell
January 2025
School of Social Sciences, Tsinghua University, Beijing 100084, China.
As psychological research progresses, the issue of concept overlap becomes increasing evident, adding to participant burden and complicating data interpretation. This study introduces an Embedding-based Semantic Analysis Approach (ESAA) for detecting redundancy in psychological concepts, which are operationalized through their respective scales, using natural language processing techniques. The ESAA utilizes OpenAI's text-embedding-3-large model to generate high-dimensional semantic vectors (i.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Engineering, Westlake University, No. 600 Dunyu Road, 310030 Zhejiang, P.R. China.
Single-cell RNA sequencing (scRNA-seq) offers remarkable insights into cellular development and differentiation by capturing the gene expression profiles of individual cells. The role of dimensionality reduction and visualization in the interpretation of scRNA-seq data has gained widely acceptance. However, current methods face several challenges, including incomplete structure-preserving strategies and high distortion in embeddings, which fail to effectively model complex cell trajectories with multiple branches.
View Article and Find Full Text PDFBiophys J
January 2025
Department of Physics and Astronomy, University College London, London WC1E 6BT, United Kingdom. Electronic address:
Photosynthetic organisms rely on a network of light-harvesting protein-pigment complexes to efficiently absorb sunlight and transfer excitation energy to reaction centre proteins where charge separation occurs. In photosynthetic purple bacteria, these complexes are embedded within the cell membrane, with lipid composition affecting complex clustering, thereby impacting inter-complex energy transfer. However, the impact of the lipid bilayer on intra-complex excitation dynamics is less understood.
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