Mapping Structure-Property Relationships in Fullerene Systems: A Computational Study from C20 to C60

Fullerenes, as characteristic carbon nanomaterials, offer significant potential for diverse applications due to their structural diversity and tunable properties. Numerous isomers can exist for a specific fullerene size, yet a comprehensive understanding of their fundamental properties remains elusive. In this study, we construct an up-to-date computational database for C20-C60 fullerenes, consisting of 5770 structures, and calculate 12 fundamental properties using DFT, including stability (binding energy), electronic properties (HOMO-LUMO gap), and solubility (partition coefficient logP). Our findings reveal that the HOMO-LUMO gap weakly correlates with both binding energy and logP, indicating that electronic properties can be tailored for specific uses without affecting stability or solubility. In addition, we introduce a set of novel topological features and geometric measures to investigate structure-property relationships. For the first time, we apply atom, bond, and hexagon features to effectively predict the stability of C20-C60 fullerenes, surpassing the conventional qualitative isolated pentagon rule, and demonstrating their robust transferability to larger-size fullerenes beyond C60. Our work offers guidance for optimizing fullerenes as electron acceptors in organic solar cells and lays a foundational understanding of their functionalization and applications in energy conversion and nanomaterial sciences

Comparative Analysis of Conventional Machine Learning and Graph Neural Network Models for Perovskite Property Prediction

Perovskite materials, renowned for their versatility and remarkable properties, pose challenges in discovering optimal candidates due to the vast compositional space. Data-driven machine learning (ML) offers promise in expediting material discovery; however, the trade-off between accuracy and efficiency across different ML models for predicting perovskite properties is not well understood. In this study, we conducted a comprehensive assessment of various ML models for predicting the formation energy (Ef) and bandgap (Eg) of perovskites. We designed a protocol to extract perovskite structures from three databases based on the stoichiometry, octahedral lattice motif, and alignment with established perovskite prototype structures. Benchmarking conventional ML algorithms (CML) against graph neural network (GNN) models across three datasets, we identified the GATGNN model as the top performer, balancing exceptional prediction accuracy and computational efficiency. We further investigated the impact of data size on model performance, emphasizing the need for over 1000 data points for optimal prediction accuracy. Additionally, through SHAP analysis, we provided valuable insights into the interpretation of CML models in predicting Ef and Eg. Our study establishes a standardized benchmark for evaluating various ML models across diverse datasets of perovskite materials, facilitating future applications in materials science, particularly in model selection and the advancement of perovskite materials

Efficacy and Safety of Adjunctive Corticosteroids Therapy for Severe Community-Acquired Pneumonia in Adults: An Updated Systematic Review and Meta-Analysis.

Adjunctive corticosteroids therapy is an attractive option for community-acquired pneumonia (CAP) treatment. However, the effectiveness of adjunctive corticosteroids on mortality of CAP remains inconsistent, especially in severe CAP. We performed a meta-analysis to evaluate the efficacy and safety of adjunctive corticosteroids in severe CAP patients.Three databases of PubMed, EMBASE and Cochrane Library were searched for related studies published in English up to December, 2015. Randomized controlled trials (RCTs) of corticosteroids in hospitalized adults with severe CAP were included. Meta-analysis was performed by a random-effect model with STATA 11.0 software. We estimated the summary risk ratios (RRs) or effect size (ES) with its corresponding 95% confidence interval (95%CI) to assess the outcomes.We included 8 RCTs enrolling 528 severe CAP patients. Adjunctive corticosteroids significantly reduced all-cause mortality (RR = 0.46, 95%CI: 0.28 to 0.77, p = 0.003), risk of adult respiratory distress syndrome (ARDS) (RR = 0.23, 95%CI: 0.07 to 0.80, p = 0.02) and need for mechanical ventilation (RR = 0.50, 95%CI: 0.27 to 0.92, p = 0.026). Adjunctive corticosteroids did not increase frequency of hyperglycemia requiring treatment (RR = 1.03, 95%CI: 0.61 to 1.72, p = 0.91) or gastrointestinal hemorrhage (RR = 0.66, 95%CI: 0.19 to 2.31, p = 0.52). In subgroup analysis by duration of corticosteroids, we found that prolonged corticosteroids therapy significantly reduced all-cause mortality (RR = 0.41, 95%CI: 0.20 to 0.83, p = 0.01) and length of hospital stay (-4.76 days, 95% CI:-8.13 to -1.40, p = 0.006).Results from this meta-analysis suggested that adjunctive corticosteroids therapy was safe and beneficial for severe CAP. In addition, prolonged corticosteroids therapy was more effective. These results should be confirmed by adequately powered studies in the future

Solar Radiation-Associated Adaptive SNP Genetic Differentiation in Wild Emmer Wheat, Triticum dicoccoides.

Whole-genome scans with large number of genetic markers provide the opportunity to investigate local adaptation in natural populations and identify candidate genes under positive selection. In the present study, adaptation genetic differentiation associated with solar radiation was investigated using 695 polymorphic SNP markers in wild emmer wheat originated in a micro-site at Yehudiyya, Israel. The test involved two solar radiation niches: (1) sun, in-between trees; and (2) shade, under tree canopy, separated apart by a distance of 2-4 m. Analysis of molecular variance showed a small (0.53%) but significant portion of overall variation between the sun and shade micro-niches, indicating a non-ignorable genetic differentiation between sun and shade habitats. Fifty SNP markers showed a medium (0.05 ≤ FST ≤ 0.15) or high genetic differentiation (FST > 0.15). A total of 21 outlier loci under positive selection were identified by using four different FST -outlier testing algorithms. The markers and genome locations under positive selection are consistent with the known patterns of selection. These results suggested that genetic differentiation between sun and shade habitats is substantial, radiation-associated, and therefore ecologically determined. Hence, the results of this study reflected effects of natural selection through solar radiation on EST-related SNP genetic diversity, resulting presumably in different adaptive complexes at a micro-scale divergence. The present work highlights the evolutionary theory and application significance of solar radiation-driven natural selection in wheat improvement

Solar Radiation-Associated Adaptive SNP Genetic Differentiation in Wild Emmer Wheat, Triticum dicoccoides

Whole-genome scans with large number of genetic markers provide the opportunity to investigate local adaptation in natural populations and identify candidate genes under positive selection. In the present study, adaptation genetic differentiation associated with solar radiation was investigated using 695 polymorphic SNP markers in wild emmer wheat originated in a micro-site at Yehudiyya, Israel. The test involved two solar radiation niches: (1) sun, in-between trees; and (2) shade, under tree canopy, separated apart by a distance of 2–4 m. Analysis of molecular variance showed a small (0.53%) but significant portion of overall variation between the sun and shade micro-niches, indicating a non-ignorable genetic differentiation between sun and shade habitats. Fifty SNP markers showed a medium (0.05 ≤ F(ST) ≤ 0.15) or high genetic differentiation (F(ST) > 0.15). A total of 21 outlier loci under positive selection were identified by using four different F(ST)-outlier testing algorithms. The markers and genome locations under positive selection are consistent with the known patterns of selection. These results suggested that genetic differentiation between sun and shade habitats is substantial, radiation-associated, and therefore ecologically determined. Hence, the results of this study reflected effects of natural selection through solar radiation on EST-related SNP genetic diversity, resulting presumably in different adaptive complexes at a micro-scale divergence. The present work highlights the evolutionary theory and application significance of solar radiation-driven natural selection in wheat improvement

Identification of genes bordering breakpoints of the pericentric inversions on 2B, 4B and 5A in Bread Wheat (Triticum aestivum L.）

Chromosome translocation is an important driving force in shaping genomes during evolution. Detailed knowledge of chromosome translocations in a given species and its close relatives should increase the efficiency and precision of chromosome engineering in crop improvement. To identify genes flanking the breakpoints of translocations and inversions as a step toward identifying breakpoints in bread wheat, we systematically analysed genes in the Brachypodium genome against wheat survey sequences and bin-mapped ESTs (Expressed Sequence Tags) derived from the hexaploid wheat genotype ‘Chinese Spring’. In addition to those well-known translocations between group 4, 5 and 7 chromosomes, this analysis identified genes flanking the 3 pericentric inversions on chromosomes 2B, 4B and 5A. However, numerous chromosomal rearrangements reported in early studies could not be confirmed. The genes flanking the breakpoints reported in this study are valuable for isolating these breakpoints.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

What Makes a Fantastic Passenger-Car Driver in Urban Contexts?

The accurate evaluation of the quality of driving behavior is crucial for optimizing and implementing autonomous driving technology in practice. However, there is no comprehensive understanding of good driving behaviors currently. In this paper, we sought to understand driving behaviors from the perspectives of both drivers and passengers. We invited 10 expert drivers and 14 novice drivers to complete a 5.7-kilometer urban road driving task. After the experiments, we conducted semi-structured interviews with 24 drivers and 48 of their passengers (two passengers per driver). Through the analysis of interview data, we found passengers' assessing logic of driving behaviors, divers' considerations and efforts to achieve good driving, and gaps between these perspectives. Our research provided insights into a systematic evaluation of autonomous driving and the design implications for future autonomous vehicles.Comment: Part of the content of the paper will be modified. One of the authors has recommended its withdrawal due to personal reason