Direct mapping of bending and torsional dynamics in individual nanostructures

Investigating coherent acoustic vibrations in nanostructured materials provides fundamental insights into optomechanical responses and microscopic energy flow. Extensive measurements of vibrational dynamics have been performed for a wide variety of nanoparticles and nanoparticle assemblies. However, virtually all of them show that only the dilation modes are launched after laser excitations, and the acoustic bending and torsional motions, which are commonly observed in photoexcited chemical bonds, are absent. Unambiguous identification and refined characterization of these “missing” modes have been a long-standing issue. In this report, we investigated the acoustic vibrational dynamics of individual Au nanoprisms on free-standing graphene substrates using an ultrafast high-sensitivity dark-field imaging approach in four-dimensional transmission electron microscopy. Following optical excitations, we observed low-frequency multiple-mode oscillations and higher superposition amplitudes at nanoprism corners and edges on the subnanoparticle level. In combination with finite-element simulations, we determined that these vibrational modes correspond to out-of-plane bending and torsional motions, superimposed by an overall tilting effect of the nanoprisms. The launch and relaxation processes of these modes are highly pertinent to substrate effects and nanoparticle geometries. These findings contribute to the fundamental understanding about acoustic dynamics of individual nanostructures and their interaction with substrates

Spatiotemporal Variations of Precipitation in the Southern Part of the Heihe River Basin (China), 1984–2014

Local precipitation variations in the context of global warming are a hot topic in the climate change research community. Using daily precipitation data spanning from 1984 to 2014 from 25 meteorological stations, the spatiotemporal variations of precipitation were analyzed for the southern part of Heihe River Basin (HRB), which is the second-largest inland river basin in Northwest China. Linear trend analysis, empirical orthogonal function (EOF) analysis, the Mann–Kendall test, and the moving t-test were employed in the study. Results showed that the regional annual precipitation exhibited an increasing trend with a slope of 13.1 mm per decade from 1984 to 2014. The increasing trend was detected at 21 sites and the first EOF illustrating the regional increasing trend explained 51.8% of the total variance. The increasing trend of annual precipitation was mainly due to an increase in autumn precipitation, while summer precipitation exhibited a weak declining trend and spring–winter precipitation remained unchanged. Moreover, the increasing precipitation trend was mainly caused by an abrupt increase around 1997, when the global warming hiatus occurred. Through 1997, the atmospheric circulation and physical structure, such as vertical upward motion, vapor transmission, and its convergence changed to be more favorable for precipitation in autumn, but unfavorable for precipitation in summer in the HRB

Acquisition and Control Systems of Distributed Data Based on STM32,

International audienc

Timed-SAS: Modeling and Analyzing the Time Behaviors of Self-Adaptive Software under Uncertainty

Self-adaptive software (SAS) is gaining in popularity as it can handle dynamic changes in the operational context or in itself. Time behaviors are of vital importance for SAS systems, as the self-adaptation loops bring in additional overhead time. However, early modeling and quantitative analysis of time behaviors for the SAS systems is challenging, especially under uncertainty environments. To tackle this problem, this paper proposed an approach called Timed-SAS to define, describe, analyze, and optimize the time behaviors within the SAS systems. Concretely, Timed-SAS: (1) provides a systematic definition on the deterministic time constraints, the uncertainty delay time constraints, and the time-based evaluation metrics for the SAS systems; (2) creates a set of formal modeling templates for the self-adaptation processes, the time behaviors and the uncertainty environment to consolidate design knowledge for reuse; and (3) provides a set of statistical model checking-based quantitative analysis templates to analyze and verify the self-adaptation properties and the time properties under uncertainty. To validate its effectiveness, we presented an example application and a subject-based experiment. The results demonstrated that the Timed-SAS approach can effectively reduce modeling and verification difficulties of the time behaviors, and can help to optimize the self-adaptation logic

Graphene therapy-related lncRNAs as prognostic and immune microenvironmental biomarkers in hepatocellular carcinoma

Background: Graphene materials have the capacity to influence the tumor microenvironment and intracellular signaling responsiveness. However, the process of graphene-assisted liver cancer treatment still lacks specific biomarkers for assessing its efficacy. Methods: We identified graphene therapy-related lncRNAs (GTLncRNAs) through gene analysis and correlation tests. Multivariate COX and LASSO regression analyses yielded significant lncRNAs for a risk score model. We evaluated clinicopathological factors and tumor microenvironment using ssGSEA. We scrutinized the pathways of immune function, the evasion of tumor immunity, and the potential for immunotherapy. GTLncRNAs with differential expression were subjected to GO/KEGG analysis, and prospective chemotherapy drugs were discerned utilizing the pRRophetic algorithm. The prognostic model was authenticated through the examination of the Imvigor210 cohort, and an analysis of mRNA stemness was executed. Results: The researchers constructed a prognostic model based on 22 graphene therapy-related lncRNAs. Protective lncRNAs (AC010280.2, AL365361.1, and LINC01549) and negative lncRNAs (AC026412.3, AL031985.3, ELFN1-AS1, SNHG4, and EB2-AS1) were identified. Higher risk scores correlated with shorter survival. Low-risk immune pathways included Type_II_IFN_Reponse and cytolytic_activity. Subgroups differed significantly in TMB, TIDE, MDSC, exclusion, and dysfunction. Low TMB values correlated with longer survival. The high-risk subgroup showed increased sensitivity to screened compounds, and mRNAsi was higher in cancer tissue. Conclusions: Our GTLncRNAs-based model accurately predicted survival of HCC patients and underscored the influence of graphene therapy-related genes on the tumor microenvironment. Potential treatment compounds were identified, and the mRNAsi index demonstrated prognostic value

Timed-SAS: Modeling and Analyzing the Time Behaviors of Self-Adaptive Software under Uncertainty

Self-adaptive software (SAS) is gaining in popularity as it can handle dynamic changes in the operational context or in itself. Time behaviors are of vital importance for SAS systems, as the self-adaptation loops bring in additional overhead time. However, early modeling and quantitative analysis of time behaviors for the SAS systems is challenging, especially under uncertainty environments. To tackle this problem, this paper proposed an approach called Timed-SAS to define, describe, analyze, and optimize the time behaviors within the SAS systems. Concretely, Timed-SAS: (1) provides a systematic definition on the deterministic time constraints, the uncertainty delay time constraints, and the time-based evaluation metrics for the SAS systems; (2) creates a set of formal modeling templates for the self-adaptation processes, the time behaviors and the uncertainty environment to consolidate design knowledge for reuse; and (3) provides a set of statistical model checking-based quantitative analysis templates to analyze and verify the self-adaptation properties and the time properties under uncertainty. To validate its effectiveness, we presented an example application and a subject-based experiment. The results demonstrated that the Timed-SAS approach can effectively reduce modeling and verification difficulties of the time behaviors, and can help to optimize the self-adaptation logic

Phase Separation Prior to Alloying Observed in Vacuum Heating of Hybrid Au/Cu₂O Core–Shell Nanoparticles

The coexistence of decomposition, phase segregation, and alloying behaviors of Au@Cu₂O core–shell nanoparticles were found through in situ heating transmission electron microscopy imaging and spectral-analysis techniques. Thermally induced compositional variations (from Cu₂O to Cu) were observed to be present in the nanoparticle shells, which was followed by a spontaneous occurrence of Au–Cu alloying. The higher-Cu loading (1:10 Au/Cu) sample displays a clear Cu/Cu₂O phase segregation driven by the internal stresses resulting from lattice mismatch. Cu extrusions also occur in this sample after storage in ethanol for 10 days. These in situ observations/findings may help enhance a fundamental understanding of remarkable experimental aspects arising in catalytic processes and other applications as well as provide a valuable reference for testing/refining potential models of hybrid nanoparticles in theoretical calculations

Integrated metabolome and transcriptome analysis of differences in quality of ripe Lycium barbarum L. fruits harvested at different periods

Abstract Background Wolfberry is well-known for its high nutritional value and medicinal benefits. Due to the continuous ripening nature of Goji berries and the fact that they can be commercially harvested within a few weeks, their phytochemical composition may change during the harvesting process at different periods. Result The involved molecular mechanisms of difference in fruit quality of ripe Lycium barbarum L. harvested at four different periods were investigated by transcriptomic and metabolomics analyses for the first time. According to the results we obtained, it was found that the appearance quality of L. barbarum fruits picked at the beginning of the harvesting season was superior, while the accumulation of sugar substances in L. barbarum fruits picked at the end of the harvesting season was better. At the same time the vitamin C and carotenoids content of wolfberry fruits picked during the summer harvesting season were richer. Ascorbic acid, succinic acid, glutamic acid, and phenolic acids have significant changes in transcription and metabolism levels. Through the network metabolic map, we found that ascorbic acid, glutamic acid, glutamine and related enzyme genes were differentially accumulated and expressed in wolfberry fruits at different harvesting periods. Nevertheless, these metabolites played important roles in the ascorbate–glutathione recycling system. Ascorbic acid, phenolic substances and the ascorbate–glutathione recycling system have antioxidant effects, which makes the L. barbarum fruits harvested in the summer more in line with market demand and health care concepts. Conclusion This study laid the foundation for understanding the molecular regulatory mechanisms of quality differences of ripe wolfberry fruits harvested at different periods, and provides a theoretical basis for enhancing the quality of L. barbarum fruits