267 research outputs found

    BBR-induced Stark shifts and level broadening in helium atom

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    The precise calculations of blackbody radiation (BBR)-induced Stark shifts and depopulation rates for low-lying states of helium atom with the use of variational approach are presented. An effect of the BBR-induced induced Stark-mixing of energy levels is considered. It is shown that this effect leads to a significant reduction of lifetimes of helium excited states. As a consequence the influence of Stark-mixing effect on the decay rates of metastable states in helium is discussed in context of formation processes of the cosmic microwave background

    The androgen receptor plays different roles in macrophage-induced proliferation in prostate stromal cells between transitional and peripheral zones of benign prostatic hypertrophy

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    Macrophages play a critical role in the process of excessive stromal proliferation of benign prostatic hyperplasia (BPH). In our previous study, we used a BPH mouse model to elucidate a potential mechanism whereby macrophage infiltration promotes stromal cell proliferation in the prostate via the androgen receptor (AR)/inflammatory cytokine CCL3-dependent pathway. In our present study, we used the co-culture system of human macrophages and various prostatic zone stromal cells to further demonstrate that infiltrating macrophages promote prostatic stromal cell proliferation through stromal AR-dependent pathways, and we show that the stroma of TZ and PZ respond to macrophages differently because of differences in stromal AR signaling; this could possibly be one of the key pathways for stromal expansion during BPH development and progression. We hypothesize that AR and different downstream inflammatory mediators between TZ and PZ could serve as potential targets for the future design of therapeutic agents for BPH and our results provide significant insights into the search for targeted therapeutic approaches to battle BPH

    Dynamic Circular Network-Based Federated Dual-View Learning for Multivariate Time Series Anomaly Detection

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    Multivariate time-series data exhibit intricate correlations in both temporal and spatial dimensions. However, existing network architectures often overlook dependencies in the spatial dimension and struggle to strike a balance between long-term and short-term patterns when extracting features from the data. Furthermore, industries within the business community are hesitant to share their raw data, which hinders anomaly prediction accuracy and detection performance. To address these challenges, the authors propose a dynamic circular network-based federated dual-view learning approach. Experimental results from four open-source datasets demonstrate that the method outperforms existing methods in terms of accuracy, recall, and F1_score for anomaly detection

    Multi-decadal trends in global terrestrial evapotranspiration and its components

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    Evapotranspiration (ET) is the process by which liquid water becomes water vapor and energetically this accounts for much of incoming solar radiation. If this ET did not occur temperatures would be higher, so understanding ET trends is crucial to predict future temperatures. Recent studies have reported prolonged declines in ET in recent decades, although these declines may relate to climate variability. Here, we used a well-validated diagnostic model to estimate daily ET during 1981–2012, and its three components: transpiration from vegetation (Et), direct evaporation from the soil (Es) and vaporization of intercepted rainfall from vegetation (Ei). During this period, ET over land has increased significantly (p < 0.01), caused by increases in Et and Ei, which are partially counteracted by Es decreasing. These contrasting trends are primarily driven by increases in vegetation leaf area index, dominated by greening. The overall increase in Et over land is about twofold of the decrease in Es. These opposing trends are not simulated by most Coupled Model Intercomparison Project phase 5 (CMIP5) models, and highlight the importance of realistically representing vegetation changes in earth system models for predicting future changes in the energy and water cycle

    Monolayer Excitonic Laser

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    Recently, two-dimensional (2D) materials have opened a new paradigm for fundamental physics explorations and device applications. Unlike gapless graphene, monolayer transition metal dichalcogenide (TMDC) has new optical functionalities for next generation ultra-compact electronic and opto-electronic devices. When TMDC crystals are thinned down to monolayers, they undergo an indirect to direct bandgap transition, making it an outstanding 2D semiconductor. Unique electron valley degree of freedom, strong light matter interactions and excitonic effects were observed. Enhancement of spontaneous emission has been reported on TMDC monolayers integrated with photonic crystal and distributed Bragg reflector microcavities. However, the coherent light emission from 2D monolayer TMDC has not been demonstrated, mainly due to that an atomic membrane has limited material gain volume and is lack of optical mode confinement. Here, we report the first realization of 2D excitonic laser by embedding monolayer tungsten disulfide (WS2) in a microdisk resonator. Using a whispering gallery mode (WGM) resonator with a high quality factor and optical confinement, we observed bright excitonic lasing in visible wavelength. The Si3N4/WS2/HSQ sandwich configuration provides a strong feedback and mode overlap with monolayer gain. This demonstration of 2D excitonic laser marks a major step towards 2D on-chip optoelectronics for high performance optical communication and computing applications.Comment: 15 pages, 4 figure

    A mendelian randomization study investigates the causal relationship between immune cell phenotypes and cerebral aneurysm

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    Background: Cerebral aneurysms (CAs) are a significant cerebrovascular ailment with a multifaceted etiology influenced by various factors including heredity and environment. This study aimed to explore the possible link between different types of immune cells and the occurrence of CAs.Methods: We analyzed the connection between 731 immune cell signatures and the risk of CAs by using publicly available genetic data. The analysis included four immune features, specifically median brightness levels (MBL), proportionate cell (PC), definite cell (DC), and morphological attributes (MA). Mendelian randomization (MR) analysis was conducted using the instrumental variables (IVs) derived from the genetic variation linked to CAs.Results: After multiple test adjustment based on the FDR method, the inverse variance weighted (IVW) method revealed that 3 immune cell phenotypes were linked to the risk of CAs. These included CD45 on HLA DR+NK (odds ratio (OR), 1.116; 95% confidence interval (CI), 1.001–1.244; p = 0.0489), CX3CR1 on CD14− CD16− (OR, 0.973; 95% CI, 0.948–0.999; p = 0.0447). An immune cell phenotype CD16− CD56 on NK was found to have a significant association with the risk of CAs in reverse MR study (OR, 0.950; 95% CI, 0.911–0.990; p = 0.0156).Conclusion: Our investigation has yielded findings that support a substantial genetic link between immune cells and CAs, thereby suggesting possible implications for future clinical interventions
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