The ensemble photometric variability of over 10510^5 quasars in the Dark Energy Camera Legacy Survey and the Sloan Digital Sky Survey

We present the ensemble variability analysis results of quasars using the Dark Energy Camera Legacy Survey (DECaLS) and the Sloan Digital Sky Survey (SDSS) quasar catalogs. Our dataset includes 119,305 quasars with redshifts up to 4.89. Combining the two datasets provides a 15-year baseline and permits analysis of the long timescale variability. Adopting a power-law form for the variability structure function, $V=A(t/1yr)^{\gamma}$, we use the multi-dimensional parametric fitting to explore the relationships between the quasar variability amplitude and a wide variety of quasar properties, including redshift (positive), bolometric luminosity (negative), rest-frame wavelength (negative), and black hole mass (uncertain). We also find that $\gamma$ can be also expressed as a function of redshift (negative), bolometric luminosity (positive), rest-frame wavelength (positive), and black hole mass (positive). Tests of the fitting significance with the bootstrap method show that, even with such a large quasar sample, some correlations are marginally significant. The typical value of $\gamma$ for the entire dataset is $\gtrsim 0.25$, consistent with the results in previous studies on both the quasar ensemble variability and the structure function. A significantly negative correlation between the variability amplitude and the Eddington ratio is found, which may be explained as an effect of accretion disk instability.Comment: 13 pages, 8 figures, 4 tables, accepted for publication in Ap

Research on the Development of Traditional Handicraft Industry in Heqing County Based on the SWOT-PESTEL Model

The traditional handicraft industry in Heqing County embodies rich ethnic culture and history, particularly the art of silver jewelry craftsmanship, which has been recognized as a national-level intangible cultural heritage, holding significant cultural and economic value. Nevertheless, the industry still faces challenges brought about by modernization and globalization, such as the disruption of skill inheritance, fluctuating market demand, and intensified market competition. This study employs the SWOT-PESTEL model to analyze the strengths of Heqing County’s handicraft industry in terms of policy support, cultural resources, and geographical advantages, while also identifying weaknesses including insufficient technological innovation, low industrial concentration, and a shortage of talent. To promote sustainable development, it is recommended to enhance policy implementation, cultivate leading enterprises, drive technological innovation, deepen the integration of cultural tourism, strengthen talent development, and raise environmental awareness. These strategies aim to provide theoretical support and practical guidance for the development of the traditional handicraft industry not only in Heqing County but also in other regions, thereby promoting the inheritance and innovation of Local traditional handicraft culture

High-resolution seismic event detection using local similarity for Large-N arrays

We develop a novel method for seismic event detection that can be applied to large-N arrays. The method is based on a new detection function named local similarity, which quantifies the signal consistency between the examined station and its nearest neighbors. Using the 5200-station Long Beach nodal array, we demonstrate that stacked local similarity functions can be used to detect seismic events with amplitudes near or below noise levels. We apply the method to one-week continuous data around the 03/11/2011 Mw 9.1 Tohoku-Oki earthquake, to detect local and distant events. In the 5–10 Hz range, we detect various events of natural and anthropogenic origins, but without a clear increase in local seismicity during and following the surface waves of the Tohoku-Oki mainshock. In the 1-Hz low-pass-filtered range, we detect numerous events, likely representing aftershocks from the Tohoku-Oki mainshock region. This high-resolution detection technique can be applied to both ultra-dense and regular array recordings for monitoring ultra-weak micro-seismicity and detecting unusual seismic events in noisy environments

Deep learning for seismic phase detection and picking in the aftershock zone of 2008 M_W 7.9 Wenchuan Earthquake

The increasing volume of seismic data from long-term continuous monitoring motivates the development of algorithms based on convolutional neural network (CNN) for faster and more reliable phase detection and picking. However, many less studied regions lack a significant amount of labeled events needed for traditional CNN approaches. In this paper, we present a CNN-based Phase-Identification Classifier (CPIC) designed for phase detection and picking on small to medium sized training datasets. When trained on 30,146 labeled phases and applied to one-month of continuous recordings during the aftershock sequences of the 2008 M_W 7.9 Wenchuan Earthquake in Sichuan, China, CPIC detects 97.5% of the manually picked phases in the standard catalog and predicts their arrival times with a five-times improvement over the ObsPy AR picker. In addition, unlike other CNN-based approaches that require millions of training samples, when the off-line training set size of CPIC is reduced to only a few thousand training samples the accuracy stays above 95%. The deployment of CPIC takes less than 12 h to pick arrivals in 31-day recordings on 14 stations. In addition to the catalog phases manually picked by analysts, CPIC finds more phases for existing events and new events missed in the catalog. Among those additional detections, some are confirmed by a matched filter method while others require further investigation. Finally, when tested on a small dataset from a different region (Oklahoma, US), CPIC achieves 97% accuracy after fine tuning only the fully connected layer of the model. This result suggests that the CPIC developed in this study can be used to identify and pick P/S arrivals in other regions with no or minimum labeled phases

Source time function clustering reveals patterns in earthquake dynamics

We cluster a global data base of 3529 M > 5.5 earthquakes in 1995-2018 based on a dynamic time warping dissimilarity of their source time functions (STFs). The clustering exhibits different degrees of STF shape complexity and suggests an association between STF complexity and earthquake source parameters. Thrust events are in large proportion with simple STF shapes and at all depths. In contrast, earthquakes with complex STF shapes tend to be located at shallow depth in complicated tectonic regions with preferentially strike slip mechanism and relatively longer duration. With 2D dynamic modeling of earthquake ruptures on heterogeneous pre-stress and linear slip-weakening friction, we find a systematic variation of the simulated STF complexity with frictional properties. Comparison between the observed and synthetic clustering distributions provides useful constraints on elements of the frictional properties. In particular, the characteristic slip-weakening distance could be constrained to be generally short (< 0.1 m) and depth dependent

Down-regulation of NRIP1 alleviates pyroptosis in human lens epithelial cells exposed to hydrogen peroxide by inhibiting NF-κB activation

Purpose: To investigate the role of nuclear receptor-interacting protein 1 (NRIP1) in oxidative stressinduced apoptosis and pyroptosis in cataract disease.Methods: Human lens epithelial cells (HLE-B3 cells) were exposed to hydrogen peroxide (H2O2). NRIP1 expression in hydrogen peroxide (H2O2)-treated HLE-B3 cells was determined by western blotting and quantitative reverse transcription polymerase chain reaction (qRT-PCR). CCK8 and EdU staining were used to assess cell viability. Flow cytometry and western blotting were used to assess pyroptosis.Results: NRIP1 was significantly up-regulated in HLE-B3 cells post-H2O2 incubation (p &lt; 0.01). Hydrogen peroxide incubation reduced cell viability and proliferation of HLE-B3 cells, while NRIP1 knockdown enhanced cell viability and proliferation. NRIP1 silencing attenuated the H2O2-induced increase in NLRP3, N-terminal domain of gasdermin D, caspase-1, interleukin (IL)-1β, and IL-18 in HLEB3 cells, but suppressed the pyroptosis of H2O2-treated HLE-B3 cells. Hydrogen peroxide incubation down-regulated protein expression of cytoplasmic NF-κB and up-regulated nuclear NF-κB, while the expression of cytoplasmic NF-κB was increased and nuclear NF-κB was decreased in HLE-B3 cells by HLE-B3 interference.Conclusion: NRIP1 down-regulation represses apoptosis and pyroptosis of H2O2-treated human lens epithelial cells by inhibiting NF-κB activation, thus, providing a potential strategy to treat cataract disease