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"Yang, Xianhui"
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Woman from Shanghai : tales of survival from a Chinese labor camp
\"Between 1957 and 1960, nearly three thousand Chinese citizens were labeled \"Rightists\" by the Communist Part and banished to Jianiangou in China's northwestern desert region of Gansu to undergo \"reeducation\" through hard labor. These exiles men and women were subjected to horrific conditions, and by 1961 the camp was closed because of the stench of death: of the rougly three thousand inmates, only about five hundred survived.\" \"In 1997, Xianhui Yang traveled to Gansu and spent the next five years interviewing more than one hundred survivors of the camp. In Woman from Shanghai he presents thirteen of their stories, which have been crafted into fiction in order to evade Chinese censorship but which lose none of their fierce power. These are tales of ordinary people facing extraordinary tribulations, time and again securing their humanity against those who were intent on taking it away.\"--Jkt. of 2009 ed.
Book
Research on the Depth Image Reconstruction Algorithm Using the Two-Dimensional Kaniadakis Entropy Threshold
The photon-counting light laser detection and ranging (LiDAR), especially the Geiger mode avalanche photon diode (Gm-APD) LiDAR, can obtain three-dimensional images of the scene, with the characteristics of single-photon sensitivity, but the background noise limits the imaging quality of the laser radar. In order to solve this problem, a depth image estimation method based on a two-dimensional (2D) Kaniadakis entropy thresholding method is proposed which transforms a weak signal extraction problem into a denoising problem for point cloud data. The characteristics of signal peak aggregation in the data and the spatio-temporal correlation features between target image elements in the point cloud-intensity data are exploited. Through adequate simulations and outdoor target-imaging experiments under different signal-to-background ratios (SBRs), the effectiveness of the method under low signal-to-background ratio conditions is demonstrated. When the SBR is 0.025, the proposed method reaches a target recovery rate of 91.7%, which is better than the existing typical methods, such as the Peak-picking method, Cross-Correlation method, and the sparse Poisson intensity reconstruction algorithm (SPIRAL), which achieve a target recovery rate of 15.7%, 7.0%, and 18.4%, respectively. Additionally, comparing with the SPIRAL, the reconstruction recovery ratio is improved by 73.3%. The proposed method greatly improves the integrity of the target under high-background-noise environments and finally provides a basis for feature extraction and target recognition.
Journal Article
A Multi-Scale Spatio-Temporal Fusion Network for Occluded Small Object Detection in Geiger-Mode Avalanche Photodiode LiDAR Systems
The Geiger-Mode Avalanche Photodiode (Gm-APD) LiDAR system demonstrates high-precision detection capabilities over long distances. However, the detection of occluded small objects at long distances poses significant challenges, limiting its practical application. To address this issue, we propose a multi-scale spatio-temporal object detection network (MSTOD-Net), designed to associate object information across different spatio-temporal scales for the effective detection of occluded small objects. Specifically, in the encoding stage, a dual-channel feature fusion framework is employed to process range and intensity images from consecutive time frames, facilitating the detection of occluded objects. Considering the significant differences between range and intensity images, a multi-scale context-aware (MSCA) module and a feature fusion (FF) module are incorporated to enable efficient cross-scale feature interaction and enhance small object detection. Additionally, an edge perception (EDGP) module is integrated into the network’s shallow layers to refine the edge details and enhance the information in unoccluded regions. In the decoding stage, feature maps from the encoder are upsampled and combined with multi-level fused features, and four prediction heads are employed to decode the object categories, confidence, widths and heights, and displacement offsets. The experimental results demonstrate that the MSTOD-Net achieves mAP50 and mAR50 scores of 96.4% and 96.9%, respectively, outperforming the state-of-the-art methods.
Journal Article
Assessment of Heavy Metal Pollution in Mangrove Sediments of Liusha Bay, Leizhou Peninsula, China
Heavy metal pollution threatens coastal ecosystems. Mangrove sediments, as transitional zones, are prone to contaminant accumulation. This study investigated eight heavy metals (Cu, Pb, Ni, As, Cr, Zn, Cd, Co) in Liusha Bay (Leizhou Peninsula, China). Field sampling, lab analysis, and multivariate statistics were used to assess pollution sources and ecological risks. The results show Al and Fe dominate sediment composition, with elevated P, Mn, and Sr. Arsenic (As) exhibiting the highest pollution severity (50% sites moderately contaminated by Igeo). Enrichment factors (EF) indicate anthropogenic contributions to As, Cu, Ni, and Co, while Cd and Pb originate mainly from natural sources. Ecological risk assessments highlight moderate risks for As and Cd at some sites. Source analysis identifies three dominant pathways: (1) lithogenic inputs (volcanic rock weathering) contributing Fe, Zn, Cr, and Ni; (2) biogenic materials (calcium carbonate-secreting organisms) influencing Cu, Mn, and Cd; and (3) anthropogenic activities (aquaculture, maritime traffic) linked to Cu and Pb. This study emphasizes localized monitoring of As and Cd in mangroves and calls for the integrated management of natural and anthropogenic drivers to mitigate pollution risks.
Journal Article
Simiao Qingwen Baidu decoction inhibits Epstein-Barr virus-induced B lymphoproliferative disease and lytic viral replication
Simiao Qingwen Baidu decoction (SQBD), a traditional Chinese medicine prescription, can ameliorate Epstein-Barr virus (EBV) induced disease. However, its mechanism still remains unknown.
To detect the mechanism of SQBD in EBV-induced B lymphoproliferative disease in vitro.
Sprague-Dawley (SD) rats (n = 20) were given SQBD (10 mL/kg) by gavage once a day for 7 d. SQBD-containing serum was obtained from abdominal aortic blood of rats, and diluted with medium to obtain 5%, 10% or 20%-medicated serum. SD rats (n = 10) were given normal saline, and normal serum was collected as a control. EBV-transformed B cells (CGM1) were cultured in medium containing 5%, 10% or 20%-medicated serum. CGM1 cells were treated with normal serum as a control. Cell viability and apoptosis were examined. The expression and activity of proteins were assessed.
We found that IC
50
(83 ± 26.07%, 24 h; 69.88 ± 4.69%, 48 h) of 10% medicated serum was higher than that of 5% (25.47 ± 6.98%, 24 h; 21.62 ± 7.30%, 48 h) and 20%-medicated serum (51 ± 7.25%, 24 h; 56.03 ± 2.56%, 48 h). Moreover, SQBD promoted apoptosis of CGM1 cells by regulating EBV latency proteins expression. SQBD inhibited EBV-induced lytic viral replication.
Our data confirmed that SQBD inhibits EBV-induced B lymphoproliferative disease and lytic viral replication. This work provides a theoretical basis for the mechanism of SQBD in EBV-induced B lymphoproliferative disease, and SQBD may be an effectively therapeutic drug for EBV-induced B lymphoproliferative disease.
Journal Article
CLAMP: predicting specific protein-mediated chromatin loops in diverse species with a chromatin accessibility language model
Emerging DNA language models provide powerful tools to address the challenge of accurately predicting chromatin loops, fundamental structures governing 3D genome organization and gene regulation. Here we present CLAMP, which utilizes a deep language model pre-trained on broad cross-species chromatin accessibility data. CLAMP achieves superior performance compared to existing methods in predicting specific protein-mediated loops across 10 species, 18 proteins, and 24 cell types. CLAMP incorporates a novel CoVE explainer that reveals context-dependent genomic feature contributions, providing insights into the features driving predictions. CLAMP predictions effectively identify functionally significant chromatin loops and associated biological pathways.
Journal Article
Amorphous CoMoSx/N-Doped Carbon Hybrid with 3D Networks as Electrocatalysts for Hydrogen Evolution
Catalytic materials without using precious metallic elements for electrocatalytic water splitting are a crucial demand to the renewable energy production. Cobalt molybdenum sulfide (CoMoS
x
) is one of the promising candidates for such purpose. Yet, the sparse catalytic active sites and poor electrical conductivity limit its catalytic performance. Here, we presented an efficient strategy to synthesize amorphous cobalt molybdenum supported on tree-dimensional network N-doped carbon nanofibers (CoMoS
x
/NCNFs) with the enlarged surface area. The obtained catalysts were characterized by scanning electron microscope (SEM), Transmission electron microscopy (TEM), powder X-ray diffraction (XRD), X-ray photoelectron spectrometer (XPS) and energy-dispersive X-ray spectroscopy (EDS) methods, and the catalytic activity was evaluated by electrochemical technique. In contrast to large aggregate CoMoS
x
particles grown on carbon paper electrode without NCNFs, CoMoS
x
/NCNFs/CP hybrid materials possess porous structure with an abundance of exposed active sites stacked onto NCNF surface. Benefiting from the synergistic effect between the amorphous CoMoS
x
and the underlying NCNF network, CoMoS
x
/NCNFs hybrid exhibits an excellent activity for hydrogen evolution reaction (HER) with a low onset overpotential of 117 mV, a Tafel slope of 75 mV/decade, and good stability.
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