A 4,000 Year Pollen Record of Vegetation Changes, Sea Level Rise, and Hurricane Disturbance in Atchafalaya March of Southern Louisiana

Sediment cores from the Atchafalaya Marsh in southern Louisiana were intensively studied by means of pollen and loss-on-ignition analyses to reconstruct the history of late-Holocene environmental changes and hurricane strikes in the area. The data indicate that the coring site was occupied by a fresh marsh about 4000 years ago. Afterwards, the fresh marsh was replaced by a brackish marsh in the following 400 years. The marsh became a salt marsh in response to sea level rise beginning 3250 yr BP. During 2800-1200 yr BP, the study site became an estuarine environment inundated by sea water as a result of sea level rise. With the development of the delta plain in the study area, brackish marsh resumed and existed for about 500 years from ca. 1200-750 BP. During the last 750 years, the coring site has been occupied by a salt marsh indicating a consistent sea level rise. The vegetation history reveals two cycles of relative sea level change in the Atchafalaya Marsh area. The Atchafalaya marsh was struck by intense hurricanes at least ten times in the past 1200 years and three times during 3100-2800 yr BP as indicated by both pollen and sediment stratigraphies. Two intriguing phenomena are found in the proxy record of hurricane strikes in the Atchafalaya Marsh. First, fewer sand layers occur between the 15th and 19th century. This coincides with the Little Ice Age. This may reflect fewer intense hurricane strikes due to a cooler ocean surface. Alternatively, the coring site may have been farther away from the coastline so that only the most intense hurricane strikes were recorded. Second, no hurricane strikes were recorded during 3100-4000 yr BP. These results are consistent with the hypothesis that the Bermuda High was situated in a more northeasterly position during the mid-Holocene

Strategies and mechanisms for enhancing receptor-specific TRAIL-induced apoptosis

Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is a promising candidate for cancer treatment due to its tumor specificity. TRAIL binds with death receptor (DR) 4 or 5 to initiate apoptotic signal transduction. In this thesis, we first introduced the protein engineering strategies of TNF ligands to target specific receptors and we reviewed the changes in the biological activity of some key ligands. In the experimental part, we worked with DR4-specific TRAIL variant 4C7 and DR5-specific TRAIL variant DHER to study combination treatments to overcome resistance. Artemisinin is an approved anti-malarial drug extracted from Artemisia annua, which has also been studied as an anti-tumor drug for decades. We showed that artemisinin-type drugs stimulate DR5-specific TRAIL-induced apoptosis by regulating wildtype P53 in colon cancer cells. Then, we investigated the possibility of performing this combination treatment in P53 mutated triple-negative breast cancer (TNBC) cells. The effectiveness of dihydroartemisinin (DHA) was improved by forming adducts with transferrin (TF). These DHA-TF adducts induce apoptosis and ferroptosis in TNBC cells. Meanwhile, they enhance TRAIL-induced apoptosis mainly through DR5 upregulation in a P53-independent and ROS-dependent manner. Based on our findings and literature research, we summarized the effects of artemisinin-type drugs on regulated cell death pathways, the combination strategies with biologics, and the nanocarriers for artemisinin delivery. Finally, the expression pattern of DR4 and DR5 and the influence of ionizing radiation on receptor-specific TRAIL in 2D and 3D spheroids were explored. The whole thesis provided new strategies to enhance receptor-specific TRAIL-induced apoptosis for cancer treatment

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

We introduce an extremely computation-efficient CNN architecture named ShuffleNet, which is designed specially for mobile devices with very limited computing power (e.g., 10-150 MFLOPs). The new architecture utilizes two new operations, pointwise group convolution and channel shuffle, to greatly reduce computation cost while maintaining accuracy. Experiments on ImageNet classification and MS COCO object detection demonstrate the superior performance of ShuffleNet over other structures, e.g. lower top-1 error (absolute 7.8%) than recent MobileNet on ImageNet classification task, under the computation budget of 40 MFLOPs. On an ARM-based mobile device, ShuffleNet achieves ~13x actual speedup over AlexNet while maintaining comparable accuracy

EAST: An Efficient and Accurate Scene Text Detector

Previous approaches for scene text detection have already achieved promising performances across various benchmarks. However, they usually fall short when dealing with challenging scenarios, even when equipped with deep neural network models, because the overall performance is determined by the interplay of multiple stages and components in the pipelines. In this work, we propose a simple yet powerful pipeline that yields fast and accurate text detection in natural scenes. The pipeline directly predicts words or text lines of arbitrary orientations and quadrilateral shapes in full images, eliminating unnecessary intermediate steps (e.g., candidate aggregation and word partitioning), with a single neural network. The simplicity of our pipeline allows concentrating efforts on designing loss functions and neural network architecture. Experiments on standard datasets including ICDAR 2015, COCO-Text and MSRA-TD500 demonstrate that the proposed algorithm significantly outperforms state-of-the-art methods in terms of both accuracy and efficiency. On the ICDAR 2015 dataset, the proposed algorithm achieves an F-score of 0.7820 at 13.2fps at 720p resolution.Comment: Accepted to CVPR 2017, fix equation (3

Comparison of ant community composition among three ur-ban habitats: a case study in Nanchong, Sichuan

As an important human-caused disturbance factor, urbanization has significantly changed the structure of natural habitats and influenced the composition of animal communities. The characterisitions of abundant population amount, high spcies diversity, and easy to be collected of ants make these species become excellent models for studying the effects of land-use types on the composition of animal communities in urban areas. In May 2018, ants were sampled from 3 land-use types (‘garden and greenland’, ‘dry farm’ and ‘woodland’) using pitfall traps in an urban area of Nanchong city, Sichuan province. A total of 1 847 ant individuals were collected. The proportion of Tetramorium tsushimae was the highest in ‘garden and greenland’ (73.80%), and significantly higher than that of Monomorium chinense in ‘dry farm’ (25.48%) and Pheidole nodus in ‘woodland’ (28.79%). There was no significant difference in the number of indiviuduals and species richness among the 3 habitats, but the Simpson diversity index and Pielou evenness index of ant community in the habitat of‘garden and greenland’were significantly lower than those in the habitats of‘dry farm’and‘woodland’; the composition of ant community in‘woodland’was moderately different from that in‘garden and greenland’(q = 0.444)and‘dry farm’(q = 0.500), and the community composition in‘garden and greenland’and‘dry farm’(q = 0.647)was moderately similar. Therefore, the compositions of ant communities are varied in different land-use types in urban areas, and the habitat of ‘garden and greenland’ is more likely to facilitate the formation of dominant species than ‘dry farm’ and ‘woodland’