Circulator based on spoof surface plasmon polaritons

Circulators based on spoof surface plasmon polaritons are designed and analyzed. In the letter, we use blade structure to realize the propagation of SSPPs wave and a matching transition is used to feed energy from coplanar waveguide to the SSPPs. And the circulator shows good nonreciprocal transmission characteristics. The simulation results indicate that in the frequency band from 5 to 6.6 GHz, the isolation degree and return loss basically reaches 15dB and the insertion loss is less than 0.5dB. Moreover, the use of confinement electromagnetic waves can decrease the size of the ferrite and show a broadband characteristic.Comment: 3 pages, 6 figures, submitted to IEEE antennas and wireless propagation letters on 27-Mar-201

Spectrally-Corrected and Regularized Global Minimum Variance Portfolio for Spiked Model

Considering the shortcomings of the traditional sample covariance matrix estimation, this paper proposes an improved global minimum variance portfolio model and named spectral corrected and regularized global minimum variance portfolio (SCRGMVP), which is better than the traditional risk model. The key of this method is that under the assumption that the population covariance matrix follows the spiked model and the method combines the design idea of the sample spectrally-corrected covariance matrix and regularized. The simulation of real and synthetic data shows that our method is not only better than the performance of traditional sample covariance matrix estimation (SCME), shrinkage estimation (SHRE), weighted shrinkage estimation (WSHRE) and simple spectral correction estimation (SCE), but also has lower computational complexity

Origin Distribution Visualization of Floating Population and Determinants Analysis: A Case study of Yiwu City

AbstractBased on registered individual floating population data from 2005 to 2008 of Yiwu, the phenomena that population floating to Yiwu City from 34 province and 91 counties in Jiangxi provinces is analyzed. The study aims at analyzing the “pull” forces of Yiwu City and developing migration models for understanding determinants factors of population migration/floating into Yiwu City from other areas in China. The spatial layout of Yiwu's pull forces is proved as a V-shaped pattern consisting of the two axes by using explorative spatial data analysis and map visualization method. The migration models with (model 3) or without (model 2) migration stock are presented and estimated using standard linear regression model, spatial error model as well as spatial lag model at the county scale in Jiangxi province. Based on the likelihood statistics, the AIC and the Moran's I statistics of residuals, the model with migration stock provides an improved fit over the model without migration stock. The correlation between migration ratio and man land ratio is significant at the 0.5 level according to estimates of model 3 and spatial version of model 2. All the three estimates of model 2 and the OLS results of model 3 confirm the distance-decay effect while results from the spatial version of model 3 failed to support the distance rule in population floating. Contrary to the previous studies at the provincial level, the correlation between per capital net income of rural labor forces and migration ratio is not significant according to the three versions of the two models due to the small disparities of income within the counties in Jiangxi. Examination of specification tests in spatial version of model 3 indicates that there is less significant spatial error dependence in the spatial lag models than spatial lag dependence in the error models, further suggesting a preference for the lag model. Model 2 does not suggest any preference for choosing spatial error model and spatial lag model

Characterization and antitumor activity of camptothecin from endophytic fungus Fusarium solani isolated from Camptotheca acuminate

Background: Camptothecin (CPT) is a potent drug against cancers, originally from plants. The endophytic fungi could produce the secondary metabolite same as the host and is used as medicine.Objectives: The aim of this paper was to investigate an endophytic fungal CPT with anti-neoplastic activity.Methods: Endophytic fungi were isolated from Camptotheca acuminata in China. CPT from strain S-019 was characterized by TLC, HPLC and EI-MS analysis. Anti-tumor activity of fungal CPT was detected by MTT and fluorescent dye methods using Vero and PC-3 cells.Results: A total of 94 endophytic fungi strains were isolated from tissues of C. acuminata and 16 fungi strains displayed cytotoxic activity on Vero or PC3 cells. Of which, the fungal strain S-019, classified as Fusarium solani, displayed impressive cytotoxic activity on cancer cells and was found to produce CPT by analysis of TLC, HPLC and EI-MS methods. Bioassay studies confirmed that the fungi CPT had potent cytotoxicity on Vero cells and induced apoptosis of Vero cells.Conclusion: The endophytic fungi from camptotheca trees are a reliable source for natural anticancer compounds. The endophytic fungi could produce CPT same as plant. The fungal CPT exhibited effective activity at inhibiting cell growth and inducing apoptosis on Vero cells.Keywords: Endophytic fungi, camptothecin, anti-tumor, Camptotheca acuminat

Multi-Granularity Archaeological Dating of Chinese Bronze Dings Based on a Knowledge-Guided Relation Graph

The archaeological dating of bronze dings has played a critical role in the study of ancient Chinese history. Current archaeology depends on trained experts to carry out bronze dating, which is time-consuming and labor-intensive. For such dating, in this study, we propose a learning-based approach to integrate advanced deep learning techniques and archaeological knowledge. To achieve this, we first collect a large-scale image dataset of bronze dings, which contains richer attribute information than other existing fine-grained datasets. Second, we introduce a multihead classifier and a knowledge-guided relation graph to mine the relationship between attributes and the ding era. Third, we conduct comparison experiments with various existing methods, the results of which show that our dating method achieves a state-of-the-art performance. We hope that our data and applied networks will enrich fine-grained classification research relevant to other interdisciplinary areas of expertise. The dataset and source code used are included in our supplementary materials, and will be open after submission owing to the anonymity policy. Source codes and data are available at: https://github.com/zhourixin/bronze-Ding.Comment: CVPR2023 accepte

Association of Wnt1-inducible signaling pathway protein-1 with the proliferation, migration and invasion in gastric cancer cells

Wnt1-inducible signaling pathway protein-1 is a cysteine-rich protein that belongs to the CCN family, which has been implicated in mediating the occurrence and progression through distinct molecular mechanisms in several tumor types. However, the association of Wnt1-inducible signaling pathway protein-1 with gastric cancer and the related molecular mechanisms remain to be elucidated. Therefore, this study aimed to clarify the biological role of Wnt1-inducible signaling pathway protein-1 in the proliferation, migration, and invasion in gastric cancer cells and further investigated the associated molecular mechanism on these biological functions. We first detected the expression level of Wnt1-inducible signaling pathway protein-1 in gastric cancer, and the reverse transcription polymerase chain reaction have shown that Wnt1-inducible signaling pathway protein-1 expression levels were upregulated in gastric cancer tissues. The expression of Wnt1-inducible signaling pathway protein-1 in gastric cancer cell lines was also detected by quantitative real-time polymerase chain reaction and Western blotting. Furthermore, two gastric cancer cell lines with high expression of Wnt1-inducible signaling pathway protein-1 were selected to explore the biological function of Wnt1-inducible signaling pathway protein-1 in gastric cancer. Function assays indicated that knockdown of Wnt1-inducible signaling pathway protein-1 suppressed cell proliferation, migration, and invasion in BGC-823 and AGS gastric cancer cells. Further investigation of mechanisms suggested that cyclinD1 was identified as one of Wnt1-inducible signaling pathway protein-1 related genes to accelerate proliferation in gastric cancer cells. In addition, one pathway of Wnt1-inducible signaling pathway protein-1 induced migration and invasion was mainly through the enhancement of epithelial-to-mesenchymal transition progression. Taken together, our findings presented the first evidence that Wnt1-inducible signaling pathway protein-1 was upregulated in gastric cancer and acted as an oncogene by promoting proliferation, migration, and invasion in gastric cancer cells

VGOS: Voxel Grid Optimization for View Synthesis from Sparse Inputs

Neural Radiance Fields (NeRF) has shown great success in novel view synthesis due to its state-of-the-art quality and flexibility. However, NeRF requires dense input views (tens to hundreds) and a long training time (hours to days) for a single scene to generate high-fidelity images. Although using the voxel grids to represent the radiance field can significantly accelerate the optimization process, we observe that for sparse inputs, the voxel grids are more prone to overfitting to the training views and will have holes and floaters, which leads to artifacts. In this paper, we propose VGOS, an approach for fast (3-5 minutes) radiance field reconstruction from sparse inputs (3-10 views) to address these issues. To improve the performance of voxel-based radiance field in sparse input scenarios, we propose two methods: (a) We introduce an incremental voxel training strategy, which prevents overfitting by suppressing the optimization of peripheral voxels in the early stage of reconstruction. (b) We use several regularization techniques to smooth the voxels, which avoids degenerate solutions. Experiments demonstrate that VGOS achieves state-of-the-art performance for sparse inputs with super-fast convergence. Code will be available at https://github.com/SJoJoK/VGOS.Comment: IJCAI 2023 Accepted (Main Track

Characterization and antitumor activity of camptothecin from endophytic fungus Fusarium solani isolated from Camptotheca acuminate .

Background: Camptothecin (CPT) is a potent drug against cancers, originally from plants. The endophytic fungi could produce the secondary metabolite same as the host and is used as medicine. Objectives:The aim of this paper was to investigate an endophytic fungal CPT with anti-neoplastic activity. Methods: Endophytic fungi were isolated from Camptotheca acuminata in China. CPT from strain S-019 was characterized by TLC, HPLC and EI-MS analysis. Anti-tumor activity of fungal CPT was detected by MTT and fluorescent dye methods using Vero and PC-3 cells. Results: A total of 94 endophytic fungi strains were isolated from tissues of C. acuminata and 16 fungi strains displayed cytotoxic activity on Vero or PC3 cells. Of which, the fungal strain S-019, classified as Fusarium solani, displayed impressive cytotoxic activity on cancer cells and was found to produce CPT by analysis of TLC, HPLC and EI-MS methods. Bioassay studies confirmed that the fungi CPT had potent cytotoxicity on Vero cells and induced apoptosis of Vero cells. Conclusion: The endophytic fungi from camptotheca trees are a reliable source for natural anticancer compounds. The endophytic fungi could produce CPT same as plant. The fungal CPT exhibited effective activity at inhibiting cell growth and inducing apoptosis on Vero cells

Staffing to Maximize Profit for Call Centers with Impatient and Repeat-Calling Customers

Motivated by call center practice, we study the optimal staffing of many-server queues with impatient and repeat-calling customers. A call center is modeled as an M/M/s+M queue, which is developed to a behavioral queuing model in which customers come and go based on their satisfaction with waiting time. We explicitly take into account customer repeat behavior, which implies that satisfied customers might return and have an impact on the arrival rate. Optimality is defined as the number of agents that maximize revenues net of staffing costs, and we account for the characteristic that revenues are a direct function of staffing. Finally, we use numerical experiments to make certain comparisons with traditional models that do not consider customer repeat behavior. Furthermore, we indicate how managers might allocate staffing optimally with various customer behavior mechanisms