NWPU-MOC: A Benchmark for Fine-grained Multi-category Object Counting in Aerial Images

Object counting is a hot topic in computer vision, which aims to estimate the number of objects in a given image. However, most methods only count objects of a single category for an image, which cannot be applied to scenes that need to count objects with multiple categories simultaneously, especially in aerial scenes. To this end, this paper introduces a Multi-category Object Counting (MOC) task to estimate the numbers of different objects (cars, buildings, ships, etc.) in an aerial image. Considering the absence of a dataset for this task, a large-scale Dataset (NWPU-MOC) is collected, consisting of 3,416 scenes with a resolution of 1024 $\times$ 1024 pixels, and well-annotated using 14 fine-grained object categories. Besides, each scene contains RGB and Near Infrared (NIR) images, of which the NIR spectrum can provide richer characterization information compared with only the RGB spectrum. Based on NWPU-MOC, the paper presents a multi-spectrum, multi-category object counting framework, which employs a dual-attention module to fuse the features of RGB and NIR and subsequently regress multi-channel density maps corresponding to each object category. In addition, to modeling the dependency between different channels in the density map with each object category, a spatial contrast loss is designed as a penalty for overlapping predictions at the same spatial position. Experimental results demonstrate that the proposed method achieves state-of-the-art performance compared with some mainstream counting algorithms. The dataset, code and models are publicly available at https://github.com/lyongo/NWPU-MOC

Shoshonitic enclaves in the high Sr/Y Nyemo pluton, southern Tibet: Implications for Oligocene magma mixing and the onset of extension of the southern Lhasa terrane

Post-collisional potassic and high Sr/Y magmatism in the Lhasa terrane provides critical constraints on the timing and mechanism of subduction of Indian lithosphere and its role in the uplift of the Tibetan Plateau. Here, we report whole-rock geochemistry, mineral geochemistry, zircon U Pb ages, and in situ zircon Hf isotope ratios for the Nyemo pluton, a representative example of such magmatism. The Nyemo pluton is composed of high Sr/Y host rocks and coeval shoshonitic mafic microgranular enclaves (MMEs). Whole-rock compositions of the host rocks and MMEs form linear trends in Harker diagrams, consistent with modification of both end-members by magma mixing. Although the main high Sr/Y phase of the pluton formed by partial melting of the lower crust of the thickened Lhasa terrane, the MMEs display abnormally enriched light rare earth elements, low whole-rock ε_(Nd)(t) and low zircon ε_(Hf)(t) that suggest derivation from low degree melting of hydrous and enriched mantle. Based on the occurrence of shoshonitic magma and high La/Yb and high Sr/Y with adakitic affinity host rocks around 30 Ma, the Nyemo pluton is best explained as a record of onset of extension that resulted from convective removal of the mantle lithosphere beneath Tibet in the Oligocene

Fintech, Bank Risk-Taking, and Risk-Warning for Commercial Banks in the Era of Digital Technology

Fintech risks commercial banks in three ways, particularly operational efficiency, financial innovation, and risk management. Based on the data of 37 Chinese-listed commercial banks from 2011 to 2020, the study empirically analyzes the impact of fintech on bank risk-taking, and the intermediary effects of the three channels, such as operational efficiency, financial innovation, and risk management. The results show that fintech can effectively reduce the risk of banks. The results of heterogeneity analysis revealed that fintech strongly affects the risk-taking of state-owned banks but not obviously for rural commercial banks. Financial efficiency, financial innovation, and risk management indirectly affect the risk-taking of banks that contributed 8.51, 7.18, and 5.77%, respectively. We also constructed the commercial bank risk-warning index. Based on the quarterly data of banks from 2011 to 2020, we empirically tested the early warning effect of the bank risk-warning index. The results showed that when the signal month is set to 12 months, the bank risk-warning index can have a warning effect in this period

Road Surface State Recognition Based on SVM Optimization and Image Segmentation Processing

Adverse road condition is the main cause of traffic accidents. Road surface condition recognition based on video image has become a central issue. However, hybrid road surface and road surface under different lighting environments are two crucial problems. In this paper, the road surface states are categorized into 5 types including dry, wet, snow, ice, and water. Then, according to the original image size, images are segmented; 9-dimensional color eigenvectors and 4 texture eigenvectors are extracted to construct road surface state characteristics database. Next, a recognition method of road surface state based on SVM (Support Vector Machine) is proposed. In order to improve the recognition accuracy and the universality, a grid searching algorithm and PSO (Particle Swarm Optimization) algorithm are used to optimize the kernel function factor and penalty factor of SVM. Finally, a large number of actual road surface images in different environments are tested. The results show that the method based on SVM and image segmentation is feasible. The accuracy of PSO algorithm is more than 90%, which effectively solves the problem of road surface state recognition under the condition of hybrid or different video scenes

Generation of Ultra-intense Gamma-ray Train by QED Harmonics

When laser intensity exceeds 10^22W/cm^2, photons with energy above MeV can be generated from high-order harmonics process in the laser-plasma interaction. We find that under such laser intensity, QED effect plays a dominating role in the radiation pattern. Contrast to the gas and relativistic HHG processes, both the occurrence and energy of gamma-ray emission produced by QED harmonics are random and QED harmonics are usually not coherent, while the property of high intensity and ultra-short duration is conserved. Our simulation shows that the period of gamma-ray train is half of the laser period and the peak intensity is 1.4e22W/cm^2. This new harmonic production with QED effects are crucial to light-matter interaction in strong field and can be verified in experiments by 10PW laser facilities in the near future.Comment: 12 pages, 4 figure

Ultra-bright, ultra-broadband hard x-ray driven by laser-produced energetic electron beams

We propose a new method of obtaining a compact ultra-bright, ultra-broadband hard X-ray source. This X-ray source has a high peak brightness in the order of 1022 photons/(s mm2 mrad2 0.1\%BW), an ultrashort duration (10 fs), and a broadband spectrum (flat distribution from 0.1 MeV to 4 MeV), and thus has wide-ranging potential applications, such as in ultrafast Laue diffraction experiments. In our scheme, laser-plasma accelerators (LPAs) provide driven electron beams. A foil target is placed oblique to the beam direction so that the target normal sheath field (TNSF) is used to provide a bending force. Using this TNSF-kick scheme, we can fully utilize the advantages of current LPAs, including their high charge, high energy, and low emittance

Development, Characterization, and Evaluation of PSMA-Targeted Glycol Chitosan Micelles for Prostate Cancer Therapy

Prostate cancer-binding peptides- (PCP-) modified polymeric micelles were prepared and used for the treatment of prostate-specific membrane antigen- (PSMA-) expressing prostate cancer in a target-specific manner. Cholesterol-modified glycol chitosan (CHGC) was synthesized. PCP-conjugated CHGC (PCP-CHGC) micelles were fabricated and characterized. The degree of substitution was 5.2 PCP groups and 5.8 cholesterol groups per 100 sugar residues of glycol chitosan. The critical aggregation concentration (CAC) of PCP-CHGC copolymer was 0.0254 mg/mL. Doxorubicin (DOX) was chosen as a model antitumor drug. The DOX-loaded micelles were prepared by an o/w method. The mean diameter of DOX-loaded PCP-CHGC (DOX-PCP-CHGC) micelles was 293 nm determined by dynamic light scattering (DLS). DOX released from drug-loaded micelles was in a biphasic manner. DOX-PCP-CHGC micelles exhibited higher cytotoxicity in vitro against PSMA-expressing LNCaP cells than DOX-loaded CHGC (DOX-CHGC) micelles. Moreover, the cellular uptake of DOX-PCP-CHGC micelles determined by confocal laser scanning microscopy (CLSM) and flow cytometry was higher than that of DOX-CHGC micelles in LNCaP cells. Importantly, DOX-PCP-CHGC micelles demonstrated stronger antitumor efficacy against LNCaP tumor xenograft models than doxorubicin hydrochloride and DOX-CHGC micelles. Taken together, this study provides a potential way in developing PSMA-targeted drug delivery system for prostate cancer therapy