Strong enhancement of chlorophyll a concentration by a weak typhoon

Recent studies demonstrate that chlorophyll a (chl a) concentrations in the surface ocean can be significantly enhanced due to typhoons. The present study investigated chl a concentrations in the middle of the South China Sea (SCS) from 1997-2007. Only the Category1 (minimal) Typhoon Hagibis (2007) had a notable effect on the chl a concentrations. Typhoon Hagibis had a strong upwelling potential due to its location near the equator, and the forcing time of the typhoon (>82 h) was much longer than the geostrophic adjustment time (~63 h). The higher upwelling velocity and the longer forcing time increased the depth of the mixed-layer, which consequently induced a strong phytoplankton bloom that accounted for about 30% of the total annual chl a concentration in the middle of the SCS. The implication is that the forcing time of a typhoon should be long enough to establish a strong upwelling and consequently for the induction of significant upper ocean responses.Comment: Typhoon-Ocean Environment interaction

Virus efficacy of recombined Autographa californica M nucleopolyhedrovirus (AcMNPV) on tea pest Ectropis obliqua

Ectropis obliqua is a major tea pest and chitin synthase (CHS) plays a key role in the pest growth and development. A 192 bp conserved domain from E. obliqua CHS gene was cloned and it was used to construct recombined Autographa californica M nucleopolyhedrovirus (AcMNPV) with double-stranded RNA interference (dsRNAi) method. The recombined AcMNPV virus could propagate in host cells sf9. Injection test showed that the virus efficacy of the recombined AcMNPV on E. obliqua larvae was significantly enhanced. It is considered that the CHS dsRNAi mediated by the nuclear polyhedrosis virus will be interesting for development of alternative bio-pesticide to control the tea pest E. obliqua.Keywords: Chitin synthase, baculovirus, double-stranded RNA interference, Ectropis obliquaAfrican Journal of Biotechnology Vol. 9(33), pp. 5412-5418, 16 August, 201

Subject-Diffusion:Open Domain Personalized Text-to-Image Generation without Test-time Fine-tuning

Recent progress in personalized image generation using diffusion models has been significant. However, development in the area of open-domain and non-fine-tuning personalized image generation is proceeding rather slowly. In this paper, we propose Subject-Diffusion, a novel open-domain personalized image generation model that, in addition to not requiring test-time fine-tuning, also only requires a single reference image to support personalized generation of single- or multi-subject in any domain. Firstly, we construct an automatic data labeling tool and use the LAION-Aesthetics dataset to construct a large-scale dataset consisting of 76M images and their corresponding subject detection bounding boxes, segmentation masks and text descriptions. Secondly, we design a new unified framework that combines text and image semantics by incorporating coarse location and fine-grained reference image control to maximize subject fidelity and generalization. Furthermore, we also adopt an attention control mechanism to support multi-subject generation. Extensive qualitative and quantitative results demonstrate that our method outperforms other SOTA frameworks in single, multiple, and human customized image generation. Please refer to our \href{https://oppo-mente-lab.github.io/subject_diffusion/}{project page}Comment: 14 pages, 10 figure