RSGPT: A Remote Sensing Vision Language Model and Benchmark

The emergence of large-scale large language models, with GPT-4 as a prominent example, has significantly propelled the rapid advancement of artificial general intelligence and sparked the revolution of Artificial Intelligence 2.0. In the realm of remote sensing (RS), there is a growing interest in developing large vision language models (VLMs) specifically tailored for data analysis in this domain. However, current research predominantly revolves around visual recognition tasks, lacking comprehensive, large-scale image-text datasets that are aligned and suitable for training large VLMs, which poses significant challenges to effectively training such models for RS applications. In computer vision, recent research has demonstrated that fine-tuning large vision language models on small-scale, high-quality datasets can yield impressive performance in visual and language understanding. These results are comparable to state-of-the-art VLMs trained from scratch on massive amounts of data, such as GPT-4. Inspired by this captivating idea, in this work, we build a high-quality Remote Sensing Image Captioning dataset (RSICap) that facilitates the development of large VLMs in the RS field. Unlike previous RS datasets that either employ model-generated captions or short descriptions, RSICap comprises 2,585 human-annotated captions with rich and high-quality information. This dataset offers detailed descriptions for each image, encompassing scene descriptions (e.g., residential area, airport, or farmland) as well as object information (e.g., color, shape, quantity, absolute position, etc). To facilitate the evaluation of VLMs in the field of RS, we also provide a benchmark evaluation dataset called RSIEval. This dataset consists of human-annotated captions and visual question-answer pairs, allowing for a comprehensive assessment of VLMs in the context of RS

Self-doping effect in confined copper selenide semiconducting quantum dots for efficient photoelectrocatalytic oxygen evolution

Self-doping can not only suppress the photogenerated charge recombination of semiconducting quantum dots by self-introducing trapping states within the bandgap, but also provide high-density catalytic active sites as the consequence of abundant non-saturated bonds associated with the defects. Here, we successfully prepared semiconducting copper selenide (CuSe) confined quantum dots with abundant vacancies and systematically investigated their photoelectrochemical characteristics. Photoluminescence characterizations reveal that the presence of vacancies reduces the emission intensity dramatically, indicating a low recombination rate of photogenerated charge carriers due to the self-introduced trapping states within the bandgap. In addition, the ultra-low charge transfer resistance measured by electrochemical impedance spectroscopy implies the efficient charge transfer of CuSe semiconducting quantum dots-based photoelectrocatalysts, which is guaranteed by the high conductivity of their confined structure as revealed by room-temperature electrical transport measurements. Such high conductivity and low photogenerated charge carriers recombination rate, combined with high-density active sites and confined structure, guaranteeing the remarkable photoelectrocatalytic performance and stability as manifested by photoelectrocatalysis characterizations. This work promotes the development of semiconducting quantum dots-based photoelectrocatalysis and demonstrates CuSe semiconducting quantum confined catalysts as an advanced photoelectrocatalysts for oxygen evolution reaction

Ubiquitin-specific peptidase 39 regulates the process of proliferation and migration of human ovarian cancer via p53/p21 pathway and EMT

Abstract(#br)Ovarian cancer is one of the most lethal gynecological cancers; owning to its late detection and chemoresistance, understanding the pathogenesis of this malignant tumor is much critical. Previous studies have reported that ubiquitin-specific peptidase 39 (USP39) is generally overexpressed in a variety of cancers, including hepatocellular carcinoma, gastric cancer and so forth. Furthermore, USP39 is proved to be associated with the proliferation of malignant tumors. However, the function and mechanism of USP39 in ovarian cancer have not been elucidated. In the present study, we observed that USP39 was frequently overexpressed in human ovarian cancer and was highly correlated with TNM stage. Suppression of USP39 markedly inhibited the growth and migration of ovarian cancer cell..

Ubiquitin-specific peptidase 39 regulates the process of proliferation and migration of human ovarian cancer via p53/p21 pathway and EMT.

Ovarian cancer is one of the most lethal gynecological cancers; owning to its late detection and chemoresistance, understanding the pathogenesis of this malignant tumor is much critical. Previous studies have reported that ubiquitin-specific peptidase 39 (USP39) is generally overexpressed in a variety of cancers, including hepatocellular carcinoma, gastric cancer and so forth. Furthermore, USP39 is proved to be associated with the proliferation of malignant tumors. However, the function and mechanism of USP39 in ovarian cancer have not been elucidated. In the present study, we observed that USP39 was frequently overexpressed in human ovarian cancer and was highly correlated with TNM stage. Suppression of USP39 markedly inhibited the growth and migration of ovarian cancer cell lines HO-8910 and SKOV3 and induced cell cycle G2/M arrest. Moreover, knockdown of USP39 inhibited ovarian tumor growth in a xenograft model. In addition, our findings indicated that cell cycle arrest induced by USP39 knockdown might be involved in p53/p21 signaling pathway. Furthermore, we found that the depletion of USP39 inhibited the migration of ovarian cancer cells via blocking epithelial-mesenchymal transition. Taken together, these results suggest that USP39 may play vital roles in the genesis and progression and may serve as a potential biomarker for diagnosis and therapeutic target of ovarian cancer

Propagation of extended fractures by local nucleation and rapid transverse expansion of crack-front distortion

Fractures are ubiquitous and can lead to the catastrophic material failure of materials. Although fracturing in a two-dimensional plane is well understood, all fractures are extended in and propagate through three-dimensional space. Moreover, their behaviour is complex. Here we show that the forward propagation of a fracture front occurs through an initial rupture, nucleated at some localized position, followed by a very rapid transverse expansion at velocities as high as the Rayleigh-wave speed. We study fracturing in a circular geometry that achieves an uninterrupted extended fracture front and use a fluid to control the loading conditions that determine the amplitude of the forward jump. We find that this amplitude correlates with the transverse velocity. Dynamic rupture simulations capture the observations for only a high transverse velocity. These results highlight the importance of transverse dynamics in the forward propagation of an extended fracture

Beth Levine in memoriam

Beth Levine was born on 7 April 1960 in Newark, New Jersey. She went to college at Brown University where she received an A.B. Magna Cum Laude, and she attended medical school at Cornell University Medical College, receiving her MD in 1986. She completed her internship and residency in Internal Medicine at Mount Sinai Hospital in New York, and her fellowship in Infectious Diseases at The Johns Hopkins Hospital. Most recently, Beth was a Professor of Internal Medicine and Microbiology, Director of the Center for Autophagy Research, and holder of the Charles Sprague Distinguished Chair in Biomedical Science at the University of Texas Southwestern Medical Center in Dallas. Beth died on 15 June 2020 from cancer. Beth is survived by her husband, Milton Packer, and their two children, Rachel (26 years old) and Ben (25 years old). Dr. Levine was as an international leader in the field of autophagy research. Her laboratory identified the mammalian autophagy gene BECN1/beclin 1; identified conserved mechanisms underlying the regulation of autophagy (e.g. BCL2-BECN1 complex formation, insulin-like signaling, EGFR, ERBB2/HER2 and AKT1-mediated BECN1 phosphosphorylation); and provided the first evidence that autophagy genes are important in antiviral host defense, tumor suppression, lifespan extension, apoptotic corpse clearance, metazoan development, Na,K-ATPase-regulated cell death, and the beneficial metabolic effects of exercise. She developed a potent autophagy-inducing cell permeable peptide, Tat-beclin 1, which has potential therapeutic applications in a range of diseases. She was a founding Associate Editor of the journal Autophagy and an editorial board member of Cell and Cell Host & Microbe. She has received numerous awards/honors in recognition of her scientific achievement, including: The American Cancer Society Junior Faculty Research Award (1994); election into the American Society of Clinical Investigation (2000); the Ellison Medical Foundation Senior Scholars Award in Global Infectious Diseases (2004); elected member, American Association of Physicians (2005); appointment as a Howard Hughes Medical Institute Investigator (2008); Edith and Peter O’Donnell Award in Medicine (2008); elected fellow, American Association for the Advancement of Science (2012); election into the National Academy of Sciences (2013); election into the Academy of Medicine, Engineering and Science of Texas (2013); the ASCI Stanley J. Korsmeyer Award (2014); Phyllis T. Bodel Women in Medicine Award, Yale University School of Medicine (2018); recipient, Barcroft Medal, Queen’s University Belfast (2018).Fil: An, Zhenyi. No especifíca;Fil: Ballabi, Andrea. No especifíca;Fil: Bennett, Lynda. 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Oficina de Coordinación Administrativa Houssay. Instituto de Bioquímica y Medicina Molecular. Universidad de Buenos Aires. Facultad Medicina. Instituto de Bioquímica y Medicina Molecular; ArgentinaFil: Virgin, Herbert W.. No especifíca;Fil: Wang, Fei. No especifíca;Fil: White, Eileen. No especifíca;Fil: Xavier, Ramnik J.. No especifíca;Fil: Yoshimori, Tamotsu. No especifíca;Fil: Yuan, Junying. No especifíca;Fil: Yue, Zhenyu. No especifíca;Fil: Zhong, Qing. No especifíca