Dynamics Model of Carrier-based Aircraft Landing Gears Landed on Dynamic Deck

AbstractIn order to study the carrier-based aircraft landing laws landed on the carrier, the dynamics model of carrier-based aircraft landing gears landed on dynamic deck is built. In this model, the interactions of the carrier-based aircraft landing attitude and the damping force acting on landing gears are considered, and the influence of dynamic deck is introduced into the model through the deck normal vectors. The wheel-deck coordinate system is put forward to solve the complex simulation problem of force-on-wheel which comes from the dynamic deck. At last, by simulation, it is demonstrated that the model can be applied to landing attitude when the carrier-based aircraft is landing on the dynamic deck, it is also proved that the model is comprehensive and suitable for any abnormal landing situation

DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment

Cross-modal garment synthesis and manipulation will significantly benefit the way fashion designers generate garments and modify their designs via flexible linguistic interfaces. However, despite the significant progress that has been made in generic image synthesis using diffusion models, producing garment images with garment part level semantics that are well aligned with input text prompts and then flexibly manipulating the generated results still remains a problem. Current approaches follow the general text-to-image paradigm and mine cross-modal relations via simple cross-attention modules, neglecting the structural correspondence between visual and textual representations in the fashion design domain. In this work, we instead introduce DiffCloth, a diffusion-based pipeline for cross-modal garment synthesis and manipulation, which empowers diffusion models with flexible compositionality in the fashion domain by structurally aligning the cross-modal semantics. Specifically, we formulate the part-level cross-modal alignment as a bipartite matching problem between the linguistic Attribute-Phrases (AP) and the visual garment parts which are obtained via constituency parsing and semantic segmentation, respectively. To mitigate the issue of attribute confusion, we further propose a semantic-bundled cross-attention to preserve the spatial structure similarities between the attention maps of attribute adjectives and part nouns in each AP. Moreover, DiffCloth allows for manipulation of the generated results by simply replacing APs in the text prompts. The manipulation-irrelevant regions are recognized by blended masks obtained from the bundled attention maps of the APs and kept unchanged. Extensive experiments on the CM-Fashion benchmark demonstrate that DiffCloth both yields state-of-the-art garment synthesis results by leveraging the inherent structural information and supports flexible manipulation with region consistency

DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment

Cross-modal garment synthesis and manipulation will significantly benefit the way fashion designers generate garments and modify their designs via flexible linguistic interfaces.Current approaches follow the general text-to-image paradigm and mine cross-modal relations via simple cross-attention modules, neglecting the structural correspondence between visual and textual representations in the fashion design domain. In this work, we instead introduce DiffCloth, a diffusion-based pipeline for cross-modal garment synthesis and manipulation, which empowers diffusion models with flexible compositionality in the fashion domain by structurally aligning the cross-modal semantics. Specifically, we formulate the part-level cross-modal alignment as a bipartite matching problem between the linguistic Attribute-Phrases (AP) and the visual garment parts which are obtained via constituency parsing and semantic segmentation, respectively. To mitigate the issue of attribute confusion, we further propose a semantic-bundled cross-attention to preserve the spatial structure similarities between the attention maps of attribute adjectives and part nouns in each AP. Moreover, DiffCloth allows for manipulation of the generated results by simply replacing APs in the text prompts. The manipulation-irrelevant regions are recognized by blended masks obtained from the bundled attention maps of the APs and kept unchanged. Extensive experiments on the CM-Fashion benchmark demonstrate that DiffCloth both yields state-of-the-art garment synthesis results by leveraging the inherent structural information and supports flexible manipulation with region consistency.Comment: accepted by ICCV202

E2F1 Suppresses Oxidative Metabolism and Endothelial Differentiation of Bone Marrow Progenitor Cells

RATIONALE: The majority of current cardiovascular cell therapy trials use bone marrow progenitor cells (BM PCs) and achieve only modest efficacy; the limited potential of these cells to differentiate into endothelial-lineage cells is one of the major barriers to the success of this promising therapy. We have previously reported that the E2F transcription factor 1 (E2F1) is a repressor of revascularization after ischemic injury. OBJECTIVE: We sought to define the role of E2F1 in the regulation of BM PC function. METHODS AND RESULTS: Ablation of E2F1 (E2F1 deficient) in mouse BM PCs increases oxidative metabolism and reduces lactate production, resulting in enhanced endothelial differentiation. The metabolic switch in E2F1-deficient BM PCs is mediated by a reduction in the expression of pyruvate dehydrogenase kinase 4 and pyruvate dehydrogenase kinase 2; overexpression of pyruvate dehydrogenase kinase 4 reverses the enhancement of oxidative metabolism and endothelial differentiation. Deletion of E2F1 in the BM increases the amount of PC-derived endothelial cells in the ischemic myocardium, enhances vascular growth, reduces infarct size, and improves cardiac function after myocardial infarction. CONCLUSION: Our results suggest a novel mechanism by which E2F1 mediates the metabolic control of BM PC differentiation, and strategies that inhibit E2F1 or enhance oxidative metabolism in BM PCs may improve the effectiveness of cell therapy

Magnetic Anisotropy of Quantum Critical Fluctuation in YBa2_2Cu3_3O7_7 at High Magnetic Fields of up to 100 T

The investigation of high-temperature superconductors under high magnetic fields is one of the most important topics in condensed matter physics. For YBa$_2$Cu$_3$O$_7$ (YBCO), the measurements of magnetoresistance under a high magnetic field are technically challenging because the required magnetic field ($B$) is 100 T class. The low temperature (from 52 to 150 K) magnetoresistance is measured in optimally-doped YBCO thin films under the condition $B$$\parallel$CuO$_2$-plane up to 103 T by employing the single-turn coil technique and a radio frequency reflection method. The electrical resistivity $\rho$ exhibits $B$-linear behavior in the normal phase in the high magnetic field region. The field slope coefficient $\beta$ (=$d\rho/dB$) becomes converged at low temperatures. The convergency of $\beta$ below $T_c$ indicates the field-induced strange metal phase, which is determined by the quantum critical fluctuation at high magnetic fields. The $\beta$ value difference under the different directions of the magnetic field suggests the strong anisotropy in quantum critical fluctuations in the strange metal phase of YBCO.Comment: 9 pages, 8 figure

Personalized anesthesia and precision medicine: a comprehensive review of genetic factors, artificial intelligence, and patient-specific factors

Precision medicine, characterized by the personalized integration of a patient’s genetic blueprint and clinical history, represents a dynamic paradigm in healthcare evolution. The emerging field of personalized anesthesia is at the intersection of genetics and anesthesiology, where anesthetic care will be tailored to an individual’s genetic make-up, comorbidities and patient-specific factors. Genomics and biomarkers can provide more accurate anesthetic protocols, while artificial intelligence can simplify anesthetic procedures and reduce anesthetic risks, and real-time monitoring tools can improve perioperative safety and efficacy. The aim of this paper is to present and summarize the applications of these related fields in anesthesiology by reviewing them, exploring the potential of advanced technologies in the implementation and development of personalized anesthesia, realizing the future integration of new technologies into clinical practice, and promoting multidisciplinary collaboration between anesthesiology and disciplines such as genomics and artificial intelligence

Multiple sex partner behavior in female undergraduate students in China: A multi-campus survey

<p>Abstract</p> <p>Background</p> <p>China is realizing increases in women engaged in premarital sex and multiple sex partner behavior. Our aim was to examine prevalence and determinants of multiple sex partner behavior among female undergraduates in China.</p> <p>Methods</p> <p>Anonymously completed questionnaires were received from 4,769 unmarried female undergraduates, recruited using randomized cluster sampling by type of university and students' major and grade. Items captured demographic, family, peer and work influence, and student factors (major, academic performance, and sex-related knowledge and attitudes). To examine risk factors for sexual behaviors, we used multi-level logistic regression, yielding odds ratios (OR) and 95% confidence intervals (95% CI).</p> <p>Results</p> <p>Of 4,769 female students, 863 (18.10%) reported ever having sexual intercourse, and 5.31% reported having multiple sex partners (29.32% of all women having sexual intercourse). Several demographic, family, peer and work influences, and student factors (including major, performance, knowledge, and attitude toward sex) were risk factors for ever having sex. However, risk factors for multiple sex partners only included working in a place of entertainment, having current close friends that were living with boyfriends, poor academic performance, and positive attitudes toward multiple partners. These women also were more likely to practice masturbation, start having sex at a younger age, have sex with married men and/or men not their "boyfriends" at first coitus, and not use condoms consistently.</p> <p>Conclusion</p> <p>A small but important subset of Chinese female undergraduates is engaged in unprotected sex with multiple sex partners. Interventions need to target at risk women, stressing the importance of consistent condom use.</p

Bone mesenchymal stem cell extracellular vesicles delivered miR let-7-5p alleviate endothelial glycocalyx degradation and leakage via targeting ABL2

Abstract Background Endothelial glycocalyx (EG) is an active player and treatment target in inflammatory-related vascular leakage. The bone marrow mesenchymal stem cells (bMSCs) are promising potential treatments for leakage; however, the therapeutic effect and mechanism of bMSC on EG degradation needs to be elucidated. Methods EG degradation and leakage were evaluated in both lipopolysaccharide (LPS)-induced mice ear vascular leakage model and LPS-stimulated human umbilical vein endothelial cells (HUVECs) model treated with bMSCs. Extracellular vesicles (EVs) were extracted from bMSCs and the containing microRNA profile was analyzed. EV and miR let-7-5p were inhibited to determine their function in the therapeutic process. The ABL2 gene was knockdown in HUVECs to verify its role as a therapeutic target in EG degradation. Results bMSCs treatment could alleviate LPS-induced EG degradation and leakage in vivo and in vitro, whereas EVs/let-7-5p-deficient bMSCs were insufficient to reduce EG degradation. LPS down-regulated the expression of let-7-5p while upregulated endothelial expression of ABL2 in HUVECs and induced EG degradation and leakage. bMSC-EVs uptaken by HUVECs could deliver let-7-5p targeting endothelial ABL2, which suppressed the activation of downstream p38MAPK and IL-6, IL-1β levels, and thus reversed LPS-induced EG degradation and leakage. Conclusion bMCSs alleviate LPS-induced EG degradation and leakage through EV delivery of miR let-7-5p targeting endothelial ABL2

{2-[1-(3-Methoxycarbonylmethyl-1H-indol-2-yl)-1-methyl-ethyl]-1H-indol-3-yl}-acetic Acid Methyl Ester Inhibited Hepatocellular Carcinoma Growth in Bel-7402 Cells and Its Resistant Variants by Activation of NOX4 and SIRT3

{2-[1-(3-Methoxycarbonylmethyl-1H-indol-2-yl)-1-methyl-ethyl]-1H-indol-3-yl}-acetic acid methyl ester (MIAM) is a novel indole compound, which possessed high efficacy against many cancers xenografted in mice without obvious toxicity. In this study, we aimed to investigate the effects of MIAM on human hepatocellular carcinoma (HCC) Bel-7402 cells and its resistant variants Bel-7402/5FU. MIAM inhibited the growth of HCC more potent in Bel-7402/5FU cells than its parent cells. MIAM increased cellular reactive oxygen species (ROS) levels, induced cell apoptosis, and arrested cell cycle in G0/G1 phase. MIAM might exert its action on Bel-7402/5FU cells through activation of NADPH oxidase 4 (NOX4)/p22, Sirtuin3 (SIRT3)/SOD2, and SIRT3/p53/p21 pathways. MIAM might inhibit HCC growth through the modulation of SIRT3. When SIRT3 was silenced, the inhibitory effect of MIAM on Bel-7402/5FU was lowered, showing the characteristic of resistance against MIAM, whereas Bel-7402/5FU cells with high expression of SIRT3 by SIRT3 adenovirus infection demonstrated the high sensitivity to MIAM. These results suggested that MIAM might exert its action against Bel-7402/5FU growth through upregulation of SIRT3. We suggested that MIAM might be a promising candidate compound which could develop as a potent anticancer agent targeting NOX4 and SIRT3 activation

A Verifiable Steganography-Based Secret Image Sharing Scheme in 5G Networks

With the development and innovation of new techniques for 5G, 5G networks can provide extremely large capacity, robust integrity, high bandwidth, and low latency for multimedia image sharing and storage. However, it will surely exacerbate the privacy problems intrinsic to image transformation. Due to the high security and reliability requirements for storing and sharing sensitive images in the 5G network environment, verifiable steganography-based secret image sharing (SIS) is attracting increasing attention. The verifiable capability is necessary to ensure the correct image reconstruction. From the literature, efficient cheating verification, lossless reconstruction, low reconstruct complexity, and high-quality stego images without pixel expansion are summarized as the primary goals of proposing an effective steganography-based SIS scheme. Compared with the traditional underlying techniques for SIS, cellular automata (CA) and matrix projection have more strengths as well as some weaknesses. In this paper, we perform a complimentary of these two techniques to propose a verifiable secret image sharing scheme, where CA is used to enhance the security of the secret image, and matrix projection is used to generate shadows with a smaller size. From the steganography perspective, instead of the traditional least significant bits replacement method, matrix encoding is used in this paper to improve the embedding efficiency and stego image quality. Therefore, we can simultaneously achieve the above goals and achieve proactive and dynamic features based on matrix projection. Such features can make the proposed SIS scheme more applicable to flexible 5G networks. Finally, the security analysis illustrates that our scheme can effectively resist the collusion attack and detect the shadow tampering over the persistent adversary. The analyses for performance and comparative demonstrate that our scheme is a better performer among the recent schemes with the perspective of functionality, visual quality, embedding ratio, and computational efficiency. Therefore, our scheme further strengthens security for the images in 5G networks