Simulation of a Solar Jet Formed from an Untwisting Flux Rope Interacting with a Null Point

Coronal jets are eruptions identified by a collimated, sometimes twisted spire. They are small-scale energetic events compared with flares. Using multi-wavelength observations from the Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) and a magnetogram from Hinode/Spectro-Polarimeter (Hinode/SP), we study the formation and evolution of a jet occurring on 2019 March 22 in the active region NOAA 12736. A zero-$\beta$ magnetohydrodynamic (MHD) simulation is conducted to probe the initiation mechanisms and appearance of helical motion during this jet event. As the simulation reveals, there are two pairs of field lines at the jet base, indicating two distinct magnetic structures. One structure outlines a flux rope lying low above the photosphere in the north of a bald patch region and the other structure shows a null point high in the corona in the south. The untwisting motions of the observed flux rope was recovered by adding an anomalous (artificial) resistivity in the simulation. A reconnection occurs at the bald patch in the flux rope structure, which is moving upwards and simultaneously encounters the field lines of the null point structure. The interaction of the two structures results in the jet while the twist of the flux rope is transferred to the jet by the reconnected field lines. The rotational motion of the flux rope is proposed to be an underlying trigger of this process and responsible for helical motions in the jet spire.Comment: 17pages, 9 figures. Accepted for publication in The Astrophysical Journa

Adaptive 3D Mesh Steganography Based on Feature-Preserving Distortion

3D mesh steganographic algorithms based on geometric modification are vulnerable to 3D steganalyzers. In this paper, we propose a highly adaptive 3D mesh steganography based on feature-preserving distortion (FPD), which guarantees high embedding capacity while effectively resisting 3D steganalysis. Specifically, we first transform vertex coordinates into integers and derive bitplanes from them to construct the embedding domain. To better measure the mesh distortion caused by message embedding, we propose FPD based on the most effective sub-features of the state-of-the-art steganalytic feature set. By improving and minimizing FPD, we can efficiently calculate the optimal vertex-changing distribution and simultaneously preserve mesh features, such as steganalytic and geometric features, to a certain extent. By virtue of the optimal distribution, we adopt the Q-layered syndrome trellis coding (STC) for practical message embedding. However, when Q varies, calculating bit modification probability (BMP) in each layer of Q-layered will be cumbersome. Hence, we contrapuntally design a universal and automatic BMP calculation approach. Extensive experimental results demonstrate that the proposed algorithm outperforms most state-of-the-art 3D mesh steganographic algorithms in terms of resisting 3D steganalysis.Comment: IEEE TVCG major revisio

Pedestrian Accessible Infrastructure Inventory: Assessing Zero-Shot Segmentation on Multi-Mode Geospatial Data for All Pedestrian Types

In this paper, a Segment Anything Model (SAM)-based pedestrian infrastructure segmentation workflow is designed and optimized, which is capable of efficiently processing multi-sourced geospatial data including LiDAR data and satellite imagery data. We used an expanded definition of pedestrian infrastructure inventory which goes beyond the traditional transportation elements to include street furniture objects that are important for accessibility but are often omitted from the traditional definition. Our contributions lie in producing the necessary knowledge to answer the following two questions. First, which data representation can facilitate zero-shot segmentation of infrastructure objects with SAM? Second, how well does the SAM-based method perform on segmenting pedestrian infrastructure objects? Our findings indicate that street view images generated from mobile LiDAR point cloud data, when paired along with satellite imagery data, can work efficiently with SAM to create a scalable pedestrian infrastructure inventory approach with immediate benefits to GIS professionals, city managers, transportation owners, and walkers, especially those with travel-limiting disabilities, such as individuals who are blind, have low vision, or experience mobility disabilities

Design of multifunctional color routers with Kerker switching using generative adversarial networks

To achieve optoelectronic devices with high resolution and efficiency, there is a pressing need for optical structural units that possess an ultrasmall footprint yet exhibit strong controllability in both the frequency and spatial domains. For dielectric nanoparticles, the overlap of electric and magnetic dipole moments can scatter light completely forward or backward, which is called Kerker theory. This effect can expand to any multipoles and any directions, re-named as generalized Kerker effect, and realize controllable light manipulation at full space and full spectrum using well-designed dielectric structures. However, the complex situations of multipole couplings make it difficult to achieve structural design. Here, generative artificial intelligence (AI) is utilized to facilitate multi-objective-oriented structural design, wherein we leverage the concept of "combined spectra" that consider both spectra and direction ratios as labels. The proposed generative adversarial network (GAN) is named as DDGAN (double-discriminator GAN) which discriminates both images and spectral labels. Using trained networks, we achieve the simultaneous design for scattering color and directivities, RGB color routers, as well as narrowband light routers. Notably, all generated structures possess a footprint less than 600x600 nm indicating their potential applications in optoelectronic devices with ultrahigh resolution

Anisodamine combined with lidocaine improves healing of myocardial ischemia reperfusion injury in rats via PI3K/Akt signaling pathway

Purpose: To study the effects of anisodamine (Ad) combined with lidocaine (Ldc) on myocardial ischemia-reperfusion injury (MIRI) in rats, and its correlation with PI3K/AKT signaling pathway.Methods: A total of 70 healthy rats were randomly divided into S group, M group, Ad group, Ldc group, Ad + Ldc group, Ad + Ldc + LY group, and LY group. The cardiac hemodynamic indices in each group were determined, and the area of myocardial infarction measured. Serum biochemical indices were also determined. Furthermore, the protein expressions of p-Akt, T-Akt, Bcl-2, and Bax in myocardial cells were determined by Western blotting.Results: Compared with those in M group, Ad group, Ldc group, Ad + Ldc + LY group, and LY group, cardiac hemodynamic indices significantly improved, while the area of myocardial infarction was significantly reduced (p < 0.01). Furthermore, serum malondialdehyde (MDA) concentration but the activities of CK, CK-MB, TNF-α, and IL-6 declined, while the activities of superoxide dismutase (SOD), CAT and GSH-Px rose in Ad + Ldc group (p < 0.01). In Ad + Ldc group, p-Akt, T-Akt, and Bcl-2 increased, while Bax significantly decreased. Through comparison LY294002 significantly inhibited the protective effect of Ad combined with Ldc against MIRI in rats (p < 0.01).Conclusion: Anisodamine combination with lidocaine has a protective effect against MIRI in rats via PI3K/Akt signaling pathway, thus indicating that it is a potential therapeutic strategy for the management of myocardial ischemia-reperfusion

A Gene Encoding Sialic-Acid-Specific 9-O-Acetylesterase Found in Human Adult Testis

Using differential display RT-PCR, we identified a gene of 2750 bp from human adult testis, named H-Lse, which encoded a putative protein of 523 amino acids and molecular weight of 58 kd with structural characteristics similar to that of mouse lysosome sialic-acid-specific 9-O-acetylesterase. Northern blot analysis showed a widespread distribution of H-Lse in various human tissues with high expression in the testis, prostate, and colon. In situ hybridization results showed that while H-Lse was not detected in embryonic testis, positive signals were found in spermatocytes but not spermatogonia in adult testis of human. The subcellular localization of H-Lse was visualized by green fluorescent protein (GFP) fused to the amino terminus of H-Lse, showing compartmentalization of H-Lse in large dense-core vesicles, presumably lysosomes, in the cytoplasm. The developmentally regulated and spermatogenic stage-specific expression of H-Lse suggests its possible involvement in the development of the testis and/or differentiation of germ cells

Ontology-based systematic representation and analysis of traditional Chinese drugs against rheumatism

Abstract Background Rheumatism represents any disease condition marked with inflammation and pain in the joints, muscles, or connective tissues. Many traditional Chinese drugs have been used for a long time to treat rheumatism. However, a comprehensive information source for these drugs is still missing, and their anti-rheumatism mechanisms remain unclear. An ontology for anti-rheumatism traditional Chinese drugs would strongly support the representation, analysis, and understanding of these drugs. Results In this study, we first systematically collected reported information about 26 traditional Chinese decoction pieces drugs, including their chemical ingredients and adverse events (AEs). By mostly reusing terms from existing ontologies (e.g., TCMDPO for traditional Chinese medicines, NCBITaxon for taxonomy, ChEBI for chemical elements, and OAE for adverse events) and making semantic axioms linking different entities, we developed the Ontology of Chinese Medicine for Rheumatism (OCMR) that includes over 3000 class terms. Our OCMR analysis found that these 26 traditional Chinese decoction pieces are made from anatomic entities (e.g., root and stem) from 3 Bilateria animals and 23 Mesangiospermae plants. Anti-inflammatory and antineoplastic roles are important for anti-rheumatism drugs. Using the total of 555 unique ChEBI chemical entities identified from these drugs, our ChEBI-based classification analysis identified 18 anti-inflammatory, 33 antineoplastic chemicals, and 9 chemicals (including 3 diterpenoids and 3 triterpenoids) having both anti-inflammatory and antineoplastic roles. Furthermore, our study detected 22 diterpenoids and 23 triterpenoids, including 16 pentacyclic triterpenoids that are likely bioactive against rheumatism. Six drugs were found to be associated with 184 unique AEs, including three AEs (i.e., dizziness, nausea and vomiting, and anorexia) each associated with 5 drugs. Several chemical entities are classified as neurotoxins (e.g., diethyl phthalate) and allergens (e.g., eugenol), which may explain the formation of some TCD AEs. The OCMR could be efficiently queried for useful information using SPARQL scripts. Conclusions The OCMR ontology was developed to systematically represent 26 traditional anti-rheumatism Chinese drugs and their related information. The OCMR analysis identified possible anti-rheumatism and AE mechanisms of these drugs. Our novel ontology-based approach can also be applied to systematic representation and analysis of other traditional Chinese drugs.https://deepblue.lib.umich.edu/bitstream/2027.42/140395/1/12918_2017_Article_510.pd