Three-Dimensional Reconstruction of Thoracic Structures: Based on Chinese Visible Human

We managed to establish three-dimensional digitized visible model of human thoracic structures and to provide morphological data for imaging diagnosis and thoracic and cardiovascular surgery. With Photoshop software, the contour line of lungs and mediastinal structures including heart, aorta and its ramus, azygos vein, superior vena cava, inferior vena cava, thymus, esophagus, diaphragm, phrenic nerve, vagus nerve, sympathetic trunk, thoracic vertebrae, sternum, thoracic duct, and so forth were segmented from the Chinese Visible Human (CVH)-1 data set. The contour data set of segmented thoracic structures was imported to Amira software and 3D thorax models were reconstructed via surface rendering and volume rendering. With Amira software, surface rendering reconstructed model of thoracic organs and its volume rendering reconstructed model were 3D reconstructed and can be displayed together clearly and accurately. It provides a learning tool of interpreting human thoracic anatomy and virtual thoracic and cardiovascular surgery for medical students and junior surgeons

Doping inorganic ions to regulate bioactivity of Ca–P coating on bioabsorbable high purity magnesium

AbstractPerformance of biomaterials was strongly affected by their surface properties and could be designed artificially to meet specific biomedical requirements. In this study, F−(F), SiO42−(Si), or HCO3−(C)-doped Ca–P coatings were fabricated by biomimetic deposition on the surface of biodegradable high-purity magnesium (HP Mg). The crystalline phases, morphologies and compositions of Ca–P coatings had been characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS). The biomineralization and corrosion resistance of doped Ca–P coatings had also been investigated. The results showed that the Ca–P coating with or without doped elements mainly contained the plate-like dicalcium phosphate dehydrate (DCPD) phase. The doped F, Si, or C changed the surface morphology of Ca–P coatings after mineralization. Doped F enhanced the mineralization of Ca–P coating, and doped Si retarded the mineralization of Ca–P coating. However, H2 evolution of HP Mg discs with different Ca–P coatings was close to 0.4–0.7ml/cm2 after two-week immersion. That meant that the corrosion resistance of the Ca–P coatings with different or without doped elements did not change significantly

Structure and Morphology Characteristics of Fullerene C 60

Fullerene C60 nanotubes (FNTs) were prepared via liquid-liquid interfacial precipitation using N-methyl-2-pyrrolidone (NMP) as solvent and isopropyl alcohol (IPA) as precipitation agent at 8°C. C60-saturated NMP solutions were exposed to visible light to promote the growth of FNTs. Scanning electron microscopy revealed that fibers prepared in the NMP/IPA system show three different morphologies. On the basis of the different morphologies of fullerene C60 nanofibers (FNFs), a possible growth mechanism to describe the formation process of FNTs is proposed

Kosmos-2.5: A Multimodal Literate Model

We present Kosmos-2.5, a multimodal literate model for machine reading of text-intensive images. Pre-trained on large-scale text-intensive images, Kosmos-2.5 excels in two distinct yet cooperative transcription tasks: (1) generating spatially-aware text blocks, where each block of text is assigned its spatial coordinates within the image, and (2) producing structured text output that captures styles and structures into the markdown format. This unified multimodal literate capability is achieved through a shared Transformer architecture, task-specific prompts, and flexible text representations. We evaluate Kosmos-2.5 on end-to-end document-level text recognition and image-to-markdown text generation. Furthermore, the model can be readily adapted for any text-intensive image understanding task with different prompts through supervised fine-tuning, making it a general-purpose tool for real-world applications involving text-rich images. This work also paves the way for the future scaling of multimodal large language models