Lightweight deep learning methods for panoramic dental X-ray image segmentation

Neural Computing and Applications - Dental X-ray image segmentation is helpful for assisting clinicians to examine tooth conditions and identify dental diseases. Fast and lightweight segmentation...     

A unified approach to reliability and edge fault tolerance of cube-based interconnection networks under three hypotheses

The Journal of Supercomputing - The topological structures of the interconnection networks of some parallel and distributed systems are designed as n-dimensional hypercube $$Q_n$$ or n-dimensional...     

Exploring the Semi-Supervised Video Object Segmentation Problem from a Cyclic Perspective

International Journal of Computer Vision - Modern video object segmentation (VOS) algorithms have achieved remarkably high performance in a sequential processing order, while most of currently...     

Hollow Pd/MOF Nanosphere with Double Shells as Multifunctional Catalyst for Hydrogenation Reaction

A new type of hollow nanostructure featured double metal‐organic frameworks shells with metal nanoparticles (MNPs) is designed and fabricated by the methods of ship in a bottle and bottle around the ship. The nanostructure material, hereinafter denoted as Void@HKUST‐1/Pd@ZIF‐8, is confirmed by the analyses of photograph, transmission electron microscopy, scanning electron microscopy, powder X‐ray diffraction, inductively coupled plasma, and N₂ sorption. It possesses various multifunctionally structural characteristics such as hollow cavity which can improve mass transfer, the adjacent of the inner HKUST‐1 shell to the void which enables the matrix of the shell to host and well disperse MNPs, and an outer ZIF‐8 shell which acts as protective layer against the leaching of MNPs and a sieve to guarantee molecular‐size selectivity. This makes the material eligible candidates for the heterogeneous catalyst. As a proof of concept, the liquid‐phase hydrogenation of olefins with different molecular sizes as a model reaction is employed. It demonstrates the efficient catalytic activity and size‐selectivity of Void@HKUST‐1/Pd@ZIF‐8.     

Design of dynamic genetic memory

In electronic systems, dynamic random access memory (DRAM) is one of the core modules in the modern silicon computer. As for a bio‐computer, one would need a mechanism for storage of bio‐information named ‘data’, which, in binary logic, has two levels, logical high and logical low, or in the normalised form, ‘1’ and ‘0’. This study proposes a possible genetic DRAM based on the modified electronic configuration, which uses the biological reaction to fulfil an equivalent RC circuit constituting a memory cell. The authors implement fundamental functions of the genetic DRAM by incorporating a genetic toggle switch for data hold. The results of simulation verify that the basic function can be used on a bio‐storage module for the future bio‐computer.Inspec keywords: DRAM chips, genetic engineering, biocomputers, bioinformatics, equivalent circuits, RC circuitsOther keywords: dynamic genetic memory design, electronic systems, dynamic random access memory, modern silicon computer, biocomputer, bioinformation, binary logic, logical high level, logical low level, normalised form, genetic DRAM, modified electronic configuration, biological reaction, equivalent RC circuit, memory cell, fundamental functions, genetic toggle switch, data hold, biostorage module     

Epitaxial growth and thermal-conductivity limit of single-crystalline Bi2Se3/In2Se3 superlattices on mica

Nano Research - Thermal transport in superlattices is governed by various phonon-scattering processes. For extracting the phonon-scattering contribution of hetero-interfaces in chalcogenide...     

Proline-derived in situ synthesis of nitrogen-doped porous carbon nanosheets with encaged Fe2O3@Fe3C nanoparticles for lithium-ion battery anodes

The homogeneous incorporation of heteroatoms into two-dimensional C nanostructures, which leads to an increased chemical reactivity and electrical conductivity as well as enhanced synergistic catalysis as a conductive matrix to disperse and encapsulate active nanocatalysts, is highly attractive and quite challenging. In this study, by using the natural and cheap hydrotropic amino acid proline—which has remarkably high solubility in water and a desirable N content of ~12.2 wt.%—as a C precursor pyrolyzed in the presence of a cubic KCl template, we developed a facile protocol for the large-scale production of N-doped C nanosheets with a hierarchically porous structure in a homogeneous dispersion. With concomitantly encapsulated and evenly spread Fe₂O₃ nanoparticles surrounded by two protective ultrathin layers of inner Fe₃C and outer onion-like C, the resulting N-doped graphitic C nanosheet hybrids (Fe₂O₃@Fe₃C-NGCNs) exhibited a very high Li-storage capacity and excellent rate capability with a reliable and prolonged cycle life. A reversible capacity as high as 857 mAh•g^–1 at a current density of 100 mA•g^–1 was observed even after 100 cycles. The capacity retention at a current density 10 times higher—1,000 mA•g^–1—reached 680 mAh•g^–1, which is 79% of that at 100 mA•g^–1, indicating that the hybrids are promising as anodes for advanced Li-ion batteries. The results highlight the importance of the heteroatomic dopant modification of the NGCNs host with tailored electronic and crystalline structures for competitive Li-storage features.