Generalized-Equiangular Geometry CT: Concept and Shift-Invariant FBP Algorithms

With advanced X-ray source and detector technologies being continuously developed, non-traditional CT geometries have been widely explored. Generalized-Equiangular Geometry CT (GEGCT) architecture, in which an X-ray source might be positioned radially far away from the focus of arced detector array that is equiangularly spaced, is of importance in many novel CT systems and designs. GEGCT, unfortunately, has no theoretically exact and shift-invariant analytical image reconstruction algorithm in general. In this study, to obtain fast and accurate reconstruction from GEGCT and to promote its system design and optimization, an in-depth investigation on a group of approximate Filtered BackProjection (FBP) algorithms with a variety of weighting strategies has been conducted. The architecture of GEGCT is first presented and characterized by using a normalized-radial-offset distance (NROD). Next, shift-invariant weighted FBP-type algorithms are derived in a unified framework, with pre-filtering, filtering, and post-filtering weights. Three viable weighting strategies are then presented including a classic one developed by Besson in the literature and two new ones generated from a curvature fitting and from an empirical formula, where all of the three weights can be expressed as certain functions of NROD. After that, an analysis of reconstruction accuracy is conducted with a wide range of NROD. We further stretch the weighted FBP-type algorithms to GEGCT with dynamic NROD. Finally, the weighted FBP algorithm for GEGCT is extended to a three-dimensional form in the case of cone-beam scan with a cylindrical detector array.Comment: 31 pages, 13 figure

Unsupervised Domain Adaptation GAN Inversion for Image Editing

Existing GAN inversion methods work brilliantly for high-quality image reconstruction and editing while struggling with finding the corresponding high-quality images for low-quality inputs. Therefore, recent works are directed toward leveraging the supervision of paired high-quality and low-quality images for inversion. However, these methods are infeasible in real-world scenarios and further hinder performance improvement. In this paper, we resolve this problem by introducing Unsupervised Domain Adaptation (UDA) into the Inversion process, namely UDA-Inversion, for both high-quality and low-quality image inversion and editing. Particularly, UDA-Inversion first regards the high-quality and low-quality images as the source domain and unlabeled target domain, respectively. Then, a discrepancy function is presented to measure the difference between two domains, after which we minimize the source error and the discrepancy between the distributions of two domains in the latent space to obtain accurate latent codes for low-quality images. Without direct supervision, constructive representations of high-quality images can be spontaneously learned and transformed into low-quality images based on unsupervised domain adaptation. Experimental results indicate that UDA-inversion is the first that achieves a comparable level of performance with supervised methods in low-quality images across multiple domain datasets. We hope this work provides a unique inspiration for latent embedding distributions in image process tasks

Atomically Well-defined Nitrogen Doping in the Cross-plane Transport through Graphene Heterojunctions

The nitrogen doping of graphene leads to graphene heterojunctions with a tunable bandgap, suitable for electronics, electrochemical, and sensing applications. However, the microscopic nature and charge transport properties of atomic-level nitrogen-doped graphene are still unknown, mainly due to the multiple doping sites with topological diversities. In this work, we fabricated the atomically well-defined N-doped graphene heterojunctions and investigated the cross-plane transport through these heterojunctions to reveal the effects of doping on their electronic properties. We found that different doping number of nitrogen atoms leads to a conductance difference of up to ~288, and the conductance of graphene heterojunctions with nitrogen-doping at different positions in the conjugated framework can also lead to a conductance difference of ~170. Combined ultraviolet photoelectron spectroscopy measurements and theoretical calculations reveal that the insertion of nitrogen atoms into the conjugation framework significantly stabilizes the frontier molecular orbitals, leading to a change in the relative positions of HOMO and LUMO to the Fermi level of the electrodes. Our work provides a unique insight into the role of nitrogen doping on the charge transport through graphene heterojunctions and materials at the single atomic level

Gene Flow Risks From Transgenic Herbicide-Tolerant Crops to Their Wild Relatives Can Be Mitigated by Utilizing Alien Chromosomes

Integration of a transgene into chromosomes of the C-genomes of oilseed rape (AACC, 2n = 38) may affect their gene flow to wild relatives, particularly Brassica juncea (AABB, 2n = 36). However, no empiric evidence exists in favor of the C-genome as a safer candidate for transformation. In the presence of herbicide selections, the first- to fourth-generation progenies of a B. juncea × glyphosate-tolerant oilseed rape cross [EPSPS gene insertion in the A-genome (Roundup Ready, event RT73)] showed more fitness than a B. juncea × glufosinate-tolerant oilseed rape cross [PAT gene insertion in the C-genome (Liberty Link, event HCN28)]. Karyotyping and fluorescence in situ hybridization–bacterial artificial chromosome (BAC-FISH) analyses showed that crossed progenies from the cultivars with transgenes located on either A- or C- chromosome were mixoploids, and their genomes converged over four generations to 2n = 36 (AABB) and 2n = 37 (AABB + C), respectively. Chromosome pairing of pollen mother cells was more irregular in the progenies from cultivar whose transgene located on C- than on A-chromosome, and the latter lost their C-genome-specific markers faster. Thus, transgene insertion into the different genomes of B. napus affects introgression under herbicide selection. This suggests that gene flow from transgenic crops to wild relatives could be mitigated by breeding transgenic allopolyploid crops, where the transgene is inserted into an alien chromosome

Charge transport through single-molecule bilayer-graphene junctions with atomic thickness

The van der Waals interactions (vdW) between the π-conjugated molecules offer new opportunities for fabricating the heterojunction-based devices and investigating charge transport in heterojunctions with atomic thickness. In this work, we fabricate sandwiched single-molecule bilayer-graphene junctions via vdW interactions and characterize their electrical transport properties by employing the cross-plane break junction (XPBJ) technique. Experimental results show that the cross-plane charge transport through single-molecule junctions is determined by the size and layer number of molecular graphene in these junctions. Density functional theory (DFT) calculations reveal that the charge transport through the molecular graphene in these molecular junctions is sensitive to the angles between the graphene flake and peripheral mesityl groups, and those rotated groups can be used to tune the electrical conductance. This study provides new insight into cross-plane charge transport in atomically thin junctions and highlights the role of through-space interactions in vdW heterojunctions at the molecular scale

Intermolecular coupling enhanced thermopower in single- molecule diketopyrrolopyrrole junctions

Sorting out organic molecules with high thermopower is essential for understanding molecular thermoelectrics. The intermolecular coupling offers a unique chance to enhance the thermopower by tuning the bandgap structure of molecular devices, but the investigation of intermolecular coupling in bulk materials remains challenging. Herein, we investigated the thermopower of diketopyrrolopyrrole (DPP) cored single-molecule junctions with different coupling strengths by varying the packing density of the self-assembled monolayers (SAM) using a customized scanning tunneling microscope break junction (STM-BJ) technique. We found that the thermopower of DPP molecules could be enhanced up to one order of magnitude with increasing packing density, suggesting that the thermopower increases with larger neighboring intermolecular interactions. The combined density functional theory (DFT) calculations revealed that the closely-packed configuration brings stronger intermolecular coupling and then reduces the highest occupied molecular orbital (HOMO)-lowest unoccupied molecular orbital (LUMO) gap, leading to an enhanced thermopower. Our findings offer a new strategy for developing organic thermoelectric devices with high thermopower