Simulation of electronic and optical properties of graphene

Graphene is a recently discovered two-dimensional crystal. Due to its excellent electronic properties, transport properties, optical properties, and many other features, it has tremendous potential for applications in many areas. This thesis discusses the structure and properties of graphene using several different models of graphene and carries out detailed theoretical studies and calculations of its electronic and optical properties. Using two modules of Materials Studio, CASTAP and Doml3, four graphene models have been constructed. Their electronic and optical properties have also been calculated via these two modules. By comparing the results of calculations with experimental results and the literature, the influence of different structures of these models has been discussed

KPNet: Towards Minimal Face Detector

The small receptive field and capacity of minimal neural networks limit their performance when using them to be the backbone of detectors. In this work, we find that the appearance feature of a generic face is discriminative enough for a tiny and shallow neural network to verify from the background. And the essential barriers behind us are 1) the vague definition of the face bounding box and 2) tricky design of anchor-boxes or receptive field. Unlike most top-down methods for joint face detection and alignment, the proposed KPNet detects small facial keypoints instead of the whole face by in a bottom-up manner. It first predicts the facial landmarks from a low-resolution image via the well-designed fine-grained scale approximation and scale adaptive soft-argmax operator. Finally, the precise face bounding boxes, no matter how we define it, can be inferred from the keypoints. Without any complex head architecture or meticulous network designing, the KPNet achieves state-of-the-art accuracy on generic face detection and alignment benchmarks with only $\sim1M$ parameters, which runs at 1000fps on GPU and is easy to perform real-time on most modern front-end chips.Comment: AAAI 202

IFKD: Implicit field knowledge distillation for single view reconstruction

In 3D reconstruction tasks, camera parameter matrix estimation is usually used to present the single view of an object, which is not necessary when mapping the 3D point to 2D image. The single view reconstruction task should care more about the quality of reconstruction instead of the alignment. So in this paper, we propose an implicit field knowledge distillation model (IFKD) to reconstruct 3D objects from the single view. Transformations are performed on 3D points instead of the camera and keep the camera coordinate identified with the world coordinate, so that the extrinsic matrix can be omitted. Besides, a knowledge distillation structure from 3D voxel to the feature vector is established to further refine the feature description of 3D objects. Thus, the details of a 3D model can be better captured by the proposed model. This paper adopts ShapeNet Core dataset to verify the effectiveness of the IFKD model. Experiments show that IFKD has strong advantages in IOU and other core indicators compared with the camera matrix estimation methods, which verifies the feasibility of the new proposed mapping method

Enhanced sensitivity of neutralizing antibody detection for different AAV serotypes using HeLa cells with overexpressed AAVR

A cell-based transduction inhibition assay (TI) is widely used in clinical trials to detect neutralizing antibody (NAb) titers against recombinant adeno-associated virus (rAAV), one of the most important criteria to exclude patients in gene therapy. Different cell lines are used in cell-based TI because the rAAV transduction efficiencies vary largely among serotypes. A cell line suitable for TI for most serotypes is highly desirable, especially for those with very low transduction efficiencies in vitro such as rAAV8 and rAAV9. Herein, we report an AAVR-HeLa, a stable cell line with overexpressed AAVR, a newly identified receptor for rAAVs, was established for cell-based TIs. The AAVR expression level in AAVR-HeLa cells was approximately 10-fold higher than in HeLa cells, and was stably transfected after twenty three passages. For all AAV serotypes (AAV1-10), except for AAV4, the transduction efficiencies increased significantly in AAVR-HeLa cells. It was demonstrated that the AAVR enhancement of transduction efficiency was only for rAAV and not for lentiviral and adenoviral vectors. According to the minimal multiplicity of infection (MOIs) for the assay, the NAb detection sensitivity increased at least 10 and 20 fold for AAV8 and AAV9, respectively. The seroprevalence of NAbs were investigated at the 1:30 level as a cutoff value using AAVR-HeLa cells. It was shown that the seropositive rate for AAV2 was 87% in serum samples from 99 adults, followed by lower seropositive rates for AAV5 (7%), AAV8 (7%) and AAV9 (1%). Venn diagram analysis showed the presence of cross-reactivity of NAbs to two or three serotypes in 13 samples (13.1%). However, no patient was found to possess NAbs for all the four serotypes. These results demonstrated that the AAVR-HeLa cell line may be utilized to detect the NAbs through cell-based TI assays for most of AAV serotypes

Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly