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As static scene 3D reconstruction algorithms become more mature, dynamic scene 3D reconstruction has become a hot and challenging research topic in recent years. Existing static scene 3D reconstruction algorithms have good reconstruction results for stationary objects. However, when objects in the scene undergo deformation or relative motion, their reconstruction results are not ideal. Therefore, developing research on 3D reconstruction of dynamic scenes is essential. This paper first introduces the related concepts and basic knowledge of 3D reconstruction, as well as the research classification and current status of static and dynamic scene 3D reconstruction. Then, the latest research progress on dynamic scene 3D reconstruction is comprehensively summarized, and the reconstruction algorithms are classified into dynamic 3D reconstruction based on RGB data sources and dynamic 3D reconstruction based on RGB-D data sources. RGB data sources can be further divided into template based dynamic 3D reconstruction, non rigid motion recovery structure based dynamic 3D reconstruction, and learning based dynamic 3D reconstruction under RGB data sources. The RGB-D data source mainly summarizes dynamic 3D reconstruction based on learning, with typical examples introduced and compared. The applications of dynamic scene 3D reconstruction in medical, intelligent manufacturing, virtual reality and augmented reality, and transportation fields are also discussed. Finally, future research directions for dynamic scene 3D reconstruction are proposed, and an outlook on the research progress in this rapidly developing field is presented.

Tomographic synthetic aperture radar is an advanced multi‐channel interferometric technique for retrieving 3‐D spatial information. It can be regarded as an inherently sparse reconstruction problem and can be solved using compressive sensing algorithms. However, the performances are limited by the number of acquisitions and suffer from computational burdens in practice. This paper proposes a novel method based on deep learning, which is carried out and optimized in an end‐to‐end manner by the generative adversarial neural networks. The proposed method applies the cascaded U‐Net architectures to achieve the reconstruction of full‐channel synthetic aperture radar images and the refinement of obtained tomographic results, respectively. The proposed network is trained using simulated data and validate the technique on simulated and real data. The tests show promising results with the limited number of acquisitions while reducing the computation time. [ABSTRACT FROM AUTHOR]

Hippocampal CA1 neurons show intense firing at specific spatial locations, modulated by isolated landmarks. However, the impact of real‐world scene transitions on neuronal activity remains unclear. Moreover, long‐term neural recording during movement challenges device stability. Conventional rigid‐based electrodes cause inflammatory responses, restricting recording durations. Inspired by the jellyfish tentacles, the multi‐conductive layer ultra‐flexible microelectrode arrays (MEAs) are developed. The tentacle MEAs ensure stable recordings during movement, thereby enabling the discovery of soft boundary neurons. The soft boundary neurons demonstrate high‐frequency firing that aligns with the boundaries of scene transitions. Furthermore, the localization ability of soft boundary neurons improves with more scene transition boundaries, and their activity decreases when these boundaries are removed. The innovation of ultra‐flexible, high‐biocompatible tentacle MEAs improves the understanding of neural encoding in spatial cognition. They offer the potential for long‐term in vivo recording of neural information, facilitating breakthroughs in the understanding and application of brain spatial navigation mehanisms. [ABSTRACT FROM AUTHOR]

In the design of flapping-wing micro-size air vehicles capable of hovering, wings serve as the primary source of hovering power, making the analysis of aerodynamics and aerodynamic efficiency crucial. Traditional quasi-steady models treat the wings as single rigid plane, neglecting the deformable characteristics of flexible wings. This paper proposes a multi-plane method that, in conjunction with various design parameters of flexible wings in a two-dimensional plane, analyzes their deformation characteristics under the assumption of multiple planes in three-dimensional space, and describes the deformation of wings during flapping. By combining the quasi-steady aerodynamic model, aerodynamic analysis of the deformed wings can be conducted. The relationship between the slack angle, wing flapping position, and wing deformation are analyzed, along with their effects on aerodynamics and aerodynamic efficiency. Experiments validate the deformation patterns of wings during flapping and compare the simulated aerodynamic forces with measured ones. The results indicate that wing deformation can be accurately described by adjusting the parameters in the multi-plane method and that the aerodynamic analysis using this method closely approximates the average lift results. Additionally, the multi-plane method establishes a connection between wing morphology and aerodynamic forces and efficiency, providing valuable insights for aerodynamic analysis. [ABSTRACT FROM AUTHOR]

High-resolution wide-swath (HRWS) imaging is the research focus of the modern spaceborne synthetic-aperture radar (SAR) imaging field, with significant relevance and vast application potential. Staggered SAR, as an innovative imaging system, mitigates blind areas across the entire swath by periodically altering the radar pulse repetition interval (PRI), thereby extending the swath width to multiples of that achievable by conventional systems. However, the staggered mode introduces inherent challenges, such as nonuniform azimuth sampling and echo data loss, leading to azimuth ambiguities and substantially impacting image quality. This paper proposes a sparse SAR imaging method for the low-oversampled staggered mode via compound regularization. The proposed method not only effectively suppresses azimuth ambiguities arising from nonuniform sampling without necessitating the restoration of missing echo data, but also incorporates total variation (TV) regularization into the sparse reconstruction model. This enhances the accurate reconstruction of distributed targets within the scene. The efficacy of the proposed method is substantiated through simulations and real data experiments from spaceborne missions. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Assessing the dynamic impacts of non-pharmaceutical and pharmaceutical intervention measures on the containment results against COVID-19 in Ethiopia." The correction addresses errors in the author affiliations. The correct affiliations are provided for each author, including institutions in China and Ethiopia. The authors are Hongli Zhu, Shiyong Liu, Wenwen Zheng, Haimanote Belay, Weiwei Zhang, Ying Qian, Yirong Wu, Tadesse Guadu Delele, and Peng Jia. [Extracted from the article]

Objectives: This study aims to investigate whether different types of electronic health record (EHR) users have distinct preferences for data quality assessment indicators (DQAI) and explore how these preferences can guide the enhancement of EHR systems and the optimization of related policies., Materials and Methods: High-frequency indicators were identified by a systematic literature review to construct a DQAI system, which was assessed by a user-oriented investigation involving doctors, nurses, hospital supervisors, and clinical researchers. The entropy weight method and fuzzy comprehensive evaluation model were employed for the system comprehensive evaluation. Exploratory factor analysis was used to construct dimensions, and visualization analysis was utilized to explore preferences at both the indicator and dimension levels., Results: Sixteen indicators were identified to construct the DQAI system and grouped into 2 dimensions: structural and relational. The DQAI system achieved a comprehensive evaluation score of 90.445, corresponding to a "very important" membership level (62.5%). Doctors and nurses exhibited a higher score mean (4.43-4.66 out of 5) than supervisors (3.73-4.55 out of 5). Researchers emphasized credibility, with a score mean of 4.79 out of 5., Discussion: The findings reveal that different types of EHR users exhibit distinct preferences for the DQAI at both indicator and dimension levels. Doctors and nurses thought that all indicators were important, clinical researchers emphasized credibility, and supervisors focused mainly on accuracy. Indicators in the relational dimension were generally more valued than structural ones. Doctors and nurses prioritized indicators of relational dimension, while researchers and supervisors leaned towards indicators of structural dimension. These insights suggest that tailored approaches in EHR system development and policy-making could enhance EHR data quality., Conclusion: This study underscores the importance of user-centered approaches in optimizing EHR systems, highlighting diverse user preferences at both indicator and dimension levels., Competing Interests: There are no competing interests to declare., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

We knocked out the retinoic acid-inducible gene I ( RIG - I) in HEK293 cells via CRISPR/Cas9 to reveal the effects of RIG-I knockout on the key factors in the type I interferon signaling pathway. Three single guide RNAs (sgRNAs) targeting RIG-I were designed, and the recombination vectors were constructed on the basis of the pX459 vector and used to transfect HEK293 cells, which were screened by puromycin subsequently. Furthermore, a mimic of virus, poly I: C, was used to transfect the cells screened out. RIG-I knockout was checked by sequencing, real-time quantitative PCR, Western blotting, and immunofluorescence assay. Meanwhile, the expression levels of key factors of type I interferon signaling pathway such as melanoma differentiation-associated gene 5 (MDA5), interferonβ1 (IFNβ1), and nuclear factor-kappa B p65 [NF-κB(p65)], as well as cell viability, were determined. The results showed that two HEK293 cell lines (S1 and S3) with RIG-I knockout were obtained, which exhibited lower mRNA and protein levels of RIG-I than the wild type HEK293 cells ( P < 0.05). The mRNA levels of MDA5 and IFNβ1 in S1 and S3 cells and the protein level of NF-κB(p65) in S3 cells were lower than those in the wild type ( P < 0.05). More extranuclear NF-κB(p65) protein was detected in S1 cells than in the wild type after transfection with poly I: C. Plus, the wild-type and S1 cells transfected with poly I: C for 48 h showcased reduced viability ( P < 0.05), while S3 cells did not display the reduction in cell viability. In summary, the present study obtained two HEK293 cell lines with RIG-I knockout via CRISPR/Cas9, which provided a stable cell model for exploring the mechanism of type I interferon signaling pathway.

The development of near-field THz microscopes has transcended the diffraction limitation traditionally constraining THz super-resolution imaging, heralding a new era of precision. Notably, Terahertz combined scanning tunneling microscopy (THz-STM) has distinguished itself by achieving unparalleled spatial resolution alongside remarkable temporal precision. Despite the significant advancements in THz-STM imaging research, a thorough exploration of its unique imaging features remains elusive, particularly in resolving local electronic spectroscopy. This study methodically explores THz-STM imaging over atomically precise 6-zigzag-edged graphene nanoribbons (6-ZGNR) on Au(111), employing a constant-current mode. The investigation reveals that intense THz-driven electric fields can induce irreversible alterations to the occupied and unoccupied state densities of the 6-ZGNR. Utilizing these THz-modified nanoribbons, analyses of both THz-driven STM imaging and THz current imaging with an external lock-in amplifier are carried out, and experimental factors affecting their imaging qualities have been investigated. It is demonstrated that the imaging with an external lock-in amplified THz current signal accurately captures the local electronic spectroscopy variations at the nanoscale. What we believe is a novel imaging technique proficiently delineates the features on the Au(111) surface and the 6-ZGNR, showcasing superior performance over direct terahertz-driven STM imaging of the samples.

Background: Previous studies have suggested the potential synergistic antitumor activity when combining immune checkpoint inhibitors with anti-angiogenic agents in various solid tumors. We aimed to assess the efficacy and safety of camrelizumab (a humanized programmed cell death-1 antibody) plus apatinib (a vascular endothelial growth factor receptor tyrosine kinase inhibitor) for patients with advanced mucosal melanoma (MM), and explore-related biomarkers., Methods: We conducted a single-center, open-label, single-arm, phase II study. Patients with unresectable or recurrent/metastatic MM received camrelizumab and apatinib. The primary endpoint was the confirmed objective response rate (ORR)., Results: Between April 2019 and June 2022, 32 patients were enrolled, with 50.0% previously received systemic therapy. Among 28 patients with evaluable response, the confirmed ORR was 42.9%, the disease control rate was 82.1%, and the median progression-free survival (PFS) was 8.05 months. The confirmed ORR was 42.9% (6/14) in both treatment-naïve and previously treated patients. Notably, treatment-naïve patients had a median PFS of 11.89 months, and those with prior treatment had a median PFS of 6.47 months. Grade 3 treatment-related adverse events were transaminase elevation, rash, hyperbilirubinemia, proteinuria, hypertension, thrombocytopenia, hand-foot syndrome and diarrhea. No treatment-related deaths were observed. Higher tumor mutation burden (TMB), increased T-cell receptor (TCR) diversity, and altered receptor tyrosine kinase (RTK)/RAS pathway correlated with better tumor response., Conclusion: Camrelizumab plus apatinib provided promising antitumor activity with acceptable toxicity in patients with advanced MM. TMB, TCR diversity and RTK/RAS pathway genes were identified as potential predictive biomarkers and warrant further validation., Trial Registration Number: Chinese Clinical Trial Registry, ChiCTR1900023277., Competing Interests: Competing interests: RM, YW and YT are employed by Jiangsu Hengrui Pharmaceuticals Co., Ltd. FW is an employee of Nanjing Geneseeq Technology Inc. The other authors declare no conflicts of interest., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)