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Abstract Two-dimensional conjugated coordination polymers exhibit remarkable charge transport properties, with copper-based benzenehexathiol (Cu-BHT) being a rare superconductor. However, the atomic structure of Cu-BHT has remained unresolved, hindering a deeper understanding of the superconductivity in such materials. Here, we show the synthesis of single crystals of Cu3BHT with high crystallinity, revealing a quasi-two-dimensional kagome structure with non-van der Waals interlayer Cu-S covalent bonds. These crystals exhibit intrinsic metallic behavior, with conductivity reaching 103 S/cm at 300 K and 104 S/cm at 2 K. Notably, superconductivity in Cu3BHT crystals is observed at 0.25 K, attributed to enhanced electron-electron interactions and electron-phonon coupling in the non-van der Waals structure. The discovery of this clear correlation between atomic-level crystal structure and electrical properties provides a crucial foundation for advancing superconductor coordination polymers, with potential to revolutionize future quantum devices.

Abstract Rare‐earth complexes are vital for separation chemistry and useful in many advanced applications including emission and energy upconversion. Here, 2D rare‐earth clusters having net charges are formed on a metal surface, enabling investigations of their structural and electronic properties on a one‐cluster‐at‐a‐time basis using scanning tunneling microscopy. While these ionic complexes are highly mobile on the surface at ≈100 K, their mobility is greatly reduced at 5 K and reveals stable and self‐limiting clusters. In each cluster, a pair of charged rare‐earth complexes formed by electrostatic and dispersive interactions act as a basic unit, and the clusters are chiral. Unlike other non‐ionic molecular clusters formed on the surfaces, these rare‐earth clusters show mechanical stability. Moreover, their high mobility on the surface suggests that they are in a 2D liquid‐like state.

Rare-earth elements are vital to advanced technological applications ranging from spintronic devices to quantum information science. Here, the authors formed charged rare-earth complexes on a material surface and demonstrated atomically precise control on their rotational dynamics.

Controlling the rotation direction of individual molecular machines requires precise design and manipulation. Here, the authors describe a surface-adsorbed molecular propeller that, upon excitation with a scanning tunneling microscope tip, can rotate clockwise or anticlockwise depending on its chirality, and directly visualize its stepwise rotation with STM images.

BackgroundPatients with non-calcified hamartoma were more susceptible to surgery or needle biopsy for the tough discrimination from lung adenocarcinoma. Radiomics have the ability to quantify the lesion features and potentially improve disease diagnosis. Thus, this study aimed to discriminate non-calcified hamartoma from adenocarcinoma by employing imaging quantification and machine learning.MethodsForty-two patients with non-calcified hamartoma and 49 patients with adenocarcinoma were retrospentation; Manual lesion segmentation, feature quantification (e.g., texture features), and artificial neural network were performed consecutively. Independent t-test was used to conduct the inter-group comparisons of those imaging features. Receiver operating characteristic curve was performed to investigate the discriminating efficacy.ResultsSignificantly higher contrast, cluster prominence, cluster shade, dissimilarity, energy, and entropy in non-calcified hamartoma were observed compared with lung adenocarcinoma. Texture-grey-level co-occurrence matrix showed a well discrimination between non-calcified hamartoma and adenocarcinoma as the detection sensitivity, specificity, accuracy, and the area under the curve were 87.22% ± 9.07%, 82.64% ± 8.07%, 85.11% ± 5.40%, and 0.942, respectively.ConclusionQuantifying imaging features is a potentially useful tool for clinical diagnosis. This study demonstrated that non-calcified hamartoma has a heterogeneous distribution of attenuations probably resulting from its complex organizations. Based on this property, imaging quantification could improve discrimination of non-calcified hamartoma from adenocarcinoma.

We have developed a new computed tomography (CT)-based 3-D volume difference reconstruction (VDR) method for building a model of soft tissue differences using facial self-referenced prototyping computation, and a computer-aided design (CAD) workflow for fabricating custom ocular prostheses (COPs). In facial self-referenced prototyping computation, an ocular prosthesis is constructed from a combination of a top surface, shape contour, and bottom surface, with key measurements being made with respect to the patient's healthy eye. The top surface is derived from the outer region of the healthy eyeball, using Hough transformation. In the meantime, the shape contour and bottom surface are computed from facial edges fitted to Fourier curves. Once these self-referenced parameters have been obtained, finite element analysis is used to generate a primitive prosthesis model. Before being converted into a format suitable for rapid prototyping techniques, the model is refined using surface equations. Oculists choose the final optimized model for printing. Geometric errors, compared with a manually-fabricated prosthesis which has gone through multiple rounds of time-consuming manual adjustment, are as low as 0.46%, and the fabrication time and human error have been greatly reduced. The fill density of the COP is 60%, the wall thickness is 1.6 mm and the weight is 1.59 g. The reconstructed contours and symmetry of the COP are satisfactory with doctors' evaluation and the patient is able to have a normal appearance. The CT-based VDR method we first proposed here can accurately build a model of the soft tissue difference. The full CAD workflow has improved prosthesis design and manufacturing efficiency. This flow can also be applied to other soft issue reconstruction.

Stomach bleeding is a kind of gastrointestinal disease which can be diagnosed noninvasively by wireless capsule endoscopy (WCE). However, it requires much time for physicians to scan large amount of WCE images. Alternatively, computer-assisted bleeding localization systems are developed where color, edge, and intensity features are defined to distinguish lesions from normal tissues. This paper proposes a saliency-based localization system where three saliency maps are computed: phase congruency-based edge saliency map derived from Log-Gabor filter bands, intensity histogram-guided intensity saliency map, and red proportion-based saliency map. Fusing the three maps together, the proposed system can detect bleeding regions by thresholding the fused saliency map. Results demonstrate the accuracy of 98.97% for our system to mark bleeding regions.

Asymmetric medullary veins (AMV) are frequently observed in stroke patients and single-echo susceptibility weighted imaging (SWIs) is the main technique in detecting AMV. Our study aimed to investigate which echo time (TE) on single-echo susceptibility is the optimal echo for visualizing AMV and to compare the ability in detecting AMV in stroke patients between SWIs and multi-echo susceptibility weighted imaging (SWIc).Twenty patients with middle cerebral artery stroke were included. SWI was acquired by using a multi-echo gradient-echo sequence with six echoes ranging from 5 ms to 35.240 ms. Three different echoes of SWIs including SWIs1 (TE = 23.144 ms), SWIs2 (TE = 29.192 ms) and SWIs3 (TE = 35.240 ms) were reconstructed. SWIc was averaged using the three echoes of SWIs. Image quality and venous contrast of medullary veins were compared between SWIs and SWIc using peak signal-to-noise ratio (PSNR), mean opinion score (MOS), contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR). The presence of AMV was evaluated in each SWIs (1-3) and SWIc.SWIs2 had the highest PSNR, MOS and CNR and SWIs1 had the highest SNR among three different echoes of SWIs. No significant difference was found in SNR between SWIs1 and SWIs2. PSNR, MOS and CNR in SWIc were significantly increased by 27.9%, 28.2% and 17.2% compared with SWIs2 and SNR in SWIc was significantly increased by 32.4% compared with SWIs1. 55% of patients with AMV were detected in SWIs2, SWIs3 and SWIc, while 50% AMV were found in SWIs1.SWIs using TE around 29ms was optimal in visualizing AMV. SWIc could improve image quality and venous contrast, but was equal to SWIs using a relative long TE in evaluating AMV. These results provide the technique basis for further research of AMV in stroke.

A generalized relative quality (RQ) assessment scheme is proposed here based on the Bayesian inference theory, which is reasonable to make use of full reference (FR) algorithms when the evaluation of the quality of homogeneous medical images is required. Each FR algorithm is taken as a kernel to represent the level of quality. Although, various kernels generate different order of magnitude, a normalization process can rationalize the quality index within 0 and 1, where 1 represent the highest quality and 0 represents the lowest quality. To validate the performance of the proposed scheme, a series of reconstructed susceptibility weighted imaging images are collected, where each image has its subjective scale. Both experimental results and a ROC analysis show that the RQ obtained from the proposed scheme is consistent with subjective evaluation. [ABSTRACT FROM AUTHOR]

A no-reference objective metric for image quality assessment by integrating the topographic independent components analysis into feature extraction is presented. By taking the topographic relationship among the initially independent features into consideration, it extracts the features of more sparsity or independency which is essentially related to inherent quality. Evaluation results demonstrate that the proposed metric is able to predict the image quality accurately across various distortion types. [ABSTRACT FROM AUTHOR]

A novel full-reference image quality assessment metric employing statistical local correlation as an indicator for quality quantification is presented. The local correlation is extracted in a wavelet domain and is pooled into an objective quality score. Simulation and testing results demonstrate that the proposed method not only outperforms the other methods in terms of high accuracy of image quality prediction, but also is consistent with the subjective evaluations. [ABSTRACT FROM AUTHOR]