Low Temperature Scanning Tunneling Microscope and Its Application to Material Characterization

A low temperature and high vacuum compatible fiber optic interferometer was designed and constructed to debug a malfunctioning low temperature scanning tunneling microscope (LT-STM). With its help, the temperature dependent behavior of a Pan-style piezoelectric actuator was studied. The scanning tunneling microscope (STM) was modified accordingly and worked reliably below 10 K. Other properties of the STM were also improved. The electronic noise was reduced from hundreds of picoamps to approximately 10 picoamps by improving the shielding and avoiding ground loops. An eddy current damper was implemented to reduce the vibrational noise. A new mechanical sample stage was introduced to allow manipulation of the sample during experiments. As a result, beautiful atomic resolution images of graphite and self-assembled dodecanethiol monolayer on gold were obtained. Scanning tunneling spectroscopy (STS) measurements were carried out on flux-grown HfNiSn single crystals. Instead of a semiconductor gap, a square root zero bias anomaly (ZBA) which typically presents in disordered systems was observed. Both the temperature dependent resistivity and the magnetoresistance of HfNiSn show characteristic features of disordered systems as well. Below 200 K, the resistivity saturates or obeys a 3 dimensional variable-range hopping (VRH) behavior. The magnetoresistance can be well explained by the Fukuyama-Hoshino (F-H) model for 3D weak anti-localization (WAL). These results indicate that the intrinsic anti-site disorder in HfNiSn may cause Anderson localization. In addition, theories developed and refined in the 1980's for the electron-electron interaction in disordered systems can be used to understand the physical properties and to guide the modifications of half Heusler materials

Contrast-free detection of myocardial fibrosis in hypertrophic cardiomyopathy patients with diffusion-weighted cardiovascular magnetic resonance.

BackgroundsPrevious studies have shown that diffusion-weighted cardiovascular magnetic resonance (DW-CMR) is highly sensitive to replacement fibrosis of chronic myocardial infarction. Despite this sensitivity to myocardial infarction, DW-CMR has not been established as a method to detect diffuse myocardial fibrosis. We propose the application of a recently developed DW-CMR technique to detect diffuse myocardial fibrosis in hypertrophic cardiomyopathy (HCM) patients and compare its performance with established CMR techniques.MethodsHCM patients (N = 23) were recruited and scanned with the following protocol: standard morphological localizers, DW-CMR, extracellular volume (ECV) CMR, and late gadolinium enhanced (LGE) imaging for reference. Apparent diffusion coefficient (ADC) and ECV maps were segmented into 6 American Heart Association (AHA) segments. Positive regions for myocardial fibrosis were defined as: ADC > 2.0 μm(2)/ms and ECV > 30%. Fibrotic and non-fibrotic mean ADC and ECV values were compared as well as ADC-derived and ECV-derived fibrosis burden. In addition, fibrosis regional detection was compared between ADC and ECV calculating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) using ECV as the gold-standard reference.ResultsADC (2.4 ± 0.2 μm(2)/ms) of fibrotic regions (ADC > 2.0 μm(2)/ms) was significantly (p < 0.01) higher than ADC (1.5 ± 0.2 μm(2)/ms) of non-fibrotic regions. Similarly, ECV (35 ± 4%) of fibrotic regions (ECV > 30%) was significantly (p < 0.01) higher than ECV (26 ± 2%) of non-fibrotic regions. In fibrotic regions defined by ECV, ADC (2.2 ± 0.3 μm(2)/ms) was again significantly (p < 0.05) higher than ADC (1.6 ± 0.3 μm(2)/ms) of non-fibrotic regions. In fibrotic regions defined by ADC criterion, ECV (34 ± 5%) was significantly (p < 0.01) higher than ECV (28 ± 3%) in non-fibrotic regions. ADC-derived and ECV-derived fibrosis burdens were in substantial agreement (intra-class correlation = 0.83). Regional detection between ADC and ECV of diffuse fibrosis yielded substantial agreement (κ = 0.66) with high sensitivity, specificity, PPV, NPV, and accuracy (0.80, 0.85, 0.81, 0.85, and 0.83, respectively).ConclusionDW-CMR is sensitive to diffuse myocardial fibrosis and is capable of characterizing the extent of fibrosis in HCM patients

Learning Spatial-Temporal Implicit Neural Representations for Event-Guided Video Super-Resolution

Event cameras sense the intensity changes asynchronously and produce event streams with high dynamic range and low latency. This has inspired research endeavors utilizing events to guide the challenging video superresolution (VSR) task. In this paper, we make the first attempt to address a novel problem of achieving VSR at random scales by taking advantages of the high temporal resolution property of events. This is hampered by the difficulties of representing the spatial-temporal information of events when guiding VSR. To this end, we propose a novel framework that incorporates the spatial-temporal interpolation of events to VSR in a unified framework. Our key idea is to learn implicit neural representations from queried spatial-temporal coordinates and features from both RGB frames and events. Our method contains three parts. Specifically, the Spatial-Temporal Fusion (STF) module first learns the 3D features from events and RGB frames. Then, the Temporal Filter (TF) module unlocks more explicit motion information from the events near the queried timestamp and generates the 2D features. Lastly, the SpatialTemporal Implicit Representation (STIR) module recovers the SR frame in arbitrary resolutions from the outputs of these two modules. In addition, we collect a real-world dataset with spatially aligned events and RGB frames. Extensive experiments show that our method significantly surpasses the prior-arts and achieves VSR with random scales, e.g., 6.5. Code and dataset are available at https: //vlis2022.github.io/cvpr23/egvsr.Comment: Accepted by CVPR202

Dynamic changes in transcripts during regeneration of the secondary vascular system in Populus tomentosa Carr. revealed by cDNA microarrays

<p>Abstract</p> <p>Background</p> <p>Wood is the end product of secondary vascular system development, which begins from the cambium. The wood formation process includes four major stages: cell expansion, secondary wall biosynthesis, lignification, and programmed cell death. Transcriptional profiling is a rapid way to screen for genes involved in these stages and their transitions, providing the basis for understanding the molecular mechanisms that control this process.</p> <p>Results</p> <p>In this study, cDNA microarrays were prepared from a subtracted cDNA library (cambium zone <it>versus </it>leaf) of Chinese white poplar (<it>Populus tomentosa </it>Carr.) and employed to analyze the transcriptional profiles during the regeneration of the secondary vascular system, a platform established in our previous study. Two hundred and seven genes showed transcript-level differences at the different regeneration stages. Dramatic transcriptional changes were observed at cambium initiation, cambium formation and differentiation, and xylem development, suggesting that these up- or downregulated genes play important roles in these stage transitions. Transcription factors such as AUX/IAA and PINHEAD, which were previously shown to be involved in meristem and vascular tissue differentiation, were strongly transcribed at the stages when cambial cells were initiated and underwent differentiation, whereas genes encoding MYB proteins and several small heat shock proteins were strongly transcribed at the stage when xylem development begins.</p> <p>Conclusion</p> <p>Employing this method, we observed dynamic changes in gene transcript levels at the key stages, including cambium initiation, cambium formation and differentiation, and xylem development, suggesting that these up- or downregulated genes are strongly involved in these stage transitions. Further studies of these genes could help elucidate their roles in wood formation.</p

The role of imaging in 2019 novel coronavirus pneumonia (COVID-19).

Almost the entire world, not only China, is currently experiencing the outbreak of a novel coronavirus that causes respiratory disease, severe pneumonia, and even death. The outbreak began in Wuhan, China, in December of 2019 and is currently still ongoing. This novel coronavirus is highly contagious and has resulted in a continuously increasing number of infections and deaths that have already surpassed the SARS-CoV outbreak that occurred in China between 2002 and 2003. It is now officially a pandemic, announced by WHO on the 11th of March. Currently, the 2019 novel coronavirus (SARS-CoV-2) can be identified by virus isolation or viral nucleic acid detection; however, false negatives associated with the nucleic acid detection provide a clinical challenge and thus make the imaging examination crucial. Imaging exams have been a main clinical diagnostic criteria for the 2019 novel coronavirus disease (COVID-19) in China. Imaging features of multiple patchy areas of ground glass opacity and consolidation predominately in the periphery of the lungs are characteristic manifestations on chest CT and extremely helpful in the early detection and diagnosis of this disease, which aids prompt diagnosis and the eventual control of this emerging global health emergency. Key Points • In December 2019, China, an outbreak of pneumonia caused by a novel, highly contagious coronavirus raised grave concerns and posed a huge threat to global public health. • Among the infected patients, characteristic findings on CT imaging include multiple, patchy, ground-glass opacity, crazy-paving pattern, and consolidation shadows, mainly distributed in the peripheral and subpleural areas of both lungs, which are very helpful for the frontline clinicians. • Imaging examination has become the indispensable means not only in the early detection and diagnosis but also in monitoring the clinical course, evaluating the disease severity, and may be presented as an important warning signal preceding the negative RT-PCR test results

Diagnostic Accuracy of Three-Dimensional Whole-Heart Magnetic Resonance Angiography to Detect Coronary Artery Disease with Invasive Coronary Angiography as a Reference: A Meta-Analysis

Objective: We aimed to evaluate the diagnostic performance of three-dimensional whole-heart magnetic resonance coronary angiography (MRCA) in detecting coronary artery disease (CAD) with invasive coronary angiography as the reference standard. Methods: We searched PubMed and Embase for studies evaluating the diagnostic performance of three-dimensional whole-heart MRCA for the diagnosis of CAD with invasive coronary angiography as the reference standard. The bivariate mixed-effects regression model was applied to synthesize available data. The clinical utility of whole-heart MRCA was calculated by the posttest probability based on Bayes’s theorem. Results: Eighteen studies were included, of which 16 provided data at the artery level. Patient-based analysis revealed a pooled sensitivity of 0.90 (95% confidence interval [CI] 0.87–0.93) and specificity of 0.79 (95% CI 0.73–0.84), while the pooled estimates were 0.86 (95% CI 0.82–0.89) and 0.89 (95% CI 0.84–0.92), respectively, at the artery level. The areas under the summary receiver operating characteristic curve were 0.93 (95% CI 0.90–0.95) and 0.92 (95% CI 0.90–0.94) at the patient and artery levels, respectively. With a pretest probability of 50%, the patients’ posttest probabilities of CAD were 81% for positive results and 11% for negative results. Conclusions: Whole-heart MRCA can be an alternative noninvasive method for diagnosis and assessment of CAD