Recent studies have demonstrated the effectiveness of simulation in radiology perceptual education. While current software exists for perceptual research, these software packages are not optimized ...for inclusion of educational materials and do not have full integration for presentation of educational materials. To address this need, we created a user-friendly software application,
RadSimPE
.
RadSimPE
simulates a radiology workstation, displays radiology cases for quantitative assessment, and incorporates educational materials in one seamless software package. RadSimPE provides simple customizability for a variety of educational scenarios and saves results to quantitatively document changes in performance. We performed two perceptual education studies involving evaluation of central venous catheters: one using RadSimPE and the second using conventional software. Subjects in each study were divided into control and experimental groups. Performance before and after perceptual education was compared. Improved ability to classify a catheter as adequately positioned was demonstrated only in the RadSimPE experimental group. Additional quantitative performance metrics were similar for both the group using conventional software and the group using
RadSimPE
. The study proctors felt that it was qualitatively easier to run the
RadSimPE
session due to integration of educational material into the simulation software. In summary, we created a user-friendly and customizable simulated radiology workstation software package for perceptual education. Our pilot test using the software for central venous catheter assessment was a success and demonstrated effectiveness of our software in improving trainee performance.
In recent times there has been an increasing level of debate whether patterns do exist in equity market movements and whether they can be predicted. In order to overcome the shortcomings of ...traditional time series models, we have focused our study on the application of non-parametric paradigms like stacked multi-layer perceptrons (MLP), long short term memory (LSTM), gated recurrent unit (GRU), bidirectional long short term memory (BLSTM) and gated bidirectional recurrent unit (BGRU) on three NSE listed banks to predict short term stock price, and compared their performance with a shallow neural network benchmark. We have predicted equity ‘Close Prices’ five minutes into the future, using a sliding window approach and have observed that average error in predictions of MLP, LSTM, GRU, BLSTM and BGRU models, varied between 0.09% and 0.1%, indicating their superior performance with regard to benchmark baseline of 0.88%. We have used the aforementioned predictions to determine price trends, which successfully outperformed the random walk baseline accuracy of 50%.
JEL Classification: C45, C58, G11, G14
A novel approach for finding and evaluating structural models of small metallic nanoparticles is presented. Rather than fitting a single model with many degrees of freedom, libraries of clusters from ...multiple structural motifs are built algorithmically and individually refined against experimental pair distribution functions. Each cluster fit is highly constrained. The approach, called cluster‐mining, returns all candidate structure models that are consistent with the data as measured by a goodness of fit. It is highly automated, easy to use, and yields models that are more physically realistic and result in better agreement to the data than models based on cubic close‐packed crystallographic cores, often reported in the literature for metallic nanoparticles.
A novel approach for finding and evaluating structural models of small metallic nanoparticles is presented.
The formation of superconducting nanocomposites from preformed nanocrystals is still not well understood. Here, we examine the case of ZrO₂ nanocrystals in a YBa₂Cu₃O
matrix. First we analyzed the ...preformed ZrO₂ nanocrystals via atomic pair distribution function analysis and found that the nanocrystals have a distorted tetragonal crystal structure. Second, we investigated the influence of various surface ligands attached to the ZrO₂ nanocrystals on the distribution of metal ions in the pyrolyzed matrix via secondary ion mass spectroscopy technique. The choice of stabilizing ligand is crucial in order to obtain good superconducting nanocomposite films with vortex pinning. Short, carboxylate based ligands lead to poor superconducting properties due to the inhomogeneity of metal content in the pyrolyzed matrix. Counter-intuitively, a phosphonate ligand with long chains does not disturb the growth of YBa₂Cu₃O
. Even more surprisingly, bisphosphonate polymeric ligands provide good colloidal stability in solution but do not prevent coagulation in the final film, resulting in poor pinning. These results thus shed light on the various stages of the superconducting nanocomposite formation.
Quasi-two-dimensional (quasi-2D) materials hold promise for future electronics because of their unique band structures that result in electronic and mechanical properties sensitive to crystal strains ...in all three dimensions. Quantifying crystal strain is a prerequisite to correlating it with the performance of the device and calls for high resolution but spatially resolved rapid characterization methods. Here, we show that using fly-scan nano X-ray diffraction, we can accomplish a tensile strain sensitivity below 0.001% with a spatial resolution of better than 80 nm over a spatial extent of 100 μm on quasi-2D flakes of 1T-TaS2. Coherent diffraction patterns were collected from a ∼100 nm thick sheet of 1T-TaS2 by scanning a 12 keV focused X-ray beam across and rotating the sample. We demonstrate that the strain distribution around micron- and submicron-sized “bubbles” that are present in the sample may be reconstructed from these images. The experiments use state-of-the-art synchrotron instrumentation and will allow rapid and nonintrusive strain mapping of thin-film samples and electronic devices based on quasi-2D materials.
We investigated the change in the structure and dynamics of a Ni–Nb bulk metallic glass upon sulfur addition on both microscopic and macroscopic scales. With the sulfur concentration of 3 at. %, ...where the composition Ni58Nb39S3 exhibits the best glass forming ability in the investigated sulfur concentration range, both the equilibrium and undercooled melt dynamics remain almost unchanged. Only in the glassy state does sulfur seem to result in mass transport less decoupled to the viscosity of the undercooled liquid, where the measured Ag tracer diffusion coefficient is slower in the ternary alloy. With the structural disorder introduced by the alloying sulfur, the improved glass forming ability is attributed to geometrical frustration, where crystal nucleation requires a depletion of sulfur and hence long range diffusion, as long as no primary sulfur-containing crystalline phase is involved.
COVID-19 was one of the deadliest and most infectious illnesses of this century. Research has been done to decrease pandemic deaths and slow down its spread. COVID-19 detection investigations have ...utilised Chest X-ray (CXR) images with deep learning techniques with its sensitivity in identifying pneumonic alterations. However, CXR images are not publicly available due to users’ privacy concerns, resulting in a challenge to train a highly accurate deep learning model from scratch. Therefore, we proposed CoviDetector, a new semi-supervised approach based on transfer learning and clustering, which displays improved performance and requires less training data. CXR images are given as input to this model, and individuals are categorised into three classes: (1) COVID-19 positive; (2) Viral pneumonia; and (3) Normal. The performance of CoviDetector has been evaluated on four different datasets, achieving over 99% accuracy on them. Additionally, we generate heatmaps utilising Grad-CAM and overlay them on the CXR images to present the highlighted areas that were deciding factors in detecting COVID-19. Finally, we developed an Android app to offer a user-friendly interface. We release the code, datasets and results’ scripts of CoviDetector for reproducibility purposes; they are available at: https://github.com/dasanik2001/CoviDetector
•CoviDetector is new semi-supervised approach based on transfer learning & clustering.•CoviDetector generates models with improved accuracy and require less training data.•CXR images are given to the deep learning model to evaluate CoviDetector.•CoviDetector utilises the GradCam to interpret the output in a graphical form.•Developed an Android app to offer a user-friendly interface.
Melting is a fundamental process of matter that is still not fully understood at the microscopic level. Here, we use time-resolved x-ray diffraction to examine the ultrafast melting of ...polycrystalline gold thin films using an optical laser pump followed by a delayed hard x-ray probe pulse. We observe the formation of an intermediate new diffraction peak, which we attribute to material trapped between the solid and melted states, that forms 50 ps after laser excitation and persists beyond 500 ps. The peak width grows rapidly for 50 ps and then narrows distinctly at longer time scales. We attribute this to a melting band originating from the grain boundaries and propagating into the grains. Our observation of this intermediate state has implications for the use of ultrafast lasers for ablation during pulsed laser deposition.
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