Pathological Evidence Exploration in Deep Retinal Image Diagnosis

Though deep learning has shown successful performance in classifying the label and severity stage of certain disease, most of them give few evidence on how to make prediction. Here, we propose to exploit the interpretability of deep learning application in medical diagnosis. Inspired by Koch's Postulates, a well-known strategy in medical research to identify the property of pathogen, we define a pathological descriptor that can be extracted from the activated neurons of a diabetic retinopathy detector. To visualize the symptom and feature encoded in this descriptor, we propose a GAN based method to synthesize pathological retinal image given the descriptor and a binary vessel segmentation. Besides, with this descriptor, we can arbitrarily manipulate the position and quantity of lesions. As verified by a panel of 5 licensed ophthalmologists, our synthesized images carry the symptoms that are directly related to diabetic retinopathy diagnosis. The panel survey also shows that our generated images is both qualitatively and quantitatively superior to existing methods.Comment: to appear in AAAI (2019). The first two authors contributed equally to the paper. Corresponding Author: Feng L

Generative Modeling in Sinogram Domain for Sparse-view CT Reconstruction

The radiation dose in computed tomography (CT) examinations is harmful for patients but can be significantly reduced by intuitively decreasing the number of projection views. Reducing projection views usually leads to severe aliasing artifacts in reconstructed images. Previous deep learning (DL) techniques with sparse-view data require sparse-view/full-view CT image pairs to train the network with supervised manners. When the number of projection view changes, the DL network should be retrained with updated sparse-view/full-view CT image pairs. To relieve this limitation, we present a fully unsupervised score-based generative model in sinogram domain for sparse-view CT reconstruction. Specifically, we first train a score-based generative model on full-view sinogram data and use multi-channel strategy to form highdimensional tensor as the network input to capture their prior distribution. Then, at the inference stage, the stochastic differential equation (SDE) solver and data-consistency step were performed iteratively to achieve fullview projection. Filtered back-projection (FBP) algorithm was used to achieve the final image reconstruction. Qualitative and quantitative studies were implemented to evaluate the presented method with several CT data. Experimental results demonstrated that our method achieved comparable or better performance than the supervised learning counterparts.Comment: 11 pages, 12 figure

Image-Force-Stabilized Interfacial Dipole Layer Impedes Charge Injection into Disordered Organic Semiconductors

We show using three-dimensional kinetic Monte Carlo simulations that the injection of charge carriers from a metallic electrode into a disordered organic semiconductor is under nominally Ohmic injection conditions strongly impeded by the short-range Coulomb interactions between the charge carriers in the image-force-stabilized interfacial dipole layer. In contrast, master equation and conventional one-dimensional drift-diffusion simulations underestimate these Coulomb interactions due to their mean-field approximation, and are found not to reveal the effect. The simulations predict a reduction of the current density in organic semiconductor devices when the nominal injection barrier is taken very small or even negative, consistent with recent experimental results [Kotadiya et al., Nat. Mater. 17, 329 (2018)]. However, whereas in that work a modification of the energetic disorder near the interface is assumed, we find that the effect is already obtained after including charge-charge interactions beyond a one-dimensional and mean-field approximation. </p

Preparation and Characterization of Multi-Doped PorousCarbon Nanofibers from Carbonization in Different Atmospheres and Their Oxygen Electrocatalytic Properties Research

Recently, electrocatalysts for oxygen reduction reaction (ORR) as well as oxygen evolution reaction (OER) hinged on electrospun nanofiber composites have attracted wide research attention. Transition metal elements and heteroatomic doping are important methods used to enhance their catalytic performances. Lately, the construction of electrocatalysts based on metal-organic framework (MOF) electrospun nanofibers has become a research hotspot. In this work, nickel-cobalt zeolitic imidazolate frameworks with different molar ratios (NixCoy-ZIFs) were synthesized in an aqueous solution, followed by NixCoy-ZIFs/polyacrylonitrile (PAN) electrospun nanofiber precursors, which were prepared by a simple electrospinning method. Bimetal (Ni-Co) porous carbon nanofiber catalysts doped with nitrogen, oxygen, and sulfur elements were obtained at high-temperature carbonization treatment in different atmospheres (argon (Ar), Air, and hydrogen sulfide (H2S)), respectively. The morphological properties, structures, and composition were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), selected area electron diffraction (SAED), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). Moreover, the specific surface area of materials and their pore size distribution was characterized by Brunauer-Emmett-Teller (BET). Linear sweep voltammetry curves investigated catalyst performances towards oxygen reduction and evolution reactions. Importantly, Ni1Co2-ZIFs/PAN-Ar yielded the best ORR activity, whereas Ni1Co1-ZIFs/PAN-Air exhibited the best OER performance. This work provides significant guidance for the preparation and characterization of multi-doped porous carbon nanofibers carbonized in different atmospheres

Probing high-momentum component in nucleon momentum distribution by neutron-proton bremsstrahlung {\gamma}-rays in heavy ion reactions

The high momentum tail (HMT) of nucleons, as a signature of the short-range correlations in nuclei, has been investigated by the high-energy bremsstrahlung $\gamma$ rays produced in $^{86}$Kr + $^{124}$Sn at 25 MeV/u. The energetic photons are measured by a CsI(Tl) hodoscope mounted on the spectrometer CSHINE. The energy spectrum above 30 MeV can be reproduced by the IBUU model calculations incorporating the photon production channel from $np$ process in which the HMTs of nucleons is considered. A non-zero HMT ratio of about $15\%$ is favored by the data. The effect of the capture channel $np \to d\gamma$ is demonstrated

L2 learners’ pronunciation of English phonetic sounds: An acoustic analysis with software Praat

Pronouncing English sounds correctly is not an easy task for second language (L2) learners because of the influence of their mother tongue. Empirical studies, based on first language (L1) interference, have investigated L2 learners’ pronunciation problems. However, these studies rarely focused on students’ development in pronunciation, and their results lack validity and reliability because of their mere employment of L2 English teachers as pronunciation assessors. The present study, using the acoustic software Praat as the instrument and taking a native speaker as the comparison, investigated Chinese L2 English learners’ problems and improvement in pronouncing the English sounds that do not have exact counterparts in Chinese. Data analysis revealed that the participants manifested different degrees of pronunciation accuracy with the target English sounds; their mispronunciations of consonants were mainly due to lacking voicing, wrong manners, and wrong places of articulation, while their mispronunciations of vowels were attributed to their improper tongue position, mouth opening, and diphthongization; and that higher-proficiency students tended to have greater pronunciation accuracy. The findings were discussed with reference to the literature, and pedagogical implications were provided at the end

3D Numerical Analysis of Synergetic Interaction between High-Rise Building Basement and CFG Piles Foundation

A strong bearing capacity and the satisfaction of strict settlement requirements are necessary for high-rise buildings. A single-raft foundation cannot meet certain settlement requirements, in which case CFG (cement/fly ash/gravel, an emerging and sustainable construction material) piles can be used in the foundation to set up a cushion between the top of the pile and the raft slab, where the piles act as settlement reducers. The rafts of disconnected piles (DPs) exhibit complex synergetic interactions involving the raft, cushion, pile, and soil under the load of the superstructure. Multiple piles in particular lead to an increase in the number of degrees of freedom of the problem, resulting in difficulty in solving it. However, when the number of piles is very large and the structure is complex&#8212;for example, many buildings are placed on the same raft with basement structures&#8212;even if the embedded pile element is used during numerical calculations, either the method remains prone to non-convergence or the time needed for numerical calculations is too long. It is, thus, difficult to satisfy the requirement of an efficient scheme of evaluation in practice. To solve this problem, a method that uses a simulation of the integral equivalent of the CFG pile reinforcement zone is proposed in this paper. In the CFG pile reinforcement zone, the effect of the pile is reflected in the enhancement of parameters of the soil in the strengthened zone, and the reinforcement zone (including the soil and the pile) is regarded as an anisotropic elastoplastic material. As the structure of the pile is no longer needed in the model, its elimination significantly reduces the complexity of the model and improves its calculation efficiency. An example of a numerical calculation is provided to verify the viability and accuracy of the integral equivalent simulation method in comparison with the embedded pile element simulation method. Finally, the proposed method is applied to the three-dimensional numerical analysis of a scheme for the treatment of foundations of high- and low-rise buildings with basements, and its effectiveness is further verified through comparison with theoretical results

ZIF-67 grown onto three-dimensional biomass cotton fibers for efficient adsorption of tetracycline

In recent years, Metal-Organic Frameworks (MOFs) have garnered significant attention for their potential in tetracycline (TC) removal. However, pure MOFs typically exist in powdered form and tend to aggregate in water, which greatly limits practical applications. To address this issue, a three-dimensional composite material was prepared by ZIF-67 grown onto cotton fibers (ZIF-670.50@CF). This composite not only enhances adsorption capacity but also reduces the adsorption equilibrium time compared to most other adsorbents. ZIF-670.50@CF boasts a BET specific surface area of 257.74 m²·g-1, with pores consisting mainly of mesopores and micropores. Moreover, ZIF-670.50@CF exhibits excellent adsorption capabilities for TC across a broad pH range of 4–9 and displays notable resilience against environmental interference. The adsorption behavior of ZIF-670.50@CF is more consistent with the Langmuir model, with a maximum adsorption capacity of 432.619 mg·g-1 for TC. Mechanistic research reveals that adsorption primarily involves chemical interactions (complexation, π-π stacking, and electrostatic interaction) and physical pore filling. Additionally, the favorable plasticity of ZIF-670.50@CF allows it to be fabricated into various shapes for use as filling materials, exhibiting admirable TC removal performance in continuous flow adsorption experiments

An Improved Large-Field Microscopic Speckle Interferometry System for Dynamic Displacement Measurement of MEMS

The traditional microscopic speckle interferometer has limited applications in engineering due to its small field of view. In this paper, we propose a large-field microscopic speckle interferometer which embeds two doublet lens groups in the improved Mach–Zehnder optical path structure to expand its field of view. At the same time, the new system can reduce the coherent noise of reflected light in the optical path. We use this new system to measure the dynamic displacement process of the entire surface of the microchips. The experimental results show that our improved measurement system can achieve large-field, real-time and high-precision dynamic measurement of micro-electromechanical systems (MEMS)