OPDN: Omnidirectional Position-aware Deformable Network for Omnidirectional Image Super-Resolution

360{\deg} omnidirectional images have gained research attention due to their immersive and interactive experience, particularly in AR/VR applications. However, they suffer from lower angular resolution due to being captured by fisheye lenses with the same sensor size for capturing planar images. To solve the above issues, we propose a two-stage framework for 360{\deg} omnidirectional image superresolution. The first stage employs two branches: model A, which incorporates omnidirectional position-aware deformable blocks (OPDB) and Fourier upsampling, and model B, which adds a spatial frequency fusion module (SFF) to model A. Model A aims to enhance the feature extraction ability of 360{\deg} image positional information, while Model B further focuses on the high-frequency information of 360{\deg} images. The second stage performs same-resolution enhancement based on the structure of model A with a pixel unshuffle operation. In addition, we collected data from YouTube to improve the fitting ability of the transformer, and created pseudo low-resolution images using a degradation network. Our proposed method achieves superior performance and wins the NTIRE 2023 challenge of 360{\deg} omnidirectional image super-resolution.Comment: Accepted to CVPRW 202

Metasurface-based Spectral Convolutional Neural Network for Matter Meta-imaging

Convolutional neural networks (CNNs) are representative models of artificial neural networks (ANNs), that form the backbone of modern computer vision. However, the considerable power consumption and limited computing speed of electrical computing platforms restrict further development of CNNs. Optical neural networks are considered the next-generation physical implementations of ANNs to break the bottleneck. This study proposes a spectral convolutional neural network (SCNN) with the function of matter meta-imaging, namely identifying the composition of matter and mapping its distribution in space. This SCNN includes an optical convolutional layer (OCL) and a reconfigurable electrical backend. The OCL is implemented by integrating very large-scale, pixel-aligned metasurfaces on a CMOS image sensor, which accepts 3D raw datacubes of natural images, containing two-spatial and one-spectral dimensions, at megapixels directly as input to realize the matter meta-imaging. This unique optoelectronic framework empowers in-sensor optical analog computing at extremely high energy efficiency eliminating the need for coherent light sources and greatly reducing the computing load of the electrical backend. We employed the SCNN framework on several real-world complex tasks. It achieved accuracies of 96.4% and 100% for pathological diagnosis and real-time face anti-spoofing at video rate, respectively. The SCNN framework, with an unprecedented new function of substance identification, provides a feasible optoelectronic and integrated optical CNN implementation for edge devices or cellphones with limited computing capabilities, facilitating diverse applications, such as intelligent robotics, industrial automation, medical diagnosis, and astronomy

Maspin differential expression patterns as a potential marker for targeted screening of esophageal adenocarcinoma/gastroesophageal junction adenocarcinoma.

Barrett's esophagus (BE) is a predisposing factor of esophageal adenocarcinoma/gastroesophageal junction adenocarcinoma (ECA/GEJ Aca). BE patients are stratified and subsequently monitored according to the risk of malignant progression by the combination of endoscopy and biopsy. This study is to evaluate the maspin expression patterns as early diagnostic markers of malignancy in BE patients. Immunohistochemistry (IHC) staining was performed on 62 archival core biopsies from 35 patients, including BE without dysplasia (intestinal metaplasia, IM), BE with low grade dysplasia, BE with high grade dysplasia, carcinoma in situ, and well to poorly differentiated ECA/GEJ Aca (PD-ECA/GEJ Aca). The intensity and the subcellular distribution of immunoreactivity were evaluated microscopically. Statistical analysis was performed using the χ2 and Fisher exact tests. The level of epithelial-specific tumor suppressor maspin protein inversely correlated with the progression from IM to PD-ECA/GEJ Aca. Lesions of each pathological grade could be divided into subtypes that exhibited distinct maspin subcellular distribution patterns, including nuclear only (Nuc), combined nuclear and cytoplasmic (Nuc+Cyt), cytoplasmic only (Cyt) and overall negligible (Neg). The Cyt subtype, which was minor in both IM and dysplasia (approximately 10%), was predominant in ECA/GEJ Aca as early as well-differentiated lesions (more than 50%: p = 0.0092). In comparison, nuclear staining of the tumor suppressor TP53 was heterogeneous in dysplasia, and did not correlate with the differentiation grades of ECA/GEJ Aca. The Cyt subtype of maspin expression pattern in core biopsies of BE patients may serve as a molecular marker for early diagnosis of ECA/GEJ Aca.This work was supported by the NIH grant P30CA022453 (to the Karmanos Cancer Institute with Sheng, S. as a program leader), the Ruth Sager Memorial Fund (to Sheng, S.), the Karmanos Cancer Institute Pilot Project Grant 25S5Z (to Sheng, S.), and the Karmanos Cancer Institute Prostate Cancer Research Pilot Project Grant (to Sheng, S.)

Insight-HXMT observations of Swift J0243.6+6124 during its 2017-2018 outburst

The recently discovered neutron star transient Swift J0243.6+6124 has been monitored by {\it the Hard X-ray Modulation Telescope} ({\it Insight-\rm HXMT). Based on the obtained data, we investigate the broadband spectrum of the source throughout the outburst. We estimate the broadband flux of the source and search for possible cyclotron line in the broadband spectrum. No evidence of line-like features is, however, found up to $\rm 150~keV$. In the absence of any cyclotron line in its energy spectrum, we estimate the magnetic field of the source based on the observed spin evolution of the neutron star by applying two accretion torque models. In both cases, we get consistent results with $B\rm \sim 10^{13}~G$, $D\rm \sim 6~kpc$ and peak luminosity of $\rm >10^{39}~erg~s^{-1}$ which makes the source the first Galactic ultraluminous X-ray source hosting a neutron star.Comment: publishe

Overview to the Hard X-ray Modulation Telescope (Insight-HXMT) Satellite

As China's first X-ray astronomical satellite, the Hard X-ray Modulation Telescope (HXMT), which was dubbed as Insight-HXMT after the launch on June 15, 2017, is a wide-band (1-250 keV) slat-collimator-based X-ray astronomy satellite with the capability of all-sky monitoring in 0.2-3 MeV. It was designed to perform pointing, scanning and gamma-ray burst (GRB) observations and, based on the Direct Demodulation Method (DDM), the image of the scanned sky region can be reconstructed. Here we give an overview of the mission and its progresses, including payload, core sciences, ground calibration/facility, ground segment, data archive, software, in-orbit performance, calibration, background model, observations and some preliminary results.Comment: 29 pages, 40 figures, 6 tables, to appear in Sci. China-Phys. Mech. Astron. arXiv admin note: text overlap with arXiv:1910.0443

Applications of Molecular Theory in Solvation of Pharmaceutical Solutes, Ions and Amine-Grafted Silica Gel

Solvation and solvent effects play an important role in diverse chemical processes ranging from reaction kinetics to molecular recognition, solubility, solvato-chromism and phase separations. Despite enormous activities in this field, quantitative solvation calculations remain an enormous intellectual challenge. My thesis is focused on development and application of molecular density functional theory (MDFT) and molecular dynamics (MD) simulation to predicting solvation properties. Accomplishments include 1) improved the average unsigned error of MDFT predictions for the room-temperature solvation free energies (SFE) of 504 pharmaceutical molecules in water from 1.04 kcal/mol to 0.66 kcal/mol; 2) established a more reliable numerical procedure to calculate the direct correlation functions (DCF) of solvent from MD simulations; 3) extended MDFT prediction of SFE to different temperatures and calibrated the theoretical results with experimental data for the hydration free energies of 5 nitrotolunenes and a library of 197 solutes at 277 K, 298 K and 313 K. In addition, I investigated the 3-dimensional (3D) solvation structure of amine-grafted silica gel in liquid water by applying a spherical harmonics expansion method to the MD trajectories. The simulation results provide evidence on the strong influence of the silica surface on hydration structure, which is often ignored in the theoretical analysis of surface reactions. Furthermore, I developed a hybrid method for predicting the SFE of spherical ions by combining MDFT with MD simulations. The numerical analysis justifies the universality of the bridge functional that can be reasonably approximated by the modified fundamental measure theory (MFMT) for hard-sphere systems.Results from this thesis demonstrate that the DCFs are important in application of MDFT to SFE predictions. Based DCF from on integral-equation methods, MDFT can also capture the temperature effect on SFE in good agreement with experiment. In addition, the hybrid MDFT-MD method provides accurate predictions of hydration free energies for charged solutes and the numerical analysis sheds light on future theoretical development. The efficient sampling method for generating 3D density profiles from MD may open up opportunities for application of MDFT to more complex systems, for example, protein solvation and enzyme kinetics. By studying the solvation structure of amine-grafted silica shell, I found that the silica surface affects not only the distribution of surrounding water but also the hydrogen-bonding network. This surface effect is long-ranged and can be reduced with longer grafted amine chains

Performance of Statistical Arbitrage in Future Markets

This paper is the replication of Alizadeh and Nomikos (2008) Performance of Statistical Arbitrage in Petroleum Futures Markets. Cited methodology from the original paper, this paper investigates the linkages between commodities in the future markets and apply trading strategy based on statistical analysis. The trading strategy is established based on cointegration relationships between commodities and execute trading rules to determine long-short positions. The robustness of trading result will be implemented by using stationary bootstrap approach. From the result, we can see the trading strategy based on cointegration relationship analysis is efficient to set up trading strategies in given datasets

Applications of Molecular Theory in Solvation of Pharmaceutical Solutes, Ions and Amine-Grafted Silica Gel

Solvation and solvent effects play an important role in diverse chemical processes ranging from reaction kinetics to molecular recognition, solubility, solvato-chromism and phase separations. Despite enormous activities in this field, quantitative solvation calculations remain an enormous intellectual challenge. My thesis is focused on development and application of molecular density functional theory (MDFT) and molecular dynamics (MD) simulation to predicting solvation properties. Accomplishments include 1) improved the average unsigned error of MDFT predictions for the room-temperature solvation free energies (SFE) of 504 pharmaceutical molecules in water from 1.04 kcal/mol to 0.66 kcal/mol; 2) established a more reliable numerical procedure to calculate the direct correlation functions (DCF) of solvent from MD simulations; 3) extended MDFT prediction of SFE to different temperatures and calibrated the theoretical results with experimental data for the hydration free energies of 5 nitrotolunenes and a library of 197 solutes at 277 K, 298 K and 313 K. In addition, I investigated the 3-dimensional (3D) solvation structure of amine-grafted silica gel in liquid water by applying a spherical harmonics expansion method to the MD trajectories. The simulation results provide evidence on the strong influence of the silica surface on hydration structure, which is often ignored in the theoretical analysis of surface reactions. Furthermore, I developed a hybrid method for predicting the SFE of spherical ions by combining MDFT with MD simulations. The numerical analysis justifies the universality of the bridge functional that can be reasonably approximated by the modified fundamental measure theory (MFMT) for hard-sphere systems. Results from this thesis demonstrate that the DCFs are important in application of MDFT to SFE predictions. Based DCF from on integral-equation methods, MDFT can also capture the temperature effect on SFE in good agreement with experiment. In addition, the hybrid MDFT-MD method provides accurate predictions of hydration free energies for charged solutes and the numerical analysis sheds light on future theoretical development. The efficient sampling method for generating 3D density profiles from MD may open up opportunities for application of MDFT to more complex systems, for example, protein solvation and enzyme kinetics. By studying the solvation structure of amine-grafted silica shell, I found that the silica surface affects not only the distribution of surrounding water but also the hydrogen-bonding network. This surface effect is long-ranged and can be reduced with longer grafted amine chains