A5100324861- Physics of Superconductivity and Magnetism
- Boron Compounds in Chemistry
- Quantum and electron transport phenomena
- Radiopharmaceutical Chemistry and Applications
- Magnetic properties of thin films
- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- Advanced X-ray Imaging Techniques
- Advanced NMR Techniques and Applications
- Model Reduction and Neural Networks
- Advanced Data Storage Technologies
- Radioactive element chemistry and processing
- 2D Materials and Applications
- Parallel Computing and Optimization Techniques
- Quantum many-body systems
- Organoboron and organosilicon chemistry
- Machine Learning in Materials Science
- Nerve Injury and Rehabilitation
- Quantum Computing Algorithms and Architecture
- Electron Spin Resonance Studies
- Acupuncture Treatment Research Studies
- Orthopedic Surgery and Rehabilitation
- Remote Sensing and Land Use
- Image Processing Techniques and Applications
- Remote Sensing in Agriculture
Northeastern University
2021-2024
Stanford University
2022-2024
Linac Coherent Light Source
2022-2024
SLAC National Accelerator Laboratory
2022-2024
Chongqing University
2023
Nanjing Medical University
2022
Wuxi People's Hospital
2022
Asia University
2019
University of Jinan
2009-2015
Emory University
2010-2013
Abstract Purpose To obtain positive contrast based on T 1 weighting from magnetic iron oxide nanoparticle (IONP) using ultrashort echo time (UTE) imaging and investigate quantitative relationship between the core size concentration of IONPs. Materials Methods Solutions IONPs with different sizes concentrations were prepared. 2 relaxation times measured inversion recovery turbo spin (TSE) multi‐echo sequences at 3 Tesla. ‐weighted UTE gradient TSE used to image IONP samples. U87MG...
The ability to reliably detect sentinel lymph nodes for node biopsy and lymphadenectomy is important in clinical management of patients with metastatic cancers. However, the traditional mapping visible dyes limited by penetration depth light fast clearance dyes. On other hand, radionucleotide technique has intrinsically low spatial resolution does not provide anatomic details procedure. This work reports development a dual modality imaging probe magnetic resonance near infrared capabilities...
Abstract Understanding the nature and origin of collective excitations in materials is fundamental importance for unraveling underlying physics a many-body system. Excitation spectra are usually obtained by measuring dynamical structure factor, S ( Q , ω ), using inelastic neutron or x-ray scattering techniques analyzed comparing experimental results against calculated predictions. We introduce data-driven analysis tool which leverages ‘neural implicit representations’ that specifically...
Calculating the spectral function of two-dimensional systems is arguably one most pressing challenges in modern computational condensed matter physics. While efficient techniques are available lower dimensions, present insurmountable hurdles, ranging from sign problem quantum Monte Carlo methods to entanglement area law tensor-network-based methods. We hereby a variational approach based on Chebyshev expansion and neural network representation for wave functions. The moments obtained by...
Minimally entangled typical thermal states are a construction that allows one to solve for the imaginary time evolution of quantum many-body systems. By using wave functions weakly entangled, can take advantage efficient representations in form matrix product states. We generalize these ideas arbitrary variational and we focus, as an illustration, on particular case restricted Boltzmann machines. The is carried out stochastic reconfiguration (natural gradient descent) combined with Monte...
Culturally sustainable environmental education is a crucial issue that inseparable from our society and environment; closely linked to life. Taiwan’s cultural environment family activities are characterized by religious beliefs temple architectures. Incorporating digital technology into learning about the of Taiwan can be an effective way achieve sustainability. To have deeper understanding culture aesthetics, this study uses AR (augmented reality) bring interactive experiences temple, so...
Abstract Van der Waals (vdW) magnetic materials are comprised of layers atomically thin sheets, making them ideal platforms for studying magnetism at the two-dimensional (2D) limit. These center a host novel types experiments, however, there notably few pathways to directly probe their structure. We confirm order within single crystal NiPS 3 and show it can be accessed with resonant elastic X-ray diffraction along edge vdW planes in carefully grown by detecting structurally forbidden...
To investigative the diagnostic performance of morphological model, radiomics and combined model in differentiating invasive adenocarcinomas (IACs) from minimally (MIAs).This study retrospectively involved 307 patients who underwent chest computed tomography (CT) examination presented as subsolid pulmonary nodules whose pathological findings were MIAs or IACs January 2010 to May 2018. These randomly assigned training validation groups a ratio 4:1 for 10 times. Eighteen categories features...
Abstract The title compound, [Et 4 N][(PPh 3 ) 2 ClRuB 12 H ], was unexpectedly isolated from the reaction of RuCl (PPh with closo ‐B 10 2− in ethanol as a red air‐stable solid, and characterized by IR single crystal X‐ray diffraction analysis. Its formation results B , which present byproduct preparation . It may be formally regarded either ruthenium(II) complex via three B‐H‐Ru three‐center two‐electron bonds, or 13‐vertex pileo 2n ‐electron ( n is number vertices) ruthenaborane cluster...
We study the properties of impurity band in heavily doped nonmagnetic semiconductors using Jacobi-Davidson algorithm and supervised deep learning method. The disorder averaged inverse participation ratio Thouless number calculation show us rich structure inside band. A convolutional neural network model, which is trained to distinguish extended/localized phase Anderson model with high accuracy, shows results good agreement conventional approach. Together, we find that there are three...
With the introduction of x-ray free electron laser sources around world, new scientific approaches for visualizing matter at fundamental length and time-scales have become possible. As it relates to magnetism "magnetic-type" systems, advanced methods are being developed studying ultrafast magnetic responses on which they occur. We describe three capabilities potential seed directions in this area present original results from each: pump-probe scattering with low energy excitation, photon...
In atomistic spin dynamics simulations, the time cost of constructing space- and time-displaced pair correlation function in real space increases quadratically as number spins $N$, leading to significant computational effort. The GEMM subroutine can be adopted accelerate calculation dynamical spin-spin function, but simulating large systems ($>40000$ spins) on CPUs remains expensive. this work, we perform simulation graphics processing unit (GPU), a hardware solution widely used an...
The reaction of dithio-o-carborane with diphenyldiselenide (PhSeSePh) affords the title compound, closo-1,2-(PhSe) 2 C B 10 H (1), which has been characterized by IR and NMR ( 1 H, 11 B) spectroscopy single-crystal X-ray diffraction. phenylselenyl groups are bonded to cage carbon atoms o-carborane cluster a -C distance 1.751(6) Å an Se-C - -Se torsion angle 10.1(3) ° . Compound displays violet emission on excitation UV light. For comparison photoluminescence known analog closo-1,2-(PhS) (2)...
An ortho-rhom-bic polymorph of the title compound, [Fe(C(5)H(5))(C(8)H(17)B(10)O)] or C(13)H(22)B(10)FeO, is described here in addition to known monoclinic [Crundwell et al. (1999 ▶). Acta Cryst.C55, IUC9900087]. The asymmetric unit contains four independent mol-ecules with C(cage)-C(cage) distances 1.636 (16)-1.700 (16) Å, and methyl-hydr-oxy groups disordered over two positions each mol-ecule [occupancy ratios 0.80 (2):0.20 (2), 0.59 (3):0.41 (3), 0.60 (2):0.40 (2) 0.793 (17):0.207 (17)].
The advent of next-generation X-ray free electron lasers will be capable delivering X-rays at a repetition rate approaching 1 MHz continuously. This require the development data systems to handle experiments these type facilities, especially for high throughput applications, such as femtosecond crystallography and photon fluctuation spectroscopy.Here, we demonstrate framework which captures single shot LCLS implements machine-learning algorithm automatically extract contrast parameter from...
Atomistic spin dynamics simulations provide valuable information about the energy spectrum of magnetic materials in different phases, allowing one to identify instabilities and nature their excitations. However, time cost evaluating dynamical correlation function $S(\mathbf{q}, t)$ increases quadratically as number spins $N$, leading significant computational effort, making simulation large systems very challenging. In this work, we propose use a highly optimized general matrix multiply...
Van der Waals (vdW) magnetic materials are comprised of layers atomically thin sheets, making them ideal platforms for studying magnetism at the two-dimensional (2D) limit. These center a host novel types experiments, however, there notably few pathways to directly probe their structure. We report order within single crystal NiPS$_3$ and show it can be accessed with resonant elastic X-ray diffraction along edge vdW planes in carefully grown by detecting structurally forbidden scattering....
The advent of next-generation X-ray free electron lasers will be capable delivering X-rays at a repetition rate approaching 1 MHz continuously. This require the development data systems to handle experiments these type facilities, especially for high throughput applications, such as femtosecond crystallography and photon fluctuation spectroscopy. Here, we demonstrate framework which captures single shot LCLS implements machine-learning algorithm automatically extract contrast parameter from...
As a non-linear extension of the classic Linear Discriminant Analysis(LDA), Deep Analysis(DLDA) replaces original Categorical Cross Entropy(CCE) loss function with eigenvalue-based to make deep neural network(DNN) able learn linearly separable hidden representations. In this paper, we first point out DLDA focuses on training cooperative discriminative ability all dimensions in latent subspace, while put less emphasis capacity single dimension. To improve DLDA, regularization method...