Search

CDK6 plays a key role in the regulation of the cell cycle and is considered a crucial target for cancer therapy. In this work, conformational transitions of CDK6 were identified by using Gaussian accelerated molecular dynamics (GaMD), deep learning (DL), and free energy landscapes (FELs). DL finds that the binding pocket as well as the T-loop binding to the Vcyclin protein are involved in obvious differences of conformation contacts. This result suggests that the binding pocket of inhibitors (LQQ and AP9) and the binding interface of CDK6 to the Vcyclin protein play a key role in the function of CDK6. The analyses of FELs reveal that the binding pocket and the T-loop of CDK6 have disordered states. The results from principal component analysis (PCA) indicate that the binding of the Vcyclin protein affects the fluctuation behavior of the T-loop in CDK6. Our QM/MM-GBSA calculations suggest that the binding ability of LQQ to CDK6 is stronger than AP9 with or without the binding of the Vcyclin protein. Interaction networks of inhibitors with CDK6 were analyzed and the results reveal that LQQ contributes more hydrogen binding interactions (HBIs) and hot interaction spots with CDK6. In addition, the binding pocket endures flexibility changes from opening to closing states and the Vcyclin protein plays an important role in the stabilizing conformation of the T-loop. We anticipate that this work could provide useful information for further understanding the function of CDK6 and developing new promising inhibitors targeting CDK6. [ABSTRACT FROM AUTHOR]

Deep transfer learning has a great success story in computer vision (CV), natural language processing, and many other fields. In this communication, we are going to push forward the deep transfer learning to the hydraulic fracture imaging problem by proposing a two-step approach: 1) train a convolutional neural network (CNN) to reconstruct target geometries by a relatively large amount of approximated field patterns generated from a simplified model and 2) fine-tune the top layers of transferred CNN by a small amount of true field patterns generated through a full model. The advantages include the rapid generation of large amount of data through the simplified model and the high reconstruction accuracy through a careful design of the deep transfer learning. The CNN trained through the deep transfer learning can accurately reconstruct the lateral extent and direction of fractures with unseen conductivity and white Gaussian noise, showing a notable acceleration/accuracy enhancement over the previous CNN trained by mixing a small number of true data into the approximated data as data augmentation. [ABSTRACT FROM AUTHOR]

The pontomesencephalic tegmentum, comprising the pedunculopontine nucleus and laterodorsal tegmental nucleus, is involved in various functions via complex connections; however, the organizational structure of these circuits in the whole brain is not entirely clear. Here, combining viral tracing with fluorescent micro-optical sectional tomography, we comprehensively investigated the input and output circuits of two cholinergic subregions in a continuous whole-brain dataset. We found that these nuclei receive abundant input with similar spatial distributions but with different quantitative measures and acquire similar neuromodulatory afferents from the ascending reticular activation system. Meanwhile, these cholinergic nuclei project to similar targeting areas throughout multiple brain regions and have different spatial preferences in 3D. Moreover, some cholinergic connections are unidirectional, including projections from the pedunculopontine nucleus and laterodorsal tegmental nucleus to the ventral posterior complex of the thalamus, and have different impacts on locomotion and anxiety. These results reveal the integrated cholinergic connectome of the midbrain, thus improving the present understanding of the organizational structure of the pontine-tegmental cholinergic system from its anatomical structure to its functional modulation. [ABSTRACT FROM AUTHOR]

To further improve the computational efficiency of the existing wave equation-based discontinuous Galerkin time-domain (DGTD) method for modeling electrically small structures, the weighted Laguerre polynomials are incorporated to span the fields in the temporal domain, which finally results in a set of recursive linear equations related to the Laguerre polynomials to be solved. Compared with conventional time integration methods, the proposed approach requires much fewer iterations and thus shows considerable improvement in terms of computational efficiency. With respect to the first-order Maxwell’s curl equation-based DGTD method with weighted Laguerre polynomials, the proposed method reduces the unknowns by more than a half and gives a lighter linear system for solution. In addition, block iterative solvers and the block lower-diagonal-upper (LDU) direct solver can be applied to facilitating the solution at the subdomain level. Three numerical examples are included to demonstrate the accuracy and efficiency of the proposed method. With the weighted Laguerre polynomials, the wave equation-based DGTD method is expected to be more efficient for electrically small structure modeling. [ABSTRACT FROM AUTHOR]

Imaging hydraulic fractures is of paramount importance to subsurface resource extraction, geologic storage, and hazardous waste disposal. The use of electrically conductive proppants and current energized steel casing provides a promising approach to monitor the distribution of fractures. In this article, a borehole-to-surface system is employed to energize the steel casing and measure electric and magnetic fields on the ground. A convolutional neural network (CNN) is then trained to learn the relationship between the measured field pattern and the parameterized fracture, namely, the lateral extent and direction. To accelerate the generation of training data with limited accuracy loss, an approximate hollow casing is modeled by the impedance transition boundary condition with a tenfold magnified radius and reduced conductivity. Two training strategies are then presented with a grid search of the network’s hyperparameters. The well-trained CNN shows good generalization to unseen fracture conductivity, the true casing model, as well as white Gaussian noise. Finally, we apply the CNN to image irregular fractures and obtain reliable results even under strong noise, indicating a promising imaging technique for more complicated fractures. [ABSTRACT FROM AUTHOR]

Axonopathy is a pathological feature observed in both Alzheimer's disease (AD) patients and animal models. However, identifying the temporal and regional progression of axonopathy during AD development remains elusive. Using the fluorescence micro-optical sectioning tomography system, we acquired whole-brain datasets in the early stage of 5xFAD/Thy1-GFP-M mice. We reported that among GFP labeled axons, GFP-positive axonopathy first formed in the lateral septal nucleus, subiculum, and medial mammillary nucleus. The axonopathy further increased in most brain regions during aging. However, most of the axonopathic varicosities disappeared significantly in the medial mammillary nucleus after 8 weeks old. Continuous three-dimensional datasets showed that axonopathy in the medial mammillary nucleus was mainly located on axons from hippocampal GFP-positive neurons. Using the rabies viral tracer in combination with immunohistochemistry, we found that axons in the medial mammillary nucleus from the subiculum were susceptible to lesions that prior to the occurrence of behavioral disorders. In conclusion, we created an early-stage spatiotemporal map of axonopathy in 5xFAD/Thy1-GFP-M mice and identified specific neural circuits which are vulnerable to axon lesions in an AD mouse model. These findings underline the importance of early interventions for AD, and may contribute to the understanding of its progression and its early symptom treatment. [ABSTRACT FROM AUTHOR]

Bioelectromagnetism focuses on the study of electromagnetic fields in biological tissues from direct current (DC) to optical frequencies. It is challenging to develop an electromagnetics (EM) simulation method to cover this entire frequency band due to the electrically small/large scattering problem at extremely low/high frequencies. This paper focuses on the band from DC to microwave frequencies in bioelectromagnetism. Its main research objective is to develop a method that can overcome the low frequency breakdown problem at low frequencies (practically DC) and still stay stable at microwave frequencies. Based on the scattered field vector Helmholtz equation, the mixed finite element method (mixed FEM) is developed for the broadband electromagnetic field simulation in biological tissues. By imposing Gauss’ law as the constraint condition, the mixed FEM overcomes the low frequency breakdown problem without resorting to the quasi-static approximation and remains effective and accurate at high frequencies. Extremely low frequency and high frequency numerical results are demonstrated to verify that the mixed FEM is a stable full-wave electromagnetic field simulation method for the full-bandwidth bioelectromagnetism. [ABSTRACT FROM AUTHOR]

This letter presents a fast and memory-efficient 3-D electromagnetic solver for logging-while-drilling (LWD) tools based on the flipped total field/scattered field-based discontinuous Galerkin frequency-domain (TF/SF DGFD) method. The new method inherits the Riemann transmission condition (RTC) with surface current sources from the mixed TF/SF DGFD method to couple nonconformal meshes as well as TF/SF solvers; it then extends to the moving-tool scenarios for the LWD application with a solver flipping technology and delivers a single global matrix of dramatically reduced dimension for all source positions, which can be solved directly on a normal-memory computer. By incorporating the tetrahedral/hexahedral mixed mesh and the curved domain decomposition method, the new solver is applied to two LWD cases and about 70% of unknowns can be saved for the flipped TF/SF DGFD remeshed regions. [ABSTRACT FROM AUTHOR]

Traditional time-domain finite-element and spectral-element methods are known to suffer from the so-called low-frequency breakdown problem, where the system matrix can become ill-conditioned, and results can be unstable for electrically fine structures. In this article, a new mixed spectral-element time-domain (SETD) and finite-element time-domain (FETD) methods are proposed to overcome this low-frequency breakdown problem by constraint equations and tree-cotree splitting. Two forms of gradient matrices or the null space of the stiffness matrix of high-order basis functions are calculated to construct the constraint equations. Then, the constraint equations are directly applied in the time-stepping matrix equation by tree-cotree splitting to improve the properties of system matrices when the implicit Newmark-beta algorithm is adopted in two different forms. In the calculation of the first form of gradient matrix, the electric field is expanded by high-order edge basis functions; in the second form of gradient matrix, high-order edge basis functions associated with cotree edges and nodal basis functions defined on the free nodes are both employed to expand the electric field. Several numerical examples demonstrate that the new mixed SETD and mixed FETD methods can effectively overcome the low-frequency breakdown with high accuracy and without increasing the number of degrees of freedom over the conventional SETD and FETD methods. [ABSTRACT FROM AUTHOR]

This letter extends the discontinuous Galerkin frequency domain (DGFD)-based domain decomposition method (DDM) to model the open borehole environment accurately with a newly developed hierarchical sudoku mesh. Both the borehole and mud invasion effects can be modeled by this framework efficiently. Furthermore, deep reading measurements can be modeled conveniently by inserting arbitrarily shaped objects into the hierarchical sudoku mesh; the capability to distinguish a cavity saturated with either oil or water with different borehole-object distances are then studied for a deep reading tool in an open borehole carbonate environment. The DGFD with the hierarchical sudoku mesh shows six times faster speed than the traditional finite-element method (FEM) for the deep reading case. [ABSTRACT FROM AUTHOR]

A periodic perfectly matched layer (PML) is proposed for the spectral element method (SEM) for the first time, which not only simplifies the recognition process of a PML domain, but also saves degrees of freedom (DoFs) when squeezing its layer number to 1. An objective function to evaluate and optimize its performance has been theoretically derived. In the use of this objective function, the PML parameters are optimized under different conditions; the relationships between the PML's performance and the scaling factor profile, the source position, the basis functions’ order, and the PML layer number are studied, which can help guide the practical applications of PML in the SEM modeling. An estimation method is also introduced to facilitate the selection of the scaling factor. [ABSTRACT FROM AUTHOR]

A nonconformal hybrid finite difference time domain (FDTD)/finite element time domain (FETD) method was previously introduced, which implemented the hybridization through a buffer zone. Although this method has been demonstrated to be accurate and long-time stable, further efforts are still desirable to remove the buffer zone and to implement an implicit–explicit time integration from the perspective of practical applications. In this paper, a novel hybrid method is proposed, which not only successfully eliminates the necessity of the buffer zone without compromising the featured advantage (e.g., nonconformal mesh) but also effectively applies an implicit–explicit time integration scheme to improve the computational efficiency. Furthermore, the new method extends the hybridization to a broader level by incorporating the spectral element time domain (SETD) method based on the discontinuous Galerkin and domain decomposition techniques, resulting in a more general hybrid FDTD/SETD/FETD framework. The framework employs the explicit leapfrog time integration for the FDTD region while it employs the implicit Crank–Nicolson time integration for the FETD region. For the SETD region, either the implicit or explicit time integration can be employed, depending on the mesh sizes in it. When the implicit region becomes large, it can be further split into multiple subdomains to reduce computational complexity. Numerical examples are included to demonstrate the performance of the proposed hybrid method, which is accurate, long-time stable and more efficient than the hybrid method with a buffer zone. [ABSTRACT FROM AUTHOR]

To model the responses of electromagnetic surveys for geophysical subsurface sensing, a mixed total field/scattered field-based discontinuous Galerkin frequency-domain (TF/SF DGFD) method is proposed in this paper. The proposed TF/SF DGFD method is implemented at a subdomain level based on the domain decomposition technique. Different subdomains can employ either the TF DGFD framework or the SF DGFD framework, which are then coupled through the Riemann transmission condition. To balance the computation efficiency and accuracy for practical applications, the proposed method prefers to using the SF DGFD framework for subdomains with sources and using the TF DGFD framework for the remaining subdomains. At the interfaces between total field and scattered field subdomains, the Riemann transmission condition is slightly modified by incorporating the background fields due to the physically imposed sources in the background media. In this way, the proposed method only requires surface integrals of the background fields as extra overhead instead of elementwise integration of the scattering objects for the purely scattered field-based method, which can improve the computational efficiency. Also, it is more accurate than the purely TF DGFD method given the same mesh. Numerical examples are studied to examine the performance of the proposed method, which is proven to have better accuracy than the TF DGFD method. The TF/SF DGFD method will facilitate modeling of electromagnetic surveys under complicated geophysical environments for subsurface sensing. [ABSTRACT FROM AUTHOR]

An unsplit-field and accurate Crank–Nicolson cycle-sweep-uniform finite-difference time-domain (CNCSU-FDTD) method based on the complex-frequency-shifted perfectly matched layer (CFS-PML) is proposed. It is applied to 3-D low-frequency subsurface electromagnetic sensing problems. The presented CNCSU-FDTD takes advantage of both CFS-PML and unconditionally stable CN method so that it can attenuate evanescent waves, eliminate late-time reflections, and overcome the stability limits of the FDTD method. The time step intervals in CNCSU-FDTD can be 1000 times larger than that in the regular FDTD for the low-frequency sensing centered at 25 Hz while remaining accurate. Several 3-D numerical examples in the airborne transient electromagnetics system have been demonstrated to validate the proposed method. The CFS-PML-based CNCSU-FDTD method not only attains good accuracy but also saves several dozen times of CPU time as compared with the regular FDTD method. [ABSTRACT FROM AUTHOR]

The second-order wave equation-based discontinuous Galerkin time-domain (DGTD) methods typically employ the first-order absorbing boundary condition for modeling open problems. To improve the modeling accuracy, this paper proposes a novel coupling algorithm of the well-posed perfectly matched layer (PML) for wave equation-based DGTD methods. Based on the domain decomposition technique, the proposed coupling algorithm divides the computational domain into two regions, that is, the physical and PML regions, whose meshes can be nonconformal with each other. Instead of introducing time convolution terms, the new coupling scheme is implemented through employing different DGTD frameworks for the two regions. Specifically, the physical region employs the wave equation-based DGTD framework, while the PML region employs the first-order Maxwell’s curl equations-based DGTD framework. To facilitate modeling of electrically small problems, the implicit Newmark-beta time integration is used for the physical region. To conveniently couple with the physical region, the implicit Crank–Nicolson algorithm is used for the PML region. Numerical results are shown to examine the accuracy and efficiency of the proposed coupling algorithm for modeling electrically small problems. [ABSTRACT FROM AUTHOR]

To facilitate the detection of hydraulic fractures by electromagnetic survey, a discontinuous Galerkin frequency-domain (DGFD) method is introduced in this paper to efficiently model the fracture responses under complicated geophysical environments. In the proposed DGFD method, the computational domain can be split into multiple subdomains with nonconformal meshes. The Riemann solver (upwind flux) is introduced to evaluate the numerical flux. The impedance transition boundary condition (ITBC) is employed to facilitate fracture modeling by approximating fractures as surfaces. Numerical results show that the ITBC works well for different fracture conductivities, dipping angles, operation frequencies, as well as different sources. For both small- and large-scale fractures, it also shows good agreement with the references. The responses of fractures increase as their conductivities become larger. Large dipping angles can cause spikes on the responses in a borehole. For a magnetic source, higher operation frequencies can enhance the signal level, while for an electric source, the sensitivity to frequency is small. When no borehole is considered, the responses due to an electric source are in general larger than those due to a magnetic one. However, when a borehole with conductive mud is included, the responses can be reversed for the electric and magnetic sources. For multiple fractures outside a cased borehole, the signal level of an electric source is significantly reduced, while that of a magnetic source remains at a similar level compared with the scenario without a casing. With the proposed technique, multiscale modeling of hydraulic fractures in complicated geophysical environments becomes possible. [ABSTRACT FROM PUBLISHER]

A new 3-D domain decomposition based hybrid finite-difference time-domain (FDTD)/finite-element time-domain (FETD) method is introduced to facilitate electromagnetic modeling by exploiting both the computational efficiency of FDTD and the meshing flexibility of FETD. The proposed hybrid method allows the FETD mesh and the FDTD grid to be nonconformal based on domain decomposition technique. It implements the hybridization with a buffer zone, which functions as a transition region between FDTD and FETD. The buffer zone helps the proposed hybrid method obviate the interpolation approach for field coupling of the nonconformal mesh and hence overcome the late-time instability issue. The discontinuous Galerkin method is utilized to couple different regions, thus improving the coupling accuracy compared with that using the Dirichlet boundary condition. Moreover, the hybrid method allows further division of the FETD region into multiple subdomains when the degrees of freedom in this region are large. For temporal discretization, a global leapfrog time integration scheme is implemented to sequentially update the fields in the FDTD, buffer, and FETD regions. The numerical results are shown to demonstrate the meshing flexibility and computational efficiency of the proposed hybrid method inherited from FETD and FDTD methods. [ABSTRACT FROM PUBLISHER]

We present an efficient nonconformal-mesh discontinuous Galerkin (DG) method for elastic wave propagation in viscous media. To include the attenuation and dispersion due to the quality factor in time domain, several sets of auxiliary ordinary differential equations (AODEs) are added. Unlike the conventional auxiliary partial differential equation-based algorithm, this new method is highly parallel with its lossless counterpart, thus requiring much less time and storage consumption. Another superior property of the AODE-based DG method is that a novel exact Riemann solver can be derived, which allows heterogeneous viscoelastic coupling, in addition to accurate coupling with purely elastic media and fluid. Furthermore, thanks to the nonconformal-mesh technique, adaptive hp-refinement and flexible memory allocation for the auxiliary variables are achieved. Numerical results demonstrate the efficiency and accuracy of our method. [ABSTRACT FROM PUBLISHER]

A second-order wave equation-based implicit discontinuous Galerkin time-domain (DGTD) method is proposed to efficiently model electrically small problems. The proposed method employs the second-order wave equation for electric field (or magnetic field) as the governing equation of the DG formulation, instead of the first-order Maxwell’s curl equations. A modified version of the Riemann solver (upwind flux) is introduced to evaluate the numerical flux resulting from the weak form of the wave equation. Compared with previous first-order Maxwell’s curl equation-based implicit DGTD methods, which typically solve all electric and magnetic field unknowns for each subdomain, the proposed method only needs to solve for the electric field unknowns plus the surface magnetic field unknowns at subdomain interfaces. This reduces the dimensions of the resultant linear system and thus allows for modeling larger problems. Furthermore, unlike element-based DGTD methods, the proposed method is subdomain-based. The computational region is divided into multiple subdomains based on the domain-decomposition method, and each subdomain may contain multiple elements. Different element types and orders of basis functions can be employed in different subdomains to exploit the geometry property of the model. A nonconformal mesh is allowed between different subdomains to increase meshing flexibility. The Newmark-beta time-integration scheme is used for implicit temporal discretization, and fast direct linear solvers, such as the lower-diagonal-upper decomposition algorithm, are employed to accelerate time integration when all the subdomains are in a sequential order. Numerical results show that the proposed method is more efficient in terms of CPU time, and also saves memory with respect to the previous implicit DGTD method when modeling electrically small problems. [ABSTRACT FROM PUBLISHER]

We present a discontinuous Galerkin pseudospectral time-domain (DG-PSTD) algorithm to solve elastic-/acoustic-wave propagation problems. The developed DG-PSTD algorithm combines the merits of flexibility from a finite-element method and spectral accuracy and efficiency from a high-order pseudospectral method, while having a flavor closer to a finite-volume method. This numerical approach not only uses structured/unstructured conformal meshes but also handles nonconformal meshes (h-adaptivity) with nonuniform approximation orders (p-adaptivity) in different regions, thus leading to high flexibility and efficiency for heterogeneous multiscale problems. To implement the discontinuous Galerkin algorithm, a concise but more general heterogeneous Riemann solver is provided to effectively and accurately resolve the coupling of multiple subdomains for both elastic–elastic/fluid–fluid and fluid–solid coupling. Finally, numerical results demonstrate the flexibility, high accuracy, and efficiency of our method for elastic-/acoustic-wave simulation. [ABSTRACT FROM PUBLISHER]

This communication presents an EB scheme subdomainlevel discontinuous Galerkin time domain (DGTD) method for multiscale simulations. It is an extension of the previous subdomain-level DGTD research by combining the degree of freedom efficiency of spectral element time domain method and the mesh flexibility of the finite element time domain method. Thus, the multiscale problems can be solved efficiently by separating the geometrically fine and coarse parts and meshing them with hexahedrons and tetrahedrons, respectively, via a nonconformal mesh. The implicit–explicit Runge-Kutta method is applied to the EB scheme DGTD method to obtain an efficient time integration approach. [ABSTRACT FROM AUTHOR]

The discontinuous Galerkin finite-element time-domain (DG-FETD) method with implicit time integration has an advantage in modeling electrically fine-scale electromagnetic problems. Based on domain decomposition methods, it avoids the direct inversion of a large system matrix as in the conventional FETD method; by employing implicit time integration, it obviates an extremely small time-step interval to maintain stability as in explicit schemes. Based on curl-conforming basis functions for the electric field intensity E field and divergence-conforming basis functions for the magnetic flux density B field, a new noniterative implicit time-stepping scheme is proposed to efficiently solve sequentially ordered systems for electrically fine-scale problems. Compared with the previous EH-based scheme, the new scheme introduces fewer unknowns and, thereby, results in a smaller matrix system. Based on the Crank–Nicholson algorithm for time integration, the matrix system is in a block tridiagonal form. Then, through separating the surface unknowns from the volume unknowns, a block lower-diagonal-upper (LDU) decomposition is implemented, reducing the computational complexity of the original system. The adaptivity of parallel computing in subdomain level during preprocessing further helps shorten the computation time. Numerical results confirm that the proposed LDU scheme presents improved efficiency in terms of memory and CPU time while retaining the same accuracy, compared with the previous implicit block-Thomas method. With respect to the explicit Runge–Kutta method and the standard FDTD, it also shows an advantage in CPU time. The proposed scheme will help improve the performance of DG-FETD in modeling electrically fine-scale problems. [ABSTRACT FROM AUTHOR]

A new discontinuous Galerkin spectral element time-domain (DG-SETD) method for Maxwell’s equations based on the field variables \mathbfE and \mathbfB is proposed to analyze three-dimensional (3-D) transient electromagnetic phenomena. Compared to the previous SETD method based on the field variables \mathbfE and \mathbfH (the \mathbfEH scheme), in which different orders of interpolation polynomials for electric and magnetic field intensities are required, the newly proposed method can eliminate spurious modes using basis functions with the same order interpolation for electric field intensity and magnetic flux density (the \mathbfEB scheme). Consequently, it can reduce the number of unknowns and computation load. Domain decomposition for the \mathbfEB scheme SETD method is completed via the DG method. In addition, the \mathbfEB scheme SETD method is extended to the well-posed time-domain perfectly matched layer (PML) to truncate the computation domain when solving open-region problems. The effectiveness and advantages of the new DG-SETD method are validated by eigenvalue analysis and numerical results. [ABSTRACT FROM PUBLISHER]

Individual cells play essential roles in the biological processes of the brain. The number of neurons changes during both normal development and disease progression. High-resolution imaging has made it possible to directly count cells. However, the automatic and precise segmentation of touching cells continues to be a major challenge for massive and highly complex datasets. Thus, an integrative cut (iCut) algorithm, which combines information regarding spatial location and intervening and concave contours with the established normalized cut, has been developed. iCut involves two key steps: (1) a weighting matrix is first constructed with the abovementioned information regarding the touching cells and (2) a normalized cut algorithm that uses the weighting matrix is implemented to separate the touching cells into isolated cells. This novel algorithm was evaluated using two types of data: the open SIMCEP benchmark dataset and our micro-optical imaging dataset from a Nissl-stained mouse brain. It has achieved a promising recall/precision of 91.2 ± 2.1%/94.1 ± 1.8% and 86.8 ± 4.1%/87.5 ± 5.7%, respectively, for the two datasets. As quantified using the harmonic mean of recall and precision, the accuracy of iCut is higher than that of some state-of-the-art algorithms. The better performance of this fully automated algorithm can benefit studies of brain cytoarchitecture. [ABSTRACT FROM AUTHOR]