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BackgroundThis study analyzed the imaging data of patients retrospectively to understand the risk of cannulated screw fixation for femoral neck fracture. At the same time, we try to use intraoperative frog lateral view to avoid the risk of screw cutout.MethodThe imaging data of patients with femoral neck fracture treated with cannulated screws between January 2015 and September 2016 was reviewed, and patients with screw cutout or suspicious cutout were found. The postoperative imaging data of 41 patients who attempted to use frog lateral view during the operation was reviewed,and patients with screw cutout or suspicious cutout were found.ResultAmong the 479 patients, only 72 patients underwent CT examination after the operation, and 18 of the 72 patients had obvious screw cutout. Screw cutout cases accounted for 3.8% of the total number of cases and 25% of the patients undergoing CT examination. Of the 41 patients who received intraoperative frog lateral view, only 2 cases were cutout from the neck, and no cases were cutout from the femoral head.ConclusionThe anterior upper part of the femoral head is a high-risk area cutout by cannulated screws. Postoperative CT is very necessary and can accurately detect the screw cutout, for the long-term prognosis of the implications. The application of frog lateral view in the operation of femoral neck fracture can effectively avoid the risk of cannulated screw cutout.

Giant panda (panda) has lived on earth for at least eight million years and is known as the living fossil. It is also a vulnerable species which requires urgent protection. It is essential to conduct population survey collecting information of their population, density, age structure, and gender ratio so as to design protection schemes and measure their effectiveness. However, it is challenging to accurately and timely obtain gender ratio of pandas because their pelage lacks distinguishable gender patterns and panda is sparsely distributed population in large habitats. All current approaches rely heavily on manual collection of samples in the wild, which are time consuming, costly, or even dangerous. With the widely deployed camera traps, if the gender of pandas can be determined from images, it is possible to monitor panda gender ratio in different regions in real-time. However, no such study was done. In this paper, a deep learning method is developed to study the distinctiveness of panda face for gender classification, in which the largest panda image dataset with 6,549 panda face images collected from 100 male and 121 female pandas is established. The experimental results show that panda faces contain some gender information, although they look very similar to human vision.

Human mobility forecasting in a city is of utmost importance to transportation and public safety, but with the process of urbanization and the generation of big data, intensive computing and determination of mobility pattern have become challenging. This study focuses on how to improve the accuracy and efficiency of predicting citywide human mobility via a simpler solution. A spatio-temporal mobility event prediction framework based on a single fully-convolutional residual network (STAR) is proposed. STAR is a highly simple, general and effective method for learning a single tensor representing the mobility event. Residual learning is utilized for training the deep network to derive the detailed result for scenarios of citywide prediction. Extensive benchmark evaluation results on real-world data demonstrate that STAR outperforms state-of-the-art approaches in single- and multi-step prediction while utilizing fewer parameters and achieving higher efficiency., Accepted by MDM 2019

In this paper, we advance an algorithm of numerical modeling for responses of multicomponent electromagnetic well logging in a deviated and layered anisotropic formation through the 3-D finite difference time domain approach (FDTD). First, we use a Yee's staggered grid and linear interpolation formula to discretize the Maxwell equation in the time domain in an anisotropic medium and determine the non-defined components of electromagnetic (EM) field in the staggered grid in order to obtain the time recursive equation of the EM field on all staggered grids in an arbitrary anisotropic media. At the same time, area weighted average and transformation matrix are utilized to calculate the effective conductive tensors on the grids, and an absorbing boundary condition is executed to reduce the reflection of outer-boundary on the base of uniaxial anisotropic perfectly matched layer (UPML). Then, we apply three mutually orthogonal transmitter coils with a singlefrequency sinusoidal current to excite EM fields in the time domain and extract the amplitude and phase of EM from the EM field through a special two-equation and two-unknown (2E2U) approach to obtain the responses of multicomponent EM propagation logging tool. Finally, by numerical results we validate the algorithm and examine systematically the influence of changes in bed thickness, formation dipping angle and radius of invasion zones on responses of the tool.

In this paper, we advance a fast iterative inversion algorithm of multicomponent induction well-logging (MCIL) datum to simultaneously reconstruct a total model vector in a deviated well in the horizontally stratified transversally isotropic (TI) formation (TI medium) with the case-neglecting borehole. The model vector consists of the horizontal and vertical conductivities, the interface depth of each bed, and a borehole dipping angle. Because an electromagnetic field emitted by a horizontal magnetic dipole is no longer axially symmetrical, we first decompose the horizontal magnetic dipole located at borehole axis as the sum of two harmonics only so that the computation of MCIL responses can be entirely transformed into three axially symmetrical problems. Therefore, we solve them through the numerical mode matching method and obtain the semianalytic (SA) solution of an EM field in an arbitrary bed. Then, based on the perturbation principle and spatial distribution of formation conductivity related to the model vector, we set up an efficient SA algorithm of Frechet derivatives of the MCIL response with respect to the model vector. Then we extract an initial model from synthetic logs for the inversion through a special blocking technique. Finally, we give an iterative process to simultaneously reconstruct all model parameters from the logs through a combination of a normalization and singular value decomposition technique. Numerical tests validate the algorithms.

The expression and algorithm of the Born approximation of dual-laterolog (DLL) are different from nonfocusing resistivity tools because the currents and potentials on the surfaces of the electrodes must be satisfied with the special focusing conditions. The Born approximation is described by a linear integral equation about the changes in current density, bucking currents, and potentials on the surfaces of all the electrodes, caused by small perturbations in the formation conductivity. Using the complex forward modeling of DLL, and the semi-analytic solution of the Green's function, we advance the fast algorithm of the Frechet derivative matrix containing the partial derivatives of both the apparent resistivities and bucking currents with respect to all components of the model vector. A normalization approach is used to transform the matrix into a dimensionless matrix. We then develop a multiparameter iterative inversion technique to simultaneously reconstruct all model parameters. Furthermore, we analyze the influence of both noises in data and errors of some model parameters on the inversion solution and give a method to choose the regularization factors. Finally, numerical result tests show the characteristics of the normalized Frechet matrix, the influence of errors of both bed thickness and flushed zone resistivity, etc, on the inversion solution when they are fixed, and the great improvement of the inversion quality when all model parameters are simultaneously reconstructed from both the apparent resistivities and bucking currents.

A microspherically focused log is a focused microresistivity device used for evaluation of the electrical property of the subsurface rock formation for oil and gas exploration. The electrodes are mounted on a flexible rubber pad that is applied against the borehole wall to be in close proximity to the formation. Unlike other nonpad-focused electrode tools that are centered in the borehole such as Dual-Laterolog, the modeling of the microspherically focused log is much more complex and requires three-dimensional (3-D) code in general because the electric field is no longer axially symmetric. However, in a horizontally layered medium, the axial symmetry of the earth formation makes the problem two-and-a-half-dimensional (2.5-D), which is much simpler. In this paper, the authors apply the semi-analytic method to tackle this 2.5-D problem and establish a fast-modeling algorithm. First, they expand the Green's function as a Fourier series in order to transform the 2.5-D problem into a sequence of the axially symmetric (2-D) problems. The semi-analytic method is used to obtain the expression of the Green's function. Applying the focusing conditions of the tool and the solution of the Green's function, we then establish the boundary integral equation with respect to the current density, currents, and potentials on the electrode surfaces, and study its numerical solutions. Then, they compare results computed from the semi-analytical method with those from the finite element method (FEM) to verify its accuracy. Finally, they study the response characteristics of the tool in several different environments by the semi-analytical method.