Search

From the perspective of spatial interaction, the impact of the modern service industry’s agglomeration on today’s increasingly connected cities is worth studying. This study uses a spatial econometric model to test the development trends and factors influencing the modern service industry’s agglomeration in the Yangtze River Delta city group. The results show that the industry has the highest agglomeration in leasing and business and the lowest in education. The overall concentration of the industry is generally low, implying a more fragmented distribution. Moreover, the agglomeration has a significant positive spatial correlation with economic development, knowledge intensity, and city size. However, it has a negative correlation with information technology level and transportation infrastructure, inconsistent with existing research. This study argues that the development of the information technology level and transportation infrastructure in a city could lead to the ‘virtual agglomeration’ of the modern service industry and gradual decentralisation in geographical distribution. This is a new paradox that city groups may face when improving their infrastructure and developing modern services. This study uses the spatial interaction perspective to propose policy recommendations for promoting the modern service industry’s agglomeration and coordinated regional development.

Extracting elevation information from single aerial images is an important and challenging task in photogrammetry and remote sensing. The difficulty lies in the ambiguity and ill-condition of the 2-D–3-D projection. As neural networks show advantages in solving ill-posed problems, fully convolutional neural networks (FCNs) have been applied to this task and have achieved worthwhile results. However, the previous works simply focus on the application of the neural network structures originally applied to monocular depth estimations or semantic segmentations to single-image elevation estimations. This procedure ignores the task-specific weak correlation problem between the elevation systems of training labels and outputs and the one between heights of adjacent pixels. To address these problems, we use the FCN to generate height differences between adjacent pixels in specific orientations (i.e., oriented elevation gradients), instead of directly generating the elevation values. Subsequently, the elevation gradients in the two orients of XY are combined to form a huge relationship chain, and the relative elevation of each pixel is calculated using the maximum likelihood method. Finally, a new surface-based soft alignment method is used to establish the correlation between the elevation systems of training labels and predicted outputs robustly. The quantitative evaluation on the International Society for Photogrammetry and Remote Sensing (ISPRS) Potsdam data set reveals a significant improvement of the bare FCN. The visual contrast evaluation indicates that the soft-aligned gradient-chaining network can retain more surface features, and its outputs are more reasonable and visually pleasing than the bare FCN.

Background subtraction is commonly employed in foreground object detection in urban traffic scenes. Most of the current color or texture feature-based background subtraction models are easily contaminated by sudden and gradual illumination variations in urban traffic scenes. To resolve this deficiency, an adaptive local median texture feature, which extracts the adaptive distance threshold employing the median information in a predefined local region of a pixel and Weber's law, is introduced. In addition, a sample consensus-based model that evolved from portable visual background extractor is proposed using an adaptive local median texture feature. Then, the foreground is labeled by comparing the input video frames feature with the model. Moreover, to adapt the dynamic background, the random update scheme is used to update the model. Extensive experimental results on the public Change Detection data set of 2014 (CDnet2014) and the real-world urban traffic videos demonstrate that our background subtraction method is superior to the other state-of-the-art texture-feature-based methods. The qualitative and quantitative results show the encouraging efficiency of the proposed technique to deal with sudden and gradual illumination variations in real-world urban traffic scenes.

In order to better extract the infrared target information of images in dark scenes and retain more background texture details, an infrared and visible light image fusion algorithm based on fuzzy C-means clustering (FCM) and guided filter is proposed. Firstly, the target information is extracted from the source infrared image by FCM, and the target area and background area of the infrared image are obtained. Then, the target region coefficients and background region coefficients are decomposed into their respective high-frequency and low-frequency subband coefficients by using non-subsampled shearlet transform (NSST). Then, according to the different characteristics of different regions, different fusion strategies are adopted. In order to retain more target information, low-frequency subband coefficients of infrared image target area are selected as fusion coefficients of low-frequency target area, and high-frequency subband coefficients of infrared image target area are selected as fusion coefficients of high-frequency target area. In order to keep more texture details, the method of maximizing low-frequency subband image coefficients and information entropy is adopted in the fusion of low-frequency background region. The method of guided filter combined with dual-channel spiking cortical model (DCSCM) is used in the fusion of low-frequency background region. Finally, the final fusion image is obtained by NSST inverse transform. Simulation results show that compared with the existing algorithms, the fusion image obtained by this algorithm has prominent infrared target in subjective vision, clear background texture details and high hierarchy. In objective evaluation, the indexes are better than other algorithms as a whole.

Three-dimensional (3D) building façade model reconstruction is of great significance in urban applications and real-world visualization. This paper presents a newly developed method for automatically generating a 3D regular building façade model from the photogrammetric mesh model. To this end, the contour is tracked on irregular triangulation, and then the local contour tree method based on the topological relationship is employed to represent the topological structure of the photogrammetric mesh model. Subsequently, the segmented contour groups are found by analyzing the topological relationship of the contours, and the original mesh model is divided into various components from bottom to top through the iteration process. After that, each component is iteratively and robustly abstracted into cuboids. Finally, the parameters of each cuboid are adjusted to be close to the original mesh model, and a lightweight polygonal mesh model is taken from the adjusted cuboid. Typical buildings and a whole scene of photogrammetric mesh models are exploited to assess the proposed method quantitatively and qualitatively. The obtained results reveal that the proposed method can derive a regular façade model from a photogrammetric mesh model with a certain accuracy.

Estimating the potential achievable solar energy in urban buildings is significantly important for the long-term planning and development of environmental protection strategies. Nevertheless, conventional methods based on LiDAR data are often costly and require more than one platform to obtain complete building surface information. The development of oblique photogrammetry technology enables fast and accurate acquiring of the 3D information of the surface. In this paper, we propose an efficient method to estimate the potential achievable solar energy of building surfaces based on photogrammetric mesh models. In this method, we use photogrammetric mesh models as the input data and then propose a hierarchical algorithm for shadow analysis. Combined with the solar radiation model, we then obtain the potential achievable solar energy of the building surface. We further investigate the performance of the proposed method and it is shown that this method outperforms the multi-source LiDAR data.

Atypical meningioma (AM) tends to be tumor with high rates of recurrence and mortality. In this retrospective study, 131 recurrent AM patients underwent AM surgery in Beijing Tiantan Hospital between January 2008 and December 2015. Of the 131 cases collected, 61 were male (46.6%), and 70 (53.4%) were female. 53 (40.5%) patients chose observation instead of therapy, 53 (40.5%) received repeat surgery and 25 patients (19.0%) received gamma knife surgery (GKS). The median overall survival (OS) was 34.6 months and actuarial OS of patients at 1, 3 and 5 years were 88.6%, 48.8%, 36.0%, respectively. In the treatment group including 78 patients with surgery and GKS group, a tumor progression happened to 35 patients (44.9%). The median duration of progression-free survival (PFS) was 34.5 months and the median OS was 61.7 months. Second PFS at 1, 3 and 5 years were 84.1%, 46.5% and 24.0%, respectively; the corresponding OS was 98.5%, 75.1%, 57.9%, respectively. Multivariate analysis revealed treatment strategy was the only independent factor (P 0.001). In the treatment group, non-peritumoral edema (P = 0.002), preoperative KPS (per 10 scores increase) (P 0.001) and GKS (P = 0.042) was related to better OS. Short interval (24 months) from symptoms onset to intervention was related to better PFS (P = 0.004) in univariate analysis. This retrospective study presents the largest cohort of recurrent AM patients, surgical treatment is recommended in patients with tumor recurrence, and GKS is considered a promising therapeutic option of recurrence atypical meningioma.

3D printing is a promising technology in construction industry. Unlike conventional construction process, 3D printing buildings are extruded by a nozzle layer-over-layer without the requirement of formwork. This paper investigates the rheological and harden properties of the high-thixotropy 3D printing concrete. Flowability, rheological property (viscosity, yield stress, thixotropy) and open time are considered as critical wet properties to control the printable property (pumpability, extrudability and buildability) of such concrete material. Five different mixtures are systematically investigated to obtain the optimum mix and then it’s used to study the harden property, such as anisotropy (compression and flexural), elastic modulus and drying shrinkage. At last, a large-scale components-bus station preliminarily was prepared by using this technology.

This A Raman fiber amplifier with multi-pump and $\mathrm{G}\mathrm{e}\mathrm{O}_{2}$ doped microstructure fiber is designed to fulfil the requirements of 6G transmission system for optical communication network which can solve the problems of narrow band width, low output gain and uneven output gain of Raman fiber amplifier suitable for 6G system. In theory, using the fourth-order Runge-Kutta method is to solve the classical Raman coupled wave differential equations. In the structure, two pairs of pump beams with the same wavelength are combined to reduce the number of pumps and simplify the structure. At the same time, the method of cascading two sections of microstructured fiber is used to realize the signal gain amplification before and after compensation at the output end of the Raman amplifier. Finally, the average gain of the amplifier is up to 35. 72dB in the bandwidth of 100nm, and the gain fluctuation is less than ± 0.43dB.

Displacement measurement is a major concept in the daily maintenance and failure assessment of engineering structures. Vision-based systems offer a cost-effective, simple alternative for non-contact displacement measurement. However, its measurement is challenging because of the errors induced by camera instability (thermal effects on camera sensor and camera motion). Researchers have tried to compensate for the errors induced by camera instability in displacement calculation methods by placing fixed objects in the background. However, remotely-located objects in the background cannot fully allow for camera rotations. Supplementary sensors can be employed to measure the camera motion in six degrees of freedom (6-DOF), although this method is unable to compensate for thermal effects on camera sensor. This paper presents a dual-view system that can compensate for the camera instability by using a camera, a beam splitter, a convex lens, and a photomask. The beam splitter and convex lens enable the camera to capture dual-view data and measure the instability of the system by using the photomask. In laboratory tests, the Root Mean Squared Error (RMSE) of the displacements measured by the proposed system did not exceed 0.05 mm under the conditions of drastic temperature variations and strong winds. Outdoor tests showed that the reflection of sunlight on the objects will seriously affect the practical performance of the proposed system, and a robust localization method for the photomask is necessary. The measurement scheme design for the track structure vibration of high-speed railways proved the acceptable engineering practicability and installation flexibility of the dual-view system.

Detecting changes between the existing building basemaps and newly acquired high spatial resolution remotely sensed (HRS) images is a time-consuming task. This is mainly because of the data labeling and poor performance of hand-crafted features. In this paper, for efficient feature extraction, we propose a fully convolutional feature extractor that is reconstructed from the deep convolutional neural network (DCNN) and pre-trained on the Pascal VOC dataset. Our proposed method extract pixel-wise features, and choose salient features based on a random forest (RF) algorithm using the existing basemaps. A data cleaning method through cross-validation and label-uncertainty estimation is also proposed to select potential correct labels and use them for training an RF classifier to extract the building from new HRS images. The pixel-wise initial classification results are refined based on a superpixel-based graph cuts algorithm and compared to the existing building basemaps to obtain the change map. Experiments with two simulated and three real datasets confirm the effectiveness of our proposed method and indicate high accuracy and low false alarm rate.

ICT industry is a knowledge-intensive industry, the development of which is highly dependent on patented technology and the competition is becoming increasingly fierce. The paper analyzes the patent of Chinese ICT Industry from 1985 to 2019 on the perspective of patent information. Patent analysis is carried out from the aspects of annual trend of patent application, main patentee, technology life cycle, important regional distribution, IPCs and patent legal status, in order to grasp the main and the most welcome area of the technology. The purpose of this paper is to provide the evidence of patent information for promoting the technology innovation of ICT Industry in China and provide a reference for the formulation of policies related to technology innovation in ICT industry.

Objectives Anaplastic meningiomas (AMs)tend to have a higher local recurrence rate and metastasize. but few studies have reported on the prognosis and management of patients with AM, this study aimed to increase the understanding of the prognosis, management and history of AM. Patients and Methods All patients (n = 56) underwent surgeries in our hospital between December 2008 and January 2016. Postoperative pathology reports confirmed the diagnosis of AM. Prognostic factors and the management were analysed in this study. AM was then divided into two groups. One group was primary AM, the other group was secondary AM. Results Of all the 56 AM patients, 31 were male and 25 were female (male to female ratio of 1.24:1). The 1-, 3-, and 5-year progression-free survival (PFS) rates were 78.6%, 41.1% and 29.7%, respectively, and the corresponding overall survival (OS) rates were 82.1%, 50.1% and 45.0%, respectively. Homogeneous contrast might be a potential better prognostic factor for PFS (HR = 1.824, P = 0.083). Treatment with postoperative radiotherapy (PRT) was significantly associated with longer PFS (HR = 0.390, P = 0.007) and OS (HR = 0.376, P = 0.008) according to univariate analysis. Gross-total resection (GTR) was a favourable factor for PFS (HR = 2.059, P = 0.035) and OS (HR = 2.802, P = 0.004). Conclusion Achieving GTR is a favourable treatment strategy for patients with AM in our study and patients receiving PRT after resection is essential.

3D printing technique is an opportunity for the development of architecture industry altered by the emergence of 3D printing concrete ink that shows unconventional characteristics mainly originated from its geometric design. In this paper, a novel 3D printing concrete ink that has good fluidity during movement and satisfying standing behavior at static state due to the structural rebuilding of cement paste advanced by the addition of nano clay (NC) and silica fume (SF) was specially designed to be extruded through a nozzle to print layer-over-layer components for an innovative additive manufacturing process. The buildability, rheological properties (viscosity, yield stress and thixotropy), workability, green strength, open time and hydration heat of the fresh 3D printing concrete were systematically investigated. Results indicated that the buildability of this concrete with a small quantity of NC or SF were increased by 150% and 117%, respectively, and remarkably enhances the thixotropy and green strength. The double-doped NC and SF optimize the buildability.

Objective Rhabdoid meningioma (RM) and papillary meningioma (PM) are rare variants of World Health Organization grade III meningiomas. In this study, we presented a series of 23 cases from our institution to investigate adverse factors of and appropriate treatment for RM and PM. Methods Clinical data from 23 cases of PM and RM between January 2011 and December 2015 were retrospectively reviewed. Results The median follow-up was 38.0 months for World Health Organization grade III meningiomas. The mean progression-free survival (PFS) was 37.6 months, with 1-year, 3-year, and 5-year PFS of 78.3%, 50.8%, and 43.6%, respectively. The mean overall survival (OS) was 48.8 months, with 1-year, 3-year, and 5-year OS of 95.7%, 82.6%, and 44.0%, respectively. Univariate analysis showed that a ki-67 proliferation index >20% (hazard ratio [HR], 4.190; 95% confidence interval [CI], 1.033–17.001; P = 0.045) and PM (HR, 3.375; 95% CI, 0.998–11.408; P = 0.005) were related to worse PFS. Patients administered postoperative radiotherapy (PRT) after surgery had longer OS than did patients who did not receive PRT (median, 60.7 vs. 35.1 months; P = 0.029). Multivariate analysis showed that PRT was an independent factor for PFS (HR, 0.147; 95% CI, 0.033–0.657; P = 0.012) and OS (HR, 0.130; 95% CI, 0.025–0.691; P = 0.017) and that RM was an independent factor for PFS (HR, 7.312; 95% CI, 1.587–33.688; P = 0.011) and OS (HR, 6.447; 95% CI, 1.310–31.740; P = 0.022). Conclusions We recommended adjuvant radiation regardless of the extent of resection. Individuals with PM or RM were at increased risk of recurrence and death; appropriate treatment for these patients should be further studied, and close follow-up is needed.

Targeting at a reliable image matching of multiple remote sensing images for the generation of digital surface models, this paper presents a geometric-constrained multi-view image matching method, based on an energy minimization framework. By employing a geometrical constraint, the cost value of the energy function was calculated from multiple images, and the cost value was aggregated in an image space using a semi-global optimization approach. A homography transform parameter calculation method is proposed for fast calculation of projection pixel on each image when calculating cost values. It is based on the known interior orientation parameters, exterior orientation parameters, and a given elevation value. For an efficient and reliable processing of multiple remote sensing images, the proposed matching method was performed via a coarse-to-fine strategy through image pyramid. Three sets of airborne remote sensing images were used to evaluate the performance of the proposed method. Results reveal that the multi-view image matching can improve matching reliability. Moreover, the experimental results show that the proposed method performs better than traditional methods.

// Yiqiang Zhou 1, 2 , Guishan Jin 1, 3 , Ruifang Mi 1, 3 , Junwen Zhang 1, 3 , Jin Zhang 1, 2 , Hengzhou Xu 1, 2 , Sen Cheng 1, 2 , Yunsheng Zhang 1, 2 , Wenjie Song 1, 2 , Fusheng Liu 1, 2, 3 1 Brain Tumor Research Center, Beijing Neurosurgical Institute, Beijing 100050, P.R. China 2 Department of Neurosurgery, Beijing Tiantan Hospital Affiliated to Capital Medical University, Beijing 100050, P.R. China 3 Beijing Laboratory of Biomedical Materials, Beijing 100050, P.R. China Correspondence to: Fusheng Liu, email: liufushengs@hotmail.com Keywords: glioma stem cells, neovascularization, transdifferentiation, P4HA1 Received: November 22, 2016 Accepted: February 28, 2017 Published: March 16, 2017 ABSTRACT Emerging evidence has demonstrated transdifferentiation process of glioma stem cells (GSCs) into endothelial cells (ECs) in glioma neovascularization. Herein, we focused on screening for genes that were differentially expressed in the transdifferentiation process using microarray analysis. Bioinformatics analysis revealed differential expression of the prolyl 4-hydroxylase subunit alpha-1 (P4HA1) gene. We determined that P4HA1 expression was correlated with histological grade, the level of Ki67 and microvessel density (MVD) in human glioma specimens. Knockdown of P4HA1 inhibited the proliferation, migration and tube formation of GSCs in vitro . In vivo studies revealed that the downregulation of P4HA1 inhibited intracranial tumor growth, prolonged the overall survival time of xenograft mice and suppressed the neovascularization in brain tumors. Moreover, P4HA1 regulates the expression of vascular endothelial growth factor A (VEGF-A), especially an anti-angiogenic isoform-VEGF165b. Additionally, knockdown of P4HA1 inhibited the synthesis of collagen IV, and hence disrupted the structures of vascular basement membranes (BMs) in gliomas. Our study indicates that P4HA1 plays a pivotal role in the process of GSC-EC transdifferentiation and the structural formation of vascular BMs.

Extrusion-based 3D printing is the manufacturing technology which shapes the material layer by layer. This deposition mode results in a weak interface between layers, which seriously deteriorates the mechanical performance of printed objects. It is well-known that bonding strength of layer interface is fundamentally controlled by the deposition process (time interval, interfacial humidity, etc.) and properties of printing material. In this paper, XCT/SEM image processing was introduced to analyze interfacial pore structure at different scales, while nano-indentation was utilized for characterizing the interface micromechanical performance. The results indicated that layer interface generates a dual hierarchical structure, where deformation ability of rough layer surface contributes to the macro-interface and hydrates structure dominates the micro-interface. The influences of such factors including material rheological properties, deposition time interval and interfacial humidity can be integrated in this dual hierarchical structure. Finally, an empirical model was proposed to combine dual hierarchical structure with bonding strength of layer interface in 3D printed concrete.

A foreground time-spatial image (FTSI) is proposed for counting vehicles in complex urban traffic scenes to resolve deficiencies of traditional counting methods, which are highly computationally expensive and become unsuccessful with increasing complexity in urban traffic scenarios. First, a self-adaptive sample consensus background model with confidence measurements for each pixel is constructed on the virtual detection line in the frames of a video. The foreground of the virtual detection line is then collected over time to form a FTSI. The occlusion cases are then estimated based on the convexity of connected components. Finally, counting the number of connected components in the FTSI reveals the number of vehicles. Based on real-world urban traffic videos, the experiments in this study are conducted using FTSI, and compared in accuracy with two other time-spatial images methods. Experimental results based on real-world urban traffic videos show that the accuracy rate of the proposed approach is above 90% and it performs better than the state-of the-art methods.

The Pixel-Based Adaptive Segmenter with Confidence Measurement (PBASCM) is proposed for vehicle detection in complex urban traffic scenes to efficiently address deficiencies of the background subtraction model, which is easily contaminated by slow-moving or temporarily stopped vehicles. The background is modeled based on the history of recently observed pixel values and each pixel in the background model is assigned a confidence measurement based on the current traffic state. The foreground decision depends on an adaptive threshold, whereas the background model is updated based on the current traffic state and whether the corresponding pixel point is in the confidence period. Using real-world urban traffic videos, the overall results of detection accuracy analyses demonstrated that PBASCM achieved better performance in both qualitative and quantitative evaluations, compared with other state-of-the-art methods. PBASCM can accurately detect slowmoving or temporarily stopped vehicles, and the similarity and F-measure results for PBASCM were 0.839 and 0.912 higher, respectively, than those obtained by other methods in a traffic light sequence during the daytime. Thus, our experimental results demonstrate that PBASCM is effective and suitable for real-time vehicle detection in complex urban traffic scenes.

Aiming to efficiently resolve the problem that the subtraction background model is easily contaminated by slow-moving or temporarily stopped vehicles, the Gaussian mixture model with confidence measurement (GMMCM) is proposed for vehicle detection in complex urban traffic scenes. According to the current traffic state, each pixel of background model is set a CM. Whether to update the background model and the corresponding adaptive learning rate depends on if the current pixel point is in confidence period. Using the real-world urban traffic videos, the first experiments are conducted by GMMCM, compared with three commonly used models including GMM, self-adaptive GMM (SAGMM) and local parameter learning algorithm for the GMM (LPLGMM). The first experimental results show that GMMCM excels GMM, SAGMM and LPLGMM in keeping the background model being unpolluted from slow-moving or temporarily stopped vehicles. The second experiments are conducted by GMMCM, compared with visual background extractor, sigma-delta with CM, SAGMM, LPLGMM and GMM. The average recalls of six methods are 0.899, 0.753, 0.679, 0.420, 0.447 and 0.205, and the average F-measures of six methods are 0.636, 0.612, 0.592, 0.373, 0.330 and 0.179, respectively. All experimental results show the effectiveness of the proposed GMMCM in vehicles detection of complex urban traffic scenes.

The thermodynamically unstable nature of aqueous foam is a challenging problem for fabrication of ultra-lightweight foamed cement-based materials. Such materials are also facing many durability problems due to their hydrophilic property and porous microstructure. In this study, a matrix superhydrophobic cement foam with high specific strength was developed by a one-step process. The rational tomographic and chemical properties of the border-air interfaces of cement foam were simultaneously modified by a nanohybrid method, in which the nano silica was grafted with water repellent functional group, promoting the adsorption of nano silica onto the air-liquid interfaces. The joint effect of increased multi-scale roughness and hydrophilization of the interfaces produced bulk superhydrophobic cement foam, which revealed excellent mechanical robustness even upon major surface damage. Such foamed cement is of great importance for industrial thermal insulation applications, and potentially provide a solution to the long-standing durability problems of cement based porous materials.

To develop the human-centric driver fatigue monitoring system for automatic understanding and charactering of driver's conditions, a novel, efficient feature extraction approach, named Local Multiresolution Derivative Pattern (LMDP), is proposed to describe the driver's fatigue expression images, and the Intersection Kernel Support Vector Machines classifier is then exploited to recognize three pre-defined classes of fatigue expressions, i.e., awake expressions, moderate fatigue expressions and severe fatigue expressions. With features extracted from a fatigue expressions dataset created at Southeast University, the holdout and cross-validation experiments on fatigue expressions classification are conducted by the Intersection Kernel Support Vector Machines classifier, compared with three commonly used classification methods including the k-nearest neighbor classifier, the multilayer perception classifier and the dissimilarity-based classifier. The experimental results of holdout and cross-validation showed that LMDP offers the better performance than Local Derivative Pattern, and the second order LMDP exceeds other order LMDP. With the second order LMDP and the Intersection Kernel Support Vector Machines classifier, the classification accuracies of the severe fatigue are over 90 in the holdout and cross-validation experiments, thus demonstrating the effectiveness of the proposed feature extraction method in automatically understanding the driver's conditions towards the human-centric driver fatigue monitoring system.

Pharmacogenomics is the study of the impact of genetic variations or genotypes of individuals on their drug response or drug metabolism. Compared to traditional genomics research, pharmacogenomic research is more closely related to clinical practice. Pharmacogenomic discoveries may effectively assist clinicians and healthcare providers in determining the right drugs and proper dose for each patient, which can help avoid side effects or adverse reactions, and improve the drug therapy. Currently, pharmacogenomic approaches have proven their utility when it comes to the use of cardiovascular drugs, antineoplastic drugs, aromatase inhibitors, and agents used for infectious diseases. The rapid innovation in sequencing technology and genome-wide association studies has led to the development of numerous data resources and dramatically changed the landscape of pharmacogenomic research. Here we describe some of these web resources along with their names, web links, main contents, and our ratings.

Chordoid meningioma (CM) and clear-cell meningioma (CCM) are rare World Health Organization grade II meningioma subtypes. This study aimed to evaluate favorable factors and appropriate therapeutic strategies for these lesions.We retrospectively reviewed clinical data from 111 cases of grade II meningiomas, including 55 cases of CM and 56 cases of CCM, between January 2011 and December 2015.The mean follow-up time of the rare World Health Organization grade II meningiomas (n = 111) was 45.3 months. In the CM group, 8 patients (14.5%) experienced recurrence, and 2 patients (3.6%) died. In the CCM group, 22 patients (39.3%) experienced recurrence, and 9 patients (16.1%) died. Significant differences were observed between the CM and CCM groups in tumor size (P = 0.019), history of surgery (P = 0.038), and peritumoral edema (P = 0.004). In the CM group, gross total resection was associated with favorable progression-free survival (hazard ratio, 0.144; 95% confidence interval, 0.029-0.714; P = 0.018). In the CCM group, univariate analyses showed that preoperative Karnofsky Performance Status80 (P 0.001), tumor size ≥5 cm (P = 0.015), tumor size (per-centimeter increase) (P = 0.022), bone invasion (P = 0.004), a history of surgery (P0.001), and subtotal resection (P = 0.009) were associated with worse progression-free survival. Male gender (P = 0.039), tumor size (per-centimeter increase) (P = 0.043), bone invasion (P = 0.030), and a history of surgery (P = 0.007) were associated with poor overall survival.This study showed that gross total resection should be achieved in grade II meningiomas. Patients with larger tumors and/or surgical histories had worse outcomes.

The Hui-style residence is an important architectural heritage of China. The hollow wall structures are widely used to build its exterior wall system. However, the thermal performance of the hollow wall is no longer able to meet the new energy-saving and environmental requirement. This article describes a laboratory study of the development of foamed mortar (FM), with the potential for use in thermal upgrading of the Hui-style hollow wall system without dramatically changing its traditional structure. The key early age, physical, mechanical and thermal properties were systematically measured. Two extended models were respectively developed to calculate compressive strength and thermal conductivity, as a function of porosity. Environment chamber test was also employed to investigate the effectiveness of this novel thermal upgrading approach and the results show that filling the voids with FM can effectively improve the overall thermal resistance of the hollow wall system by 44%, which is almost equal to th...

In this paper we consider the problem of resource allocation for video transmission over mesh networks with delay bound constraints and priority-based packet scheduling. We observe that priority-driven packet scheduling at the intermediate network routers has a direct and significant impact on the queuing behaviors and delay bound violation probabilities of video packets, as well as the overall end-to-end video distortion. Using learning methods, we develop a packet delay bound violation probability model for video transmission over multihop networks with priority-based packet scheduling. With this model, we can successfully predict the probability of packets being dropped due to violation of specified delay bounds. We also observe that the transmission distortion caused by packet drops exhibits a unique exponential behavior with priority-based packet scheduling. With these analysis results, we formulate the resource allocation for multisession video transmission over networks with priority-driven packet scheduling under delay bound constraints as a multiobjective optimization problem. Evolutionary optimization methods based on single- and multiobjective genetic algorithms are proposed to solve the problem and obtain the optimal resource allocation. Extensive experiment results demonstrate the effectiveness of the proposed resource-distortion models and optimization algorithms.

The filtering of point clouds is a ubiquitous task in the processing of airborne laser scanning (ALS) data; however, such filtering processes are difficult because of the complex configuration of the terrain features. The classical filtering algorithms rely on the cautious tuning of parameters to handle various landforms. To address the challenge posed by the bundling of different terrain features into a single dataset and to surmount the sensitivity of the parameters, in this study, we propose an adaptive surface filter (ASF) for the classification of ALS point clouds. Based on the principle that the threshold should vary in accordance to the terrain smoothness, the ASF embeds bending energy, which quantitatively depicts the local terrain structure to self-adapt the filter threshold automatically. The ASF employs a step factor to control the data pyramid scheme in which the processing window sizes are reduced progressively, and the ASF gradually interpolates thin plate spline surfaces toward the ground with regularization to handle noise. Using the progressive densification strategy, regularization and self-adaption, both performance improvement and resilience to parameter tuning are achieved. When tested against the benchmark datasets provided by ISPRS, the ASF performs the best in comparison with all other filtering methods, yielding an average total error of 2.85% when optimized and 3.67% when using the same parameter set.

This paper presents a coarse-to-fine large-size very high resolution image registration method. This method uses compute unified device architecture to speed up the acquisition of control points and image rectification. In coarse registration, the scale-invariant feature transform algorithm is used to match control points to estimate the initial global transformation parameters between images to be registered. The initial parameters are then used to guide Oriented FAST and Rotated BRIEF (ORB) feature matching in fine registration. To fix local distortion, image rectification is based on a linear mapping function computed from triangulations, and a self-adaptive scan filling algorithm is proposed to determine which triangle each pixel belongs to. Experiments are conducted with large-size satellite images. Results show that a graphics processing unit can obtain significant-acceleration factors while maintaining registration accuracy. We presented a method for CUDA-accelerated VHR images registration through coarse-to-fine matching.A self-adaptive triangle scan line filling method is developed for efficiently rectification image adapts to local distortion by linear mapping function.Image rectification using CUDA is implemented and it can increases the speed of image rectification by about 40 times. If considering the memory copy time, speed can still be increased by more than 16 times.

In order to develop Human-centered Driver Assistance Systems (HDAS), an efficient Combined Feature (CF) extraction approach from Contourlet Transform (CT) and Edge Orientation Histogram (EOH) is proposed for vehicle driving posture descriptions. A Random Subspace Ensemble (RSE) of Intersection Kernel Support Vector Machines (IKSVMs) is then exploited as the base classifier. Four testing driving postures are grasping the steering wheel, operating the shift lever, eating a cake, and talking on a cellar phone. On a dedicated Southeast University Driving Posture (SEU-DP) Database, the holdout and cross-validation experiments were conducted. The experimental results show that the proposed CF-RSE approach outperforms single Contourlet-IKSVM, EOH-IKSVM recognition strategies. With CF-RSE, the average classification accuracies of four driving posture classes are over 90%. Among the four classes of driving postures, the class of grasping the steering wheel is the most difficult to recognize and the proposed approach achieved over 85% accuracy in both experiments. These encouraging results show that the proposed CF-RSE approach is effective and hence has great promises in developing a successful HDAS.

Combined with the construction of Jinghang Canal Bridge of Jiangliu highway, shrinkage and creep property of the cast-in-situ high performance concrete of bridge girder was researched. The results showed early shrinkage and creep development of the high performance concrete was relatively rapid, and creep tended to be stable 120 days later. With the admixture increasing, shrinkage and creep of the concrete were reduced. Meanwhile, early creep rate deceased. Similar results applied to the reduction of sand rate and water-cement ratio. Based on creep prediction models both at home and abroad, hyperbolic power function and exponential function model were put forward, taking the influence of material parameter and environmental factors on shrinkage and creep into consideration. In accordance with the model, concrete creep formula was given out and would provide a relatively scientific basis for practical prediction of concrete creep.

To generate corresponding points for large size satellite, aerial or high resolution close-range image, it is always needed to downscale the original image to low resolution image via pyramid image generating to detect local features. So this paper studies the affection of the pyramid image on the repeatability performance of the state-of-the-art local feature detectors. For generating pyramid image with ground truth data, a method for calculating the homography parameters between pyramid images of stereo pair with homography parameters is proposed. Benchmark data sets with ground truth are used to generate pyramid images and derive homography parameters directly. Experiment results revealed that pyramid image can reduce the affection of scale change and image distortion to some extent.

This paper presents an innovative image matching method for reliable and dense image matching on poor textural images, which is the integrated point and edge matching based on the self-adaptive edge-constrained triangulations. Firstly, several seed points and seed edges are obtained on the stereo images, and they are used to construct a pair of initial edge-constrained triangulations on the images. Then, points and edges are matched based on the triangle constraint and other constraints. The newly matched points and edges are inserted into the triangulations and the constrained triangulations are updated dynamically along with the matching propagation. The final results will be the final edge-constrained triangulations generated from the successfully matched points and edges. Experiments using typical space-borne, airborne, and terrestrial images with poor textures revealed that the integrated point and edge matching method based on self-adaptive triangulations is able to produce dense and reliable matching results. Moreover, from the final matched points and edges, 3D points and edges preserving the physical boundaries of objects can be further derived based on photogrammetric techniques, which is ideal for further object modeling applications.

Single and multiple dynamic impacts tests were conducted on ultra-high performance cementitious composite (UHPCC) with various volume fractions of steel fibers (0, 1%, 2%, 3%, 4%) by using the split hopkinson pressure bar (SHPB). Besides, the ultrasonic velocity method was used to test the damage on specimens caused by dynamic impacts. For single dynamic impact, the data suggest that UHPCC obviously presents dynamic strength enhancement. With increasing of strain rate, the peak stress and peak strain increase rapidly. For multiple dynamic impacts, the results show that addition of steel fibers can obviously enhance the properties of UHPCC to resist the repeated dynamic impacts. Firstly, the number of impacts sharply increases with the increasing of volume fraction of steel fibers. Secondly, the energy absorption ability linearly increases with addition of steel fibers. Thirdly, the steel fibers can prevent the disruption phenomenon and maintain the integrity of specimen.

We present a novel multiscale dynamic methodology for automatic machine vision inspection aiming at characterizing temporal features of tobacco leaves. The image sequences of tobacco leaves are transformed from RGB color space to L*a*b* color space, which provides a uniform perceptual difference measure. The image sequences are then represented by a multiscale Dynamic Hidden Markov tree (DHMT), which models not only inter and intra scale dependences of wavelet coefficients, but also temporal dependences of foreground/background observational properties. Experimental results demonstrate temporal consistent mean and covariance values of model coefficients in a* color channel.

Considering the low efficiency and accuracy of existing straight line extraction methods from large-scale imagery, a multi-scale Hough transform HT method based on the pre-storage weight matrix is proposed. Improvements of the proposed HT include: using the pre-storage weight matrix to save storage space and improve the efficiency of the HT, applying a multi-scale method to enable the detection of smaller features from large-size images, using overlapping adjacent tiles to avoid the fragmented lines, optimizing the dimensions of the discrete transform domain, normalizing the accumulator to extract off-centred lines and using a dual threshold for distributed line detection. The experimental results show that the proposed algorithm is not only more efficient and robust but also can obtain richer and more accurate information about features, especially for large-size images.

The early hydration process was investigated using ultrasonic monitoring apparatus for pastes made with various mineral admixtures: silica fume (4%, 13%), slag (10%, 30%, 50%, 70%), and fly ash (10%, 30%, 50%). The influence of water to binder ratio (0.23, 0.35 and 0.53) was also studied. The results show that the hydration rate of cementitious material is obviously accelerated with decreasing in water to cement ratio and Silica fume addition, while the reverse phenomenon is observed when fly ash and slag are incorporated.

Reliable image matching is an essential and difficult task in digital photogrammetry and computer vision. Possible problems from geometric distortions, illumination changes, scale changes and difficult texture conditions will result in matching ambiguity, especially for close-range image matching. This paper presents a multiple close-range image matching method for surface reconstruction based on a selfadaptive triangle constraint. This method features two aspects. First, the triangles constructed from the previously matched interest points provide strong geometric constraints for the subsequent point matching combined with gradient orientation and disparity constraints. The dynamic update of the triangulation adapts automatically to the changes of image textures. Secondly, a consistency check in object space is performed to remove possible mismatches. Using three sets of actual triple overlapped close-range images for the experiment, the results revealed that the proposed method provides improved matching reliability.

Resource allocation plays a critical role in multisession video streaming over mesh networks to maximize the overall video presentation quality under transmission delay and network resource constraints. A critical component in efficient resource allocation is to analyze and model the multihop queuing behavior along the transmission path, estimate the packet loss ratio due to delay bound violation, and predict the amount of video quality degradation after multihop video transmission. In this work, we develop a multihop packet delay bound violation model to predict the packet loss probability and end-to-end distortion for video streaming over multihop networks. To this end, we extract salient features to characterize the input source and network conditions of links along the transmission path and construct a learning-based model using artificial neural network (ANN). Based on this model, we then formulate the resource allocation into a nonconvex optimization problem which aims to minimize the overall video distortion while maintaining fairness between sessions. We solve this optimization problem using Lagrangian duality methods. Extensive experimental results demonstrate that, with this widely-used offline-training-online-estimation mechanism, the proposed model is potentially applicable to almost all network conditions and can provide fairly accurate estimation results as compared with other models with a given sample data set. The proposed optimization algorithm achieves more efficient resource allocation than existing schemes.

To investigate the effect of nicorandil of potassium channel opener on myocardial ischemia-reperfusion injury in rats and to explore the mechanism of nicorandil on cardioprotective effect relative with mitochondrial ALDH2. Wistar rats were randomly divided into four groups: normal group (N Group)

Zirconia-coated rutile TiO2 composites were prepared by the chemical liquid deposition method starting from rutile TiO2 and ZrOCl2. The amorphous zirconia coating layers were anchored at the TiO2 surface via Zr–O–Ti bond. The formation of continuous and dense zirconia coating layers was dependent on the pH value of the reaction solution and the mole ratio of ZrOCl2 to TiO2. As compared to the naked rutile TiO2, the water dispersibility, whiteness, brightness, and relative light scattering index of the zirconia-coated rutile TiO2 composites were increased.

Since object boundaries appear blurry, reduced localization accuracy of wavelet-domain hidden Markov tree-based (WHMT) method poses a problem during the object extraction process. A novel approach to improve localization accuracy by fusing multiscale information of the tree model is presented. We start with calculating the multiscale classification likelihoods of wavelet coefficients by expectation-maximization (EM) algorithm. Energy function is then generated by combining boundary term estimated by classification likelihoods with regional term obtained by approximation coefficients. Through energy minimization via graph cuts, objects are extracted accurately from the images. A performance measure for tobacco leaf inspection is used to evaluate our algorithm.

The mix ratio of steel fiber reinforced concrete (SFRC) was optimized using the principles that workability must meet the pumping demand and anti-cracking performance should be optimal. The effect of SFRC on the initial cracking load, the ultimate load and the crack width of the reinforced concrete (RC) member were analyzed in this paper. It was found that the admixture had good preservation of moisture and adhesion and the fibers distributed homogeneously in one hour out of the machine. According to the pumping results, the SFRC could be pumped vertically up to 306 m. Based on the standard computation formula of cracks, the maximum crack width of an RC member with 0.8% steel fiber (by volume) is about 32% lower than that of standard RC member. Through an experimental research on full-scale model tests for the steel and concrete composite anchorage zone on a pylon, the SFRC not only remarkably increases the crack resistance and the ultimate load, but the initial load also improves 33%a pproximately. It is also indicated that plastic shrinkage cracking of SFRC in which volume fraction of steel fibers is 0.8% can be restrained obviously and the unrestrained drying shrinkage can be diminished by about 50% at early age. The results confirmed that the SFRC can lessen the shrinkage crack of concrete and enhance markedly the direct tensile strength. Therefore, the SFRC can solve the key question of crack resistance for the anchorage zone of a bridge tower.