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Background The purpose of this study was to evaluate the clinical and radiological outcomes of the briaded suture tape system augmentation in the treatment of flexible flatfoot. Methods Patients who underwent suture tape system augmentation in addition to spring ligament repair and flexor digitorum longus (FDL) transfer were reviewed. Clinical and radiological outcomes were studied. The results were compared to a matched control group who underwent the conventional surgical treatment, which involved FDL transfer only or FDL transfer plus medial sliding calcaneal osteotomy. Results A total of 40 patients (11 males and 29 females) who underwent hindfoot reconstruction for flexible flatfoot (Johnson stage 2) were reviewed. There were 18 patients in the suture tape system group and 22 patients in the control group. In the suture tape system group, there was excellent improvement in patients’ symptoms, AOFAS score (97.9 improved from 76.7) and significantly more number of patients with stable single leg stance. Radiographic parameters improved postoperatively too. Conclusions This is the first clinical study which studied the outcome of suture tape system augmentation for spring ligament repair. Patients with suture tape system reconstruction showed more number of patients with single leg stance and better correction of forefoot abduction. It is a reasonable component of hindfoot reconstruction.

This experimental study aims to investigate the effects of incorporating an emotional design into multimedia materials on problem-solving skills, and attention and motivation levels in primary mathematics. We divided 60 primary school students into control and experimental groups. In the experimental group, the face-like shape and “happy” color were used in the emotional design. We used pre- and postests to measure score gains, a post-questionnaire measure attention and motivation levels. The results of this study showed that the experimental group performed significantly better than the control group on problem-solving skill. The results also showed that students learning with the emotional design had higher attention and motivation levels. Further discussion suggests that, if positive emotional designs were applied, students felt happier and more hopeful during multimedia learning. We suggest teachers should use face-like shape approach to teach geometry to make the content knowledge more interesting and positive. We also suggest teacher could present happy images in the beginning of mathematics classroom for attracting student attention.

In multiview video plus depth (MVD) format, virtual views are generated from decoded texture videos with corresponding decoded depth images through depth image based rendering (DIBR). 3DV-ATM is a reference model for the H.264/AVC based multiview video coding (MVC) and aims at achieving high coding efficiency for 3D video in MVD format. Depth images are first downsampled then coded by 3DV-ATM. However, sharp object boundary characteristic of depth images does not well match with the transform coding based nature of H.264/AVC in 3DV-ATM. Depth boundaries are often blurred with ringing artifacts in the decoded depth images that result in noticeable artifacts in synthesized virtual views. This paper presents a low complexity adaptive depth truncation filter to recover the sharp object boundaries of the depth images using adaptive block repositioning and expansion for increasing the depth values refinement accuracy. This new approach is very efficient and can avoid false depth boundary refinement when block boundaries lie around the depth edge regions and ensure sufficient information within the processing block for depth layers classification. Experimental results demonstrate that the sharp depth edges can be recovered using the proposed filter and boundary artifacts in the synthesized views can be removed. The proposed method can provide improvement up to 3.25dB in the depth map enhancement and bitrate reduction of 3.06% in the synthesized views.

The quality of the synthesized views by Depth Image Based Rendering (DIBR) highly depends on the accuracy of the depth map, especially the alignment of object boundaries of texture image. In practice, the misalignment of sharp depth map edges is the major cause of the annoying artifacts at the disoccluded regions of the synthesized views. Conventional smooth filter approach blurs the depth map to reduce the disoccluded regions. The drawbacks are the degradation of 3D perception of the reconstructed 3D videos and the destruction of the texture in background regions. Conventional edge preserving filter utilizes the color image information in order to align the depth edges with color edges. Unfortunately, the characteristics of color edges and depth edges are very different which causes annoying boundaries artifacts in the synthesized virtual views. Recent solution of reliability-based approach uses reliable warping information from other views to fill the holes. However, it is not suitable for the view synthesis in video-plus-depth based DIBR applications. In this paper, a new depth map preprocessing approach is proposed. It utilizes Watershed color segmentation method to correct the depth map misalignment and then the depth map object boundaries are extended to cover the transitional edge regions of color image. This approach can handle the sharp depth map edges lying inside or outside the object boundaries in 2D sense. The quality of the disoccluded regions of the synthesized views can be significantly improved and unknown depth values can also be estimated. Experimental results show that the proposed method achieves superior performance for view synthesis by DIBR especially for generating large baseline virtual views.

This paper presents a new Chinese input method that utilises finger gestures for improving stroke-based input method on touchscreen devices. It is a radical-stroke (RS) based method with a dynamic radical keypad (DRK), in which single radical multiple strokes coding is used. It speeds up the input of complex Chinese characters by simply sliding a finger. Experimental results show that the proposed RS–DRK outperforms the conventional Chinese input methods on an Android platform.

In multiview video coding (MVC), disparity-compensated prediction (DCP) exploits the correlation among different views. A common approach is to use block-based motion-compensated prediction (MCP) tools to predict the disparity effect among different views. However, some regions in different views may have various deformations due to nonconstant depth. Thus, performance of DCP is not satisfactory with the simple translational model assumed in conventional block-based MCP tools. Previous attempts to achieve better disparity prediction were usually too complex for practical use. In this paper, horizontal scaling and shearing (HSS) effects are investigated to increase interview prediction accuracy for stereo video. HSS deformations are common among images of horizontally aligned views, due to horizontal and vertical flat surfaces that are not parallel with projection image planes. To achieve HSS-based DCP with minimal complexity, an efficient subsampled block-matching technique is adopted and integrated into MVC extension of H.264/AVC in stereo profile. Affine parameters estimation and additional frame buffers are not required and the overall increase of computational complexity and memory requirements are moderate. Experimental results show that the new technique can achieve up to 5.25% bitrate reduction in interview prediction using JM17.0 reference software implementation.

A Rh(III)-catalyzed direct aromatic C-H amination is achieved using N-chloroamines as a reagent. Furthermore, we also developed a one-pot amination protocol involving in situ chlorination of the secondary amines. The catalytic amination operates at mild conditions with excellent functional group tolerance and regioselectivity.

Motion compensated prediction plays a vital role in achieving enormous video compression efficiency in advanced video coding standards. Most practical motion compensated prediction techniques implicitly assume pure translational motions in the video contents for effective operation. Some attempts aiming at more general motion models are usually too complex requiring parameter estimation in practical implementation. In this paper, zoom motion compensation is investigated to extend the assumed model to support both zoom and translation motions. To accomplish practical complexity, a novel and efficient subsampled block-matching zoom motion estimation technique is proposed which makes use of the interpolated reference frames for subpixel motion estimation in a conventional hybrid video coding structure. Specially designed subsampling patterns in block matching are used to realize the translation and zoom motion estimation and compensation. No zoom parameters estimation and additional frame buffers are required in the encoder implementation. The complexity of the decoder is similar to the conventional hybrid video codec that supports subpixel motion compensation. The overall increase in memory requirement and computational complexity is moderate. Experimental results show that the new technique can achieve up to 9.89% bitrate reduction using KTA2.2r1 reference software implementation.

In this paper, a modified degree-based strategy is proposed for pinning control of complex networks under constrained control capacity. Limited by the total control strength, the pinning strategy design problem is reconsidered as a constrained optimization problem. To provide a fast and effective solution, a decrease-and-conquer approach has been designed to assign the best control strengths to the pinned highest-degree nodes. Simulation results have demonstrated that the obtained strategy provides an outperformed control effect on various kinds of complex networks, as compared with strategies derived from degree, betweenness or closeness using evenly-distributed control strength.

Search point pattern-based fast block motion estimation algorithms provide significant speedup for motion estimation but usually suffer from being easily trapped in local minima. This may lead to low robustness in prediction accuracy particularly for video sequences with complex motions. This problem is especially serious in one-at-a-time search (OTS) and block-based gradient descent search (BBGDS), which provide very high speedup ratio. A multipath search using more than one search path has been proposed to improve the robustness of BBGDS but the computational requirement is much increased. To tackle this drawback, a novel directional gradient descent search (DGDS) algorithm using multiple OTSs and gradient descent searches on the error surface in eight directions is proposed in this letter. The search point patterns in each stage depend on the minima found in these eight directions, and thus the global minimum can be traced more efficiently. In addition, a fast version of the DGDS (FDGDS) algorithm is also described to further improve the speed of DGDS. Experimental results show that DGDS reduces computation load significantly compared with the well-known fast block motion estimation algorithms. Moreover, FDGDS can achieve faster speedup compared with the UMHexagonS algorithm in H.264/AVC implementation while maintaining very similar rate-distortion performance.

Center-biased fast motion estimation algorithms, e.g., block-based gradient descent search and diamond search, can perform much better than coarse-to-fine search algorithms, such as 2-D logarithmic search and three-step search. The latter type of algorithms, however, is more suitable for handling large motion content. To combine the advantages of both types of algorithms, an adaptive algorithm performing search patterns switching (SPS) is proposed in this paper. The proposed SPS algorithm classifies the motion content of a block using a simple yet efficient motion content classifier called error descent rate. Unlike other classifiers with heavy overhead, this classifier requires only the searching of a few points in the search window and then a division operation. Experimental results show that the proposed SPS algorithm is very robust.

Recently, an enhanced hexagon-based (EHS) search algorithm was proposed to speedup the original hexagon-based search (HS) using a 6-side-based fast inner search. However, this 6-side-based method is quite irregular by inspecting the distance between the inner search points and the coarse search points that would lower prediction accuracy. In this paper, a new point-oriented grouping strategy is proposed to develop fast inner search techniques for speeding up the HS and diamond search (DS) algorithms. Experimental results show that the new HS and DS using point-oriented inner searches are faster than their original algorithms up to 30% with negligible peak signal-to-noise ratio degradation

In Multiview Video plus Depth (MVD) format, virtual views are generated from decoded texture videos with decoded depth images through Depth Image based Rendering (DIBR). 3DV-ATM is a reference model for H.264/AVC based Multiview Video Coding (MVC) and aims at achieving high coding efficiency for 3D video in MVD format. Depth images are first downsampled then coded by 3DV-ATM. However, sharp object boundary characteristic of depth images does not well match with the transform coding of 3DV-ATM. Depth boundaries are often blurred with ringing artifacts in the decoded depth images that result in noticeable artifacts in synthesized views. This paper presents a low complexity adaptive block truncation filter to recover the sharp object boundaries of depth images using adaptive block repositioning and expansion for increasing the depth values refinement accuracy. This new approach is very efficient and can avoid false depth boundary refinement when block boundaries lie around the depth edge regions and ensure sufficient information within the processing block for depth layers classification. Experimental results show that sharp depth edges can be recovered using the proposed filter and boundary artifacts in the synthesized views can be removed. The proposed method can provide improvement up to 3.25dB in the depth map enhancement and bitrate reduction of 3.06% in the synthesized views. Index Terms— Multiview Video plus Depth (MVD), Depth Image based Rendering (DIBR), 3DV-ATM, Multiview Video Coding (MVC), depth image compression, depth image filter.

The corresponding N-chloroalkylamines (II) and (IV) are prepared in situ by reaction of the primary amines with N-chlorosuccinimide.

The launch of Kinect provides a convenient way to access the depth information in real time. However the depth map quality still needs to be enhanced for 3D visual applications. In this paper, an adaptive background biased depth map hole-filling method is proposed. First, depth holes caused by abnormal reflection are filled by color similarity in-painting, and a soft decision for color similarity checking is performed by the use of probabilities in random walks color segmentation. Afterwards it is assumed that the lost information in the rest of depth holes belongs to the background. The background depth information is extracted by automatic thresholding in the neighborhood of each hole. Depth holes are in-painted with the background information in their local neighborhood. Combination of color similarity in-painting and background biased in-painting is able to perform depth map hole-filling adaptively for different kinds of depth holes for Kinect. The hole-filling results and virtual view synthesis results show that the Kinect depth map quality can be improved significantly by the proposed method.

Quality of synthesized view by Depth-Image-Based Rendering (DIBR) highly depends on hole filling, especially for synthesized view with large disocclusion. Many hole filling methods are proposed to improve the synthesized view quality and inpainting is the most popular approach to recover the disocclusions. However, the conventional inpainting either makes the hole regions blurred via diffusion or propagates the foreground information to the disoclusion regions. Annoying artifacts are created in the synthesized virtual views. This paper proposes a depth-aided exemplar-based inpainting method for recovering large disoclusion. It consists of two processes, warped depth map filling and warped color image filling. Since depth map can be considered as a grey-scale image without texture, it is much easier to be filled. Disoccluded regions of color image are predicted based on its associated filled depth map information. Regions with texture lying around the background have higher priority to be filled than other regions and disoccluded regions are filled by propagating the background texture through the exemplar-based inpainting. Thus artifacts created by diffusion or using foreground information for prediction can be eliminated. Experimental results show texture can be recovered in large disocclusions and the proposed method has better visual quality compared to existing methods.

An efficient method for synthesis of anthranilic acids by Pd-catalyzed ortho-C–H amidation of benzoic acids is disclosed. The amidation is proposed to proceed by carboxylate-assisted ortho-C–H palladation to form an arylpalladium(II) complex, followed by nitrene insertion to the Pd–C bond.

An efficient method for synthesis of anthranilic acids by Pd-catalyzed ortho-C–H amidation of benzoic acids is disclosed. The amidation is proposed to proceed by carboxylate-assisted ortho-C–H palladation to form an arylpalladium(II) complex, followed by nitrene insertion to the Pd–C bond.

Depth map estimation from a single image is the key problem for the 2D to 3D image conversion. Many 2D to 3D converting processes, either automatic or semi-automatic, are proposed before. Quality of the depth map from automatic methods is low and there exists wrong depth values due to errors estimation in depth cue extraction. The semi-automatic approaches can generate a better quality of depth map based on the user-defined labels, which indicate a rough estimation of depth values in the scene, to generate the rest of depth value and reconstruct the stereoscopic image. However, they require complexity system and are very computational intensive. A simplified approach is to combine the depth maps from Graph Cuts and Random Walks to persevering the sharp boundary and fine detail inside the objects. The drawback is the time consuming of the energy minimization in the Graph Cuts. In this paper, a fast Watershed segmentation based on the priority queue, which indicates the neighbor distance relationship, is used to replace the Graph Cuts to generate the hard constraints depth map. It is appended to the neighbor cost in the Random Walks to generate the final depth map with hard constraints in the objects boundaries regions and fine detail inside objects. The Watershed and Random Walks are low computational intensive and can achieve approximate real time estimation which results in a fast stereoscopic conversion process. Experimental results demonstrate that it can produce good quality stereoscopic image in very short time.

Adaptive intra mode bit skip (AIMBS) can improve the coding efficiency of intra coding in H.264/AVC. However, it has two shortcomings: one is that DC mode is not effectively handled in AIMBS as DC mode is duplicated in both Single-Prediction and Multiple-Prediction processing; the other is that AIMBS does not well match the most probable mode (MPM) estimation scheme of H.264/AVC. To tackle these two shortcomings, an enhanced AIMBS (EAIMBS) scheme with larger bitrate reduction and better QP robustness is presented. In addition, EAIMBS almost maintains as low computational complexity as AIMBS. The proposed technique introduces distance-based weighted prediction (DWP) to replace DC mode in Multiple-Prediction and it calculates the MPM by simplified L-shaped most probable mode estimation (SLMPME) method. Experimental results show that EAIMBS gives in average 3.97% bit-rate reduction and 51% computation reduction at QP=32 compared with H.264/AVC.

The one-pot two-step process without isolation of the chloroamines succeeds with comparable yields, cf.(XIX).

A new MCP method called Neighbor Predicted Superimposed Search (NPSS) algorithm that uses superimposed inter-frame signals to achieve higher prediction accuracy is proposed in this paper. It outperforms other Multi-Hypothesis MCP (MHMCP) methods as it does not require the transmission of multiple motion vectors. The proposed method has better prediction quality and yet having comparable computational complexity as conventional block-based MCP with no extra side-information overhead.

The performance of view synthesis using depth image based rendering (DIBR) highly depends on the accuracy of depth map. Inaccurate boundary alignment between texture image and depth map especially for large depth discontinuities always cause annoying artifacts in disocclusion regions of the synthesized view. Pre-filtering approach and reliability-based approach have been proposed to tackle this problem. However, pre-filtering approach blurs the depth map with drawback of degradation of the depth map and may also cause distortion in non-hole region. Reliability-based approach uses reliable warping information from other views to fill up holes and is not suitable for the view synthesis with single texture video such as video-plus-depth based DIBR applications. This paper presents a simple and efficient depth map preprocessing method with use of texture edge information to refine depth pixels around the large depth discontinuities. The refined depth map can make the whole texture edge pixels assigned with foreground depth values. It can significantly improve the quality of the synthesized view by avoiding incorrect use of foreground texture information in hole filling. The experimental results show the proposed method achieves superior performance for view synthesis by DIBR especially for large baseline.

With the popularity of touchscreen devices, physical button-based keyboards are being replaced by finger-operated virtual keyboards. Entering text on these touchscreen devices is no longer limited by finger tapping activities on the keys. Text input can be performed by finger sliding over the virtual keyboard, which is well realized by the Swype technology on a typical QWERTY keyboard. Such shorthand gesturing for text input, however, may be inefficient when directly applied to Chinese input, especially in Chinese stroke-based input method. In this paper, a novel dynamic candidate keypad with use of unidirectional finger gesture on the stroke key for character selection is proposed for enhancing stroke-based Chinese input method. The new design can enhance frequently used Chinese characters searching and input using stroke-based input. The new method is implemented on the Android 2.2 platform for performance evaluation using Traditional Chinese characters set. Experimental results show that the proposed method enables users to input popular Chinese characters easier than conventional stroke-based input methods.

Title reaction provides access to a wide range of amide-protected o-amino anilines in good yields and with excellent regioselectivity.

Adaptive Intra Mode Bit Skip (AIMBS) technique using boundary pixels smoothness has been shown to achieve coding efficiency improvement for H.264/AVC's Intra_4x4 coding in relatively large QPs. However, the DC mode in the Multiple-Prediction of the AIMBS becomes much less effective. To tackle this problem and further improve the coding efficiency, distance-based weighted prediction (DWP) is proposed to replace DC mode in Multiple-Prediction for predicting blocks without directional preferences. The proposed method is named as AIMBS-DWP that can enhance the robustness of AIMBS in much larger range of QPs and achieve higher rate-distortion performance. Experimental results show that an average bitrate reduction of 3.79% with lower computational requirement can be obtained by AIMBS-DWP as compared with H.264/AVC. The improvement is especially obvious in high visual quality configurations with small QPs.