Miracle-dz/UniFAR-FTUs huggingface dataset:
An ink-diffusion-based rendering method for Chinese ink painting

In non-photorealistic rendering (NPR), the Chinese ink painting style rendering is a traditional NPR skill of China. In this paper, we propose a method for image-based and ink-diffusion-based Chinese ink painting NPR. Users without painting experience can also convert a normal image to a Chinese ink painting automatically. As we known, ink is an important pigment for Chinese ink painting and the various ink shade effects on the painting are produced by ink mixed with water. In addition, the ink diffusion along the boundaries is a very important aspect of Chinese ink painting. In order to realize the effects described above, we present a Chinese ink painting NPR method based on ink diffusion. We use Mean Shift based image segmentation algorithm to preprocess the input image to get regions with different tones. Then, we detect the segmentation regions' edges letting the edge points to be the start points for diffusion. We set each point an ink value which is corresponding to its gray value. At the same time, a new algorithm simulating ink diffusion is proposed to make the segmentation image look like a black-ink painting. Results in this paper demonstrate our method is promising.
LMMSE channel estimation with soft statistics for turbo-MIMO receivers

Channel estimation techniques for turbo multiple-input multiple-output receivers are addressed, which exploit a priori information to refine the poor performance of initial channel estimates solely using training symbols. We study linear minimum mean squared error channel estimation (LMMSE-CE) using second-order soft statistics to incorporate the degree of decoding reliability. Utilizing this additional information effectively minimizes the error propagation which the maximum likelihood based expectation maximization channel estimation (ML-CE) suffers. The LMMSE-CE provides a smaller mean square error of channel estimation and block error rate than the ML-CE.
Texram: a smart memory for texturing

Logic embedded memory is an emerging technology that combines high transfer rates and computing power. Texram implements this technology and a new filtering algorithm to achieve high speed, high quality texture mapping. Integrating arithmetic units and large memory arrays on the same chip and thus exploiting the enormous internal transfer rates provides an elegant solution to the memory access bottleneck of high quality texture mapping. Using this technology, we can not only achieve higher texturing speed at lower system costs, we can also incorporate new functionalities such as detail mapping and footprint assembly to produce higher quality images at real time rendering speeds. Environment and video mapping are also integrated on the Texram, which therefore represents an autonomous and versatile texturing coprocessor. Logic enhanced memories might become the computing paradigm of the future, not just in graphics applications. Technological advances will foster this trend by providing an ever increasing amount of memory capacity and chip space for arithmetic units. As the ultimate solution, we can expect a complete 3D graphics pipeline including all memory systems integrated on a single chip.
Locales: supporting large multiuser virtual environments

Creators of multiuser virtual environments naturally desire to make them large in spatial extent, large in numbers of objects, and large in numbers of users interacting with the environment. However, doing so creates several problems: efficiently managing the flow of large amounts of data between large numbers of users, representing precise position and velocity information about objects arrayed across a large volume of space, and allowing designers to create parts of a virtual environment separately and combine them together later. The concept of locales is based on the idea that even in a very large virtual world, most of what a single user can observe at a given moment is nevertheless local in nature. You would expect a large virtual world to be large primarily because, like a city, it combines a large number of relatively small, localized activities not because it contains very large individual activities. Locales divide a virtual world into chunks that can be processed separately. This division is purely an implementation issue-it is not apparent to the user. A user sees several locales at once-generally the locale containing the user's point of view and those neighboring it. The user does not see any seams between the locales nor any abrupt changes as the point of view moves from one locale to another, thereby changing the neighborhood set.
Visualizing Ocean Circulation Models Through Virtual Environments

The visualization scientists at Mississippi State University, working with the computational oceanographers at the Naval Research Laboratory, designed and implemented an interactive, real-time visualization tool called cthru. The cthru system, which provides visualization in a virtual environment, gives researchers the ability to alter model parameters and communicate these changes to the ocean model calculating the solution. The paper discusses the implementation of the cthru system.
Impact of plant extracts tested in attention‐deficit/hyperactivity disorder treatment on cell survival and energy metabolism in human neuroblastoma SH‐SY5Y cells

Plant extracts such as Hypericum perforatum and Pycnogenol® have been tested as alternatives to the classical ADHD drugs. It has been possible to describe neuroprotective effects of such plant extracts. A reduction of ADHD symptoms could be shown in clinical studies after the application of Pycnogenol®, which is a pine bark extract. The impacts of the standardized herbal extracts Hypericum perforatum, Pycnogenol® and Enzogenol® up to a concentration of 5000 ng/mL on cell survival and energy metabolism in human SH‐SY5Y neuroblastoma cells has been investigated in the present examination. Hypericum perforatum significantly decreased the survival of cells after treatment with a concentration of 5000 ng/mL, whereas lower concentrations exerted no significant effects. Pycnogenol® induced a significant increase of cell survival after incubation with a concentration of 32.25 ng/mL and a concentration of 250 ng/mL. Other applied concentrations of Pycnogenol® failed to exert significant effects. Treatment with Enzogenol® did not lead to significant changes in cell survival.
From Research to Real World with Z-GUI

The paper discusses research on Z-GUI which builds on the principles of graphical user interfaces, adding 3D and new interaction modes to create a more powerful way to see data. Pushing graphics, space, and animation to an extreme, the GUI paradigm can reach an entirely different level of power with Z-GUI.
Application-Based Congestion Control Policy for the Communication Channel in VANETs

This letter proposes a novel proactive congestion control policy for vehicular ad-hoc networks, in which each vehicle's communication parameters are adapted based on their individual application requirements. Contrary to other approaches, where transmission resources tend to be assigned based on system-level performance metrics, the technique proposed in this paper aims to individually satisfy the target application performance of each vehicle, while globally minimising the channel load to prevent channel congestion.
Fast illumination normalization for robust eye localization under variable illumination

Most eye localization methods suffer from illumination variation. To overcome this problem, we propose an illumination nor- malization technique as a preprocessing step before localizing eyes. This technique requires no training process, no assumption on the light conditions, and no alignment between different images for illu- mination normalization. Moreover, it is fast and thus effective for real-time applications. Experiment results verify the effectiveness and efficiency of the eye localization scheme with the proposed illu- mination normalization technique. © 2009 SPIE and
Counterfeits or Shanzhai? The Role of Face and Brand Consciousness in Luxury Copycat Consumption

This study responds to the emergence of the Shanzhai phenomenon in the international marketplace and introduces the Shanzhai phenomenon into the consumer behavior literature by defining it and comparing it with well-known concepts like luxury counterfeits. More specifically, it examines how consumers’ face and brand consciousness influence their willingness to buy luxury counterfeits rather than Shanzhai products. The results show that consumers who are more face conscious are more likely to choose luxury counterfeits than Shanzhai products. In addition, consumers’ face consciousness elicits a high concern for well-known brands, which also in turn leads to a more favorable attitude toward luxury counterfeits than Shanzhai products. These findings enable researchers to better understand consumers’ responses toward both Shanzhai and counterfeit products and help companies that are protecting their original brands to tailor their consumer-directed measures more effectively.
MAP Detection of Misbehaving Relay in Wireless Multiple Access Relay Networks

We propose the maximum a posteriori (MAP) detection of the misbehaving relay that injects false data or adds channel errors into the network encoder in multiple access relay networks. The proposed scheme does not require sending extra bits at the source and is optimal in the sense of minimizing the probability of incorrect detection. We derive the probability of false alarm and misdetection, taking into account the lossy nature of wireless links. The side information regarding the presence of relay misbehavior is exploited at the decoder to mitigate the relay misbehavior and enhance the reliability of decoding.
Longitudinal Predictions of Depression Symptoms Using the Activation and Avoidance Subscales of the Japanese Behavioral Activation for Depression Scale-Short Form

The Behavioral Activation for Depression Scale-Short Form (BADS-SF) is a questionnaire containing two subscales: Activation and Avoidance and was developed to measure changes in client behavior over the course of behavioral activation therapy. This study examines whether the subscales of the Japanese BADS-SF predict the future development of depression. Japanese university students (N = 129) completed the BADS-SF and the Center for Epidemiologic Studies Depression Scale (CES-D) at the baseline and second test conducted eight weeks later, with no intervention in between. Multiple regression analyses revealed that baseline avoidance scores predicted the scores of CES-D during the second test, after controlling for baseline CES-D and the other BADS-SF subscale scores, but the relationship of the Activation subscale with the CES-D scores was not significant. Therefore, the results indicate that the avoidance scale predicts the occurrence of symptoms of depression.
Cultural Differences in Shame and Guilt as Understandable Reasons for Suicide

According to the World Health Organization, a major barrier to suicide prevention work is the social stigma surrounding suicide. Since clinical research has long shown that shame and guilt are often involved in suicide and suicide ideation, the present two studies explore the extent to which individuals associate shame and guilt with suicide ideation and behavior according to their cultural background. Using a scenario approach, 1,147 Americans in two separate studies read about a traumatic situation in which the target person experienced intense shame or intense guilt. A mini meta-analysis of these studies showed that all participants were more likely to link the experience of shame to suicidality than guilt. Additionally, participants from U.S. dignity states were more likely to report suicide ideation when the target experienced guilt as opposed to shame. Our findings support the notion that the centrality of the emotions of shame and guilt varies relative to the social context, which has implications on how others perceive suicide.
Exercise-Induced Physiological Arousal Biases Attention Toward Threatening Scene Details

The present experiment examined whether physiological arousal induced by acute bouts of aerobic exercise would influence attention and memory for scenes depicting or not depicting weapons. In a repeated-measures design, participants exercised at either low or high exertion levels. During exercise, they were presented with images, some of which depicted weapons; immediately following exercise, they completed a recognition test for portions of central and peripheral scene regions. Two primary results emerged. First, in the low exertion condition, we replicated extant research showing inferior peripheral scene memory when images contained, versus did not contain, weapons. Second, the high exertion condition increased central scene memory relative to low exertion, and this effect was specific to images containing weapons. Thus, we provide evidence for accentuated weapon focus effects during states of exercise-induced physiological arousal. These results contribute new applied and theoretical understandings regarding the interactions between physiological state, breadth of attention, and memory.
Using Population-Size Estimation and Cross-sectional Survey Methods to Evaluate HIV Service Coverage Among Key Populations in Burkina Faso and Togo

Objectives: The objective of our study was to measure progress toward the UNAIDS 90-90-90 HIV care targets among key populations in urban areas of 2 countries in West Africa: Burkina Faso and Togo. Methods: We recruited female sex workers (FSWs) and men who have sex with men (MSM) through respondent-driven sampling. From January to July 2013, 2738 participants were enrolled, tested for HIV, and completed interviewer-administered surveys. We used population-size estimation methods to calculate the number of people who were engaged in the HIV continuum of care. Results: HIV prevalence ranged from 0.6% (2 of 329) of MSM in Kara, Togo, to 32.9% (115 of 350) of FSWs in Bobo Dioulasso, Burkina Faso. Of those confirmed to be HIV infected, a range of 0.0% (0 of 2) of MSM in Kara to 55.7% (64 of 115) of FSWs in Bobo Dioulasso were using ART. Based on population estimates, the percentage gap between HIV-infected people who should be using ART (per the 90-90-90 targets) and those who reported using ART ranged from 31.5% among FSWs in Bobo Dioulasso to 100.0% among MSM in Kara. Conclusions: HIV service coverage among MSM and FSWs in Burkina Faso and Togo was low in 2013. Interventions for improving engagement of these at-risk populations in the HIV continuum of care should include frequent, routine HIV testing and linkage to evidence-based HIV treatment services. Population-size estimates can be used to inform governments, policy makers, and funding agencies about where elements of HIV service coverage are most needed.
Detection of Rotavirus G3P[22]Genotype in Gnotobiotic Rabbit Model

Detection of Rotavirus G3P[22]Genotype in Gnotobiotic Rabbit Model Rotaviruses have been recognized as important agents of acute diarrhea in both humans and animals. The use of animal models, including the gnotobiotic rabbit, mouse, piglets, lambs and calves models, has been essential to the understanding of rotavirus infection, pathology, disease, immunity, and testing of vaccine prototypes. The aim of this study was to describe the first detection of rotavirus G3P[22] in rabbits in Brazil and to demonstrate the importance of monitoring gnotobiotic animals used in vaccine clinical tests.
Parameterized variety for multi-view multi-exposure image synthesis and high dynamic range stereo reconstruction

Multi-view stereo, novel view synthesis and high dynamic range (HDR) imaging are three pertinent areas of concern for high quality 3D view generation. This paper presents a novel parameterized variety based model that integrates these different domains into one common framework with an envisioned goal, to accommodate multi-view stereo for multiple exposure input views and to render photo-realistic HDR images from arbitrary virtual viewpoints for high quality 3D reconstruction. We extend the parameterized variety approach for rendering presented earlier by Genc and Ponce [1] to handle full perspective cameras. An efficient algebraic framework is proposed to construct an explicit parameterization of the space of all multi-view multi-exposed images. This characterization of differently exposed views allow to simultaneously recover artifacts free HDR images, and reliable depth maps from arbitrary camera viewpoints. High quality, HDR textured 3D model of the scene is obtained using these images and recovered geometry information.
MakeVR: A 3D world-building interface

MakeVR is an intuitive and accessible digital sandbox for making 3D objects scenes with game-like simplicity for beginners and with advanced tools for experts. It presents a professional CAD engine through a natural immersive two-handed interface. Users reach into space to move themselves through a geometric playground, placing primitive shapes and more complex objects into the scene and then reaching out to modify them via booleans, sweeps, deformation, and other CAD operations. We conducted a preliminary user evaluation of four participant case studies and plan to use this evaluation to improve the system.
Penetrating neck injury: a review

Penetrating injury to the neck has inspired considerable controversy with regard to its management, owing to the large number of important, susceptible structures contained in this area. Mandatory exploration of all wounds has generally given way to selective operative management. Clinical assessment has, once again, become the prime diagnostic tool. This review describes the evolution of management and the value of various diagnostic modalities. It concludes with a summary of appropriate operative techniques.
Robust Absolute Rotation Estimation via Low-Rank and Sparse Matrix Decomposition

This paper proposes a robust method to solve the absolute rotation estimation problem, which arises in global registration of 3D point sets and in structure-from-motion. A novel cost function is formulated which inherently copes with outliers. In particular, the proposed algorithm handles both outlier and missing relative rotations, by casting the problem as a "low-rank & sparse" matrix decomposition. As a side effect, this solution can be seen as a valid and cost-effective detector of inconsistent pair wise rotations. Computational efficiency and numerical accuracy, are demonstrated by simulated and real experiments.
Convolutional Fisher Kernels for RGB-D Object Recognition

This paper studies the problem of improving object recognition using the novel RGB-D data. To address the problem, a new convolutional Fisher Kernels (CFK) method is proposed to represent RGB-D objects powerfully yet efficiently. The core idea of our approach is to integrate the both advantages of the convolutional neural networks (CNN) and Fisher Kernel encoding (FK): CNN model is flexible to adapt to new data sources, but requires for large amounts of training data with significant computational resources for good generalization, In comparison, FK encoding is able to represent objects powerfully and efficiently with small training data, however, its success highly depends on the well-designed SIFT features in literature, which may not be suitable for the new depth data. CFK can be interpreted as a two-layer feature learning structure to bridge the two models. The first layer employs a single-layer CNN to learn low-level translation ally invariant features for both RGB and depth data efficiently. The second layer aggregates the convolutional responses by FK encoding. Here 2D and 3D spatial pyramids are applied to further improve the Fisher vector representation of each modality. Experiments on RGB-D object recognition benchmarks demonstrate that our approach can achieve the state-of-the-art results.
Synthetic Prior Design for Real-Time Face Tracking

Real-time facial performance capture has recently been gaining popularity in virtual film production, driven by advances in machine learning, which allows for fast inference of facial geometry from video streams. These learning-based approaches are significantly influenced by the quality and amount of labelled training data. Tedious construction of training sets from real imagery can be replaced by rendering a facial animation rig under on-set conditions expected at runtime. We learn a synthetic actor-specific prior by adapting a state-of-the-art facial tracking method. Synthetic training significantly reduces the capture and annotation burden and in theory allows generation of an arbitrary amount of data. But practical realities such as training time and compute resources still limit the size of any training set. We construct better and smaller training sets by investigating which facial image appearances are crucial for tracking accuracy, covering the dimensions of expression, viewpoint and illumination. A reduction of training data in 1-2 orders of magnitude is demonstrated whilst tracking accuracy is retained for challenging on-set footage.
Antiulcer Effect of Bark Extract of Tabebuia avellanedae: Activation of Cell Proliferation in Gastric Mucosa During the Healing Process

Tabebuia avellanedae (syn. Handroanthus impetiginosus) is popularly known as ‘ipê‐roxo’ and has been used in folk medicine as anti‐inflammatory and in the treatment of ulcers, bacterial and fungal infections. This study evaluated the gastric ulcer healing property of the ethanolic extract (EET) of barks from Tabebuia avellanedae and investigated the mechanisms that may underlie this effect. Rats were treated with EET (twice a day for 7 days) after induction of chronic gastric ulcers by 80% acetic acid. Following treatment, histological and immunohistochemical analysis were performed in gastric ulcer tissues. Oral administration of EET (100 and 300 mg/kg) significantly reduced the gastric lesion induced by acetic acid in 44 and 36%, respectively. Histopathological evaluation demonstrated a contraction of gastric ulcer size, increase of mucus layer (periodic acid‐Schiff stained mucin‐like glycoproteins) and cell proliferation (proliferating cell nuclear antigen immunohistochemistry) in animals treated with EET (100 and 300 mg/kg). The results demonstrate that EET significantly accelerates healing of acetic acid induced gastric ulcer in rats through increase of mucus content and cell proliferation, indicating a potential usefulness for treatment of peptic ulcer diseases. Copyright © 2012 John Wiley & Sons, Ltd.
Inter-Chunk Popularity-Based Edge-First Caching in Content-Centric Networking

Content-centric networking (CCN) is considered promising for the efficient support of ever-increasing streaming multimedia services. Inter-chunk popularity-based caching is one of the key requirements in CCN multimedia services because some chunks of a content file tend to be requested more frequently than others. For multimedia contents, forepart chunks often have higher popularity than others as users may interrupt and abort before finishing its service. This paper presents a novel cache replication scheme, which places more popular chunks ahead on the edge router, and establishes a cache pipelining on the relaying routers along the path to reduce user-perceived delay. Simulation results show that the proposed scheme incurs less delay and reduces the overall redundant network traffic while guaranteeing a higher cache hit ratio.