Miracle-dz/UniFAR-FTUs huggingface dataset:
High-Quality Real-Time Stereo Using Adaptive Cost Aggregation and Dynamic Programming

We present a stereo algorithm that achieves high quality results while maintaining real-time performance. The key idea is simple: we introduce an adaptive aggregation step in a dynamic-programming (DP) stereo framework. The per-pixel matching cost is aggregated in the vertical direction only. Compared to traditional DP, our approach reduces the typical "streaking" artifacts without the penalty of blurry object boundaries. Evaluation using the benchmark Middlebury stereo database shows that our approach is among the best (ranked first in the new evaluation system) for DP-based approaches. The performance gain mainly comes from a computationally expensive weighting scheme based on color and distance proximity. We utilize the vector processing capability and parallelism in commodity graphics hardware to speed up this process over two orders of magnitude. Over 50 million disparity evaluations per second (MDE/s)1 are achieved in our current implementation.
Metastasis-Associated Protein 3 (MTA3) Regulates G2/M Progression in Proliferating Mouse Granulosa Cells1

ABSTRACT Metastasis-associated protein 3 (MTA3) is a constituent of the Mi-2/nucleosome remodeling and deacetylase (NuRD) protein complex that regulates gene expression by altering chromatin structure and can facilitate cohesin loading onto DNA. The biological function of MTA3 within the NuRD complex is unknown. Herein, we show that MTA3 was expressed highly in granulosa cell nuclei of all ovarian follicle stages and at lower levels in corpora lutea. We tested the hypothesis that MTA3-NuRD complex function is required for granulosa cell proliferation. In the ovary, MTA3 interacted with NuRD proteins CHD4 and HDAC1 and the core cohesin complex protein RAD21. In cultured mouse primary granulosa cells, depletion of endogenous MTA3 using RNA interference slowed cell proliferation; this effect was rescued by coexpression of exogenous MTA3. Slowing of cell proliferation correlated with a significant decrease in cyclin B1 and cyclin B2 expression. Granulosa cell populations lacking MTA3 contained a significantly higher percentage of cells in G2/M phase and a lower percentage in S phase compared with control cells. Furthermore, MTA3 depletion slowed entry into M phase as indicated by reduced phosphorylation of histone H3 at serine 10. These findings provide the first evidence to date that MTA3 interacts with NuRD and cohesin complex proteins in the ovary in vivo and regulates G2/M progression in proliferating granulosa cells.
In vitro Cytotoxic Effect of Brazilian Green Propolis on Human Laryngeal Epidermoid Carcinoma (HEp-2) Cells

Propolis is a sticky dark-colored material showing a very complex chemical composition that honeybees collect from plants. It has been used in folk medicine since ancient times, due to several biological properties, such as antimicrobial, anti-inflammatory, antioxidant and immunomodulatory activities, among others. Its antitumor action in vivo and in vitro has also been reported, using propolis extracts or its isolated compounds. The goal of this work was to evaluate propolis's cytotoxic action in vitro on human laryngeal epidermoid carcinoma (Hep-2) cells. These cells were incubated with different concentrations of this bee product for different time periods, and morphology and the number of viable HEp-2 cells analyzed. Data showed that propolis exhibited a cytotoxic effect in vitro against HEp-2 cells, in a dose- and time-dependent way. Propolis solvent had no effects on morphology and number of viable cells, proving that the cytotoxic effects were exclusively due to propolis components. Since humans have been using propolis for a long time, further assays will provide a better comprehension of propolis's antitumor action.
Effects of Vocabulary Games on Lexical Growth and Retention of Low-Motivated EFL Learners in Taiwan

To examine the effects of a vocabulary strategy game program on compound noun learning and consolidation, a 20-hour quasi-experimental single group time-series research study was designed. A total of 79 low-motivated Taiwanese college students at the CEFR A1 (pre-basic) and A2 (basic) English proficiency levels participated in the study. Poker, Chinese chess, and gobang, along with several memorization-enhancing techniques, were utilized to facilitate vocabulary learning. Four specific research questions guided the study. The first looked independently at the effects of the invented poker, chess, and gobang games on vocabulary learning; the second at the holistic effect of the vocabulary program; the third at the effect of the game program on lexical retention one month later; and, finally, the fourth examined the effects across subgroups of different proficiency levels. Data were collected via the administration of a 174-item compound-noun test as pretest, after-poker test, after-chess test, posttest, and retention test. The data were analyzed with one-way repeated measures ANOVAs with subsequent protected t tests on top of descriptive statistics and independent-samples t tests. The results have shown that the vocabulary games, whether utilized independently or as a whole program, effectively facilitate learners’ lexical growth and retention. Pedagogical implications and suggestions for further studies are addressed.
An Algorithm to Extract Jamaican Geographic Locations from News Articles - Using NLP Techniques

Natural Language Processing (NLP) has long been used to extract information from large bodies of text. NLP is often used to intelligently parse large volumes of data where the manual alternative may be infeasible. Named Entity Recognition (NER) is used to extract named entities such as people, places or organizations from text written in natural language. Using NER, NLP algorithms can be created to extract the mentions of geographic locations of different types from current and archived news articles. This information can be used to add a spatial window into previously flat datasets, allowing users to access information by filtering location information. Information that is derived can be used to support intelligent decision making and influence expert systems. This paper describes the development of an algorithm that uses the principles of both NLP and NER to extract references to geographic locations within news articles. The algorithm has been developed using the NLTK and Pattern Web Toolkit for Python and performs with a precision and accuracy above eighty (80) percent.
The 14-3-3 proteins in the teleost fish rainbow trout (Oncorhynchus mykiss)

SUMMARY We report studies of 14-3-3 genes in rainbow trout, adding to current understanding of the molecular evolution of this multigene family and its functional importance in fish. Ten genes were identified that are apparent duplicates of five ancestors. The duplicated 14-3-3 genes diverged rapidly and their cladogram is markedly different from the phylogenetic tree. The mean rate of nonsynonymous divergence of trout 14-3-3 genes is one order of magnitude greater than that of mammalian genes. An evolutionarily recent genome duplication in salmonid fish relaxed functional constraints, and selection favored establishment of novel isoforms. Differences in tissue distribution of 14-3-3 genes were minor; however, results of 31 microarray experiments showed divergence of expression profiles, which was related to structural divergence of the duplicates. We observed remarkable coordination of expression of all isoforms in our study of stress response in the brain. Profiles of the 14-3-3 genes correlated with a large group of chaperones and genes involved in cell communication and signal transduction. We studied embryonic expression of 14-3-3 genes and found abundant transcripts in the rapidly growing and differentiating parts of embryos such as eyes, tail bud and yolk syncytium during somitogenesis and in gills and pectoral fins after completion of somitogenesis. Consistent expression was observed in the neural crest, which is known to have high morphogenetic potential.
Classification of Boar Sperm Head Images using Learning Vector Quantization

We apply Learning Vector Quantization (LVQ) in automated boar semen quality assessment. The classification of single boar sperm heads into healthy (normal) and non-normal ones is based on grey-scale microscopic images only. Sample data was classified by veterinary experts and is used for training a system with a number of prototypes for each class. We apply as training schemes Kohonen’s LVQ1 and the variants Generalized LVQ (GLVQ) and Generalized Relevance LVQ (GRLVQ). We compare their performance and study the influence of the employed metric.
Measles Outbreak in South of Iran, Where Vaccine Coverage Was High: A Case-Series Study

Abstract Background Measles is a highly contagious viral disease that remains an important cause of mortality among children despite the availability of a safe and effective vaccine around the world. We aimed this study to show a measles out-break occurring. Methods In early 2012, a report of measles outbreak was recorded on center for disease control (CDC) of Fars province, south of Iran. With this case-series study, characteristics of cases and network transition model were described. Results The primary case was an Afghan refugee who is likely to carry the measles virus from its country or from anywhere in Iran to Koordeh, a small village in south of Iran. Followed by the Afghan case, 6 secondary and tertiary cases including rural health worker, were occurred. Except a case of 35 year old, in which her vaccination status was unknown, all cases has had adherence to vaccination protocol. Conclusion More immunologic and vaccine quality investigations are needed to find the main cause of the outbreak. Nonetheless, due to the warm weather, probable bad temperature management of cold chain and technical problem in vaccination are the main suspicious reasons of the outbreak.
Patient Preference and Adherence Complex sleep apnea syndrome

Correspondence: Jing Feng Respiratory Department of Tianjin Medical University General Hospital, Tianjin 300052, People's Republic of China Email zyyhxkfj@126.com; jing.feng2@duke.edu Abstract: Complex sleep apnea syndrome (CompSAS) is a distinct form of sleep-disordered breathing characterized as central sleep apnea (CSA), and presents in obstructive sleep apnea (OSA) patients during initial treatment with a continuous positive airway pressure (CPAP) device. The mechanisms of why CompSAS occurs are not well understood, though we have a high loop gain theory that may help to explain it. It is still controversial regarding the prevalence and the clinical significance of CompSAS. Patients with CompSAS have clinical features similar to OSA, but they do exhibit breathing patterns like CSA. In most CompSAS cases, CSA events during initial CPAP titration are transient and they may disappear after continued CPAP use for 4∼8 weeks or even longer. However, the poor initial experience of CompSAS patients with CPAP may not be avoided, and nonadherence with continued therapy may often result. Treatment options like adaptive servo-ventilation are available now that may rapidly resolve the disorder and relieve the symptoms of this disease with the potential of increasing early adherence to therapy. But these approaches are associated with more expensive and complicated devices. In this review, the definition, potential plausible mechanisms, clinical characteristics, and treatment approaches of CompSAS will be summarized.
High-Resolution Mapping and Functional Analysis of se2.1

The degree to which stigmas are exserted above the stamen in flowers is a key determinant of cross-pollination (and hence allogamy) in many plant species. Most species in the genus Lycopersicon are obligate or facultative outcrossers and bear flowers with highly exserted stigmas. In contrast, the cultivated tomato (Lycopersicon esculentum) bears flowers with flush or inserted stigmas promoting self-fertilization. It has been observed that a major QTL, se2.1, on chromosome 2 is responsible for a large portion of phenotypic variation for this trait and that mutation(s) at this locus were likely involved in the evolution from allogamy to autogamy in this genus. To understand the genetic and molecular basis of stigma exsertion, we have conducted a high-resolution mapping at the chromosome region harboring the se2.1 QTL. The results indicate that this is a compound locus, comprising at least five tightly linked genes, one controlling style length, three controlling stamen length, and the other affecting anther dehiscence, a taxonomic character used to distinguish Lycopersicon species from other solanaceous species. This cluster of genes may represent the vestiges of an ancient coadapted gene complex in controlling mating behavior.
Reinforcement Social Learning of Coordination in Networked Cooperative Multiagent Systems

The problem of coordination in cooperative multiagent systems has been widely studied in the literature. In practical complex environments, the interactions among agents are usually regulated by their underlying network topology, which, however, has not been taken into consideration in previous work. To this end, we firstly investigate the multiagent coordination problems in cooperative environments under the networked social learning framework focusing on two representative topologies: the small-world and the scale-free network. We consider a population of agents where each agent interacts with another agent randomly chosen from its neighborhood in each round. Each agent learns its policy through repeated interactions with its neighbors via social learning. It is not clear a priori if all agents can learn a consistent optimal coordination policy and what kind of impact different topology parameters could have on the learning performance of agents. We distinguish two types of learners: individual action learner and joint action learner. The learning performances of both learners are evaluated extensively in different cooperative games, and the influence of different factors on the learning performance of agents is investigated and analyzed as well.
Advanced Pattern based Memory Controller for FPGA based HPC applications

The ever-increasing complexity of high-performance computing applications limits performance due to memory constraints in FPGAs. To address this issue, we propose the Advanced Pattern based Memory Controller (APMC), which supports both regular and irregular memory patterns. The proposed memory controller systematically reduces the latency faced by processors/accelerators due to irregular memory access patterns and low memory bandwidth by using a smart mechanism that collects and stores the different patterns and reuses them when it is needed. In order to prove the effectiveness of the proposed controller, we implemented and tested it on a Xilinx ML505 FPGA board. In order to prove that our controller is efficient in a variety of scenarios, we used several benchmarks with different memory access patterns. The benchmarking results show that our controller consumes 20% less hardware resources, 32% less on chip power and achieves a maximum speedup of 52× and 2.9× for regular and irregular applications respectively.
Evolution of amber suppressor tRNAs for efficient bacterial production of proteins containing nonnatural amino acids.

Open in a separate window Regions of the M. jannaschii tyrosyl tRNACUA thought to interact with elongation factor Tu were randomized, and the resulting tRNA libraries were subjected to in vitro evolution. The tRNAs identified resulted in significantly improved unnatural amino acid-containing protein yields. In some cases, the degree of improvement varied in an amino acid-dependent manner.
Effects of body fat distribution on regional lipolysis in obesity.

UNLABELLED To determine the contribution of the major body fat depots to systemic free fatty acid (FFA) availability, palmitate ([1-14C]-palmitate) release was measured from leg (lower body) and non-leg (upper body) fat in eight upper body obese (UB Ob), six lower body obese (LB Ob), and six nonobese (Non Ob) age-matched premenopausal women in the overnight postabsorptive state. Splanchnic palmitate release was determined in 16 of these subjects. RESULTS total palmitate release was greater in UB Ob (P less than 0.005) than LB Ob or Non Ob women (161 +/- 16 vs. 111 +/- 9 vs. 92 +/- 9 mumol/min, respectively). Despite increased leg fat mass in obese women, leg palmitate release was similar in each group. Therefore, leg fat palmitate release was greater in Non Ob women than LB Ob (P less than 0.01) or UB Ob (P = 0.06) women (3.7 +/- 0.3 vs. 2.4 +/- 0.2 vs. 2.7 +/- 0.2 mumol.kg fat-1.min-1, respectively). Upper body fat palmitate release was less (P less than 0.01) in LB Ob than Non Ob or UB Ob women (3.0 +/- 0.4 vs. 5.0 +/- 0.3 vs. 4.9 +/- 0.4 mumol.kg fat-1.min-1, respectively). Splanchnic palmitate release accounted for 20-32% of upper body fat palmitate release in each group (P = NS between groups). Leg fat palmitate release was significantly less than upper body fat palmitate release. We conclude that the major difference in resting FFA metabolism between UB Ob and LB Ob women is the ability of the later to down-regulate upper body fat lipolysis to maintain normal FFA availability.
A Framework for Video Network Coding with Multi-generation Mixing

Multi-Generation Mixing (MGM) is a generalized approach of Network Coding (NC) that has its improvements when applied in packet loss networks. In this paper we apply MGM network coding in networks communicating video contents. NC has shown viable improvements when applied in packet loss networks. With practical network coding (generation based network coding), packets are grouped in chunks called generations. Generation is the unit of network coding encoding and decoding. The generation grouping of packets is necessary for the practical deployment of network coding. On the other hand it increases the cost of NC losses. NC losses reduce the ability of receiver to decode packets, and hence can severely degrade the quality of recovered video. Video is encoded in layers with Scalable Video Coding (SVC) a base layer and one or more enhancement layers. MGM employs the layering of scalable video to enhance the reliability of communication. MGM provides different levels of reliable communication for the different video layers to improve the overall reliability of video communication. SVC enhancement layers are dependent on lower layers to be recovered. With MGM enhancement layers support the recovery of lower layers. This is done by network encoding lower video layers in higher layers. Through extensive simulations, we show that MGM highly improves the quality of recovered video.
Model selection in non-nested hidden Markov models for ion channel gating.

An important task in the application of Markov models to the analysis of ion channel data is the determination of the correct gating scheme of the ion channel under investigation. Some prior knowledge from other experiments can reduce significantly the number of possible models. If these models are standard statistical procedures nested like likelihood ratio testing, provide reliable selection methods. In the case of non-nested models, information criteria like AIC, BIC, etc., are used. However, it is not known if any of these criteria provide a reliable selection method and which is the best one in the context of ion channel gating. We provide an alternative approach to model selection in the case of non-nested models with an equal number of open and closed states. The models to choose from are embedded in a properly defined general model. Therefore, we circumvent the problems of model selection in the non-nested case and can apply model selection procedures for nested models.
CONSTRAINED OPTIMISATION OF 3 D POLYGONAL MESHWATERMARKING BY QUADRATIC PROGRAMMING

In this paper, we propose a blind and robust watermarking method for 3D polygonal meshes by minimising the mean square error between the original mesh and the watermarked mesh under several constraints. We have formulated the problem of assigning distortions to points in a 3D mesh to a quadratic programming problem, so it can be solved reliably and efficiently. Comparing with similar approaches in [1], experiments indicate the advantages of our method in resisting Gaussian noise.
Ordering and Elimination Based Component Learning Method

In this paper, we propose a component learning method to learn a set of Gaussian components that fit the given data distribution. An ordering and visualization technique called OPTICS and tests of multinormality are used in this method. We consider the applications of the proposed method to the tasks of classification and clustering. Here, the components are used to define a feature space to which the data points are transformed. In that feature space, classification is performed using linear support vector machines and clustering is performed using support vector clustering. The performance of the component learning method and its application to classification and clustering is demonstrated on synthetic datasets.
Author ' s personal copy Establishing object correspondence across eye movements : Flexible use of spatiotemporal and surface feature information q

Visual input is frequently disrupted by eye movements, blinks, and occlusion. The visual system must be able to establish correspondence between objects visible before and after a disruption. Current theories hold that correspondence is established solely on the basis of spatiotemporal information, with no contribution from surface features. In five experiments, we tested the relative contributions of spatiotemporal and surface feature information in establishing object correspondence across saccades. Participants generated a saccade to one of two objects, and the objects were shifted during the saccade so that the eyes landed between them, requiring a corrective saccade to fixate the target. To correct gaze to the appropriate object, correspondence must be established between the remembered saccade target and the target visible after the saccade. Target position and surface feature consistency were manipulated. Contrary to existing theories, surface features and spatiotemporal information both contributed to object correspondence, and the relative weighting of the two sources of information was governed by the demands of the task. These data argue against a special role for spatiotemporal information in object correspondence, indicating instead that the visual system can flexibly use multiple sources of relevant information. 2008 Elsevier B.V. All rights reserved.
Document image dewarping using Kinect depth sensor

This paper presents a novel approach for document de-warping using Microsoft Kinect camera sensor. The proposed method makes use of the 3D model of the warped document using Kinect sensor. Due to the low resolution of Kinect's RGB camera, an external high resolution camera is used for capturing a higher quality image. The point cloud captured by Kinect depth sensor is down sampled and then the voxilized grid approach is applied. Then a triangulation mesh is generated using greedy fast triangulation method. In the next step, a conformal 3D to 2D mapping is applied to the curved mesh. This creates a flat plane of the 3D mesh. Eventually, the original image is converted to the flatted version by a 2D to 2D mapping method. Text independency of this method distinguishes it from the other methods which use the document text lines to estimate the curvature of the plane. By using this method, documents with different distortions and with any kind of content such as pictures, graphs and tables can be de-warped.