Miracle-dz/UniFAR-FTUs huggingface dataset:
Papillorenal Syndrome-Causing Missense Mutations in PAX2/Pax2 Result in Hypomorphic Alleles in Mouse and Human

Papillorenal syndrome (PRS, also known as renal-coloboma syndrome) is an autosomal dominant disease characterized by potentially-blinding congenital optic nerve excavation and congenital kidney abnormalities. Many patients with PRS have mutations in the paired box transcription factor gene, PAX2. Although most mutations in PAX2 are predicted to result in complete loss of one allele's function, three missense mutations have been reported, raising the possibility that more subtle alterations in PAX2 function may be disease-causing. To date, the molecular behaviors of these mutations have not been explored. We describe a novel mouse model of PRS due to a missense mutation in a highly-conserved threonine residue in the paired domain of Pax2 (p.T74A) that recapitulates the ocular and kidney findings of patients. This mutation is in the Pax2 paired domain at the same location as two human missense mutations. We show that all three missense mutations disrupt potentially critical hydrogen bonds in atomic models and result in reduced Pax2 transactivation, but do not affect nuclear localization, steady state mRNA levels, or the ability of Pax2 to bind its DNA consensus sequence. Moreover, these mutations show reduced steady-state levels of Pax2 protein in vitro and (for p.T74A) in vivo, likely by reducing protein stability. These results suggest that hypomorphic alleles of PAX2/Pax2 can lead to significant disease in humans and mice.
Experimental study on modulus and hardness of ettringite

The experimental study on the modulus and hardness (in-press rigidity) of ettringite is carried out in this work. Firstly, the ettringite is obtained by chemical synthesis method. Secondly, samples are formed by filling the ettringite into resin matrix. Thirdly, the indentation modulus and hardness of ettringite are measured with different indentation depths by virtue of the instrument of MTS Nanoindenter XP. Finally, analysis on the modulus and hardness of the ettringite is performed according to the sample unloading curves. The results given by this work indicate that the magnitude of the modulus is 20.07 GPa and the hardness is 0.613 GPa.
Research on singlemode fiber and graded index multimode fiber simulating collimator

An all-fiber device using single mode fiber with graded-index multimode fiber to fabricate a collimator is investigated. This device has advantages of small size, low splicing loss and ease of fabrication, and it could substitute bulky GRIN lens. Experiments show that it has the best collimating effect when the length of graded-index fiber is between 305 μm and 315 μm.
Neural Gas for Sequences

For unsupervised sequence processing, standard self organizing maps (SOM) can be naturally extended by recurrent connections and explicit context representations. Known models are the temporal Kohonen map (TKM), recursive SOM, SOM for structured data (SOMSD), and HSOM for sequences (HSOM-S). We discuss and compare the capabilities of exemplary approaches to store different types of sequences. A new efficient model, the Merge-SOM (MSOM), is proposed, combining ideas of TKM and SOMSD, and which is well suited for processing sequences with dynamic multimodal densities.
Chronic Childhood Constipation Is Associated with Impaired Quality of Life: A Case-Controlled Study

Objective: The objective of this study was to investigate the effect of chronic constipation on children's quality of life. Methods: From October 2002 to November 2003, 224 children (140 male, 84 female, aged 10.6 ± 2.9 years) and 224 parents were evaluated by a health related quality of life tool during initial outpatient consultation. Children with constipation (n = 80) were compared with controls with inflammatory bowel disease (n = 42), controls with gastroesophageal reflux disease (n = 56), and with healthy children (n = 46). Results: Children with constipation had lower quality of life scores than did those with inflammatory bowel disease (70 versus 84; P < 0.05), gastroesophageal reflux disease (70 versus 80; P < 0.05), and healthy children (70 versus 88; P < 0.05). Children with constipation reported lower physical scores than did inflammatory bowel disease patients (75 versus 85; P < 0.02), gastroesophageal reflux disease patients (75 versus 85; P < 0.05), or healthy children (75 versus 87; P < 0.05). Parents of children with constipation reported lower scores than did their children (61 versus 70; P < 0.05). Children with constipation had longer duration of symptoms than did the controls with inflammatory bowel disease and gastroesophageal reflux disease (43.8 months versus 14.2 months; P < 0.001). Prolonged duration of symptoms for children with constipation correlated with lower parent-reported scores (P < 0.002). Conclusions: At initial evaluation, children with constipation have a lower quality of life than do children with inflammatory bowel disease or gastroesophageal reflux disease. Self-reported lower scores may be a reflection of impaired physical ability. Parental perceptions of low quality of life are probably impacted by the duration of their child's symptoms and by family members with similar complaints. Practitioners should be aware of the high level of parental concern and the relatively low self-reported and parent-reported quality of life in children with chronic constipation as they plan therapy.
Barycentric quantization for planning in continuous domains

We consider the class of planning and sequential decision making problems where the state space has continuous components, but the available actions come from a discrete set, and argue that a suitable approach for solving them could involve an appropriate quantization scheme for the continuous state variables, followed by approximate dynamic programming. We propose one such scheme based on barycentric approximations that effectively converts the continuous dynamics into a Markov decision process, and demonstrate that it can be viewed both as an approximation to the continuous dynamics, as well as a value function approximator over the continuous domain. We describe the application of this method to several hard industrial problems, and point out additional candidate problems that could be amenable to it.
Subpixel edge detection for dimensional control by artificial vision

Dimensional control by artificial vision is becoming a standard tool for industrialists interested in such remote and without contact measurement methods. The expected precision of those systems is largely dependent on camera resolution and high precision requires very costly CCD sensor and frame grabber. A method is proposed which tends to increase significantly the precision of dimensional measurements without increasing the hardware complexity. This algorithm is also quite robust against noisy images such that it could be encountered in real world imaging, a precision of 1/16 pixel can easily be obtained with SNR equals 2 dB. Dimensional control by artificial vision generally involves an edge detection stage in its process, it is this step that we propose to improve. A lot of edge detection techniques with pixel resolution are well known and some of them are designed in order to be robust against image corruption. On the other hand B-spline interpolation methods have been considerably improved and popularized by the signal processing techniques proposed by M. Unser and Al. An algorithm resulting from the merging of these two ideas is proposed in this paper. In this algorithm, the interpolation is prepared by an optimized filtering and by a detection of local maxima of gradient.
"Shin-hanga" Filter with Improved Contour Lines and Gradation

The filter simulates "Shinhanga," multi-colored woodblock print, which was once popular in Japan around one hundred years ago. We expect that the filter sheds light again on this fascinating art style. The filter follows three steps to simulate contour lines and gradation, which characterize "Shinhanga"; The filter extracts contour lines based on hue of an original image, then determines the direction of color gradient in each region either vertically or horizontally, based on the amount and the direction of variation of hue in each region. We improved the contour lines and gradation process from the previous filter to broaden its applicability and conducted an experiment to assess it. The result suggests that the filter has less dependency to the types of images comparing to our previously proposed method.
Payload estimation based on identified coefficients of robot dynamics — With an application to collision detection

We revisit the classical problem of estimating the dynamic parameters of an unknown payload rigidly held by the robot end effector. The approach relies on the analysis of the symbolic expressions of the robot dynamic coefficients (i.e., combinations of dynamic parameters) when working with and without payload, with no special assumptions on payload structure. The linearity of the associated changes in the dynamic coefficients due to the payload addition is exploited so as to estimate the gravity and inertial parameters of the payload. The procedure is illustrated in simulation on a planar 2R robot with asymmetric payload and through experiments on a 7R KUKA LWR arm with medium payloads. Accurate estimates of non-inertial payload parameters can be obtained even by running the identification scheme on few small motions in a restricted area. The results are shown to be useful for improving the sensorless collision detection capabilities of a robot arm in the presence of an a priori unknown payload.
Stationary Mixing Bandits

We study the bandit problem where arms are associated with stationary phi-mixing processes and where rewards are therefore dependent: the question that arises from this setting is that of recovering some independence by ignoring the value of some rewards. As we shall see, the bandit problem we tackle requires us to address the exploration/exploitation/independence trade-off. To do so, we provide a UCB strategy together with a general regret analysis for the case where the size of the independence blocks (the ignored rewards) is fixed and we go a step beyond by providing an algorithm that is able to compute the size of the independence blocks from the data. Finally, we give an analysis of our bandit problem in the restless case, i.e., in the situation where the time counters for all mixing processes simultaneously evolve.
Automating Service Negotiation Process for Service Architecture on the cloud by using Semantic Methodology

the appearance of Cloud Computing is changing the way in which software services are delivered and consumed. There is increased the need for Cloud environment to control the quality and standards of software offered on their environment by having different kinds of policy. Virtualized service models are now appearing and redefining the way of Information Technology is delivered. Dealing with all these services perform on the cloud is the open challenge. This unified method for architecture of services that delivered on the cloud. These services architecture is divided into five parts of Specification, Finding, Negotiation, Composition, and Utilization. These five parts are very important in the architecture of services and also describe the high level framework for services. The Goal of this to automating composite IT related services using Negotiation process. Keywords-Cloud Computing; Semantic Web; Web Based Services; Service Architecture.
Engineering graph clustering: Models and experimental evaluation

A promising approach to graph clustering is based on the intuitive notion of intracluster density versus intercluster sparsity. As for the weighted case, clusters should accumulate lots of weight, in contrast to their connection to the remaining graph, which should be light. While both formalizations and algorithms focusing on particular aspects of this rather vague concept have been proposed, no conclusive argument on their appropriateness has been given. In order to deepen the understanding of particular concepts, including both quality assessment as well as designing new algorithms, we conducted an experimental evaluation of graph-clustering approaches. By combining proved techniques from graph partitioning and geometric clustering, we also introduce a new approach that compares favorably.
Activation of Duck RIG-I by TRIM25 Is Independent of Anchored Ubiquitin

Retinoic acid inducible gene I (RIG-I) is a viral RNA sensor crucial in defense against several viruses including measles, influenza A and hepatitis C. RIG-I activates type-I interferon signalling through the adaptor for mitochondrial antiviral signaling (MAVS). The E3 ubiquitin ligase, tripartite motif containing protein 25 (TRIM25), activates human RIG-I through generation of anchored K63-linked polyubiquitin chains attached to lysine 172, or alternatively, through the generation of unanchored K63-linked polyubiquitin chains that interact non-covalently with RIG-I CARD domains. Previously, we identified RIG-I of ducks, of interest because ducks are the host and natural reservoir of influenza viruses, and showed it initiates innate immune signaling leading to production of interferon-beta (IFN-β). We noted that K172 is not conserved in RIG-I of ducks and other avian species, or mouse. Because K172 is important for both mechanisms of activation of human RIG-I, we investigated whether duck RIG-I was activated by TRIM25, and if other residues were the sites for attachment of ubiquitin. Here we show duck RIG-I CARD domains are ubiquitinated for activation, and ubiquitination depends on interaction with TRIM25, as a splice variant that cannot interact with TRIM25 is not ubiquitinated, and cannot be activated. We expressed GST-fusion proteins of duck CARD domains and characterized TRIM25 modifications of CARD domains by mass spectrometry. We identified two sites that are ubiquitinated in duck CARD domains, K167 and K193, and detected K63 linked polyubiquitin chains. Site directed mutagenesis of each site alone, does not alter the ubiquitination profile of the duck CARD domains. However, mutation of both sites resulted in loss of all attached ubiquitin and polyubiquitin chains. Remarkably, the double mutant duck RIG-I CARD still interacts with TRIM25, and can still be activated. Our results demonstrate that anchored ubiquitin chains are not necessary for TRIM25 activation of duck RIG-I.
On the Desirability of Acyclic Database Schemes

A class of database schemes, called acychc, was recently introduced. It is shown that this class has a number of desirable properties. In particular, several desirable properties that have been studied by other researchers m very different terms are all shown to be eqmvalent to acydicity. In addition, several equivalent charactenzauons of the class m terms of graphs and hypergraphs are given, and a smaple algorithm for determining acychclty is presented. Also given are several eqmvalent characterizations of those sets M of multivalued dependencies such that M is the set of muRlvalued dependencies that are the consequences of a given join dependency. Several characterizations for a conflict-free (in the sense of Lien) set of muluvalued dependencies are provided.
Leave-one-out Authentication of Persons Using 40 Hz EEG Oscillations

It has been shown previously that recognizing persons using 40 Hz electroencephalogram (EEG) oscillations is possible. In the method, features were computed from the visual evoked potential (VEP) signals recorded from 61 electrodes while subjects perceived a picture. Here, two modifications have been proposed to improve the classification performance: principal component analysis (PCA) to reduce the noise and background EEG effects from the VEP signals and normalization. Two classifiers were used: simplified fuzzy ARTMAP (SFA), and k-nearest neighbor (kNN). The experimental results using 800 VEP signals from 20 subjects with leave-one-out cross validation strategy showed that PCA and normalization improved the classification performance for both the classifiers. The best classification performance of 95.25% obtained using the improved method shows that 40 Hz EEG oscillations are suitable for use as biometrics
Distributed attitude and position consensus for networked rigid bodies based on unit dual quaternion

This paper provides unified solutions for distributed attitude and position consensus problems for networked fully actuated rigid bodies under the fixed and undirected communication topology, based on unit dual quaternion. We investigate two kinds of consensus, i.e., leader-following consensus with a static leader and leaderless consensus. Firstly, the dynamics of rigid bodies are presented by unit dual quaternion. The control torques and the control forces of rigid bodies are also given from unit dual quaternion. Secondly, the consensus problem with a static leader is studied. And with the proposed control law, all rigid bodies converge to the constant desired attitude and the constant desired position. Thirdly, we propose a distributed control law to guarantee that the attitudes and positions of all rigid bodies converge to the same values respectively without a leader.
Cardiac arrest during long-distance running races.

BACKGROUND Approximately 2 million people participate in long-distance running races in the United States annually. Reports of race-related cardiac arrests have generated concern about the safety of this activity. METHODS We assessed the incidence and outcomes of cardiac arrest associated with marathon and half-marathon races in the United States from January 1, 2000, to May 31, 2010. We determined the clinical characteristics of the arrests by interviewing survivors and the next of kin of nonsurvivors, reviewing medical records, and analyzing postmortem data. RESULTS Of 10.9 million runners, 59 (mean [±SD] age, 42-13 years; 51 men) had cardiac arrest (incidence rate, 0.54 per 100,000 participants; 95% confidence interval [CI], 0.41 to 0.70). Cardiovascular disease accounted for the majority of cardiac arrests. The incidence rate was significantly higher during marathons (1.01 per 100,000; 95% CI, 0.72 to 1.38) than during half-marathons (0.27; 95% CI, 0.17 to 0.43) and among men (0.90 per 100,000; 95% CI, 0.67 to 1.18) than among women (0.16; 95% CI, 0.07 to 0.31). Male marathon runners, the highest-risk group, had an increased incidence of cardiac arrest during the latter half of the study decade (2000-2004, 0.71 per 100,000 [95% CI, 0.31 to 1.40]; 2005-2010, 2.03 per 100,000 [95% CI, 1.33 to 2.98]; P=0.01). Of the 59 cases of cardiac arrest, 42 (71%) were fatal (incidence, 0.39 per 100,000; 95% CI, 0.28 to 0.52). Among the 31 cases with complete clinical data, initiation of bystander-administered cardiopulmonary resuscitation and an underlying diagnosis other than hypertrophic cardiomyopathy were the strongest predictors of survival. CONCLUSIONS Marathons and half-marathons are associated with a low overall risk of cardiac arrest and sudden death. Cardiac arrest, most commonly attributable to hypertrophic cardiomyopathy or atherosclerotic coronary disease, occurs primarily among male marathon participants; the incidence rate in this group increased during the past decade.
Experimental study of the effects of transmission power control and blacklisting in wireless sensor networks

We experimentally investigate the impact of variable transmission power on link quality, and propose variable power link quality control techniques to enhance the performance of data delivery in wireless sensor networks. This study extends the state of the art in two key respects: first, while there are a number of previous results on power control techniques for wireless ad hoc and sensor networks, to our knowledge, nearly all of them have been simulated and analytically studied that assumes the idealized link conditions; second, while there are several recent experimental studies that have shown the prevalence of non-ideal unreliable communication links in sensor networks, the paper has not thoroughly investigated the impact of variable transmission power. We perform a systematic set of experiments to analyze how the transmission power changes affect the quality of low power RF wireless links between nodes. These experiments show how significant variation in link qualities occur in real-world deployments and how these effects strongly influence the effectiveness of transmission power control. We then present a packet-based transmission power control mechanism that incorporates blacklisting to enhance link reliability while minimizing interference. The effectiveness of the proposed scheme is demonstrated via test bed experiments.
Natural Video Matting with Depth Jonathan Finger University of California Santa Cruz Department of Computer Science jfinger

Video matting is the process of taking a sequence of frames, isolating the foreground, and replacing the background with something different in each frame. This is an under-constrained problem when the background is unknown. Matting techniques exist to approximate these values using manual input cues. We look at existing singleframe matting techniques and present a method that improves upon them by adding depth information acquired by a time-of-flight range scanner. We use the depth information to automate the process so it can be practically used for video sequences. In addition, we show that we can improve the results from natural matting algorithms by adding a depth channel. The additional depth information allows us to reduce the artifacts that arise from ambiguities that occur when an object is a similar color to its background. Figure 1. Natural matting. From left to right, top to bottom: The original image, a trimap, alpha matte, foreground composed on a new background.
Complex Event Detection Using Joint Max Margin and Semantic Features

In this paper the problem of complex event detection is addressed. Existing event detection methods are limited to features that are extracted from local spatial or spatio-temporal patches from the videos. However, this makes the model more vulnerable to the events that have similar concepts with different actions e.g. "Open drawer" and "Open cupboard". Furthermore, current methods typically assume that events have already been segmented from the video stream, and do not generalize well to events with unknown starting and ending locations. In this work, in order to address the aforementioned limitations we present a novel model based on the combination of semantic and temporal features extracted from video frames. We train a max-margin classifier on top of the extracted features in an adaptive framework that is able to detect the events with unknown starting and ending locations. Our model is based on the Bidirectional Region Neural Network and large margin Structural Output SVM. The generality of our model allows it to be simply applied on different labeled and unlabeled datasets. We finally test our algorithm on three challenging datasets: "UCF 101-Action Recognition", "MPII Cooking Activities" and "Hollywood"; and we report the state-of-the-art performance.