Miracle-dz/UniFAR-FTUs huggingface dataset:
Probabilistic Models for High-Order Projective Dependency Parsing

This paper presents generalized probabilistic models for high-order projective dependency parsing and an algorithmic framework for learning these statistical models involving dependency trees. Partition functions and marginals for high-order dependency trees can be computed efficiently, by adapting our algorithms which extend the inside-outside algorithm to higher-order cases. To show the effectiveness of our algorithms, we perform experiments on three languages---English, Chinese and Czech, using maximum conditional likelihood estimation for model training and L-BFGS for parameter estimation. Our methods achieve competitive performance for English, and outperform all previously reported dependency parsers for Chinese and Czech.
Appearance Modeling Using a Geometric Transform

A general transform, called the geometric transform (GeT), that models the appearance inside a closed contour is proposed. The proposed GeT is a functional of an image intensity function and a region indicator function derived from a closed contour. It can be designed to combine the shape and appearance information at different resolutions and to generate models invariant to deformation, articulation, or occlusion. By choosing appropriate functionals and region indicator functions, the GeT unifies Radon transform, trace transform, and a class of image warpings. By varying the region indicator and the types of features used for appearance modeling, five novel types of GeTs are introduced and applied to fingerprinting the appearance inside a contour. They include the GeTs based on a level set, shape matching, feature curves, and the GeT invariant to occlusion, and a multiresolution GeT (MRGeT). Applications of GeT to pedestrian identity recognition, human body part segmentation, and image synthesis are illustrated. The proposed approach produces promising results when applied to fingerprinting the appearance of a human and body parts despite the presence of nonrigid deformations and articulated motion.
Haemodynamic Changes in the Superior Mesenteric Artery Induced by Acupuncture Stimulation on the Lower Limbs

Acupuncture is commonly performed on acupoints. A comparison of quantitative physiological alterations induced by stimulation on different acupoints has never been performed in the superior mesenteric artery (SMA) in humans. Therefore, we investigated changes in blood flow volume (BFV) in the SMA as an indicator of physiological effects induced by stimulation on 3 points. Thirty healthy participants aged 29 ± 10 years (mean ± SD) were enrolled. All participants underwent stimulations on 3 points located in the lower legs: ST36, LR3, and a non-acupoint. Control pertains to a condition with no-stimulation. Stimulation was performed bilaterally with manual rotation of the needles. BFV was measured by ultrasonography before insertion and 10, 20, 30, and 60 minutes after stimulation. Following acupuncture on ST36, BFV increased significantly 20 and 30 minutes after stimulation, compared to BFV before insertion (P < 0.05). Following stimulation on LR3 and the non-acupoint, no significant differences in BFV could be found. Relative to the no-stimulation group, stimulation on LR3, and the non-acupoint, stimulation on ST36 elicited a significant increase in BFV (P < 0.05). The results suggest that stimulation on the different points causes distinct physiological effects in BFV in the SMA.
A Statistics and Local Homogeneity Based Color Edge Detection Algorithm

Edge detection is one of the most commonly used operations in image processing and pattern recognition, the reason for this is that edges form the outline of an object. An edge is the boundary between an object and the background, and indicates the boundary between overlapping objects. This means that if the edges in an image can be identified accurately, all of the objects can be located and basic properties such as area, perimeter, and shape can be measured. Since computer vision involves the identification and classification of objects in an image, edge detection is an essential tool. Efficient and accurate edge detection will lead to increase the performance of subsequent image processing techniques, including image segmentation, object-based image coding, and image retrieval. A novel color edge detection algorithm is proposed in this paper. On the basis of standard deviation calculation of pixels the discontinuity among the pixels are detected. Then the image is segmented into a binary image with a fixed threshold where black pixels signify homogeneous region and white pixels signify edges. Finally, a thinning technique is applied to extract thin edges. The proposed method is applied over large database of color images both synthetic and real life images and performance of the algorithm is evident from the results and is comparable with other edge detection algorithms.
Development of a Tabletop Guidance System for Educational Robots

The guidance of a vehicle in an outdoor setting is typically implemented using a Real Time Kinematic Global Positioning System (RTK-GPS) potentially enhanced by auxiliary sensors such as electronic compasses, rotation encoders, gyroscopes, and vision systems. Since GPS does not function in an indoor setting where educational competitions are often held, an alternative guidance system was developed. This article describes a guidance method that contains a laser-based localization system, which uses a robot-borne single laser transmitter spinning in a horizontal plane at an angular velocity up to 81 radians per second. Sensor arrays positioned in the corners of a flat rectangular table with dimensions of 1.22 m × 1.83 m detected the laser beam passages. The relative time differences among the detections of the laser passages gave an indication of the angles of the sensors with respect to the laser beam transmitter on the robot. These angles were translated into Cartesian coordinates. The guidance of the robot was implemented using a uni-directional wireless serial connection and position feedback from the localization system. Three experiments were conducted to test the system: 1) the accuracy of the static localization system was determined while the robot stood still. In this test the average error among valid measurements was smaller than 0.3 %. However, a maximum of 3.7 % of the measurements were invalid due to several causes. 2) The accuracy of the guidance system was assessed while the robot followed a straight line. The average deviation from this straight line was 3.6 mm while the robot followed a path with a length of approximately 0.9 m. 3) The overall performance of the guidance system was studied while the robot followed a complex path consisting of 33 sub-paths. The conclusion was that the system worked reasonably accurate, unless the robot came in close proximity (<0.2 m) to one of the sensor arrays where errors occurred due to a high angle of incidence of the laser beam onto the sensor arrays and due to a high tangential velocity of the laser beam at the opposite sensor array. Hence, this article presents a low-cost guidance system which is simple, reliable, and reasonably accurate.
Stochastic fusion of heterogeneous multisensor information for robust data-to-decision

In this paper, based on the measure-theoretic probability theory and the theory of stochastic differential equation (SDE), a stochastic fusion framework is proposed for the heterogeneous sensor network for the purpose of robust decision making. In this framework, for each sensor, its sample space and the corresponding σ-algebra are defined. Then, random variables, which are designed to meet the requirements of the operation in the battle field, are defined over the pairs of sample space and its σ-algebra. After that, the conditional expectation is taken for those random variables conditional on the union of σ-algebras to finish the information fusion process. Furthermore, to make the decision making process more robust, the undesired uncertainty in the fused information is hedged out based on the theory of SDEs, before the fused information is used for the decision making.
Experimental Studies of Electron and Gas Sources in a Heavy-Ion Beam

We use the High Current Experiment (HCX) to study three mitigation measures: a rough surface to reduce electron emission and gas desorption from ions striking walls near grazing incidence, a suppressor electrode after the magnets to block beam-induced electrons off the end structures from drifting upstream, and clearing electrodes to remove electrons from drift regions between magnets. We find that each technique performs as intended.
An information theoretic method for designing multiresolution principal component transforms

In signal processing, multiresolution transforms are used to decompose a time signal into components of different resolutions. In this paper, we consider designing optimal multiresolution transforms such that components in each resolution provide the best approximation to the original signal in that resolution. We call a transformation that admits this optimality property a principal component multiresolution transform (PCMT). We show that PCMTs can be designed by minimizing the information transfer through their basic building blocks. We then propose a method to do the minimization in a stage-by-stage manner. This latter method has a great appeal in terms of its computational simplicity as well as theoretical interpretations. In particular, it agrees with Linsker's principle of self organization. Finally, we provide analytic arguments and computer simulations to demonstrate the efficiency of our method.
An output signal based combination of three LMS adaptive filters

This paper investigates a combination of three LMS adaptive algorithms. The structure consists of filters that simultaneously adapt on the same input and desired signals but have different step sizes. The outputs of the individual filters are then adaptively combined together to form a common output signal. This combination is an interesting new way of achieving a fast initial convergence and a small steady state error of an adaptive filter at the same time. We compute the combination parameters from the output signals of the individual filters. In this paper we show that the straightforward posing of the minimization problems we need to solve for the combination parameters results in a need to solve a singular system of linear equations. We therefore suggest to include a regularization term to our optimization problem. We also provide an analysis of the resulting algorithm. The theoretical results are verified by simulations.
In Search of Epigenetic Marks in Testes and Sperm Cells of Differentially Fed Boars

In search of transmittable epigenetic marks we investigated gene expression in testes and sperm cells of differentially fed F0 boars from a three generation pig feeding experiment that showed phenotypic differences in the F2 generation. RNA samples from 8 testes of boars that received either a diet enriched in methylating micronutrients or a control diet were analyzed by microarray analysis. We found moderate differential expression between testes of differentially fed boars with a high FDR of 0.82 indicating that most of the differentially expressed genes were false positives. Nevertheless, we performed a pathway analysis and found disparate pathway maps of development_A2B receptor: action via G-protein alpha s, cell adhesion_Tight junctions and cell adhesion_Endothelial cell contacts by junctional mechanisms which show inconclusive relation to epigenetic inheritance. Four RNA samples from sperm cells of these differentially fed boars were analyzed by RNA-Seq methodology. We found no differential gene expression in sperm cells of the two groups (adjusted P-value>0.05). Nevertheless, we also explored gene expression in sperm by a pathway analysis showing that genes were enriched for the pathway maps of bacterial infections in cystic fibrosis (CF) airways, glycolysis and gluconeogenesis p.3 and cell cycle_Initiation of mitosis. Again, these pathway maps are miscellaneous without an obvious relationship to epigenetic inheritance. It is concluded that the methylating micronutrients moderately if at all affects RNA expression in testes of differentially fed boars. Furthermore, gene expression in sperm cells is not significantly affected by extensive supplementation of methylating micronutrients and thus RNA molecules could not be established as the epigenetic mark in this feeding experiment.
Detecting Pedestrians and Cars in 3 D

In this report, we address the task of detecting pedestrians and cars and further localizing them in 3D. This is a challenging task owing to variable appearance that humans can adopt and different viewpoints for cars. Pedestrian and car detection has been well studied over the years. A number of robust feature sets [8],[3], [9] have been proposed which successfully discriminates the human form from cluttered background and even making the detection task illumination invariant. We choose one such feature set, locally normalized Histogram of Oriented Gradient (HOG) in order to implement our pedestrian and car detection task. Once the module for person and car detection is constructed, it can be subsequently fused to get the 3D detection in the following way. We use a single video stream from a calibrated stereo rig and then compute the camera pose and ground plane estimate for each image of the video stream. This can be achieved through standard Structure from Motion technique. The ground plane is then estimated by fitting a plane to the 3D points available from the horizontal sweeping of the scene. Taking help of known camera pose, 2D detections would then be converted to 3D observations, similar to Leibe et.al [4]. The input data for Leibe et.al. [4] are two video streams from a calibrated stereo rig. Car and pedestrian detectors are applied to both the camera images and then using the estimated camera pose these detections are converted to 3D observation by combining responses of multiple detectors if they refer to the same object in the scene. In this project, we just use a single video stream and its corresponding depth map as input data. In brief, we perform the following three steps: (1) Using standard car and pedestrian detector on the video frames to get the bounding boxes (2) Estimating a reasonable ground plane from the depth map data for mapping the bounding boxes in 2D to 3D and (3) Correcting for the orientation of the 3D boxes. We demonstrate this method on the Urbanscape Video stream, the depth map data for which are available.
Information Retrieval Oriented Word Segmentation based on Character Association Strength Ranking

This paper presents a novel, ranking-style word segmentation approach, called RSVM-Seg, which is well tailored to Chinese information retrieval(CIR). This strategy makes segmentation decision based on the ranking of the internal associative strength between each pair of adjacent characters of the sentence. On the training corpus composed of query items, a ranking model is learned by a widely-used tool Ranking SVM, with some useful statistical features, such as mutual information, difference of t-test, frequency and dictionary information. Experimental results show that, this method is able to eliminate overlapping ambiguity much more effectively, compared to the current word segmentation methods. Furthermore, as this strategy naturally generates segmentation results with different granularity, the performance of CIR systems is improved and achieves the state of the art.
Enhancing privacy on Mobile Health: An integrated privacy module

The evolution of mobile communication in the health sector has improved patients' quality of care. Nowadays, doctors can make diagnosis even though the patient is miles away using mobile technologies such as smart phones or tablet PCs. Nevertheless, the exchange of medical information through mobile devices brings on serious threats to patients' privacy. We believe that privacy must be considered during the development of any mobile healthcare system. In this paper we discuss the efficiency of current privacy and security protection mechanisms used in current mobile systems. The nature and the diversity of medical information shared between different entities (physicians, hospitals, laboratories, pharmacies.) increases privacy and security risks. Thus, we introduce a new conceptual module to preserve privacy in mobile healthcare. By integrating this module into current mobile healthcare systems architecture, we obtain a privacy-preserving system enabling patients to monitor and manage the disclosure of their sensitive health information during a mobile transaction.
Simulation analysis of protected B2B e-commerce processes

In this paper a simulation analysis of certain trust models (complex PKI architectures) with regard to the security support of B2B applications on the Internet is presented. The objective of such an analysis has been the choice of the most efficient PKI architecture and a solution of the cryptographic interoperability problem. A simulation model of protected B2B e-commerce has also been presented, based on the chosen PKI architecture. This paper has shown the significance of the up-to-date cryptographic mechanisms: digital signature and digital certificate to deliver the main security services based on PKI.
Estimating timestamp from incomplete news corpus

Recently there have been a lot of researches for summarizing news stream and for detecting edges of new events in the news stream. But, in these tasks, all data are assumed to carry timestamp (temporal information). It is noteworthy that news articles without timestamp can't make any contribution to these tasks. In this investigation, we propose a new technique to estimate timestamps to any news articles using small number of incomplete news corpus. Here we learn tem- poral information and topic information by means of both EM algorithm and incremental clustering, then we estimate timestamp of news article based on events that are discussed in news corpus. In this work, we examine TDT2 corpus and we show how well our approach works by some experiments.
Influence and Profit: Two Sides of the Coin

Influence maximization problem is to find a set of seeds in social networks such that the cascade influence is maximized. Traditional models assume all nodes are willing to spread the influence once they are influenced, and they ignore the disparity between influence and profit of a product. In this paper by considering the role that price plays in viral marketing, we propose price related (PR) frame that contains PR-I and PR-L models for classic IC and LT models respectively, which is a pioneer work. We find that influence and profit are like two sides of the coin, high price hinders the influence propagation and to enlarge the influence some sacrifice on profit is inevitable. We propose Balanced Influence and Profit (BIP) maximization problem. We prove the NP-hardness of BIP maximization under PR-I and PR-L model. Unlike influence maximization, the BIP objective function is not monotone. Despite the non-monotony, we show BIP objective function is sub modular under certain conditions. Two unbudgeted greedy algorithms separately are devised. We conduct simulations on real-world datasets and evaluate the superiority of our algorithms over existing ones.
An unconstrained hybrid active contour model for image segmentation

In this paper, we propose an unconstrained active contour model combining edge and region information for image segmentation. The new method achieves the segmentation by filternating the regularization term and the data-fidelity term. We use a morphological approach to the regularization term which is the most time-consuming in the energy function. The proposed method is robust to noise and avoids re-initialization. The efficiency of our method is validated by testing it on various images.
Vitamin D Receptor Gene Expression and Function in a South African Population: Ethnicity, Vitamin D and FokI

Polymorphisms of the vitamin D receptor gene (VDR) have been associated inconsistently with various diseases, across populations of diverse origin. The T(f) allele of the functional SNP FokI, in exon 2 of VDR, results in a longer vitamin D receptor protein (VDR) isoform, proposed to be less active. Genetic association of VDR with disease is likely confounded by ethnicity and environmental factors such as plasma 25(OH)D3 status. We hypothesized that VDR expression, VDR level and transactivation of target genes, CAMP and CYP24A1, depend on vitamin D, ethnicity and FokI genotype. Healthy volunteers participated in the study (African, n = 40 and White, n = 20). Plasma 25(OH)D3 levels were quantified by LC-MS and monocytes cultured, with or without 1,25(OH)2D3. Gene expression and protein level was quantified using qRT-PCR and flow cytometry, respectively. Mean plasma 25(OH)D3 status was normal and not significantly different between ethnicities. Neither 25(OH)D3 status nor 1,25(OH)2D3 supplementation significantly influenced expression or level of VDR. Africans had significantly higher mean VDR protein levels (P<0.050), nonetheless transactivated less CAMP expression than Whites. Genotyping the FokI polymorphism by pyrosequencing together with HapMap data, showed a significantly higher (P<0.050) frequency of the CC genotype in Africans than in Whites. FokI genotype, however, did not influence VDR expression or VDR level, but influenced overall transactivation of CAMP and 1,25(OH)2D3-elicited CYP24A1 induction; the latter, interacting with ethnicity. In conclusion, differential VDR expression relates to ethnicity, rather than 25(OH)D3 status and FokI genotype. Instead, VDR transactivation of CAMP is influenced by FokI genotype and, together with ethnicity, influence 1,25(OH)2D3-elicited CYP24A1 expression. Thus, the expression and role of VDR to transactivate target genes is determined not only by genetics, but also by ethnicity and environment involving complex interactions which may confound disease association.
Tusanqi-Related Sinusoidal Obstruction Syndrome in China

Abstract In West, sinusoidal obstruction syndrome (SOS) is often complicated with hemopoietic stem cell transplantation. By comparison, in China, SOS is frequently caused by Tusanqi-containing pyrrolizidine alkaloids. A systematic review aimed to evaluate the clinical profiles, diagnostic workup, treatment, and outcomes of Tusanqi-related SOS in China. All relevant articles were searched via PubMed, China Knowledge Resource Integrated, VIP, and Wanfang databases. Case reports were defined, as the data were available in every individual patient. Otherwise, case series were defined. Overall, 106 articles were eligible. Fifty-six case reports included 84 individual patients with SOS secondary to Tusanqi alone. All of them presented with ascites, but only 1 patient presented with upper gastrointestinal bleeding. The 1-, 3-, and 6-month cumulative survival rate was 98%, 87%, and 76%, respectively. Increased bilirubin and aspartate transaminase levels were significantly associated with poor outcome. Thirty-one case series included 402 patients with SOS secondary to Tusanqi alone. Ascites was observed in 94% of patients, but upper gastrointestinal bleeding was observed in 40% of patients. Recovery, stabilization, progression, and death were observed in 41%, 30%, 14%, and 16% of patients, respectively. Nineteen case series included 281 patients with SOS secondary to mixed etiologies. The pooled proportion of Tusanqi-related SOS was 66% (95% confidence interval: 56%–75%). Tusanqi is a major cause of SOS in China. Ascites is the most common clinical presentation of Tusanqi-related SOS. Despite a relatively good short-term outcome, further studies should be necessary to explore the long-term outcome and refine the treatment strategy.