Miracle-dz/UniFAR-FTUs huggingface dataset:
Semi-automatic Matching of Heterogeneous Model-based Specifications

IT-systems are often described by a variety of specifications such as UML, Java, BPMN, WSDL, etc. These heterogeneous specifications constitute different views on the same system, resulting in the challenge of matching. That is in context of Model Driven Engineering the discovery of semantic correspondences between model elements, which can be used for tasks such as transformation or trace link generation. Although support by semi-automatic matching has been proposed, current approaches show deficits. They leave room for improvement in matching quality, do not appropriately address scalability, and miss a thorough evaluation. They were proposed to specifically target differencing and versioning in contrast to matching. We tackle these issues by proposing a configurable combination of matchers that considers both: meta-models and models. We propose to adopt established schema matching techniques and to utilize information gained from meta-model matching for the task of model matching. Additionally, the graph qualities planarity and reducibility are used to apply graph isomorphism and clustering algorithms for enhanced structural matching. Finally, we build upon a generic model-based infrastructure (EMF) allowing for an easy integration of heterogeneous specifications and the realization of scenarios from the area of service engineering for our proposed evaluation.
Spectral techniques for expander codes and generalized cyclic codes

We show that spectral techniques can be used to encode the explicit expander codes constructed by Sipser and Spielman (see IEEE Trans. on Information Theory, vol.42, no.6, p.1710-22, 1996) . These codes can be viewed as generalized cyclic codes for certain non-abelian groups. Many of the classical spectral techniques for cyclic codes extend to this general setting.
Selective Interaction Between Chloroplast β-ATPase and TGB1L88 Retards Severe Symptoms Caused by Alternanthera mosaic virus Infection

The multifunctional triple gene block protein 1 (TGB1) of the Potexvirus Alternanthera mosaic virus (AltMV) has been reported to have silencing suppressor, cell-to-cell movement, and helicase functions. Yeast two hybrid screening using an Arabidopsis thaliana cDNA library with TGB1 as bait, and co-purification with TGB1 inclusion bodies identified several host proteins which interact with AltMV TGB1. Host protein interactions with TGB1 were confirmed by biomolecular fluorescence complementation, which showed positive TGB1 interaction with mitochondrial ATP synthase delta′ chain subunit (ATP synthase delta′), light harvesting chlorophyll-protein complex I subunit A4 (LHCA4), chlorophyll a/b binding protein 1 (LHB1B2), chloroplast-localized IscA-like protein (ATCPISCA), and chloroplast β-ATPase. However, chloroplast β-ATPase interacts only with TGB1L88, and not with weak silencing suppressor TGB1P88. This selective interaction indicates that chloroplast β-ATPase is not required for AltMV movement and replication; however, TRV silencing of chloroplast β-ATPase in Nicotiana benthamiana induced severe tissue necrosis when plants were infected by AltMV TGB1L88 but not AltMV TGB1P88, suggesting that β-ATPase selectively responded to TGB1L88 to induce defense responses.
Generalized or abdominal obesity: which one better identifies cardiometabolic risk factors among children and adolescents? The CASPIAN III study.

OBJECTIVES We investigated the association of generalized and abdominal obesity with cardiometabolic risk factors in children and adolescents. METHODS Data were obtained from a surveillance system entitled CASPIAN-III study in school students aged 10-18 years in Iran. Data of subjects with normal body mass index (BMI) or above (BMI ≥ 5th percentile) were analyzed. The associations of obesity with cardiometabolic risk factors were tested using logistic regression models. RESULTS In the sample of 4641 children and adolescents, overweight/obese children were more likely to have metabolic syndrome and cardiometabolic risk factors compared with their normal weight counterparts. Among these parameters, elevated TG had the strongest association with degree of obesity (overweight: OR = 2.28 [95% CI 1.59-3.26]; obesity: OR = 5.63 [95% CI 4.27,7.43]). Combined generalized and abdominal obesity increased the risk of high blood pressure, elevated triglyceride and total cholesterol. CONCLUSIONS Combined type of generalized and abdominal obesity is a predictor of cardiometabolic risk factors.
Fuzzy Parking Manoeuvres of Wheeled Mobile Robots

This work deals with the parking manoeuvres problem for a wheeled mobile robot (WMR). The robot has the same non-holonomic kinematic constraint that has a car vehicle. This constraint makes the robot having its direction always tangent to the trajectory. Two sub-cases of parking problems are considered. These are forward and backward maneuvers, aiming to stabilize the robot at a pre-specified pose. The environment is assumed to be known, obstacle-free and a local map of the area is already done by prior processing the information obtained from ultrasonic sensors mounted on the robot. A linguistic fuzzy model to represent the robot and its environment is developed. From this model, the parking manoeuvres are carried out by mimicking a human car driver using a fuzzy control system. Upon simulation tests this approach has been proved efficient giving very encouraging results.
Empirical analysis of the dependence structure in traffic data using copula function

Statistical distributions of link and path travel times are important inputs to reliability-sensitive transportation models. This paper proposes to use copula functions for specifying and calibrating a tractable dependence structure for link travel times. Our empirical study indicates that travel time data tend to have a quasi-tail dependence structure, which is inconsistent with those embedded in commonly used copulas. This means that comparing with traditional fields using copula function, such as financial, traffic data demonstrate special features. A new copula function needs to be proposed to model this newly discovered feature.
Unsupervised Anomalous Vertices Detection Utilizing Link Prediction Algorithms

In the past decade, complex network structures have penetrated nearly every aspect of our lives. The detection of anomalous vertices in these networks can uncover important insights, such as exposing intruders in a computer network. In this study, we present a novel unsupervised twolayered meta classifier that can be employed to detect irregular vertices in complex networks using solely features extracted from the network topology. Our method is based on the hypothesis that a vertex having many links with low probabilities of existing has a higher likelihood of being anomalous. We evaluated our method on ten networks, using three fully simulated, five semi-simulated, and two real world datasets. In all the scenarios, our method was able to identify anomalous and irregular vertices with low false positive rates and high AUCs. Moreover, we demonstrated that our method can be applied to security-related use cases and is able to detect malicious profiles in online social networks. Project Links: Website I Data I Code
Learning from evolved next release problem instances

Taking the Next Release Problem (NRP) as a case study, we intend to analyze the relationship between heuristics and the software engineering problem instances. We adopt an evolutionary algorithm to evolve NRP instances that are either hard or easy for the target heuristic (GRASP in this study), to investigate where a heuristic works well and where it does not, when facing a software engineering problem. Thereafter, we use a feature-based approach to predict the hardness of the evolved instances, with respect to the target heuristic. Experimental results reveal that, the proposed algorithm is able to evolve NRP instances with different hardness. Furthermore, the problem-specific features enables the prediction of the target heuristic's performance.
A More Effective Method of Extracting the Characteristic Value of Pulse Wave Signal Based on Wavelet Transform

Pulse wave contains human physiological and pathological information. Different people will exhibit different characteristics, and hence determining the characteristic points of the pulse wave of human physiological health makes sense. It is common that we extract the characteristic value of pulse wave signal with the method based on wavelet transform on a small scale, and then determine the locations of the characteristic points by modulus maxima and modulus minima. Before determining characteristic value by detecting modulus maxima and modulus minima, we need to determine every period of the pulse wave. This paper presents a new kind of adaptive threshold determination method which is more effective. It can accurately determine every period of the pulse wave, and then extract characteristic values by modulus maxima and modulus minima in every period of the pulse wave. The method presented in this paper promotes the research utilizing pulse wave on health life.
SIRT1 Deacetylates TopBP1 and Modulates Intra-S-Phase Checkpoint and DNA Replication Origin Firing

SIRT1, the mammalian homolog of yeast Sir2, is a founding member of a family of 7 protein and histone deacetylases that are involved in numerous biological functions. Previous studies revealed that SIRT1 deficiency results in genome instability, which eventually leads to cancer formation, yet the underlying mechanism is unclear. To investigate this, we conducted a proteomics study and found that SIRT1 interacted with many proteins involved in replication fork protection and origin firing. We demonstrated that loss of SIRT1 resulted in increased replication origin firing, asymmetric fork progression, defective intra-S-phase checkpoint, and chromosome damage. Mechanistically, SIRT1 deacetylates and affects the activity of TopBP1, which plays an essential role in DNA replication fork protection and replication origin firing. Our study demonstrated that ectopic over-expression of the deacetylated form of TopBP1 in SIRT1 mutant cells repressed replication origin firing, while the acetylated form of TopBP1 lost this function. Thus, SIRT1 acts upstream of TopBP1 and plays an essential role in maintaining genome stability by modulating DNA replication fork initiation and the intra-S-phase cell cycle checkpoint.
IR-97-026 / August Spatio-Temporal Processes in Plant Communities

Ecological systems evolve in space and time. Until recently, however, research in ecology separately has focused either on the spatial domain (patterns) or on the temporal domain (processes). In this paper we describe novel approaches for progressing towards an integration of pattern and process, a goal long called for in ecology. First, we present a sequence of alternative stochastic models of spatially extended processes. Second, we advance two new methods for the estimation, or calibration, of model parameters from spatio-temporal processes observed in the field. Third, we provide tools for reducing the complexity of spatially extended ecological processes to manageable dynamical systems. Steps and techniques are illustrated in the context of data from a montane grassland community from the Czech Republic.
Activin a signaling regulates cell invasion and proliferation in esophageal adenocarcinoma

TGFβ signaling has been implicated in the metaplasia from squamous epithelia to Barrett's esophagus and, ultimately, esophageal adenocarcinoma. The role of the family member Activin A in Barrett's tumorigenesis is less well established. As tumorigenesis is influenced by factors in the tumor microenvironment, such as fibroblasts and the extracellular matrix, we aimed to determine if epithelial cell-derived Activin affects initiation and progression differently than Activin signaling stimulation from a mimicked stromal source. Using Barrett's esophagus cells, CPB, and the esophageal adenocarcinoma cell lines OE33 and FLO-1, we showed that Activin reduces colony formation only in CPB cells. Epithelial cell overexpression of Activin increased cell migration and invasion in Boyden chamber assays in CPB and FLO-1 cells, which exhibited mesenchymal features such as the expression of the CD44 standard form, vimentin, and MT1-MMP. When grown in organotypic reconstructs, OE33 cells expressed E-cadherin and Keratin 8. As mesenchymal characteristics have been associated with the acquisition of stem cell-like features, we analyzed the expression and localization of SOX9, showing nuclear localization of SOX9 in esophageal CPB and FLO-1 cells. In conclusion, we show a role for autocrine Activin signaling in the regulation of colony formation, cell migration and invasion in Barrett's tumorigenesis.
Peripheral Adaptation Codes for High Odor Concentration in Glomeruli

Adaptation is a general property of sensory receptor neurons and has been extensively studied in isolated cell preparation of olfactory receptor neurons. In contrast, little is known about the conditions under which peripheral adaptation occurs in the CNS during odorant stimulation. Here, we used two-photon laser-scanning microscopy and targeted extracellular recording in freely breathing anesthetized rats to investigate the correlate of peripheral adaptation at the first synapse of the olfactory pathway in olfactory bulb glomeruli. We find that during sustained stimulation at high concentration, odorants can evoke local field potential (LFP) postsynaptic responses that rapidly adapt with time, some within two inhalations. Simultaneous measurements of LFP and calcium influx at olfactory receptor neuron terminals reveal that postsynaptic adaptation is associated with a decrease in odorant-evoked calcium response, suggesting that it results from a decrease in glutamate release. This glomerular adaptation was concentration-dependent and did not change the glomerular input–output curve. In addition, in situ application of antagonists of either ionotropic glutamate receptors or metabotropic GABAB receptors did not affect this adaptation, thus discarding the involvement of local presynaptic inhibition. Glomerular adaptation, therefore, reflects the response decline of olfactory receptor neurons to sustained odorant. We postulate that peripheral fast adaptation is a means by which glomerular output codes for high concentration of odor.
OC-3072 packet classification using BDDs and pipelined SRAMs

We present a solution to the problem of quickly classifying packets. Our approach is based on techniques from logic synthesis. Specifically, we express the classification rules as Boolean logic equations, build binary decision diagrams for these equations, and then map the BDDs to a logic network consisting of a pipeline of static RAM banks. We illustrate our approach by applying it to the longest prefix matching for IP forwarding, and present evidence that our scheme can perform a billion matches per second on a CAIDA backbone forwarding table containing 60,000 prefixes. We show how our approach generalizes to classifying packets on multiple fields.
Iterative learning control based automatic train operation with iteration-varying parameter

An iterative learning control (ILC) based on Automatic Train Operation (ATO) is proposed to address train speed tracking problem under iteration-varying operation condition, that is, the air resistance coefficients of the train at any two consecutive iterations are completely different. Using the data measured by the sensors, repetitive requirement of traditional ILC is partially relaxed in the proposed method. The effectiveness of the proposed method is verified by theoretical analysis and numerical simulation.
Flooding time in edge-Markovian dynamic graphs

We introduce stochastic time-dependency in evolving graphs: starting from an arbitrary initial edge probability distribution, at every time step, every edge changes its state (existing or not) according to a two-state Markovian process with probabilities p (edge birth-rate) and q (edge death-rate). If an edge exists at time t then, at time t+1, it dies with probability q. If instead the edge does not exist at time t, then it will come into existence at time t+1 with probability p. Such evolving graph model is a wide generalization of time-independent dynamic random graphs [6] and will be called edge-Markovian dynamic graphs. We investigate the speed of information dissemination in such dynamic graphs. We provide nearly tight bounds (which in fact turn out to be tight for a wide range of probabilities p and q) on the completion time of the flooding mechanism aiming to broadcast a piece of information from a source node to all nodes. In particular, we provide: i) A tight characterization of the class of edge-Markovian dynamic graphs where flooding time is constant and, thus, it does not asymptotically depend on the initial probability distribution. ii) A tight characterization of the class of edge-Markovian dynamic graphs where flooding time does not asymptotically depend on the edge death-rate q.
Robust Facial Attribute-Specific Subspace-Based Principal Component Analysis for Face Recognition

Facial attribute-specific subspace-based PCA (FASS-based PCA) considers the information of class labels, and the discriminant power can be improved. However, it doesn't consider the outliers which are . common in realistic training sets. To address this problem, we propose robust facial attribute-specific subspace-based PCA (robust FASS-based PCA) algorithm in this paper, which gives a new weighted method for the evaluation of the total squared error of each class. The detailed algorithm for robust FASS-based PCA is also given. The results of experiments conducted on Yale databases show the effectiveness of the new feature extraction algorithm.
Spatial ability and g.

Spatial abilities have long been relegated to a secondary status in accounts of human intelligence. Tests of spatial abilities are viewed as measures of practical and mechanical abilities that are useful in predicting success in technical occupations, but not as measures of abstract reasoning abilities (Smith, 1964). This conflicts with the important role afforded to spatial imagery in accounts of creative thinking (Shepard, 1978), and with the observed correlations between spatial tests and other measures of intelligence. In fact, Spearman (see Spearman & Wynn Jones, 1950) considered spatial tests merely as unreliable measures of G. Hierarchical factor analyses generally support Spearman's conclusion, especially for complex spatial tests. Such tests are primarily measures of G, secondarily measures of something task-specific, and thirdly, measures of something that covaries uniquely with performance on other spatial tasks (Lohman, 1988). Simpler, speeded spatial tasks show lower G loadings, higher task specific loadings, and higher spatial factor loadings. In this paper, I first summarize and then attempt to explain these findings. The relationship between spatial task performance and G may reflect both statistical artifacts and psychological factors. Psychological factors include the attentional demands of maintaining and transforming images in working memory (Kyllonen & Christal, 1990) and the importance of mental models in reasoning (JohnsonLaird, 1983). Indeed, one can turn Spearman's conclusion around and with equal conviction conclude that measures of G are by and large unreliable measures of the ability to generate and coordinate different types of mental models in working memory. Evidence that supports and challenges such a conclusion is reviewed. Spatial Ability and G Page 3
Development of tele-operation control for a free-floating robot during the grasping of a tumbling target

This paper addresses the singularities avoidance problem while performing a grasping maneuver in teleoperation with a manipulator mounted on a free-floating spacecraft. Firstly, the independence of the singularities of the end-effector Jacobian of a generic free-floating system from the inertial parameters of the last link is demonstrated. Secondly, the possibility to represent all the singularities in the Cartesian space for a freefloating system provided with three reaction wheels is shown. Finally an optimization algorithm is presented, which provides the optimal spacecraft initial Cartesian position and attitude, to allow the operator to keep a trajectory in the vicinity of the nominal motion while satisfying operational constrains as long as possible.
Design and Evaluation of The Soft Hand WSH-1 For The Emotion Expression Humanoid Robot KOBIAN

(RT)-based assistive devices are expected to play a major role in our elderly-dominated society, with an active participation to joint works and community life with humans, as partners and as friends. In particular, these robots are expected to be fundamental for helping and assisting elderly and disabled people during their activities of daily living (ADLs). Therefore we developed a new bipedal walking robot, named KOBIAN, capable of human-like movements and of human-like emotions. This robot is expected to be capable of interacting with surrounding people both physically and psychologically. A fundamental role for this interaction is played by the hand, which should both be capable of grasping and of gestures. To this purpose, the Waseda Soft-Hand 1 (WSH-1) was designed and realized. This paper presents the description of WSH-1 and its preliminary evaluation. The results clearly emphasize the importance of having a robotic hand with soft fingers for the interaction with other people.
TCP Optimal Performance in Wireless Networks Applications

Mobile Ad Hoc Network (MANET) consists of dynamic topology as nodes in the network are mobile, and connected via wireless links. The nodes are grouped in clusters for the purpose of routing. Nodes within the cluster communicate directly. However, nodes communicate outside the cluster through a centralized node that is called a clusterhead. An elected clusterhead is assigned for communication with all other clusters. The centralized clusterhead can become a bottleneck and possibly cause a lower throughput for the clustering system. We propose a mechanism in which communication outside the cluster is distributed through separate clusterheads. We prove that the overall averaged throughput for the clustering system increases considerably, about doubles for our distributed number of clusterheads. We also show that the increase in overall averaged throughput is reduced by the increase in the overall averaged error rate ratio resulting from the added clusterheads. Additionally, the routing reliability to outside the cluster is increased since routes to different clusters use distinct clusterhead.
Efficient Unsupervised Authorship Clustering Using Impostor Similarity

Some real world authorship analysis applications require techniques that scale to thousands of documents with little or no a priori information about the number of candidate authors. While there is extensive research on identifying authors given a small set of candidates and ample training data, almost none is based on real-world applications of clustering documents by authorship, independent of prior knowledge of the authors. We adapt the impostor method of authorship verification to authorship clustering using agglomerative clustering and, for efficiency, locality sensitive hashing. We validate our methods on a publicly available blog corpus that has been used in previous authorship research before applying these methods to our dataset of anonymous classified ads. We show that our efficient method matches previous results for authorship verification on the blog corpus and achieves comparable results on the ads. We extend previous results to show that the impostor algorithm is robust to incorrectly selected impostors. On the authorship clustering task, we show that the impostor similarity method clearly outperforms other techniques on the blog corpus but has no consistent advantage when applied to finding authors of anonymous ads.