Miracle-dz/UniFAR-FTUs huggingface dataset:
Team 2 Data Mining in an Online Encyclopedia

We have surveyed and implemented different mathematical models to find the most relevant pages pertaining to some query for the case of an online encyclopedia. We have used the concepts of the webpage ranking to determine the ranking of the different topics and hence find the most important topics. The pages of an online encyclopedia are hyperlinked and this is represented by a directed graph and a corresponding matrix. The ranking of the relevant topics turns out to be an eigenvector problem. We show the existence and uniqueness of the solution and use both the power method and the linear system approach to solve this eigenvector problem. We also investigate the effect of α, a parameter used in the formation of the famous Google matrix from the adjacency matrix obtained from the directed graph, on the convergence rate of the power method. Rankings of the topics based on the three models have been implemented and obtained.
Impact of arterial load on left ventricular diastolic function in patients undergoing cardiac catheterization for coronary artery disease.

BACKGROUND Although left ventricular (LV) diastolic dysfunction is associated with increased risk for incident heart failure in patients with coronary artery disease (CAD), no specific treatment for diastolic abnormalities has been established. Animal and small human studies have shown that an acute increase in LV afterload adversely impacts on LV early diastolic relaxation, but little is known about its chronic effect on diastolic function. METHODS AND RESULTS The relationships of various components of arterial load (arterial compliance, total vascular resistance index, and augmentation index [AI] in the ascending aorta) with LV diastolic function indices determined on cardiac catheterization (relaxation time constant [Tau] and end-diastolic pressure [EDP]) and those on tissue Doppler echocardiography (early diastolic mitral annular velocity [E'] and the ratio of early diastolic mitral inflow to annular velocities [E/E']) were investigated in 303 consecutive patients undergoing cardiac catheterization for CAD. All components of arterial load correlated with diastolic function indices, with AI, an index reflecting late-systolic load, having the strongest correlations with diastolic function indices. After adjustment for potential confounders, AI correlated with Tau (standardized beta=0.25, P<0.001), EDP (beta=0.25, P<0.001), E' (beta=-0.21, P<0.001), and E/E' (beta=0.23, P<0.001). CONCLUSIONS Increased AI is independently associated with LV diastolic function in patients with known or suspected CAD. Late-systolic load may be a therapeutic target to improve LV diastolic abnormalities in this population.
Robust actuator force Analysis of a heavy-Duty manipulator using GMM/GMR

Uncertainty is inevitable in modelling of physical world, including sensor noise, control errors and inaccurate models of the environment. In robotic grasping force analysis (GFA), the uncertainties mainly come from the location of contact points and the coefficient of friction. Previous researches of uncertainty analysis are mainly focusing on of robotic grasp synthesis and planning, while little work has been done from the aspect of grasping force. In this paper, a point contact model with uncertainty is proposed to investigate the effect of uncertainty in GFA, which was solved using Monte Carlo simulation. Moreover, to predict the minimal actuator force in an industrial heavy-duty manipulator, a Gaussian mixture model (GMM) is proposed to describe the relationship between the object configuration and the minimal actuator force.
Development of a C Language Education Instructor Training Course Using Animated Characters

The purpose of this study is to develop online lecture contents that can effectively teach C language to 5th, 6th grade or middle school students. Unlike existing cyber lectures, the proposed contents were created by using animated characters to help beginner level students learn C language through interesting storytelling, role playing games, and card games. This C language education contents were devel-oped for teachers to effectively educate elementary and middle school students who are presumed to have no prior knowledge of C lan-guage. The proposed contents motivate young learners to learn the introductory concepts of C language through the animated characters based on storytelling, more than using mere focus on rote memorization.
A Novel Approach for Finding Clusters from Complex Networks

A feasible structural clustering method based on breadth-first-search is proposed for graphs. Clustering is very important and widely used in analyzing complex networks such as community identification. There are clusters with different shapes such as cliques and stars in practical application. Some existing algorithms can find clique-shaped clusters, but they are unable to identify star-shaped clusters that are familiar in scale free networks. A feasible solution is provided to solve the problem. It is super ior to other algorithms in one or several of the following aspects: An algorithm without any input parameters, Running time on a network with n nodes and m links is O ( n ), Extracting clusters of mixed shapes.
Quantifying the impact of current and future tropospheric ozone on tree biomass, growth, physiology and biochemistry: a quantitative meta‐analysis

The northern hemisphere temperate and boreal forests currently provide an important carbon sink; however, current tropospheric ozone concentrations ([O3]) and [O3] projected for later this century are damaging to trees and have the potential to reduce the carbon sink strength of these forests. This meta‐analysis estimated the magnitude of the impacts of current [O3] and future [O3] on the biomass, growth, physiology and biochemistry of trees representative of northern hemisphere forests. Current ambient [O3] (40 ppb on average) significantly reduced the total biomass of trees by 7% compared with trees grown in charcoal‐filtered (CF) controls, which approximate preindustrial [O3]. Above‐ and belowground productivity were equally affected by ambient [O3] in these studies. Elevated [O3] of 64 ppb reduced total biomass by 11% compared with trees grown at ambient [O3] while elevated [O3] of 97 ppb reduced total biomass of trees by 17% compared with CF controls. The root‐to‐shoot ratio was significantly reduced by elevated [O3] indicating greater sensitivity of root biomass to [O3]. At elevated [O3], trees had significant reductions in leaf area, Rubisco content and chlorophyll content which may underlie significant reductions in photosynthetic capacity. Trees also had lower transpiration rates, and were shorter in height and had reduced diameter when grown at elevated [O3]. Further, at elevated [O3], gymnosperms were significantly less sensitive than angiosperms. There were too few observations of the interaction of [O3] with elevated [CO2] and drought to conclusively project how these climate change factors will alter tree responses to [O3]. Taken together, these results demonstrate that the carbon‐sink strength of northern hemisphere forests is likely reduced by current [O3] and will be further reduced in future if [O3] rises. This implies that a key carbon sink currently offsetting a significant portion of global fossil fuel CO2 emissions could be diminished or lost in the future.
High resolution audio synchronization using chroma onset features

The general goal of music synchronization is to automatically align the multiple information sources such as audio recordings, MIDI files, or digitized sheet music related to a given musical work. In computing such alignments, one typically has to face a delicate tradeoff between robustness and accuracy. In this paper, we introduce novel audio features that combine the high temporal accuracy of onset features with the robustness of chroma features. We show how previous synchronization methods can be extended to make use of these new features. We report on experiments based on polyphonic Western music demonstrating the improvements of our proposed synchronization framework.
Assessing brain effective connectivity from EEG – a simulation study

Information flow between brain areas from EEG measurements is hard to estimate reliably due to the presence of noise, as well as due to volume conduction. We present results of a simulation study, in which we test the ability of popular measures of effective connectivity to detect neuronal interactions, as well as machine learning approaches to inverse source reconstruction and blind source separation to improve the estimation. We find that volume conduction limits the neurophysiological interpretability of sensor-space connectivity analyses and may even lead to conflicting Preprint submitted to NeuroImage 15 May 2012 results. On the other hand, the estimation of connectivity on the basis of source activity, which has been estimated with some of the tested machine learning methods, yields correct and interpretable results. The success here crucially depends on the correctness of the source reconstruction, which in turn depends on the capability of the method to model multiple spatially-distinct interacting sources. As a novel methodological contribution, we propose to use time-reversed data as surrogates in order to cancel out artifactual confounders that are not related to true interaction, e. g. , due to the volume conduction. We show that this novel approach improves the performance of Granger-causal connectivity measures. Finally, integrating the insights of our study, we provide a guidance for measuring information flow in EEG. Software and benchmark data is made available.
Medical image registration based on phase congruency and RMI

In this paper, a new approach of multi-modality image registration is represented with not only image intensity, but also features describing image structure. There are two novelties in the proposed method. First, instead of standard Mutual Information (MI) based on joint intensity histogram, Regional Mutual Information (RMI) is employed, which allows neighborhood information to be taken into account. Second, a new feature images obtained by means of phase congruency are invariants to brightness or contrast changes. By incorporating these features and intensity into RMI, we can combine aspects of both structural and neighborhood information together, which offers a more robust and a high level of registration accuracy.
Addressing the health benefits and risks, involving vitamin D or skin cancer, of increased sun exposure

Solar radiation is the main cause of skin cancers. However, it also is a main source of vitamin D for humans. Because the optimal status of vitamin D protects against internal cancers and a number of other diseases, a controversy exists: Will increased sun exposure lead to net health benefits or risks? We calculated the relative yield of vitamin D photosynthesis as a function of latitude with a radiative transfer model and cylinder geometry for the human skin surface. The annual yield of vitamin D is 3.4 and 4.8 times larger below the equator than in the U.K. and Scandinavia, respectively. In populations with similar skin types, there are clear latitude gradients of all major forms of skin cancer, indicating a north–south gradient in real sun exposure. Surprisingly, the incidence rates of major internal cancers also increase from north to south. However, the survival prognosis also improves significantly from north to south. Reasons for these findings are discussed in view of the role of vitamin D. In Norway, melanoma rates increased by a factor of 6 from 1960 to 1990, while the prognosis improved in the same period. After 1990, melanoma rates have remained constant or even decreased in age groups <50 years, whereas the prognosis has not improved further. These data, together with those for internal cancers and the beneficial effects of an optimal vitamin D status, indicate that increased sun exposure may lead to improved cancer prognosis and, possibly, give more positive than adverse health effects.
Fast 3D reconstruction of human shape and motion tracking by parallel fast level set method

This paper presents a parallel algorithm of the Level Set Method named the Parallel Fast Level Set Method, and its application for real-time 3D reconstruction of human shape and motion. The Fast Level Set Method is an efficient implementation algorithm of the Level Set Method and has been applied to several applications such as object tracking in video images and 3D shape reconstruction using multiple stereo cameras. In this paper, we implement the Fast Level Set Method on a PC cluster and develop a real-time motion capture system for arbitrary viewpoint image synthesis. To obtain high performance on a PC cluster, efficient load-balancing and resource allocation algorithms are crucial problems. We develop a novel optimization technique of load distribution based on the estimation of moving direction of object boundaries. In this technique, the boundary motion is estimated in the framework of the Fast Level Set Method, and the optimum load distribution is predicted and performed according to the estimated boundary motion and the current load balance. Experiments of human shape reconstruction and arbitrary viewpoint image synthesis using the proposed system are successfully carried out.
Extracting Emotions from Texts in E-Learning Environments

Affective and emotional factors seem to affect student motivation and, in general, the outcome of the learning process. By detecting and managing the emotions underlying a learning activity it would be possible to contribute to improve the student motivation and performance. In this work we explore different possibilities aimed at automatically extracting emotions from texts. We present a case study in which twelve essays written by a fresher student along her first semester in college are analyzed. Those results support the idea of using non-intrusive emotion detection for providing feedback to students. An example of use in an existing context-based adaptive e-learning system is presented. Incorporating emotions to this type of systems broadens their possibilities, allowing dynamic recommendation of activities according to the student emotions at each time, as well as emotion-based content adaptation, among others.
Open loop stable control in repetitive manipulation tasks

Most conventional robotic arms depend on sensory feedback to perform their tasks. When feedback is inaccurate, slow or otherwise unreliable, robots should behave more like humans: rely on feedforward instead. This paper presents an approach to perform repetitive tasks with robotic arms, without the need for feedback (i.e. the control is open loop). The cyclic motions of the repetitive tasks are analyzed using an approach similar to limit cycle theory. We optimize open loop control signals that result in open loop stable motions. This approach to manipulator control was implemented on a two DOF arm in the horizontal plane with a spring on the first DOF, of which we show simulation and hardware results. The results show that both in simulation and in hardware experiments, it is possible to create open loop stable cycles. However, the two resulting cycles are different due to model inaccuracies. We also show simulation and hardware results for an inverted pendulum, of which we have a more accurate model. These results show stable cycles that are the same in simulation and hardware experiments.
The Use of Field Experiments for Studies of Employment Discrimination: Contributions, Critiques, and Directions for the Future

Have we conquered the problems of racial discrimination? Or have acts of discrimination become too subtle and covert for detection? This discussion serves to situate current debates about discrimination within the context of available measurement techniques. In this article, the author (1) considers the arguments from recent debates over the contemporary relevance of labor market discrimination; (2) provides a detailed introduction to experimental field methods for studying discrimination (also called audit studies), including an overview of the findings of recent audit studies of employment; (3) addresses the primary critiques of the audit methodology and the potential threats to the validity of studies of this kind; and (4) considers how we might reconcile evidence from field experiments with those from analyses of large-scale survey data, each of which points to markedly different conclusions. Only by gathering rigorous empirical evidence can we begin to understand the nature of race and racial discrimination in labor markets today.
4he Therapies Tumor Blockinassociated Protease Therapeutic )ntroduction

Great inroads have been made in defining the oncogenic pathways intrinsic to neoplastic cells and the mechanisms by which they are activated in tumors. Knowledge of these pathways provides numerous opportunities that are actively being pursued to develop targeted therapies for cancer. Complementary studies, focused on the non-transformed components of the tumor microenvironment (TME), have revealed that the extrinsic cues provided by the TME are also essential for tumor cells to manifest a fully transformed phenotype, angiogenesis and metastasis. Delineation of these cues and their underlying cellular and molecular pathways will thus lead to a new era of integrative cancer therapy based on combinatorial drug regiments that act synergistically to destroy the neoplastic cells by targeting both the intrinsic and extrinsic pro-oncogenic pathways. Tumor-associated fibroblasts (TAFs) and proteases are two of the key regulators of epithelialderived tumors that represent potential targets of such integrative therapies. Herein, we consider the potential therapeutic benefit of inhibiting the function of fibroblast activation protein (FAP), a cell surface serine protease with dipeptidyl peptidase and endopeptidase activity that is expressed on TAFs and pericytes, in an integrative approach to treating cancer.
Residual Toxicity of Abamectin, Milbemectin and Chlorfenapyr to Different Populations of Two Spotted Spider Mite, Tetranychus Urticae Koch, (Acari: Tetranychidae) on Cucumber in Jordan

3 Abstract: Laboratory studies were conducted during the year 2010 to evaluate the duration of residual toxicity of the acaricides; abamectin, milbemectin and chlorfenapyr to six populations of the two spotted spider mite (Tetranychus urticae Koch, (Acari: Tetranychidae) collected from cucumber grown under plastic houses in the six main cultivated areas in Jordan ( Ramta, Baqa', Zyzya, Krimeh, Dier Alla and Karamah), compared to a Syrian susceptible strain. Loss of susceptibility in the six populations to the closely related acaricides abamectin and milbemectin were clearly indicated even after one day of application, where the mortality did not exceed 24 and 33%, compared to 96 and 97% for Syrian susceptible strain for the two acaricides, respectively. In contrast, mortality from residual toxicity of chlorfenapyr were considered efficacious after one day of application and reached acceptable level even after 15 days of application. The mortality was ranged between 92 - 98% after one day of application and 48 - 68% after 15 days of application, in four out of six populations. The mite populations collected from Karamah and Krimeh were the least susceptible. Mortality from residual toxicity after one day of application were 75 and 88%, respectively, compared to 98% mortality in the Syrian susceptible strain.
Observation Reconsidered

Several arguments are considered which purport to demonstrate the impossibility of theory-neutral observation. The most important of these infers the continuity of observation with theory from the presumed continuity of perception with cognition, a doctrine widely espoused in recent cognitive psychology. An alternative psychological account of the relation between cognition and perception is proposed and its epistemological consequences for the observation/theory distinction are then explored.
Toward Advancing Nano-Object Count Metrology: A Best Practice Framework

Background: A movement among international agencies and policy makers to classify industrial materials by their number content of sub–100-nm particles could have broad implications for the development of sustainable nanotechnologies. Objectives: Here we highlight current particle size metrology challenges faced by the chemical industry due to these emerging number percent content thresholds, provide a suggested best-practice framework for nano-object identification, and identify research needs as a path forward. Discussion: Harmonized methods for identifying nanomaterials by size and count for many real-world samples do not currently exist. Although particle size remains the sole discriminating factor for classifying a material as “nano,” inconsistencies in size metrology will continue to confound policy and decision making. Moreover, there are concerns that the casting of a wide net with still-unproven metrology methods may stifle the development and judicious implementation of sustainable nanotechnologies. Based on the current state of the art, we propose a tiered approach for evaluating materials. To enable future risk-based refinements of these emerging definitions, we recommend that this framework also be considered in environmental and human health research involving the implications of nanomaterials. Conclusion: Substantial scientific scrutiny is needed in the area of nanomaterial metrology to establish best practices and to develop suitable methods before implementing definitions based solely on number percent nano-object content for regulatory purposes. Strong cooperation between industry, academia, and research institutions will be required to fully develop and implement detailed frameworks for nanomaterial identification with respect to emerging count-based metrics. Citation: Brown SC, Boyko V, Meyers G, Voetz M, Wohlleben W. 2013. Toward advancing nano-object count metrology: a best practice framework. Environ Health Perspect 121:1282–1291; http://dx.doi. org/10.1289/ehp.1306957