Miracle-dz/UniFAR-FTUs huggingface dataset:
New Cluster Detection Based on Multi-Representation Index Tree Text Clustering

Traditional Clustering is a powerful technique for revealing the "hot" topics among documents. However, it's hard to discover the new type events coming out gradually. In this paper, we propose a novel model for detecting new clusters from time-streaming documents. It consists of three parts: the cluster definition based on Multi-Representation Index Tree (MI-Tree), the new cluster detecting process and the metrics for measuring a new cluster. Compared with the traditional method, we process the newly coming data first and merge the old clustering tree into the new one. This algorithm can avoid this effect: the documents enjoying high similarity were assigned to different clusters. We designed and implemented a system for practical application, the experimental results on a variety of domains demonstrate that our algorithm can recognize new valuable clusters during the iteration process, and produce quality clusters.
An algorithmic version of the blow-up lemma

Recently we developed a new method in graph theory based on the regularity lemma. The method is applied to find certain spanning subgraphs in dense graphs. The other main general tool of the method, besides the regularity lemma, is the so-called blow-up lemma (Komlos, Sarkozy, and Szemeredi [Combinatorica,17, 109–123 (1997)]. This lemma helps to find bounded degree spanning subgraphs in e-regular graphs. Our original proof of the lemma is not algorithmic, it applies probabilistic methods. In this paper we provide an algorithmic version of the blow-up lemma. The desired subgraph, for an n-vertex graph, can be found in time O(nM(n)), where M(n)=O(n2.376) is the time needed to multiply two n by n matrices with 0, 1 entires over the integers. We show that the algorithm can be parallelized and implemented in NC5. © 1998 John Wiley & Sons, Inc. Random Struct. Alg. , 12, 297–312, 1998
Accommodating Individual Differences.

The childhood pastime of cutting out lookalike paper dolls connected to one another in a row is a skill that is easily acquired. A pair of scissors, properly folded paper, and the small motor skills needed are all that are necessary. Given time, even a beginner can produce an assembly line of look-alike figures resembling humans. If people were like paper dolls, schooling would be simple, and results could be absolutely guaranteed. In the real world the teacher in a classroom meets students who, like the dolls in a row, are connected. Because of age, years in school, or some other common criterion, a group is formed and a classroom identity established. Then, when students begin to interact, their individuality comes through. No two are exactly alike. There is variability found in learners' emotional, social, and physical reactions as well as their intellectual readiness to learn specific concepts or skills. A student's personality cannot be segmented for instructional purposes. Although it is desirable for students to become independent, responsible, and knowing, it is also accepted that students come into classrooms as generally irresponsible and dependent individuals. The challenge to the teacher is to accept each learner, no matter what the individual's pattern is like. Then, it is the teacher's task to help each child grow and leam as much as he/she can. It is here that learning occurs in spite of us. As educators, to channel learning into desired directions is our challenge. It follows that the more accurate the diagnosis of student needs and prescription of tasks to be accomplished is, the more potential there is for effective outcome.
Reframing Health Behavior Change With Behavioral Economics

Contents: G.A. Marlatt, Foreword. R.E. Vuchinich, W.K. Bickel, Preface. Part I:Behavioral Economic Concepts and Methods. G.J. Madden, A Behavioral Economics Primer. S.R. Hursh, Behavioral Economic Concepts and Methods for Studying Health Behavior. Part II:Price and Consumption. M.E. Carroll, U.C. Campbell, A Behavioral Economic Analysis of the Reinforcing Effects of Drugs: Transition States of Addiction. F.J. Chaloupka, R.L. Pacula, Economics and Antihealth Behavior: The Economic Analysis of Substance Use and Abuse. Part III:Substitutability Relations Between Activities. L. Green, E.B. Fisher, Jr., Economic Substitutability: Some Implications for Health Behavior. H. Rachlin, The Lonely Addict. Part IV:Health Behavior as Intertemporal Choice. A.W. Logue, Self-Control and Health Behavior. C.A. Simpson, R.E. Vuchinich, Temporal Changes in the Value of Objects of Choice: Discounting, Behavior Patterns, and Health Behavior. Part V:Specific Health Behaviors: Help Seeking, Smoking, Eating, Exercise, and Gambling. J.A. Tucker, J.W. Davison, Waiting to See the Doctor: The Role of Time Constraints in the Utilization of Health and Behavioral Health Services. K.A. Perkins, M.E. Hickcox, J.E. Grobe, Behavioral Economics of Tobacco Smoking. L.H. Epstein, B.E. Saelens, Behavioral Economics of Obesity: Food Intake and Energy Expenditure. P.M. Ghezzi, C.A. Lyons, M.R. Dixon, Gambling in Socioeconomic Perspective. Part VI:The Cultural Context of Health Behavior. W.K. Bickel, L.A. Marsch, The Tyranny of Small Decisions: Origins, Outcomes, and Proposed Solutions.
Strategic Flexibility and IT Infrastructure Investments - Empirical Evidence in two Case Studies

This paper presents an empirical study to explore how firms invest in their IT infrastructure to support strategic flexibility. It investigates how IT infrastructure capabilities relate to strategic flexibility, how firms build flexibility into their IT investment decisions, and how the firms use IT to support strategic flexibility. Our cases indicate that different types of needed flexibility at the organizational level, ask for different types of IT infrastructure capabilities. In both cases, flexibility is supported by centrally organized management-oriented IT infrastructure capabilities. In the IT investment process, flexibility in the investment decision-making process is implicitly taken into account, whereas IT infrastructure flexibility is explicitly valued for. In both cases, management expects more explorative use of applications supported by IT infrastructure investments to better enhance strategic flexibility than exploitative use does. The implications for further research are discussed.
Biogeophysical feedbacks trigger shifts in the modelled vegetation-atmosphere system at multiple scales

Abstract. Terrestrial vegetation influences climate by modifying the radiative-, momentum-, and hydrologic-balance. This paper contributes to the ongoing debate on the question whether positive biogeophysical feedbacks between vegetation and climate may lead to multiple equilibria in vegetation and climate and consequent abrupt regime shifts. Several modelling studies argue that vegetation-climate feedbacks at local to regional scales could be strong enough to establish multiple states in the climate system. An Earth Model of Intermediate Complexity, PlaSim, is used to investigate the resilience of the climate system to vegetation disturbance at regional to global scales. We hypothesize that by starting with two extreme initialisations of biomass, positive vegetation-climate feedbacks will keep the vegetation-atmosphere system within different attraction domains. Indeed, model integrations starting from different initial biomass distributions diverged to clearly distinct climate-vegetation states in terms of abiotic (precipitation and temperature) and biotic (biomass) variables. Moreover, we found that between these states there are several other steady states which depend on the scale of perturbation. From here global susceptibility maps were made showing regions of low and high resilience. The model results suggest that mainly the boreal and monsoon regions have low resiliences, i.e. instable biomass equilibria, with positive vegetation-climate feedbacks in which the biomass induced by a perturbation is further enforced. The perturbation did not only influence single vegetation-climate cell interactions but also caused changes in spatial patterns of atmospheric circulation due to neighbouring cells constituting in spatial vegetation-climate feedbacks. Large perturbations could trigger an abrupt shift of the system towards another steady state. Although the model setup used in our simulation is rather simple, our results stress that the coupling of feedbacks at multiple scales in vegetation-climate models is essential and urgent to understand the system dynamics for improved projections of ecosystem responses to anthropogenic changes in climate forcing.
Short paper: smartphones: not smart enough?

Today's mobile devices are packed with sensors that are capable of gathering rich contextual information, such as location, wireless device signatures, ambient noise, and photographs. This paper exhorts the security community to re-design authentication mechanisms for users on mobile devices. Instead of relying on one simplistic, worst-case threat model, we should use contextual information to develop more nuanced models that assess the risk level of the user's current environment. This would allow us to decrease or eliminate the level of user interaction required to authenticate in some situations, improving usability without any effective impact on security. Ideally, authentication mechanisms will scale up or down to match users' own mental threat models of their environments. We sketch out several scenarios demonstrating how contextual information can be used to assess risks and adapt authentication mechanisms. This is a research-rich area, and we outline future research directions for developing and evaluating dynamic security mechanisms using contextual information.
On the repeatability of planar 2R manipulators with rotary encoders

The performance of position control systems for manipulators directly depends on the accuracy of its measurement system. Robots with revolute joints typically use rotary encoders for measuring the joint angles. The quantization in the joint angle measurements leads to a discretization of the configuration space and thereby limits accuracy and repeatability. Configuration space coordinates transform to workspace coordinates via nonlinear direct kinematic maps. The equidistant discretization of the configuration space therefore results in a non-equidistant discretization of the workspace. One effect of this non-equidistant workspace discretization is that repeatability is not constant over the workspace but depends on the configuration of the robot. In this work, we present a measure for repeatability that is able to deal with this configuration-dependence. Based on this measure, we are able to provide regions of maximal repeatability, which are regions where the positioning error due to discretization is minimal. The methodology is demonstrated for planar 2R manipulators.
Recursive parameter and state estimation for a mining industry process

In this paper we consider the problem of recursive state and parameter estimation of a nonlinear system. We propose an approach where we combine Particle Filter (for state estimation) and Recursive Least Squares (for parameter estimation) The class of nonlinear systems is motivated by a real process of the copper mining industry. The proposed approach is tested with real data.
Integrating Prior Knowledge Into Prognostic Biomarker Discovery based on Network Structure

Background: Predictive, stable and interpretable gene signatures are generally seen as an important step towards a better personalized medicine. During the last decade various methods have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinics is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Results: We propose a novel algorithm, called FrSVM, which integrates protein-protein interaction network information into gene selection for prognostic biomarker discovery. Our method is a simple filter based approach, which focuses on central genes with large differences in their expression. Compared to several other competing methods our algorithm reveals a significantly better prediction performance and higher signature stability. More- over, obtained gene lists are highly enriched with known disease genes and drug targets. We extendd our approach further by integrating information on candidate disease genes and targets of disease associated Transcript Factors (TFs).
Reconciling responsiveness with performance in pure object-oriented languages

Dynamically dispatched calls often limit the performance of object-oriented programs, since opject-oriented programming encourages factoring code into small, reusable units, thereby increasing the frequency of these expensive operations. Frequent calls not only slow down execution with the dispatch overhead per se, but more importantly they hinder optimization by limiting the range and effectiveness of standard global optimizations. In particular, dynamically dispatched calles prevent standard interprocedual optimizations that depend on the availability of a static call graph. The SELF implementation described here offers tow novel approaches to optimization. Type feedback speculatively inlines dynamically dispatched calls based on profile information that predicts likely receiver classes. Adaptive optimization reconciles optimizing compilation with interactive performance by incrementally optimizing only the frequently executed parts of a program. When combined, these two techniques result in a system that can execute programs significantly faster than previous systems while retaining much of the interactiveness of an interpreted system.
The Discovery of an Evolving Dust-scattered X-Ray Halo around GRB 031203

We report the first detection of a time-dependent dust-scattered X-ray halo around a gamma-ray burst (GRB). GRB 031203 was observed by XMM-Newton starting 6 hr after the burst. The halo appeared as concentric ringlike structures centered on the GRB location. The radii of these structures increased with time as t1/2, consistent with small-angle X-ray scattering caused by a large column of dust along the line of sight to a cosmologically distant GRB. The rings are due to dust concentrated in two distinct slabs in the Galaxy located at distances of 880 and 1390 pc, consistent with known Galactic features. The halo brightness implies an initial soft X-ray pulse consistent with the observed GRB.
C-terminal 37 residues of LRP promote the amyloidogenic processing of APP independent of FE65

The major defining pathological hallmark of Alzheimer's disease (AD) is the accumulation of amyloid β protein (Aβ), a small peptide derived from β‐ and γ‐secretase cleavages of the amyloid precursor protein (APP). Recent studies have shown that the Low‐density lipoprotein receptor‐related protein (LRP) plays a pivotal role in the trafficking of APP and generation of Aβ. In particular, we recently showed that the soluble cytoplasmic tail of LRP (LRP‐ST) without a membrane tether was sufficient to promote Aβ generation. In this study, we demonstrate that the last 37 residues of LRP cytoplasmic tail (LRP‐C37) lacking the NPxY motifs and FE65 binding mediate the core pro‐amyloidogenic activity of LRP‐ST. Moreover, we show that the conserved dileucine motif within the LRP‐C37 region is a key determinant of its Aβ promoting activity. Finally, results from a yeast two‐hybrid screen using LRP‐C37 region as bait reveal four new LRP‐binding proteins implicated in intracellular signalling and membrane protein trafficking. Our findings indicate that the LRP‐C37 sequence represents a new protein‐binding domain that may be useful as a therapeutic target and tool to lower Aβ generation in AD.
Life‐cycle exposure to the estrogenic mycotoxin zearalenone affects zebrafish (Danio rerio) development and reproduction

Zearalenone (ZON) is one of the worldwide most common mycotoxin and exhibits estrogenic activity in the range of natural steroid estrogens. The occurrence of ZON has been reported in soil, drainage water, wastewater effluents, and rivers, but its ecotoxicological effects on fish have hardly been investigated. The consequences of continuous long‐term ZON exposure, including a subsequent depuration period, as well as transgenerational effects of F0 short‐term exposure on F1 generation were investigated. Effects on growth, reproduction activity, physiology, and morphology of zebrafish (Danio rerio) were examined in a 182 day live‐cycle experiment. Life‐long exposure to ZON for 140 days increased wet weight, body length, and condition factor of female fish at 1000 ng/L, and sex ratio was shifted toward female from 320 ng/L ZON. Only females at 1000 ng/L ZON revealed a 1.5‐fold induction of plasma vitellogenin (VTG). Relative fecundity at 1000 ng/L recovered significantly during the depuration period. An increased condition factor in adult female F1 fish implies that exposure of F0 generation to 1000 ng/L ZON affected growth of F1 generation. A negative correlation between relative fecundity in the F1 generation (all groups exposed to 320 ng/L ZON) and the nominal ZON concentrations of the F0 exposure might indicate an influence of F0 exposure on reproductive performance of F1 generation. No exposure scenario affected fertility, hatch, embryo survival, and gonad morphology of zebrafish. Evaluating the environmental relevance of this data, the risk for fish to be harmed by exposure to ZON solely seems rather marginal, but ZON might contribute to the overall estrogenicity in the environment. © 2011 Wiley Periodicals, Inc. Environ Toxicol 2013.
Using the Training Reactions Questionnaire to Analyze the Reactions of University Students Undergoing Career‐Related Training in Jordan: A Prospective Human Resource Development Approach

The primary purpose of the present study was to validate Morgan and Casper's training reactions questionnaire (TRQ) for use in Jordan. The study also investigated the reactions of university students to career‐related training programs. Another purpose of the study was to determine the impact of certain aspects of training programs on the overall satisfaction of university students with the quality of the programs. The validated TRQ was administered to a purposive sample of 304 participants who completed at least two training programs. Results showed that the TRQ is valid for use in Jordan. Results also indicated that participants exhibited high levels of satisfaction with all aspects of the training programs completed. Further, based on regression analyses, results indicated that utility of training had the highest explained variance followed by course materials and course structure. Finally, the study provided a number of practical and theoretical implications for the field of study.
A Study of the Skew-Symmetric Models

Since Azzalini (1985,1986) introduced the fundamental properties of the skew-normal distribution, there are many investigations about the skew distributions based on certain symmetric probability density functions. These classes of the skew-symmetric distributions include the original symmetric distribution and have some properties like the original one and yet is skew. In this thesis, we consider two topics of the skew-symmetric models. In Chapter 1, we study the quadratic forms of multivariate skew normal-symmetric distributions. Following the paper by Gupta and Chang (2003) we generalize a multivariate skew normal-symmetric distribution with p.d. f. of the form fZ(z) = 2φp(z;Ω)G(α ′z), where Ω > 0, α ∈ R, φp(z;Ω) is the p-dimensional normal p.d. f. with zero mean vector and correlation matrix Ω, and G is taken to be an absolutely continuous distribution function such that G′ is symmetric about 0. First we obtain the moment generating function of certain quadratic forms. It is interesting to find that the distributions of some quadratic forms are independent of G. Then the joint moment generating functions of a linear compound and a quadratic form, and two quadratic forms, and conditions for their independence are given. Finally we take G to be one of normal, Laplace, logistic or uniform distribution, and determine the distribution of a special quadratic form for each case. In Chapter 2, we study the generalized skew-Cauchy distributions. We investigate the generalized skew-symmetric distributions. Suppose Y is an absolutely continuous random variable symmetric about 0 with probability density function f and cumulative distribution function F . If a random variable X satisfies X d = Y , then X is said to have a generalized skew distribution of F (or f). The generalized skew-Cauchy (GSC) distribution are considered and special examples of GSC distribution are presented. Some of these examples are generated from generalized skew-normal or generalized skew-t distributions.
Fast computation of data correlation using BDDs

Data correlation is a well-known problem that causes difficulty in VLSI testing. Based on a correlation metric, an efficient heuristic to select BIST registers has been proposed in the previous work. However, the computation of data correlation itself was a computational intensive process and became a bottleneck in the previous work. This paper presents an efficient technique to compute data correlation using Binary Decision Diagrams (BDDs). Once a BDD is built, our algorithms take linear time to compute the corresponding data correlation. The experimental results show that this technique is much faster than the previous technique based on simulation. It enables testing approaches based on data correlation to handle more practical designs. As one of the successful applications, partial scan is demonstrated by integrating our computation results.
conTEXT - A Mashup Platform for Lightweight Text Analytics

Social media technologies such as Weblogs, Microblogging, Wikis and Social Networks have become one of the most important parts of our daily life as they enable us to communicate and share stories with a lot of people. The more the amount of published information grows, the more important are solutions for accessing, analyzing, summarizing and visualizing information. While substantial progress has been made in the last years in each of these areas individually, we argue, that only the intelligent combination of approaches will make this progress truly useful and leverage further synergies between techniques. conTEXT aims to provide a user-friendly and lightweight Mashup platform enabling endusers to use sophisticated NLP techniques for analyzing and visualizing their content. it provides a flexible text analytics architecture of participation by innovative combination of different pieces of services for content collection and analysis. Named Entity Recognition (e.g. DBpedia Spotlight, FOX), Relation Extraction (e.g. BOA), Sentiment Analysis (e.g. Vivekn), Social Media (e.g. Twitter, Fcebook, Google+, LinkedIn), and Visualization (e.g. Exhibit, D3js) are some of the example services and APIs currently utilized in conTEXT.
Spin connection of twisted geometry

Twisted geometry is a piecewise-flat geometry less rigid than Regge geometry. In Loop Gravity, it provides the classical limit for each step of the truncation utilized in the definition of the quantum theory. We define the torsionless spin-connection of a twisted geometry. The difficulty given by the discontinuity of the triad is addressed by interpolating between triads. The curvature of the resulting spin connection reduces to the Regge curvature in the case of a Regge geometry.
GUI Development in TDD Model - Case Study

Test Driven Development model is identified for the quality of the final product and the ease of development. This model has a few obstacles while applying for Graphical User Interface development, as User Interface Testing possesses a few challenges. This paper is a case study of developing a User Interface feature, based on the test driven development model.