Miracle-dz/UniFAR-FTUs huggingface dataset:
Managing and Recovering High Data Availability in a DHT under Churn

An essential issue in peer-to-peer data management is to keep data highly available all the time. A common idea is to replicate data hoping that at least one replica is available when needed. However, due to churns, the number of created replicas could be not sufficient for guaranteeing the intended data availability. If the number of replicas is computed according to the lowest expected peer availability (a classical case), but the expectation were too high, then the peer availability after a churn could be too low, and the system could not be able to recover the requested data availability. The paper is a continuation of previous work (Knezevic et al., 2006) and presents a replication protocol that delivers a configured data availability guarantee, and is resistant to, or recovers fast from churns. The protocol is based on a distributed hash table (DHT), measurement of peer online probability in the system, and adjustment of the number of replicas accordingly. The evaluation shows that we are able to maintain or recover the requested data availability during or shortly after stronger or weaker churns, and at the same time the storage overhead is close to the theoretical minimum
A cascading framework for uncovering spammers in social networks

With tremendous popularity, OSNs have become the most important platform for marketing and advertising during the past years. Meanwhile, spamming has already become a very serious problem in OSNs, drawing the attention of both academic and industry communities. In this paper, we investigate the problem of spammer detection from the perspective of user behaviors, including relation creation, user activeness, user interaction and tweet content. We quantitatively explore their correlations with spammer detection and find that tweet content is the most important factor for spammer detection, followed by relation creation. Based on these behavior factors, we propose a novel cascading framework CWB-SPAM for spammer detection in OSNs. Experiments on dataset crawled from Sina Microblog show that the proposed algorithm outperforms over all classical algorithms we investigated in terms of F-score1. Experiments also demonstrate that as a probabilistic classification model, the proposed CWB-SPAM has a good ranking quality. It enables the OSN operators to make tradeoff between precision and recall easily so that the proposed algorithm can be used in different scenarios. Besides, we also note that the proposed framework can be used in other probabilistic binary classification models and thus applied in more scenarios.
Two Taxonomies of Deception for Attacks on Information Systems

'Cyberwar' is information warfare directed at the software of information systems. It represents an increasing threat to our militaries and civilian infrastructures. Six principles of military deception are enumerated and applied to cyberwar. Two taxonomies of deception methods for cyberwar are then provided, making both offensive and defensive analogies from deception strategies and tactics in conventional war to this new arena. One taxonomy has been published in the military literature, and the other is based on case theory in linguistics. The application of both taxonomies to cyberwar is new. We then show how to quantify and rank proposed deceptions for planning using 'suitability' numbers associated with the taxonomies. The paper provides planners for cyberwar with a more comprehensive enumeration than any yet published to the tactics and strategies that they and their enemies may use. Some analogies to deception in conventional warfare hold, but many do not, and careful thought and preparation must be applied to any deception effort.
Enhancing Technology-Mediated Communication: Tools, Analyses, and Predictive Models

Abstract : For most of us, interpersonal communication is at the center of our professional and personal lives. With the growing distribution of business organizations and of our social networks, so grows the need for and use of communication technologies. Many of today's communication tools, however, suffer from a number of shortcomings. For example, the inherent discrepancy between one's desire to initiate communication and another's ability or desire to receive it, often leads to unwanted interruptions on the one hand, or failed communication on the other. I have taken an interdisciplinary approach to address these shortcomings, and also in order to provide a better understanding of human behavior and the use of communication tools, combining tool-building and the creation of predictive models, with investigation and analysis of large volumes of field data. At the focus of this dissertation is my research on Instant Messaging (IM) communication, a popular, interesting, and highly observable point on the continuum between synchronous and asynchronous communication mediums. I present the creation of a set of statistical models that are able to predict, with high accuracy, users' responsiveness to incoming communication. A quantitative analysis complements these models by revealing major factors that influence responsiveness, illuminating its role in IM communication. I then describe an investigation of the effect of interpersonal relationships on communication, and statistical models that can predict these relationships. Finally, I describe a tool I have created that allows users to balance their responsiveness to IM with their ability to stay on task.
Reduced functional connectivity of somatosensory network in writer's cramp patients

The involvement of motor cortex and sensorimotor integration in patients with writer's cramp (WC) has been well documented. However, the exact neurophysiological profile within the somatosensory system, including primary somatosensory cortex (SI), contralateral (SIIc), and ipsilateral (SIIi) secondary somatosensory areas remains less understood.
Dialog Move Generation and Conversation Management in AutoTutor

AutoTutor is an automated computer literacy tutor that participates in a conversation with the student. AutoTutor simulates the discourse patterns and pedagogical dialog moves of human tutors. This paper describes how the Dialog Advancer Network (DAN) manages AutoTutor’s conversations and how AutoTutor generates pedagogically effective dialog moves that are sensitive to the quality and nature of the learner’s dialog contributions. Two versions of AutoTutor are discussed. AutoTutor-1 simulates the dialog moves of normal, untrained human tutors, whereas AutoTutor-2 simulates dialog moves that are motivated by more ideal tutoring strategies.
The Cassowary linear arithmetic constraint solving algorithm

Linear equality and inequality constraints arise naturally in specifying many aspects of user interfaces, such as requiring that one window be to the left of another, requiring that a pane occupy the leftmost third of a window, or preferring that an object be contained within a rectangle if possible. Previous constraint solvers designed for user interface applications cannot handle simultaneous linear equations and inequalities efficiently. This is a major limitation, as such systems of constraints arise often in natural declarative specifications. We describe Cassowary---an incremental algorithm based on the dual simplex method, which can solve such systems of constraints efficiently. We have implemented the algorithm as part of a constraint-solving toolkit. We discuss the implementation of the toolkit, its application programming interface, and its performance.
Truncated Hilbert transform and image reconstruction from limited tomographic data

A data sufficiency condition for 2D or 3D region-of-interest (ROI) reconstruction from a limited family of line integrals has recently been introduced using the relation between the backprojection of a derivative of the data and the Hilbert transform of the image along certain segments of lines covering the ROI. This paper generalizes this sufficiency condition by showing that unique and stable reconstruction can be achieved from an even more restricted family of data sets, or, conversely, that even larger ROIs can be reconstructed from a given data set. The condition is derived by analysing the inversion of the truncated Hilbert transform, here defined as the problem of recovering a function of one real variable from the knowledge of its Hilbert transform along a segment which only partially covers the support of the function but has at least one end point outside that support. A proof of uniqueness and a stability estimate are given for this problem. Numerical simulations of a 2D thorax phantom are presented to illustrate the new data sufficiency condition and the good stability of the ROI reconstruction in the presence of noise.
Understanding process in group cognitive behaviour therapy for psychosis.

BACKGROUND Group cognitive behaviour therapy for psychosis (GCBTp) has shown to be effective in diminishing symptoms, as well as in improving other psychosocial dimensions such as self-esteem. But little is known regarding the processes that generate these therapeutic improvements and might be harnessed to further improve its effectiveness. OBJECTIVES The current study aimed at investigating these processes, particularly those linked to interpersonal relationships. DESIGN The participants were all assessed at baseline, were given 24 sessions of GCBTp over the course of 3 months and were assessed again at post-treatment as well as 6 months later (9 months from baseline). METHOD Sixty-six individuals with early psychosis took part in a study of GCBTp where therapist alliance and group cohesion were assessed at three time points during the therapy, and punctual (each session) self-perceptions on symptoms and optimism were collected. RESULTS Improvements in symptoms (BPRS), self-esteem (SERS-SF) and in self-perceived therapeutic improvements (CHOICE) were linked to specific aspects of the alliance, group cohesion, as well as optimism. The variables retained were not always overall scores, suggesting the importance of the variables at key moments during the therapy. CONCLUSIONS The results clearly demonstrate the importance of the alliance and group cohesion, together significantly explaining improvements measured at post-therapy or follow-up. PRACTITIONER POINTS This study has attempted to focus mostly on relational aspects, as well as on self-perceptions, in the context of a GCBTp for individuals with early psychosis. This study also showed that these therapeutic relationships are especially useful when they are more stable and at specific moments during the therapy, namely when more difficult psychological work is done.
State feedback controller design of networked control systems with interval time‐varying delay and nonlinearity

This paper proposes a method for robust state feedback controller design of networked control systems with interval time‐varying delay and nonlinearity. The key steps in the method are to construct an improved interval‐delay‐dependent Lyapunov functional and to introduce an extended Jessen's inequality. Neither free weighting nor model transformation is employed in the derivation of system stability criteria. It is shown that the maximum allowable bound on the nonlinearity could be computed through solving a constrained convex optimization problem; and the maximum allowable delay bound and the feedback gain of a memoryless controller could be derived by solving a set of linear matrix inequalities. Numerical examples are given to demonstrate the effectiveness of the proposed method. Copyright © 2007 John Wiley & Sons, Ltd.
Listen to Your Inner Voice: Using Your Intuition in Outdoor Leadership.

Intuition is knowledge of something without the conscious use of reasoning. The question of where intuitive knowledge comes from may be addressed from neurophysiological, spiritual, or philosophical perspectives. In some cases, hunches may be traced to the unconscious processing of immediate sensory input with previous knowledge. In other cases, the source of intuitive knowledge is not apparent. Two anecdotes about skiing and fears of avalanche potential illustrate these types of intuitive knowledge. For the administrator of an outdoor program or an outdoor leader in the field, intuition can increase effectiveness in the areas of problem solving, judgment and decision making, route finding, safety management and danger evaluation, assessment of student readiness for adventure activities, staff selection, and group processes. However, intuitive insights must be used in conjunction with logical thinking. Methods of developing intuition include overcoming obstacles such as the fear of looking ridiculous or irrational; thinking of one's intuition as a metaphorical helper; and practicing various techniques such as relaxation, listening to one's inner voice during deliberate periods of silence, paying attention to the symbolism in one's dreams, memory games, creative visualization, and meditation. Contains 11 references. (SV) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. *********************************************************************** U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) his document has been reproduced as received from the person or organization originating it. O Minor changes have been made to improve reproduction quality. e Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. , "PERMISSION TO REPRODUCE THIS MATERIAL HAS BEEN GRANTED BY
The Extraordinary SVD

Abstract The singular value decomposition (SVD) is a popular matrix factorization that has been used widely in applications ever since an efficient algorithm for its computation was developed in the 1970s. In recent years, the SVD has become even more prominent due to a surge in applications and increased computational memory and speed. To illustrate the vitality of the SVD in data analysis, we highlight three of its lesser-known yet fascinating applications. The SVD can be used to characterize political positions of congressmen, measure the growth rate of crystals in igneous rock, and examine entanglement in quantum computation. We also discuss higher-dimensional generalizations of the SVD, which have become increasingly crucial with the newfound wealth of multidimensional data, and have launched new research initiatives in both theoretical and applied mathematics. With its bountiful theory and applications, the SVD is truly extraordinary.
Sampling Properties of the Spectrum and Coherency of Sequences of Action Potentials

The spectrum and coherency are useful quantities for characterizing the temporal correlations and functional relations within and between point processes. This article begins with a review of these quantities, their interpretation, and how they may be estimated. A discussion of how to assess the statistical significance of features in these measures is included. In addition, new work is presented that builds on the framework established in the review section. This work investigates how the estimates and their error bars are modified by finite sample sizes. Finite sample corrections are derived based on a doubly stochastic inhomogeneous Poisson process model in which the rate functions are drawn from a low-variance gaussian process. It is found that in contrast to continuous processes, the variance of the estimators cannot be reduced by smoothing beyond a scale set by the number of point events in the interval. Alternatively, the degrees of freedom of the estimators can be thought of as bounded from above by the expected number of point events in the interval. Further new work describing and illustrating a method for detecting the presence of a line in a point process spectrum is also presented, corresponding to the detection of a periodic modulation of the underlying rate. This work demonstrates that a known statistical test, applicable to continuous processes, applies with little modification to point process spectra and is of utility in studying a point process driven by a continuous stimulus. Although the material discussed is of general applicability to point processes, attention will be confined to sequences of neuronal action potentials (spike trains), the motivation for this work.
Humoral antibody to Mobiluncus curtisii, a potential serological marker for bacterial vaginosis

While bacterial vaginosis (BV) is a polymicrobial syndrome, Mobiluncus spp. are the organisms most highly associated with this condition. It is possible that serum antibody to Mobiluncus spp. could be used as a serological marker for BV. Using immunofluorescence techniques, we studied the prevalence of antibody to M. curtisii among three cohorts-pregnant women, pediatric patients, and sexually inexperienced women. The prevalence of antibody in each of these three groups was 75, 6, and 0%, respectively. Of the three pediatric patients with antibody to Mobiluncus curtisii, two were neonates, and the only class of antibody detected was immunoglobulin G. Among the cohort of pregnant women, the presence of antibody could not be correlated with a clinical history of BV. Serum antibody to M. curtisii could be a useful serological marker for BV. The lack of correlation of antibody positivity to historical information regarding BV suggests that unrecognized or undiagnosed episodes of BV may be common.
A pragmatic use of Semantic Web technologies for preschool cognitive skills tutoring system

Primarily preschool cognitive skills are abilities of acquiring generic knowledge. Generic knowledge is said to be the knowledge about kinds of things. Currently these cognitive skills are taught through the use of pre-authored (in the form of books or worksheets) learning contents containing the objects and concepts of the real world. This method of teaching is known as instructional pedagogy that has several limitations such as it require specialized skills and a large amount of time for content authoring, thinking and dedication and it does not support individualized learning. As a remedy to the limitations of instructional pedagogy, constructive pedagogical method provides learning through exploration. The present work proposes an intelligent tutoring system (ITS) that follows the constructive approach for preschool cognitive skills tutoring. The proposed ITS uses the Semantic Web technologies namely Ontologies and Semantic Web Rule Language (SWRL) for the construction of a rule-based ITS. The reason is, Ontologies natively (by definition) provides a formal explicit way of modeling concepts in a domain of discourse specially the real world objects and also support rule base reasoning. Finally shortcomings of the existing knowledge sources (ontologies) and step by step processing of the inference engine to generate learning contents is provided in the present work.
Cleaning up Linux's CPU hotplug for real time and energy management

Linux's CPU-Hotplug facility was originally designed to allow failing hardware to be removed from a running system. Hardware fails quite infrequently, so CPU-hotplug performance (much less real-time response) was not a major consideration. However, CPU hotplug is now used for energy management and (believe it or not! ) real-time response, both of which have unsurprisingly exposed some shortcomings in CPU hotplug. This document reviews a number of these shortcomings, and then proposes an alternative CPU-hotplug approach that we believe will address these shortcomings.
Creating domain-specific semantic lexicons for aspect-based sentiment analysis

Aspect based sentiment analysis (ABSA) is an opinion mining process where texts are analyzed to extract the sentiments that their authors express towards certain features and characteristics of particular entities, such as products or persons. Key role in the effectiveness of this process plays the accurate and complete identification of the entities' discussed aspects within the text, as well as of the evaluation expressions that accompany these aspects. Nevertheless, what entities may be considered as aspects and what evaluation expressions may characterize them, depends largely on the domain at hand. With that in mind, in this paper we propose an approach for representing and populating semantic lexicons that contain domain-specific aspect-evaluation-polarity relations and, as such, can be (re-)used towards more effective ABSA in concrete domains and scenarios.
Paradoxical rise in blood pressure during ultrafiltration is caused by increased cardiac output.

BACKGROUND In some haemodialysis patients, blood pressure increases during the dialysis session despite ultrafiltration (UF). METHODS We investigated six such patients who were not responsive to hypotensive drugs. Their echocardiograms were obtained prior to and during the dialysis session. RESULTS After the mean 2520 +/- 1698 (4.5 +/- 2.3% of BW) ml of fluid was removed, the cardiac systolic function parameters significantly improved and maximum mean arterial pressure rose (from 107 +/- 5 to 118 +/- 6 mmHg, p < 0.027). This increase in blood pressure was accompanied by an increase in cardiac index (from 3.8 +/- 0.6 to 4.8 +/- 1.1 L/min/m2, p < 0.027). With continuing UF, after a mean fluid removal of 4133 +/- 1622 (7.5 +/- 2.1% of BW) ml, normal blood pressure was achieved in all patients. Previously increased ejection fraction and fractional shortening decreased. End-diastolic volume significantly decreased from 98 +/- 34 to 78 +/- 35 ml/m2 indicating normovolemia. This decrease in blood pressure was accompanied by a return of cardiac index to normal values (from 4.8 +/- 1.1 to 3.1 +/- 0.8 L/min/m2, p < 0.027). There was a positive correlation between mean arterial pressure and cardiac index (r = 0.56, p = 0.017). CONCLUSION We hypothesize that our patients had passed the top of the Frank-Starling curve and were on the descending limb at the initial examination. With UF, patients first shifted to the left and upward on the curve. With further UF, they came down the ascending limb of the curve. In conclusion, paradoxical blood pressure rise during UF is caused by increased cardiac output, mediated by volume overload and can be treated by intensified UF.
What makes a good researcher ?

In this paper we investigate the characteristics of a good researcher and contrast them with that of other researchers which would give further insights into how to become a good researcher. For this we analyze the collaboration and citation pattern of an author. Furthermore, we propose a new metric which takes into account just the local characteristics of an author and show how well it performs with respect to a global metric like pageRank in determining the goodness of an author. For our experiments, we use the DBLP citation data which has more than four hundred and fifty thousand papers and close to a million authors.
Phosphorylation of human Argonaute proteins affects small RNA binding

Argonaute (Ago) proteins are highly conserved between species and constitute a direct-binding platform for small RNAs including short-interfering RNAs (siRNAs), microRNAs (miRNAs) and Piwi interacting RNAs (piRNAs). Small RNAs function as guides whereas Ago proteins are the actual mediators of gene silencing. Although the major steps in RNA-guided gene silencing have been elucidated, not much is known about Ago-protein regulation. Here we report a comprehensive analysis of Ago2 phosphorylation in human cells. We find that the highly conserved tyrosine Y529, located in the small RNA 5′-end-binding pocket of Ago proteins can be phosphorylated. By substituting Y529 with a negatively charged glutamate (E) mimicking a phosphorylated tyrosine, we show that small RNA binding is strongly reduced. Our data suggest that a negatively charged phospho-tyrosine generates a repulsive force that prevents efficient binding of the negatively charged 5′ phosphate of the small RNA.