Miracle-dz/UniFAR-FTUs huggingface dataset:
How children search the internet with keyword interfaces

Children are among the most frequent users of the Internet, yet searching and browsing the web can present many challenges. Studies over the past two decades on how children search were conducted with finite and pre-determined content found in CD-ROM applications, online digital libraries, and web directories. However, with the current popularity of the open Internet and keyword-based interfaces for searching it, more critical analysis of the challenges children face today is needed. This paper presents the findings of our initial study to understand how children ages 7, 9, and 11 search the Internet using keyword interfaces in the home. Our research has revealed that although today's children have been exposed to computers for most of their lives, spelling, typing, query formulation, and deciphering results are all still potential barriers to finding the information they need.
Differential var gene expression in the organs of patients dying of falciparum malaria

Sequestration of parasitized erythrocytes in the microcirculation of tissues is thought to be important in the pathogenesis of severe falciparum malaria. A major variant surface antigen, var/Plasmodium falciparum erythrocyte membrane protein 1, expressed on the surface of the infected erythrocyte, mediates cytoadherence to vascular endothelium. To address the question of tissue‐specific accumulation of variant types, we used the unique resource generated by the clinicopathological study of fatal paediatric malaria in Blantyre, Malawi, to analyse var gene transcription in patients dying with falciparum malaria. Despite up to 102 different var genes being expressed by P. falciparum populations in a single host, only one to two of these genes were expressed at high levels in the brains and hearts of these patients. These major var types differed between organs. However, identical var types were expressed in the brains of multiple patients from a single malaria season. These results provide the first evidence of organ‐specific accumulation of P. falciparum variant types and suggest that parasitized erythrocytes can exhibit preferential binding in the body, supporting the hypothesis of cytoadherence‐linked pathogenesis.
Evolving a behavior-based control architecture- From simulations to the real world

Genetic programming makes it possible to automatically search the space of possible programs. First we evolved a behavior-based control architecture using computer simulations. Then we replicated one of the experiments with a service robot, showing that Koza's classic experiment of evolving a control architecture can be transfered to the real world with a change of representation. The use of a service robot necessitates safety measures which are also explained. Results are reported for the experiments using computer simulations and with the real robot.
Detecting unstructured events through multi-source data analysis

There is increasing interest in using urban data analysis for different applications, particularly in relation to urban management, transport optimisation and fields related to cities becoming ‘smarter’. Data used in the analyses comes from different sources and involves various domains, from transportation engineering to urban planning. Three forms of data in particular have been of interest within the research community for a number of years. The first one includes data sourced from what are called ‘smart cards’ (for ticketing purposes): mainly used for calculating commuting flows and tracking users trajectories (Munizaga and Palma 2012; Hasan et al. 2012), it also has some applications for urban zoning and activity detection (Roth et al. 2010; Zhong et al. 2014). The second type concerns mobile phone data, generally aggregated and anonymised by providers, used mainly for detecting urban dynamics and activities because of the fine granularity, considering mobile phone as a proxy for each single user. Research focus has been similar from pioneering works till recent ones (Ratti et al. 2006; Candia et al. 2008; Calabrese et al. 2011; Hasan et al. 2012). Finally, the third one involves social media data, which use increased in latest years mainly because of the users’ growth and its availability through API. Spatial applications are particularly relevant when data attributes include location information, as seen in Twitter (Hawelka et al. 2014), or Foursquare (Cranshaw et al. 2012) data. In this paper we will discuss how a deeper understanding of urban dynamics can be yielded through the joint analysis of all three datasets. Specifically we seek to develop a platform for the identification of events, with a view to informing urban planning and management.
SINUSOIDAL AND ENVELOPE-MODULATION MODELING OF ACOUSTIC SIGNALS

An acoustic signal representation based on sinusoidal and envelope-modulation modeling is described. Such studies are crucial to acoustic events modeling for structured audio-signal representation and rendering through interactive networks. This paper confirmed that; (1) sinusoidal modeling is useful for constructing an intelligible speech using only a few dominant components, (2) envelope modulation modeling enables modification of a talker’s pitch and speech rate without sacrificing intelligibility through use of the simple carriers, and (3) the narrow-band envelope could be also estimated by clustered linespectrum modeling (CLSM) based on the least square error criterion in the frequency domain. INTRODUCTION An immersive communication system requires rendering of acoustic events to enable effective collaboration through an interactive network – i.e., an interactive sound field network (ISFN) [1-3]. An acoustic events modeling language (AEML) is essential to acoustic events rendering based on structured audio representation [4]. This article describes a signal theoretical approach to rendering acoustic events. Signal theory itself can be an effective tool for acoustic engineering, since the human ear might be sensitive only to a resultant signal waveform. However, a signal theory for acoustic events must be deeply and effectively related to the source signal content or information that ensures a listener understands acoustic events through the signal sensation. The author will focus on speech intelligibility as the fundamental signal information that underlies acoustic events. This is because speech communication through acoustic events is a critical function, although the source signal information of acoustic events varies. This article, which mainly focuses on the representation of intelligible speech from the viewpoint of envelope-modulation modeling, should contribute significantly to AEML development. SINUSOIDAL ANALYSIS BY ITERATIVE SPECTRUM-PEAK PICKING BY FFT Signal representation, rendering, or morphing requires signal modeling that uses the fewest possible parameters, and spectrum-peak picking is a possible means of such signal representation [5]. Let us assume a target signal can be expressed in an analytic form as ), ( ) ( 1 2 n e A n x k K k n f j k a k ε π + ≡ ∑ = (1) where Ak and fk, respectively, denote the k-th sinusoidal component’s complex magnitude and frequency, K is the number of dominant sinusoidal components, and ) (n K ε denotes the residual component including the modeling error and external noise. The dominant components can be chosen by the following procedure. Step 1: Take the M-point FFT of the signal in the analytic (complex) form after zero-adding. Step 2: Find the component ) ( p k X that has the maximum in the power spectrum record obtained in Step 1. Step 3: Subtract the maximum component from the original signal , 1 , 1 , 0 for ) ( ) ( ) ( 2 − = − ≡ N n e k X n x n e M n k j p a a p L π and newly set . 1 , 1 , 0 for ) ( ) ( − = ← N n n e n x a a L Step 4: Repeat steps 1 to 3 until , ) ( 1
Viruses in the Mammalian Male Genital Tract and Their Effects on the Reproductive System

SUMMARY This review describes the various viruses identified in the semen and reproductive tracts of mammals (including humans), their distribution in tissues and fluids, their possible cell targets, and the functional consequences of their infectivity on the reproductive and endocrine systems. The consequences of these viral infections on the reproductive tract and semen can be extremely serious in terms of organ integrity, development of pathological and cancerous processes, and transmission of diseases. Furthermore, of essential importance is the fact that viral infection of the testicular cells may result not only in changes in testicular function, a serious risk for the fertility and general health of the individual (such as a fall in testosteronemia leading to cachexia), but also in the possible transmission of virus-induced mutations to subsequent generations. In addition to providing an exhaustive account of the data available in these domains, this review focuses attention on the fact that the interface between endocrinology and virology has so far been poorly explored, particularly when major health, social and economical problems are posed. Our conclusions highlight the research strategies that need to be developed. Progress in all these domains is essential for the development of new treatment strategies to eradicate viruses and to correct the virus-induced dysfunction of the endocrine system.
Online reverse auctions: Issues, themes, and prospects for the future

Online reverse auctions are increasingly being used in industrial sourcing activities. This phenomenon represents a novel emerging area of inquiry with significant implications for sourcing strategies. However, there is little systematic thinking or empirical evidence on the topic. This article reviews the use of these auctions in sourcing activities and highlights four key aspects: (1) the differences from physical auctions and those of the theoretical literature, (2) the conditions for using online reverse auctions, (3) the methods for structuring the auctions, and (4) the evaluations of auction performance. Some empirical evidence on these issues is also provided.
Optimum Structures for Sample Rate Conversion from CD to DAT and DAT to CD Using Multistage Interpolation and Decimation

This paper presents the optimum and minimum order structures for sample rate conversion from 44.1 KHz compact disc (CD) to 48 KHz digital audio tape (DAT) and from DAT to CD when using multirate method. We apply multistage up-sampling and down-sampling technique to obtain the optimum or minimum order configurations. The results show that the proposed structures are much more efficient than the previously presented multirate multistage interpolation and decimation structures, that is, they have the least computational complexity and lower order of filters
Notice of RetractionVehicle red-light violation detection base on region

Red-light violation video detection is one of the critical techniques in the intelligent transportation system, it is superior to traditional detection methods in aspect of function and maintenance. According to the practice of crossroads and the characteristics of vehicles running red-light, this paper presents a vision vehicle detection algorithm based on detection region to detect moving vehicles, and then analysis movement trend for vehicles by processing. The system implements the correct judgment of running red-light with two steps of process above. The experiment results show that the algorithm not only satisfies the real time requirement but also detects red-light violation with a high accuracy.
Mining hidden constrained streams in practice: Informed search in dynamic filter spaces

In this paper we tackle the recently proposed problem of hidden streams. In many situations, the data stream that we are interested in, is not directly accessible. Instead, part of the data can be accessed only through applying filters (e.g. keyword filtering). In fact this is the case of the most discussed social stream today, Twitter. The problem in this case is how to retrieve as many relevant documents as possible by applying the most appropriate set of filters to the original stream and, at the same time, respect a number of constrains (e.g. maximum number of filters that can be applied). In this work we introduce a search approach on a dynamic filter space. We utilize heterogeneous filters (not only keywords) making no assumptions about the attributes of the individual filters. We advance current research by considering realistically hard constraints based on real-world scenarios that require tracking of multiple dynamic topics. We demonstrate the effectiveness of our approaches on a set of topics of static and dynamic nature. The development of the approach was motivated by a real application. Our system is deployed in Dublin City's Traffic Management Center and allows the city officers to analyze large sources of heterogeneous data and identify events related to traffic as well as emergencies.
Cadherin-11 in poor prognosis malignancies and rheumatoid arthritis: common target, common therapies

Cadherin-11 (CDH11), associated with epithelial to mesenchymal transformation in development, poor prognosis malignancies and cancer stem cells, is also a major therapeutic target in rheumatoid arthritis (RA). CDH11 expressing basal-like breast carcinomas and other CDH11 expressing malignancies exhibit poor prognosis. We show that CDH11 is increased early in breast cancer and ductal carcinoma in-situ. CDH11 knockdown and antibodies effective in RA slowed the growth of basal-like breast tumors and decreased proliferation and colony formation of breast, glioblastoma and prostate cancer cells. The repurposed arthritis drug celecoxib, which binds to CDH11, and other small molecules designed to bind CDH11 without inhibiting COX-2 preferentially affect the growth of CDH11 positive cancer cells in vitro and in animals. These data suggest that CDH11 is important for malignant progression, and is a therapeutic target in arthritis and cancer with the potential for rapid clinical translation
Data Mining and XML Documents

XML is touted as the breakthrough in data exchange on the web. As XML material becomes more abundant, the ability to gain knowledge from XML sources decreases. Thus, there is a great need to apply data mining techniques to XML data. This paper suggests taxonomy of XML mining as a stepping-stone to further XML mining research. This paper explicitly expresses the available classes of XML material. This paper also proposes/surveys a number of possible data mining techniques that can be applied on structure or content of XML documents.
F2RL3 Methylation as a Biomarker of Current and Lifetime Smoking Exposures

Background: Recent genome-wide DNA methylation studies have found a pronounced difference in methylation of the F2RL3 gene (also known as PAR-4) in blood DNA according to smoking exposure. Knowledge on the variation of F2RL3 methylation by various degrees of smoking exposure is still very sparse. Objectives: We aimed to assess dose–response relationships of current and lifetime active smoking exposure with F2RL3 methylation. Methods: In a large population-based study, we quantified blood DNA methylation at F2RL3 for 3,588 participants using matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Associations of smoking exposure with methylation intensity were examined by multiple linear regression, controlling for potential confounding factors and paying particular attention to dose–response patterns with respect to current and lifetime smoking exposure as well as time since cessation of smoking. Results: F2RL3 methylation intensity showed a strong association with smoking status (p < 0.0001), which persisted after controlling for potential confounding factors. Clear inverse dose–response relationships with F2RL3 methylation intensity were seen for both current intensity and lifetime pack-years of smoking. Among former smokers, F2RL3 methylation intensity increased gradually from levels close to those of current smokers for recent quitters to levels close to never smokers for long-term (> 20 years) quitters. Conclusions: F2RL3 methylation is a promising biomarker for both current and long-term past tobacco exposure, and its predictive value for smoking-related diseases warrants further exploration. Citation: Zhang Y, Yang R, Burwinkel B, Breitling LP, Brenner H. 2014. F2RL3 methylation as a biomarker of current and lifetime smoking exposures. Environ Health Perspect 122:131–137; http://dx.doi. org/10.1289/ehp.1306937
Provisional chapter 1 Magnetic-Based Contact and Non-Contact 2 Manipulation of Cell Mockups and Biological MCF-7 3 Cells 4

The use of wireless magnetic control to transport and deliver chemotherapeutic agents selectively to tumor cells has become a promising strategy to mitigate the negative side effects associated with conventional treatment. It is necessary to manipulate and penetrate biological cells using magnetic agent to achieve this targeted drug delivery. Contact and non-contact micromanipulation of cell mockups and biological cells (human astrocytoma cell line U-373 MG and human breast adenocarcinoma cell line MCF-7) is achieved using magnetic agents (paramagnetic microparticles and iron oxide nanoparticles). The contact manipulation is accomplished under the influence of the controlled magnetic field gradients exerted on the magnetic agent, whereas the non-contact manipulation is done under the influence of the magnetic field and pressure gradients exerted on the agent and biological cells, respectively. We develop a magnetic-based teleoperation system that allows us to control the motion of the magnetic agents using microscopic feedback. This teleoperation is used to manipulate cell mockups toward reference positions in the presence and absence of contact between the cells and the magnetic agents. In addition, we demonstrate that iron oxide nanoparticles selectively move toward an MCF-7 cell and penetrate its walls without permanently damaging the membrane. This penetration is achieved in 28 seconds using controlled external magnetic fields and under microscopic vision guidance. The precise non-contact manipulation of biological cells using microparticles provides broad possibilities in targeted therapy and biomedical applications that require successful releases and selective penetration of cells without causing a permanent damage to the membrane.
A Machine Learning Approach for Future Career Planning

In this paper, we work on the modeling of peoples career paths. We ﬁrst collect a large number of people’s proﬁle and extract features from the descriptive information. Hand rules and clustering algorithm has been applied to help avoid the negative effect of natural language. We model people’s career developments with Markov Chain, and present our approach to estimate the transition probability matrix. Finally, we solve the problem that given a person’s current career path and his/her goal, what is the best best career development recommendation for him/her. As a conclusion, we will analyze the results and discuss possible improvements of our model
Performance Bounds for Parallel Processors.

Abstract : A general model of computation on a p-parallel processor is proposed, distinguishing clearly between the logical parallelism (p* processes) inherent in a computation, and the physical parallelism (p processor) available in the computer organization. This shows the dependence of performance bounds on both the computation being executed and the computer architecture.
Household Debt and Arrears: What Role Do Institutions Play? *

Despite the heightened debate on rising household debt, personal bankruptcy filings, and arrears, household debt repayment behaviour has been understudied, especially at the empirical level. This paper uses data from the European Community Household Panel to analyze the determinants of household debt arrears. The paper's primary aim is to understand the role of institutions in household arrears by exploiting crosscountry differences and the panel nature of the data set. We first analyze how the propensity to fall into arrears is affected by adverse events, while controlling for other observable demographic characteristics. We then show how the effects of the adverse events themselves vary across countries, depending on local financial and judicial institutions, which captures the differences in punishment and cost of default. Our findings indicate that adverse events matter, and the extent to which they do depends on the punishment associated with default. For example, our results show that in almost all cases unemployment shocks lead to a failure to repay loans on time—but all the more so in countries with limited information sharing, such as France. Similarly, where creditor rights are very poor, as in Finland and in Greece, negative earnings shocks are more likely to lead to household arrears.
TWO-VARIABLE p-ADIC L-FUNCTIONS

This is a write-up of my talk in the Stanford reading group on the work of BertoliniDarmon. The objective of my talk is to present a construction a two-variable p-adic Lfunction attached to a Hida family, and show that, in some sense, it p-adically interpolates special values of L-functions of the specializations of the Hida family. Let me be very imprecise in this passage and give a quick introduction to what lies ahead. Let f be an ordinary eigenform of weight k ≥ 2 living in a Hida family f∞. To f , one can associate a concrete object called a modular symbol, Ĩf , and one can even divide by an appropriate period, and obtain an algebraically-defined modular symbol, If . Let a, b be elements in P1(Q). The modular symbol is defined such that to any path from a to b in the completed complex upper half-plane, and any homogenous polynomial of degree k−2 in two variables X,Y , it associates an element in our coefficient field, essentially, by integrating f against P on the path. In particular, given a = 0, b = ∞, and P (X,Y ) = Xs0−1Y k−1−s0 (for integers 1 ≤ s0 ≤ k − 1), we obtain an element in our coefficient field denoted
Market-based Proportional Resource Sharing for Clusters

Enabling technologies in high speed communication and global process scheduling have pushed clusters of computers into the mainstream as general-purpose high-performance computing systems. More generality, however, implies more sharing and this raises new questions in the area of cluster resource management. In particular, in systems where the aggregate demand for computing resources can exceed the aggregate supply, how to allocate resources amongst competing applications is an important problem. Traditional solutions to this problem have focused mainly on global optimization with respect to system-centric performance metrics, metrics which ignore higher level user intent. In this paper, we propose an alternative market-based approach based on the notion of a computational economy which optimizes for user value. Starting with fundamental requirements, we describe an abstract architecture for market-based cluster resource management based on the idea of proportional resource sharing of basic computing resources. Using this architecture, we have implemented a 32-node (64 processors) prototype system that provides a market for time-shared CPU usage for sequential and parallel programs. To begin evaluating our ideas, we are currently in the process of studying how users respond to the system by collecting data on real day-to-day usage of the cluster.