Miracle-dz/UniFAR-FTUs huggingface dataset:
INsite: introduction to a generic paradigm for interpreting user-Web space interaction

INsite is a heuristic-based implementation to provide consistent tracking, analysis and visualization of users' interactions with a generic web site. Our research has immediate applicability in such disparate fields as Business, E-commerce, Distance Education, Entertainment and Management for capturing individual and collective profiles of customers, learners and employees. INsite can identify trends and changes in user(s) behavior (interests) by monitoring their online interactions. It has a three-tier architecture for tracking, analysis and visualization. First, a remote agent transparently tracks user-navigation-paths within a site. Second, a unique Connectivity Matrix (CM) Model (a set of Connectivity Matrices) represents each path (and cluster of paths). Third, the user-web site interaction, thus translated to a finite number of CM-Models, is readily visualized by graphically representing the member matrices of the models. Each member matrix of a representative CM-Model captures a single navigational attribute. Our dimensionally static approach to path and cluster representation by the Connectivity Matrices can reduce the complexity of analysis by several orders. Consequently, we employ a new paradigm for dynamic clustering that leverages on the unique CM-Model of representation.
Enabling near real-time central control for live video delivery in CDNs

User-created live video streaming is marking a fundamental shift in the workload of live video delivery. However, live-video-specific challenges and the viral nature of user-created content makes it difficult for current CDNs to deliver 1) high-quality, 2) highly-scalable, and 3) highly-responsive service. We present the design and implementation of VDN, a new control plane for CDNs designed to optimize the delivery of live streams within the CDN. VDN satisfies these requirements by using two approaches: 1) optimizing directly for video quality (not just throughput) and 2) combining centralized control with local control, allowing VDN to adapt to traffic dynamics and network failures at fine timescales.
Multidrug Resistance: An Emerging Crisis

The resistance among various microbial species (infectious agents) to different antimicrobial drugs has emerged as a cause of public health threat all over the world at a terrifying rate. Due to the pacing advent of new resistance mechanisms and decrease in efficiency of treating common infectious diseases, it results in failure of microbial response to standard treatment, leading to prolonged illness, higher expenditures for health care, and an immense risk of death. Almost all the capable infecting agents (e.g., bacteria, fungi, virus, and parasite) have employed high levels of multidrug resistance (MDR) with enhanced morbidity and mortality; thus, they are referred to as “super bugs. ” Although the development of MDR is a natural phenomenon, the inappropriate use of antimicrobial drugs, inadequate sanitary conditions, inappropriate food-handling, and poor infection prevention and control practices contribute to emergence of and encourage the further spread of MDR. Considering the significance of MDR, this paper, emphasizes the problems associated with MDR and the need to understand its significance and mechanisms to combat microbial infections.
On Doctors, Mechanics and Computer Specialists - the Economics of Credence Goods

Most of us need the services of an expert when our apartment's heating or our washing machine breaks down, or when our car starts to make strange noises. And for most of us commissioning an expert to solve the problem causes concern. This concern does not disappear even after repair and payment of the bill. On the contrary, one worries about paying for a service that was not provided, or receiving some unnecessary treatment. This article studies the economics underlying these worries. Under which conditions do experts have an incentive to exploit the informational problems associated with markets for diagnosis and treatment? What types of fraud exist? What are the methods and institutions for dealing with these informational problems? Under which conditions does the market provide incentives to deter fraudulent behavior? And what happens if all or some of those conditions are violated?
Invariant games and non-homogeneous Beatty sequences

We characterize all the pairs of complementary non-homogenous Beatty sequences $(A_n)_{n\ge 0}$ and $(B_n)_{n\ge 0}$ for which there exists an invariant game having exactly $\{(A_n,B_n)\mid n\ge 0\}\cup \{(B_n,A_n)\mid n\ge 0\}$ as set of $\mathcal{P}$-positions. Using the notion of Sturmian word and tools arising in symbolic dynamics and combinatorics on words, this characterization can be translated to a decision procedure relying only on a few algebraic tests about algebraicity or rational independence. Given any four real numbers defining the two sequences, up to these tests, we can therefore decide whether or not such an invariant game exists.
A practical method for image rectification

A unitary, molded plastic device for holding and displaying a decorative article, such as a plate, from a vertical surface, such as a wall, which holder includes an annular body member having projecting radially outward therefrom three support members that include hook elements, for engaging and holding said plate, and positioning elements, for spacing said holder from a wall on which said holder is supported.
Beyond consumer responsibilization: Slow Food’s actually existing neoliberalism

Critics of political consumerism argue that it perpetuates a neoliberal belief that complex societal problems are best redressed through the market-coordinated choices and actions of socially responsible consumers. However, such critiques overlook how neoliberalism is actually enacted in particular socio-cultural contexts and the variegated ideological effects that result. To redress this gap, we analyze the “actually existing neoliberalism” manifest in a Slow Food network. This discursive system presents an intersection between a neoliberal discourse of passionate entrepreneurialism and a politicized therapeutic ethos that traces to the organization’s historical roots in Italian leftist politics. Through this actually existing neoliberalism, Slow Food enthusiasts constitute themselves as ethical agents who are sharing their passion and helping others gain autonomy from the corporate controlled, industrialized food system. This ideological framing buttresses the ethical authority of the Slow Food movement by countering the cultural condemnation that its politicized taste practices are elitist affectations.
Chinese Sentiment Analysis Using Maximum Entropy

This paper presents the use of Maximum Entropy technique for Chinese sentiment analysis. Berger, Vincent and Stephen (1996) prove that Maximum Entropy is a technique that is effective in a number of natural language processing applications. In this paper, Maximum Entropy classification is used to estimating the polarity of given comments of from electronic product. These messages are classified into either positive or negative. Apart from presenting the results obtained via Maximum Entropy technique, we also analyze the feature selection and pre-processing of the comments for training and testing purpose.
A Survey of Personalized Web Search in Current Techniques

World wide web(WWW) is very popular and commonly used internet’s information retrieval service. Nowa-days commonly used task on internet is web search. User get variety of related information for their queries. To provide more relevant and effective results to user, Personalization technique is used. Personalized web search refer to search information that is tailored specifically to a person’s interests by incorporating information about query provided. Two general types of approaches to personalizing search results are modifying user’s query and reranking search results. Several personalized web search techniques based on web contents, web link structure, browsing history ,user profiles and user queries. The proposed paper is to represent survey on various techniques of personalization. Keywords— Personalized web search, user profile, Information retrieval , search queries, User model, Data mining .
Mixed Reality Games

OUR RESEARCH WORK DEALS WITH THE DEVELOPMENT OF NEW GAME-BASED LEARNING (GBL) ENVIRONMENTS. WE THINK THAT THE WAY OF ACQUIRING KNOWLEDGE DURING A LEARNING SESSION IS SIMILAR TO FOLLOWING AN ADVENTURE IN A ROLE-PLAYING GAME AND WE APPLY THE METAPHOR OF EXPLORING A VIRTUAL WORLD, WHERE EACH STUDENT EMBARKS ON A QUEST IN ORDER TO COLLECT KNOWLEDGE RELATED TO A LEARNING ACTIVITY. IN OUR UNIVERSITY, WE HAVE SET UP NUMBERS OF EXPERIMENTS WITH STUDENTS USING GBL ENVIRONMENTS. THEY REVEALED WEAKNESSES FOR SPECIFIC LEARNING ACTIVITIES. SOMETIMES, LEARNERS SEEM TO ACQUIRE A SKILL IN THE GAME, BUT THEY ARE NOT ABLE TO REUSE IT EASILY IN THE REAL WORLD. THIS IS PARTICULARLY THE CASE FOR SKILLS THAT REQUIRE CONCRETE MANIPULATION OF REAL OBJECTS TO BE ACQUIRED. GBL ENVIRONMENTS THUS LACK OF MEANS TO LEARN KNOW-HOW ASPECTS. SOME OF THE LEARNING PROCESSES INVOLVING REAL WORLD OBJECTS ARE VERY DIFFICULT TO REPRODUCE IN GBL ENVIRONMENTS AND THERE IS AN ESSENTIAL TECHNOLOGICAL ISSUE IN MIXING VIRTUAL AND REAL ASPECTS IN GBL ENVIRONMENTS. IN THIS ARTICLE, WE DESCRIBE THE POSSIBLE PROBLEMS THAT CAN APPEAR WHEN USING THIS MIXED APPROACH, GIVE HINTS ON HOW TO AVOID THEM AND ILLUSTRATE OUR PROPOSITION WITH EXAMPLES ISSUED FROM THE ELECTRONIC DOMAIN. WE FOCUS ON ISSUES LINKED TO THE TRANSITION BETWEEN VIRTUAL AND REAL WORLDS AND WE EXPLORE HOW NEW ELECTRONIC FEATURES CAN FACILITATE THIS MIXED APPROACH, WHERE IDENTIFICATION, LOCALISATION AND UPDATE OF THE USER MODELS ARE KEY ISSUES.
CUMULATIVE RESEARCH KNOWLEDGE AND SOCIAL POLICY FORMULATION : The Critical Role of Meta-Analysis

For many years, policymakers expressed increasing frustration with social science research. On every issue there were studies arguing for diametrically opposed conclusions. Methods of meta-analysis that correct for the effects of sampling error have shown that almost all such conflicting results were caused by sampling error. Furthermore, the effects of sampling error are greatly exaggerated by using significance test methodology. In many areas, meta-analysis has now provided dependable answers to the original research questions. Meta-analysis is now increasingly being used by policymakers, by textbook writers, and by theorists to provide the basic facts needed to draw both practical and explanatory conclusions. Sophisticated meta-analysis procedures are now used to correct for the effects of other study imperfections, such as measurement error, range restriction, and artificial dichotomization. In domains where the data on artifacts are available, the effect sizes in necessarily imperfect studies have been found to be considerably understated. Path analysis can be applied to the findings from meta-analysis to yield improved causal analyses that result in both explanation of results and improved generalization of results to new settings.
Incorporating Information on Neighboring Coefficients Into Wavelet Estimation

In standard wavelet methods, the empirical wavelet coe cients are thresholded term by term, on the basis of their individual magnitudes. Information on other coe cients has no in uence on the treatment of particular coe cients. We propose a wavelet shrinkage method that incorporates information on neighboring coe cients into the decision making. The coe cients are considered in overlapping blocks; the treatment of coe cients in the middle of each block depends on the data in the whole block. The asymptotic and numerical performances of two particular versions of the estimator are investigated. We show that, asymptotically, one version of the estimator achieves the exact optimal rates of convergence over a range of Besov classes for global estimation, and attains adaptive minimax rate for estimating functions at a point. In numerical comparisons with various methods, both versions of the estimator perform excellently.
Learning the sparse representation for classification

In this work, we propose a novel supervised matrix factorization method used directly as a multi-class classifier. The coefficient matrix of the factorization is enforced to be sparse by ℓ1-norm regularization. The basis matrix is composed of atom dictionaries from different classes, which are trained in a jointly supervised manner by penalizing inhomogeneous representations given the labeled data samples. The learned basis matrix models the data of interest as a union of discriminative linear subspaces by sparse projection. The proposed model is based on the observation that many high-dimensional natural signals lie in a much lower dimensional subspaces or union of subspaces. Experiments conducted on several datasets show the effectiveness of such a representation model for classification, which also suggests that a tight reconstructive representation model could be very useful for discriminant analysis.
Spatial organization of firms: local vs. national firms and the impact of trade liberalization

What is the impact of international trade on cities and rural areas within a country? Existing studies on this topic are built on new economic geography models, which focus on the effect of international trade on the change in the balance between agglomeration and dispersion forces of the manufacturing firms. Recent studies, however, suggest that large cities today can be characterized as specializing in providing business services to host corporate headquarters, rather than as agglomeration of manufacturing. The aim of this paper is then to analyse the impact of international trade on internal cities and rural areas, taking into account the changing spatial organization of firms and the role of cities today. We construct and analyse an urban-rural model with a city hosting headquarters of firms, but allowing for the coexistence of headquarters in rural areas. The balance between the gains from having headquarters in the city with access to business services and the urban cost determines the spatial organization of firms and the corresponding city size. The model is extended to analyse the impact of trade liberalization. In an open economy, the city is likely to grow larger despite the urban costs. However, when exporting requires additional fixed costs in the form of larger headquarters, the result may be reversed; opening up to international trade may work in favour of smaller local firms, leading to a dispersion of economic activities away from the city. JEL Classifications: F12, R12
Model-Based Concurrency Analysis of Network Simulations

To achieve highest performance, parallel simulation of networks on modern hardware architectures depends on large numbers of independent computational tasks. However, the properties determining a network model's concurrency are still not well understood. In this paper, we propose an analytical model that enables concurrency estimations based on model knowledge and on statistics gathered from sequential simulation runs. In contrast to an automated concurrency analysis of event traces, the analytical approach enables insights into the relationship between the topology and communication patterns of the simulated network, and the resulting concurrency. We consider three fundamentally different network models as implemented in the network simulators PeerSim and ns-3: a large-scale application-layer peer-to-peer network, IP-based routing in a fixed topology, and a wireless ad-hoc network. For each model, we conduct an in-depth analysis, exposing the relationships between model characteristics and concurrency. Our analysis is validated by comparing estimated concurrency values to reference results of a trace-based analysis. The identification of key factors for concurrency forms a step towards a classification of network models according to their potential for parallelization.
Association of Insulin Receptor Substrate 1 (IRS-1) Y895 with Grb-2 Mediates the Insulin Signaling Involved in IRS-1-Deficient Brown Adipocyte Mitogenesis

ABSTRACT We have recently generated immortalized fetal brown adipocyte cell lines from insulin receptor substrate 1 (IRS-1) knockout mice and demonstrated an impairment in insulin-induced lipid synthesis as compared to wild-type cell lines. In this study, we investigated the consequences of IRS-1 deficiency on mitogenesis in response to insulin. The lack of IRS-1 resulted in the inability of insulin-stimulated IRS-1-deficient brown adipocytes to increase DNA synthesis and enter into S/G2/M phases of the cell cycle. These cells showed a severe impairment in activating mitogen-activated protein kinase kinase (MEK1/2) and p42-p44 mitogen-activated protein kinase (MAPK) upon insulin stimulation. IRS-1-deficient cells also lacked tyrosine phosphorylation of SHC and showed no SHC–Grb-2 association in response to insulin. The mitogenic response to insulin could be partially restored by enhancing IRS-2 tyrosine phosphorylation and its association with Grb-2 by inhibition of phosphatidylinositol 3-kinase activity through a feedback mechanism. Reconstitution of IRS-1-deficient brown adipocytes with wild-type IRS-1 restored insulin-induced IRS-1 and SHC tyrosine phosphorylation and IRS-1–Grb-2, IRS-1–SHC, and SHC–Grb-2 associations, leading to the activation of MAPK and enhancement of DNA synthesis. Reconstitution of IRS-1-deficient brown adipocytes with the IRS-1 mutant Tyr895Phe, which lacks IRS-1–Grb-2 binding, restored SHC–IRS-1 association and SHC–Grb-2 association. However, the lack of IRS-1–Grb-2 association impaired MAPK activation and DNA synthesis in insulin-stimulated mutant cells. These data provide strong evidence for an essential role of IRS-1 and its direct association with Grb-2 in the insulin signaling pathway leading to MAPK activation and mitogenesis in brown adipocytes.
Electroacupuncture Ameliorates Learning and Memory via Activation of the CREB Signaling Pathway in the Hippocampus to Attenuate Apoptosis after Cerebral Hypoperfusion

Studies have shown that electroacupuncture (EA) ameliorates learning and memory after ischemic injury. However, there have been few studies elucidating the mechanisms of EA on learning and memory in cerebral hypoperfusion. In this study, we explored the cAMP response element-binding protein (CREB) signaling pathway-mediated antiapoptotic action involved in EA-induced improvement of learning and memory. EA at GV20 and GV14 acupoints was applied in cerebral hypoperfusion rats. A Morris water maze task was performed, and the immunoreactivities of pCREB, Bcl-2, and Bax in the hippocampal CA1 area were evaluated by the Western blotting technique. Our findings indicated that (1) EA ameliorated spatial learning and memory impairment in cerebral hypoperfusion rats; (2) EA increased the immunoreactivities of pCREB and Bcl-2 and decreased the immunoreactivity of Bax; (3) intracerebroventricular administration of H89 (the inhibitor of protein kinase A) blocked EA-induced, pCREB-mediated antiapoptotic action and improved learning and memory. These results suggest that EA can ameliorate learning and memory via activation of the CREB signaling pathway in the hippocampus to attenuate apoptosis after cerebral hypoperfusion.
Dictionary and Monolingual Corpus-based Query Translation for Basque-English CLIR

This paper deals with the main problems that arise in the query translation process in dictionary-based Cross-lingual Information Retrieval (CLIR): translation selection, presence of Out-Of-Vocabulary (OOV) terms and translation of Multi-Word Expressions (MWE). We analyse to what extent each problem affects the retrieval performance for the Basque-English pair of languages, and the improvement obtained when using parallel corpora free methods to address them. To tackle the translation selection problem we provide novel extensions of an already existing monolingual target co-occurrence-based method, the Out-Of Vocabulary terms are dealt with by means of a cognate detection-based method and finally, for the Multi-Word Expression translation problem, a naïve matching technique is applied. The error analysis shows significant differences in the deterioration of the performance depending on the problem, in terms of Mean Average Precision (MAP), the translation selection problem being the cause of most of the errors. Otherwise, the proposed combined strategy shows a good performance to tackle the three above-mentioned main problems.
ULTRASONIC ELASTOGRAPHY MEASUREMENTS OF THE MECHANICAL PROPERTIES OF PORCINE CORONARY VESSEL WALLS

being a part of my thesis committee. from Vito lab for their kind help. Dr. Guldberg and lab, thank you for letting me use the mechanical testing facility. Tracey Couse, thank you for doing everything that you could do to make my research successful. To Dr. Y's lab, Dr. Ku's lab and Daniel thank you for helping me bring those innumerable porcine hearts. Thank you Mr. Hollifield and Hollifield Farms for letting me use the porcine hearts, an integral part of my research. I thank the administrative staff of Biomedical Engineering, Bioengineering and Petit Institute of Biosciences. A special mention of Chris Ruffin and Pat Fowler for welcoming me into Tech and helping me fill those numerous forms. Rohit my life in Atlanta wouldn't have been same if it wasn't for you all. Ruchira, Kaustubh, Gokul, Manjiri and Vaishali thank you for being there for me when I needed for always being there for me. I am grateful for having many wonderful people in my life, my friends, my relatives and my grandparents for making my world a better place. I would like to dedicate this thesis to my parents and my brother for their support, encouragement and great love throughout my life.
Learning by annotating: A system development study of real-time synchronous supports for distributed learning in multiple locations

This paper presents an annotative system to facilitate a real-time, synchronous distributed-learning in multiple locations - the SynTag system. The system offers an ICT-mediated support for collaborative learning in both on-site and off-site environments via the technology of broadcasting, interactive tagging and dynamic chart. The assessment of the practical experiment recognizes that the system is able to frame an online, instant communicative social network for system-users in varying locations. System-users are encouraged to concentrate on learning materials at the meanwhile embed in the presented feedbacks of collaborative learning. The SynTag system offers an opportunity of multi-locational collaborative learning for groups and individual participants. The current system has been addressed in learning programs for around a year, and its practical experiments are embedded for revised developments.
Internal Adequacy of Bookkeeping in Coq

We focus on a common problem encountered in encoding and formally reasoning about a wide range of formal systems, namely, the representation of a typing environment. In particular, we apply the bookkeeping technique to a well-known case study (i.e., System F<:'s type language), proving in Coq an internal correspondence with a more standard representation of the typing environment as a list of pairs. In order to keep the signature readable and concise, we make use of higher-order abstract syntax (HOAS), which allows us to deal smoothly with the representation of the universal binder of System F<: type language.