Miracle-dz/UniFAR-FTUs huggingface dataset:
Re-citation Analysis: A Promising Method for Improving Citation Analysis for Research Evaluation, Knowledge Network Analysis, Knowledge Representation and Information Retrieval

Citation analysis is used in research evaluation exercises around the globe, directly affecting the lives of millions of researchers and the expenditure of billions of dollars. It is therefore crucial to seriously address the problems and limitations that plague it. Central amongst critiques of the common practice of citation analysis has long been that it treats all citations equally, be they crucial to the citing paper or perfunctory. Weighting citations by their value to the citing paper has long been proposed as a theoretically promising solution to this problem. Recitation analysis proposes to tune out the large percentage of perfunctory citations in a paper and tune in on crucial ones when performing citation analysis, by ignoring uni-citations (mentioned just once in a paper) and counting and analyzing only re-citations (used again and again in a citing paper). By focusing on core connections in knowledge networks, re-citation analysis can help research evaluation become more sensitive to the distinction between essential and perfunctory impact of research. It may benefit citation-link based knowledge representation and retrieval systems with improved precision by better capturing “aboutness” of articles, the essence of subject indexing in knowledge representation and retrieval, rather than merely providing “relatedness” information. Conference Topic Theory; Methods and techniques
Simulation of imprecise ordinary differential equations using evolutionary algorithms

This paper proposes a new approach, I n t e r ac t i ve Evol u t i o n a r y A l g o r i t h m Approach , for solving differential equations given imprecise initial values and/or imprecise differential equation parameters. A modified Evolutionary Algorithm with fuzzy sets representing the imprecise values simulates an imprecise ordinary differential equation.
Crenarchaeal chromatin proteins Cren7 and Sul7 compact DNA by inducing rigid bends

Archaeal chromatin proteins share molecular and functional similarities with both bacterial and eukaryotic chromatin proteins. These proteins play an important role in functionally organizing the genomic DNA into a compact nucleoid. Cren7 and Sul7 are two crenarchaeal nucleoid-associated proteins, which are structurally homologous, but not conserved at the sequence level. Co-crystal structures have shown that these two proteins induce a sharp bend on binding to DNA. In this study, we have investigated the architectural properties of these proteins using atomic force microscopy, molecular dynamics simulations and magnetic tweezers. We demonstrate that Cren7 and Sul7 both compact DNA molecules to a similar extent. Using a theoretical model, we quantify the number of individual proteins bound to the DNA as a function of protein concentration and show that forces up to 3.5 pN do not affect this binding. Moreover, we investigate the flexibility of the bending angle induced by Cren7 and Sul7 and show that the protein–DNA complexes differ in flexibility from analogous bacterial and eukaryotic DNA-bending proteins.
Music Recommendation System : Offline Evaluation of Learning Methodologies ( Based on Million Song Dataset Challenge by Kaggle )

We designed, implemented and analyzed a music recommendation system for our course project. Using the dataset provided by Kaggle [1] for their Million Song Dataset Challenge [2], we have analyzed various state-of-the-art techniques which can be used to build a music recommendation system. In this paper, we focus on describing different learning algorithms, which we employed in providing music recommendations. Apart from doing offline evaluations and analysis of different solutions, we also describe our experiences and learnings from building a prototype music recommendation system. Our results suggest that ensemble methods applied with user-based collaborative filtering work better than other methodologies for the chosen dataset in generating high quality recommendations for the music lovers.
A Comparative Prototype Research Methodology

1. Methodology Evaluating ubiquitous systems is hard, and has attracted the attention of others in the research community [5]. These investigators, like others in CSCW [3][6], argue there is a basic mismatch between traditional evaluation techniques and the needs posed by ubiquitous systems. Namely, these systems are embedded in a variety of complex real world environments that cannot be easily modeled (as required by theoretical analyses), simulated, measured, or controlled (as required by laboratory experiments). These concerns are shared by Abowd, Mynatt and Rodden, who argue “deeper evaluation results cannot be obtained through controlled studies in traditional, contained, usability laboratory. ” [2]. As a result, many investigators have abandoned traditional comparative evaluation techniques and opted instead for techniques adapted from the social sciences, such as anthropology. We wanted to perform a comparative evaluation similar to a laboratory experiment, but in such a way that we could observe the effects of our design decisions in relatively unconstrained, real world use. This led us to the following process: 1. Design with alternatives. Pick a design decision to vary and build prototypes (or configurations of an existing system) to embody multiple design alternatives. a. Make the system variants provide the same basic underlying functionality. b. Make the underlying system functionality as simple as possible but at the same time compelling and useful enough to produce real usage. 2. Vary deployment situations. Deploy the prototypes in varied situations to help answer the question: are observed effects linked to a single situation or are they more general? 3. Compare and contrast. Use qualitative or quantitative data collection and analysis techniques to compare and contrast the alternatives and situations. a. Try to determine whether observed effects vary depending on the design alternatives, the varied situations, or both. In addition, the prototypes (or configurations) need to be useful – they need to be used by real people to address real problems and fit in with existing practices. This should be accomplished through techniques such as informal observation of current work practices and problems, or by using more principled studies. This evaluative method gives us a framework for better understanding a ubiquitous computing system. It goes beyond designing for use and promotes designing for evaluation. The framework produces a matrix of observations and measurements across situations of use that help us to think about ubiquitous computing design.
Konrad-zuse-zentrum F ¨ Ur Informationstechnik Berlin Interior Point Methods in Function Space for State Constraints -inexact Newton and Adaptivity Interior Point Methods in Function Space for State Constraints -inexact Newton and Adaptivity

We consider an interior point method in function space for PDE constrained optimal control problems with state constraints. Our emphasis is on the construction and analysis of an algorithm that integrates a Newton path-following method with adaptive grid refinement. This is done in the framework of inexact Newton methods in function space, where the discretization error of each Newton step is controlled by adaptive grid refinement in the innermost loop. This allows to perform most of the required Newton steps on coarse grids, such that the overall computational time is dominated by the last few steps. For this purpose we propose an a-posteriori error estimator for a problem suited norm.
Black Hole Entropy and Fourier-Mukai Transform

We propose a microscopic CFT description of magnetically charged black holes in IIA compactifications on elliptic fibrations based on the Fourier-Mukai transform. The physical derivation of this model involves a chain of string duality transformations including the 4D/5D black hole correspondence. We compute the asymptotic behavior of the microstate degeneracy in a certain limit of large charges and show that it agrees with the macroscopic entropy formula. An interesting aspect of this setup is that the attractor points are situated deep in a hybrid phase of the quantum Kähler moduli space. duiliu@physics.rutgers. edu bflorea@slac.stanford. edu
High-Resolution Genome-Wide Analysis of Irradiated (UV and γ-Rays) Diploid Yeast Cells Reveals a High Frequency of Genomic Loss of Heterozygosity (LOH) Events

In diploid eukaryotes, repair of double-stranded DNA breaks by homologous recombination often leads to loss of heterozygosity (LOH). Most previous studies of mitotic recombination in Saccharomyces cerevisiae have focused on a single chromosome or a single region of one chromosome at which LOH events can be selected. In this study, we used two techniques (single-nucleotide polymorphism microarrays and high-throughput DNA sequencing) to examine genome-wide LOH in a diploid yeast strain at a resolution averaging 1 kb. We examined both selected LOH events on chromosome V and unselected events throughout the genome in untreated cells and in cells treated with either γ-radiation or ultraviolet (UV) radiation. Our analysis shows the following: (1) spontaneous and damage-induced mitotic gene conversion tracts are more than three times larger than meiotic conversion tracts, and conversion tracts associated with crossovers are usually longer and more complex than those unassociated with crossovers; (2) most of the crossovers and conversions reflect the repair of two sister chromatids broken at the same position; and (3) both UV and γ-radiation efficiently induce LOH at doses of radiation that cause no significant loss of viability. Using high-throughput DNA sequencing, we also detected new mutations induced by γ-rays and UV. To our knowledge, our study represents the first high-resolution genome-wide analysis of DNA damage-induced LOH events performed in any eukaryote.
Observed Issue Selling: The Effects of Role Models, Willingness to Issue Sell, and Inclusion in Decision Making

This study examines issue selling (an early component of the change process in which higher-level managers are influenced to pay attention to issues). Building on the conservation of resources model, social contextual factors (role models for issue selling and inclusion in decision making) are proposed to explain when and how issue selling occurs during the early stages of change. This research breaks new ground by examining issue selling behavior (as observed by supervisors) in conjunction with willingness to issue sell. Results based on a sample of 191 employee–supervisor dyads suggest that role models positively contributed to willingness to issue sell, which was positively related to issue selling when individuals perceived that they were involved in decision making. To increase the likelihood that employees will engage in issue selling to facilitate change, managers should provide exposure to issue selling role models and should increase employees’ perceived inclusion in decision making.
Extremal human curves: A new human body shape and pose descriptor

Automatic estimation of 3D shape similarity from video is a very important factor for human action analysis, but also a challenging task due to variations in body topology and the high dimensionality of the pose configuration space. We consider the problem of 3D shape similarity in 3D video sequence for different actors and motions. Most current approaches use conventional global features as a shape descriptor and define the shape similarity using L2 distance. However, such methods are limited to coarse representation and do not sufficiently reflect the pose similarity of human perception. In this paper, we present a novel 3D human pose descriptor called Extremal Human Curves (EHC), extracted from both the spatial and the topological dimensions of body surface. To compare tow shapes, we use an elastic metric in Shape Space between their descriptors, based on static features, and then perform temporal convolutions, thereby capturing the pose information encoded in multiple adjacent frames. We quantitatively analyze the effectiveness of our descriptors for both 3D shape similarity in video and content-based pose retrieval for static shape, and show that each one can contribute, sometimes substantially, to more reliable human shape and pose analysis. Experimental results are promising and show the robustness and accuracy of the proposed approach by comparing the recognition performance against several state-of-the-art methods.
Improving RRT with Context Sensitivity 15-780 Grad

The RRT algorithm represents an extreme in the design space of planning algorithms. It forsakes optimality and explores the space through randomness and a small bias towards goals. This is in marked contrast to other planning strategies such as visibility graphs or voronoi diagrams which carefully analyze and partition the space to find paths. This difference makes RRT very efficient even in higher dimensional spaces because its computational overhead is small in comparison to other algorithms which attempt to precisely characterize the world. However, this also means that RRT does not take advantage of information that it learns about the world while exploring. The central idea of our project is to introduce learning of the environment into the RRT algorithm for online use in the search and also for re-planning purposes. We focus our efforts on the extension length for two reasons. First, the RRT algorithm gets information about good and bad extension lengths from given points when it tests to see if a given extension fails. Second, the optimal extension length varies based on the obstacles surrounding a given point. The goal of this project is to extend the RRT planning and the ERRT re-planning algorithm to store and use information learned about good extension lengths while searching the space. Our hope is that we can realize significant improvements in how fast and often RRT-based planning finds the goal, without sacrificing its key principles. Our main goal is to explore a set of variations in the standard RRT (and ERRT) algorithms to try and offer a better algorithm for these heterogeneous worlds both in planning and re-planning scenarios. Some other papers describing extensions to the RRT algorithm which include [Lav98],[LL04],[JYLS05], and [YL09].
From preprocessing to fuzzy classification of IR images of paraffin embedded cancerous skin samples

Mid-Infrared (IR) micro-spectral imaging is an efficient method to analyze molecular composition of biomedical samples. In clinical oncology, this non-invasive technique is generally used on frozen biopsies to localize and diagnose cancerous tissues in their early stages. However, samples are usually fixed in paraffin in order to be preserved from decay, but the IR signature of paraffin prevents the study of the underlying tissue. To neutralize the paraffin signal from the recorded data, preprocessing methods based on Independent Component Analysis (ICA) and Nonnegatively Constrained Least Squares (NCLS) or on Extended Multiplicative Signal Correction (EMSC) have been recently developed. Then, in order to identify tumor areas, clustering techniques are applied on the preprocessed data, the final result being a false-color map of the biomedical sample which is comparable to the conventional histological image. By allowing each recorded spectrum to be assigned to every cluster, the fuzzy clustering gives more realistic results for unclear tissue boundaries by better highlighting the tumor and peritumoral areas. A recent algorithm based on the redundancy of classes allows to automatically estimate the optimal number of classes and the optimal fuzzy parameter. In this paper, we analyze the effects of the preprocessing methods on the optimal parameter extraction and on the results of the fuzzy clustering on different paraffin embedded cancerous skin samples.
Immunogenicity and protective efﬁcacy of orally administered recombinant Lactococcus lactis expressing surface-bound HIV Env

This study investigates whether genetically modiﬁed orally administered Lactococcus lactis ( L lactis ) could be used as an HIV vaccine. L lactis is immunogenic and extremely safe when delivered orally. We created a recombinant L lactis vector expressing the envelope protein of HIV on its cell surface. Oral immunization with this vector induced high levels of HIV-speciﬁc serum IgG and fecal IgA antibodies. Cell-mediated immune responses also were generated in both the regional lymph nodes and the spleen. Dendritic cells are readily infected by L lactis and appear to play a potential role in mediating the development of these immune responses. The protective efﬁcacy of this vaccine strategy was demonstrated by challenging mice intraperitoneally with an HIV Env–expressing vaccinia virus. Their viral loads were 350-fold lower than those of control mice. These ﬁndings support the further development of L lactis –based HIV vaccines. (Blood. 2003; 102:223-228)
Teachers' Changing Conceptions of Writing Instruction.

In the 1970s a shift in the dominant theory of writing instruction began, away from a focus on the written product and form of writing toward an emphasis on the writing process in all of its complexity (Freedman, Dyson, Flower, & Chafe, 1987). Several overlapping but distinct definitions and theories of process writing arising from cognitive, social constructivist, and naturalistic frameworks have evolved. For instance, Hayes and Flower (1980; 1986) have seen writing as a goal-directed cognitive activity involving planning, translating, and reviewing that requires rhetorical knowledge, subject matter knowledge, and strategic knowledge. Other researchers emphasize writing as a social activity associated with particular practices (Bruffee, 1984; Freedman, Dyson, Flower, & Chafe, 1987; Scribner & Cole, 1981). As a social process, the features of audience and purpose are highlighted. Shaunessey (1977) sees composing as a socialization process in which the writer brings his/her thinking in line with discourse conventions of the community of readers. Nystrand (1989) argues in a similar way that writing is a social interactive process between readers and writers within discourse communities. Educators and researchers from a more naturalistic tradition see writing as a natural process that can be activated by encouraging environments (e.g., Emig, 1981). Graves (1983) and Calkins (1986) also see the establishment of a literate environment as crucial to teaching students how to express themselves. Although these theories of writing and their links to process approaches dominate the literature, a gap remains between the theories and how they are enacted in classrooms (Applebee, 1986). Applebee found that writing was used primarily to assess learning, that prewriting activities constituted a minimum amount of time, and that peer response groups occurred in only a minority of classrooms. District-wide writing tests, minimal support for instructional innovation, and system-wide pressure for improving achievement tests scores are some of the reasons researchers have suggested for the difficulties of changing classroom norms that would support process approaches (Florio-Ruane, 1991; Michaels, 1987; Ulichney & Watson-Gegeo, 1989). Additionally, teachers' views about writing may play a role in how they implement writing programs within classrooms similar to the relationship between teachers' stated beliefs about the reading process and their classroom practices (Richardson, Anders, Tidwell, & Lloyd, 1991). If teachers hold traditional views of writing as consisting of appropriate syntax, grammatical structures,
Structural basis of thrombin–protease‐activated receptor interactions

Aggregation of platelets is an essential step in the formation of a stable blood clot during vascular injury. The trypsin‐like protease thrombin acts as the dominant agonist of platelet activation on engagement of protease‐activated receptors (PARs). Important details on the molecular aspects of thrombin–PAR interactions have been revealed recently by structural biology. In the case of human platelets, PAR1 engages thrombin via an extended surface of recognition encompassing the active site and exosite I. In the case of murine platelets, PAR4 binds to the active site in a conformation that leaves exosite I free for interaction with cofactors like PAR3. Human PAR4 mimics the murine receptor binding mechanism for residues upstream of the scissile bond. This information is consistent with existing functional data and provides a solid background for future structural and mutagenesis studies of PAR interaction with thrombin and related proteases. © 2011 IUBMB IUBMB Life, 63(6): 375–382, 2011
Wavelength division multiplexed optical interconnects using femtosecond optical pulses

We demonstrate the operation of a multiple channel chip-to-chip wavelength division multiplexed (WDM) interconnect through a single fiber using GaAs diodes flip-chip bonded onto silicon. Multiplexing information onto a single fiber can minimize the high costs of fiber pigtailing, while avoiding time-division multiplexing circuits with their associated power consumption, latency, and very high-speed electronics. Additionally, traditional WDM systems use a separate laser for each channel. This increases both cost and complexity by requiring multiple sources and wavelength stabilization. We eliminate these concerns by using a mode-locked Ti:sapphire femtosecond laser as a broadband WDM source and employing the technique of "spectral slicing" to define our WDM channels.
Multi-Agent Decision Making with Assumption-based Argumentation Paper 490

Much research has been devoted in recent years to argumentationbased decision making. However, less attention has been given to argumentation-based decision making amongst multiple agents. We present a multi-agent decision framework based on Assumptionbased Argumentation. In our model, agents have goals and decisions have attributes which satisfy goals. Our framework supports agents with different goals, candidate decisions, attributes and relations amongst them. Using an existing argumentation-based dialogue framework, we show how two agents can argue towards “good” decisions in a distributed manner. We show that, under specific conditions, “good” decisions correspond to (1) admissible arguments for the two agents and (2) claims of successful dialogues between the two agents. Thus, this work connects decision making with multi-agent argumentation and dialogues.
3-D Path-Following Control for a Model-Scaled Autonomous Helicopter

A 3-D path-following controller is proposed in this brief for a 6-degrees-of-freedom model-scaled autonomous helicopter. The reference path and path-following errors are newly defined using implicit expressions. On the basis of geometric analysis, a new speed error is designed for singularity avoidance. The proposed control algorithm is designed using command filtered backstepping, such that complicated solutions for derivatives of virtual controls are circumvented. It is proved that, with the proposed controller, path-following errors are locally ultimately bounded. Theoretical results are demonstrated by the numerical simulation.
Medical image segmentation on the basic of a variational level set

In this paper, on the basis of techniques of curve evolution, we propose a novel variational level set model for segmentation of intensity inhomogeneity images. The model is integrated with some advantages of fitting statistical model and region-based active contour model to the intensity in each of a set of regions. Furthermore, the experimental results show the validity of this model for various image modalities. All of these results may be useful in the study of the image segmentation.