Miracle-dz/UniFAR-FTUs huggingface dataset:
Antibody-Induced Shedding of CD44 from Adherent Cells Is Linked to the Assembly of the Cytoskeleton1

CD44 is a widely expressed integral membrane glycoprotein that serves as a specific adhesion receptor for the extracellular matrix glycosaminoglycan hyaluronan. CD44 participates in a variety of physiological and pathological processes through its role in cell adhesion. Under appropriate conditions, the ectodomain of CD44 is proteolytically removed from the cell surface. In this study we show that excessive CD44 shedding can be induced in mouse fibroblasts and monocytes upon exposure of these cells to a CD44-specific Ab immobilized on plastic, whereas treatment with phorbol ester induces significantly enhanced CD44 release from the monocytes only. CD44 shedding proceeds normally in fibroblasts and monocytes deficient in TNF-α converting enzyme (TACE), a sheddase involved in the processing of several substrates. Conversely, activation of the CD44 protease has no effect on the release of TNF-α from TACE-expressing cells, although the same metalloprotease inhibitor effectively blocks both TACE and the CD44 sheddase. Concomitant with anti-CD44 Ab- or phorbol ester-induced CD44 shedding, dramatic changes are observed in cell morphology and the structure of the actin cytoskeleton. Disruption of actin assembly with cytochalasin reduces CD44 shedding, but not the release of TNF-α. Moreover, pharmacological activation of Rho family GTPases Rac1 and Cdc42, which regulate actin filament assembly into distinct cytoskeletal structures, has a profound effect on CD44 release. We conclude that the CD44 sheddase and TACE are distinct enzymes, and that Ab- and phorbol ester-enhanced cleavage of CD44 is controlled in a cell type-dependent fashion by Rho GTPases through the cytoskeleton.
Squeezing Birth into Working Life

Part 1 Introduction: subject relevance positioning in the scientific field data outline. Part 2 Breadwinner ideology against individual and equal role-sharing ideology: introduction social policy ideologies 1 - principle of need, market work performance and citizenship social policy ideologies 2 - principles of maintenance and care actual public policies on the family conclusions. Part 3 Creating comparative fertility and work files from household panel data sets: introduction description of household panel data sets birth events in a woman's life labour market histories around births finding husbands and/or cohabiting men earnings of women and men around the date of having children comparing education across countries comparing years of experience in paid work between countries conclusions. Part 4 Women's labour force transitions in connection with childbirth: introduction labour force participation before entering motherhood homemakers and market career women the timing of entering the labour force after birth conclusions. Part 5 Women's share in earnings before and after the birth of children: introduction data and definition of variables women's contribution to family income an explanation of the change in earnings around childbirth decomposition of after-birth's earnings - a comparison between Germany and Sweden using simulations concluding remarks. Part 6 Paid careers and the timing and spacing of births in Germany, Great Britain and Sweden: introduction theoretical considerations on timing and spacing of births effects of family policies on timing and spacing of children in Germany, United Kingdom and Sweden data and comparability of variable definitions across countries who postpones first birth? clustering births or second career break? conclusions. Part 7 Optimal age at maternity in the Netherlands: introduction women's education, labour force participation, hours of work and fertility theoretical considerations on optimal age at maternity wages of future mothers simulations of lifetime earnings loss of timing of maternity lifetime earnings gain by postponement of first birth conclusions.
GaGa : a Parsimonious and Flexible Hierarchical Model for Microarray Data Analysis

Bayesian hierarchical models are attractive for microarray data since they allow sharing information across genes and across different analyses in a coherent manner. Kendziorski et al. (2003) and Newton et al. (2004) introduced the gamma-gamma hierarchical model. The model parsimoniously describes the expression of thousands of genes with a small number of hyper-parameters. This makes the model easy to interpret and analytically tractable. However, we find important limitations of the model when fitting real datasets. The limitations are due to some of the assumptions being too restrictive. We propose a simple extension of the model that improves the fit substantially with almost no increase in complexity. The model allows comparing not only mean expression between groups but also the distributional shape, which we argue to be of biological relevance. We propose a second extension that uses a mixture of gamma distributions to further improve the fit, at the expense of increased computational burden. We propose several approximations that significantly reduce the computational cost. We use our approach for inference about differential gene expression and for class prediction, both in simulated and real datasets. We find that both extensions are preferable to the original formulation of the model, and that they provide advantages over several other popular methods, especially for small samples.
A New Realistic Tone Mapping Model

To properly reproduce a highy dynamic range image on a graphic display system is a harder problem than is commonly acknowledged. The last years have seen great progress in this area, and for non-interactive tone mapping problems adequate levels of realism have already been demonstrated, namely through the multiscale model of adaptation of Pattanaik[9] et al. Unfortunately, the high computational cost of their methods has so far precluded their use for the purposes of real-time rendering, and they have also been confined to single images without a temporal dependency. Conversely, the work of Tumblin[14] et al. have demonstrated time dependency and interactivity for tone mapping techniques, but at the cost of significantly reduced realism. In this paper we present a new high-quality time–dependent tone mapping algorithm which is comparable to the work of Pattanaik et al. in terms of visual realism, and demonstrate its viability on a number of test scenes.
Enterprise Library Management for Digital Media with Dynamic Media Synthesis

Media players, personal digital assistants and cell phones are rapidly becoming more adept at rendering media files. Support for a plethora of CODECS can be found even in fairly inexpensive devices. While these devices are becoming increasingly capable of rendering media, the media itself has largely been relegated to prerecorded music, radio and television excerpts, and pay per download entertainment content. This paper is intended to introduce both the concept and the system surrounding digital media in the enterprise realm. This digital media is created dynamically, from enterprise resources, databases, XML data and other repositories. In addition to our innovations that will give corporate users access to enterprise media in a handheld form factor, our research is also focused on globalization, investigating ways in which products can be transformed into multi-lingual offerings to serve a new generation of global business needs
A Secure High-Speed Identification Scheme for RFID Using Bloom Filters

As pervasive computing environments become popular, RFID tags are introduced into our daily life. However, there exists a privacy problem that an adversary can trace users' behavior by linking the tag's ID. Although a Hash-chain scheme can solve this privacy problem, the scheme needs a long identification time or a large amount of memory. In this paper, we propose an efficient identification scheme using Bloom filters, which are space-efficient probabilistic data structures. Our Bloom pre-calculation scheme provides a high-speed identification with a small amount of memory by storing pre-calculated outputs of the tags in Bloom filters.
TMPRSS4 as an emerging potential poor prognostic factor for solid tumors: A systematic review and meta-analysis

Recent studies have investigated the potential prognostic value of the transmembrane protease serine 4 (TMPRSS4) in various solid tumors. Yet, the results are inconclusive. Here, we performed this meta-analysis to clarify this issue. Relevant articles were identified by searching PubMed, Web of Science and Embase databases. The primary outcome endpoints were patients' overall survival (OS) and time to tumor progression (TTP). Twelve studies involving 1,955 participants were included. We showed that high TMPRSS4 expression in tumor tissues was significantly associated with patients' poor OS (pooled HR = 2.981, 95% CI = 2.296-3.869, P < 0.001) and short TTP (pooled HR = 2.456, 95% CI = 1.744-3.458, P < 0.001). A subgroup analysis revealed that the association between TMPRSS4 and the outcome endpoints (OS or TTP) was also significant within China region. We conclude that TMPRSS4 overexpression in solid tumors is associated with patients' poor prognosis. TMPRSS4 could be a valuable prognosis biomarker or a promising therapeutic target of solid tumor.
Feature matricization for document classification

Generally, the dimension of feature vector in text classification depends on the number of words in the specific domain. Many documents of considered categories make it numerous. Therefore, the dimension of feature vector is very high that makes it consumes a lot of time and memory to process. Moreover, it is a cause of the small sample size problem when the number of available training documents is far smaller than the dimension of these feature vectors. This paper proposes the alternative technique of dimensionality reduction for the feature vector in two-dimensional manner by previously transforming the feature vector to the feature matrix and then using Two-Dimensional Principal Component Analysis (2DPCA) for reducing the dimension of this feature matrix. Based on 2DPCA, the original weighted term matrix is not necessary to store in the memory anymore because the scatter matrix of 2DPCA can be computed incrementally. The small reduction in matrix form impacts to the plenty of dimensionality reduction in vector form. From the experimental results on well-known dataset, the proposed method not only significantly reduce the dimensionality but also achieve the higher accuracy rate than the original feature space.
An Ontology-Based Recommendation System Using Long-Term and Short-Term Preferences

Personalized information retrieval and recommendation systems have been proposed to deliver the right information to users with different interests. However, most of previous systems are using keyword frequencies as the main factor for personalization, and as a result, they could not analyze semantic relations between words. Also, previous methods often fail to provide the documents that are related semantically with the query words. To solve these problems, we propose a recommendation system which provides relevant documents to users by identifying semantic relations between an ontology that semantically represents the documents crawled by a Web robot and user behavior history. Recommendation is mainly based on content-based similarity, semantic similarity, and preference weights.
Producing Geo-historical Context from Implicit Sources: A Geovisual Analytics Approach

Abstract Geo-historical context, or GHC, is a contextual setting based on the interconnectedness of phenomena, events, and place across multiple spatial and temporal scales. GHC allows for situations to be understood and reasoned with, often with aid of visual representations such as maps. This paper introduces a conceptual model of GHC that theoretically motivates a Geovisual Analytics application called the Context Discovery Application (CDA), which is also presented. The CDA is designed to aid in the production of geo-historical context by using computational processes to identify and extract potentially relevant context information from heterogeneous, implicit situation information. This information can then be explored through visual interfaces to help users explain and understand the information. A hypothetical humanitarian context analysis case study is used to show how the CDA can be applied to real world problems.
Multiple moving objects tracking for automated visual surveillance

Moving objects tracking is of great significance for automated visual surveillance. Conventional tracking algorithms, such as Kalman filter or particle filter, have shown the effectiveness and robustness in many practical applications. However, the Bayesian filter is not designed for tacking multiple moving objects. The difficulty is the data association between the measurements and the tracks. Tracking can fail due to the confusion of similar measurements from adjacent moving objects. This paper proposes an approach for multiple moving objects tracking. We formulate the measurement assignment process as a problem of finding the matching with the maximum weight in a bipartite graph. Moving objects are detected by background subtraction. We test our approach using public datasets. The experimental results demonstrate that our approach is able to track multiple moving objects correctly.
The Shifting Discourse of the European Central Bank: Exploring Structural Space in Semantic Networks

Convenient access to vast and untapped collections of documents generated by organizations is a valuable resource for research. These documents (e.g., Press releases, reports, speech transcriptions, etc.) are a window into organizational strategies, communication patterns, and organizational behavior. However, the analysis of such large document corpora does not come without challenges. Two of these challenges are 1) the need for appropriate automated methods for text mining and analysis and 2) the redundant and predictable nature of the formalized discourse contained in these collections of texts. Our article proposes an approach that performs well in overcoming these particular challenges for the analysis of documents related to the recent financial crisis. Using semantic network analysis and a combination of structural measures, we provide an approach that proves valuable for a more comprehensive analysis of large and complex semantic networks of formal discourse, such as the one of the European Central Bank (ECB). We find that identifying structural roles in the semantic network using centrality measures jointly reveals important discursive shifts in the goals of the ECB which would not be discovered under traditional text analysis approaches.
An Overview of Human-Computer

This paper introduces the special issue of Knowledge-Based Systems on Human-Computer Collaboration (HCC). It derives a set of fundamental issues from a deenition of collaboration, introduces two major approaches to HCC, and surveys each approach, showing how it formulates and addresses the issues. It concludes by proposing some themes that should characterize a uniied approach to human-computer collaboration.
Price Competition between Pure Play vs. Bricks-and-Clicks E-Tailers: Analytical Model and Empirical Analysis

In this paper, we first develop a game theoretic model of price competition between a pure play e-tailer and a bricks-and-clicks e-tailer. We show that in general, the pure play e-tailer has a lower equilibrium price. We then develop a simultaneous equation model of e-tailer price and traffic and estimate this model using data collected from 905 e-tailers across eight product categories. The empirical results show that after controlling for the effects of other variables, prices at pure play e-tailers are generally lower. E-tailers with high traffic do not always command higher prices. E-tailers with high level of reliability, shopping convenience, and deep information, generally do not generate high web traffic and do not enjoy high prices. However, trust enhances e-tailer traffic and early online entry is associated with both high e-tailer traffic and high prices.
Engineering streptococcal protein G for increased alkaline stability.

Most protein-based affinity chromatography media are very sensitive towards alkaline treatment, which is a preferred method for regeneration and removal of contaminants from the purification devices in industrial applications. In a previous study, we concluded that a simple and straightforward strategy consisting of replacing asparagine residues could improve the stability towards alkaline conditions. In this study, we have shown the potential of this rationale by stabilizing an IgG-binding domain of streptococcal protein G, i.e. the C2 domain. In order to analyze the contribution of the different amino acids to the alkaline sensitivity of the domain we used a single point mutation strategy. Amino acids known to be susceptible towards high pH, asparagine and glutamine, were substituted for less-alkali-susceptible residues. In addition, aspartic acid residues were mutated to evaluate if the stability could be further increased. The stability of the different C2 variants was subsequently analyzed by exposing them to NaOH. The obtained results reveal that the most sensitive amino acid towards alkaline conditions in the structure of C2 is Asn36. The double mutant, C2(N7,36A), was found to be the most stable mutant constructed. In addition to the increased alkaline stability and also very important for potential use as an affinity ligand, this mutated variant also retains the secondary structure, as well as the affinity to the Fc fragment of IgG.
Syntheses and Functional Properties of Phthalocyanines

Metal phthalocyanine tetrasulfonic acids, metal phthalocyanine octacarboxylic acids, metal octakis(hexyloxymethyl)phthalocyanines, and metal anthraquinocyanines have been synthesized. Then, zinc bis(1,4-didecylbenzo)-bis(3,4-pyrido)porphyrazines, the cyclotetramerization products of a 1:1 mixture of 3,6-didecylphthalonitrile and 3,4-dicyanopyridine, were synthesized. Futher, subphthalocyanine and its derivatives, with substituents such as thiobutyl and thiophenyl moieties were synthesized. Electrochemical measurements were performed on the abovementioned phthalocyanine derivatives and analogues in order to examine their electron transfer abilities and electrochemical reaction mechanisms in an organic solvent. Moreover, 1,4,8,11,15,18,22,25-octakis(thio-phenylmethyl)phthalocyanes were synthesized. The Q-bands of the latter compounds appeared in the near-infrared region. Furthermore, non-colored transparent films in the visible region can be produced.
An Investigation Into the Implementation of the Instructional Consultation Team Model

The reauthorization of the Individuals With Disabilities Education Act (IDEA) in 2004 made Response to Intervention (RtI) an acceptable alternative for identifying students with specific learning disabilities (SLD). The purpose of this study was to examine one particular problem-solving approach, Instructional Consultation (IC) teams within an RtI framework, to determine the knowledge, skills, and beliefs of teachers and administrators about this model and its effect in identifying and supporting students with learning disabilities between two elementary schools in one Michigan school district. Interviews were done with a typical case sampling of interviewees from within both buildings. Interviewees were both participants and nonparticipants within the IC model. Each interview was completed at a time convenient for participants. A second, more specific interview was completed with key participants for deeper understanding of initial data analysis. Subfindings included: 1) although interviewees have a good understanding of the IC process, the understanding doesn’t preclude them from being resistant to its use; 2) a lack of significant understanding of the process and leadership styles have a major effect on the implementation and engagement of the IC team and staff; 3) factors including teacher professional development, building culture, and instructional practices intertwine in their effect on IC implementation; 4) the role of the IC facilitator and administrator have a large effect on the implementation and engagement of the IC team and staff; and 5) understanding of the IC process and how it is presented to building teams affects staff knowledge of understanding the process for identification of students with SLD. INSTRUCTIONAL CONSULTATION IMPLEMENTATION v Underlying all subfindings is the key finding of communication, which I will refer to as the “telephone game. ” In other words, IC communication—and how it travels throughout the school system—affects every subfinding. Identifying key people in the process, such as the facilitator and the administrator, are crucial to the implementation and engagement of a building’s IC team. One could use resulting information to create tools, such as rubrics, to monitor IC model understanding and implementation and engagement status of IC teams within a building and district. Further, the rubrics could guide problem solving and decision making for strong implementation of the IC team model. INSTRUCTIONAL CONSULTATION IMPLEMENTATION vi
An Extended Search for Circularly Polarized Infrared Radiation from the OMC-1 Region of Orion

We present new observations of circular polarization (CP) at 2.2 μm in the Orion (OMC-1) molecular cloud. Our results extend a previously published study of the region. We show that the degree of CP correlates spatially with the molecular cloud and appears to be generally very low in regions dominated by H II. We detect a feature with 3%-5% CP that extends approximately 60'' to the southwest of the BN/IRc2 region. Although the morphology of the observed CP is broadly consistent with a model in which radiation from a central source (probably IRc2) is scattered by aligned spheroidal grains, we conclude that dichroic extinction in the foreground molecular cloud also plays a major role in its production. Implications of our results for the hypothesis that CP radiation imposes chiral asymmetry upon prebiotic organic molecules in protoplanetary disks are discussed. Mechanisms invoked to explain the observed CP in the near infrared can also produce CP in the range of ultraviolet wavelengths capable of chiral selection by photolysis; however, the polarized flux is likely to be of limited spatial extent and to have lower percentage CP compared with the infrared.
Spectrophotometric analysis of the interiors of seventeenth century churches in Arbanassi

This paper presents the use of a new method of assessment and comparison of the appearance of colour in an art historical context, using some seventeenth century churches in Bulgaria as a case-study. The method also allows initial identification of the main colour agent of the pigments used. It contains the results of the identification of the colour red. This research provides a possible basis for further investigation into the use of colour in seventeenth century Bulgaria, in a way that overcomes the limitations of colour reproduction in print. In addition, a faithful and unambiguous record of the existing colours will make it possible to create the non-metameric subtractive mixtures that are needed for the restoration of the frescoes.
The Four-Phase Model of Interest Development

Building on and extending existing research, this article proposes a 4-phase model of interest development. The model describes 4 phases in the development and deepening of learner interest: triggered situational interest, maintained situational interest, emerging (less-developed) individual interest, and well-developed individual interest. Affective as well as cognitive factors are considered. Educational implications of the proposed model are identified.