Miracle-dz/UniFAR-FTUs huggingface dataset:
A Distinct Macrophage Population Mediates Metastatic Breast Cancer Cell Extravasation, Establishment and Growth

Background The stromal microenvironment and particularly the macrophage component of primary tumors influence their malignant potential. However, at the metastatic site the role of these cells and their mechanism of actions for establishment and growth of metastases remain largely unknown. Methodology/Principal Findings Using animal models of breast cancer metastasis, we show that a population of host macrophages displaying a distinct phenotype is recruited to extravasating pulmonary metastatic cells regardless of species of origin. Ablation of this macrophage population through three independent means (genetic and chemical) showed that these macrophages are required for efficient metastatic seeding and growth. Importantly, even after metastatic growth is established, ablation of this macrophage population inhibited subsequent growth. Furthermore, imaging of intact lungs revealed that macrophages are required for efficient tumor cell extravasation. Conclusion/Significance These data indicate a direct enhancement of metastatic growth by macrophages through their effects on tumor cell extravasation, survival and subsequent growth and identifies these cells as a new therapeutic target for treatment of metastatic disease.
An Anytime Boosting Scheme for Bounding Posterior Beliefs 1

This paper presents an any-time scheme for computing lower and upper bounds on the posterior marginals in Bayesian networks with discrete variables. Its power is in that it can use any available scheme that bounds the probability of evidence, enhance its performance in an anytime manner, and transform it effectively into bounds for posterior marginals. The scheme is novel in that using the cutset condition principle (Pearl, 1988), it converts a bound on joint probabilities into a bound on the posterior marginals that is tighter than earlier schemes, while at the same time facilitates anytime improved performance. At the heart of the scheme is a new data structure which facilitate the efficient computation of such a bound without enumerating all the cutset tuples. Using a variant of bound propagation algorithm (Leisink & Kappen, 2003) as the plugged-in scheme, we demonstrate empirically the value of our scheme, for bounding posterior marginals and probability of evidence.
IBM Research and Columbia University TRECVID-2011 Multimedia Event Detection (MED) System

The IBM Research/Columbia team investigated a novel range of low-level and high-level features and their combination for the TRECVID Multimedia Event Detection (MED) task. We submitted four runs exploring various methods of extraction, modeling and fusing of low-level features and hundreds of high-level semantic concepts. Our Run 1 developed event detection models utilizing Support Vector Machines (SVMs) trained from a large number of low-level features and was interesting in establishing the baseline performance for visual features from static video frames. Run 2 trained SVMs from classification scores generated by 780 visual, 113 action and 56 audio high-level semantic classifiers and explored various temporal aggregation techniques. Run 2 was interesting in assessing performance based on different kinds of high-level semantic information. Run 3 fused the lowand high-level feature information and was interesting in providing insight into the complementarity of this information for detecting events. Run 4 fused all of these methods and explored a novel Scene Alignment Model (SAM) algorithm that utilized temporal information discretized by scene changes in the video.
Modelling ultrafine structure in dark matter haloes

Various laboratory-based experiments are underway attempting to detect dark matter directly. The event rates and detailed signals expected in these experiments depend on the dark matter phase-space distribution on submilliparsec scales. These scales are many orders of magnitude smaller than those that can be resolved by conventional N-body simulations, so one cannot hope to use such tools to investigate the effect of mergers in the history of the Milky Way on the detailed phase-space structure probed by the current experiments. In this paper, we present an alternative approach to investigate the results of such mergers, by studying a simplified model for a merger of a subhalo with a larger parent halo. With an appropriate choice of parent halo potential, the evolution of material from the subhalo can be expressed analytically in action-angle variables, so it is possible to obtain its entire orbit history very rapidly without numerical integration. Furthermore by evolving backwards in time, we can obtain arbitrarily high spatial resolution for the current velocity distribution at a fixed point. Although this model cannot provide a detailed quantitative comparison with the Milky Way, its properties are sufficiently generic that it offers qualitative insight into the expected structure arising from a merger at a resolution that cannot be approached with full numerical simulations. Preliminary results indicate that the velocity-space distribution of dark matter particles remains characterized by discrete and well-defined peaks over an extended period of time, both for single and multimerging systems, in contrast to the simple smooth velocity distributions sometimes assumed in predicting laboratory experiment detection rates. In principle, this structure contains a wealth of information about the formation history of the Milky Way's dark halo.
Simulation of Layout-Dependent STI Stress and Its Impact on Circuit Performance

The impact of STI stress with layout dependency on circuit performance is investigated. A 3D stress simulator has been developed using finite element method, which considers both the layout design and process information (PDK). The mobility change due to stress is included in the transistor modeling for circuit simulation. The circuit performance can thus be analyzed with nonlocal stress. As a test case, a buffered SR flip-flop was simulated with and without STI stress considered. It can be seen that STI stress has non-negligible influence on the circuit performance.
Scalable OFDMA Physical Layer in IEEE 802.16 WirelessMAN

The concept of scalability was intr oduced to the IEEE 802.16 WirelessMAN Orthogonal Frequency Division Multiplexing Access (OFDMA) mode by the 802.16 Task Group e (TGe). A scalable physical layer enables standard-based solutions to deliver optimum performance in channel bandwidths ranging from 1.25 MHz to 20 MHz with fixed subcarrier spacing for both fixed and portable/mobile usage models, while keeping the product cost low. The architecture is based on a scalable subchannelization structure with variable Fast Fourier Transform (FFT) sizes according to the channel bandwidth. In addition to variable FFT sizes, the specification supports other features such as Advanced Modulation and Coding (AMC) subchannels, Hybrid Automatic Repeat Request (H-ARQ), high-efficiency uplink subchannel structures, Multiple-Input-Multiple- Output (MIMO) diversity, and coverage enhancing safety channels, as well as other OFDMA default features such as different subcarrier allocations and diversity schemes. The purpose of this paper is to provide a brief tutorial on the IEEE 802.16 WirelessMAN OFDMA with an emphasis on scalable OFDMA.
Text-independent speaker recognition based on the Hurst parameter and the multidimensional fractional Brownian motion model

In this paper, a text-independent automatic speaker recognition (ASkR) system is proposed-the SR/sub Hurst/-which employs a new speech feature and a new classifier. The statistical feature pH is a vector of Hurst (H) parameters obtained by applying a wavelet-based multidimensional estimator (M/spl I.bar/dim/spl I.bar/wavelets ) to the windowed short-time segments of speech. The proposed classifier for the speaker identification and verification tasks is based on the multidimensional fBm (fractional Brownian motion) model, denoted by M/spl I.bar/dim/spl I.bar/fBm. For a given sequence of input speech features, the speaker model is obtained from the sequence of vectors of H parameters, means, and variances of these features. The performance of the SR/sub Hurst/ was compared to those achieved with the Gaussian mixture models (GMMs), autoregressive vector (AR), and Bhattacharyya distance (dB) classifiers. The speech database-recorded from fixed and cellular phone channels-was uttered by 75 different speakers. The results have shown the superior performance of the M/spl I.bar/dim/spl I.bar/fBm classifier and that the pH feature aggregates new information on the speaker identity. In addition, the proposed classifier employs a much simpler modeling structure as compared to the GMM.
Children’s engagement in play at home: a parent’s role in supporting play opportunities during early childhood

ABSTRACT This study examined parents’ developmentally appropriate beliefs about young children’s play and parents’ views on their child’s play skills. This exploratory secondary data analysis was drawn from data on low-income African-American and Latino parents and their children (n = 109) participating in Head Start programmes in the USA. Compared with African-American parents, Latino parents were more likely to endorse play as valuable (Play Support) for promoting preschool children’s social skills and school readiness, yet were also more likely to see play as not as important as academic readiness activities (Academic Focus). Parental endorsement of Play Support beliefs positively related to children’s interactive play skills; Academic Focus beliefs negatively related to interactive play. These relations emerged for African American, but not Latino, children. Implications for understanding how culture may intersect with parents’ play beliefs, opportunities to promote children’s play competence, and alignment with play-based pedagogies are discussed.
Review of single-stage time-interval measurement modules implemented in FPGA devices

High resolution Time Interval Measurement Systems (TIMS) can be applied in experimental physics, ultrasonic flow meters, distance meters, or clock period meters. In this paper the problem of single-stage, high resolution TIMS design and implementation in programmable CMOS FPGA devices is discussed. Different architectures of TIMS are compared. Moreover, main parameters of TIMS, such as resolution, double pulse resolution, nonlinearity and sensitivity to temperature fluctuation are also discussed.
Adaptive face identification for small-scale social dynamic environment

This article focuses on the problem of modifying the standard face identification approach for use in small-scale social dynamic environments, by focusing on adaptability rather than robustness. A design of adaptive face identification system is presented, along with the employed methods of online learning. The problem of ensuing bias-variance dilemma of an adaptive system is described and solved. The system is shown to be able to aptly adapt to new information and changes the environment, the final classification rate on MUG database was near 99%.
Auditory Feedback of Human EEG for Direct Brain-Computer Communication

The Thought-Translation-Device (TTD) is a Brain-ComputerInterface (BCI) that enables completely paralyzed patients to communicate by the use of their brain signals only. Selfregulation of brain signals (e.g. the slow cortical potentials) is achieved by a feedback training. Visual impairment of these patients asks for an auditory feedback mode. The TTD can be entirely operated by combined listening and mental activity. It provides auditory feedback of brain signals which can operate a verbal spelling interface. The extension POSER allows for sonified orchestral real-time feedback of multiple EEG parameters for the training of self-regulation. The properties of the system are reported and the results of some studies and experiments with auditory feedback are presented.
A Scalable Limited Feedback Design for Network MIMO Using Per-Cell Codebook

In network MIMO systems, channel state information is required at the transmitter side to multiplex users in the spatial domain. Since perfect channel knowledge is difficult to obtain in practice, \emph{limited feedback} is a widely accepted solution. The {\em dynamic number of cooperating BSs} and {\em heterogeneous path loss effects} of network MIMO systems pose new challenges on limited feedback design. In this paper, we propose a scalable {\em limited feedback framework using per-cell codebooks}, along with a {\em low-complexity feedback indices selection algorithm}. We show that the proposed per-cell codebook limited feedback design can asymptotically achieve the same performance as the joint-cell codebook approach. We also derive an asymptotic \emph{per-user throughput loss} due to limited feedback with per-cell codebooks. Based on that, we show that when the number of per-user feedback-bits $B_{k}$ is $O\big( Nn_{T}n_{R}\log_{2}(\rho g_{k}^{sum} )\big)$, the system operates in the \emph{noise-limited} regime in which the per-user throughput is $O \left( n_{R} \log_{2} \big( \frac{n_{R}\rho g_{k}^{sum}}{Nn_{T}} \big) \right)$. On the other hand, when the number of per-user feedback-bits does not scale with the \emph{system SNR} $\rho$, the system operates in the \emph{interference-limited} regime where the per-user throughput is $O\left( \frac{n_{R}B_{k}}{(Nn_{T})^{2}} \right)$. Numerical results show that the proposed design is very flexible to accommodate dynamic number of cooperating BSs and achieves much better performance compared with other baselines (such as the Givens rotation approach).
Time continuity in cohesive finite element modeling

We introduce the notion of time continuity for the analysis of cohesive zone interface finite element models. We focus on ‘initially rigid’ models in which an interface is inactive until the traction across it reaches a critical level. We argue that methods in this class are time discontinuous, unless special provision is made for the opposite. Time discontinuity leads to pitfalls in numerical implementations: oscillatory behavior, non‐convergence in time and dependence on nonphysical regularization parameters. These problems arise at least partly from the attempt to extend uniaxial traction–displacement relationships to multiaxial loading. We also argue that any formulation of a time‐continuous functional traction–displacement cohesive model entails encoding the value of the traction components at incipient softening into the model. We exhibit an example of such a model. Most of our numerical experiments concern explicit dynamics. Copyright © 2003 John Wiley & Sons, Ltd.
University of Amsterdam at TREC 2014: Contextual Suggestion and Web Tracks

This paper presents the University of Amsterdam’s participation in TREC 2014. For the Contextual Suggestion Track, we experimented with the use of anchor text representations in the language modeling framework, and base our runs either on full ClueWeb12 or the subset of touristic aggregators (e.g., tripadvisor) provided by the organizers of the track. We also look at the eectiveness of priors (in particular, PageRank) and ways of formulating the query based on the context. Our main nding is that the anchor text representation is eective for retrieving candidate attractions, and performs better than a standard document text index. A linear combination of both anchor and document text leads to further improvement. For the Web Track, we continued our experiment with the fusion of anchor text relative to the text-based baseline run. Our main nding is, again, that the combination of anchor and document text leads to improvement, and we demonstrate how the fusion weight can be used as a handle to tune the amount of risk acceptable for the risk sensitive evaluation.
Conformal Field Theory of AdS Background with Ramond-Ramond Flux

We review a formalism of superstring quantization with manifest six-dimensional spacetime supersymmetry, and apply it to AdS3 × S3 backgrounds with Ramond-Ramond flux. The resulting description is a conformal field theory based on a sigma model whose target space is a certain supergroup SU'(2|2).
A generic virus detection agent on the Internet

The dissemination of software has never been so easy since the Internet became widely available. This ease of access to free software has also pushed the wide spread of viruses to a new plateau. We present VICEd, a system for generic virus detection over the Internet. VICEd is based on a virus detection methodology which is a combination of software emulation and knowledge base. It detects viruses using their behaviour instead of pattern matching. It is thus more effective against unknown or mutated viruses than scanners. This methodology is interesting in its own right. VICEd is a member of a group of system management agents currently under development at the National Taiwan University.
Fault Detection by Mining Association Rules from House-keeping Data

This paper proposes a novel anomaly detection method for spacecraft systems based on data-mining techniques. This method automatically constructs a system behavior model in the form of a set of rules by applying pattern clustering and association rule mining to the time-series data obtained in the learning phase, then detects anomalies by checking the subsequent on-line data with the acquired rules. A major advantage of this approach is that it requires little a priori knowledge on the system.
The Triterpenoid CDDO-Me Inhibits Bleomycin-Induced Lung Inflammation and Fibrosis

Pulmonary Fibrosis (PF) is a devastating progressive disease in which normal lung structure and function is compromised by scarring. Lung fibrosis can be caused by thoracic radiation, injury from chemotherapy and systemic diseases such as rheumatoid arthritis that involve inflammatory responses. CDDO-Me (Methyl 2-cyano-3,12-dioxooleana-1,9(11)dien-28-oate, Bardoxolone methyl) is a novel triterpenoid with anti-fibrotic and anti-inflammatory properties as shown by our in vitro studies. Based on this evidence, we hypothesized that CDDO-Me would reduce lung inflammation, fibrosis and lung function impairment in a bleomycin model of lung injury and fibrosis. To test this hypothesis, mice received bleomycin via oropharyngeal aspiration (OA) on day zero and CDDO-Me during the inflammatory phase from days -1 to 9 every other day. Bronchoalveolar lavage fluid (BALF) and lung tissue were harvested on day 7 to evaluate inflammation, while fibrosis and lung function were evaluated on day 21. On day 7, CDDO-Me reduced total BALF protein by 50%, alveolar macrophage infiltration by 40%, neutrophil infiltration by 90% (p≤0.01), inhibited production of the inflammatory cytokines KC and IL-6 by over 90% (p≤0.001), and excess production of the pro-fibrotic cytokine TGFβ by 50%. CDDO-Me also inhibited α-smooth muscle actin and fibronectin mRNA by 50% (p≤0.05). On day 21, CDDO-Me treatment reduced histological fibrosis, collagen deposition and αSMA production. Lung function was significantly improved at day 21 by treatment with CDDO-Me, as demonstrated by respiratory rate and dynamic compliance. These new findings reveal that CDDO-Me exhibits potent anti-fibrotic and anti-inflammatory properties in vivo. CDDO-Me is a potential new class of drugs to arrest inflammation and ameliorate fibrosis in patients who are predisposed to lung injury and fibrosis incited by cancer treatments (e.g. chemotherapy and radiation) and by systemic autoimmune diseases.
Analysis of Neurons Created from Wild-Type and Alzheimer's Mutation Knock-In Embryonic Stem Cells by a Highly Efficient Differentiation Protocol

It is impossible to obtain and amplify live neurons from Alzheimer's disease (AD) patients. To establish the neurons harboring AD abnormality, we constructed mouse embryonic stem (ES) cells, in which the AD-causative V642I mutation was introduced to the endogenous amyloid precursor protein (APP) gene, in combination with a protocol to efficiently differentiate ES cells into postmitotic neurons without using a cell sorter. By this protocol, ES cells differentiated into >90% of the central type of adult postmitotic neurons. Neurons derived from V642I–APP knock-in ES cells were indistinguishable from wild-type ES-derived neurons, as determined by the expression of various markers for neuronal differentiation. Notably, V642I–APP knock-in ES cell-derived neurons exhibited significantly increased secretion of Aβ42 without AD-related hyperphosphorylation of tau, indicating that the direct output of the AD-causative mutation is increased Aβ42 secretion. In this study, we analyze created neurons with wild-type and AD genotypes and propose a new strategy for generating neurons for any dominantly inherited neurodegenerative diseases. The strategy can be applied to create human neurons with AD or any other neurodegenerative disease by using human ES cells.
A Feature Set for Cytometry on Digitized Microscopic Images

Feature extraction is a crucial step in most cytometry studies. In this paper a systematic approach to feature extraction is presented. The feature sets that have been developed and used for quantitative cytology at the Laboratory for Biomedical Image Analysis of the GSF as well as at the Center for Image Analysis in Uppsala over the last 25 years are described and illustrated. The feature sets described are divided into morphometric, densitometric, textural and structural features. The latter group is used to describe the eu‐ and hetero‐chromatin in a way complementing the textural methods. The main goal of the paper is to bring attention to the need of a common and well defined description of features used in cyto‐ and histometrical studies. The application of the sets of features is shown in an overview of projects from different fields. Finally some rules of thumb for the design of studies in this field are proposed. Colour figures can be viewed on http://www.esacp. org/acp/2003/25‐1/rodenacker.htm.
Challenges of keyword-based location disclosure

A practical solution to location privacy should be incrementally deployable. We claim it should hence reconcile the economic value of location to aggregators, usually ignored by prior works, with a user's control over her information. Location information indeed is being collected and used by many mobile services to improve revenues, and this gives rise to a heated debate: Privacy advocates ask for stricter regulation on information collection, while companies argue that it would jeopardize the thriving economy of the mobile web. We describe a system that gives users control over their information and does not degrade the data given to aggregators. Recognizing that the first challenge is to express locations in a way that is meaningful for advertisers and users, we propose a keyword-based design. Keywords characterize locations, let the users inform the system about their sensitivity to disclosure, and build information directly usable by an advertiser's targeting campaign. Our work makes two main contributions: we design a market of location information based on keywords and we analyze its robustness to attacks using data from ad-networks, geo-located services, and cell networks.
CONVENTION THEORY: IS THERE A FRENCH SCHOOL OF ORGANIZATIONAL INSTITUTIONALISM?

This paper highlights overlap and differences between Convention Theory and New Organizational Institutionalism and thus states the strong case for profitable dialog. It shows how the former can facilitate new institutional approaches. First, convention theory rounds off the model of institutionalized action by turning the spotlight to the role of evaluation in the coordination effort. In parallel, the attention focused on the two components of the qualification process also sheds new light on the institutional dynamics issue at the heart of organizational institutionalism research since the mid-90s.