Miracle-dz/UniFAR-FTUs huggingface dataset:
Localization of the tight junction protein, ZO-1, is modulated by extracellular calcium and cell-cell contact in Madin-Darby canine kidney epithelial cells

Using the monoclonal antibody R26.4, we have previously identified a approximately 225-kD peripheral membrane protein, named ZO-1, that is uniquely associated with the tight junction (zonula occludens) in a variety of epithelia including the Madin-Darby canine kidney (MDCK) epithelial cell line (Stevenson, B. R., J. D. Siliciano, M. S. Mooseker, and D. A. Goodenough. 1986. J. Cell Biol. 103:755-766). In this study we have analyzed the effects of cell-cell contact and extracellular calcium on the localization and the solubility of ZO-1. In confluent monolayers under normal calcium conditions, ZO-1 immunoreactivity is found exclusively at the plasma membrane in the region of the junctional complex. If MDCK cells are maintained in spinner culture under low calcium conditions, ZO-1 is diffusely organized within the cytoplasm. After the plating of suspension cells at high cell density in medium with normal calcium concentrations, ZO-1 becomes localized to the plasma membrane at sites of cell-cell contact within 5 h in a process that is independent of de novo protein synthesis. However, if suspension cells are plated at high density in low calcium medium or if suspension cells are plated at low cell density in normal calcium growth medium, ZO-1 remains diffusely organized. ZO-1 localization also becomes diffuse in monolayers that have been established in normal calcium medium and then subsequently switched into low calcium medium. These results suggest that both extracellular calcium and cell-cell contact are necessary for normal localization of ZO-1 to the plasma membrane. An analysis of the solubility properties of ZO-1 from suspension cells and monolayers revealed that high salt, nonionic detergent, and a buffer containing chelators were somewhat more effective at solubilizing ZO-1 from suspension cells than from monolayers.
A Supply Approach to Valuation

A new methodology for equity valuation arises from the perspective of managers' supply of capital assets. Under q-theory, managers optimally adjust the supply of assets to changes in their market value. The first-order condition of investment then provides a valuation equation that infers asset prices from managers' costs of supplying the assets. This equation fits well the Tobin's q levels across many testing assets, including portfolios formed on q. With current investment-to-capital as the only input, the supply approach does not require cash flow forecasts or discount rate estimates, both of which are notoriously difficult to obtain in practice. The Author 2013. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com. , Oxford University Press.
MCG +00-32-16: An Irregular Galaxy Close to the Lowest Redshift Absorber on the 3C 273 Line of Sight

MCG +00-32-16 is the galaxy closest in position-velocity space to the lowest redshift Lyα absorber along the line of sight to the quasar 3C 273. Its projected separation is 204(d/19 Mpc) kpc, where d is the distance from the Milky Way to the galaxy, and the redshift difference is only 94 km s-1; H I 1225+01 is slightly closer in projected separation to the absorber, but has a greater redshift difference. We present H I synthesis array mapping and CCD photometry in B and R for MCG +00-32-16. The H I disk is rotating in such a way that the side of the galaxy closer to the sight line to the quasar has the larger velocity difference from the absorber. The absorber may be a "failed dwarf" member of a poor galaxy group of which MCG +00-32-16 and H I 1225+01 are the only members to have formed stars.
An Efficient Approach for Clustering Web Access Patterns from Web Logs

The interests of web users can be revealed by their visited web pages and time duration on these web pages during their surfing. Time duration on a web page is characterized as a fuzzy linguistic variable because linguistic variable makes users easily understand the expression of time duration and can disregard subtle difference between two time durations. Each web access pattern from web logs is transformed as corresponding fuzzy web access pattern, which is a fuzzy vector composed of fuzzy linguistic variables or 0. Each element in fuzzy web access patterns represents visited web page and time duration on this web page. This paper proposed a rough k-means clustering algorithm based on properties of rough variable to group the gained fuzzy web access patterns. Finally, an example and experiment is provided to illustrate the clustering process. Using this approach, users can effectively mine web logs records to discover interesting user access patterns.
Finding and Excluding b-ary Machin-Type Individual Digit Formulae

Abstract Constants with formulae of the form treated by D. Bailey, P. Borwein, and S. Plouffe ( $b$ formulae to a given base $b$ ) have interesting computational properties, such as allowing single digits in their base $b$ expansion to be independently computed, and there are hints that they should be normal numbers, i.e., that their base $b$ digits are randomly distributed. We study a formally limited subset of BBP formulae, which we call Machin-type BBP formulae, for which it is relatively easy to determine whether or not a given constant $K$ has a Machin-type BBP formula. In particular, given $b\,\in \,\mathbb{N},\,b\,>\,2,\,b$ not a proper power, a $b$ -ary Machin-type BBP arctangent formula for $K$ is a formula of the form $k\,=\,{{\Sigma }_{m}}\,{{a}_{m}}\,\arctan \,(-{{b}^{-m}}),\,{{a}_{m}}\,\in \,\mathbb{Q}$ , while when $b\,=\,2$ , we also allow terms of the form ${{a}_{m}}\,\arctan \,(1/1\,-\,{{2}^{m}}))$ . Of particular interest, we show that $\pi$ has no Machin-type BBP arctangent formula when $b\,\ne \,2$ . To the best of our knowledge, when there is no Machin-type BBP formula for a constant then no BBP formula of any form is known for that constant.
Efficient advanced scientific computing with Rheolef

Rheolef is a computer environment that serves as a convenient laboratory for computations involving finite element methods. It provides a set of unix commands and C++ algorithms and containers. In particular, this environment allows the user to express a partial derivative problem in terms of finite element spaces, discrete fields, bilinear forms, geometries and meshes. Rheolef is the only one environment to our knowledge that bases on such powerful variational concepts as basic data structures. This set of data structure is completed by the most up-to-date algorithms: preconditioned sparse solvers for incompressible elasticity, Stokes and Navier-Stokes flows, characteristic method for convection dominated heat problems, \ldots All these brick can be combined, as a Lego game, in order to solve more complex nonlinear problems: the library provides also nonlinear generic solvers such as damped Newton methods.
DAVA: Distributing Vaccines over Networks under Prior Information

Given a graph, like a social/computer network or the blogosphere, in which an infection (or meme or virus) has been spreading for some time, how to select the k best nodes for immunization/quarantining immediately? Most previous works for controlling propagation (say via immunization) have concentrated on developing strategies for vaccination pre-emptively before the start of the epidemic. While very useful to provide insights in to which baseline policies can best control an infection, they may not be ideal to make real-time decisions as the infection is progressing. In this paper, we study how to immunize healthy nodes, in presence of already infected nodes. Efficient algorithms for such a problem can help public-health experts make more informed choices. First we formulate the Data-Aware Vaccination problem, and prove it is NP-hard and also that it is hard to approximate. Secondly, we propose two effective polynomial-time heuristics DAVA and DAVA-fast. Finally, we also demonstrate the scalability and effectiveness of our algorithms through extensive experiments on multiple real networks including epidemiology datasets, which show substantial gains of up to 10 times more healthy nodes at the end.
Deficiency in Serine Protease Inhibitor Neuroserpin Exacerbates Ischemic Brain Injury by Increased Postischemic Inflammation

The only approved pharmacological treatment for ischemic stroke is intravenous administration of plasminogen activator (tPA) to re-canalize the occluded cerebral vessel. Not only reperfusion but also tPA itself can induce an inflammatory response. Microglia are the innate immune cells of the central nervous system and the first immune cells to become activated in stroke. Neuroserpin, an endogenous inhibitor of tPA, is up-regulated following cerebral ischemia. To examine neuroserpin-dependent mechanisms of neuroprotection in stroke, we studied neuroserpin deficient (Ns−/−) mice in an animal model of temporal focal ischemic stroke. Infarct size and neurological outcome were worse in neuroserpin deficient mice even though the fibrinolytic activity in the ischemic brain was increased. The increased infarct size was paralleled by a selective increase in proinflammatory microglia activation in Ns−/− mice. Our results show excessive microglial activation in Ns−/− mice mediated by an increased activity of tPA. This activation results in a worse outcome further underscoring the potential detrimental proinflammatory effects of tPA.
Using helpful sets to improve graph bisections

We describe a new, linear time heuristic for the improvement of graph bisections. The method is a variant of local search with sophisticated neighborhood relations. It is based on graph-theoretic observations that were used to (cid:12)nd upper bounds for the bisection width of regular graphs. E(cid:14)ciently implemented, the new method can serve as an alternative to the commonly used local heuristics, not only in terms of the quality of attained solutions, but also in terms of space and time requirements. We compare our heuristic with a number of well known bisection algorithms. Extensive measurements show that the new method is a real improvementfor graphs of certain types.
Predicting evacuation time using learnable building block method

Evacuation simulator is an important tool which can create solution for emergency circumstance. Evacuation simulation becomes more realistic but it has to tradeoff between memory consumption and processing time. This paper proposes a method to predict evacuation time by converting floor layout to building block structure and predicts evacuation time of each building block. Then we can use the predicted result to calculate total evacuation time of scenario without re-simulate whole scenario. The proposed method can reduce the processing time and memory usage which make user get total evacuation time faster but still maintain correctness of result.
Influence of pilot symbol configuration on data-aided phase noise estimation from a DCT basis expansion

This contribution deals with phase noise estimation from pilot symbols. The phase noise process is approximated by an expansion of DCT basis functions containing only a few terms. We propose an algorithm that estimates the DCT coefficients without requiring detailed knowledge about the phase noise statistics. We demonstrate that the resulting (linearized) mean-square estimation error consists of two contributions: a contribution from the additive noise, that equals the Cramer-Rao lower bound, and a noise-independent contribution that results from the phase noise modeling error. Performance can be optimized by a proper selection of the pilot symbol placement scheme, the number of pilot symbols and the number of estimated DCT coefficients. Choosing the pilot symbol positions such that the DCT basis functions are orthogonal and choosing the pilot symbol ratio such that the phase estimation is accurate while minimizing the overhead energy loss leads to considerable performance improvement as compared to other pilot symbol configurations.
On Image Block Loss Restoration Using the Sparsity Pattern as Side Information

In this paper, we propose a method for image block loss restoration based on the notion of sparse representation. We use the sparsity pattern as side information to efficiently restore block losses by iteratively imposing the constraints of spatial and transform domains on the corrupted image. Two novel features, including a pre-interpolation and a criterion for stopping the iterations, are proposed to improve the performance. Also, to deal with practical applications, we develop a technique to transmit the side information along with the image. In this technique, we first compress the side information and then embed its LDPC coded version in the least significant bits of the image pixels. This technique ensures the error-free transmission of the side information, while causing only a small perturbation on the transmitted image. Mathematical analysis and extensive simulations are performed to validate the method and investigate the efficiency of the proposed techniques. The results verify that the proposed method outperforms its counterparts for image block loss restoration.
A mobility-aware medium access control protocol for wireless sensor networks

This paper introduces a light-weight mobility-aware medium access control protocol for wireless sensor networks (MA-MAC). In many respects, the protocol is similar to preamble based, low power listening MAC protocols. It defines a duty-cycle to let nodes sleep when they have no packets to transmit. During active communication, the protocol estimates mobility by evaluating the received signal strength of incoming ACK packets and initiates seamless handover by embedding neighbour discovery requests in data packets. Neighbour nodes randomly wake up from their sleep to participate in a handover process. Moreover, at the beginning of each active cycle, they first listen for handover request before they transmit. A prototype was developed and tested with TinyOS and Micaz platforms. The paper reports the experiment results.
A Small Model of the Australian Macroeconomy

This paper presents a small model of the Australian macroeconomy. The model is empirically based, aggregate in nature and consists of five estimated equations – for non-farm output, the real exchange rate, import prices, unit labour costs and consumer prices. The stylised facts underlying each equation are discussed and estimation results are presented. The model’s primary use is to examine macroeconomic developments over the short to medium term, although it also has a well-defined steady state in the longer run with appropriate theoretical properties. Dynamic responses of the model to monetary policy changes and selected shocks are illustrated in the paper.
How Good Is Genetic Programming at Predicting Changes and Defects?

One of the main problems practitioners have to deal with is the identification of change and defect proneness of source code entities (e.g., Classes). During the last years a lot of techniques have been employed for predicting change and defect proneness of classes. In this paper we study the capabilities of Genetic Programming for performing the addressed problem by measuring the precision and recall of the obtained predictions.
Derivational suffixes as cues to stress position in reading Greek

Background In languages with lexical stress, reading aloud must include stress assignment. Stress information sources across languages include word-final letter sequences. Here, we examine whether such sequences account for stress assignment in Greek and whether this is attributable to absolute rules involving accenting morphemes or to probabilistic lexical information. Methods Pseudowords were constructed to not resemble particular words and were suffixed with derivational morphemes associated with specific stress patterns, to be read aloud, presented either without a stress diacritic or with a diacritic congruent or incongruent with the suffix. Morphemes differed in whether or not there were stress competitors ending in the same letter sequences. Results Stress was assigned consistent with the suffix in the absence of the diacritic, more so when there were no stress competitors in the lexicon. Conclusions Results suggest a lexically based probabilistic mechanism taking into account pattern distributions rather than absolute rules based on the morphological accenting.
The role of subsyllabic units in the visual word recognition of Korean monosyllabic words: A masked priming study

Native speakers of Korean have been shown to prefer a left-branching body-coda subsyllabic structure over a right branching onset-rime structure when processing monosyllabic words in written language. However, counterarguments have been made that the highly transparent nature of Korean hangul provides no preference for larger subsyllabic units beyond the phoneme. A masked priming lexical decision experiment was conducted to determine whether this subsyllabic preference occurs for orthographic processing in Korean. C 1VC2 structured monosyllabic target words preceded by one of four different types of primes at a short prime duration (50 ms): body (C1VC), rime (CVC2), identical (C1VC2), and non-match (C2VC1). Both identical and body prime conditions elicited a significant priming effect as consistent with the leftbranching model in Korean. The present study provides converging evidence for a left-branching model of subsyllabic structure in visual word recognition in Korean using a masked priming paradigm.
On Practical Verification of Processes

The integration of a formal process theory with a practically usable notation is not straightforward, but it is necessary for practical verification of process specifications. Given such an intermediate language, a verification process that gives useful feedback is not trivial either: Model checkers are not powerful enough to deal with object models, and theorem provers provide insu#cient feedback and are not certain to find a proof.
XRCE's Participation in ImageCLEF 2009

This year, our participation to ImageCLEF 2008 (Photo Retrieval sub-task) was motivated by trying to address three dierent problems: visual concept detection and its exploitation in a retrieval context, multimedia fusion methods for improved retrieval performance and diversity-based re-ranking methods. From a purely visual perspective, the representation based on Fisher vectors derived from a generative mixture model appeared to be ecient for both visual concept detection and content-based image retrieval. From a multimedia perspective, we used an intermediate fusion approach, based on cross-media relevance feedback that can be seen as a multigraph-based query regularization method with alternating steps. The combination allowed to improve both mono-media systems by more than 50% (relative). Finally, as one of main goals of the organizers was to promote both relevance and diversity in the retrieval outputs, we designed and assessed several re-ranking strategies that turned out to preserve standard retrieval performance (such at precision at 20 or mean average precision) while significantly decreasing the redundancy in the top documents.
Sourcing the Crowd for a Few Good Ones: Event Type Detection

This paper reports a crowdsourcing experiment on the identification and classification of event types in Italian. The data collected show that the task is not trivial (360 trusted judgments collected vs. 475 untrsuted ones) but it has been shown to be linguistically felicitous. The overall accuracy of the annotation is 61.6%. A reliability threshold assigned to the workers allows us to indentify the sub-population who has the awareness to perform this complex task and the accuracy of this sub-population is raised to 93%. Our hypothesis is that although the initial crowdsourced data is necessarily noisy, it can yield high quality results if the sub-population of ‘good’ workers can be identified. In other words, crowdsourcing offers a solution to difficult annotation tasks as long as there is an effective way to identify the reliable workers. TITLE AND ABSTRACT IN ANOTHER LANGUAGE, L2 (OPTIONAL, AND ON SAME PAGE) Identificare Annotatori Affidabili: Riconoscimento di Tipi di Evento Questo articolo descrive un esperimento di crowdsourcing per il riconoscimento e la classificazione dei tipi di evento in Italiano. I dati raccolti mostrano che il compito non è banale (360 giudizi affidabili vs. 475 giudizi non affidabili), ma dimostra di essere linguisticamente “felice”. L’accuratezza globale della annotazione è del 61,6%. Una soglia di affidabilità assegnata ai lavoratori ci permette di identificare la sotto-popolazione che ha la consapevolezza di svolgere questo compito complesso la cui accuratezza arriva fino al 93%. La nostra ipotesi è che, sebbene i dati iniziali ottenuti tramite tecniche di crowdsourcing siano necessariamente rumorosi, dei risultati di buona qualità possono essere ottenuti se la sotto-popolazione di "buoni" lavoratori è identificabile. In altre parole, il crowdsourcing offre una soluzione per compiti di annotazione difficili finché vi è un modo efficace per identificare i lavoratori affidabili.
Reconciling Dynamic System Sizing and Content Locality through Hierarchical Workload Forecasting

The cloud has recently surged as a promising paradigm for hosting scalable Web systems serving a large number of users with large workload variations. It makes possible to dynamically add and remove resources to horizontally scalable architectures in order to save costs, while maintaining the quality of service. However, in order to achieve these goals the resource management of a platform must include policies and mechanisms for dynamically resizing the system, redistributing content and redirecting user requests. In this work, we address the problem of reconciling dynamic system sizing and content locality. There are three main contributions of our study. First, we address the problem of determining the system size by employing a hierarchical prediction framework that proactively provisions resources based on statistical models of the incoming workload. Second, we show how to employ the hierarchical prediction framework for designing a dispatching mechanism which can be used with any request distribution policy. Third, we propose two novel prediction-based locality-aware request distribution policies: Oblivious Locality-Aware Request Distribution (OLARD) and Affinity-Based Locality-Aware Request Distribution (ABLARD). We demonstrate the advantages of using our hierarchical prediction framework and how our approach achieves a high content locality, while adapting to unexpected workload changes.
CDS wide slit time-series of EUV coronal bright points

Wide slit (90" x 240" ) movies of four Extreme Ultraviolet coronal bright points (BPs) obtained with the Coronal Diagnostic Spectrometer (CDS) on board the Solar and Heliospheric Observatory (SoHO) have been inspected. The wavelet analysis of the He I 584.34 A, O V 629.73 A and Mg VII/IX 368 A time-series confirms the oscillating nature of the BPs, with periods ranging between 600 and 1100 s. In one case we detect periods as short as 236 s. We suggest that these oscillations are the same as those seen in the chromospheric network and that a fraction of the network bright points are most likely the cool footpoints of the loops comprising coronal bright points. These oscillations are interpreted in terms of global acoustic modes of the closed magnetic structures associated with BPs.