Miracle-dz/UniFAR-FTUs huggingface dataset:
Tag Spotting at the Interference Range

Many of the challenges encountered in the design of wireless networks with multiple transmission and reception points stem from the quirks of wireless signal propagation. Using currently prevailing transmission techniques, wireless signals cannot be focused exclusively towards their intended recipient, making wireless an inherently shared medium. Wireless transmissions are local in their coverage, and, in general, no sender or receiver will have access to complete channel state information. Because of these characteristics, a wireless network is commonly modeled as a set of links among which interference may occur depending on the particular choice of senders transmitting at the same time. The effects of wireless interference are far reaching, affecting all network layers, from physical layer and medium access to flow control and user satisfaction. They extend beyond the space of a single host or a single link, as flows that do not share any hosts or links in their paths might in fact find themselves competing for resources. Its direct consequence is unfairness leading to flow starvation and underutilization of available resources. A study of the exact mechanisms through which interference leads to unfairness reveals problems at multiple network layers. The most general statements of these problems frequently preclude finding a decentralized and optimal solution. However, interference is a local disruption, and therefore leaves hope that a local, if imperfect, solution may be found. Distributed algorithms often make use of local exchanges of information. This creates a need for a communication backplane capable of connecting each host to the set of hosts affected by its transmissions. This requirement is more cumbersome than it might seem at first sight, for successful data transmission at common data rates requires rather large signal to noise ratios. The capacity of links is however affected even by interferers reaching them at far lower signal levels. Connecting the recipients of interference with transmitters requires thus a
Quinolone Resistance Mechanisms among Extended-Spectrum Beta-Lactamase (ESBL) Producing Escherichia coli Isolated from Rivers and Lakes in Switzerland

Sixty extended-spectrum β-lactamase (ESBL)-producing Escherichia coli isolated from rivers and lakes in Switzerland were screened for individual strains additionally exhibiting a reduced quinolone susceptibility phenotype. Totally, 42 such isolates were found and further characterized for their molecular (fluoro)quinolone resistance mechanisms. PCR and sequence analysis were performed to identify chromosomal mutations in the quinolone resistance-determining regions (QRDR) of gyrA, gyrB, parC and parE and to describe the occurrence of the following plasmid-mediated quinolone resistance genes: qepA, aac-6′-Ib-cr, qnrA, qnrB, qnrC, qnrD and qnrS. The contribution of efflux pumps to the resistance phenotype of selected strains was further determined by the broth microdilution method in the presence and absence of the efflux pump inhibitor phe-arg-β-naphthylamide (PAβN). Almost all strains, except two isolates, showed at least one mutation in the QRDR of gyrA. Ten strains showed only one mutation in gyrA, whereas thirty isolates exhibited up to four mutations in the QRDR of gyrA, parC and/or parE. No mutations were detected in gyrB. Most frequently the amino-acid substitution Ser83→Leu was detected in GyrA followed by Asp87→Asn in GyrA, Ser80→Ile in ParC, Glu84→Val in ParC and Ser458→Ala in ParE. Plasmid-mediated quinolone resistance mechanisms were found in twenty isolates bearing QnrS1 (4/20), AAC-6′-Ib-cr (15/20) and QepA (1/20) determinants, respectively. No qnrA, qnrB, qnrC and qnrD were found. In the presence of PAβN, the MICs of nalidixic acid were decreased 4- to 32-fold. (Fluoro) quinolone resistance is due to various mechanisms frequently associated with ESBL-production in E. coli from surface waters in Switzerland.
Cultural Capital: The Promises and Pitfalls in Education Research.

Executive Summary. Foreword. Acknowledgments. Foundations of Educational Inequality: Cultural Capital and Social Reproduction. Pierre Bourdieu's Theory of Social Reproduction. Cultural Capital and Education. Promises and Pitfalls of Cultural Capital in Educational Research. Uses and Abuses of Cultural Capital in Educational Research. Methodological Approach and Analysis. Definitions of Cultural Capital in Educational Research. Cultural Capital in Educational Research. Conclusion. "Strikes and Gutters": Examining Applications and Interpretations of Cultural Capital. The Merits of Cultural Capital in Educational Research. Substantive Limitations of Cultural Capital. Methodological Limitations of Cultural Capital Applications. Conclusion. Revolutionary Possibilities? The Future of Cultural Capital in Educational Research. Theoretical Considerations. Methodological Considerations. Educational Practice Applications of Cultural Capital Research. Conclusion. Notes. References. Name Index. Subject Index. About the Author.
Documentum ECI self-repairing wrappers: performance analysis

Documentum Enterprise Content Integration (ECI) services is a content integration middleware that provides one-query access to the Intranet and Internet content resources. The ECI Adapter technology offers an interface to any application for data and metadata extraction from unstructured Web pages. It offers a unique frame-work of wrapper production, automatic recovery and maintenance, developed at Xerox Research Centre Europe and based on state-of-art algorithms from machine learning and grammatical inference. In this presentation we analyze the performance of ECI adapters deployed in current commercial installations. We benefit from accessing reports on daily tests for all ECI commercially deployed adapters collected from June 2003 to September 2005. Using the daily reports, we analyze different aspects of the wrapper technology.
MONOLOGUE: A Tool for Negotiating Exchanges of Private Information in E-Commerce

The MONOLOGUE system (Multi-Object Negotiator for On-Line Offers Guided by Utility Elicitation) for privacy negotiation is described. It integrates a number of innovative components. Negotiations are alternating offers, where each offer may have multiple attributes which can be scalar-, discreteor set-valued, and so are general enough to allow P3P statements to be negotiated. It relies on the PrivacyPact protocol, which ensures that a mutually acceptable deal, if present, will be found. The utility of private information is elicited from the user by posing questions, bearing in mind the bother cost of asking. Several negotiation strategies are available. MONOLOGUE analyses the opponent’s responses to classify the opponent; better knowledge of the opponent can help to find mutually acceptable agreements. Experiments with simple strategies show that negotiations can converge to an agreement quite quickly.
Gender Difference in Event Related Potentials to Masked Emotional Stimuli in the Oddball Task

Objective We investigated gender differences in event-related potential (ERP) responses to subliminally presented threat-related stimuli. Methods Twenty-four participants were presented with threat-related and neutral pictures for a very brief period of time (17 ms). To explore gender differences in ERP responses to subliminally presented stimuli, we examined six ERP components [P1, N170, N250, P300, Early Posterior Negativity (EPN) and Late Positive Potential (LPP)]. Results The result revealed that only female participants showed significant increases in the N170 and the EPN in response to subliminally presented threat-related stimuli compared to neutral stimuli. Conclusion Our results suggest that female participants exhibit greater cortical processing of subliminally presented threat-related stimuli than male participants.
Unsupervised Sentiment Analysis with Signed Social Networks

Huge volumes of opinion-rich data is user-generated in social media at an unprecedented rate, easing the analysis of individual and public sentiments. Sentiment analysis has shown to be useful in probing and understanding emotions, expressions and attitudes in the text. However, the distinct characteristics of social media data present challenges to traditional sentiment analysis. First, social media data is often noisy, incomplete and fast-evolved which necessitates the design of a sophisticated learning model. Second, sentiment labels are hard to collect which further exacerbates the problem by not being able to discriminate sentiment polarities. Meanwhile, opportunities are also unequivocally presented. Social media contains rich sources of sentiment signals in textual terms and user interactions, which could be helpful in sentiment analysis. While there are some attempts to leverage implicit sentiment signals in positive user interactions, little attention is paid on signed social networks with both positive and negative links. The availability of signed social networks motivates us to investigate if negative links also contain useful sentiment signals. In this paper, we study a novel problem of unsupervised sentiment analysis with signed social networks. In particular, we incorporate explicit sentiment signals in textual terms and implicit sentiment signals from signed social networks into a coherent model SignedSenti for unsupervised sentiment analysis. Empirical experiments on two real-world datasets corroborate its effectiveness.
Endomyocardial nitric oxide synthase and left ventricular preload reserve in dilated cardiomyopathy.

BACKGROUND Patients with heart failure have modified myocardial expression of nitric oxide synthase (NOS), as is evident from induction of calcium-insensitive NOS isoforms. The functional significance of this modified NOS gene expression for left ventricular (LV) contractile performance was investigated in patients with dilated nonischemic cardiomyopathy. METHODS AND RESULTS In patients with dilated, nonischemic cardiomyopathy, invasive measures of LV contractile performance were derived from LV microtip pressure recordings and angiograms and correlated with intensity of gene expression of inducible (NOS2) and constitutive (NOS3) NOS isoforms in simultaneously procured LV endomyocardial biopsies (n=20). LV endomyocardial expression of NOS2 was linearly correlated with LV stroke volume (P=0.001; r=0.66), LV ejection fraction (P=0.007; r=0.58), and LV stroke work (P=0.003; r=0.62). In patients with elevated LV end-diastolic pressure (>16 mm Hg), a closer correlation was observed between endomyocardial expression of NOS2 and LV stroke volume (P=0.001; r=0.74), LV ejection fraction (P=0.0007; r=0.77), and LV stroke work (r=0.82; P=0.0002). LV endomyocardial expression of NOS3 was linearly correlated with LV stroke volume (P=0.01; r=0.53) and LV stroke work (P=0.01; r=0.52). To establish the role of nitric oxide (NO) as a mediator of the observed correlations, substance P (which causes endothelial release of NO) was infused intracoronarily (n=12). In patients with elevated LV end-diastolic pressure, an intracoronary infusion of substance P increased LV stroke volume from 72+/-13 to 91+/-16 mL (P=0.06) and LV stroke work from 67+/-11 to 90+/-15 g. m (P=0.03) and shifted the LV end-diastolic pressure-volume relation to the right. CONCLUSIONS In patients with dilated cardiomyopathy, an increase in endomyocardial NOS2 or NOS3 gene expression augments LV stroke volume and LV stroke work because of a NO-mediated rightward shift of the diastolic LV pressure-volume relation and a concomitant increase in LV preload reserve.
Treating hepatitis C: current standard of care and emerging direct‐acting antiviral agents

Summary. During the late 1990s and early 2000s, major advances were made in the treatment of patients with chronic hepatitis C virus (HCV) infection. Interferon, combination interferon plus ribavirin (RBV) and pegylated interferon plus RBV increased sustained virologic response (SVR) rates from ∼5% to ∼40–80%, depending on the genotype of HCV infection. Advances in molecular biology have allowed investigators to begin to understand the mechanisms of HCV infection and replication. Advances in understanding of viral kinetics have provided tools to identify patients who are most likely to attain SVR. With the advances in the science of HCV infection, the first part of the 21st century has seen the development and early introduction of a number of direct‐acting antiviral (DAA) drugs. These novel medications interfere with critical steps in HCV replication and have the potential to significantly increase SVR rates. This article will review the key elements of HCV replication and evaluate the various classes of new and investigational DAA that have the potential to create a revolution in the management of patients with chronic hepatitis C.
Information and Market Power

We analyze demand function competition with a finite number of agents and private information. We show that the nature of the private information determines the market power of the agents and thus price and volume of equilibrium trade.We establish our results by providing a characterization of the set of all joint distributions over demands and payoff states that can arise in equilibrium under any information structure. In demand function competition, the agents condition their demand on the endogenous information contained in the price.We compare the set of feasible outcomes under demand function to the feasible outcomes under Cournot competition. We find that the first and second moments of the equilibrium distribution respond very differently to the private information of the agents under these two market structures. The first moment of the equilibrium demand, the average demand, is more sensitive to the nature of the private information in demand function competition, reflecting the strategic impact of private information. By contrast, the second moments are less sensitive to the private information, reflecting the common conditioning on the price among the agents.
Cosmic-Ray Production of 6Li by Structure Formation Shocks in the Early Milky Way: A Fossil Record of Dissipative Processes during Galaxy Formation

While the abundances of Be and B observed in metal-poor halo stars are well explained as resulting from spallation of CNO-enriched cosmic rays (CRs) accelerated by supernova shocks, accounting for the observed 6Li in such stars with supernova CRs is more problematic. Here we propose that gravitational shocks induced by infalling and merging subgalactic clumps during hierarchical structure formation of the Galaxy should dissipate enough energy at early epochs so that the CRs accelerated by such shocks can provide a natural explanation of the observed 6Li. In clear contrast to supernovae, structure formation shocks do not eject freshly synthesized CNO nor Fe, so that α-α fusion, which is the only effective production channel at low metallicity, is capable of generating sufficient 6Li with no accompanying Be or B and no direct correspondence with Fe. Correlations between the 6Li abundance and the kinematic properties of the halo stars may also be expected in this scenario. Further, more extensive observations of 6Li in metal-poor halo stars, e.g., by the Subaru High Dispersion Spectrograph or the Very Large Telescope UV-Visual Echelle Spectrograph, may offer us an invaluable fossil record of dissipative dynamical processes that occurred during the formation of our Galaxy.
New insights into 10nm FinFET BTI and its variation considering the local layout effects

In this paper, BTI variation of 10nm FinFET is experimentally studied taking into account of the local layout effects. Although Fin shape is further optimized in 10nm compared with 14nm, the BTI and its variation show no obvious differences from the previous node. And this result is further confirmed by SRAM level reliability characterizations. In addition, the impacts of local layout effects on reliability are also investigated. Through Si data, BTI and its variation are not very sensitive to the layout effects which show within about 10% of the differences and the adopted structure for qualification can cover with all the different structures. Moreover, the results are also helpful for the accurate reliability modeling and circuit simulation.
On Fast Computation of Gradients for CANDECOMP/PARAFAC Algorithms

Product between mode-$n$ unfolding $\bY_{(n)}$ of an $N$-D tensor $\tY$ and Khatri-Rao products of $(N-1)$ factor matrices $\bA^{(m)}$, $m = 1,. , n-1, n+1, . , N$ exists in algorithms for CANDECOMP/PARAFAC (CP). If $\tY$ is an error tensor of a tensor approximation, this product is the gradient of a cost function with respect to factors, and has the largest workload in most CP algorithms. In this paper, a fast method to compute this product is proposed. Experimental verification shows that the fast CP gradient can accelerate the CP_ALS algorithm 2 times and 8 times faster for factorizations of 3-D and 4-D tensors, and the speed-up ratios can be 20-30 times for higher dimensional tensors.
The partition of solutes between buffer solutions and solutions containing hyaluronic acid.

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Profiling Network Performance for Multi-tier Data Center Applications

Network performance problems are notoriously tricky to diagnose, and this is magnified when applications are often split into multiple tiers of application components spread across thousands of servers in a data center. Problems often arise in the communication between the tiers, where either the application or the network (or both! ) could be to blame. In this paper, we present SNAP, a scalable network-application profiler that guides developers in identifying and fixing performance problems. SNAP passively collects TCP statistics and socket-call logs with low computation and storage overhead, and correlates across shared resources (e.g., host, link, switch) and connections to pinpoint the location of the problem (e.g., send buffer mismanagement, TCP/application conflicts, application-generated microbursts, or network congestion). Our one-week deployment of SNAP in a production data center (with over 8,000 servers and over 700 application components) has already helped developers uncover 15 major performance problems in application software, the network stack on the server, and the underlying network.
Caldendrin–Jacob: A Protein Liaison That Couples NMDA Receptor Signalling to the Nucleus

NMDA (N-methyl-D-aspartate) receptors and calcium can exert multiple and very divergent effects within neuronal cells, thereby impacting opposing occurrences such as synaptic plasticity and neuronal degeneration. The neuronal Ca2+ sensor Caldendrin is a postsynaptic density component with high similarity to calmodulin. Jacob, a recently identified Caldendrin binding partner, is a novel protein abundantly expressed in limbic brain and cerebral cortex. Strictly depending upon activation of NMDA-type glutamate receptors, Jacob is recruited to neuronal nuclei, resulting in a rapid stripping of synaptic contacts and in a drastically altered morphology of the dendritic tree. Jacob's nuclear trafficking from distal dendrites crucially requires the classical Importin pathway. Caldendrin binds to Jacob's nuclear localization signal in a Ca2+-dependent manner, thereby controlling Jacob's extranuclear localization by competing with the binding of Importin-α to Jacob's nuclear localization signal. This competition requires sustained synapto-dendritic Ca2+ levels, which presumably cannot be achieved by activation of extrasynaptic NMDA receptors, but are confined to Ca2+ microdomains such as postsynaptic spines. Extrasynaptic NMDA receptors, as opposed to their synaptic counterparts, trigger the cAMP response element-binding protein (CREB) shut-off pathway, and cell death. We found that nuclear knockdown of Jacob prevents CREB shut-off after extrasynaptic NMDA receptor activation, whereas its nuclear overexpression induces CREB shut-off without NMDA receptor stimulation. Importantly, nuclear knockdown of Jacob attenuates NMDA-induced loss of synaptic contacts, and neuronal degeneration. This defines a novel mechanism of synapse-to-nucleus communication via a synaptic Ca2+-sensor protein, which links the activity of NMDA receptors to nuclear signalling events involved in modelling synapto-dendritic input and NMDA receptor–induced cellular degeneration.
Short-term traffic flow prediction based on ratio-median lengths of intervals two-factors high-order fuzzy time series

Due to the complexity of traffic flow characteristics, the traditional statistical regression models have been unsuitable for the traffic flow prediction. And thereby the paper proposes the fuzzy time series method to predict short- term traffic flow. First, we proposes an improved fuzzy time series prediction model, i.e. , ratio-median lengths of intervals two-factors high-order fuzzy time series. The prediction model simultaneously considers impact of many factors on the traffic flow formulation. For achieving higher prediction accuracy, the ratio-median lengths of intervals method is adopted to adaptively partition the universe of discourse of linguistic variable. Then it is used to predict the raw traffic flow data which are collected at Zizhu Bridge in Beijing. The experiment result verifies that the improved fuzzy time series prediction model can achieve high prediction accuracy.
A game-theoretical approach for finding optimal strategies in an intruder classification game

We consider a game in which a strategic defender classifies an intruder as spy or spammer. The classification is based on the number of file server and mail server attacks observed during a fixed window. The spammer naively attacks (with a known distribution) his main target: the mail server. The spy strategically selects the number of attacks on his main target: the file server. The defender strategically selects his classification policy: a threshold on the number of file server attacks. We model the interaction of the two players (spy and defender) as a nonzero-sum game: The defender needs to balance missed detections and false alarms in his objective function, while the spy has a tradeoff between attacking the file server more aggressively and increasing the chances of getting caught. We give a characterization of the Nash equilibria in mixed strategies, and demonstrate how the Nash equilibria can be computed in polynomial time. Our characterization gives interesting and non-intuitive insights on the players' strategies at equilibrium: The defender uniformly randomizes between a set of thresholds that includes very large values. The strategy of the spy is a truncated version of the spammer's distribution. We present numerical simulations that validate and illustrate our theoretical results.