Miracle-dz/UniFAR-FTUs huggingface dataset:
Iteration-Complexity of a Generalized Forward Backward Splitting Algorithm

In this paper, we analyze the iteration-complexity of Generalized Forward--Backward (GFB) splitting algorithm, as proposed in \cite{gfb2011}, for minimizing a large class of composite objectives $f + \sum_{i=1}^n h_i$ on a Hilbert space, where $f$ has a Lipschitz-continuous gradient and the $h_i$'s are simple (\ie their proximity operators are easy to compute). We derive iteration-complexity bounds (pointwise and ergodic) for the inexact version of GFB to obtain an approximate solution based on an easily verifiable termination criterion. Along the way, we prove complexity bounds for relaxed and inexact fixed point iterations built from composition of nonexpansive averaged operators. These results apply more generally to GFB when used to find a zero of a sum of $n > 0$ maximal monotone operators and a co-coercive operator on a Hilbert space. The theoretical findings are exemplified with experiments on video processing.
Environmental Health: A Global Access Science Source

Background: Bone marrow stromal cells produce cytokines required for the normal growth and development of all eight hematopoietic cell lineages. Aberrant cytokine production by stromal cells contributes to blood cell dyscrasias. Consequently, factors that alter stromal cell cytokine production may significantly compromise the development of normal blood cells. We have shown that environmental chemicals, such as aromatic hydrocarbon receptor (AhR) agonists, suppress B lymphopoiesis by modulating bone marrow stromal cell function. Here, we extend these studies to evaluate the potential for two prototypic AhR agonists, 7,12-dimethylbenz [a]anthracene (DMBA) and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), to alter stromal cell cytokine responses. Methods: Bone marrow stromal cells were treated with AhR agonists and bacterial lipopolysaccharide (LPS) to mimic innate inflammatory cytokine responses and to study the effects of AhR ligands on those responses. Steady state cytokine RNA levels were screened by RNAse protection assays (RPA) and quantified by real-time PCR. Cytokine (IL-6) protein production was measured by ELISA. NF-κB EMSAs were used to study IL-6 transcriptional regulation. Results: RPAs indicated that AhR+ bone marrow stromal cells consistently up-regulated genes encoding IL-6 and LIF in response to LPS, presumably through activation of Toll-like receptor 4. Pre-treatment with low doses of DMBA or TCDD selectively abrogated IL-6 gene induction but had no effect on LIF mRNA. Real-time-PCR indicated a significant inhibition of IL-6 mRNA by AhR ligands within 1 hour of LPS challenge which was reflected in a profound down-regulation of IL-6 protein induction, with DMBA and TCDD suppressing IL-6 levels as much as 65% and 88%, respectively. This potent inhibitory effect persisted for at least 72 hours. EMSAs measuring NF-κB binding to IL-6 promoter sequences, an event known to induce IL-6 transcription, indicated a significant decrease in the LPS-mediated induction of DNA-binding RelA/p50 and c-Rel/p50 heterodimers in the presence of DMBA. Conclusions: Common environmental AhR agonists can suppress the response to bacterial lipopolysaccharide, a model for innate inflammatory responses, through down-regulation of IL-6, a cytokine critical to the growth of several hematopoietic cell subsets, including early B cells. This suppression occurs at least at the level of IL-6 gene transcription and may be regulated by NF-κB.
ITIL maturity model of IT outsourcing: Evidence from a “leading user”

This paper reports the results of a two year study of “lead users” of ITIL. The study formed part of a multi study investigation into the role played by ITIL in improving outsourcing outcomes. These “lead users” provided evidence of how, used effectively, ITIL can improve the outsourcing relationship. Informants suggested that the extent to which the client and vendor understand each others' expectations is crucial to using ITIL effectively, as are knowledge sharing and other aspects of good communication. This is also consistent with a further study of 83 ITIL users' experience. However, informants observed that it can take time before ITIL processes are fully understood and incorporated into practice. The paper concludes that where ITIL practices and principles are internalized into the day-to-day processes and behaviours of the firm (and its IT culture) the greatest benefits will be obtained.
Identification of a New Rhoptry Neck Complex RON9/RON10 in the Apicomplexa Parasite Toxoplasma gondii

Apicomplexan parasites secrete and inject into the host cell the content of specialized secretory organelles called rhoptries, which take part into critical processes such as host cell invasion and modulation of the host cell immune response. The rhoptries are structurally and functionally divided into two compartments. The apical duct contains rhoptry neck (RON) proteins that are conserved in Apicomplexa and are involved in formation of the moving junction (MJ) driving parasite invasion. The posterior bulb contains rhoptry proteins (ROPs) unique to an individual genus and, once injected in the host cell act as effector proteins to co-opt host processes and modulate parasite growth and virulence. We describe here two new RON proteins of Toxoplasma gondii, RON9 and RON10, which form a high molecular mass complex. In contrast to the other RONs described to date, this complex was not detected at the MJ during invasion and therefore was not associated to the MJ complex RON2/4/5/8. Disruptions of either RON9 or RON10 gene leads to the retention of the partner in the ER followed by subsequent degradation, suggesting that the RON9/RON10 complex formation is required for proper sorting to the rhoptries. Finally, we show that the absence of RON9/RON10 has no significant impact on the morphology of rhoptry, on the invasion and growth in fibroblasts in vitro or on virulence in vivo. The conservation of RON9 and RON10 in Coccidia and Cryptosporidia suggests a specific relation with development in intestinal epithelial cells.
A Semantic QoS-based Web Service Discovery Algorithm for Over-Constrained Demands

Discovery of Web Services (WSs) has gained great research attention due to proliferation of available WSs and the failure of the syntactic approach of UDDI. Semantic discovery mechanisms have been invented in order to provide more precise results. However, many functionally-equivalent WSs are returned by semantic WS registries. Fortunately, the solution is to enforce the semantic QoS-based description and discovery of WSs. We have already presented a rich and extensible ontology language for QoS-based WS description and we have proposed a semantic QoS metric matching algorithm. Based on this algorithm, we have extended a CSP-based approach for QoS-based WS discovery. In this paper, we show an extension of OWL-Q with SWRL rules as OWL alone fails in some aspects of QoS description. We also propose a modification to the metric matching algorithm to make it more feasible. Finally, we propose and analyze an automated approach for semantic QoS-based WS discovery that provides solutions even for over-constrained QoS-based WS demands.
On Robust Output Feedback Control For Polytopic Systems

Robust dynamic output feedback design is an open problem, computationally speaking, since its determination asks for the solution of nonlinear matrix inequalities, namely bilinear ones. This is particularly the case, for polytopic uncertainty. Here a new sufficient condition is proposed by the use of bounds and scaling for completion of squares. The usefulness of the provided conditions stands in the fact that its solution can be performed using the Frank-Wolfe algorithm which runs in only one shot. The control design of an inverted pendulum with uncertain friction coefficients illustrates the theory.
Regularized Policy Gradients: Direct Variance Reduction in Policy Gradient Estimation

Policy gradient algorithms are widely used in reinforcement learning problems with continuous action spaces, which update the policy parameters along the steepest direction of the expected return. However, large variance of policy gradient estimation often causes instability of policy update. In this paper, we propose to suppress the variance of gradient estimation by directly employing the variance of policy gradients as a regularizer. Through experiments, we demonstrate that the proposed variance-regularization technique combined with parameter-based exploration and baseline subtraction provides more reliable policy updates than non-regularized counterparts.
Affine Invariant and Recognizing of 3 D Objects

The increasing number of objects 3D are available on the Internet or in specialized databases and require the establishment of methods to develop description and recognition techniques to access intelligently to the contents of these objects . In this context, our work whose objective is to present an affine invariant method [1,2,3] of 3D objects . An invariant is a numerical quantity calculated from an object that keeps the same value when it is transformed by an element of one of all transformations. All transformations considered in this work is the similarity group. In this paper, we present three methods for the invariant of 3D objects. The proposed methods based on the extraction of the quantity: statistical variables , coefficients and barycenter from the 3D object, these quantity remain invariant against affine transformation of the 3D object. In this work, the 3D objects are transformations of 3D objects by one element of the overall transformation. The set of transformations considered here is the general affine group. The measure of similarity between two invariants vectors are achieved by a similarity function using the euclidean distance.
An introduction to mobile payments: market drivers, applications, and inhibitors

This paper provides a market view of mobile payments. It starts with a discussion of the variety and growth of payments being made with mobile devices. The relationship between mobile payments and their core business drivers, mobile banking and mobile commerce, are explored. How mobile devices reduce costs, increase reach and enable omnichannel business processes are discussed. The disintermediating effect of mobile payments on existing payment processes is explored. Finally, a review of some of the inhibitors for mobile payments growth is considered.
Performance enhancement of TCP over adaptive multi-rate IEEE 802.11 wireless LANs

This paper presents a new TCP window size adjustment scheme for the automatic rate fallback (ARF) algorithm. The proposed scheme utilizes the information about radio usage monitored on the IEEE 802.11 MAC layer. Each station calculates the maximum available window size on each long-lived connection based on these information when the data transmission/reception rate is switched, and limits the maximum sending window size. The performance of the proposed scheme is investigated and compared with that of standard TCP through several simulations. The simulation results show that the proposed scheme enhances the transmission efficiency of TCP.
Cognitive telepresence in human-robot interactions

Remote teleoperation of advanced, semi-autonomous robotic technologies has great potential in many industries critical to the economy and for the environment of the Middle East. Applications include maintenance of under-water oil wells, maintenance of nuclear power plants, counter-terrorism and national defense, law enforcement, remote sensing, and health care. In each of these applications, a user, likely without technology expertise, must operate a complex robot in uncertain and unknown environments. The nature of the tasks and environments encountered by the robot in these applications make it highly likely that the robot's limited autonomy will fail or be insufficient to complete the desired task. In this paper, we argue that, in such scenarios, cognitive telepresence, defined as the ability of the user to comprehend and control the robot's cognition, is an important design principle for human-robot systems. We compare and contrast cognitive telepresence to existing design principles commonly discussed in the literature, and define various metrics of cognitive telepresence. Finally, via two illustrative examples and a user study, we demonstrate the usefulness of cognitive telepresence as an important design principle of human-robot systems consisting of a user with limited technology expertise and a robot with limited and error-prone artificial intelligence.
Performance trade-off analysis of analog circuits by normal-boundary intersection

We present a new technique to examine the trade-off regions of a circuit where its competing performances become "simultaneously optimal", i.e. Pareto optimal. It is based on circuit simulation, sizing rules, which capture elementary topological and technological constraints, and an advanced multicriteria optimization formulation called normal-boundary intersection. We are able to efficiently calculate a well-balanced discretization of a Pareto surface, identify the active constraints, which prevent a further improvement, and even rank these constraints in terms of stringency. Experimental results demonstrate the efficacy and efficiency of the method and its potential for topology selection and analog synthesis.
EVA versus Earnings: Does it Matter which is More Highly Correlated with Stock Returns?

Dissatisfaction with traditional accounting-based performance measures has spawned a number of alternatives, of which Economic Value Added (EVA) is clearly the most prominent. How can we tell which performance measures best capture managerial contributions to value? There is currently a heated debate among practitioners as to whether the new performance measures have a higher correlation with stock values and returns than do traditional accounting earnings. Academic researchers have instead relied on the variance of performance measures to gauge their relative accuracy. Our analysis pits EVA against earnings as two candidate performance measures. We use a relatively standard principal-agent model, but recognize that while the variability of each measure is observable, their exact information (signal) content is not. The model provides a formal method for ascertaining the relative value of such measures based on two distinct uses of the stock price. First, as is well-known, prices provide a noisy measure of managerial value-added. Our novel insight is that stock prices can also reveal the signal content of alternative accounting-based performance measures. We then show how to combine stock prices, earnings, and EVA to produce an optimally weighted compensation scheme. Surprisingly, we find that the simple correlation between EVA or earnings and stock returns is a reasonably reliable guide to their value as an incentive contracting tool. This is not because stock returns are themselves an ideal performance measure, rather it is because correlation places appropriate weights on both the signal and noise components of alternative measures. We then calibrate the theoretical improvement in incentive contracts from optimally using EVA in addition to accounting earnings at the firm and industry level. That is, we empirically estimate the "value-added" of EVA by firm and industry. These estimates are positive and significant in predicting which firms have actually adopted EVA as an internal performance measure.
Modeling Transmembrane Domain Dimers/Trimers of Plexin Receptors: Implications for Mechanisms of Signal Transmission across the Membrane

Single-pass transmembrane (TM) receptors transmit signals across lipid bilayers by helix association or by configurational changes within preformed dimers. The structure determination for such TM regions is challenging and has mostly been accomplished by NMR spectroscopy. Recently, the computational prediction of TM dimer structures is becoming recognized for providing models, including alternate conformational states, which are important for receptor regulation. Here we pursued a strategy to predict helix oligomers that is based on packing considerations (using the PREDDIMER webserver) and is followed by a refinement of structures, utilizing microsecond all-atom molecular dynamics simulations. We applied this method to plexin TM receptors, a family of 9 human proteins, involved in the regulation of cell guidance and motility. The predicted models show that, overall, the preferences identified by PREDDIMER are preserved in the unrestrained simulations and that TM structures are likely to be diverse across the plexin family. Plexin-B1 and –B3 TM helices are regular and tend to associate, whereas plexin-A1, -A2, –A3, -A4, -C1 and –D1 contain sequence elements, such as poly-Glycine or aromatic residues that distort helix conformation and association. Plexin-B2 does not form stable dimers due to the presence of TM prolines. No experimental structural information on the TM region is available for these proteins, except for plexin-C1 dimeric and plexin-B1 – trimeric structures inferred from X-ray crystal structures of the intracellular regions. Plexin-B1 TM trimers utilize Ser and Thr sidechains for interhelical contacts. We also modeled the juxta-membrane (JM) region of plexin-C1 and plexin-B1 and show that it synergizes with the TM structures. The structure and dynamics of the JM region and TM-JM junction provide determinants for the distance and distribution of the intracellular domains, and for their binding partners relative to the membrane. The structures suggest experimental tests and will be useful for the interpretation of future studies.
Switching Strategies for Sequential Decision Problems With Multiplicative Loss With Application to Portfolios

A wide variety of problems in signal processing can be formulated such that decisions are made by sequentially taking convex combinations of vector-valued observations and these convex combinations are then multiplicatively compounded over time. A ldquouniversalrdquo approach to such problems might attempt to sequentially achieve the performance of the best fixed convex combination, as might be achievable noncausally, by observing all of the outcomes in advance. By permitting different piecewise-fixed strategies within contiguous regions of time, the best algorithm in this broader class would be able to switch between different fixed strategies to optimize performance to the changing behavior of each individual sequence of outcomes. Without knowledge of the data length or the number of switches necessary, the algorithms developed in this paper can achieve the performance of the best piecewise-fixed strategy that can choose both the partitioning of the sequence of outcomes in time as well as the best strategy within each time segment. We compete with an exponential number of such partitions, using only complexity linear in the data length and demonstrate that the regret with respect to the best such algorithm is at most O(ln(n)) in the exponent, where n is the data length. Finally, we extend these results to include finite collections of candidate algorithms, rather than convex combinations and further investigate the use of an arbitrary side-information sequence.
Virus-encoded microRNA contributes to the molecular profile of EBV-positive Burkitt lymphomas

Burkitt lymphoma (BL) is an aggressive neoplasm characterized by consistent morphology and phenotype, typical clinical behavior and distinctive molecular profile. The latter is mostly driven by the MYC over-expression associated with the characteristic translocation (8;14) (q24; q32) or with variant lesions. Additional genetic events can contribute to Burkitt Lymphoma pathobiology and retain clinical significance. A pathogenetic role for Epstein-Barr virus infection in Burkitt lymphomagenesis has been suggested; however, the exact function of the virus is largely unknown. In this study, we investigated the molecular profiles (genes and microRNAs) of Epstein-Barr virus-positive and -negative BL, to identify specific patterns relying on the differential expression and role of Epstein-Barr virus-encoded microRNAs. First, we found significant differences in the expression of viral microRNAs and in selected target genes. Among others, we identified LIN28B, CGNL1, GCET2, MRAS, PLCD4, SEL1L, SXX1, and the tyrosine kinases encoding STK10/STK33, all provided with potential pathogenetic significance. GCET2, also validated by immunohistochemistry, appeared to be a useful marker for distinguishing EBV-positive and EBV-negative cases. Further, we provided solid evidences that the EBV-encoded microRNAs (e.g. BART6) significantly mold the transcriptional landscape of Burkitt Lymphoma clones. In conclusion, our data indicated significant differences in the transcriptional profiles of EBV-positive and EBV-negative BL and highlight the role of virus encoded miRNA.
Functional verification of the POWER4 microprocessor and POWER4 multiprocessor system

This paper describes the methods and simulation techniques used to verify the microarchitecture design and functional performance of the IBM POWER4 processor and the POWER4-based Regatta system. The approach was hierarchical, based on but considerably expanding the practice used for verification of the CMOS-based IBM S/390 Parallel Enterprise Server™ G4. For POWER4, verification began at the abstract, high-level design phase and continued throughout the designer and unit levels, the multi-unit level, and finally the multiple-chip system level. The abstract (high-level design) phase permitted early validation of the POWER4 processor design prior to its commitment to HDL. The designer and unit-level stages focused on ensuring the correctness of the microarchitectural components. Multiunitlevel verification, performed on storage and I/O components as well as on the processor, confirmed architectural compliance for each of the chips and subsystems. Finally, systemlevel verification tested multiprocessor coherence and system-level function, including processor-to-I/O communication and validation of multiple hardware configurations. In parallel with design and functional validation, verification of reliability functions, performance, and degraded configurations was also performed at most of the levels in the hierarchy.
PEARL: a programmable virtual router platform

Programmable routers supporting virtualization are a key building block for bridging the gap between new Internet protocols and their deployment in real operational networks. This article presents the design and implementation of PEARL, a programmable virtual router platform with relatively high performance. It offers high flexibility by allowing users to control the configuration of both hardware and software data paths. The platform makes use of fast lookup in hardware and software exceptions in commodity multicore CPUs to achieve highspeed packet processing. Multiple isolated packet streams and virtualization techniques ensure isolation among virtual router instances.