Miracle-dz/UniFAR-FTUs huggingface dataset:
VON NEUMANN CAPACITY OF NOISY QUANTUM CHANNELS

We discuss the capacity of quantum channels for information transmission and storage. Quantum channels have dual uses: they can be used to transmit known quantum states which code for classical information, and they can be used in a purely quantum manner, for transmitting or storing quantum entanglement. We propose here a definition of thevon Neumanncapacity of quantum channels, which is a quantum-mechanical extension of the Shannon capacity and reverts to it in the classical limit. As such, the von Neumann capacity assumes the role of a classical or quantum capacity depending on the usage of the channel. In analogy to the classical construction, this capacity is defined as the maximumvon Neumann mutual entropyprocessed by the channel, a measure which reduces to the capacity for classical information transmission through quantum channels ~the ‘‘Kholevo capacity’’ ! when known quantum states are sent. The quantum mutual entropy fulfills all basic requirements for a measure of information, and observes quantum data-processing inequalities. We also derive a quantum Fano inequality relating the quantum loss of the channel to the fidelity of the quantum code. The quantities introduced are calculated explicitly for the quantum depolarizing channel. The von Neumann capacity is interpreted within the context of superdense coding, and an extended Hamming bound is derived that is consistent with that capacity. @S1050-2947~97! 04511-3#
Efficient Hardware Barrier Synchronization in Many-Core CMPs

Traditional software-based barrier implementations for shared memory parallel machines tend to produce hotspots in terms of memory and network contention as the number of processors increases. This could limit their applicability to future many-core CMPs in which possibly several dozens of cores would need to be synchronized efficiently. In this work, we develop GBarrier, a hardware-based barrier mechanism especially aimed at providing efficient barriers in future many-core CMPs. Our proposal deploys a dedicated G-line-based network to allow for fast and efficient signaling of barrier arrival and departure. Since GBarrier does not have any influence on the memory system, we avoid all coherence activity and barrier-related network traffic that traditional approaches introduce and that restrict scalability. Through detailed simulations of a 32-core CMP, we compare GBarrier against one of the most efficient software-based barrier implementations for a set of kernels and scientific applications. Evaluation results show average reductions of 54 and 21 percent in execution time, 53 and 18 percent in network traffic, and also 76 and 31 percent in the energy-delay2 product metric for the full CMP when the kernels and scientific applications, respectively, are considered.
Network layer mobility: an architecture and survey

We explore various network layer concepts that play a crucial role in the design of mobile networking systems. We show that mobility is essentially an address translation problem and is best resolved at the network layer. We describe services that must be supported at the network layer to carry out the task of address translation. Using these service primitives as building blocks, we describe a network-layer architecture which enables smooth integration of mobile end systems within the existing Internet. A summary of some of the key mobile IP proposals is presented, and it is shown that each proposal can be viewed as a special case of the architecture outlined in this article.
A New Data Transformation Method Based on Adaptive Binarization for Bag-of-Features Model

Visual object categorization has gained more and more attention in computer vision and bag-of-features model has become an important approach to form an object categorization system. As for image feature representation, "continuous valued" histogram that records frequency of each visual word and "binarized value" histogram that records only absence/presence of each visual word are commonly used in bag- of-features model. In this paper, we utilize the merits of both representations and propose a scheme to use adaptive binarization method to transform "continuous valued" histogram to "binarized value" histogram. Experiments on "The PASCAL Visual Object Classes Challenge 2006" show that this data transformation approach improves the performance of object categorization system. Keywords-data transformation; binarization; bag-of-features model
Low body temperature associated with severe ischemic stroke within 6 hours of onset: The Bergen NORSTROKE Study

Background Hypothermia is considered neuroprotective and a potential treatment in cerebral ischemia. Some studies suggest that hyperthermia may promote clot lysis. We hypothesized that low body temperature would prolong time to spontaneous clot lysis resulting in an association between low body temperature and severe neurological deficits in the early phase of ischemic stroke. Methods In this prospective study, patients (n = 516) exhibiting ischemic stroke with symptom onset within 6 hours were included. Body temperature and National Institute of Health Stroke Scale (NIHSS) score were registered on admission. Because low body temperature on admission may be secondary to immobilization due to large stroke, separate analyses were performed on patients with cerebral hemorrhage admitted within 6 hours (n = 85). Results Linear regression showed that low body temperature on admission was independently associated with a high NIHSS score within 6 hours of stroke onset in patients with ischemic stroke (P < 0.001). The association persisted when NIHSS was measured at 24 hours after admission. No such associations were found in patients with cerebral hemorrhage admitted within 6 hours of stroke onset. Conclusion Our study suggests that low body temperature within 6 hours of symptom onset is associated with severe ischemic stroke. This is in support of our hypothesis, although other contributing mechanisms cannot be excluded.
Trade and Financial Integration, Extensive Margin, and Income Divergence

We revisit the classical question on economic integration and income convergence in a two-sector OLG model with nancial frictions and sectoral heterogeneity in minimum investment requirements (MIR, hereafter). The extensive margin of investment is a critical channel through which aggregate income may become a determinant of comparative advantage. Free trade allows the rich (poor) countries to specialize partially or completely in the high-MIR (low-MIR) sector which has a high (low) return endogenously. The specialization eect interacts with the neo
AUTOMATIC GEOREFERENCING OF AERIAL IMAGES USING HIGH- RESOLUTION STEREO SATELLITE IMAGES

For airborne surveys, direct georeferencing has become the primary source for EOPs (Exterior Orientation Parameters) determination since integrated GPS/INS (Global Positioning System/Inertial Navigation System) systems were introduced. However, there is still need for alternative indirect georeferencing since there are remote, inaccessible areas that lack a geodetic infrastructure and thus GPS/INS-based georeferencing is not feasible. In addition, terrain-referenced navigation is gaining momentum, where the assumption is that no GPS is available. High-resolution satellite images have been globally available and newer high-resolution satellite images offer not only better spatial resolution with decreasing revisit time, but high positional accuracy up to subpixel if ground control is available. Therefore, high-resolution satellite imagery has high potential as a ground control source for aerial image georeferencing and terrain-referenced navigation. Indirect georeferencing of aerial images usually requires accurate 3D ground control points. Unfortunately, ortho-rectified imagery, which is conventionally used as a reference for image-to-image georegistration, contains relief displacement due objects on the ground, resulting in horizontal errors; note that accurate DSM (Digital Surface Model), including terrain and all features on the ground, is usually not available globally. In this study, a high-resolution stereo satellite image-based automatic georeferencing approach is proposed. The use of stereo images can avoid the impact of relief displacement and requires no DSM to obtain ground heights. The matching between aerial and satellite stereo images is based on the SIFT (Scale-Invariant Feature Transform) features, and outliers are pruned utilizing RANSAC (RANdom SAmple Consensus). Finally, to recover 3D ground coordinates, cross correlation matching is performed for epipolar resampled satellite images using FFT (Fast Fourier Transform). An experiment was carried out for a strip of aerial images, including various terrain textures, and showed good potential for the approach.
Multiple low-turbulence starless cores associated with intermediate- to high-mass star formation

Aims. Characterizing the gas and dust properties prior to and in the neighborhood of active intermediate- to high-mass star formation. Methods. Two Infrared Dark Clouds (IRDCs) – IRDC 19175-4 and IRDC 19175-5 – that are located in the vicinity of the luminous massive star-forming region IRAS 19175+1357, but that remain absorption features up to 70 μm wavelength, were observed with the Plateau de Bure Interferometer in the 3.23 mm dust continuum as well as the N2H + (1–0) and 13 CS(2–1) line emission. Results. While IRDC 19175-4 is clearly detected in the 3.23 mm continuum, the second source in the field, IRDC 19175-5, is only barely observable above the 3σ continuum detection threshold. However, the N2H + (1–0) observations reveal 17 separate sub-sources in the vicinity of the two IRDCs. Most of them exhibit low levels of turbulence (Δv ≤ 1k m s −1 ), indicating that the fragmentation process in these cores may be dominated by the interplay of thermal pressure and gravity, but not so much by turbulence. Combining the small line widths with the non-detection up to 70 μm and the absence of other signs of star formation activity, most of these 17 cores
Design of Reversible Sequential Circuit Using Reversible Logic Synthesis

Reversible logic is one of the most vital issue at present time and it has different areas for its application, those are low power CMOS, quantum computing, nanotechnology, cryptography, optical computing, DNA computing, digital signal processing (DSP), quantum dot cellular automata, communication, computer graphics. It is not possible to realize quantum computing without implementation of reversible logic. The main purposes of designing reversible logic are to decrease quantum cost, depth of the circuits and the number of garbage outputs. In this paper, we have proposed a new reversible gate. And we have designed RS flip flop and D flip flop by using our proposed gate and Peres gate. The proposed designs are better than the existing proposed ones in terms of number of reversible gates and garbage outputs. So, this realization is more efficient and less costly than other realizations.
Can the Threshold Performance of Maximum Likelihood DOA Estimation be Improved by Tools from Random Matrix Theory

For direction of arrival (DOA) estimation in the threshold region, it has been shown that use of Random Matrix Theory (RMT) eigensubspace estimates provides significant improvement in MUSIC performance. Here we investigate whether these RMT methods can also improve the threshold performance of unconditional (stochastic) maximum likelihood DOA estimation (MLE).
Using a global aerosol model adjoint to unravel the footprint of spatially‐distributed emissions on cloud droplet number and cloud albedo

The adjoints of the GEOS‐Chem Chemical Transport Model and a comprehensive cloud droplet parameterization are coupled to study the sensitivity of cloud droplet number concentration (Nd) over US regions and Central Europe to global emissions of anthropogenic fine mode aerosol precursors. Simulations reveal that the Nd over the midwestern and southeastern US is mostly sensitive to SO2 emissions during August, and to NH3 emissions during February. Over the western US, Nd is mostly sensitivity to SO2 and primary organic aerosol emissions. In Central Europe, Nd is most sensitive to NH3 and NOx emissions. As expected, local emissions strongly affect Nd; long‐range transport, however, is also important for the western US and Europe. Emissions changes projected for the year 2050 are estimated to have the largest impacts on cloud albedo andNd over Central Europe during August (42% and 82% change, respectively) and western US during February (12% and 36.5% change, respectively).
A soft error analysis tool for high-speed digital designs

Evaluation of soft error hardness becomes more important for modern electrical and electronic devices as the semi-conductor technology advances. Recent studies have mainly focused on soft error rate analysis of combinational logic circuits which has been used with simulation and/or path-based statistical estimation. Only a few studies suggested the techniques for evaluating sequential circuits. To assess soft error susceptibility for general cell-based designs, it is essential to analyze variation of total SER between clock-to-clock transitions as well as initial soft error rates. This paper presents a two-pass soft error analysis technique, which provides both initial and dynamic error rate of digital circuits. Especially, the logical probabilities for noise generation and propagation are considered in detail without much computational complexity. Experimental results are reported from a pre-characterized 130nm technology cell library.
Time series feature extraction for data mining using DWT and DFT

A planter for plants comprising a lamp of the oil-burning type and comprising a glass base adapted to contain water, a burner having a wick extending therethrough, and a transparent chimney, the lower end of which is sealed relative to the perimeter of the burner and soil is disposed in at least the lower portion of said chimney and said wick extending into said soil to convey moisture from the base into said soil by capillary action.
Evaluation of linear ozone photochemistry parametrizations in a stratosphere-troposphere data assimilation system

This paper evaluates the performance of various linear ozone photochemistry parametrizations using the stratosphere-troposphere data assimilation system of the Met Office. A set of experiments were run for the period 23 September 2003 to 5 November 2003 using the Cariolle (v1.0 and v2.1), LINOZ and Chem2D-OPP (v0.1 and v2.1) parametrizations. All operational meteorological observations were assimilated, together with ozone retrievals from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). Experiments were validated against independent data from the Halogen Occultation Experiment (HALOE) and ozonesondes. Additionally, a simple offline method for comparing the parametrizations is introduced. It is shown that in the upper stratosphere and mesosphere, outside the polar night, ozone analyses are controlled by the photochemistry parametrizations and not by the assimilated observations. The most important factor in getting good results at these levels is to pay attention to the ozone and temperature climatologies in the parametrizations. There should be no discrepancies between the climatologies and the assimilated observations or the model, but there is also a competing demand that the climatologies be objectively accurate in themselves. Conversely, in the lower stratosphere outside regions of heterogeneous ozone depletion, the ozone analyses are dominated by observational increments and the photochemistry parametrizations have little influence. We investigate a number of known problems in LINOZ and Cariolle v1.0 in more detail than previously, and we find discrepancies in Cariolle v2.1 and Chem2D-OPP v2.1, which are demonstrated to have been removed in the latest available versions (v2.8 and v2.6 respectively). In general, however, all the parametrizations work well through much of the stratosphere, helped by the presence of good quality assimilated MIPAS observations.
Learning in Lines of Action

This paper investigates to what extent learning methods are beneficial for the Lines of Action tournament program MIA. We focus on two components of the program: (1) the evaluation function and (2) the move ordering. Using temporal difference learning the evaluation function was improved by tuning the weights. We found substantial improvements for three weights. The move ordering was enhanced by the Neural MoveMap (NMM) heuristic, which is based on learning. The two learning techniques improved both the playing quality and the speed of the program. Test results are given. The new evaluation function improved the program with a winning ratio of 1.68. The speed up of the NMM heuristic is 17 percent.
A Parallel Network Simulation Scheduling Algorithm Oriented Towards Multi-task

To meet the demands of the large-scale network simulation platform technology, we have improved the classical Min-min algorithm widely used in Grid application. We proposed a novel multi-task network simulation scheduling algorithm based on multi-valued mapping and the new algorithm is called MUNS-Min-min, we also discussed how to determine the weight of simulation time and the resource consumption. Experimental results show that our algorithm is suitable for complex computing environment, and the performance of the simulation platform has improved nearly 20%, compared with traditional scheduling algorithms.
8-OHdG in Cerebrospinal Fluid as a Marker of Oxidative Stress in Various Neurodegenerative Diseases

Background: The 8-hydroxy-2 deoxyguanosine (8-OHdG) is a product of nucleoside oxidation of DNA and a reliable marker of oxidative stress markers. Increased levels of oxidative stress have been reported in the cerebrospinal fluid (CSF) of patients with various neurodegenerative disorders. Objective: In search of a biochemical indicator of Parkinson’s disease (PD), we analyzed the levels 8-OHdG in the CSF of 99 patients, using ELISA to assess the differences between various neurodegenerative disorders. Results: Statistically significant higher CSF levels (p = 0.022) of 8-OHdG in non-demented PD patients as compared to the control group were observed. No differences between CSF 8-OHdG levels and age at the time of lumbar puncture, presence or severity of dementia, or gender were found. Conclusions: 8-OHdG levels could be potentially useful in the neurochemically supported diagnosis of PD.
Direct Determination of the Kinematics of the Universe and Properties of the Dark Energy as Functions of Redshift

Understanding the nature of dark energy, which appears to drive the expansion of the universe, is one of the central problems of physical cosmology today. In an earlier paper we proposed a novel method to determine the expansion rate E(z) and the deceleration parameter q(z) in a largely model-independent way, directly from the data on coordinate distances y(z). Here we expand this methodology to include measurements of the pressure of dark energy p(z), its normalized energy density fraction f(z), and the equation-of-state parameter w(z). We then apply this methodology to a new, combined data set of distances to supernovae and radio galaxies. In evaluating E(z) and q(z), we make only the assumptions that the FRW metric applies and that the universe is spatially flat (an assumption strongly supported by modern cosmic microwave background radiation measurements). The determinations of E(z) and q(z) are independent of any theory of gravity. For evaluations of p(z), f(z), and w(z), a theory of gravity must be adopted, and general relativity is assumed here. No a priori assumptions regarding the properties or redshift evolution of the dark energy are needed. We obtain trends for y(z) and E(z) that are fully consistent with the standard Friedmann-Lemaître concordance cosmology with Ω0 = 0.3 and Λ0 = 0.7. The measured trend for q(z) deviates systematically from the predictions of this model on a ~1-2 σ level but may be consistent for smaller values of Λ0. We confirm our previous result that the universe transitions from acceleration to deceleration at a redshift zT ≈ 0.4. The trends for p(z), f(z), and w(z) are consistent with being constant at least out to z ~ 0.3-0.5 and broadly consistent with being constant out to higher redshifts, but with large uncertainties. For the present values of these parameters we obtain E0 = 0.97 ± 0.03, q0 = -0.35 ± 0.15, p0 = -0.6 ± 0.15, f0 = -0.62 - (Ω0 - 0.3) ± 0.05, and w0 = -0.9 - ϵ(Ω0 - 0.3) ± 0.1, where Ω0 is the density parameter for nonrelativistic matter and ϵ ≈ 1.5 ± 0.1. We note that in the standard Friedmann-Lemaître models p0 = -Λ0, and thus we can measure the value of the cosmological constant directly and obtain results in agreement with other contemporary results.
Spectral clustering and dimensionality reduction applied to Content based image retrieval with hybrid Descriptors

The topic of research exposed in this paper concerns Content Based image retrieval in a heterogeneous high database. The increase of storage capacities and the evolution of compression techniques have generated an explosion of the digital information quantity. Their computerization opens a vast field of applications. In this setting we are interested more especially in the problem of the dimensionality reduction and spectral clustering of a heterogeneous database of images in order to image retrieval by the content. Our new gait described in this paper consists to:  In first phase the description of the database images by a hybrid descriptor which are Interest SIFT points combined with texture descriptor given by the application of Wavelet transform. The descriptor is multi-dimensional, robust and invariant to changes and scales.  In second phase the representation of the database images as a convex graph.  In third phase the reduction of the space of representation by the application of an unsupervised spectral classification (The Spectral training uses information contained in the eigenvectors of the normalized matrix of transition to detect structures in data.) That will provide us classes of images that has shortcoming the Eigen-values calculated on the matrix of symmetry. As last phase, we use the Nyström theory that will permit us, not to recalculate the all Eigen-values, but only the lasts one.
Drosophila topoisomerase II double-strand DNA cleavage: analysis of DNA sequence homology at the cleavage site.

In order to study the sequence specificity of double-strand DNA cleavage by Drosophila topoisomerase II, we have mapped and sequenced 16 strong and 47 weak cleavage sites in the recombinant plasmid p pi 25.1. Analysis of the nucleotide and dinucleotide frequencies in the region near the site of phosphodiester bond breakage revealed a nonrandom distribution. The nucleotide frequencies observed would occur by chance with a probability less than 0.05. The consensus sequence we derived is 5'GT.A/TAY decrease ATT.AT. G 3', where a dot means no preferred nucleotide, Y is for pyrimidine, and the arrow shows the point of bond cleavage. On average, strong sites match the consensus better than weak sites.
L 2-optimal model reduction for unstable systems using iterative rational Krylov algorithm

Unstable dynamical systems can be viewed from a variety of perspectives. We discuss the potential of an inputoutput map associated with an unstable system to represent a bounded map from L2(R) to itself and then develop criteria for optimal reduced order approximations to the original (unstable) system with respect to an L2-induced Hilbert-Schmidt norm. Our optimality criteria extend the Meier-Luenberger interpolation conditions for optimal H2 approximation of stable dynamical systems. Based on this interpolation framework, we describe an iteratively corrected rational Krylov algorithm for L2 model reduction. A numerical example involving a hardto-approximate full-order model illustrates the effectiveness of the proposed approach.