Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Power Consumption in Future High-Capacity Network Nodes

Power consumption and the footprint of future network elements are expected to become the main limiting factors for scaling the current architectures and approaches to capacities of hundreds of terabits or even petabits per second. Since the underlying demand for network capacity can be satisfied only by contemporaneously increasing transmission bit rate, processing speed, and switching capacity, it unavoidably will lead to increased power consumption of network nodes. On the one hand, using optical switching fabrics could relax the limitations to some extent, but large optical buffers occupy larger areas and dissipate more power than electronic ones. On the other hand, electronic technology has made fast progress during the past decade regarding reduced feature size and decreased power consumption. It is expected that this trend will continue in the future. This paper addresses power consumption issues in future high-capacity switching and routing elements and examines different architectures based on both pure packet-switched and pure circuit-switched designs by assuming either all-electronic or all-optical implementation, which can be seen as upper and lower bounds regarding power consumption. The total power consumption of a realistic and appropriate technology for future high-performance core network nodes would probably lie somewhere between those two extreme cases. Our results show that implementation in optics is generally more power efficient; especially circuit-switched architectures have a low power consumption. When taking into account possible future developments of Si CMOS technology, even very large electronic packet routers having capacities of more than hundreds of terabits per second seem to be feasible. Because circuit switching is more power efficient and easier to implement in optics than pure packet switching, the scalability limitation due to increased power consumption could be considerably relaxed when a kind of dynamic optical circuit switching is used within the core network together with an efficient flow aggregation at edge nodes.
Dying in Yoghurt: The Number of Living Bacteria in Probiotic Yoghurt Decreases under Exposure to Room Temperature

Background/Aims: While probiotic bacteria are successfully used in the treatment of ulcerative colitis, the effect of commercially available probiotic products is still controversial. Here, we study whether the number of living probiotic bacteria in yoghurts is altered by an interruption of the cold chain. Methods: Three commonly available probiotic yoghurts were kept at 4°C or put at room temperature (RT) for 6 h or 24 h. An aliquot of each yoghurt was applied on Man-Rogosa-Sharpe agar and incubated at 37°C for 48 h. Colony forming units (CFU) were counted by microscopy. Results: The first yoghurt, containing Lactobacillus johnsonii, showed a significant decrease in CFU after 6 h of storage at RT, which was further pronounced after 24 h. The number of CFU of the second yoghurt, containing Lactobacillus GG, was also decreased after 6 h and further diminished after 24 h at RT. From the third yoghurt, containing Lactobacillus acidophilus, only 53.8% of the CFU remained after 6 h at RT; after 24 h, only about one fourth of the CFU were found. Conclusions: Our data demonstrate that the number of living probiotic bacteria in yoghurt products decreases dramatically after exposure to RT. This represents an important information for consumers of such products.
Attack Evaluation and Mitigation Framework

This paper proposes an implementation of an intrusion detection and prevention system in a Linux environment, with an extensive database of attack signatures, but also with a flexible interface for defining new signatures. The project relies on the analysis of current requirements and challenges in network security, leading to an evaluation of existing detection and network attack mitigation techniques. Attack evaluation and mitigation framework has a modular design, with multiple configuration options and availability during configuration. For increased accessibility, the solution provides a graphical interface available through a web browser, and a command line interface for the network administrator.
Cisplatin-DNA damage and repair in peripheral blood leukocytes in vivo and in vitro.

We have extended our studies on the relationship between cisplatin/carboplatin-induced DNA damage in readily accessible tissue(s) and clinical response to therapy. Such an approach may assist in the study of cancer drug resistance and in establishing parameters for assessing human populations for sensitivity to DNA damaging agents in the environment. Platinum-DNA adduct levels were measured by atomic absorbance spectrometry. DNA repair capacity was assessed in human T-lymphocytes by the ability to repair cisplatin lesions in cellular DNA or in transfected plasmid DNA. In a "blinded" study of 21 patients receiving combination cisplatin/carboplatin drug therapy, there was a direct relationship between DNA damage in leukocytes and disease response (summary two-sided p = 0.00011). The cohort of patients had 15 different tumor types, suggesting that blood tissue and tumor tissue of an individual may process platinum-DNA damage similarly regardless of the tissue of origin of the tumor. In leukocytes in vivo, persistence and accumulation were prominent features of the cisplatin-DNA adduct profile. Functional DNA repair capacity has been studied in eight human leukocyte cell lines in vitro (three, T-cells; three, B-cells; one, monocytic; one, promyelocytic), using a host cell reactivation assay with cisplatin-damaged pRSVcat. In the three T cell lines studied, host cell reactivation efficiency was directly related to the cells' abilities to repair cisplatin-damaged cellular DNA (correlation coefficient = 0.993). (ABSTRACT TRUNCATED AT 250 WORDS)
Combined Neuropeptide S and D-Cycloserine Augmentation Prevents the Return of Fear in Extinction-Impaired Rodents: Advantage of Dual versus Single Drug Approaches

Background: Despite its success in treating specific anxiety disorders, the effect of exposure therapy is limited by problems with tolerability, treatment resistance, and fear relapse after initial response. The identification of novel drug targets facilitating fear extinction in clinically relevant animal models may guide improved treatment strategies for these disorders in terms of efficacy, acceleration of fear extinction, and return of fear. Methods: The extinction-facilitating potential of neuropeptide S, D-cycloserine, and a benzodiazepine was investigated in extinction-impaired high anxiety HAB rats and 129S1/SvImJ mice using a classical cued fear conditioning paradigm followed by extinction training and several extinction test sessions to study fear relapse. Results: Administration of D-cycloserine improved fear extinction in extinction-limited, but not in extinction-deficient, rodents compared with controls. Preextinction neuropeptide S caused attenuated fear responses in extinction-deficient 129S1/SvImJ mice at extinction training onset and further reduced freezing during this session. While the positive effects of either D-cycloserine or neuropeptide S were not persistent in 129S1/SvImJ mice after 10 days, the combination of preextinction neuropeptide S with postextinction D-cycloserine rendered the extinction memory persistent and context independent up to 5 weeks after extinction training. This dual pharmacological adjunct to extinction learning also protected against fear reinstatement in 129S1/SvImJ mice. Conclusions: By using the potentially nonsedative anxiolytic neuropeptide S and the cognitive enhancer D-cycloserine to facilitate deficient fear extinction, we provide here the first evidence of a purported efficacy of a dual over a single drug approach. This approach may render exposure sessions less aversive and more efficacious for patients, leading to enhanced protection from fear relapse in the long term.
Configuration Of Near-Surface Shear-Wave Velocity By Inverting Surface Wave

The shear (S)-wave velocity of near-surface materials (such as soil, rocks, and pavement) and its effect on seismic wave propagation are of fundamental interest in many groundwater, engineering, and environmental studies. Ground roll is a Rayleigh-type surface wave that travels along or near the surface of the ground. Rayleigh wave phase velocity of a layered earth model is a function of frequency and four groups of earth parameters: S-wave velocity, P-wave velocity, density, and thickness of layers. Analysis of Jacobian matrix in a high frequency range (530 Hz) provides a measure of sensitivity of dispersion curves to earth model parameters. S-wave velocities are the dominant influence of the four earth model parameters. With the lack of sensitivity of the Rayleigh wave to P-wave velocities and densities, estimations of near-surface S-wave velocities can be made from high frequency Rayleigh wave for a layered earth model. An iterative technique applied to a weighted equation proved very effective when using the LevenbergMarquardt method and singular value decomposition techniques. The convergence of the weighted damping solution is guaranteed through selection of the damping factor of the Levenberg-Marquardt method. Three real world examples are presented in this paper. The first and second examples demonstrate the sensitivity of inverted S-wave velocities to their initial values, the stability of the inversion procedure, and/or accuracy of the inverted results. The third example illustrates the combination of a standard CDP (common depth point) roll-along acquisition format with inverting surface wave one shot gather by one shot gather to generate a cross section of S-wave velocity. The inverted S-wave velocities are confirmed by borehole data.
Curve skeleton skinning for human and creature characters

The skeleton driven skinning technique is still the most popular method for animating deformable human and creature characters. Albeit an industry de facto due to its computational performance and intuitiveness, it suffers from problems like collapsing elbow and candy wrapper joint. To remedy these problems, one needs to formulate the non‐linear relationship between the skeleton and the skin shape of a character properly, which however proves mathematically very challenging. Placing additional joints where the skin bends increases the sampling rate and is an ad hoc way of approximating this non‐linear relationship. In this paper, we propose a method that is able to accommodate the inherent non‐linear relationships between the movement of the skeleton and the skin shape. We use the so‐called curve skeletons along with the joint‐based skeletons to animate the skin shape. Since the deformation follows the tangent of the curve skeleton and also due to higher sampling rates received from the curve points, collapsing skin and other undesirable skin deformation problems are avoided. The curve skeleton retains the advantages of the current skeleton driven skinning. It is easy to use and allows full control over the animation process. As a further enhancement, it is also fairly simple to build realistic muscle and fat bulge effect. A practical implementation in the form of a Maya plug‐in is created to demonstrate the viability of the technique. Copyright © 2006 John Wiley & Sons, Ltd.
Segmentation of motion textures using mixed-state Markov random fields

The aim of this work is to model the apparent motion in image sequences depicting natural dynamic scenes (rivers, sea-waves, smoke, fire, grass etc) where some sort of stationarity and homogeneity of motion is present. We adopt the mixed-state Markov Random Fields models recently introduced to represent so-called motion textures. The approach consists in describing the distribution of some motion measurements which exhibit a mixed nature: a discrete component related to absence of motion and a continuous part for measurements different from zero. We propose several extensions on the spatial schemes. In this context, Gibbs distributions are analyzed, and a deep study of the associated partition functions is addressed. Our approach is valid for general Gibbs distributions. Some particular cases of interest for motion texture modeling are analyzed. This is crucial for problems of segmentation, detection and classification. Then, we propose an original approach for image motion segmentation based on these models, where normalization factors are properly handled. Results for motion textures on real natural sequences demonstrate the accuracy and efficiency of our method.
CORONAL IMPLOSION AND PARTICLE ACCELERATION IN THE WAKE OF A FILAMENT ERUPTION

We study the evolution of a group of TRACE 195 Å coronal loops overlying a reverse S-shaped filament on 2001 June 15. These loops were initially pushed upward with the filament ascending and kinking slowly, but as soon as the filament rose explosively, they began to contract at a speed of ∼100 km s−1, and sustained for at least 12 minutes, presumably due to the reduced magnetic pressure underneath with the filament escaping. Despite the contraction following the expansion, the loops of interest remained largely intact during the filament eruption, rather than formed via reconnection. These contracting loops naturally formed a shrinking trap, in which hot electrons of several keV, in an order of magnitude estimation, can be accelerated to nonthermal energies. A single hard X-ray (HXR) burst, with no corresponding rise in GOES soft X-ray (SXR) flux, was recorded by the Hard X-ray Telescope (HXT) on board Yohkoh, when the contracting loops expectedly approached the post-flare arcade originating from the filament eruption. HXT images reveal a coronal source distinctly above the top of the SXR arcade by ∼15″. The injecting electron population for the coronal source (thin target) is hardening by ∼1.5 powers relative to the footpoint emission (thick target), which is consistent with electron trapping in the weak diffusion limit. Although we cannot rule out additional reconnection, observational evidence suggests that the shrinking coronal trap may play a significant role in the observed nonthermal HXR emission during the flare decay phase.
Industry 4.0 with cyber-physical integration: A design and manufacture perspective

Foreseeing changes in the way companies manufacture products and provide services, future trends are emerging in design and manufacture. Together with growing internet applications and technologies connected through the cloud, a new Industrial Revolution, named “Industry 4.0”, aims to integrate cyber-virtual and cyber-physical systems to aid smart manufacturing, as presented in this paper. Connecting information and physical machinery, this new paradigm relies on how effective and fast connectivity are achieved for Industry 4.0. A new generation of wireless connection, 5G, will help and accelerate this trend. Following analysis of the present cyber-physical integration for the 4th Industrial Revolution, this paper also investigates future methodologies and trends in smart manufacturing, design and innovation.
Analysis of Spatio-chromatic Decorrelation for Colour Image Reconstruction

We investigate the implications of a unified spatiochromatic basis for image compression and reconstruction. Different adaptive and general methods (PCA, ICA, and DCT) are applied to generate bases. While typically such bases with spatial extent are investigated in terms of their correspondence to human visual perception, we are interested in their applicability to multimedia encoding. The performance of the extracted spatio-chromatic spatial patch bases is evaluated in terms of quality of reconstruction with respect to their potential for data compression. The results discussed here are intended to provide another path towards perceptually-based encoding of visual data. This leads to a deeper understanding of the role played by chromatic features in data reduction.
Range-Based Estimation of Stochastic Volatility Models

We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that range-based volatility proxies are not only highly efficient, but also approximately Gaussian and robust to microstructure noise. Hence range-based Gaussian quasi-maximum likelihood estimation produces highly efficient estimates of stochastic volatility models and extractions of latent volatility. We use our method to examine the dynamics of daily exchange rate volatility and find the evidence points strongly toward two-factor models with one highly persistent factor and one quickly mean-reverting factor. Copyright The American Finance Association 2002.
Norm Emergence via Influential Weight Propagation in Complex Networks

We propose an influence-based aggregative learning framework that facilitates the emergence of social norms in complex networks and investigate how a norm converges by learning through iterated local interactions in a coordination game. In society, humans decide to coordinate their behavior not only by exchanging information but also on the basis of norms that are often individually derived from interactions without a centralized authority. Coordination using norms has received much attention in studies of multi-agent systems. In addition, because agents often work as delegates of humans, they should have "mental" models about how to interact with others and incorporate differences of opinion. Because norms make sense only when all or most agents have the same one and they can expect that others will follow, it is important to investigate the mechanism of norm emergence through learning with local and individual interactions in agent society. Our method of norm learning borrows from the opinion aggregation process while taking into account the influence of local opinions in tightly coordinated human communities. We conducted experiments showing how our learning framework facilitates propagation of norms in a number of complex agent networks.
Increased Fos expression among midbrain dopaminergic cell groups during birdsong tutoring

During avian vocal learning, birds memorize conspecific song patterns and then use auditory feedback to match their vocal output to this acquired template. Some models of song learning posit that during tutoring, conspecific visual, social and/or auditory cues activate neuromodulatory systems that encourage acquisition of the tutor’s song and attach incentive value to that specific acoustic pattern. This hypothesis predicts that stimuli experienced during social tutoring activate cell populations capable of signaling reward. Using immunocytochemistry for the protein product of the immediate early gene c‐Fos, we found that brief exposure of juvenile male zebra finches to a live familiar male tutor increased the density of Fos+ cells within two brain regions implicated in reward processing: the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc). This activation of Fos appears to involve both dopaminergic and non‐dopaminergic VTA/SNc neurons. Intriguingly, a familiar tutor was more effective than a novel tutor in stimulating Fos expression within these regions. In the periaqueductal gray, a dopamine‐enriched cell population that has been implicated in emotional processing, Fos labeling also was increased after tutoring, with a familiar tutor again being more effective than a novel conspecific. As several neural regions implicated in song acquisition receive strong dopaminergic projections from these midbrain nuclei, their activation in conjunction with hearing the tutor’s song could help to establish sensory representations that later guide motor sequence learning.
Cache sharing using a Bloom filter in Named Data Networking

In Named Data Networking (NDN), routers have caches to store frequently requested contents, and hence cache management scheme becomes a key factor for efficient content delivery. In this paper, we propose the sharing of cache summaries using a Bloom filter among neighboring routers for efficient content delivery and high cache utilization at NDN. When an Interest packet is received, a router can forward the Interest to a neighboring router which has the high potential of the requested content. The proposed scheme is evaluated by using ndnSIM, which is a NS-3 based named data networking simulator. Simulation results show that the summary sharing using our proposed method is beneficial in content diversity and average content delivery time.
Institutional Coordination in the UK: The Strengths and Weaknesses of a Variable System

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Coverage of a microarchitecture-level fault check regimen in a superscalar processor

Conventional processor fault tolerance based on time/space redundancy is robust but prohibitively expensive for commodity processors. This paper explores an unconventional approach to designing a cost-effective fault-tolerant superscalar processor. The idea is to engage a regimen of microarchitecture-level fault checks. A few simple microarchitecture-level fault checks can detect many arbitrary faults in large units, by observing microarchitecture-level behavior and anomalies in this behavior. Previously, we separately proposed checks for the fetch and decode stages, rename stage, and issue stage of a contemporary superscalar processor. While each piece hinted at the possibility of a complete regimen - for an overall fault-tolerant superscalar processor - this totality was not explored. This paper provides the culmination by building a full regimen into a superscalar processor. We show for the first time that the regimen-based approach provides substantial coverage of an entire superscalar processor. Analysis reveals vulnerable areas which should be the focus for regimen additions.
Girdled versus Bark Beetle-created Ponderosa Pine Snags: Utilization by Cavity-dependent Species and Differences in Decay Rate and Insect Diversity 1

Snags are a natural component of forest ecosystems and provide a variety of functions and values to forests and their constituents. Snags provide important feeding substrates, nesting sites, and habitat for a variety of invertebrates and vertebrates, and many of these functions continue after the snag eventually falls and becomes a log (coarse woody debris). Some forest landscapes are thought to be “snag deficient” for wildlife needs because of the direct action of forest managers or because of natural events such as winter storms or fire. Therefore, it is not unusual for forest managers to desire to create snags by various means. In this study we compared snags created by mechanical girdling (chainsaw) and bark beetle (western pine beetle aggregation pheromone) attack to determine acceptability and suitability to cavity dependent species, tree decomposition characteristics, and insect diversity. After 6 years we have found differences in the rate of deterioration (tree fading rates, branchlet retention, bole failure, top breakage, bark sloughing), woodpecker feeding activity, cavity excavation, and insect diversity. Our data indicate that bark beetle-killed trees provide a more biologically rich snag that is both suitable and acceptable to cavity dependent species.