Miracle-dz/UniFAR-FTUs huggingface dataset:
State-Dependent Proportional Fair Scheduling Algorithms for Wireless Forward Link Data Services

For wireless forward link data services, the proportional fair algorithm (PFA) incorporating opportunistic scheduling was originally designed to maintain service fairness among users as well as to exploit channel fluctuations in fading environments. The operation of PFA necessitates throughput monitoring for each user, in general through exponentially smoothing received services. In the paper, we adapt the PFA for use in more generic traffic conditions where the number of active users may change with time and data for a user may arrive intermittently. Our approach is not only to simply stop throughput monitoring for idle users but also to further accommodate in throughput monitoring changes in the number of active users. Moreover, we use in throughput monitoring different smoothing factors depending on the state of backlogged data loads, in order to exploit the variation of multiuser diversity gain. Consequently, our PFA, taking into account both channel state and system queue fluctuations, presents several favorable performance features.
A hidden Markov model information retrieval system

We present a new method for information retrieval using hidden Markov models (HMMs). We develop a general framework for incorporating multiple word generation mechanisms within the same model. We then demonstrate that an extremely simple realization of this model substantially outperforms standard tf :idf ranking on both the TREC-6 and TREC-7 ad hoc retrieval tasks. We go on to present a novel method for performing blind feedback in the HMM framework, a more complex HMM that models bigram production, and several other algorithmic re nements. Together, these methods form a state-of-the-art retrieval system that ranked among the best on the TREC-7 ad hoc retrieval task.
Towards manifold learning for gamebot behavior modeling

Traditionally Computer Game Agent behaviors are generated by top-down approaches like finite state machines or scripts. So far, however, this had only mediocre success in creating life-like impressions. The bottom-up approach of imitation learning for agents has become very popular in recent robotics research and, in earlier work, we already discussed how imitation learning may apply to the programming of life-like computer game characters. However, so far we ignored problems concerning high dimensional state spaces for the most part, although behavior execution and learning takes place in such spaces.In this paper, we investigate the usage of non-linear dimensionality reduction for gamedata. We therefore focus on the aspect of topological gameworld representations and their dimensionality reduced counterparts. Dimensionality reduction is achieved by learning manifolds using Locally Linear Embedding. A mapping between data and embedding space is realized by Radial Basis Function interpolators. Experiments focus on movement path calculation and comparison in 3D and 2D embedding space world representations. The results indicate certain problems inherent to this approach but nevertheless justify further investigations.
Nonexistence of simple hyperbolic blow-up for the quasi-geostrophic equation

The problem we are concerned with is whether singularities form in finite time in incompressible fluid flows. It is well known that the answer is "no" in the case of Euler and Navier-Stokes equations in dimension two. In dimension three it is still an open problem for these equations. In this paper we focus on a two-dimensional active scalar model for the 3D Euler vorticity equation. Constantin, Majda and Tabak [7] suggested, by studying rigorous theorems and detailed numerical experiments, a general principle: "If the level set topology in the temperature field for the 2D quasi-geostrophic active scalar in the region of strong scalar gradients does not contain a hyperbolic saddle, then no finite time singularity is possible. " Numerical simulations showed evidence of singular behavior when the geometry of the level sets of the active scalar contain a hyperbolic saddle. There is a naturally associated notion of simple hyperbolic saddle breakdown. The main theorem we present in this paper shows that such breakdown cannot occur in finite time. We also show that the angle of the saddle cannot close in finite time and it cannot be faster than a double exponential in time. Using the same techniques, we see that analogous results hold for incompressible 2D and 3D Euler. These results were announced in [9], but with a slight difference in the definition of a simple hyperbolic saddle. The definition given in Section 4 generalizes the one given in the announcement. See also Constantin [4], discussed in Section 7, Remark 5 below. The whole work described in this paper is basically part of the author's thesis. I am particularly grateful to my thesis advisor Charles Fefferman for his attention, support, guidance and advice. I am indebted to D. Christodoulou and P. Constantin for helpful corrections and suggestions. I wish to thank A. Majda for suggesting the subject and E. Tabak for discussions and com-
Autonomic thread scaling library for QoS management

Over the last years embedded system industry faced a revolution thanks to the introduction of multicores and heterogeneous devices. The availability of these new platforms opens new paths for these devices that can be nowadays used for more high demand tasks, exploiting the parallelism made available by the muticore processors. Nonetheless the progresses of the HW technology are not backed up by improvements of the SW side, and runtime mechanisms to manage resource allocation and contention on resources are still lacking the proper effectiveness. This paper tackles the problem of dynamic resource management from the application point of view and presents a user space library to control application performance. The control knob exploited by the library is the possibility of scaling the number of threads used by an application and seamlessly integrates with OpenMP. A case study illustrates the benefits that this library has in a classic embedded system scenario, introducing an overhead of less than 0.5%.
Anaerobic capacity determined by maximal accumulated O2 deficit.

We present a method for quantifying the anaerobic capacity based on determination of the maximal accumulated O2 deficit. The accumulated O2 deficit was determined for 11 subjects during 5 exhausting bouts of treadmill running lasting from 15 s to greater than 4 min. The accumulated O2 deficit increased with the duration for exhausting bouts lasting up to 2 min, but a leveling off was found for bouts lasting 2 min or more. Between-subject variation in the maximal accumulated O2 deficit ranged from 52 to 90 ml/kg. During exhausting exercise while subjects inspired air with reduced O2 content (O2 fraction = 13.5%), the maximal O2 uptake was 22% lower, whereas the accumulated O2 deficit remained unchanged. The precision of the method is 3 ml/kg. The method is based on estimation of the O2 demand by extrapolating the linear relationship between treadmill speed and O2 uptake at submaximal intensities. The slopes, which reflect running economy, varied by 16% between subjects, and the relationships had to be determined individually. This can be done either by measuring the O2 uptake at a minimum of 10 different submaximal intensities or by two measurements close to the maximal O2 uptake and by making use of a common Y-intercept of 5 ml.kg-1.min-1. By using these individual relationships the maximal accumulated O2 deficit, which appears to be a direct quantitative expression of the anaerobic capacity, can be calculated after measuring the O2 uptake during one exhausting bout of exercise lasting 2-3 min.
Natural Language Processing : A Model to Predict a Sequence of Words

With the growth of social media, the value of text-based information continues to increase. It is difficult to analyze a large corpus of text to discover the structure within the data using computational methods. Alan Turing (1950) opens his influential article "Computing Machinery and Intelligence" with the statement, "I propose to consider the question, 'Can machines think? '" (p. 433). Overall, this Turing Test has become a basis of natural language processing. The essence of this project is to take a corpus of text and build a predictive model to present a user with a prediction of the next likely word based on their input. A key aspect of the paper is discussion of techniques balancing accuracy and scalability for large data sets. This paper provides the analysis decisions used to develop that predictive text model for a corpus of over 500,000 blog articles. The resultant model exists as a web-based data product that allows for customizable user reporting. Additionally, the work presented in this project follows the tenets of reproducible research and all code is available in an open-source repository to enable readers to review the approach, reproduce the results, and collaborate to enhance the model.
A new periplasmic protein of Escherichia coli which is synthesized in spheroplasts but not in intact cells

The gene spy from Escherichia coli has been cloned and sequenced. It encodes a precursor of a so far unknown 139-residue, rather basic periplasmic protein. It was not detectable immunologically in intact cells but was produced abundantly in spheroplasts. It could be a stress protein specific for spheroplasting.
SAR image denoising: a multiscale robust statistical approach

Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the coherent nature of the scattering phenomenon. It appears sensible to reduce speckle in SAR images, provided that the structural features and textural information are not lost. We present a novel speckle removal algorithm within the framework of wavelet analysis. First, we show that the subband decompositions of logarithmically transformed SAR images are best described by alpha-stable distributions, a family of heavy-tailed densities. Consequently, we design a maximum a posteriori (MAP) estimator that exploits this a priori information. We use the alpha-stable model to develop a blind speckle-suppression processor that performs a non-linear operation on the data, and we relate this non-linearity to the degree of non-Gaussianity of the data. Finally, we compare our proposed method to a current state-of-the-art soft thresholding technique applied on an aerial image and we quantify the achieved performance improvement.
Learning to Generate with Memory

Memory units have been widely used to enrich the capabilities of deep networks on capturing long-term dependencies in reasoning and prediction tasks, but little investigation exists on deep generative models (DGMs) which are good at inferring high-level invariant representations from unlabeled data. This paper presents a deep generative model with a possibly large external memory and an attention mechanism to capture the local detail information that is often lost in the bottom-up abstraction process in representation learning. By adopting a smooth attention model, the whole network is trained end-to-end by optimizing a variational bound of data likelihood via auto-encoding variational Bayesian methods, where an asymmetric recognition network is learnt jointly to infer high-level invariant representations. The asymmetric architecture can reduce the competition between bottom-up invariant feature extraction and top-down generation of instance details. Our experiments on several datasets demonstrate that memory can significantly boost the performance of DGMs on various tasks, including density estimation, image generation, and missing value imputation, and DGMs with memory can achieve state-of-the-art quantitative results.
A CMOS elliptic low-pass switched capacitor ladder filter for video communication using bilinear implementation

This paper presents an approach to design of high frequency switched capacitor filters for video communication networks. In the case of low OSR, using common methods reduces the SNDR and accuracy of the filter. Bilinear implementation techniques are applied to an untried fifth-order elliptic SC filter, and are simulated in a 0.35 /spl mu/m CMOS technology. Cutoff frequency of the filter is 3.6 MHz and with bilinear implementation, we achieve 72 dB SFDR, 62 dB THD and stop band attenuation greater than -30 dB. All the capacitors are scaled down in order to reduce the settling time of the amplifiers. The circuit operates with +3 V supply and typically dissipates 15 mW when sampled at 18 MHz and has full swing about 1.8 V.
Système de déploiement d'un robot mobile autonome basé sur des balises

Cette these s’inscrit dans le cadre d’un projet visant a developper un robot mobile autonome capable de realiser des tâches specifiques dans une zone prealablement definie par l’utilisateur. Afin de faciliter la mise en œuvre du systeme, des balises radiofrequences fournissant des mesures de distance par rapport au robot sont disposees au prealable autour du terrain. Le deploiement du robot s’effectue en deux phases, une premiere d’apprentissage du terrain, puis une seconde, ou le robot effectue ses tâches de facon autonome. Ces deux etapes necessitent de resoudre les problemes de localisation et de localisation et cartographie simultanees pour lesquels differentes solutions sont proposees et testees en simulation et sur des jeux de donnees reelles. De plus, afin de faciliter l’installation et d’ameliorer les performances du systeme, un algorithme de placement des balises est presente puis teste en simulation afin de valider notamment l’amelioration des performances de localisation.
Estimating scattering mechanism at oyster farm site by polarimetry SAR

-Tide height in coastal area are possible to measure by using interferometric phase and intensity of SAR data. This SAR technique for measuring the tide height within a near coastal zone can be applied to double bounce dominant area. In this paper, we investigate the backscattering characteristics of the oyster farm structures. Laboratory experiments were carried out using Ku-band according to the target scale. Radar returns from vertical poles are stronger than those from horizontal poles by 10.5 dB. Single bounce components were as strong as double bounce components and more sensitive to antenna look direction. Double bounce components show quasi-linear relation with height of vertical poles, which implies double bounce is more useful to determine water level than total power. L-band NASA/JPL airborne SAR (AIRSAR) image was classified into single bounce and double bounce, and volume scattering. It is observed that not all oyster farms are characterized by double bounced scattering. The image intensity of the double bounce dominant oyster farm was investigated with respect to that of oyster farm dominated by single bounce in JERS-1 SAR data. The image intensity model results in a correlation coefficient of, R2 , 0.78 in double bounce dominant area while that of 0.54 in single bouncing dominant area. This shows that double bounce dominant area should be selected for water height measurement using InSAR technique. Keywords-component; tide height, AIRSAR, double bounce, image intensity, sea farms.
Analyzing focal adhesion structure by atomic force microscopy

Atomic force microscopy (AFM) can produce high-resolution topographic images of biological samples in physiologically relevant environments and is therefore well suited for the imaging of cellular surfaces. In this work we have investigated focal adhesion complexes by combined fluorescence microscopy and AFM. To generate high-resolution AFM topographs of focal adhesions, REF52 (rat embryo fibroblast) cells expressing YFP-paxillin as a marker for focal adhesions were de-roofed and paxillin-positive focal adhesions subsequently imaged by AFM. The improved resolution of the AFM topographs complemented the optical images and offered ultrastructural insight into the architecture of focal adhesions. Focal adhesions had a corrugated dorsal surface formed by microfilament bundles spaced 127±50 nm (mean±s.d.) apart and protruding 118±26 nm over the substratum. Within focal adhesions microfilaments were sometimes branched and arranged in horizontal layers separated by 10 to 20 nm. From the AFM topographs focal adhesion volumes could be estimated and were found to range from 0.05 to 0.50 μm3. Furthermore, the AFM topographs show that focal adhesion height increases towards the stress-fiber-associated end at an angle of about 3°. Finally, by correlating AFM height information with fluorescence intensities of YFP-paxillin and F-actin staining, we show that the localization of paxillin is restricted to the ventral half of focal adhesions, whereas F-actin-containing microfilaments reside predominantly in the membrane-distal half.
Comparative immunogenetics of autism and schizophrenia

Autism and schizophrenia are highly heritable neurodevelopmental disorders, each mediated by a diverse suite of genetic and environmental risk factors. Comorbidity and familial aggregation of such neurodevelopmental disorders with other disease‐related conditions can provide important insights into their etiology. Epidemiological studies have documented reduced rates of rheumatoid arthritis, a systemic autoimmune condition, in schizophrenia, and recent work has shown increased rates of rheumatoid arthritis in first‐degree relatives of autistic individuals, especially mothers. Advances in understanding the genetic basis of rheumatoid arthritis have shown that much of the genetic liability to this condition is due to risk and protective alleles at the HLA DRB1 locus. These data allow robust testing of the hypotheses that allelic variation at DRB1 pleiotropically modulates risk of rheumatoid arthritis, autism and schizophrenia. Systematic review of the literature indicates that reported associations of DRB1 variants with these three conditions are congruent with a pleiotropic model: DRB1*04 alleles have been associated with increased risk of rheumatoid arthritis and autism but decreased risk of schizophrenia, and DRB1*13 alleles have been associated with protection from rheumatoid arthritis and autism but higher risk of schizophrenia. These convergent findings from genetics and epidemiology imply that a subset of autism and schizophrenia cases may be underlain by genetically based neuroimmune alterations, and that analyses of the causes of risk and protective effects from DRB1 variants may provide new approaches to therapy.
Sequential use of biologic therapy in rheumatoid arthritis

Purpose of reviewWith an increasing range of biological therapies available in the management of rheumatoid arthritis, sequencing of such therapies is becoming more frequent, particularly with more ambitious treatment aims. This review will address the evidence to date on use of successive targeted agents. Recent findingsDouble-blind, randomized controlled trials have confirmed the role of alternative tumour necrosis factor (TNF) inhibitors (TNFi), rituximab, abatacept and tocilizumab, following TNFi failure with no comparative studies to date. Registry data have demonstrated efficacy of switching from a first to a second TNFi. Observational experience has confirmed benefits of switching from TNFi to TNFi and TNFi to rituximab. Within available randomized controlled trial data, tocilizumab appears effective in TNFi failure group, irrespective of number of TNFi previously failed with similar data on abatacept. No safety signals have been identified thus far with biologic sequencing. Although formal comparative, controlled studies do not exist, type of previous failure to TNFi and disease characteristics (serology, comorbidity, concomitant therapy) can provide a good platform for choosing the next biologic treatment. SummaryAlthough biological sequencing is well established, optimal approach represents a significant knowledge gap; well designed clinical studies with associated mechanistic investigation are necessary to identify disease subgroups that would benefit from one sequence over another.
Mathematical Model of the Pharmacokinetic Behavior of Warfarin

The current study is a companion piece of an earlier study by Colburn published in August 1983 Issue of the Journal of Pharmacokinetics and Biopharmaceutics; therefore the data published in the study cited here were used. For modeling purposes, an advanced mathematical modeling method based on the theory of dynamic systems was employed. The modeling method employed, has been introduced to pharmacokinetics in the study by Dedík et al. entitled: “Estimation of influence of gastric emptying on shape of glucose concentration-time profile measured in oral glucose tolerance test”, published in September 2007 Issue of the journal Diabetes Research and Clinical Practice. The goal of the current study was to continue presenting some interesting views on a successful use of an advanced mathematical modeling method based on the theory of dynamic systems in a pharmacokinetic study. The mathematical model of the pharmacokinetic behavior of warfarin was developed using the data from the study cited above. The mathematical model developed successfully described the pharmacokinetic behavior warfarin in the subject described in the study by Colburn.
Lidar scan feature for localization with highly precise 3-D map

In recent years, automated vehicle researches move on to the next stage, that is auto-driving experiments on public roads. Major challenge is how to robustly drive at complicated situations such as narrow or non-featured road. In order to realize practical performance, some static information should be kept on memory such as road topology, building shape, white line, curb, traffic light and so on. Currently, some measurement companies have already begun to prepare map database for automated vehicles. They are able to provide highly-precise 3-D map for robust automated driving. This study focuses on what kind of data should be observed during automated driving with such precise database. In particular, we focus on the accurate localization based on the use of lidar data and precise 3-D map, and propose a feature quantity for scan data based on distribution of clusters. Localization experiment shows that our method can measure surrounding uncertainty and guarantee accurate localization.
Impact of Background Magnetic Field for EMIC Wave‐Driven Electron Precipitation

Wave‐particle interaction between relativistic electrons and electromagnetic ion cyclotron (EMIC) waves is a highly debated loss process contributing to the dynamics of Earth's radiation belts. Theoretical studies show that EMIC waves can result in strong loss of relativistic electrons in the radiation belts (Summers & Thorne, 2003, https://doi.org/10.1029/2002JA009489). However, many of these studies have not been validated by observations. Li et al. (2014, https://doi.org/10.1002/2014GL062273) modeled the relativistic electron precipitation observed by Balloon Array for Radiation belt Relativistic Electron Losses (BARREL) in a single‐event case study based on a quasi‐linear diffusion model and observations by Van Allen Probes and GOES 13. We expand upon that study to investigate the localization of the precipitation region and the effectiveness of EMIC waves as an electron loss mechanism.The model results of BARREL 1I observations on 17 January 2013 show that as the BARREL balloon drifts in local time to regions that map to lower equatorial magnetic field strength, the flux of precipitating electrons increases and peaks at lower energy. The hypothesis that the energy of the precipitating electrons is controlled by background magnetic field strength is further tested by considering observations from balloon campaigns conducted from 2000 to 2014, including BARREL. Consistent with theory for wave‐particle interaction between relativistic electrons and EMIC waves, we find observationally that stronger equatorial magnetic field strength generally correlates with more energetic electron precipitation and further conclude that magnetic field strength can drive the localization and distribution of precipitating electrons.