Today's heterogeneous networks comprised of mostly macrocells and indoor small cells will not be able to meet the upcoming traffic demands. Indeed, it is forecasted that at least a 100\times network ...capacity increase will be required to meet the traffic demands in 2020. As a result, vendors and operators are now looking at using every tool at hand to improve network capacity. In this epic campaign, three paradigms are noteworthy, i.e., network densification, the use of higher frequency bands and spectral efficiency enhancement techniques. This paper aims at bringing further common understanding and analysing the potential gains and limitations of these three paradigms, together with the impact of idle mode capabilities at the small cells as well as the user equipment density and distribution in outdoor scenarios. Special attention is paid to network densification and its implications when transiting to ultra-dense small cell deployments. Simulation results show that comparing to the baseline case with an average inter site distance of 200 m and a 100 MHz bandwidth, network densification with an average inter site distance of 35 m can increase the average UE throughput by 7.56\times, while the use of the 10 GHz band with a 500 MHz bandwidth can further increase the network capacity up to 5\times, resulting in an average of 1.27 Gbps per UE. The use of beamforming with up to 4 antennas per small cell BS lacks behind with average throughput gains around 30% and cell-edge throughput gains of up to 2\times. Considering an extreme densification, an average inter site distance of 5 m can increase the average and cell-edge UE throughput by 18\times and 48\times, respectively. Our study also shows how network densification reduces multi-user diversity, and thus proportional fair alike schedulers start losing their advantages with respect to round robin ones. The energy efficiency of these ultra-dense small cell deployments is also analysed, indicating the benefits of energy harvesting approaches to make these deployments more energy-efficient. Finally, the top ten challenges to be addressed to bring ultra-dense small cell deployments to reality are also discussed.
We discuss application of methods from the Kraichnan model of turbulent advection to the study of non-equilibrium concentration fluctuations arising during diffusion in liquid mixtures at high ...Schmidt numbers. This approach treats nonlinear advection of concentration fluctuations exactly, without linearization. Remarkably, we find that static and dynamic structure functions obtained by this method reproduce precisely the predictions of linearized fluctuating hydrodynamics. It is argued that this agreement is an analogue of anomaly non-renormalization which does not, however, protect higher-order multi-point correlations. The latter should thus yield non-vanishing cumulants, unlike those for the Gaussian concentration fluctuations predicted by linearized theory.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Global efforts for engineering desired materials which are able to treat the water sources still are ongoing in the bench level methods. Considering adsorbent and photocatalytic materials as the main ...reliable candidates still are encountering with struggles because of many challenges that restrict their large-scale application. This review comprehensively considered the recent advanced materials water treatment methods which involve to magnetic, activated carbon, carbon nanotubes (CNTs), graphene (G), graphene oxide (GO), (Graphene) quantum dots, carbon nanorods, carbon nano-onions, and reduced graphene oxide (RGO), zeolite, silica and clay-based nanomaterials. The adsorption and photocatalytic properties of these nanomaterials introduced them as highly potent option for heavy metal ions and organic dyes removal and photocatalytic degradation. High specific surface area in conjugation with presenting higher kinetics of adsorption and decomposition are the main characteristics of these materials which make them appropriate to treat wastewater even in ultralow concentration of the pollutants. Considering the mechanistic aspects of the adsorption and photocatalytic decomposition process, challenges and opportunities were other subjects that have been highlighted for the discussed nanomaterials. In term of the adsorption approaches, the mechanism of adsorptions and their influence on the maximum adsorption capacity were discussed and also for photocatalyst approach the radical active spices and their role in kinetic and efficiency of the organic pollutant decomposition were provided a deep discussion.
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•Adsorption and photodegradation approaches can be as efficient methods for water treatment.•In adsorption approach, nanomaterials can adsorb heavy metal ions and dye pollutants.•In photocatalytic methods, the organic dyes can degrade under light irradiation condition.•High adsorption capacity and photocatalytic reaction efficiency are the main advantages of these methods.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
6.
Magnetic Field Transport in Accretion Disks Jafari, Amir; Vishniac, Ethan T.
Astrophysical journal/The Astrophysical journal,
02/2018, Volume:
854, Issue:
1
Journal Article
Peer reviewed
Open access
The leading models for launching astrophysical jets rely on strong poloidal magnetic fields threading the central parts of their host accretion disks. Numerical simulations of magneto-rotationally ...turbulent disks suggest that such fields are actually advected from the environment by the accreting matter rather than generated by internal dynamos. This is puzzling from a theoretical point of view, since the reconnection of the radial field across the midplane should cause an outward drift on timescales much shorter than the accretion time. We suggest that a combination of effects are responsible for reducing the radial field near the midplane, causing efficient inward advection of the poloidal field. Magnetic buoyancy in subsonic turbulence pushes the field lines away from the midplane, decreasing the large-scale radial field in the main body of the disk. In magneto-rotationally driven turbulence, magnetic buoyancy dominates over the effects of turbulent pumping, which works against it, and turbulent diamagnetism, which works with it, in determining the vertical drift of the magnetic field. Balancing buoyancy with diffusion implies that the bending angle of the large-scale poloidal field can be very large near the surface, as required for outflows, but vanishes near the midplane, which impedes turbulent reconnection and outward diffusion. This effect becomes less efficient as the poloidal flux increases. This suggests that accretion disks are less likely to form jets if they have a modest ratio of outer to inner radii or if the ambient field is very weak. The former effect is probably responsible for the scarcity of jets in cataclysmic variable systems.
Homomorphic (resp. abelian) secret sharing is a generalization of ubiquitous linear secret sharing in which the secret value and the shares are taken from finite (resp. abelian) groups instead of ...vector spaces over a finite field. Homomorphic secret sharing was first defined by Benaloh and, later in the early nineties, Frankel and Desmedt presented some relevant results. Except for a few other related topics such as black-box secret sharing and secret sharing over rings, the subject has remained dormant for about three decades. The study of homomorphic secret sharing is resumed in this paper and three main results are presented: (1) mixed-linear schemes, a subclass of abelian schemes to be introduced in this paper, are more powerful than linear schemes in terms of the best achievable information ratio (the claim is proved for the port of a well-known almost entropic matroid), (2) the information ratios of dual access structures are equal for the class of abelian schemes and (3) every ideal homomorphic scheme can be transformed into an ideal linear scheme with the same access structure.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Internal physiological states influence behavioral decisions. We have investigated the underlying cellular and molecular mechanisms at the first olfactory synapse for starvation modulation of ...food-search behavior in Drosophila. We found that a local signal by short neuropeptide F (sNPF) and a global metabolic cue by insulin are integrated at specific odorant receptor neurons (ORNs) to modulate olfactory sensitivity. Results from two-photon calcium imaging show that starvation increases presynaptic activity via intraglomerular sNPF signaling. Expression of sNPF and its receptor (sNPFR1) in Or42b neurons is necessary for starvation-induced food-search behavior. Presynaptic facilitation in Or42b neurons is sufficient to mimic starvation-like behavior in fed flies. Furthermore, starvation elevates the transcription level of sNPFR1 but not that of sNPF, and insulin signaling suppresses sNPFR1 expression. Thus, starvation increases expression of sNPFR1 to change the odor map, resulting in more robust food-search behavior.
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► Starvation reshapes olfactory representation in the antennal lobe ► Activation of sNPF receptors upon starvation sensitizes select sensory neurons ► Insulin is a global satiety signal to suppress sNPFR1 expression ► Starvation modulation of Or42b sensory neurons promotes food-search behavior
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Cortico-muscular interactions play important role in sensorimotor control during motor task and are commonly studied by cortico-muscular coherence (CMC) method using joint ...electroencephalogram-surface electromyogram (EEG-sEMG) signals. As noise and time delay between the two signals weaken the CMC value, coupling difference between non-task sEMG channels is often undetectable. We used sparse representation of EEG channels to compute CMC and detect coupling for task-related and non-task sEMG signals. High-density joint EEG-sEMG (53 EEG channels, 4 sEMG bipolar channels) signals were acquired from 15 subjects (30.26 ± 4.96 years) during four specific hand and foot contraction tasks (2 dynamic and 2 static contraction). Sparse representations method was applied to detect projection of EEG signals on each sEMG channel. Bayesian optimization was employed to select best-fitted method with tuned hyperparameters on the input feeding data while using 80% data as the train set and 20% as test set. K-fold (K = 5) cross-validation method was used for evaluation of trained model. Two models were trained separately, one for CMC data and the other from sparse representation of EEG channels on each sEMG channel. Sensitivity, specificity, and accuracy criteria were obtained for test dataset to evaluate the performance of task-related and non-task sEMG channels detection. Coupling values were significantly different between grand average of task-related compared to the non-task sEMG channels (Z = -6.33, p< 0.001, task-related median = 2.011, non-task median = 0.112). Strong coupling index was found even in single trial analysis. Sparse representation approach (best fitted model: SVM, Accuracy = 88.12%, Sensitivity = 83.85%, Specificity = 92.45%) outperformed CMC method (best fitted model: KNN, Accuracy = 50.83%, Sensitivity = 52.17%, Specificity = 49.47%). Sparse representation approach offers high performance to detect CMC for discerning the EMG channels involved in the contraction tasks and non-tasks.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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