Network Slicing Based 5G and Future Mobile Networks: Mobility, Resource Management, and Challenges

5G networks are expected to be able to satisfy users' different QoS requirements. Network slicing is a promising technology for 5G networks to provide services tailored for users' specific QoS demands. Driven by the increased massive wireless data traffic from different application scenarios, efficient resource allocation schemes should be exploited to improve the flexibility of network resource allocation and capacity of 5G networks based on network slicing. Due to the diversity of 5G application scenarios, new mobility management schemes are greatly needed to guarantee seamless handover in network-slicing-based 5G systems. In this article, we introduce a logical architecture for network-slicing-based 5G systems, and present a scheme for managing mobility between different access networks, as well as a joint power and subchannel allocation scheme in spectrum-sharing two-tier systems based on network slicing, where both the co-tier interference and cross-tier interference are taken into account. Simulation results demonstrate that the proposed resource allocation scheme can flexibly allocate network resources between different slices in 5G systems. Finally, several open issues and challenges in network-slicing-based 5G networks are discussed, including network reconstruction, network slicing management, and cooperation with other 5G technologies

Human System Engineering Applications from Distracted Driving Simulations

Most of the studies to explore the impact of distracted driving have been descriptive in nature; i.e. the research is conducted in naturalistic settings to evaluate the performance of the driver with and without distracters. However simulation models can also be used that predict the workload for driving tasks. Using concepts from process modeling, baseline models of driving tasks can be created for different driving sequences that include the associated fine motor, visual and cognitive human resources. These models can then be used to evaluate incidents of workload overload caused by different distracters, from both the internal and external vehicle environment. Identifying specific overloaded resources can lead to mitigation strategies to reduce workload and minimize distracted driving. Lessons learned from distracted driving research can then be applied to evaluation other types of manual, visual, and cognitive intensive tasks. Identifying combinations of tasks that contribute to peak workload of operators, and then simulating the impact of multi-tasking using personal devices (i.e. cell phones) can lead to management insights for other types of work environments. Additionally, iterative modeling can also include the impact of sensors and alerts, as well as enhanced workstation displays. Individual component overload can help understand causes for performance detriments during different task sequences, and the impact of additional types of technologies and activities. Using the simulation analysis, the impact on overall workload, identification of peak workload occurrences, and specific overloaded resources can lead to mitigation strategies to reduce workload and improve operator performance

A Comparative Study Between Weighing and Image Analysis Techniques for Predicting the Amount of Deposited Electrospun Nanofibres

Weighing and direct measurement are currently the two most common techniques used for estimating the amount of deposited nanofibres in electrospinning process. Nevertheless, due to its extremely small fibre size and mass, the task of measuring the weight or thickness of an electrospun nanofibres membrane is difficult and the results are arguable. This study evaluates the effectiveness of using greyscale image analysis for predicting the amount of deposited nanofibres compared to weighing technique. Polyvinyl alcohol electrospun nanofibres were collected at different deposition times on A4 black paper substrates. The substrates were weighed before and after deposition process and then scanned into 8 bit greyscale images. Analyses were carried out using ImageJ software, statistical analysis, high speed camera and scanning electron microscopy. At long deposition times, both techniques showed significant correlations between the measured values and deposition times. However, at short deposition times the weighing technique was found unreliable (p>0.05) compared to image analysis technique due to insignificant fibre masses compared to the weight variation of the substrates. Results suggest that image analysis technique was a better option to be used compared to weighing technique. This technique has the potential to be used as an automated online quality control in electrospun nanofibres manufacture

An investigation of using grey scale image analysis for predicting the amount of deposited electrospun nanofibres

When electrospinning, the amount of electrospun fibres deposited is difficult to determine due to the extremely small size and light weight of the fibres. Several methods have been used to predict the amount of deposited fibres including weighing, imaging and direct measurement. Although these methods work to a certain extent, they all have drawbacks that make them unsuitable for commercial scale process control. The methods are generally time consuming, destructive and only examine a small area of web. In this study, an image analysis method is used to predict the amount of electrospun fibres deposited over a significant area. When images of electrospun fibres are converted into grey scale images, it is suggested that the amount of fibres deposited can be predicted by measuring the grey scale intensity. A conventional weighing method was used to validate the image analysis results. The weighing method was found wanting when the deposition time was short (p>0.05). This was because the measured fibre masses were insignificant compared to the weight variation of the collector substrates. Statistical analyses showed that there were a strong correlation between grey scale intensity and deposition time especially at short deposition times. The results suggest that image analysis method could be used to predict the amount of deposited electrospun nanofibres. Further test on different polymers and different coloured substrates showed that the method was still capable to distinguish the samples. The developed method has the potential to be applied as an in-line non-destructive quality control method for electrospun fibre manufacture

A new synthesis route for sustainable gold copper utilization in direct formic acid fuel cells

In the efforts to develop a more sustainable energy mix there is an urgent need to develop new materials for environmentally friendly processes. Developing low metal loading anode catalyst with high electrocatalytic activity for liquid fuel cells remains a great challenge. Polyvinylpyrrolodoneprotected AuCu-C core-shell was fabricated by a facile one-pot modified chemical reduction method. The nanoparticles were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), and atomic force microscopy (AFM) analyses. XRD analysis indicates the preferential orientation of catalytically active (111) planes in AuCu-C core-shell nanoparticles. The inclusion of Cu in the AuCuC catalysts increased catalytic activities, which can be attributed to the increases lattice parameters. Comparative results show that AuCu-C catalyst exhibited much better electrocatalytic activity and stabilization compared to commercial Au nanoparticle on carbon support catalyst. The high performance of AuCu-C catalyst may be attributed to the electronic coupling or synergistic interaction between Cu core structure, and the Au shell makes it a promising for DFAFCs application

Magnetic fields in supernova remnants and pulsar-wind nebulae

We review the observations of supernova remnants (SNRs) and pulsar-wind nebulae (PWNe) that give information on the strength and orientation of magnetic fields. Radio polarimetry gives the degree of order of magnetic fields, and the orientation of the ordered component. Many young shell supernova remnants show evidence for synchrotron X-ray emission. The spatial analysis of this emission suggests that magnetic fields are amplified by one to two orders of magnitude in strong shocks. Detection of several remnants in TeV gamma rays implies a lower limit on the magnetic-field strength (or a measurement, if the emission process is inverse-Compton upscattering of cosmic microwave background photons). Upper limits to GeV emission similarly provide lower limits on magnetic-field strengths. In the historical shell remnants, lower limits on B range from 25 to 1000 microGauss. Two remnants show variability of synchrotron X-ray emission with a timescale of years. If this timescale is the electron-acceleration or radiative loss timescale, magnetic fields of order 1 mG are also implied. In pulsar-wind nebulae, equipartition arguments and dynamical modeling can be used to infer magnetic-field strengths anywhere from about 5 microGauss to 1 mG. Polarized fractions are considerably higher than in SNRs, ranging to 50 or 60% in some cases; magnetic-field geometries often suggest a toroidal structure around the pulsar, but this is not universal. Viewing-angle effects undoubtedly play a role. MHD models of radio emission in shell SNRs show that different orientations of upstream magnetic field, and different assumptions about electron acceleration, predict different radio morphology. In the remnant of SN 1006, such comparisons imply a magnetic-field orientation connecting the bright limbs, with a non-negligible gradient of its strength across the remnant.Comment: 20 pages, 24 figures; to be published in SpSciRev. Minor wording change in Abstrac

FGF receptor genes and breast cancer susceptibility: results from the Breast Cancer Association Consortium

Background:Breast cancer is one of the most common malignancies in women. Genome-wide association studies have identified FGFR2 as a breast cancer susceptibility gene. Common variation in other fibroblast growth factor (FGF) receptors might also modify risk. We tested this hypothesis by studying genotyped single-nucleotide polymorphisms (SNPs) and imputed SNPs in FGFR1, FGFR3, FGFR4 and FGFRL1 in the Breast Cancer Association Consortium. Methods:Data were combined from 49 studies, including 53 835 cases and 50 156 controls, of which 89 050 (46 450 cases and 42 600 controls) were of European ancestry, 12 893 (6269 cases and 6624 controls) of Asian and 2048 (1116 cases and 932 controls) of African ancestry. Associations with risk of breast cancer, overall and by disease sub-type, were assessed using unconditional logistic regression. Results:Little evidence of association with breast cancer risk was observed for SNPs in the FGF receptor genes. The strongest evidence in European women was for rs743682 in FGFR3; the estimated per-allele odds ratio was 1.05 (95 confidence interval=1.02-1.09, P=0.0020), which is substantially lower than that observed for SNPs in FGFR2. Conclusion:Our results suggest that common variants in the other FGF receptors are not associated with risk of breast cancer to the degree observed for FGFR2. © 2014 Cancer Research UK

A measurement of the tau mass and the first CPT test with tau leptons

We measure the mass of the tau lepton to be 1775.1+-1.6(stat)+-1.0(syst.) MeV using tau pairs from Z0 decays. To test CPT invariance we compare the masses of the positively and negatively charged tau leptons. The relative mass difference is found to be smaller than 3.0 10^-3 at the 90% confidence level.Comment: 10 pages, 4 figures, Submitted to Phys. Letts.

Pion, kaon, proton and anti-proton transverse momentum distributions from p+p and d+Au collisions at sNN=200\sqrt{s_{NN}} = 200 GeV

Identified mid-rapidity particle spectra of $\pi^{\pm}$, $K^{\pm}$, and $p(\bar{p})$ from 200 GeV p+p and d+Au collisions are reported. A time-of-flight detector based on multi-gap resistive plate chamber technology is used for particle identification. The particle-species dependence of the Cronin effect is observed to be significantly smaller than that at lower energies. The ratio of the nuclear modification factor ($R_{dAu}$) between protons $(p+\bar{p})$ and charged hadrons ($h$) in the transverse momentum range $1.2<{p_{T}}<3.0$ GeV/c is measured to be $1.19\pm0.05$(stat)$\pm0.03$(syst) in minimum-bias collisions and shows little centrality dependence. The yield ratio of $(p+\bar{p})/h$ in minimum-bias d+Au collisions is found to be a factor of 2 lower than that in Au+Au collisions, indicating that the Cronin effect alone is not enough to account for the relative baryon enhancement observed in heavy ion collisions at RHIC.Comment: 6 pages, 4 figures, 1 table. We extended the pion spectra from transverse momentum 1.8 GeV/c to 3. GeV/