What is the minimal systemic risk in financial exposure networks?

We quantify how much systemic risk can be eliminated in financial contract networks by rearranging their network topology. By using mixed integer linear programming, financial linkages are optimally organized, whereas the overall economic conditions of banks, such as capital buffers, total interbank assets and liabilities, and average risk-weighted exposure remain unchanged. We apply the new optimization procedure to 10 snapshots of the Austrian interbank market where we focus on the largest 70 banks covering 71% of the market volume. The optimization reduces systemic risk (measured in DebtRank) by about 70%, showing the huge potential that changing the network structure has on the mitigation of financial contagion. Existing capital levels would need to be scaled up by a factor of 3.3 to obtain similar levels of DebtRank. These findings underline the importance of macro-prudential rules that focus on the structure of financial networks. The new optimization procedure allows us to benchmark actual networks to networks with minimal systemic risk. We find that simple topological measures, like link density, degree assortativity, or clustering coefficient, fail to explain the large differences in systemic risk between actual and optimal networks. We find that if the most systemically relevant banks are tightly connected, overall systemic risk is higher than if they are unconnected

Synthesis and proton conduction properties of lanthanide amino-sulfophosphonates

Crystalline acid-functionalized metal phosphonates are potential candidates as proton conducting electrolytes. Their frameworks can be chemically modified to contain proton carriers such as acidic groups (P-OH; -SO3H, -COOH,…) and guest molecules (H2O, NH3,…) that generates hydrogen bond networks stable in a wide range of temperature [1,2]. In this work, focus is laid on properties derived from the combination of lanthanide ions with the amino-sulfophosphonate ligand (H2O3PCH2)2-N-(CH2)2-SO3H. Hightrough-put screening was followed to reach the optimal synthesis conditions under solvothermal conditions at 140 ºC. Isolated polycrystalline solids, Ln[(O3PCH2)2-NH-(CH2)2-SO3H].2H2O (Ln= La, Pr and Sm), crystallize in the monoclinic (La) and orthorhombic (Pr and Sm) systems with unit cell volume of ~2548 Å3. Preliminary proton conductivity measurements for Sm derivative have been carried out between 25º and 80 ºC at relative humidity (RH) values of 70 % and 95 %. The sample exhibits enhanced conductivity at high RH and T (Figure 1) and constant activation energies of 0.4 eV, typical of a Grothuss mechanism of proton.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. FQM-1656; MAT2013-41836-

Green Segment Routing for Improved Sustainability of Backbone Networks

Improving the energy efficiency of Internet Service Provider (ISP) backbone networks is an important objective for ISP operators. In these networks, the overall traffic load throughout the day can vary drastically, resulting in many backbone networks being highly overprovisioned during periods of lower traffic volume. In this paper, we propose a new Segment Routing (SR)-based optimization algorithm that aims at reducing the energy consumption of networks during such low-traffic periods. It uses the traffic steering capabilities of SR to remove traffic from as many links as possible to allow the respective hardware components to be switched off. Furthermore, it simultaneously ensures that solutions comply to additional operator requirements regarding the overall Maximum Link Utilization in the network. Based on data from a Tier-1 ISP and a public available dataset, we show that our approach allows for up to 70 % of the overall linecards to be switched off, corresponding to an around 56% reduction of the overall energy consumption of the network in times of low traffic demands.Comment: This work has been submitted to IEEE for possible publication. Copyright may be transferred without notic

Synthesis and proton conduction properties of lanthanide amino-sulfophosphonates

Acidic groups-containing metal phosphonates exhibit a wide range of proton conductivity depending on the water content and functionality. Moreover, this property can be enhanced by appropriate post-synthesis chemical and/or thermal treatments [1,2]. In this work, focus is laid on properties derived from the combination of lanthanide ions with the amino-sulfophosphonate ligand (H2O3PCH2)2-N-(CH2)2-SO3H. Highthrough-put screening was used to reach the optimal synthesis conditions under hydrothermal conditions at 140 ºC. Isolated polycrystalline solids, Ln[(O3PCH2)2-NH-(CH2)2-SO3H]·2H2O (Ln= La, Pr, Sm, Eu, Gd, Tb and Er), crystallize in the monoclinic (La and Er) and orthorhombic (Pr, Sm, Eu, Gd and Tb) systems with unit cell volume of ~1200 and 2548 Å3 respectively. Their crystal structures, solved ab initio from X-ray powder diffraction data, correspond to different layered frameworks depending on the lanthanide cation size. Thus, compounds with orthorhombic symmetry show free acidic sulfonic pointing to the interlayer space, while La- and Er- derivatives display layered structures where both phosphonate and sulfonated groups are coordinated to the metal, leaving free P-OH groups. As consequence of this structural variability, different H-bond networks and proton transfer pathways are generated. Preliminary proton conductivity measurements have been carried out between 25 and 80 ºC at 70-95 % relative humidity. The sample exhibits conductivities near to 3.10-3 S.cm-1 and activation energies characteristics of a Grotthuss-type mechanism of proton transfer.Proyectos de investigación del ministerio MICINN, Españam(MAT2016-77648-R), Proyectos de la Junta de Andalucía (P12-FQM-1656), Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Image Transmission over Resource-constrained Low-Power Radio Networks

The transmission of large amounts of data over resource-constrained radio frequency (RF) networks is impacted by regulatory constraints and can affect reliability due to channel congestion. These barriers limit the use case to specific applications. This research extends the use case scenario to include the transmission of digital images over such networks which to date has not been widely documented. To achieve this, the overall data volume needs to be reduced to manageable limits. Drawing on previous theoretical work this research explored, developed and implemented novel image compression techniques suitable for use in resource-constrained RF networks. A compression technique was developed which allows variable compression ratios to be selected dependent on the specific use case. This was implemented in an end-to-end low-power radio network operating in license-free spectrum using a customised radio frequency testbed. The robust compression scheme which was developed here enabled out-of-sequence packet reception, further increasing the reliability of the transmission. To allow detailed viewing of a region of interest (ROI) within a large format image (quarter video graphics array) to be transmitted, a novel algorithm was designed and implemented. This enabled the transmission of a region of interest (ROI) in an uncompressed format as a stand-alone image portion, or in combination with a fully compressed image. Significantly, this yielded flexibility in the quantity of data to be transmitted which could increase the lifespan of battery powered devices. A further development allowed direct manipulation of individual image pixels. This permitted additional data, such as battery voltage level to be directly embedded in the transmitted image data. An advantage of this innovative method was that it did not incur any extra overhead in data volume requirements. The embodied system developed is an agnostic image compression algorithm and is suitable for use with resource-constrained devices and networks. Results showed that high compression ratios (70%) with good peak signal-to-noise ratio (PSNR) of approximately 36dB was achievable for a complete end-to-end transmission system

On the Relative Contribution of Deep Convolutional Neural Networks for SSVEP-based Bio-Signal Decoding in BCI Speller Applications

Brain-computer interfaces (BCI) harnessing Steady State Visual Evoked Potentials (SSVEP) manipulate the frequency and phase of visual stimuli to generate predictable oscillations in neural activity. For BCI spellers, oscillations are matched with alphanumeric characters allowing users to select target numbers and letters. Advances in BCI spellers can, in part, be accredited to subject-speci?c optimization, including; 1) custom electrode arrangements, 2) ?lter sub-band assessments and 3) stimulus parameter tuning. Here we apply deep convolutional neural networks (DCNN) demonstrating cross-subject functionality for the classi?cation of frequency and phase encoded SSVEP. Electroencephalogram (EEG) data are collected and classi?ed using the same parameters across subjects. Subjects ?xate forty randomly cued ?ickering characters (5 ×8 keyboard array) during concurrent wet-EEG acquisition. These data are provided by an open source SSVEP dataset. Our proposed DCNN, PodNet, achieves 86% and 77% of?ine Accuracy of Classi?cation across-subjects for two data capture periods, respectively, 6-seconds (information transfer rate= 40bpm) and 2-seconds (information transfer rate= 101bpm). Subjects demonstrating sub-optimal (< 70%) performance are classi?ed to similar levels after a short subject-speci?c training period. PodNet outperforms ?lter-bank canonical correlation analysis (FBCCA) for a low volume (3channel) clinically feasible occipital electrode con?guration. The networks de?ned in this study achieve functional performance for the largest number of SSVEP classes decoded via DCNN to date. Our results demonstrate PodNet achieves cross-subject, calibrationless classi?cation and adaptability to sub-optimal subject data and low-volume EEG electrode arrangements

Multiscale core-periphery structure in a global liner shipping network

Maritime transport accounts for a majority of trades in volume, of which 70% in value is carried by container ships that transit regular routes on fixed schedules in the ocean. In the present paper, we analyse a data set of global liner shipping as a network of ports. In particular, we construct the network of the ports as the one-mode projection of a bipartite network composed of ports and ship routes. Like other transportation networks, global liner shipping networks may have core-periphery structure, where a core and a periphery are groups of densely and sparsely interconnected nodes, respectively. Core-periphery structure may have practical implications for understanding the robustness, efficiency and uneven development of international transportation systems. We develop an algorithm to detect core-periphery pairs in a network, which allows one to find core and peripheral nodes on different scales and uses a configuration model that accounts for the fact that the network is obtained by the one-mode projection of a bipartite network. We also found that most ports are core (as opposed to peripheral) ports and that ports in some countries in Europe, America and Asia belong to a global core-periphery pair across different scales, whereas ports in other countries do not.Comment: 22 pages, 10 figures and 1 tabl

Novel optical transmitters for high speed optical networks

The objective of this thesis is to investigate the performance of novel optical transmitter lasers for use in high speed optical networks. The laser technology considered is the discrete mode laser diode (DMLD) which is designed to achieve single wavelength operation by etching features on the surface of the ridge waveguide. This leads to a simplified manufacturing process by eliminating the regrowth step used in conventional approaches, presenting an economic approach to high volume manufacture of semiconductor lasers. Two application areas are investigated in this work. The bit rate in next generation access networks is moving to 10 Gbit/s. This work characterises the performance of DMLDs designed for high speed operation with the objective of identifying the limitations and improving performance to meet the specifications for uncooled operation at 10 Gbit/s. With the deployment of advanced modulation formats the phase noise of the laser source has become an important parameter, particularly for higher order formats. DMLDs were developed for narrow linewidth operation. The linewidth of these devices was characterised and a value as low as 70 kHz was demonstrated. Transmission experiments were also carried out using a coherent transmission test bed and the performance achieve is compared with that of an external cavity laser