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On Economic Complexity and the Fitness of Nations
No full textComplex economic systems can often be described by a network, with nodes representing economic entities and edges their interdependencies, while network centrality is often a good indicator of importance. Recent publications have implemented a nonlinear iterative Fitness-Complexity (FC) algorithm to measure centrality in a bipartite trade network, which aims to represent the ‘Fitness’ of national economies as well as the ‘Complexity’ of the products being traded. In this paper, we discuss this methodological approach and conclude that further work is needed to identify stable and reliable measures of fitness and complexity. We provide theoretical and numerical evidence for the intrinsic instability in the nonlinear definition of the FC algorithm. We perform an in-depth evaluation of the algorithm’s rankings in two real world networks at the country level: the global trade network, and the patent network in different technological domains. In both networks, we find evidence of the instabilities predicted theoretically, and show that ‘complex’ products or patents tend often to be those that countries rarely produce, rather than those that are intrinsically more difficult to produce
Heart rate variability analysis during muscle fatigue due to prolonged isometric contraction
No full textSummary form only given. Strong light-matter coupling has been recently successfully explored in the GHz and THz 1 range with on-chip platforms. New and intriguing quantum optical phenomena have been predicted in the ultrastrong coupling regime 2, when the coupling strength Ω becomes comparable to the unperturbed frequency of the system ω. We recently proposed a new experimental platform where we couple the inter-Landau level transition of an high-mobility 2DEG to the highly subwavelength photonic mode of an LC meta-atom 3 showing very large Ω/ωc = 0.87. Our system benefits from the collective enhancement of the light-matter coupling which comes from the scaling of the coupling Ω ∝ √n, were n is the number of optically active electrons. In our previous experiments 3 and in literature 4 this number varies from 104-103 electrons per meta-atom. We now engineer a new cavity, resonant at 290 GHz, with an extremely reduced effective mode surface Seff = 4 × 10-14 m2 (FE simulations, CST), yielding large field enhancements above 1500 and allowing to enter the few (<;100) electron regime. It consist of a complementary metasurface with two very sharp metallic tips separated by a 60 nm gap (Fig.1(a, b)) on top of a single triangular quantum well. THz-TDS transmission experiments as a function of the applied magnetic field reveal strong anticrossing of the cavity mode with linear cyclotron dispersion. Measurements for arrays of only 12 cavities are reported in Fig.1(c). On the top horizontal axis we report the number of electrons occupying the topmost Landau level as a function of the magnetic field. At the anticrossing field of B=0.73 T we measure approximately 60 electrons ultra strongly coupled (Ω/ω- |
Verifying Properties of Systems Relying on Attribute-Based Communication
No full textAbC is a process calculus designed for describing collective adaptive systems, whose distinguishing feature is the communication mechanism relying on predicates over attributes exposed by components. A novel approach to the analysis of concurrent systems modelled as AbC terms is presented that relies on the UMC model checker, a tool based on modelling concurrent systems as communicating UML-like state machines. A structural translation from AbC specifications to the UMC internal format is provided and used as the basis for the analysis. Three different algorithmic solutions of the well studied stable marriage problem are described in AbC and their translations are analysed with UMC. It is shown how the proposed approach can be exploited to identify emerging properties of systems and unwanted behaviour
Congenital blindness affects diencephalic but not mesencephalic structures in the human brain
No full textWhile there is ample evidence that the structure and function of visual cortical areas are affected by early visual deprivation, little is known of how early blindness modifies subcortical relay and association thalamic nuclei, as well as mesencephalic structures. Therefore, in the present multicenter study, we used MRI to measure volume of the superior and inferior colliculi, as well as of the thalamic nuclei relaying sensory and motor information to the neocortex, parcellated according to atlas-based thalamo-cortical connections, in 29 individuals with congenital blindness of peripheral origin (17 M, age 35.7 ± 14.3 years) and 29 sighted subjects (17 M, age 31.9 ± 9.0). Blind participants showed an overall volume reduction in the left (p = 0.008) and right (p = 0.007) thalami, as compared to the sighted individuals. Specifically, the lateral geniculate (i.e., primary visual thalamic relay nucleus) was 40 % reduced (left: p = 4 × 10−6, right: p < 1 × 10−6), consistent with findings from animal studies. In addition, associated thalamic nuclei that project to temporal (left: p = 0.005, right: p = 0.005), prefrontal (left: p = 0.010, right: p = 0.014), occipital (left: p = 0.005, right: p = 0.023), and right premotor (p = 0.024) cortical regions were also significantly reduced in the congenitally blind group. Conversely, volumes of the relay nuclei directly involved in auditory, motor, and somatosensory processing were not affected by visual deprivation. In contrast, no difference in volume was observed in either the superior or the inferior colliculus between the two groups. Our findings indicate that visual loss since birth leads to selective volumetric changes within diencephalic, but not mesencephalic, structures. Both changes in reciprocal cortico-thalamic connections or modifications in the intrinsic connectivity between relay and association nuclei of the thalamus may contribute to explain these alterations in thalamic volumes. Sparing of the superior colliculi is in line with their composite, multisensory projections, and with their not exclusive visual nature
Cascades in interdependent flow networks
No full textIn this manuscript, we investigate the abrupt breakdown behavior of coupled distribution grids under load growth. This scenario mimics the ever-increasing customer demand and the foreseen introduction of energy hubs interconnecting the different energy vectors. We extend an analytical model of cascading behavior due to line overloads to the case of interdependent networks and find evidence of first order transitions due to the long-range nature of the flows. Our results indicate that the foreseen increase in the couplings between the grids has two competing effects: on the one hand, it increases the safety region where grids can operate without withstanding systemic failures; on the other hand, it increases the possibility of a joint systems’ failure
Workload Change Point Detection for Runtime Thermal Management of Embedded Systems
No full textApplications executed on multicore embedded systems interact with system software [such as the operating system (OS)] and hardware, leading to widely varying thermal profiles which accelerate some aging mechanisms, reducing the lifetime reliability. Effectively managing the temperature therefore requires: 1) autonomous detection of changes in application workload and 2) appropriate selection of control levers to manage thermal profiles of these workloads. In this paper, we propose a technique for workload change detection using density ratio-based statistical divergence between overlapping sliding windows of CPU performance statistics. This is integrated in a runtime approach for thermal management, which uses reinforcement learning to select workload-specific thermal control levers by sampling on-board thermal sensors. Identified control levers override the OSs native thread allocation decision and scale hardware voltage-frequency to improve average temperature, peak temperature, and thermal cycling. The proposed approach is validated through its implementation as a hierarchical runtime manager for Linux, with heuristic-based thread affinity selected from the upper hierarchy to reduce thermal cycling and learningbased voltage-frequency selected from the lower hierarchy to reduce average and peak temperatures. Experiments conducted with mobile, embedded, and high performance applications on ARM-based embedded systems demonstrate that the proposed approach increases workload change detection accuracy by an average 3.4×, reducing the average temperature by 4 °C-25 °C, peak temperature by 6 °C-24 °C, and thermal cycling by 7%-35% over state-of-the-art approaches
A 3D coupled thermo-visco-elastic shear-lag formulation for the prediction of residual stresses in photovoltaic modules after lamination
No full textEvaluation of the residual stress distribution arising from lamination of photovoltaic (PV) modules is important to address thermomechanically induced failure of PV modules during service. In view of the fact that PV modules contain several Silicon cells, modelling the thermo-mechanical response of PV laminates during cooling after lamination is computationally challenging. Due to the coupling between the thermal and the mechanical fields, the stress state experienced by each silicon cell in a module varies from one position to another. Here, a novel 3D coupled thermo-visco-elastic shear-lag model is proposed to determine the stress distribution in a PV module after lamination. To enhance the prediction of stress distribution in the laminate, viscoelastic properties of the EVA encapsulant are taken into account by using an asymptotic model which is stable for small and large time steps of strain increments. The results for a simulated mini-module show that residual stresses vary significantly from point to point inside the PV module