Synchronization of dynamical hypernetworks: dimensionality reduction through simultaneous block-diagonalization of matrices

We present a general framework to study stability of the synchronous solution for a hypernetwork of coupled dynamical systems. We are able to reduce the dimensionality of the problem by using simultaneous block-diagonalization of matrices. We obtain necessary and sufficient conditions for stability of the synchronous solution in terms of a set of lower-dimensional problems and test the predictions of our low-dimensional analysis through numerical simulations. Under certain conditions, this technique may yield a substantial reduction of the dimensionality of the problem. For example, for a class of dynamical hypernetworks analyzed in the paper, we discover that arbitrarily large networks can be reduced to a collection of subsystems of dimensionality no more than 2. We apply our reduction techique to a number of different examples, including a class of undirected unweighted hypermotifs of three nodes.Comment: 9 pages, 6 figures, accepted for publication in Phys. Rev.

monotonic and low cycle fatigue properties of earthquake damaged new zealand steel reinforcing bars the experience after the christchurch 2010 2011 earthquakes

Abstract The 2010 and 2011 Christchurch seismic events have highlighted the limitations of the current knowledge in assessing the residual capacity of earthquake-damaged reinforced concrete (RC) buildings. An important challenge during the assessment phase was determining the residual ductility and the remaining low-cycle fatigue life of damaged rebars. Low-cycle fatigue is a possible failure mechanism of steel reinforcing bars when subjected to large-amplitude cyclic loads, such as due to earthquakes. While a single seismic event may not cause rebar failure, the low-cycle fatigue life will be reduced due to plastic strain. Also, New Zealand (NZ)-manufactured Grade 300E is prone to strain ageing. This phenomenon causes a change in mechanical properties, such as increase in yield and ultimate tensile strength, return of a discontinuous yield point, reduction in ductility and rise in the ductile/brittle transition temperature, and must be considered in damage assessment. This paper discusses the effects of strain ageing on the monotonic and cyclic steel mechanical properties. Low-cycle fatigue tests were conducted on Grade 300E steel rebars. Reinforcing bar samples were subjected to constant and fully-reversed strain amplitude cycles. Strain amplitudes ranged from 0.5% to 3%. The strain-fatigue life curve for the un-aged steel was determined. The strain ageing effects on the fatigue life of Grade 300E were then investigated. Specimens were cyclically tested up to the 33% and 66% fatigue life previously determined and "artificially" aged at 100°C. Finally, they were cyclically tested until failure. The experimental data were analyzed and low-cycle fatigue models were calibrated using the Coffin-Manson empirical relationship. Fatigue lives of the un-aged and aged samples were then compared. Preliminary observations suggested that strain-ageing triggers a premature crack initiation which propagates until failure

Hubungan Kebiasaan Merokok Di Dalam Rumah Dengan Kejadian Ispa Pada Anak Umur 1-5 Tahun Di Puskesmas Sario Kota Manado

ISPA (Infeksi Saluran Pernapasan Akut) akan terjadi apabila kekebalan tubuh menurun.Beberapa upaya dapat dilakukan untuk menurunkan resiko penyakit ISPA, antara lain denganmenghilangkan kebiasaan merokok di dalam rumah. Kejadian ISPA pada anak di Puskesmas SarioKota Manado menduduki peringkat pertama diantara 10 penyakit yang paling menonjol. Tujuanpenelitian ini untuk mengidentifikasi kebiasaan merokok di dalam rumah dan kejadian ISPA sertauntuk menganalisis hubungan antara kebiasaan merokok dengan kejadian ISPA.Desain penelitianyang digunakan adalah desain Cross Sectional dan data dikumpulkan dari responden menggunakanlembar kuisioner.Sampel pada penelitian ini berjumlah 51 responden yang didapat menggunakanteknik consecutive sampling.Hasil penelitianuji statistik menggunakan uji chi-square pada tingkatkemaknaan 95% (α ≤ 0,05),maka didapatkan nilai p= 0,002. Ini berarti bahwa nilai p< α(0,05).Kesimpulan dalam penelitian ini ada hubungan antara kebiasaan merokok dengan kejadianISPA pada anak. Rekomendasi untuk peneliti selanjutnya diharapkan dapat meneliti mengenaifaktor-faktor lain seperti Ventilasi Rumah, Kepadatan Hunian, Status sosioekonomi yang dapatmenyebabkan penyakit ISPA

Mice Lacking GABA(A) Receptor delta Subunit Have Altered Pharmaco-EEG Responses to Multiple Drugs

In the brain, extrasynaptically expressed ionotropic, delta subunit-containing gamma-aminobutyric acid A-type receptors (delta-GABA(A)Rs) have been implicated in drug effects at both neuronal and behavioral levels. These alterations are supposed to be caused via drug-induced modulation of receptor ionophores affecting chloride ion-mediated inhibitory tonic currents. Often, a transgenic mouse model genetically lacking the delta-GABA(A)Rs (delta-KO) has been used to study the roles of delta-GABA(A)Rs in brain functions, because a specific antagonist of the delta-GABA(A)Rs is still lacking. We have previously observed with these delta-KO mice that activation of delta-GABA(A)Rs is needed for morphine-induced conditioning of place preference, and others have suggested that delta-GABA(A)Rs act as targets selectively for low doses of ethanol. Furthermore, activation of these receptors via drug-mediated agonism induces a robust increase in the slow-wave frequency bands of electroencephalography (EEG). Here, we tested delta-KO mice (compared to littermate wild-type controls) for the pharmaco-EEG responses of a broad spectrum of pharmacologically different drug classes, including alcohol, opioids, stimulants, and psychedelics. Gaboxadol (THIP), a known superagonist of delta-GABA(A)Rs, was included as the positive control, and as expected, delta-KO mice produced a blunted pharmaco-EEG response to 6 mg/kg THIP. Pharmaco-EEGs showed notable differences between treatments but also differences between delta-KO mice and their wild-type littermates. Interestingly mephedrone (4-MMC, 5 mg/kg), an amphetamine-like stimulant, had reduced effects in the delta-KO mice. The responses to ethanol (1 g/kg), LSD (0.2 mg/kg), and morphine (20 mg/kg) were similar in delta-KO and wild-type mice. Since stimulants are not known to act on delta-GABA(A)Rs, our findings on pharmaco-EEG effects of 4-MMC suggest that delta-GABA(A)Rs are involved in the secondary indirect regulation of the brain rhythms after 4-MMC.Peer reviewe

Physics-based modeling approaches of resistive switching devices for memory and in-memory computing applications

The semiconductor industry is currently challenged by the emergence of Internet of Things, Big data, and deep-learning techniques to enable object recognition and inference in portable computers. These revolutions demand new technologies for memory and computation going beyond the standard CMOS-based platform. In this scenario, resistive switching memory (RRAM) is extremely promising in the frame of storage technology, memory devices, and in-memory computing circuits, such as memristive logic or neuromorphic machines. To serve as enabling technology for these new fields, however, there is still a lack of industrial tools to predict the device behavior under certain operation schemes and to allow for optimization of the device properties based on materials and stack engineering. This work provides an overview of modeling approaches for RRAM simulation, at the level of technology computer aided design and high-level compact models for circuit simulations. Finite element method modeling, kinetic Monte Carlo models, and physics-based analytical models will be reviewed. The adaptation of modeling schemes to various RRAM concepts, such as filamentary switching and interface switching, will be discussed. Finally, application cases of compact modeling to simulate simple RRAM circuits for computing will be shown

Wave Optics Approach to Solar Cell BRDF Modeling with Experimental Results

Light curve analysis is often used to discern information about satellites in geosynchronous orbits. Solar panels, comprising a large part of the satellite’s body, contribute significantly to these light curves. Historically, theoretical bidirectional reflectance distribution functions (BRDFs) have failed to capture key features in the scattered light from solar panels. In recently published work, a new solar cell BRDF was developed by combining specular microfacet and “two-slit” diffraction terms to capture specular and periodic/array scattering, respectively. This BRDF was experimentally motivated and predicted many features of the solar cell scattered irradiance. However, the experiments that informed the BRDF were limited to a single laser wavelength, single beam size, and single solar cell sample. In addition, the BRDF was not physics based and therefore, physical insight into what causes certain features in the scattered irradiance was not evident. In this work, we examine solar cell scattering from first principles and derive a simple physics-based expression for the scattered irradiance. We analyze this expression and physically link terms to important scattering features, e.g., out-of-plane phenomena. In addition, we compare our model with experimental data and find good agreement in the locations and behaviors of these features. Our new model, being more predictive by nature, will allow for greater flexibility and accuracy when modeling reflection from solar cells in both real-world and experimental situations

Graph Metrics for Temporal Networks

Temporal networks, i.e., networks in which the interactions among a set of elementary units change over time, can be modelled in terms of time-varying graphs, which are time-ordered sequences of graphs over a set of nodes. In such graphs, the concepts of node adjacency and reachability crucially depend on the exact temporal ordering of the links. Consequently, all the concepts and metrics proposed and used for the characterisation of static complex networks have to be redefined or appropriately extended to time-varying graphs, in order to take into account the effects of time ordering on causality. In this chapter we discuss how to represent temporal networks and we review the definitions of walks, paths, connectedness and connected components valid for graphs in which the links fluctuate over time. We then focus on temporal node-node distance, and we discuss how to characterise link persistence and the temporal small-world behaviour in this class of networks. Finally, we discuss the extension of classic centrality measures, including closeness, betweenness and spectral centrality, to the case of time-varying graphs, and we review the work on temporal motifs analysis and the definition of modularity for temporal graphs.Comment: 26 pages, 5 figures, Chapter in Temporal Networks (Petter Holme and Jari Saram\"aki editors). Springer. Berlin, Heidelberg 201

Little-Parks effect and multiquanta vortices in a hybrid superconductor--ferromagnet system

Within the phenomenological Ginzburg-Landau theory we investigate the phase diagram of a thin superconducting film with ferromagnetic nanoparticles. We study the oscillatory dependence of the critical temperature on an external magnetic field similar to the Little-Parks effect and formation of multiquantum vortex structures. The structure of a superconducting state is studied both analytically and numerically.Comment: 7 pages, 1 figure. Submitted to J. Phys.: Condens. Mat

Discovering universal statistical laws of complex networks

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their generalisation power, which we identify with large structural variability and absence of constraints imposed by the construction scheme. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This allows, for instance, to infer global features from local ones using regression models trained on networks with high generalisation power. Our results confirm and extend previous findings regarding the synchronisation properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks with good approximation. Finally, we demonstrate on three different data sets (C. elegans' neuronal network, R. prowazekii's metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models

Cell fueling and metabolic energy conservation in synthetic cells

We aim for a blue print for synthesizing complex subcellular systems from molecular components and ultimately for constructing life. Without comprehensive instructions and design principles we rely on simple reaction routes to operate the essential functions of life. The first forms of synthetic life will not make every building block for polymers de novo via complex pathways, rather they will be fed with amino acids, fatty acids and nucleotides. Controlled energy supply is crucial for any synthetic cell, no matter how complex. Here, we describe the simplest pathways for efficient generation of ATP and electrochemical ion gradients. We estimated the demand for ATP by polymer synthesis and maintenance processes in small cell-like systems, and we describe circuits to control the needs for ATP. We also present fluorescence-based sensors for pH, ionic strength, excluded volume, ATP/ADP, and viscosity, which allow monitoring and tuning of the major physicochemical conditions inside cells