Effect of Liberalization on Banking Competition

The paper analyzes the impact of major policy changes on banking structure, performance and competition, using bank-specific data from 1990-2002. We find that the entry of more market players is correlated with drops in interest spread and profits which, partly, bespeaks of possible dissipation of previous monopoly profits of large commercial banks. We also compute the H-stat based on the Panzar-Rosse methodology and find that, in general, despite the characteristic presence of few, large commercial banks, the sector is fairly competitive, specially in the loan-granting business. Moreover, competition has increased in the latter half of 1990s, primarily due to the presence of more small commercial banks, rather than big banks

High-order Discretization of a Gyrokinetic Vlasov Model in Edge Plasma Geometry

We present a high-order spatial discretization of a continuum gyrokinetic Vlasov model in axisymmetric tokamak edge plasma geometries. Such models describe the phase space advection of plasma species distribution functions in the absence of collisions. The gyrokinetic model is posed in a four-dimensional phase space, upon which a grid is imposed when discretized. To mitigate the computational cost associated with high-dimensional grids, we employ a high-order discretization to reduce the grid size needed to achieve a given level of accuracy relative to lower-order methods. Strong anisotropy induced by the magnetic field motivates the use of mapped coordinate grids aligned with magnetic flux surfaces. The natural partitioning of the edge geometry by the separatrix between the closed and open field line regions leads to the consideration of multiple mapped blocks, in what is known as a mapped multiblock (MMB) approach. We describe the specialization of a more general formalism that we have developed for the construction of high-order, finite-volume discretizations on MMB grids, yielding the accurate evaluation of the gyrokinetic Vlasov operator, the metric factors resulting from the MMB coordinate mappings, and the interaction of blocks at adjacent boundaries. Our conservative formulation of the gyrokinetic Vlasov model incorporates the fact that the phase space velocity has zero divergence, which must be preserved discretely to avoid truncation error accumulation. We describe an approach for the discrete evaluation of the gyrokinetic phase space velocity that preserves the divergence-free property to machine precision

Immunization for complex network based on the effective degree of vertex

The basic idea of many effective immunization strategies is first to rank the importance of vertices according to the degrees of vertices and then remove the vertices from highest importance to lowest until the network becomes disconnected. Here we define the effective degrees of vertex, i.e., the number of its connections linking to un-immunized nodes in current network during the immunization procedure, to rank the importance of vertex, and modify these strategies by using the effective degrees of vertices. Simulations on both the scale-free network models with various degree correlations and two real networks have revealed that the immunization strategies based on the effective degrees are often more effective than those based on the degrees in the initial network.Comment: 16 pages, 5 figure

Immobilization of Adult Bull Bison With Etorphine

Between 1967 and 1972, 66 bison (Bison bison) (Linnaeus) bulls, 1 cow and 1 calf were dosed with the narcotic etorphine (M-99) on open range at Fort Niobrara National Wildlife Refuge, Valentine, Nebraska and at Wind Cave National Park, Hot Springs, South Dakota. Etorphine administered at levels of 5 to 6.3 mcg/lb of body weight brought the animals to sternal recumbency. Underdosing was associated with long, difficult pursuit and considerable chance of not apprehending the drugged animal. Adding of methotrimeprazine (Levoprome) up to 74.88 mcg/lb of body weight to the etorphine dosages for some old bulls seemed to have no noticeable effect. The efficiency of antagonists for etorphine is indicated by the fact that dosages of diprenorphine brought 71 percent of 28 bison to their feet in less than I 0 minutes and all the animals in less than 20 minutes. Cyprenorphine brought 52 percent of 25 bison to their feet in less than 10 minutes, 84 percent in less than 20, and all within a period of 27 minutes

Reflection of an electromagnetic pulse from a relativistically moving plasma

The reflection of an obliquely incident electromagnetic pulse from a moving plasma half-space is studied. Using the Lorentz transformations, covariance of Maxwell\u27s equations and the principle of phase invariance to transform between the rest frame and the moving frame, calculations can be conveniently performed in the moving frame. An analytical formula for the linear reflected waveform as a function of the incident angle shows temporal compression and pulse amplification at relativistic velocities of relevance for the generation of ultra-short laser optical pulses

Trauma’s distinctive and combined effects on subsequent substance use, mental health, and neurocognitive functioning with the NCANDA sample

PurposeTraumatic brain injury (TBI) and potentially traumatic events (PTEs) contribute to increased substance use, mental health issues, and cognitive impairments. However, there's not enough research on how TBI and PTEs combined impact mental heath, substance use, and neurocognition.MethodsThis study leverages a subset of The National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) multi-site dataset with 551 adolescents to assess the combined and distinctive impacts of TBI, PTEs, and TBI+PTEs (prior to age 18) on substance use, mental health, and neurocognitive outcomes at age 18.ResultsTBI, PTEs, and TBI+PTEs predicted greater lifetime substance use and past-year alcohol and cannabis use. PTEs predicted greater internalizing symptoms, while TBI+PTEs predicted greater externalizing symptoms. Varying effects on neurocognitive outcomes included PTEs influencing attention accuracy and TBI+PTEs predicting faster speed in emotion tasks. PTEs predicted greater accuracy in abstraction-related tasks. Associations with working memory were not detected.ConclusionThis exploratory study contributes to the growing literature on the complex interplay between TBI, PTEs, and adolescent mental health, substance use, and neurocognition. The developmental implications of trauma via TBIs and/or PTEs during adolescence are considerable and worthy of further investigation

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

Multilevel HfO2-based RRAM devices for low-power neuromorphic networks

Training and recognition with neural networks generally require high throughput, high energy efficiency, and scalable circuits to enable artificial intelligence tasks to be operated at the edge, i.e., in battery-powered portable devices and other limited-energy environments. In this scenario, scalable resistive memories have been proposed as artificial synapses thanks to their scalability, reconfigurability, and high-energy efficiency, and thanks to the ability to perform analog computation by physical laws in hardware. In this work, we study the material, device, and architecture aspects of resistive switching memory (RRAM) devices for implementing a 2-layer neural network for pattern recognition. First, various RRAM processes are screened in view of the device window, analog storage, and reliability. Then, synaptic weights are stored with 5-level precision in a 4 kbit array of RRAM devices to classify the Modified National Institute of Standards and Technology (MNIST) dataset. Finally, classification performance of a 2-layer neural network is tested before and after an annealing experiment by using experimental values of conductance stored into the array, and a simulation-based analysis of inference accuracy for arrays of increasing size is presented. Our work supports material-based development of RRAM synapses for novel neural networks with high accuracy and low-power consumption. (C) 2019 Author(s)

Patterns of subnet usage reveal distinct scales of regulation in the transcriptional regulatory network of Escherichia coli

The set of regulatory interactions between genes, mediated by transcription factors, forms a species' transcriptional regulatory network (TRN). By comparing this network with measured gene expression data one can identify functional properties of the TRN and gain general insight into transcriptional control. We define the subnet of a node as the subgraph consisting of all nodes topologically downstream of the node, including itself. Using a large set of microarray expression data of the bacterium Escherichia coli, we find that the gene expression in different subnets exhibits a structured pattern in response to environmental changes and genotypic mutation. Subnets with less changes in their expression pattern have a higher fraction of feed-forward loop motifs and a lower fraction of small RNA targets within them. Our study implies that the TRN consists of several scales of regulatory organization: 1) subnets with more varying gene expression controlled by both transcription factors and post-transcriptional RNA regulation, and 2) subnets with less varying gene expression having more feed-forward loops and less post-transcriptional RNA regulation.Comment: 14 pages, 8 figures, to be published in PLoS Computational Biolog