Search results for "complex"
showing 10 items of 5889 documents
Biochemical Responses of European Sea Bass (Dicentrarchus labrax L.) to the Stress Induced by Off Shore Experimental Seismic Prospecting
1999
The paper reports the results of an experimental seismic survey in the open sea by an air gun, carried out to evaluate the effects of air gun acoustic waves on marine animals. Air gun blast exposition was found to have a marked influence on confined Dicentrarchus labrax. Our data, in fact, demonstrated a biochemical response to acoustic stress induced by air gun blasts. Variations of cortisol, glucose, lactate, AMP, ADP, ATP and cAMP in different tissues of D. labrax, indicate that fish have a typical primary and secondary stress response after air gun detonations. Radiography indicates that air gun blasts do not induce any macroscopic effect on skeletal apparatus. The variations of biochem…
Dynamic Regret Analysis for Online Tracking of Time-varying Structural Equation Model Topologies
2020
Identifying dependencies among variables in a complex system is an important problem in network science. Structural equation models (SEM) have been used widely in many fields for topology inference, because they are tractable and incorporate exogenous influences in the model. Topology identification based on static SEM is useful in stationary environments; however, in many applications a time-varying underlying topology is sought. This paper presents an online algorithm to track sparse time-varying topologies in dynamic environments and most importantly, performs a detailed analysis on the performance guarantees. The tracking capability is characterized in terms of a bound on the dynamic re…
Dynamic network identification from non-stationary vector autoregressive time series
2018
Learning the dynamics of complex systems features a large number of applications in data science. Graph-based modeling and inference underpins the most prominent family of approaches to learn complex dynamics due to their ability to capture the intrinsic sparsity of direct interactions in such systems. They also provide the user with interpretable graphs that unveil behavioral patterns and changes. To cope with the time-varying nature of interactions, this paper develops an estimation criterion and a solver to learn the parameters of a time-varying vector autoregressive model supported on a network of time series. The notion of local breakpoint is proposed to accommodate changes at individu…
Fast Channel Estimation in the Transformed Spatial Domain for Analog Millimeter Wave Systems
2021
Fast channel estimation in millimeter-wave (mmWave) systems is a fundamental enabler of high-gain beamforming, which boosts coverage and capacity. The channel estimation stage typically involves an initial beam training process where a subset of the possible beam directions at the transmitter and receiver is scanned along a predefined codebook. Unfortunately, the high number of transmit and receive antennas deployed in mmWave systems increase the complexity of the beam selection and channel estimation tasks. In this work, we tackle the channel estimation problem in analog systems from a different perspective than used by previous works. In particular, we propose to move the channel estimati…
Random Feature Approximation for Online Nonlinear Graph Topology Identification
2021
Online topology estimation of graph-connected time series is challenging, especially since the causal dependencies in many real-world networks are nonlinear. In this paper, we propose a kernel-based algorithm for graph topology estimation. The algorithm uses a Fourier-based Random feature approximation to tackle the curse of dimensionality associated with the kernel representations. Exploiting the fact that the real-world networks often exhibit sparse topologies, we propose a group lasso based optimization framework, which is solve using an iterative composite objective mirror descent method, yielding an online algorithm with fixed computational complexity per iteration. The experiments con…
Inference of Spatio-Temporal Functions over Graphs via Multi-Kernel Kriged Kalman Filtering
2018
Inference of space-time varying signals on graphs emerges naturally in a plethora of network science related applications. A frequently encountered challenge pertains to reconstructing such dynamic processes, given their values over a subset of vertices and time instants. The present paper develops a graph-aware kernel-based kriged Kalman filter that accounts for the spatio-temporal variations, and offers efficient online reconstruction, even for dynamically evolving network topologies. The kernel-based learning framework bypasses the need for statistical information by capitalizing on the smoothness that graph signals exhibit with respect to the underlying graph. To address the challenge o…
Energy Efficiency Optimization for Multi-cell Massive MIMO : Centralized and Distributed Power Allocation Algorithms
2021
This paper investigates the energy efficiency (EE) optimization in downlink multi-cell massive multiple-input multiple-output (MIMO). In our research, the statistical channel state information (CSI) is exploited to reduce the signaling overhead. To maximize the minimum EE among the neighbouring cells, we design the transmit covariance matrices for each base station (BS). Specifically, optimization schemes for this max-min EE problem are developed, in the centralized and distributed ways, respectively. To obtain the transmit covariance matrices, we first find out the closed-form optimal transmit eigenmatrices for the BS in each cell, and convert the original transmit covariance matrices desi…
Transporter (TAP)- and proteasome-independent presentation of a melanoma-associated tyrosinase epitope.
2000
The melanosomal protein tyrosinase is considered as a target of specific immunotherapy against melanoma. Two tyrosinase-derived peptides are presented in association with HLA-A2.1 [Wolfel et al., Eur. J. Immunol., 24, 759-764 (1994)]. Peptide 1-9 (MLLAVLYCL) is generated from the putative signal sequence. The internal peptide 369-377 is posttranslationally converted at residue 371, and its presentation is dependent on functional TAP transporters and proteasomes [Mosse et al., J. exp. Med.187, 37-48 (1998)]. Herein, we report on the processing and transport requirements for the signal sequence-derived peptide 1-9 that were studied in parallel to those for peptide 369-377. After infection of …
Diplopod hemocyanin sequence and the phylogenetic position of the Myriapoda
2001
Hemocyanins are copper-containing respiratory proteins of the Arthropoda that have so far been thoroughly investigated only in the Chelicerata and the Crustacea but have remained unstudied until now in the Myriapoda. Here we report the first sequence of a myriapod hemocyanin. The hemocyanin of Spirostreptus sp. (Diplopoda: Spirostreptidae) is composed of two distinct subunits that are arranged in a 6 x 6 native molecule. The cloned hemocyanin subunit cDNA codes of for a polypeptide of 653 amino acids (75.5 kDa) that includes a signal peptide of 18 amino acids. The sequence closely resembles that of the chelicerate hemocyanins. Molecular phylogenetic analyses reject with high statistical con…
Incipient damage identification through characteristics of the analytical signal response
2008
The analytical signal is a complex representation of a time domain signal: the real part is the time domain signal itself, while the imaginary part is its Hilbert transform. It has been observed that damage, even at a very low level, yields clearly detectable variations of analytical signal quantities such as phase and instantaneous frequency. This observation can represent a step toward a quick and effective tool to recognize the presence of incipient damage where other frequency-based techniques fail. In this paper a damage identification procedure based on an adimensional functional of the square of the difference between the characteristics of the analytical theoretical and measured sig…