beyond zoster sensory and immune changes in zoster affected dermatomes a review

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Phase diagram and complexity of mode-locked lasers: from order to disorder

We investigate mode-locking processes in lasers displaying a variable degree of structural randomness, from standard optical cavities to multiple-scattering media. By employing methods mutuated from spin-glass theory, we analyze the mean-field Hamiltonian and derive a phase-diagram in terms of the pumping rate and the degree of disorder. Three phases are found: i) paramagnetic, corresponding to a noisy continuous wave emission, ii) ferromagnetic, that describes the standard passive mode-locking, and iii) the spin-glass in which the phases of the electromagnetic field are frozen in a exponentially large number of configurations. The way the mode-locking threshold is affected by the amount of disorder is quantified. The results are also relevant for other physical systems displaying a random Hamiltonian, like Bose-Einstein condensates and nonlinear optical beams.Comment: 4 pages, 2 figure

General features of the energy landscape in Lennard-Jones like model liquids

Features of the energy landscape sampled by supercooled liquids are numerically analyzed for several Lennard-Jones like model systems. The properties of quasisaddles (minima of the square gradient of potential energy W=|grad V|^2), are shown to have a direct relationship with the dynamical behavior, confirming that the quasisaddle order extrapolates to zero at the mode-coupling temperature T_MCT. The same result is obtained either analyzing all the minima of W or the saddles (absolute minima of W), supporting the conjectured similarity between quasisaddles and saddles, as far as the temperature dependence of the properties influencing the slow dynamics is concerned. We find evidence of universality in the shape of the landscape: plots for different systems superimpose into master curves, once energies and temperatures are scaled by T_MCT. This allows to establish a quantitative relationship between T_MCT and potential energy barriers for LJ-like systems, and suggests a possible generalization to different model liquids.Comment: 8 pages, 5 figure

ORIGIN OF LIGHT SCATTERING FROM DISORDERED SYSTEMS

Anelastic light scattering is computed numerically for model disordered systems (linear chains and 2-dimensional site and bond percolators), with and without electrical disorder. A detailed analysis of the vibrational modes and of their Raman activity evidences that two extreme mechanisms for scattering may be singled out. One of these resembles scattering from finite size systems, while the other mechanisms originates from spatial fluctuations of the polarizability and is such that modes in even small frequency intervals may have very different Raman activities. As a consequence, the average coupling coefficient $C(\omega)$ is the variance of a zero-average quantity. Our analysis shows that for both linear chains and 2-dimensional percolators the second mechanism dominates over the first, and therefore Raman scattering from disordered systems is essentially due to spatial fluctuations.Comment: 12 pages, Latex, 7 figures available on request

Global Transformer Architecture for Indoor Room Temperature Forecasting

A thorough regulation of building energy systems translates in relevant energy savings and in a better comfort for the occupants. Algorithms to predict the thermal state of a building on a certain time horizon with a good confidence are essential for the implementation of effective control systems. This work presents a global Transformer architecture for indoor temperature forecasting in multi-room buildings, aiming at optimizing energy consumption and reducing greenhouse gas emissions associated with HVAC systems. Recent advancements in deep learning have enabled the development of more sophisticated forecasting models compared to traditional feedback control systems. The proposed global Transformer architecture can be trained on the entire dataset encompassing all rooms, eliminating the need for multiple room-specific models, significantly improving predictive performance, and simplifying deployment and maintenance. Notably, this study is the first to apply a Transformer architecture for indoor temperature forecasting in multi-room buildings. The proposed approach provides a novel solution to enhance the accuracy and efficiency of temperature forecasting, serving as a valuable tool to optimize energy consumption and decrease greenhouse gas emissions in the building sector

Inflammation, neurodegeneration and protein aggregation in the retina as ocular biomarkers for Alzheimer’s Disease in the 3xTg-AD mouse model

Alzheimer's disease (AD) is the most common cause of dementia in the elderly. In the pathogenesis of AD a pivotal role is played by two neurotoxic proteins that aggregate and accumulate in the central nervous system: amyloid beta and hyper-phosphorylated tau. Accumulation of extracellular amyloid beta plaques and intracellular hyper-phosphorylated tau tangles, and consequent neuronal loss begins 10-15 years before any cognitive impairment. In addition to cognitive and behavioral deficits, sensorial abnormalities have been described in AD patients and in some AD transgenic mouse models. Retina can be considered a simple model of the brain, as some pathological changes and therapeutic strategies from the brain may be observed or applicable to the retina. Here we propose new retinal biomarkers that could anticipate the AD diagnosis and help the beginning and the follow-up of possible future treatments. We analyzed retinal tissue of triple-transgenic AD mouse model (3xTg-AD) for the presence of pathological hallmarks during disease progression. We found the presence of amyloid beta plaques, tau tangles, neurodegeneration, and astrogliosis in the retinal ganglion cell layer of 3xTg-AD mice, already at pre-symptomatic stage. Moreover, retinal microglia in pre-symptomatic mice showed a ramified, anti-inflammatory phenotype which, during disease progression, switches to a pro-inflammatory, less ramified one, becoming neurotoxic. We hypothesize retina as a window through which monitor AD-related neurodegeneration process

Condensation in disordered lasers: theory, 3D+1 simulations and experiments

The complex processes underlying the generation of a coherent-like emission from the multiple-scattering of photons and wave-localization in the presence of structural disorder are still mostly un-explored. Here we show that a single nonlinear Schroedinger equation, playing the role of the Schawlow-Townes law for standard lasers, quantitatively reproduces experimental results and three-dimensional time-domain parallel simulations of a colloidal laser system.Comment: 4 pages, 5 figure

A simulation-based performance analysis tool for aircraft design workflows

A simulation-based approach for take-off and landing performance assessments is presented in this work. In the context of aircraft design loops, it provides a detailed and flexible formulation that can be integrated into a wider simulation methodology for a complete commercial aviation mission. As a matter of fact, conceptual and preliminary aircraft design activities require iterative calculations to quickly make performance predictions on a set of possible airplane configurations. The goal is to search for a design that best fits all top level aircraft requirements among the results of a great number of multi-disciplinary analyses, as fast as possible, and with a certain grade of accuracy. Usually, such a task is carried out using statistical or semi-empirical approaches which can give pretty accurate results in no time. However, those prediction methods may be inappropriate when dealing with innovative aircraft configurations or whenever a higher level of accuracy is necessary. Simulation-based design has become crucial to make the overall process affordable and effective in cases where higher fidelity analyses are required. A common example when flight simulations can be effectively used to support a design loop is given by aircraft mission analyses and performance predictions. These usually include take-off, climb, en route, loiter, approach, and landing simulations. This article introduces the mathematical models of aircraft take-off and landing and gives the details of how they are implemented in the software library JPAD. These features are not present in most of the currently available pieces of preliminary aircraft design software and allow one to perform high fidelity, simulation-based take-off and landing analyses within design iterations. Although much more detailed than classical semi-empirical approaches, the presented methodologies require very limited computational effort. An application of the proposed formulations is introduced in the second part of the article. The example considers the Airbus A220-300 as a reference aircraft model and includes complete take-off and landing performance studies, as well as the simulation of both take-off and landing certification noise trajectories

Network dilution and asymmetry in an efficient brain

The ultimate goal of neuroscience is to ultimately understand how the brain functions. The advancement of brain imaging shows us how the brain continuously alternates complex activity patterns and experimentally reveals how these patterns are responsible for memory, association, reasoning, and countless other tasks. Two fundamental parameters, dilution (the number of connections per node), and symmetry (the number of bidirectional connections of the same weight) characterise two fundamental features underlying the networks that connect the single neurons in the brain and generate these patterns. Mammalian brains show large variations of dilution, and mostly asymmetric connectivity, unfortunately the advantages which drove evolution to these state of network dilution and asymmetry are still unknown. Here, we studied the effects of symmetry and dilution on a discrete-time recurrent neural network with McCulloch–Pitts neurons. We use an exhaustive approach, in which we probe all possible inputs for several randomly connected neuron networks with different degrees of dilution and symmetry. We find an optimum value for the synaptic dilution and symmetry, which turns out to be in striking quantitative agreement with what previous researchers have found in the brain cortex, neocortex and hippocampus. The diluted asymmetric brain shows high memory capacity and pattern recognition speed, but most of all it is the less energy-consumptive with respect to fully connected and symmetric network topologies