427 research outputs found

    Dorsal Prefrontal Cortex Impairment in Methoxetamine-Induced Psychosis: an 18F-FDG PET/CT Case Study

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    Submitted15 June 2018. Accepted 13 December 2018. Epub ahead of print 13 February 2019Novel psychoactive substances (NPSs) have currently become a major public health concern because of relatively easy accessibility to these compounds and difficulty in identifying them with routine laboratory techniques. Here, we report the 18 F-fluorodeoxyglucose positron emission tomography/computerized tomography ( 18 F-FDG PET/CT) case study of a 23-year-old man who developed a substance-induced psychotic disorder after having intravenously injected himself with an unspecified amount of methoxetamine (MXE), a ketamine derivative hallucinogen. From a clinical perspective, a blunted affective responsiveness with diminished social drive and sense of purpose, along with a profound detachment from the environment, was observed. Psychometric and neuropsychological assessments highlighted severe dissociative symptoms and lack of motivation, along with a mild impairment of verbal fluency, working memory, and attention. Patient’s 18 F-FDG PET/CT scans displayed a significant bilateral deficit of tracer uptake within the dorsolateral prefrontal cortex (DLPFC). DLPFC activity is critical to goal-oriented cognitive functions, including working memory and sustained attention. DLPFC is also involved in both the temporal integration across multiple sensory modes and in the volitional control of actions, leading to the possibility to construct logically coherent temporal configurations of thought, speech, and behavior. This report highlights that a single acute MXE intoxication may produce severe brain impairment.Peer reviewedFinal Accepted Versio

    Development of a multifunctional panel for aerospace use through SLM additive manufacturing

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    Lattice materials can overcome the need of light and stiff structures in the aerospace industry. The wing leading edge is one of the most critical parts for both on-board subsystem and structure features: it must withstand to the aerodynamic loads and bird-strike, integrating also the anti-ice system functions. Nowadays, this part is made by different components bonded together such as external skin, internal passageways, and feeding tubes. In the present work, a single-piece multifunctional panel made by additive manufacturing will be developed. Optimal design and manufacturing are discussed according to technological constraints, aeronautical performances and sustainability

    Molecular dynamics recipes for genome research

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    Molecular dynamics (MD) simulation allows one to predict the time evolution of a system of interacting particles. It is widely used in physics, chemistry and biology to address specific questions about the structural properties and dynamical mechanisms of model systems. MD earned a great success in genome research, as it proved to be beneficial in sorting pathogenic from neutral genomic mutations. Considering their computational requirements, simulations are commonly performed on HPC computing devices, which are generally expensive and hard to administer. However, variables like the software tool used for modeling and simulation or the size of the molecule under investigation might make one hardware type or configuration more advantageous than another or even make the commodity hardware definitely suitable for MD studies. This work aims to shed lights on this aspect

    a comparison between 3d printing and milling process for a spar cap fitting wing fuselage of uav aircraft

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    Abstract Topology optimization is playing an important role in the aircraft design. The demand of lower fuel consumption reflects on the optimization of the airframe of flying vehicles to reduce the structure weight, therefore improving the fraction of the payload. This work focuses on the replacement of an existing part (spar cap fitting) with the new topologically optimized part to be manufactured with 3D printing (Selective Laser Sintering -SLS). The manufacturing constraints (minimum dimension, growth orientation) influence on the optimal results is evaluated to compare traditional milling process' performance with the new SLS technique

    Small-Coupling Dynamic Cavity: a Bayesian mean-field framework for epidemic inference

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    A novel generalized mean field approximation, called the Small-Coupling Dynamic Cavity (SCDC) method, for Bayesian epidemic inference and risk assessment is presented. The method is developed within a fully Bayesian framework and accounts for non-causal effects generated by the presence of observations. It is based on a graphical model representation of the epidemic stochastic process and utilizes dynamic cavity equations to derive a set of self-consistent equations for probability marginals defined on the edges of the contact graph. By performing a small-coupling expansion, a pair of time-dependent cavity messages is obtained, which capture the probability of individual infection and the conditioning power of observations. In its efficient formulation, the computational cost per iteration of the SCDC algorithm is linear in the duration of the epidemic dynamics and in the number of contacts. The SCDC method is derived for the Susceptible-Infected (SI) model and straightforwardly applicable to other Markovian epidemic processes, including recurrent ones. It exhibits high accuracy in assessing individual risk on par with Belief Propagation techniques and outperforming heuristic methods based on individual-based mean-field approximations. Although convergence issues may arise due to long-range correlations in contact graphs, the estimated marginal probabilities remain sufficiently accurate for reliable risk estimation. Future work includes extending the method to non-Markovian recurrent epidemic models and investigating the role of second-order terms in the small coupling expansion of the observation-reweighted Dynamic Cavity equations.Comment: 29 pages, 7 figures (including appendices
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