6,449 research outputs found

    Semiempirical Modeling of Reset Transitions in Unipolar Resistive-Switching based Memristors

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    We have measured the transition process from the high to low resistivity states, i.e., the reset process of resistive switching based memristors based on Ni/HfO2/Si-n+ structures, and have also developed an analytical model for their electrical characteristics. When the characteristic curves are plotted in the current-voltage (I-V) domain a high variability is observed. In spite of that, when the same curves are plotted in the charge-flux domain (Q-phi), they can be described by a simple model containing only three parameters: the charge (Qrst) and the flux (rst) at the reset point, and an exponent, n, relating the charge and the flux before the reset transition. The three parameters can be easily extracted from the Q-phi plots. There is a strong correlation between these three parameters, the origin of which is still under study

    Fuzzy Optimal Control for Robot Manipulators

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    Mortality in hemodialysis patients with COVID-19, the effect of paricalcitol or calcimimetics

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    BACKGROUND: In COVID-19 patients, low serum vitamin D (VD) levels have been associated with severe acute respiratory failure and poor prognosis. In regular hemodialysis (HD) patients, there is VD deficiency and markedly reduced calcitriol levels, which may predispose them to worse outcomes of COVID-19 infection. Some hemodialysis patients receive treatment with drugs for secondary hyperparathyroidism, which have well known pleiotropic effects beyond mineral metabolism. The aim of this study was to evaluate the impact of VD status and the administration of active vitamin D medications, used to treat secondary hyperparathyroidism, on survival in a cohort of COVID-19 positive HD patients. METHODS: A cross-sectional retrospective observational study was conducted from 12 March to 21 May 2020 in 288 HD patients with positive PCR for SARS-CoV2. Patients were from 52 different centers in Spain. RESULTS: The percent of HD patients with COVID-19 was 6.1% (288 out of 4743). Mortality rate was 28.4% (81/285). Three patients were lost to follow-up. Serum 25(OH)D (calcidiol) level was 17.1 [10.6-27.5] ng/mL and was not significantly associated to mortality (OR 0.99 (0.97-1.01), CONCLUSIONS: Our findings suggest that the use of paricalcitol, calcimimetics or the combination of both, seem to be associated with the improvement of survival in HD patients with COVID-19. No correlation was found between serum VD levels and prognosis or outcomes in HD patients with COVID-19. Prospective studies and clinical trials are needed to support these findings

    mTORC2 sustains thermogenesis via Akt-induced glucose uptake and glycolysis in brown adipose tissue

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    Activation of non-shivering thermogenesis (NST) in brown adipose tissue (BAT) has been proposed as an anti-obesity treatment. Moreover, cold-induced glucose uptake could normalize blood glucose levels in insulin-resistant patients. It is therefore important to identify novel regulators of NST and cold-induced glucose uptake. Mammalian target of rapamycin complex 2 (mTORC2) mediates insulin-stimulated glucose uptake in metabolic tissues, but its role in NST is unknown. We show that mTORC2 is activated in brown adipocytes upon ÎČ-adrenergic stimulation. Furthermore, mice lacking mTORC2 specifically in adipose tissue (AdRiKO mice) are hypothermic, display increased sensitivity to cold, and show impaired cold-induced glucose uptake and glycolysis. Restoration of glucose uptake in BAT by overexpression of hexokinase II or activated Akt2 was sufficient to increase body temperature and improve cold tolerance in AdRiKO mice. Thus, mTORC2 in BAT mediates temperature homeostasis via regulation of cold-induced glucose uptake. Our findings demonstrate the importance of glucose metabolism in temperature regulation

    Consistent estimation of panel data sample selection models

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    Consistent estimation of panel data sample selection model

    Gender influence on brand recommendation at an esports event

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    Esports events are a mainstay of the esports industry and have become increasingly popular among the younger population. The purpose of this study was to use a predictive model to determine whether the variables of congruence, commitment and trust could be predictors of brand recommendation of an esports event and, if so, to what extend they did so and whether they were influenced by gender. To obtain the required information, a questionnaire was provided, validated and made up of scales adapted from previous studies at a national esports event organised in Sevilla, Spain. The SPSS version 25 statistical software was used for the analysis of all results. First, a descriptive analysis of the results and a t-test for independent samples were performed, followed by a Pearson correlation analysis to test and independence of the three predictor variables of the recommendation. Finally, a linear regression was performed to test whether the proposed variables predicted the recommendation and, if so, to what extent they did so. The obtained results indicate that, in general, the variables significantly predicted the recommendation, with congruence being the most important predictor. The model as a whole was able to explain 51% of the variance of the recommendation. When distinguishing users by gender, the same analysis showed that the predictor variables for the recommendation remained significant in men, explaining 53% of the variance. In contrast, in the analysis of women, there were no variables that showed significant values for predicting the recommendation. These data demonstrated gender differences in the esports sector, which suggests that esports event companies should change their branding strategies to avoid gender differences

    Bi-Lateral Changes to Hippocampal Cholesterol Levels During Epileptogenesis and in Chronic Epilepsy Following Focal-Onset Status Epilepticus in Mice

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    Brain cholesterol homeostasis has been shown to be disrupted in neurodegenerative conditions such as Alzheimer\u27s and Huntington\u27s diseases. Investigations in animal models of seizure-induced brain injury suggest that brain cholesterol levels are altered by prolonged seizures (status epilepticus) and are a feature of the pathophysiology of temporal lobe epilepsy. The present study measured hippocampal sterol levels in a model of unilateral hippocampal injury triggered by focal-onset status epilepticus, and in chronically epileptic mice. Status epilepticus was induced by intra-amygdala microinjection of kainic acid and ipsilateral and contralateral hippocampus analyzed. No significant changes were found for ipsilateral or contralateral hippocampal levels of desmosterol or lathosterol at any time after SE as measured by gas chromatography–mass spectrometry. 24S-hydroxycholesterol and cholesterol levels were unchanged up to 24 h after status epilepticus but were decreased in the ipsilateral hippocampus during early epileptogenesis and in chronically epileptic mice. Levels of cholesterol were also reduced in the contralateral hippocampus during epileptogenesis and in chronic epileptic mice. Treatment of mice with the anti-inflammatory cholesterol synthesis inhibitor lovastatin did not alter seizures during status epilepticus or seizure-induced neuronal death. Thus, changes to hippocampal cholesterol homeostasis predominantly begin during epileptogenesis, occur bi-laterally even when the initial precipitating injury is unilateral, and continue into the chronic epileptic period

    Integrated multimodal airport operations for efficient passenger flow management: Two case studies

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    Predictive models and decision support tools allow information sharing, common situational awareness and real-time collaborative decision-making between airports and ground transport stakeholders. To support this general goal, IMHOTEP has developed a set of models able to anticipate the evolution of an airport’s passenger flows within the day of operations. This is to assess the operational impact of different management measures on the airport processes and the ground transport system. Two models covering the passenger flows inside the terminal and of passengers accessing and egressing the airport have been integrated to provide a holistic view of the passenger journey from door-to-gate and vice versa. This paper describes IMHOTEP’s application at two case study airports, Palma de Mallorca (PMI) and London City (LCY), at Proof of Concept (PoC-level) assessing impact and service improvements for passengers, airport operators and other key stakeholders. For the first time one measurable process is created to open up opportunities for better communication across all associated stakeholders. Ultimately the successful implementation will lead to a reduction of the carbon footprint of the passenger journey by better use of existing facilities and surface transport services, and the delay or omission of additional airport facility capacities

    SpikingLab: modelling agents controlled by Spiking Neural Networks in Netlogo

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    The scientific interest attracted by Spiking Neural Networks (SNN) has lead to the development of tools for the simulation and study of neuronal dynamics ranging from phenomenological models to the more sophisticated and biologically accurate Hodgkin-and-Huxley-based and multi-compartmental models. However, despite the multiple features offered by neural modelling tools, their integration with environments for the simulation of robots and agents can be challenging and time consuming. The implementation of artificial neural circuits to control robots generally involves the following tasks: (1) understanding the simulation tools, (2) creating the neural circuit in the neural simulator, (3) linking the simulated neural circuit with the environment of the agent and (4) programming the appropriate interface in the robot or agent to use the neural controller. The accomplishment of the above-mentioned tasks can be challenging, especially for undergraduate students or novice researchers. This paper presents an alternative tool which facilitates the simulation of simple SNN circuits using the multi-agent simulation and the programming environment Netlogo (educational software that simplifies the study and experimentation of complex systems). The engine proposed and implemented in Netlogo for the simulation of a functional model of SNN is a simplification of integrate and fire (I&F) models. The characteristics of the engine (including neuronal dynamics, STDP learning and synaptic delay) are demonstrated through the implementation of an agent representing an artificial insect controlled by a simple neural circuit. The setup of the experiment and its outcomes are described in this work
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