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Many engineering applications can be approached as optimization problems whose solution commonly involves the execution of computational expensive objective functions. Recently, Evolutionary Algorithms (EAs) are gaining popularity for solving complex problems that are encountered in many disciplines, delivering a more robust and effective way to locate global optima in comparison to classical optimization methods. However, applying EA’s to real-world problems demands a large number of function evaluations before delivering a satisfying result. Under such circumstances, several EAs have been adapted to reduce the number of function evaluations by using alternative models to substitute the original objective function. Despite such approaches employ a reduced number of function evaluations, the use of alternative models seriously affects their original EA search capacities and their solution accuracy. Recently, a new evolutionary method called the Adaptive Population with Reduced Evaluations (APRE) has been proposed to solve several image processing problems. APRE reduces the number of function evaluations through the use of two mechanisms: (1) The dynamic adaptation of the population and (2) the incorporation of a fitness calculation strategy, which decides when it is feasible to calculate or only estimate new generated individuals. As a result, the approach can substantially reduce the number of function evaluations, yet preserving the good search capabilities of an evolutionary approach. In this paper, the performance of APRE as a global optimization algorithm is presented. In order to illustrate the proficiency and robustness of APRE, it has been compared to other approaches that have been previously conceived to reduce the number of function evaluations. The comparison examines several standard benchmark functions, which are commonly considered within the EA field. Conducted simulations have confirmed that the proposed method achieves the best balance over its counterparts, in terms of the number of function evaluations and the solution accuracy. [ABSTRACT FROM AUTHOR]

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The article focuses on the application of adaptive network-based fuzzy inference system (ANFIS) algorithm to lessen the delay in real-time gaze control. It describes the fuzzy inference system and learning algorithm for ANFIS architecture and reveals the use of colour segmentation algorithm and of proportional-integral-derivative (PID) controller to explain the whole system implementation. It reveals that the neurofuzzy system allows fast and precise motion control of the target object.

Abstract: The actions of the ciliary neurotrophic factor (CNTF) were assessed on adult mouse skeletal muscle L-type Ca2+ currents and on Ca2+ release from sarcoplasmic reticulum. Currents were measured with the whole cell patch clamp technique. Ca2+ signals in response to single action potentials were recorded with Fluo3-AM. CNTF (20ng/ml) reversibly reduced the amplitude of Ca2+ channel currents by 50% within 15min. In addition, CNTF greatly increased the rate of inactivation during depolarizing pulses and shifted the steady state inactivation curve by −12mV. The effects of CNTF were mimicked by the PKC activator PMA and prevented by the PKC-inhibitor chelerythrine. In contrast to the effects on the Ca2+ conductance, charge movement and Ca2+ signals remained unaffected by CNTF. These results suggest that CNTF can rapidly decrease muscle Ca2+ channel currents by promoting inactivation, probably through an intracellular PKC-dependent mechanism. [Copyright &y& Elsevier]

The global pandemic caused by the coronavirus (COVID-19) disease has collapsed the worldwide economy. Elements such as non-obligatory vaccination, new strain variants and lack of discipline to follow social distancing measures suggest the possibility that COVID-19 may continue to exist, exhibiting the behavior of a seasonal disease. As the socio-economic crisis has become unsustainable, all countries are planning strategies to gradually restart their economic and social activities. Initially, several containment measures have been adopted involving social distancing, infection detection tests, and ventilation systems. Despite the implementation of such policies, there exists a lack of evaluation of their performance to reduce the contagion index. This means there are no appropriate indicators to decide which intervention or set of interventions present the most effective result. Under these conditions, the development of models that provide useful information in the design and evaluation of containment measures and re-opening policies is of prime concern. In this paper, a novel approach to model the transmission process of COVID-19 in closed environments is proposed. The proposed model can simulate the effects that result from the complex interaction among individuals when they follow a particular containment measure or re-opening policy. With the proposed model, different hypothetical re-opening policies, that are otherwise impossible to analyze in real conditions, can be tested. Computer experiments demonstrate that the proposed model provides suitable information and realistic predictions, which are appropriate for designing strategies that allow a safe return to economic activities., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Cholinergic neuromodulation is involved in all aspects of sensory processing and is crucial for processes such as attention, learning and memory, etc. However, despite the known roles of acetylcholine (ACh), we still do not how to disentangle ACh contributions from sensory or task-evoked changes in functional magnetic resonance imaging (fMRI). Here, we investigated the effects of local injection of ACh on fMRI and neural signals in the primary visual cortex (V1) of anesthetized macaques by combining pharmaco-based MRI (phMRI) with electrophysiological recordings, using single electrodes and electrode arrays. We found that local injection of ACh elicited two distinct profiles of fMRI and neurophysiological activity, depending on the distance from the injector. Near the injection site, we observed an increase in the baseline blood oxygen-level-dependent (BOLD) and cerebral blood flow (CBF) responses, while their visual modulation decreased. In contrast, further from the injection site, we observed an increase in the visually induced BOLD and CBF modulation without changes in baseline. Neurophysiological recordings suggest that the spatial correspondence between fMRI responses and neural activity does not change in the gamma, high-gamma, and multiunit activity (MUA) bands. The results near the injection site suggest increased inhibitory drive and decreased metabolism, contrasting to the far region. These changes are thought to reflect the kinetics of ACh and its metabolism to choline., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)

Purpose: To perform exchange-rate measurements on the in vivo human brain downfield spectrum (5-10 ppm) at 9.4 T and to compare the variation in concentrations of the downfield resonances and of known upfield metabolites to determine potential peak labels., Methods: Non-water-suppressed metabolite cycling was used in combination with an inversion transfer technique in two brain locations in healthy volunteers to measure the exchange rates and T 1 values of exchanging peaks. Spectra were fitted with a heuristic model of a series of 13 or 14 Voigt lines, and a Bloch-McConnell model was used to fit the exchange rate curves. Concentrations from non-water-inverted spectra upfield and downfield were compared., Results: Mean T 1 values ranged from 0.40 to 0.77 s, and exchange rates from 0.74 to 13.8 s -1 . There were no significant correlations between downfield and upfield concentrations, except for N-acetylaspartate, with a correlation coefficient of 0.63 and P < 0.01., Conclusions: Using ultrahigh field allowed improved separation of peaks in the 8.2 to 8.5 ppm amide proton region, and the exchange rates of multiple downfield resonances including the 5.8-ppm peak, previously tentatively assigned to urea, were measured in vivo in human brain. Downfield peaks consisted of overlapping components, and largely missing correlations between upfield and downfield resonances-although not conclusive-indicate limited contributions from metabolites present upfield to the downfield spectrum. Magn Reson Med 79:2863-2873, 2018. © 2017 International Society for Magnetic Resonance in Medicine., (© 2017 International Society for Magnetic Resonance in Medicine.)

Neural oscillations are ubiquitously observed in cortical activity, and are widely believed to be crucial for mediating transmission of information across the cortex. Yet, the neural phenomena contributing to each oscillation band, and their effect on information coding and transmission, are largely unknown. Here, we investigated whether individual frequency bands specifically reflect changes in the concentrations of dopamine, an important neuromodulator, and how dopamine affects oscillatory information processing. We recorded the local field potential (LFP) at different depths of primary visual cortex (V1) in anesthetized monkeys (Macaca mulatta) during spontaneous activity and during visual stimulation with Hollywood movie clips while pharmacologically mimicking dopaminergic neuromodulation by systemic injection of L-DOPA (a metabolic precursor of dopamine). We found that dopaminergic neuromodulation had marked effects on both spontaneous and movie-evoked neural activity. During spontaneous activity, dopaminergic neuromodulation increased the power of the LFP specifically in the [19-38 Hz] band, suggesting that the power of endogenous visual cortex oscillations in this band can be used as a robust marker of dopaminergic neuromodulation. Moreover, dopamine increased visual information encoding over all frequencies during movie stimulation. The information increase due to dopamine was prominent in the supragranular layers of cortex that project to higher cortical areas and in the gamma [50-100 Hz] band that has been previously implicated in mediating feedforward information transfer. These results thus individuate new neural mechanisms by which dopamine may promote the readout of relevant sensory information by strengthening the transmission of information from primary to higher areas., (Copyright © 2017 Elsevier Ltd. All rights reserved.)