87 research outputs found
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Greek long-term energy consumption prediction using artificial neural networks
In this paper artificial neural networks (ANN) are addressed in order the Greek long-term energy consumption to be predicted. The multilayer perceptron model (MLP) has been used for this purpose by testing several possible architectures in order to be selected the one with the best generalizing ability. Actual recorded input and output data that influence long-term energy consumption were used in the training, validation and testing process. The developed ANN model is used for the prediction of 2005-2008, 2010, 2012 and 2015 Greek energy consumption. The produced ANN results for years 2005-2008 were compared with the results produced by a linear regression method, a support vector machine method and with real energy consumption records showing a great accuracy. The proposed approach can be useful in the effective implementation of energy policies, since accurate predictions of energy consumption affect the capital investment, the environmental quality, the revenue analysis, the market research management, while conserve at the same time the supply security. Furthermore it constitutes an accurate tool for the Greek long-term energy consumption prediction problem, which up today has not been faced effectively
An Integrated Cloud-based Healthcare Infrastructure
Abstract—We present a cloud-based healthcare system that integrates a formal care system (DACAR) with an informal care system (Microsoft HealthVault). The system provides high levels of security and privacy within a cloud environment, enabling sharing of both health records and the access rights, along the patient pathway. We also define a case study that can help in evaluating and in demonstrating the usefulness of a cloud-based integrated health care system
ATP signalling in epilepsy
This paper focuses on a role for ATP neurotransmission and gliotransmission in the pathophysiology of epileptic seizures. ATP along with gap junctions propagates the glial calcium wave, which is an extraneuronal signalling pathway in the central nervous system. Recently astrocyte intercellular calcium waves have been shown to underlie seizures, and conventional antiepileptic drugs have been shown to attenuate these calcium waves. Blocking ATP-mediated gliotransmission, therefore, represents a potential target for antiepileptic drugs. Furthermore, while knowledge of an antiepileptic role for adenosine is not new, a recent study showed that adenosine accumulates from the hydrolysis of accumulated ATP released by astrocytes and is believed to inhibit distant synapses by acting on adenosine receptors. Such a mechanism is consistent with a surround-inhibitory mechanism whose failure would predispose to seizures. Other potential roles for ATP signalling in the initiation and spread of epileptiform discharges may involve synaptic plasticity and coordination of synaptic networks. We conclude by making speculations about future developments
Bio-inspired algorithm optimization of neural network for the prediction of Dubai crude oil price
Previous studies proposed several bio-inspired algorithms for the optimization
of Neural Network (NN) to avoid local minima and to improve accuracy
and convergence speed. To advance the performance of NN, a new bio-inspired algorithm
called Flower Pollination Algorithm (FPA) is used to optimize the weights and
bias of NN due to its ability to explore very large search space and frequent chosen
of similar solution. The FPA optimized NN (FPNN) was applied to build a
model for the prediction of Dubai crude oil price unlike previous studies that mainly
focus on theWest Texas Intermediate and Brent crude oil price benchmarks. Result
Emergent properties of neural repair: elemental biology to therapeutic concepts
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137471/1/ana24653_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137471/2/ana24653.pd
Neuroprotection by adenosine in the brain: From A1 receptor activation to A2A receptor blockade
Adenosine is a neuromodulator that operates via the most abundant inhibitory adenosine A1 receptors (A1Rs) and the less abundant, but widespread, facilitatory A2ARs. It is commonly assumed that A1Rs play a key role in neuroprotection since they decrease glutamate release and hyperpolarize neurons. In fact, A1R activation at the onset of neuronal injury attenuates brain damage, whereas its blockade exacerbates damage in adult animals. However, there is a down-regulation of central A1Rs in chronic noxious situations. In contrast, A2ARs are up-regulated in noxious brain conditions and their blockade confers robust brain neuroprotection in adult animals. The brain neuroprotective effect of A2AR antagonists is maintained in chronic noxious brain conditions without observable peripheral effects, thus justifying the interest of A2AR antagonists as novel protective agents in neurodegenerative diseases such as Parkinson’s and Alzheimer’s disease, ischemic brain damage and epilepsy. The greater interest of A2AR blockade compared to A1R activation does not mean that A1R activation is irrelevant for a neuroprotective strategy. In fact, it is proposed that coupling A2AR antagonists with strategies aimed at bursting the levels of extracellular adenosine (by inhibiting adenosine kinase) to activate A1Rs might constitute the more robust brain neuroprotective strategy based on the adenosine neuromodulatory system. This strategy should be useful in adult animals and especially in the elderly (where brain pathologies are prevalent) but is not valid for fetus or newborns where the impact of adenosine receptors on brain damage is different
Gi/o-protein coupled receptors in the aging brain
Cells translate extracellular signals to regulate processes such as differentiation, metabolism and proliferation, via transmembranar receptors. G protein-coupled receptors (GPCRs) belong to the largest family of transmembrane receptors, with over 800 members in the human species. Given the variety of key physiological functions regulated by GPCRs, these are main targets of existing drugs. During normal aging, alterations in the expression and activity of GPCRs have been observed. The central nervous system (CNS) is particularly affected by these alterations, which results in decreased brain functions, impaired neuroregeneration, and increased vulnerability to neuropathologies, such as Alzheimer's and Parkinson diseases. GPCRs signal via heterotrimeric G proteins, such as Go, the most abundant heterotrimeric G protein in CNS. We here review age-induced effects of GPCR signaling via the Gi/o subfamily at the CNS. During the aging process, a reduction in protein density is observed for almost half of the Gi/o-coupled GPCRs, particularly in age-vulnerable regions such as the frontal cortex, hippocampus, substantia nigra and striatum. Gi/o levels also tend to decrease with aging, particularly in regions such as the frontal cortex. Alterations in the expression and activity of GPCRs and coupled G proteins result from altered proteostasis, peroxidation of membranar lipids and age-associated neuronal degeneration and death, and have impact on aging hallmarks and age-related neuropathologies. Further, due to oligomerization of GPCRs at the membrane and their cooperative signaling, down-regulation of a specific Gi/o-coupled GPCR may affect signaling and drug targeting of other types/subtypes of GPCRs with which it dimerizes. Gi/o-coupled GPCRs receptorsomes are thus the focus of more effective therapeutic drugs aiming to prevent or revert the decline in brain functions and increased risk of neuropathologies at advanced ages.This work was supported by Fundação para a Ciência e
Tecnologia, Centro 2020 and Portugal 2020, the COMPETE
program, QREN, and the European Union (FEDER program)
via the GoBack project (PTDC/CVT-CVT/32261/2017),
the pAGE program (Centro-01-0145-FEDER-000003), and
Institute for Biomedicine iBiMED (UID/BIM/04501/2013;
UID/BIM/04501/2019).publishe
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