A sustainable electrical interface to mitigate emissions due to power supply in ports

The paper presents a proposal of an innovative sustainable power supply solution for seaports with the related design and control. This solution differs from the classical solution for the presence of a smart electrical interface composed by two basic components: the first one, a rotating converter instead of the widely used static converter that ensures higher and therefore much more detectable short-circuit currents; the second, an advanced static var compensator specifically designed for enhancing power quality issues and hence favoring these seaport connection to the main grid for cold ironing applications. The designed control strategy for the tailored power supply solution is proven successful and effective by the numerical applications reported in the last part of the paper

Affine arithmetic-based methodology for energy hub operation-scheduling in the presence of data uncertainty

In this study, the role of self-validated computing for solving the energy hub-scheduling problem in the presence of multiple and heterogeneous sources of data uncertainties is explored and a new solution paradigm based on affine arithmetic is conceptualised. The benefits deriving from the application of this methodology are analysed in details, and several numerical results are presented and discussed

Enhancement of Short-Term prediction capabilities of Inter-Area Grid Oscillations with a Multi-Variate Ensemble-based Method.

The actual and future even higher penetration of renewable energy sources into the power grid sets challenging issues for transmission system operators, especially concerning the hard-to-solve problem of inter-area electromechanical oscillations. Despite the useful existing monitoring systems, the possibility of having predictive monitoring features for such phenomena could be an appealing tool. The work presented in this paper aims to assess the possibility of enhancing the predictive monitoring features offered by machine learning techniques based on the combination of ensemble methods and Long-Short-Term Memory units using multi-variate methods. The development steps of a multi-variate prediction strategy are presented together with the assessment of its performance versus uni-variate solutions. The assessment takes into account different kinds of datasets, taken from real grid measurements, and strategy configurations. Either transient low frequency oscillation phenomena or normal grid operation are considered as representative cases of real-world scenarios. Finally, some preliminary considerations about improving prediction performance and the limitations are outlined

Investigating alkyl nitrates as nitric oxide releasing precursors of multitarget acetylcholinesterase-monoamine oxidase B inhibitors

Herein we envisaged the possibility of exploiting alkyl nitrates as precursors of alcohol-bearing dual inhibitors targeting acetylcholinesterase (AChE) and monoamine oxidase B (MAO B), key enzymes in neurodegenerative syndromes such as Alzheimer's disease (AD), through biotransformation unmasking an alcoholic function upon nitric oxide (NO) release. The cooperation to neuroprotection of low fluxes of NO and target enzymes’ inhibition by the alcohol metabolites might return a multitargeting effect. The in vitro screening towards ChEs and MAOs of a collection of 21 primary alcohols disclosed a subset of dual inhibitors, among which three diverse chemotypes were selected to study the corresponding nitrates. Nitrate 14 proved to be a brain permeant, potent AChE-MAO B inhibitor by itself. Moreover, it protected human SH-SY5Y lines against rotenone and hydrogen peroxide with a poor inherent cytotoxicity and showed a slow conversion profile to its alcohol metabolite 9d that still behaved as bimodal and neuroprotective molecule

First-in-Class Isonipecotamide-Based Thrombin and Cholinesterase Dual Inhibitors with Potential for Alzheimer Disease

Recently, the direct thrombin (thr) inhibitor dabigatran has proven to be beneficial in animal models of Alzheimer’s disease (AD). Aiming at discovering novel multimodal agents addressing thr and AD-related targets, a selection of previously and newly synthesized potent thr and factor Xa (fXa) inhibitors were virtually screened by the Multi-fingerprint Similarity Searching aLgorithm (MuSSeL) web server. The N-phenyl-1-(pyridin-4-yl)piperidine-4-carboxamide derivative 1, which has already been experimentally shown to inhibit thr with a Ki value of 6 nM, has been flagged by a new, upcoming release of MuSSeL as a binder of cholinesterase (ChE) isoforms (acetyl- and butyrylcholinesterase, AChE and BChE), as well as thr, fXa, and other enzymes and receptors. Interestingly, the inhibition potency of 1 was predicted by the MuSSeL platform to fall within the low-to-submicromolar range and this was confirmed by experimental Ki values, which were found equal to 0.058 and 6.95 μM for eeAChE and eqBChE, respectively. Thirty analogs of 1 were then assayed as inhibitors of thr, fXa, AChE, and BChE to increase our knowledge of their structure-activity relationships, while the molecular determinants responsible for the multiple activities towards the target enzymes were rationally investigated by molecular cross-docking screening

Pharmacophore Modeling and 3D-QSAR Study of Indole and Isatin Derivatives as Antiamyloidogenic Agents Targeting Alzheimer's Disease

Thirty-six novel indole-containing compounds, mainly 3-(2-phenylhydrazono) isatins and structurally related 1H-indole-3-carbaldehyde derivatives, were synthesized and assayed as inhibitors of beta amyloid (Aβ) aggregation, a hallmark of pathophysiology of Alzheimer's disease. The newly synthesized molecules spanned their IC50 values from sub- to two-digit micromolar range, bearing further information into structure-activity relationships. Some of the new compounds showed interesting multitarget activity, by inhibiting monoamine oxidases A and B. A cell-based assay in tau overexpressing bacterial cells disclosed a promising additional activity of some derivatives against tau aggregation. The accumulated data of either about ninety published and thirty-six newly synthesized molecules were used to generate a pharmacophore hypothesis of antiamyloidogenic activity exerted in a wide range of potencies, satisfactorily discriminating the 'active' compounds from the 'inactive' (poorly active) ones. An atom-based 3D-QSAR model was also derived for about 80% of 'active' compounds, i.e., those achieving finite IC50 values lower than 100 μM. The 3D-QSAR model (encompassing 4 PLS factors), featuring acceptable predictive statistics either in the training set (n = 45, q2 = 0.596) and in the external test set (n = 14, r2ext = 0.695), usefully complemented the pharmacophore model by identifying the physicochemical features mainly correlated with the Aβ anti-aggregating potency of the indole and isatin derivatives studied herein

Bionic for Training: Smart Framework Design for Multisensor Mechatronic Platform Validation

: Home monitoring supports the continuous improvement of the therapy by sharing data with healthcare professionals. It is required when life-threatening events can still occur after hospital discharge such as neonatal apnea. However, multiple sources of external noise could affect data quality and/or increase the misdetection rate. In this study, we developed a mechatronic platform for sensor characterizations and a framework to manage data in the context of neonatal apnea. The platform can simulate the movement of the abdomen in different plausible newborn positions by merging data acquired simultaneously from three-axis accelerometers and infrared sensors. We simulated nine apnea conditions combining three different linear displacements and body postures in the presence of self-generated external noise, showing how it is possible to reduce errors near to zero in phenomena detection. Finally, the development of a smart 8Ws-based software and a customizable mobile application were proposed to facilitate data management and interpretation, classifying the alerts to guarantee the correct information sharing without specialized skills

Structure-Based Design and Optimization of Multitarget-Directed 2H-Chromen-2-one Derivatives as Potent Inhibitors of Monoamine Oxidase B and Cholinesterases

The multifactorial nature of Alzheimer’s disease calls for the development of multitarget agents addressing key pathogenic processes. To this end, by following a docking-assisted hybridization strategy, a number of aminocoumarins were designed, prepared, and tested as monoamine oxidases (MAOs) and acetyl- and butyryl-cholinesterase (AChE and BChE) inhibitors. Highly flexible N-benzyl-N-alkyloxy coumarins 2–12 showed good inhibitory activities at MAO-B, AChE, and BChE but low selectivity. More rigid inhibitors, bearing meta- and para-xylyl linkers, displayed good inhibitory activities and high MAO-B selectivity. Compounds 21, 24, 37, and 39, the last two featuring an improved hydrophilic/lipophilic balance, exhibited excellent activity profiles with nanomolar inhibitory potency toward hMAO-B, high hMAO-B over hMAO-A selectivity and submicromolar potency at hAChE. Cell-based assays of BBB permeation, neurotoxicity, and neuroprotection supported the potential of compound 37 as a BBB-permeant neuroprotective agent against H2O2-induced oxidative stress with poor interaction as P-gp substrate and very low cytotoxicity