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

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

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

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

An Original Educational Algorithm Assessing the Behaviours of Angular Frequency Deviations of a Multimachine System in Small Signal Analysis

The paper presents a fully self-implementable algorithm that has demonstrated to be an effective tool for power education at the University of Padova-Department of Industrial Engineering. It deals with the small signal analysis of the electromechanical transients of a multimachine system. The algorithm allows analytically building both the state matrix and the input matrix. Moreover, by exploiting the matrix exponential, the angular frequency deviations of synchronous generators can be computed and plotted so to help students to evaluate transient stability. Besides the full exposition of the algorithm, the paper presents a comparison between a self-implemented linearized dynamic in Matlab environment and the dynamic simulation obtained by the commercial software DIgSILENT PowerFactory

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

Real Time tracking of electromechanical oscillations in ENTSO-e Continental European Synchronous Area

Small signal stability is a crucial aspect to accurately keep under control in modern interconnected power systems in order to ensure their security and reliability. Such an aspect could represent a serious limiting factor in the search for ever higher power systems exploitation levels. Power oscillations not well-damped may jeopardize the system integrity on large scale: several incidents caused by the establishment of large oscillations have been recorded in the past around the world. Therefore, a basic assessment that must be done before setting a certain optimal operational framework is the determination of the actual dynamic stability margins. The fast deployment of measurement and instrumentation facilities provided by the Wide Area Measurement Systems (WAMS) technology offers a valid support in this sense. Large amount of data coming from Phasor Measurement Units (PMU) installed in the key points of power systems (e.g. primary substations) increases the Transmission System Operators (TSO) situational awareness. Thanks to accurate and timely information the stability margins can be precisely determined and optimized so that power systems can be operated at their actual full capacity while staying within the stability boundaries. A deep investigation about the WAMS currently in operation or under testing around the world confirms how power oscillations tracking is one of the main functionality/application envisaged in these architectures. Real time detection of dangerous power oscillations and hence their related continuous parameters estimation, in wide area sense, is vital in the framework pointed out above. The output of this task is therefore represented by estimates of the oscillations fundamental parameters (e.g. frequency, damping factor/ratio, amplitude and phase). If potential unstable phenomena are detected (e.g. estimating a damping ratio lower than a certain threshold value) all the necessary countermeasures have to be implemented for restoring secure and stable operating conditions (e.g. generators’ re-dispatch, tie line flows adjustment, load reduction, network topology change etc.). It was moreover found that the major problems which characterize these infrastructures rely on their own technological complexity, on the data management but especially on the research of robust identification techniques for implementing all the Dynamic Security Assessment (DSA) tasks that must be run in parallel in the central control centres. In this regard, two fundamental approaches could be applied for tracking the electromechanical modes in an electrical power system. Model-based methods (a.k.a. Component-based method), which use an electric power system model linearized around a certain equilibrium point to identify the electromechanical modes characteristics through eigenvalue analysis (whose chief rudiments are reported in the Chapter 3). Eigenvalue analysis is not suitable for on-line tracking, especially for large scale power systems due to both high computational time and uncertainties in power system modeling. Measurement-based methods (a.k.a. Mode Meters), estimate an updated model of the electric power system from direct system measurements which come from measurement devices installed on power systems. These techniques, freeing themselves from the system modeling, they consider the power system as a black box and by making use of the signal processing expertise, estimate the modal content of the acquired signals. Being moreover less expensive than the first class of methods in large scale power systems model set up, it appears clear that they are suitable for an on-line DSA task. However, the set of available measurement-based estimation techniques is fairly wide. Besides I note that relevant journal databases are regularly filled by novel more and more advanced algorithms. My personal feeling in this regard is that the basic methodologies are really few, while several refinements of the same algorithms, aimed at overcoming specific weaknesses, are regularly proposed. From the experience gained working hardly on the topic I can state that no best estimator exists due to the lack of an accepted definition of optimality. Furthermore, it is a difficult task to assess the performance of different estimation methods because each of them was initially designed for a specific field, has its own features and sometimes presents parameters chosen according to experience or through heuristic considerations. This means that for instance a method could show good performance in damping and frequency estimation if the modes number is known while may fail if it is not know in advance. In addition, a method could work better than another for noiseless sampled signals while could deteriorate its efficiency when the signal-to-noise ratio (SNR) decreases. Nonetheless, there exist estimation techniques which are “generally” characterized by good performance with respect to the others. The meaning of the term “generally” should be intended as “with respect to the main situations that may occur”(different data typologies, various SNR levels, a priori knowledge of the intrinsic power system modes etc.). A wide set of estimation techniques will be analyzed in the present thesis. Afterwards, a performance comparison among the techniques will be accomplished with the objective of pointing out strengths and drawbacks of each of them. Once ascertained the points to improve, three novel estimation algorithms will be introduced. They represent a good complementary tool to the ordinary model-based methods implemented in the central control centres for real time monitoring power system oscillations. Almost all the estimation algorithms considered in the thesis were tested in real time on the Italian WAMS thanks to the support of the TSO, Terna. The complex infrastructure owned by Terna, thanks also to the real time information exchange with some European partners, represents a vigilant eye on the entire European Network of Transmission System Operators for electricity-Continental European Synchronous Area (ENTSO-e CESA) for the purposes of analysis. The emphasis of this research was hence to tailor high accurate and resilient estimation algorithms for real time monitoring of electromechanical oscillations, in particular of inter-area type, in such a large interconnected system. Although the doctorate course ends achieving the predetermined objectives the research on the topic will continue