105,242 research outputs found
Ligand Binding to Telomeric DNA G-quadruplex through Metadynamics Calculations
No full textTelomeres are DNA-proteins complexes which protect the ends of human chromosomes. Telomeric DNA consists of repetitive Guanine-rich (G-rich) sequences which can fold into unusual structural motifs termed G-quadruplexes (G4). In recent times, DNA G4 have emerged as promising targets in anticancer therapy since G4 ligands are able to promote apoptosis in tumor cells. Most of G4 binders are end-stackers whose clinical use is hampered by poor drug-like properties and weak selectivity. Such properties are instead improved in G4 groove binders. Among these, 3-benzothiazol-2-yl-7-hydroxy-8-{[4-(2-hydroxyethyl)piperazinyl]methyl}chrom-en-2-one has been identified as a potent groove binder of the G4 [d(TGGGGT)]4. Here we have set up a metadynamics-based protocol to disclose at molecular level the binding mechanism of this compound to the G4 [d(TGGGGT)]4. Our approach has allowed dealing with target flexibility and solvation during ligand binding and computing the binding free energy of the ligand/DNA G4 complex. Finally, once the binding free energy surface was converged, the lowest energy binding modes have been identified. Our computational protocol is of valuable help for future studies on ligand/DNA interaction and the development of new potent and selective DNA binders
Risk-based optimization of operational procedures
No full textThe maturity of management systems allows drawing the conclusion that in modern industries the activities are mostly written, consolidated and verified within operational procedures. This also applies for the activities that are carried out infrequently, e.g., rare maintenance or testing activities, that being uncommon, are less known and thus characterized by an higher potential risk. In order to optimize the procedure, both from the productivity and from the safety (occupational and process) point of view, a risk assessment of the procedure has to be performed, highlighting which of the tasks within the procedure mainly contributes to the risk of the working activity. Usually the analysis of the procedures is carried on through a task analysis (as in Builes et al., 2014). In this paper the task analysis is used as a starting point for a quantitative risk assessment carried on through an integrated decision analysis (as in Leva et al., 2015). Through the integrated decision analysis, the logical-probabilistic model of the procedure is elaborated jointly with a consequences estimation obtaining a risk assessment for all the sequences of tasks from work procedure under analysis. The comparative risk analysis considered two (original and optimized) procedure alternatives. The risk assessment considered both possible equipment failures and the potential personnel errors in executing, mainly manual, testing procedure. In this paper, an application of the integrated decision analysis, through the SPACCO software tool, is shown for a cold water pressure test of the LPG storage tank in industrial installation. The risk has been assessed in terms of delays in the operations and economical impact in case of occupational and/or process accidents. Observing the variation of the risk distribution the procedure optimization has been performed and the risk reduction calculated
Morfo-anatomia e fisiologia dell’ape
No full textAnatomia dell'ape mellifera. Fisiologia dell'ape e dell'alveare
Performance analysis of a hybrid micro-grid in Somalia
No full textThis paper presents a data analysis of an islanded diesel-PV-battery system, placed in Somalia. Operation of each generator is observed, concerning the most relevant performance indicators. Analysis is carried out during the first 11 months of operation, from November 2015 to September 2016. Investigations are divided into two periods, according to a significant load variation due to the connection of a new distribution line to the power plant. Thus, a comparison on load demand sharing among generators is realized between the two periods. In conclusion, benefits in terms of fuel consumption, CO2emissions and money savings are presented
Ensuring consistency in scalable-detail models for DT-based control
No full textDigital Twins (DTs for short) are a powerful aid for creating, assessing and maintaining control strategies. This use of DTs however requires that the physical entities to control be described at different levels of detail. For example, simple I/O models are used to compute parameters of modulating controllers, more time-accurate ones may be required to set up and assess logic controls, high-accuracy, possibly nonlinear ones may serve for overall strategy verification, and for software-in-the-loop testing, also the host computing/network architecture needs representing. In such a complex scenario, guaranteeing that all the descriptions of all elements are consistent with one another is a relevant problem. We discuss this matter and propose a solution, in the form of a modelling paradigm where - as a novel contributions - relationships (in a sense analogous to what the term means in database theory) can be instated and enforced. This allows to create and maintain knowledge based made of interrelate data and models, embracing all the major DT interpretations proposed so far in the literature, or said more explicitly, combining data-driven and model-driven DTs in a single framework. We also provide an illustrative example
VALIDATION OF DRUM BOILER MODELS THROUGH COMPLETE DYNAMIC TESTS
No full textThis paper describes the validation of a model library for the simulation of drum boilers on the basis of static and dynamic experimental data obtained from a small-scale plant. All the steps of the validation process are described in detail, with particular reference to the modelling principles, to the trade-off between model complexity and accuracy, to the solution strategy and to the data-reconciliation policy. The results of the validation have formed an important knowledge base, which might be made available to other research groups
Fine-Grained Dynamic Resource Allocation for Big-Data Applications
No full textMany big-data applications are batch applications that exploit dedicated frameworks to perform massively parallel computations across clusters of machines. The time needed to process the entirety of the inputs represents the application's response time, which can be subject to deadlines. Spark, probably the most famous incarnation of these frameworks today, allocates resources to applications statically at the beginning of the execution and deviations are not managed: to meet the applications' deadlines, resources must be allocated carefully. This paper proposes an extension to Spark, called dynaSpark, that is able to allocate and redistribute resources to applications dynamically to meet deadlines and cope with the execution of unanticipated applications. This work is based on two key enablers: containers, to isolate Spark's parallel executors and allow for the dynamic and fast allocation of resources, and control-theory to govern resource allocation at runtime and obtain required precision and speed. Our evaluation shows that dynaSpark can (i) allocate resources efficiently to execute single applications with respect to set deadlines and (ii) reduce deadline violations (w.r.t. Spark) when executing multiple concurrent applications
Harmonising and integrating the Digital Twins multiverse: A paradigm and a toolset proposal
No full textDigital Twins are of paramount relevance in the Industry 4.0 framework. However, the idea of Digital Twin has many different interpretations. These are tied to the intended use of a Digital Twin, thus to the viewpoint of the involved professionals (process designers, control specialists, managers, and so on). The said interpretations are often highly incompatible with one another, since they can involve as heterogeneous entities as a CAD drawing and a neural network. A convergence of Digital Twin interpretations is desirable, to take full profit of the contained knowledge. In this research we argue that this desired convergence cannot be found at the same abstraction level of the available Digital Twin interpretations, and calls for a higher one. We consequently propose a paradigm – that we name Digital Multiverse – to comprehend the major Digital Twin interpretations not only in the sense of data integration, which is the goal of promising complementary ideas like that of Asset Administration Shell, but also by establishing and enforcing consistency rules that involve both data and models. We also show some examples to support the usefulness and viability of our proposal
HOT-SPOT PHENOMENON IN PV SYSTEMS WITH OVERHEAD LINES PARTIAL SHADING
No full textThis paper deals with the occurrence of hot-spot phenomenon in photovoltaic systems under PV partial shadowing. In an experimental campaign, the hot-spot phenomenon was revealed on a PV installation in Italy, caused my medium voltage overhead lines shadowing the PV cells. Starting from these practice case studies, at the SolarTech laboratory of Politecnico di Milano, the conditions for hot-spot phenomenon occurrence due to the overhead lines shading the PV cells were reproduced. Two experimental campaigns were carried out to investigate the current-voltage and power-voltage characteristics, and the energy production. In each experimental campaign, the built shadowing structure was considered fixed, and different shadowing conditions were created based on the natural displacement of the sun. Still, for occurring the hot- spot phenomenon during the laboratory tests, more PV modules must be connected in parallel
Implementation of different pv forecast approaches in a multigood microgrid: Modeling and experimental results
No full textMicrogrids represent a flexible way to integrate renewable energy sources with program-mable generators and storage systems. In this regard, a synergic integration of those sources is cru-cial to minimize the operating cost of the microgrid by efficient storage management and generation scheduling. The forecasts of renewable generation can be used to attain optimal management of the controllable units by predictive optimization algorithms. This paper introduces the implementation of a two-layer hierarchical energy management system for islanded photovoltaic microgrids. The first layer evaluates the optimal unit commitment, according to the photovoltaic forecasts, while the second layer deals with the power-sharing in real time, following as close as possible the daily schedule provided by the upper layer while balancing the forecast errors. The energy management system is experimentally tested at the Multi-Good MicroGrid Laboratory under three different pho-tovoltaic forecast models: (i) day-ahead model, (ii) intraday corrections and (iii) nowcasting tech-nique. The experimental study demonstrates the capability of the proposed management system to operate an islanded microgrid in safe conditions, even with inaccurate day-ahead photovoltaic fore-casts
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