scholarly journals SBML2Modelica: integrating biochemical models within open-standard simulation ecosystems

2019 ◽  
Vol 36 (7) ◽  
pp. 2165-2172 ◽  
Author(s):  
F Maggioli ◽  
T Mancini ◽  
E Tronci

Abstract Motivation SBML is the most widespread language for the definition of biochemical models. Although dozens of SBML simulators are available, there is a general lack of support to the integration of SBML models within open-standard general-purpose simulation ecosystems. This hinders co-simulation and integration of SBML models within larger model networks, in order to, e.g. enable in silico clinical trials of drugs, pharmacological protocols, or engineering artefacts such as biomedical devices against Virtual Physiological Human models. Modelica is one of the most popular existing open-standard general-purpose simulation languages, supported by many simulators. Modelica models are especially suited for the definition of complex networks of heterogeneous models from virtually all application domains. Models written in Modelica (and in 100+ other languages) can be readily exported into black-box Functional Mock-Up Units (FMUs), and seamlessly co-simulated and integrated into larger model networks within open-standard language-independent simulation ecosystems. Results In order to enable SBML model integration within heterogeneous model networks, we present SBML2Modelica, a software system translating SBML models into well-structured, user-intelligible, easily modifiable Modelica models. SBML2Modelica is SBML Level 3 Version 2—compliant and succeeds on 96.47% of the SBML Test Suite Core (with a few rare, intricate and easily avoidable combinations of constructs unsupported and cleanly signalled to the user). Our experimental campaign on 613 models from the BioModels database (with up to 5438 variables) shows that the major open-source (general-purpose) Modelica and FMU simulators achieve performance comparable to state-of-the-art specialized SBML simulators. Availability and implementation SBML2Modelica is written in Java and is freely available for non-commercial use at https://bitbucket.org/mclab/sbml2modelica.

2021 ◽  
pp. 088541222199424
Author(s):  
Mauro Francini ◽  
Lucia Chieffallo ◽  
Annunziata Palermo ◽  
Maria Francesca Viapiana

This work aims to reorganize theoretical and empirical research on smart mobility through the systematic literature review approach. The research goal is to reach an extended and shared definition of smart mobility using the cluster analysis. The article provides a summary of the state of the art that can have broader impacts in determining new angles for approaching research. In particular, the results will be a reference for future quantitative developments for the authors who are working on the construction of a territorial measurement model of the smartness degree, helping them in identifying performance indicators consistent with the definition proposed.


2022 ◽  
Vol 15 (2) ◽  
pp. 1-27
Author(s):  
Andrea Damiani ◽  
Giorgia Fiscaletti ◽  
Marco Bacis ◽  
Rolando Brondolin ◽  
Marco D. Santambrogio

“Cloud-native” is the umbrella adjective describing the standard approach for developing applications that exploit cloud infrastructures’ scalability and elasticity at their best. As the application complexity and user-bases grow, designing for performance becomes a first-class engineering concern. As an answer to these needs, heterogeneous computing platforms gained widespread attention as powerful tools to continue meeting SLAs for compute-intensive cloud-native workloads. We propose BlastFunction, an FPGA-as-a-Service full-stack framework to ease FPGAs’ adoption for cloud-native workloads, integrating with the vast spectrum of fundamental cloud models. At the IaaS level, BlastFunction time-shares FPGA-based accelerators to provide multi-tenant access to accelerated resources without any code rewriting. At the PaaS level, BlastFunction accelerates functionalities leveraging the serverless model and scales functions proactively, depending on the workload’s performance. Further lowering the FPGAs’ adoption barrier, an accelerators’ registry hosts accelerated functions ready to be used within cloud-native applications, bringing the simplicity of a SaaS-like approach to the developers. After an extensive experimental campaign against state-of-the-art cloud scenarios, we show how BlastFunction leads to higher performance metrics (utilization and throughput) against native execution, with minimal latency and overhead differences. Moreover, the scaling scheme we propose outperforms the main serverless autoscaling algorithms in workload performance and scaling operation amount.


Ekonomika ◽  
2004 ◽  
Vol 68 ◽  
Author(s):  
Gediminas Ramanauskas

Competitiveness can be defined in a number of ways. We can think of it as of a successful performance of a company or organization; or we may talk about competitiveness in a macro context such as a favourable exchange rate of a national currency. Can we also talk about competitiveness of a nation? What is it and how can it be evaluated?There does not seem to be a common definition of what the international competitiveness of nations is. Some feel that the very notion of international competitiveness of nations is unfair and unacceptable. They argue that the nations themselves do not compete, their enterprises do. For others the notion of international competitiveness of nations is fair. They believe that creating appropriate measures of international competitiveness is central for tracking and understanding the sources of competitiveness of countries.In this paper I classify and compare the measures developed by various authors. I suggest that the studies on the measurement of competitiveness can be classified into five groups:1. Particular sector studies.2. Competitiveness studies at the regional / country level.3. Particular competitiveness indicator studies.4. Competitiveness studies at an international level.5. Cross-country economic policy studies.Since the competitiveness studies serve a different audience and purpose, we cannot discuss which is best without first asking: best at what?


Author(s):  
Rosa Romano

The Smart Skin Envelope research analyses the recent revolution that has taken place in the sector of planning and production of smart skin components, made up of dynamic layers. The aim is to identify the technological, functional, qualitative and performance parameters that guide the decisions of the actors in the innovation process. It explores the factors that drive them to develop solutions and proposals designed to transform the envelope of the building from a static to a dynamic element, featuring interoperable components that can interact with the input from the outdoor and indoor environments, in relation to which the smart skin acts as a system of boundary and delimitation. The proposed research programme explores in particular the sector of Smart Envelopes, setting as its priority objective the identification and definition of the energy performance, both through analysis of the state of the art and through the development of a facade component that is dynamic in terms of the adaptive variability of its performance.


Actuators ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 215
Author(s):  
Antonio Carlo Bertolino ◽  
Andrea De Martin ◽  
Giovanni Jacazio ◽  
Massimo Sorli

Electro-hydraulic servo-actuators (EHSAs) are currently considered the state-of-the art solution for the control of the primary flight control systems of civil and military aircraft. Combining the expected service life of a commercial aircraft with the fact that electro-hydraulic technology is employed in the vast majority of currently in-service aircraft and is planned to be used on future platforms as well, the development of an effective Prognostic and Health Management (PHM) system could provide significant advantages to fleet operators and aircraft maintenance, such as the reduction of unplanned flight disruptions and increased availability of the aircraft. The occurrence of excessive internal leakage within the EHSAs is one of the most common causes of return from the field of flight control actuators, making this failure mode a priority in the definition of any dedicated PHM routine. This paper presents a case study on the design of a prognostic system for this degradation mode, in the context of a wider effort toward the definition of a prognostic framework suitable to work on in-flight data. The study is performed by means of a high-fidelity simulation model supported by experimental activities. Results of both the simulation and the experimental work are used to select a suitable feature, then implemented within the prognostic framework based on particle filtering. The algorithm is at first theoretically discussed, and then tested against several degradation patterns. Performances are evaluated through state-of-the-art metrics, showing promising results and providing the basis towards future applications on real in-flight data.


2020 ◽  
Vol 34 (07) ◽  
pp. 11029-11036
Author(s):  
Jiabo Huang ◽  
Qi Dong ◽  
Shaogang Gong ◽  
Xiatian Zhu

Convolutional neural networks (CNNs) have achieved unprecedented success in a variety of computer vision tasks. However, they usually rely on supervised model learning with the need for massive labelled training data, limiting dramatically their usability and deployability in real-world scenarios without any labelling budget. In this work, we introduce a general-purpose unsupervised deep learning approach to deriving discriminative feature representations. It is based on self-discovering semantically consistent groups of unlabelled training samples with the same class concepts through a progressive affinity diffusion process. Extensive experiments on object image classification and clustering show the performance superiority of the proposed method over the state-of-the-art unsupervised learning models using six common image recognition benchmarks including MNIST, SVHN, STL10, CIFAR10, CIFAR100 and ImageNet.


2021 ◽  
Author(s):  
Jinfeng Liu ◽  
Jianwei Dong ◽  
Xuwen Jing ◽  
Xuwu Cao ◽  
Chenxiao Du ◽  
...  

Abstract In the process design and reuse of marine component products, there are a lot of heterogeneous models, causing the problem that the process knowledge and process design experience contained in them are difficult to express and reuse. Therefore, a process knowledge representation model for ship heterogeneous model is proposed in this paper. Firstly, the multi-element process knowledge graph is constructed, and the heterogeneous ship model is described in a unified way. Then, the multi-strategy ontology mapping method is applied, and the semantic expression between the process knowledge graph and the entity model is realized. Finally, by obtaining implicit semantics based on case-based reasoning and checking the similarity of the matching results, the case knowledge reuse is achieved, to achieve rapid design of the process. This method provides reliable technical support for the design of ship component assembly and welding process, greatly shortens the design cycle, and improves the working efficiency. In addition, a case study of the test model is carried out to verify the feasibility and efficiency of the proposed method.


Author(s):  
O.I. Zozuliak

The article is devoted to the theoretical and legal analysis of issues related to the range of problems connected with development of such legal model as ‘nonentrepreneurial legal entity’. In the scientific work the author makes an analysis of those concepts which are submitted by the leading Ukrainian scholars and concern the formation of civil-law terminology in general and that is applied to the nonentrepreneurial legal entities, in particular. The author has concluded that it is expedient to apply the set of criteria during formation of the non-entrepreneurial legal entity. The article gives the definition of non-entrepreneurial legal entity in the narrow and broad meanings. It is proved that a non-business entity should be singled out as a separate category according to the non-distribution of profit (income) rather than to the specifics of its business activity. The author demonstrates the feasibility to change classification criteria and levels while classifying the legal entities and on the mentioned ground she has singled out: 1) procedure for establishment of the legal entity; 2) structure of the legal entity as a criterion of the second classification level; 3) specific character of the profit distribution as a criterion of the third level of classification. It is based on the argument that non-business entities are an independent group of the legal entities, which is divided into subgroups: the non-business entities of corporate type and the non-business entities of unitary type. Each subgroup of the non-business legal entity distinguishes several legal forms within of which specific types of non-business entities are allocated. The author presents one’s own definition of the non-entrepreneurial legal entity, as a legal entity of public or private law, whether of corporate or unitary type, which is specially established in the different areas of social life and endowed with a special legal capacity. The non-entrepreneurial legal entity shall be entitled to carry out activities with a view to profit but it doesn’t distribute it among participants (members).


Author(s):  
Pushpak Bhattacharyya ◽  
Mitesh Khapra

This chapter discusses the basic concepts of Word Sense Disambiguation (WSD) and the approaches to solving this problem. Both general purpose WSD and domain specific WSD are presented. The first part of the discussion focuses on existing approaches for WSD, including knowledge-based, supervised, semi-supervised, unsupervised, hybrid, and bilingual approaches. The accuracy value for general purpose WSD as the current state of affairs seems to be pegged at around 65%. This has motivated investigations into domain specific WSD, which is the current trend in the field. In the latter part of the chapter, we present a greedy neural network inspired algorithm for domain specific WSD and compare its performance with other state-of-the-art algorithms for WSD. Our experiments suggest that for domain-specific WSD, simply selecting the most frequent sense of a word does as well as any state-of-the-art algorithm.


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