A Blockchain-Based Solution for Enabling Log-Based Resolution of Disputes in Multi-party Transactions

We are witnessing an ongoing global trend towards the automation of almost any transaction through the employment of some Internet-based mean. Furthermore, the large spread of cloud computing and the massive emergence of the software as a service (Saas) paradigm have unveiled many opportunities to combine distinct services, provided by different parties, to establish higher level and more advanced services, that can be offered to end users and enterprises. Business-to-business (B2B) integration and third-party authorization (i.e. using standards like OAuth) are examples of processes requiring more parties to interact with each other to deliver some desired functionality. These kinds of interactions mostly consist of transactions and are usually regulated by some agreement which defines the obligations that involved parties have to comply with. In case one of the parties claims a violation of some clause of such agreement, disputes can occur if the party accused of the infraction refuses to recognize its fault. Moreover, in case of auditing, for convenience reasons a party may deny to have taken part in a given transaction, or may forge historical records related to that transaction. Solutions based on a trusted third party (TTP) have drawbacks: high overhead due to the involvement of an additional party, possible fees to pay for each transaction, and the risks stemming from having to blindly trust another party. If it were possible to only base on transaction logs to sort disputes out, then it would be feasible to get rid of any TTP and related shortcomings. In this paper we propose SLAVE, a blockchain-based solution which does not require any TTP. Storing transactions in a public blockchain like Bitcoin’s or Ethereum’s provides strong guarantees on transactions’ integrity, hence they can be actually used as proofs when controversies arise. The solution we propose defines how to embed transaction logs in a public blockchain, so that each involved party can verify the identity of the others while keeping confident the content of transactions

Arrhythmic death and ICD implantation after myocardial infarction

Arrhythmic death remains one of the most important causes of mortality after an acute myocardial infarction also in the revascularization era. As a consequence, identification of patients at risk should be performed before discharge. Unfortunately, in the clinical practice, this evaluation is mainly based on detection of a depressed left ventricular ejection. This approach, however, cannot adequately distinguish arrhythmic versus non-arrhythmic risk

Origin of Heart Rate Variability and Turbulence: An Appraisal of Autonomic Modulation of Cardiovascular Function

Heart period constantly changes on a beat to beat basis, due to autonomic influences on the sinoatrial node, and changes can be quantified as heart rate variability (HRV). In addition, after a premature ventricular beat, there are reproducible variations in RR interval, also due to baroreflex mediated autonomic influences on the sinoatrial node, that can be measured as heart rate turbulence (HRT). Impaired autonomic function as measured by HRV and HRT has proven to predict adverse outcomes in clinical settings. The ability of reduced HRV and HRT to predict adverse outcomes has been explained by their dependency on vagal mechanisms that could reflect an increased sympathetic and a reduced vagal modulation of sinus node, thus favoring cardiac electrical instability. Analysis of non-linear dynamics of HRV has also been utilized to describe the fractal like characteristic of the variability signal and proven effective in identify patients at risk for sudden cardiac death. Despite the clinical validity of these measures, it has also been evident that the relationship between neural input and sinus node responsiveness is extremely complex and variable in different clinical conditions. Thus, abnormal HRV or HRT on a clinical Holter recordings may reflect non-neural as well as autonomic mechanisms, and this also needs to be taken into account when interpreting any findings. However, under controlled conditions, the computation of the low and high frequency components of HRV and of their normalized powers or ratio seems capable of providing valid information on sympatho-vagal balance in normal subjects, as well as in most patients with a preserved left ventricular function. Thus, analysis of HRV does provide a unique tool to specifically assess autonomic control mechanisms in association with various perturbations. In conclusion, HRV measures are of substantial utility to identify patients with an increased cardiac mortality and to evaluate autonomic control mechanisms, but their ability to capture specific levels of autonomic control may be limited to controlled laboratory studies in relatively healthy subjects

FULL AND PERFORATED METAL PLATE SHEAR WALLS AS BRACING SYSTEMS FOR SEISMIC UPGRADING OF EXISTING RC BUILDINGS

Metal Plate Shear Walls (MPSWs) represent an effective, practical and economical system for the seismic protection of existing RC framed buildings. They consist of one or more metallic thin plates, bolted or welded to a stiff steel frame, which are installed in the bays of RC framed structures. A case study of an existing RC residential 5-storey building, designed between the ‘60s and ‘70s of the last century and retrofitted with MPSWs, has been examined in this paper. The retrofitting design of the existing structure has been carried out by using four different MPSWs, namely three common full panels made of steel, low yield steel and aluminium and one innovative perforated steel plates. Finally, the used retrofitting solutions have been compared each to other in terms of performance and economic parameters, allowing to select the best intervention

DETERMINE: Novel Radar Techniques for Humanitarian Demining

Today the plague of landmines represent one of the greatest curses of modern time, killing and maiming innocent people every day. It is not easy to provide a global estimate of the problem dimension, however, reported casualties describe that the majority of the victims are civilians, with almost a half represented by children. Among all the technologies that are currently employed for landmine clearance, Ground Penetrating Radar (GPR) is one of those expected to increase the efficiency of operation, even if its high-resolution imaging capability and the possibility of detecting also non-metallic landmines are unfortunately balanced by the high sensor false alarm rate. Most landmines may be considered as multiple layered dielectric cylinders that interact with each other to produce multiple reflections, which will be not the case for other common clutter objects. Considering that each scattering component has its own angular radiation pattern, the research has evaluated the improvements that multistatic configurations could bring to the collected information content. Employing representative landmine models, a number of experimental campaigns have confirmed that GPR is capable of detecting the internal reflections and that the presence of such scattering components could be highlighted changing the antennas offset. In particular, results show that the information that can be extracted relevantly changes with the antenna separation, demonstrating that this approach can provide better confidence in the discrimination and recognition process. The proposed bistatic approach aims at exploiting possible presence of internal structure beneath the target, which for landmines means the activation or detonation assemblies and possible internal material diversity, maintaining a limited acquisition effort. Such bistatic configurations are then included in a conceptual design of a highly flexible GPR system capable of searching for landmines across a large variety of terrains, at reasonably low cost and targeting operators safety

Un gesuita spagnolo in Cina

L’articolo offre una visione d’insieme della vita e dell’opera di Diego de Pantoja (1571-1618), uno dei pionieri della missione gesuitica in Cina. Seguendo la strada aperta da Francesco Saverio, Diego de Pantoja raggiunse Pechino al seguito di Matteo Ricci, entrando in contatto con i letterati cinesi attivi nella corte imperiale e riuscendo così a dare alla missione la necessaria stabilità. Partendo dagli anni di formazione giovanile per giungere, attraverso l’epoca di attività missionaria svolta a Pechino come collaboratore prima e successore poi del padre Matteo Ricci, sino alla persecuzione di Nanchino, l’esilio e la morte avvenuta a Macao, il testo prende in esame i principali contributi offerti da Diego di Pantoja alla causa missionaria, tra cui la stesura della Relación de la entrada de algunos padres de la Compañia de Jesús en la China e de Le sette vittorie sui sette peccati capitali (Qikedaquan) e la riforma del calendario

Landmine internal structure detection from ground penetrating radar images

Reliable landmine detection is still an unresolved problem. Demining operations are complex activities because of the large variety of existing landmine types, many different possible soil and terrain conditions, and environmental circumstances. Due to its ability of detecting both metallic and non-metallic objects, ground penetrating radar (GPR) is a promising method for detecting landmines that may allow faster and safer operations. As the performance of GPR is mainly governed by the target signature, the potential of discriminating target based on the presence of internal reflections could be a valuable advantage for identification and recognition process. This study demonstrates that from a set of high resolution GPR slices the internal design of the landmine can be properly imaged and characterised, confirming the applicability of the methodology and the validity of such an approach

An analysis of Universal Differential Equations for data-driven discovery of Ordinary Differential Equations

In the last decade, the scientific community has devolved its attention to the deployment of data-driven approaches in scientific research to provide accurate and reliable analysis of a plethora of phenomena. Most notably, Physics-informed Neural Networks and, more recently, Universal Differential Equations (UDEs) proved to be effective both in system integration and identification. However, there is a lack of an in-depth analysis of the proposed techniques. In this work, we make a contribution by testing the UDE framework in the context of Ordinary Differential Equations (ODEs) discovery. In our analysis, performed on two case studies, we highlight some of the issues arising when combining data-driven approaches and numerical solvers, and we investigate the importance of the data collection process. We believe that our analysis represents a significant contribution in investigating the capabilities and limitations of Physics-informed Machine Learning frameworks