Space shuttle pogo studies

Topics covered include: (1) pogo suppression for main propulsion subsystem operation; (2) application of quarter-scale low pressure oxidizer turbopump transfer functions; (3) pogo stability during orbital maneuvering subsystem operation; and (4) errors in frequency response measurements

Facing the blockchain endpoint vulnerability, an SGX-based solution for secure eHealth auditing

According to McAfee Labs, even in 2019, the eHealth sector is confirmed as one of the most critical in terms of cybersecurity incidents. It is estimated that more than 176 million patient records were target of attacks between 2009 and 2017, and with a single attack, in 2018, more than 1.4 million patient records were affected at UnityPoint Health. To cope with such a dramatic situation, one of the main strategic priority in the eHealth field is represented by the adoption of Blockchain. Specifically, according to a Deloittes survey, 55% of healthcare executives believe that blockchain technology will disrupt the healthcare industry. Unfortunately, while blockchain provides a valuable tool for enhancing the security of health applications and related data, it cannot be assumed as a panacea for data security. As an example, the so-called Endpoint Vulnerability issue is a well-known problem of Blockchain-based solutions: in such a case the attacker successful in gaining control of the end-point can tamper data off-chain during its generation and/or before it is sent to the chain. In this paper, we face such an issue by shielding the endpoint through the Intel Software Guard eXtension (SGX) technology. We demonstrate our solution for an auditing software belonging to the European eHealth management system (namely OpenNCP). We also discuss how our solution can be generalized to any other Blockchain-based solution. Finally, an experimental evaluation has been conducted to prove the actual feasibility of the proposed solution under the requirements of the real eHealth system

A resilient architecture for forensic storage of events in critical infrastructures

In Critical Infrastructures, forensic analysis of stored events is an essential task when a security breach occurs. The goal of forensic analysis is to provide evidence to be used as valid proofs in a legal proceeding. So, it is very important to ensure the integrity of the events stored in order to perform a correct forensic analysis. Today, most of the SIEMs used to protect the Critical Infrastructures sign the security events with RSA classic algorithm in order to ensure their integrity. The signed security events cannot be admissible as evidence if the secret key is compromised, or when the module responsible for signing operations is down for any reason. In this paper a new architecture that overcomes these limitations has been proposed. Experimental tests show the performance of our architecture and the high resilience in faulty situations, i.e. some nodes are under attack

Privacy-Preserving Credit Scoring via Functional Encryption

The majority of financial organizations managing confidential data are aware of security threats and leverage widely accepted solutions (e.g., storage encryption, transport-level encryption, intrusion detection systems) to prevent or detect attacks. Yet these hardening measures do little to face even worse threats posed on data-in-use. Solutions such as Homomorphic Encryption (HE) and hardware-assisted Trusted Execution Environment (TEE) are nowadays among the preferred approaches for mitigating this type of threats. However, given the high-performance overhead of HE, financial institutions —whose processing rate requirements are stringent— are more oriented towards TEE-based solutions. The X-Margin Inc. company, for example, offers secure financial computations by combining the Intel SGX TEE technology and HE-based Zero-Knowledge Proofs, which shield customers’ data-in-use even against malicious insiders, i.e., users having privileged access to the system. Despite such a solution offers strong security guarantees, it is constrained by having to trust Intel and by the SGX hardware extension availability. In this paper, we evaluate a new frontier for X-Margin, i.e., performing privacy-preserving credit risk scoring via an emerging cryptographic scheme: Functional Encryption (FE), which allows a user to only learn a function of the encrypted data. We describe how the X-Margin application can benefit from this innovative approach and —most importantly— evaluate its performance impact

Development of the first in vivo GPR17 ligand through an iterative drug discovery pipeline: A novel disease-modifying strategy for multiple sclerosis

The GPR17 receptor, expressed on oligodendroglial precursors (OPCs, the myelin producing cells), has emerged as an attractive target for a pro-myelinating strategy in multiple sclerosis (MS). However, the proof-of-concept that selective GPR17 ligands actually exert protective activity in vivo is still missing. Here, we exploited an iterative drug discovery pipeline to prioritize novel and selective GPR17 pro-myelinating agents out of more than 1,000,000 compounds. We first performed an in silico high-throughput screening on GPR17 structural model to identify three chemically-diverse ligand families that were then combinatorially exploded and refined. Top-scoring compounds were sequentially tested on reference pharmacological in vitro assays with increasing complexity, ending with myelinating OPC-neuron co-cultures. Successful ligands were filtered through in silico simulations of metabolism and pharmacokinetics, to select the most promising hits, whose dose and ability to target the central nervous system were then determined in vivo. Finally, we show that, when administered according to a preventive protocol, one of them (named by us as galinex) is able to significantly delay the onset of experimental autoimmune encephalomyelitis (EAE), a mouse model of MS. This outcome validates the predictivity of our pipeline to identify novel MS-modifying agents

Expression and function of αβ1 integrins in pancretic beta (INS-1) cells

Integrin-extracellular matrix interactions are important determinants of beta cell behaviours. The β1 integrin is a well-known regulator of beta cell activities; however, little is known of its associated α subunits. In the present study, αβ1 integrin expression was examined in the rat insulinoma cell line (INS-1) to identify their role in beta cell survival and function. Seven α subunits associated with β1 integrin were identified, including α1-6 and αV. Among these heterodimers, α3β1 was most highly expressed. Common ligands for the α3β1 integrin, including fibronectin, laminin, collagen I and collagen IV were tested to identify the most suitable matrix for INS-1 cell proliferation and function. Cells exposed to collagen I and IV demonstrated significant increases in adhesion, spreading, cell viability, proliferation, and FAK phosphorylation when compared to cells cultured on fibronectin, laminin and controls. Integrin-dependent attachment also had a beneficial effect on beta cell function, increasing Pdx-1 and insulin gene and protein expression on collagens I and IV, in parallel with increased basal insulin release and enhanced insulin secretion upon high glucose challenge. Furthermore, functional blockade of α3β1 integrin decreased cell adhesion, spreading and viability on both collagens and reduced Pdx-1 and insulin expression, indicating that its interactions with collagen matrices are important for beta cell survival and function. These results demonstrate that specific αβ1 integrin-ECM interactions are critical regulators of INS-1 beta cell survival and function and will be important in designing optimal conditions for cell-based therapies for diabetes treatment

The future of Cybersecurity in Italy: Strategic focus area

This volume has been created as a continuation of the previous one, with the aim of outlining a set of focus areas and actions that the Italian Nation research community considers essential. The book touches many aspects of cyber security, ranging from the definition of the infrastructure and controls needed to organize cyberdefence to the actions and technologies to be developed to be better protected, from the identification of the main technologies to be defended to the proposal of a set of horizontal actions for training, awareness raising, and risk management

GPR17 molecular modelling: interactions with non-conventional pro-inflammatory ligands

GPR17 is a class A-GPCRs operated by di erent classes of ligands, such as uracil nucleotides, cysteinyl-leukotrienes and oxysterols. Similar to other receptors of the same class, GPR17 can associate into homo- and hetero-dimers. Recent ndings suggest its promiscuous behavior namely the possibility to be operated by ligands able to transversely interact with more than one GPCRs. In fact, both GPR17 and CXCR2 are operated by oxysterols, and both GPR17 and CXCRn ligands have demonstrated roles in orchestrating in ammatory responses and oligodendrocyte precursor cell (OPC) di erentiation to myelinating cells in acute and chronic diseases of the CNS. Here we demonstrate that GPR17 can be activated by the chemokine stromal-derived factor-1 (SDF-1), a ligand of CXCR4 and CXCR7, and investigate the underlying molecular recognition mechanism, by combining in silico modelling data with in vitro validation in (i) a classical reference pharmacological assay for GPCR activity and (ii) a model of maturation of primary OPCs. We also demonstrate that cangrelor, a GPR17 orthosteric antagonist, can block the SDF-1-mediated activation of GPR17 in a concentration-dependent manner. The ability of GPR17 to respond to di erent classes of GPCR ligands suggests that this receptor modi es its function depending on changes occurring in the extracellular mileu changes occurring under speci c pathophysiological conditions and advocates it as a strategic target for neurodegenerative diseases with an in ammatory/immune component