Structural and Fluid-Structure Interaction Analysis of Stenotic Aortic Valves: Application to Percutaneous Aortic Valve Replacement

The main objective of this thesis is to study and investigate the mechanical behavior of the aortic valve with an emphasis on aortic stenosis. Moreover, this thesis aims to characterize the severity of AS in terms of material properties. The development of percutaneous heart valves allows valve replacement without open chest surgery. This is the most desirable option for patients with elevated surgical risks. To avoid the risk of failure in percutaneous valve implantation, determination of material properties of diseased leaflets before surgery is necessary. Therefore in this study, a series of numerical simulations, including both structural and fluid-structure interaction approach, and experimental studies were performed to achieve the objectives of this research. The results of the numerical simulations of the aortic stenosis are compared with in vitro results before testing the method using in vivo data. There is good agreement between the results of the numerical simulation and the in vitro experiments and the literature. An algorithm is suggested to estimate the material properties of the stenotic valve, considering the realistic material of the aortic valve with hyperelastic, nonlinear and anisotropic properties. The simulations using the structural modeling allow determination of the patient’s specific material property of a calcified aortic valve, knowing invasively measured aortic and ventricular pressure waveforms and the geometrical orifice area prior to percutaneous valve replacement. Also, fluidstructure interaction modeling helps to estimate a more realistic dynamic behavior of the aortic valve and also obtains the hemodynamic performance

Deep Learning meets Blockchain for Automated and Secure Access Control

Access control is a critical component of computer security, governing access to system resources. However, designing policies and roles in traditional access control can be challenging and difficult to maintain in dynamic and complex systems, which is particularly problematic for organizations with numerous resources. Furthermore, traditional methods suffer from issues such as third-party involvement, inefficiency, and privacy gaps, making transparent and dynamic access control an ongoing research problem. Moreover detecting malicious activities and identifying users who are not behaving appropriately can present notable difficulties. To address these challenges, we propose DLACB, a Deep Learning Based Access Control Using Blockchain, as a solution to decentralized access control. DLACB uses blockchain to provide transparency, traceability, and reliability in various domains such as medicine, finance, and government while taking advantage of deep learning to not rely on predefined policies and eventually automate access control. With the integration of blockchain and deep learning for access control, DLACB can provide a general framework applicable to various domains, enabling transparent and reliable logging of all transactions. As all data is recorded on the blockchain, we have the capability to identify malicious activities. We store a list of malicious activities in the storage system and employ a verification algorithm to cross-reference it with the blockchain. We conduct measurements and comparisons of the smart contract processing time for the deployed access control system in contrast to traditional access control methods, determining the time overhead involved. The processing time of DLBAC demonstrates remarkable stability when exposed to increased request volumes.Comment: arXiv admin note: text overlap with arXiv:2303.1475

An in vitro model of aortic stenosis for the assessment of transcatheter aortic valve implantation

A significant number of elderly patients with severe symptomatic aortic stenosis are denied surgical aortic valve replacement (SAVR) because of high operative risk. Transcatheter aortic valve implantation (TAVI) has emerged as a valid alternative to SAVR in these patients. One of the main characteristics of TAVI, when compared to SAVR, is that the diseased native aortic valve remains in place. For hemodynamic testing of new percutaneous valves and clinical training, one should rely on animal models. However, the development of an appropriate animal model of severe aortic stenosis is not straightforward. This work aims at developing and testing an elastic model of the ascending aorta including a severe aortic stenosis. The physical model was built based on a previous silicone model and tested experimentally in this study. Experimental results showed that the error between the computer-aided design (CAD) file and the physical elastic model was <5%, the compliance of the ascending aorta was 1.15 ml/mm Hg, the effective orifice area (EOA) of the stenotic valve was 0.86 cm2, the peak jet velocity was 4.9 m/s and mean transvalvular pressure gradient was 50 mm Hg, consistent with as severe. An EDWARDS-SAPIEN 26 mm valve was then implanted in the model leading to a significant increase in EOA (2.22 cm2) and a significant decrease in both peak jet velocity (1.29 m/s) and mean transvalvular pressure gradient (3.1 mm Hg). This model can be useful for preliminary in vitro testing of percutaneous valves before more extensive animal and in vivo tests

ForensiBlock: A Provenance-Driven Blockchain Framework for Data Forensics and Auditability

Maintaining accurate provenance records is paramount in digital forensics, as they underpin evidence credibility and integrity, addressing essential aspects like accountability and reproducibility. Blockchains have several properties that can address these requirements. Previous systems utilized public blockchains, i.e., treated blockchain as a black box, and benefiting from the immutability property. However, the blockchain was accessible to everyone, giving rise to security concerns and moreover, efficient extraction of provenance faces challenges due to the enormous scale and complexity of digital data. This necessitates a tailored blockchain design for digital forensics. Our solution, Forensiblock has a novel design that automates investigation steps, ensures secure data access, traces data origins, preserves records, and expedites provenance extraction. Forensiblock incorporates Role-Based Access Control with Staged Authorization (RBAC-SA) and a distributed Merkle root for case tracking. These features support authorized resource access with an efficient retrieval of provenance records. Particularly, comparing two methods for extracting provenance records off chain storage retrieval with Merkle root verification and a brute-force search the offchain method is significantly better, especially as the blockchain size and number of cases increase. We also found that our distributed Merkle root creation slightly increases smart contract processing time but significantly improves history access. Overall, we show that Forensiblock offers secure, efficient, and reliable handling of digital forensic dataComment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

LightSource: Ultra Lightweight Clone Detection of RFID Tags from Software Unclonable Responses

Radio-Frequency Identification (RFID) tags have been widely used as a low-cost wireless method for detection of counterfeit product injection in supply chains. In order to adequately perform authentication, current RFID monitoring schemes need to either have a persistent online connection between supply chain partners and the back-end database or have a local database on each partner site. A persistent online connection is not guaranteed and local databases on each partner site impose extra cost and security issues. We introduce a new method in which we use 2-3kb Non-Volatile Memory (NVM) in RFID tags themselves to function as a very small “encoded local database”. Our method allows us to get rid of local databases and there is no need to have any connection between supply chain partners and the back-end database except when they want to verify products. We formally define black-box software unclonability and prove our scheme to satisfy this property. To this purpose, we introduce a simple “XOR-ADD” function and prove it is hard to predict its challenge-response behavior if given only one challenge response pair. The XOR-ADD function with control logic can be implemented using at most 170 gates. This implies that our scheme is compatible with the strict power consumption constraints of cheap EPC Class 1 Gen 2 RFIDs

The Role of the Extracellular Matrix Microenvironment in Regulating Aortic Valve Cell Phenotypes

Calcific aortic valve disease (CAVD) is an active, cell-mediated pathology associated with significant cardiovascular morbidity but with no current pharmacologic treatments. In late CAVD, the aortic valve (AV) leaflets become fibrotic and calcified, but early CAVD is characterized by proteoglycan-rich subendothelial lesions in the fibrosa layer of the leaflets. Valve interstitial cells (VICs) in these early lesions express higher levels of genes associated with bone and cartilage formation in situ, motivating the hypothesis that the lesion microenvironment promotes VIC pathological gene expression. VIC pathological differentiation has been shown to be affected by both ECM mechanics and composition, but the relevance of these in vitro studies to the lesion microenvironment was unknown. I first determined if early AV lesions have local mechanical properties that are distinct from those normal valve tissue. A custom microindentation device was developed and validated. For the first time, I showed that the compressive moduli of early lesions were ~2.4 fold softer than healthy non-lesion regions. As a top-down approach to test the effect of the lesion microenvironment on VIC responses, I then established a novel ex vivo decellularized valve model of normal valve ECM and early CAVD, defining decellularization conditions that maximally removed cells and preserved ECM microenvironment. I then applied the model to investigate the influence of normal versus diseased ECM on VIC phenotypic expression. Several genes involved in osteogenic (e.g., RUNX2, MSX2 and SPP1) and chondrongenic (e.g., ACAN, HYAL2 and CHSY1) processes were upregulated in naïve VICs grown in lesion microenvironments compared to non-lesion fibrosa areas. Inflammatory and ECM related genes were differentially expressed between lesion and non-lesion fibrosa. These in vitro expression patterns match lesion vs. non-lesion gene expression profiles measured in vivo, supporting the validity of my decellularized tissue model and a role for the ECM in driving VIC gene expression associated with pathologic differentiation. The significant findings of this thesis provide novel insights into the role the ECM plays in regulating native valve (dys)function. This thesis also contributes new tools and knowledge to disease modeling research, with broad applications towards better understanding the role of the ECM in health and disease.Ph.D

Towards Security Analysis of OpenStack

OpenStack is the prevalent open-source, non-proprietary package for managing cloud services and data centers. It is highly complex and consists of multiple inter-related components which are developed by separate, loosely coordinated groups. All of these properties make the security analysis of OpenStack both a crucial mission and a challenging one. In this dissertation, we demonstrate how we can provide a rigorous, perceptible and holistic security analysis of OpenStack. We base our modeling and security analysis in the universally composable (UC) security framework, which has been so far used mainly for analyzing the security of cryptographic protocols. Indeed, demonstrating how the UC framework can be used to argue about security-sensitive systems which are mostly non-cryptographic, in nature, is one of the main contributions of this work. Our analysis has the following key features: 1- It is user-centric: It stresses the security guarantees given to users of the system, in terms of privacy, correctness, and timeliness of the services. 2- It provides defense in depth: It considers the security of OpenStack even when some of the components are compromised. This departs from the traditional design approach of OpenStack, which assumes that all services are fully trusted. 3- It is modular: It formulates security properties for individual components and uses them to assert security properties of the overall system. We formulate ideal functionalities that correspond to several OpenStack modules and then prove the security of the overall OpenStack protocol given the ideal components. The modeling paves the way toward a comprehensive analysis of OpenStack: it is extensible to the addition of new components and modular to an intra-component analysis. It turns out that some salient issues come up even at this relatively high level of representation and analysis. Specifically, we demonstrate that the scoping of permissions given by users to proxy tokens causes the overall security to fail as soon as any one of the components fails. We propose an alternative, more finely scoped token mechanism and assert that the new mechanisms suffice for regaining overall security even when some of the components are faulty

Relationship Between Spiritual Health and Job Performance Among Pharmacy Personnel in Qom, Iran

Background and Objectives: Spiritual health has a positive effect on the way of interaction, organizational belonging, and job commitment of people. Therefore, it is expected that in sensitive jobs, such as pharmacy and prescribing medicine for patients, errors will be reduced and patient safety will be improved. This study was conducted to investigate the relationship between spiritual health and job performance among pharmacists and pharmacy staff in Qom Province in 2017-2018. Methods: This cross-sectional study was carried out on a total of 140 staff of pharmacies in Qom. The performance measurement tool was Paterson’s occupational performance questionnaire. Along with demographic information, the state of spiritual health was also evaluated using an authentic Iranian questionnaire. The data were analyzed using an independent t-test and Pearson’s correlation coefficient. Results: The mean age and work experience of the participants were 31.05±8.3 and 7.94±7.4 years, respectively. The total score of occupational performance and spiritual health was obtained as 70±10 and 211.9±23.6, respectively. The results of the Pearson correlation coefficient showed a statistically significant relationship between spiritual health and job performance (P<0.01). Conclusion: Considering the existence of a relationship between the spiritual health of personnel and job performance, it can be concluded that by improving the level of the spiritual health of the personnel working in the pharmacy, the effectiveness factors of organizational behavior will improve. It is recommended that more research be done in the field of job performance improvement

An In Vitro Model of Aortic Stenosis for the Assessment of Transcatheter Aortic Valve Implantation

A significant number of elderly patients with severe symptomatic aortic stenosis are denied surgical aortic valve replacement (SAVR) because of high operative risk. Transcatheter aortic valve implantation (TAVI) has emerged as a valid alternative to SAVR in these patients. One of the main characteristics of TAVI, when compared to SAVR, is that the diseased native aortic valve remains in place. For hemodynamic testing of new percutaneous valves and clinical training, one should rely on animal models. However, the development of an appropriate animal model of severe aortic stenosis is not straightforward. This work aims at developing and testing an elastic model of the ascending aorta including a severe aortic stenosis. The physical model was built based on a previous silicone model and tested experimentally in this study. Experimental results showed that the error between the computer-aided design (CAD) file and the physical elastic model was &lt;5%, the compliance of the ascending aorta was 1.15 ml/mm Hg, the effective orifice area (EOA) of the stenotic valve was 0.86 cm 2 , the peak jet velocity was 4.9 m/s and mean transvalvular pressure gradient was 50 mm Hg, consistent with as severe. An EDWARDS-SAPIEN 26 mm valve was then implanted in the model leading to a significant increase in EOA (2.22 cm 2 ) and a significant decrease in both peak jet velocity (1.29 m/s) and mean transvalvular pressure gradient (3.1 mm Hg). This model can be useful for preliminary in vitro testing of percutaneous valves before more extensive animal and in vivo tests