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Blockchain and distributed ledger technologies (DLT) are emerging decentralized infrastructures touted by researchers to improve existing systems that have been limited by centralized governance and proprietary control. These technologies have shown continued success in sustaining the operational models of modern cryptocurrencies and decentralized finance applications (DeFi). These applications has incentivized growing discussions in their potential applications and adoption in other sectors such as healthcare, which has a high demand for data liquidity and interoperability. Despite the increasing research efforts in adopting blockchain and DLT in healthcare with conceptual designs and prototypes, a major research gap exists in literature: there is a lack of design recommendations that discuss concrete architectural styles and domain-specific considerations that are necessary for implementing health data exchange systems based on these technologies. This paper aims to address this gap in research by introducing a collection of design patterns for constructing blockchain and DLT-based healthcare systems that support secure and scalable data sharing. Our approach adapts traditional software patterns and proposes novel patterns that take into account both the technical requirements specific to healthcare systems and the implications of these requirements on naive blockchain-based solutions. 

Patients often have their healthcare data stored in centralized systems, leading to challenges when reconciling or consolidating their data across providers due to centralized databases that store patient identities. The challenges disrupt the flow of patient care where time is sensitive for both patients and providers. Decentralized technologies have enabled a new identity model–Self-Sovereign Identity (SSI)–that grants individuals the right to freely control, access, and share their own data. This work proposes a system that achieves SSI in a semi-permissioned blockchain network using an open protocol as the certificate of authority and several guidelines for securely handling transactions in the network. Open protocols like Keccak can grant access to a permission-based network such as Hyperledger Fabric. The network architecture ensures data security and privacy through mechanisms of multi-signature transactions and guidelines for storing transactions locally, making this architecture ideal for privacy-centered use cases, such as healthcare data-sharing applications. The ultimate goal is to give patients full control over their identity and other data derived from their identity within a semi-permissioned network. 

In multilayered magnetic topological insulator structures, magnetization reversal processes can drive topological phase transitions between quantum anomalous Hall, axion insulator, and normal insulator states. Here we report an examination of the critical behavior of two such transitions: the quantum anomalous Hall to normal insulator (QAH-NI), and quantum anomalous Hall to axion insulator (QAH-AXI) transitions. By introducing a new analysis protocol wherein temperature dependent variations in the magnetic coercivity are accounted for, the critical behavior of the QAH-NI and QAH-AXI transitions are evaluated over a wide range of temperature and magnetic field. Despite the uniqueness of these different transitions, quantized longitudinal resistance and Hall conductance are observed at criticality in both cases. Furthermore, critical exponents were extracted for QAH-AXI transitions occurring at magnetization reversals of two different magnetic layers. The observation of consistent critical exponents and resistances in each case, independent of the magnetic layer details, demonstrates critical behaviors in quantum anomalous Hall transitions to be of electronic rather than magnetic origin. Our finding offers a new avenue for studies of phase transition and criticality in QAH insulators.

 

Increasing the capacity of biological nitrogen fixation (BNF) is an effective strategy to enhance food security while simultaneously reducing the carbon and nitrogen footprint of agriculture. Nanotechnology offers several pathways to enhance BNF successfully. 

Network verification often requires analyzing properties across different spaces (header space, failure space, or their product) under different failure models (deterministic and/or probabilistic). Existing verifiers efficiently cover the header or failure space, but not both, and efficiently reason about deterministic or probabilistic failures, but not both. Consequently, no single verifier can support all analyses that require different space coverage and failure models. This paper introduces Symbolic Router Execution (SRE), a general and scalable verification engine that supports various analyses. SRE symbolically executes the network model to discover what we call packet failure equivalence classes (PFECs), each of which characterises a unique forwarding behavior across the product space of headers and failures. SRE enables various optimizations during the symbolic execution, while remaining agnostic of the failure model, so it scales to the product space in a general way. By using BDDs to encode symbolic headers and failures, various analyses reduce to graph algorithms (e.g., shortest-path) on the BDDs. Our evaluation using real and synthetic topologies show SRE achieves better or comparable performance when checking reachability, mining specifications, etc. compared to state-of-the-art methods.