Graph-tree-based software control flow checking for COTS processors on pico-satellites

AbstractThis paper proposes a generic high-performance and low-time-overhead software control flow checking solution, graph-tree-based control flow checking (GTCFC) for space-borne commercial-off-the-shelf (COTS) processors. A graph tree data structure with a topology similar to common trees is introduced to transform the control flow graphs of target programs. This together with design of IDs and signatures of its vertices and edges allows for an easy check of legality of actual branching during target program execution. As a result, the algorithm not only is capable of detecting all single and multiple branching errors with low latency and time overheads along with a linear-complexity space overhead, but also remains generic among arbitrary instruction sets and independent of any specific hardware. Tests of the algorithm using a COTS-processor-based on-board computer (OBC) of in-service ZDPS-1A pico-satellite products show that GTCFC can detect over 90% of the randomly injected and all-pattern-covering branching errors for different types of target programs, with performance and overheads consistent with the theoretical analysis; and beats well-established preeminent control flow checking algorithms in these dimensions. Furthermore, it is validated that GTCGC not only can be accommodated in pico-satellites conveniently with still sufficient system margins left, but also has the ability to minimize the risk of control flow errors being undetected in their space missions. Therefore, due to its effectiveness, efficiency, and compatibility, the GTCFC solution is ready for applications on COTS processors on pico-satellites in their real space missions

A deoxyribozyme that synthesizes 2′,5′-branched RNA with any branch-site nucleotide

RNA molecules with internal 2′,5′-branches are intermediates in RNA splicing, and branched RNAs have recently been proposed as retrotransposition intermediates. A broadly applicable in vitro synthetic route to branched RNA that does not require self-splicing introns or spliceosomes would substantially improve our ability to study biochemical processes that involve branched RNA. We recently described 7S11, a deoxyribozyme that was identified by in vitro selection and has general RNA branch-forming ability. However, an important restriction for 7S11 is that the branch-site RNA nucleotide must be a purine (A or G), because a pyrimidine (U or C) is not tolerated. Here, we describe the compact 6CE8 deoxyribozyme (selected using a 20 nt random region) that synthesizes 2′,5′-branched RNA with any nucleotide at the branch site. The Mn(2+)-dependent branch-forming ligation reaction is between an internal branch-site 2′-hydroxyl nucleophile on one RNA substrate with a 5′-triphosphate on another RNA substrate. The preference for the branch-site nucleotide is U > C ≅ A > G, although all four nucleotides are tolerated with useful ligation rates. Nearly all other nucleotides elsewhere in both RNA substrates allow ligation activity, except that the sequence requirement for the RNA strand with the 5′-triphosphate is 5′-pppGA, with 5′-pppGAR (R = purine) preferred. These characteristics permit 6CE8 to prepare branched RNAs of immediate practical interest, such as the proposed branched intermediate of Ty1 retrotransposition. Because this branched RNA has two strands with identical sequence that emerge from the branch site, we developed strategies to control which of the two strands bind with the deoxyribozyme during the branch-forming reaction. The ability to synthesize the proposed branched RNA of Ty1 retrotransposition will allow us to explore this important biochemical pathway in greater detail

Impact of minerals and water on bitumen-mineral adhesion and debonding behaviours using molecular dynamics simulations

This study aims to evaluate the effects of mineral types and water on the adhesion properties and debonding behaviours of bitumen-mineral interface systems. A molecular dynamics modelling approach was employed to simulate the interactions between minerals and bitumen with and without the presence of water. Four representative minerals (quartz, calcite, albite and microcline) were selected to build the mineral-bitumen interface systems and the mineral-water-bitumen interface systems in the molecular dynamics models. The adhesion property between minerals and bitumen was quantified by work of adhesion, defined as the energy required to separate a unit area of the bitumen-mineral interface. The debonding behaviour between minerals and bitumen is characterised by work of debonding, defined as the energy required to displace bitumen by water at the mineral-bitumen interface. The simulation results were validated by available experimental results reported in the literature. It was found that the work of adhesion and the work of debonding for the four bitumen-minerals interface systems are ranked microcline > albite > calcite > quartz at both dry and wet conditions. Moisture can reduce the adhesion between minerals and bitumen by 82%, 84%, 18% and 1% for the quartz, calcite, albite and microcline, respectively. The adhesion between minerals and bitumen is attributed to the non-bond interaction energy, in which the major component is van der Waals interaction for neutral minerals (e.g., quartz) and the electrostatic interaction for the alkali minerals (e.g., calcite, albite and microcline). The bitumen-mineral debonding is a thermodynamically favourable process with reduced total potential energy of the system. It is concluded that the bitumen-mineral adhesion and debonding behaviours strongly depends on the chemistry and mineralogical properties of the minerals. This work provides a fundamental understanding of the adhesion and debonding behaviours of the bitumen-mineral interface at the atomistic scale

Fast and Accurate Recognition of Chinese Clinical Named Entities with Residual Dilated Convolutions

Clinical Named Entity Recognition (CNER) aims to identify and classify clinical terms such as diseases, symptoms, treatments, exams, and body parts in electronic health records, which is a fundamental and crucial task for clinical and translation research. In recent years, deep learning methods have achieved significant success in CNER tasks. However, these methods depend greatly on Recurrent Neural Networks (RNNs), which maintain a vector of hidden activations that are propagated through time, thus causing too much time to train models. In this paper, we propose a Residual Dilated Convolutional Neural Network with Conditional Random Field (RD-CNN-CRF) to solve it. Specifically, Chinese characters and dictionary features are first projected into dense vector representations, then they are fed into the residual dilated convolutional neural network to capture contextual features. Finally, a conditional random field is employed to capture dependencies between neighboring tags. Computational results on the CCKS-2017 Task 2 benchmark dataset show that our proposed RD-CNN-CRF method competes favorably with state-of-the-art RNN-based methods both in terms of computational performance and training time.Comment: 8 pages, 3 figures. Accepted as regular paper by 2018 IEEE International Conference on Bioinformatics and Biomedicine. arXiv admin note: text overlap with arXiv:1804.0501

Ultra-high-linearity integrated lithium niobate electro-optic modulators

Integrated lithium niobate (LN) photonics is a promising platform for future chip-scale microwave photonics systems owing to its unique electro-optic properties, low optical loss and excellent scalability. A key enabler for such systems is a highly linear electro-optic modulator that could faithfully covert analog electrical signals into optical signals. In this work, we demonstrate a monolithic integrated LN modulator with an ultrahigh spurious-free dynamic range (SFDR) of 120.04 dB Hz4/5 at 1 GHz, using a ring-assisted Mach-Zehnder interferometer configuration. The excellent synergy between the intrinsically linear electro-optic response of LN and an optimized linearization strategy allows us to fully suppress the cubic terms of third-order intermodulation distortions (IMD3) without active feedback controls, leading to ~ 20 dB improvement over previous results in the thin-film LN platform. Our ultra-high-linearity LN modulators could become a core building block for future large-scale functional microwave photonic integrated circuits, by further integration with other high-performance components like low-loss delay lines, tunable filters and phase shifters available on the LN platform