An Efficient Built-in Temporal Support in MVCC-based Graph Databases

Real-world graphs are often dynamic and evolve over time. To trace the evolving properties of graphs, it is necessary to maintain every change of both vertices and edges in graph databases with the support of temporal features. Existing works either maintain all changes in a single graph or periodically materialize snapshots to maintain the historical states of each vertex and edge and process queries over proper snapshots. The former approach presents poor query performance due to the ever-growing graph size as time goes by, while the latter one suffers from prohibitively high storage overheads due to large redundant copies of graph data across different snapshots. In this paper, we propose a hybrid data storage engine, which is based on the MVCC mechanism, to separately manage current and historical data, which keeps the current graph as small as possible. In our design, changes in each vertex or edge are stored once. To further reduce the storage overhead, we simply store the changes as opposed to storing the complete snapshot. To boost the query performance, we place a few anchors as snapshots to avoid deep historical version traversals. Based on the storage engine, a temporal query engine is proposed to reconstruct subgraphs as needed on the fly. Therefore, our alternative approach can provide fast querying capabilities over subgraphs at a past time point or range with small storage overheads. To provide native support of temporal features, we integrate our approach into Memgraph, and call the extended database system TGDB(Temporal Graph Database). Extensive experiments are conducted on four real and synthetic datasets. The results show TGDB performs better in terms of both storage and performance against state-of-the-art methods and has almost no performance overheads by introducing the temporal features

FENDI: High-Fidelity Entanglement Distribution in the Quantum Internet

A quantum network distributes quantum entanglements between remote nodes, which is key to many quantum applications. However, unavoidable noise in quantum operations could lead to both low throughput and low quality of entanglement distribution. This paper aims to address the simultaneous exponential degradation in throughput and quality in a buffered multi-hop quantum network. Based on an end-to-end fidelity model with worst-case (isotropic) noise, we formulate the high-fidelity remote entanglement distribution problem for a single source-destination pair, and prove its NP-hardness. To address the problem, we develop a fully polynomial-time approximation scheme for the control plane of the quantum network, and a distributed data plane protocol that achieves the desired long-term throughput and worst-case fidelity based on control plane outputs. To evaluate our algorithm and protocol, we develop a discrete-time quantum network simulator. Simulation results show the superior performance of our approach compared to existing fidelity-agnostic and fidelity-aware solutions

Case Report: Response to crizotinib treatment in a patient with advanced non-small cell lung cancer with LDLR-ROS1 fusion

C-ros oncogene 1 (ROS1) fusion is a pathogenic driver gene in non-small cell lung cancer (NSCLC). Currently, clinical guidelines from the National Comprehensive Cancer Network (NCCN) have recommended molecular pathologic tests for patients with NSCLC, including the detection of the ROS1 gene. Crizotinib is a small molecule tyrosine kinase inhibitor of anaplastic lymphoma kinase (ALK), ROS1, and mesenchymal-epithelial transition (MET). In recent years, the efficacy of crizotinib in NSCLC patients with ROS1 fusion has been reported. Here, a 77-year-old woman was diagnosed with stage IVA lung adenocarcinoma harboring a novel low-density lipoprotein receptor (LDLR)-ROS1 fusion variant. This novel LDLR-ROS1 fusion was identified by targeted DNA next-generation sequencing (NGS) panel and then verified by RNA fusion panel based on amplicon sequencing. This patient benefited from subsequent crizotinib therapy and achieved progression-free survival of 15 months without significant toxic symptoms. Our case report recommended a promising targeted therapeutic option for patients with metastatic NSCLC with LDLR-ROS1 fusion and highlighted the importance of genetic testing for accurate treatment

A Novel Modeling Method in Metal Strip Leveling Based on a Roll-Strip Unit

In the metal strip-multiroll leveling process, the action behavior of each roll is different. However, modeling each roll individually will result in redundancy which is not conducive to the modeling of the entire leveling process. To overcome this problem, a roll-strip unit (RSU) model is proposed to uniformly describe the behavior of each roll during the leveling process. The RSU and its equivalent model are defined on the basis of analyzing the force relationship between the roll and the strip. According to the linear distribution of the bending moment in the longitudinal direction of the strip, the position of the zero bending moment, that is, the virtual fulcrum, is obtained to determine the interval of the RSU. A plastic deformation function is established to describe the influence of plastic extension on the tension and velocity of the strip. The fitting of the deformation curve of the strip is optimized by the tension influence factor and the zero curvature moment. The static friction condition between the roll and the strip which ensures the normal operation of the RSU is given. The AMESim model of the RSU is established to lay the foundation for the dynamic modeling of the multiroll leveler

A Facile One-Pot Process for the Formation of Hindered Tertiary Amines

molecule

One-Pot Route from Halogenated Amides to Piperidines and Pyrrolidines

Piperidine and pyrrolidine derivatives are important nitrogen heterocyclic structures with a wide range of biological activities. However, reported methods for their construction often face problems of requiring the use of expensive metal catalysts, highly toxic reaction reagents or hazardous reaction conditions. Herein, an efficient route from halogenated amides to piperidines and pyrrolidines was disclosed. In this method, amide activation, reduction of nitrile ions, and intramolecular nucleophilic substitution were integrated in a one-pot reaction. The reaction conditions were mild and no metal catalysts were used. The synthesis of a variety of N-substituted and some C-substituted piperidines and pyrrolidines became convenient, and good yields were obtained

UNCERTAINTY ANALYSIS TO C5G7-TD BENCHMARK BASED ON THE COST METHOD

A method of Covariance-Oriented Sample Transformation (COST) has been proposed in our previous work to provide the converged uncertainty analysis results with a minimal sample size. The transient calculation of nuclear reactor is a key part of the reactor-physics simulation, so the accuracy and confidence of the neutron kinetics results have attracted much attention. In this paper, the Uncertainty Quantification (UQ) function of the high fidelity neutronics code NECP-X has been developed based on our home-developed uncertainty analysis code UNICORN, building a platform for the UQ of the transient calculation. Furthermore, the well-known space-time heterogeneous neutron kinetics benchmark C5G7 and its uncertainty propagation from the nuclear data to the interested key parameters of the core have been investigated. To address the problem of “the curse of dimensionality” caused by the large number of input parameters, the COST method has been applied to generate multivariate normal-distribution samples in uncertainty analysis. As a result, the law of the assembly/pin normalized power and their uncertainty with respect to time after introducing an instantaneous perturbation has been obtained. From the numerical results, it can be observed that the maximum relative uncertainties for the assembly normalized power can up to be about 1.65% and the value for the pin-wise power distributions can be about 2.71%

UNCERTAINTY ANALYSIS TO C5G7-TD BENCHMARK BASED ON THE COST METHOD

A method of Covariance-Oriented Sample Transformation (COST) has been proposed in our previous work to provide the converged uncertainty analysis results with a minimal sample size. The transient calculation of nuclear reactor is a key part of the reactor-physics simulation, so the accuracy and confidence of the neutron kinetics results have attracted much attention. In this paper, the Uncertainty Quantification (UQ) function of the high fidelity neutronics code NECP-X has been developed based on our home-developed uncertainty analysis code UNICORN, building a platform for the UQ of the transient calculation. Furthermore, the well-known space-time heterogeneous neutron kinetics benchmark C5G7 and its uncertainty propagation from the nuclear data to the interested key parameters of the core have been investigated. To address the problem of “the curse of dimensionality” caused by the large number of input parameters, the COST method has been applied to generate multivariate normal-distribution samples in uncertainty analysis. As a result, the law of the assembly/pin normalized power and their uncertainty with respect to time after introducing an instantaneous perturbation has been obtained. From the numerical results, it can be observed that the maximum relative uncertainties for the assembly normalized power can up to be about 1.65% and the value for the pin-wise power distributions can be about 2.71%