van der Waals Stacking-Induced Topological Phase Transition in Layered Ternary Transition Metal Chalcogenides

Novel materials with nontrivial electronic and photonic band topology are crucial for realizing novel devices with low power consumption and heat dissipation and quantum computing free of decoherence. Here, we theoretically predict a novel class of ternary transition metal chalcogenides that exhibit dual topological characteristics, quantum spin Hall insulators (QSHIs) in their two-dimensional (2D) monolayers and topological Weyl semimetals in their 3D noncentrosymmetric crystals upon van der Waals (vdW) stacking. Remarkably, we find that one can create and annihilate Weyl fermions and realize the transition between Type-I and Type-II Weyl fermions by tuning vdW interlayer spacing, providing the missing physical picture of the evolution from 2D QSHIs to 3D Weyl semimetals. Our results also show that these materials possess excellent thermodynamic stability and weak interlayer binding; some of them were synthesized two decades ago, implying their great potentials for experimental synthesis, characterization, and vdW heterostacking. Moreover, their ternary nature will offer more tunability for electronic structure by controlling different stoichiometry and valence charges. Our findings provide an ideal materials platform for realizing QSH effect and exploring fundamental topological phase transition and will open up a variety of new opportunities for two-dimensional materials and topological materials research.National Science Foundation (U.S.). Materials Research Science and Engineering Centers (Program) (Award DMR-1419807)United States. Department of Energy. Division of Materials Sciences and Engineering (Award DE-SC0010526

Alioth: A Machine Learning Based Interference-Aware Performance Monitor for Multi-Tenancy Applications in Public Cloud

Multi-tenancy in public clouds may lead to co-location interference on shared resources, which possibly results in performance degradation of cloud applications. Cloud providers want to know when such events happen and how serious the degradation is, to perform interference-aware migrations and alleviate the problem. However, virtual machines (VM) in Infrastructure-as-a-Service public clouds are black-boxes to providers, where application-level performance information cannot be acquired. This makes performance monitoring intensely challenging as cloud providers can only rely on low-level metrics such as CPU usage and hardware counters. We propose a novel machine learning framework, Alioth, to monitor the performance degradation of cloud applications. To feed the data-hungry models, we first elaborate interference generators and conduct comprehensive co-location experiments on a testbed to build Alioth-dataset which reflects the complexity and dynamicity in real-world scenarios. Then we construct Alioth by (1) augmenting features via recovering low-level metrics under no interference using denoising auto-encoders, (2) devising a transfer learning model based on domain adaptation neural network to make models generalize on test cases unseen in offline training, and (3) developing a SHAP explainer to automate feature selection and enhance model interpretability. Experiments show that Alioth achieves an average mean absolute error of 5.29% offline and 10.8% when testing on applications unseen in the training stage, outperforming the baseline methods. Alioth is also robust in signaling quality-of-service violation under dynamicity. Finally, we demonstrate a possible application of Alioth's interpretability, providing insights to benefit the decision-making of cloud operators. The dataset and code of Alioth have been released on GitHub.Comment: Accepted by 2023 IEEE International Parallel & Distributed Processing Symposium (IPDPS

Bioactive conformational generation of small molecules: A comparative analysis between force-field and multiple empirical criteria based methods

<p>Abstract</p> <p>Background</p> <p>Conformational sampling for small molecules plays an essential role in drug discovery research pipeline. Based on multi-objective evolution algorithm (MOEA), we have developed a conformational generation method called Cyndi in the previous study. In this work, in addition to Tripos force field in the previous version, Cyndi was updated by incorporation of MMFF94 force field to assess the conformational energy more rationally. With two force fields against a larger dataset of 742 bioactive conformations of small ligands extracted from PDB, a comparative analysis was performed between pure force field based method (FFBM) and multiple empirical criteria based method (MECBM) hybrided with different force fields.</p> <p>Results</p> <p>Our analysis reveals that incorporating multiple empirical rules can significantly improve the accuracy of conformational generation. MECBM, which takes both empirical and force field criteria as the objective functions, can reproduce about 54% (within 1Å RMSD) of the bioactive conformations in the 742-molecule testset, much higher than that of pure force field method (FFBM, about 37%). On the other hand, MECBM achieved a more complete and efficient sampling of the conformational space because the average size of unique conformations ensemble per molecule is about 6 times larger than that of FFBM, while the time scale for conformational generation is nearly the same as FFBM. Furthermore, as a complementary comparison study between the methods with and without empirical biases, we also tested the performance of the three conformational generation methods in MacroModel in combination with different force fields. Compared with the methods in MacroModel, MECBM is more competitive in retrieving the bioactive conformations in light of accuracy but has much lower computational cost.</p> <p>Conclusions</p> <p>By incorporating different energy terms with several empirical criteria, the MECBM method can produce more reasonable conformational ensemble with high accuracy but approximately the same computational cost in comparison with FFBM method. Our analysis also reveals that the performance of conformational generation is irrelevant to the types of force field adopted in characterization of conformational accessibility. Moreover, post energy minimization is not necessary and may even undermine the diversity of conformational ensemble. All the results guide us to explore more empirical criteria like geometric restraints during the conformational process, which may improve the performance of conformational generation in combination with energetic accessibility, regardless of force field types adopted.</p

Functional exchangeability of the nuclear localization signal (NLS) of capsid protein between PCV1 and PCV2 in vitro: Implications for the role of NLS in viral replication

<p>Abstract</p> <p>Background</p> <p>Porcine circovirus type 2 (PCV2) is believed to be the primary causative agent of postweaning multisystemic wasting syndrome (PMWS). It is supposed that capsid protein of PCV may contribute to replication control via interaction between Cap and Rep in the nucleoplasm. In this study, we described the construction and in vitro characterization of NLS-exchanged PCV DNA clones based on a PMWS-associated PCV2b isolate from China to determine the role of ORF2 NLS in PCV replication.</p> <p>Results</p> <p>The PCV1, PCV2, PCV2-NLS1 and PCV1-NLS2 DNA clone were generated by ligating a copy of respective genome in tandem with a partial duplication. The PCV2-NLS1 and PCV1-NLS2 DNA clone contained a chimeric genome in which the ORF2 NLS was exchanged. The four DNA clones were all confirmed to be infectious in vitro when transfected into PK-15 cells, as PCV capsid protein were expressed in approximately 10-20% of the transfected cells. The in vitro growth characteristics of the DNA clones were then determined and compared. All the recovered progeny viruses gave rise to increasing infectious titers during passages and were genetically stable by genomic sequencing. The chimeric PCV1-NLS2 and PCV2-NLS1 viruses had the final titers of about 10^4.2and 10^3.8TCID₅₀/ml, which were significantly lower than that of PCV1 and PCV2 (10^5.6and 10^5.0TCID₅₀/ml, respectively). When the ORF2 NLS exchanged, the mutant PCV2 (PCV2-NLS1) still replicated less efficiently and showed lower infectious titer than did PCV1 mutant (PCV1-NLS2), which was consistent with the distinction between wild type PCV1 and PCV2.</p> <p>Conclusions</p> <p>Recovery of the chimeiric PCV1-NLS2 and PCV2-NLS1 progeny viruses indicate that the nuclear localization signal sequence of capsid protein are functionally exchangeable between PCV1 and PCV2 with respect to the role of nuclear importing and propagation. The findings also reveal that ORF2 NLS play an accessory role in the replication of PCV. However, we found that ORF2 NLS was not responsible for the distinction of in vitro growth characteristic between PCV1 and PCV2. Further studies are required to determine the in vivo viral replication and pathogenicity of the NLS chimeric DNA clones.</p