5,5′-Bis[(2,2,2-trifluoro­eth­oxy)meth­yl]-2,2′-bipyridine

The complete molecule of the title compound, C16H14F6N2O2, is generated by crystallographic inversion symmetry, which results in two short intramolecular C—H⋯N hydrogen-bond contacts per molecule. In the crystal, aromatic π–π stacking [centroid–centroid distance = 3.457 (2) Å] and weak C—H⋯π inter­actions occur. A short H⋯H [2.32 (3) Å] contact is present

On the Importance and Applicability of Pre-Training for Federated Learning

Pre-training is prevalent in nowadays deep learning to improve the learned model's performance. However, in the literature on federated learning (FL), neural networks are mostly initialized with random weights. These attract our interest in conducting a systematic study to explore pre-training for FL. Across multiple visual recognition benchmarks, we found that pre-training can not only improve FL, but also close its accuracy gap to the counterpart centralized learning, especially in the challenging cases of non-IID clients' data. To make our findings applicable to situations where pre-trained models are not directly available, we explore pre-training with synthetic data or even with clients' data in a decentralized manner, and found that they can already improve FL notably. Interesting, many of the techniques we explore are complementary to each other to further boost the performance, and we view this as a critical result toward scaling up deep FL for real-world applications. We conclude our paper with an attempt to understand the effect of pre-training on FL. We found that pre-training enables the learned global models under different clients' data conditions to converge to the same loss basin, and makes global aggregation in FL more stable. Nevertheless, pre-training seems to not alleviate local model drifting, a fundamental problem in FL under non-IID data.Comment: Preprin

Accelerating Spatial Data Processing with MapReduce

Abstract—MapReduce is a key-value based programming model and an associated implementation for processing large data sets. It has been adopted in various scenarios and seems promising. However, when spatial computation is expressed straightforward by this key-value based model, difficulties arise due to unfit features and performance degradation. In this paper, we present methods as follows: 1) a splitting method for balancing workload, 2) pending file structure and redundant data partition dealing with relation between spatial objects, 3) a strip-based two-direction plane sweep-ing algorithm for computation accelerating. Based on these methods, ANN(All nearest neighbors) query and astronomical cross-certification are developed. Performance evaluation shows that the MapReduce-based spatial applications outperform the traditional one on DBMS

Robust Positioning Patterns with Low Redundancy

A robust positioning pattern is a large array that allows a mobile device to locate its position by reading a possibly corrupted small window around it. In this paper, we provide constructions of binary positioning patterns, equipped with efficient locating algorithms, that are robust to a constant number of errors and have redundancy within a constant factor of optimality. Furthermore, we modify our constructions to correct rank errors and obtain binary positioning patterns robust to any errors of rank less than a constant number. Additionally, we construct $q$-ary robust positioning sequences robust to a large number of errors, some of which have length attaining the upper bound. Our construction of binary positioning sequences that are robust to a constant number of errors has the least known redundancy amongst those explicit constructions with efficient locating algorithms. On the other hand, for binary robust positioning arrays, our construction is the first explicit construction whose redundancy is within a constant factor of optimality. The locating algorithms accompanying both constructions run in time cubic in sequence length or array dimension.Comment: Extended Version of SODA 2019 Pape

The Regulatory Effects of Paeoniflorin and Its Derivative Paeoniflorin-6′-O-Benzene Sulfonate CP-25 on Inflammation and Immune Diseases

The plant extract “total glucosides of peony” (TGP) constitutes a mixture of glycosides that is isolated from the roots of the well-known traditional Chinese herb Paeonia lactiflora Pall. Paeoniflorin (Pae) is the most abundant component and the main biologically active ingredient of TGP. Pharmacologically, Pae exhibits powerful anti-inflammatory and immune regulatory effects in some animal models of autoimmune diseases including Rheumatoid Arthritis (RA) and Systemic Lupus Erythematosus (SLE). Recently, we modified Pae with an addition of benzene sulfonate to achieve better bioavailability and higher anti-inflammatory immune regulatory effects. This review summarizes the pharmacological activities of Pae and the novel anti-inflammatory and immunomodulatory agent Paeoniflorin-6′-O-benzenesulfonate (CP-25) in various chronic inflammatory and autoimmune disorders. The regulatory effects of Pae and CP-25 make them promising agents for other related diseases, which require extensive investigation in the future

Identification, Characterization, and Effects of Xenopus laevis PNAS-4 Gene on Embryonic Development

Apoptosis plays an important role in embryonic development. PNAS-4 has been demonstrated to induce apoptosis in several cancer cells. In this study, we cloned Xenopus laevis PNAS-4 (xPNAS-4), which is homologous to the human PNAS-4 gene. Bioinformatics analysis for PNAS-4 indicated that xPNAS-4 shared 87.6% identity with human PNAS-4 and 85.5% with mouse PNAS-4. The phylogenetic tree of PNAS-4 protein was also summarized. An analysis of cellular localization using an EGFP-fused protein demonstrated that xPNAS-4 was localized in the perinuclear region of the cytoplasm. RT-PCR analysis revealed that xPNAS-4, as a maternally expressed gene, was present in all stages of early embryo development. Whole-mount in situ hybridization showed that xPNAS-4 was mainly expressed in ectoderm and mesoderm. Furthermore, microinjection of xPNAS-4 mRNA in vivo caused developmental defects manifesting as a small eye phenotype in the Xenopous embryos, and as a small eye or one-eye phenotype in developing zebrafish embryos. In addition, embryos microinjected with xPNAS-4 antisense morpholino oligonucleotides (MOs) exhibited a failure of head development and shortened axis

CpG-binding protein CFP1 promotes ovarian cancer cell proliferation by regulating BST2 transcription

Epigenetic alterations have been functionally linked to ovarian cancer development and occurrence. The CXXC zinc finger protein 1 (CFP1) is an epigenetic regulator involved in DNA methylation and histone modification in mammalian cells. However, its role in ovarian cancer cells is unknown. Here, we show that CFP1 protein is highly expressed in human ovarian cancer tissues. Loss of CFP1 inhibited the growth of human ovarian cancer cells, promoted apoptosis, and increased senescence. CFP1 knockdown resulted in reduced levels of SETD1 (a CFP1 partner) and histone H3 trimethylation at the fourth lysine residue (H3K4me3). RNA-sequencing revealed that deletion of CFP1 resulted in mRNA reduction of bone marrow stromal cell antigen 2 (BST2). Bioinformatics analysis and chromatin immunoprecipitation showed that CFP1 binds to the promoter of BST2 and regulates its transcription directly. Overexpression of BST2 rescued the growth inhibitory effect of CFP1 loss. Furthermore, depletion of cullin-RING ubiquitin ligases 4 (CRL4) components ROC1 or CUL4A had significantly inhibited the expression of CFP1 and BST2 similar to MLN4924 treatment that blocked cullin neddylation and inactivated CRL4s. In conclusion, CFP1 promotes ovarian cancer cell proliferation and apoptosis by regulating the transcription of BST2, and the expression of CFP1 was affected by CRL4 ubiquitin ligase complex