Distributed joint optimization of traffic engineering and server selection

Internet service providers (ISP) apply traffic engineering (TE) in the underlay network to avoid congestion. On the other hand, content providers (CP) use different server selection (SS) strategies in the overlay network to reduce delay. It has been shown that a joint optimization of TE and SS is beneficial to the performance from both ISP's and CP's perspectives. One challenging issue in such a network is to design a distributed protocol which achieves optimality while revealing as little information as possible between ISP and CP. To address this problem, we propose a distributed protocol termed PETS, in which each router of ISP makes independent traffic engineering decision and each server of CP makes independent server selection decision. We prove that PETS can achieve optimality for the joint optimization of TE and SS. We also show that PETS can significantly reduce message passing and enables ISP to hide important underlay network information (e.g., topology) from CP. Furthermore, PETS can be easily extended to handle the case of multiple CPs in the network

Disordered structure for long-range charge density wave order in annealed crystals of magnetic kagome FeGe

Recently, charge density wave (CDW) has been observed well below the order of antiferromagnetism (AFM) in kagome FeGe in which magnetism and CDW are intertwined to form an emergent quantum ground state. The mechanism of CDW precipitating from an A-type AFM of Fe kagome sublattice is intensively debated. The structural distortion originating from the CDW has yet to be accurately determined in FeGe. Here we resolved the structure model of the CDW in annealed FeGe crystals through single crystal x-ray diffraction via a synchrotron radiation source. The annealed crystals exhibit strong CDW transition signals exemplified by sharp magnetic susceptibility drop and specific heat jump, as well as intense superlattice reflections from 2 $\times$ 2 $\times$ 2 CDW order. Occupational disorder of Ge atoms resulting from short-range CDW correlations above $T_\mathrm{CDW}$ has also been identified from the structure refinements. The dimerization of Ge atoms along c axis has been demonstrated to be the dominant distortion for CDW. The Fe kagome and Ge honeycomb sublattices only undergo subtle distortions. Occupational disorder of Ge atoms is also proved to exist in the CDW phase due to the random selection of partial Ge sites to be dimerized to realize the structural distortion. Our work paves the way to understanding the unconventional nature of CDW in FeGe not only by solving the structural distortion below $T_\mathrm{CDW}$ and identifying fluctuations above it but also by rationalizing the synthesis of high-quality crystals for in-depth investigations in the future.Comment: 18 pages, 4 figures. Comments are welcom

Modeling the Evolution of Biological Neural Networks Based on <i>Caenorhabditis elegans</i> Connectomes across Development

Knowledge of the structural properties of biological neural networks can help in understanding how particular responses and actions are generated. Recently, Witvliet et al. published the connectomes of eight isogenic Caenorhabditis elegans hermaphrodites at different postembryonic ages, from birth to adulthood. We analyzed the basic structural properties of these biological neural networks. From birth to adulthood, the asymmetry between in-degrees and out-degrees over the C. elegans neuronal network increased with age, in addition to an increase in the number of nodes and edges. The degree distributions were neither Poisson distributions nor pure power-law distributions. We have proposed a model of network evolution with different initial attractiveness for in-degrees and out-degrees of nodes and preferential attachment, which reproduces the asymmetry between in-degrees and out-degrees and similar degree distributions via the tuning of the initial attractiveness values. In this study, we present the well-preserved structural properties of C. elegans neuronal networks across development, and provide some insight into understanding the evolutionary processes of biological neural networks through a simple network model

Frequency-division-multiplexing based period-coded fringe pattern for reliable depth sensing

The fringe pattern can realize high-resolution and dense depth sensing. However, the phase ambiguity is a challenge in the fringe pattern. In this paper, one period-code pattern is embedded to the fringe pattern by the frequency-division-multiplexing (FDM) framework. The nonparametric skew and De Bruijn sequence are utilized to determine the label of the period. For a more reliable phase unwrapping, three criteria are utilized to rectify the period numbers further. Quantitative and qualitative experiments show that the proposed method can achieve more reliable depth sensing compared with the counterparts. Even the measured scene contains discontinuous surfaces or sharp edges, the proposed algorithm can attain reliable depth

Frequency-division-multiplexing based period-coded fringe pattern for reliable depth sensing

Abstract The fringe pattern can realize high-resolution and dense depth sensing. However, the phase ambiguity is a challenge in the fringe pattern. In this paper, one period-code pattern is embedded to the fringe pattern by the frequency-division-multiplexing (FDM) framework. The nonparametric skew and De Bruijn sequence are utilized to determine the label of the period. For a more reliable phase unwrapping, three criteria are utilized to rectify the period numbers further. Quantitative and qualitative experiments show that the proposed method can achieve more reliable depth sensing compared with the counterparts. Even the measured scene contains discontinuous surfaces or sharp edges, the proposed algorithm can attain reliable depth

Application of EPMA and LA-ICP-MS to Study Mineralogy of Arsenopyrite from the Haoyaoerhudong Gold Deposit, Inner Mongolia, China

BACKGROUND: The composition of major and trace elements in arsenopyrite can be used to identify the occurrence of elements and explore the remobilization and migration behaviour of elements in different stages. The Haoyaoerhudong gold deposit in Inner Mongolia is a super large gold deposit hosted in the black shales of the Bayan Obo Group. Gold-bearing minerals such as arsenopyrite and loellingite are present. Previous researchers have used the traditional powder dissolution method to analyze the isotope of the ore and discussed the source of ore-forming materials, but the migration and enrichment mechanism of gold has not been unraveled.OBJECTIVES: To understand the gold migration and enrichment process of this deposit.METHODS: Based on mineralogy, different types of arsenopyrite were analyzed by electron probe microanalyzer (EPMA) and inductively coupled plasma-mass spectrometry (ICP-MS). The data measured by EPMA was corrected by ZAF program, and the data measured by LA-ICP-MS was quantitatively calculated by "no internal standard-matrix normalized calibration".RESULTS: The results showed that loellingite was developed in arsenopyrite. They can be divided into Apy-Ⅰ1, Apy-Ⅰ2, Lo-Ⅰ in progressive shear deformation stage and Apy-Ⅱ1, Apy-Ⅱ2 and Lo-Ⅱ in post shear deformation stage. The major element composition of arsenopyrite in different generations was stable, with a small amount of Co and Ni and a trace amount of Sb, Te, Bi, Pb, Au and Ag. Cobalt was higher in Apy-Ⅱ1 and Apy-Ⅱ2, whereas Au, Bi, Pb and Te were obviously enriched in Apy-Ⅰ1. Loellingite was rich in As (64.06%-67.87%), Co (0.33%-4.98%), Ni (1.23%-6.37%). Trace elements such as Au, Te, Bi, Pb and Ag were more enriched in Lo-Ⅱ.CONCLUSIONS: Lo-Ⅱ is the most important gold-bearing mineral. The changes of temperature and sulfur fugacity lead to the precipitation of loellingite and native gold. Native gold is precipitated by remobilization and migration of "invisible gold" in early arsenopyrite and loellingite

C-176 loaded Ce DNase nanoparticles synergistically inhibit the cGAS-STING pathway for ischemic stroke treatment

The neuroinflammatory responses following ischemic stroke cause irreversible nerve cell death. Cell free-double strand DNA (dsDNA) segments from ischemic tissue debris are engulfed by microglia and sensed by their cyclic GMP-AMP synthase (cGAS), which triggers robust activation of the innate immune stimulator of interferon genes (STING) pathway and initiate the chronic inflammatory cascade. The decomposition of immunogenic dsDNA and inhibition of the innate immune STING are synergistic immunologic targets for ameliorating neuroinflammation. To combine the anti-inflammatory strategies of STING inhibition and dsDNA elimination, we constructed a DNase-mimetic artificial enzyme loaded with C-176. Nanoparticles are self-assembled by amphiphilic copolymers (P[CL35-b-(OEGMA20.7-co-NTAMA14.3)]), C-176, and Ce4+ which is coordinated with nitrilotriacetic acid (NTA) group to form corresponding catalytic structures. Our work developed a new nano-drug that balances the cGAS-STING axis to enhance the therapeutic impact of stroke by combining the DNase-memetic Ce4+ enzyme and STING inhibitor synergistically. In conclusion, it is a novel approach to modulating central nervus system (CNS) inflammatory signaling pathways and improving stroke prognosis

Single‐cell transcriptomics identify TNFRSF1B as a novel T‐cell exhaustion marker for ovarian cancer

Abstract Background: Ovarian cancer (OC) patients routinely show poor immunotherapeutic response due to the complex tumour microenvironment (TME). It is urgent to explore new immunotherapeutic markers. Methods: Through the single‐cell RNA sequencing (scRNA‐seq) analyses on high‐grade serous OC (HGSOC), moderate severity borderline tumour and matched normal ovary, we identified a novel exhausted T cells subpopulation that related to poor prognosis in OC. Histological staining, multiple immunofluorescences, and flow cytometry were applied to validate some results from scRNA‐seq. Furthermore, a tumour‐bearing mice model was constructed to investigate the effects of TNFRSF1B treatment on tumour growth in vivo. Results: Highly immunosuppressive TME in HGSOC is displayed compared to moderate severity borderline tumour and matched normal ovary. Subsequently, a novel exhausted subpopulation of CD8+TNFRSF1B+ T cells is identified, which is associated with poor survival. In vitro experiments demonstrate that TNFRSF1B is specifically upregulated on activated CD8+ T cells and suppressed interferon‐γ secretion. The expression of TNFRSF1B on CD8+T cells is closely related to OC clinical malignancy and is a marker of poor prognosis through 140 OC patients’ verification. In addition, the blockade of TNFRSF1B inhibits tumour growth via profoundly remodeling the immune microenvironment in the OC mouse model. Conclusions: Our transcriptomic results analyzed by scRNA‐seq delineate a high‐resolution snapshot of the entire tumour ecosystem of OC TME. The major applications of our findings were an exhausted subpopulation of CD8+TNFRSF1B+ T cells for predicting OC patient prognosis and the potential therapeutic value of TNFRSF1B. These findings demonstrated the clinical value of TNFRSF1B as a potential immunotherapy target and extended our understanding of factors contributing to immunotherapy failure in OC