CoFlux:Robustly Correlating KPIs by Fluctuations for Service Troubleshooting

Internet-based service companies monitor a large number of KPIs (Key Performance Indicators) to ensure their service quality and reliability. Correlating KPIs by fluctuations reveals interactions between KPIs under anomalous situations and can be extremely useful for service troubleshooting. However, such a KPI flux-correlation has been little studied so far in the domain of Internet service operations management. A major challenge is how to automatically and accurately separate fluctuations from normal variations in KPIs with different structural characteristics (such as seasonal, trend and stationary) for a large number of KPIs. In this paper, we propose CoFlux, an unsupervised approach, to automatically (without manual selection of algorithm fitting and parameter tuning) determine whether two KPIs are correlated by fluctuations, in what temporal order they fluctuate, and whether they fluctuate in the same direction. CoFlux's robust feature engineering and robust correlation score computation enable it to work well against the diverse KPI characteristics. Our extensive experiments have demonstrated that CoFlux achieves the best Fl-Scores of 0.84 (0.90),0.92 (0.95), 0.95 (0.99), in answering these three questions, in the two real datasets from a top global Internet company, respectively. Moreover, we showed that CoFlux is effective in assisting service troubleshooting through the applications of alert compression, recommending Top N causes, and constructing fluctuation propagation chains

Unveil the transcriptional landscape at the Cryptococcus-host axis in mice and nonhuman primates.

Pathogens and hosts require rapid modulation of virulence and defense mechanisms at the infection axis, but monitoring such modulations is challenging. In studying the human fungal pathogen Cryptococcus neoformans, mouse and rabbit infection models are often employed to shed light on the disease mechanisms but that may not be clinically relevant. In this study, we developed an animal infection model using the non-human primate cynomolgus monkey Macaca fascicularis. In addition, we systematically profiled and compared transcriptional responses between the infected mice and the cynomolgus monkey, using simultaneous or dual RNA next-generation sequencing. We demonstrated that there are shared but distinct transcriptional profiles between the two models following C. neoformans infection. Specifically, genes involved in immune and inflammatory responses are all upregulated. Osteoclastogenesis and insulin signaling are also significantly co-regulated in both models and disrupting an osteoclastogenesis-associated gene (OC-STAMP) or the insulin-signaling process significantly altered the host tolerance to C. neoformans. Moreover, C. neoformans was shown to activate metal sequestration, dampen the sugar metabolism, and control cell morphology during infection. Taking together, we described the development of a non-human primate model of cryptococcosis that allowed us to perform an in-depth analysis and comparison of transcriptome profiles during infections of two animal models and conceptually identify host genes important in disease responses. This study provides new insights in understanding fungal pathogenesis mechanisms that potentially facilitate the identification of novel drug targets for the treatment of cryptococcal infection

Confined Liquid-Phase Growth of Crystalline Compound Semiconductors on Any Substrate

The growth of crystalline compound semiconductors on amorphous and non-epitaxial substrates is a fundamental challenge for state-of-the-art thin-film epitaxial growth techniques. Direct growth of materials on technologically relevant amorphous surfaces, such as nitrides or oxides results in nanocrystalline thin films or nanowire-type structures, preventing growth and integration of high-performance devices and circuits on these surfaces. Here, we show crystalline compound semiconductors grown directly on technologically relevant amorphous and non-epitaxial substrates in geometries compatible with standard microfabrication technology. Furthermore, by removing the traditional epitaxial constraint, we demonstrate an <i>atomically sharp lateral heterojunction</i> between indium phosphide and tin phosphide, two materials with vastly different crystal structures, a structure that cannot be grown with standard vapor-phase growth approaches. Critically, this approach enables the growth and manufacturing of crystalline materials without requiring a nearly lattice-matched substrate, potentially impacting a wide range of fields, including electronics, photonics, and energy devices