Refining the Optimization Target for Automatic Univariate Time Series Anomaly Detection in Monitoring Services

Time series anomaly detection is crucial for industrial monitoring services that handle a large volume of data, aiming to ensure reliability and optimize system performance. Existing methods often require extensive labeled resources and manual parameter selection, highlighting the need for automation. This paper proposes a comprehensive framework for automatic parameter optimization in time series anomaly detection models. The framework introduces three optimization targets: prediction score, shape score, and sensitivity score, which can be easily adapted to different model backbones without prior knowledge or manual labeling efforts. The proposed framework has been successfully applied online for over six months, serving more than 50,000 time series every minute. It simplifies the user's experience by requiring only an expected sensitive value, offering a user-friendly interface, and achieving desired detection results. Extensive evaluations conducted on public datasets and comparison with other methods further confirm the effectiveness of the proposed framework.Comment: Accepted by 2023 IJCAI Worksho

Network resilience

Many systems on our planet are known to shift abruptly and irreversibly from one state to another when they are forced across a "tipping point," such as mass extinctions in ecological networks, cascading failures in infrastructure systems, and social convention changes in human and animal networks. Such a regime shift demonstrates a system's resilience that characterizes the ability of a system to adjust its activity to retain its basic functionality in the face of internal disturbances or external environmental changes. In the past 50 years, attention was almost exclusively given to low dimensional systems and calibration of their resilience functions and indicators of early warning signals without considerations for the interactions between the components. Only in recent years, taking advantages of the network theory and lavish real data sets, network scientists have directed their interest to the real-world complex networked multidimensional systems and their resilience function and early warning indicators. This report is devoted to a comprehensive review of resilience function and regime shift of complex systems in different domains, such as ecology, biology, social systems and infrastructure. We cover the related research about empirical observations, experimental studies, mathematical modeling, and theoretical analysis. We also discuss some ambiguous definitions, such as robustness, resilience, and stability.Comment: Review chapter

Evaluating the Risk of Roof Fall in Phosphate Mines: Case Study of the Shanshuya Phosphate Mine in China

AbstractRoof fall in phosphate mines seriously endangers the safety of the mining activity. In this paper, the risk of roof fall occurring in phosphate mines is evaluated using the underground phosphate mine in Shanshuya, China, as an engineering background. The factors affecting roof fall in phosphate mines are analyzed, and an index system for evaluating the risk of roof fall in phosphate mine is established. Four evaluation models are employed to evaluate the risk of roof fall occurring: a set pair analysis model based on combination weights, a comprehensive fuzzy model based on hierarchical analysis, an approximately ideal ranking model based on entropy weight, and a gray relational analysis model. The evaluation results of the first two models are moderate risk with a bias toward intense risk. And the evaluation results of the last two models are slight risk with a bias toward moderate risk and moderate risk with a bias toward slight risk, respectively. The suitability of each of the evaluation models is analyzed which reveals that the evaluation results obtained using the different models are inconsistent. A combined evaluation method based on the four original evaluation models is subsequently proposed. Application of the combined evaluation method to the Shanshuya phosphate mine produces results that the roof fall risk is moderate with a bias toward slight risk. It is consistent with the actual situation in this phosphate mine. The results of the study can be used to provide technical support to engineers evaluating the risk of roof fall occurring in similar phosphate mines

Schlafen 12 restricts HIV-1 latency reversal by a codon-usage dependent post-transcriptional block in CD4+ T cells

Latency is a major barrier towards virus elimination in HIV-1-infected individuals. Yet, the mechanisms that contribute to the maintenance of HIV-1 latency are incompletely understood. Here we describe the Schlafen 12 protein (SLFN12) as an HIV-1 restriction factor that establishes a post-transcriptional block in HIV-1-infected cells and thereby inhibits HIV-1 replication and virus reactivation from latently infected cells. The inhibitory activity is dependent on the HIV-1 codon usage and on the SLFN12 RNase active sites. Within HIV-1-infected individuals, SLFN12 expression in PBMCs correlated with HIV-1 plasma viral loads and proviral loads suggesting a link with the general activation of the immune system. Using an RNA FISH-Flow HIV-1 reactivation assay, we demonstrate that SLFN12 expression is enriched in infected cells positive for HIV-1 transcripts but negative for HIV-1 proteins. Thus, codon-usage dependent translation inhibition of HIV-1 proteins participates in HIV-1 latency and can restrict the amount of virus release after latency reversal.We thank Drs Yingying Li, Feng Gao and Beatrice H. Hahn for providing codon-optimized HIV-1 Gag expression vector, Drs James Hoxie and Susan Zolla-Pazner for supplying anti-Nef and -p24 antibodies, respectively through the NIH AIDS reagent program. We also thank Dr Song Gao for providing SLFN13-tRNA structure information, and Dr Maria-Eugenia Gas Lopez and Dr Ester Gea-Mallorquí for advise. This work was supported by following grants: M.K.I., JSPS Oversea Research Fellowship and Takeda Science Foundation; A.E.C., PT17/0009/0019 (ISCIII/MINECO and FEDER); M.J.B., RTI2018-101082-B-I00 and PID2021-123321OB-I00 [MINECO/FEDER]), and the Miguel Servet program by ISCIII (CP17/00179 and CPII22/00005); C.B., M.R.R., C.D.C., European Union’s Horizon 2020 research and innovation program under grant agreement 681137-EAVI2020 and NIH grant P01-AI131568; J.D., the Spanish Ministry of Science and Innovation (PID2019106959RB-I00/AEI/10.13039/501100011033); A.M., the Spanish Ministry of Science and Innovation (PID2019-106323RB-I00 AEI//10.13039/501100011033) and the institutional “María de Maeztu” Programme for Units of Excellence in R&D (CEX2018-000792-M).info:eu-repo/semantics/publishedVersio

Schlafen 12 restricts HIV-1 latency reversal by a codon-usage dependent post-transcriptional block in CD4+ T cells

Latency is a major barrier towards virus elimination in HIV-1-infected individuals. Yet, the mechanisms that contribute to the maintenance of HIV-1 latency are incompletely understood. Here we describe the Schlafen 12 protein (SLFN12) as an HIV-1 restriction factor that establishes a post-transcriptional block in HIV-1-infected cells and thereby inhibits HIV-1 replication and virus reactivation from latently infected cells. The inhibitory activity is dependent on the HIV-1 codon usage and on the SLFN12 RNase active sites. Within HIV-1-infected individuals, SLFN12 expression in PBMCs correlated with HIV-1 plasma viral loads and proviral loads suggesting a link with the general activation of the immune system. Using an RNA FISH-Flow HIV-1 reactivation assay, we demonstrate that SLFN12 expression is enriched in infected cells positive for HIV-1 transcripts but negative for HIV-1 proteins. Thus, codon-usage dependent translation inhibition of HIV-1 proteins participates in HIV-1 latency and can restrict the amount of virus release after latency reversal. In cell lines and HIV-1 patient PBMCs, the Schlafen 12 protein (SLFN12) is shown to be an HIV-1 restriction factor that inhibits HIV-1 replication and virus reactivatio