Open-Source ANSS Quake Monitoring System Software

ANSS stands for the Advanced National Seismic System of the U.S.A., and ANSS Quake Monitoring System (AQMS) is the earthquake management system (EMS) that most of its member regional seismic networks (RSNs) use. AQMS is based on Earthworm, but instead of storing files on disk, it uses a relational database with replication capability to store pick, amplitude, waveform, and event parameters. The replicated database and other features of AQMS make it a fully redundant system. A graphical user interface written in Java, Jiggle, is used to review automatically generated picks and event solutions, relocate events, and recalculate magnitudes. Add‐on mechanisms to produce various postearthquake products such as ShakeMaps and focal mechanisms are available as well. It provides a configurable automatic alarming and notification system. The Pacific Northwest Seismic Network, one of the Tier 1 ANSS RSNs, has modified AQMS to be compatible with a freely available, capable, open‐source database system, PostgreSQL, and is running this version successfully in production. The AQMS Software Working Group has moved the software from a subversion repository server hosted at the California Institute of Technology to a public repository at gitlab.com. The drawback of AQMS as a whole is that it is complex to fully configure and comprehend. Nevertheless, the fact that it is very capable, documented, and now free to use, might make it an attractive EMS choice for many seismic networks

Open-Source ANSS Quake Monitoring System Software

ANSS stands for the Advanced National Seismic System of the U.S.A., and ANSS Quake Monitoring System (AQMS) is the earthquake management system (EMS) that most of its member regional seismic networks (RSNs) use. AQMS is based on Earthworm, but instead of storing files on disk, it uses a relational database with replication capability to store pick, amplitude, waveform, and event parameters. The replicated database and other features of AQMS make it a fully redundant system. A graphical user interface written in Java, Jiggle, is used to review automatically generated picks and event solutions, relocate events, and recalculate magnitudes. Add‐on mechanisms to produce various postearthquake products such as ShakeMaps and focal mechanisms are available as well. It provides a configurable automatic alarming and notification system. The Pacific Northwest Seismic Network, one of the Tier 1 ANSS RSNs, has modified AQMS to be compatible with a freely available, capable, open‐source database system, PostgreSQL, and is running this version successfully in production. The AQMS Software Working Group has moved the software from a subversion repository server hosted at the California Institute of Technology to a public repository at gitlab.com. The drawback of AQMS as a whole is that it is complex to fully configure and comprehend. Nevertheless, the fact that it is very capable, documented, and now free to use, might make it an attractive EMS choice for many seismic networks

Earthquake Early Warning ShakeAlert System: Testing and Certification Platform

Earthquake early warning systems provide warnings to end users of incoming moderate to strong ground shaking from earthquakes. An earthquake early warning system, ShakeAlert, is providing alerts to beta end users in the western United States, specifically California, Oregon, and Washington. An essential aspect of the earthquake early warning system is the development of a framework to test modifications to code to ensure functionality and assess performance. In 2016, a Testing and Certification Platform (TCP) was included in the development of the Production Prototype version of ShakeAlert. The purpose of the TCP is to evaluate the robustness of candidate code that is proposed for deployment on ShakeAlert Production Prototype servers. TCP consists of two main components: a real‐time in situ test that replicates the real‐time production system and an offline playback system to replay test suites. The real‐time tests of system performance assess code optimization and stability. The offline tests comprise a stress test of candidate code to assess if the code is production ready. The test suite includes over 120 events including local, regional, and teleseismic historic earthquakes, recentering and calibration events, and other anomalous and potentially problematic signals. Two assessments of alert performance are conducted. First, point‐source assessments are undertaken to compare magnitude, epicentral location, and origin time with the Advanced National Seismic System Comprehensive Catalog, as well as to evaluate alert latency. Second, we describe assessment of the quality of ground‐motion predictions at end‐user sites by comparing predicted shaking intensities to ShakeMaps for historic events and implement a threshold‐based approach that assesses how often end users initiate the appropriate action, based on their ground‐shaking threshold. TCP has been developed to be a convenient streamlined procedure for objectively testing algorithms, and it has been designed with flexibility to accommodate significant changes in development of new or modified system code. It is expected that the TCP will continue to evolve along with the ShakeAlert system, and the framework we describe here provides one example of how earthquake early warning systems can be evaluated

Earthquake Early Warning ShakeAlert 2.0: Public Rollout

The ShakeAlert earthquake early warning system is designed to automatically identify and characterize the initiation and rupture evolution of large earthquakes, estimate the intensity of ground shaking that will result, and deliver alerts to people and systems that may experience shaking, prior to the occurrence of shaking at their location. It is configured to issue alerts to locations within the West Coast of the United States. In 2018, ShakeAlert 2.0 went live in a regional public test in the first phase of a general public rollout. The ShakeAlert system is now providing alerts to more than 60 institutional partners in the three states of the western United States where most of the nation’s earthquake risk is concentrated: California, Oregon, and Washington. The ShakeAlert 2.0 product for public alerting is a message containing a polygon enclosing a region predicted to experience modified Mercalli intensity (MMI) threshold levels that depend on the delivery method. Wireless Emergency Alerts are delivered for M 5+ earthquakes with expected shaking of MMI≥IV⁠. For cell phone apps, the thresholds are M 4.5+ and MMI≥III⁠. A polygon format alert is the easiest description for selective rebroadcasting mechanisms (e.g., cell towers) and is a requirement for some mass notification systems such as the Federal Emergency Management Agency’s Integrated Public Alert and Warning System. ShakeAlert 2.0 was tested using historic waveform data consisting of 60 M 3.5+ and 25 M 5.0+ earthquakes, in addition to other anomalous waveforms such as calibration signals. For the historic event test, the average M 5+ false alert and missed event rates for ShakeAlert 2.0 are 8% and 16%. The M 3.5+ false alert and missed event rates are 10% and 36.7%. Real‐time performance metrics are also presented to assess how the system behaves in regions that are well‐instrumented, sparsely instrumented, and for offshore earthquakes

Curated Pacific Northwest AI-ready Seismic Dataset

The curation of seismic datasets is the cornerstone of seismological research and the starting point of machine-learning applications in seismology. We present a 21-year-long AI-ready dataset of diverse seismic event parameters, instrumentation metadata, and waveforms, as curated by the Pacific Northwest Seismic Network and ourselves. The dataset contains about 190,000 three-component (3C) waveform traces from more than 65,000 earthquake and explosion events, and about 9,200 waveforms from 5,600 exotic events. The magnitude of the events ranges from 0 to 6.4, while the biggest one is 20 December 2022 M6.4 Ferndale Earthquake. We include waveforms from high-gain (EH, BH, and HH channels) and strong-motion (EN channels) seismometers and resample to 100 Hz. We describe the earthquake catalog and the temporal evolution of the data attributes (e.g., event magnitude type, channel type, waveform polarity, and signal-tonoise ratio, phase picks) as the network earthquake monitoring system evolved through time. We propose this AI-ready dataset as a new open-source benchmark dataset

Earthquake Early Warning ShakeAlert System: West Coast Wide Production Prototype

Earthquake early warning (EEW) is an application of seismological science that can give people, as well as mechanical and electrical systems, up to tens of seconds to take protective actions before peak earthquake shaking arrives at a location. Since 2006, the U.S. Geological Survey has been working in collaboration with several partners to develop EEW for the United States. The goal is to create and operate an EEW system, called ShakeAlert, for the highest risk areas of the United States, starting with the West Coast states of California, Oregon, and Washington. In early 2016, the Production Prototype v.1.0 was established for California; then, in early 2017, v.1.2 was established for the West Coast, with earthquake notifications being distributed to a group of beta users in California, Oregon, and Washington. The new ShakeAlert Production Prototype was an outgrowth from an earlier demonstration EEW system that began sending test notifications to selected users in California in January 2012. ShakeAlert leverages the considerable physical, technical, and organizational earthquake monitoring infrastructure of the Advanced National Seismic System, a nationwide federation of cooperating seismic networks. When fully implemented, the ShakeAlert system may reduce damage and injury caused by large earthquakes, improve the nation’s resilience, and speed recovery

Earthquake Early Warning ShakeAlert System: Testing and Certification Platform

Earthquake early warning systems provide warnings to end users of incoming moderate to strong ground shaking from earthquakes. An earthquake early warning system, ShakeAlert, is providing alerts to beta end users in the western United States, specifically California, Oregon, and Washington. An essential aspect of the earthquake early warning system is the development of a framework to test modifications to code to ensure functionality and assess performance. In 2016, a Testing and Certification Platform (TCP) was included in the development of the Production Prototype version of ShakeAlert. The purpose of the TCP is to evaluate the robustness of candidate code that is proposed for deployment on ShakeAlert Production Prototype servers. TCP consists of two main components: a real‐time in situ test that replicates the real‐time production system and an offline playback system to replay test suites. The real‐time tests of system performance assess code optimization and stability. The offline tests comprise a stress test of candidate code to assess if the code is production ready. The test suite includes over 120 events including local, regional, and teleseismic historic earthquakes, recentering and calibration events, and other anomalous and potentially problematic signals. Two assessments of alert performance are conducted. First, point‐source assessments are undertaken to compare magnitude, epicentral location, and origin time with the Advanced National Seismic System Comprehensive Catalog, as well as to evaluate alert latency. Second, we describe assessment of the quality of ground‐motion predictions at end‐user sites by comparing predicted shaking intensities to ShakeMaps for historic events and implement a threshold‐based approach that assesses how often end users initiate the appropriate action, based on their ground‐shaking threshold. TCP has been developed to be a convenient streamlined procedure for objectively testing algorithms, and it has been designed with flexibility to accommodate significant changes in development of new or modified system code. It is expected that the TCP will continue to evolve along with the ShakeAlert system, and the framework we describe here provides one example of how earthquake early warning systems can be evaluated

Safety of Intraoperative Blood Salvage during Liver Transplantation in Patients with Hepatocellular Carcinoma: A Systematic Review and Meta-analysis

Objective: The effects of intraoperative blood salvage (IBS) on time to tumor recurrence, disease-free survival and overall survival in hepatocellular carcinoma (HCC) patients undergoing liver transplantation were assessed to evaluate the safety of IBS. Background: IBS is highly effective to reduce the use of allogeneic blood transfusion. However, the safety of IBS during liver transplantation for patients with HCC is questioned due to fear of disseminating malignant cells. Methods: Comprehensive searches through June 2021 were performed in 8 databases. The methodological quality of included studies was assessed using the Robins-I tool. Meta-analysis with the generic inverse variance method was performed to calculate pooled hazard ratios (HRs) for disease-free survival, HCC recurrence and overall survival. Results: Nine studies were included (n=1997, IBS n=1200, no-IBS n=797). Use of IBS during liver transplantation was not associated with impaired disease-free survival [HR=0.90, 95% confidence interval (CI)=0.66-1.24, P=0.53, IBS n=394, no-IBS n=329], not associated with increased HCC recurrence (HR=0.83, 95% CI=0.57-1.23, P=0.36, IBS n=537, no-IBS n=382) and not associated with impaired overall survival (HR=1.04, 95% CI=0.79-1.37, P=0.76, IBS n=495, no-IBS n=356). Conclusions: Based on available observational data, use of IBS during liver transplantation in patients with HCC does not result in impaired disease-free survival, increased HCC recurrence or impaired overall survival. Therefore, use of IBS during liver transplantation for HCC patients is a safe procedure

Demonstration of the Cascadia G‐FAST Geodetic Earthquake Early Warning System for the Nisqually, Washington, Earthquake

A prototype earthquake early warning (EEW) system is currently in development in the Pacific Northwest. We have taken a two‐stage approach to EEW: (1) detection and initial characterization using strong‐motion data with the Earthquake Alarm Systems (ElarmS) seismic early warning package and (2) the triggering of geodetic modeling modules using Global Navigation Satellite Systems data that help provide robust estimates of large‐magnitude earthquakes. In this article we demonstrate the performance of the latter, the Geodetic First Approximation of Size and Time (G‐FAST) geodetic early warning system, using simulated displacements for the 2001 Mw 6.8 Nisqually earthquake. We test the timing and performance of the two G‐FAST source characterization modules, peak ground displacement scaling, and Centroid Moment Tensor‐driven finite‐fault‐slip modeling under ideal, latent, noisy, and incomplete data conditions. We show good agreement between source parameters computed by G‐FAST with previously published and postprocessed seismic and geodetic results for all test cases and modeling modules, and we discuss the challenges with integration into the U.S. Geological Survey’s ShakeAlert EEW system

The Role of Interleukin-21 in COVID-19 Vaccine-Induced B Cell-Mediated Immune Responses in Kidney Disease Patients and Kidney Transplant Recipients.

T cell mediated help to B cells is required for the development of humoral responses, in which the cytokine interleukin (IL)-21 is key. Here, we studied the mRNA-1273 vaccine-induced SARS-CoV-2-specific memory T cell IL-21 response, memory B cell response and IgG antibody levels in peripheral blood at 28 days after the 2nd vaccination by ELISpot and the fluorescent bead-based multiplex-immunoassay, respectively. We included 40 chronic kidney disease (CKD) patients, 34 patients on dialysis, 63 kidney transplant recipients (KTR) and 47 controls. We found that KTR, but not CKD and dialysis patients, had a significantly lower number of SARS-CoV-2-specific IL-21 producing T cells than controls (p<0.001). KTR and CKD patients showed lower numbers of SARS-CoV-2-specific IgG producing memory B cells when compared with controls (p<0.001 and p=0.01, respectively). The T cell IL-21 response was positively associated with the SARS-CoV-2-specific B cell response and the SARS-CoV-2 Spike S1-specific IgG antibody levels (both Pearson's r 0.5, p<0.001). In addition, SARS-CoV-2-specific B cell responses were shown to be IL-21 dependent. Taken together, we show that IL-21 signaling is important in eliciting robust B cell-mediated immune responses, also in kidney disease patients and KTR