Level Trigger Research Articles

Effect of Setup Times and Workload Trigger Levels on Order Review and Release Policies Performance in a Stochastic Dynamic Job Shop with Sequence-Dependent Setup Time — A Simulation Approach

Order review and release (ORR) in a job shop considering sequence-dependent setup time (SDST) is among the most challenging job shop problems. This study investigates the effect of varying setup times and workload trigger levels on ORR policies performance in a stochastic dynamic job shop considering SDST. It is essential to examine the effect of varying setup times and workload trigger levels on ORR policies, because, for different ORR policies, workload trigger level plays a major role to control the work-in-process on the shop floor. Further, in manufacturing industries, less setup time is required in some cases, but it can also be equal to or greater than the processing time in others. Promodel[Formula: see text] simulation software is used to develop the simulation model for conducting experiments. The performance of the system is evaluated in terms of mean lead time (MLT), mean throughput time (MTT), number of tardy jobs (NOTJ), and total setups (TS) performance measures. From results, it is found that for a given ORR policy and at a given setup time level, lower workload trigger level provides minimum MTT and maximum MLT, TS, and NOTJ performance measures. As the workload trigger level increases, MTT performance measure increases, whereas MLT, TS, and NOTJ performance measures decrease. Further, for a given ORR policy and workload trigger level, as the setup time level increases, MTT and MLT performance measures increase. In contrast, TS and NOTJ performance measures decrease. A stochastic dynamic job shop considering ORR and SDST where setup time is either less than, equal to or more than operation processing time is the novelty of the work.

Advance Landslide Prediction and Warning Model Based on Stacking Fusion Algorithm

In landslide disaster warning, a variety of monitoring and warning methods are commonly adopted. However, most monitoring and warning methods cannot provide information in advance, and serious losses are often caused when landslides occur. To advance the warning time before a landslide, an innovative advance landslide prediction and warning model based on a stacking fusion algorithm using Baishuihe landslide data is proposed in this paper. The Baishuihe landslide area is characterized by unique soil and is in the Three Gorges region of China, with a subtropical monsoon climate. Based on Baishuihe historical data and real-time monitoring of the landslide state, four warning level thresholds and trigger conditions for each warning level are established. The model effectively integrates the results of multiple prediction and warning submodels to provide predictions and advance warnings through the fusion of two stacking learning layers. The possibility that a risk priority strategy can be used as a substitute for the stacking model is also discussed. Finally, an experimental simulation verifies that the proposed improved model can not only provide advance landslide warning but also effectively reduce the frequency of false warnings and mitigate the issues of traditional single models. The stacking model can effectively support disaster prevention and reduction and provide a scientific basis for land use management.

Neural-network-based level-1 trigger upgrade for the SuperCDMS experiment at SNOLAB

The extended physics program of the SuperCDMS SNOLAB dark matter search experiment aims to maximize the sensitivity to low-mass dark matter. To realize this, an upgrade of the existing level-1 trigger of the data acquisition system is proposed by making use of a recurrent neural network to be implemented on the trigger FPGA. This provides an improved amplitude estimator and signal-noise discriminator based on the combined information of filtered traces from individual detector channels. The architecture and configuration of this neural trigger are discussed in this article, and the improvements in key performance indicators such as the efficiency, resolution, and noise rate are quantified based on signal simulations and noise data. Based on the findings in this proof of concept, the trigger threshold is expected to be lowered by ∼ 22%.

System Design and Prototyping for the CMS Level-1 Trigger at the High-Luminosity LHC

The High-Luminosity Large Hadron Collider (HL-LHC) is planned to offer a very ambitious physics program, with high-precision measurement and evaluation of the Standard Model (SM), and motivate the searches for new physics. The efficient data collection and precise events reconstruction in the harsh environment of 200 proton-proton interactions are vital for achieving the success of the HL-LHC program. To realize these requirements, the CMS detector has planned to completely replace the data acquisition (DAQ) and trigger system. The CMS Level-1 trigger system will handle the enormous detector input bandwidth of 63 Tbps with the maximum output rate of 750 kHz and is desired to complete the processing within 12.5 μs. For this purpose, CMS has planned to replace the Phase-1 μTCA-based processor boards and crates with an ATCA form factor. Each ATCA board will host Xilinx large UltraScale/UltraScale+ family FPGA and support more than a hundred high-speed optical links (~28 Gbps), capable of meeting the high bandwidth and processing requirements of HL-LHC. Along with the advancement in hardware, the Level-1 trigger system will employ highly modular, flexible, and adequately sophisticated algorithms that were only possible in offline reconstruction, such as the particle-flow algorithm. The modular and flexible architecture will help address the HL-LHC dynamic physics requirements. We will discuss the details of system design, prototyping, and the algorithms employed for the Level-1 trigger system.

A FPGA-Based Architecture for Real-Time Cluster Finding in the LHCb Silicon Pixel Detector

This article describes a custom VHDL firmware implementation of a two-dimensional cluster-finder architecture for reconstructing hit positions in the new vertex pixel detector (VELO) that is part of the LHCb Upgrade. This firmware has been deployed to the existing FPGA cards that perform the readout of the VELO, as a further enhancement of the DAQ system, and will run in real time during physics data taking, reconstructing VELO hits coordinates on-the-fly at the LHC collision rate. This pre-processing allows the first level of the software trigger to accept a 11% higher rate of events, as the ready-made hits coordinates accelerate the track reconstruction and consumes significantly less electrical power. It additionally allows the raw pixel data to be dropped at the readout level, thus saving approximately 14% of the DAQ bandwidth. Detailed simulation studies have shown that the use of this real-time cluster finding does not introduce any appreciable degradation in the tracking performance in comparison to a full-fledged software implementation. This work is part of a wider effort aimed at boosting the real-time processing capability of HEP experiments by delegating intensive tasks to dedicated computing accelerators deployed at the earliest stages of the data acquisition chain.

Progress in Design and Testing of the DAQ and Data-Flow Control for the Phase-2 Upgrade of the CMS Experiment

The second phase of the LHC, the High-Luminosity LHC, is scheduled to start in 2029, after a shutdown during which the beam intensity and focusing will be significantly upgraded. For this HL-LHC era, also the CMS detector will receive an extensive upgrade, primarily to maintain its physics performance at increasing pileup. The Phase-2 CMS Level-1 trigger rate will increase to 750 kHz, for an estimated data rate in excess of 50 Tbit/s. The Phase-2 CMS off-detector electronics will be based on the ATCA standard, with back-end boards receiving the detector data from the on-detector front-ends via custom, radiation-tolerant, optical links. The CMS Phase-2 data acquisition design tightens the integration between trigger control and data flow, extending the synchronous regime of the DAQ system. At the core of the design is the DAQ and Timing Hub, a custom ATCA hub card forming the bridge between the different, detector-specific, control and readout electronics and the common timing, trigger, and control systems. The overall synchronisation and data flow of the experiment is handled by the Trigger and Timing Control and Distribution System. For increased flexibility during commissioning and calibration runs, the design of the Phase-2 trigger and timing distribution system breaks with the traditional distribution tree, in favour of a configurable network connecting multiple independent control units to all off-detector endpoints. In order to reduce the number of custom hardware designs required, the DAQ hardware is designed such that it can also be used to implement the Trigger and Timing Control and Distribution System.

Design and Commissioning of the First 32-Tbit/s Event-Builder

The LHCb experiment is a forward spectrometer, designed to study beauty and charm quarks Physics at the LHC. To exploit of the higher luminosity that will be delivered during Run3, the full experiment needed a substantial upgrade, from the detector to the Data Acquisition (DAQ) and High Level Trigger (HLT). In this paper, we will focus on the new DAQ system for the LHCb experiment; that represents a substantial paradigm shift compared to the previous one, and to similar systems used by similar experiments in the past and present times. To overcome the inefficiencies introduced by a local selection implemented directly with the readout hardware, the Run3 system is designed to perform a full software reconstruction of all the produced events. To achieve this, both the DAQ and the HLT need to process the ~ 30 MHz full event-rate. In particular, this paper will introduce the final design of the system; it will provide a focus on the hardware and software design of the Event Building (EB) and how we integrated technologies designed for the High Performance Computing (HPC) world - like InfiniBand HDR (200 Gb/s)- into the DAQ system; we will present performance measurements of the full EB system under different operational conditions; and we will provide a feedback from EB operation during the beginning of the data-taking.

In vitro bioassays to monitor complex chemical mixtures at a carbon-based indirect potable reuse plant

Potable water reuse technologies are used to treat wastewater to drinking water quality to help sustain a community's water resources. California has long led the adoption of potable water reuse technologies in the United States and more states are exploring these technologies as water resources decline. Reuse technologies also need to achieve adequate reductions in microbial and chemical contaminant risks to meet public health goals and secure public acceptance. In vitro bioassays are a useful tool for screening if reuse treatment processes adequately reduce toxicity associated with a range of chemical classes that are contaminants of concern. In this study, we used an aryl hydrocarbon receptor (AhR) and an estrogen receptor luciferase bioassay to detect the presence of dioxin-like and estrogenic compounds across a 3800 m3/d carbon-based indirect potable reuse plant that uses carbon-based treatment (SWIFT-RC). Our results demonstrate significant removal of dioxin-like compounds across the SWIFT-RC treatment train. Estrogenicity declined across the treatment train for some months but was extremely variable and low with many samples falling below the method quantification level; consequently, we were not able to reliably determine estrogenicity trends for SWIFT-RC. Comparing the bioanalytical equivalent concentrations detected in the SWIFT-RC water with established monitoring trigger levels from the state of California suggests that SWIFT-RC produced water that met the bioassay guidelines. The log total organic carbon concentration and AhR assay equivalent concentrations are weakly correlated when data across all SWIFT-RC processes are included. Overall, this research demonstrates the performance of in vitro bioassays at a demonstration-scale carbon-based IPR system and highlights both the potential utility and challenges associated with these methods for assessing system performance.

Proposed Drinking Water Standards for PFAS

Proposed Drinking Water Standards for PFAS

İn Vitro Fertilizasyon/İntrasitoplazmik Sperm Enjeksiyonu Uygulanan Çiftlerde Paternal Yaşın Düşük Oranlarına Etkisi

Aim: The aim of this study was to determine the effect of paternal age on miscarriage rates in couples undergoing in vitro fertilization/intracytoplasmic sperm injection treatment cycles. Material and Methods: Patients were classified into two groups. The study group consisted of the patients whose pregnancy resulted in a miscarriage (n=73) and a control group in which the patients had a live singleton birth (n=256). Demographic characteristics, treatment indications, duration of infertility, menstruation day 3 follicle stimulating hormone, estradiol, luteinizing hormone, total antral follicle count, anti-Mullerian hormone levels and controlled ovarian stimulation parameters, day of trigger, estradiol and progesterone levels on the day of trigger, the total number of oocytes retrieved, the number of mature oocytes, the number and quality of the embryo, endometrial thickness on the day of trigger, oocyte pick up and embryo transfer, the distance of embryo-fundus and the day of embryo transfer were recorded. Results: Totally 329 women were included in the present study. The number of patients with the diagnosis of unexplained infertility was statistically significantly higher in the study group than in the control group (p=0.020). Maternal age was found statistically significantly higher in the study group than in the control group (p=0.025). When maternal age increased by 1 unit, the risk of miscarriage increased by 8.7% and those with unexplained infertility had a 75.6% higher risk of miscarriage than those without unexplained infertility. Conclusion: Paternal age was not associated with miscarriage whereas maternal age and unexplained infertility had a positive correlation with miscarriage rate.

Enzyme‐Inspired Nanoreactor Containing Light‐Controlled “Trojan Horse” for Redox‐Hypersensitive Drug Delivery

AbstractThe applications of bioresponsive materials are limited by the low levels of physiological triggers and spatiotemporal barriers in vivo. To address these issues, a light‐controlled “Trojan horse” strategy is proposed by encapsulating a photo‐caged reducing agent within reduction‐responsive polymer vesicles. The polymersomes act as an enzyme‐inspired nanoreactor for efficient photo‐synthesis of dithiothreitol in situ, which attacks the disulfide bonds in polymer backbones and disintegrates the vehicles from the inside in a nanoconfined space. The assembly‐catalyzed photoreduction reaction overcomes the temporal and spatial barriers for hyper‐responsivity and enables ultrafast drug release even at 0.014 mm of dithiothreitol residues, a concentration 715 times lower than that required to cleave disulfide bonds. In addition, in both vitro and vivo, the equipment of upconverting nanoparticles and photothermal agents creates a near‐infrared light‐activated and self‐heating nanoreactor, which allows for efficient intracellular drug delivery and excellent photo‐chemo‐immunotherapy of tumors. This work presents a new approach to designing smart materials and a promising platform for on‐demand drug delivery applications.

Test beam performance of a CBC3-based mini-module for the Phase-2 CMS Outer Tracker before and after neutron irradiation

The Large Hadron Collider (LHC) at CERN will undergo major upgrades to increase the instantaneous luminosity up to 5–7.5×1034 cm-2s-1. This High Luminosity upgrade of the LHC (HL-LHC) will deliver a total of 3000–4000 fb-1 of proton-proton collisions at a center-of-mass energy of 13–14 TeV. To cope with these challenging environmental conditions, the strip tracker of the CMS experiment will be upgraded using modules with two closely-spaced silicon sensors to provide information to include tracking in the Level-1 trigger selection. This paper describes the performance, in a test beam experiment, of the first prototype module based on the final version of the CMS Binary Chip front-end ASIC before and after the module was irradiated with neutrons. Results demonstrate that the prototype module satisfies the requirements, providing efficient tracking information, after being irradiated with a total fluence comparable to the one expected through the lifetime of the experiment.

Risk of stream loss from changing irrigation, climate and groundwater extraction on the southern riverine plain of the Murray-Darling Basin in south-eastern Australia

ABSTRACTThe rivers of the south-eastern Murray-Darling Basin (MDB) and the associated irrigation areas of the southern riverine plain (SRP) in south-eastern Australia have undergone major hydrological changes over the last 30 years. These include a period of lower rainfall; a rebalance of surface water diversions between consumptive and environmental water uses under the MDB Basin Plan, improvements in water infrastructure; water trade out of the region; and falling groundwater levels. All these changes increase losses from streams to groundwater systems; potentially leading to the need for greater releases from dams to maintain baseflow in the major rivers. Baseflow is important for conveyance of water, water quality and baseflow-dependent ecosystems during dry periods. Hydrological changes in the SRP will reduce the streamflow by 2029–30 by an estimated 80 to 320 GL/yr. Further hydrological changes by 2029–30 will reduce the streamflow by another 50 GL/yr in the following decade. This is the first assessment of the cumulative stream impacts of the SRP and is relatively lower than previous assessments for single drivers. The current approach of mitigating unexpected losses is to increase conveyance loss budgets as required. This could be extended to mitigate the lower end of potential impacts; but further steps to reduce losses may be required towards the upper end. Further actions include a review of extraction limits for surface water and groundwater, trigger levels, and a greater shift towards conjunctive water management. Groundwater extraction, which has dominated impacts, is increasing from a relatively low proportion of the extraction limit in Goulburn-Murray Sedimentary Plain and shallow aquifers of the SRP. Over time, climate change will become more dominant as a driver. Most monitoring required to support mitigation already exists, but data is not collated or reported in a form relevant for stream impacts. Modelling also needs to be updated with reporting of more relevant outputs.

Commissioning of the new muon-to-central-trigger-processor interface at ATLAS

The ATLAS trigger system includes a Level-1 (L1) trigger based on custom electronics and firmware, and a high-level software trigger running on off-the-shelf hardware. The L1 trigger system uses information from the forward detectors, the calorimeters and the muon trigger detectors. Once information from all muon trigger sectors has been received, trigger candidate multiplicities are calculated by the Muon-to-Central-Trigger-Processor Interface (MUCTPI). Muon multiplicity information is sent to the Central-Trigger-Processor (CTP) and trigger objects are sent to the L1 Topological Trigger Processor (L1Topo). The CTP combines the information received from the MUCTPI with the trigger information from the forward detectors, the calorimeters and the L1Topo, and takes the L1 trigger decision. As part of the ATLAS L1 trigger system upgrade for Run-3 of the Large Hadron Collider (LHC) a new MUCTPI has been designed and commissioned. We discuss the commissioning and operation of the new MUCTPI used in ATLAS from the beginning of Run-3. In particular, we describe the integration tests which have been carried out for the commissioning and operation of the new MUCTPI.

The Credit Suisse CoCo wipeout: Facts, misperceptions, and lessons for financial regulation

The Credit Suisse CoCo wipeout: Facts, misperceptions, and lessons for financial regulation

Mechanoelectric effects in healthy cardiac function and under Left Bundle Branch Block pathology

Mechanoelectric feedback (MEF) in the heart operates through several mechanisms which serve to regulate cardiac function. Stretch activated channels (SACs) in the myocyte membrane open in response to cell lengthening, while tension generation depends on stretch, shortening velocity, and calcium concentration. How all of these mechanisms interact and their effect on cardiac output is still not fully understood. We sought to gauge the acute importance of the different MEF mechanisms on heart function.An electromechanical computer model of a dog heart was constructed, using a biventricular geometry of 500K tetrahedral elements. To describe cellular behavior, we used a detailed ionic model to which a SAC model and an active tension model, dependent on stretch and shortening velocity and with calcium sensitivity, were added. Ventricular inflow and outflow were connected to the CircAdapt model of cardiovascular circulation. Pressure–volume loops and activation times were used for model validation.Simulations showed that SACs did not affect acute mechanical response, although if their trigger level was decreased sufficiently, they could cause premature excitations. The stretch dependence of tension had a modest effect in reducing the maximum stretch, and stroke volume, while shortening velocity had a much bigger effect on both. MEF served to reduce the heterogeneity in stretch while increasing tension heterogeneity. In the context of left bundle branch block, a decreased SAC trigger level could restore cardiac output by reducing the maximal stretch when compared to cardiac resynchronization therapy. MEF is an important aspect of cardiac function and could potentially mitigate activation problems.

A 40 MHz Level-1 trigger scouting system for the CMS Phase-2 upgrade

The CMS Phase-2 upgrade for the HL-LHC aims at preserving and expanding the current physics capability of the experiment under extreme pileup conditions. A new tracking system incorporates a track finder processor, providing tracks to the Level-1 (L1) trigger. A new high-granularity calorimeter provides fine-grained energy deposition information in the endcap region. New front-end and back-end electronics feed the L1 trigger with high-resolution information from the barrel calorimeter and the muon systems. The upgraded L1 will be based primarily on the Xilinx Ultrascale Plus series of FPGAs, capable of sophisticated feature searches with resolution often similar to the offline reconstruction. The L1 Data Scouting system (L1DS) will capture L1 intermediate data produced by the trigger processors at the beam-crossing rate of 40 MHz, and carry out online analyses based on these limited-resolution data. The L1DS will provide fast and virtually unlimited statistics for detector diagnostics, alternative luminosity measurements, and, in some cases, calibrations. It also has the potential to enable the study of otherwise inaccessible signatures, either too common to fit in the L1 trigger accept budget or with requirements that are orthogonal to “mainstream” physics. The requirements and architecture of the L1DS system are presented, as well as some of the potential physics opportunities under study. The first results from the assembly and commissioning of a demonstrator currently being installed for LHC Run-3 are also presented. The demonstrator collects data from the Global Muon Trigger, the Layer-2 Calorimeter Trigger, the Barrel Muon Track Finder, and the Global Trigger systems of the current CMS L1. This demonstrator, as a data acquisition (DAQ) system operating at the LHC bunch-crossing rate, faces many of the challenges of the Phase-2 system, albeit with scaled-down connectivity, reduced data throughput and physics capabilities, providing a testing ground for new techniques of online data reduction and processing.

Upgrade of ATLAS Hadronic Tile Calorimeter for the High Luminosity LHC

The Tile Calorimeter (TileCal) is a sampling hadron calorimeter covering the central region of the ATLAS experiment, with steel as absorber and plastic scintillators as active medium. The High Luminosity phase of the Large Hadron Collider (LHC) is expected to start in 2029 and five times the present instantaneous luminosity will be delivered by the machine. TileCal will require new electronics to meet the requirements of a 1 MHz trigger, to be robust against higher radiation level, and to ensure better performance under high pile-up conditions. Both the on- and off-detector TileCal electronics will be replaced during the shutdown of 2026-2028. PMT signals from every TileCal cell will be digitized and sent directly to the back-end electronics, where the signals are reconstructed, stored, and sent to the first level of trigger at a rate of 40 MHz. This will provide better precision of the calorimeter signals used by the trigger system and will allow the development of more complex trigger algorithms. The modular front-end electronics feature radiation-tolerant commercial off-the-shelf components and redundant design to minimise single points of failure. The timing, control and communication interface with the off-detector electronics is implemented with modern Field Programmable Gate Arrays and high speed fibre optic links running up to 9.6 Gb/s. The TileCal upgrade program has included extensive research and development studies, and test beam studies. A Demonstrator module with reverse compatibility with the existing system was inserted in ATLAS in August 2019 for testing in actual detector conditions. The ongoing developments for on- and off-detector systems, together with expected performance characteristics and results of test-beam campaigns with the electronics prototypes are discussed.

Neural Network-Based Primary Vertex Reconstruction with FPGAs for the Upgrade of the CMS Level-1 Trigger System

The CMS experiment will be upgraded to maintain physics sensitivity and exploit the improved performance of the High Luminosity LHC. Part of this upgrade will see the first level (Level-1) trigger use charged particle tracks reconstructed within the full outer silicon tracker volume as an input for the first time and new algorithms are being designed to make use of these tracks. One such algorithm is primary vertex finding which is used to identify the hard scatter in an event and separate the primary interaction from additional simultaneous interactions. This work presents a novel approach to regress the primary vertex position and to reject tracks from additional soft interactions, which uses an end-to-end neural network. This neural network possesses simultaneous knowledge of all stages in the reconstruction chain, which allows for end-to-end optimisation. The improved performance of this network versus a baseline approach in the primary vertex regression and track-to-vertex classification is shown. A quantised and pruned version of the neural network is deployed on an FPGA to match the stringent timing and computing requirements of the Level-1 Trigger.

An ATCA processor for Level-1 trigger primitive generation and readout of the CMS barrel muon detectors

An ATCA processor was designed to instrument the first layer of the CMS Barrel Muon Trigger. The processor receives and processes DT and RPC data and produces muon track segments. Furthermore, it provides readout for the DT detector. The ATCA processor is based on a Xilinx XCVU13P FPGA, receives data via 10 Gbps optical links and transmits track segments via 25 Gbps optical links. The processor is instrumented with a Zynq Ultrascale+ SoM connected with an SSD which provides the necessary resources for enhanced monitoring and control information. The design of the board as well as results on its performance are presented.