Trigger Signal Research Articles

Development of a TAC-based TDC in 130 nm CMOS technology

The design and measurement results of a prototype Time-to-Digital Converter (TDC) fabricated in 130 nm CMOS technology are presented. The TDC architecture with analog interpolators was chosen, which was motivated by previous experience in Analog-to-Digital Converter (ADC) design [1]. The measured time difference between the event and the trigger signal is converted to the amplitude and then digitised by a 10-bit ADC. The TDC prototype is functional and achieved good Differential Non-Linearity (DNL) and jitter (below 1 LSB), slightly dependent of the selected time precision. The obtained Integral Non-Linearity (INL) is significantly higher than simulated and should be still improved. The prototype Application-Specific Integrated Circuit (ASIC) has configurable time resolution from 15 ps to 140 ps, which gives the total possible time measure range from ±9.5 ns to ±70 ns. In this paper the architecture of the developed TDC is described, comprising the implementation of the Time-to-Analog Converter (TAC) and 10-bit ADC. The measurements of the prototype 8 channel TDC ASIC, showing its linearity and timing resolution are also shown.

Real-time electron density measurement technique using a microwave resonant probe for low-pressure plasmas

Abstract This paper presents a technique to perform a time-resolved electron density measurement in a plasma using a microwave resonant probe named curling probe and a Voltage Controlled Oscillator (VCO) fast-swept circuit. The technique is an interesting alternative to the Vector Network Analyzer (VNA) used in on-point mode on repetitive triggered discharges as it also works for non-repeatable events or in cases where trigger signals are unavailable. First, the temporal resolution of the presented setup is assessed to be 5 μs with an uncertainty on the electron density of 5x107 cm-3. Second, the accuracy of the diagnostic is successfully demonstrated by measuring similar electron density for different measurement rates and by measuring forced plasma oscillations at 25 kHz in a magnetic nozzle thruster. Third, the ability of the diagnostic to perform real-time measurements is demonstrated by capturing the transient dynamic of the electron density during the switch-off of the thruster, with a fast plasma density variation of the order of 6x107 cm-3/μs being measured during the first tens of microseconds after plasma extinction.

Comparative liver transcriptome analysis in hamsters infected with food-borne trematodes Opisthorchis felineus, Opisthorchis viverrini, or Clonorchis sinensis.

Epidemiologically important food-borne trematodes Opisthorchis viverrini and Clonorchis sinensis are recognized as biological carcinogens of Group 1A, while Opisthorchis felineus is in Group 3 as noncarcinogenic to humans. Mechanisms of the biological carcinogenesis are still elusive. Some studies highlight chronic inflammation as a key factor and common pathway for cancer initiation and progression. Nonetheless, the chronic inflammation alone does not explain why these three species differ in carcinogenicity. We focused this study on genome-wide landscapes of liver gene expression and activation of cellular pathways in Mesocricetus auratus golden hamsters infected with C. sinensis (South Korea), O. viverrini (Thailand), or O. felineus (Russia) at 1 and 3 months after infection initiation. Liver transcriptomes of golden hamsters (HiSeq Illumina, 2X150 bp) were sequenced at 1 and 3 months postinfection. Data processing was carried out using the following bioinformatic and experimental approaches: analysis of differential gene expression, estimates of proportions of affected liver cell types, liver histopathology, and examination of weighted gene coexpression networks. All infections caused enrichment with inflammatory response signaling pathways, fibrogenesis and cell proliferation, and IL2-STAT5, TNF-NF-κB, TGF-β, Hippo, MAPK, and PI3K-Akt signaling pathways. Nevertheless, species-specific responses to each infection were noted too. We also identified species-specific responses of liver cell types, differentially expressed gene clusters, and cellular pathways associated with structural liver damage (such as periductal fibrosis, epithelial neoplasia, and inflammation). This is the first comparative analysis of gene expression landscapes in the liver of experimental animals infected with O. viverrini, O. felineus, or C. sinensis. The trematodes have species-specific effects on the hepatobiliary system by triggering signaling pathways, thereby leading to differences in the severity of hepatobiliary structural lesions and contributing to the pathogenicity of closely related foodborne trematodes.

Effectiveness of Bacterial Lysates as Immune-Boosting Supplements: Evaluating a Novel Approach to Immune Health

The increasing prevalence of recurrent infections and immune-related disorders has intensified the search for effective immune-modulating interventions. Bacterial lysates, derived from inactivated bacterial components, have emerged as promising immune-boosting supplements. These lysates activate both innate and adaptive immune responses by interacting with pattern recognition receptors such as Toll-like receptors (TLRs), triggering signaling pathways that enhance immune surveillance and pathogen recognition. Among the most extensively studied is OM-85, which has demonstrated efficacy in reducing the frequency and severity of respiratory tract infections (RTIs) and modulating immune pathways involved in asthma and allergic rhinitis. This review evaluates the mechanisms of action, clinical efficacy, and safety profiles of bacterial lysates, particularly focusing on their role in preventing RTIs and managing chronic inflammatory diseases. Evidence supports their potential to reduce antibiotic use and improve overall clinical outcomes in both pediatric and adult populations. Despite their general safety, certain contraindications exist, especially in patients with hypersensitivity or autoimmune conditions. Further research is required to optimize their use, particularly in immunocompromised populations and for broader applications, such as viral infections. Bacterial lysates represent a novel, cost-effective approach to enhancing immune health and reducing the global reliance on antibiotics.

Bridgeless Cuk PFC converter with full load range soft switching operation by using a simple auxiliary circuit

This paper proposes a fully soft-switched bridgeless Cuk converter for power factor correction. The main converter utilizes a common ground structure with a single switch, simplifying the trigger signal generation and eliminating the need for positive and negative half-line cycle detection. This switch operates under Zero Voltage Switching (ZVS) enabled by a simple auxiliary circuit with just one switch. This auxiliary switch achieves Zero Current Switching (ZCS). Full soft switching allows for increased switching frequency without compromising efficiency, leading to a reduction in the size of passive components. Additionally, the shared ground between input and output minimizes Electromagnetic Interference (EMI) noise. The converter operates in Discontinuous Conduction Mode (DCM) to simplify the control circuit and inherently provides power factor correction without requiring an input filter due to the presence of input inductor and continuous nature of the input current. To validate the theoretical analysis, a laboratory prototype with 200 W output power, 80V output voltage, and 150kHz switching frequency is implemented. The results demonstrate the maximum theoretical and experimental efficiency of almost 96.2% and 95.8%, while, the full load theoretical and experimental efficiency is around 96% and 95.4%, in sequence. Also, an input current Total Harmonic Distortion (THD) and Power Factor (PF) of around 5.2% and 0.998 at full load is achieved, respectively.

Low-Timing Jitter Single-Frequency Pulse Output from a Passively Q-Switched Monolithic Non-Planar Ring Oscillator

A low-timing jitter passively Q-switched monolithic non-planar ring oscillator (NPRO) with diffusion-bonded Cr4+: YAG in a single-frequency operation was realized. The pulse parameters were controlled by a Cr4+: YAG saturable absorber, while the single-frequency operation was ensured by the unidirectional ring cavity structure. The pulse trigger was actively provided by a gain switcher utilizing a composite pumping scheme. The dependence of the timing jitter between the output pulse and the trigger signal on the parameters of the composite pumping scheme was investigated both theoretically and experimentally. Using this approach, we achieved a single-frequency pulsed laser output with a timing jitter of 14.568 ns (RMS) at a repetition rate of 100 Hz corresponding to a pulse width of 5.99 ns. This novel Q-switched monolithic NPRO, which integrates the benefits of both active and passive Q-switching, results in a simple and reliable structure that achieves a low-timing jitter single-frequency pulse output.

(Invited) Electrochemical Induction of Insulin Secretion from Cultured Pancreatic β Cells

Recently, various methods have been developed to create functional cells through cell cultivation techniques, particularly with the utilization of embryonic stem (ES) cells or induced pluripotent stem (iPS) cells. These methodologies have unlocked the potential to produce promising applications across various fields, including regenerative medicine, disease modeling, and drug discovery. Furthermore, methodologies for engineering cell aggregates that exhibit specific functions, known as organoids, are paving the way for innovative biomedical applications. As such, there is a need for methodologies that enable precise control over cellular functions, allowing researchers to manipulate cell behavior in a desired manner. Addressing this need, the present study aimed to develop a method for manipulating cell functions through easily controllable ON/OFF regulation using electrochemical operations. In this study, secretion function, which is a representative function of cellular activities involving changes in cellular membrane potential, was focused on as a cellular function. Specifically, the insulin secretion of pancreatic β cells was targeted as a concrete model.Insulin, a pivotal endocrine hormone synthesized and secreted by pancreatic β cells, plays a critical role in glucose homeostasis. The secretion of insulin by pancreatic β cells is tightly regulated in response to blood glucose concentration. Within pancreatic β cells, glucose uptake via Glucose transporter initiates glycolysis and the citric acid cycle, leading to ATP production. As the intracellular ATP level increases, ATP-sensitive potassium ion channels on the cell membrane close. This event prevents the efflux of potassium ions. Consequently, membrane potential increases and the voltage-dependent calcium ion channels on the cell membrane open, allowing calcium ions to flow into the cell. This influx of calcium ions becomes a trigger signal for insulin secretion, inducing insulin release via endocytosis. Considering this mechanism, it was hypothesized that the electrochemical control of the membrane potential could manipulate the function of pancreatic β cells artificially, specifically insulin secretion.To test this hypothesis, an original cell culture device was created by attaching acrylic rings to transparent electrodes, allowing the cultivation, observation and electrochemical stimulation of cells on electrodes. When iGL cells (a pancreatic β cell line expressing a fusion protein of insulin and a bioluminescent protein, available from Cosmo Bio, Japan) were cultured in this cell culture device, they exhibited proliferation, thus confirming the feasibility of further experiments based on live cell imaging. Next, the response of iGL cells cultured in the device to electrochemical stimulation was monitored using bioluminescent live cell imaging. The electrical stimulation by applying a potential to the electrode was performed using a three-electrode system. In the beginning, iGL cells exhibited bright bioluminescence. However, upon the application of the potential to the electrode, the cells immediately became dark. Subsequently, the bioluminescent intensities of the culture medium collected before and after electrochemical stimulation were compared. As a result, it was observed that the medium collected after the electrochemical stimulation exhibited a brighter intensity, indicating higher concentration of fusion proteins of insulin and the bioluminescent protein. Additionally, morphological analyses showed no significant changes in cell morphology during the stimulation process. This finding confirmed that the decrease in bioluminescence observed in the cellular response to electrochemical stimulation was attributable to the secretion of the fusion protein of insulin and the bioluminescent protein from the cells into the culture medium.Based on these observations, it was concluded that insulin secretion from the cells on the electrode was electrochemically induced by applying a potential. While further analysis of the mechanisms is necessary, it is expected to develop a novel living cellular device whose function is regulated by electrochemical methods that can easily linked to current electronic devices.

Evaluation of an Infinite-Level Inverter Operation Powered by a DC–DC Converter in Open and Closed Loop

This paper evaluates the open- and closed-loop DC–DC converter operation within a DC coupling multilevel inverter architecture to obtain an infinite-level stepped sinusoidal voltage. Adding a cascade controller to the DC–DC converter should reduce the settling time and increase the number of levels in the output voltage waveform; it could decrease the speed error and phase shift concerning the sinusoidal reference signal. The proposed methodology consists of implementing an experimental multilevel inverter with DC coupling through a single-phase bridge inverter energized from a BUCK converter. Trigger signals for the two converters are obtained from a control circuit based in an ATMEGA644P microcontroller to explore its capabilities in power electronics applications. A digital controller is also implemented to evaluate the operation of the BUCK converter in open and closed loop and observe its influence in the stepped sinusoidal output voltage. The evaluation is performed to energize a resistive load with common output voltage in multilevel inverters, i.e., 3, 5, 7, 11, and infinity levels. Results show that during the design stage, fast dynamic elements, like the storage capacitor, can be used to obtain a minimum THD because the settling time is sufficiently fast, the speed error remains small, and there is no need for a controller. A digital controller requires processing time, and although in theory it can reduce the settling time to a minimum, the processor introduces latency in the control signals generation, producing the opposite effect. Controller complexity of the digital controller must be considered because it increases processing time and influences the efficiency of the closed-loop operation.

Consensus for Heterogeneous Multiagent Systems: Output Rate-Coded Secure Control.

This article investigates an output rate-coded secure control based on backstepping for the consensus of heterogeneous multiagent systems (MASs) with output-triggering condition. Due to the nondifferentiable virtual control inputs caused by discontinuous triggering signals, it presents a technical obstacle in implementing the recursive backstepping, rendering previous results inapplicable. To address this problem, an auxiliary high-order filter is elaborately constructed to guarantee the required-order derivatives of virtual control inputs. As this filter is driven by local triggering consensus error, it allows our MASs to have different system orders and relative degrees. Besides, to reduce communication bit and strengthen communication security, we propose a novel distributed rate-coded algorithm from an encoding-decoding viewpoint. When it is triggered, agent's output is encrypted into an L-length codeword, then transmitted to neighbors without exposing any sensitive system states or real control inputs. It is shown that all the closed-loop system signals are ultimately bounded, and the mean square consensus tracking error can be reduced by appropriately selecting control parameters. Simulations illustrate our theoretical finding.

Research on Stator Sections Switching Process of High-Thrust Linear Motors

The high-thrust linear motor used for the electromagnetic launch is switched by switches composed of anti-shunt thyristors. During the switching process, different current path states will appear, which will lead to changes in motor parameters and current fluctuation. Focusing on the air-core synchronous linear motor with parallel and series power supply, this paper analyzes the change in current path caused by the change in the trigger signal of anti-parallel thyristors in the process of sectionalized stator switching. The motor circuit model of the switching process is derived. A new sectionalized stators switching method is proposed to realize the smooth switching of the sectionalized stators linear motor. Finally, the correctness of the analysis and modeling is verified by simulation, and the effectiveness of the sectionalized stators switching method is tested by using the test prototype.

Approximation-based adaptive two-bit-triggered bipartite tracking control for nonlinear networked MASs subject to periodic disturbances

PurposeThis paper aims to investigate the problem of adaptive bipartite tracking control in nonlinear networked multi-agent systems (MASs) under the influence of periodic disturbances. It considers both cooperative and competitive relationships among agents within the MASs.Design/methodology/approachIn response to the inherent limitations of practical systems regarding transmission resources, this paper introduces a novel approach. It addresses both control signal transmission and triggering conditions, presenting a two-bit-triggered control method aimed at conserving system transmission resources. Additionally, a command filter is incorporated to address the problem of complexity explosion. Furthermore, to model the uncertain nonlinear dynamics affected by time-varying periodic disturbances, this paper combines Fourier series expansion and radial basis function neural networks. Finally, the effectiveness of the proposed methodology is demonstrated through simulation results.FindingsBased on neural networks and command filter control method, an adaptive two-bit-triggered bipartite control strategy for nonlinear networked MASs is proposed.Originality/valueThe proposed control strategy effectively addresses the challenges of limited transmission resources, nonlinear dynamics and periodic disturbances in networked MASs. It guarantees the boundedness of all signals within the closed-loop system while also ensuring effective bipartite tracking performance.

High-pulse-energy ultrafast 3 µm laser generation through OPG/DFG in PPMgLN

Abstract We report high-pulse-energy ultrafast 3 µm laser generation through optical parametric generation/difference frequency generation (OPG/DFG) in periodically poled magnesium-oxide-doped lithium niobate (PPMgLN). A commercial 1030 nm femtosecond laser is applied as the pump light and a homemade broadband nanosecond pulse laser around 1580 nm is used as the signal light in DFG. The broadband 1580 nm laser has a master oscillator power amplifier (MOPA) structure with a directly modulated superluminescent light-emitting diode (SLED) as the pulse seed and three stages of Er/Yb fiber amplifiers to lift its average power. A portion of the 1030 nm output pulse is converted to an electronic pulse via a pin detector, which is used as the trigger signal of the SLED driving circuit to ensure synchronization between the signal and the 1030 nm pump pulse. When injecting 2.12 W pump light into the PPMgLN, a broadband mid-infrared (MIR) output of 280 mW can be achieved directly through OPG with a center wavelength around 2.94 μm, a pulse width of 1.38 ps and a pulse repetition frequency of 500 kHz. The corresponding MIR pulse energy is 0.56 µJ. When injecting 2.62 W signal light simultaneously, a MIR output of 300 mW is achieved through the DFG process at the same pulse repetition frequency, corresponding to a pulse energy of 0.6 µJ. The conversion efficiency of the ultrafast pump laser to MIR reaches 14.1%. This high-pulse-energy 3 μm ultrafast laser has great prospects for applications in biological tissue ablation.

Input panel for handwriting detection based on triboelectric nanogenerator

Handwritten signatures are widely used in our daily lives, which focuses on how to obtain handwritten information comprehensively and effectively. Triboelectric nanogenerators can sensitively sense externally applied trigger signals and can be used to collect user handwriting signals and related features for handwriting input character detection and user identification. In this paper, an intelligent handwriting input panel based on triboelectric nanogenerator is proposed, which, combined with deep learning algorithms, achieves an accuracy of 99.32%, 98.96%, 99.14%, and 99.53% for recognizing handwritten signals in Arabic numerals, English words, Chinese characters, and different users, respectively. It is also possible to use different encoding methods for encrypted communication to transmit signals on the proposed handwriting input panel, demonstrating its potential applications. The results show that the smart handwritten input panel has great potential for personal handwritten signature recognition, privacy information, and human–computer interaction.

Effects of ketamine on GABAergic and glutamatergic activity in the mPFC: biphasic recruitment of GABA function in antidepressant-like responses.

Major depressive disorder (MDD) is associated with disruptions in glutamatergic and GABAergic activity in the medial prefrontal cortex (mPFC), leading to altered synaptic formation and function. Low doses of ketamine rapidly rescue these deficits, inducing fast and sustained antidepressant effects. While it is suggested that ketamine produces a rapid glutamatergic enhancement in the mPFC, the temporal dynamics and the involvement of GABA interneurons in its sustained effects remain unclear. Using simultaneous photometry recordings of calcium activity in mPFC pyramidal and GABA neurons, as well as chemogenetic approaches in Gad1-Cre mice, we explored the hypothesis that initial effects of ketamine on glutamate signaling trigger subsequent enhancement of GABAergic responses, contributing to its sustained antidepressant responses. Calcium recordings revealed a biphasic effect of ketamine on activity of mPFC GABA neurons, characterized by an initial transient decrease (phase 1, <30 min) followed by an increase (phase 2, >60 min), in parallel with a transient increase in excitation/inhibition levels (10 min) and lasting enhancement of glutamatergic activity (30-120 min). Previous administration of ketamine enhanced GABA neuron activity during the sucrose splash test (SUST) and novelty suppressed feeding test (NSFT), 24 h and 72 h post-treatment, respectively. Chemogenetic inhibition of GABA interneurons during the surge of GABAergic activity (phase 2), or immediately before the SUST or NSFT, occluded ketamine's behavioral actions. These results indicate that time-dependent modulation of GABAergic activity is required for the sustained antidepressant-like responses induced by ketamine, suggesting that approaches to enhance GABAergic plasticity and function are promising therapeutic targets for antidepressant development.

Detection of KIT Mutations in Systemic Mastocytosis: How, When, and Why.

More than 90% of patients affected by mastocytosis are characterized by a somatic point mutation of KIT, which induces ligand-independent activation of the receptor and downstream signal triggering, ultimately leading to mast cell accumulation and survival. The most frequent mutation is KIT p.D816V, but other rarer mutations can also be found. These mutations often have a very low variant allele frequency (VAF), well below the sensitivity of common next-generation sequencing (NGS) methods used in routine diagnostic panels. Highly sensitive methods are developing for detecting mutations. This review summarizes the current indications on the recommended methods and on how to manage and interpret molecular data for the diagnosis and follow-up of patients with mastocytosis.

Dual-channel event-triggered prescribed performance adaptive fuzzy time-varying formation tracking control for nonlinear multi-agent systems

This paper is concerned with the problem of dual-channel event-triggered prescribed performance adaptive fuzzy time-varying formation tracking control for multi-agent systems subject to actuator saturation, in which state variables are unmeasurable and nonlinear functions are totally unknown. A fuzzy state observer is constructed to estimate unmeasurable states. Meanwhile, fuzzy logic systems are used to approximate unknown nonlinear functions. To effectively save the usage of communication resources, this paper designs both sensor output signal and control signal triggering mechanisms, respectively. Unfortunately, the output triggering can lead to a problem that virtual control laws are non-differentiable. To solve this problem, we first utilize observer output signals to construct virtual control laws to ensure the first-order differentiation of virtual control laws. Then, a dynamic filtering technology is introduced to avoid the repeated differentiation of virtual control laws. Furthermore, an improved first-order auxiliary system is designed to compensate for the impact of actuator saturation. It is shown that the designed controller can guarantee tracking errors steer to a preset accuracy within a prescribed settling time, and all signals in the closed-loop system are semi-globally uniformly ultimately bounded. Finally, simulation results verify the effectiveness of the developed control scheme.

Active Control of Properties of Fresh and Hardening Concrete

Concrete mixtures have an optimized mix design in view of attaining desired properties. However, after mixing, during further processing, it is typically not possible to further adjust the performance of the fresh and hardening concrete. A new and emerging approach is to actively control the concrete properties by means of responsive particles or polymers triggered by an externally applied signal. Active control of properties of concrete refers to the concept of on- demand changes of one or more properties of the concrete after mixing by triggering a response to one or more of the constituents using a specific trigger signal (e.g. thermal, chemical, electrical, magnetic...). The on-demand control of properties can focus on the processing stage (including e.g. pumping, casting, 3D printing), the curing and hardening stage (including e.g. control of capillary pressure, shrinkage, setting, and hardening) and even on the hardened stage during service life (e.g. active corrosion control, active crack healing...). Addressing specific obstacles in cementitious environments, ensuring responsive material stability, controlling signal applicability, cost, logistics, and on-site safety is crucial for successful implementation. A RILEM technical committee has been initiated in 2023, working on the concept of Active Control of Properties of Concrete (RILEM TC 317-ACP). The committee will focus on active control of properties of fresh and hardening concrete. This paper gives a short introduction to scope and activities of TC 317-ACP.

Reinforcement learning-based adaptive event-triggered control of multi-agent systems with time-varying dead-zone

In this paper, a novel reinforcement learning (RL)-based adaptive event-triggered control problem is studied for non-affine multi-agent systems (MASs) with time-varying dead-zone. The purpose is to design an efficient event-triggered mechanism to achieve optimal control of MASs. Compared with the existing results, an improved smooth event-triggered mechanism is proposed, which not only overcomes the design difficulties caused by discontinuous trigger signals, but also reduces the waste of communication resources. In order to achieve optimal event-triggered control, RL algorithm of the identifier-critic-actor structure based on fuzzy logic systems (FLSs) is applied to estimate system dynamics, evaluate control performance, and execute control behavior, respectively. In addition, considering time-varying dead-zone in non-affine MASs brings obstacles to controller design, which makes system applications more generalized. Through Lyapunov theory, it is proved that the optimal control performance can be achieved and the tracking error converges to a small neighborhood of the origin. Finally, simulation proves the feasibility of the proposed method.

Release of ATP in the lung evoked by inhalation of irritant gases in rats.

Adenosine triphosphate (ATP) can be released into the extracellular milieu from various types of cells in response to a wide range of physical or chemical stresses. In the respiratory tract, extracellular ATP is recognized as an important signal molecule and trigger of airway inflammation. Chlorine (Cl2), sulfur dioxide (SO2), and ammonia (NH3) are potent irritant gases and common industrial air pollutants due to their widespread uses as chemical agents. This study was carried out to determine if acute inhalation challenges of these irritant gases, at the concentration and duration simulating the accidental exposures to these chemical gases in industrial operations, triggered the release of ATP in the rat respiratory tract; and if so, whether the level of ATP in bronchoalveolar lavage fluid (BALF) evoked by inhalation challenge of a given irritant gas was elevated by chronic allergic airway inflammation. Our results showed: 1) inhalation of these irritant gases caused significant increases in the ATP level in BALF, and the magnitude of evoked ATP release was in the order of Cl2 > SO2 > NH3. 2) Chronic airway inflammation induced by ovalbumin-sensitization markedly elevated the ATP level in BALF during baseline (breathing room air) but did not potentiate the release of ATP in the lung triggered by inhalation challenges of these irritant gases. These findings suggested a possible involvement of the ATP release in the lung in the regulation of overall airway responses to acute inhalation of irritant gases and the pathogenesis of chronic allergic airway inflammation.NEW & NOTEWORTHY Extracellular adenosine triphosphate (ATP) is a contributing factor and signaling molecule of airway inflammation. This study demonstrated for the first time that the ATP release in the lung was markedly elevated after acute inhalation challenges of three common industrial air pollutants; the order of the response magnitude was chlorine > sulfur dioxide > ammonia. These findings provided new information and improved our understanding of the adverse pulmonary effects caused by accidental inhalation exposures to these irritant gases.

Triggers for self-regulated learning: A conceptual framework for advancing multimodal research about SRL

This paper introduces a theory-driven trigger regulation framework for advancing multimodal analytical approaches to research about self-regulated learning. Events and/or situations that may inhibit learning processes and, thus, require regulatory responses are defined as trigger events. Empirically identifying trigger signals in multimodal data as markers for the regulation of cognition, motivation, emotion, and behavior has great potential for advancing the field. We propose a trigger regulation framework and explain how it can be leveraged in multimodal research for detecting trigger signals focusing analysis on meaningful regulatory responses. This conceptual framework offers potential to guide methodological and analytical advances in research to examine the situated nature of regulatory responses and within-person individual differences in SRL as they play out during complex task work and teamwork. Educational relevance and implications statementThe trigger regulation framework contributes to advancing multimodal approaches to the study of SRL. It presents a theory driven analytical approach for detecting, modeling, and interpreting adaptive and maladaptive regulation during individual or collaborative work. Grounding analytical approaches to multimodal data analysis in this framework has potential to increase the quality and accuracy of research findings and interpretations and inform the development of interventions and AI systems.