Feedback Research Articles

How am I going? Behavioral engagement mediates the effect of individual feedback on writing performance

BackgroundSuccessful feedback should provide learning goals, evaluate current performance and indicate improvement strategies. Furthermore, feedback can only positively affect student performance if students actively engage with it. Thus, it is necessary to consider the feedback reception process in addition to the feedback information itself. AimsThis study compares the effects of different types of feedback information on the writing performance of lower secondary students of English as a foreign language (EFL) in a digital learning environment. Behavioral engagement was considered as a mediator of the feedback effect. SampleParticipants were N = 338 eighth- and ninth-grade EFL students (54.7% female) enrolled in lower-secondary education within the Swiss school system. MethodsWe conducted a web-based randomized-controlled experiment, in which students were randomly assigned to four conditions receiving varying amounts of rubric-based feedback information. We used log data (time on feedback page) as a proxy for their behavioral engagement with the feedback. ResultsEven though writing performance improved substantially across conditions, there were no differential effects of the type of feedback information on performance. However, EFL learners who received individual performance information spent more time with the feedback, especially those with low prior achievement. Mediation analysis showed that the effectiveness of the feedback was mediated by the time spent on the feedback as an indicator of students' behavioral engagement. ConclusionsAdvantages for individual performance feedback over more general information were observed as a function of time spent with the feedback. This finding implies that engagement should be considered in feedback research.

Unilateral effects of mergers with price regulation and quality competition

Merger screening tools are increasingly used in the review of horizontal mergers. They offer insights into the firms’ incentives to increase prices post-transaction. This paper proposes a new indicator, the Quality Reduction Incentive (QRI) index, that can be applied when competition is based on quality rather than prices, as in some healthcare and higher education markets. It represents the minimum percentage reduction in marginal costs necessary to eliminate the merging firms’ incentives to lower quality. Therefore, it can be directly compared to the cost efficiency gains claimed by the parties. Two versions of the QRI index are provided. The first one ignores the feedback effects between the parties, while the second one, more comprehensive, incorporates these interactions. The paper then explains how antitrust authorities can apply this tool with relatively little data.

Exotic plants introduction changed soil nutrient cycle and symbiotic relationship with arbuscular mycorrhizal fungi in wetland ecological projects.

In the process of applying exotic plants to wetland ecological restoration, insufficiently evaluated alien species may exhibit strong competitiveness and fecundity. Once introduced, they can displace native flora, disrupt the original ecological balance, diminish biodiversity, and even induce ecosystem dysfunction. Furthermore, exotic plants have the potential to alter soil microbial community structure, including the composition and activity of beneficial symbiotic microorganisms such as arbuscular mycorrhizal fungi (AMF), thereby impacting soil nutrient cycling and interplant nutrient competition. Here, we conducted three consecutive years of sampling experiments to investigate the succession of AMF communities associated with the invasive plant Spartina alterniflora along an initial introduction chronosequence, and to identify the key environmental factors influencing its response to S. alterniflora invasion. Our findings reveal that early-stage invasion by S. alterniflora alters the composition of soil AMF communities with unclassified_c__Glomeromycetes and Glomus-viscosum-VTX00063 consistently dominating. Additionally, as the duration of introduction increases, the diversity of rhizosphere soil AMF significantly decreases, while its evenness remains relatively stable. It's indicated that soil ω, AN, AK and N/P ratio were the main influencing factors of the integral AMF community. Notably, soil available phosphorus (AP) emerges as a positive influence on the important AMF taxa. The results confirm the mutual feedback effect between the invasion of the perennial herb S. alterniflora and AMF, in which specific AMF assist in nutrient absorption to promote S. alterniflora growth, potentially facilitating its rapid and successful invasion of new habitats. Given the likely differential effects of AMF communities on various plant species, our findings could contribute to anticipating future AMF-mediated effects during the introduction of alien plants.

To what extent does post-identification feedback translate into witness behaviour?

ABSTRACT When eyewitness receive feedback implying they have accurately identified the perpetrator from a lineup, it boosts their confidence and possibly distorts their memory. Most research investigating this “post-identification feedback effect” (PIF effect) suggests the feedback changes eyewitness’ retrospective memory of their actual experiences. But it remains unclear to what extent this feedback might change the eyewitness’s subsequent behaviour. Across four experiments, we addressed this issue. We investigated whether people who received confirming feedback were more likely to provide recorded or written statements as evidence for an ongoing trial. Across the four experiments, we replicated the basic PIF effect. But we found no consistent evidence that these same people were more willing to offer their experimental data nor to submit a statement about what they saw. We did find preliminary evidence that people who received confirming feedback submitted longer statements. Taken together, these findings have theoretical implications establishing boundary conditions on the influence of feedback. On the practical side, these findings suggest caution in extrapolating the influence of PIF beyond a relatively small set of retrospective reports, beliefs, and inclinations.

Constraining neutrino-DM interactions with Milky Way dwarf spheroidals and supernova neutrinos

We constrain the neutrino-dark matter cross section using properties of the dark matter density profiles of Milky Way dwarf spheroidal galaxies. The constraint arises from core-collapse supernova neutrinos scattering on dark matter as a form of energy injection, allowing the transformation of the dark matter density profile from a cusped profile to a flatter profile. We assume a standard cosmology of dark energy and cold, collisionless, and non-self-interacting dark matter. By requiring that the dark matter cores do not lose too much mass or overshoot constraints from stellar kinematics, we place an upper limit on the cross section of σν−DM(Eν=15 MeV,mχ≲130 GeV)≈3.4×10−23 cm2 and σν−DM(Eν=15 MeV,mχ≳130 GeV)≈3.2×10−27(mχ1 GeV)2 cm2, which is stronger than previous bounds for these energies. Consideration of baryonic feedback or host galaxy effects on the dark matter profile can strengthen this constraint. Published by the American Physical Society 2024

A Potential Surface Warming Regime for Volcanic Super‐Eruptions Through Stratospheric Water Vapor Increases

AbstractLarge volcanic eruptions are known to influence the climate through a variety of mechanisms including aerosol‐forced cooling and warming via emitted CO2. The January 2022 Hunga shallow underwater eruption caused an increase in stratospheric water vapor, and demonstrated how the associated positive radiative forcing can be an important component of an eruption's climate forcing. We present interactive stratospheric aerosol model simulations of super‐volcanic eruptions with a range of SO2 emissions that can produce climate warming through feedback effects produced by a large igneous province (or “flood basalt”) mid‐latitude super‐eruption using Goddard Earth Observing System Chemistry Climate Model climate model simulations. The model experiments suggest total SO2 emissions ≳4,000 Tg/4 Gt generate a multi‐year period of sustained aerosol absorptive local‐heating of the upper troposphere and lower stratosphere and hence produce net climate warming after strong initial cooling. The eruptions produce stratospheric water vapor increases of factors of 8–600. The initiation of these feedbacks within the simulations suggest they could occur for individual stratovolcano eruptions of the scale of the Toba or Tambora eruptions. We note the sensitivity of our results to volcanic sulfate aerosol microphysics and model chemistry.

A Novel Non-invasive Predictor Measure of Left Atrial Pressure and Practical Implicates in High Frequency Ventilation: Theory.

A new prototype of ventilator mode, based on high-frequency ventilation (HFV), aims to address the interrelations among diverse respiratory variables, several intercardiovascular parameters rapports, and instantaneously the intrarespiratory and cardiac interactions. This article proposes a logarithmic network of integrated correlation ratio H/V, R correlation, that primarily relates both dependent respiratory (V) and independent hemodynamic variables (H). Given a constant steady state of the heart and vasculature, a difference between calculated ratio (R calc), and optimized ratio (R opt) could be utilized to adjust many aspects of several parameters and outcomes in critically ill patients. The central venous pressure (CVP) waveanalysis aims to approachseveral cardiovascular parameters, endpoints of left atrial (LA) pressure, and the cardiac output (CO) with the help of thermodilution curve analysis. This might result in several innovative formulas of mathematical base. Their relevant clinical implicates demonstrated a wide area of normalized distribution capacity (Cd), systemic vascular capacity (Cs), pulmonary vascular capacitance (Cp), pulmonary vascular resistance (PVR), and mean pulmonary artery pressure (MPAP). The authors claim that prepared software programming helps network integration of all these variables, feeding back and addressing the prototypeof novel mode for the oldnew applicationof HFV. One potential unique criterion is adjusting LA and ultimately CO through a feedback control mechanism. Though this all sounds very plausible, the reader must be reminded that everything in this work is based on the most expected speculations and experience and could be potentially different than that in vivo.More importantly, animalexperimental studies are warranted.

Three Birds with One Stone: Copper Ions Assisted Synergistic Cuproptosis/Chemodynamic/Photothermal Therapy by a Three-Pronged Approach.

Copper is indispensable to organisms, while its homeostatic imbalance may interference normal cellular physiological processes and even induce cell death. Artificially regulating cellular copper content provides a viable strategy to activate antineoplastic effect. In light of this, a copper ions homeostasis perturbator (CuP-CL) with cinnamaldehyde (Cin) packaging and thermosensitive liposome coating is reported. Following laser exposure, the doping of Cu2+ in polydopamine initiates enhanced photothermal therapy (PTT) and unlocks the outer layer of liposome, leading to the release of copper ions and Cin in tumor microenvironment with mild acidity and high glutathione (GSH) levels. The liberative Cu2+ can evoke cuproptosis and chemodynamic therapy (CDT). Meanwhile, leveraging the merits of H2O2 supply and GSH consumption, Cin serves as a tumor microenvironment regulator to amplify Cu2+ mediated cuproptosis and CDT. Additionally, the positive feedback effects of "laser-triggered PTT, PTT accelerates reactive oxygen species (ROS) generation, ROS amplifies lipid peroxide (LPO) accumulation, LPO mediates heat shock proteins (HSPs) clearance, down-regulated HSPs promote PTT" entailed the overall benefit to therapeutic outcomes. Both in vitro and in vivo results corroborate the remarkable antineoplastic performance of CuP-CL by the synergy of cuproptosis/CDT/PTT. Collectively, based on the three-pronged approach, this work plots a viable multimodal regimen for cancer therapy.

Exploring the effects of negative supervisory feedback on creativity among research and development personnel: challenge or threat?

Supervisory feedback to stimulate research and development (R&D) employee creativity is a management issue that concerns scholars and practitioners. However, there are divergences and contradictions regarding whether negative feedback promotes or hinders employee creativity. Integrating the feedback intervention and cognitive appraisal theories, we developed a double-edged sword model for negative supervisory feedback's influence on creativity. We tested the proposed model using a field sample of 513 R&D employees from seven science and technology enterprises. The results indicated that R&D employee challenge and threat appraisal moderated negative supervisory feedback's effect on prevention focus and the distal consequences for creativity. Individuals with high (low) levels of challenge (threat) appraisal have decreased prevention focus, thereby increasing their creativity when receiving negative supervisory feedback. In contrast, individuals with low (high) challenge (threat) appraisal have increased prevention focus, thereby decreasing their creativity when receiving negative supervisory feedback. These findings offer interesting implications for research on negative feedback and stimulation of science and technology R&D employee creativity in organizations.

ALMA-IMF

Context. The star formation process leads to an increased chemical complexity in the interstellar medium. Sites associated with high-mass star and cluster formation exhibit a so-called hot core phase, characterized by high temperatures and column densities of complex organic molecules. Aims. We aim to systematically search for and identify a sample of hot cores toward the 15 Galactic protoclusters of the ALMA-IMF Large Program and investigate their statistical properties. Methods. We built a comprehensive census of hot core candidates toward the ALMA-IMF protoclusters based on the detection of two CH3OCHO emission lines at 216.1 GHz. We used the source extraction algorithm GExt2D to identify peaks of methyl formate (CH3OCHO) emission, a complex species commonly observed toward sites of star formation. We performed a cross-matching with the catalog of thermal dust continuum sources from the ALMA-IMF 1.3 mm continuum data to infer their physical properties. Results. We built a catalog of 76 hot core candidates with masses ranging from ~0.2 M⊙ to ~80 M⊙, of which 56 are new detections. A large majority of these objects, identified from methyl formate emission, are compact and rather circular, with deconvolved full width at half maximum (FWHM) sizes of ~2300 au on average. The central sources of two target fields show more extended, but still rather circular, methyl formate emission with deconvolved FWHM sizes of ~6700 au and 13 400 au. About 30% of our sample of methyl formate sources have core masses above 8 M⊙ and range in size from ~1000 au to 13 400 au, which is in line with measurements of archetypical hot cores. The origin of the CH3OCHO emission toward the lower-mass cores may be explained as a mixture of contributions from shocks or may correspond to objects in a more evolved state (i.e., beyond the hot core stage). We find that the fraction of hot core candidates increases with the core mass, suggesting that the brightest dust cores are all in the hot core phase. Conclusions. Our results suggest that most of these compact methyl formate sources are readily explained by simple symmetric models, while collective effects from radiative heating and shocks from compact protoclusters are needed to explain the observed extended CH3OCHO emission. The large fraction of hot core candidates toward the most massive cores suggests that they rapidly enter the hot core phase and that feedback effects from the forming protostar(s) impact their environment on short timescales.

Deep Learning Application as a Method for Classification Equipment Failure on Natural Gas Pipeline

Predicting maintenance and preventing failures in natural gas pipelines is critical for safety and efficiency in the oil and gas industry. This research utilizes machine learning (ML) and deep learning (DL) methods to predict failures in natural gas transmission pipelines. Using a dataset from the U.S. Department of Transportation’s Pipeline and Hazardous Materials Safety Administration (PHMSA), the study examines failure incidents from 2010-2019 and non-failure data from 2020-2023. The research involves comprehensive data preprocessing, addressing missing values and dataset imbalances. Key pipeline attributes such as diameter, wall thickness, age, and operating pressure are used for failure prediction. The ML approach employs logistic regression, optimized for binary classification tasks, to establish the probability of pipeline failures. For the DL approach, an Artificial Neural Network (ANN) with Feed Forward and Back Propagation algorithms is developed. Key parameters, including activation functions and hyperparameters, are finely tuned to enhance predictive performance. ReLU activation functions are used in input and hidden layers, while the sigmoid function is applied to the output layer. Performance evaluation of both ML and DL models is based on accuracy, F1 Score, and Area Under Curve (AUC). In summary, ML showed better performance than DL, with value of accuracy is 0.74, F1 Score is 0.85, and AUC is 0.55 while the value of accuracy, F1 score, AUC from DL is 0.61, 0.003, and 0.58 respectively. DL offers superior performance in handling complex and huge amounts of data. In the other hand, ML offers more robust models and simpler adjustable models than DL. Because of the amount of computed data in this research, it is better to have ML as a predictive algorithm.

Neutron star accretion events in AGN discs: mutimessenger implications

ABSTRACT This paper investigates the accretion of neutron stars (NSs) in active galactic nucleus (AGN) accretion discs. We classify potential accretion modes of NSs in AGN discs, proposing a hierarchical model of NS accretion: accretion flow from the Bondi sphere to accretion columns. The accretion of NSs in AGN discs differs from that of BHs, especially within the scale of the NS’s magnetosphere due to its hard surface and magnetic field. As the accretion flow approaches the magnetosphere, the magnetic fields guide the accretion flow to form accretion columns, primarily dominated by neutrinos. While neutrinos generated from single NS accretion may not have observable effects, considering the all-sky background, they contribute to the neutrino background in the sub-MeV energy range comparable to that of supernova explosions. NS accretion may also lead to the generation of mass quadrupole moments, consequently generating gravitational waves (GWs). The GWs, which exhibit characteristic effects like periodic modulations and echoes, could be observed by third-generation GW detectors. The emission of neutrinos and GWs carries away energy and angular momentum brought by accretion, reducing the feedback effect on the AGN disc. This results in an exceptionally high NS accretion rate, leading to a collapse time-scale shorter than the migration-merge time-scale, making it less likely that binary NS mergers originate from AGN discs.

Feedback and Learning: The Causal Effects of Reversals on Judicial Decision-Making

Abstract Do judges respond to reversals of their decisions? Using random assignment of cases across two stages of the criminal justice system in Norway and a novel dataset linking trial court decisions to reversals in appeals courts, we provide causal evidence on feedback effects in judicial decision-making. By exploiting differences in the tendencies of randomly assigned appeal panels to reverse trial court decisions, we show that trial court judges who receive a reversal of a sentence respond by updating the likelihood of imposing a prison sentence in the direction of the reversal in future cases. Consistent with a Bayesian learning model, we find that the responses are stronger for judges with weaker priors and for reversals corresponding to stronger signals. Our estimates, however, also indicate that judges overreact to reversals compared to Bayes’ rule.

Can Public Policy Influence Public Opinion? Studying Feedback Effects and Elite Influence Using the Affordable Care Act

Abstract Political elites often claim that the passage of new public programs will shift the political debate by influencing public opinion. These expectations also motivate elites to engage in messaging that they believe will further shape public opinion toward these new programs. In Stable Condition, Daniel J. Hopkins subjects these beliefs—and their social science analogues of policy feedback and opinion leadership—to rigorous and exhaustive scrutiny in a comprehensive assessment of how the Affordable Care Act (ACA) affected public opinion. Contrary to much of the elite and scholarly consensus, Hopkins finds little or no effect of the ACA or its attendant messaging wars on public opinion. In this essay, I highlight what I see as some of the key contributions of the book to the literature on policy feedbacks. One of these contributions is the strength of the empirical analysis, which convinces me that the author's conclusions about the ACA's limited effects are correct. In the latter part of the review, however, I question how much we can learn about feedback effects in general from this particular case, given the strategic considerations that informed the ACA's passage. Last, I re-evaluate the book's conclusions of opinion stability given longer-term trends in both policy and opinion.

Effects of the Co-Application of Glucose, Nitrogen, and Elevated Temperature on Buried Black Soil Carbon in a Cool Temperate Deciduous Broad-Leaved Forest

Accurately predicting the feedback mechanisms between forest ecosystem carbon cycling and climate change is crucial for effective climate mitigation. Understanding soil organic carbon (SOC) responses to the combined impacts of plant biomass, litter, and nitrogen deposition, especially regarding temperature sensitivity, is essential but remains poorly understood. We conducted incubation experiments using buried black soil from a cool temperate deciduous broad-leaved forest in Japan, which has high C content and a highly stable molecular structure. The stepwise addition of glucose and a temperature increase from 15 to 35 °C accelerated SOC mineralization by 74.0 mg C kg−1 with a positive priming effect (PE) during the 49-day incubation period, while the simultaneous addition of nitrogen had no significant effect on this phenomenon, with SOC mineralization measured at 75.5 mg C kg−1. Conversely, glucose mineralization was significantly accelerated by 10%, from 241.0 to 261.3 mg C kg−1, by stepwise nitrogen addition and temperature increase. Under the combined impacts, the Q10 value of the soil increased significantly from 1.6 to 2.0 compared to that in the unmodified conditions, primarily due to the stepwise addition of glucose. We also found a strong positive correlation between activation energy (Ea) and Q10. This result strongly supports the carbon quality–temperature (CQT) hypothesis. These results likely stem from interactions between SOC quality and carbon availability, suggesting that, in the future, climate change is likely to have a positive feedback effect, especially on buried black soils.

Diffusion of small-size aliphatic alcohols and the chemical actuation of shape memory polyurethane

Three types of aliphatic alcohols (methanol, ethanol, and 1-propanol) are used to actuate a programmed ESTANE ETE 75DT3 (abb. SMP-E), a polyether-based polyurethane shape memory polymer (SMP). In this paper, we analyze the diffusion behavior of these small molecules in SMP-E and the relationship between the solvent diffusion and shape recovery using a weight gain study and small-angle x-ray scattering (SAXS). From the results, all three alcohols show behavior similar to Fickian diffusion in SMP-E. During the diffusion process, the molecular switch (MS) of thermoplastic SMP-E transforms from the glassy state to the rubber-like state depending on the time-dependent local alcohol concentration. The diffusion of small molecules enhances shape recovery and the related evolution of the polymer structure. As a feedback effect, the rate of diffusion changes as small molecules penetrate into the sample. To study this issue, we used three methods to determine the diffusion coefficients at short, intermediate and long times. The data on short time diffusion reflects the glassy state of the sample. The intermediate times correspond to 50% solvent saturation, where the shape recovery is nearly completed. The long-time analysis, on the other hand, provides an average diffusion coefficient for the entire process. The SAXS results show the diffusion path and provide evidence that the alcohol molecules equally diffuse into both MS and entropy elastic component phase of SMP-E.

Enhance the management of perioperative crisis events, improve the safety and quality of pediatric anesthesia

Perioperative crisis events refer to unexpected seriously life-threatening when the patient is during or after surgery, and require rapid identification, evaluation, and management by clinical teams to minimize harm. The pediatric anesthesia management during perioperative period is special and challenging for anesthesiologists, requiring professional technical and non-technical skills. The article mainly elaborates on the incidence and risk factors of pediatric anesthesia crisis events during perioperative period and introduces the concept of anesthesia crisis resource management and strategies. The anesthesiologist team needs to adopt a crisis resource management strategy, taking a typical crisis event of malignant hyperthermia as an example, including identification of crisis signs immediately, termination of trigger drugs rapidly, intravenous injection of the special drug dantrolene, physical cooling, and symptomatic support treatment, seeking assistance from other teams actively, recording and feeding back. This study aims to improve the cognitive decision-making ability and teamwork ability of anesthesiologists and their teams, effectively preventing and responding to potential crisis events effectively, and ensuring the safety of pediatric patients during perioperative period.

Parametric Sensitivity Analysis of Stability Margins of Holos-Quad Microreactor

An analysis of the stability margins of the innovative Holos-Quad microreactor design is presented. This high-temeprature gas-cooled reactor (HTGR) system is designed to operate fully autonomously with passive safety mechanisms. Therefore, the inherent stability of the reactor is of great importance. Using a point-reactor model, which couples point kinetics to thermal-hydraulic heat balance equations and includes reactivity feedback effects of the fuel and moderator temperatures, the closed-loop transfer function of the reactor is derived. Applying the approach of linear systems and control theory, both the gain and phase margins of the Holos-Quad design are obtained. The analysis demonstrates that the design is stable, with an infinite gain margin and a finite phase margin. A parametric uncertainty quantification study is also performed using a total Monte Carlo approach. The stability of the reactor for different power levels, such as during reactor startup or load-following transients, is also explored. Finally, two sensitivity analysis methods are applied, namely, multiple regression (deriving standardized regression coefficients) and variance-based sensitivity analysis (known as the Sobol method), to study the contribution of each of the parameters to the stability margins’ uncertainty. This analysis improves our understanding of the role of each of the parameters in the stability of the reactor.

Procedure Matters: The Distinct Attitudinal Feedback Effects of Immigration Policy

AbstractNatives who dislike immigrants prefer restrictive immigration policies, but do those policies deepen or alleviate anti-immigrant attitudes? Existing theories have offered mixed predictions. Restrictions imposed on immigrants may harden intergroup boundaries and thus deepen hostilities. However, they may also soften attitudes by addressing the economic and identity concerns of natives. Using a conjoint experiment conducted in Hong Kong, I test the multidimensional effects of immigration policies on natives’ attitudes toward highly skilled immigrants. I find that restrictive measures consistently generate more positive attitudes. Strikingly, this effect cannot be fully accounted for by major theoretical explanations, including labor market competition, social identity, and welfare attitudes. Preexisting policy preferences do not condition the effect either. These findings point to the importance of attitudinal policy feedback beyond traditional accounts of immigration attitudes. In-depth qualitative interviews identify two novel causal mechanisms: moralizing and quality assurance effects.

Dynamics of teacher autonomy support in early adolescence: feedforward and feedback effects with students’ autonomy, competence, relatedness, and engagement

Dynamics of teacher autonomy support in early adolescence: feedforward and feedback effects with students’ autonomy, competence, relatedness, and engagement