Feedback Efficiency Research Articles

Conditions for Super-Eddington Accretion onto the First Black Holes

Abstract Observations of supermassive black holes at high redshift challenge our understanding of the evolution of the first generation of black holes (BHs) in proto-galactic environments. One possibility is that they grow much more rapidly than current estimates of feedback and accretion efficiency permit. Following our previous analysis of super-Eddington accretion onto stellar-mass black holes in mini-haloes under no-feedback conditions, we now investigate whether this can be sustained when thermal feedback is included. We use four sets of cosmological simulations at sub-pc resolution with initial black hole masses varying from 1 × 103 M⊙ − 6 × 104 M⊙, exploring a range of feedback efficiencies. We also vary the feedback injection radius to probe the threshold of numerical overcooling. We find that super-Eddington growth sustained on the order of ∼$100 \, \rm kyr$ is possible with weak thermal feedback efficiency in all environments and moderate efficiency for two of the BHs. Trans-Eddington growth is possible for a 1 × 103 M⊙ − 6 × 103 M⊙ BH at moderate feedback efficiencies. We discuss the effectiveness of thermal feedback in heating the gas, suppressing accretion, and driving outflows at these parameter configurations. Our results suggest that super-Eddington growth may be possible in the presence of thermal feedback for black holes formed from the first stars.

Coherent feedback control for cavity optomechanical systems with a frequency-dependent mirror

Ground-state cooling of mechanical resonators is a prerequisite for the observation of various quantum effects in optomechanical systems and thus has always been a crucial task in quantum optomechanics. In this paper, we study how to realize ground-state cooling of the mechanical mode in a Fano-mirror optomechanical setup, which allows for enhanced effective optomechanical interaction but typically works in the (deeply) unresolved-sideband regime. We reveal that for such a two-sided cavity geometry with very different decay rates at the two cavity mirrors, it is possible to cool the mechanical mode down to its ground state within a broad range of parameters by using an appropriate single-sided coherent feedback. This is possible even if the total optical loss is more than seven orders of magnitude larger than the mechanical frequency and the feedback efficiency is relatively low. Importantly, we show that a more standard double-sided feedback scheme is not appropriate to cooperate with a Fano-mirror system. Published by the American Physical Society 2025

Mixing Corrupted Preferences for Robust and Feedback-Efficient Preference-Based Reinforcement Learning

Preference-based reinforcement learning (RL) trains agents using non-expert feedback without the need for detailed reward design. Human teacher guides the agent by comparing two behavior trajectories and labeling the preference. Although recent studies improved feedback efficiency through methods like unsupervised exploration and self- or semi-supervised learning, they often assume flawless human annotation. In practice, human teachers might make mistakes or have conflicting opinions on trajectory preferences, posing a challenge in capturing user intent. To address this, we introduce mixing corrupted preferences (MCP) for robust and feedback-efficient preference-based RL. Inspired by the robustness of mixup against corrupted labels, MCP offers three key advantages. Firstly, by component-wise mixing of two labeled preferences, MCP mitigates the impact of corrupted feedback, enhancing robustness. Secondly, MCP improves feedback efficiency by generating unlimited new data even with limited labeled feedback. Lastly, MCP helps regulate overconfidence in preference predictor, moderating excessive reward divergence between two trajectories. We evaluate our method on three locomotion and six robotic manipulation tasks in B-Pref benchmark, in contexts with both perfectly rational and imperfect teachers (including actual human teachers). Our results show that MCP significantly outperforms PEBBLE, requiring fewer feedback instances and a shorter training period, highlighting its superior feedback efficiency. Our code is available at https://github.com/JongKook-Heo/MCP.

PAD resin: An intelligent adsorbent for solving Cr(VI) pollution with real-time feedback and high efficiency

To address the urgent issue of Cr(VI) pollution and protect aquatic ecosystems, we conducted an exhaustive investigation into a Poly(acrylamide-co-methacryloyloxyethyl trimethylammonium chloride) (PAD) resin synthesized through an environmentally friendly aqueous polymerization process. This resin not only boasts a high capacity for Cr(VI) removal but also incorporates a colorimetric sensing mechanism that visually transitions from transparent to yellow upon Cr(VI) adsorption, offering real-time, non-invasive monitoring and optimization of the remediation process. According to the Langmuir model, at a pH of 4.78 and a temperature of 15 ℃, the maximum adsorption capacity of PAD for Cr (VI) is 135.32 mg/g. Its adsorption kinetics conform to a pseudo-first-order model and Langmuir isotherm, indicating uniform adsorption sites and favorable interactions. Thermodynamic analysis further reveals the spontaneous and exothermic nature of the adsorption process, making it suitable for large-scale applications at ambient temperatures.In natural lake water-based Cr(VI) simulated wastewater, PAD resin achieved a remarkable removal efficiency of 99.54 % for 4.82 mg/L Cr(VI) （The filling column had a diameter of 3 cm and a height of 30 cm; The PAD dosage was 1.6 g, with a flow rate of 5 mL/min and an adsorption time of 60 min, at a neutral pH）, effectively reducing residual Cr(VI) concentrations to 0.022 mg/L, well under WHO limits (0.05 mg/L). Additionally, its 93.68 % capacity retention after four HCl regeneration cycles underscores economic feasibility & sustainability.In summary, PAD resin stands out as an innovative, high-performance, and intelligent Cr(VI) adsorbent that transcends the limitations of traditional adsorbents.

Analysis of Positive Discipline Implementation Strategy through Technology Utilization in Providing Feedback to Parents of Students

This research aims to analyze strategies for implementing positive discipline through the use of technology in providing feedback to students' parents. Positive discipline emphasizes the development of constructive behavior through a dialogue and empathy approach, not repressive punishment. However, one of the challenges in implementing this discipline is the lack of effective communication between schools and parents, which is often caused by limited time and access. In the digital era, technology offers innovative solutions to overcome this problem by facilitating the provision of fast and real-time feedback through school applications, digital platforms and instant messaging. This research uses a qualitative approach with a case study method in schools that implement positive discipline. Data was collected through in-depth interviews, participant observation, and documentation from teachers and parents. The research results show that technology can increase the effectiveness of communication between schools and parents, allowing parents to monitor student behavior developments more efficiently. Technology also provides easier access for parents to get involved in supporting children's positive behavior at home, which in turn strengthens positive discipline at school. However, this research also identified several challenges, including gaps in technology access among parents, data security and privacy issues, and the potential for reducing the quality of personal interactions between teachers and parents. Therefore, it is important to develop inclusive and safe communication strategies to ensure optimal parental involvement. This research contributes to the development of a technology-based positive discipline approach, which it is hoped will be implemented more widely in schools, particularly in the context of increasing parental involvement and the efficiency of feedback provided.

A deep learning-based approach to lightweight CSI feedback

Some deep learning-based CSI feedback models have high computational and storage requirements, which limit their feedback efficiency on mobile devices, making them challenging to deploy on a large scale. Therefore, to address the poor feasibility of existing deep learning-based CSI feedback methods in practical deployment on user devices, a lightweight CSI feedback network suitable for mobile terminals is proposed to reduce the demand for computational and storage resources. This network enables efficient feedback on mobile devices. It leverages the design concept of a multi-resolution network to enhance feedback performance while reducing the number of parameters and computational load of the feedback network. Additionally, it employs dynamic convolution to effectively capture the contextual information of CSI. Through simulation comparison, it is found that compared with other lightweight CSI feedback networks based on deep learning, the feedback accuracy in each scenario is improved by 8.57% on average.

Hidden cooling flows − IV. More details on Centaurus and the efficiency of AGN feedback in clusters

ABSTRACT Cooling flows are common in galaxy clusters which have cool cores. The soft X-ray emission below 1 keV from the flows is mostly absorbed by cold dusty gas within the central cooling sites. Further evidence for this process is presented here through a more detailed analysis of the nearby Centaurus cluster and some additional clusters. Predictions of JWST near and mid-infrared spectra from cooling gas are presented. [Ne vi] emission at $7.65\,\mu$m should be an important diagnostic of gas cooling between 6 and $1.5\times 10^5{\rm \, K}$. The emerging overall picture of hidden cooling flows is explored. The efficiency of active galactic nucleus feedback in reducing the total cooling rate in cool cores is shown to be above 50 per cent for many clusters but is rarely above 90 per cent. The reduction is mostly in outer gas. Cooling dominates in elliptical galaxies and galaxy groups that have mass flow rates below about $15{{\rm \, {\rm M}_{\odot }}{\rm \, yr}^{-1}\, }$ and in some massive clusters where rates can exceed $1000{{\rm \, {\rm M}_{\odot }}{\rm \, yr}^{-1}\, }.$

Critical Peer Feedback for Oral Presentation at TEFL Tertiary Education: Comparison, Perception and Reflection

Critical peer feedback is regarded as an effective means to facilitate quality of peer feedback in TEFL class. In this study, a comparative study was conducted between two experimental classes (Nc1=31, Nc2=31) to study Chinese undergraduate perception and efficiency of critical peer feedback in oral presentation. By a mixed study, the 5-scale Likert questionnaires and semi-structured interviews (N=8) were implemented at the setting. The study finds that students have strong confidence that critical peer feedback can improve their quality of oral presentation and the quality of peer feedback. And the quality of oral presentation and quality of peer feedback are facilitated in this comparative study. However, the students still perceive that they are inefficient of the skills of oral presentation like eye contact, PPT design and language organization, and critical peer feedback like critical questions and rubrics. In addition, this implies that the skill training of oral presentation and critical peer feedback is the prerequisite for the novice users in TEFL class which can be facilitated by training, and critical peer feedback focuses on the critical content of peer feedback by critical thinking.

Magnetized Accretion onto and Feedback from Supermassive Black Holes in Elliptical Galaxies

We present 3D magnetohydrodynamic simulations of the fueling of supermassive black holes in elliptical galaxies from a turbulent cooling medium on galactic scales, taking M87* as a typical case. We find that the mass accretion rate is increased by a factor of ∼10 compared with analogous hydrodynamic simulations. The scaling of Ṁ∼r1/2 roughly holds from ∼10 pc to ∼10−3 pc (∼10 r g) with the accretion rate through the event horizon being ∼10−2 M ⊙ yr−1. The accretion flow on scales ∼0.03–3 kpc takes the form of magnetized filaments. Within ∼30 pc, the cold gas circularizes, forming a highly magnetized (β ∼ 10−3) thick disk supported by a primarily toroidal magnetic field. The cold disk is truncated and transitions to a turbulent hot accretion flow at ∼0.3 pc (103 r g). There are strong outflows toward the poles driven by the magnetic field. The outflow energy flux increases with smaller accretor size, reaching ∼3 × 1043 erg s−1 for r in = 8 r g; this corresponds to a nearly constant energy feedback efficiency of η ∼ 0.05–0.1 independent of accretor size. The feedback energy is enough to balance the total cooling of the M87/Virgo hot halo out to ∼50 kpc. The accreted magnetic flux at small radii is similar to that in magnetically arrested disk models, consistent with the formation of a powerful jet on horizon scales in M87. Our results motivate a subgrid model for accretion in lower-resolution simulations in which the hot gas accretion rate is suppressed relative to the Bondi rate by ∼(10rg/rB)1/2 .

Empowering virtual collaboration: harnessing AI for enhanced teamwork in higher education

The emergence of Artificial Intelligence (AI) has brought about a significant change in higher education. It has led to the adoption of more digitally advanced and collaborative models. This paper examines the potential of AI in promoting dynamic virtual teamwork and improving the collective experience in the academic world. It discusses how AI tools can be integrated into various sectors of virtual teamwork, such as academic learning, group projects, communication, assessment, research collaboration, administrative efficiency, engagement strategies, and continuous feedback mechanisms. The paper provides a comprehensive analysis of AI's role in these areas, showing how AI can personalize learning, facilitate complex group tasks, streamline communication, and provide real-time feedback. Ultimately, this will prepare students for the challenges of the professional world and enhance educational efficacy. The paper evaluates the significance of AI in each sector, offering insights into how higher education institutions can use these technologies to create an environment that fosters advanced virtual collaboration. The paper argues that strategic integration of AI is crucial in equipping students with the necessary skills and competencies for the evolving digital landscape of the 21st century.

Internet of robotic things with a local LoRa network for teleoperation of an agricultural mobile robot using a digital shadow

In unstructured agricultural fields where autonomous navigation is challenging and demands additional safety, the operator’s experience and knowledge are essential for supervising operations and making decisions beyond the robot’s autonomous capabilities. Local networks with long-range wireless communication combined with digital twin concepts are promising solutions that can be used for robot teleoperation. The purpose of this study was to demonstrate the feasibility of supervising a mobile robot inside berry orchards using a digital shadow from a long-range distance (between 300 and 3000 m), with the primary objective of assisting the robot in navigating in complex situations such as row-end turning. This involved creating a virtual representation of the robot that mirrors its state and actions, allowing the remote operator to monitor and guide the robot effectively. The system comprised a GPS-based navigation controller with collision avoidance sensors, two sets of LoRa transmitters and repeaters, a simulation environment with a digital shadow of the robot, and a graphical user interface for the remote operator. Information about the digital shadow’s state, including location, orientation, and distances to obstacles, was received as a message by the LoRa gateway and was used to update the path for the actual robot that interfaced with the Robot Operating System (ROS). The main research hypothesis aimed to test the quality of the LoRa communication link between the robot and the operator, as well as the robustness of the robot’s control system, with an emphasis on the architecture, communication link, and situation awareness creation. Preliminary results showed that depending on the environment, the average packet loss was 12% at distances of approximately 2300 m. Our results highlight some of the core technical challenges that need to be addressed for an effective teleoperation system, including latency, stability, and the limited range of wireless communication. Future works involves evaluating the performance and reliability of the proposed method under different field conditions and scenarios, as well as considering the use of the 5G network for a significant improvement in data transmission speed, navigation efficiency, and visual feedback. Upon successful implementation, this study has the potential to enhance the efficiency and safety of robot navigation, providing a practical solution for remote supervision in challenging environments.

External‐Cavity Free Plasmonic Nano‐Lasers Based on Quasi‐2D Perovskite Films

AbstractPlasmonic nano‐lasers possess enormous potential for miniaturization of on‐chip integrated light sources. However, achieving plasmonic lasing requires high‐quality plasmonic resonant cavities, which are currently limited by complex, small‐scale, and costly production methods. Here, a new type of external‐cavity free plasmonic nano‐lasers is first presented with ultra‐thin thickness, achieved through the facile spin‐coating of quasi‐2D perovskite films onto monocrystalline silver sheets. The external‐cavity free plasmonic nano‐lasers exhibit obvious lasing behaviors, evidenced by a well‐defined threshold, significant linewidth narrowing, and distinct polarization dependence. The internal lasing mechanism relies on the scattering loop of surface plasmon polaritons (SPPs) by the disordered grains of the polycrystalline perovskite film. Based on this loop, SPPs experience feedback and amplification at the interface between silver sheets and perovskite films, leading to the lasing. Compared to photonic mode lasers, plasmonic nano‐lasers exhibit a significantly reduced feature size (< 80 nm), a dramatically faster lasing dynamic process (17 ps), and enhanced feedback stability and efficiency. The external‐cavity free plasmonic nano‐lasers eliminate the strict requirements for plasmonic resonant cavities to overcome traditional optical diffraction limits, making them highly significant for future applications in on‐chip photoelectric or all‐optical integration.

Design of a Novel Delivery Efficiency Feedback System for Biphasic Dissolving Microarray Patches Based on Poly(Lactic Acid) and Moisture‐Indicating Silica (Adv. Healthcare Mater. 17/2024)

Design of a Novel Delivery Efficiency Feedback System for Biphasic Dissolving Microarray Patches Based on Poly(Lactic Acid) and Moisture‐Indicating Silica (Adv. Healthcare Mater. 17/2024)

Sustained super-Eddington accretion in high-redshift quasars

Observations of z ≳ 6 quasars provide information on the early evolution of the most massive black holes (MBHs) and galaxies. Current observations, able to trace both gas and stellar properties, reveal a population of MBHs that is significantly more massive than expected from the local MBH-stellar mass relation. The population lies on, but mostly above, the relation observed in the nearby Universe. This suggests that these objects grew very rapidly. To explain their presence when the Universe was less than 1 Gyr old and to assess the physical conditions for their rapid growth, we explored whether episodes of accretion above the Eddington limit can occur across cosmic epochs. By employing state-of-the-art high-resolution cosmological zoom-in simulations of a z ∼ 7 quasar, where different accretion regimes are included consistently, together with their associated radiative and kinetic feedback, we show that super-Eddington phases can be sustained for relatively long timescales (tens of millions of years). This allows the MBH to rapidly grow by up to three orders of magnitude, depending on the strength of the kinetic feedback. We also show by means of a semianalytic calculation that the MBH spin remains moderate and does not take on extremely high values during the super-Eddington phases. This results in a lower feedback efficiency, which may allow the rapid growth required to explain over-massive high-redshift MBHs.

Performance Evaluation and Influencing Factors of Scientific Communication in Research Institutions

Scientific communication holds a pivotal role within research institutions. This study establishes three distinct categories of indicators, tailored to the unique attributes of these institutions, aiming to assess their performance in scientific communication. Employing a rigorous two-stage data envelopment analysis (DEA) approach, we meticulously calculate output efficiency, feedback efficiency, and overall efficiency. Subsequently, we cluster the efficiency outcomes and delve into the factors that influence them. Drawing from the clustering insights and identified influencing factors, we formulate targeted scientific communication strategies tailored to the needs of these research institutions.

Enhancing active learning through collaboration between human teachers and generative AI

To address the increasing demand for AI literacy, we introduced a novel active learning approach that leverages both teaching assistants (TAs) and generative AI to provide feedback during in-class exercises. This method was evaluated through two studies in separate Computer Science courses, focusing on the roles and impacts of TAs in this learning environment, as well as their collaboration with ChatGPT in enhancing student feedback. The studies revealed that TAs were effective in accurately determining students’ progress and struggles, particularly in areas such as “backtracking”, where students faced significant challenges. This intervention’s success was evident from high student engagement and satisfaction levels, as reported in an end-of-semester survey. Further findings highlighted that while TAs provided detailed technical assessments and identified conceptual gaps effectively, ChatGPT excelled in presenting clarifying examples and offering motivational support. Despite some TAs’ resistance to fully embracing the feedback guidelines-specifically their reluctance to provide encouragement-the collaborative feedback process between TAs and ChatGPT improved the quality of feedback in several aspects, including technical accuracy and clarity in explaining conceptual issues. These results suggest that integrating human and artificial intelligence in educational settings can significantly enhance traditional teaching methods, creating a more dynamic and responsive learning environment. Future research will aim to improve both the quality and efficiency of feedback, capitalizing on unique strengths of both human and AI to further advance educational practices in the field of computing.

Is Green Transition in Europe Fostered by Energy and Environmental Efficiency Feedback Loops? The Role of Eco-Innovation, Renewable Energy and Green Taxation

Green transition is in the core of the European policy agenda to achieve the ambitious goal of climate neutrality following the launch of the European Green Deal. The cornerstone of the new growth strategy of Europe is resource efficiency which focuses on shifting to a more sustainable production paradigm by conserving scarce resources and by prioritizing enhanced environmental performance. Scattered efforts to investigate the drivers of resource efficiency measures have shed light on the key drivers, however, those consider resource efficiency measures in isolation neglecting for feedback loops influencing green transition. Therefore, we develop a conceptual framework to study green transition as a system of resource efficiency measures affected by feedback loops, path dependence, green technologies, and green policy tools. We mobilize the analysis by devising a unique balanced panel covering the EU-28 from 2010 through 2019, including policy efforts paving the way for green transition. Econometric results based on a system of fractional probit models, indicate that resource efficiency measures are intertwined via feedback loops, especially in the case of environmental efficiency. Green technologies affect green transition, however, rebound effects emerge in the case of energy efficiency. Past performance affects current levels pushing towards divergence. Evidence suggests that green taxation fosters energy efficiency whereas hinders environmental efficiency. The asymmetric operation of feedback loops and green taxation on energy and environmental efficiency highlights that horizontal policies hinder rather than foster green transition. This study contributes to SDGs 7, 12, 13 and 16.

Enhancing Customer Experience and Satisfaction through Mobile-Based Salon and Spa Reservations on Android Platforms

Salons and spas in Indonesia need to utilize information technology to improve business performance and provide customers with a more personalized experience. The integration of digital reservation systems, online marketing, and technology-based customer management will help improve operational efficiency and gain valuable customer feedback. Digital reservation systems enable salons and spas to improve business performance by providing easy access to customers, increasing the efficiency of scheduling management, and providing a more personalized experience, which is an important strategy in the competitive digital era. One of the alternative digital reservation systems that can be used by salons and spas in Indonesia is Android-based. This research resulted in an Android-based digital reservation system that focuses on customer experience. The object of the research is Spaque Salon & Day Spa, an MSME in Indonesia. Through mobile technology, customers can easily book and manage their treatments. Test results showed positive feedback regarding the user interface, reservation steps, and interactive features. The system also helps with schedule management, additional services, offers, as well as revenue and financial tracking. This research combines customer and technology perspectives, contributing to the salon and spa industry as well as mobile technology developers.

Design of a Novel Delivery Efficiency Feedback System for Biphasic Dissolving Microarray Patches Based on Poly(Lactic Acid) and Moisture-Indicating Silica.

Dissolving microarray patches (DMAPs) represent an innovative approach to minimally invasive transdermal drug delivery, demonstrating efficacy in delivering both small and large therapeutic molecules. However, concerns raised in end-user surveys have hindered their commercialization efforts. One prevalent issue highlighted in these surveys is the lack of clear indicators for successful patch insertion and removal time. To address this challenge, a color-change-based feedback system is devised, which confirms the insertion and dissolution of DMAPs, aiming to mitigate the aforementioned problems. The approach combines hydrophilic needles containing model drugs (fluorescein sodium and fluorescein isothiocyanate (FITC)-dextran) with a hydrophobic poly(lactic acid) baseplate infused with moisture-sensitive silica gel particles. The successful insertion and subsequent complete dissolution of the needle shaft are indicated by the progressive color change of crystal violet encapsulated in the silica. Notably, distinct color alterations on the baseplate, observed 30 min and 1 h after insertion for FITC-dextran and fluorescein sodium DMAPs respectively, signal the full dissolution of the needles, confirming the complete cargo delivery and enabling timely patch removal. This innovative feedback system offers a practical solution for addressing end-user concerns and may significantly contribute to the successful commercializationof DMAPs by providing a visualized drug delivery method.

Dual-Readout Ultrasensitive Lateral Flow Immunosensing of Salmonella typhimurium in Dairy Products by Doping Engineering-Powered Nanoheterostructure with Enhanced Photothermal Performance.

The photothermal lateral flow immunoassay (LFIA) is of great significance to suitable for on-site semiquantitative detection, which has the upper hand in further constructing detection methods for low-concentration targets. Herein, we presented a doping engineering-powered nanoheterostructure with an enhanced photothermal performance strategy, employing bimetallic nanocuboid Pt3Sn (PSNCs) as a proof of concept. With the help of finite element simulation analysis, the contrast of direct temperature experiment, and the evaluation of photothermal conversion efficiency (η), the distinguished and enthusiastic photothermal feedback of PSNCs is proved. Based on steady bright black of colorimetric and superior photothermal performance, the PSNCs were employed to construct an ultrasensitive model LIFA for detecting Salmonella typhimurium (S. typhimurium), which achieved the double-signal semiquantitative detection, the detection limit reached 103 cfu mL-1 (colorimetric mode) and 102 cfu mL-1 (photothermal mode), which is 100 times higher than that of the traditional colloidal gold method. In addition, the method was effective for the detection of targets in dairy samples only through a simple dilution treatment, which was completed within 15 min. Meanwhile, this PSNCs dual-signal LFIA demonstrated the sensitive detection of S. typhimurium due to the excellent colorimetric signal and significant photothermal performance, which provides a broad spectrum for the future detection of foodborne pathogens.