Self-regulation Capabilities Research Articles

Obesity treatment-associated transfer of exercise-related self-regulation to eating-related self-regulation changes in women

ABSTRACT Obesity in the United States has risen to 42 percent of its adult population and is similarly problematic in many other countries. Although the U.S. government has provided education on healthy eating and the need to exercise regularly, behavioral obesity treatments have largely failed to sustain reductions in weight. Self-regulation, and the incorporation of exercise for its psychological impacts on eating, has sometimes been targeted. While there has been sporadic investigation into the carry-over of exercise-related self-regulation to eating-related self-regulation, the present aim is to further inquiry in that area to inform future treatment content for improved effects. Women enrolled in community-based obesity treatments with either a self-regulation (n = 106) or education (n = 54) focus were assessed on changes in exercise- and eating-related self-regulation, negative mood, completed exercise, and weight. Improvements were significantly greater in the self-regulation-focused group. After controlling for initial change in eating-related self-regulation, change in that measure from Month 3 to 6 was significantly predicted by change in exercise-related self-regulation during the initial 3 treatment months. This suggested a carry-over effect. A stronger predictive relationship was associated with the self-regulation-focused treatment. In further analyses, paths from changes in exercise→negative mood→self-regulation of both exercise and eating were significant. Increase in eating-related self-regulation was significantly associated with weight loss over 6, 12, and 24 months. The self-regulation-focused group had stronger relationships, again. Findings suggested utility in targeting exercise-related self-regulation to impact later change in eating-related self-regulation, and the use of exercise-associated mood improvement to bolster participants’ self-regulation capabilities.

Preliminary developmental challenges of children at risk for specific learning disabilities: Insights from parents and teachers—a qualitative study

This study aims to uncover the preliminary developmental challenges experienced by children from infancy to their primary school years, who are subsequently diagnosed with specific learning disabilities during their primary education. The ultimate goal is to develop an item pool to identify early symptoms of specific learning disabilities. This qualitative descriptive design study employed semi-structured interviews with 20 participants, comprising both parents and teachers of 10 children aged 8–11. The interviews lasted between 45 and 60 min. To ensure the research's quality and reliability, we applied evaluation criteria and performed six-stage thematic analysis framework. The results indicate that children experienced developmental difficulties from infancy to preschool period that impacted their social-emotional development, language and communication, motor and self-care skills, as well as their perception, memory, attention, and self-regulation capabilities. These challenges were exacerbated during the school years by motivation-related issues. Parental observations primarily highlighted difficulties in language and communication, such as pronunciation, initiating conversations, and speech, during the first three years of life. Significant issues in social-emotional development included introversion, a need for physical contact, challenges in maintaining relationships, and adherence to rules. These challenges emerged during the first three years of children and progressively worsened across all developmental domains. This study contributes valuable insights into the literature by providing past observations from parents and teachers, thus enhancing understanding of the preliminary developmental challenges faced by children at risk of specific learning disabilities.

A study on the resource scheduling strategy in substations with high penetration of photovoltaic electricity

Abstract In 2020, China introduced the strategic objectives of reaching the peak of carbon emissions and achieving carbon neutrality. However, due to the limited self-regulation capabilities of the power grid and increasingly prominent issues such as insufficient consumption of photovoltaic electricity generation, there are challenges. Therefore, in this paper, a coordinated interaction model of source-load-storage is established with the aim of optimizing the on-site utilization of photovoltaic electricity. Rolling scheduling of substation resources is conducted at three temporal scales: pre-scheduled, interim, and actual-time, and the effectiveness of the proposed approach is verified using actual case studies. The data suggests that compared with single-time-scale scheduling schemes, the on-site consumption rate of photovoltaic electricity increases by 0.32% in the case study substations, validating that the scheduling approach can improve the photovoltaic electricity consumption rate in the substations.

Advancements in energy-efficient building technologies: An enhanced lee model for precision simulation and optimization of heat pipe applications

The rising demand for energy, coupled with growing environmental concerns, has intensified the focus on building energy consumption. Heat pipe technology, particularly gravity heat pipes, is recognized as a promising solution for building cooling and energy conservation due to its high efficiency, simple design, and strong adaptability. To comprehensively investigate the intricate heat transfer process in gravity heat pipes, an effective integration of heat pipes with building systems is realized. This study focuses on strategies to enhance the Lee model with the primary objective of improving simulation accuracy and overall performance through systematic refinement and innovative modifications. This study seeks to offer valuable insights to enhance the validity and applicability of the Lee model across diverse scenarios, enabling a cost-effective and accurate visualization of the application of heat pipe technology in building cooling system processes. The improved Lee model demonstrates heightened self-regulation capabilities in terms of thermal and mass balance, outperforming traditional models in prediction accuracy. Numerical simulations extend the investigation to explore the impact of various factors on the flow dynamics of gravity heat pipes, encompassing liquid filling rate, wall hydrophilicity, heating power, and inner diameter of heat pipes. The research aims to provide crucial insights into the design and application of gravity heat pipes in buildings, particularly in understanding the fundamental influence of these factors on heat transfer performance and gas-liquid phase transition processes. The overarching message underscores the significance of promoting energy-saving technologies, such as gravity heat pipes, for sustainable building practices.

Surface structure regulation of sulfidated zero-valent iron by H2O2 for efficient pH self-regulation and proton cycle to boost heterogeneous Fenton-like reaction for pollutant control

Sulfidated zero-valent iron (SZVI) has been widely used in controlling organic pollutants. However, the significant decrease in catalytic activity of SZVI-based Fenton-like systems under neutral and alkaline conditions remains a large problem. Herein, it was found that surface structure regulation of SZVI with H2O2 (HT-SZVI) greatly enhanced its reactivity and efficiently activated H2O2 to oxidize various organics in a wide pH range. The HT-SZVI/H2O2 system exhibited a pH self-regulation capability that stabilized the eventual solution pH at ∼3.5 at the initial pH of 3.0–9.0. The excellent oxidation performance was primarily attributed to surface-bound •OH produced from H2O2 activation by surface Fe(II) sites on HT-SZVI. Additionally, dissolved Fe(II) converted from surface Fe(II) induced proton generation to self-regulate pH. Newly formed high proton-conductive FeS and Fe3O4 shells accelerated the transfer of accumulated protons in solution to iron core to produce Fe(II), enabling efficient proton consumption-regeneration cycle and enhancing •OH production.

Investigation of the relationship between screen usage habits, behavioral problems and self-regulation skills of children aged 4–6

PurposeAmidst the multifaceted changes taking place in our dynamic world, the study of screen usage habits and their impacts on children has emerged as a burgeoning area of research interest. The current research endeavors to investigate and establish the correlation that exists between screen usage patterns, behavioral challenges, and self-regulation capabilities within the demographic of children aged 4–6 years. Design and methodsIn the study, descriptive cross-sectional and relationship-seeking research model. The sample of the study consisted of 557 people with children between the ages of 4 and 6 years who voluntarily participated in the study between December 2022 and April 2023. The “Personal Information Form”,“Problematic Media Use Measure (PMUM)”, “Preschool Behavior Questionnaire” and “Instrument for Measuring Self-Regulation Skills” were used to collect data. ResultsIt was found that 53% of the children were girls, 87.4% lived in the city center. The rate of children with no siblings was 59.4%, 48.1% spent between 1 and 2 in front of a screen and 52.4% used mobile phones. Furthermore, there appears to be a reciprocal interaction among self-regulation skills, behavioral problems, and problematic internet usage. ConclusionIt can be asserted that as children's self-regulation skills increased, behavioral problems decreased and it can be asserted that as children's problematic internet use levels increased, behavioral problems also increased. Practice implicationsIn line with these results, pediatric and public health nurses have a great deal of work, parents should be made aware of these issues with large-scale trainings, and it should not be forgotten that these age groups are the most sensitive periods.

PENINGKATAN REGULASI MAHASISWA PPG MELALUI AKTIVITAS PENGEMBANGAN PERANGKAT PEMBELAJARAN

The development of learning tools aims to facilitate students to design innovative learning activities by utilizing the results of analysis of problem-based, literacy and HOTS teaching materials. Project-Based Learning is aimed at improving high-level thinking skills, understanding problems and strengthening literacy. This classroom action research describes increasing the regulatory abilities of PPG students in using Project Based Learning (PjBL). This research was carried out in two cycles. The research results show that Project Based Learning (PjBL) model learning through the Learning Management System can improve the regulatory abilities of Teacher Professional Program (PPG) students. In the first cycle, the achievement of indicators of student regulatory success reached the quite good category with a percentage of 71%. In the second cycle of action, PPG students' regulatory abilities increased to the good category with a percentage achievement of 76%. It can be concluded hat self-regulation abilities to increase and be consistent, the implementation of Project Based Learning can be carried out in three cycles and reinforced with various learning topics in the Learning Management System (LMS). This effort is important with a focus on improving aspects of self-regulation capabilities, namely deepening essential questions, strengthening plans and implementation of HOTS-based projects.

Enhancing students’ hyperactivity disorder through physical education classroom design and blended teaching: a research study

Background Hyperactivity disorder significantly affects their academic and mental health. The research aims to explore whether the design of physical education classrooms using blended learning can have a positive effect on students’ ADHD psychology.Subjects and MethodsParticipants were selected from a school and divided into an experimental group and a control group. The experimental group experienced a blended teaching approach within the physical education classroom, combining conventional sports activities with interactive e-learning resources. In contrast, the control group followed a traditional physical education classroom design. Data collection tools comprised a hyperactivity disorder questionnaire and psychological assessment tools, with Epidata 2.0 employed for data processing.ResultsThe scores of hyperactivity disorder in the experimental group were significantly lower than those in the control group. The average ADHD score of the experimental group students decreased from the initial 6.78 to 3.92, while the average ADHD score of the control group students decreased from the initial 7.12 to 6.28. The difference between the experimental group and the control group was verified to be statistically significant using appropriate statistical methods.Conclusions The incorporation of blended learning within the physical education classroom design yields a positive impact on students’ hyperactivity disorder psychology. The integration of traditional sports activities with interactive e-learning resources establishes a more diverse and adaptable learning environment. This approach enables students to channel excess energy effectively, thereby enhancing their focus and self-regulation capabilities.

The Triple P System of Evidence-Based Parenting Support: Past, Present, and Future Directions

Triple P is an integrated, multi-level system of evidence-based parenting support designed to promote the well-being of children and families to reduce prevalence rates of social, emotional, and behavioral problems in children and adolescents and to prevent child maltreatment. The system developed gradually over four decades to address the complex needs of parents and children from diverse family, socioeconomic and cultural backgrounds. It blends universal and targeted programs, a focus on developing parental self-regulation capabilities, and adopts a life span perspective with a population health framework. The Triple P system is used as a case example to discuss the past, present and future challenges, and opportunities involved in developing, evaluating, adapting, scaling and maintaining a sustainable system of evidence-based parenting intervention. Seven stages of program development are outlined from initial theory building and development of the core parenting program through to the sustained deployment of the intervention system delivered at scale. The importance of ongoing research and evaluation is highlighted so that different programs within the system evolve and adapt to address the contemporary concerns and priorities of families in diverse cultural contexts. A well-trained workforce is essential to deliver evidence-based programs, in a need-responsive manner that blends both fidelity of delivery and flexibility and is tailored to respond to the needs of individual families and local context. Programs need to be gender-sensitive, culturally informed, and attuned to the local context including relevant policies, resources, cultural factors, funding, workforce availability and their capacity to implement programs.

Efforts to Increase Academic Resilience of IAIN Syekh Nurjati Cirebon Students Through Strengthening Self-Regulation Capabilities

In an educational environment, encountering difficulties and challenges is natural. Someone who is able to adapt and overcome these difficulties and challenges means that he has academic resilience abilities. Academic resilience can be increased by using self-regulation abilities. This study aims to determine: (1) students' academic resilience abilities; (2) students' self-regulation abilities; (3) The efforts of IAIN Syekh Nurjati Cirebon students in increasing academic resilience through strengthening their self-regulation abilities. This study uses a qualitative method. The data collection technique used in this research is using interviews. The results of this study reveal that the majority of students have a fairly high level of academic resilience. They say that they will fight the panic and fear of the difficulties and failures that come their way. Even when faced with difficult assignments, they feel challenged and motivated.

An adaptive event-driven fault-tolerant consensus proposed for decentralized multiple AUVs with actuator multiplicative faults

The present paper studies a distributed leaderless multi-autonomous underwater vehicle (AUV) system under a heterogeneous topology network where multiplicative faults and input saturation affect actuators, and the actuator fault severity could not be equal in each AUV. For this system, an adaptive event-driven fault-tolerant consensus control protocol is proposed. The present paper also introduces adaptive parameters in the trigger function to improve the self-regulation capability of the event-driven mechanism system. The proposed fully distributed event-driven fault-tolerant consensus strategy depends on the adaptive coupling gain of the system, and it eliminates the global information restriction. It was found that the designed event-driven controller has a good fault tolerance effect on multiplicative faults of actuators. The states of the multi-AUV system could asymptotically converge to the same conditions without Zeno behavior. Finally, the Lyapunov functional method proves the system's astringency and stability, and the numerical simulation presents the strategy's effectiveness.

Experimental investigation of self-regulating capability of open-cathode PEMFC under different fan working conditions

Self-regulation capability of the open-cathode PEMFC generally means that the stack itself can adjust its state to response to different operating conditions to achieve better performance when the external control strategy remains unchanged. In this paper, self-regulating capability of the stack are analyzed when its cooling fan works under blow or suction mode at different voltages. The result of output voltage shows that the stack achieves better self-regulation when the fan operates at 8.5 V in both blow mode and suction mode. Analysis of impedance spectra reveals that the stack can realize self-regulating function by adjusting activation resistance and ohmic resistance, and the cathode activation resistance is dominant. Furthermore, the result of a cycle load test indicates that the stack can better reflect the self-regulating capability in fan suction mode than in blow mode, and the stack can achieve better water and heat regulation in suction mode. Finally, according to the air velocity distribution and temperature change, it is found that self-regulating capability in suction mode play a better role due to more uniform heat remove. A suitable fan operating voltage and mode are critical for the self-regulating capability of the open-cathode PEMFC stack to maintain a water-heat balance.

Receding horizon control based secondary frequency regulation for power systems with wind energy integration

During the last decade, the integration of large-scale renewable energy resources like wind energy into the existing power girds has increased dramatically. In particular, the inherent intermittency and uncertainty of wind power poses new challenges for reliable and stable of power grids. Frequency control is one of the most significant challenges, especially in systems with few control reserves. To address this problem, we propose an optimization-based method for secondary frequency regulation that enables wind turbines to respond to frequency variations. Instead of relying on energy storage systems, the wind turbine’s kinetic energy storage and self-regulation capabilities are leveraged to optimize the trade off between providing frequency regulation and maximizing wind power yield. Moreover, the proposed method is amenable to online implementation and shows good performance in scenarios with time varying wind speeds. A detailed case study in a dedicated co-simulation environment is used to validate the proposed optimal control method and demonstrate its improved performance over standard approaches combining maximum power point tracking and conventional automatic generation control.

Improving the Behavioral Intention of Continuous Online Learning Among Learners in Higher Education During COVID-19.

The COVID-19 pandemic caused colleges and universities to rely heavily on online learning to continue knowledge dissemination to learners. This study used the second-generation model of unified theory of acceptance and use of technology (UTAUT2) to comprehensively analyze the mediating effects of self-efficacy, which affects learners’ effective use of online tools for learning, and capability of metacognition and self-regulation, which can independently adjust learning progress into the UTAUT2 model, on the learner’s willingness to continue online learning [i.e., their behavioral intention (BI)] by constructing a UTAUT2-based e-learning model. This study administered questionnaires to undergraduates in universities in East China to collect data. The effects of performance expectancy, effort expectancy (EE), social influence (SI), and facilitating conditions (FCs), hedonic motivation (HM), price value (PV), and habits on BI (directly or through mediators) were analyzed through data analysis and structural equation modeling, and the UTAUT2-based e-learning model was accordingly modified. The results indicated that the self-efficacy enhanced the effects of EE, SI, FCs, HM, and PV on learners’ BI; that metacognition and self-regulation (MS) capabilities enhanced the effects of EE on learners’ BI; and that habits had a direct and strong effect on BI. This study also provided some suggestions to enhance higher education learners’ willingness to continue online learning, such as improving social recognition and support, careful design of teaching content, easy-to-use technology, financial support. These results and suggestions may guide colleges and universities in conducting, continuing, or enhancing online education, particularly as the pandemic continues.

High-Voltage Isolated Multiple Output Auxiliary Power Supply with Output Voltage Self-Regulation

Power electronic transformers (PETs) have high voltage isolation requirements and a large number of modules, which requires the auxiliary power supply (APS) to achieve high voltage isolation and multiple outputs. This paper proposes a parameter optimization method for the current source APS applied to PETs, enabling the APS to have multiple output voltage self-regulation capabilities. By optimizing the excitation inductance and leakage inductance for the current transformer of the APS, the excitation current plays a regulating role in energy transmission, thus realizing the self-regulation of the output voltages. The proposed method enables the voltage deviation and voltage change of the output modules to be suppressed under the unbalanced loads and large load fluctuations. Moreover, the APS can still operate normally when a short-circuit or an open-circuit fault occurs on the output sides. Therefore, the stability and reliability of the APS are improved, and the design difficulty of the post-stage voltage regulator circuit is also reduced. Finally, the simulation results are given, and a prototype containing three output modules was built to verify the effectiveness of the proposed parameter optimization method.

Individual Differences in Cognitive Functioning Predict Compliance With Restoration Skills Training but Not With a Brief Conventional Mindfulness Course.

Mindfulness training is often promoted as a method to train cognitive functions and has shown such effects in previous studies. However, many conventional mindfulness exercises for beginners require cognitive effort, which may be prohibitive for some, particularly for people who have more pronounced cognitive problems to begin with. An alternative mindfulness-based approach, called restoration skills training (ReST), draws on a restorative natural practice setting to help regulate attention effortlessly and promote meditative states during exercises. Previous research has shown that a 5-week ReST course requires less effort and is attended by higher compliance with practice recommendations than a conventional mindfulness course, without compromising long-term outcomes. Here, we compare ReST and a formally matched conventional mindfulness course regarding the role that initial individual differences in cognitive functioning play in determining practice compliance and long-term improvements in dispositional mindfulness and cognitive functioning. In line with expectations, ReST participants who had more pronounced cognitive problems to begin with practiced more during the course, which in turn explained much of their improvement in dispositional mindfulness and cognitive functioning. In contrast, initial cognitive functioning did not explain practice and improvement in the conventional mindfulness course. The results provide further support for the potential utility of ReST as a low-effort method for enhancing cognitive functioning among people who would struggle with the demands of conventional mindfulness training. With careful integration of mindfulness practices with a restorative natural setting, these people can develop mindfulness and self-regulation capabilities without relying on effortful training.

Intelligent Learning Based Active Power Regulation of Wind Turbines Considering Fatigue Reduction

The variability and uncertainty of wind power generation pose severe challenges in balancing supply and demand in real time. To overcome this challenge, one promising solution is to exploit the self-regulation capabilities of wind turbines (WTs) and operate them as “semi-dispatchable” resources. In this article, the rotor speed control and pitch angle control are utilized simultaneously to regulate wind power output. It should be noted that changing the operating point of a WT affects the forces and moments it experienced. To increase the life span of WTs and decrease maintenance costs, an optimization problem that aims to track the dispatch command while minimize fatigue loads is formulated. Due to the nonlinearity and nonconvexity of the WT model and load estimation model, the resulting optimization problem cannot be solved online. To address this issue, an intelligent learning based method is designed. Extensive case studies are conducted, and simulation results demonstrate that the proposed method can effectively exploit the regulation capability of WTs to trace the given dispatch command while also reducing the shaft torque and thrust-induced loads.

Thermal self-regulatory smart biosensor based on horseradish peroxidase-immobilized phase-change microcapsules for enhancing detection of hazardous substances

Conventional enzyme-based biosensors are highly sensitive to operation temperature due to a strong temperature dependency of biocatalytic activity. Aiming to enhance the biosensing detection of hazardous substances at high ambient temperatures, we focused on the design and construction of a thermal self-regulatory smart biosensor through an innovative combination of phase change material (PCM) and bioelectrocatalytic material. A bioelectrocatalytic phase-change microcapsule system was first fabricated by microencapsulating n-eicosane as a PCM core in the TiO2 shell and then depositing polypyrrole (PPy) as an electroactive coating layer on the surface of TiO2 shell, followed by immobilizing horseradish peroxidase on the surface of PPy coating layer through physical adsorption. The resultant microcapsules exhibit a regular spherical morphology and layer-by-layer core–shell microstructure with the desired chemical compositions. The microcapsules not only exhibit a good thermal management ability to perform effective temperature regulation under a latent-heat capacity of approximately 115 J/g, but also reveal high thermal impact resistance and good thermal cycle stability for the long-term thermal management application in biosensors. A working electrode was modified with the microcapsules obtained above and then used to construct an electrochemical biosensing system imparted with a thermal self-regulation capability. With a high sensitivity of 5.571 µA·L·µmol−1·cm−2 and a low detection limit of 5.384 µmol/L at 55 °C, the resultant smart biosensor exhibits a better determination ability to detect catechol as a model hazardous substance at high operation temperatures than conventional biosensors thanks to the in-situ thermal management derived from its n-eicosane core. This study provides a new approach for development of thermal self-regulatory smart biosensors with an enhanced identification capability to detect hazardous substances over a wide range of temperatures.

Thermal self-regulatory intelligent biosensor based on carbon-nanotubes-decorated phase-change microcapsules for enhancement of glucose detection

Enzyme-based biosensors are sensitive to temperature due to their strong temperature dependency of catalytic activity. Aiming at enhancing biosensing detection for glucose assay over a wide range of applicable temperatures, we designed a thermal self-regulatory intelligent biosensor through an innovative integration of phase change material (PCM) and bioelectrocatalytic substances. An electroactive phase-change microcapsule system was firstly fabricated by microencapsulating n-docosane as a PCM core in the SiO2 shell, followed by depositing polydopamine along with carbon nanotubes as an electroactive layer on the surface of SiO2 shell. The resultant microcapsules showed a regularly spherical morphology and well-defined core-shell microstructure. They also exhibited a satisfactory latent heat capacity of around 137 J/g for implementing temperature regulation with a good working stability. An electrochemical biosensing system was constructed with the resultant electroactive microcapsules together with glucose oxidase as a redox enzyme, achieving a thermal self-regulation capability to enhance the biosensing detection of glucose under in-situ thermal management at higher temperatures. With a high sensitivity of 5.95 μA⋅mM−1⋅cm−2 and a lower detection limit of 13.11 μM at 60 °C, the intelligent biosensor developed by this study demonstrated a superior determination capability and better detection performance toward glucose than conventional biosensors in a high temperature region thanks to effective regulation of microenvironment temperature in the electrode system. This study provides a promising strategy for the development of thermal self-regulatory smart biosensors with an enhanced identification ability to detect various chemical substances over a wide range of applicable temperatures.

A Fixed Bed Pervious Concrete Anaerobic Bioreactor for Biological Sulphate Remediation of Acid Mine Drainage Using Simple Organic Matter

The development of low-operational-cost and low-operational-complexity active sulphate (SO4) reducing bioremediation for Acid Mine Drainage (AMD) is an ongoing pursuit towards sustainable mining. This study introduces a fixed bed pervious concrete anaerobic bioreactor as a second stage AMD remediation process. The study investigated the pH self-regulation capabilities, SO4 remediation capabilities and the rate limiting parameters of the bioreactor using glucose as an organic matter source. The AMD was pre-treated using a permeable reactive barrier. A 21-day trial comprised of an increase in the SO4 loading rate while reducing the organic loading rate was undertaken to identify performance limiting conditions. A daily average SO4 concentration reduction rate of 55.2% was achieved over the initial 13 days of the experiments. The study found that a COD to SO4 ratio and VFA to alkalinity ratio below 5:1 and 0.5:1 respectively were performance limiting. The bioreactor was capable of self-regulating pH within the neutral range of 6.5 and 7.5. The study findings indicate that the bioreactor design can reduce operational costs and operational complexity of active AMD bioremediation.