Adaptive Regulation Research Articles

Nutraceuticals and pharmacological to balance the transitional microbiome to extend immunity during COVID-19 and other viral infections

Abstract Scope The underlying medical conditions and gut dysbiosis is known to influence COVID-19 severity in high-risk patients. The current review proposed the optimal usage of nutraceuticals & pharmacological interventions can help regulate the protective immune response and balance the regulatory functionality of gut microbiota. Summary Many studies have revealed that the probiotic interventions viz., Lactobacillus rhamnosus, L. plantarum & other bacterial spp. reduce IFNγ & TNF-α and increase IL-4 & IL-10 secretions to control the immunostimulatory effects in upper respiratory tract infection. Dietary fibres utilized by beneficial microbiota and microbial metabolites can control the NF-kB regulation. Vitamin C halts the propagation of pathogens and vitamin D and A modulate the GM. Selenium and Flavonoids also control the redox regulations. Interferon therapy can antagonize the viral replications, while corticosteroids may reduce the death rates. BCG vaccine reprograms the monocytes to build trained immunity. Bifidobacterium and related microbes were found to increase the vaccine efficacy. Vaccines against COVID-19 and season flu also boost the immunity profile for robust protection. Over all, the collective effects of these therapeutics could help increase the opportunities for faster recovery from infectious diseases. Conclusion The nutraceutical supplements and pharmacological medicines mediate the modulatory functionalities among beneficial microbes of gut, which in turn eliminate pathogens, harmonize the activity of immune cells to secrete essential regulatory molecular receptors and adaptor proteins establishing the homeostasis in the body organs through essential microbiome. Therefore, the implementation of this methodology could control the severity events during clinical sickness and reduce the mortalities.

Epigenetic Regulation for Heat Stress Adaptation in Plants: New Horizons for Crop Improvement under Climate Change

Global warming poses a significant threat to plant ecosystems and agricultural productivity, primarily through heat stress (HS), which disrupts photosynthesis, respiration, and overall plant metabolism. Epigenetic modifications, including DNA methylation, histone modifications, and RNA modifications, enable plants to dynamically and heritably adjust gene expression in response to environmental stressors. These mechanisms not only help plants survive immediate stress but also confer stress memory, enhancing their resilience to future HS events. This review explores the mechanisms underlying plant thermotolerance, emphasizing the critical role of epigenetic regulation in adapting to HS. It also highlights how DNA methylation modulates stress-responsive genes, histone modifications facilitate transcriptional memory, and RNA modifications influence mRNA stability and translation. Recent advancements in genome editing technologies, such as CRISPR-Cas9, have enabled precise modifications of epigenetic traits, offering new avenues for breeding climate-resilient crops. The integration of these modern tools with traditional breeding methods holds significant promise for developing crops with enhanced thermotolerance. Despite the potential, challenges such as the stability and heritability of epigenetic marks and the complex interplay between different epigenetic modifications need to be addressed. Future research should focus on elucidating these interactions and identifying reliable epigenetic markers for selection. By leveraging the insights gained from epigenetic studies, we can develop innovative breeding strategies to improve crop resilience and ensure sustainable agricultural productivity in the face of global warming. This review underscores the importance of epigenetic regulation in plant adaptation to heat stress and its potential to revolutionize crop breeding, offering a pathway to secure food production and sustainability under changing climatic conditions.

Non-Coding RNAs in Myasthenia Gravis: From Immune Regulation to Personalized Medicine.

Myasthenia gravis (MG) is an antibody-mediated autoimmune disorder characterized by altered neuromuscular transmission, which causes weakness and fatigability in the skeletal muscles. The etiology of MG is complex, being associated with multiple genetic and environmental factors. Over recent years, progress has been made in understanding the immunological alterations implicated in the disease, but the exact pathogenesis still needs to be elucidated. A pathogenic interplay between innate immunity and autoimmunity contributes to the intra-thymic MG development. Epigenetic changes are critically involved in both innate and adaptive immune response regulation. They can act as (i) pathological factors besides genetic predisposition and (ii) co-factors contributing to disease phenotypes or patient-specific disease course/outcomes. This article reviews the role of non-coding RNAs (ncRNAs) as epigenetic factors implicated in MG. Particular attention is dedicated to microRNAs (miRNAs), whose expression is altered in MG patients' thymuses and circulating blood. The long ncRNA (lncRNA) contribution to MG, although not fully characterized yet, is also discussed. By summarizing the most recent and fast-growing findings on ncRNAs in MG, we highlight the therapeutic potential of these molecules for achieving immune regulation and their value as biomarkers for the development of personalized medicine approaches to improve disease care.

The role of fathers’ and mothers’ acceptance in adaptive emotion regulation in Chinese preadolescents: Distinguishing between- and within-person effects

The relationship between parental styles and the regulation of emotions in adolescents has been extensively explored in previous research conducted in Western countries. However, the absence of research conducted within the cultural context of China, combined with imprecise methodologies, impedes the empirical validation of this association. This study aims to examine the longitudinal relationship between parental acceptance and preadolescent emotion regulation in the Chinese cultural context, utilizing a cross-lagged panel model with random intercepts. The sample comprised 1987 middle school students, with 56.10 % being male and a mean age of 12.32 years, from Guangdong and Shandong provinces. Participants provided feedback on assessments of parental acceptance and emotion regulation at three time points: the first and final semesters of seventh grade and the initial semester of eighth grade. The findings revealed a significant association between the random intercepts of paternal and maternal acceptance and adaptive emotion regulation in preadolescents at the between-person level. However, no statistically significant within-person cross-lagged effect was observed from parental acceptance to preadolescent adaptive emotion regulation. Similarly, changes in preadolescent emotion regulation did not significantly predict changes in parental acceptance. These findings challenge the tripartite model and suggest that the association between parental acceptance and preadolescent adaptive emotion regulation is predominantly influenced by trait-related factors.

How I think about how I feel: Personal beliefs about emotion prospectively predict suicide-related outcomes and depression symptoms

One transdiagnostic process that may be critical to depression and suicidal ideation is beliefs about the nature of one's own emotions, both concurrently and longitudinally. In a sample of community adults (n = 143), we assessed personal emotion beliefs about the degree to which one's own emotions are malleable, unique, and last a long time. There were significant associations between stronger views that one's own emotions were fixed, unique to you, and had a longer duration and higher clinical symptom severity, including higher levels of current suicidal ideation, and less adaptive emotion regulation. Mediation analyses using longitudinal data clarified that the differential engagement in emotion regulation, specifically rumination, represented the link tying specific personal emotion beliefs to clinical symptoms and that, in certain cases, the opposite pathway is also significant – differences in clinical symptoms mediated the relationship between specific personal emotion beliefs and emotion regulation (rumination) longitudinally. Additionally, personal emotion beliefs varied based on depression status, as determined using a semi-structured clinical interview. For example, individuals meeting current criteria for Major Depressive Disorder (MDD) held stronger views that their emotions were unique to them compared to individuals with remitted MDD or no history of MDD. The current study's findings highlight the important role of specific personal emotion beliefs in clinical symptoms concurrently and longitudinally and mechanisms in these relationships. These results could guide future research on interventions to promote more adaptive beliefs about emotion to improve clinical outcomes.

State Space Model Reference Adaptive Control for a Class of Second-Degree Fractional Order Systems with Different Eigenvalues

This study proposes an adaptive control synthesis for a class of second-degree fractional order systems with different eigenvalues in the state-space domain. The proposed fractional order adaptive controller is a generalization of the MRAC controller for the class of scalar fractional order systems. In order to control the fractional order plant, an adaptive state space feedback controller is applied based on the error between the system output and a chosen reference model using a fractional adaptation law to make the fractional order plant track the fractional order reference model. We show that the resulting adaptive regulator is able to stabilize the fractional order second degree system with a satisfying performance. A simulation example illustrating these performance properties is provided along with a comparison with a fractional order sliding mode control (FOSMC) to demonstrate the superiority of the proposed control scheme.

Structural Relationships among Mentalization, Adaptive Cognitive Emotion Regulation and Problem Drinking in New Middle-Aged: A Multigroup Analysis According to Adult Attachment Types

Structural Relationships among Mentalization, Adaptive Cognitive Emotion Regulation and Problem Drinking in New Middle-Aged: A Multigroup Analysis According to Adult Attachment Types

Multifunctional evaluation and multiscenario regulation of non-grain farmlands from the grain security perspective: Evidence from the Wuhan Metropolitan Area, China

Non-grain production (NGP) represents a complex social phenomenon driven by a range of interests that involve agricultural development, livelihood security, and ecological preservation. It significantly alters the structure of agricultural production and vegetation cover, influencing regional grain supply and the multifunctional composition of agriculture. To achieve sustainable development goals related to grain supply and ecological stability, this study proposes a research framework for multifunctional evaluation and multiscenario regulation of non-grain farmlands (NGFs). First, NGFs in the Wuhan metropolitan area (WHM) were extracted based on land survey data to carry out multifunctional evaluation of NGFs, including production function, ecological functions and recreational function. Second, the SOM+K-means algorithm is used to identify and explore the multifunctional bundle characteristics of NGFs to determine the regulation priority order of NGFs. Finally, a multiscenario simulation of the rigid control scale and layout arrangement of NGFs from the grain security perspective is carried out. The research results show that (1) there are 1294.34 thousand ha of NGFs in the WHM, mainly of grain and non-grain rotation type (52.36 %). The production function is higher in the central and western Jianghan Plain areas than in the northeastern and southern hilly mountainous areas; the ecological functions are the opposite; the high-value areas of recreational function are mainly located around the built-up areas of the city. (2) Multifunctional bundles divide NGFs into seven categories and determine the order of regulation based on the principle of "production priority, functional diversity". (3) By setting different grain security scenarios, it is predicted that the rigid control scale of NGFs in the WHM in 2030 is 256.08–797.55 thousand ha. Divide and restore grain production in order of the priority zone for grain production, the reserve zone for grain production, the resilience zone for grain production, the ecological improvement zone and the agricultural improvement zone, so as to achieve a regulatory layout of strict control and adaptable regulation of NGFs. The research supports the regulation of NGFs in balancing grain security and ecological stability to promote sustainable agricultural production.

A method for image–text matching based on semantic filtering and adaptive adjustment

As image–text matching (a critical task in the field of computer vision) links cross-modal data, it has captured extensive attention. Most of the existing methods intended for matching images and texts explore the local similarity levels between images and sentences to align images with texts. Even though this fine-grained approach has remarkable gains, how to further mine the deep semantics between data pairs and focus on the essential semantics in data remains to be quested. In this work, a new semantic filtering and adaptive approach (FAAR) was proposed to ease the above problem. To be specific, the filtered attention (FA) module selectively focuses on typical alignments with the interference of meaningless comparisons eliminated. Next, the adaptive regulator (AR) further adjusts the attention weights of key segments for filtered regions and words. The superiority of our proposed method was validated by a number of qualitative experiments and analyses on the Flickr30K and MSCOCO data sets.

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

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

Enrichment of novel CD3+F4/80+ cells in brown adipose tissue following adrenergic stimulation.

Macrophages play a multifaceted role in maintaining tissue homeostasis, fighting infections, and regulating cold-induced thermogenesis. The brown adipose tissue (BAT) is crucial for maintaining body temperature during cold exposure. Cold stress triggers the sympathetic nervous system to release norepinephrine (NE), which activates BAT via β3-adrenergic receptors, initiating lipolysis and glycolysis. BAT-infiltrating macrophages can either hinder or enhance thermogenesis by controlling the interplay between BAT cells and sympathetic nerves. In this study we report on a unique population of CD3+F4/80+ dual lineage co-expressing (DE) cells within the interscapular BAT (iBAT), that increased following chronic adrenergic stimulation. In forward scatter/side scatter plots, they formed a cluster distinct from lymphocytes, appearing larger and more complex. These CD3+F4/80+ DE cells demonstrated the lack of T cell markers CD62L and TCRβ and expressed higher levels of Ly6C, F4/80, and CD11b markers compared to T cells and CD3- macrophages. Furthermore, analysis revealed two subpopulations within the CD3+F4/80+ DE population based on MHCII expression, with the proportion of MHCII-low subset increasing with adrenergic stimulation. This novel DE population within iBAT, unequivocally identified by the its unique surface marker profile, warrants further investigation into the intricate mechanisms governing adaptive thermogenesis regulation.

A map neuron with piezoelectric membrane, energy regulation and coherence resonance

The cell membrane has a layered structure, which separates the intracellular and extracellular ions for developing gradient electromagnetic field, and its flexible property enables the capacitance dependence on the shape deformation due to external stimuli. Therefore, piezoelectric membrane can be suitable to describe the biophysical characteristic of cell membrane and equivalent circuit approach becomes important. In this paper, two capacitors are connected via a piezoelectric ceramic and two additive memristive channels are combined to mimic the neural activity response with exact energy description. Furthermore, linear transformation is applied to obtain an equivalent piezoelectric map neuron and energy function is provided to explore the adaptive energy regulation on mode selection in neural activities. Coherence resonance is detected and analyzed. The map neuron can also be considered as an auditory neuron for perceiving acoustic signals and its membrane property is considered from physical aspect.

The Role of Administrative Law in Realizing Village Autonomy Based on Local Wisdom

This study aims to analyze the role of State Administrative Law in realizing village autonomy based on local wisdom. The method used in this research was a qualitative approach with interviews, observations, and analysis of documents in some of the villages that were the subject of the study. These results show that State Administrative Law is vital in providing a foundation for villages to manage resources and development based on local potential and needs. Local wisdom is crucial for decision-making and resource management within villages, contributing to environmental sustainability and cultural preservation. The synergy between State Administrative Law and local wisdom creates effective policies that empower communities. Challenges in implementation, such as regulatory mismatches with local values, low legal literacy, and conflicts of interest, need to be addressed through legal socialization, capacity building, and collaboration. Therefore, it is recommended that the Government formulate inclusive and adaptive regulations to local wisdom and enhance human resource capacity in villages. Academics should conduct further research and provide policy recommendations. The private sector should play an active role in village economic empowerment, and village communities should actively participate in development and preserve local wisdom.

The impact of cognitive emotion regulation strategies on math and science anxieties with or without controlling general anxiety

It is well-established that general anxiety associates with the lower use of adaptive emotion regulation and the higher use of maladaptive emotion regulation. However, no study has previously investigated the impact of cognitive emotion regulation on academic anxieties. Using a sample of secondary school students (N = 391), this study examined the impact of cognitive emotion regulation on math and science anxieties. Math anxiety showed stronger correlations with adaptive than maladaptive emotion regulation, whereas general anxiety showed stronger correlations with maladaptive than adaptive emotion regulation. Hierarchical regression analyses showed that math anxiety was associated with the high uses of acceptance, rumination and other-blame and the low uses of positive reappraisal and putting into perspective. However, with controlling science and general anxieties, math anxiety was associated with the high use of rumination and the low use of positive reappraisal. In contrast, science anxiety was associated with the high uses of acceptance and other-blame and the low use of positive reappraisal. Importantly, however, with controlling math and general anxieties, those science anxiety associations did not remain. Accordingly, these results might provide important insights for the specificity, etiology, and intervention of math anxiety.

Distributed adaptive cooperative optimal output regulation via integral reinforcement learning

This paper studies the optimal cooperative output regulation problem for unknown linear multi-agent systems by the integral reinforcement learning technique. Existing results on this problem were obtained by a non-fully distributed learning process. In contrast, we propose a distributed learning algorithm over the jointly connected switching communication networks. Moreover, by modifying the existing algorithm, we reduce the computational cost and weaken the solvability conditions. Two numerical examples are used to illustrate the effectiveness of our approach.

Adaptive event-triggered robust output regulation for uncertain switched T-S fuzzy systems

This paper focuses on the adaptive event-triggered robust output regulation issue for uncertain switched Takagi–Sugeno fuzzy systems with unknown exosystems and model uncertainty. The purpose is to pursue the output regulationcharacteristic and the disturbances suppression characteristic. First, an event-triggered mechanism is introduced to ease the communication burden. Then, on the basis of the event-triggered program, an adaptive event-triggered robust output regulation control law is developed to battle the uncertainty and disturbances. Further, constraints are arrived to force the solvability of the adaptive event-triggered robust output regulation issue for uncertain switched Takagi–Sugeno fuzzy systems by virtue of the average dwell-time way. In the end, a simulation instance with a mass–spring-damping model employed is arranged to showcase the practicality and effectiveness of the developed control methodology.

Model experimental studies on active heave compensation control strategy for electric-driven offshore cranes

Ship-mounted heave compensation offshore cranes are indispensable for isolating connected payloads from the support vessel during lifting operations under harsh sea conditions. In this paper, an innovative adaptive robust control strategy is presented for the electric-driven active heave compensation (EDAHC) system, combining an equivalent model predictive control (EMPC) method with a bias proportional integral derivative (BPID) framework to effectively mitigate the adverse effects of wave-induced heave motions from the support vessel on the suspended payload. Building upon the inherent field-oriented control in the permanent magnet synchronous motor (PMSM), the BPID-based control structure is introduced, motivated by its prompt responsiveness and robust resistance against model discrepancies and irregular disturbances. Facilitated by a torque compensation mechanism, the EMPC-based control scheme, synthesized with an autoregressive integrated moving average (ARIMA)-based heave motion prediction algorithm, is subsequently developed to achieve nonlinear friction deadzone correction and adaptive regulation of BPID parameters, thereby ensuring optimal performance of the EDAHC system within specified state and input constraints. Comparative experimental tests conducted on a scaled EDAHC testbed validate the superior capabilities of the proposal in station-keeping, position tracking, constraint satisfaction, and robustness against parametric uncertainties.

Decoding acceptance and reappraisal strategies from resting state macro networks

Acceptance and reappraisal are considered adaptive emotion regulation strategies. While previous studies have explored the neural underpinnings of these strategies using task-based fMRI and sMRI, a gap exists in the literature concerning resting-state functional brain networks’ contributions to these abilities, especially regarding acceptance. Another intriguing question is whether these strategies rely on similar or different neural mechanisms. Building on the well-known improved emotion regulation and increased cognitive flexibility of individuals who rely on acceptance, we expected to find decreased activity inside the affective network and increased activity inside the executive and sensorimotor networks to be predictive of acceptance. We also expect that these networks may be associated at least in part with reappraisal, indicating a common mechanism behind different strategies. To test these hypotheses, we conducted a functional connectivity analysis of resting-state data from 134 individuals (95 females; mean age: 30.09 ± 12.87 years, mean education: 12.62 ± 1.41 years). To assess acceptance and reappraisal abilities, we used the Cognitive Emotion Regulation Questionnaire (CERQ) and a group-ICA unsupervised machine learning approach to identify resting-state networks. Subsequently, we conducted backward regression to predict acceptance and reappraisal abilities. As expected, results indicated that acceptance was predicted by decreased affective, and executive, and increased sensorimotor networks, while reappraisal was predicted by an increase in the sensorimotor network only. Notably, these findings suggest both distinct and overlapping brain contributions to acceptance and reappraisal strategies, with the sensorimotor network potentially serving as a core common mechanism. These results not only align with previous findings but also expand upon them, illustrating the complex interplay of cognitive, affective, and sensory abilities in emotion regulation.

Affective Regulation and Trait Anger Personalities: The Buffering Effect of the Companion Animal Bond.

Emotional dysregulation involving anger can have severe consequences on the individual's psychosocial and emotional functioning. This study aimed to investigate the role that the companion animal bond and the personality dimension of trait anger play in explaining affective dysregulation. A cross-sectional online survey was administered to 365 participants. Using the PROCESS macro for SPSS, a moderated model was tested to analyze the hypothesis that affective dysregulation depends on trait anger and that the companion animal bond moderates the relationship between trait anger and affective dysregulation. The results showed that the effect of trait anger on affective dysregulation increases especially when the degree of bonding to an animal companion is low, suggesting that a strong bond to a companion animal may protect individuals with trait anger from the likelihood of experiencing affective regulation problems. The psychological, health-related, and educational implications of the current anthrozoological study include the potential of the human-animal bond in acting as a facilitator of adaptive affective regulation processes, which can reduce the levels of uncontrolled anger-related emotions and the subsequent risk of out-of-control behaviors.

Specific emotion regulation difficulties mediate the relationship between personal distress and depressive symptoms in medical students.

Several studies indicate a link between personal distress and vulnerability to depression. The literature also suggests that personal distress is associated with emotion dysregulation and that emotion dysregulation plays a role in depression. However, which of the various emotion regulation difficulties mediates the relationship between personal distress and depression remains unexplored. This study therefore aims to investigate the mediating role of specific emotion regulation difficulties in the relationship between personal distress and depression. Of the 702 initially recruited participants, 635 completed a survey comprising the Interpersonal Reactivity Index, the Difficulties in Emotion Regulation Scale, and the Beck Depression Inventory. A mediation analysis was used to explore which emotion regulation difficulties mediate the relationship between personal distress and depression. Over a quarter (27%) of participants reported moderate-severe depression symptoms. Difficulties in accessing adaptive emotion regulation strategies and in having a clear understanding about one's own emotions partly mediated the relationship between personal distress and depression symptoms. Our results are the first to indicate that personal distress is linked to depression risk through specific emotion regulation difficulties in medical students. They also highlight possible modifiable skills that could be targeted by prevention intervention.