Internal Model Research Articles

The Evolution of the Optimization of Cognitive and Social Functions in the Cerebellum and Thereby the Rise of Homo sapiens Through Cumulative Culture.

The evolution of the prominent role of the cerebellum in the development of composite tools, and cumulative culture, leading to the rise of Homo sapiens is examined. Following Stout and Hecht's (2017) detailed description of stone-tool making, eight key repetitive involvements of the cerebellum are highlighted. These key cerebellar learning involvements include the following: (1) optimization of cognitive-social control, (2) prediction (3) focus of attention, (4) automaticity of smoothness, appropriateness, and speed of movement and cognition, (5) refined movement and social cognition, (6) learns models of extended practice, (7) learns models of Theory of Mind (ToM) of teachers, (8) is predominant in acquisition of novel behavior and cognition that accrues from the blending of cerebellar models sent to conscious working memory in the cerebral cortex. Within this context, the evolution of generalization and blending of cerebellar internal models toward optimization of social-cognitive learning is described. It is concluded that (1) repetition of movement and social cognition involving the optimization of internal models in the cerebellum during stone-tool making was the key selection factor toward social-cognitive and technological advancement, (2) observational learning during stone-tool making was the basis for both technological and social-cognitive evolution and, through an optimizing positive feedback loop between the cerebellum and cerebral cortex, the development of cumulative culture occurred, and (3) the generalization and blending of cerebellar internal models related to the unconscious forward control of the optimization of imagined future states in working memory was the most important brain adaptation leading to intertwined advances in stone-tool technology, cognitive-social processes behind cumulative culture (including the emergence of language and art) and, thereby, with the rise of Homo sapiens.

Probing the content of affective semantic memory following caregiving-related early adversity.

Cognitive science has demonstrated that we construct knowledge about the world by abstracting patterns from routinely encountered experiences and storing them as semantic memories. This preregistered study tested the hypothesis that caregiving-related early adversities (crEAs) shape affective semantic memories to reflect the content of those adverse interpersonal-affective experiences. We also tested the hypothesis that because affective semantic memories may continue to evolve in response to later-occurring positive experiences, child-perceived attachment security will inform their content. The sample comprised 160 children (ages 6-12 at Visit 1; 87F/73M), 66% of whom experienced crEAs (n=105). At Visit 1, crEA exposure prior to study enrollment was operationalized as parental-reports endorsing a history of crEAs (abuse/neglect, permanent/significant parent-child separation); while child-reports assessed concurrent attachment security. A false memory task was administered online ∼2.5 years later (Visit 2) to probe the content of affective semantic memories-specifically attachment schemas. Results showed that crEA exposure (vs. no exposure) was associated with a higher likelihood of falsely endorsing insecure (vs. secure) schema scenes. Attachment security moderated the association between crEA exposure and insecure schema-based false recognition. Findings suggest that interpersonal-affective semantic schemas include representations of parent-child interactions that may capture the quality of one's own attachment experiences and that these representations shape how children remember attachment-relevant narrative events. Findings are also consistent with the hypothesis that these affective semantic memories can be modified by later experiences. Moving forward, the approach taken in this study provides a means of operationalizing Bowlby's notion of internal working models within a cognitive neuroscience framework. RESEARCH HIGHLIGHTS: Affective semantic memories representing insecure schema knowledge (child needs + needs-not-met) may be more salient, elaborated, and persistent among youths exposed to early caregiving adversity. All youths, irrespective of early caregiving adversity exposure, may possess affective semantic memories that represent knowledge of secure schemas (child needs + needs-met). Establishing secure relationships with parents following early-occurring caregiving adversity may attenuate the expression of insecure semantic memories, suggesting potential malleability. Affective semantic memories include schema representations of parent-child interactions that may capture the quality of one's own attachment experiences and shape how youths remember attachment-relevant events.

Quantitative data processing of whole service value chain for power grid internal simulation market

The internal simulation market system can stimulate employee initiative, reduce costs and improve information processing efficiency. However, the complexity of the internal simulation market poses a challenge to computing resources. Efficient data processing techniques are crucial for internal simulation market systems. In this paper, the internal simulation market model and the value chain theory are first put forward. Second, the internal simulation market construction within power grid enterprises is proposed. Then we propose a data mining-based collaborative fusion and processing method for multi-value chain quantitative data in power grid internal simulation markets to conduct data processing, including data fusion, abnormal data elimination and data dimensionality reduction, thereby improving the accuracy of information processing and data sharing. Finally, we validate the superior performance of the proposed method through simulations.

Fixed-time cooperative output regulation for second-order nonlinear multiagent systems with an unknown exosystem

This paper investigates the fixed-time cooperative output regulation (FTCOR) problem with unknown exosystem of second-order nonlinear multiagent systems. To solve this problem, it is necessary to ensure that each agent can obtain the reference trajectory originating from an unknown exosystem and reconstruct the solution of the regulator equation containing the exogenous signal and unknown parameter vectors within a fixed time, and the unknown exosystem makes it difficult to solve these two problems with existing tools. By using auxiliary filtering variables, we propose a fixed-time adaptive distributed observer (FTADO) and design a fixed-time distributed internal model (FTDIM) based on this FTADO. These two new tools ensure the solvability of the two problems just mentioned. Then, based on these two tools, we transform the problem into a fixed-time stabilization problem of a so-called augmented system. Through the backstepping technique, we propose a distributed controller that solves this fixed-time stabilization problem while relaxing the assumptions of similar references.

Local DER Control with Reduced Loop Interactions in Active Distribution Networks

Active Distribution Networks are Multi-Input Multi-Output (MIMO) systems with coupled dynamics, which cause interactions among the control loops of Distributed Energy Resources (DERs). This undesired effect leads to performance degradation of voltage control. To mitigate the effects of this unavoidable coupling, the present paper proposes a systematic design procedure based on the analysis of the interaction’s sources. In detail, each DER is equipped with a double-loop PI to control the active and reactive power output of the voltage source converter, which connects the DER to the network’s node. Furthermore, to guarantee ancillary services, the two loops are coupled by a simple mechanism of cooperation of the active power to voltage regulation realized by a filtered droop law. To achieve voltage regulation with reduced loop interactions, the PI parameters and the filter’s pulse are designed according to a procedure with two sequential steps based on the Internal Model Control (IMC) technique. Simulation studies are finally presented to demonstrate that the proposed design method achieves both reduction of the loop interaction and robust voltage control in the presence of model parameter uncertainty in the MIMO plant, modeling various operating conditions of the ADN, including a step connection of large loads, renewable energy source variations, and changes in the substation transformer ratio.

Non-square internal model control for mode transition of hybrid electric vehicles with multiple time delays

Mode transitions of multi-mode hybrid electric vehicles need careful coordination among the engine torque, motor torque, and clutch transmitted torque. However, the three torques have different actuation delays which make it difficult to ensure mode transition performance. A non-square internal model controller (IMC) is proposed in this paper for mode transition during which the input number is greater than the output number and each input has a different actuation delay. At first, the Moore-Penrose generalized inverse matrix is introduced to solve the inverse of the non-square matrix and make the IMC applicable. Secondly, the all-pole method is adopted to approximate the three delay models. Based on these specialized techniques, the tracking controller and anti-disturbance controller of the IMC are derived. Experiment results verify the effectiveness of the proposed controller.

Gain scheduled internal model control based on the dynamic sliding mode method for the water level of nuclear steam generators

Gain scheduled internal model control based on the dynamic sliding mode method for the water level of nuclear steam generators

Studying the Internal Wave Generation Mechanism in the Northern South China Sea Using Numerical Simulation, Synthetic Aperture Radar, and In Situ Measurements

The internal waves in the South China Sea are highly correlated with the tidal currents in the Luzon Strait, which makes it possible to establish an internal wave prediction model based on internal wave kinematics. However, the kinematic model requires the input of the exact location and time of the initial internal wave for which the generation mechanism of internal waves in the northern South China Sea must be well understood. By analyzing the internal wave field in the northern South China Sea (SCS) simulated using the MIT General Circulation Model (MITgcm) and observations from satellite synthetic aperture radar (SAR) and mooring temperature–salinity–depth (TSD) chains, the source regions and propagation initiation times of internal waves are identified for three typical tidal phases, i.e., the diurnal-tide-dominated phase (DTP), transition tide phase (TTP), and semidiurnal-tide-dominated phase (STP). The generation procedures of Type A and Type B internal waves are discussed in detail with those data. The present study reveals that Type A and Type B waves are generated at the eastern and western ridges, respectively, and both commence their westward propagation at the peak of the eastward tidal flow. The dynamics of lee waves and the resonance effect with double ridges constitute the generation mechanisms of internal waves in the northern SCS. Combined with varying configurations of tidal conditions, topography, and stratification, the generation procedures of Type A and Type B waves in the DTP, TTP, and STP are elucidated with the generation mechanism in a unified and self-consistent way. In short, during DTP, weaker A waves alternate with weaker B waves each day; during TTP, strong A waves and strong B waves appear alternately every day; and there are two weak A waves per day during the STP. The generation mechanism can help in developing future empirical models for generating internal waves using tidal currents, topography, and stratification without requiring complex fluid dynamics calculations.

A robust internal model control design for low-quality waste heat power generation systems

Recovering low-quality waste heat using industrial waste heat is challenging, and the reuse technology needs to erupt. Moreover, the gas source of low-quality waste heat is relatively volatile, which makes it challenging to keep the actual working condition of the plant stable. Therefore, it is inspiring to research the robustness of root-waste heat power generation processed measurement and control system to improve the stability of the plant operation. Hence, in this paper, we have applied uncertainty theory to analyze it and formulate the uncertainty model based on the Bode diagram. We also proposed a control method based on the uncertainty model, which combines robust control and internal model control to make the roots waste heat power generation system operate stably under the effect of external disturbances and changes of internal structure or parameters in actual operation. Experimental results show that the robust internal model control method has a speed deviation of no more than 7.9 r/min compared with the PID control method. The adjustment time to track the set value does not exceed 73.1 seconds within the allowed fluctuation range. The fluctuation variance is 30.95% of that of the PID controller. The dynamic performance is better, with strong anti-interference capability and significantly improved tracking performance. It ensures the stability of the roots-type waste heat utilization system, which is essential for future intelligent grid-connected power generation.

Role of the Cerebellum in the Construction of Functional and Geometrical Spaces.

The perceptual and motor systems appear to have a set of movement primitives that exhibit certain geometric and kinematic invariances. Complex patterns and mental representations can be produced by (re)combining some simple motor elements in various ways using basic operations, transformations, and respecting a set of laws referred to as kinematic laws of motion. For example, point-to-point hand movements are characterized by straight hand paths with single-peaked-bell-shaped velocity profiles, whereas hand speed profiles for curved trajectories are often irregular and more variable, with speed valleys and inflections extrema occurring at the peak curvature. Curvature and speed are generically related by the 2/3 power law. Mathematically, such laws can be deduced from a combination of Euclidean, affine, and equi-affine geometries, whose neural correlates have been partially detected in various brain areas including the cerebellum and the basal ganglia. The cerebellum has been found to play an important role in the control of coordination, balance, posture, and timing over the past years. It is also assumed that the cerebellum computes forward internal models in relationship with specific cortical and subcortical brain regions but its motor relationship with the perceptual space is unclear. A renewed interest in the geometrical and spatial role of the cerebellum may enable a better understanding of its specific contribution to the action-perception loop and behavior's adaptation. In this sense, we complete this overview with an innovative theoretical framework that describes a possible implementation and selection by the cerebellum of geometries adhering to different mathematical laws.

Brain oscillations during emotion regulation and the two-dimensional model of adult attachment

Emotion Regulation (ER) refers to the processes by which individuals influence their own emotions. It is a crucial aspect of human behavior, affecting everything from interpersonal relationships to mental health. The relationship between ER and Attachment Theory (AT) is pivotal. AT suggests that early bonds with primary caregivers influence future relationship expectations and behaviors. These initial experiences shape internal models of self and others, affecting how individuals regulate their emotions. Understanding the interplay between ER and AT is essential for comprehending the human affective system. In this study, we explored the neural underpinnings of ER, focusing on two distinct strategies: cognitive reappraisal and expressive suppression. Using electroencephalography (EEG), we examined changes in neural oscillations from 52 adults during an ER task. Specifically, we observed increased frontal theta activity (3–6 Hz) during reappraisal compared to suppression strategies. This frontal theta activity suggests enhanced cognitive control engagement. Conversely, during suppression, we noted a decrease in beta frequency (15–30 Hz) activity from central electrodes, indicative of differing neural processes. Further integrating psychological theories, we explored the relationship between these neural markers and dimensions of human attachment. Employing the Experiences in Close Relationships-12 scale (ECR-12), we identified a negative correlation between attachment anxiety and frontal theta activity. Lower levels of attachment anxiety were associated with increased theta activity, reflecting potentially more effective emotion regulation. Additionally, we found that higher theta activity corresponded with fewer difficulties in emotional control measured by the Difficulties in Emotion Regulation Scale (DERS). Regarding central beta activity, our findings revealed an interesting correlation with Emotional Inattention, a concept tied to Attachment Avoidance. This suggests that central beta activity may serve as a neural marker for specific attachment-related ER processing. These results highlight the distinct neural pathways involved in different ER strategies and their relationship with the AT and neural responses during emotional processing.

Prediction error in implicit adaptation during visually- and memory-guided reaching tasks

Human movements are adjusted by motor adaptation in order to maintain their accuracy. There are two systems in motor adaptation, referred to as explicit or implicit adaptation. It has been suggested that the implicit adaptation is based on the prediction error and has been used in a number of motor adaptation studies. This study aimed to examine the effect of visual memory on prediction error in implicit visuomotor adaptation by comparing visually- and memory-guided reaching tasks. The visually-guided task is thought to be implicit learning based on prediction error, whereas the memory-guided task requires more cognitive processes. We observed the adaptation to visuomotor rotation feedback that is gradually rotated. We found that the adaptation and retention rates were higher in the visually-guided task than in the memory-guided task. Furthermore, the delta-band power obtained by electroencephalography (EEG) in the visually-guided task was increased immediately following the visual feedback, which indicates that the prediction error was larger in the visually-guided task. Our results show that the visuomotor adaptation is enhanced in the visually-guided task because the prediction error, which contributes update of the internal model, was more reliable than in the memory-guided task. Therefore, we suggest that the processing of the prediction error is affected by the task-type, which in turn affects the rate of the visuomotor adaptation.

Removal of isobaric interference using pseudo-multiple reaction monitoring and energy-resolved mass spectrometry for the isotope dilution quantification of a tryptic peptide.

Energy-resolved mass spectrometry (ERMS) and an isotopically labelled internal standard were successfully combined to accurately quantify a tryptic peptide despite the presence of an isobaric interference. For this purpose, electrospray ionisation tandem mass spectrometry (ESI-MS/MS) experiments were conducted into an ion trap instrument using an unconventional 8m/z broadband isolation window, which encompassed both the tryptic peptide and its internal standard. Interference removal was assessed by determining an excitation voltage that was high enough to maintain a constant value for the analyte/internal standard peaks intensity ratio, thus ensuring accurate quantification even in the presence of isobaric contamination. Pseudo-multiple reaction monitoring (MRM) was employed above this excitation voltage to quantify the trypic peptide. The internal standard calibration model showed no lack of fit and exhibited a linear dynamic range from 0.5μM up to 2.5μM. The detection limit was 0.08 μM. The accuracy of the method was evaluated by quantifying the tryptic peptide of three reference samples intentionally contaminated with the isobaric interference. All the reference samples were accurately quantified with ∼1% deviation despite the isobaric contamination. Furthermore, we have demonstrated that this methodology can also be applied to quantify the isobaric peptide by standard additions down to 0.2μM. Finally, liquid chromatography ERMS (LC ERMS) experiments yielded similar results, suggesting the potential of the proposed methodology for analysing complex samples.

Optimizing sintering conditions and microstructure for enhanced dielectric and humidity sensing properties of Na1/3Ca1/3Tb1/3Cu3Ti4O12 ceramics

This study investigated the impact of sintering temperature and resultant microstructure on the dielectric behavior and humidity sensing performance of Na1/3Ca1/3Tb1/3Cu3Ti4O12 (NCTCTO). The pure NCTCTO phase was obtained. Relative density and grain size tended to increase with the sintering temperature. The porous NCTCTO exhibited remarkable humidity sensing performance with minimal hysteresis error (2 %) and rapid response and recovery times (1.5 min). The dense NCTCTO ceramic with a high relative density of about 99 %, demonstrated significant giant dielectric properties, with ε′∼8500 and low loss tangent (0.08). The dielectric behavior was interpreted using the internal barrier layer capacitor model. The increase in ε′ with humidity was ascribed to the absorption of H2O molecules at the grain boundary, leading to increased interfacial polarization. This work delineates the critical influence of ceramic microstructure on the humidity sensing and giant dielectric properties of NCTCTO ceramics, paving the way for their application in advanced electronic devices.

Design of two-degree-of-freedom position tracking controller for hypergravity unidirectional airborne shaking table

Hypergravity centrifugal shaking table is widely used in the field of civil engineering and is considered to be the most effective means to study geotechnical earthquake disaster effect in the world today. Here, the structure of hypergravity centrifugal shaking table system is briefly introduced, and then the necessity and difficulty of the precise control of the position ring of the airborne shaking table in the hypergravity centrifugal shaking table are explained. On this premise, the system modeling and analysis of the unidirectional airborne shaking table with hypergravity are carried out in this paper. A new two-degree-of-freedom controller of the unidirectional airborne shaking table with hypergravity is designed by combining the [Formula: see text] control and an improved internal model control (IIMC) strategy, and the designed two-degree-of-freedom controller is experimentally verified. The experimental results show that compared with the traditional PID control strategy and the single [Formula: see text] control strategy, the two-degree-of-freedom controller designed in this paper can make the position loop control of the unidirectional airborne shaking table with hypergravity have higher control accuracy and anti-interference ability.

Internal Quality Management Model in Islamic Boarding School-Based Madrasah

This research aims to (1) analyze the need for an internal quality management model and (2) design an internal quality management model in Islamic boarding school-based madrasas. This research uses the Research and Development (R&D) method using ADDIE (Analysis, Design, Develop, Implement, Evaluate) procedures and steps. The research results show that the Pesantren-Based Madrasah Quality Assurance Team must receive full support from the Islamic boarding school leadership. The Ministry of Religion's version of the Madrasah Self-Evaluation Instrument (EDM) must be developed to accommodate educational evaluations in Islamic boarding schools. Islamic boarding school-based madrasa's internal quality management model consists of four stages. First, the planning stage which consists of (1) mission alignment, (2) SWOT analysis, (3) EDM gap analysis, and (4) preparation of a quality plan. Second, the quality fulfillment stage consists of (1) determining the person responsible for the program, (2) funding allocation, and (3) reporting on quality implementation. Third, the quality evaluation stage consists of (1) formative evaluation, (2) summative evaluation, (3) preparation of evaluation instruments, (4) data collection, and (5) analysis and preparation of recommendations. Fourth is the quality follow-up stage, which consists of (1) follow-up improvement and (2) follow-up standardization of changes.

Developmentally Unique Cerebellar Processing Prioritizes Self- over Other-Generated Movements.

Animals must distinguish the sensory consequences of self-generated movements (reafference) from those of other-generated movements (exafference). Only self-generated movements entail the production of motor copies (i.e., corollary discharges), which are compared with reafference in the cerebellum to compute predictive or internal models of movement. Internal models emerge gradually over the first three postnatal weeks in rats through a process that is not yet fully understood. Previously, we demonstrated in postnatal day (P) 8 and P12 rats that precerebellar nuclei convey corollary discharge and reafference to the cerebellum during active (REM) sleep when pups produce limb twitches. Here, recording from a deep cerebellar nucleus (interpositus, IP) in P12 rats of both sexes, we compared reafferent and exafferent responses with twitches and limb stimulations, respectively. As expected, most IP units showed robust responses to twitches. However, in contrast with other sensory structures throughout the brain, relatively few IP units showed exafferent responses. Upon finding that exafferent responses occurred in pups under urethane anesthesia, we hypothesized that urethane inhibits cerebellar cortical cells, thereby disinhibiting exafferent responses in IP. In support of this hypothesis, ablating cortical tissue dorsal to IP mimicked the effects of urethane on exafference. Finally, the results suggest that twitch-related corollary discharge and reafference are conveyed simultaneously and in parallel to cerebellar cortex and IP. Based on these results, we propose that twitches provide opportunities for the nascent cerebellum to integrate somatotopically organized corollary discharge and reafference, thereby enabling the development of closed-loop circuits and, subsequently, internal models.

Transgenerational trauma and attachment.

An integrative approach is presented to understand the transmission mechanisms of attachment trauma and the quality of the internal working model through manifestations of bodily symptoms concerning physical and mental health. A case of dissociative symptomatology is described in a woman whose ancestors experienced individual and collective trauma related to the political regime. The approach allows for an analytical view beyond the standard complaints of anxiety, depression, post-traumatic symptoms, eating disorders, etc. A brief description of the transgenerational transmission of trauma is presented.

Influence of gear modification on dynamic characteristics of star gearing system in geared turbofan (GTF) gearbox based on a closed-loop dynamic analysis method

The star gearing transmission system is a key component of a geared turbofan (GTF) aero-engine. Accurate prediction of the dynamic characteristics of the star gearing transmission system, especially after gear modification, is important for the design of high-performance engines. Firstly, this paper establishes a dynamic time-varying mesh stiffness (TVMS) and a comprehensive transmission error (TE) calculation model for herringbone gear pair considering changes in the meshing state. Then, the dynamic internal excitation calculation model is combined with the lumped parameter dynamic model of the system to form the “excitation–response–feedback” closed-loop coupling dynamic analysis method of the GTF star gearing system. Compared with traditional analysis methods, this method takes into account the effect of contact state changes on internal excitation during the calculation process and corrects internal excitation in real time. Finally, the effect of different topology modification schemes on the system's dynamic characteristics is investigated based on this method. The results show that the closed-loop coupled dynamics analysis method is able to capture contact state changes of the same gear pair at different moments and between different gear pairs at the same moment. Modified #2 is only to modify the planet gear. This scheme can effectively reduce the vibration displacement of the ring gear, and reduce the peak-to-peak value of the ring gear's vibration displacement in all directions by more than 70%. At the same time, the scheme also reduces the load-sharing coefficient of the internal and external meshing pairs of the system by 1.92% and 2.01%, respectively, and the peak-to-peak value of the dynamic factor of the internal and external meshing pairs can be reduced by 57.91% at most.

A Solvency II Partial Internal Model Considering Reinsurance and Counterparty Default Risk

Estimating the expected capital and its variability is a crucial objective for a non-life insurance company, which enables the firm to develop effective management strategies. Many studies have been devoted to this topic, with simulative approaches being especially employed for solving the complexity of the interacting risks, not manageable through closed-form solutions. In this paper, we present a realistic framework based on Solvency II for the definition of next-year capital of a non-life insurer, including reinsurance treaties and counterparty default risk, in a multi-line of business setting. We determine the mean and variance of the stochastic capital considering both quota share and excess-of-loss reinsurance. We show how these closed-form results enable the analysis of many different real-world strategies, granting the insurer the possibility of choosing the optimal policy without the computational resources and time constraints required by simulative approaches.