Loop Model Research Articles

Neurobiological Correlates of Psychedelic Experiences and Psychedelic-Associated Adverse Effects.

This chapter offers a comprehensive overview of our current understanding of the neural mechanisms underlying the effects of psychedelic drugs, with a primary focus on human neuroimaging studies. Whenever possible, we explore the neurobiological mechanisms that may underly acute and subacute adverse effects and describe hypotheses on how these results may inform on the pathophysiology of psychiatric illnesses. We delve into the general effects of psychedelics on EEG, fMRI, and PET measurements, drawing insights from experiments that have assessed their acute biological mechanisms. Additionally, we review the relatively limited literature exploring pre- to postdrug changes. Throughout this chapter, we explore the prevailing models of psychedelic drug actions, including the Cortico-Striato-Thalamo-Cortical (CSTC) feedback loop model, the entropic brain hypothesis, the REBUS principle (an extension of predictive brain theories), and the claustrum hypothesis. Finally, we delve into the neural correlates of distinct features of the psychedelic experience, encompassing visual effects, social and emotional impacts, and the phenomenon of ego dissolution. We offer speculations on how our current understanding of acute drug effects might relate to the rarely occurring long-term adverse effects. It is important to note that due to the scarcity of data, these speculations remain tentative.

Analysis of the Construction of Resilient Governance System for Public Safety in Urban Communities in Jiangsu--Based on the Perspective of Adaptive Loop Modeling

Abstract As urbanization and informatization progress, human societies increasingly face unforeseeable public safety risks, necessitating a comprehensive governance system for early risk prevention. This paper introduces a model for community public safety resilience governance grounded in the adaptive cycle model and formulates research hypotheses. We derive a mathematical formula for calculating the safety disaster risk value using risk management theory, which aids in determining the resilience value and risk level of communities. The proposed governance model assesses community resilience through a four-faceted approach that encompasses natural disasters, accidents, public health events, and social security incidents. The public safety resilience of Community L in N city, Jiangsu Province, was evaluated using this model. Furthermore, it was determined that urban communities in NJ City, WX City, and XZ City had resilience governance scores of 77.655, 73.18, and 73.475, with scores exceeding 70 points. An analysis of 16 subject cities revealed that only five are currently in the renewal stage, representing an optimal state of high resilience and low risk. The remaining 11 cities face varying degrees of challenges. To prevent systemic decay, it is crucial to implement customized public safety governance strategies for different urban types.

Dynamically updated digital twin for prognostics and health management: Application in permanent magnet synchronous motor

Current research on Digital Twin (DT) based Prognostics and Health Management (PHM) focuses on establishment of DT through integration of real-time data from various sources to facilitate comprehensive product monitoring and health management. However, there still exist gaps in the seamless integration of DT and PHM, as well as in the development of DT multi-field coupling modeling and its dynamic update mechanism. When the product experiences long-period degradation under load spectrum, it is challenging to describe the dynamic evolution of the health status and degradation progression accurately. In addition, DT update algorithms are difficult to be integrated simultaneously by current methods. This paper proposes an innovative dual loop DT based PHM framework, in which the first loop establishes the basic dynamic DT with multi-filed coupling, and the second loop implements the PHM and the abnormal detection to provide the interaction between the dual loops through updating mechanism. The proposed method pays attention to the internal state changes with degradation and interactive mapping with dynamic parameter updating. Furthermore, the Independence Principle for the abnormal detection is proposed to refine the theory of DT. Events at the first loop focus on accurate modeling of multi-field coupling, while the events at the second loop focus on real-time occurrence of anomalies and the product degradation trend. The interaction and collaboration between different loop models are also discussed. Finally, the Permanent Magnet Synchronous Motor (PMSM) is used to verify the proposed method. The results show that the modeling method proposed can accurately track the lifecycle performance changes of the entity and carry out remaining life prediction and health management effectively.

Cascade control of electrical drives of a pumping station based on an astatic fuzzy regulator

The article discusses the main features of cascade pressure control in a water supply system with a controlled and additional uncontrolled pumps. The disadvantages of the existing control systems are formulated and it is proposed to control the pump station electric drives using correction of speed of the controlled pump depending on the mode of operation of the uncontrolled pump. A simplified mathematical model of the pressure control loop was developed, with the representation of the switching on of the additional pump as a disturbance effect of an aperiodic behavior. At the same time, the control algorithm of the additional pump is described in the form of unequivocal nonlinearities based on single step and signature functions, which allows to significantly simplify its implementation in the case of using microprocessor devices. To reduce the impact of disturbances in transient operating modes, namely when the additional pump is switched on, it is proposed to use the speed correction component for the main pump in the control algorithm. To avoid the formation of a static error, it is suggested to use a pressure regulator with integral component. Next, a refined mathematical model in the MATLAB environment was developed and an investigation of system operation using proportional-integral-derivative controller of pressure main pump speed control was carried out. It was determined that using of correction component allows to increase the accuracy of pressure control, but does not allow to compensate the presence of transport delay and nonlinearities of the system. Therefore, as a pressure regulator of the hydraulic system output, a combined astatic fuzzy regulator based on a proportional-integral control algorithm is used. The main difference of such a regulator is the automatic change of the gain factor when the error changes, which prevents the occurrence of unstable modes with large coefficients of the open system. The developed fuzzy control system provides a lot of benefits, such as increasing the reliability of the water supply network, improving the performance of the water supply system for consumers, reducing the wear and tear of pumping equipment, and reducing electricity consumption, which is confirmed by the results of numerical modeling.

Dual simulation of a Polyakov loop model at finite baryon density: Correlations and screening masses

Computations of screening masses in finite-temperature QCD at finite density are plagued by the sign problem and have been performed so far with an imaginary chemical potential. Here, we use a dual formulation of a Polyakov-loop model which allows the determination of screening masses at real baryon chemical potential. This is a second paper in a series devoted to a detailed study of dual Polyakov-loop models at finite density. While the first paper was mainly devoted to establishing the phase diagram of the model, here we compute correlation functions of the Polyakov loops and the second-moment correlation length at non-zero chemical potential. This enables us to evaluate numerically the screening masses from correlations of the real and imaginary parts of the Polyakov loops. We also compute these masses in the mean-field approximation and compare with numerical results. In addition, we provide a quantitative improvement of the general phase diagram presented in the first paper.

PLM-GAN: A Large-Scale Protein Loop Modeling Using pix2pix GAN.

Revealing the tertiary structure of proteins holds huge significance as it unveils their vital properties and functions. These intricate three-dimensional configurations comprise diverse interactions including ionic, hydrophobic, and disulfide forces. In certain instances, these structures exhibit missing regions, necessitating the reconstruction of specific segments, thereby resulting in challenges in protein design, which encompasses loop modeling, circular permutation, and interface prediction. To address this problem, we present two pioneering models: pix2pix generative adversarial network (GAN) and PLM-GAN. The pix2pix GAN model is adept at generating and inpainting distance matrices of protein structures, whereas the PLM-GAN model incorporates residual blocks into the U-Net network of the GAN, building upon the foundation of the pix2pix GAN model. To bolster the models' performance, we introduce a novel loss function named the "missing to real regions loss" (LMTR) within the GAN framework. Additionally, we introduce a distinctive approach of pairing two different distance matrices: one representing the native protein structure and the other representing the same structure with a missing region that undergoes changes in each successive epoch. Moreover, we extend the reconstruction of missing regions, encompassing up to 30 amino acids and increase the protein length by 128 amino acids. The evaluation of our pix2pix GAN and PLM-GAN models on a random selection of natural proteins (4ZCB, 3FJB, and 2REZ) demonstrated promising experimental results. Our models constitute significant contributions to addressing intricate challenges in protein structure design. These contributions hold immense potential to propel advancements in protein-protein interactions, drug design, and further innovations in protein engineering. Data, code, trained models, examples, and measurements are available on https://github.com/mena01/PLM-GAN-A-Large-Scale-Protein-Loop-Modeling-Using-pix2pix-GAN_.

Parameters calculation method of energetic model for symmetrical static hysteresis loop and asymmetrical minor loop

PurposeThis paper aims to propose an energetic model parameter calculation method for predicting the materials’ symmetrical static hysteresis loop and asymmetrical minor loop to improve the accuracy of electromagnetic analysis of equipment.Design/methodology/approachFor predicting the symmetrical static hysteresis loop, this paper deduces the functional relationship between magnetic flux density and energetic model parameters based on the materials’ magnetization mechanism. It realizes the efficient and accurate symmetrical static hysteresis loop prediction under different magnetizations. For predicting the asymmetrical minor loop, a new algorithm is proposed that updates the energetic model parameters of the asymmetrical minor loop to consider the return-point memory effect.FindingsThe comparison of simulation and experimental results verifies that the proposed parameters calculation method has high accuracy and strong universality.Originality/valueThe proposed parameter calculation method improves the existing parameter calculation method’s problem of relying on too much experimental data and inaccuracy. Consequently, the presented work facilitates the application of the finite element electromagnetic field analysis method coupling the hysteresis model.

Non-invertible symmetries and RG flows in the two-dimensional O(n) loop model

In a recent paper, Gorbenko and Zan [1] observed that O(n) symmetry alone does not protect the well-known renormalization group flow from the dilute to the dense phase of the two-dimensional O(n) model under thermal perturbations. We show in this paper that the required “extra protection” is topological in nature, and is related to the existence of certain non-invertible topological defect lines. We define these defect lines and discuss the ensuing topological protection, both in the context of the O(n) lattice model and in its recently understood continuum limit, which takes the form of a conformal field theory governed by an interchiral algebra.

A critical signal for phenotype transition driven by negative feedback loops

The biological rhythms governed by negative feedback loops have undergone extensive investigation. However, developing reliable and versatile warning signals to predict periodic fluctuations in physiological processes and behaviors associated with these rhythms remains a challenge. Here, we monitored the heart rate and tracked ovulation dates of 91 fertile women. The finding strongly links the velocity (derivative) of heart rate with ovulation in menstrual cycles, providing a predictive warning signal. Similarly, an analysis of calcium signaling in the suprachiasmatic nucleus (SCN) of mice reveals that the maximum velocity of rising calcium signal aligns with locomotor activity offsets. To demonstrate the generality of derivative-transitions link, numerical simulations using a negative feedback loop model were conducted. Statistical analysis indicated that over 90% of the oscillations exhibited a correlation between maximum velocity and transition points. Consequently, the maximum velocity derived from oscillatory curves holds significant potential as an early warning signal for critical transitions.

Modeling and design of a photovoltaic‐fed single‐ended primary‐inductor converter for maximum power point tracking with current mode control

SummaryIn this work, the control of a Single‐Ended Primary‐Inductor Converter (SEPIC) supplied from a photovoltaic energy source and linked at its output to a DC current sink is addressed. The system is used for maximum power point tracking under varying environmental conditions. A strategy based on two loops of control is considered. A peak current mode controller is used for the inner loop, and a Proportional‐Integral (PI) controller is used for the outer voltage loop. Then, a comprehensive time‐domain and frequency‐domain modeling of the inner loop is theoretically addressed and then verified by the switched model of the system implemented in PSIM© software. The obtained results show that the system exhibits accurate tracking of the desired PV voltage while guaranteeing a fast maximum power point tracking under sudden changes in the environmental conditions. The mathematical modeling, design procedures, and the numerical simulations are validated using experimental results obtained from a laboratory prototype.

Tuning the magnetic properties of doped ZnS using transition metal doping: A multi-scale computational approach

Transition metal (TM)-doped dilute magnetic semiconductors (DMS) have emerged as promising materials for spintronic applications such as spin-polarized transport and information storage. However, achieving robust room-temperature ferromagnetism in DMS remains a key challenge. This work undertakes a comprehensive investigation of the effects of Ti- and Cr-doping and (Ti,Cr)-codoping on the structural, electronic, and magnetic properties of wurtzite ZnS using first-principles pseudopotential plane-wave self-consistent field calculations and Monte Carlo simulations. The first-principles DFT calculations were performed using the spin-polarized GGA+U approach to account for strong electron–electron interactions. Structural relaxations revealed expanded lattice parameters and bond lengths for the doped systems compared to pure ZnS, attributed to the larger ionic radii of the dopants. Formation energy calculations confirmed the thermodynamic stability of doping. The band structure and density of states analysis demonstrated the half-metallic nature of the doped ZnS systems with 100% spin polarization induced by strong hybridization between the TM-3d and S-3p states. This mediates robust ferromagnetic coupling, with total magnetic moments around 4-8 μB/cell depending on dopant type and concentration. To complement the zero-temperature DFT results, temperature-dependent Monte Carlo simulations using the single-spin flip Heat Bath algorithm were implemented. The modeling of magnetization, susceptibility, specific heat, and hysteresis loops enabled extracting Curie temperatures up to 427.6 K for 12.5% Cr-doped ZnS. The synergistic combination of first-principles DFT and Monte Carlo computational techniques provides significant insights into tailoring the magnetic properties of TM-doped ZnS dilute magnetic semiconductors. The tunability of structural, electronic, and magnetic characteristics through control of dopant selection and concentration demonstrates the promising potential of transition metal-doped ZnS for spintronic devices operable at room-temperature.

Optimal analytical cascade control for FOPDT systems

This paper proposes a novel control strategy based on optimal Linear Quadratic Regulator (LQR) design applied to cascade systems with stable, integrative, and unstable First Order plus Dead-Time (FOPDT) outer loop models. The secondary (inner) and primary (outer) loop controller designs are performed using the Simplified Filtered Smith Predictor (SFSP). The optimal analytical design is derived from a novel strategy where the pole of the internal loop is placed so that the LQR criterion can be achieved with a simple tuning of the external loop. In contrast to related work, the secondary controller is designed using an SFSP control structure to nominally achieve optimal LQR performance and accelerated rejection of disturbances acting on the inner-loop process. To illustrate the usefulness of the proposed design, we evaluated the strategy in different scenarios, showing the optimality and performance of the analytical design.

Nesting Statistics in the O(n) Loop Model on Random Planar Maps

In the O(n) loop model on random planar maps, we study the depth—in terms of the number of levels of nesting—of the loop configuration, by means of analytic combinatorics. We focus on the ‘refined’ generating series of pointed disks or cylinders, which keep track of the number of loops separating the marked point from the boundary (for disks), or the two boundaries (for cylinders). For the general O(n) loop model, we show that these generating series satisfy functional relations obtained by a modification of those satisfied by the unrefined generating series. In a more specific O(n) model where loops cross only triangles and have a bending energy, we explicitly compute the refined generating series. We analyse their non generic critical behavior in the dense and dilute phases, and obtain the large deviations function of the nesting distribution, which is expected to be universal. Using the framework of Liouville quantum gravity (LQG), we show that a rigorous functional KPZ relation can be applied to the multifractal spectrum of extreme nesting in the conformal loop ensemble (CLEκ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{CLE}_{\\kappa }$$\\end{document}) in the Euclidean unit disk, as obtained by Miller et al. (Ann Probab 44(2):1013–1052, 2016, arXiv:1401.0217), or to its natural generalisation to the Riemann sphere. It allows us to recover the large deviations results obtained for the critical O(n) random planar map models. This offers, at the refined level of large deviations theory, a rigorous check of the fundamental fact that the universal scaling limits of random planar map models as weighted by partition functions of critical statistical models are given by LQG random surfaces decorated by independent CLEs.

A Current Loop Model for the Fast Simulation of Ferrofluids.

Ferrofluids are oil-based liquids containing magnetic particles that interact with magnetic fields without solidifying. Leveraging the exploration of new applications of these promising materials (such as in optics, medicine and engineering) requires high fidelity modeling and simulation capabilities in order to accurately explore ferrofluids in silico. While recent work addressed the macroscopic simulation of large-scale ferrofluids using smoothed-particle hydrodynamics (SPH), such simulations are computationally expensive. In their work, the Kelvin force model has been used to calculate interactions between different SPH particles. The application of this model results in a force pointing outwards with respect to the fluid surface causing significant levitation problems. This drawback limits the application of more advanced and efficient SPH frameworks such as divergence-free SPH (DFSPH) or implicit incompressible SPH (IISPH). In this contribution, we propose a current loop magnetic force model which enables the fast macroscopic simulation of ferrofluids. Our new force model results in a force term pointing inwards allowing for more stable and fast simulations of ferrofluids using DFSPH and IISPH.

Ab Initio Prediction of 3-D Conformations for Protein Long Loops with High Accuracy and Applications to Antibody CDRH3 Modeling.

Residue-level potentials of mean force were widely used for protein backbone refinements to avoid simultaneous sampling of side-chain conformations. The interaction energy between the reduced side chains and backbone atoms was not considered explicitly. In this study, we developed novel methods to calculate the residue-atom interaction energy in combination with atomic and residue-level terms. The parameters were optimized step by step to remove the overcounting or overlap problem between different energy terms. The mixing energy functions were then used to evaluate the generated backbone conformations at the initial sampling stage of protein loop modeling (OSCAR-loop), including the interaction energy between the reduced loop residues and full atoms of the protein framework. The accuracies of top-ranked decoys were 1.18 and 2.81 Å for 8-residue and 12-residue loops, respectively. We then selected diverse decoys for side-chain modeling, backbone refinement, and energy minimization. The procedure was repeated multiple times to select one prediction with the lowest energy. Consequently, we obtained an accuracy of 0.74 Å for a prevailing test set of 12-residue loops, compared with >1.4 Å reported by other researchers. The OSCAR-loop was also effective for modeling the H3 loops of antibody complementary determining regions (CDRs) in the crystal environment. The prediction accuracy of OSCAR-loop (1.74 Å) was better than the accuracy of the Rosetta NGK method (3.11 Å) or those achieved by deep learning methods (>2.2 Å) for the CDRH3 loops of 49 targets in the Rosetta antibody benchmark. The performance of OSCAR-loop in a model environment was also discussed.

Study on the transport and internalisation mechanism of dietary supplement nattokinase in the small intestine using animal and Caco-2 cell monolayer models

Maintaining proper blood flow is critical to promoting good health. Nattokinase is a serine protease from Bacillus subtilis that has significant in vitro thrombolytic activity, but its mechanism as a dietary supplement to prevent thrombosis through intestinal absorption and transport is still unclear. The purpose of this study is to study the transport and internalisation mechanism of NK in the small intestine using animal models and Caco-2 cell monolayer models. This study first evaluated the preventive effect of supplementing low dose (4000 FU (Fibrin Unit)/kg, n = 6), medium dose (8000 FU/kg, n = 6), and high dose (12000 FU/kg, n = 6) of nattokinase on carrageenan induced thrombosis in mice. Subsequently, we used the rat gut sac model, ligated intestinal loop model, and Caco-2 cell uptake model to study the intestinal transport mechanism of NK. Results indicate that NK is a moderately absorbed biomolecule whose transport through enterocytes is energy- and time-dependent. Chlorpromazine, nystatin and EIPA all inhibited the endocytosis of NK to varying degrees, indicating that the endocytosis of NK in Caco-2 cells involves macropinocytosis, clathrin-mediated and caveolae-mediated pathway. These findings offer a theoretical basis for investigating the mechanism of oral NK supplementation in greater depth.

CASP15 cryo-EM protein and RNA targets: Refinement and analysis using experimental maps.

CASP assessments primarily rely on comparing predicted coordinates with experimental reference structures. However, experimental structures by their nature are only models themselves-their construction involves a certain degree of subjectivity in interpreting density maps and translating them to atomic coordinates. Here, we directly utilized density maps to evaluate the predictions by employing a method for ranking the quality of protein chain predictions based on their fit into the experimental density. The fit-based ranking was found to correlate well with the CASP assessment scores. Overall, the evaluation against the density map indicated that the models are of high accuracy, and occasionally even better than the reference structure in some regions of the model. Local assessment of predicted side chains in a 1.52 Å resolution map showed that side-chains are sometimes poorly positioned. Additionally, the top 118 predictions associated with 9 protein target reference structures were selected for automated refinement, in addition to the top 40 predictions for 11 RNA targets. For both proteins and RNA, the refinement of CASP15 predictions resulted in structures that are close to the reference target structure. This refinement was successful despite large conformational changes often being required, showing that predictions from CASP-assessed methods could serve as a good starting point for building atomic models in cryo-EM maps for both proteins and RNA. Loop modeling continued to pose a challenge for predictors, and together with the lack of consensus amongst models in these regions suggests that modeling, in combination with model-fit to the density, holds the potential for identifying more flexible regions within the structure.

Comprehensive assessment of protein loop modeling programs on large-scale datasets: prediction accuracy and efficiency.

Protein loops play a critical role in the dynamics of proteins and are essential for numerous biological functions, and various computational approaches to loop modeling have been proposed over the past decades. However, a comprehensive understanding of the strengths and weaknesses of each method is lacking. In this work, we constructed two high-quality datasets (i.e. the General dataset and the CASP dataset) and systematically evaluated the accuracy and efficiency of 13 commonly used loop modeling approaches from the perspective of loop lengths, protein classes and residue types. The results indicate that the knowledge-based method FREAD generally outperforms the other tested programs in most cases, but encountered challenges when predicting loops longer than 15 and 30 residues on the CASP and General datasets, respectively. The ab initio method Rosetta NGK demonstrated exceptional modeling accuracy for short loops with four to eight residues and achieved the highest success rate on the CASP dataset. The well-known AlphaFold2 and RoseTTAFold require more resources for better performance, but they exhibit promise for predicting loops longer than 16 and 30 residues in the CASP and General datasets. These observations can provide valuable insights for selecting suitable methods for specific loop modeling tasks and contribute to future advancements in the field.

Research on optimization scheme for boiling heat transfer models of mini-channels casing-pipes once-through steam generator

The mini-channels casing-pipes once-through steam generator(MCOTSG) is used for a certain type of small modular reactor. The boiling heat transfer model is crucial to the accuracy of simulating the heat transfer process on the secondary loop of MCOTSG. In this paper, the heat transfer tubes of MCOTSG are taken as the research object. The thermal–hydraulic model of primary and secondary loops is established based on the RELAP5 program. Then the different nucleate boiling heat transfer models are calibrated and analyzed based on the experimental results of the steady state under low flow rate conditions. On this basis, the secondary loop heat transfer characteristics and the overall operating characteristics of OTSG under the transient state of feedwater flow rate reduction are simulated. The results of the steady state and transient state analysis show that the revised model that the Bertsch correlation is used to correct the Chen correlation performs the best in terms of computational stability and computational accuracy. The results of the study can provide a basis for the safety analysis and optimal design of MCOTSG and small modular reactor under low flow rate conditions.

Modeling of a Broadband Microwave Composite Thin Film Absorber.

Composite thin film absorbers show superior performance and have a wide range of applications. Obtaining a broadband composite thin film absorber is a challenge. In this work, we proposed a modeling of a broadband microwave composite thin film absorber based on the impedance matching theory and equivalent circuit model of the square loop. The unit cell of the absorber was composed of metal square loops with high magnetic conductivity deposited on the polyethylene substrate, and an FR-4 (epoxy glass cloth) substrate was the spacer substrate layer. The simulation results show that the absorptivity of the absorber reached more than 90% in the frequency range of 8.7-18 GHz for TE and TM waves under normal incidence. The thickness of the designed absorber was 2.05 mm (0.059 λmax, λmax corresponds to the maximum absorption wavelength). The simulation results show that the energy distribution in the proposed absorber was mainly localized in the top metal FSS layer due to the ohmic loss of metal, and the dielectric loss played a small role in the absorption of the absorber. Our work provides a design approach to improve the efficiency of optoelectronic devices and thermal detectors and has application prospects in radar and aircraft stealth applications.