Loop Model Research Articles

Morphological and Functional Principles Governing the Plasticity Reserve in the Cerebellum: The Cortico-Deep Cerebellar Nuclei Loop Model.

Cerebellar reserve compensates for and restores functions lost through cerebellar damage. This is a fundamental property of cerebellar circuitry. Clinical studies suggest (1) the involvement of synaptic plasticity in the cerebellar cortex for functional compensation and restoration, and (2) that the integrity of the cerebellar reserve requires the survival and functioning of cerebellar nuclei. On the other hand, recent physiological studies have shown that the internal forward model, embedded within the cerebellum, controls motor accuracy in a predictive fashion, and that maintaining predictive control to achieve accurate motion ultimately promotes learning and compensatory processes. Furthermore, within the proposed framework of the Kalman filter, the current status is transformed into a predictive state in the cerebellar cortex (prediction step), whereas the predictive state and sensory feedback from the periphery are integrated into a filtered state at the cerebellar nuclei (filtering step). Based on the abovementioned clinical and physiological studies, we propose that the cerebellar reserve consists of two elementary mechanisms which are critical for cerebellar functions: the first is involved in updating predictions in the residual or affected cerebellar cortex, while the second acts by adjusting its updated forecasts with the current status in the cerebellar nuclei. Cerebellar cortical lesions would impair predictive behavior, whereas cerebellar nuclear lesions would impact on adjustments of neuronal commands. We postulate that the multiple forms of distributed plasticity at the cerebellar cortex and cerebellar nuclei are the neuronal events which allow the cerebellar reserve to operate in vivo. This cortico-deep cerebellar nuclei loop model attributes two complementary functions as the underpinnings behind cerebellar reserve.

Research on the Current Control Strategy of a Brushless DC Motor Utilizing Infinite Mixed Sensitivity Norm

During the brushless DC (BLDC) motor working process, the system encounters inevitable uncertainties. These ambiguities stem from potential fluctuations, random occurrences, measurement inaccuracies, varying operational conditions, environmental shifts such as temperature alterations, among other factors. Uncertainties, an inherent aspect of any real control system, can be broadly classified into two categories: sensor signal uncertainties and discrepancies between the mathematical and actual models due to parameter perturbations. To mitigate the impact of sensor noise and parameter perturbations on the BLDC motor, a robust control strategy utilizing infinite norm mixed sensitivity based on PI control strategy (PI-H∞-MIX) is proposed in this paper. Firstly, the closed-loop control structure and transfer function model of the BLDC motor control system current loop are analyzed based on the current loop circuit topology, and then, the model parameters perturbation is analyzed, and the multiplicative uncertainty bound is given. In addition, the appropriate weighting function is selected to ensure the robustness of the system. In this case, the controller design problem is transformed into the H∞ standard control problem, and then, the system augmentation matrix is established, and the controller is solved by Matlab/Simulink. Finally, the performances of the traditional PI control strategy and the PI-H∞-MIX are compared and analyzed. The results show that (1) the proposed PI-H∞-MIX strategy can improve the control system robustness under the parameter perturbation condition effectively, and (2) the proposed PI-H∞-MIX strategy can suppress the noise signal of the sensor.

The bad and the good of trends in model building and refinement for sparse-data regions: pernicious forms of overfitting versus good new tools and predictions.

Model building and refinement, and the validation of their correctness, are very effective and reliable at local resolutions better than about 2.5 Å for both crystallography and cryo-EM. However, at local resolutions worse than 2.5 Å both the procedures and their validation break down and do not ensure reliably correct models. This is because in the broad density at lower resolution, critical features such as protein backbone carbonyl O atoms are not just less accurate but are not seen at all, and so peptide orientations are frequently wrongly fitted by 90-180°. This puts both backbone and side chains into the wrong local energy minimum, and they are then worsened rather than improved by further refinement into a valid but incorrect rotamer or Ramachandran region. On the positive side, new tools are being developed to locate this type of pernicious error in PDB depositions, such as CaBLAM, EMRinger, Pperp diagnosis of ribose puckers, and peptide flips in PDB-REDO, while interactive modeling in Coot or ISOLDE can help to fix many of them. Another positive trend is that artificial intelligence predictions such as those made by AlphaFold2 contribute additional evidence from large multiple sequence alignments, and in high-confidence parts they provide quite good starting models for loops, termini or whole domains with otherwise ambiguous density.

A Review on the prospects and challenges of integrating IoT technologies in circular business models

In recent times, there has been an increasing imperative to embrace Circular Business Models (CBM) as an indispensable means for enhancing businesses. Nevertheless, existing academic discourse rarely investigates the complex relationship between the Internet of Things (IoT) and CBM. This research paper initiates its investigation by identifying four pivotal IoT capabilities, namely monitoring, tracking, optimisation, and design evolution, all of which are instrumental in enhancing the performance of CBM, as grounded in the ReSOLVE framework. Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines were employed for systematic literature review in order to scrutinise how these identified IoT capabilities contribute to the core concepts of the 6R-CBM and CBM-IoT cross-section heatmaps and relationship frameworks. Finally, a comprehensive examination of the challenges impeding the realisation of IoT-enabled CBM is presented. The findings of this study reveal that Loop and Optimise business models are the predominant subjects of current research endeavours. IoT emerges as a pivotal player in these business models, primarily through its tracking, monitoring, and optimisation capabilities. In contrast, there is a noticeable absence of (quantitative) case studies pertaining to Virtualize, Exchange, and Regenerate CBM. Notably, IoT exhibits the potential to limit energy consumption significantly. However, it is essential to acknowledge that impediments associated with IoT hardware, software, protocol energy consumption, interoperability, security, and financial investments may pose substantial challenges to the broader adoption of IoT within the CBM.

Temporal dynamics of attitude decisions: A test of the iterative reprocessing model using event-related potentials

Although evaluative judgments are a central component of everyday decision making little is known about the temporal dynamics of the processes used to make them. The present study used the high temporal resolution of event-related brain potentials (ERPs) to test Cunningham and Zelazo's (2007) posited differences in the timing of attitude tag retrieval relative to stimulus categorization for ‘attitudes’ and ‘evaluations,’ as well as tenets of their Iterative Reprocessing (IR) loop model. Participants made agree/disagree decisions about their attitudes and You/Not You decisions about their autobiographical memories in separate reaction time (RT) tasks while brain activity was recorded from 32 scalp sites. A median-split analysis on RT was used to separate fast and slow decisions. Decisions about autobiographical stimuli produced the typical results in which retrieval and stimulus categorization occurred together just before the response regardless of decision difficulty. By contrast, the relative timing of tag retrieval and categorization differed with difficulty for attitude decisions as predicted by the model. Fast attitude decisions were processed similarly to fast You decisions with retrieval and categorization timing coupled to the response. Slow attitude decisions, however, differed because, while tag retrieval timing was the same as for fast attitude decisions, post-retrieval processing delayed stimulus categorization and a response by 450 msec. ERP activity over dorsolateral prefrontal cortex (DLPFC) in the pre-response interval was asymmetrical, with greater activity for attitude and autobiographical decisions over left and right hemispheres, respectively, while amplitude and duration increased with decision difficulty for both. Slow attitude decisions alone elicited a reduced pre-response positivity, a correlate of goal-directed response selection. The results provide empirical support for key aspects of Cunningham and Zelazo's (2007) attitude-evaluation dichotomy and the timing of the posited component processes in their IR model as well as novel information about the roles of stored tags and reflective processes in different attitude decisions.

A single framework of precision surveillance of diabetes disease prognosis for better care with collaboration

We present a decision support model for patient-centered precision surveillance that assists clinicians and patients for the whole disease prospect to provide a single operational framework of whole type 2 diabetic person care management while introducing experts in the loop modeling that facilitates data collection. Based on real-world data, the scientific computation shall be adopted with experts’ experiences for providing the patient health education and accessing complication risks thereby easily delineating disease pathways. A decision tree technique is used to build a single framework consisting of every possible diabetes complication in the decision process. Coping with the complex medical system for the prevention of diabetes and diabetic complications, a patient-centered framework gives the patient interactive, transparent and useful information for better communication in the decision process that includes experts’ experience as well as the value of the prediction generated from population-based data.

From combinatorial maps to correlation functions in loop models

In two-dimensional statistical physics, correlation functions of the O(N)O(N) and Potts models may be written as sums over configurations of non-intersecting loops. We define sums associated to a large class of combinatorial maps (also known as ribbon graphs). We allow disconnected maps, but not maps that include monogons. Given a map with nn vertices, we obtain a function of the moduli of the corresponding punctured Riemann surface. Due to the map’s combinatorial (rather than topological) nature, that function is single-valued, and we call it an nn-point correlation function. We conjecture that in the critical limit, such functions form a basis of solutions of certain conformal bootstrap equations. They include all correlation functions of the O(N)O(N) and Potts models, and correlation functions that do not belong to any known model. We test the conjecture by counting solutions of crossing symmetry for four-point functions on the sphere.

Problematizing feedback loops: ‘on’, ‘with’, and ‘beyond’ analytics dashboards in MOOCs

ABSTRACT This paper examines the enactment of feedback in Massive Open Online Courses (MOOCs), focusing on analytics dashboards. Building on scholarship that recognizes data practices as entangled and ‘messy’, the paper problematizes the model of the feedback loop that assumes that analytics dashboards ‘feed back’ data to instructors and/or learners through a singular flow of data processing. By setting out an empirical study that focuses on four MOOCs, in two universities and on two platforms, the paper maps where, when, and how design teams, instructors, and learners are involved in the enactment of feedback through and beyond analytics dashboards. The findings draw on visualizations that highlight complex relations among people and technologies, which include multiple ‘loops’. The paper concludes with questioning the need to capture feedback in a singular loop and suggests prioritizing continued attention to the roles and responsibilities of people – educational designers, instructors, and learners – in MOOCs.

Pressure drop of cemented high-concentration backfill in pipe flow: Loop test, model comparison and numerical simulation

Cemented high-concentration backfill (CHB) is an indispensable solution for mitigating risks associated with underground mining voids and surface tailings ponds. The accurate prediction of pressure drop of CHB in pipe flow is crucial for the design of backfilling systems. In this study, full factorial loop tests were conducted to obtain observed pressure drop data and rheological parameters of CHB, while considering the variables of binder content, solid fraction, and flow velocity. The rheometer method was also utilized to acquire the rheological parameters of CHB for comparison. Three analytical models and one numerical simulation method, which are considered highly accurate in the literature, were employed to predict the pressure drop of CHB in pipe flow. The findings indicate that the Buckingham model and the Darby–Melson model produce identical results as they are fundamentally equivalent. The Swamee–Aggarwal model and the single-phase flow simulation employ a similar mechanism as the Buckingham model, albeit with minor variations in mathematical treatment. The rheological parameters of CHB obtained through the rheometer method are considerably greater than those acquired by the loop test method, leading to significantly higher predicted pressure drop values from both the three analytical models and single-phase flow simulation when compared to the measured values. Whereas the mean deviation of the three analytical models is within 6.5% when employing rheological parameters of CHB determined by the loop test, with the Swamee–Aggarwal model being the most accurate, the mean error of single-phase flow simulation remains within 10%. It is suggested that the rheological parameters of CHB be determined through small-diameter loop testing. The Buckingham model and single-phase flow simulation are subsequently recommended for predicting pressure drop in industrial straight horizontal pipelines and complex piping systems, respectively. The results of this study facilitate the selection of the simplest method for accurately predicting the pressure drop of CHB in pipe flow.

Microporous Polylactic Acid Scaffolds Enable Fluorescence-Based Perfusion Imaging of Intrinsic In Vivo Vascularization.

In vivo tissue engineering (TE) techniques like the AV loop model provide an isolated and well-defined microenvironment to study angiogenesis-related cell interactions. Functional visualization of the microvascular network within these artificial tissue constructs is crucial for the fundamental understanding of vessel network formation and to identify the underlying key regulatory mechanisms. To facilitate microvascular tracking advanced fluorescence imaging techniques are required. We studied the suitability of microporous polylactic acid (PLA) scaffolds with known low autofluorescence to form axial vascularized tissue constructs in the AV loop model and to validate these scaffolds for fluorescence-based perfusion imaging. Compared to commonly used collagen elastin (CE) scaffolds, the total number of vessels and cells in PLA scaffolds was lower. In detail, CE-based constructs exhibited significantly higher vessel numbers on day 14 and 28 (d14: 316 ± 53; d28: 610 ± 74) compared to the respective time points in PLA-based constructs (d14: 144 ± 18; d28: 327 ± 34; each p < 0.05). Analogously, cell counts in CE scaffolds were higher compared to corresponding PLA constructs (d14: 7661.25 ± 505.93 and 5804.04 ± 716.59; d28: 11211.75 + 1278.97 and 6045.71 ± 572.72, p < 0.05). CE scaffolds showed significantly higher vessel densities in proximity to the main vessel axis compared to PLA scaffolds (200-400 µm and 600-800 µm on day 14; 400-1000 µm and 1400-1600 µm on day 28). CE scaffolds had significantly higher cell counts on day 14 at distances from 800 to 2000 µm and at distances from 400 to 1600 µm on day 28. While the total number of vessels and cells in PLA scaffolds were lower, both scaffold types were ideally suited for axial vascularization techniques. The intravascular perfusion of PLA-based constructs with fluorescence dye MHI148-PEI demonstrated dye specificity against vascular walls of low- and high-order branches as well as capillaries and facilitated the fluorescence-based visualization of microcirculatory networks. Fluorophore tracking may contribute to the development of automated quantification methods after 3D reconstruction and image segmentation. These technologies may facilitate the characterization of key regulators within specific subdomains and add to the current understanding of vessel formation in axially vascularized tissue constructs.

Research on the Coupling Effect of Communication Display Interface under Strong Electromagnetic Pulse

In the high-altitude electromagnetic pulse (HEMP) environment, high-intensity broadband electromagnetic pulse energy is transmitted to the display interface circuit through the interconnection cable, causing interference or damage to the internal electronic components and chips, resulting in various damage effects such as the display cannot be displayed normally, and even restart. To investigate the coupling effect of strong electromagnetic pulses on the display interface circuit, the existing field-line coupling model is utilized as the basis of this study, with a specific focus on the VGA interface. The influence of different terminal impedances on the coupling effect is examined, aiming to determine the significance of terminal impedances in the simulation estimation of interface circuit coupling response. A HEMP coupling signal loop model is established based on the signal loop defined in the VGA datasheet, replicating the normal working conditions of VGA. HEMP pulse injection experiments are conducted to compare the response waveforms of the simulated VGA interface equivalent impedance circuit model with the measured data. This allows the accuracy of the established equivalent impedance model to be verified using key parameters.

Smith-Predictor-Based Design of Analytical PI-PD Control for Series Cascade Processes with Time Delay

For series cascade processes with a time delay, such as the first-order with time-delay (FOTD) process, the integral with time-delay (ITD) process, second-order integral with time-delay (SOITD) process, and unstable first-order with time-delay (UFOTD) process, this paper proposes a Smith-predictor-based design of analytical PI-PD control for these series cascade processes with a time delay. Firstly, targeting the common FOTD model in the secondary loop, a controller with a PID structure is designed using the direct synthesis method. Additionally, a Smith-predictor-based PI-PD control structure is adopted for the prevalent process model in the primary loop. Then, expressions representing the relationship between the corresponding controller parameters and the maximum sensitivity (Ms) index are established to facilitate the analytical design of the controllers. Finally, based on simulation experiments, the effectiveness and superiority are validated by using the proposed method.

Transcription factor competition facilitates self-sustained oscillations in single gene genetic circuits.

Genetic feedback loops can be used by cells to regulate internal processes or to keep track of time. It is often thought that, for a genetic circuit to display self-sustained oscillations, a degree of cooperativity is needed in the binding and unbinding of actor species. This cooperativity is usually modeled using a Hill function, regardless of the actual promoter architecture. Furthermore, genetic circuits do not operate in isolation and often transcription factors are shared between different promoters. In this work we show how mathematical modelling of genetic feedback loops can be facilitated with a mechanistic fold-change function that takes into account the titration effect caused by competing binding sites for transcription factors. The model shows how the titration effect facilitates self-sustained oscillations in a minimal genetic feedback loop: a gene that produces its own repressor directly without cooperative transcription factor binding. The use of delay-differential equations leads to a stability contour that predicts whether a genetic feedback loop will show self-sustained oscillations, even when taking the bursty nature of transcription into account.

Hidden Critical Points in the Two-Dimensional O(n>2) Model: Exact Numerical Study of a Complex Conformal Field Theory.

The presence of nearby conformal field theories (CFTs) hidden in the complex plane of the tuning parameter was recently proposed as an elegant explanation for the ubiquity of "weakly first-order" transitions in condensed matter and high-energy systems. In this work, we perform an exact microscopic study of such a complex CFT (CCFT) in the two-dimensional O(n) loop model. The well-known absence of symmetry-breaking of the O(n>2) model is understood as arising from the displacement of the nontrivial fixed points into the complex temperature plane. Thanks to a numerical finite-size study of the transfer matrix, we confirm the presence of a CCFT in the complex plane and extract the real and imaginary parts of the central charge and scaling dimensions. By comparing those with the analytic continuation of predictions from Coulomb gas techniques, we determine the range of validity of the analytic continuation to extend up to n_{g}≈12.34, beyond which the CCFT gives way to a gapped state. Finally, we propose a beta function which reproduces the main features of the phase diagram and which suggests an interpretation of the CCFT as a liquid-gas critical point at the end of a first-order transition line.

Comparative Analysis of Sinusoidal Oscillators with Surface Acoustic Wave Sensor in the Feedback Loop

Surface acoustic wave sensors can be implemented within the feedback loop of sinusoidal oscillators for detecting pollutants. This detection process involves analyzing the variation of oscillator output voltage parameters, such as amplitude and oscillation frequency. However, each oscillator topology has a distinct operating range concerning frequency and component values. Therefore, a comparative analysis is necessary to determine the oscillator with optimal performance to use with the sensor. To obtain results, a surface acoustic wave sensor model was chosen based on a piezoelectric crystal with a resonant frequency of 117.6 MHz, and three sinusoidal oscillator topologies were used: Pierce, Colpitts, and Clapp. The oscillators were simulated with the sensor model in the feedback loop using the Montecarlo method. The simulation occurred in two steps: individually varying each component by +/- 20% with 250 iterations, and simultaneously varying all components by +/- 20% with 1000 iterations. The variables analyzed in the simulations were amplitude, oscillation frequency, and a new parameter indicating the percentage of time there is an oscillation, termed "robustness." As a result, it was determined that all three oscillators generated oscillations in the output voltage, making them viable for use with the sensor. Furthermore, it was discovered that the Clapp oscillator had a robustness of 84.5%, while the Colpitts and Pierce oscillators had a robustness of 56.3% and 49.9%, respectively. Therefore, based on the results presented in this study, the Clapp oscillator is the optimal choice for use with the surface acoustic wave sensor.

Model-free fast integral terminal sliding-mode control method based on improved fast terminal sliding-mode observer for PMSM with unknown disturbances

This paper presents a novel model-free fast integral terminal sliding-mode control (MFFITSMC) method based on an improved fast terminal sliding-mode observer (IFTSMO) for permanent magnet synchronous motor (PMSM) drive system, which can effectively eliminate the impact caused by unknown disturbances, such as parameter perturbations and external disturbances. The PMSM mathematical model with unknown disturbances is first established, and the ultra-local model (ULM) of the PMSM speed loop is constructed. Next, the model-free fast integral terminal sliding-mode controller is designed in the speed loop based on the ULM. Then, the IFTSMO is designed to precisely estimate the unknown term of the ULM, and the estimated unknown term is fed back to the MFFITSMC controller to perform compensation for unknown disturbances in real time. Finally, compared with the proportional–integral (PI) control method and the conventional model-free sliding-mode control (MFSMC) method, the results of simulations and experiments demonstrate that the presented MFFITSMC method reduces the dependence on the precise model and achieves the purpose of anti-disturbance control of the PMSM drive system.

Human-environment feedback and the consistency of proenvironmental behavior.

Addressing global environmental crises such as anthropogenic climate change requires the consistent adoption of proenvironmental behavior by a large part of a population. Here, we develop a mathematical model of a simple behavior-environment feedback loop to ask how the individual assessment of the environmental state combines with social interactions to influence the consistent adoption of proenvironmental behavior, and how this feeds back to the perceived environmental state. In this stochastic individual-based model, individuals can switch between two behaviors, 'active' (or actively proenvironmental) and 'baseline', differing in their perceived cost (higher for the active behavior) and environmental impact (lower for the active behavior). We show that the deterministic dynamics and the stochastic fluctuations of the system can be approximated by ordinary differential equations and a Ornstein-Uhlenbeck type process. By definition, the proenvironmental behavior is adopted consistently when, at population stationary state, its frequency is high and random fluctuations in frequency are small. We find that the combination of social and environmental feedbacks can promote the spread of costly proenvironmental behavior when neither, operating in isolation, would. To be adopted consistently, strong social pressure for proenvironmental action is necessary but not sufficient-social interactions must occur on a faster timescale compared to individual assessment, and the difference in environmental impact must be small. This simple model suggests a scenario to achieve large reductions in environmental impact, which involves incrementally more active and potentially more costly behavior being consistently adopted under increasing social pressure for proenvironmentalism.

How numerical treatments of the transition region modify energy flux into the solar corona

ABSTRACT The large temperature gradients in the solar transition region present a significant challenge to large-scale numerical modelling of the Sun’s atmosphere. In response, a variety of techniques have been developed which modify the thermodynamics of the system. This sacrifices accuracy in the transition region in favour of accurately tracking the coronal response to heating events. Invariably, the modification leads to an artificial broadening of the transition region. Meanwhile, many contemporary models of the solar atmosphere rely on tracking energy flux from the lower atmosphere, through the transition region and into the corona. In this paper, we quantify how the thermodynamic modifications affect the rate of energy injection into the corona. We consider a series of one-dimensional models of atmospheric loops with different numerical resolutions and treatments of the thermodynamics. Then, using Alfvén waves as a proxy, we consider how energy injection rates are modified in each case. We find that the thermodynamic treatment and the numerical resolution significantly modify Alfvén traveltimes, the eigenfrequencies and eigenmodes of the system, and the rate at which energy is injected into the corona. Alarmingly, we find that the modification of the energy flux is frequency dependent, meaning that it may be difficult to compare the effects of different velocity drivers on coronal heating if they are imposed below an under-resolved transition region, even if the sophisticated thermodynamic adaptations are implemented.

A Current Control Method for Grid-Connected Inverters

It is simple to implement conventional current control with a proportional integral (PI) controller. However, system stability and dynamic performance are not perfect, particularly when operating under unfavorable conditions. In this paper, an improved control method is proposed by introducing a compensation unit. The compensation unit can effectively compensate the system’s phase around the crossover frequency, greatly enhancing the system’s phase margin and stability. It is also capable of handling weak-grid conditions. In this paper, the concept of the proposed compensation unit is explained first. Then, the corresponding mathematical model for the current control loop is built, and system bode diagrams for the conventional and proposed methods are compared. Furthermore, the effect of the parameters for the compensation unit is investigated, and an optimization method is proposed to determine optimal parameters. In addition, to handle weak-grid conditions, the proposed scheme is expanded by including the compensation unit in the grid’s feed-forward loop. Finally, an experimental platform is constructed, and the experimental results are presented to validate the proposed method.

Modelling the PbLi flow including tritium transport and permeation with GETTHEM

One of the main challenges to be addressed to achieve a reliable electricity production from the EU DEMO reactor is the realization of a closed fuel cycle, for which a suitable Tritium Extraction and Removal System (TERS) is required. One of the possible technologies identified for the EU DEMO TERS is the Permeator Against Vacuum (PAV): the tritium dissolved in the liquid PbLi flowing within several parallel channels will permeate towards the vacuum pumped on the other side of the channel wall (the membrane).A recently-developed model of the tritium permeation across the membrane in the PAV, involving both transport phenomena in the wall and surface processes, was already used to size the EU DEMO PAV. However, besides the component itself, it is important to properly define the interfaces of the PAV in the TERS, and of the TERS in the entire PbLi and tritium loops. The model of such a complex system is therefore implemented here in the Modelica object-oriented language used by system-level tool GETTHEM, that already includes a model of the PbLi loop. The resulting, lumped-parameter component will be able to capture the thermal-hydraulic behaviour of the PbLi, to model the tritium transport in the fluid and to estimate the tritium permeated flux supplied to the tritium processing. Such a model is tested here on a sub-scale circuit to demonstrate its capability to simulate the operation of the EU DEMO TERS using the GETTHEM code.As the physical parameters of the model are subject to a large uncertainty, an uncertainty propagation analysis is also performed, to have a preliminary quantification of the impact of such uncertainties on the model output and, therefore, on the TERS efficiency, and to drive further investigations of these physical properties. In particular, results show how the uncertainty on the solubility constant of hydrogen in PbLi represents the dominant contribution on the total variance, highlighting the need for a better accuracy of such parameter.