Generic Model Research Articles

In-plane magnetization orientation driven topological phase transition in OsCl3 monolayer

Abstract The quantum anomalous Hall effect resulting from the in-plane magnetization in the OsCl3 monolayer is shown to exhibit different electronic topological phases determined by the crystal symmetries and magnetism. In this Chern insulator, the Os-atoms form a two dimensional planar honeycomb structure with an easy-plane ferromagnetic configuration and the required non-adiabatic paths to tune the topology of electronic structure exist for specific magnetic orientations based on mirror symmetries of the system. Using density functional theory (DFT) calculations, these tunable phases are identified by changing the orientation of the magnetic moments. We argue that in contrast to the buckled system, here the Cl-ligands bring non-trivial topology into the system by breaking the in-plane mirror symmetry. The interplay between the magnetic anisotropy and electronic band-topology changes the Chern number and hence the topological phases. Our DFT study is corroborated with comprehensive analysis of relevant symmetries as well as a detailed explanation of topological phase transitions using a generic tight binding model.

Angular acceleration estimation and aerodynamic parameter identification based on angular velocity equivalent model

Conventional angular acceleration estimation methods generate non-negligible errors when the control surface rapidly deflects; hence, the estimated angular acceleration cannot be used for aerodynamic parameter identification directly. This paper proposes an angular acceleration estimation method based on angular velocity equivalent model. The angular acceleration of the angular velocity equivalent model, whose angular velocity response is consistent with the flight test data, is used as the estimated angular acceleration. Firstly, the equivalent angular velocity model is established by combining the generic aerodynamic model with the rotational dynamic equations of aircraft. Secondly, the angular velocity data and the control surface deflection data are synchronized. Finally, the angular velocity response of the equivalent model is used as the predictor, and the estimated angular acceleration is obtained by extended Kalman filter. The aerodynamic parameter identification and validation are carried out using the estimated angular acceleration of a large civil aircraft flight test data. The results show that the angular acceleration obtained through the proposed angular acceleration estimation method meets the accuracy requirement of aerodynamic parameter identification.

Dynamics of Vortex Structures: From Planets to Black Hole Accretion Disks

Thermo-vortices (bright spots, blobs, swirls) in cosmic fluids (planetary atmospheres, or even black hole accretion disks) are sometimes observed as clustered into quasi-symmetrical quasi-stationary groups but conceptualized in models as autonomous items. We demonstrate—using the (analytical) Sharp Boundaries Evolution Method and a generic model of a thermo-vorticial field in a rotating “thin” fluid layer in a spacetime that may be curved or flat—that these thermo-vortices may be not independent but represent interlinked parts of a single, coherent, multi-petal macro-structure. This alternative conceptualization may influence the designs of numerical models and image-reconstruction methods.

Evaluation and instantiation of a generic process model for early-stage sustainable product-service system design within three manufacturing companies

Although product-service systems (PSS) have been in focus in literature and industry for some years, no generically agreed or applied PSS design process exists thus far, in contrast to the neighbouring fields of product development or service design, respectively. This paper presents the evaluation and instantiation of a recently proposed generic process model (GPM) for early-stage sustainable PSS design in capital goods manufacturing companies. The model was applied in three case studies with an aim to quantitatively and qualitatively evaluate the GPM concerning eight criteria, and study its instantiation process actions to a company-specific model while simultaneously identifying and proposing solutions for challenges to instantiation. Based on observation and feedback received from the companies, the GPM shows promise for widespread applicability, aided by proposed guidelines for instantiating the GPM to company-specific contexts, as also described in this paper. These guidelines aim to facilitate the translation of the GPM into pragmatic models for practitioners in the field of PSS design, thus increasing its chances of successful implementation as well as impact.

Generic model with unconventional Rashba bands and giant spin galvanic effect

Generic model with unconventional Rashba bands and giant spin galvanic effect

Prevalence and mortality of haemophagocytic lymphohistiocytosis in dengue fever: a systematic review and meta-analysis.

Haemophagocytic lymphohistiocytosis (HLH) is a rare complication of dengue fever with potentially life-threatening consequences and high mortality. Therefore, this study aims to investigate the prevalence, management and outcome of HLH in dengue fever. The major electronic databases, including PubMed, ScienceDirect and Ovid SP, were searched from inception until 31 January 2024 to identify relevant studies. Pooled prevalence and mortality were calculated using the random-effects generic inverse variance model with a 95% CI. All the statistical analysis was conducted using R programming. A total of nine studies with 157 patients with HLH, 576 patients with severe dengue and 5081 patients with dengue fever were included in this meta-analysis. The prevalence of HLH in severe dengue (22.1%, 95% CI 8.07 to 48.0%) was significantly higher than the prevalence in dengue fever (3.12%, 95% CI 0.37 to 21.9%). The prevalence of HLH in severe dengue was higher in the paediatric population (22.8%, 95% CI 3.9 to 68.4%) compared with the adult population (19.0%, 95% CI 3.0 to 63.9%). The overall mortality rate was 20.2% (95% CI 9.7 to 37.2%). The prevalence of dengue-associated HLH was low in patients with dengue fever but is significantly higher in patients with severe dengue and a high mortality rate.

Systematic evaluation of high-throughput PBK modelling strategies for the prediction of intravenous and oral pharmacokinetics in humans.

Physiologically based kinetic (PBK) modelling offers a mechanistic basis for predicting the pharmaco-/toxicokinetics of compounds and thereby provides critical information for integrating toxicity and exposure data to replace animal testing with in vitro or in silico methods. However, traditional PBK modelling depends on animal and human data, which limits its usefulness for non-animal methods. To address this limitation, high-throughput PBK modelling aims to rely exclusively on in vitro and in silico data for model generation. Here, we evaluate a variety of in silico tools and different strategies to parameterise PBK models with input values from various sources in a high-throughput manner. We gather 2000 + publicly available human in vivo concentration-time profiles of 200 + compounds (IV and oral administration), as well as in silico, in vitro and in vivo determined compound-specific parameters required for the PBK modelling of these compounds. Then, we systematically evaluate all possible PBK model parametrisation strategies in PK-Sim and quantify their prediction accuracy against the collected in vivo concentration-time profiles. Our results show that even simple, generic high-throughput PBK modelling can provide accurate predictions of the pharmacokinetics of most compounds (87% of Cmax and 84% of AUC within tenfold). Nevertheless, we also observe major differences in prediction accuracies between the different parameterisation strategies, as well as between different compounds. Finally, we outline a strategy for high-throughput PBK modelling that relies exclusively on freely available tools. Our findings contribute to a more robust understanding of the reliability of high-throughput PBK modelling, which is essential to establish the confidence necessary for its utilisation in Next-Generation Risk Assessment.

Tracking the Cellular Degradation of Silver Nanoparticles: Development of a Generic Kinetic Model.

Understanding the degradation of nanoparticles (NPs) after crossing the cell plasma membrane is crucial in drug delivery designs and cytotoxicity assessment. However, the key factors controlling the degradable kinetics remain unclear due to the absence of a quantification model. In this study, subcellular imaging of silver nanoparticles (AgNPs) was used to determine the intracellular transfer of AgNPs, and single particle ICP-MS was utilized to track the degradation process. A cellular kinetic model was subsequently developed to describe the uptake, transfer, and degradation behaviors of AgNPs. Our model demonstrated that the intracellular degradation efficiency of AgNPs was much higher than that determined by mimicking testing, and the degradation of NPs was highly influenced by cellular factors. Specifically, deficiencies in Ca or Zn primarily decreased the kinetic dissolution of NPs, while a Ca deficiency also resulted in the retardation of NP transfer. The biological significance of these kinetic parameters was strongly revealed. Our model indicated that the majority of internalized AgNPs dissolved, with the resulting ions being rapidly depurated. The release of Ag ions was largely dependent on the microvesicle-mediated route. By changing the coating and size of AgNPs, the model results suggested that size influenced the transfer of NPs into the degradation process, whereas coating affected the degradation kinetics. Overall, our developed model provides a valuable tool for understanding and predicting the impacts of the physicochemical properties of NPs and the ambient environment on nanotoxicity and therapeutic efficacy.

Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes

Abstract. The newly developed offline land ecosystem model Terrestrial Ecosystem Model in R (TEMIR) version 1.0 is described here. This version of the model simulates plant ecophysiological (e.g., photosynthetic and stomatal) responses to varying meteorological conditions and concentrations of CO2 and ground-level ozone (O3) based on prescribed meteorological and atmospheric chemical inputs from various sources. Driven by the same meteorological data used in the GEOS-Chem chemical transport model, this allows asynchronously coupled experiments with GEOS-Chem simulations with unique coherency for investigating biosphere–atmosphere chemical interactions. TEMIR agrees well with FLUXNET site-level gross primary productivity (GPP) in terms of both the diurnal and monthly cycles (correlation coefficients R2>0.85 and R2>0.8, respectively) for most plant functional types (PFTs). Grass and shrub PFTs have larger biases due to generic model representations. The model performs best when driven by local site-level meteorology rather than reanalyzed gridded meteorology. Simulation using gridded meteorology agrees well for annual GPP in seasonality and spatial distribution with a global average of 134 Pg C yr−1. Application of Monin–Obukhov similarity theory to infer canopy conditions from gridded meteorology does not improve model performance, predicting an increase of +7 % in global GPP. Present-day O3 concentrations simulated by GEOS-Chem and an O3 damage scheme at high sensitivity show a 2 % reduction in global GPP with prominent reductions of up to 15 % in eastern China and the eastern USA. Regional correlations are generally unchanged when O3 is present and biases are reduced, especially for regions with high O3 damage. An increase in atmospheric CO2 concentration of 20 ppmv from the level in 2000 to the level in 2010 modestly decreases O3 damage due to reduced stomatal uptake, consistent with ecophysiological understanding. Our work showcases the utility of this version of TEMIR for evaluating biogeophysical responses of vegetation to changes in atmospheric composition and meteorological conditions.

3D hand pose and mesh estimation via a generic Topology-aware Transformer model.

In Human-Robot Interaction (HRI), accurate 3D hand pose and mesh estimation hold critical importance. However, inferring reasonable and accurate poses in severe self-occlusion and high self-similarity remains an inherent challenge. In order to alleviate the ambiguity caused by invisible and similar joints during HRI, we propose a new Topology-aware Transformer network named HandGCNFormer with depth image as input, incorporating prior knowledge of hand kinematic topology into the network while modeling long-range contextual information. Specifically, we propose a novel Graphformer decoder with an additional Node-offset Graph Convolutional layer (NoffGConv). The Graphformer decoder optimizes the synergy between the Transformer and GCN, capturing long-range dependencies and local topological connections between joints. On top of that, we replace the standard MLP prediction head with a novel Topology-aware head to better exploit local topological constraints for more reasonable and accurate poses. Our method achieves state-of-the-art 3D hand pose estimation performance on four challenging datasets, including Hands2017, NYU, ICVL, and MSRA. To further demonstrate the effectiveness and scalability of our proposed Graphformer Decoder and Topology aware head, we extend our framework to HandGCNFormer-Mesh for the 3D hand mesh estimation task. The extended framework efficiently integrates a shape regressor with the original Graphformer Decoder and Topology aware head, producing Mano parameters. The results on the HO-3D dataset, which contains various and challenging occlusions, show that our HandGCNFormer-Mesh achieves competitive results compared to previous state-of-the-art 3D hand mesh estimation methods.

How reliable are femoropelvic kinematics during deep squats? The influence of subject-specific skeletal modelling on measurement variability

BackgroundBiplanar radiography displays promising results in the production of subject-specific (S.specific) biomechanical models. However, the focus has predominantly centred on methodological investigations in gait analysis. Exploring the influence of such models on the analysis of high range of motion tasks linked to hip pathologies is warranted. The aim of this study is to investigate the effect of S.Specific modelling techniques on the reliability of deep squats kinematics in comparison to generic modelling. Methods8 able-bodied male participants attended 5 motion capture sessions conducted by 3 observers and performed 5 deep squats in each. Prior to each session a biplanar scan was acquired with the reflective-markers attached. Inverse kinematics of pelvis and thigh segments were calculated based on S.specific and Generic model definition. Agreement between the two models femoropelvic orientation in standing was assessed with Bland-Altman plots and paired t- tests. Inter-trial, inter-session, inter-observer variability and observer/trial difference and ratio were calculated for squat kinematic data derived from the two modelling approaches. ResultsCompared to the Generic model, the S.Specific model produced a calibration trial that is significantly offset into more posterior pelvis tilt (-2.8±2.7), hip extension (-2.2±3.8), hip abduction (-1.2±3.6) and external rotation (-13.8±11.4). The S.specific model produced significantly different squat kinematics in the sagittal plane of the pelvis (entire squat cycle) and hip (between 40-60% of the squat cycle). Variability analysis indicated that the error magnitude between the two models was comparable (difference<2°). The S.specific model exhibited a lower variability in the observer/trial ratio in the sagittal pelvis and hip, the frontal hip, but showed a higher variability in the transverse hip. SignificanceS.specific modelling appears to introduce a calibration offset that primarily translates into an effect in the sagittal plane kinematics. However, the clinical added value of S.specific modelling in terms of reducing experimental sources of kinematic variability was limited.

Dynamic network-aware container allocation in Cloud/Fog computing with mobile nodes

The massive adoption of movable devices, created a new use cases such as Internet of Things (IoT), autonomous vehicles, spacecraft computing, etc. Not only end users, but also computing infrastructures can change their location. The applications are composed of many interdependent microservices with specific resource requirements. Latest state of the art in Cloud/Fog infrastructures is considering only the computational and network (latency, bandwidth) resources during scheduling of microservices, but in a static way. The network variability when the nodes are moving in space is not considered. This leads to increased total latency, hindering the Quality of Service (QoS) and network costs. Many researchers are focused only on a theoretical level. This paper proposes a novel technique for network-aware dynamic allocation of interdependent microservices on moving infrastructure nodes, applicable in practice. It is composed of a generic MILP optimization model and implementation in a Cloud/Fog platform. Several examples with sample Edge-Native application are obtained. The results show reduction in the total end-to-end network latency compared to the latest state of the art.

Learning multi-granularity semantic interactive representation for joint low-light image enhancement and super-resolution

Images captured in challenging conditions often suffer from the co-existence of low contrast and low resolution. However, most joint enhancement methods focus on fitting a direct mapping from degraded images to high-quality images, which proves insufficient to handle complex degradation. To mitigate this, we propose a novel semantic prior guided interactive network (MSIRNet) to enable effective image representation learning for joint low-light enhancement and super-resolution. Specifically, a local HE-based domain transfer strategy is developed to remedy the domain gap between low-light images and the recognition scope of a generic segmentation model, thereby obtaining a rich granularity of semantic prior. To represent hybrid-scale features with semantic attributes, we propose a multi-grained semantic progressive interaction module that formulates an omnidirectional blend self-attention mechanism, facilitating deep interaction between diverse semantic knowledge and visual features. Moreover, employing our feature normalized complementary module that perceives context and cross-feature relationships, MSIRNet adaptively integrates image features with the auxiliary visual atoms provided by the Codebook, endowing the model with high-fidelity reconstruction capability. Extensive experiments demonstrate the superior performance of our MSIRNet, showing its ability to restore visually and perceptually pleasing normal-light high-resolution images.

On thermal and strain-rate dependences of polymethacrylimide (PMI) foam materials

Polymethacrylimide (PMI) foams exhibit great potentials in engineering applications thanks to its outstanding lightweight and superior mechanical properties. However, the temperature and loading rate can greatly affect its mechanical behaviors, which are the key factors in analysis and design of the PMI foam structures for practical applications. Unfortunately, there is lack of fundamental data and constitutive models available concerning the elastic-plastic properties of the PMI foam in various stress states at different ambient temperatures and different strain rates. Therefore, this study aims to fill this knowledge gap by generating basic experimental data and providing a generic modeling solution for PMI foam materials and structures. To better reflect the actual service conditions in practice, different stress states are considered under different temperatures and strain rates. The cyclic loads are applied to characterize the actual mechanical responses of the PMI foam where the initial and subsequent yield surfaces were calibrated and analyzed. Following the experimental results, the elasticity, plasticity, viscosity and damage of the PMI foam are investigated thoroughly, especially for the initial and subsequent yielding behaviors. Further, the thermal and strain rate dependent constitutive models are established and calibrated based on the in-house experimental data for finite element (FE) modeling. A novel damage model is proposed to replicate the phenomenon of the stiffness degradation in compression. It is found that accurate predictions on the mechanical responses of PMI foam can be achieved under different temperatures and strain rates. This study is anticipated to provide fundamental experimental data and effective constitutive models of PMI foam for real engineering applications, such as lightweight design of sandwich structures under some harsh conditions.

A Generic Model for a Persistent Radio Source around Fast Radio Bursts

The repeated fast radio bursts FRB 121102A and FRB 190520B have been reported, along with a spatially coincident, compact, persistent radio emission. In this paper, we present a parameterized one-zone model, with the basic scenario that a relativistic magnetized wind from the pulsar sweeps up the surroundings, e.g., freely expanding supernova ejecta, giving rise to a power-law distribution of electrons between the forward shock and the termination shock. We show that via appropriate adjustment of the model parameters, we can obtain synchrotron radio emission properties from the one-zone model bright enough to account for the observation, simply and analytically fitting the observed spectra well. Through dynamical evolution of the model, we can also obtain time-varying relevant properties. This parameterized model does not depend on concrete physical models such as a central engine; instead, we can constraint the physical model via comparison between parameters and observations, indicating the information about the central engine and surroundings. We also discuss the synchrotron self-Compton emission in our scenario in the end but find no clue about the counterparts at other wave bands.

A multi-stage optimization of battery electric bus transit with battery degradation

Battery electric buses (BEBs) are appealing to transit operators for their elevated comfort, low noise, and zero tailpipe emissions. However, the degradation of BEB batteries over time challenges their performance and necessitates infrastructure adjustments. This study develops a generic multi-stage optimization model for BEB systems. The model addresses the dynamic influence of BEB battery degradation rates on the optimal BEB system configuration and operation, including component sizing, charging infrastructure allocation, BEB charging schedule, and battery replacement throughout the BEB usage lifecycle. A surrogate model-based space mapping (SMSM) algorithm is employed to address the inherent nonlinearity of incorporating battery degradation rates within the developed model. The model is tested on a real-world, multi-hub transit network, and the results highlight significant implications of battery degradation on the optimal spatiotemporal allocation of charging infrastructure, charging schedules, and battery replacement decisions throughout the 12-year BEB usage lifecycle. Sensitivity analysis highlights the influence of operational conditions on total system cost, indicating a 16.3 % increase in cost with a 50 % rise in both energy consumption rates and time-of-use (ToU) tariffs. Overall, the proposed model is a valuable decision-making tool for transit operators navigating BEB transit system planning.

Prediction of horizontal and vertical turning maneuvers of a generic submarine model by closed-form solutions and CFD

Turning maneuvering performance of a generic submarine in both the horizontal and vertical planes is investigated using closed-form (analytical) solutions and the Computational Fluid Dynamics (CFD) method. The aim is to provide a simple yet improvable method throughout the design phase of an underwater vehicle. Both the turning circle maneuver in the horizontal plane and the rising maneuver in the vertical plane are performed. Vehicle trajectories are obtained using closed-form solutions and a linearized maneuvering model with a limited set of hydrodynamic coefficients computed from the CFD model. The derivation of the closed-form solution is based on the basic mechanical principles of steady circular motion, while the hydrodynamic coefficients are determined via steady CFD simulations using a single grid topology. The steady turning diameter serves as the figure of merit in a turning circle maneuver. For the rising maneuver, trajectories predicted by both methods are directly compared. The methods are found to be in good agreement for both maneuvers. Maneuvering predictions made with the linear coefficient set are also open to development. As the design of the submarine evolve, nonlinear and coupled effects can be included in the mathematical model by incorporating related hydrodynamic coefficients to obtain more accurate results.

The Hidden Hand of Asymptomatic Infection Hinders Control of Neglected Tropical Diseases: A Modeling Analysis.

Neglected tropical diseases are responsible for considerable morbidity and mortality in low-income populations. International efforts have reduced their global burden, but transmission is persistent and case-finding-based interventions rarely target asymptomatic individuals. We develop a generic mathematical modeling framework for analyzing the dynamics of visceral leishmaniasis in the Indian sub-continent (VL), gambiense sleeping sickness (gHAT), and Chagas disease and use it to assess the possible contribution of asymptomatics who later develop disease (pre-symptomatics) and those who do not (non-symptomatics) to the maintenance of infection. Plausible interventions, including active screening, vector control, and reduced time to detection, are simulated for the three diseases. We found that the high asymptomatic contribution to transmission for Chagas and gHAT and the apparently high basic reproductive number of VL may undermine long-term control. However, the ability to treat some asymptomatics for Chagas and gHAT should make them more controllable, albeit over relatively long time periods due to the slow dynamics of these diseases. For VL, the toxicity of available therapeutics means the asymptomatic population cannot currently be treated, but combining treatment of symptomatics and vector control could yield a quick reduction in transmission. Despite the uncertainty in natural history, it appears there is already a relatively good toolbox of interventions to eliminate gHAT, and it is likely that Chagas will need improvements to diagnostics and their use to better target pre-symptomatics. The situation for VL is less clear, and model predictions could be improved by additional empirical data. However, interventions may have to improve to successfully eliminate this disease.

Using Passive Surveillance to Maintain Elimination as a Public Health Problem for Neglected Tropical Diseases: A Model-Based Exploration.

Great progress is being made toward the goal of elimination as a public health problem for neglected tropical diseases such as leprosy, human African trypanosomiasis, Buruli ulcer, and visceral leishmaniasis, which relies on intensified disease management and case finding. However, strategies for maintaining this goal are still under discussion. Passive surveillance is a core pillar of a long-term, sustainable surveillance program. We use a generic model of disease transmission with slow epidemic growth rates and cases detected through severe symptoms and passive detection to evaluate under what circumstances passive detection alone can keep transmission under control. Reducing the period of infectiousness due to decreasing time to treatment has a small effect on reducing transmission. Therefore, to prevent resurgence, passive surveillance needs to be very efficient. For some diseases, the treatment time and level of passive detection needed to prevent resurgence is unlikely to be obtainable. The success of a passive surveillance program crucially depends on what proportion of cases are detected, how much of their infectious period is reduced, and the underlying reproduction number of the disease. Modeling suggests that relying on passive detection alone is unlikely to be enough to maintain elimination goals.

The potential impact of the new ‘Right to Repair’ rules on electrical and electronic equipment waste: A case study of the UK

Every year an estimated two million tonnes of waste electrical and electronic equipment (WEEE) are discarded by householders and companies in the United Kingdom (UK). While the UK has left the European Union (EU), its waste-related policies still mirror those of the EU, including the WEEE-related policies. Motivated by the recent introduction the so-called ‘Right to Repair’ policy for electrical and electronic equipment (EEE) across the EU and UK, this paper aims to demonstrate that, depending on the commitment and behavioural changes by the consumers and the government, the future of the WEEE management of the UK will vary. To this end, focusing on landfilled WEEE reduction we develop a generic system dynamics model and apply it to eleven WEEE categories. They depict the flow of EEE and WEEE representing the interaction among the stakeholders (e.g., consumers and producers of EEE) and relevant government regulations of the UK. Our four scenario analyses find that longer use of EEE and better WEEE collection seem to be effective in reducing landfilled WEEE, while more reuse and more recycling and recovery have negligible impacts, despite excluding the additional generation of landfilled WEEE as a result of recycling and recovery. Comparing with the business-as-usual scenario, one year longer EEE use and 10% more of WEEE collection could at maximum reduce landfilled WEEE by 14.05% of monitoring and control instruments and 93.93% of display equipment respectively. Backcasting scenario analyses reveal that significant efforts are required to reduce the targeted amounts.