Scaling Model Research Articles

Scaling models for Regreening Africa: enhancing agroecological integration through smallholders’ assets and agency in Kenya

Urgent action is needed to address climate change, land degradation, and biodiversity loss. The Regreening Africa project (2017–2023), recently recognized as a UN World Restoration Flagship, aimed to reverse land degradation over large areas of land for the triple benefit of people, biodiversity, and climate in eight African countries. Based on projections and early lessons learned, the project sought to identify sustainable scaling models to achieve its ambitious targets. The so-called “Asset-Based Community-driven Development (ABCD) in Regreening” project aimed to demonstrate the positive contribution of deliberate community engagement and co-design. The project introduced ABCD sessions to 30 purposively selected community groups in the Regreening intensification sites in western Kenya. ABCD combines a unique set of framings, methods, and processes that focus on people’s assets and agency, and emphasizes the importance of their attitudes toward self and others for sustainable behavior change. To evidence that ABCD intrinsically contributes to sustainable adoption and scaling of Regreening practices, the project developed the F-ACT+ tool to assess the alignment between ABCD and agroecological practices, and collected baseline and endline data from 300 project and 300 non-project participants. Results showed accelerated agroecological integration among ABCD project participants. ABCD participants showed significant improvements in nine agroecological principles and eight system components, particularly in the economic diversification, social values and diets, and knowledge co-creation principles, as well as in the pest and disease, household, and value chain system components. Summary ATT between ABCD and non-ABCD respondents was positive and significant in 10 principles and eight system components. The results support the synergistic contribution of ABCD to projects targeting sustainable behavior change at the individual and collective levels. Due to its focus on outcomes, this study provided limited insight into the specific mechanisms of ABCD, which are the subject of a separate publication on parallel theory-based contribution analysis work.

Coupling cubic equations of state with the concept of entropy scaling to model the viscosity of ionic liquids

This short paper investigates the applicability of our previously developed entropy scaling model to pure ionic liquids and concludes that it can be used without any modification and leads to very satisfactory results when coupled with the Peng-Robinson or Soave-Redlich-Kwong cubic equations of state. For the considered ionic liquids, the average deviations between calculated and experimental viscosities were found to be around 4.6 and 5.8% for the two cubic equations of state, respectively.

Study on pose-based deep learning models for gloss-free Sign Language Translation

Sign Language Translation (SLT) is a challenging task due to its cross-domain nature, different grammars and lack of data. Currently, many SLT models rely on intermediate gloss annotations as outputs or latent priors. Glosses can help models to correctly segment and align signs to better understand the video. How- ever, the use of glosses comes with significant limitations, since obtaining annotations is quite difficult. Therefore, scaling gloss-based models to millions of samples remains impractical, specially considering the scarcity of sign language datasets. In a similar fashion, many models use video data that requires larger models which typically only work on high end GPUs, and are less invariant to signers appearance and context. In this work we propose a gloss-free pose-based SLT model. Using the extracted pose as feature allow fora sign significant reduction in the dimensionality of the data and the size of the model. We evaluate the state of the art, compare available models and develop a keypoint-based Transformer model for gloss-free. SLT, trained on RWTH-Phoenix, a standard dataset for benchmarking SLT models alongside GSL, a simpler laboratory-made Greek Sign Language dataset.

Is the GFR-based scaling approach adequate for predicting pediatric renal clearance of drugs with passive tubular reabsorption? Insights from PBPK modeling.

Empirical maturation models (e.g., Johnson and Rhodin models) for glomerular filtration rate (GFR) are commonly used as scaling factors for predicting pediatric renal clearance, but their predictive performance for drugs featured with tubular reabsorption is poorly understood. This study investigated the adequacy of GFR-based scaling models for predicting pediatric renal clearance in drugs with passive tubular reabsorption by comparing with a mechanistic kidney model (Mech-KiM) that encompasses the physiological processes of glomerular filtration, tubular secretion, and reabsorption. The analysis utilized hypothetical drugs with varying fractions of tubular reabsorption (Freabs), alongside the model drug metronidazole, which has a Freabs of 96%. Our simulations showed that when Freabs is ≤70%, the discrepancies between the GFR-based scaling methods and the Mech-KiM model in predicting pediatric renal clearance were generally within a twofold range throughout childhood. However, for drugs with substantial tubular reabsorption (e.g., Freabs > 70%), discrepancies greater than twofold were observed between the GFR-based scaling methods and the Mech-KiM model in predicting renal clearance for young children. In neonates, the differences ranged from 5- to 10-fold when the adult Freabs was 95%. Pediatric physiologically based pharmacokinetic (PBPK) modeling of metronidazole revealed that using a GFR-based scaling method (Johnson model) significantly overestimated drug concentrations in children under 2 months, whereas utilizing the Mech-KiM model for renal clearance predictions yielded estimates closely aligned with observed concentrations. Our study demonstrates that using GFR-based scaling models to predict pediatric renal clearance might be inadequate for drugs with extensive passive tubular reabsorption (e.g., Freabs > 70%).

Geographical Variation in the Sand Cat, Felis margarita (Carnivora: Felidae)

Sand cats, Felis margarita, range from northern Africa and the Arabian Peninsula to Central Asia. Their apparently discontinuous distribution is recognized as comprising four subspecies. Recent genetic research found little differentiation between subspecies except for the North African form. In this study, 90 skins and 88 skulls were analyzed from the four subspecies. A discriminant function analysis of the scores, ranging from 1 to 4, of four pelage characteristics revealed differentiation between putative subspecies, except between Turkmenian and Pakistani sand cats. Northern African and Arabian sand cats tend to be spotted and striped, while Turkmenian and Pakistani sand cats are less spotted and have a dorsal crest of fur. Nonmetric multidimensional scaling (NMDS) models generated from 21 skull measurements revealed an overlap in morphospace between all subspecies, except for larger Turkmenian sand cats; northern African sand cats were smallest. Therefore, both pelage characteristics and skull morphometrics support up to three subspecies. However, considering recent genetic research, it is likely that two subspecies should be recognized, F. m. margarita from northern Africa and F. m. thinobia from the Arabian Peninsula, and Southwest and Central Asia. Widening of the dataset and nuclear DNA evidence are required to increase our understanding of geographical variation in this little studied species.

Measuring the extent of trees outside of forests: a nature-based solution for net zero emissions in South Asia

Abstract To reduce emissions of carbon and other greenhouse gases on a pathway that does not overshoot and keeps global average temperature increase to below the 1.5 oC target stipulated by the Paris Agreement, it shall be necessary to rely on nature-based solutions with atmospheric removals. Without activities that create removals from carbon sequestration it will not be possible to balance residual emissions. Policies that focus solely on reducing deforestation will only lower future emissions. On the other hand, activities that include regeneration or regrowth of tree biomass can be used to create net-zero emissions through carbon sequestration and atmospheric removals now. New methods demonstrated here using high resolution remote sensing and deep machine learning enable analyses of carbon stocks of individual trees outside of forests (TOF). Allometric scaling models based on tree crowns at very high spatial resolution (<0.5 m) can map carbon stocks across large landscapes with millions of trees outside of forests. In addition to carbon removals, these landscapes are also important to livelihoods for millions of rural farmers and most TOF activities have the capacity to bring more countries into climate mitigation while also providing adaptation benefits. Here were present a multi-resolution, multi-sensor method that provides a way to measure carbon at the individual tree level in TOF landscapes in India. The results of this analysis show the effectiveness of mapping trees outside of forest across a range of satellite data resolution from 0.5 m to 10 m and for measuring carbon across large landscapes at the individual tree scale.

A Study on the Mechanical Behavior of a Wind Turbine Foundation with a Constrained Structural Shear Connector

Aiming to solve the problems that a wind turbine foundation with a foundation pipe may suffer from grouting, where the concrete around the interface collapses and the interface disintegrates under a long-term wind load, a kind of wind turbine foundation with a constrained structural shear connector is proposed. In this article, the scaling model tests and a finite element simulation of a traditional stud foundation pipe, perforated steel shear connector foundation pipe, and three groups of constrained structural shear connector foundation pipes with different anchored depths are presented. The force transmission mechanism and damage mechanism of constrained structural shear connector wind turbine foundations are revealed, and the shear resistance of a constrained structural shear connector is analyzed. The influences of buried depth and other parameters on the mechanical properties of the shear connector are also investigated. The results show that the constrained structural shear connector has the advantages of stronger interfacial stiffness and significant force transfer and diffusion, and can more effectively connect the foundation pipe and concrete foundation to work together. It can give full play to the material advantages of concrete and reinforcements, and effectively improve the embedded stiffness and durability of concrete foundations. It can solve the problem of cracks in concrete caused by local pressure. At the same time, it is suggested that the diameter of the surrounding concrete should be in the range of 3 to 4 D, and the embedment depth of the stud should not be less than 0.4 D to give full play to the performance of the constrained structural shear connector.

Dissecting the mystery of embryonic scaling: The Scalers Hypothesis and its confirmation in sea urchin embryos

Embryonic scaling, the ability of embryos to regulate their spatial structure in proportion to size, remains a fascinating yet poorly studied problem in developmental biology. First described in sea urchin embryos by Hans Driesch, this phenomenon is now recognized as a striking example of how living organisms use non-equilibrium self-organization, based on reaction-diffusion (RD) systems, to generate pattern-determining morphogen concentration gradients that scale with size. Although specific molecular mechanisms for scaling such gradients have been described in some cases, a general approach for the targeted identification of such mechanisms had not been developed until recently. In search of a solution, we hypothesized the obligatory participation in scaling mechanisms of special genes, which we named “scalers.” We supposed that these genes share two critical features: their expression is sensitive to embryo size, and their protein products determine the scale of morphogen concentration gradients. As proof of principle, we recently identified scalers by detecting differentially expressed genes in wild-type and half-size Xenopus laevis gastrula embryos. Furthermore, we described a mechanism by which one of the identified scalers, the gene encoding Metalloproteinase 3 (Mmp3), regulates the scaling of gradients of the morphogenic protein Bmp and its antagonists, Chordin and Noggin1/2. In the present work, we have made an important theoretical generalization of the Scalers Hypothesis by proving a statement regarding the obligatory presence of scalers in closed RD systems generating morphogen concentration gradients. Furthermore, through a systematic analysis of all known types of embryonic scaling models based on RD systems, we demonstrate that scalers are present in all known types of such models, either explicitly or implicitly. Finally, to test the universality of the Scalers Hypothesis, we applied our method to identify scalers that adjust Bmp/Chordin gradients to the size of the sea urchin embryo, Strongylocentrotus droebachiensis. Our results show that at least two members of the gene cluster encoding astacin metalloproteinases of the Span family, namely bp10 and Span, exhibit properties characteristic of scalers. Namely, their expression levels increase significantly in half-size embryos, and their protein products specifically degrade Chordin. Additionally, we found that the loss of function of bp10 and span leads to a narrowing of the dorsal domain of the Bmp signaling nuclear effector, pSmad1/5. These findings not only validate the Scalers Hypothesis but also uncover a novel mechanism by which Span proteinases fine-tune Chordin and Bmp morphogen concentration gradients in sea urchins. Thus, the Scalers Hypothesis and the approach to targeted search for such genes developed on its basis open up promising avenues for future research into scaling mechanisms in various biological systems.

Calculation of in-situ steady-state heat flux on EAST lower divertor

Heat flux is a key issue in tokamak devices. The non-uniform high heat flux on Plasma-Facing Components (PFCs) has led to local severe damage, including cracks and melting, in current tokamaks such as EAST and WEST. To characterize the non-uniform heat flux loading on the divertor surfaces, the parallel incident heat flux q‖, the decay length λq along the radial direction and the Gaussian spreading width S are used. The q‖ can lead to a very high peak heat flux loading on the divertor surfaces, which may cause critical heat flux problems. Additionally, the decay length is a key consideration for future tokamak designs like ITER. Every effort on the present tokamak devices contributes to updating the scaling of the heat flux. In EAST, a calculation method based on a high spatial resolution IR camera is employed to obtain the heat flux and decay length. The main process involves comparing the surface temperature distribution calculated by Fluent simulation with that measured by an infrared camera. Taking a high heating source discharge (#123059 ∼ 10 MW heating source) as an example, the heat flux is as follows: q‖=216-14+19 MW/m2, with λq=6.2-1.1+1 mm, and S=1.2±0.4 mm; it is in line with Langmuir probe data. The infrared-based heat flux calculation method can calculate the peak incident heat flux and the decay length simultaneously, its result can help to update the scaling model of heat flux, thus not only helping to improve the present device but also offering important reference for future tokamaks

Ncorpi[formula omitted]N : A [formula omitted] software for N-body integration in collisional and fragmenting systems

NcorpiON is a general purpose N-body software initially developed for the time-efficient integration of collisional and fragmenting systems of planetesimals or moonlets orbiting a central mass. It features a fragmentation model, based on crater scaling and ejecta models, able to realistically simulate a violent impact.The user of NcorpiON can choose between four different built-in modules to compute self-gravity and detect collisions. One of these makes use of a mesh-based algorithm to treat mutual interactions in O(N) time. Another module, much more efficient than the standard Barnes–Hut tree code, is a O(N) tree-based algorithm called FalcON. It relies on fast multipole expansion for gravity computation and we adapted it to collision detection as well. Computational time is reduced by building the tree structure using a three-dimensional Hilbert curve. For the same precision in mutual gravity computation, NcorpiON is found to be up to 25 times faster than the famous software REBOUND.NcorpiON is written entirely in the C language and only needs a C compiler to run. A python add-on, that requires only basic python libraries, produces animations of the simulations from the output files. NcorpiON can communicate with REBOUND’s webGL viewer via MPI for 3D visualization. The name NcorpiON, reminding of a scorpion, comes from the French N-corps, meaning N-body, and from the mathematical notation O(N), due to the running time of the software being almost linear in the total number N of bodies. NcorpiON detects collisions and computes mutual gravity faster than REBOUND, and unlike other N-body integrators, it can resolve a collision by fragmentation. The fast multipole expansions are implemented up to order eight to allow for a high precision in mutual gravity computation.

Experimental investigation of effects of ullage height on the burning rate and heat feedback in pool fires

Pool fire with varying ullage height is a common type of accident that occurs in industrial parks. This paper explores the ullage height effects on the burning rate and heat feedback in pool fires through the experimental and theoretical study. A series of experiments were conducted using heptane with four tray sizes and five ullage heights. The results show that, the burning rate initially decreases, then increases and finally decreases as the ullage height increases. These results are mainly dependent on the change of internal flame behavior and thus heat feedback mechanisms with increasing ullage height. In the small ullage height conditions, the convective heat feedback reduces substantially whereas the radiative one rises slightly. When the ullage height reaches to a certain value, the convective heat feedback suddenly increases because of the flame inside the tray. The radiative heat feedback decreases gradually as the ullage height increase continually, while the convective one becomes nearly constant. Based on these results, three regimes are identified in terms of the burning rate variation with heat feedback: (1) convection controlled, (2) convection-radiation controlled and (3) radiation controlled. The new controlling mechanism of the burning rate variation (with ullage height), as a further extension of the classic scaling model by Blinov and Khudyakov on the burning rate variation (with pool diameter), could lay a solid foundation for future studies of the other key parameters in tank fires.

Analysis of the effect of lactobacillus exopolysaccharide on the rheological properties of fermented soybean protein gel: Using acid-induced soybean protein as the model

In order to accurately describe the contribution of extracellular polysaccharide (EPS) to the rheological properties of the gel in the complex system induced by lactic acid bacteria fermentation, acid-induced soy protein isolate (SPI) was used as the model. The effect of exopolysaccharide produced by Lactobacillus casei (CEPS) on the macro rheological properties and microstructural changes of acid-induced SPI gel were analyzed by scaling model and image analyses. The estimated value of storage modulus (G′) at time infinity, gel point, G′ at 37 °C, enhancement effect of G′ during cooling (ΔG'), recovery rate, critical strain (γc) and fractal dimension (Df) exhibited strong CEPS concentration dependence. The addition of CEPS led to the formation of uniform and compact three-dimensional network, which was mainly represented by small voids and apertures. Therefore, by reducing the complexity of the fermentation gel system, this study explored the effect of CEPS on the rheological properties of fermented soy protein gels and the fermented soybean protein gel with good rheological properties can be selected by quantitative image analysis.

Determination of Microtopography of Low-Relief Tidal Freshwater Forested Wetlands Using LiDAR

The microtopography of tidal freshwater forested wetlands (TFFWs) impacts biogeochemical processes affecting the carbon and nitrogen dynamics, ecological parameters, and habitat diversity. However, it is challenging to quantify low-relief microtopographic features that might only vary by a few tens of centimeters. We assess the high-resolution fine-scale microtopographic features of a TFFW with terrestrial LiDAR and aerial LiDAR to test a method appropriate to quantify microtopography in low-relief forested wetlands. Our method uses a combination of water-level and elevation thresholding (WALET) to delineate hollows in terrestrial and aerial LiDAR data. Close-range remote sensing technologies can be used for microtopography in forested regions. However, the aerial and terrestrial LiDAR technologies have not been used to analyze or compare microtopographic features in TFFW ecosystems. Therefore, the objectives of this study were (1) to characterize and assess the microtopography of low-relief tidal freshwater forested wetlands and (2) to identify optimal elevation thresholds for widely available aerial LiDAR data to characterize low-relief microtopography. Our results suggest that the WALET method can correctly characterize the microtopography in this area of low-relief topography. The microtopography characterization method described here provides a basis for advanced applications and scaling mechanistic models.

Quantitative analysis of the morphological variation within the tiger beetle Calomera littoralis (Fabricius, 1787) (Coleoptera: Cicindelidae) in Mongolia

For the past couple of centuries, much of tiger beetle taxonomic work has been focused on explaining intraspecific variation. In the Northern Hemisphere, over a thousand subspecies have been described and many have since been relegated to synonymy. Generally, the phenotypic-based subspecies circumscription has been purely descriptive. More quantitative and integrative analyses of the color and pattern variation in tiger beetles would be valuable. The geographically wide-ranging species, Calomera littoralis (Fabricius, 1987) contains 11 currently recognized subspecies, including two described from Mongolia that have been of questionable status due to the paucity of material available when they were described. Here, we assess the distribution of phenotypic variation within C. l. peipingensis (Mandl, 1934) and C. l. mongolensis (Mandl, 1981) to determine whether it best fits a pattern of two subspecies with a contact zone or a gradual cline, based on 494 specimens from 34 populations. Non-metric multidimensional scaling analyses and modeling of the fit between longitude and black dorsal phenotypes both indicate that the variation is best explained by a gradual cline of phenotype along an east-west gradient, not the presence of separate subspecies. As a result, we synonymize C. littoralis mongolensis, syn, nov. with C. littoralis peipingensis.

Seismic response prediction method of train-bridge coupled system based on convolutional neural network-bidirectional long short-term memory-attention modeling

Seismic response prediction is crucial for the safety analysis of train-bridge coupled systems. However, due to the complexity, suddenness, and high-risk nature of earthquakes, there are strong nonlinear relationships among different parts of bridges, making it challenging to express their spatial correlations using analytical models and traditional neural networks. To address this, this paper establishes a ballast track shaker scaling model and employs the grating monitoring measurement method to construct a spatial quasi-distributed monitoring system for the ballast track, thereby collecting seismic strain responses of the train-bridge coupled system under various seismic conditions. A hybrid neural network method is proposed for predicting the seismic responses of the train-bridge coupled system. This hybrid neural network integrates the features of a Convolutional Neural Network (CNN), Bidirectional Long Short-Term Memory Neural Network (BiLSTM), and the attention mechanism, thereby termed the CNN-BiLSTM-attention hybrid neural network. The model was validated using strain responses from 54 seismic scenarios. The results indicate that the model has a Mean Absolute Error (MAE) of 0.2349 and a coefficient of determination (R2) of 0.9446. Comparing the prediction results with those from RNN and LSTM models, it was found that the CNN effectively extracts features under various seismic parameters, while the BiLSTM better captures the temporal information of the strain responses, ensuring effective prediction regardless of the magnitude of strain responses. Therefore, the CNN-BiLSTM-attention hybrid neural network model is recommended for predicting seismic response.

Impact of prototype scale effect on the dynamic responses and damage of steel plates under explosions

Scaling model was widely used in engineering to reveal the responses of full-scale prototype model. This study provided insight into the impact of the scale effect on the dynamic response and damage of stiffened and unstiffened steel plates under explosions. A numerical model consider fluid-structure-interaction (FSI) was established using LS-DYNA platform, and the numerical model was verified by the blast test results. Moreover, the scaling factors (S) equal to 1 (prototype), 1/2, and 1/4, and 1/8, and 1/12 were considered in the study, the scaling effects on the breach size, plastic area, and the deformation shape were analyzed. The results showed that the breach size and plastic area of the scaled model deviated from the ideal results based on the replica law. However, the deformation shapes of scaled-down plates accurately reflected the deformation characteristics of the full prototype plate. The scaling factor significantly influenced the dynamic responses of stiffened and unstiffened steel plates; as the scaling factor (S) increased, the dimensionless displacement decreased. The results indicated that a smaller S led to a larger deviation in response. The influencing factors of the scaling effect were investigated, and it was found that stiffened steel plates were more sensitive to the scaling factor than unstiffened steel plates. By comparing the detonation of cuboid, cylindrical, and spherical explosives blast-loaded onto stiffened steel plates, it was determined that the detonation of cubic explosives caused the most severe scaling effect on stiffened steel plates under blast loads. The study also found that explosive mass and standoff distance influenced the scaling effect of stiffened steel plates under blast loads. Additionally, steel plates in the plastic stage and the critical state between the elastic and plastic stages were particularly sensitive to the scaling effect. Due to the strain rate effect, which can lead to a deviation from the ideal scale law, different steel materials exhibit varying scale sensitivities. Comparing stiffened plates made from Q235, Q345, DH36, and L907A, the order of sensitivity to the scaling factor was: Q235 > Q345 ≈ DH36 > L907A.

ProSAAS is preferentially up-regulated during homeostatic scaling and reduces amyloid plaque burden in the 5xFAD mouse hippocampus.

The accumulation of β-amyloid in Alzheimer's disease greatly impacts neuronal health and synaptic function. To maintain network stability in the face of altered synaptic activity, neurons engage a feedback mechanism termed homeostatic scaling; however, this process is thought to be disrupted during disease progression. Previous proteomics studies have shown that one of the most highly regulated proteins in cell culture models of homeostatic scaling is the small secretory chaperone proSAAS. Our prior work has shown that proSAAS exhibits anti-aggregant behavior against alpha-synuclein and β-amyloid fibrillation invitro and is up-regulated in cell models of proteostatic stress. However, the specific role that this protein might play in homeostatic scaling, and its anti-aggregant role in Alzheimer's progression, is not clear. To learn more about the role of proSAAS in maintaining hippocampal proteostasis, we compared its expression in a primary neuron model of homeostatic scaling to other synaptic components using western blotting and qPCR, revealing that proSAAS protein responses to homeostatic up- and down-regulation were significantly higher than those of two other synaptic vesicle components, 7B2 and carboxypeptidase E. However, proSAAS mRNA expression was static, suggesting translational control and/or altered protein degradation. ProSAAS was readily released upon depolarization of differentiated hippocampal cultures, supporting its synaptic localization. Immunohistochemical analysis demonstrated abundant proSAAS within the mossy fiber layer of the hippocampus in both wild-type and 5xFAD mice; in the latter, proSAAS was also concentrated around amyloid plaques. Importantly, overexpression of proSAAS in the CA1 region via stereotaxic injection of proSAAS-encoding AAV2/1 significantly decreased amyloid plaque burden in 5xFAD mice. We hypothesize that dynamic changes in proSAAS expression play a critical role in hippocampal proteostatic processes, both in the context of normal homeostatic plasticity and in the control of protein aggregation during Alzheimer's disease progression.

Predicting extinction limits of concurrent smoldering spread by a reduced analytical model

Smoldering is a flameless combustion mode occurring on the surface of charring fuels, such as wood and cigarettes. Although the smoldering process is slow and has a low temperature compared to flaming, it is easy to be initiated by a weak heat source and persists under poor oxygen conditions. Extensive work has been done for flame extinction to develop scaling models to predict the limiting oxygen concentration (LOC), but limited work is available for the smoldering extinction. This study develops a reduced analytical model to predict the extinction limits of smoldering. The model simultaneously solves smoldering propagation rate, surface temperature, and surface oxygen mass fraction as part of the solutions. The extinction limit is determined as the critical condition where solutions satisfying all governing equations cease to exist. The model provides a qualitative description and captures the essential characteristics of a previous experiment. The smoldering rate decreases with increasing fuel diameter, and a larger-diameter fuel is easier to extinguish. The mechanisms of the extinction process are investigated, showing the dominant role of radiative heat loss in the smothering limit at low airflow velocities and convective heat loss near the blowoff limit at high airflow velocities. Further analysis of the effect of oxygen concentration shows an increasing trend of LOC with fuel diameter, and the smothering branch cannot be predicted without considering the heat loss through radiation from the solid surface. Novelty and Significance StatementThe novelty of this research is the prediction of smoldering propagation rates and extinction limits across various fuel diameters using a reduced analytical model. The model is modified to accommodate a thin fuel configuration and high airflow velocity condition, where convective heat and mass transfer play a more important role. The model's significance is that it not only provides essential insights into the mechanisms but also has the capability to simultaneously determine key parameters such as spread rate, reaction temperatures, and surface oxygen concentration as part of the solutions. Additionally, this study demonstrates the model's ability to reproduce the limit conditions, including smothering/blowoff limits and limiting oxygen concentration (LOC).

Anomalous hot electron generation from two-plasmon decay instability driven by broadband laser pulses with intensity modulations

We investigate the hot electrons generated from two-plasmon decay (TPD) instability driven by laser pulses with intensity modulated by a frequency Δω m using theoretical and numerical approaches. Our primary focus lies on scenarios where Δω m is on the same order of the TPD growth rate γ 0 ( Δωm∼γ0 ), corresponding to moderate laser frequency bandwidths for TPD mitigation. With Δω m conveniently modeled by a basic two-color scheme of the laser wave fields in fully-kinetic particle-in-cell simulations, we demonstrate that the energies of TPD modes and hot electrons exhibit intermittent evolution at the frequency Δω m , particularly when Δωm∼γ0 . With the dynamic TPD behavior, the overall ratio of hot electron energy to the incident laser energy, fhot , changes significantly with Δω m . While fhot drops notably with increasing Δω m at large Δω m limit as expected, it goes anomalously beyond the hot electron energy ratio for a single-frequency incident laser pulse with the same average intensity when Δω m falls below a specific threshold frequency Δω c . This anomaly arises from the pronounced sensitivity of fhot to variations in laser intensity. We find this threshold frequency Δω c primarily depends on γ 0 and the collisional damping rate of plasma waves, with relatively lower sensitivity to the density scale length. We develop a scaling model characterizing the relation of Δω c and laser plasma conditions, enabling the potential extention of our findings to more complex and realistic scenarios.

Steepness-fragility insights from the temperature derivative analysis of dielectric data of a highly nonsymmetric liquid crystal dimer.

A comprehensive dynamic analysis of the dielectric relaxation-time data across a broad temperature range for both isotropic and nematic phases has been conducted on the CBO3O.Py liquid crystal dimer, the shorter chain-length compound within the highly nonsymmetric pyrene-based series of liquid crystal dimers (CBOnO.Py, with n ranging from 3 to 11). It was known from another previous study that in the nematic phase, three different relaxation processes contribute to the complex dielectric permittivity depending on the orientation of the alignment axis with respect to the probing electric field direction. The temperature-derivative analysis of the relaxation-time data using different analytic functions reveals that the critical-like description, through the dynamic scaling model, best portrays the relaxation-time data in the nematic phase as the system approaches the glass transition. A single glass transition temperature is obtained which is consistent with thermal stimulated depolarization currents experimental determinations published elsewhere. From temperature-dependent steepness index m(T), the activation-critical model is also considered as a more general analytic function from which the dynamic scaling model is a terminal approximation. Additionally, the critical-like parametrization provides insight into obtaining a universal description of the temperature-dependent steepness index m(T), for all liquid crystal compounds belonging to symmetry-selected glass formers, such as rodlike liquid crystal monomers.