Aggregation Rate Research Articles

Characterization of the in-situ degradation process of P3HT:PCBM based on hyperspectral and neural networks

In situ online observation of surface morphology during degradation processes is of paramount importance for exploring the stability of organic photovoltaic materials. In this study, we designed an in situ online characterization system based on hyperspectral and neural network technologies, and observed the degradation processes of P3HT:PCBM thin film materials. The system is capable of collecting hyperspectral image data from 101 channels within the 400–700 nm wavelength range for characterizing detailed surface features of materials. Additionally, to automate the processing of hyperspectral image data, we designed a spectral image segmentation algorithm based on neural networks and proposed a foreground attention mechanism to improve the segmentation accuracy of the algorithm. The experimental results indicate that the system can achieve high spectral characterization of P3HT:PCBM thin film materials and automate image data processing through artificial intelligence algorithms, with an image segmentation accuracy of 99.62 %. Furthermore, owing to the higher spectral resolution of this system and its computer-assisted analysis capabilities for material image data, not only are the in-situ variations in size, density, and formation rate of aggregates formed during the thermal degradation process of P3HT:PCBM thin film materials experimentally analyzed, but also the fluorescence changes at the edges of aggregates during the photodegradation process are revealed. The reliable code can be found at the following link: https://github.com/HyperSystemAndImageProc/IONFMDP-UHHNN.

Distribution characteristics of TiO2 NPs in Daihai lake and their stability regulated by abiotic factors

Accurate detection and stability analysis of titanium dioxide (TiO2 NPs) in surface water are critical for ecological risk assessment. Quantitative analysis of TiO2 NPs in water and sediment of Daihai Lake was performed and their occurrence forms was characterized by TEM, XRD and FTIR. Further investigation into the impact of pH, ionic strength (IS) and dissolved organic matter (DOM) on the stability of TiO2 NPs was carried out, along with a correlation analysis between abiotic factors and TiO2 NPs concentration. Results showed that TiO2 NPs in water and sediment are 1.01 × 105 and 5.66 × 105 particles/mL in July 2023, respectively. After transformed in water sample from Daihai Lake, the hydrodynamic particle (HDD) of TiO2 NPs reach 600–700 nm, with reduced crystallinity and observable characteristic peaks of NaCl, which is related to the high concentration of NaCl in Daihai Lake. Structural defects and changes in surface properties of TiO2 NPs are introduced due to the adsorption of organic matter, leading to higher aggregation and sedimentation rates. Specifically, Ca2+ promote the sedimentation of TiO2 NPs more than Na+. Conversely, A/A0 increased to 0.80–0.94 from 0.64 after humic acid (HA) and fulvic acid (FA) added. Hydroxyl and carboxyl groups of FA enhanced steric hindrance and inhibited TiO2 NPs sedimentation. While a strong promotion effect on the sedimentation of TiO2 NPs is detected when 10 mmol/L Ca2+ coexisted with 10 mg/L HA, with 70% of the TiO2 NPs settled within 120 min. Additionally, the concentration of TiO2 NPs in Daihai Lake is significantly positively correlated with dissolved organic carbon (DOC) and humification index, which might be relate to the enhancement of TiO2 NPs stability of aromatic organic matter. And the high concentration of DOC will also lead to the stable existence of TiO2 NPs in water and exacerbate aquatic toxicity.

Impact of dissolved organic matter characteristics and inorganic species on the stability and removal by coagulation of nanoplastics in aqueous media

The aggregation of rough, raspberry-type polystyrene nanoparticles (PS-NPs) was investigated in the presence of six hydrophobic and hydrophilic dissolved organic matter (DOM) isolates and biopolymers (effluent OM) in NaCl and CaCl2 solutions using time-resolved dynamic light scattering. Results showed that the stability of PS-NPs mainly depends on OM characteristics and ionic composition. Due to cation bridging, the aggregation rate of PS-NPs in Ca2+-containing solutions was significantly higher than at similar Na+-ionic strength. Biopolymers rich in protein and carbohydrate moieties showed higher affinity to the surface of PS-NPs than the other DOM isolates in the absence of both Ca2+ and Na+. Overall, the stability of PS-NPs followed the order of biopolymers > hydrophobic isolates > hydrophilic isolates in the presence of Na+ and biopolymers > hydrophilic isolates > hydrophobic isolates in Ca2+-containing solutions. In the presence of high MW structures (biopolymers), PS-NPs aggregation in both NaCl and CaCl2 solutions was attributed to steric repulsive forces. The impact of hydrophilic and hydrophobic isolates on PS-NPs aggregation highly relied on the ionic composition. Coagulation was an effective pretreatment for PS-NPs removal. Using inductively coupled plasma-mass spectrometry, higher removals were recorded with Al2(SO4)3 in the absence of DOM, while PACl more efficiently coagulated PS-NPs in the presence of DOM isolates.

Comparative Assessment of Expected Safety Performance of Freeway Automated Vehicle Managed Lanes

The use of dedicated lanes, known as managed lanes (MLs), on freeways is an established traffic management strategy to reduce congestion. Allowing automated vehicles (AVs) in existing MLs or dedicating MLs for AVs, referred to as AVMLs, has been suggested in the literature as a tool to improve traffic operation and safety performance as AVs and driver-operated vehicles (DVs) coexist in a mixed-vehicle environment. This paper focuses on investigating the safety impacts of deploying AVMLs on freeways by repurposing general-purpose lanes (GPLs). Four ML strategies considering different lane positions and access controls were implemented in a traffic microsimulation under different AV market adoption rates (MARs) and traffic demand levels, and trajectories were used to extract rear-end and lane change conflicts. The time-to-collision (TTC) surrogate safety measure was used to identify critical conflicts using a time threshold dependent on the type of following vehicle. Rates of conflicts involving different vehicle types for all ML strategies were compared to the case of heterogeneous traffic. The results indicated that the rates of rear-end conflicts involving the same vehicle type as the lead and following vehicle, namely DV-DV and AV-AV conflicts, increased with ML implementation as more vehicles of the same type traveled in the same lane(s). By comparing the aggregated conflict rates, the design options that were deemed to negatively impact traffic efficiency and capacity were also found to negatively impact traffic safety. However, other ML options were found to be feasible in terms of traffic operation and safety performance, especially at traffic demand levels below capacity. Specifically, one left-side AVML with continuous access was found to have lower or comparable aggregated conflict rates compared to heterogenous traffic at 25% and 50% MARs, and, thus, it is expected to have positive or neutral safety impacts.

Two-way 5G NR FSO-HCF-UWOC converged systems with R/G/B 3-wavelength and SLM-based beam-tracking scheme.

A two-way fifth-generation (5G) new radio (NR) free-space optical (FSO)-hollow-core fibre (HCF)-underwater wireless optical communication (UWOC) converged systems with a red/green/blue (R/G/B) 3-wavelengths and spatial light modulator (SLM)-based beam-tracking scheme is practically built. It is the first to practically build a two-way FSO-HCF-UWOC converged system with high-speed and long-distance optical wireless-wired-underwater wireless communication characteristics. It shows a 5G NR FSO-HCF-UWOC convergence from drone or buildings to undersea, using R/G/B 3-wavelengths and an SLM as a demonstration. The R/G/B 3-wavelengths are used to enhance the downstream and upstream aggregate transmission rates. An SLM with electrical comparator is used to adjust the laser beam and mitigate laser beam misalignment caused by drone movement or ocean flow. Over a hybrid of 1-km FSO, 10-m HCF, and 10.44-m ocean water-air-ocean water medium, downstream/upstream 5G-millimeter-wave (MMW) 9.1-Gb/s/24-GHz signals are transmitted with satisfactorily low bit error rates and error vector magnitudes, as well as distinct constellations. This demonstrated that the 5G NR FSO-HCF-UWOC converged system exhibits promising potential as it advances the scenario implemented by the 5G-MMW signals over FSO, HCF, and UWOC convergence, paving the way for high-speed and long-distance communications across diverse media.

Mechanical properties investigation on recycled rubber desert sand concrete

The mechanical properties of recycled rubber desert sand concrete were studied to determine the effect of the replacement rate of recycled rubber and desert sand. The replacement rates of recycled rubber aggregates were set to 0 %, 5 %, 10 %, and 15 %, respectively, and for dessert sand aggregates were set to 0 %, 10 %, 20 %, and 30 %, respectively, during concrete preparation. The concrete's compressive, tensile, and freeze-thaw mechanical properties were tested at each replacement rate. The experimental results show that when the replacement rate of desert sand increases from 0 % to 30 %, the replacement rate of recycled rubber is 15 %, and the splitting tensile strength of concrete shows a pattern of first increasing and then decreasing. When the replacement rate for desert sand is 30 %, the replacement rate for recycled rubber rises from 0 % to 15 %, and the splitting tensile strength shows a pattern of first decreasing. With replacement rates of 10 percent for recycled rubber aggregate and 20 percent for desert sand aggregate, the damage to the concrete from external forces is relatively ideal. The compressive strength values are the highest, and the split tensile strength is the best, demonstrating good compressive and tensile strength. The results of CO2 emission analysis show that as the amount of recycled rubber increases, the CO2 emissions per unit volume of concrete also increase. The interface of the micro-optical structure in the concrete is straightforward, the pores are few, and it exhibits good mechanical properties. The concrete undergoes freeze-thaw cycles with relatively stable changes in compressive strength and split tensile strength, demonstrating a solid freeze-thaw resistive mechanical property.

Floating active carpets drive transport and aggregation in aquatic ecosystems

Communities of swimming microorganisms often thrive near liquid–air interfaces. We study how such ‘active carpets’ shape their aquatic environment by driving biogenic transport in the water column beneath them. The hydrodynamic stirring that active carpets generate leads to diffusive upward fluxes of nutrients from deeper water layers, and downward fluxes of oxygen and carbon. Combining analytical theory and simulations, we examine the biogenic transport by studying fundamental metrics, including the single and pair diffusivity, the first passage time for particle pair encounters and the rate of particle aggregation. Our findings reveal that the hydrodynamic fluctuations driven by active carpets have a region of influence that reaches orders of magnitude further in distance than the size of the organisms. These non-equilibrium fluctuations lead to a strongly enhanced diffusion of particles, which is anisotropic and space dependent. Fluctuations also facilitate encounters of particle pairs, which we quantify by analysing their velocity pair correlation functions as a function of distance between the particles. We found that the size of the particles plays a crucial role in their encounter rates, with larger particles situated near the active carpet being more favourable for aggregation. Overall, this research broadens our comprehension of aquatic systems out of equilibrium and how biologically driven fluctuations contribute to the transport of fundamental elements in biogeochemical cycles.

Storage-induced changes in β-strand interactions within bovine lactoferrin powder analyzed through X-ray diffraction

Bovine lactoferrin (bLF) is a multifunctional protein used in the food and pharmaceutical industries. Various commercially available bLF powders (bLFPs) have different ratios of protein monomers to aggregates, which affects the aggregation rate. However, the changes in molecular structure and interactions during aggregation are unclear. This study investigated changes in the structure and interactions of stored bLFPs during aggregation. Five commercially available bLFPs with different molecular weight distributions were analyzed before and after storage using size-exclusion chromatography and X-ray diffraction (XRD) to monitor aggregation and β-strand interaction, respectively. These bLFPs were stored for four weeks under high temperature and humidity conditions as a stress test. The XRD results revealed changes in peak II (around 2θ = 20°), corresponding to β-strand interactions. The peak II change rate suggested that the aggregation occurs due to partial structural fluctuations and interaction changes. Furthermore, time-course analysis of peak II and correlations with the pre-storage monomer ratio and aggregation phase index demonstrated that β-strand interactions decreased during the transformation of monomers to low-molecular-weight (LMW) aggregates, while it increased during the LMW-to-high-molecular-weight aggregate phase. These results provide novel insights into the conformational changes and molecular interactions of bLFPs during aggregation.

Large language models and humans converge in judging public figures' personalities.

ChatGPT-4 and 600 human raters evaluated 226 public figures' personalities using the Ten-Item Personality Inventory. The correlation between ChatGPT-4 and aggregate human ratings ranged from r = 0.76 to 0.87, outperforming the models specifically trained to make such predictions. Notably, the model was not provided with any training data or feedback on its performance. We discuss the potential explanations and practical implications of ChatGPT-4's ability to mimic human responses accurately.

Collective exploitation of large prey by group foraging shapes aggregation and fitness of cnidarian polyps

Group living is widespread and beneficial to metazoans. It improves protection and survival opportunities, reinforcing interspecific competitiveness. Benthic cnidarians often colonize large surfaces. Evidence of collective capture and exploitation of large prey by small, clumped polyps suggests that aggregation is functional to access food resources hardly achievable by isolated individuals. In turn, the chance to catch large prey may represents a driver of aggregation in polyps, whether beneficial to their fitness. Here, the effects of group foraging on aggregation, asexual reproduction, and growth rates of Aurelia coerulea von Lendenfeld 1884 polyps were experimentally tested by providing them with either small or large prey, or a mix of both to simulate the co-occurrence of preys at sea. As expected, some polyps were not able to reach the large prey. Hence, the population was a posteriori divided into group-foragers and solitary-feeders. In general, the large prey diet resulted in higher population fitness and when simultaneously supplied with the small prey represented an energetic booster resulting beneficial for all group-members. The decrease of interindividual distances was reported among group-foragers, that converged towards each other. Cnidarians are basal in metazoan evolution, and the comprehension of their collective foraging behavior, as well as the processes leading to the selective feature driving them to forage in group or not, may be essential to better understand the evolution and spread of social foraging in animals. Moreover, the access to large prey by sessile polyps of Aurelia coerulea could be pivotal in determining the increase in abundance of adult bloom-forming medusae.

Numerical simulation of hydrate flow in gas-dominated undulating pipes considering nucleation and deposition behaviors

The distribution and deposition of hydrates in deep-water gas transportation pipelines are crucial for safety. Current simulations of hydrate flow based on the population balance model have predominantly focused on water-dominant systems and neglect the nucleation and deposition of hydrates. By establishing a model for a hydrate flow in a gas-dominant system that considers the uneven distribution of the liquid film on the wall, hydrate nucleation, gas–liquid mass transfer, particle adhesion and aggregation, and dynamic deposition, we achieved simulation of the entire process of hydrate formation, aggregation, breakage, and deposition. Simulations in undulating pipelines were carried out to investigate the effects of gas velocity, liquid injection, pressure, and pipeline structure on distribution patterns. The results showed increasing the gas velocity enhanced the dispersion of particles and increasing the pressure increased the rate of aggregation. The formation of blocky aggregates posed significant risk in the rear section of the lower-bend pipe.

A Standardized Sky Condition Classification Method for Multiple Timescales and Its Applications in the Solar Industry

The deployment of photovoltaic (PV) systems has increased globally to meet renewable energy targets. Intermittent PV power generated due to cloud-induced variability introduces reliability and grid stability issues at higher penetration levels. Variability in power generation can induce voltage fluctuations within the distribution system and cause adverse effects on power quality. Therefore, it is essential to quantify resource variability to mitigate an intermittent power supply. In this study, we propose a new scheme to classify the sky conditions that are based on two common variability metrices: daily clear-sky index and normalized aggregate ramp rates. The daily clear-sky index estimates the cloudiness in the sky, and ramp rates account for the variability introduced in the system generation due to sudden cloud movements. This classification scheme can identify clear-sky, highly variable, low intermittent, high intermittent and overcast days. By performing a Chi-square test on the training and test sets, we obtain Chi-square statistic values greater than 3 with p-value > 0.05. This indicates that the distribution of the training and test clusters are similar, indicating the robustness of the proposed sky classification scheme. We have demonstrated the applicability of the scheme with diverse datasets to show that the proposed classification scheme can be homogenously applied to any dataset globally despite their temporal resolution. Using various case studies, we demonstrate the potential applications of the scheme for understanding resource allocation, site selection, estimating future intermittency due to climate change, and cloud enhancement effects. The proposed sky classification scheme enhances the precision and reliability of solar energy forecasts, optimizing system performance and maximizing energy production efficiency. This improved accuracy is crucial for variability control and planning, ensuring optimal output from PV plants.

Rosuvastatin inhibit ox-LDL-induced platelet activation by the p38/MAPK pathway.

This study intends to explore the effects of Rosuvastatin on ox-LDL induced platelet activation and its molecular mechanism. Platelet aggregation rate was detected by aggregometer. ELISA kit was used to detect the levels of cAMP. Immunofluorescence staining was used to detect the platelet adhesion. The expression levels of platelet surface markers CD62p and PAC-1 were detected by flow cytometry. The protein levels of p-p38, p-IKKa and p-IKKB in platelets were detected by western blot. We found that rosuvastatin significantly inhibited platelet aggregation and increased the level of cAMP in a dose-dependent manner. Immunofluorescence staining results showed that rosuvastatin could inhibit platelet adhesion. Flow cytometry results showed that rosuvastatin could reduce the expression of platelet activation markers. Western blot results showed that rosuvastatin could down-regulate the expression levels of p-p38, p-IKKa and p-IKKb. Our study revealed the rosuvastatin could inhibit the aggregation, adhesion and activation of platelet induced by ox-LDL, its mechanism may be related to inhibition of p38/MAPK signal pathway.

Ion Correlations Decrease Particle Aggregation Rate by Increasing Hydration Forces at Interfaces.

The connection between solution structure, particle forces, and emergent phenomena at solid-liquid interfaces remains ambiguous. In this case study on boehmite aggregation, we established a connection between interfacial solution structure, emerging hydration forces between two approaching particles, and the resulting structure and kinetics of particle aggregation. In contrast to expectations from continuum-based theories, we observed a nonmonotonic dependence of the aggregation rate on the concentration of sodium chloride, nitrate, or nitrite, decreasing by 15-fold in 4 molal compared to 1 molal solutions. These results are accompanied by an increase in repulsive hydration forces and interfacial oscillatory features from 0.27-0.31 nm in 0.01 molal to 0.38-0.52 nm in 2 molal. Moreover, molecular dynamics (MD) simulations indicated that these changes correspond to enhanced ion correlations near the interface and produced loosely bound aggregates that retain electrolyte between the particles. We anticipate that these results will enable the prediction of particle aggregation, attachment, and assembly, with broad relevance to interfacial phenomena.

Alteration of cement rheological properties and setting-hardening: Novel insight into the impact of polyaluminum sulfate

The accelerator significantly influences the setting and hardening performance of shotcrete, in order to develop novel setting components, this study investigates the underlying mechanisms through which polyaluminum sulfate (PAS) facilitates the setting of cement paste. QXRD, Isothermal calorimetry, Zeta potential and Rheological test were employed to analyze the effects of PAS addition on the setting and hardening behavior, hydration kinetics, and rheological properties of cement paste. When the dosage of PAS is 10 %, the initial and final setting times are reduced by 54.39 % and 38.57 % respectively, meanwhile the compressive strength after 6 hours increases by 659.09 %. The influence of PAS on cement setting acceleration and rheological properties were analyzed using the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory and the Water Film Thickness (WFT) theory. PAS leads to an acceleration in particle aggregation rate and an increase in shear stress and plastic viscosity of the cement paste. Furthermore, the accelerated hydration effect of PAS promotes the formation of additional hydration products, strengthens the interparticle connectivity, and facilitates the formation of a rigid network. This study highlights a novel pathway for understanding the rapid setting mechanism of aluminum-based accelerators.

Multivalency drives interactions of alpha-synuclein fibrils with tau.

Age-related neurodegenerative disorders like Alzheimer's disease (AD) and Parkinson's disease (PD) are characterized by deposits of protein aggregates, or amyloid, in various regions of the brain. Historically, aggregation of a single protein was observed to be correlated with these different pathologies: tau in AD and α-synuclein (αS) in PD. However, there is increasing evidence that the pathologies of these two diseases overlap, and the individual proteins may even promote each other's aggregation. Both tau and αS are intrinsically disordered proteins (IDPs), lacking stable secondary and tertiary structure under physiological conditions. In this study we used a combination of biochemical and biophysical techniques to interrogate the interaction of tau with both soluble and fibrillar αS. Fluorescence correlation spectroscopy (FCS) was used to assess the interactions of specific domains of fluorescently labeled tau with full length and C-terminally truncated αS in both monomer and fibrillar forms. We found that full-length tau as well as individual tau domains interact with monomer αS weakly, but this interaction is much more pronounced with αS aggregates. αS aggregates also mildly slow the rate of tau aggregation, although not the final degree of aggregation. Our findings suggest that co-occurrence of tau and αS in disease are more likely to occur through monomer-fiber binding interactions, rather than monomer-monomer or co-aggregation.

Large-scale molecular dynamics simulation and aggregate behavior research on asphalt

In this comprehensive study, a molecular dynamics (MD) model consisting of approximately 150,000 atoms was developed within the Strategic Highway Research Program (SHRP) framework to investigate the behavior of AAA asphalt, focusing on asphaltene aggregate dynamics behavior over a simulation time span of 0.282 microseconds. The findings reveal that the model achieves a stable state in terms of both energy and microstructure without significant changes or the formation of densely clustered molecules, despite the extensive simulation period. Notably, the patterns of asphaltene aggregation were found to significantly influence the MD system energy, with variations ranging from loosely organized structures due to dispersed asphaltenes to more structured, energy-efficient clusters formed by encapsulated asphaltene pentamers. The size of asphaltene aggregates emerged as a pivotal factor, affecting their encapsulation and leading to distinct formation patterns. Furthermore, the research highlighted that increasing shear rates prompt the depolymerization of asphaltene aggregates, shifting from large-scale structures to smaller ones and adapting dynamically to the flow conditions by aligning parallel to the shear direction. This study underscores the critical impact of asphaltene aggregate behavior and shear rates on the structural integrity and distribution within the asphalt model, offering profound insights into the MD of asphalt materials.

Striding towards a greener future: Unlocking the potential of natural resources and employment dynamics in green energy transition in sub‐Saharan Africa

AbstractThe adoption and utilization of renewable energy offer potential benefits such as enhanced energy efficiency, cost savings, and ecological advantages. However, a key research question addressed in this analysis is whether natural resource rent and employment dynamics influence renewable energy consumption in Africa. Previous research has predominantly focused on the aggregate employment rate, overlooking the nuances of labor diversity across sectors and employment types. Hence, this study evaluates the importance of natural resource rent and employment in driving the transition to green energy in sub‐Saharan Africa from 1991 to 2022. It employs the innovative method of moments quantile regression (MMQR) model for this purpose. The findings reveal a positive connection between natural resource rent and the adoption of green energy. When considering employment types, the study observes that self‐employment and wages/salaried workers undermine clean energy utilization. Moreover, the study highlights that employment across key economic sectors also plays a role. While employment in the agriculture and service sectors fosters green energy utilization, employment in the industrial sector impedes renewable energy consumption. To advance the development of green energy in Africa, this study underscores a range of policy options.

Dynamics of waste proteins in brain tissue: Numerical insights into Alzheimer's risk factors.

Over the past few decades, research has indicated that the buildup of waste proteins, like amyloid-β (Aβ), in the brain's interstitial spaces is linked to neurodegenerative diseases like Alzheimer's, but the details of how such proteins are removed from the brain are not well understood. We have developed a numerical model to investigate the aggregation and clearance mechanisms of Aβ in the interstitial spaces of the brain. The model describes the volume-averaged transport of Aβ in a segment of the brain interstitium modeled as a porous medium, oriented between the perivascular space (fluid-filled channel surrounding a blood vessel) of a penetrating arteriole and that of a venule. Our numerical approach solves N coupled advection-diffusion-aggregation equations that model the production, aggregation, fragmentation, and clearance of N species of Aβ. We simulate N=50 species to investigate the oligomer-size dependence of clearance and aggregation. We introduce a timescale plot that helps predict Aβ buildup for different neurological conditions. We show that a sudden increase in monomer concentration, as occurs in conditions like traumatic brain injury, leads to significant plaque formation, which can qualitatively be predicted using the timescale plot. Our results also indicate that impaired protein clearance (as occurs with aging) and fragmentation are both mechanisms that sustain large intermediate oligomer concentrations. Our results provide novel insight into several known risk factors for Alzheimer's disease and cognitive decline, and we introduce a unique framing of Aβ dynamics as a competition between different timescales associated with production rates, aggregation rates, and clearance conditions.

Simulating the Growth of TATA-Box Binding Protein-Associated Factor 15 Inclusions in Neuron Soma.

To the best of the author's knowledge, this paper presents the first attempt to develop a mathematical model of the formation and growth of inclusions containing misfolded TATA-box binding protein associated factor 15 (TAF15). It has recently been shown that TAF15 inclusions are involved in approximately 10% of cases of frontotemporal lobar degeneration (FTLD). FTLD is the second most common neurodegenerative disease after Alzheimer's disease (AD). It is characterized by a progressive loss of personality, behavioral changes, and a decline in language skills due to the degeneration of the frontal and anterior temporal lobes. The model simulates TAF15 monomer production, nucleation and autocatalytic growth of free TAF15 aggregates, and their deposition into TAF15 inclusions. The accuracy of the numerical solution of the model equations is validated by comparing it with analytical solutions available for limiting cases. Physiologically relevant parameter values were used to predict TAF15 inclusion growth. It is shown that the growth of TAF15 inclusions is influenced by two opposing mechanisms: the rate at which free TAF15 aggregates are deposited into inclusions and the rate of autocatalytic production of free TAF15 aggregates from monomers. A low deposition rate slows inclusion growth, while a high deposition rate hinders the autocatalytic production of new aggregates, thus also slowing inclusion growth. Consequently, the rate of inclusion growth is maximized at an intermediate deposition rate of free TAF15 aggregates into TAF15 inclusions.