Growth Phenomena Research Articles

Stochastic Models for Ontogenetic Growth

Based on allometric theory and scaling laws, numerous mathematical models have been proposed to study ontogenetic growth patterns of animals. Although deterministic models have provided valuable insight into growth dynamics, animal growth often deviates from strict deterministic patterns due to stochastic factors such as genetic variation and environmental fluctuations. In this study, we extend a general model for ontogenetic growth proposed by West et al. to stochastic models for ontogenetic growth by incorporating stochasticity using white noise. According to data variance fitting for stochasticity, we propose two stochastic models for ontogenetic growth, one is for determinate growth and one is for indeterminate growth. To develop a universal stochastic process for ontogenetic growth across diverse species, we approximate stochastic trajectories of two stochastic models, apply random time change, and obtain a geometric Brownian motion with a multiplier of an exponential time factor. We conduct detailed mathematical analysis and numerical analysis for our stochastic models. Our stochastic models not only predict average growth well but also variations in growth within species. This stochastic framework may be extended to studies of other growth phenomena.

Fishmeal intervention after short-term novel proteins stimulates compensatory growth and affects intestinal health in largemouth bass (Micropterus salmoides).

This research utilized a compensatory growth phenomenon aimed at reducing the use of fishmeal in aquatic animal feed. However, the compensatory growth triggered by fishmeal restriction with novel protein replacement has yet to be understood. Five isonitrogenous and isolipidic diets containing different proteins were manufactured, with fishmeal serving as the control and diets containing novel proteins, i.e., Chlorella (Chlorella vulgaris), cottonseed protein concentrate, Clostridium autoethanogenum, and yellow mealworm (Tenebrio molitor), serving as the experimental diets. Largemouth bass (Micropterus salmoides) with a starting body weight of 4.73 ± 0.04g were respectively fed these five diets for the first 29days (first stage), followed by a fishmeal diet for the remaining 29days (second stage). The diet of fishmeal, Chlorella vulgaris, cottonseed protein concentrate, Clostridium autoethanogenum, and Tenebrio molitor was referred to as FM, ChM, CSM, CAP, and TM, respectively. All novel protein groups showed a 60-73% higher weight gain compared to the fishmeal group during the second phase; however, they did not reach the weight level seen in the control group. In addition, the second stage of fishmeal intervention resulted in a reduction of approximately 35% in the area of positive Alcian blue (AB) staining of intestinal tissues in the CSM group, and about 40% in the CAP group, compared to the first stage. Furthermore, the area of intestinal apoptosis in TM was enlarged after fishmeal intervention while it was decreased in other experimental groups. At day 58, gene expression analysis of the CAP group fish at the end of the trial revealed increased levels of the anti-apoptotic gene bcl-2, as well as higher expression of intestinal inflammatory cytokines il-1β, tnf-α, nf-κb p65, and il-10, compared to the FM group. In terms of the biochemical indices, the levels of catalase (CAT) and glutathione peroxidase (GSH-Px) were reduced in CSM on day 58. An assessment of potential microbial function at end of trial demonstrated that CAP could reduce the lipid metabolism and amino acid metabolism, and increased carbohydrate metabolism pathways in the largemouth bass intestine. In conclusion, both CAP and ChM groups showed promise to reduce fishmeal with respect to intestinal health rather than growth. This study should be of value to practitioners wishing to use novel proteins to reduce fishmeal via the utilization of the compensatory growth phenomenon.

Monte Carlo simulation of recrystallization and grain growth in Annealed Al–4% Cu alloy: Validation through experimental microstructure comparison

The study of recrystallization and grain growth in annealed metals has been extensively investigated using various computational approaches, with Monte Carlo (MC) simulations proving particularly effective. This research highlights the application of the MC method in simulating microstructures that closely resemble experimentally observed ones. The experimental microstructures were obtained from a 50% cold-worked Al–4% Cu (Duralumin) alloy, annealed at different conditions. The Metropolis algorithm was employed to simulate the microstructures using a two-dimensional Potts model on a square lattice. The simulated results strongly correlate with the actual microstructures, validating the effectiveness of the MC method in exploring grain growth phenomena. This study underscores the potential of MC simulations as a robust tool for investigating recrystallization and grain evolution in annealed metals.

Increased consumption of cardiovascular drugs under volume-based procurement (VBP) policy: demand release or assessment inducing?

BackgroundThe phenomenon of growth in drug consumption within the framework of national volume-based procurement (VBP) policy raises speculations about demand release and policy inducing. This study aims to explore the reasons and mechanisms of drug consumption increases following VBP policy from two perspectives.MethodsWe collected data from the China Drug Supply Information Platform, National Bureau of Statistics and the Joint Procurement Office. Twenty cardiovascular international non-proprietary names (INNs) in the first three VBP batches and 28 observation regions were included, constructing 418 valid INN-region combinations as the unit for analysis. The average monthly consumption volume of VBP cardiovascular drug was assigned as the explained variable. The generalized difference-in-difference method was conducted using the price reduction level and the size of policy assessment task as the policy intensity indicator. Moderating effect model was employed to examine the role of resident’s income level.ResultsIncreased cardiovascular drug consumption was observed in 285 (68.18%) INN-region combinations after policy implementation. Under VBP policy, the price reduction level was significantly correlated with drug consumption in total (β = 0.144, p < 0.001), as well as in tertiary hospitals, secondary hospitals and primary healthcare centers (PHCs) (all p-values < 0.05). Resident’s income level negatively moderated the impact of price reduction level on drug consumption in total (β = −0.089, p < 0.001) and in secondary hospitals (β = 0.154, p < 0.001) and PHCs (β = −0.2.9, p < 0.001), rather than in tertiary hospitals (β = −0.079, p > 0.05). The size of policy assessment task was positively associated with drug consumption in total (β = 0.052, p < 0.001), as well as in tertiary hospitals, secondary hospitals and PHCs (all p-values < 0.05).ConclusionsTwo mechanisms codrive drug consumption increases under VBP policy: first is the improvement of cardiovascular medication access and consumption toward lower-income groups following price reduction, pointing to the fulfillment of unmet needs, and second is policy pressure from supporting assessment measures on hospital drug use, indicating potential overprescribing.

On the Emden-Fowler equation type involving double critical growth

In this article, we investigate a class of nonlinear elliptic equations driven by the p-Laplacian operator in the entire space RN, known as the Emden-Fowler equation type. The complexity of the problem arises from the interplay of two distinct critical growth phenomena, characterized by both Sobolev and Hardy senses. We explore the existence of positive radial solutions, with the proof relying on variational methods. Due to multiple critical nonlinearities, the Mountain Pass Lemma does not yield critical points but only Palais-Smale sequences. The primary challenge lies in the asymptotic competition among the energies carried by these multiple critical nonlinearities.

Nanocarbon Materials: Synthesis of Newly Discovered Carbon Nanoframes and Hollow Carbon Nanocubes

AbstractNanocarbons are emerging at the forefront of nanoscience, and a wide variety of nanocarbons with unique structures have appeared over the past two decades. Currently, many carbon nanostructures have not been synthesized in the field of nanocarbons. The focus of this work is to present a new ideology and report two carbon nanostructures that have never been reported before. Inspired by the phenomenon of crystal growth, a new concept of thought is proposed. In brief, the diversity of crystal structures is utilized to enable surfactants to replicate their framework structures to create carbon nanomaterials with novel structures. In this work, carbon nanoframes (CNFEs) and hollow carbon nanocubes (HCNBs) synthesized by the 3‐(N,N‐dimethyldodecylammonio) propanesulfonate (SB3‐12)@NaCl self‐assembly strategy are used as proof of the ideology concept. It is shown that the prepared CNFEs have tunable dimensions (320–565 nm) and specific optical properties (fluorescence). The obtained HCNBs are 575 ± 20 nm in size and have fluorescent properties. It is found that changes in the concentration of SB3‐12 are a key driver of size changes, especially morphological evolution. It is believed that the ideology of this work provides a new entry point for the synthesis of carbon nanomaterials.

Effect of heat input on microstructure and mechanical properties of AA6061 alloys fabricated by additive friction stir deposition

Heat input (HI) is the major factor that affects the surface quality, microstructure and mechanical properties of the deposition during the additive friction stir deposition (AFSD) process. Effect of HI on the microstructure and mechanical performance of the AFSDed AA6061 has been in-depth explored via adjusting the values of traverse speed (v) and layer thickness (t). Results indicate that deposition with a higher HI promotes the material flow behavior as well as the plastic deformation, which effectively enhances the grain refinement and structural uniformity, and avoids the formation of defects. Meanwhile, TEM results confirm that the enhanced HI leads to the formation of a higher volume fraction of the finer precipitations (Mg2Si and AlFeSi phases), which assists in suppressing abnormal grain growth phenomenon and improves the bonding strength of the deposition. As HI decreases, the transfer efficiency of materials clearly reduces because of the incompletely softened materials, causing less plastic deformation and poor interlayer bonding strength of the deposition. The deposition with the lowest HI displays the worst tensile properties with the lowest micro-hardness (107 HV0.5), YS (273 MPa) and UTS (303 MPa).

Microstructure and property alterations and toughening mechanism of cast TC4 alloy by solid state treatment with low-density DC electric field

In this paper, the impact of low-density DC electric field treatment (LDCT) on the microstructure and mechanical properties of cast TC4 titanium alloy (CTC4) was investigated. The findings indicate that the driving force for the current provided by LDCT enhances the texture of CTC4. When the current density is sufficiently high, the induced recrystallization effect weakens the texture, leading to an isotropic state. The polygonization of grain boundaries in the LDCT state CTC4 has been identified, along with the emergence of a secondary α phase due to recrystallization. Additionally, this study highlights the phenomenon of preferential nucleation and growth occurring at the grain boundaries. LDCT induces a grain refinement effect in the CTC4 material, whereby the average grain size of the LDCT3 sample decreases from 31.05 μm in the untreated sample to 28.93 μm. The observed reduction in dislocation density in the LDCT states is believed to result from the diffusion of impurity atoms and vacancies. The observation of dislocation plugging at the inner grain boundary of the LDCT3 sample suggests that the electron wind promotes dislocation slip toward the grain boundary. Furthermore, the simultaneous enhancement of strength and toughness in the LDCT state of the CTC4 alloy has been achieved. The LDCT3 sample demonstrates superior performance, exhibiting noteworthy increases of 7.7%, 22.0%, and 10.9% in tensile strength, elongation, and fracture energy, respectively, compared to the untreated sample. The significant role of non-thermal effects in LDCT and the mechanism of atomic diffusion induced by this effect are discussed. The origins of dislocation motion and phase transition are elucidated from the perspective of atomic diffusion.

Fracture of polymer-like networks with hybrid bond strengths

The design and functionality of polymeric materials hinge on failure resistance. While molecular-level details drive crack evolution in polymer networks, the connection between individual chain scission and bulk failure remains unclear and difficult to probe. In this work, we systematically study the fracture mechanics of polymer-like networks with hybrid bond strengths. We reveal that varying the ratio of strong and weak strands within otherwise identical networks gives a non-monotonic relationship between intrinsic fracture energy and strong strand fraction. Networks with some weak strands can counterintuitively outperform those with exclusively strong strands. Experiments on poly(ethylene glycol) gels and architected polymer-like lattices together with simulations unveil these properties. We show through computational visualization that strand type concentrations impact crack growth patterns and fracture energy trends. Cracks propagate through weak layers at low strong strand fractions. Aggregate clusters deflect or pin cracks at similar concentrations of strong and weak strands. Cracks blunt due to dispersed weak strand failure at high strong strand fractions. The sacrificial weak strands can notably deconcentrate stress near the crack tip, which toughens by delaying crack advancement. The interplay between concentration and clustering of strand types in networks with hybrid bond strengths, combined with crack growth phenomena and nonlocal energy release, provides insights into unusual fracture characteristics. Results shed light on fracture in polymer networks and percolated lattices.

Effect of chemical bonding and relative density on microwave dielectric properties of LiInW2O8 ceramics

To meet the demands of the growing field of electronic communications, LiInW2O8 ceramics with low dielectric loss (high Q×f) and low dielectric constant (εr) are prepared by a solid phase reaction method. X-ray diffractometry reveals a scheelite single-phase structure for the prepared ceramics. Compared with the standard LiInW2O8, the as-prepared LiInW2O8 has a higher relative diffraction intensity for the (200) crystal plane, indicating an anisotropic growth phenomenon in the present case. Raman spectroscopy and calculations of the P-V-L complex chemical bonding theory show that W-O bonding is a key factor affecting the dielectric properties of LiInW2O8 ceramics. Furthermore, excellent microwave dielectric properties with εr ≈ 14.2, Q×f ≈ 63000 GHz, and τf ≈ −28 ppm/℃ are obtained by sintering the ceramic at 1025°C.

The newly discovered competitive growth behavior of γ and α2 phases

This study reports a new phenomenon of competitive growth between TiAl alloy structures. By annealing the β-solidified Ti-44Al-8Nb-0.1B alloy for a short time, a new phenomenon of repeated competitive growth between α2 and γ phases is found. Finally, the (α2 + γ) lamellar structure engulfs other structures and grows, transforming into a full lamellar structure.

Mathematical Modelling of Spatially Inhomogeneous Non-Stationary Interaction of Pests with Transgenic and Non-Modified Crops Considering Taxis

Introduction. This paper addresses a unified spatially inhomogeneous, non-stationary model of interaction between genetically modified crop resources (corn) and the corn borer pest, which is also present on a relatively small section of non-modified corn. The model assumes that insect pests influence both types of crops and are capable of independent movement (taxis) towards the gradient of plant resources. It also considers diffusion processes in the dynamics of all components of the unified model, biomass growth, genetic characteristics of both types of plant resources, processes of crop consumption, phenomena of growth and degradation, diffusion, and mutation of pests. The model allows for predictive calculations aimed at reducing crop losses and increasing the resistance of transgenic crops to pests by slowing down the natural mutation rate of the pest. Materials and Methods. The mathematical model is an extension of Kostitsin’s model and is formulated as an initial-boundary value problem for a nonlinear system of convection-diffusion equations. These equations describe the spatiotemporal dynamics of biomass density changes in two types of crops — transgenic and non-modified — as well as the specific populations (densities) of three genotypes of pests (the corn borer) resulting from mutations. The authors linearized the convection-diffusion equations by applying a time-lag method on the time grid, with nonlinear terms from eachequation taken from the previous time layer. The terms describing taxis are presented in a symmetric form, ensuring the skew-symmetry of the corresponding continuous operator and, in the case of spatial grid approximation, the finite-difference operator. Results. A stable monotonic finite-difference scheme is developed, approximating the original problem with second-order accuracy on a uniform 2D spatial grid. Numerical solutions of model problems are provided, qualitatively corresponding to observed processes. Solutions are obtained for various ratios of modified and non-modified sections of the field. Discussion and Conclusion. The obtained results regarding pest behavior, depending on the type of taxis, could significantly extend the time for pests to acquire Bt resistance. The concentration dynamics of pests moving in the direction of the food gradient differs markedly from the concentration of pests moving towards a mate for reproduction.

High-Accuracy Positivity-Preserving Finite Difference Approximations of the Chemotaxis Model for Tumor Invasion.

Numerical simulation of the complex evolution process for tumor invasion plays an extremely important role in-depth exploring the bio-taxis phenomena of tumor growth and metastasis. In view of the fact that low-accuracy numerical methods often have large errors and low resolution, very refined grids have to be used if we want to get high-resolution simulating results, which leads to a great deal of computational cost. In this paper, we are committed to developing a class of high-accuracy positivity-preserving finite difference methods to solve the chemotaxis model for tumor invasion. First, two unconditionally stable implicit compact difference schemes for solving the model are proposed; second, the local truncation errors of the new schemes are analyzed, which show that they have second-order accuracy in time and fourth-order accuracy in space; third, based on the proposed schemes, the high-accuracy numerical integration idea of binary functions is employed to structure a linear compact weighting formula that guarantees fourth-order accuracy and nonnegative, and then a positivity-preserving and time-marching algorithm is established; and finally, the accuracy, stability, and positivity-preserving of the proposed methods are verified by several numerical experiments, and the evolution phenomena of tumor invasion over time are numerically simulated and analyzed.

Beyond the Surface: Interconnection of Viscosity, Crystal Growth, and Diffusion in Ge25Se75 Glass-Former.

The knowledge of viscosity behavior, crystal growth phenomenon, and diffusion is important in producing, processing, and practical applications of amorphous solids prepared in different forms (bulk glasses and thin films). This work uses microscopy to study volume crystal growth in Ge25Se75 bulk glasses and thermally evaporated thin films. The collected growth data measured over a wide temperature range show a significant increase in crystal growth rates in thin films. The crystal growth is analyzed using near-surface viscosities obtained in bulks and thin films using nanoindentation and melt viscosities measured by a pressure-assisted melt filling technique. The crystal growth analysis provides information on the size of the structural units incorporated into the growing crystals, essential for estimating the diffusion coefficients and explaining the difference in crystal growth rates in bulk and thin films. The crystal growth analysis also reveals the decoupling between diffusion and viscous flow described by the Stokes-Einstein-Eyring relation. Moreover, to the authors' best knowledge, the manuscript provides the first evaluation estimation of the effective self-diffusion coefficient directly from growth data in chalcogenide glass-formers. The present data show a similar relation between diffusion coefficients (D) and crystal growth rates (u): u ≈ D0.87, which is found in several molecular glasses.

Is financial development a prerequisite for the tourism-led growth phenomenon? World-wide evidence

Purpose This study aims to re-examine the growth effects of tourism and role of financial development in this process for countries across the globe for the period 1995–2018. Design/methodology/approach Considering the asymmetric effect of tourism on economic performance, the author makes use of a recently developed method of moments approach of quantile regression with fixed effects proposed by Machado and Silva (2019). Findings Model-based on tourist arrival shows a positive effect of tourism on economic performance. Yet, the effect is conditional and shows that relatively low-income economies are benefited more than high-income economies. The results also show that all types of tourism are beneficial for growth, yet business-related tourist arrivals are found to be comparatively more effective than other types of tourism. The evidence also shows that excess tourism does not dampen growth. Finally, the evidence suggests that financial development offers critical absorptive capacity, and tourism-led growth cannot be realised without it. Originality/value In contrast to previous studies, the approach effectively deals with non-normality, endogeneity and heterogeneity across issues. Furthermore, this study uniquely tests the role of financial development in channelling tourism-led development.

Energy allocation theory for bacterial growth control in and out of steady state

Efficient allocation of energy resources to key physiological functions allows living organisms to grow and thrive in diverse environments and adapt to a wide range of perturbations. To quantitatively understand how unicellular organisms utilize their energy resources in response to changes in growth environment, we introduce a theory of dynamic energy allocation that describes cellular growth dynamics by partitioning metabolizable energy into key physiological functions: growth, division, cell shape regulation, energy storage and loss through dissipation. By optimizing the energy flux for growth, we develop the equations governing the time evolution of cell morphology and growth rate in diverse environments. The resulting model accurately captures experimentally observed dependencies of bacterial cell size on growth rate, superlinear scaling of metabolic rate with cell size and predicts nutrient-dependent trade-offs between energy expended for growth, division and shape maintenance. By calibrating model parameters with experimental data for the model organism Escherichia coli , our model describes bacterial growth control in dynamic conditions, particularly during nutrient shifts and osmotic shocks. Integrating both the mechanical properties of the cell and underlying biochemical regulation, our model predicts the driving factors behind a wide range of observed morphological and growth phenomena with minimal added complexity.

Construction of a lung cancer 3D culture model based on alginate/gelatin micro-beads for drug evaluation.

Lung cancer is one of the most common malignant tumors worldwide. Despite advances in lung cancer treatment, patients still face challenges related to drug resistance and recurrence. Current methods for evaluating anti-cancer drug activity are insufficient, as they rely on two-dimensional (2D) cell culture and animal models. Therefore, the development of an in vitro drug evaluation model capable of predicting individual sensitivity to anti-cancer drugs would greatly enhance the success rate of drug treatments for lung cancer patients. The purpose of this research is to utilise conditional reprogramming technology to cultivate patient-derived lung cancer cells and to construct an in vitro 3D culture model using sodium alginate (SA) and gelatin. The aim is to study the biological characteristics of cells in the 3D culture model and to further investigate the sensitivity of anti-cancer drugs based on the alginate-gelatin 3D culture model. This approach provides new means and insights for personalized precision anti-cancer therapy and the development of new anti-cancer drugs. Conditional reprogramming technology was used to generate conditionally reprogrammed lung adenocarcinoma cells (CRLCs). Alginate-gelatin hydrogel micro-beads were created to explore their potential use in the assessment of anti-cancer drugs. Cell proliferation was also examined using the MTS assay method. Live/dead staining was performed to estimate cell distribution and viability using calcein acetoxymethyl ester/propidium iodide (calcein-AM/PI) double staining. Protein expression was assessed by Western blot. The cells grown in the three-dimensional (3D) culture were in a state of continuous proliferation, and there was an obvious phenomenon of cell mass growth. The drug sensitivity assay results demonstrated that compared with the 2D-grown cells, the CRLCs grown in the alginate-gelatin hydrogel micro-beads exhibited more resistance to anti-cancer drugs. The results also showed that the 3D-cultured CRLCs showed greater protein expression levels of stem cell hallmarks, such as Nanog Homeobox (NANOG), SRY-Box Transcription Factor 2 (SOX-2), and aldehyde dehydrogenase 1 family member A1 (ALDH1A1), than the 2D-grown cells. These findings suggest that the 3D hydrogel cell culture models more closely mimicked the in vivo biological and clinical behavior of cells, and demonstrated higher innate resistance to anti-cancer drugs than the 2D cell culture models, and thus could serve as valuable tools for diagnosis, drug screening, and personalized medicine.

Monitoring a batch crystallization process by acoustic emission

Crystallization is regarded as an important unit operation for separation and purification, as well as the production of solid particles with specified end-use properties. However, it is still difficult to control or to optimize the crystallization process due to the complexity of the coupled phenomena taking place simultaneously in the liquid and solid phases. In order to overcome such drawback, different analytical technologies have been implemented in the literature for monitoring (in situ, at best) the key crystallization parameters, e.g. solute concentration and crystal size distribution, which in turn enhances the comprehension about this operation. In our work, a multi-probe monitoring system composed of acoustic emission, ATR-FTIR and imaging probes was applied to the crystallization of a model system (an aqueous solution of adipic acid) in a semi-batch crystallizer. The crystallization was carried out under two different feed rates and under vacuum or atmospheric pressure. The goal was to demonstrate the usefulness of the multi-probe system for monitoring the crystallization process and to study the influence of the process (stirring rotation speed, cooling speed, etc.) on the acoustic emission. As a matter of fact, the multi-probe system tracked information about the dissolved adipic acid in the liquid phase with the ATR-FTIR spectrometry, while the crystal size, shape and number were monitored with the help of the imaging probe (with image treatment methods). The acoustic emission probes were used to detect the beginning of crystallization and the phenomena of crystal growth and agglomeration

In situ EBSD study on the abnormal grain growth phenomenon in high-purity cobalt

In situ EBSD study on the abnormal grain growth phenomenon in high-purity cobalt

Fractal-Dependent Growth of Solidlike Condensates.

The phenomenon of droplet growth occurs in various industrial and natural processes. Recently, the discovery of liquidlike condensates within cells has sparked an increasing interest in understanding their growth behaviors. These condensates exhibit varying material properties that are closely related to many cellular functions and diseases, particularly during the phase transition from liquidlike droplets to solidlike aggregates. However, how the liquid-to-solid phase transition affects the growth of condensates remains largely unknown. In this study, we investigate the growth of peptide-RNA condensates, which behave as either liquidlike droplets or solidlike aggregates depending on the RNA sequences. Dynamic light scattering experiments show that solidlike condensates grow surprisingly faster, with their hydrodynamic diameters increasing over time as d_{h}(t)∼t^{1/2}, contrasting with d_{h}(t)∼t^{1/3} for liquidlike droplets. By combining theoretical analysis and simulations, we demonstrate that this accelerated growth is caused by the noncoalescence aggregation of solidlike condensates and thus formation of percolated swollen structures with a decreased fractal dimension. Moreover, we demonstrate that the accelerated growth can be slowed down by introducing agents that can revert solidlike condensates back to their liquidlike states, such as urea or specific RNAs. Together, our work reveals a fractal-dependent growth mechanism of condensates, with useful insights for understanding the aging of condensates and modulating their aggregation behaviors in synthetic and biological systems.