Size Ratio Research Articles

Interaction rewiring can buffer the reduction of long‐distance dispersal of seeds when large birds go extinct: an allometric perspective

The loss of large frugivorous birds can impact their plant partners through loss of ecological services, like long‐distance dispersal of seeds. Yet, interaction rewiring, or the redistribution of interactions among remaining bird species, might help counteract the loss of long‐distance dispersal from large bird extinctions. Here, we tested if rewiring could mitigate loss of long‐distance dispersal and whether its effectiveness differed among plants with small and large fruits at different scales. We analyzed interaction data from eight Andean bird–plant seed dispersal networks, simulated extinction of large birds, allowed for lost interactions to rewire based on previous observed interactions, trait‐matching between birds and plants, and similarity in body sizes among birds (trait‐resemblance), and related changes in long‐distance dispersal to fruit‐size ratios. At the local scale, reduction in long‐distance dispersal varied among individual networks depending on whether rewiring occurred or not and the type of rewiring. At the regional scale, after aggregating results across local networks, reduction in long‐distance dispersal was between 20 and 40% for relatively small‐fruited plants (size ratio ≤ 0.25) and between 40 and 80% for relatively large‐fruited plants (size ratio ≥ 0.75) without interaction rewiring. However, with rewiring, reduction in long‐distance dispersal of smaller‐fruited plants was limited to 4% and between 4 and 10% for larger‐fruited plants. Thus, interaction rewiring can buffer losses in ecological functions, such as long‐distance dispersal, in response to large bird extinction, although relatively large‐fruited plants remain more vulnerable than smaller‐fruited plants.

New Wine in Old Bottles: The Sustainable Application of Slow Sand Filters for the Removal of Emerging Contaminants, a Critical Literature Review

The current treatment of wastewater has unintended negative environmental impacts. Conventional methods frequently involve the use of harmful chemicals, generate disinfectant by-products, consume significant amounts of energy, and produce wastes requiring additional efforts for safe disposal. Water stress exacerbated by contaminants of emerging concern (CECs) and climate change, is further straining aging treatment systems. A slow sand filter (SSF), with ligno-cellulosic layers, offers a novel, promising, and economic alternative for wastewater reclamation. This review examines the key SSF characteristics, obtained from recent studies, and explores the use of sustainable materials such as ligno-cellulose, as a treatment companion. The optimal SSF design includes a bed depth of >0.6 m, particle effective size (D10) between 0.15 mm and 0.40 mm, and a uniformity coefficient (CU grain size ratio) of ≤2.0. It is established that SSF’s characteristic biolayer of microorganisms enhances contaminant removal via biodegradation. While biofilm-based removal of micropollutants is a proven mechanism, further research is needed to address CEC challenges. For example, the inclusion of sawdust in SSF filter layers can reduce energy consumption compared to conventional methods and can be recycled through thermal conversion, aligning with circular economy principles. This approach has the potential to improve wastewater treatment in emerging economies, contributing to the achievement of the UN Sustainability Goals.

Deep learning-based recognition of construction activities in real construction site environment

PurposeToday’s technological advancements have had a significant impact on the construction industry. Managing and controlling complex construction projects has been made significantly easier using technological tools. One such advancement is the automatic identification of workers’ activities. This study aims to classify construction worker activities by analyzing real-time motion data collected from sensors.Design/methodology/approachIn accordance with our specific goals, we utilized advanced deep-learning methodologies such as deep neural networks, convolutional neural network, long short-term memory and convolutional long short-term memory to analyze the data thoroughly. This involved experimenting with various window sizes and overlap ratios to determine the optimal combination that would result in the most accurate predictions.FindingsBased on the analysis results, the convolutional long short-term memory (ConvLSTM) deep learning model with a window size of 4.8 s and an overlap rate of 75% was found to be the most accurate prediction model. This model correctly predicted 98.64% of the basic construction worker activities in a real construction site environment.Originality/valuePrevious studies have mainly been conducted in laboratory environments and have focused on basic construction activities such as lifting, moving, sawing and hammering. However, this study collected data from real workers in a real construction site environment. Various deep learning models were employed to determine the most accurate one. Additionally, several options were tested to determine the optimal window size and overlap ratio during the data segmentation phase, aiming to select the most suitable ones for preparing the data for the model.

Grooved single-channel dual media tank thermal energy storage systems to improve overall thermal performance: Numerical analysis

In this study, a numerical analysis of a single-channel structured dual media tank (DMT) thermal energy storage (TES) system is done to investigate the effect of grooves on thermo-hydraulic performance. Due to computational complexity, a single channel is considered, and results are validated by the numerical results of other studies. The study encompasses the analysis of unsteady temperature distribution, heat transfer coefficient, and friction factor by varying the groove size ratio with the diameter of the pebbles. The φ ratio (grooves diameter/pebbles diameter) is varied from 3.15 to 4.73, and the effect of the Re for different widths of the channel is studied. The numerical result reveals a 50 % increase in heat transfer coefficient when φ is varied from 3.15 to 4.73 at a Reynolds number of 22.4. Similarly, a small variation in the frictional factor can be observed. amounts to 22 % while keeping a Reynolds number of 22.4 and a diameter ratio (φ) ranging from 3.15 to 4.73. Furthermore, research is done on how Reynolds number affects volumetric heat transfer (ℎv). The results indicate a 31 % decrease in ℎv at φ = 3.15. on the other hand, a larger value of φ is observed to result in a lesser drop in ℎv. Additionally, the computation performance improvement factor (PEF) shows greater values for φ = 3.15, indicating that the ideal groove diameter to achieve maximum heat transfer rate and minimum pressure drop is smaller.

Optimizing mass transfer performance in triply periodic minimal surface porous scaffolds through isosurface offset

Efficient bone tissue regeneration remains a critical challenge in orthopedic medicine, with scaffold mass transfer capabilities playing a pivotal role. Triply periodic minimal surface (TPMS) scaffolds have emerged as promising candidates due to their unique structure characterized by smooth, continuous surfaces with zero mean curvature and high specific surface area. However, optimizing their mass transfer performance to meet the diverse needs of bone tissues at different anatomical sites has been a persistent challenge. This study addresses this gap by investigating the effects of isosurface offset on mass transfer performance in three TPMS scaffolds (Fisher-Koch S, Gyroid, and Split-P) using computational fluid dynamics (CFD). The results showed that isosurface offset significantly increased the effective scaffold permeability range (by 116.8%, 5.3%, and 64.3% for F, G, and S scaffolds, respectively) and improved the wall shear stress (WSS) distribution, enhancing the area that effectively stimulates cell proliferation (by 25.2%, 8.7%, and 14.3% increase, respectively). Additionally, it was found that porosity, specific surface area, the ratio of maximum pore size to tortuosity, and curvature significantly influenced the permeability and WSS distribution of the scaffolds. Finally, permeation experiments using porous scaffolds fabricated by laser powder bed fusion (LPBF) technology were performed to validate the simulation results. This study provides new insights into the design of TPMS porous scaffolds and customized bone implants, enhancing their application prospects in bone tissue engineering.

The Effect of Liquidity Management on the Viability of Microfinance Institutions of Ethiopia

Purpose: Micro finance institutions have a great contribution to the development of every country’s economy through strengthening society's financial requirements. The institutions need to have adequate liquidity to generate sustainable profit. The main intention of the paper was to investigate liquidity’s impact on Micro finance institutions’ profitability. Research Methodology: Ten years of secondary data were used from 12 Microfinance institutions and fixed effect regression analysis by the use of E-views version 7 software. Return on assets used as the proxy of profitability to evaluate the financial healthiness of MFIs. Results: This study found that the deposit loan ratio has a significant and negative impact on profitability statistically. Whereas, the debt to equity ratio shows a negative signal on Micro finance Institutions (MFIs) profitability but statistically insignificant. The impact regarding size and deposit asset ratios was positive and significant on MFIs’ profitability of Ethiopia. Limitations: Lack of empirical study on the topic was the basic constraint of the study. Contribution: The study concentrated on the financial institutions specifically on microfinance firms. This study helps the institution’s management to give appropriate considerations for each component to preserve an optimal level of liquidity and sustainable profit.

Unveiling the effect of non-performing loans on lending behaviour: Evidence from Vietnam’s banking system

This study shows how non-performing loans (NPLs) and other variables specific to banks affect loan growth and the risk-weighted composition of assets in the Vietnamese banking sector. We use a large panel dataset of Vietnamese commercial banks from 2008 to 2022 and different econometric estimators to look at how NPLs, loan loss provisions (LLPs), and bank-specific factors affect how banks lend money. Additionally, we conduct a sensitivity analysis to bolster the robustness of our empirical findings. Our analysis reveals a statistically significant inverse relationship between NPLs/LLPs and loan growth rates, underscoring the critical role of effective credit risk management. Furthermore, institutional characteristics such as bank size, liquidity position, profitability metrics, and tangible asset ratios substantially influence lending patterns and risk exposure. Conversely, macroeconomic and broader institutional factors demonstrate mixed effects, with many exhibiting statistical insignificance. This study addresses a notable gap in the extant literature concerning the determinants of bank lending behaviour in Vietnam, offering nuanced insights into the role of credit risk indicators and bank-specific attributes. Our findings yield substantial implications for regulatory bodies, policymakers, and banking executives in their pursuit of enhancing the stability and operational efficiency of Vietnam's financial system. By elucidating these relationships, our research contributes to the ongoing discourse on banking sector dynamics in emerging economies. It provides an empirical foundation for informed decision-making in financial policy and risk management strategies.

An up-to-date perspective of levelized cost of hydrogen for PV-based grid-connected power-to-hydrogen plants across all Italy

Green hydrogen holds potential for decarbonizing the energy sector, but high production costs are a major barrier. This study provides a comprehensive techno-economic-financial-environmental analysis of PV-based grid-connected hydrogen production plants, targeting hard-to-abate industries having constant hydrogen demand across all Italy. Using real hourly data, the Multi Energy System Simulator (MESS), an in-house developed rule-based tool, was employed and integrated with Genetic Algorithm for optimal plant sizing. The aim is to minimize the Levelized Cost of Hydrogen (LCOH) while complying with regulatory frameworks for green hydrogen incentives access. Key findings show that hydrogen storage is more advantageous than battery storage for supply-side flexibility, and the optimal PV-to-electrolyzer size ratio ranges from 1.8 in Southern Italy to 2.1 in Northern Italy, with hydrogen tank designed for daily storage. Considering photovoltaic, electrolyzer and battery aging models grid dependence increases by 60 % when comparing the first and worst year of operation and leads to a 7 % increase in LCOH. Transitioning from the strictest (hourly) to the least stringent (annual) temporal correlation increases certified green hydrogen by 22 %, while LCOH decreases by only 3 %, suggesting that the environmental benefits of stringent temporal requirements outweigh their moderate economic drawbacks. These findings underscore the need for additional national-level incentives to allow the deployment of this technology and achieving cost parity with grey hydrogen.

Exploring the factors associated with difficulties in extracting tablets or capsules from press-through-package sheets.

Exploring factors related to difficulties in extracting tablets or capsules from press-through-packages is essential for optimizing the dosage form. To achieve this, the involvement of patient insight is important. In the present study, the preferences of patients regarding drugs that are difficult to extract from their packaging were collected using an electronic medication notebook ('harmo®') based on dispensing data. We found that approximately 30% of respondents had difficulty removing tablets or capsules from their packaging, with 125 specific drugs identified as 'hard to push out'. Independent factors related to 'hard-to-push-out' drugs were female sex and feeling of weakness in the hands or fingers. Furthermore, several 'hard-to-push-out' drugs had characteristics such as a spherical shape or small major axis or small major axis drug-to-pocket size ratio. The findings of this study may help improve the quality of drug packaging, thus enhancing the patients' medication experience.

STOCK MARKET PERFORMANCE: THE FIRM SIZE AND PRICE-EARNINGS RATIO OF SHARIAH AND NON-SHARIAH COMPLIANT SHARES

Stock markets serve as vital components of financial markets, providing avenues for short and long-term capital investment. The coexistence of two entities, namely Shariah Compliant Shares (SCS) and Non-Shariah Compliant Shares (NSCS) as supervised by the Shariah Advisory Council of the Securities Commission of Malaysia (SACSCM) characterizes Malaysia as a unique financial market. Stock return is a good indicator of a company’s performance, and many variables are said to have an impact on stock return. This study aims to investigate how firm size and price-earnings ratio would influence the stock return of a company. A total of 63 companies were selected consisting of 32 Shariah compliance companies and 31 conventional companies. Data from January 2018 until December 2022 were analyzed using descriptive statistics, correlation analysis, and regression analysis. This study discovered there is a significant negative relationship between firm size and stock return for SCS and NSCS indicating small companies often make higher returns than large companies. Meanwhile, the price-earnings ratio insignificantly affects the stock return, especially for NSCS. Whether the shares are Shariah compliant or Non-Shariah compliant, firm size has a more significant impact on stock return. To maximize shareholder wealth, the company will prioritize maintaining the optimal firm size, and investors will consider the firm size when planning their investment portfolios. The findings offer valuable insights for future research, companies, and investors seeking guidance on choosing shares for potentially higher returns.

The integrated effect of grain configuration and δ phase on micro-scaled mechanical stability of nickel-based superalloy foil

The variety and complexity of the size effect make it difficult to predict the plastic deformation behavior of foil. In this study, 0.08 mm foils with different thickness-to-grain size ratios (t/d) and δ phase distribution were obtained by adjusting the rolling and annealing processes, and the microstructure evolution before and after tensile deformation was investigated. The results show that with the decrease of the t/d ratio, the reduced grain layers number in the thickness direction facilitates grain rotation and grain boundary sliding, which accelerates the dislocation annihilation and leads to poor work hardening ability and low flow stress. Meanwhile, the lack of restrictions between adjacent grains leads to the rapid expansion of cracks after void nucleation, mainly manifested as brittle fractures. The diffuse δ phase and fine grain enhance the constraining effect on dislocations and promote dislocation proliferation and interactions. The increased number of grain layers coordinates the deformation and contributes to an increase in the Schmid factor, which supports the sliding system opening and exhibits a superior elongation of 18.1 %. The uniform δ phase exhibits good deformation compatibility and alleviates the stress concentration during the deformation process, and the interaction between neighboring grains promotes the development of uniform dimples after void nucleation, exhibiting a dominant ductile fracture. This study provides a new idea for the regulation of foil mechanical properties.

3D Topological Toron‐Like Domains in Magnetic Nanoparticles: A Micromagnetic Simulation

Abstract3D topological textures have attracted significant attention from researchers due to their distinctive spatial arrangements and intriguing physical properties. However, investigating their topological domain structures at the submicron scale (<1000 nm) proves exceedingly elusive and under‐explored. Here, the size‐dependent behaviors of non‐uniform magnetic domain structures within submicron‐sized FeNi magnetic nanoparticles by micromagnetic simulations are systematically explored. Notably, the existence of magnetic toron‐like structures at the submicron scale and discuss their spatial arrangement and topological properties are identified. Furthermore, critical transition sizes are calculated under various aspect ratios, and the domain structure phase diagram based on nanoparticle size and aspect ratio is constructed. Through visualizations of domain flipping processes and dynamic energy changes, the stable existence of toron‐like magnetic configuration resulting from the competition among demagnetization energy, magnetic anisotropy energy, and magnetic exchange energy are unveiled. Finally, the utilization of core‐shell structures to achieve the stable existence of 3D topological textures are proposed. This work provides important theoretical insights for understanding and designing multi‐domain structures of FeNi nanoparticles at the submicron scale, as well as for constructing topological textures.

A FFT-based phase-field framework for simulating dendritic growth in binary alloy

In the present study, a Fourier pseudo-spectral-based, phase-field framework is developed to simulate the binary alloy solidification using fixed grids. The motivation behind this proposition of a new model towards overcoming existing limitations is two-fold: firstly, to create a fully validated high-order phase-field model that closely aligns with LKT predictions of tip kinetics across various undercoolings and compositions, and secondly, to achieve accurate simulations using fixed Cartesian meshes with a grid size of order more than unity. In the Fourier pseudo-spectral method, the nonlinear terms of the PF equations are de-aliased using zero padding and high-order Fourier smoothing exponential filters. Accurate growth kinetics during binary alloy solidification are observed despite employing fixed mesh sizes, even when the ratio of grid size to diffuse interface thickness is 1.42. A hybrid, integrating factor (IF)-based, strongly stable third-order Runge-Kutta method (SSPRK3) is implemented to obtain improved temporal stability at high Lewis numbers. A novel scaling relationship between dimensionless tip velocity and undercooling is obtained from the growth of a four-arm equiaxed dendrite at different levels of undercooling. The growth of several randomly oriented dendrites is also accurately simulated without using any mesh refinement schemes. Likewise, the tip velocity closely matched the LKT predictions at dilute concentrations at the boundary. Furthermore, the effects of the coupling parameter and the anti-trapping term on dendritic growth kinetics are explored. Overall, the proposed FFT-based framework is expected to capture the crystals' global chemical wave features precisely with fewer points per wavelength (PPW) and has the potential to be scaled up for large-scale simulations.

Pickering Emulsions Stabilized with Millimeter-Sized Polymer Plates.

Hexagonal polymer plates of (sub)millimeter size that were uniform in shape and size were used as a stabilizer for emulsions, and the correlations of plate size, oil polarity, and plate dispersing media before emulsification with the formability, type, and droplet shape of emulsions were studied. The formability of the emulsions was improved by decreasing the plate size. The lower the oil polarity was, the more preferably O/W-type emulsions were formed, and as the oil polarity increased, the formability of W/O-type emulsions increased, whereas too high of an oil polarity resulted in no emulsion formation or macrophase separation of the oil dispersion of the plates and water. Furthermore, when the plate dispersing medium before emulsification was oil, the plates tended to be lipophilic compared with those dispersed in water before emulsification. In addition, we confirmed that there was a correlation between the droplet/stabilizer size ratio and droplet shape: when the droplet/plate size ratios are >2, droplets with near-spherical shapes are formed; when the size ratios are between 1 and 2, droplets with polyhedral shapes (e.g., hexahedral and tetrahedral shapes) are formed; and when the size ratios are <1, sandwich-shaped droplets are formed. Droplets with similar structures tended to form if the droplet/plate size ratios were close, even though the sizes of the plate and droplet were different.

Reducing segregation in vibrated binary-sized granular mixtures by excessive small particle introduction

We numerically examine binary-sized granular mixtures confined between two parallel walls subjected to vertical vibration using the discrete element method. For a size ratio of 3 between large and small particles, we study the structure of large particles in moderately dense regimes where the combined two-dimensional packing fractions of both particle sizes exceed 1. When the fraction of small particles is small, segregation of the large particles occurs. In contrast, as the fraction of small particles increases, an effective repulsion between the large particles emerges over distances greater than the large particle diameter, suppressing their segregation. The emergence of reduction in segregation is confirmed for another size ratio, vibrational acceleration, system size, and for a case of bidisperse size distribution. Additionally, at the size ratio of 3, the effective repulsion induces a hexagonal phase of the large particles at packing fractions lower than in mono-component systems. This work will provide a fresh insight into granular physics, prompting further experimental and theoretical study.Graphical This article numerically investigates the structures of quasi-two-dimensional binary-sized granular mixtures under vibration, and finds that segregation is reduced with increasing packing fraction of small particles

Thermo‐Mechanical Study on Auxetic Shape Memory Periodic Open Cellular Structures—Part I: Characterization of Reentrant Geometry and Effective Heat Conductivity

Periodic open cellular structures (POCS) are additively manufactured supports for heterogeneous catalysts in the field of chemical reaction engineering. Constructed from a repeated unit cell, POCS offer excellent heat transport characteristics due to heat conduction in the continuous solid matrix. However, when inserted into tubular reactors, a loose fit between structure and tube wall results. This considerably hinders heat transfer across the wall. The novel POCS concept presented in this work aims at an intensified wall heat transfer by utilizing a reentrant structure design to ensure auxetic behavior. If the POCS is made of shape memory alloy, it can recover its original shape. Combining these two effects with an initial radial oversize, an interference fit with the tube is established. This contribution comprises the geometric description of reentrant POCS and heat conduction simulations for characterization of the effective heat conductivity, yielding scaling correlations dependent on geometric parameters. Moreover, the effective radial heat conductivity of POCS in cylindrical shape is explicitly investigated. The influencing factor identified is the ratio of tube diameter and cell size: while the ratio increases, the effective radial heat conductivity decreases, but remains well above the effective heat conductivity of the unit cell.

The Role of Gender Diversity on Debt Policy

This study aims to evaluate the effect of gender diversity in the board of directors on debt policy in the Indonesian banking sector. Using balanced panel data analysis, this study examines the impact of gender diversity, firm size, profitability, and current ratio on debt policy. The results show that gender diversity does not have a significant influence on debt policy. Meanwhile, firm size is shown to have a positive influence, and profitability has a negative influence on debt policy. The current ratio does not show a significant influence. This study contributes to the existing literature by highlighting the factors that influence debt policy in the banking sector, particularly in the context of a modernizing economy and gender diversity in debt policy decision-making. It also provides a reference for other academic studies exploring the relationship between board gender diversity, capital structure, financial performance, and corporate governance across different industries and regions.

Analyzing convective heat transfer in combined solar chimneys: A theoretical and numerical study of key influencing parameters

Combined solar chimneys represent a potent mechanism for harnessing solar energy to bolster natural ventilation in green building designs. This study focuses on the impact of structural parameters and external conditions on the ventilation and heat transfer performance of such systems. Through scaling analysis and numerical simulations, this study investigate the flow dynamics and heat transfer mechanisms. The mechanism and the influence of three critical control parameters: inlet size ratio (h/H), ratio of inclined to vertical section lengths (L/H), and Rayleigh number (Ra) is examined. The results indicate that ventilation and heat exchange performance exhibit an initial increase followed by a decline as the inlet size ratio expands from 0.10 to 0.40. Optimal ventilation efficiency is observed at a Rayleigh number of 1.98 × 1014 with an inlet size ratio of 0.15. Conversely, a low ratio of inclined to vertical section lengths (L/H = 0.20) correlates with suboptimal ventilation performance. Both ventilation intensity and efficiency are positively correlated with increases in Ra. This research quantitatively delineates these relationships, providing a theoretical foundation for the design of natural ventilation systems in sustainable buildings using combined solar chimneys.

The illusion of success: Test set disproportion causes inflated accuracy in remote sensing mapping research

In remote sensing mapping studies, selecting an appropriate test set to accurately evaluate the results is critical. An imprecise accuracy assessment can be misleading and fail to validate the applicability of mapping products. Commencing with the WHU-Hi-HanChuan dataset, this paper revealed the impact of sample size ratios in test sets on accuracy metrics by generating a series of test sets with varying ratios of positive and negative sample size to evaluate the same map. A rigorous approach for accuracy assessment was suggested, and an example of tea plantations mapping is used to demonstrate the process and analyse potential issues in traditional approaches. A scale factor (λ) was constructed to measure the discrepancy in sample size ratios between test sets and actual conditions. Accuracy adjustment formulas were developed and applied to adjust the accuracy of 42 previous maps based on the λ. Results showed a higher ratio of positive to negative sample size in test set led to inflated user’s accuracy (UA), F1-score (F1) and overall accuracy (OA), but had little impact on producer’s accuracy. When the ratio aligned with that in the target area, the UA, F1, and OA closely matched the true values, indicating the proportion of positive and negative samples in test set should be consistent with that in actual situation. The accuracies reported by the traditional approaches including test set sampling from labelled data and 5-fold cross validation were far from the true accuracy and could not reflect the performance of the map. Among 42 previous maps, nearly 60% of the maps had UAs overestimated by 10%, and 9.5% of the maps had UAs and F1s deviations of more than 25%. The conclusions of this study provide a clear caution for future mapping research and assist in producing and identifying truly excellent maps.

Investigation of the impact load characteristics of micro-jet induced by cavitation collapse on rigid wall surface

This study examines the micro-jet generated by cavitation collapse, a phenomenon prevalent in chemical processes, with a focus on the impact load characteristics of the micro-jet on rigid wall surfaces. The expansion and collapse of cavitation bubbles generated by electric spark near the wall were recorded using a high-speed camera. Coupled with numerical simulations, a parameter λ, representing the ratio of bubble size to the distance from the wall, was introduced to comprehensively analyze the micro-jet morphology, velocity, impact force, and the resulting impact intensity on the wall surface. It was observed that the impact effect of the micro-jet on the wall surface is most pronounced when λ ≈ 1. The rapidly varying impact force of the micro-jet on the wall can be approximated as the impulse due to the average force acting on the wall over an extremely short time interval Δt. Under the condition where λ ≈ 1, both the velocity and impact force of the micro-jet, as well as the resulting impact intensity on the wall surface, increase with the bubble size. Through impact experiments on aluminum foil, it was determined that the cross-sectional shape of the micro-jet head is circular. Identified the three-dimensional shape of the micro-jet as a conical structure with a circular base. A size relationship coefficient was introduced to define the geometric model of the micro-jet. This model was based on the size relationship between the upper and lower cross-sections of the conical jet, as determined from experimental results. Key parameters affecting the impact intensity of the micro-jet were identified. The intensity values for micro-jets of different bubble sizes under the condition of λ≈1 were calculated.